WorldWideScience

Sample records for geographic exposure modeling

  1. A geographic approach to modelling human exposure to traffic air pollution using GIS. Separate appendix report

    Energy Technology Data Exchange (ETDEWEB)

    Solvang Jensen, S.

    1998-10-01

    A new exposure model has been developed that is based on a physical, single media (air) and single source (traffic) micro environmental approach that estimates traffic related exposures geographically with the postal address as exposure indicator. The micro environments: residence, workplace and street (road user exposure) may be considered. The model estimates outdoor levels for selected ambient air pollutants (benzene, CO, NO{sub 2} and O{sub 3}). The influence of outdoor air pollution on indoor levels can be estimated using average (I/O-ratios. The model has a very high spatial resolution (the address), a high temporal resolution (one hour) and may be used to predict past, present and future exposures. The model may be used for impact assessment of control measures provided that the changes to the model inputs are obtained. The exposure model takes advantage of a standard Geographic Information System (GIS) (ArcView and Avenue) for generation of inputs, for visualisation of input and output, and uses available digital maps, national administrative registers and a local traffic database, and the Danish Operational Street Pollution Model (OSPM). The exposure model presents a new approach to exposure determination by integration of digital maps, administrative registers, a street pollution model and GIS. New methods have been developed to generate the required input parameters for the OSPM model: to geocode buildings using cadastral maps and address points, to automatically generate street configuration data based on digital maps, the BBR and GIS; to predict the temporal variation in traffic and related parameters; and to provide hourly background levels for the OSPM model. (EG)

  2. A geographic approach to modelling human exposure to traffic air pollution using GIS

    Energy Technology Data Exchange (ETDEWEB)

    Solvang Jensen, S.

    1998-10-01

    A new exposure model has been developed that is based on a physical, single media (air) and single source (traffic) micro environmental approach that estimates traffic related exposures geographically with the postal address as exposure indicator. The micro environments: residence, workplace and street (road user exposure) may be considered. The model estimates outdoor levels for selected ambient air pollutants (benzene, CO, NO{sub 2} and O{sub 3}). The influence of outdoor air pollution on indoor levels can be estimated using average (I/O-ratios. The model has a very high spatial resolution (the address), a high temporal resolution (one hour) and may be used to predict past, present and future exposures. The model may be used for impact assessment of control measures provided that the changes to the model inputs are obtained. The exposure model takes advantage of a standard Geographic Information System (GIS) (ArcView and Avenue) for generation of inputs, for visualisation of input and output, and uses available digital maps, national administrative registers and a local traffic database, and the Danish Operational Street Pollution Model (OSPM). The exposure model presents a new approach to exposure determination by integration of digital maps, administrative registers, a street pollution model and GIS. New methods have been developed to generate the required input parameters for the OSPM model: to geocode buildings using cadastral maps and address points, to automatically generate street configuration data based on digital maps, the BBR and GIS; to predict the temporal variation in traffic and related parameters; and to provide hourly background levels for the OSPM model. (EG) 109 refs.

  3. A Geographic Approach to Modelling Human Exposure to Traffic Air Pollution using GIS

    DEFF Research Database (Denmark)

    Jensen, S. S.

    on gender and age from the Central Population Register (CPR); the number of employees from the Central Business Register (CER); standardised time-activity profiles for the different age groups in the residence and workplace microenvironments; and meteorological parameters (hourly). The exposure model...

  4. Geographic exposure risk of variant Creutzfeldt-Jakob disease in US blood donors: a risk-ranking model to evaluate alternative donor-deferral policies.

    Science.gov (United States)

    Yang, Hong; Huang, Yin; Gregori, Luisa; Asher, David M; Bui, Travis; Forshee, Richard A; Anderson, Steven A

    2017-04-01

    Variant Creutzfeldt-Jakob disease (vCJD) has been transmitted by blood transfusion (TTvCJD). The US Food and Drug Administration (FDA) recommends deferring blood donors who resided in or traveled to 30 European countries where they may have been exposed to bovine spongiform encephalopathy (BSE) through beef consumption. Those recommendations warrant re-evaluation, because new cases of BSE and vCJD have markedly abated. The FDA developed a risk-ranking model to calculate the geographic vCJD risk using country-specific case rates and person-years of exposure of US blood donors. We used the reported country vCJD case rates, when available, or imputed vCJD case rates from reported BSE and UK beef exports during the risk period. We estimated the risk reduction and donor loss should the deferral be restricted to a few high-risk countries. We also estimated additional risk reduction by leukocyte reduction (LR) of red blood cells (RBCs). The United Kingdom, Ireland, and France had the greatest vCJD risk, contributing approximately 95% of the total risk. The model estimated that deferring US donors who spent extended periods of time in these three countries, combined with currently voluntary LR (95% of RBC units), would reduce the vCJD risk by 89.3%, a reduction similar to that achieved under the current policy (89.8%). Limiting deferrals to exposure in these three countries would potentially allow donations from an additional 100,000 donors who are currently deferred. Our analysis suggests that a deferral option focusing on the three highest risk countries would achieve a level of blood safety similar to that achieved by the current policy. © 2016 AABB.

  5. Conceptual Model of Dynamic Geographic Environment

    Directory of Open Access Journals (Sweden)

    Martínez-Rosales Miguel Alejandro

    2014-04-01

    Full Text Available In geographic environments, there are many and different types of geographic entities such as automobiles, trees, persons, buildings, storms, hurricanes, etc. These entities can be classified into two groups: geographic objects and geographic phenomena. By its nature, a geographic environment is dynamic, thus, it’s static modeling is not sufficient. Considering the dynamics of geographic environment, a new type of geographic entity called event is introduced. The primary target is a modeling of geographic environment as an event sequence, because in this case the semantic relations are much richer than in the case of static modeling. In this work, the conceptualization of this model is proposed. It is based on the idea to process each entity apart instead of processing the environment as a whole. After that, the so called history of each entity and its spatial relations to other entities are defined to describe the whole environment. The main goal is to model systems at a conceptual level that make use of spatial and temporal information, so that later it can serve as the semantic engine for such systems.

  6. Composing Models of Geographic Physical Processes

    Science.gov (United States)

    Hofer, Barbara; Frank, Andrew U.

    Processes are central for geographic information science; yet geographic information systems (GIS) lack capabilities to represent process related information. A prerequisite to including processes in GIS software is a general method to describe geographic processes independently of application disciplines. This paper presents such a method, namely a process description language. The vocabulary of the process description language is derived formally from mathematical models. Physical processes in geography can be described in two equivalent languages: partial differential equations or partial difference equations, where the latter can be shown graphically and used as a method for application specialists to enter their process models. The vocabulary of the process description language comprises components for describing the general behavior of prototypical geographic physical processes. These process components can be composed by basic models of geographic physical processes, which is shown by means of an example.

  7. Geographically weighted regression model on poverty indicator

    Science.gov (United States)

    Slamet, I.; Nugroho, N. F. T. A.; Muslich

    2017-12-01

    In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.

  8. A geographic information system for characterizing exposure to Agent Orange and other herbicides in Vietnam.

    Science.gov (United States)

    Stellman, Jeanne Mager; Stellman, Steven D; Weber, Tracy; Tomasallo, Carrie; Stellman, Andrew B; Christian, Richard

    2003-03-01

    Between 1961 and 1971, U.S. military forces dispersed more than 19 million gallons of phenoxy and other herbicidal agents in the Republic of Vietnam, including more than 12 million gallons of dioxin-contaminated Agent Orange, yet only comparatively limited epidemiologic and environmental research has been carried out on the distribution and health effects of this contamination. As part of a response to a National Academy of Sciences' request for development of exposure methodologies for carrying out epidemiologic research, a conceptual framework for estimating exposure opportunity to herbicides and a geographic information system (GIS) have been developed. The GIS is based on a relational database system that integrates extensive data resources on dispersal of herbicides (e.g., HERBS records of Ranch Hand aircraft flight paths, gallonage, and chemical agent), locations of military units and bases, dynamic movement of combat troops in Vietnam, and locations of civilian population centers. The GIS can provide a variety of proximity counts for exposure to 9,141 herbicide application missions. In addition, the GIS can be used to generate a quantitative exposure opportunity index that accounts for quantity of herbicide sprayed, distance, and environmental decay of a toxic factor such as dioxin, and is flexible enough to permit substitution of other mathematical exposure models by the user. The GIS thus provides a basis for estimation of herbicide exposure for use in large-scale epidemiologic studies. To facilitate widespread use of the GIS, a user-friendly software package was developed to permit researchers to assign exposure opportunity indexes to troops, locations, or individuals.

  9. Geographical information modelling for land resource survey

    NARCIS (Netherlands)

    Bruin, de S.

    2000-01-01

    The increasing popularity of geographical information systems (GIS) has at least three major implications for land resources survey. Firstly, GIS allows alternative and richer representation of spatial phenomena than is possible with the traditional paper map. Secondly, digital technology has

  10. Generalisation of geographic information cartographic modelling and applications

    CERN Document Server

    Mackaness, William A; Sarjakoski, L Tiina

    2011-01-01

    Theoretical and Applied Solutions in Multi Scale MappingUsers have come to expect instant access to up-to-date geographical information, with global coverage--presented at widely varying levels of detail, as digital and paper products; customisable data that can readily combined with other geographic information. These requirements present an immense challenge to those supporting the delivery of such services (National Mapping Agencies (NMA), Government Departments, and private business. Generalisation of Geographic Information: Cartographic Modelling and Applications provides detailed review

  11. Geographic variation in risk factors for SFG rickettsial and leptospiral exposure in Colombia.

    Science.gov (United States)

    Padmanabha, Harish; Hidalgo, Marylin; Valbuena, Gustavo; Castaneda, Elizabeth; Galeano, Armando; Puerta, Henry; Cantillo, Cesar; Mantilla, Gilma

    2009-10-01

    In order to characterize the patterns of human exposure to spotted fever group (SFG) rickettsial and leptospiral infection, IgG surveys were conducted on 642 residents of ten different areas of the rural district of Necoclí, Colombia. Areas were selected based on forest cover and human settlement pattern, and individual risk factors were elucidated through multivariate logistic models, controlling for variance clustering within communities. Overall, prevalence of high antibody titers indicating previous exposure to SFG rickettsia and leptospira was 29.2% and 35.6%, respectively, and both were most prevalent in the same peri-urban neighborhood. Forest cover .10% demonstrated the strongest independent association with leptospiral exposure, followed by homes with outdoor storage sheds. Isolated rural housing was the only variable independently associated with SFG rickettsia exposure. Community-level variables significantly modified the effects of individual risk factors. For both pathogens the eldest quartile was less exposed in periurban areas although there was no age effect overall for either. Females living in population settlements were more exposed to SFG rickettsiae but there was no sex association in isolated rural houses. Similarly, in sites with forest cover .10%, individuals working at home had higher leptospira seroprevalence, but place of work was not a risk factor in areas of forest cover ,10%. These data suggest that the patterns of maintenance and/or exposure to leptospira and rickettsia vary across different human created landscapes and settlement patterns. While contrasting risk factors may reflect the unique transmission cycles of each pathogen, the observed patterns of geographic variation suggest that both diseases may respond similarly larger scale human-ecological dynamics.

  12. Probabilistic dietary exposure models

    NARCIS (Netherlands)

    Boon, Polly E.; Voet, van der H.

    2015-01-01

    Exposure models are used to calculate the amount of potential harmful chemicals ingested by a human population. Examples of harmful chemicals are residues of pesticides, chemicals entering food from the environment (such as dioxins, cadmium, lead, mercury), and chemicals that are generated via

  13. Modelling exposure opportunities

    DEFF Research Database (Denmark)

    Sabel, Clive E.; Gatrell, Anthony C.; Löytönen, Markku

    2000-01-01

    This paper addresses the issues surrounding an individual's exposure to potential environmental risk factors, which can be implicated in the aetiology of a disease. We hope to further elucidate the 'lag' or latency period between the initial exposure to potential pathogens and the physical...... boundaries.We use kernel estimation to model space-time patterns. Raised relative risk is assessed by adopting appropriate adjustments for the underlying population at risk, with the use of controls. Significance of the results is assessed using Monte Carlo simulation, and comparisons are made with results...

  14. Geographic delivery models for radiotherapy services

    International Nuclear Information System (INIS)

    Roberts, G.H.; Dunscombe, P.B.; Samant, R.S.

    2002-01-01

    The study described here was undertaken to quantify the societal cost of radiotherapy in idealized urban and rural populations and, hence, to generate a measure of impediment to access. The costs of centralized, distributed comprehensive and satellite radiotherapy delivery formats were examined by decomposing them into institutional, productivity and geographical components. Our results indicate that centralized radiotherapy imposes the greatest financial burden on the patient population in both urban and rural scenarios. The financial burden faced by patients who must travel for radiotherapy can be interpreted as one component of the overall impediment to access. With advances in remote-monitoring systems, it is possible to maintain technical quality while enhancing patient access. However, the maintenance of professional competence will remain a challenge with a distributed service-delivery format. Copyright (2002) Blackwell Science Pty Ltd

  15. Modeling the geographical studies with GeoGebra-software

    Directory of Open Access Journals (Sweden)

    Ionica Soare

    2010-01-01

    Full Text Available The problem of mathematical modeling in geography is one of the most important strategies in order to establish the evolution and the prevision of geographical phenomena. Models must have a simplified structure, to reflect essential components and must be selective, structured, and suggestive and approximate the reality. Models could be static or dynamic, developed in a theoretical, symbolic, conceptual or mental way, mathematically modeled. The present paper is focused on the virtual model which uses GeoGebra software, free and available at www.geogebra.org, in order to establish new methods of geographical analysis in a dynamic, didactic way.

  16. Comparison of GARP and Maxent in modelling the geographic ...

    African Journals Online (AJOL)

    A number of presence-only models can be used in the prediction of the geographic distribution of diseases and/or their vectors. The predictive performance of these models differs depending on a number of factors but primarily the modeled species' ecological traits. In this study, the performance of GARP and Maxent, two of ...

  17. Using Geographic Information Systems for Exposure Assessment in Environmental Epidemiology Studies

    OpenAIRE

    Nuckols, John R.; Ward, Mary H.; Jarup, Lars

    2004-01-01

    Geographic information systems (GIS) are being used with increasing frequency in environmental epidemiology studies. Reported applications include locating the study population by geocoding addresses (assigning mapping coordinates), using proximity analysis of contaminant source as a surrogate for exposure, and integrating environmental monitoring data into the analysis of the health outcomes. Although most of these studies have been ecologic in design, some have used GIS in estimating enviro...

  18. The influence of geographic location on population exposure to emissions from power plants throughout China

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Y.; Levy, J.I.; Evans, J.S.; Hammitt, J.K. [Harvard University, Boston, MA (United States). School of Public Health

    2006-04-15

    This analysis seeks to evaluate the influence of emission source location on population exposure in China to fine particles and sulfur dioxide. We use the concept of intake fraction, defined as the fraction of material or its precursor released from a source that is eventually inhaled or ingested by a population. We select 29 power-plant sites throughout China and estimate annual average intake fractions at each site, using identical source characteristics to isolate the influence of geographic location. In addition, we develop regression models to interpret the intake fraction values and allow for extrapolation to other sites. To model the concentration increase due to emissions from selected power plants, we used a detailed long-range atmospheric dispersion model, CALPUFF. Primary fine particles have the highest average intake fraction (1 x 10{sup -5}), followed by sulfur dioxide (5 x 10{sup -6}), sulfate from sulfur dioxide (4 x 10{sup -6}), and nitrate from nitrogen oxides (4 x 10{sup -6}). In the regression analysis, the independent variables are meteorological proxies (such as climate region and precipitation) and population at various distances from the source. We find that population terms can explain a substantial percentage of variability in the intake fraction for all pollutants, with a significant modifying influence of meteorological regime. Near-source population is more important for primary coarse particles while population at medium to long distance is more important for primary fine particles and secondary particles. A significant portion of intake fraction (especially for secondary particles and primary fine particles) occurs beyond 500 km of the source, emphasizing the need for detailed long-range dispersion modeling.

  19. Random-growth urban model with geographical fitness

    Science.gov (United States)

    Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

    2012-12-01

    This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

  20. Geographic Video 3d Data Model And Retrieval

    Science.gov (United States)

    Han, Z.; Cui, C.; Kong, Y.; Wu, H.

    2014-04-01

    Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today's video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

  1. The influence of geographic location on population exposure to emissions from power plants throughout China

    Energy Technology Data Exchange (ETDEWEB)

    Ying Zhou; Levy, J.I. [Harvard School of Public Health, Boston, MA (United States); Evans, J.S.; Hammitt, J.K. [Harvard Center for Risk Analysis, Boston, MA (United States)

    2006-04-15

    This analysis seeks to evaluate the influence of emission source location on population exposure in China to fine particles and sulfur dioxide. We use the concept of intake fraction, defined as the fraction of material or its precursor released from a source that is eventually inhaled or ingested by a population. We select 29 power-plant sites throughout China and estimate annual average intake fractions at each site, using identical source characteristics to isolate the influence of geographic location. In addition, we develop regression models to interpret the intake fraction values and allow for extrapolation to other sites. To model the concentration increase due to emissions from selected power plants, we used a detailed long-range atmospheric dispersion model, CALPUFF. Primary fine particles have the highest average intake fraction (1 x 10{sup -5}), followed by sulfur dioxide (5 x 10{sup -6}), sulfate from sulfur dioxide (4 x 10{sup -6}), and nitrate from nitrogen oxides (4 x 10{sup -6}). For all pollutants, the intake fractions span approximately an order of magnitude across sites. In the regression analysis, the independent variables are meteorological proxies (such as climate region and precipitation) and population at various distances from the source. We find that population terms can explain a substantial percentage of variability in the intake fraction for all pollutants (R{sup 2} between 0.86 and 0.95 across pollutants), with a significant modifying influence of meteorological regime. Near-source population is more important for primary coarse particles while population at medium to long distance is more important for primary fine particles and secondary particles. A significant portion of intake fraction (especially for secondary particles and primary fine particles) occurs beyond 500 km of the source, emphasizing the need for detailed long-range dispersion modeling. These findings demonstrate that intake fractions for power plants in China can be

  2. The influence of geographic location on population exposure to emissions from power plants throughout China

    International Nuclear Information System (INIS)

    Ying Zhou; Levy, J.I.; Evans, J.S.; Hammitt, J.K.

    2006-01-01

    This analysis seeks to evaluate the influence of emission source location on population exposure in China to fine particles and sulfur dioxide. We use the concept of intake fraction, defined as the fraction of material or its precursor released from a source that is eventually inhaled or ingested by a population. We select 29 power-plant sites throughout China and estimate annual average intake fractions at each site, using identical source characteristics to isolate the influence of geographic location. In addition, we develop regression models to interpret the intake fraction values and allow for extrapolation to other sites. To model the concentration increase due to emissions from selected power plants, we used a detailed long-range atmospheric dispersion model, CALPUFF. Primary fine particles have the highest average intake fraction (1 x 10 -5 ), followed by sulfur dioxide (5 x 10 -6 ), sulfate from sulfur dioxide (4 x 10 -6 ), and nitrate from nitrogen oxides (4 x 10 -6 ). For all pollutants, the intake fractions span approximately an order of magnitude across sites. In the regression analysis, the independent variables are meteorological proxies (such as climate region and precipitation) and population at various distances from the source. We find that population terms can explain a substantial percentage of variability in the intake fraction for all pollutants (R 2 between 0.86 and 0.95 across pollutants), with a significant modifying influence of meteorological regime. Near-source population is more important for primary coarse particles while population at medium to long distance is more important for primary fine particles and secondary particles. A significant portion of intake fraction (especially for secondary particles and primary fine particles) occurs beyond 500 km of the source, emphasizing the need for detailed long-range dispersion modeling. These findings demonstrate that intake fractions for power plants in China can be estimated with

  3. Geographical influence on the radiation exposure of an air crew on board a subsonic aircraft

    International Nuclear Information System (INIS)

    Bottollier-Depois, J.F.; Spurny, F.; Votockova, I.

    1996-01-01

    Radiation fields on board a subsonic aircraft have been studied on board an Airbus A310-300 during the flights Prague - Abu Dhabi - Bangkok and Bangkok - Abu Dhabi - Prague, during February 1995. A complex set of measuring instruments has been used for these studies: tissue equivalent proportional counter, moderator-type neutron rem-meter, environmental radiation dose rate meter, thermoluminescent and track etch detectors and bubble detectors. The results obtained are presented and analyzed; they are compared with the results obtained in the flights Prague - Montreal - Prague. Conclusions concerning the influence of geographical parameters on the aircrew exposure levels are formulated. (author). 13 refs., 2 figs., 3 tabs

  4. Parameters Estimation of Geographically Weighted Ordinal Logistic Regression (GWOLR) Model

    Science.gov (United States)

    Zuhdi, Shaifudin; Retno Sari Saputro, Dewi; Widyaningsih, Purnami

    2017-06-01

    A regression model is the representation of relationship between independent variable and dependent variable. The dependent variable has categories used in the logistic regression model to calculate odds on. The logistic regression model for dependent variable has levels in the logistics regression model is ordinal. GWOLR model is an ordinal logistic regression model influenced the geographical location of the observation site. Parameters estimation in the model needed to determine the value of a population based on sample. The purpose of this research is to parameters estimation of GWOLR model using R software. Parameter estimation uses the data amount of dengue fever patients in Semarang City. Observation units used are 144 villages in Semarang City. The results of research get GWOLR model locally for each village and to know probability of number dengue fever patient categories.

  5. Demographic and geographic differences in exposure to secondhand smoke in Missouri workplaces, 2007-2008.

    Science.gov (United States)

    Harris, Jenine K; Geremakis, Caroline; Moreland-Russell, Sarah; Carothers, Bobbi J; Kariuki, Barbara; Shelton, Sarah C; Kuhlenbeck, Matthew

    2011-11-01

    African Americans, Hispanics, service and blue-collar workers, and residents of rural areas are among those facing higher rates of workplace secondhand smoke exposure in states without smokefree workplace laws. Consequently, these groups also experience more negative health effects resulting from secondhand smoke exposure. The objective of this study was to examine disparities in workplace secondhand smoke exposure in a state without a comprehensive statewide smokefree workplace law and to use this information in considering a statewide law. We developed a logistic multilevel model by using data from a 2007-2008 county-level study to account for individual and county-level differences in workplace secondhand smoke exposure. We included sex, age, race, annual income, education level, smoking status, and rural or urban residence as predictors of workplace secondhand smoke exposure. Factors significantly associated with increased exposure to workplace secondhand smoke were male sex, lower education levels, lower income, living in a small rural or isolated area, and current smoking. For example, although the overall rate of workplace exposure in Missouri is 11.5%, our model predicts that among young white men with low incomes and limited education living in small rural areas, 40% of nonsmokers and 56% of smokers may be exposed to secondhand smoke at work. Significant disparities exist in workplace secondhand smoke exposure across Missouri. A statewide smokefree workplace law would protect all citizens from workplace secondhand smoke exposure.

  6. Geographically Weighted Logistic Regression Applied to Credit Scoring Models

    Directory of Open Access Journals (Sweden)

    Pedro Henrique Melo Albuquerque

    Full Text Available Abstract This study used real data from a Brazilian financial institution on transactions involving Consumer Direct Credit (CDC, granted to clients residing in the Distrito Federal (DF, to construct credit scoring models via Logistic Regression and Geographically Weighted Logistic Regression (GWLR techniques. The aims were: to verify whether the factors that influence credit risk differ according to the borrower’s geographic location; to compare the set of models estimated via GWLR with the global model estimated via Logistic Regression, in terms of predictive power and financial losses for the institution; and to verify the viability of using the GWLR technique to develop credit scoring models. The metrics used to compare the models developed via the two techniques were the AICc informational criterion, the accuracy of the models, the percentage of false positives, the sum of the value of false positive debt, and the expected monetary value of portfolio default compared with the monetary value of defaults observed. The models estimated for each region in the DF were distinct in their variables and coefficients (parameters, with it being concluded that credit risk was influenced differently in each region in the study. The Logistic Regression and GWLR methodologies presented very close results, in terms of predictive power and financial losses for the institution, and the study demonstrated viability in using the GWLR technique to develop credit scoring models for the target population in the study.

  7. Fuzzy modeling with spatial information for geographic problems

    CERN Document Server

    Petry, Frederick E; Cobb, Maria A

    2005-01-01

    The capabilities of modern technology are rapidly increasing, spurred on to a large extent by the tremendous advances in communications and computing. Automated vehicles and global wireless connections are some examples of these advances. In order to take advantage of such enhanced capabilities, our need to model and manipulate our knowledge of the geophysical world, using compatible representations, is also rapidly increasing. In response to this one fundamental issue of great concern in modern geographical research is how to most effectively capture the physical world around us in systems like geographical information systems (GIS). Making this task even more challenging is the fact that uncertainty plays a pervasive role in the representation, analysis and use of geospatial information. The types of uncertainty that appear in geospatial information systems are not the just simple randomness of observation, as in weather data, but are manifested in many other forms including imprecision, incompleteness and ...

  8. A Framework for Conceptual Modeling of Geographic Data Quality

    DEFF Research Database (Denmark)

    Friis-Christensen, Anders; Christensen, J.V.; Jensen, Christian Søndergaard

    2004-01-01

    Sustained advances in wireless communications, geo-positioning, and consumer electronics pave the way to a kind of location-based service that relies on the tracking of the continuously changing positions of an entire population of service users. This type of service is characterized by large...... an object is moving. Empirical performance studies based on a real road network and GPS logs from cars areThe notion of data quality is of particular importance to geographic data. One reason is that such data is often inherently imprecise. Another is that the usability of the data is in large part...... determined by how "good" the data is, as different applications of geographic data require different qualities of the data are met. Such qualities concern the object level as well as the attribute level of the data. This paper presents a systematic and integrated approach to the conceptual modeling...

  9. Differential tolerance to cyanobacterial exposure between geographically distinct populations of Perca fluviatilis.

    Science.gov (United States)

    Persson, Karl-Johan; Bergström, Kristofer; Mazur-Marzec, Hannah; Legrand, Catherine

    2013-12-15

    Toxic cyanobacterial blooms are an important problem worldwide. Cyanobacteria may negatively impact young-of-the-year (YOY) fish directly (toxin production, turbidity, decrease in water quality) or indirectly (trophic toxin transfer, changes in prey species composition). Here we test whether there are any differences in cyanobacterial tolerance between four geographically distinct populations of European perch (Perca fluviatilis). We show that P. fluviatilis may develop tolerance against cyanobacteria demonstrated by the ability of individuals from a marine site (exposed to annual cyanobacterial blooms) to increase their detoxification more than individuals from an oligotrophic site (rarely exposed to cyanobacteria). Our results also revealed significant interaction effects between genotypes within a population and response to cyanobacterial exposure in terms of absolute growth and detoxification activity. This genotype by treatment interaction may result in local adaptations to cyanobacterial exposure in P. fluviatilis. Hence, the sensitivity against cyanobacterial exposure may differ between within species populations increasing the importance of local management of fish populations. Copyright © 2013 Elsevier Ltd. All rights reserved.

  10. The Geographic Distribution of Liver Cancer in Canada Does Not Associate with Cyanobacterial Toxin Exposure

    Directory of Open Access Journals (Sweden)

    Meaghan A. Labine

    2015-11-01

    Full Text Available Background: The incidence of liver cancer has been increasing in Canada over the past decade, as has cyanobacterial contamination of Canadian freshwater lakes and drinking water sources. Cyanotoxins released by cyanobacteria have been implicated in the pathogenesis of liver cancer. Objective: To determine whether a geographic association exists between liver cancer and surrogate markers of cyanobacterial contamination of freshwater lakes in Canada. Methods: A negative binomial regression model was employed based on previously identified risk factors for liver cancer. Results: No association existed between the geographic distribution of liver cancer and surrogate markers of cyanobacterial contamination. As predicted, significant associations existed in areas with a high prevalence of hepatitis B virus infection, large immigrant populations and urban residences. Discussion and Conclusions: The results of this study suggest that cyanobacterial contamination of freshwater lakes does not play an important role in the increasing incidence of liver cancer in Canada.

  11. Geographical point cloud modelling with the 3D medial axis transform

    NARCIS (Netherlands)

    Peters, R.Y.

    2018-01-01

    A geographical point cloud is a detailed three-dimensional representation of the geometry of our geographic environment.
    Using geographical point cloud modelling, we are able to extract valuable information from geographical point clouds that can be used for applications in asset management,

  12. Modeled population exposures to ozone

    Data.gov (United States)

    U.S. Environmental Protection Agency — Population exposures to ozone from APEX modeling for combinations of potential future air quality and demographic change scenarios. This dataset is not publicly...

  13. Modelling Participatory Geographic Information System for Customary Land Conflict Resolution

    Science.gov (United States)

    Gyamera, E. A.; Arko-Adjei, A.; Duncan, E. E.; Kuma, J. S. Y.

    2017-11-01

    Since land contributes to about 73 % of most countries Gross Domestic Product (GDP), attention on land rights have tremendously increased globally. Conflicts over land have therefore become part of the major problems associated with land administration. However, the conventional mechanisms for land conflict resolution do not provide satisfactory result to disputants due to various factors. This study sought to develop a Framework of using Participatory Geographic Information System (PGIS) for customary land conflict resolution. The framework was modelled using Unified Modelling Language (UML). The PGIS framework, called butterfly model, consists of three units namely, Social Unit (SU), Technical Unit (TU) and Decision Making Unit (DMU). The name butterfly model for land conflict resolution was adopted for the framework based on its features and properties. The framework has therefore been recommended to be adopted for land conflict resolution in customary areas.

  14. COMPLEMENTARITY OF HISTORIC BUILDING INFORMATION MODELLING AND GEOGRAPHIC INFORMATION SYSTEMS

    Directory of Open Access Journals (Sweden)

    X. Yang

    2016-06-01

    Full Text Available In this paper, we discuss the potential of integrating both semantically rich models from Building Information Modelling (BIM and Geographical Information Systems (GIS to build the detailed 3D historic model. BIM contributes to the creation of a digital representation having all physical and functional building characteristics in several dimensions, as e.g. XYZ (3D, time and non-architectural information that are necessary for construction and management of buildings. GIS has potential in handling and managing spatial data especially exploring spatial relationships and is widely used in urban modelling. However, when considering heritage modelling, the specificity of irregular historical components makes it problematic to create the enriched model according to its complex architectural elements obtained from point clouds. Therefore, some open issues limiting the historic building 3D modelling will be discussed in this paper: how to deal with the complex elements composing historic buildings in BIM and GIS environment, how to build the enriched historic model, and why to construct different levels of details? By solving these problems, conceptualization, documentation and analysis of enriched Historic Building Information Modelling are developed and compared to traditional 3D models aimed primarily for visualization.

  15. Development of a spatial stochastic multimedia exposure model to assess population exposure at a regional scale

    International Nuclear Information System (INIS)

    Caudeville, Julien; Bonnard, Roseline; Boudet, Céline; Denys, Sébastien; Govaert, Gérard; Cicolella, André

    2012-01-01

    Analyzing the relationship between the environment and health has become a major focus of public health efforts in France, as evidenced by the national action plans for health and the environment. These plans have identified the following two priorities: -identify and manage geographic areas where hotspot exposures are a potential risk to human health; and -reduce exposure inequalities. The aim of this study is to develop a spatial stochastic multimedia exposure model for detecting vulnerable populations and analyzing exposure determinants at a fine resolution and regional scale. A multimedia exposure model was developed by INERIS to assess the transfer of substances from the environment to humans through inhalation and ingestion pathways. The RESPIR project adds a spatial dimension by linking GIS (Geographic Information System) to the model. Tools are developed using modeling, spatial analysis and geostatistic methods to build and discretize interesting variables and indicators from different supports and resolutions on a 1-km 2 regular grid. We applied this model to the risk assessment of exposure to metals (cadmium, lead and nickel) using data from a region in France (Nord-Pas-de-Calais). The considered exposure pathways include the atmospheric contaminant inhalation and ingestion of soil, vegetation, meat, egg, milk, fish and drinking water. Exposure scenarios are defined for different reference groups (age, dietary properties, and the fraction of food produced locally). The two largest risks correspond to an ancient industrial site (Metaleurop) and the Lille agglomeration. In these areas, cadmium, vegetation ingestion and soil contamination are the principal determinants of the computed risk. -- Highlights: ► We present a multimedia exposure model for mapping environmental disparities. ► We perform a risk assessment on a region of France at a fine scale for three metals. ► We examine exposure determinants and detect vulnerable population. ► The largest

  16. [Multicriteria evaluation of environmental risk exposure using a geographic information system in Argentina].

    Science.gov (United States)

    Pietri, Diana De; Dietrich, Patricia; Mayo, Patricia; Carcagno, Alejandro

    2011-10-01

    Develop a spatial model that includes environmental factors posing a health hazard, for application in the Matanza-Riachuelo River Basin (MRB) in Argentina. Multicriteria evaluation procedures were used with geographic information systems to obtain territorial zoning based on the degree of suitability for residence. Variables that characterize the habitability of housing and potential sources of basin pollution were geographically referenced. Health information was taken from the Risk Factor Survey (RFS) to measure the relative risk of living in unsuitable areas (exposed population) compared with suitable areas (unexposed population). Sixty percent of the MRB area is in suitable condition, a situation that affects 40% of residents. The rest of the population lives in unsuitable territory, and 6% live in the basin's most unsuitable conditions. Environmental conditions that are detrimental to health in the unsuitable areas became evident during the interviews through three of the pathologies considered: diarrheal diseases, respiratory diseases, and cancer. A regional analysis that provides valid information to support decisionmaking was obtained. Considering the basin as a unit of analysis allowed the use of a single protocol to undertake comprehensive measurement of the magnitude of risk and, thus, set priorities.

  17. [Geographic distribution and exposure population of drinking water with high concentration of arsenic in China].

    Science.gov (United States)

    Zhang, L; Chen, C

    1997-09-01

    According to the data obtained from the "National Survey on Drinking Water Quality and Waterborne Diseases", the geographic distribution and exposure population of high arsenic drinking water were reported. From the data of more than 28,800 water samples, we found 9.02 million people drinking the water with As concentration of 0.030-0.049 mg/L, 3.34 million people having their water of 0.050-0.099 mg/L and 2.29 million people having water of > 0.1 mg/L. A total of 14.6 million people, about 1.5% of the surveyed population was exposed to As (> 0.030 mg/L) from drinking water. 80% of high-As-drinking water was groundwater. The situation of As in drinking water in provinces, autonomous regions and municipalities were listed. The locations of sampling site where water As exceeded the national standard for drinking water were illustrated.

  18. Modelling Technology for Building Fire Scene with Virtual Geographic Environment

    Science.gov (United States)

    Song, Y.; Zhao, L.; Wei, M.; Zhang, H.; Liu, W.

    2017-09-01

    Building fire is a risky activity that can lead to disaster and massive destruction. The management and disposal of building fire has always attracted much interest from researchers. Integrated Virtual Geographic Environment (VGE) is a good choice for building fire safety management and emergency decisions, in which a more real and rich fire process can be computed and obtained dynamically, and the results of fire simulations and analyses can be much more accurate as well. To modelling building fire scene with VGE, the application requirements and modelling objective of building fire scene were analysed in this paper. Then, the four core elements of modelling building fire scene (the building space environment, the fire event, the indoor Fire Extinguishing System (FES) and the indoor crowd) were implemented, and the relationship between the elements was discussed also. Finally, with the theory and framework of VGE, the technology of building fire scene system with VGE was designed within the data environment, the model environment, the expression environment, and the collaborative environment as well. The functions and key techniques in each environment are also analysed, which may provide a reference for further development and other research on VGE.

  19. A preliminary geodetic data model for geographic information systems

    Science.gov (United States)

    Kelly, K. M.

    2009-12-01

    Our ability to gather and assimilate integrated data collections from multiple disciplines is important for earth system studies. Moreover, geosciences data collection has increased dramatically, with pervasive networks of observational stations on the ground, in the oceans, in the atmosphere and in space. Contemporary geodetic observations from several space and terrestrial technologies contribute to our knowledge of earth system processes and thus are a valuable source of high accuracy information for many global change studies. Assimilation of these geodetic observations and numerical models into models of weather, climate, oceans, hydrology, ice, and solid Earth processes is an important contribution geodesists can make to the earth science community. Clearly, the geodetic observations and models are fundamental to these contributions. ESRI wishes to provide leadership in the geodetic community to collaboratively build an open, freely available content specification that can be used by anyone to structure and manage geodetic data. This Geodetic Data Model will provide important context for all geographic information. The production of a task-specific geodetic data model involves several steps. The goal of the data model is to provide useful data structures and best practices for each step, making it easier for geodesists to organize their data and metadata in a way that will be useful in their data analyses and to their customers. Built on concepts from the successful Arc Marine data model, we introduce common geodetic data types and summarize the main thematic layers of the Geodetic Data Model. These provide a general framework for envisioning the core feature classes required to represent geodetic data in a geographic information system. Like Arc Marine, the framework is generic to allow users to build workflow or product specific geodetic data models tailored to the specific task(s) at hand. This approach allows integration of the data with other existing

  20. Geographically weighted negative binomial regression applied to zonal level safety performance models.

    Science.gov (United States)

    Gomes, Marcos José Timbó Lima; Cunto, Flávio; da Silva, Alan Ricardo

    2017-09-01

    Generalized Linear Models (GLM) with negative binomial distribution for errors, have been widely used to estimate safety at the level of transportation planning. The limited ability of this technique to take spatial effects into account can be overcome through the use of local models from spatial regression techniques, such as Geographically Weighted Poisson Regression (GWPR). Although GWPR is a system that deals with spatial dependency and heterogeneity and has already been used in some road safety studies at the planning level, it fails to account for the possible overdispersion that can be found in the observations on road-traffic crashes. Two approaches were adopted for the Geographically Weighted Negative Binomial Regression (GWNBR) model to allow discrete data to be modeled in a non-stationary form and to take note of the overdispersion of the data: the first examines the constant overdispersion for all the traffic zones and the second includes the variable for each spatial unit. This research conducts a comparative analysis between non-spatial global crash prediction models and spatial local GWPR and GWNBR at the level of traffic zones in Fortaleza/Brazil. A geographic database of 126 traffic zones was compiled from the available data on exposure, network characteristics, socioeconomic factors and land use. The models were calibrated by using the frequency of injury crashes as a dependent variable and the results showed that GWPR and GWNBR achieved a better performance than GLM for the average residuals and likelihood as well as reducing the spatial autocorrelation of the residuals, and the GWNBR model was more able to capture the spatial heterogeneity of the crash frequency. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Geographical distribution of radiation risk unaccountable by direct exposure dose in hiroshima A-bomb victims

    International Nuclear Information System (INIS)

    Tonda, Tetsuji; Satoh, Kenichi; Ohani, Keiko

    2012-01-01

    Death risks due to solid cancer were estimated from region to region where the A-bomb survivors had been actually exposed, to visualize the risk distribution on the map, which resulting in risk regional difference that had been unaccountable by direct exposure dose estimation. Analysis was performed with 3 hazard models of the previous one, + direct exposed dose as a confounding factor and, further, + spatial distance from the explosion point. Subjects were 37,382 A-bomb survivors at Jan. 1, 1970 with known positional coordinate at explosion, followed until Dec. 31, 2009, whose endpoint was set by 4,371 deaths due to cancer except leukemia, cancers of thyroid and breast. Confounding factors in the previous hazard model were sex, age at the exposure, dose and shielding. With the previous model, risk distribution was observed in a concentric circular region around the hypocenter and in an additional west to northwestern suburbs. The latter risk distribution was also seen with the second model in the same region, where dose decreased with -7 powers of the distance. When adjusted with -3 powers of the distance with the third model, the actual risk distribution was found best fitted, indicating the presence of distance-dependent risk. It was suggested that the region exposed to additional dose possibly derived from fallout had been the actual black rainfall area as those regions agreed with each other. (T.T.)

  2. Development of a spatial stochastic multimedia exposure model to assess population exposure at a regional scale.

    Science.gov (United States)

    Caudeville, Julien; Bonnard, Roseline; Boudet, Céline; Denys, Sébastien; Govaert, Gérard; Cicolella, André

    2012-08-15

    Analyzing the relationship between the environment and health has become a major focus of public health efforts in France, as evidenced by the national action plans for health and the environment. These plans have identified the following two priorities: - identify and manage geographic areas where hotspot exposures are a potential risk to human health; and - reduce exposure inequalities. The aim of this study is to develop a spatial stochastic multimedia exposure model for detecting vulnerable populations and analyzing exposure determinants at a fine resolution and regional scale. A multimedia exposure model was developed by INERIS to assess the transfer of substances from the environment to humans through inhalation and ingestion pathways. The RESPIR project adds a spatial dimension by linking GIS (Geographic Information System) to the model. Tools are developed using modeling, spatial analysis and geostatistic methods to build and discretize interesting variables and indicators from different supports and resolutions on a 1-km(2) regular grid. We applied this model to the risk assessment of exposure to metals (cadmium, lead and nickel) using data from a region in France (Nord-Pas-de-Calais). The considered exposure pathways include the atmospheric contaminant inhalation and ingestion of soil, vegetation, meat, egg, milk, fish and drinking water. Exposure scenarios are defined for different reference groups (age, dietary properties, and the fraction of food produced locally). The two largest risks correspond to an ancient industrial site (Metaleurop) and the Lille agglomeration. In these areas, cadmium, vegetation ingestion and soil contamination are the principal determinants of the computed risk. Copyright © 2012 Elsevier B.V. All rights reserved.

  3. A geographical model of radio-frequency power density around mobile phone masts

    International Nuclear Information System (INIS)

    Briggs, David; Beale, Linda; Bennett, James; Toledano, Mireille B.; Hoogh, Kees de

    2012-01-01

    Public concern about possible health effects of EMF radiation from mobile phone masts has led to an increase of epidemiological studies and health risk assessments which, in turn, require adequate methods of exposure estimation. Difficulties in exposure modelling are exacerbated both by the complexity of the propagation processes, and the need to obtain estimates for large study populations in order to provide sufficient statistical power to detect or exclude the small relative risks that might exist. Use of geographical information system (GIS) techniques offers the means to make such computations efficiently. This paper describes the development and field validation of a GIS-based exposure model (Geomorf). The model uses a modified Gaussian formulation to represent spatial variations in power densities around mobile phone masts, on the basis of power output, antenna height, tilt and the surrounding propagation environment. Obstruction by topography is allowed for, through use of a visibility function. Model calibration was done using field data from 151 measurement sites (1510 antenna-specific measurements) around a group of masts in a rural location, and 50 measurement sites (658 antenna-specific measurements) in an urban area. Different parameter settings were found to be necessary in urban and rural areas to obtain optimum results. The calibrated models were then validated against independent sets of data gathered from measurement surveys in rural and urban areas, and model performance was compared with that of two commonly used path-loss models (the COST-231 adaptations of the Hata and Walfisch–Ikegami models). Model performance was found to vary somewhat between the rural and urban areas, and at different measurement levels (antenna-specific power density, total power density), but overall gave good estimates (R 2 = 0.641 and 0.615, RMSE = 10.7 and 6.7 dB m at the antenna and site-level respectively). Performance was considerably better than that of both

  4. Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

    NARCIS (Netherlands)

    P.C. Austin (Peter); D. van Klaveren (David); Y. Vergouwe (Yvonne); D. Nieboer (Daan); D.S. Lee (Douglas); E.W. Steyerberg (Ewout)

    2016-01-01

    textabstractObjective: Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting: We

  5. Violent crime exposure classification and adverse birth outcomes: a geographically-defined cohort study

    Directory of Open Access Journals (Sweden)

    Herring Amy

    2006-05-01

    Full Text Available Abstract Background Area-level socioeconomic disparities have long been associated with adverse pregnancy outcomes. Crime is an important element of the neighborhood environment inadequately investigated in the reproductive and public health literature. When crime has been used in research, it has been variably defined, resulting in non-comparable associations across studies. Methods Using geocoded linked birth record, crime and census data in multilevel models, this paper explored the relevance of four spatial violent crime exposures: two proximal violent crime categorizations (count of violent crime within a one-half mile radius of maternal residence and distance from maternal residence to nearest violent crime and two area-level crime categorizations (count of violent crimes within a block group and block group rate of violent crimes for adverse birth events among women in living in the city of Raleigh NC crime report area in 1999–2001. Models were adjusted for maternal age and education and area-level deprivation. Results In black and white non-Hispanic race-stratified models, crime characterized as a proximal exposure was not able to distinguish between women experiencing adverse and women experiencing normal birth outcomes. Violent crime characterized as a neighborhood attribute was positively associated with preterm birth and low birth weight among non-Hispanic white and black women. No statistically significant interaction between area-deprivation and violent crime category was observed. Conclusion Crime is variably categorized in the literature, with little rationale provided for crime type or categorization employed. This research represents the first time multiple crime categorizations have been directly compared in association with health outcomes. Finding an effect of area-level violent crime suggests crime may best be characterized as a neighborhood attribute with important implication for adverse birth outcomes.

  6. Modelling grid losses and the geographic distribution of electricity generation

    DEFF Research Database (Denmark)

    Østergaard, Poul Alberg

    2005-01-01

    In Denmark more than 40% of the electricity consumption is covered by geographically scattered electricity sources namely wind power and local CHP (cogeneration of heat and power) plants. This causes problems in regard to load balancing and possible grid overloads. The potential grid problems...... and methods for solving these are analysed in this article on the basis of energy systems analyses, geographic distribution of consumption and production and grid load-flow analyses. It is concluded that by introducing scattered load balancing using local CHP plants actively and using interruptible loads...

  7. Development of a spatial stochastic multimedia exposure model to assess population exposure at a regional scale

    Energy Technology Data Exchange (ETDEWEB)

    Caudeville, Julien, E-mail: Julien.CAUDEVILLE@ineris.fr [INERIS (French National Institute for Industrial Environment and Risks), Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Joint research unit UMR 6599, Heudiasyc (Heuristic and Diagnoses of Complex Systems), University of Technology of Compiegne and CNRS, Rue du Dr Schweitzer, 60200 Compiegne (France); Bonnard, Roseline, E-mail: Roseline.BONNARD@ineris.fr [INERIS (French National Institute for Industrial Environment and Risks), Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Boudet, Celine, E-mail: Celine.BOUDET@ineris.fr [INERIS (French National Institute for Industrial Environment and Risks), Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Denys, Sebastien, E-mail: Sebastien.DENYS@ineris.fr [INERIS (French National Institute for Industrial Environment and Risks), Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Govaert, Gerard, E-mail: gerard.govaert@utc.fr [Joint research unit UMR 6599, Heudiasyc (Heuristic and Diagnoses of Complex Systems), University of Technology of Compiegne and CNRS, Rue du Dr Schweitzer, 60200 Compiegne (France); Cicolella, Andre, E-mail: Andre.CICOLELLA@ineris.fr [INERIS (French National Institute for Industrial Environment and Risks), Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France)

    2012-08-15

    Analyzing the relationship between the environment and health has become a major focus of public health efforts in France, as evidenced by the national action plans for health and the environment. These plans have identified the following two priorities: -identify and manage geographic areas where hotspot exposures are a potential risk to human health; and -reduce exposure inequalities. The aim of this study is to develop a spatial stochastic multimedia exposure model for detecting vulnerable populations and analyzing exposure determinants at a fine resolution and regional scale. A multimedia exposure model was developed by INERIS to assess the transfer of substances from the environment to humans through inhalation and ingestion pathways. The RESPIR project adds a spatial dimension by linking GIS (Geographic Information System) to the model. Tools are developed using modeling, spatial analysis and geostatistic methods to build and discretize interesting variables and indicators from different supports and resolutions on a 1-km{sup 2} regular grid. We applied this model to the risk assessment of exposure to metals (cadmium, lead and nickel) using data from a region in France (Nord-Pas-de-Calais). The considered exposure pathways include the atmospheric contaminant inhalation and ingestion of soil, vegetation, meat, egg, milk, fish and drinking water. Exposure scenarios are defined for different reference groups (age, dietary properties, and the fraction of food produced locally). The two largest risks correspond to an ancient industrial site (Metaleurop) and the Lille agglomeration. In these areas, cadmium, vegetation ingestion and soil contamination are the principal determinants of the computed risk. -- Highlights: Black-Right-Pointing-Pointer We present a multimedia exposure model for mapping environmental disparities. Black-Right-Pointing-Pointer We perform a risk assessment on a region of France at a fine scale for three metals. Black-Right-Pointing-Pointer We

  8. Environmental statistical modelling of mosquito vectors at different geographical scales

    NARCIS (Netherlands)

    Cianci, D.

    2015-01-01

    Vector-borne diseases are infections transmitted by the bite of infected arthropod vectors, such as mosquitoes, ticks, fleas, midges and flies. Vector-borne diseases pose an increasingly wider threat to global public health, both in terms of people affected and their geographical spread. Mosquitoes

  9. Modelling the geographic distribution of wind power and the impact on transmission needs

    DEFF Research Database (Denmark)

    Østergaard, Poul Alberg

    2003-01-01

    Through energy systems modelling, transmission systems modelling and geographical modelling, the article examines the sensitivity of the response of the transmission system to the geographic distributions of wind power and in particular the sensitivity of the results to the accuracy...... of the distributed modelled. The results show that accuracy of the geographic modelling while important for the analysis of specific single transmission lines is not important for the analysis of the general response of the transmission system. The analyses thus corroborate previous analyses that demonstrated...

  10. Demographic and Geographic Differences in Exposure to Secondhand Smoke in Missouri Workplaces, 2007-2008

    OpenAIRE

    Harris, Jenine K.; Geremakis, Caroline; Moreland-Russell, Sarah; Carothers, Bobbi J.; Shelton, Sarah C.; Kariuki, Barbara; Kuhlenbeck, Matthew

    2011-01-01

    Introduction African Americans, Hispanics, service and blue-collar workers, and residents of rural areas are among those facing higher rates of workplace secondhand smoke exposure in states without smokefree workplace laws. Consequently, these groups also experience more negative health effects resulting from secondhand smoke exposure. The objective of this study was to examine disparities in workplace secondhand smoke exposure in a state without a comprehensive statewide smokefree workplace ...

  11. A coregionalization model can assist specification of Geographically Weighted Poisson Regression: Application to an ecological study.

    Science.gov (United States)

    Ribeiro, Manuel Castro; Sousa, António Jorge; Pereira, Maria João

    2016-05-01

    The geographical distribution of health outcomes is influenced by socio-economic and environmental factors operating on different spatial scales. Geographical variations in relationships can be revealed with semi-parametric Geographically Weighted Poisson Regression (sGWPR), a model that can combine both geographically varying and geographically constant parameters. To decide whether a parameter should vary geographically, two models are compared: one in which all parameters are allowed to vary geographically and one in which all except the parameter being evaluated are allowed to vary geographically. The model with the lower corrected Akaike Information Criterion (AICc) is selected. Delivering model selection exclusively according to the AICc might hide important details in spatial variations of associations. We propose assisting the decision by using a Linear Model of Coregionalization (LMC). Here we show how LMC can refine sGWPR on ecological associations between socio-economic and environmental variables and low birth weight outcomes in the west-north-central region of Portugal. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Modeling exposure to air pollution and cardiovascular mortality: the ESCAPE study

    NARCIS (Netherlands)

    Wang, M.|info:eu-repo/dai/nl/345480279

    2013-01-01

    Exposure assessment is one of the key issues for health effect estimates in environmental epidemiology. Recent interest has increased in exposure modeling incorporating Geographic Information System (GIS) data to capture small-scale spatial variability in air pollution concentrations. Land use

  13. Retail tobacco exposure: using geographic analysis to identify areas with excessively high retail density.

    Science.gov (United States)

    Rodriguez, Daniel; Carlos, Heather A; Adachi-Mejia, Anna M; Berke, Ethan M; Sargent, James

    2014-02-01

    There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need.

  14. Exploitation of geographic information system at mapping and modelling of selected soil parameters

    International Nuclear Information System (INIS)

    Palka, B.; Makovnikova, J.; Siran, M.

    2005-01-01

    In this presentation authors describe using of computers and geographic information systems (GIS) at effective use of soil fund, rational exploitation and organization of agricultural soil fund on the territory of the Slovak Republic, its monitoring and modelling. Using and creating of some geographically oriented information systems and databases about soils as well as present trends are discussed

  15. Open-Source web-based geographical information system for health exposure assessment

    Directory of Open Access Journals (Sweden)

    Evans Barry

    2012-01-01

    Full Text Available Abstract This paper presents the design and development of an open source web-based Geographical Information System allowing users to visualise, customise and interact with spatial data within their web browser. The developed application shows that by using solely Open Source software it was possible to develop a customisable web based GIS application that provides functions necessary to convey health and environmental data to experts and non-experts alike without the requirement of proprietary software.

  16. Open-Source web-based geographical information system for health exposure assessment

    DEFF Research Database (Denmark)

    Evans, Barry; Sabel, Clive E

    2012-01-01

    This paper presents the design and development of an open source web-based Geographical Information System allowing users to visualise, customise and interact with spatial data within their web browser. The developed application shows that by using solely Open Source software it was possible to d...... to develop a customisable web based GIS application that provides functions necessary to convey health and environmental data to experts and non-experts alike without the requirement of proprietary software....

  17. Asymptotic behaviour of a nonlinear model for the geographic diffusion of infections diseases

    International Nuclear Information System (INIS)

    Kirane, M.; Kouachi, S.

    1994-01-01

    In this paper a nonlinear diffusion model for the geographical spread of infective diseases is studied. In addition to proving well-posedness of the associated initial-boundary value problem, the large time behaviour is analyzed. (author). 4 refs

  18. Geographic and seasonal variation in mercury exposure of the declining Rusty Blackbird

    Science.gov (United States)

    Samuel T. Edmonds; David C. Evers; Daniel A. Cristol; Claudia Mettke-Hofmann; Luke L. Powell

    2010-01-01

    Recent evidence suggests that mercury exposure has negative effects on the health of songbirds, and species that forage in wetlands may be at a greater risk of bioaccumulation of mercury than are those of other habitats. We examined mercury concentrations in blood and feathers from the wetland obligate and rapidly declining Rusty Blackbird (Euphagus carolinus) from...

  19. Modeling population exposures to silver nanoparticles present in consumer products

    Science.gov (United States)

    Royce, Steven G.; Mukherjee, Dwaipayan; Cai, Ting; Xu, Shu S.; Alexander, Jocelyn A.; Mi, Zhongyuan; Calderon, Leonardo; Mainelis, Gediminas; Lee, KiBum; Lioy, Paul J.; Tetley, Teresa D.; Chung, Kian Fan; Zhang, Junfeng; Georgopoulos, Panos G.

    2014-11-01

    Exposures of the general population to manufactured nanoparticles (MNPs) are expected to keep rising due to increasing use of MNPs in common consumer products (PEN 2014). The present study focuses on characterizing ambient and indoor population exposures to silver MNPs (nAg). For situations where detailed, case-specific exposure-related data are not available, as in the present study, a novel tiered modeling system, Prioritization/Ranking of Toxic Exposures with GIS (geographic information system) Extension (PRoTEGE), has been developed: it employs a product life cycle analysis (LCA) approach coupled with basic human life stage analysis (LSA) to characterize potential exposures to chemicals of current and emerging concern. The PRoTEGE system has been implemented for ambient and indoor environments, utilizing available MNP production, usage, and properties databases, along with laboratory measurements of potential personal exposures from consumer spray products containing nAg. Modeling of environmental and microenvironmental levels of MNPs employs probabilistic material flow analysis combined with product LCA to account for releases during manufacturing, transport, usage, disposal, etc. Human exposure and dose characterization further employ screening microenvironmental modeling and intake fraction methods combined with LSA for potentially exposed populations, to assess differences associated with gender, age, and demographics. Population distributions of intakes, estimated using the PRoTEGE framework, are consistent with published individual-based intake estimates, demonstrating that PRoTEGE is capable of capturing realistic exposure scenarios for the US population. Distributions of intakes are also used to calculate biologically relevant population distributions of uptakes and target tissue doses through human airway dosimetry modeling that takes into account product MNP size distributions and age-relevant physiological parameters.

  20. Validity of covariance models for the analysis of geographical variation

    DEFF Research Database (Denmark)

    Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio

    2014-01-01

    1. Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. 2. We focus here on a class of parametric covariance models that received sustained att...

  1. AirPEx. Air Pollution Exposure Model

    Energy Technology Data Exchange (ETDEWEB)

    Freijer, J.I.; Bloemen, H.J.Th.; De Loos, S.; Marra, M.; Rombout, P.J.A.; Steentjes, G.M.; Van Veen, M.P.

    1997-12-01

    Analysis of inhalatory exposure to air pollution is an important area of investigation when assessing the risks of air pollution for human health. Inhalatory exposure research focuses on the exposure of humans to air pollutants and the entry of these pollutants into the human respiratory tract. The principal grounds for studying the inhalatory exposure of humans to air pollutants are formed by the need for realistic exposure/dose estimates to evaluate the health effects of these pollutants. The AirPEx (Air Pollution Exposure) model, developed to assess the time- and space-dependence of inhalatory exposure of humans to air pollution, has been implemented for use as a Windows 3.1 computer program. The program is suited to estimating various exposure and dose quantities for individuals, as well as for populations and subpopulations. This report describes the fundamentals of the AirPEx model and provides a user manual for the computer program. Several examples included in the report illustrate the possibilities of the AirPEx model in exposure assessment. The model will be used at the National Institute of Public Health and the Environment as a tool in analysing the current exposure of the Dutch population to air pollutants. 57 refs.

  2. 76 FR 365 - Exposure Modeling Public Meeting

    Science.gov (United States)

    2011-01-04

    ... classification for ecological risk assessments using aerial photography and GIS data. Dermal contact, movement... ENVIRONMENTAL PROTECTION AGENCY [EPA-HQ-OPP-2009-0879; FRL-8860-5] Exposure Modeling Public Meeting AGENCY: Environmental Protection Agency (EPA). ACTION: Notice. SUMMARY: An Exposure Modeling...

  3. QUALITY INSPECTION AND ANALYSIS OF THREE-DIMENSIONAL GEOGRAPHIC INFORMATION MODEL BASED ON OBLIQUE PHOTOGRAMMETRY

    Directory of Open Access Journals (Sweden)

    S. Dong

    2018-04-01

    Full Text Available In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

  4. Quality Inspection and Analysis of Three-Dimensional Geographic Information Model Based on Oblique Photogrammetry

    Science.gov (United States)

    Dong, S.; Yan, Q.; Xu, Y.; Bai, J.

    2018-04-01

    In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

  5. Web-Based Survey Application to Collect Contextually Relevant Geographic Data With Exposure Times: Application Development and Feasibility Testing

    Science.gov (United States)

    Tobin, Karin; Rudolph, Jonathan; Latkin, Carl

    2018-01-01

    Background Although studies that characterize the risk environment by linking contextual factors with individual-level data have advanced infectious disease and substance use research, there are opportunities to refine how we define relevant neighborhood exposures; this can in turn reduce the potential for exposure misclassification. For example, for those who do not inject at home, injection risk behaviors may be more influenced by the environment where they inject than where they live. Similarly, among those who spend more time away from home, a measure that accounts for different neighborhood exposures by weighting each unique location proportional to the percentage of time spent there may be more correlated with health behaviors than one’s residential environment. Objective This study aimed to develop a Web-based application that interacts with Google Maps application program interfaces (APIs) to collect contextually relevant locations and the amount of time spent in each. Our analysis examined the extent of overlap across different location types and compared different approaches for classifying neighborhood exposure. Methods Between May 2014 and March 2017, 547 participants enrolled in a Baltimore HIV care and prevention study completed an interviewer-administered Web-based survey that collected information about where participants were recruited, worked, lived, socialized, injected drugs, and spent most of their time. For each location, participants gave an address or intersection which they confirmed using Google Map and Street views. Geographic coordinates (and hours spent in each location) were joined to neighborhood indicators by Community Statistical Area (CSA). We computed a weighted exposure based on the proportion of time spent in each unique location. We compared neighborhood exposures based on each of the different location types with one another and the weighted exposure using analysis of variance with Bonferroni corrections to account for

  6. A growing social network model in geographical space

    Science.gov (United States)

    Antonioni, Alberto; Tomassini, Marco

    2017-09-01

    In this work we propose a new model for the generation of social networks that includes their often ignored spatial aspects. The model is a growing one and links are created either taking space into account, or disregarding space and only considering the degree of target nodes. These two effects can be mixed linearly in arbitrary proportions through a parameter. We numerically show that for a given range of the combination parameter, and for given mean degree, the generated network class shares many important statistical features with those observed in actual social networks, including the spatial dependence of connections. Moreover, we show that the model provides a good qualitative fit to some measured social networks.

  7. Model Checking Geographically Distributed Interlocking Systems Using UMC

    DEFF Research Database (Denmark)

    Fantechi, Alessandro; Haxthausen, Anne Elisabeth; Nielsen, Michel Bøje Randahl

    2017-01-01

    the relevant distributed protocols. By doing that we obey the safety guidelines of the railway signalling domain, that require formal methods to support the certification of such products. We also show how formal modelling can help designing alternative distributed solutions, while maintaining adherence...

  8. Modeling social networks in geographic space: approach and empirical application

    NARCIS (Netherlands)

    Arentze, T.A.; Berg, van den P.E.W.; Timmermans, H.J.P.

    2012-01-01

    Social activities are responsible for a large proportion of travel demands of individuals. Modeling of the social network of a studied population offers a basis to predict social travel in a more comprehensive way than currently is possible. In this paper we develop a method to generate a whole

  9. Landscape Epidemiology Modeling Using an Agent-Based Model and a Geographic Information System

    Directory of Open Access Journals (Sweden)

    S. M. Niaz Arifin

    2015-05-01

    Full Text Available A landscape epidemiology modeling framework is presented which integrates the simulation outputs from an established spatial agent-based model (ABM of malaria with a geographic information system (GIS. For a study area in Kenya, five landscape scenarios are constructed with varying coverage levels of two mosquito-control interventions. For each scenario, maps are presented to show the average distributions of three output indices obtained from the results of 750 simulation runs. Hot spot analysis is performed to detect statistically significant hot spots and cold spots. Additional spatial analysis is conducted using ordinary kriging with circular semivariograms for all scenarios. The integration of epidemiological simulation-based results with spatial analyses techniques within a single modeling framework can be a valuable tool for conducting a variety of disease control activities such as exploring new biological insights, monitoring epidemiological landscape changes, and guiding resource allocation for further investigation.

  10. Design and Establishment of Quality Model of Fundamental Geographic Information Database

    Science.gov (United States)

    Ma, W.; Zhang, J.; Zhao, Y.; Zhang, P.; Dang, Y.; Zhao, T.

    2018-04-01

    In order to make the quality evaluation for the Fundamental Geographic Information Databases(FGIDB) more comprehensive, objective and accurate, this paper studies and establishes a quality model of FGIDB, which formed by the standardization of database construction and quality control, the conformity of data set quality and the functionality of database management system, and also designs the overall principles, contents and methods of the quality evaluation for FGIDB, providing the basis and reference for carry out quality control and quality evaluation for FGIDB. This paper designs the quality elements, evaluation items and properties of the Fundamental Geographic Information Database gradually based on the quality model framework. Connected organically, these quality elements and evaluation items constitute the quality model of the Fundamental Geographic Information Database. This model is the foundation for the quality demand stipulation and quality evaluation of the Fundamental Geographic Information Database, and is of great significance on the quality assurance in the design and development stage, the demand formulation in the testing evaluation stage, and the standard system construction for quality evaluation technology of the Fundamental Geographic Information Database.

  11. Chapter three: methodology of exposure modeling

    CSIR Research Space (South Africa)

    Moschandreas, DJ

    2002-12-01

    Full Text Available methodologies and models are reviewed. Three exposure/measurement methodologies are assessed. Estimation methods focus on source evaluation and attribution, sources include those outdoors and indoors as well as in occupational and in-transit environments. Fate...

  12. Case control study of the geographic variability of exposure to disinfectant byproducts and risk for rectal cancer

    Directory of Open Access Journals (Sweden)

    Rogerson Peter A

    2007-05-01

    Full Text Available Abstract Background Levels of byproducts that result from the disinfection of drinking water vary within a water distribution system. This prompted us to question whether the risk for rectal cancer also varies, depending upon one's long term geographic location within the system. Such a geographic distribution in rectal cancer risk would follow naturally from an association between level of byproduct and rectal cancer risk. We assess the effects of estimated geographic variability in exposure to some of the components of the trihalomethane group of disinfectant byproducts (DBPs on the odds ratios and probabilities for rectal cancer in white males in a case control study of 128 cases and 253 controls, conducted in Monroe County, Western New York State, U.S.A. The study was designed around health data initially collected at the University at Buffalo (Department of Social and Preventative Medicine as part of the Upstate New York Diet Study, and trihalomethane (THM data collected from a separate independent study of THMs conducted by Monroe County Department of Health. Case participants were chosen from hospital pathology records. The controls are disease-free white males between 35–90 years old, living in Monroe County, and chosen from control groups for studies from cancer of five other (unrelated sites. Using a combination of case control methodology and spatial analysis, the spatial patterns of THMs and individual measures of tap water consumption provide estimates of the effects of ingestion of specific amounts of some DBPs on rectal cancer risk. Trihalomethane (THM data were used to spatially interpolate levels at the taps of cases and controls, and odds ratios were estimated using logistic regression to assess the effects of estimated THM exposure dose on cancer risk, adjusting for alcohol, dietary beta carotene intake, tap water intake, and total caloric intake. Results Trihalomethane levels varied spatially within the county; although

  13. CONSEXPO 3.0, consumer exposure and uptake models

    NARCIS (Netherlands)

    Veen MP van; LBM

    2001-01-01

    The report provides a modelling approach to consumer exposure to chemicals, based on mathematical contact, exposure and uptake models. For each route of exposure, a number of exposure and uptake models are included. A general framework joins the exposure and uptake models selected by the user. By

  14. Estimators for longitudinal latent exposure models: examining measurement model assumptions.

    Science.gov (United States)

    Sánchez, Brisa N; Kim, Sehee; Sammel, Mary D

    2017-06-15

    Latent variable (LV) models are increasingly being used in environmental epidemiology as a way to summarize multiple environmental exposures and thus minimize statistical concerns that arise in multiple regression. LV models may be especially useful when multivariate exposures are collected repeatedly over time. LV models can accommodate a variety of assumptions but, at the same time, present the user with many choices for model specification particularly in the case of exposure data collected repeatedly over time. For instance, the user could assume conditional independence of observed exposure biomarkers given the latent exposure and, in the case of longitudinal latent exposure variables, time invariance of the measurement model. Choosing which assumptions to relax is not always straightforward. We were motivated by a study of prenatal lead exposure and mental development, where assumptions of the measurement model for the time-changing longitudinal exposure have appreciable impact on (maximum-likelihood) inferences about the health effects of lead exposure. Although we were not particularly interested in characterizing the change of the LV itself, imposing a longitudinal LV structure on the repeated multivariate exposure measures could result in high efficiency gains for the exposure-disease association. We examine the biases of maximum likelihood estimators when assumptions about the measurement model for the longitudinal latent exposure variable are violated. We adapt existing instrumental variable estimators to the case of longitudinal exposures and propose them as an alternative to estimate the health effects of a time-changing latent predictor. We show that instrumental variable estimators remain unbiased for a wide range of data generating models and have advantages in terms of mean squared error. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  15. Parameter estimation and statistical test of geographically weighted bivariate Poisson inverse Gaussian regression models

    Science.gov (United States)

    Amalia, Junita; Purhadi, Otok, Bambang Widjanarko

    2017-11-01

    Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.

  16. Integrating Geographical Information Systems (GIS) with Hydrological Modelling – Applicability and Limitations

    OpenAIRE

    Rajesh VijayKumar Kherde; Dr. Priyadarshi. H. Sawant

    2013-01-01

    The evolution of Geographic information systems (GIS) facilitated the use digital terrain data for topography based hydrological modelling. The use of spatial data for hydrological modelling emerged from the great capability of GIS tools to store and handle the data associated hydro-morphology of the basin. These models utilize the spatially variable terrain data for converting rainfall into surface runoff.Manual map manipulation has always posed difficulty in analysing and designing large sc...

  17. A framework to specify agent-based models in geographic sciences

    OpenAIRE

    Grueau, Cédric; Araújo, João

    2015-01-01

    Agent-Based Modeling (ABM) and simulation have gained popularity in the Geographic Information Systems (GIS) domain. Despite the increasing number of models built by experts and users, it remains challenging for users to specify their models in a manner in which one can understand it. This constraint represents an inhibition to the development and acceptance of the ABM approach. In this paper, we raise the questions that need to be answered in order to cope with ABM specification issues. We r...

  18. The role of geographical ecological studies in identifying diseases linked to UVB exposure and/or vitamin D.

    Science.gov (United States)

    Grant, William B

    2016-01-01

    Using a variety of approaches, researchers have studied the health effects of solar ultraviolet (UV) radiation exposure and vitamin D. This review compares the contributions from geographical ecological studies with those of observational studies and clinical trials. Health outcomes discussed were based on the author's knowledge and include anaphylaxis/food allergy, atopic dermatitis and eczema, attention deficit hyperactivity disorder, autism, back pain, cancer, dental caries, diabetes mellitus type 1, hypertension, inflammatory bowel disease, lupus, mononucleosis, multiple sclerosis, Parkinson disease, pneumonia, rheumatoid arthritis, and sepsis. Important interactions have taken place between study types; sometimes ecological studies were the first to report an inverse correlation between solar UVB doses and health outcomes such as for cancer, leading to both observational studies and clinical trials. In other cases, ecological studies added to the knowledge base. Many ecological studies include other important risk-modifying factors, thereby minimizing the chance of reporting the wrong link. Laboratory studies of mechanisms generally support the role of vitamin D in the outcomes discussed. Indications exist that for some outcomes, UVB effects may be independent of vitamin D. This paper discusses the concept of the ecological fallacy, noting that it applies to all epidemiological studies.

  19. Media Exposure: How Models Simplify Sampling

    DEFF Research Database (Denmark)

    Mortensen, Peter Stendahl

    1998-01-01

    In media planning, the distribution of exposures to more ad spots in more media (print, TV, radio) is crucial to the evaluation of the campaign. If such information should be sampled, it would only be possible in expensive panel-studies (eg TV-meter panels). Alternatively, the distribution...... of exposures may be modelled statistically, using the Beta distribution combined with the Binomial Distribution. Examples are given....

  20. Development of a new fuzzy exposure model

    International Nuclear Information System (INIS)

    Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira; Texeira, Marcello Goulart

    2007-01-01

    The main topic of this study is the development of an exposure fuzzy model to evaluate the exposure of inhabitants in an area containing uranium, which present a high natural background. In this work, a fuzzy model was created, based on some of the following main factors: activity concentration of uranium, physiological factors and characteristic customs of the exposed individuals. An inference block was created to evaluate some factors of radiation exposure. For this, AHP-fuzzy technique (Analytic Hierarchic Process) was used and its application was demonstrated for a subjected population to the radiation of the natural uranium. The Mandami type fuzzy model was also created from the opinion of specialists. The Monte Carlo method was used to generate a statistics of input data and the daily average exposure served as comparison parameter between the three techniques. The output fuzzy sets were expressed in form of linguistic variables, such as high, medium and low. In the qualitative analysis, the obtained results were satisfactory when translating the opinion of the specialists. In the quantitative analysis, the obtained values are part of the same fuzzy set as the values found in literature. The global results suggest that this type of fuzzy model is highly promising for analysis of exposure to ionizing radiation. (author)

  1. Development of a new fuzzy exposure model

    Energy Technology Data Exchange (ETDEWEB)

    Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira [Universidade Federal de Pernambuco (UFPE), Recife, PE (Brazil). Dept. de Energia Nuclear. Grupo de Engenharia de Reatores], E-mail: wagner@ufpe.br, E-mail: cabol@ufpe.br; Texeira, Marcello Goulart [Instituto Militar de Engenharia (IME), Rio de Janeiro, RJ (Brazil). Terrestrial Modelling Group], E-mail: marcellogt@ime.eb.br

    2007-07-01

    The main topic of this study is the development of an exposure fuzzy model to evaluate the exposure of inhabitants in an area containing uranium, which present a high natural background. In this work, a fuzzy model was created, based on some of the following main factors: activity concentration of uranium, physiological factors and characteristic customs of the exposed individuals. An inference block was created to evaluate some factors of radiation exposure. For this, AHP-fuzzy technique (Analytic Hierarchic Process) was used and its application was demonstrated for a subjected population to the radiation of the natural uranium. The Mandami type fuzzy model was also created from the opinion of specialists. The Monte Carlo method was used to generate a statistics of input data and the daily average exposure served as comparison parameter between the three techniques. The output fuzzy sets were expressed in form of linguistic variables, such as high, medium and low. In the qualitative analysis, the obtained results were satisfactory when translating the opinion of the specialists. In the quantitative analysis, the obtained values are part of the same fuzzy set as the values found in literature. The global results suggest that this type of fuzzy model is highly promising for analysis of exposure to ionizing radiation. (author)

  2. The distance-decay function of geographical gravity model: Power law or exponential law?

    International Nuclear Information System (INIS)

    Chen, Yanguang

    2015-01-01

    Highlights: •The distance-decay exponent of the gravity model is a fractal dimension. •Entropy maximization accounts for the gravity model based on power law decay. •Allometric scaling relations relate gravity models with spatial interaction models. •The four-parameter gravity models have dual mathematical expressions. •The inverse power law is the most probable distance-decay function. -- Abstract: The distance-decay function of the geographical gravity model is originally an inverse power law, which suggests a scaling process in spatial interaction. However, the distance exponent of the model cannot be reasonably explained with the ideas from Euclidean geometry. This results in a dimension dilemma in geographical analysis. Consequently, a negative exponential function was used to replace the inverse power function to serve for a distance-decay function. But a new puzzle arose that the exponential-based gravity model goes against the first law of geography. This paper is devoted for solving these kinds of problems by mathematical reasoning and empirical analysis. New findings are as follows. First, the distance exponent of the gravity model is demonstrated to be a fractal dimension using the geometric measure relation. Second, the similarities and differences between the gravity models and spatial interaction models are revealed using allometric relations. Third, a four-parameter gravity model possesses a symmetrical expression, and we need dual gravity models to describe spatial flows. The observational data of China's cities and regions (29 elements indicative of 841 data points) in 2010 are employed to verify the theoretical inferences. A conclusion can be reached that the geographical gravity model based on power-law decay is more suitable for analyzing large, complex, and scale-free regional and urban systems. This study lends further support to the suggestion that the underlying rationale of fractal structure is entropy maximization. Moreover

  3. Comparison of average global exposure of population induced by a macro 3G network in different geographical areas in France and Serbia.

    Science.gov (United States)

    Huang, Yuanyuan; Varsier, Nadège; Niksic, Stevan; Kocan, Enis; Pejanovic-Djurisic, Milica; Popovic, Milica; Koprivica, Mladen; Neskovic, Aleksandar; Milinkovic, Jelena; Gati, Azeddine; Person, Christian; Wiart, Joe

    2016-09-01

    This article is the first thorough study of average population exposure to third generation network (3G)-induced electromagnetic fields (EMFs), from both uplink and downlink radio emissions in different countries, geographical areas, and for different wireless device usages. Indeed, previous publications in the framework of exposure to EMFs generally focused on individual exposure coming from either personal devices or base stations. Results, derived from device usage statistics collected in France and Serbia, show a strong heterogeneity of exposure, both in time, that is, the traffic distribution over 24 h was found highly variable, and space, that is, the exposure to 3G networks in France was found to be roughly two times higher than in Serbia. Such heterogeneity is further explained based on real data and network architecture. Among those results, authors show that, contrary to popular belief, exposure to 3G EMFs is dominated by uplink radio emissions, resulting from voice and data traffic, and average population EMF exposure differs from one geographical area to another, as well as from one country to another, due to the different cellular network architectures and variability of mobile usage. Bioelectromagnetics. 37:382-390, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  4. A Geographic Information System approach to modeling nutrient and sediment transport

    Energy Technology Data Exchange (ETDEWEB)

    Levine, D.A. [Automated Sciences Group, Inc., Oak Ridge, TN (United States); Hunsaker, C.T.; Beauchamp, J.J. [Oak Ridge National Lab., TN (United States); Timmins, S.P. [Analysas Corp., Oak Ridge, TN (United States)

    1993-02-01

    The objective of this study was to develop a water quality model to quantify nonpoint-source (NPS) pollution that uses a geographic information system (GIS) to link statistical modeling of nutrient and sediment delivery with the spatial arrangement of the parameters that drive the model. The model predicts annual nutrient and sediment loading and was developed, calibrated, and tested on 12 watersheds within the Lake Ray Roberts drainage basin in north Texas. Three physiographic regions are represented by these watersheds, and model success, as measured by the accuracy of load estimates, was compared within and across these regions.

  5. Application of a random walk model to geographic distributions of animal mitochondrial DNA variation.

    Science.gov (United States)

    Neigel, J E; Avise, J C

    1993-12-01

    In rapidly evolving molecules, such as animal mitochondrial DNA, mutations that delineate specific lineages may not be dispersed at sufficient rates to attain an equilibrium between genetic drift and gene flow. Here we predict conditions that lead to nonequilibrium geographic distributions of mtDNA lineages, test the robustness of these predictions and examine mtDNA data sets for consistency with our model. Under a simple isolation by distance model, the variance of an mtDNA lineage's geographic distribution is expected be proportional to its age. Simulation results indicated that this relationship is fairly robust. Analysis of mtDNA data from natural populations revealed three qualitative distributional patterns: (1) significant departure of lineage structure from equilibrium geographic distributions, a pattern exhibited in three rodent species with limited dispersal; (2) nonsignificant departure from equilibrium expectations, exhibited by two avian and two marine fish species with potentials for relatively long-distance dispersal; and (3) a progression from nonequilibrium distributions for younger lineages to equilibrium distributions for older lineages, a condition displayed by one surveyed avian species. These results demonstrate the advantages of considering mutation and genealogy in the interpretation of mtDNA geographic variation.

  6. Russian and Foreign Experience of Integration of Agent-Based Models and Geographic Information Systems

    Directory of Open Access Journals (Sweden)

    Konstantin Anatol’evich Gulin

    2016-11-01

    Full Text Available The article provides an overview of the mechanisms of integration of agent-based models and GIS technology developed by Russian and foreign researchers. The basic framework of the article is based on critical analysis of domestic and foreign literature (monographs, scientific articles. The study is based on the application of universal scientific research methods: system approach, analysis and synthesis, classification, systematization and grouping, generalization and comparison. The article presents theoretical and methodological bases of integration of agent-based models and geographic information systems. The concept and essence of agent-based models are explained; their main advantages (compared to other modeling methods are identified. The paper characterizes the operating environment of agents as a key concept in the theory of agent-based modeling. It is shown that geographic information systems have a wide range of information resources for calculations, searching, modeling of the real world in various aspects, acting as an effective tool for displaying the agents’ operating environment and allowing to bring the model as close as possible to the real conditions. The authors also focus on a wide range of possibilities for various researches in different spatial and temporal contexts. Comparative analysis of platforms supporting the integration of agent-based models and geographic information systems has been carried out. The authors give examples of complex socio-economic models: the model of a creative city, humanitarian assistance model. In the absence of standards for research results description, the authors focus on the models’ elements such as the characteristics of the agents and their operation environment, agents’ behavior, rules of interaction between the agents and the external environment. The paper describes the possibilities and prospects of implementing these models

  7. Hospital distribution in a metropolitan city: assessment by a geographical information system grid modelling approach

    Directory of Open Access Journals (Sweden)

    Kwang-Soo Lee

    2014-05-01

    Full Text Available Grid models were used to assess urban hospital distribution in Seoul, the capital of South Korea. A geographical information system (GIS based analytical model was developed and applied to assess the situation in a metropolitan area with a population exceeding 10 million. Secondary data for this analysis were obtained from multiple sources: the Korean Statistical Information Service, the Korean Hospital Association and the Statistical Geographical Information System. A grid of cells measuring 1 × 1 km was superimposed on the city map and a set of variables related to population, economy, mobility and housing were identified and measured for each cell. Socio-demographic variables were included to reflect the characteristics of each area. Analytical models were then developed using GIS software with the number of hospitals as the dependent variable. Applying multiple linear regression and geographically weighted regression models, three factors (highway and major arterial road areas; number of subway entrances; and row house areas were statistically significant in explaining the variance of hospital distribution for each cell. The overall results show that GIS is a useful tool for analysing and understanding location strategies. This approach appears a useful source of information for decision-makers concerned with the distribution of hospitals and other health care centres in a city.

  8. Robust geographically weighted regression of modeling the Air Polluter Standard Index (APSI)

    Science.gov (United States)

    Warsito, Budi; Yasin, Hasbi; Ispriyanti, Dwi; Hoyyi, Abdul

    2018-05-01

    The Geographically Weighted Regression (GWR) model has been widely applied to many practical fields for exploring spatial heterogenity of a regression model. However, this method is inherently not robust to outliers. Outliers commonly exist in data sets and may lead to a distorted estimate of the underlying regression model. One of solution to handle the outliers in the regression model is to use the robust models. So this model was called Robust Geographically Weighted Regression (RGWR). This research aims to aid the government in the policy making process related to air pollution mitigation by developing a standard index model for air polluter (Air Polluter Standard Index - APSI) based on the RGWR approach. In this research, we also consider seven variables that are directly related to the air pollution level, which are the traffic velocity, the population density, the business center aspect, the air humidity, the wind velocity, the air temperature, and the area size of the urban forest. The best model is determined by the smallest AIC value. There are significance differences between Regression and RGWR in this case, but Basic GWR using the Gaussian kernel is the best model to modeling APSI because it has smallest AIC.

  9. A geographic information system-based 3D city estate modeling and simulation system

    Science.gov (United States)

    Chong, Xiaoli; Li, Sha

    2015-12-01

    This paper introduces a 3D city simulation system which is based on geographic information system (GIS), covering all commercial housings of the city. A regional- scale, GIS-based approach is used to capture, describe, and track the geographical attributes of each house in the city. A sorting algorithm of "Benchmark + Parity Rate" is developed to cluster houses with similar spatial and construction attributes. This system is applicable for digital city modeling, city planning, housing evaluation, housing monitoring, and visualizing housing transaction. Finally, taking Jingtian area of Shenzhen as an example, the each unit of 35,997 houses in the area could be displayed, tagged, and easily tracked by the GIS-based city modeling and simulation system. The match market real conditions well and can be provided to house buyers as reference.

  10. Latitude, sunshine, and human lactase phenotype distributions may contribute to geographic patterns of modern disease: the inflammatory bowel disease model

    Directory of Open Access Journals (Sweden)

    Szilagyi A

    2014-05-01

    Full Text Available Andrew Szilagyi,1 Henry Leighton,2 Barry Burstein,3 Xiaoqing Xue41Division of Gastroenterology, Department of Medicine, Jewish General Hospital, 2Department of Atmospheric and Oceanic Sciences, 3Department of Medicine, Jewish General Hospital, 4Department of Emergency Medicine, Jewish General Hospital, McGill University, Montreal, QC, CanadaAbstract: Countries with high lactase nonpersistence (LNP or low lactase persistence (LP populations have lower rates of some “western” diseases, mimicking the effects of sunshine and latitude. Inflammatory bowel disease (IBD, ie, Crohn's disease and ulcerative colitis, is putatively also influenced by sunshine. Recent availability of worldwide IBD rates and lactase distributions allows more extensive comparisons. The aim of this study was to evaluate the extent to which modern day lactase distributions interact with latitude, sunshine exposure, and IBD rates. National IBD rates, national distributions of LP/LNP, and population-weighted average national annual ultraviolet B exposure were obtained, estimated, or calculated from the literature. Negative binomial analysis was used to assess the relationship between the three parameters and IBD rates. Analyses for 55 countries were grouped in three geographic domains, ie, global, Europe, and non-Europe. In Europe, both latitude and ultraviolet B exposure correlate well with LP/LNP and IBD. In non-Europe, latitude and ultraviolet B exposure correlate weakly with LP/LNP, but the latter retains a more robust correlation with IBD. In univariate analysis, latitude, ultraviolet B exposure, and LP/LNP all had significant relationships with IBD. Multivariate analysis showed that lactase distributions provided the best model of fit for IBD. The model of IBD reveals the evolutionary effects of the human lactase divide, and suggests that latitude, ultraviolet B exposure, and LP/LNP mimic each other because LP/LNP follows latitudinal directions toward the equator

  11. Modeling residential exposure to secondhand tobacco smoke

    Science.gov (United States)

    Klepeis, Neil E.; Nazaroff, William W.

    We apply a simulation model to explore the effect of a house's multicompartment character on a nonsmoker's inhalation exposure to secondhand tobacco smoke (SHS). The model tracks the minute-by-minute movement of people and pollutants among multiple zones of a residence and generates SHS pollutant profiles for each room in response to room-specific smoking patterns. In applying the model, we consider SHS emissions of airborne particles, nicotine, and carbon monoxide in two hypothetical houses, one with a typical four-room layout and one dominated by a single large space. We use scripted patterns of room-to-room occupant movement and a cohort of 5000 activity patterns sampled from a US nationwide survey. The results for scripted and cohort simulation trials indicate that the multicompartment nature of homes, manifested as inter-room differences in pollutant levels and the movement of people among zones, can cause substantial variation in nonsmoker SHS exposure.

  12. [Analysis on the exposure level and geographic distribution trend of toxicological indicators in rural drinking water, Shandong Province, in 2015].

    Science.gov (United States)

    Shi, F; Lyu, S P; Kong, F L; Yang, X T; Zhou, J Y

    2017-09-06

    Objective: To analyze the exposure level and the geographical distribution trend of toxicological indicators of rural drinking water in Shandong Province. Methods: The drawing method was used to randomly select no less than 60% villages and towns from 137 counties (cities, districts) of 17 cities in Shandong Province in 2015, and then 1-3 rural centralized water supply units were selected according to the circumstance of rural centralized water supply units in each village and town. In total, 735 villages and towns, 1 473 rural centralized water supply units were selected, and 1 473 water samples were collected. The water treatment process, water supply population and other circumstances of the rural centralized water supply units were investigated, the water quality was monitored, the content of toxicological indicators of drinking water in different areas was compared, and the trend surface isogram of excessive toxicological indicators was drawn. Results: The qualified rate of toxicological indicators in 1 473 water samples was 83.64% ( n =1 232). The main toxicological indicators that affected the qualified rate of toxicological indicators of drinking water in rural areas in Shandong Province were nitrate and fluoride. The excessive rate of fluoride was 5.70% ( n =84) and the exposed population was 1 736 709 (4.22%). The excessive rate of nitrate (as nitrogen) was 12.29% ( n =181) and the exposed population was 1 393 612 (3.39%). The P (5)0 content of fluoride in the eastern, middle and western regions was 0.24, 0.29 and 0.59 mg/L, respective;which was higher in the western region than in the east and the middle regions ( P 0.05). The P (50) content of nitrate (as nitrogen) in the eastern, middle and western regions was 8.00, 7.48, and 2.00 mg/L, which was higher in the eastern and middle regions than in the west region ( P 0.05). The trend surface isogram of nitrate and fluoride content showed that the content of nitrate (as nitrogen) in rural drinking water in

  13. Modeling the Geographic Consequence and Pattern of Dengue Fever Transmission in Thailand.

    Science.gov (United States)

    Bekoe, Collins; Pansombut, Tatdow; Riyapan, Pakwan; Kakchapati, Sampurna; Phon-On, Aniruth

    2017-05-04

    Dengue fever is one of the infectious diseases that is still a public health problem in Thailand. This study considers in detail, the geographic consequence, seasonal and pattern of dengue fever transmission among the 76 provinces of Thailand from 2003 to 2015. A cross-sectional study. The data for the study was from the Department of Disease Control under the Bureau of Epidemiology, Thailand. The quarterly effects and location on the transmission of dengue was modeled using an alternative additive log-linear model. The model fitted well as illustrated by the residual plots and the  Again, the model showed that dengue fever is high in the second quarter of every year from May to August. There was an evidence of an increase in the trend of dengue annually from 2003 to 2015. There was a difference in the distribution of dengue fever within and between provinces. The areas of high risks were the central and southern regions of Thailand. The log-linear model provided a simple medium of modeling dengue fever transmission. The results are very important in the geographic distribution of dengue fever patterns.

  14. Land Use Regression Modeling of Outdoor Noise Exposure in Informal Settlements in Western Cape, South Africa.

    Science.gov (United States)

    Sieber, Chloé; Ragettli, Martina S; Brink, Mark; Toyib, Olaniyan; Baatjies, Roslyn; Saucy, Apolline; Probst-Hensch, Nicole; Dalvie, Mohamed Aqiel; Röösli, Martin

    2017-10-20

    In low- and middle-income countries, noise exposure and its negative health effects have been little explored. The present study aimed to assess the noise exposure situation in adults living in informal settings in the Western Cape Province, South Africa. We conducted continuous one-week outdoor noise measurements at 134 homes in four different areas. These data were used to develop a land use regression (LUR) model to predict A-weighted day-evening-night equivalent sound levels (L den ) from geographic information system (GIS) variables. Mean noise exposure during day (6:00-18:00) was 60.0 A-weighted decibels (dB(A)) (interquartile range 56.9-62.9 dB(A)), during night (22:00-6:00) 52.9 dB(A) (49.3-55.8 dB(A)) and average L den was 63.0 dB(A) (60.1-66.5 dB(A)). Main predictors of the LUR model were related to road traffic and household density. Model performance was low (adjusted R 2 = 0.130) suggesting that other influences than those represented in the geographic predictors are relevant for noise exposure. This is one of the few studies on the noise exposure situation in low- and middle-income countries. It demonstrates that noise exposure levels are high in these settings.

  15. Land Use Regression Modeling of Outdoor Noise Exposure in Informal Settlements in Western Cape, South Africa

    Science.gov (United States)

    Sieber, Chloé; Ragettli, Martina S.; Toyib, Olaniyan; Baatjies, Roslyn; Saucy, Apolline; Probst-Hensch, Nicole; Dalvie, Mohamed Aqiel; Röösli, Martin

    2017-01-01

    In low- and middle-income countries, noise exposure and its negative health effects have been little explored. The present study aimed to assess the noise exposure situation in adults living in informal settings in the Western Cape Province, South Africa. We conducted continuous one-week outdoor noise measurements at 134 homes in four different areas. These data were used to develop a land use regression (LUR) model to predict A-weighted day-evening-night equivalent sound levels (Lden) from geographic information system (GIS) variables. Mean noise exposure during day (6:00–18:00) was 60.0 A-weighted decibels (dB(A)) (interquartile range 56.9–62.9 dB(A)), during night (22:00–6:00) 52.9 dB(A) (49.3–55.8 dB(A)) and average Lden was 63.0 dB(A) (60.1–66.5 dB(A)). Main predictors of the LUR model were related to road traffic and household density. Model performance was low (adjusted R2 = 0.130) suggesting that other influences than those represented in the geographic predictors are relevant for noise exposure. This is one of the few studies on the noise exposure situation in low- and middle-income countries. It demonstrates that noise exposure levels are high in these settings. PMID:29053590

  16. Advanced model for expansion of natural gas distribution networks based on geographic information systems

    Energy Technology Data Exchange (ETDEWEB)

    Ramirez-Rosado, I.J.; Fernandez-Jimenez, L.A.; Garcia-Garrido, E.; Zorzano-Santamaria, P.; Zorzano-Alba, E. [La Rioja Univ., La Rioja (Spain). Dept. of Electrical Engineering; Miranda, V.; Montneiro, C. [Porto Univ., Porto (Portugal). Faculty of Engineering]|[Inst. de Engenharia de Sistemas e Computadores do Porto, Porto (Portugal)

    2005-07-01

    An advanced geographic information system (GIS) model of natural gas distribution networks was presented. The raster-based model was developed to evaluate costs associated with the expansion of electrical networks due to increased demand in the La Rioja region of Spain. The model was also used to evaluate costs associated with maintenance and amortization of the already existing distribution network. Expansion costs of the distribution network were modelled in various demand scenarios. The model also considered a variety of technical factors associated with pipeline length and topography. Soil and slope data from previous pipeline projects were used to estimate real costs per unit length of pipeline. It was concluded that results obtained by the model will be used by planners to select zones where expansion is economically feasible. 4 refs., 5 figs.

  17. A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

    Science.gov (United States)

    Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

    2005-01-01

    This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

  18. Modeling of geographical pricing: A game analysis of siberian fuel costs

    Science.gov (United States)

    Sivushina, Anastasiya; Kombu, Anchy; Ryumkin, Valeriy

    2017-11-01

    In the present study, we propose a novel game-theoretic pricing model describing the interaction between producers and retailers of goods in conditions of poor transport infrastructure and sparse geographical distribution of the points of sale. The proposed model generalizes the Stackelberg leadership model for an arbitrary number of leaders and followers. We show that the model always has a Nash and Stackelberg equilibria. We also provide formulas for the equilibrium prices and volume of sales. As an example we model diesel pricing in south Siberia. Our model found no signs of a cartel. The results of this paper can be used by policymakers to inform market regulations aimed at promoting free competition and avoiding monopolies in production and retail of goods.

  19. Handbook on advances in remote sensing and geographic information systems paradigms and applications in forest landscape modeling

    CERN Document Server

    Favorskaya, Margarita N

    2017-01-01

    This book presents the latest advances in remote-sensing and geographic information systems and applications. It is divided into four parts, focusing on Airborne Light Detection and Ranging (LiDAR) and Optical Measurements of Forests; Individual Tree Modelling; Landscape Scene Modelling; and Forest Eco-system Modelling. Given the scope of its coverage, the book offers a valuable resource for students, researchers, practitioners, and educators interested in remote sensing and geographic information systems and applications.

  20. Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).

    Science.gov (United States)

    Akil, Luma; Ahmad, H Anwar

    2016-03-03

    Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the extent of Salmonella and Escherichia coli infections in MS, and determine the Salmonella infections correlation with socioeconomic status using geographical information system (GIS) and neural network models. In this study, the relevant updated data of foodborne illness for southern states, from 2002 to 2011, were collected and used in the GIS and neural networks models. Data were collected from the Centers for Disease Control and Prevention (CDC), MS state Department of Health and the other states department of health. The correlation between low socioeconomic status and Salmonella infections were determined using models created by several software packages, including SAS, ArcGIS @RISK and NeuroShell. Results of this study showed a significant increase in Salmonella outbreaks in MS during the study period, with highest rates in 2011 (47.84 ± 24.41 cases/100,000; pGIS maps of Salmonella outbreaks in MS in 2010 and 2011 showed the districts with higher rates of Salmonella. Regression analysis and neural network models showed a moderate correlation between cases of Salmonella infections and low socioeconomic factors. Poverty was shown to have a negative correlation with Salmonella outbreaks (R(2)=0.152, p<0.05). Geographic location besides socioeconomic status may contribute to the high rates of Salmonella outbreaks in MS. Understanding the geographical and economic relationship with infectious diseases will help to determine effective methods to reduce outbreaks within low socioeconomic status communities. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  1. Analysis of errors introduced by geographic coordinate systems on weather numeric prediction modeling

    Directory of Open Access Journals (Sweden)

    Y. Cao

    2017-09-01

    Full Text Available Most atmospheric models, including the Weather Research and Forecasting (WRF model, use a spherical geographic coordinate system to internally represent input data and perform computations. However, most geographic information system (GIS input data used by the models are based on a spheroid datum because it better represents the actual geometry of the earth. WRF and other atmospheric models use these GIS input layers as if they were in a spherical coordinate system without accounting for the difference in datum. When GIS layers are not properly reprojected, latitudinal errors of up to 21 km in the midlatitudes are introduced. Recent studies have suggested that for very high-resolution applications, the difference in datum in the GIS input data (e.g., terrain land use, orography should be taken into account. However, the magnitude of errors introduced by the difference in coordinate systems remains unclear. This research quantifies the effect of using a spherical vs. a spheroid datum for the input GIS layers used by WRF to study greenhouse gas transport and dispersion in northeast Pennsylvania.

  2. New spatial clustering-based models for optimal urban facility location considering geographical obstacles

    Science.gov (United States)

    Javadi, Maryam; Shahrabi, Jamal

    2014-03-01

    The problems of facility location and the allocation of demand points to facilities are crucial research issues in spatial data analysis and urban planning. It is very important for an organization or governments to best locate its resources and facilities and efficiently manage resources to ensure that all demand points are covered and all the needs are met. Most of the recent studies, which focused on solving facility location problems by performing spatial clustering, have used the Euclidean distance between two points as the dissimilarity function. Natural obstacles, such as mountains and rivers, can have drastic impacts on the distance that needs to be traveled between two geographical locations. While calculating the distance between various supply chain entities (including facilities and demand points), it is necessary to take such obstacles into account to obtain better and more realistic results regarding location-allocation. In this article, new models were presented for location of urban facilities while considering geographical obstacles at the same time. In these models, three new distance functions were proposed. The first function was based on the analysis of shortest path in linear network, which was called SPD function. The other two functions, namely PD and P2D, were based on the algorithms that deal with robot geometry and route-based robot navigation in the presence of obstacles. The models were implemented in ArcGIS Desktop 9.2 software using the visual basic programming language. These models were evaluated using synthetic and real data sets. The overall performance was evaluated based on the sum of distance from demand points to their corresponding facilities. Because of the distance between the demand points and facilities becoming more realistic in the proposed functions, results indicated desired quality of the proposed models in terms of quality of allocating points to centers and logistic cost. Obtained results show promising

  3. Soil erosion fragility assessment using an impact model and geographic information system

    OpenAIRE

    Jorge,Luiz Alberto Blanco

    2009-01-01

    A study was taken in a 1566 ha watershed situated in the Capivara River basin, municipality of Botucatu, São Paulo State, Brazil. This environment is fragile and can be subjected to different forms of negative impacts, among them soil erosion by water. The main objective of the research was to develop a methodology for the assessment of soil erosion fragility at the various different watershed positions, using the geographic information system ILWIS version 3.3 for Windows. An impact model wa...

  4. Long- and short-term exposure to PM2.5 and mortality: using novel exposure models.

    Science.gov (United States)

    Kloog, Itai; Ridgway, Bill; Koutrakis, Petros; Coull, Brent A; Schwartz, Joel D

    2013-07-01

    Many studies have reported associations between ambient particulate matter (PM) and adverse health effects, focused on either short-term (acute) or long-term (chronic) PM exposures. For chronic effects, the studied cohorts have rarely been representative of the population. We present a novel exposure model combining satellite aerosol optical depth and land-use data to investigate both the long- and short-term effects of PM2.5 exposures on population mortality in Massachusetts, United States, for the years 2000-2008. All deaths were geocoded. We performed two separate analyses: a time-series analysis (for short-term exposure) where counts in each geographic grid cell were regressed against cell-specific short-term PM2.5 exposure, temperature, socioeconomic data, lung cancer rates (as a surrogate for smoking), and a spline of time (to control for season and trends). In addition, for long-term exposure, we performed a relative incidence analysis using two long-term exposure metrics: regional 10 × 10 km PM2.5 predictions and local deviations from the cell average based on land use within 50 m of the residence. We tested whether these predicted the proportion of deaths from PM-related causes (cardiovascular and respiratory diseases). For short-term exposure, we found that for every 10-µg/m increase in PM 2.5 exposure there was a 2.8% increase in PM-related mortality (95% confidence interval [CI] = 2.0-3.5). For the long-term exposure at the grid cell level, we found an odds ratio (OR) for every 10-µg/m increase in long-term PM2.5 exposure of 1.6 (CI = 1.5-1.8) for particle-related diseases. Local PM2.5 had an OR of 1.4 (CI = 1.3-1.5), which was independent of and additive to the grid cell effect. We have developed a novel PM2.5 exposure model based on remote sensing data to assess both short- and long-term human exposures. Our approach allows us to gain spatial resolution in acute effects and an assessment of long-term effects in the entire population rather than a

  5. Modeling the adoption of innovations in the presence of geographic and media influences.

    Directory of Open Access Journals (Sweden)

    Jameson L Toole

    Full Text Available While there is a large body of work examining the effects of social network structure on innovation adoption, models to date have lacked considerations of real geography or mass media. In this article, we show these features are crucial to making more accurate predictions of a social contagion and technology adoption at a city-to-city scale. Using data from the adoption of the popular micro-blogging platform, Twitter, we present a model of adoption on a network that places friendships in real geographic space and exposes individuals to mass media influence. We show that homophily both among individuals with similar propensities to adopt a technology and geographic location is critical to reproducing features of real spatiotemporal adoption. Furthermore, we estimate that mass media was responsible for increasing Twitter's user base two to four fold. To reflect this strength, we extend traditional contagion models to include an endogenous mass media agent that responds to those adopting an innovation as well as influencing agents to adopt themselves.

  6. Modeling the adoption of innovations in the presence of geographic and media influences.

    Science.gov (United States)

    Toole, Jameson L; Cha, Meeyoung; González, Marta C

    2012-01-01

    While there is a large body of work examining the effects of social network structure on innovation adoption, models to date have lacked considerations of real geography or mass media. In this article, we show these features are crucial to making more accurate predictions of a social contagion and technology adoption at a city-to-city scale. Using data from the adoption of the popular micro-blogging platform, Twitter, we present a model of adoption on a network that places friendships in real geographic space and exposes individuals to mass media influence. We show that homophily both among individuals with similar propensities to adopt a technology and geographic location is critical to reproducing features of real spatiotemporal adoption. Furthermore, we estimate that mass media was responsible for increasing Twitter's user base two to four fold. To reflect this strength, we extend traditional contagion models to include an endogenous mass media agent that responds to those adopting an innovation as well as influencing agents to adopt themselves.

  7. EXPOSURE ANALYSIS MODELING SYSTEM (EXAMS): USER MANUAL AND SYSTEM DOCUMENTATION

    Science.gov (United States)

    The Exposure Analysis Modeling System, first published in 1982 (EPA-600/3-82-023), provides interactive computer software for formulating aquatic ecosystem models and rapidly evaluating the fate, transport, and exposure concentrations of synthetic organic chemicals - pesticides, ...

  8. A population-based case-control study of drinking-water nitrate and congenital anomalies using Geographic Information Systems (GIS) to develop individual-level exposure estimates.

    Science.gov (United States)

    Holtby, Caitlin E; Guernsey, Judith R; Allen, Alexander C; Vanleeuwen, John A; Allen, Victoria M; Gordon, Robert J

    2014-02-05

    Animal studies and epidemiological evidence suggest an association between prenatal exposure to drinking water with elevated nitrate (NO3-N) concentrations and incidence of congenital anomalies. This study used Geographic Information Systems (GIS) to derive individual-level prenatal drinking-water nitrate exposure estimates from measured nitrate concentrations from 140 temporally monitored private wells and 6 municipal water supplies. Cases of major congenital anomalies in Kings County, Nova Scotia, Canada, between 1988 and 2006 were selected from province-wide population-based perinatal surveillance databases and matched to controls from the same databases. Unconditional multivariable logistic regression was performed to test for an association between drinking-water nitrate exposure and congenital anomalies after adjusting for clinically relevant risk factors. Employing all nitrate data there was a trend toward increased risk of congenital anomalies for increased nitrate exposure levels though this was not statistically significant. After stratification of the data by conception before or after folic acid supplementation, an increased risk of congenital anomalies for nitrate exposure of 1.5-5.56 mg/L (2.44; 1.05-5.66) and a trend toward increased risk for >5.56 mg/L (2.25; 0.92-5.52) was found. Though the study is likely underpowered, these results suggest that drinking-water nitrate exposure may contribute to increased risk of congenital anomalies at levels below the current Canadian maximum allowable concentration.

  9. A Population-Based Case-Control Study of Drinking-Water Nitrate and Congenital Anomalies Using Geographic Information Systems (GIS) to Develop Individual-Level Exposure Estimates

    Science.gov (United States)

    Holtby, Caitlin E.; Guernsey, Judith R.; Allen, Alexander C.; VanLeeuwen, John A.; Allen, Victoria M.; Gordon, Robert J.

    2014-01-01

    Animal studies and epidemiological evidence suggest an association between prenatal exposure to drinking water with elevated nitrate (NO3-N) concentrations and incidence of congenital anomalies. This study used Geographic Information Systems (GIS) to derive individual-level prenatal drinking-water nitrate exposure estimates from measured nitrate concentrations from 140 temporally monitored private wells and 6 municipal water supplies. Cases of major congenital anomalies in Kings County, Nova Scotia, Canada, between 1988 and 2006 were selected from province-wide population-based perinatal surveillance databases and matched to controls from the same databases. Unconditional multivariable logistic regression was performed to test for an association between drinking-water nitrate exposure and congenital anomalies after adjusting for clinically relevant risk factors. Employing all nitrate data there was a trend toward increased risk of congenital anomalies for increased nitrate exposure levels though this was not statistically significant. After stratification of the data by conception before or after folic acid supplementation, an increased risk of congenital anomalies for nitrate exposure of 1.5–5.56 mg/L (2.44; 1.05–5.66) and a trend toward increased risk for >5.56 mg/L (2.25; 0.92–5.52) was found. Though the study is likely underpowered, these results suggest that drinking-water nitrate exposure may contribute to increased risk of congenital anomalies at levels below the current Canadian maximum allowable concentration. PMID:24503976

  10. Determinants of Dermal Exposure Relevant for Exposure Modelling in Regulatory Risk Assessment

    NARCIS (Netherlands)

    Marquart, J.; Brouwer, D.H.; Gijsbers, J.H.J.; Links, I.H.M.; Warren, N.; Hemmen, J.J. van

    2003-01-01

    Risk assessment of chemicals requires assessment of the exposure levels of workers. In the absence of adequate specific measured data, models are often used to estimate exposure levels. For dermal exposure only a few models exist, which are not validated externally. In the scope of a large European

  11. Modeling Exposure of Mammalian Predatorsto Anticoagulant Rodenticides

    DEFF Research Database (Denmark)

    Topping, Christopher John; Elmeros, Morten

    2016-01-01

    as vectors of AR, and was used to evaluate likely impacts of restrictions imposed on AR use in Denmark banning the use of rodenticides for plant protection in woodlands and tree-crops. The model uses input based on frequencies and timings of baiting for rodent control for urban, rural and woodland locations......Anticoagulant rodenticides (AR) are a widespread and effective method of rodent control but there is concern about the impact these may have on non-target organisms, in particular secondary poisoning of rodent predators. Incidence and concentration of AR in free-living predators in Denmark is very...... high. We postulate that this is caused by widespread exposure due to widespread use of AR in Denmark in and around buildings. To investigate this theory a spatio-temporal model of AR use and mammalian predator distribution was created. This model was supported by data from an experimental study of mice...

  12. Integrating remote sensing, geographic information systems and global positioning system techniques with hydrological modeling

    Science.gov (United States)

    Thakur, Jay Krishna; Singh, Sudhir Kumar; Ekanthalu, Vicky Shettigondahalli

    2017-07-01

    Integration of remote sensing (RS), geographic information systems (GIS) and global positioning system (GPS) are emerging research areas in the field of groundwater hydrology, resource management, environmental monitoring and during emergency response. Recent advancements in the fields of RS, GIS, GPS and higher level of computation will help in providing and handling a range of data simultaneously in a time- and cost-efficient manner. This review paper deals with hydrological modeling, uses of remote sensing and GIS in hydrological modeling, models of integrations and their need and in last the conclusion. After dealing with these issues conceptually and technically, we can develop better methods and novel approaches to handle large data sets and in a better way to communicate information related with rapidly decreasing societal resources, i.e. groundwater.

  13. A Spatial Model of the Mere Exposure Effect.

    Science.gov (United States)

    Fink, Edward L.; And Others

    1989-01-01

    Uses a spatial model to examine the relationship between stimulus exposure, cognition, and affect. Notes that this model accounts for cognitive changes that a stimulus may acquire as a result of exposure. Concludes that the spatial model is useful for evaluating the mere exposure effect and that affective change does not require cognitive change.…

  14. Model for Determining Geographical Distribution of Heat Saving Potentials in Danish Building Stock

    Directory of Open Access Journals (Sweden)

    Stefan Petrovic

    2014-02-01

    Full Text Available Since the global oil crisis in the 1970s, Denmark has followed a path towards energy independency by continuously improving its energy efficiency and energy conservation. Energy efficiency was mainly tackled by introducing a high number of combined heat and power plants in the system, while energy conservation was predominantly approached by implementing heat saving measures. Today, with the goal of 100% renewable energy within the power and heat sector by the year 2035, reductions in energy demand for space heating and the preparation of domestic hot water remain at the top of the agenda in Denmark. A highly detailed model for determining heat demand, possible heat savings and associated costs in the Danish building stock is presented. Both scheduled and energy-saving renovations until year 2030 have been analyzed. The highly detailed GIS-based heat atlas for Denmark is used as a container for storing data about physical properties for 2.5 million buildings in Denmark. Consequently, the results of the analysis can be represented on a single building level. Under the assumption that buildings with the most profitable heat savings are renovated first, the consequences of heat savings for the economy and energy system have been quantified and geographically referenced. The possibilities for further improvements of the model and the application to other geographical regions have been discussed.

  15. Geographical Information System Model for Potential Mines Data Management Presentation in Kabupaten Gorontalo

    Science.gov (United States)

    Roviana, D.; Tajuddin, A.; Edi, S.

    2017-03-01

    Mining potential in Indonesian is very abundant, ranging from Sabang to Marauke. Kabupaten Gorontalo is one of many places in Indonesia that have different types of minerals and natural resources that can be found in every district. The abundant of mining potential must be balanced with good management and ease of getting information by investors. The current issue is, (1) ways of presenting data/information about potential mines area is still manually (the maps that already capture from satellite image, then printed and attached to information board in the office) it caused the difficulties of getting information; (2) the high cost of maps printing; (3) the difficulties of regency leader (bupati) to obtain information for strategic decision making about mining potential. The goal of this research is to build a model of Geographical Information System that could provide data management of potential mines, so that the investors could easily get information according to their needs. To achieve that goal Research and Development method is used. The result of this research, is a model of Geographical Information System that implemented in an application to presenting data management of mines.

  16. An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

    Science.gov (United States)

    Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

    2018-05-01

    Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

  17. Understanding the geographic distribution of tropical cyclone formation for applications in climate models

    Science.gov (United States)

    Tory, Kevin J.; Ye, H.; Dare, R. A.

    2018-04-01

    Projections of Tropical cyclone (TC) formation under future climate scenarios are dependent on climate model simulations. However, many models produce unrealistic geographical distributions of TC formation, especially in the north and south Atlantic and eastern south Pacific TC basins. In order to improve confidence in projections it is important to understand the reasons behind these model errors. However, considerable effort is required to analyse the many models used in projection studies. To address this problem, a novel diagnostic is developed that provides compelling insight into why TCs form where they do, using a few summary diagrams. The diagnostic is developed after identifying a relationship between seasonal climatologies of atmospheric variables in 34 years of ECMWF reanalysis data, and TC detection distributions in the same data. Geographic boundaries of TC formation are constructed from four threshold quantities. TCs form where Emanuel's Maximum Potential Intensity, V_{{PI}}, exceeds 40 {ms}^{{ - 1}}, 700 hPa relative humidity, RH_{{700}}, exceeds 40%, and the magnitude of the difference in vector winds between 850 and 200 hPa, V_{{sh}}, is less than 20 {ms}^{{ - 1}}. The equatorial boundary is best defined by a composite quantity containing the ratio of absolute vorticity (η ) to the meridional gradient of absolute vorticity (β ^{*}), rather than η alone. {β ^*} is also identified as a potentially important ingredient for TC genesis indices. A comparison of detected Tropical Depression (TD) and Tropical Storm (TS) climatologies revealed TDs more readily intensify further to TS where {V_{PI}} is elevated and {V_{sh}} is relatively weak. The distributions of each threshold quantity identify the factors that favour and suppress TC formation throughout the tropics in the real world. This information can be used to understand why TC formation is poorly represented in some climate models, and shows potential for understanding anomalous TC formation

  18. Model of cholera dissemination using geographic information systems and fuzzy clustering means: case study, Chabahar, Iran.

    Science.gov (United States)

    Pezeshki, Z; Tafazzoli-Shadpour, M; Mansourian, A; Eshrati, B; Omidi, E; Nejadqoli, I

    2012-10-01

    Cholera is spread by drinking water or eating food that is contaminated by bacteria, and is related to climate changes. Several epidemics have occurred in Iran, the most recent of which was in 2005 with 1133 cases and 12 deaths. This study investigated the incidence of cholera over a 10-year period in Chabahar district, a region with one of the highest incidence rates of cholera in Iran. Descriptive retrospective study on data of patients with Eltor and NAG cholera reported to the Iranian Centre of Disease Control between 1997 and 2006. Data on the prevalence of cholera were gathered through a surveillance system, and a spatial database was developed using geographic information systems (GIS) to describe the relation of spatial and climate variables to cholera incidences. Fuzzy clustering (fuzzy C) method and statistical analysis based on logistic regression were used to develop a model of cholera dissemination. The variables were demographic characteristics, specifications of cholera infection, climate conditions and some geographical parameters. The incidence of cholera was found to be significantly related to higher temperature and humidity, lower precipitation, shorter distance to the eastern border of Iran and local health centres, and longer distance to the district health centre. The fuzzy C means algorithm showed that clusters were geographically distributed in distinct regions. In order to plan, manage and monitor any public health programme, GIS provide ideal platforms for the convergence of disease-specific information, analysis and computation of new data for statistical analysis. Copyright © 2012 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

  19. Geographic information system-coupling sediment delivery distributed modeling based on observed data.

    Science.gov (United States)

    Lee, S E; Kang, S H

    2014-01-01

    Spatially distributed sediment delivery (SEDD) models are of great interest in estimating the expected effect of changes on soil erosion and sediment yield. However, they can only be applied if the model can be calibrated using observed data. This paper presents a geographic information system (GIS)-based method to calculate the sediment discharge from basins to coastal areas. For this, an SEDD model, with a sediment rating curve method based on observed data, is proposed and validated. The model proposed here has been developed using the combined application of the revised universal soil loss equation (RUSLE) and a spatially distributed sediment delivery ratio, within Model Builder of ArcGIS's software. The model focuses on spatial variability and is useful for estimating the spatial patterns of soil loss and sediment discharge. The model consists of two modules, a soil erosion prediction component and a sediment delivery model. The integrated approach allows for relatively practical and cost-effective estimation of spatially distributed soil erosion and sediment delivery, for gauged or ungauged basins. This paper provides the first attempt at estimating sediment delivery ratio based on observed data in the monsoon region of Korea.

  20. A geographical information system-based analysis of cancer mortality and population exposure to coal mining activities in West Virginia, United States of America

    Directory of Open Access Journals (Sweden)

    Michael Hendryx

    2010-05-01

    Full Text Available Cancer incidence and mortality rates are high in West Virginia compared to the rest of the United States of America. Previous research has suggested that exposure to activities of the coal mining industry may contribute to elevated cancer mortality, although exposure measures have been limited. This study tests alternative specifications of exposure to mining activity to determine whether a measure based on location of mines, processing plants, coal slurry impoundments and underground slurry injection sites relative to population levels is superior to a previously-reported measure of exposure based on tons mined at the county level, in the prediction of age-adjusted cancer mortality rates. To this end, we utilize two geographical information system (GIS techniques – exploratory spatial data analysis and inverse distance mapping – to construct new statistical analyses. Total, respiratory and “other” age-adjusted cancer mortality rates in West Virginia were found to be more highly associated with the GIS-exposure measure than the tonnage measure, before and after statistical control for smoking rates. The superior performance of the GIS measure, based on where people in the state live relative to mining activity, suggests that activities of the industry contribute to cancer mortality. Further confirmation of observed phenomena is necessary with person-level studies, but the results add to the body of evidence that coal mining poses environmental risks to population health in West Virginia.

  1. Task-based dermal exposure models for regulatory risk assessment.

    Science.gov (United States)

    Warren, Nicholas D; Marquart, Hans; Christopher, Yvette; Laitinen, Juha; VAN Hemmen, Joop J

    2006-07-01

    The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of new measurements of dermal exposure together with detailed contextual information. This article describes the development of a set of generic task-based models capable of predicting potential dermal exposure to both solids and liquids in a wide range of situations. To facilitate modelling of the wide variety of dermal exposure situations six separate models were made for groupings of exposure scenarios called Dermal Exposure Operation units (DEO units). These task-based groupings cluster exposure scenarios with regard to the expected routes of dermal exposure and the expected influence of exposure determinants. Within these groupings linear mixed effect models were used to estimate the influence of various exposure determinants and to estimate components of variance. The models predict median potential dermal exposure rates for the hands and the rest of the body from the values of relevant exposure determinants. These rates are expressed as mg or microl product per minute. Using these median potential dermal exposure rates and an accompanying geometric standard deviation allows a range of exposure percentiles to be calculated.

  2. Feasibility of Close-Range Photogrammetric Models for Geographic Information System

    International Nuclear Information System (INIS)

    2011-01-01

    The objective of this project was to determine the feasibility of using close-range architectural photogrammetry as an alternative three dimensional modeling technique in order to place the digital models in a geographic information system (GIS) at SLAC. With the available equipment and Australis photogrammetry software, the creation of full and accurate models of an example building, Building 281 on SLAC campus, was attempted. After conducting several equipment tests to determine the precision achievable, a complete photogrammetric survey was attempted. The dimensions of the resulting models were then compared against the true dimensions of the building. A complete building model was not evidenced to be obtainable using the current equipment and software. This failure was likely attributable to the limits of the software rather than the precision of the physical equipment. However, partial models of the building were shown to be accurate and determined to still be usable in a GIS. With further development of the photogrammetric software and survey procedure, the desired generation of a complete three dimensional model is likely still feasible.

  3. Mapping and Modelling the Geographical Distribution and Environmental Limits of Podoconiosis in Ethiopia.

    Science.gov (United States)

    Deribe, Kebede; Cano, Jorge; Newport, Melanie J; Golding, Nick; Pullan, Rachel L; Sime, Heven; Gebretsadik, Abeba; Assefa, Ashenafi; Kebede, Amha; Hailu, Asrat; Rebollo, Maria P; Shafi, Oumer; Bockarie, Moses J; Aseffa, Abraham; Hay, Simon I; Reithinger, Richard; Enquselassie, Fikre; Davey, Gail; Brooker, Simon J

    2015-01-01

    Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues. Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF) conducted in 2013, supplemented by data from an earlier mapping of LF in western Ethiopia in 2008-2010. The integrated mapping used woreda (district) health offices' reports of podoconiosis and LF to guide selection of survey sites. A suite of environmental and climatic data and boosted regression tree (BRT) modelling was used to investigate environmental limits and predict the probability of podoconiosis occurrence. Data were available for 141,238 individuals from 1,442 communities in 775 districts from all nine regional states and two city administrations of Ethiopia. In 41.9% of surveyed districts no cases of podoconiosis were identified, with all districts in Affar, Dire Dawa, Somali and Gambella regional states lacking the disease. The disease was most common, with lymphoedema positivity rate exceeding 5%, in the central highlands of Ethiopia, in Amhara, Oromia and Southern Nations, Nationalities and Peoples regional states. BRT modelling indicated that the probability of podoconiosis occurrence increased with increasing altitude, precipitation and silt fraction of soil and decreased with population density and clay content. Based on the BRT model, we estimate that in 2010, 34.9 (95% confidence interval [CI]: 20.2-51.7) million people (i.e. 43.8%; 95% CI: 25.3-64.8% of Ethiopia's national population) lived in areas environmentally suitable for the occurrence of podoconiosis. Podoconiosis is more widespread in Ethiopia than previously estimated, but occurs in distinct geographical regions that are tied to identifiable environmental factors. The resultant maps can be used to guide programme planning

  4. Mapping and Modelling the Geographical Distribution and Environmental Limits of Podoconiosis in Ethiopia.

    Directory of Open Access Journals (Sweden)

    Kebede Deribe

    Full Text Available Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues.Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF conducted in 2013, supplemented by data from an earlier mapping of LF in western Ethiopia in 2008-2010. The integrated mapping used woreda (district health offices' reports of podoconiosis and LF to guide selection of survey sites. A suite of environmental and climatic data and boosted regression tree (BRT modelling was used to investigate environmental limits and predict the probability of podoconiosis occurrence.Data were available for 141,238 individuals from 1,442 communities in 775 districts from all nine regional states and two city administrations of Ethiopia. In 41.9% of surveyed districts no cases of podoconiosis were identified, with all districts in Affar, Dire Dawa, Somali and Gambella regional states lacking the disease. The disease was most common, with lymphoedema positivity rate exceeding 5%, in the central highlands of Ethiopia, in Amhara, Oromia and Southern Nations, Nationalities and Peoples regional states. BRT modelling indicated that the probability of podoconiosis occurrence increased with increasing altitude, precipitation and silt fraction of soil and decreased with population density and clay content. Based on the BRT model, we estimate that in 2010, 34.9 (95% confidence interval [CI]: 20.2-51.7 million people (i.e. 43.8%; 95% CI: 25.3-64.8% of Ethiopia's national population lived in areas environmentally suitable for the occurrence of podoconiosis.Podoconiosis is more widespread in Ethiopia than previously estimated, but occurs in distinct geographical regions that are tied to identifiable environmental factors. The resultant maps can be used to guide

  5. Development of cesium 137 plant uptake predicting model using geographical information systems

    International Nuclear Information System (INIS)

    Lomonos, O.V.

    2002-01-01

    Soil-plant system is a critical component of food chain in processes of Cs 137 migration. In this component it is possible to decrease greatly Cs 137 uptake in food chain. Development of Cs 137 migration model in soil-plant system enable to determine amount of Cs 137 in plant uptake and evaluate agricultural produce accordance with modern ecological requirements. Also this model can help with management of agricultural production. Geographical information systems (GIS) have a wide propagation in radioecology at present time. Models using GIS have several advantages: relative simplicity of evaluation, visualization of evaluated results etc. As a result, plots with possible Cs 137 uptake increasing could be easily discovered. Physical decay, Cs 137 sorption and fixation by soil, Cs 137 vertical migration in soil profile and plant uptake are the main components of the Cs 137 migration model in soil-plant system. Content of biologically available Cs 137 calculated taking into account all of these components. Using GIS with Cs 137 migration model in soil-plant system lets efficiently discover those factors that have major influence on Cs 137 plant uptake increasing. This model improves agricultural production on territories, which polluted by Cs 137

  6. The effect of modifiable risk factors on geographic mortality differentials: a modelling study

    Directory of Open Access Journals (Sweden)

    Stevenson Christopher E

    2012-01-01

    Full Text Available Abstract Background Australian mortality rates are higher in regional and remote areas than in major cities. The degree to which this is driven by variation in modifiable risk factors is unknown. Methods We applied a risk prediction equation incorporating smoking, cholesterol and blood pressure to a national, population based survey to project all-causes mortality risk by geographic region. We then modelled life expectancies at different levels of mortality risk by geographic region using a risk percentiles model. Finally we set high values of each risk factor to a target level and modelled the subsequent shift in the population to lower levels of mortality risk and longer life expectancy. Results Survival is poorer in both Inner Regional and Outer Regional/Remote areas compared to Major Cities for men and women at both high and low levels of predicted mortality risk. For men smoking, high cholesterol and high systolic blood pressure were each associated with the mortality difference between Major Cities and Outer Regional/Remote areas--accounting for 21.4%, 20.3% and 7.7% of the difference respectively. For women smoking and high cholesterol accounted for 29.4% and 24.0% of the difference respectively but high blood pressure did not contribute to the observed mortality differences. The three risk factors taken together accounted for 45.4% (men and 35.6% (women of the mortality difference. The contribution of risk factors to the corresponding differences for inner regional areas was smaller, with only high cholesterol and smoking contributing to the difference in men-- accounting for 8.8% and 6.3% respectively-- and only smoking contributing to the difference in women--accounting for 12.3%. Conclusions These results suggest that health intervention programs aimed at smoking, blood pressure and total cholesterol could have a substantial impact on mortality inequities for Outer Regional/Remote areas.

  7. A validation of ground ambulance pre-hospital times modeled using geographic information systems.

    Science.gov (United States)

    Patel, Alka B; Waters, Nigel M; Blanchard, Ian E; Doig, Christopher J; Ghali, William A

    2012-10-03

    Evaluating geographic access to health services often requires determining the patient travel time to a specified service. For urgent care, many research studies have modeled patient pre-hospital time by ground emergency medical services (EMS) using geographic information systems (GIS). The purpose of this study was to determine if the modeling assumptions proposed through prior United States (US) studies are valid in a non-US context, and to use the resulting information to provide revised recommendations for modeling travel time using GIS in the absence of actual EMS trip data. The study sample contained all emergency adult patient trips within the Calgary area for 2006. Each record included four components of pre-hospital time (activation, response, on-scene and transport interval). The actual activation and on-scene intervals were compared with those used in published models. The transport interval was calculated within GIS using the Network Analyst extension of Esri ArcGIS 10.0 and the response interval was derived using previously established methods. These GIS derived transport and response intervals were compared with the actual times using descriptive methods. We used the information acquired through the analysis of the EMS trip data to create an updated model that could be used to estimate travel time in the absence of actual EMS trip records. There were 29,765 complete EMS records for scene locations inside the city and 529 outside. The actual median on-scene intervals were longer than the average previously reported by 7-8 minutes. Actual EMS pre-hospital times across our study area were significantly higher than the estimated times modeled using GIS and the original travel time assumptions. Our updated model, although still underestimating the total pre-hospital time, more accurately represents the true pre-hospital time in our study area. The widespread use of generalized EMS pre-hospital time assumptions based on US data may not be appropriate in a

  8. Geographical Detector Model for Influencing Factors of Industrial Sector Carbon Dioxide Emissions in Inner Mongolia, China

    Directory of Open Access Journals (Sweden)

    Rina Wu

    2016-02-01

    Full Text Available Studying the influencing factors of carbon dioxide emissions is not only practically but also theoretically crucial for establishing regional carbon-reduction policies, developing low-carbon economy and solving the climate problems. Therefore, we used a geographical detector model which is consists of four parts, i.e., risk detector, factor detector, ecological detector and interaction detector to analyze the effect of these social economic factors, i.e., GDP, industrial structure, urbanization rate, economic growth rate, population and road density on the increase of energy consumption carbon dioxide emissions in industrial sector in Inner Mongolia northeast of China. Thus, combining with the result of four detectors, we found that GDP and population more influence than economic growth rate, industrial structure, urbanization rate and road density. The interactive effect of any two influencing factors enhances the increase of the carbon dioxide emissions. The findings of this research have significant policy implications for regions like Inner Mongolia.

  9. Geographical Research Model of the Relation Between Tourism and Industry on the Framework of Pula

    Directory of Open Access Journals (Sweden)

    Nikola Vojnović

    2002-01-01

    Full Text Available The research gives a proposal of a theoretical research model, and can be the basis of geographical research of the relation between tourism and industry as two opposite human activities and branches of economy. The accent is set on the consideration of their relation in major urban areas, which show a parallel development of tourism and industry of the Second Industrial Revolution, typical for Croatian coastline region. The proposal of the research scheme, from the analysis of the present structure and the quantity, harmony and disharmony of both branches, to the possibility of creating an industrial-tourism region are analyzed in the first part of the work, whereas the results of the initial research are presented in the second part.

  10. AirPEx: Air Pollution Exposure Model

    NARCIS (Netherlands)

    Freijer JI; Bloemen HJTh; Loos S de; Marra M; Rombout PJA; Steentjes GM; Veen MP van; LBO

    1997-01-01

    Analysis of inhalatory exposure to air pollution is an important area of investigation when assessing the risks of air pollution for human health. Inhalatory exposure research focuses on the exposure of humans to air pollutants and the entry of these pollutants into the human respiratory tract. The

  11. Geographically weighted lasso (GWL) study for modeling the diarrheic to achieve open defecation free (ODF) target

    Science.gov (United States)

    Arumsari, Nurvita; Sutidjo, S. U.; Brodjol; Soedjono, Eddy S.

    2014-03-01

    Diarrhea has been one main cause of morbidity and mortality to children around the world, especially in the developing countries According to available data that was mentioned. It showed that sanitary and healthy lifestyle implementation by the inhabitants was not good yet. Inadequacy of environmental influence and the availability of health services were suspected factors which influenced diarrhea cases happened followed by heightened percentage of the diarrheic. This research is aimed at modelling the diarrheic by using Geographically Weighted Lasso method. With the existence of spatial heterogeneity was tested by Breusch Pagan, it was showed that diarrheic modeling with weighted regression, especially GWR and GWL, can explain the variation in each location. But, the absence of multi-collinearity cases on predictor variables, which were affecting the diarrheic, resulted in GWR and GWL modelling to be not different or identical. It is shown from the resulting MSE value. While from R2 value which usually higher on GWL model showed a significant variable predictor based on more parametric shrinkage value.

  12. Spatial modelling of assumption of tourism development with geographic IT using

    Directory of Open Access Journals (Sweden)

    Jitka Machalová

    2010-01-01

    Full Text Available The aim of this article is to show the possibilities of spatial modelling and analysing of assumptions of tourism development in the Czech Republic with the objective to make decision-making processes in tourism easier and more efficient (for companies, clients as well as destination managements. The development and placement of tourism depend on the factors (conditions that influence its application in specific areas. These factors are usually divided into three groups: selective, localization and realization. Tourism is inseparably connected with space – countryside. The countryside can be modelled and consecutively analysed by the means of geographical information technologies. With the help of spatial modelling and following analyses the localization and realization conditions in the regions of the Czech Republic have been evaluated. The best localization conditions have been found in the Liberecký region. The capital city of Prague has negligible natural conditions; however, those social ones are on a high level. Next, the spatial analyses have shown that the best realization conditions are provided by the capital city of Prague. Then the Central-Bohemian, South-Moravian, Moravian-Silesian and Karlovarský regions follow. The development of tourism destination is depended not only on the localization and realization factors but it is basically affected by the level of local destination management. Spatial modelling can help destination managers in decision-making processes in order to optimal use of destination potential and efficient targeting their marketing activities.

  13. [Prediction of potential geographic distribution of Lyme disease in Qinghai province with Maximum Entropy model].

    Science.gov (United States)

    Zhang, Lin; Hou, Xuexia; Liu, Huixin; Liu, Wei; Wan, Kanglin; Hao, Qin

    2016-01-01

    To predict the potential geographic distribution of Lyme disease in Qinghai by using Maximum Entropy model (MaxEnt). The sero-diagnosis data of Lyme disease in 6 counties (Huzhu, Zeku, Tongde, Datong, Qilian and Xunhua) and the environmental and anthropogenic data including altitude, human footprint, normalized difference vegetation index (NDVI) and temperature in Qinghai province since 1990 were collected. By using the data of Huzhu Zeku and Tongde, the prediction of potential distribution of Lyme disease in Qinghai was conducted with MaxEnt. The prediction results were compared with the human sero-prevalence of Lyme disease in Datong, Qilian and Xunhua counties in Qinghai. Three hot spots of Lyme disease were predicted in Qinghai, which were all in the east forest areas. Furthermore, the NDVI showed the most important role in the model prediction, followed by human footprint. Datong, Qilian and Xunhua counties were all in eastern Qinghai. Xunhua was in hot spot areaⅡ, Datong was close to the north of hot spot area Ⅲ, while Qilian with lowest sero-prevalence of Lyme disease was not in the hot spot areas. The data were well modeled in MaxEnt (Area Under Curve=0.980). The actual distribution of Lyme disease in Qinghai was in consistent with the results of the model prediction. MaxEnt could be used in predicting the potential distribution patterns of Lyme disease. The distribution of vegetation and the range and intensity of human activity might be related with Lyme disease distribution.

  14. Modeling Exposure to Heat Stress with a Simple Urban Model

    Directory of Open Access Journals (Sweden)

    Peter Hoffmann

    2018-01-01

    Full Text Available As a first step in modeling health-related urban well-being (UrbWellth, a mathematical model is constructed that dynamically simulates heat stress exposure of commuters in an idealized city. This is done by coupling the Simple Urban Radiation Model (SURM, which computes the mean radiant temperature ( T m r t , with a newly developed multi-class multi-mode traffic model. Simulation results with parameters chosen for the city of Hamburg for a hot summer day show that commuters are potentially most exposed to heat stress in the early afternoon when T m r t has its maximum. Varying the morphology with respect to street width and building height shows that a more compact city configuration reduces T m r t and therefore the exposure to heat stress. The impact resulting from changes in the city structure on traffic is simulated to determine the time spent outside during the commute. While the time in traffic jams increases for compact cities, the total commuting time decreases due to shorter distances between home and work place. Concerning adaptation measures, it is shown that increases in the albedo of the urban surfaces lead to an increase in daytime heat stress. Dramatic increases in heat stress exposure are found when both, wall and street albedo, are increased.

  15. Air Pollution Exposure Modeling for Health Studies | Science ...

    Science.gov (United States)

    Dr. Michael Breen is leading the development of air pollution exposure models, integrated with novel personal sensor technologies, to improve exposure and risk assessments for individuals in health studies. He is co-investigator for multiple health studies assessing the exposure and effects of air pollutants. These health studies include participants with asthma, diabetes, and coronary artery disease living in various U.S. cities. He has developed, evaluated, and applied novel exposure modeling and time-activity tools, which includes the Exposure Model for Individuals (EMI), GPS-based Microenvironment Tracker (MicroTrac) and Exposure Tracker models. At this seminar, Dr. Breen will present the development and application of these models to predict individual-level personal exposures to particulate matter (PM) for two health studies in central North Carolina. These health studies examine the association between PM and adverse health outcomes for susceptible individuals. During Dr. Breen’s visit, he will also have the opportunity to establish additional collaborations with researchers at Harvard University that may benefit from the use of exposure models for cohort health studies. These research projects that link air pollution exposure with adverse health outcomes benefit EPA by developing model-predicted exposure-dose metrics for individuals in health studies to improve the understanding of exposure-response behavior of air pollutants, and to reduce participant

  16. Evaluation of the 3d Urban Modelling Capabilities in Geographical Information Systems

    Science.gov (United States)

    Dogru, A. O.; Seker, D. Z.

    2010-12-01

    Geographical Information System (GIS) Technology, which provides successful solutions to basic spatial problems, is currently widely used in 3 dimensional (3D) modeling of physical reality with its developing visualization tools. The modeling of large and complicated phenomenon is a challenging problem in terms of computer graphics currently in use. However, it is possible to visualize that phenomenon in 3D by using computer systems. 3D models are used in developing computer games, military training, urban planning, tourism and etc. The use of 3D models for planning and management of urban areas is very popular issue of city administrations. In this context, 3D City models are produced and used for various purposes. However the requirements of the models vary depending on the type and scope of the application. While a high level visualization, where photorealistic visualization techniques are widely used, is required for touristy and recreational purposes, an abstract visualization of the physical reality is generally sufficient for the communication of the thematic information. The visual variables, which are the principle components of cartographic visualization, such as: color, shape, pattern, orientation, size, position, and saturation are used for communicating the thematic information. These kinds of 3D city models are called as abstract models. Standardization of technologies used for 3D modeling is now available by the use of CityGML. CityGML implements several novel concepts to support interoperability, consistency and functionality. For example it supports different Levels-of-Detail (LoD), which may arise from independent data collection processes and are used for efficient visualization and efficient data analysis. In one CityGML data set, the same object may be represented in different LoD simultaneously, enabling the analysis and visualization of the same object with regard to different degrees of resolution. Furthermore, two CityGML data sets

  17. Predicting geographic distributions of Phacellodomus species (Aves: Furnariidae in South America based on ecological niche modeling

    Directory of Open Access Journals (Sweden)

    Maria da Salete Gurgel Costa

    2014-08-01

    Full Text Available Phacellodomus Reichenbach, 1853, comprises nine species of Furnariids that occur in South America in open and generally dry areas. This study estimated the geographic distributions of Phacellodomus species in South America by ecological niche modeling. Applying maximum entropy method, models were produced for eight species based on six climatic variables and 949 occurrence records. Since highest climatic suitability for Phacellodomus species has been estimated in open and dry areas, the Amazon rainforest areas are not very suitable for these species. Annual precipitation and minimum temperature of the coldest month are the variables that most influence the models. Phacellodomus species occurred in 35 ecoregions of South America. Chaco and Uruguayan savannas were the ecoregions with the highest number of species. Despite the overall connection of Phacellodomus species with dry areas, species such as P. ruber, P. rufifrons, P. ferrugineigula and P. erythrophthalmus occurred in wet forests and wetland ecoregions.

  18. Variation in calculated human exposure. Comparison of calculations with seven European human exposure models

    NARCIS (Netherlands)

    Swartjes F; ECO

    2003-01-01

    Twenty scenarios, differing with respect to land use, soil type and contaminant, formed the basis for calculating human exposure from soil contaminants with the use of models contributed by seven European countries (one model per country). Here, the human exposures to children and children

  19. Advanced REACH tool: A Bayesian model for occupational exposure assessment

    NARCIS (Netherlands)

    McNally, K.; Warren, N.; Fransman, W.; Entink, R.K.; Schinkel, J.; Van Tongeren, M.; Cherrie, J.W.; Kromhout, H.; Schneider, T.; Tielemans, E.

    2014-01-01

    This paper describes a Bayesian model for the assessment of inhalation exposures in an occupational setting; the methodology underpins a freely available web-based application for exposure assessment, the Advanced REACH Tool (ART). The ART is a higher tier exposure tool that combines disparate

  20. Validation of the dermal exposure model in ECETOC TRA.

    Science.gov (United States)

    Marquart, Hans; Franken, Remy; Goede, Henk; Fransman, Wouter; Schinkel, Jody

    2017-08-01

    The ECETOC TRA model (presently version 3.1) is often used to estimate worker inhalation and dermal exposure in regulatory risk assessment. The dermal model in ECETOC TRA has not yet been validated by comparison with independent measured exposure levels. This was the goal of the present study. Measured exposure levels and relevant contextual information were gathered via literature search, websites of relevant occupational health institutes and direct requests for data to industry. Exposure data were clustered in so-called exposure cases, which are sets of data from one data source that are expected to have the same values for input parameters in the ECETOC TRA dermal exposure model. For each exposure case, the 75th percentile of measured values was calculated, because the model intends to estimate these values. The input values for the parameters in ECETOC TRA were assigned by an expert elicitation and consensus building process, based on descriptions of relevant contextual information.From more than 35 data sources, 106 useful exposure cases were derived, that were used for direct comparison with the model estimates. The exposure cases covered a large part of the ECETOC TRA dermal exposure model. The model explained 37% of the variance in the 75th percentiles of measured values. In around 80% of the exposure cases, the model estimate was higher than the 75th percentile of measured values. In the remaining exposure cases, the model estimate may not be sufficiently conservative.The model was shown to have a clear bias towards (severe) overestimation of dermal exposure at low measured exposure values, while all cases of apparent underestimation by the ECETOC TRA dermal exposure model occurred at high measured exposure values. This can be partly explained by a built-in bias in the effect of concentration of substance in product used, duration of exposure and the use of protective gloves in the model. The effect of protective gloves was calculated to be on average a

  1. Geographic Names

    Data.gov (United States)

    Minnesota Department of Natural Resources — The Geographic Names Information System (GNIS), developed by the United States Geological Survey in cooperation with the U.S. Board of Geographic Names, provides...

  2. Virtual Geographic Simulation of Light Distribution within Three-Dimensional Plant Canopy Models

    Directory of Open Access Journals (Sweden)

    Liyu Tang

    2017-12-01

    Full Text Available Virtual geographic environments (VGEs have been regarded as an important new means of simulating, analyzing, and understanding complex geological processes. Plants and light are major components of the geographic environment. Light is a critical factor that affects ecological systems. In this study, we focused on simulating light transmission and distribution within a three-dimensional plant canopy model. A progressive refinement radiosity algorithm was applied to simulate the transmission and distribution of solar light within a detailed, three-dimensional (3D loquat (Eriobotrya japonica Lindl. canopy model. The canopy was described in three dimensions, and each organ surface was represented by a set of triangular facets. The form factors in radiosity were calculated using a hemi-cube algorithm. We developed a module for simulating the instantaneous light distribution within a virtual canopy, which was integrated into ParaTree. We simulated the distribution of photosynthetically active radiation (PAR within a loquat canopy, and calculated the total PAR intercepted at the whole canopy scale, as well as the mean PAR interception per unit leaf area. The ParaTree-integrated radiosity model simulates the uncollided propagation of direct solar and diffuse sky light and the light-scattering effect of foliage. The PAR captured by the whole canopy based on the radiosity is approximately 9.4% greater than that obtained using ray tracing and TURTLE methods. The latter methods do not account for the scattering among leaves in the canopy in the study, and therefore, the difference might be due to the contribution of light scattering in the foliage. The simulation result is close to Myneni’s findings, in which the light scattering within a canopy is less than 10% of the incident PAR. Our method can be employed for visualizing and analyzing the spatial distribution of light within a canopy, and for estimating the PAR interception at the organ and canopy

  3. Pesticide exposure and hepatocellular carcinoma risk: A case-control study using a geographic information system (GIS) to link SEER-Medicare and California pesticide data.

    Science.gov (United States)

    VoPham, Trang; Brooks, Maria M; Yuan, Jian-Min; Talbott, Evelyn O; Ruddell, Darren; Hart, Jaime E; Chang, Chung-Chou H; Weissfeld, Joel L

    2015-11-01

    Hepatocellular carcinoma (HCC), the most common type of primary liver cancer, is associated with low survival. U.S. studies examining self-reported pesticide exposure in relation to HCC have demonstrated inconclusive results. We aimed to clarify the association between pesticide exposure and HCC by implementing a novel data linkage between Surveillance, Epidemiology, and End Results (SEER)-Medicare and California Pesticide Use Report (PUR) data using a geographic information system (GIS). Controls were frequency-matched to HCC cases diagnosed between 2000 and 2009 in California by year, age, race, sex, and duration of residence in California. Potential confounders were extracted from Medicare claims. From 1974 to 2008, pounds (1 pound represents 0.45 kg) of applied organophosphate, organochlorine, and carbamate pesticides provided in PURs were aggregated to the ZIP Code level using area weighting in a GIS. ZIP Code exposure estimates were linked to subjects using Medicare-provided ZIP Codes to calculate pesticide exposure. Agricultural residents were defined as living in ZIP Codes with a majority area intersecting agricultural land cover according to the 1992, 2001, and 2006 National Land Cover Database (NLCD) rasters. Multivariable conditional logistic regression was used to estimate the association between pesticide exposure and HCC. Among California residents of agriculturally intensive areas, previous annual ZIP Code-level exposure to over 14.53 kg/km(2) of organochlorine pesticides (75(th) percentile among controls) was associated with an increased risk of HCC after adjusting for liver disease and diabetes (adjusted odds ratio [OR] 1.87, 95% confidence interval [CI] 1.17, 2.99; p=0.0085). ZIP Code-level organochlorines were significantly associated with an increased risk of HCC among males (adjusted OR 2.76, 95% CI 1.58, 4.82; p=0.0004), but not associated with HCC among females (adjusted OR 0.83, 95% CI 0.35, 1.93; p=0.6600) (interaction p=0.0075). This is

  4. A Global User-Driven Model for Tile Prefetching in Web Geographical Information Systems.

    Science.gov (United States)

    Pan, Shaoming; Chong, Yanwen; Zhang, Hang; Tan, Xicheng

    2017-01-01

    A web geographical information system is a typical service-intensive application. Tile prefetching and cache replacement can improve cache hit ratios by proactively fetching tiles from storage and replacing the appropriate tiles from the high-speed cache buffer without waiting for a client's requests, which reduces disk latency and improves system access performance. Most popular prefetching strategies consider only the relative tile popularities to predict which tile should be prefetched or consider only a single individual user's access behavior to determine which neighbor tiles need to be prefetched. Some studies show that comprehensively considering all users' access behaviors and all tiles' relationships in the prediction process can achieve more significant improvements. Thus, this work proposes a new global user-driven model for tile prefetching and cache replacement. First, based on all users' access behaviors, a type of expression method for tile correlation is designed and implemented. Then, a conditional prefetching probability can be computed based on the proposed correlation expression mode. Thus, some tiles to be prefetched can be found by computing and comparing the conditional prefetching probability from the uncached tiles set and, similarly, some replacement tiles can be found in the cache buffer according to multi-step prefetching. Finally, some experiments are provided comparing the proposed model with other global user-driven models, other single user-driven models, and other client-side prefetching strategies. The results show that the proposed model can achieve a prefetching hit rate in approximately 10.6% ~ 110.5% higher than the compared methods.

  5. Technical note: Modeling primate occlusal topography using geographic information systems technology.

    Science.gov (United States)

    Zuccotti, L F; Williamson, M D; Limp, W F; Ungar, P S

    1998-09-01

    Most functional analyses of primate tooth form have been limited to linear or area measurements. Such studies have offered but a limited glimpse at differences in occlusal relief among taxa. Such differences in dental topography may relate to tooth function and, so, have considerable implications for the inference of diet from fossil teeth. In this article, we describe a technique to model and compare primate molars in three dimensions using Geographic Resources Analysis Support System (GRASS) software. We examine unworn lower second molars of three extant hominoids with known differences in diet (Gorilla gorilla, Pan troglodytes, and Pongo pygmaeus), and two fossil forms, (Afropithecus turkanesis and Dryopithecus laietanus). First, we obtained approximately 400 landmarks on the occlusal surfaces of each tooth using an electromagnetic digitizer. Raster "terrain models" of occlusal surfaces were then created by interpolation of the coordinate data. We used GRASS terrain analysis automated techniques to quantify the volumes and slopes of individual cusps. We also used the GRASS watershed technique to identify the volume of liquid that would accumulate in each tooth's basin (a measure of basin area), and the directions and intensity of drainage over the occlusal surface. In sum, GRASS shows considerable potential for the characterization and comparison of tooth surfaces. Furthermore, techniques described here are not limited to the study of teeth, but may be broadly applicable to studies of skulls, joints, and other biological structures.

  6. A Conceptual Model for Delineating Land Management Units (LMUs Using Geographical Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Deniz Gerçek

    2017-06-01

    Full Text Available Land management and planning is crucial for present and future use of land and the sustainability of land resources. Physical, biological and cultural characteristics of land can be used to define Land Management Units (LMUs that aid in decision making for managing land and communicating information between different research and application domains. This study aims to describe the classification of ecologically relevant land units that are suitable for land management, planning and conservation purposes. Relying on the idea of strong correlation between landform and potential landcover, a conceptual model for creating Land Management Units (LMUs from topographic data and biophysical information is presented. The proposed method employs a multi-level object-based classification of Digital Terrain Models (DTMs to derive landform units. The sensitivity of landform units to changes in segmentation scale is examined, and the outcome of the landform classification is evaluated. Landform classes are then aggregated with landcover information to produce ecologically relevant landform/landcover assemblages. These conceptual units that constitute a framework of connected entities are finally enriched given available socio-economic information e.g., land use, ownership, protection status, etc. to generate LMUs. LMUs attached to a geographic database enable the retrieval of information at various levels to support decision making for land management at various scales. LMUs that are created present a basis for conservation and management in a biodiverse area in the Black Sea region of Turkey.

  7. Air pollution exposure modeling of individuals

    Science.gov (United States)

    Air pollution epidemiology studies of ambient fine particulate matter (PM2.5) often use outdoor concentrations as exposure surrogates. These surrogates can induce exposure error since they do not account for (1) time spent indoors with ambient PM2.5 levels attenuated from outdoor...

  8. Comprehensive Regional Modeling for Long-Range Planning: Linking Integrated Urban Models and Geographic Information Systems

    OpenAIRE

    Johnston, Robert; de la Barra, Thomas

    2000-01-01

    This study demonstrates the sequential linking of two types of models to permit the comprehensive evaluation of regional transportation and land use policies. First, we operate an integrated urban model (TRANUS), which represents both land and travel markets with zones and networks. The travel and land use projections from TRANUS are outlined, to demonstrate the general reasonableness of the results, as this is the first application of a market-based urban model in the US. Second, the land us...

  9. Modelling of human exposure to air pollution in the urban environment: a GPS-based approach.

    Science.gov (United States)

    Dias, Daniela; Tchepel, Oxana

    2014-03-01

    The main objective of this work was the development of a new modelling tool for quantification of human exposure to traffic-related air pollution within distinct microenvironments by using a novel approach for trajectory analysis of the individuals. For this purpose, mobile phones with Global Positioning System technology have been used to collect daily trajectories of the individuals with higher temporal resolution and a trajectory data mining, and geo-spatial analysis algorithm was developed and implemented within a Geographical Information System to obtain time-activity patterns. These data were combined with air pollutant concentrations estimated for several microenvironments. In addition to outdoor, pollutant concentrations in distinct indoor microenvironments are characterised using a probabilistic approach. An example of the application for PM2.5 is presented and discussed. The results obtained for daily average individual exposure correspond to a mean value of 10.6 and 6.0-16.4 μg m(-3) in terms of 5th-95th percentiles. Analysis of the results shows that the use of point air quality measurements for exposure assessment will not explain the intra- and inter-variability of individuals' exposure levels. The methodology developed and implemented in this work provides time-sequence of the exposure events thus making possible association of the exposure with the individual activities and delivers main statistics on individual's air pollution exposure with high spatio-temporal resolution.

  10. Modeling wind energy potential in a data-poor region: A geographic information systems model for Iraq

    Science.gov (United States)

    Khayyat, Abdulkareem Hawta Abdullah Kak Ahmed

    Scope and Method of Study: Most developing countries, including Iraq, have very poor wind data. Existing wind speed measurements of poor quality may therefore be a poor guide to where to look for the best wind resources. The main focus of this study is to examine how effectively a GIS spatial model estimates wind power potential in regions where high-quality wind data are very scarce, such as Iraq. The research used a mixture of monthly and hourly wind data from 39 meteorological stations. The study applied spatial analysis statistics and GIS techniques in modeling wind power potential. The model weighted important human, environmental and geographic factors that impact wind turbine siting, such as roughness length, land use⪉nd cover type, airport locations, road access, transmission lines, slope and aspect. Findings and Conclusions: The GIS model provided estimations for wind speed and wind power density and identified suitable areas for wind power projects. Using a high resolution (30*30m) digital elevation model DEM improved the GIS wind suitability model. The model identified areas suitable for wind farm development on different scales. The model showed that there are many locations available for large-scale wind turbines in the southern part of Iraq. Additionally, there are many places in central and northern parts (Kurdistan Region) for smaller scale wind turbine placement.

  11. Road traffic noise: self-reported noise annoyance versus GIS modelled road traffic noise exposure.

    Science.gov (United States)

    Birk, Matthias; Ivina, Olga; von Klot, Stephanie; Babisch, Wolfgang; Heinrich, Joachim

    2011-11-01

    self-reported road traffic noise annoyance is commonly used in epidemiological studies for assessment of potential health effects. Alternatively, some studies have used geographic information system (GIS) modelled exposure to road traffic noise as an objective parameter. The aim of this study was to analyse the association between noise exposure due to neighbouring road traffic and the noise annoyance of adults, taking other determinants into consideration. parents of 951 Munich children from the two German birth cohorts GINIplus and LISAplus reported their annoyance due to road traffic noise at home. GIS modelled road traffic noise exposure (L(den), maximum within a 50 m buffer) from the noise map of the city of Munich was available for all families. GIS-based calculated distance to the closest major road (≥10,000 vehicles per day) and questionnaire based-information about family income, parental education and the type of the street of residence were explored for their potential influence. An ordered logit regression model was applied. The noise levels (L(den)) and the reported noise annoyance were compared with an established exposure-response function. the correlation between noise annoyance and noise exposure (L(den)) was fair (Spearman correlation r(s) = 0.37). The distance to a major road and the type of street were strong predictors for the noise annoyance. The annoyance modelled by the established exposure-response function and that estimated by the ordered logit model were moderately associated (Pearson's correlation r(p) = 0.50). road traffic noise annoyance was associated with GIS modelled neighbouring road traffic noise exposure (L(den)). The distance to a major road and the type of street were additional explanatory factors of the noise annoyance appraisal.

  12. What are we 'tweeting' about obesity? Mapping tweets with Topic Modeling and Geographic Information System.

    Science.gov (United States)

    Ghosh, Debarchana Debs; Guha, Rajarshi

    2013-01-01

    Public health related tweets are difficult to identify in large conversational datasets like Twitter.com. Even more challenging is the visualization and analyses of the spatial patterns encoded in tweets. This study has the following objectives: How can topic modeling be used to identify relevant public health topics such as obesity on Twitter.com? What are the common obesity related themes? What is the spatial pattern of the themes? What are the research challenges of using large conversational datasets from social networking sites? Obesity is chosen as a test theme to demonstrate the effectiveness of topic modeling using Latent Dirichlet Allocation (LDA) and spatial analysis using Geographic Information System (GIS). The dataset is constructed from tweets (originating from the United States) extracted from Twitter.com on obesity-related queries. Examples of such queries are 'food deserts', 'fast food', and 'childhood obesity'. The tweets are also georeferenced and time stamped. Three cohesive and meaningful themes such as 'childhood obesity and schools', 'obesity prevention', and 'obesity and food habits' are extracted from the LDA model. The GIS analysis of the extracted themes show distinct spatial pattern between rural and urban areas, northern and southern states, and between coasts and inland states. Further, relating the themes with ancillary datasets such as US census and locations of fast food restaurants based upon the location of the tweets in a GIS environment opened new avenues for spatial analyses and mapping. Therefore the techniques used in this study provide a possible toolset for computational social scientists in general and health researchers in specific to better understand health problems from large conversational datasets.

  13. Determinants of the geographical distribution of endemic giardiasis in Ontario, Canada: a spatial modelling approach.

    Science.gov (United States)

    Odoi, A; Martin, S W; Michel, P; Holt, J; Middleton, D; Wilson, J

    2004-10-01

    Giardiasis surveillance data as well as drinking water, socioeconomic and land-use data were used in spatial regression models to investigate determinants of the geographic distribution of endemic giardiasis in southern Ontario. Higher giardiasis rates were observed in areas using surface water [rate ratio (RR) 2.36, 95 % CI 1.38-4.05] and in rural areas (RR 1.79, 95 % CI 1.32-2.37). Lower rates were observed in areas using filtered water (RR 0.55, 95 % CI 0.42-0.94) and in those with high median income (RR 0.62, 95 % CI 0.42-0.92). Chlorination of drinking water, cattle density and intensity of manure application on farmland were not significant determinants. The study shows that waterborne transmission plays an important role in giardiasis distribution in southern Ontario and that well-collected routine surveillance data could be useful for investigation of disease determinants and identification of high-risk communities. This information is useful in guiding decisions on control strategies.

  14. Household energy consumption in the UK: A highly geographically and socio-economically disaggregated model

    International Nuclear Information System (INIS)

    Druckman, A.; Jackson, T.

    2008-01-01

    Devising policies for a low carbon society requires a careful understanding of energy consumption in different types of households. In this paper, we explore patterns of UK household energy use and associated carbon emissions at national level and also at high levels of socio-economic and geographical disaggregation. In particular, we examine specific neighbourhoods with contrasting levels of deprivation, and typical 'types' (segments) of UK households based on socio-economic characteristics. Results support the hypothesis that different segments have widely differing patterns of consumption. We show that household energy use and associated carbon emissions are both strongly, but not solely, related to income levels. Other factors, such as the type of dwelling, tenure, household composition and rural/urban location are also extremely important. The methodology described in this paper can be used in various ways to inform policy-making. For example, results can help in targeting energy efficiency measures; trends from time series results will form a useful basis for scenario building; and the methodology may be used to model expected outcomes of possible policy options, such as personal carbon trading or a progressive tax regime on household energy consumption

  15. Geographic Distribution of Chagas Disease Vectors in Brazil Based on Ecological Niche Modeling

    Directory of Open Access Journals (Sweden)

    Rodrigo Gurgel-Gonçalves

    2012-01-01

    Full Text Available Although Brazil was declared free from Chagas disease transmission by the domestic vector Triatoma infestans, human acute cases are still being registered based on transmission by native triatomine species. For a better understanding of transmission risk, the geographic distribution of Brazilian triatomines was analyzed. Sixteen out of 62 Brazilian species that both occur in >20 municipalities and present synanthropic tendencies were modeled based on their ecological niches. Panstrongylus geniculatus and P. megistus showed broad ecological ranges, but most of the species sort out by the biome in which they are distributed: Rhodnius pictipes and R. robustus in the Amazon; R. neglectus, Triatoma sordida, and T. costalimai in the Cerrado; R. nasutus, P. lutzi, T. brasiliensis, T. pseudomaculata, T. melanocephala, and T. petrocchiae in the Caatinga; T. rubrovaria in the southern pampas; T. tibiamaculata and T. vitticeps in the Atlantic Forest. Although most occurrences were recorded in open areas (Cerrado and Caatinga, our results show that all environmental conditions in the country are favorable to one or more of the species analyzed, such that almost nowhere is Chagas transmission risk negligible.

  16. Modelling social vulnerability in sub-Saharan West Africa using a geographical information system

    Directory of Open Access Journals (Sweden)

    Olanrewaju Lawal

    2015-05-01

    Full Text Available In recent times, disasters and risk management have gained significant attention, especially with increasing awareness of the risks and increasing impact of natural and other hazards especially in the developing world. Vulnerability, the potential for loss of life or property from disaster, has biophysical or social dimensions. Social vulnerability relates to societal attributes which has negative impacts on disaster outcomes. This study sought to develop a spatially explicit index of social vulnerability, thus addressing the dearth of research in this area in sub-Saharan Africa. Nineteen variables were identified covering various aspects. Descriptive analysis of these variables revealed high heterogeneity across the South West region of Nigeria for both the state and the local government areas (LGAs. Feature identification using correlation analysis identified six important variables. Factor analysis identified two dimensions, namely accessibility and socioeconomic conditions, from this subset. A social vulnerability index (SoVI showed that Ondo and Ekiti have more vulnerable LGAs than other states in the region. About 50% of the LGAs in Osun and Ogun have a relatively low social vulnerability. Distribution of the SoVI shows that there are great differences within states as well as across regions. Scores of population density, disability and poverty have a high margin of error in relation to mean state scores. The study showed that with a geographical information system there are opportunities to model social vulnerability and monitor its evolution and dynamics across the continent.

  17. Data Sources Available for Modeling Environmental Exposures in Older Adults

    Science.gov (United States)

    This report, “Data Sources Available for Modeling Environmental Exposures in Older Adults,” focuses on information sources and data available for modeling environmental exposures in the older U.S. population, defined here to be people 60 years and older, with an emphasis on those...

  18. A conceptual model of the automated credibility assessment of the volunteered geographic information

    International Nuclear Information System (INIS)

    Idris, N H; Jackson, M J; Ishak, M H I

    2014-01-01

    The use of Volunteered Geographic Information (VGI) in collecting, sharing and disseminating geospatially referenced information on the Web is increasingly common. The potentials of this localized and collective information have been seen to complement the maintenance process of authoritative mapping data sources and in realizing the development of Digital Earth. The main barrier to the use of this data in supporting this bottom up approach is the credibility (trust), completeness, accuracy, and quality of both the data input and outputs generated. The only feasible approach to assess these data is by relying on an automated process. This paper describes a conceptual model of indicators (parameters) and practical approaches to automated assess the credibility of information contributed through the VGI including map mashups, Geo Web and crowd – sourced based applications. There are two main components proposed to be assessed in the conceptual model – metadata and data. The metadata component comprises the indicator of the hosting (websites) and the sources of data / information. The data component comprises the indicators to assess absolute and relative data positioning, attribute, thematic, temporal and geometric correctness and consistency. This paper suggests approaches to assess the components. To assess the metadata component, automated text categorization using supervised machine learning is proposed. To assess the correctness and consistency in the data component, we suggest a matching validation approach using the current emerging technologies from Linked Data infrastructures and using third party reviews validation. This study contributes to the research domain that focuses on the credibility, trust and quality issues of data contributed by web citizen providers

  19. Evaluation of AirGIS: a GIS-based air pollution and human exposure modelling system

    DEFF Research Database (Denmark)

    Ketzel, Matthias; Berkowicz, Ruwim; Hvidberg, Martin

    2011-01-01

    This study describes in brief the latest extensions of the Danish Geographic Information System (GIS)-based air pollution and human exposure modelling system (AirGIS), which has been developed in Denmark since 2001 and gives results of an evaluation with measured air pollution data. The system...... shows, in general, a good performance for both long-term averages (annual and monthly averages), short-term averages (hourly and daily) as well as when reproducing spatial variation in air pollution concentrations. Some shortcomings and future perspectives of the system are discussed too....

  20. A statistical framework for the validation of a population exposure model based on personal exposure data

    Science.gov (United States)

    Rodriguez, Delphy; Valari, Myrto; Markakis, Konstantinos; Payan, Sébastien

    2016-04-01

    Currently, ambient pollutant concentrations at monitoring sites are routinely measured by local networks, such as AIRPARIF in Paris, France. Pollutant concentration fields are also simulated with regional-scale chemistry transport models such as CHIMERE (http://www.lmd.polytechnique.fr/chimere) under air-quality forecasting platforms (e.g. Prev'Air http://www.prevair.org) or research projects. These data may be combined with more or less sophisticated techniques to provide a fairly good representation of pollutant concentration spatial gradients over urban areas. Here we focus on human exposure to atmospheric contaminants. Based on census data on population dynamics and demographics, modeled outdoor concentrations and infiltration of outdoor air-pollution indoors we have developed a population exposure model for ozone and PM2.5. A critical challenge in the field of population exposure modeling is model validation since personal exposure data are expensive and therefore, rare. However, recent research has made low cost mobile sensors fairly common and therefore personal exposure data should become more and more accessible. In view of planned cohort field-campaigns where such data will be available over the Paris region, we propose in the present study a statistical framework that makes the comparison between modeled and measured exposures meaningful. Our ultimate goal is to evaluate the exposure model by comparing modeled exposures to monitor data. The scientific question we address here is how to downscale modeled data that are estimated on the county population scale at the individual scale which is appropriate to the available measurements. To assess this question we developed a Bayesian hierarchical framework that assimilates actual individual data into population statistics and updates the probability estimate.

  1. The Impacts of Exposure to Environmental Risk on Physical and Mental Health in a Small Geographic Community in Houston, TX.

    Science.gov (United States)

    Sansom, Garett; Parras, Juan; Parras, Ana; Nieto, Yudith; Arellano, Yvette; Berke, Philip; McDonald, Thomas; Shipp, Eva; Horney, Jennifer A

    2017-08-01

    Previous research has shown that communities with low average socioeconomic status (SES) and majority minority populations are more likely to be exposed to industrial buildings, waste facilities, and poor infrastructure compared to white communities with higher average SES. While some studies have demonstrated linkages between exposures to specific environmental contaminates within these communities and negative health outcomes, little research has analyzed the effects of environmental contaminants on the mental and physical health of these populations. A cross-sectional survey collected data from residents of Manchester, a small neighborhood in Houston, TX, that is characterized by industrial sites, unimproved infrastructure, nuisance flooding, and poor air quality. Our study (N = 109) utilized the 12 item Short Form Health Survey version 2 (SF12v2) to assess the general mental and physical health of the community. The community as a whole had reduced physical health scores compared to U.S. national averages. The time residents had lived in the neighborhood was also correlated with a reported reduction in physical health scores (r2 = 0.136; p-value health scores remained after adjusting for age, race, and gender (coef = -0.27, p-value Mental health scores were within national averages and time spent living in the neighborhood did not appear to negatively impact respondent's mental health scores. These findings point to the need for more research to determine the potential for additive physical and mental health impacts in long-term residents in neighborhoods characterized by environmental justice issues.

  2. Radiation exposure modeling and project schedule visualization

    International Nuclear Information System (INIS)

    Jaquish, W.R.; Enderlin, V.R.

    1995-10-01

    This paper discusses two applications using IGRIP (Interactive Graphical Robot Instruction Program) to assist environmental remediation efforts at the Department of Energy (DOE) Hanford Site. In the first application, IGRIP is used to calculate the estimated radiation exposure to workers conducting tasks in radiation environments. In the second, IGRIP is used as a configuration management tool to detect interferences between equipment and personnel work areas for multiple projects occurring simultaneously in one area. Both of these applications have the capability to reduce environmental remediation costs by reducing personnel radiation exposure and by providing a method to effectively manage multiple projects in a single facility

  3. A dermatotoxicokinetic model of human exposures to jet fuel.

    Science.gov (United States)

    Kim, David; Andersen, Melvin E; Nylander-French, Leena A

    2006-09-01

    Workers, both in the military and the commercial airline industry, are exposed to jet fuel by inhalation and dermal contact. We present a dermatotoxicokinetic (DTK) model that quantifies the absorption, distribution, and elimination of aromatic and aliphatic components of jet fuel following dermal exposures in humans. Kinetic data were obtained from 10 healthy volunteers following a single dose of JP-8 to the forearm over a surface area of 20 cm2. Blood samples were taken before exposure (t = 0 h), after exposure (t = 0.5 h), and every 0.5 h for up to 3.5 h postexposure. The DTK model that best fit the data included five compartments: (1) surface, (2) stratum corneum (SC), (3) viable epidermis, (4) blood, and (5) storage. The DTK model was used to predict blood concentrations of the components of JP-8 based on dermal-exposure measurements made in occupational-exposure settings in order to better understand the toxicokinetic behavior of these compounds. Monte Carlo simulations of dermal exposure and cumulative internal dose demonstrated no overlap among the low-, medium-, and high-exposure groups. The DTK model provides a quantitative understanding of the relationship between the mass of JP-8 components in the SC and the concentrations of each component in the systemic circulation. The model may be used for the development of a toxicokinetic modeling strategy for multiroute exposure to jet fuel.

  4. Analisis Faktor – Faktor yang Mempengaruhi Jumlah Kejahatan Pencurian Kendaraan Bermotor (Curanmor) Menggunakan Model Geographically Weighted Poisson Regression (Gwpr)

    OpenAIRE

    Haris, Muhammad; Yasin, Hasbi; Hoyyi, Abdul

    2015-01-01

    Theft is an act taking someone else's property, partially or entierely, with intention to have it illegally. Motor vehicle theft is one of the most highlighted crime type and disturbing the communities. Regression analysis is a statistical analysis for modeling the relationships between response variable and predictor variable. If the response variable follows a Poisson distribution or categorized as a count data, so the regression model used is Poisson regression. Geographically Weighted Poi...

  5. Modelling the geographical distribution of soil-transmitted helminth infections in Bolivia.

    Science.gov (United States)

    Chammartin, Frédérique; Scholte, Ronaldo G C; Malone, John B; Bavia, Mara E; Nieto, Prixia; Utzinger, Jürg; Vounatsou, Penelope

    2013-05-25

    The prevalence of infection with the three common soil-transmitted helminths (i.e. Ascaris lumbricoides, Trichuris trichiura, and hookworm) in Bolivia is among the highest in Latin America. However, the spatial distribution and burden of soil-transmitted helminthiasis are poorly documented. We analysed historical survey data using Bayesian geostatistical models to identify determinants of the distribution of soil-transmitted helminth infections, predict the geographical distribution of infection risk, and assess treatment needs and costs in the frame of preventive chemotherapy. Rigorous geostatistical variable selection identified the most important predictors of A. lumbricoides, T. trichiura, and hookworm transmission. Results show that precipitation during the wettest quarter above 400 mm favours the distribution of A. lumbricoides. Altitude has a negative effect on T. trichiura. Hookworm is sensitive to temperature during the coldest month. We estimate that 38.0%, 19.3%, and 11.4% of the Bolivian population is infected with A. lumbricoides, T. trichiura, and hookworm, respectively. Assuming independence of the three infections, 48.4% of the population is infected with any soil-transmitted helminth. Empirical-based estimates, according to treatment recommendations by the World Health Organization, suggest a total of 2.9 million annualised treatments for the control of soil-transmitted helminthiasis in Bolivia. We provide estimates of soil-transmitted helminth infections in Bolivia based on high-resolution spatial prediction and an innovative variable selection approach. However, the scarcity of the data suggests that a national survey is required for more accurate mapping that will govern spatial targeting of soil-transmitted helminthiasis control.

  6. A geographic information system forecast model for strategic control of fasciolosis in Ethiopia.

    Science.gov (United States)

    Yilma, J M; Malone, J B

    1998-07-31

    A geographic information system (GIS) forecast model based on moisture and thermal regime was developed to assess the risk of Fasciola hepatica, a temperate species, and its tropical counterpart, Fasciola gigantica, in Ethiopia. Agroecological map zones and corresponding environmental features that control the distribution and abundance of the disease and its snail intermediate hosts were imported from the Food and Agriculture Organization (FAO) Crop Production System Zones (CPSZ) database on east Africa and used to construct a GIS using ATLAS GIS 3.0 software. Base temperatures of 10 degrees C and 16 degrees C were used for F. hepatica and F. gigantica, respectively, to calculate growing degree days in a previously developed climate forecast system that was modified to allow use of monthly climate data values. The model was validated by comparison of risk indices and environmental features to available survey data on fasciolosis. Monthly Fasciola risk indices of four climatic regions in Ethiopia were used to project infection transmission patterns under varying climatic conditions and strategic chemotherapeutic fasciolosis control schemes. Varying degrees of F. hepatica risk occurred in most parts of the country and distinct regional F. hepatica transmission patterns could be identified. In the humid west, cercariae-shedding was predicted to occur from May to October. In the south it occurred from April to May and September to October, depending on the annual abundance of rain. In the north-central and central regions, risk was highest during heavy summer rains and pasture contamination with metacercariae was predicted to occur during August-September, except in wet years, when it may start as early as July and extend up to October. At cooler sites above altitude of 2800 m, completion of an infection cycle may require more than a year. Fasciola gigantica risk was present in the western, southern and north-central regions of the country at altitudes of 1440-2560 m

  7. A geographically weighted regression model for geothermal potential assessment in mediterranean cultural landscape

    Science.gov (United States)

    D'Arpa, S.; Zaccarelli, N.; Bruno, D. E.; Leucci, G.; Uricchio, V. F.; Zurlini, G.

    2012-04-01

    Geothermal heat can be used directly in many applications (agro-industrial processes, sanitary hot water production, heating/cooling systems, etc.). These applications respond to energetic and environmental sustainability criteria, ensuring substantial energy savings with low environmental impacts. In particular, in Mediterranean cultural landscapes the exploitation of geothermal energy offers a valuable alternative compared to other exploitation systems more land-consuming and visual-impact. However, low enthalpy geothermal energy applications at regional scale, require careful design and planning to fully exploit benefits and reduce drawbacks. We propose a first example of application of a Geographically Weighted Regression (GWR) for the modeling of geothermal potential in the Apulia Region (South Italy) by integrating hydrological (e.g. depth to water table, water speed and temperature), geological-geotechnical (e.g. lithology, thermal conductivity) parameters and land-use indicators. The GWR model can effectively cope with data quality, spatial anisotropy, lack of stationarity and presence of discontinuities in the underlying data maps. The geothermal potential assessment required a good knowledge of the space-time variation of the numerous parameters related to the status of geothermal resource, a contextual analysis of spatial and environmental features, as well as the presence and nature of regulations or infrastructures constraints. We create an ad hoc geodatabase within ArcGIS 10 collecting relevant data and performing a quality assessment. Cross-validation shows high level of consistency of the spatial local models, as well as error maps can depict areas of lower reliability. Based on low enthalpy geothermal potential map created, a first zoning of the study area is proposed, considering four level of possible exploitation. Such zoning is linked and refined by the actual legal constraints acting at regional or province level as enforced by the regional

  8. Systems-based modeling of generation variability under alternate geographic configurations of photovoltaic (PV) installations in Virginia

    International Nuclear Information System (INIS)

    Collins, Ross D.; Crowther, Kenneth G.

    2011-01-01

    With increased focus on renewable energy in our modern era, it is increasingly important to understand the impact of policies on the performance and reliability of regional energy systems. This research develops a model to understand how geographic dispersion of PV installations impacts the reliability of electricity generated from the total PV network, measured by the variance of the distribution of generated electricity. Using NREL data, beta probability distributions of sunlight (kWh/m 2 /day) in various regions of Virginia are estimated using a fitting method that minimizes the Kolmogorov-Smirnov test statistic. A Monte Carlo simulation model is developed to measure PV electricity generation from multiple centralized and dispersed configurations over 100,000 days of probabilistic sunlight. There is a calculable tradeoff between average generation and generation variability, and increased geographic dispersion of PV installations can decrease this variability. Controlling variable generation through policies that promote efficient PV siting can help provide reliable power, minimizing the need for load-balancing peaking power infrastructure and costly electricity purchases from the grid. Using a tradeoff framework of generation and costs, this paper shows that geographically dispersed generation can mitigate the risk of unreliable solar generation that can significantly impact the end-user costs and make PV infrastructure unattractive. - Highlights: → We model how uncertain sunlight affects generation of different PV systems. → We show that geographically dispersed systems decrease generation variability. → Geographically dispersed PV systems are potentially more costly in the short run. → Controlling variability provides reliable power, which can decrease long-run costs. → Promoting mixes of uncertain energy sources requires assessment of these tradeoffs.

  9. Geographic information modeling of Econet of Northwestern Federal District territory on graph theory basis

    Science.gov (United States)

    Kopylova, N. S.; Bykova, A. A.; Beregovoy, D. N.

    2018-05-01

    Based on the landscape-geographical approach, a structural and logical scheme for the Northwestern Federal District Econet has been developed, which can be integrated into the federal and world ecological network in order to improve the environmental infrastructure of the region. The method of Northwestern Federal District Econet organization on the basis of graph theory by means of the Quantum GIS geographic information system is proposed as an effective mean of preserving and recreating the unique biodiversity of landscapes, regulation of the sphere of environmental protection.

  10. Animal Model Selection for Inhalational HCN Exposure

    Science.gov (United States)

    2016-08-01

    effects. Following acute inhalation exposure in humans and animals, cyanide is found in the lung, heart, blood , kidneys, and brain (Ballantyne, 1983...Pritchard, 2007). Other direct or secondary effects associated with CN are reacting with the ferric and carbonyl group of enzymes (e.g. catalase...mechanisms occurs before myocardial depression. Clinically, an initial period of bradycardia and hypertension may occur, followed by hypotension with reflex

  11. Determinants of dermal exposure relevant for exposure modelling in regulatory risk assessment.

    Science.gov (United States)

    Marquart, J; Brouwer, D H; Gijsbers, J H J; Links, I H M; Warren, N; van Hemmen, J J

    2003-11-01

    Risk assessment of chemicals requires assessment of the exposure levels of workers. In the absence of adequate specific measured data, models are often used to estimate exposure levels. For dermal exposure only a few models exist, which are not validated externally. In the scope of a large European research programme, an analysis of potential dermal exposure determinants was made based on the available studies and models and on the expert judgement of the authors of this publication. Only a few potential determinants appear to have been studied in depth. Several studies have included clusters of determinants into vaguely defined parameters, such as 'task' or 'cleaning and maintenance of clothing'. Other studies include several highly correlated parameters, such as 'amount of product handled', 'duration of task' and 'area treated', and separation of these parameters to study their individual influence is not possible. However, based on the available information, a number of determinants could clearly be defined as proven or highly plausible determinants of dermal exposure in one or more exposure situation. This information was combined with expert judgement on the scientific plausibility of the influence of parameters that have not been extensively studied and on the possibilities to gather relevant information during a risk assessment process. The result of this effort is a list of determinants relevant for dermal exposure models in the scope of regulatory risk assessment. The determinants have been divided into the major categories 'substance and product characteristics', 'task done by the worker', 'process technique and equipment', 'exposure control measures', 'worker characteristics and habits' and 'area and situation'. To account for the complex nature of the dermal exposure processes, a further subdivision was made into the three major processes 'direct contact', 'surface contact' and 'deposition'.

  12. Exporters’ exposures to currencies: Beyond the loglinear model

    NARCIS (Netherlands)

    Boudt, K.M.R.; Liu, F.; Sercu, P.

    2016-01-01

    We extend the constant-elasticity regression that is the default choice when equities' exposure to currencies is estimated. In a proper real-option-style model for the exporters' equity exposure to the foreign exchange rate, we argue, the convexity of the relationship implies that the elasticity

  13. Hydrologic connectivity between geographically isolated wetlands and surface water systems: A review of select modeling methods

    Science.gov (United States)

    Heather E. Golden; Charles R. Lane; Devendra M. Amatya; Karl W. Bandilla; Hadas Raanan Kiperwas Kiperwas; Christopher D. Knightes; Herbert. Ssegane

    2014-01-01

    Geographically isolated wetlands (GIW), depressional landscape features entirely surrounded by upland areas, provide a wide range of ecological functions and ecosystem services for human well-being. Current and future ecosystem management and decision-making rely on a solid scientific understanding of how hydrologic processes affect these important GIW services and...

  14. Density-Based Clustering with Geographical Background Constraints Using a Semantic Expression Model

    Directory of Open Access Journals (Sweden)

    Qingyun Du

    2016-05-01

    Full Text Available A semantics-based method for density-based clustering with constraints imposed by geographical background knowledge is proposed. In this paper, we apply an ontological approach to the DBSCAN (Density-Based Geospatial Clustering of Applications with Noise algorithm in the form of knowledge representation for constraint clustering. When used in the process of clustering geographic information, semantic reasoning based on a defined ontology and its relationships is primarily intended to overcome the lack of knowledge of the relevant geospatial data. Better constraints on the geographical knowledge yield more reasonable clustering results. This article uses an ontology to describe the four types of semantic constraints for geographical backgrounds: “No Constraints”, “Constraints”, “Cannot-Link Constraints”, and “Must-Link Constraints”. This paper also reports the implementation of a prototype clustering program. Based on the proposed approach, DBSCAN can be applied with both obstacle and non-obstacle constraints as a semi-supervised clustering algorithm and the clustering results are displayed on a digital map.

  15. Exposure to Indoor Allergens in Different Residential Settings and Its Influence on IgE Sensitization in a Geographically Confined Austrian Cohort.

    Directory of Open Access Journals (Sweden)

    Teresa Stemeseder

    Full Text Available Exposure to indoor allergens is crucial for IgE sensitization and development of allergic symptoms. Residential settings influence the allergen amount in house dust and hence allergic sensitization. Within this study, we investigated allergen exposure and molecule-based IgE levels in a geographically confined region and evaluated the impact of housing, pets and cleaning.501 adolescents from Salzburg, Austria participated in this cross-sectional study. House dust samples were examined regarding major mite, cat, dog, and mold allergens using a multiplex assay. Serum samples of participants were analyzed for specific IgE to Der p 1, Der p 2, Fel d 1, Can f 1 and Alt a 1 using the multiplex array ImmunoCAP ISAC. Information on allergies, living areas, dwelling form (house, flat, farm, pets, and household cleanliness were obtained by a questionnaire.In investigated house dust samples, the concentration of cat allergen was highest while the prevalence of mold allergens was very low. Participants showed IgE sensitization to Der p 1 (13.2%, Der p 2 (18.2%, Fel d 1 (14.4%, Can f 1 (2.4% and Alt a 1 (2.0%. In alpine regions, lower mite allergen concentrations were detected which correlated with reduced IgE levels. A trend for increased sensitization prevalence from rural to alpine to urban regions was noted. Living on farms resulted in lower sensitization prevalence to mite and cat allergens, even though exposure to mites was significantly elevated. The presence of cats was associated with a lower sensitization rate and IgE levels to cat and mite allergens, and less frequent allergic diseases. Cleaning did not impact allergen concentrations, while IgE reactivity to mites and allergic diseases were more pronounced when living in cleaner homes.Allergen exposure to indoor allergens was influenced by setting of homes. Living in a farm environment and having a cat at home showed a protective effect for IgE sensitization and allergies. This cross

  16. Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential.

    Science.gov (United States)

    Mitchell, Jade; Arnot, Jon A; Jolliet, Olivier; Georgopoulos, Panos G; Isukapalli, Sastry; Dasgupta, Surajit; Pandian, Muhilan; Wambaugh, John; Egeghy, Peter; Cohen Hubal, Elaine A; Vallero, Daniel A

    2013-08-01

    While only limited data are available to characterize the potential toxicity of over 8 million commercially available chemical substances, there is even less information available on the exposure and use-scenarios that are required to link potential toxicity to human and ecological health outcomes. Recent improvements and advances such as high throughput data gathering, high performance computational capabilities, and predictive chemical inherency methodology make this an opportune time to develop an exposure-based prioritization approach that can systematically utilize and link the asymmetrical bodies of knowledge for hazard and exposure. In response to the US EPA's need to develop novel approaches and tools for rapidly prioritizing chemicals, a "Challenge" was issued to several exposure model developers to aid the understanding of current systems in a broader sense and to assist the US EPA's effort to develop an approach comparable to other international efforts. A common set of chemicals were prioritized under each current approach. The results are presented herein along with a comparative analysis of the rankings of the chemicals based on metrics of exposure potential or actual exposure estimates. The analysis illustrates the similarities and differences across the domains of information incorporated in each modeling approach. The overall findings indicate a need to reconcile exposures from diffuse, indirect sources (far-field) with exposures from directly, applied chemicals in consumer products or resulting from the presence of a chemical in a microenvironment like a home or vehicle. Additionally, the exposure scenario, including the mode of entry into the environment (i.e. through air, water or sediment) appears to be an important determinant of the level of agreement between modeling approaches. Copyright © 2013 Elsevier B.V. All rights reserved.

  17. Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential

    Science.gov (United States)

    Mitchell, Jade; Arnot, Jon A.; Jolliet, Olivier; Georgopoulos, Panos G.; Isukapalli, Sastry; Dasgupta, Surajit; Pandian, Muhilan; Wambaugh, John; Egeghy, Peter; Cohen Hubal, Elaine A.; Vallero, Daniel A.

    2014-01-01

    While only limited data are available to characterize the potential toxicity of over 8 million commercially available chemical substances, there is even less information available on the exposure and use-scenarios that are required to link potential toxicity to human and ecological health outcomes. Recent improvements and advances such as high throughput data gathering, high performance computational capabilities, and predictive chemical inherency methodology make this an opportune time to develop an exposure-based prioritization approach that can systematically utilize and link the asymmetrical bodies of knowledge for hazard and exposure. In response to the US EPA’s need to develop novel approaches and tools for rapidly prioritizing chemicals, a “Challenge” was issued to several exposure model developers to aid the understanding of current systems in a broader sense and to assist the US EPA’s effort to develop an approach comparable to other international efforts. A common set of chemicals were prioritized under each current approach. The results are presented herein along with a comparative analysis of the rankings of the chemicals based on metrics of exposure potential or actual exposure estimates. The analysis illustrates the similarities and differences across the domains of information incorporated in each modeling approach. The overall findings indicate a need to reconcile exposures from diffuse, indirect sources (far-field) with exposures from directly, applied chemicals in consumer products or resulting from the presence of a chemical in a microenvironment like a home or vehicle. Additionally, the exposure scenario, including the mode of entry into the environment (i.e. through air, water or sediment) appears to be an important determinant of the level of agreement between modeling approaches. PMID:23707726

  18. Simple Urban Simulation Atop Complicated Models: Multi-Scale Equation-Free Computing of Sprawl Using Geographic Automata

    Directory of Open Access Journals (Sweden)

    Yu Zou

    2013-07-01

    Full Text Available Reconciling competing desires to build urban models that can be simple and complicated is something of a grand challenge for urban simulation. It also prompts difficulties in many urban policy situations, such as urban sprawl, where simple, actionable ideas may need to be considered in the context of the messily complex and complicated urban processes and phenomena that work within cities. In this paper, we present a novel architecture for achieving both simple and complicated realizations of urban sprawl in simulation. Fine-scale simulations of sprawl geography are run using geographic automata to represent the geographical drivers of sprawl in intricate detail and over fine resolutions of space and time. We use Equation-Free computing to deploy population as a coarse observable of sprawl, which can be leveraged to run automata-based models as short-burst experiments within a meta-simulation framework.

  19. Energy Facility Siting by Means of Environmental Modelling with LANDSAT, Thematic Mapper and Geographic Information System (GIS) Data

    Science.gov (United States)

    1982-01-01

    Currently based on ground and aerial surveys, the land cover data base of the Pennsylvania Power and Light Company is routinely used for modelling the effects of alternative generating plant and transmission line sites on the local and regional environment. The development of a satellite-based geographic information system would facilitate both the preparation of environmental impact statements by power companies and assessment of the data by the Nuclear Regulatory Commission. A cooperative project is planned to demonstrate the methodology for integrating satellite data into an existing geographic information system, d to further evaluate the ability of satellite data in modeling environmental conditions that would be applied in the preparation and assessment of environmental impact statements.

  20. Efficient workload management in geographically distributed data centers leveraging autoregressive models

    Science.gov (United States)

    Altomare, Albino; Cesario, Eugenio; Mastroianni, Carlo

    2016-10-01

    The opportunity of using Cloud resources on a pay-as-you-go basis and the availability of powerful data centers and high bandwidth connections are speeding up the success and popularity of Cloud systems, which is making on-demand computing a common practice for enterprises and scientific communities. The reasons for this success include natural business distribution, the need for high availability and disaster tolerance, the sheer size of their computational infrastructure, and/or the desire to provide uniform access times to the infrastructure from widely distributed client sites. Nevertheless, the expansion of large data centers is resulting in a huge rise of electrical power consumed by hardware facilities and cooling systems. The geographical distribution of data centers is becoming an opportunity: the variability of electricity prices, environmental conditions and client requests, both from site to site and with time, makes it possible to intelligently and dynamically (re)distribute the computational workload and achieve as diverse business goals as: the reduction of costs, energy consumption and carbon emissions, the satisfaction of performance constraints, the adherence to Service Level Agreement established with users, etc. This paper proposes an approach that helps to achieve the business goals established by the data center administrators. The workload distribution is driven by a fitness function, evaluated for each data center, which weighs some key parameters related to business objectives, among which, the price of electricity, the carbon emission rate, the balance of load among the data centers etc. For example, the energy costs can be reduced by using a "follow the moon" approach, e.g. by migrating the workload to data centers where the price of electricity is lower at that time. Our approach uses data about historical usage of the data centers and data about environmental conditions to predict, with the help of regressive models, the values of the

  1. Measuring and modeling exposure from environmental radiation on tidal flats

    International Nuclear Information System (INIS)

    Gould, T.J.; Hess, C.T.

    2005-01-01

    To examine the shielding effects of the tide cycle, a high pressure ion chamber was used to measure the exposure rate from environmental radiation on tidal flats. A theoretical model is derived to predict the behavior of exposure rate as a function of time for a detector placed one meter above ground on a tidal flat. The numerical integration involved in this derivation results in an empirical formula which implies exposure rate ∝tan-1(sint). We propose that calculating the total exposure incurred on a tidal flat requires measurements of only the slope of the tidal flat and the exposure rate when no shielding occurs. Experimental results are consistent with the model

  2. Literature review on induced exposure models, Task 2 HS-270

    Science.gov (United States)

    1982-02-01

    Sections 1, 2 and 3 of this report describe the development of : induced exposure models, together with d discussion of questions : of validity. These Sections focus on the most important and : relevant results from the literature, while Appendix A c...

  3. The role of geographic information systems inwildlife epidemiology: models of chronic wasting disease in Colorado mule deer

    OpenAIRE

    Farnsworth, Matthew L.; Hoeting, Jennifer A.; Hobbs, N. Thompson; Conner, Mary M.; Burnham, Kenneth P.; Wolfe, Lisa L.; Williams, Elizabeth S.; Theobald, David M.; Miller, Michael W.

    2007-01-01

    The authors present findings from two landscape epidemiology studies of chronic wasting disease (CWD) in northern Colorado mule deer (Odocoileus hemionus). First, the effects of human land use on disease prevalence were explored by formulating a set of models estimating CWD prevalence in relation to differences in human land use, sex and geographic location. Prevalence was higher in developed areas and among male deer suggesting that anthropogenic influences (changes in land use), differences...

  4. Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.

    Science.gov (United States)

    Long, Nguyen Phuoc; Lim, Dong Kyu; Mo, Changyeun; Kim, Giyoung; Kwon, Sung Won

    2017-08-17

    Geographical origin determination of white rice has become the major issue of food industry. However, there is still lack of a high-throughput method for rapidly and reproducibly differentiating the geographical origins of commercial white rice. In this study, we developed a method that employed lipidomics and deep learning to discriminate white rice from Korea to China. A total of 126 white rice of 30 cultivars from different regions were utilized for the method development and validation. By using direct infusion-mass spectrometry-based targeted lipidomics, 17 lysoglycerophospholipids were simultaneously characterized within minutes per sample. Unsupervised data exploration showed a noticeable overlap of white rice between two countries. In addition, lysophosphatidylcholines (lysoPCs) were prominent in white rice from Korea while lysophosphatidylethanolamines (lysoPEs) were enriched in white rice from China. A deep learning prediction model was built using 2014 white rice and validated using two different batches of 2015 white rice. The model accurately discriminated white rice from two countries. Among 10 selected predictors, lysoPC(18:2), lysoPC(14:0), and lysoPE(16:0) were the three most important features. Random forest and gradient boosting machine models also worked well in this circumstance. In conclusion, this study provides an architecture for high-throughput classification of white rice from different geographical origins.

  5. Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression.

    Science.gov (United States)

    Song, Chao; Kwan, Mei-Po; Zhu, Jiping

    2017-04-08

    An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.

  6. Reconstructing exposures from biomarkers using exposure-pharmacokinetic modeling--A case study with carbaryl.

    Science.gov (United States)

    Brown, Kathleen; Phillips, Martin; Grulke, Christopher; Yoon, Miyoung; Young, Bruce; McDougall, Robin; Leonard, Jeremy; Lu, Jingtao; Lefew, William; Tan, Yu-Mei

    2015-12-01

    Sources of uncertainty involved in exposure reconstruction for short half-life chemicals were characterized using computational models that link external exposures to biomarkers. Using carbaryl as an example, an exposure model, the Cumulative and Aggregate Risk Evaluation System (CARES), was used to generate time-concentration profiles for 500 virtual individuals exposed to carbaryl. These exposure profiles were used as inputs into a physiologically based pharmacokinetic (PBPK) model to predict urinary biomarker concentrations. These matching dietary intake levels and biomarker concentrations were used to (1) compare three reverse dosimetry approaches based on their ability to predict the central tendency of the intake dose distribution; and (2) identify parameters necessary for a more accurate exposure reconstruction. This study illustrates the trade-offs between using non-iterative reverse dosimetry methods that are fast, less precise and iterative methods that are slow, more precise. This study also intimates the necessity of including urine flow rate and elapsed time between last dose and urine sampling as part of the biomarker sampling collection for better interpretation of urinary biomarker data of short biological half-life chemicals. Resolution of these critical data gaps can allow exposure reconstruction methods to better predict population-level intake doses from large biomonitoring studies. Published by Elsevier Inc.

  7. Comprehensive European dietary exposure model (CEDEM) for food additives.

    Science.gov (United States)

    Tennant, David R

    2016-05-01

    European methods for assessing dietary exposures to nutrients, additives and other substances in food are limited by the availability of detailed food consumption data for all member states. A proposed comprehensive European dietary exposure model (CEDEM) applies summary data published by the European Food Safety Authority (EFSA) in a deterministic model based on an algorithm from the EFSA intake method for food additives. The proposed approach can predict estimates of food additive exposure provided in previous EFSA scientific opinions that were based on the full European food consumption database.

  8. Mapping and Modelling the Geographical Distribution and Environmental Limits of Podoconiosis in Ethiopia

    OpenAIRE

    Deribe, Kebede; Cano, Jorge; Newport, Melanie J.; Golding, Nick; Pullan, Rachel L.; Sime, Heven; Gebretsadik, Abeba; Assefa, Ashenafi; Kebede, Amha; Hailu, Asrat; Rebollo, Maria P.; Shafi, Oumer; Bockarie, Moses J.; Aseffa, Abraham; Hay, Simon I.

    2015-01-01

    Background\\ud \\ud Ethiopia is assumed to have the highest burden of podoconiosis globally, but the geographical distribution and environmental limits and correlates are yet to be fully investigated. In this paper we use data from a nationwide survey to address these issues.\\ud \\ud Methodology\\ud \\ud Our analyses are based on data arising from the integrated mapping of podoconiosis and lymphatic filariasis (LF) conducted in 2013, supplemented by data from an earlier mapping of LF in western Et...

  9. Modeling Exposure to Persistent Chemicals in Hazard and Risk Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Cowan-Ellsberry, Christina E.; McLachlan, Michael S.; Arnot, Jon A.; MacLeod, Matthew; McKone, Thomas E.; Wania, Frank

    2008-11-01

    Fate and exposure modeling has not thus far been explicitly used in the risk profile documents prepared to evaluate significant adverse effect of candidate chemicals for either the Stockholm Convention or the Convention on Long-Range Transboundary Air Pollution. However, we believe models have considerable potential to improve the risk profiles. Fate and exposure models are already used routinely in other similar regulatory applications to inform decisions, and they have been instrumental in building our current understanding of the fate of POP and PBT chemicals in the environment. The goal of this paper is to motivate the use of fate and exposure models in preparing risk profiles in the POP assessment procedure by providing strategies for incorporating and using models. The ways that fate and exposure models can be used to improve and inform the development of risk profiles include: (1) Benchmarking the ratio of exposure and emissions of candidate chemicals to the same ratio for known POPs, thereby opening the possibility of combining this ratio with the relative emissions and relative toxicity to arrive at a measure of relative risk. (2) Directly estimating the exposure of the environment, biota and humans to provide information to complement measurements, or where measurements are not available or are limited. (3) To identify the key processes and chemical and/or environmental parameters that determine the exposure; thereby allowing the effective prioritization of research or measurements to improve the risk profile. (4) Predicting future time trends including how quickly exposure levels in remote areas would respond to reductions in emissions. Currently there is no standardized consensus model for use in the risk profile context. Therefore, to choose the appropriate model the risk profile developer must evaluate how appropriate an existing model is for a specific setting and whether the assumptions and input data are relevant in the context of the application

  10. Modeling exposure to persistent chemicals in hazard and risk assessment.

    Science.gov (United States)

    Cowan-Ellsberry, Christina E; McLachlan, Michael S; Arnot, Jon A; Macleod, Matthew; McKone, Thomas E; Wania, Frank

    2009-10-01

    Fate and exposure modeling has not, thus far, been explicitly used in the risk profile documents prepared for evaluating the significant adverse effect of candidate chemicals for either the Stockholm Convention or the Convention on Long-Range Transboundary Air Pollution. However, we believe models have considerable potential to improve the risk profiles. Fate and exposure models are already used routinely in other similar regulatory applications to inform decisions, and they have been instrumental in building our current understanding of the fate of persistent organic pollutants (POP) and persistent, bioaccumulative, and toxic (PBT) chemicals in the environment. The goal of this publication is to motivate the use of fate and exposure models in preparing risk profiles in the POP assessment procedure by providing strategies for incorporating and using models. The ways that fate and exposure models can be used to improve and inform the development of risk profiles include 1) benchmarking the ratio of exposure and emissions of candidate chemicals to the same ratio for known POPs, thereby opening the possibility of combining this ratio with the relative emissions and relative toxicity to arrive at a measure of relative risk; 2) directly estimating the exposure of the environment, biota, and humans to provide information to complement measurements or where measurements are not available or are limited; 3) to identify the key processes and chemical or environmental parameters that determine the exposure, thereby allowing the effective prioritization of research or measurements to improve the risk profile; and 4) forecasting future time trends, including how quickly exposure levels in remote areas would respond to reductions in emissions. Currently there is no standardized consensus model for use in the risk profile context. Therefore, to choose the appropriate model the risk profile developer must evaluate how appropriate an existing model is for a specific setting and

  11. Modelling of individual subject ozone exposure response kinetics.

    Science.gov (United States)

    Schelegle, Edward S; Adams, William C; Walby, William F; Marion, M Susan

    2012-06-01

    A better understanding of individual subject ozone (O(3)) exposure response kinetics will provide insight into how to improve models used in the risk assessment of ambient ozone exposure. To develop a simple two compartment exposure-response model that describes individual subject decrements in forced expiratory volume in one second (FEV(1)) induced by the acute inhalation of O(3) lasting up to 8 h. FEV(1) measurements of 220 subjects who participated in 14 previously completed studies were fit to the model using both particle swarm and nonlinear least squares optimization techniques to identify three subject-specific coefficients producing minimum "global" and local errors, respectively. Observed and predicted decrements in FEV(1) of the 220 subjects were used for validation of the model. Further validation was provided by comparing the observed O(3)-induced FEV(1) decrements in an additional eight studies with predicted values obtained using model coefficients estimated from the 220 subjects used in cross validation. Overall the individual subject measured and modeled FEV(1) decrements were highly correlated (mean R(2) of 0.69 ± 0.24). In addition, it was shown that a matrix of individual subject model coefficients can be used to predict the mean and variance of group decrements in FEV(1). This modeling approach provides insight into individual subject O(3) exposure response kinetics and provides a potential starting point for improving the risk assessment of environmental O(3) exposure.

  12. The modelling of external exposure and inhalation pathways in COSYMA

    International Nuclear Information System (INIS)

    Brown, J.; Simmonds, JR.; Ehrhardt, J.; Hasemann, I.

    1991-01-01

    Following an accidental release of radionuclides to atmosphere the major direct exposure pathways of concern are: external irradiation from material in the cloud; internal exposure following inhalation of material in the cloud; external irradiation from material deposited on the ground; and external irradiation due to contamination of skin and clothes. In addition material resuspended from the ground can be inhaled and lead to internal exposure. In this paper the way that these exposure pathways are modelled in COSYMA is described. At present in COSYMA external exposure from deposited material is modelled using a dataset of doses per unit deposit of various radionuclides. This dataset, is based on activity deposited on undisturbed soil. The basic data are for doses outdoors and shielding factors are used to estimate doses for people indoors. Various groups of people spending different amounts of time indoors and out can be considered and shielding factors appropriate to three building types can be adopted. A more complex model has also been developed to predict radiation exposure following deposition to different surfaces in the environment. This model called EXPURT is briefly described in this paper. Using EXPURT, doses as a function of time after a single deposit have been calculated for people living in three types of area. These results are described in the paper and compared with those that are currently used in COSYMA. The paper will also discuss what future work is required in this area and the adequacy of existing models

  13. Modelling survival: exposure pattern, species sensitivity and uncertainty.

    Science.gov (United States)

    Ashauer, Roman; Albert, Carlo; Augustine, Starrlight; Cedergreen, Nina; Charles, Sandrine; Ducrot, Virginie; Focks, Andreas; Gabsi, Faten; Gergs, André; Goussen, Benoit; Jager, Tjalling; Kramer, Nynke I; Nyman, Anna-Maija; Poulsen, Veronique; Reichenberger, Stefan; Schäfer, Ralf B; Van den Brink, Paul J; Veltman, Karin; Vogel, Sören; Zimmer, Elke I; Preuss, Thomas G

    2016-07-06

    The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans.

  14. Neurotoxicity in Preclinical Models of Occupational Exposure to Organophosphorus Compounds

    Science.gov (United States)

    Voorhees, Jaymie R.; Rohlman, Diane S.; Lein, Pamela J.; Pieper, Andrew A.

    2017-01-01

    Organophosphorus (OPs) compounds are widely used as insecticides, plasticizers, and fuel additives. These compounds potently inhibit acetylcholinesterase (AChE), the enzyme that inactivates acetylcholine at neuronal synapses, and acute exposure to high OP levels can cause cholinergic crisis in humans and animals. Evidence further suggests that repeated exposure to lower OP levels insufficient to cause cholinergic crisis, frequently encountered in the occupational setting, also pose serious risks to people. For example, multiple epidemiological studies have identified associations between occupational OP exposure and neurodegenerative disease, psychiatric illness, and sensorimotor deficits. Rigorous scientific investigation of the basic science mechanisms underlying these epidemiological findings requires valid preclinical models in which tightly-regulated exposure paradigms can be correlated with neurotoxicity. Here, we review the experimental models of occupational OP exposure currently used in the field. We found that animal studies simulating occupational OP exposures do indeed show evidence of neurotoxicity, and that utilization of these models is helping illuminate the mechanisms underlying OP-induced neurological sequelae. Still, further work is necessary to evaluate exposure levels, protection methods, and treatment strategies, which taken together could serve to modify guidelines for improving workplace conditions globally. PMID:28149268

  15. Modelling indoor exposure to natural radioactive nuclides

    International Nuclear Information System (INIS)

    Hofmann, W.; Daschil, F.

    1986-01-01

    Radon enters buildings from several sources primarily from building materials and from the soil or rocks that underlie or surround building fundaments. A multicompartment model was developed which describes the fate of radon and attached or free radon decay products in a model room by a set of linear time-dependent differential equations. Time-dependent coefficients allow to model temporal parameter changes, e.g. the opening of windows, or a sudden pressure drop leading to enhanced exhalation. While steady-state models were used to study the effect of parameter changes on steady state nuclide concentrations, the time-dependent models provided additional information on the time scale of these changes. (author)

  16. Underwater Sound Propagation Modeling Methods for Predicting Marine Animal Exposure.

    Science.gov (United States)

    Hamm, Craig A; McCammon, Diana F; Taillefer, Martin L

    2016-01-01

    The offshore exploration and production (E&P) industry requires comprehensive and accurate ocean acoustic models for determining the exposure of marine life to the high levels of sound used in seismic surveys and other E&P activities. This paper reviews the types of acoustic models most useful for predicting the propagation of undersea noise sources and describes current exposure models. The severe problems caused by model sensitivity to the uncertainty in the environment are highlighted to support the conclusion that it is vital that risk assessments include transmission loss estimates with statistical measures of confidence.

  17. Developing landscape habitat models for rare amphibians with small geographic ranges: a case study of Siskiyou Mountains salamanders in the western USA

    Science.gov (United States)

    Nobuya Suzuki; Deanna H. Olson; Edward C. Reilly

    2007-01-01

    To advance the development of conservation planning for rare species with small geographic ranges, we determined habitat associations of Siskiyou Mountains salamanders (Plethodon stormi) and developed habitat suitability models at fine (10 ha), medium (40 ha), and broad (202 ha) spatial scales using available geographic information systems data and...

  18. An instantaneous spatiotemporal model to predict a bicyclist's Black Carbon exposure based on mobile noise measurements

    Science.gov (United States)

    Dekoninck, Luc; Botteldooren, Dick; Int Panis, Luc

    2013-11-01

    Several studies have shown that a significant amount of daily air pollution exposure, in particular Black Carbon (BC), is inhaled during trips. Assessing this contribution to exposure remains difficult because on the one hand local air pollution maps lack spatio-temporal resolution, at the other hand direct measurement of particulate matter concentration remains expensive. This paper proposes to use in-traffic noise measurements in combination with geographical and meteorological information for predicting BC exposure during commuting trips. Mobile noise measurements are cheaper and easier to perform than mobile air pollution measurements and can easily be used in participatory sensing campaigns. The uniqueness of the proposed model lies in the choice of noise indicators that goes beyond the traditional overall A-weighted noise level used in previous work. Noise and BC exposures are both related to the traffic intensity but also to traffic speed and traffic dynamics. Inspired by theoretical knowledge on the emission of noise and BC, the low frequency engine related noise and the difference between high frequency and low frequency noise that indicates the traffic speed, are introduced in the model. In addition, it is shown that splitting BC in a local and a background component significantly improves the model. The coefficients of the proposed model are extracted from 200 commuter bicycle trips. The predicted average exposure over a single trip correlates with measurements with a Pearson coefficient of 0.78 using only four parameters: the low frequency noise level, wind speed, the difference between high and low frequency noise and a street canyon index expressing local air pollution dispersion properties.

  19. Hydroquinone PBPK model refinement and application to dermal exposure.

    Science.gov (United States)

    Poet, Torka S; Carlton, Betsy D; Deyo, James A; Hinderliter, Paul M

    2010-11-01

    A physiologically based pharmacokinetic (PBPK) model for hydroquinone (HQ) was refined to include an expanded description of HQ-glucuronide metabolites and a description of dermal exposures to support route-to-route and cross-species extrapolation. Total urinary excretion of metabolites from in vivo rat dermal exposures was used to estimate a percutaneous permeability coefficient (K(p); 3.6×10(-5) cm/h). The human in vivo K(p) was estimated to be 1.62×10(-4) cm/h, based on in vitro skin permeability data in rats and humans and rat in vivo values. The projected total multi-substituted glutathione (which was used as an internal dose surrogate for the toxic glutathione metabolites) was modeled following an exposure scenario based on submersion of both hands in a 5% aqueous solution of HQ (similar to black and white photographic developing solution) for 2 h, a worst-case exposure scenario. Total multi-substituted glutathione following this human dermal exposure scenario was several orders of magnitude lower than the internal total glutathione conjugates in rats following an oral exposure to the rat NOEL of 20 mg/kg. Thus, under more realistic human dermal exposure conditions, it is unlikely that toxic glutathione conjugates (primarily the di- and, to a lesser degree, the tri-glutathione conjugate) will reach significant levels in target tissues. Copyright © 2010. Published by Elsevier Ltd.

  20. Offer acceptance practices and geographic variability in allocation model for end-stage liver disease at transplant.

    Science.gov (United States)

    Wey, Andrew; Pyke, Joshua; Schladt, David P; Gentry, Sommer E; Weaver, Tim; Salkowski, Nicholas; Kasiske, Bertram L; Israni, Ajay K; Snyder, Jon J

    2018-04-01

    Offer acceptance practices may cause geographic variability in allocation Model for End-Stage Liver Disease (aMELD) score at transplant and could magnify the effect of donor supply and demand on aMELD variability. To evaluate these issues, offer acceptance practices of liver transplant programs and donation service areas (DSAs) were estimated using offers of livers from donors recovered between January 1, 2016, and December 31, 2016. Offer acceptance practices were compared with liver yield, local placement of transplanted livers, donor supply and demand, and aMELD at transplant. Offer acceptance was associated with liver yield (odds ratio, 1.32; P offer acceptance (r = 0.09; P = 0.50). Additionally, the association between DSA-level donor-to-candidate ratios and aMELD at transplant did not change after adjustment for offer acceptance. The average squared difference in median aMELD at transplant across DSAs was 24.6; removing the effect of donor-to-candidate ratios reduced the average squared differences more than removing the effect of program-level offer acceptance (33% and 15% reduction, respectively). Offer acceptance practices and donor-to-candidate ratios independently contributed to geographic variability in aMELD at transplant. Thus, neither offer acceptance nor donor-to-candidate ratios can explain all of the geographic variability in aMELD at transplant. Liver Transplantation 24 478-487 2018 AASLD. © 2018 by the American Association for the Study of Liver Diseases.

  1. Modelling of indoor exposure to nitrogen dioxide in the UK

    Science.gov (United States)

    Dimitroulopoulou, C.; Ashmore, M. R.; Byrne, M. A.; Kinnersley, R. P.

    A dynamic multi-compartment computer model has been developed to describe the physical processes determining indoor pollutant concentrations as a function of outdoor concentrations, indoor emission rates and building characteristics. The model has been parameterised for typical UK homes and workplaces and linked to a time-activity model to calculate exposures for a representative homemaker, schoolchild and office worker, with respect to NO 2. The estimates of population exposures, for selected urban and rural sites, are expressed in terms of annual means and frequency of hours in which air quality standards are exceeded. The annual mean exposures are estimated to fall within the range of 5-21 ppb for homes with no source, and 21-27 ppb for homes with gas cooking, varying across sites and population groups. The contribution of outdoor exposure to annual mean NO 2 exposure varied from 5 to 24%, that of indoor penetration of outdoor air from 17 to 86% and that of gas cooking from 0 to 78%. The frequency of exposure to 1 h mean concentrations above 150 ppb was very low, except for people cooking with gas.

  2. Separation of uncertainty and interindividual variability in human exposure modeling.

    NARCIS (Netherlands)

    Ragas, A.M.J.; Brouwer, F.P.E.; Buchner, F.L.; Hendriks, H.W.; Huijbregts, M.A.J.

    2009-01-01

    The NORMTOX model predicts the lifetime-averaged exposure to contaminants through multiple environmental media, that is, food, air, soil, drinking and surface water. The model was developed to test the coherence of Dutch environmental quality objectives (EQOs). A set of EQOs is called coherent if

  3. Mechanistic models for cancer development after short time radiation exposure

    International Nuclear Information System (INIS)

    Kottbauer, M. M.

    1997-12-01

    In this work two biological based models were developed. First the single-hit model for solid tumors (SHM-S) and second the single-hit model for leukemia (SHM-L). These models are a further development of the Armitage-Doll model for the special case of a short time radiation exposure. The basis of the models is the multistage process of carcinogeneses. The single-hit models provide simultaneously the age-dependent cancer-rate of spontaneous and radiation induced tumors as well as the dose-effect relationships at any age after exposure. The SHM-S leads to a biological based dose-effect relationship, which is similar to the relative risk model suggested by the ICRP 60. The SHM-S describes the increased mortality rate of the bomb survivors more accurate than the relative risk model. The SHM-L results in an additive dose-effect relationship. It is shown that only small differences in the derivation of the two models lead to the two dose-effect relationships. Beside the radiation exposure the new models consider the decrease of the cancer mortality rate at higher ages (age>75) which can be traced back mainly to three causes: competitive causes of death, reduction of cell proliferation and reduction of risk groups. The single-hit models also consider children cancer, the different rates of incidence and mortality, influence of the immune system and the cell-killing effect. (author)

  4. Stoffenmanager exposure model: company-specific exposure assessments using a Bayesian methodology.

    NARCIS (Netherlands)

    Ven, P. van de; Fransman, W.; Schinkel, J.; Rubingh, C.; Warren, N.; Tielemans, E.

    2010-01-01

    The web-based tool "Stoffenmanager" was initially developed to assist small- and medium-sized enterprises in the Netherlands to make qualitative risk assessments and to provide advice on control at the workplace. The tool uses a mechanistic model to arrive at a "Stoffenmanager score" for exposure.

  5. A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

    Science.gov (United States)

    Zhang, Feng; Xu, Yuetong; Chou, Jarong

    2016-01-01

    The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples. PMID:27681730

  6. A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

    Directory of Open Access Journals (Sweden)

    Feng Zhang

    2016-09-01

    Full Text Available The service of sensor device in Emerging Sensor Networks (ESNs is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples.

  7. Modelling exposure of mammalian predators to anticoagulant rodenticide

    Directory of Open Access Journals (Sweden)

    Christopher John Topping

    2016-12-01

    Full Text Available Anticoagulant rodenticides (AR are a widespread and effective method of rodent control but there is concern about the impact these may have on non-target organisms, in particular secondary poisoning of rodent predators. Incidence and concentration of AR in free-living predators in Denmark is very high. We postulate that this is caused by widespread exposure due to widespread use of AR in Denmark in and around buildings. To investigate this theory a spatio-temporal model of AR use and mammalian predator distribution was created. This model was supported by data from an experimental study of mice as vectors of AR, and was used to evaluate likely impacts of restrictions imposed on AR use in Denmark banning the use of rodenticides for plant protection in woodlands and tree-crops. The model uses input based on frequencies and timings of baiting for rodent control for urban, rural and woodland locations and creates an exposure map based on spatio-temporal modelling of movement of mice-vectored AR (based on Apodemus flavicollis. Simulated predator territories are super-imposed over this exposure map to create an exposure index. Predictions from the model concur with field studies of AR prevalence both before and after the change in AR use. In most cases incidence of exposure to AR is predicted to be greater than 90%, although cessation of use in woodlots and Christmas tree plantations should reduce mean exposure concentrations. Model results suggest that the driver of high AR incidence in non-target small mammal predators is likely to be the pattern of use and not the distance AR is vectored. Reducing baiting frequency by 75% had different effects depending on the landscape simulated, but having a maximum of 12% reduction in exposure incidence, and in one landscape a maximum reduction of <2%. We discuss sources of uncertainty in the model and directions for future development of predictive models for environmental impact assessment of rodenticides. The

  8. Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.

    Science.gov (United States)

    Samoli, Evangelia; Butland, Barbara K

    2017-12-01

    Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.

  9. An improved model for the reconstruction of past radon exposure.

    Science.gov (United States)

    Cauwels, P; Poffijn, A

    2000-05-01

    If the behavior of long-lived radon progeny was well understood, measurements of these could be used in epidemiological studies to estimate past radon exposure. Field measurements were done in a radon-prone area in the Ardennes (Belgium). The surface activity of several glass sheets was measured using detectors that were fixed on indoor glass surfaces. Simultaneously the indoor radon concentration was measured using diffusion chambers. By using Monte Carlo techniques, it could be proven that there is a discrepancy between this data set and the room model calculations, which are normally used to correlate surface activity and past radon exposure. To solve this, a modification of the model is proposed.

  10. Applied exposure modeling for residual radioactivity and release criteria

    International Nuclear Information System (INIS)

    Lee, D.W.

    1989-01-01

    The protection of public health and the environment from the release of materials with residual radioactivity for recycle or disposal as wastes without radioactive contents of concern presents a formidable challenge. Existing regulatory criteria are based on technical judgment concerning detectability and simple modeling. Recently, exposure modeling methodologies have been developed to provide a more consistent level of health protection. Release criteria derived from the application of exposure modeling methodologies share the same basic elements of analysis but are developed to serve a variety of purposes. Models for the support of regulations for all applications rely on conservative interpretations of generalized conditions while models developed to show compliance incorporate specific conditions not likely to be duplicated at other sites. Research models represent yet another type of modeling which strives to simulate the actual behavior of released material. In spite of these differing purposes, exposure modeling permits the application of sound and reasoned principles of radiation protection to the release of materials with residual levels of radioactivity. Examples of the similarities and differences of these models are presented and an application to the disposal of materials with residual levels of uranium contamination is discussed. 5 refs., 2 tabs

  11. BETR-World: a geographically explicit model of chemical fate: application to transport of α-HCH to the Arctic

    International Nuclear Information System (INIS)

    Toose, L.; Woodfine, D.G.; MacLeod, M.; Mackay, D.; Gouin, J.

    2004-01-01

    The Berkeley-Trent (BETR)-World model, a 25 compartment, geographically explicit fugacity-based model is described and applied to evaluate the transport of chemicals from temperate source regions to receptor regions (such as the Arctic). The model was parameterized using GIS and an array of digital data on weather, oceans, freshwater, vegetation and geo-political boundaries. This version of the BETR model framework includes modification of atmospheric degradation rates by seasonally variable hydroxyl radical concentrations and temperature. Degradation rates in all other compartments vary with seasonally changing temperature. Deposition to the deep ocean has been included as a loss mechanism. A case study was undertaken for α-HCH. Dynamic emission scenarios were estimated for each of the 25 regions. Predicted environmental concentrations showed good agreement with measured values for the northern regions in air, and fresh and oceanic water and with the results from a previous model of global chemical fate. Potential for long-range transport and deposition to the Arctic region was assessed using a Transfer Efficiency combined with estimated emissions. European regions and the Orient including China have a high potential to contribute α-HCH contamination in the Arctic due to high rates of emission in these regions despite low Transfer Efficiencies. Sensitivity analyses reveal that the performance and reliability of the model is strongly influenced by parameters controlling degradation rates. - A geographically explicit multi-compartment model is applied to the transport of α-HCH to the Arctic, showing Europe and the Orient are key sources

  12. The effects of photovoltaic electricity injection into microgrids: Combination of Geographical Information Systems, multicriteria decision methods and electronic control modeling

    International Nuclear Information System (INIS)

    Roa-Escalante, Gino de Jesús; Sánchez-Lozano, Juan Miguel; Faxas, Juan-Gabriel; García-Cascales, M. Socorro; Urbina, Antonio

    2015-01-01

    Highlights: • Geographical Information Systems can be used as a support to classify the viable locations for photovoltaic facilities. • Multicriteria decision methods are useful tools to choose the optimal locations for photovoltaic systems. • Variations of photovoltaic power injected into the grid have been calculated for the optimum locations. • Grid stabilization can be achieved within 500 ms with electronic control strategies. - Abstract: This article presents a model to calculate the impact on the grid of the injection of electricity generated from photovoltaic systems. The methodology combines the use of Geographical Information System tools to classify the optimal locations for the installation of photovoltaic systems with the calculation of the impact into microgrids of the electricity generated in such locations. The case study is focused on Murcia region, in South-east Spain, and on medium size photovoltaic systems. The locations have been selected from a Geographical Information System database including several parameters, and evaluated and classified using a fuzzy version of the multicriteria decision method called Technique for Order Preference by Similarity to Ideal Solution. In order to obtain the weights for the criteria used in the evaluation, the Analytic Hierarchy Process has been used. Finally, using meteorological data from a small set of possible locations, the impact on the grid arising from the injection of power generated from photovoltaic systems that are connected to the grid via a module implementing different control electronic strategies has been calculated. Different electronic control strategies have been modeled to demonstrate that stabilization of the electrical parameters of a microgrid can be obtained within 500 ms in all cases, even when a relatively large power surge, or slower variations, are injected into the grid from the medium size photovoltaic systems

  13. Hierarchical Distributed-Lag Models: Exploring Varying Geographic Scale and Magnitude in Associations Between the Built Environment and Health.

    Science.gov (United States)

    Baek, Jonggyu; Sanchez-Vaznaugh, Emma V; Sánchez, Brisa N

    2016-03-15

    It is well known that associations between features of the built environment and health depend on the geographic scale used to construct environmental attributes. In the built environment literature, it has long been argued that geographic scales may vary across study locations. However, this hypothesized variation has not been systematically examined due to a lack of available statistical methods. We propose a hierarchical distributed-lag model (HDLM) for estimating the underlying overall shape of food environment-health associations as a function of distance from locations of interest. This method enables indirect assessment of relevant geographic scales and captures area-level heterogeneity in the magnitudes of associations, along with relevant distances within areas. The proposed model was used to systematically examine area-level variation in the association between availability of convenience stores around schools and children's weights. For this case study, body mass index (weight kg)/height (m)2) z scores (BMIz) for 7th grade children collected via California's 2001-2009 FitnessGram testing program were linked to a commercial database that contained locations of food outlets statewide. Findings suggested that convenience store availability may influence BMIz only in some places and at varying distances from schools. Future research should examine localized environmental or policy differences that may explain the heterogeneity in convenience store-BMIz associations. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  14. Chlorpyrifos PBPK/PD model for multiple routes of exposure.

    Science.gov (United States)

    Poet, Torka S; Timchalk, Charles; Hotchkiss, Jon A; Bartels, Michael J

    2014-10-01

    1. Chlorpyrifos (CPF) is an important pesticide used to control crop insects. Human Exposures to CPF will occur primarily through oral exposure to residues on foods. A physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model has been developed that describes the relationship between oral, dermal and inhalation doses of CPF and key events in the pathway for cholinergic effects. The model was built on a prior oral model that addressed age-related changes in metabolism and physiology. This multi-route model was developed in rats and humans to validate all scenarios in a parallelogram design. 2. Critical biological effects from CPF exposure require metabolic activation to CPF oxon, and small amounts of metabolism in tissues will potentially have a great effect on pharmacokinetics and pharmacodynamic outcomes. Metabolism (bioactivation and detoxification) was therefore added in diaphragm, brain, lung and skin compartments. Pharmacokinetic data are available for controlled human exposures via the oral and dermal routes and from oral and inhalation studies in rats. The validated model was then used to determine relative dermal versus inhalation uptake from human volunteers exposed to CPF in an indoor scenario.

  15. A Critical Review of the Integration of Geographic Information System and Building Information Modelling at the Data Level

    Directory of Open Access Journals (Sweden)

    Junxiang Zhu

    2018-02-01

    Full Text Available The benefits brought by the integration of Building Information Modelling (BIM and Geographic Information Systems (GIS are being proved by more and more research. The integration of the two systems is difficult for many reasons. Among them, data incompatibility is the most significant, as BIM and GIS data are created, managed, analyzed, stored, and visualized in different ways in terms of coordinate systems, scope of interest, and data structures. The objective of this paper is to review the relevant research papers to (1 identify the most relevant data models used in BIM/GIS integration and understand their advantages and disadvantages; (2 consider the possibility of other data models that are available for data level integration; and (3 provide direction on the future of BIM/GIS data integration.

  16. Geographically Weighted Regression Model with Kernel Bisquare and Tricube Weighted Function on Poverty Percentage Data in Central Java Province

    Science.gov (United States)

    Nugroho, N. F. T. A.; Slamet, I.

    2018-05-01

    Poverty is a socio-economic condition of a person or group of people who can not fulfil their basic need to maintain and develop a dignified life. This problem still cannot be solved completely in Central Java Province. Currently, the percentage of poverty in Central Java is 13.32% which is higher than the national poverty rate which is 11.13%. In this research, data of percentage of poor people in Central Java Province has been analyzed through geographically weighted regression (GWR). The aim of this research is therefore to model poverty percentage data in Central Java Province using GWR with weighted function of kernel bisquare, and tricube. As the results, we obtained GWR model with bisquare and tricube kernel weighted function on poverty percentage data in Central Java province. From the GWR model, there are three categories of region which are influenced by different of significance factors.

  17. Use of geographically weighted logistic regression to quantify spatial variation in the environmental and sociodemographic drivers of leptospirosis in Fiji: a modelling study

    Directory of Open Access Journals (Sweden)

    Helen J Mayfield, PhD

    2018-05-01

    Full Text Available Summary: Background: Leptospirosis is a globally important zoonotic disease, with complex exposure pathways that depend on interactions between human beings, animals, and the environment. Major drivers of outbreaks include flooding, urbanisation, poverty, and agricultural intensification. The intensity of these drivers and their relative importance vary between geographical areas; however, non-spatial regression methods are incapable of capturing the spatial variations. This study aimed to explore the use of geographically weighted logistic regression (GWLR to provide insights into the ecoepidemiology of human leptospirosis in Fiji. Methods: We obtained field data from a cross-sectional community survey done in 2013 in the three main islands of Fiji. A blood sample obtained from each participant (aged 1–90 years was tested for anti-Leptospira antibodies and household locations were recorded using GPS receivers. We used GWLR to quantify the spatial variation in the relative importance of five environmental and sociodemographic covariates (cattle density, distance to river, poverty rate, residential setting [urban or rural], and maximum rainfall in the wettest month on leptospirosis transmission in Fiji. We developed two models, one using GWLR and one with standard logistic regression; for each model, the dependent variable was the presence or absence of anti-Leptospira antibodies. GWLR results were compared with results obtained with standard logistic regression, and used to produce a predictive risk map and maps showing the spatial variation in odds ratios (OR for each covariate. Findings: The dataset contained location information for 2046 participants from 1922 households representing 81 communities. The Aikaike information criterion value of the GWLR model was 1935·2 compared with 1254·2 for the standard logistic regression model, indicating that the GWLR model was more efficient. Both models produced similar OR for the covariates, but

  18. Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

    Science.gov (United States)

    Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

    2017-03-01

    Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

  19. Population Structure in the Model Grass Brachypodium distachyon Is Highly Correlated with Flowering Differences across Broad Geographic Areas

    Directory of Open Access Journals (Sweden)

    Ludmila Tyler

    2016-07-01

    Full Text Available The small, annual grass (L. Beauv., a close relative of wheat ( L. and barley ( L., is a powerful model system for cereals and bioenergy grasses. Genome-wide association studies (GWAS of natural variation can elucidate the genetic basis of complex traits but have been so far limited in by the lack of large numbers of well-characterized and sufficiently diverse accessions. Here, we report on genotyping-by-sequencing (GBS of 84 , seven , and three accessions with diverse geographic origins including Albania, Armenia, Georgia, Italy, Spain, and Turkey. Over 90,000 high-quality single-nucleotide polymorphisms (SNPs distributed across the Bd21 reference genome were identified. Our results confirm the hybrid nature of the genome, which appears as a mosaic of -like and -like sequences. Analysis of more than 50,000 SNPs for the accessions revealed three distinct, genetically defined populations. Surprisingly, these genomic profiles are associated with differences in flowering time rather than with broad geographic origin. High levels of differentiation in loci associated with floral development support the differences in flowering phenology between populations. Genome-wide association studies combining genotypic and phenotypic data also suggest the presence of one or more photoperiodism, circadian clock, and vernalization genes in loci associated with flowering time variation within populations. Our characterization elucidates genes underlying population differences, expands the germplasm resources available for , and illustrates the feasibility and limitations of GWAS in this model grass.

  20. Virulence Studies of Different Sequence Types and Geographical Origins of Streptococcus suis Serotype 2 in a Mouse Model of Infection

    Directory of Open Access Journals (Sweden)

    Jean-Philippe Auger

    2016-07-01

    Full Text Available Multilocus sequence typing previously identified three predominant sequence types (STs of Streptococcus suis serotype 2: ST1 strains predominate in Eurasia while North American (NA strains are generally ST25 and ST28. However, ST25/ST28 and ST1 strains have also been isolated in Asia and NA, respectively. Using a well-standardized mouse model of infection, the virulence of strains belonging to different STs and different geographical origins was evaluated. Results demonstrated that although a certain tendency may be observed, S. suis serotype 2 virulence is difficult to predict based on ST and geographical origin alone; strains belonging to the same ST presented important differences of virulence and did not always correlate with origin. The only exception appears to be NA ST28 strains, which were generally less virulent in both systemic and central nervous system (CNS infection models. Persistent and high levels of bacteremia accompanied by elevated CNS inflammation are required to cause meningitis. Although widely used, in vitro tests such as phagocytosis and killing assays require further standardization in order to be used as predictive tests for evaluating virulence of strains. The use of strains other than archetypal strains has increased our knowledge and understanding of the S. suis serotype 2 population dynamics.

  1. Integrating remote sensing, geographic information system and modeling for estimating crop yield

    Science.gov (United States)

    Salazar, Luis Alonso

    This thesis explores various aspects of the use of remote sensing, geographic information system and digital signal processing technologies for broad-scale estimation of crop yield in Kansas. Recent dry and drought years in the Great Plains have emphasized the need for new sources of timely, objective and quantitative information on crop conditions. Crop growth monitoring and yield estimation can provide important information for government agencies, commodity traders and producers in planning harvest, storage, transportation and marketing activities. The sooner this information is available the lower the economic risk translating into greater efficiency and increased return on investments. Weather data is normally used when crop yield is forecasted. Such information, to provide adequate detail for effective predictions, is typically feasible only on small research sites due to expensive and time-consuming collections. In order for crop assessment systems to be economical, more efficient methods for data collection and analysis are necessary. The purpose of this research is to use satellite data which provides 50 times more spatial information about the environment than the weather station network in a short amount of time at a relatively low cost. Specifically, we are going to use Advanced Very High Resolution Radiometer (AVHRR) based vegetation health (VH) indices as proxies for characterization of weather conditions.

  2. Geographical accessibility and spatial coverage modeling of the primary health care network in the Western Province of Rwanda

    Directory of Open Access Journals (Sweden)

    Huerta Munoz Ulises

    2012-09-01

    Full Text Available Abstract Background Primary health care is essential in improving and maintaining the health of populations. It has the potential to accelerate achievement of the Millennium Development Goals and fulfill the “Health for All” doctrine of the Alma-Ata Declaration. Understanding the performance of the health system from a geographic perspective is important for improved health planning and evidence-based policy development. The aims of this study were to measure geographical accessibility, model spatial coverage of the existing primary health facility network, estimate the number of primary health facilities working under capacity and the population underserved in the Western Province of Rwanda. Methods This study uses health facility, population and ancillary data for the Western Province of Rwanda. Three different travel scenarios utilized by the population to attend the nearest primary health facility were defined with a maximum travelling time of 60 minutes: Scenario 1 – walking; Scenario 2 – walking and cycling; and Scenario 3 – walking and public transportation. Considering these scenarios, a raster surface of travel time between primary health facilities and population was developed. To model spatial coverage and estimate the number of primary health facilities working under capacity, the catchment area of each facility was calculated by taking into account population coverage capacity, the population distribution, the terrain topography and the travelling modes through the different land categories. Results Scenario 2 (walking and cycling has the highest degree of geographical accessibility followed by Scenario 3 (walking and public transportation. The lowest level of accessibility can be observed in Scenario 1 (walking. The total population covered differs depending on the type of travel scenario. The existing primary health facility network covers only 26.6% of the population in Scenario 1. In Scenario 2, the use of a bicycle

  3. Sex Differences in Adolescent Depression: Stress Exposure and Reactivity Models

    Science.gov (United States)

    Hankin, Benjamin L.; Mermelstein, Robin; Roesch, Linda

    2007-01-01

    Stress exposure and reactivity models were examined as explanations for why girls exhibit greater levels of depressive symptoms than boys. In a multiwave, longitudinal design, adolescents' depressive symptoms, alcohol usage, and occurrence of stressors were assessed at baseline, 6, and 12 months later (N=538; 54.5% female; ages 13-18, average…

  4. Task-based dermal exposure models for regulatory risk assessment

    NARCIS (Netherlands)

    Warren, N.D.; Marquart, H.; Christopher, Y.; Laitinen, J.; Hemmen, J.J. van

    2006-01-01

    The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of

  5. Population-based nutrikinetic modeling of polyphenol exposure

    NARCIS (Netherlands)

    van Velzen, E.J.J.; Westerhuis, J.A.; Grün, C.H.; Jacobs, D.M.; Eilers, P.H.C.; Mulder, Th.P.; Foltz, M.; Garczarek, U.; Kemperman, R.; Vaughan, E. E.; van Duynhoven, J.P.M.; Smilde, A.K.

    2014-01-01

    The beneficial health effects of fruits and vegetables have been attributed to their polyphenol content. These compounds undergo many bioconversions in the body. Modeling polyphenol exposure of humans upon intake is a prerequisite for understanding the modulating effect of the food matrix and the

  6. Population-based nutrikinetic modelling of phytochemical exposure

    NARCIS (Netherlands)

    Velzen, van E.J.J.; Westerhuis, J.A.; Grün, C.H.; Duynhoven, van J.P.M.; Jacobs, D.M.; Eilers, P.H.C.; Mulder, T.P.; Foltz, M.; Garczarek, U.; Kemperman, R.; Vaughan, E.E.; Smilde, A.K.

    2014-01-01

    The beneficial health effects of fruits and vegetables have been attributed to their polyphenol content. These compounds undergo many bioconversions in the body. Modeling polyphenol exposure of humans upon intake is a prerequisite for understanding the modulating effect of the food matrix and the

  7. Population models for time-varying pesticide exposure

    NARCIS (Netherlands)

    Jager T; Jong FMW de; Traas TP; LER; SEC

    2007-01-01

    A model has recently been developed at RIVM to predict the effects of variable exposure to pesticides of plant and animal populations in surface water. Before a pesticide is placed on the market, the environmental risk of the substance has to be assessed. This risk is estimated by comparing

  8. Parameterization models for pesticide exposure via crop consumption.

    Science.gov (United States)

    Fantke, Peter; Wieland, Peter; Juraske, Ronnie; Shaddick, Gavin; Itoiz, Eva Sevigné; Friedrich, Rainer; Jolliet, Olivier

    2012-12-04

    An approach for estimating human exposure to pesticides via consumption of six important food crops is presented that can be used to extend multimedia models applied in health risk and life cycle impact assessment. We first assessed the variation of model output (pesticide residues per kg applied) as a function of model input variables (substance, crop, and environmental properties) including their possible correlations using matrix algebra. We identified five key parameters responsible for between 80% and 93% of the variation in pesticide residues, namely time between substance application and crop harvest, degradation half-lives in crops and on crop surfaces, overall residence times in soil, and substance molecular weight. Partition coefficients also play an important role for fruit trees and tomato (Kow), potato (Koc), and lettuce (Kaw, Kow). Focusing on these parameters, we develop crop-specific models by parametrizing a complex fate and exposure assessment framework. The parametric models thereby reflect the framework's physical and chemical mechanisms and predict pesticide residues in harvest using linear combinations of crop, crop surface, and soil compartments. Parametric model results correspond well with results from the complex framework for 1540 substance-crop combinations with total deviations between a factor 4 (potato) and a factor 66 (lettuce). Predicted residues also correspond well with experimental data previously used to evaluate the complex framework. Pesticide mass in harvest can finally be combined with reduction factors accounting for food processing to estimate human exposure from crop consumption. All parametric models can be easily implemented into existing assessment frameworks.

  9. Geographic variation in Chinese children' forced vital capacity and its association with long-term exposure to local PM10: a national cross-sectional study.

    Science.gov (United States)

    Wang, Hai-Jun; Li, Qin; Guo, Yuming; Song, Jie-Yun; Wang, Zhiqiang; Ma, Jun

    2017-10-01

    The purpose of this study was to estimate the association between Chinese children's forced vital capacity (FVC) and particulate matter with aerodynamic diameter ≤10 μm (PM 10 ). The FVC data of 71,763 children aged 7 to 18 was collected from 2010 Chinese National Survey on Students' Construction and Health (CNSSCH). The local annual average concentration of PM 10 , relative humidity, ambient temperature, and other air pollutant data of 30 cities was collected from China Meteorological Administration and Ministry of Environment Protection of China. Then, we used generalized additive model (GAM) to estimate the association between children's FVC and PM 10 . The obvious geographic variation in FVC was found in children of 30 Chinese cities ranging from 1647 ml in Xining to 2571 ml in Beijing. The annual average concentration of PM 10 was also different, ranging from 40 μg/m 3 in Haikou to 155 μg/m 3 in Lanzhou. After adjusted individual characteristics, socioeconomic conditions, ambient temperature, relative humidity, and other air pollutants (e.g., NO 2 and SO 2 ) in the generalized additive model, we found that the increase of PM 10 was associated with decrease of FVC in Chinese children. A 10-μg/m 3 increase of PM 10 was associated with 1.33-ml decrease in FVC (95% confidence interval: -2.18 to -0.47). We also found a larger effect estimate of PM 10 on FVC in boys than that in girls. Consistent associations were found in both physically inactive and active children. The increase of PM 10 was associated with decrease of children's FVC. We should develop proper public health policy to protect children's respiratory health during growth and development in polluted areas.

  10. Exposure to traffic pollution: comparison between measurements and a model.

    Science.gov (United States)

    Alili, F; Momas, I; Callais, F; Le Moullec, Y; Sacre, C; Chiron, M; Flori, J P

    2001-01-01

    French researchers from the Building Scientific and Technical Center have produced a traffic-exposure index. To achieve this, they used an air pollution dispersion model that enabled them to calculate automobile pollutant concentrations in front of subjects' residences and places of work. Researchers used this model, which was tested at 27 Paris canyon street sites, and compared nitrogen oxides measurements obtained with passive samplers during a 6-wk period and calculations derived from the model. There was a highly significant correlation (r = .83) between the 2 series of values; their mean concentrations were not significantly different. The results suggested that the aforementioned model could be a useful epidemiological tool for the classification of city dwellers by present-or even cumulative exposure to automobile air pollution.

  11. Improved Predictions of the Geographic Distribution of Invasive Plants Using Climatic Niche Models

    Science.gov (United States)

    Ramírez-Albores, Jorge E.; Bustamante, Ramiro O.

    2016-01-01

    Climatic niche models for invasive plants are usually constructed with occurrence records taken from literature and collections. Because these data neither discriminate among life-cycle stages of plants (adult or juvenile) nor the origin of individuals (naturally established or man-planted), the resulting models may mispredict the distribution ranges of these species. We propose that more accurate predictions could be obtained by modelling climatic niches with data of naturally established individuals, particularly with occurrence records of juvenile plants because this would restrict the predictions of models to those sites where climatic conditions allow the recruitment of the species. To test this proposal, we focused on the Peruvian peppertree (Schinus molle), a South American species that has largely invaded Mexico. Three climatic niche models were constructed for this species using high-resolution dataset gathered in the field. The first model included all occurrence records, irrespective of the life-cycle stage or origin of peppertrees (generalized niche model). The second model only included occurrence records of naturally established mature individuals (adult niche model), while the third model was constructed with occurrence records of naturally established juvenile plants (regeneration niche model). When models were compared, the generalized climatic niche model predicted the presence of peppertrees in sites located farther beyond the climatic thresholds that naturally established individuals can tolerate, suggesting that human activities influence the distribution of this invasive species. The adult and regeneration climatic niche models concurred in their predictions about the distribution of peppertrees, suggesting that naturally established adult trees only occur in sites where climatic conditions allow the recruitment of juvenile stages. These results support the proposal that climatic niches of invasive plants should be modelled with data of

  12. Spatial Random Effects Survival Models to Assess Geographical Inequalities in Dengue Fever Using Bayesian Approach: a Case Study

    Science.gov (United States)

    Astuti Thamrin, Sri; Taufik, Irfan

    2018-03-01

    Dengue haemorrhagic fever (DHF) is an infectious disease caused by dengue virus. The increasing number of people with DHF disease correlates with the neighbourhood, for example sub-districts, and the characteristics of the sub-districts are formed from individuals who are domiciled in the sub-districts. Data containing individuals and sub-districts is a hierarchical data structure, called multilevel analysis. Frequently encountered response variable of the data is the time until an event occurs. Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in DHF survival. Using a case study approach, we report on the implications of using multilevel with spatial survival models to study geographical inequalities in all cause survival.

  13. Using Geographic Information System-based Ecologic Niche Models to Forecast the Risk of Hantavirus Infection in Shandong Province, China

    Science.gov (United States)

    Wei, Lan; Qian, Quan; Wang, Zhi-Qiang; Glass, Gregory E.; Song, Shao-Xia; Zhang, Wen-Yi; Li, Xiu-Jun; Yang, Hong; Wang, Xian-Jun; Fang, Li-Qun; Cao, Wu-Chun

    2011-01-01

    Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in Shandong Province, China. In this study, we combined ecologic niche modeling with geographic information systems (GIS) and remote sensing techniques to identify the risk factors and affected areas of hantavirus infections in rodent hosts. Land cover and elevation were found to be closely associated with the presence of hantavirus-infected rodent hosts. The averaged area under the receiver operating characteristic curve was 0.864, implying good performance. The predicted risk maps based on the model were validated both by the hantavirus-infected rodents' distribution and HFRS human case localities with a good fit. These findings have the applications for targeting control and prevention efforts. PMID:21363991

  14. A dermal model for spray painters, part I : subjective exposure modelling of spray paint deposition

    NARCIS (Netherlands)

    Brouwer, D.H.; Semple, S.; Marquart, J.; Cherrie, J.W.

    2001-01-01

    The discriminative power of existing dermal exposure models is limited. Most models only allow occupational hygienists to rank workers between and within workplaces according to broad bands of dermal exposure. No allowance is made for the work practices of different individuals. In this study a

  15. Predictive models and spatial variations of vital capacity in healthy people from 6 to 84 years old in China based on geographical factors.

    Science.gov (United States)

    He, Jinwei; Ge, Miao; Wang, Congxia; Jiang, Naigui; Zhang, Mingxin; Yun, Pujun

    2014-07-01

    The aim of this study was to provide a scientific basic for a unified standard of the reference value of vital capacity (VC) of healthy subjects from 6 and 84 years old in China. The normal reference value of VC was correlated to seven geographical factors, including altitude (X1), annual duration of sunshine (X2), annual mean air temperature (X3), annual mean relative humidity (X4), annual precipitation amount (X5), annual air temperature range (X6) and annual mean wind speed (X7). Predictive models were established by five different linear and nonlinear methods. The best models were selected by t-test. The geographical distribution map of VC in different age groups can be interpolated by Kriging's method using ArcGIS software. It was found that the correlation of VC and geographical factors in China was quite significant, especially for both males and females aged from 6 to 45. The best models were built for different age groups. The geographical distribution map shows the spatial variations of VC in China precisely. The VC of healthy subjects can be simulated by the best model or acquired from the geographical distribution map provided the geographical factors for that city or county of China are known.

  16. Factors affecting CO_2 emissions in China’s agriculture sector: Evidence from geographically weighted regression model

    International Nuclear Information System (INIS)

    Xu, Bin; Lin, Boqiang

    2017-01-01

    China is currently the world's largest emitter of carbon dioxide. Considered as a large agricultural country, carbon emission in China’s agriculture sector keeps on growing rapidly. It is, therefore, of great importance to investigate the driving forces of carbon dioxide emissions in this sector. The traditional regression estimation can only get “average” and “global” parameter estimates; it excludes the “local” parameter estimates which vary across space in some spatial systems. Geographically weighted regression embeds the latitude and longitude of the sample data into the regression parameters, and uses the local weighted least squares method to estimate the parameters point–by–point. To reveal the nonstationary spatial effects of driving forces, geographically weighted regression model is employed in this paper. The results show that economic growth is positively correlated with emissions, with the impact in the western region being less than that in the central and eastern regions. Urbanization is positively related to emissions but produces opposite effects pattern. Energy intensity is also correlated with emissions, with a decreasing trend from the eastern region to the central and western regions. Therefore, policymakers should take full account of the spatial nonstationarity of driving forces in designing emission reduction policies. - Highlights: • We explore the driving forces of CO_2 emissions in the agriculture sector. • Urbanization is positively related to emissions but produces opposite effect pattern. • The effect of energy intensity declines from the eastern region to western region.

  17. Geographical Tatoos

    Directory of Open Access Journals (Sweden)

    Valéria Cazetta

    2014-08-01

    Full Text Available The article deals with maps tattooed on bodies. My interest in studying the corporeality is inserted in a broader project entitled Geographies and (in Bodies. There is several published research on tattoos, but none in particular about tattooed maps. However some of these works interested me because they present important discussions in contemporary about body modification that helped me locate the body modifications most within the culture than on the nature. At this time, I looked at pictures of geographical tattoos available in several sites of the internet.

  18. Entrepreneural adaptation processes. An industry-geographic working model, illustrated by the example of Saarbergwerke AG

    International Nuclear Information System (INIS)

    Doerrenbaecher, P.

    1992-01-01

    The study has two goals: Solutions based in industrial geography and chronogeography are to be synthesized in order to develop a model of entrepreneurial adaptation processes. On the basis of this model, the development of Saarbergwerke AG in the first phase of the coal crisis (1957-1962) is reconstructed as an entrepreneurial adaptation process. (orig.) [de

  19. An analytical model for the performance of geographical multi-hop broadcast

    NARCIS (Netherlands)

    Klein Wolterink, W.; Heijenk, G.; Berg, J.L. van den

    2012-01-01

    In this paper we present an analytical model accurately describing the behaviour of a multi-hop broadcast protocol. Our model covers the scenario in which a message is forwarded over a straight road and inter-node distances are distributed exponentially. Intermediate forwarders draw a small random

  20. BETR global - A geographically-explicit global-scale multimedia contaminant fate model

    International Nuclear Information System (INIS)

    MacLeod, Matthew; Waldow, Harald von; Tay, Pascal; Armitage, James M.; Woehrnschimmel, Henry; Riley, William J.; McKone, Thomas E.; Hungerbuhler, Konrad

    2011-01-01

    We present two new software implementations of the BETR Global multimedia contaminant fate model. The model uses steady-state or non-steady-state mass-balance calculations to describe the fate and transport of persistent organic pollutants using a desktop computer. The global environment is described using a database of long-term average monthly conditions on a 15 o x 15 o grid. We demonstrate BETR Global by modeling the global sources, transport, and removal of decamethylcyclopentasiloxane (D5). - Two new software implementations of the Berkeley-Trent Global Contaminant Fate Model are available. The new model software is illustrated using a case study of the global fate of decamethylcyclopentasiloxane (D5).

  1. Application of Geographic Information System (GIS) to Model the Hydrocarbon Migration: Case Study from North-East Malay Basin, Malaysia

    Science.gov (United States)

    Rudini; Nasir Matori, Abd; Talib, Jasmi Ab; Balogun, Abdul-Lateef

    2018-03-01

    The purpose of this study is to model the migration of hydrocarbon using Geographic Information System (GIS). Understanding hydrocarbon migration is important since it can mean the difference between success and failure in oil and gas exploration project. The hydrocarbon migration modeling using geophysical method is still not accurate due to the limitations of available data. In recent years, GIS has emerged as a powerful tool for subsurface mapping and analysis. Recent studies have been carried out about the abilities of GIS to model hydrocarbon migration. Recent advances in GIS support the establishment and monitoring of prediction hydrocarbon migration. The concept, model, and calculation are based on the current geological situation. The spatial data of hydrocarbon reservoirs is determined by its geometry of lithology and geophysical attributes. Top of Group E horizon of north-east Malay basin was selected as the study area due to the occurrence of hydrocarbon migration. Spatial data and attributes data such as seismic data, wells log data and lithology were acquired and processed. Digital Elevation Model (DEM) was constructed from the selected horizon as a result of seismic interpretation using the Petrel software. Furthermore, DEM was processed in ArcGIS as a base map to shown hydrocarbon migration in north-east Malay Basin. Finally, all the data layers were overlaid to produce a map of hydrocarbon migration. A good data was imported to verify the model is correct.

  2. Application of Geographic Information System (GIS to Model the Hydrocarbon Migration: Case Study from North-East Malay Basin, Malaysia

    Directory of Open Access Journals (Sweden)

    Rudini

    2018-01-01

    Full Text Available The purpose of this study is to model the migration of hydrocarbon using Geographic Information System (GIS. Understanding hydrocarbon migration is important since it can mean the difference between success and failure in oil and gas exploration project. The hydrocarbon migration modeling using geophysical method is still not accurate due to the limitations of available data. In recent years, GIS has emerged as a powerful tool for subsurface mapping and analysis. Recent studies have been carried out about the abilities of GIS to model hydrocarbon migration. Recent advances in GIS support the establishment and monitoring of prediction hydrocarbon migration. The concept, model, and calculation are based on the current geological situation. The spatial data of hydrocarbon reservoirs is determined by its geometry of lithology and geophysical attributes. Top of Group E horizon of north-east Malay basin was selected as the study area due to the occurrence of hydrocarbon migration. Spatial data and attributes data such as seismic data, wells log data and lithology were acquired and processed. Digital Elevation Model (DEM was constructed from the selected horizon as a result of seismic interpretation using the Petrel software. Furthermore, DEM was processed in ArcGIS as a base map to shown hydrocarbon migration in north-east Malay Basin. Finally, all the data layers were overlaid to produce a map of hydrocarbon migration. A good data was imported to verify the model is correct.

  3. SHEDS-HT: an integrated probabilistic exposure model for prioritizing exposures to chemicals with near-field and dietary sources.

    Science.gov (United States)

    Isaacs, Kristin K; Glen, W Graham; Egeghy, Peter; Goldsmith, Michael-Rock; Smith, Luther; Vallero, Daniel; Brooks, Raina; Grulke, Christopher M; Özkaynak, Halûk

    2014-11-04

    United States Environmental Protection Agency (USEPA) researchers are developing a strategy for high-throughput (HT) exposure-based prioritization of chemicals under the ExpoCast program. These novel modeling approaches for evaluating chemicals based on their potential for biologically relevant human exposures will inform toxicity testing and prioritization for chemical risk assessment. Based on probabilistic methods and algorithms developed for The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals (SHEDS-MM), a new mechanistic modeling approach has been developed to accommodate high-throughput (HT) assessment of exposure potential. In this SHEDS-HT model, the residential and dietary modules of SHEDS-MM have been operationally modified to reduce the user burden, input data demands, and run times of the higher-tier model, while maintaining critical features and inputs that influence exposure. The model has been implemented in R; the modeling framework links chemicals to consumer product categories or food groups (and thus exposure scenarios) to predict HT exposures and intake doses. Initially, SHEDS-HT has been applied to 2507 organic chemicals associated with consumer products and agricultural pesticides. These evaluations employ data from recent USEPA efforts to characterize usage (prevalence, frequency, and magnitude), chemical composition, and exposure scenarios for a wide range of consumer products. In modeling indirect exposures from near-field sources, SHEDS-HT employs a fugacity-based module to estimate concentrations in indoor environmental media. The concentration estimates, along with relevant exposure factors and human activity data, are then used by the model to rapidly generate probabilistic population distributions of near-field indirect exposures via dermal, nondietary ingestion, and inhalation pathways. Pathway-specific estimates of near-field direct exposures from consumer products are also modeled

  4. BETR Global - A geographically explicit global-scale multimedia contaminant fate model

    Energy Technology Data Exchange (ETDEWEB)

    Macleod, M.; Waldow, H. von; Tay, P.; Armitage, J. M.; Wohrnschimmel, H.; Riley, W.; McKone, T. E.; Hungerbuhler, K.

    2011-04-01

    We present two new software implementations of the BETR Global multimedia contaminant fate model. The model uses steady-state or non-steady-state mass-balance calculations to describe the fate and transport of persistent organic pollutants using a desktop computer. The global environment is described using a database of long-term average monthly conditions on a 15{sup o} x 15{sup o} grid. We demonstrate BETR Global by modeling the global sources, transport, and removal of decamethylcyclopentasiloxane (D5).

  5. Inhalation Exposure Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    M. Wasiolek

    2006-06-05

    This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This

  6. Inhalation Exposure Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    M. Wasiolek

    2006-01-01

    This analysis is one of the technical reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), referred to in this report as the biosphere model. ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. ''Inhalation Exposure Input Parameters for the Biosphere Model'' is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the biosphere model is presented in Figure 1-1 (based on BSC 2006 [DIRS 176938]). This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and how this analysis report contributes to biosphere modeling. This analysis report defines and justifies values of atmospheric mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of the biosphere model to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception. This report is concerned primarily with the

  7. Extending the formal model of a spatial data infrastructure to include volunteered geographical information

    CSIR Research Space (South Africa)

    Cooper, Antony K

    2011-07-01

    Full Text Available , Information and Computational Viewpoints of the Reference Model for Open Distributed Processing (RM-ODP). We identified six stakeholders: Policy Maker, Producer, Provider, Broker, Value-added Reseller and End User. The Internet has spawned the development...

  8. [Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

    Science.gov (United States)

    Zhang, Ling Yu; Liu, Zhao Gang

    2017-12-01

    Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

  9. Modelling hurricane exposure and wind speed on a mesoclimate scale: a case study from Cusuco NP, Honduras.

    Science.gov (United States)

    Batke, Sven P; Jocque, Merlijn; Kelly, Daniel L

    2014-01-01

    High energy weather events are often expected to play a substantial role in biotic community dynamics and large scale diversity patterns but their contribution is hard to prove. Currently, observations are limited to the documentation of accidental records after the passing of such events. A more comprehensive approach is synthesising weather events in a location over a long time period, ideally at a high spatial resolution and on a large geographic scale. We provide a detailed overview on how to generate hurricane exposure data at a meso-climate level for a specific region. As a case study we modelled landscape hurricane exposure in Cusuco National Park (CNP), Honduras with a resolution of 50 m×50 m patches. We calculated actual hurricane exposure vulnerability site scores (EVVS) through the combination of a wind pressure model, an exposure model that can incorporate simple wind dynamics within a 3-dimensional landscape and the integration of historical hurricanes data. The EVSS was calculated as a weighted function of sites exposure, hurricane frequency and maximum wind velocity. Eleven hurricanes were found to have affected CNP between 1995 and 2010. The highest EVSS's were predicted to be on South and South-East facing sites of the park. Ground validation demonstrated that the South-solution (i.e. the South wind inflow direction) explained most of the observed tree damage (90% of the observed tree damage in the field). Incorporating historical data to the model to calculate actual hurricane exposure values, instead of potential exposure values, increased the model fit by 50%.

  10. Human Exposure Model (HEM): A modular, web-based application to characterize near-field chemical exposures and releases

    Science.gov (United States)

    The U.S. EPA’s Chemical Safety and Sustainability research program is developing the Human Exposure Model (HEM) to assess near-field exposures to chemicals that occur in various populations over the entire life cycle of a consumer product. The model will be implemented as a...

  11. Assessing the status and trend of bat populations across broad geographic regions with dynamic distribution models

    Science.gov (United States)

    Rodhouse, Thomas J.; Ormsbee, Patricia C.; Irvine, Kathryn M.; Vierling, Lee A.; Szewczak, Joseph M.; Vierling, Kerri T.

    2012-01-01

    Bats face unprecedented threats from habitat loss, climate change, disease, and wind power development, and populations of many species are in decline. A better ability to quantify bat population status and trend is urgently needed in order to develop effective conservation strategies. We used a Bayesian autoregressive approach to develop dynamic distribution models for Myotis lucifugus, the little brown bat, across a large portion of northwestern USA, using a four-year detection history matrix obtained from a regional monitoring program. This widespread and abundant species has experienced precipitous local population declines in northeastern USA resulting from the novel disease white-nose syndrome, and is facing likely range-wide declines. Our models were temporally dynamic and accounted for imperfect detection. Drawing on species–energy theory, we included measures of net primary productivity (NPP) and forest cover in models, predicting that M. lucifugus occurrence probabilities would covary positively along those gradients.

  12. Modelling the ecological vulnerability to forest fires in mediterranean ecosystems using geographic information technologies.

    Science.gov (United States)

    Duguy, Beatriz; Alloza, José Antonio; Baeza, M Jaime; De la Riva, Juan; Echeverría, Maite; Ibarra, Paloma; Llovet, Juan; Cabello, Fernando Pérez; Rovira, Pere; Vallejo, Ramon V

    2012-12-01

    Forest fires represent a major driver of change at the ecosystem and landscape levels in the Mediterranean region. Environmental features and vegetation are key factors to estimate the ecological vulnerability to fire; defined as the degree to which an ecosystem is susceptible to, and unable to cope with, adverse effects of fire (provided a fire occurs). Given the predicted climatic changes for the region, it is urgent to validate spatially explicit tools for assessing this vulnerability in order to support the design of new fire prevention and restoration strategies. This work presents an innovative GIS-based modelling approach to evaluate the ecological vulnerability to fire of an ecosystem, considering its main components (soil and vegetation) and different time scales. The evaluation was structured in three stages: short-term (focussed on soil degradation risk), medium-term (focussed on changes in vegetation), and coupling of the short- and medium-term vulnerabilities. The model was implemented in two regions: Aragón (inland North-eastern Spain) and Valencia (eastern Spain). Maps of the ecological vulnerability to fire were produced at a regional scale. We partially validated the model in a study site combining two complementary approaches that focused on testing the adequacy of model's predictions in three ecosystems, all very common in fire-prone landscapes of eastern Spain: two shrublands and a pine forest. Both approaches were based on the comparison of model's predictions with values of NDVI (Normalized Difference Vegetation Index), which is considered a good proxy for green biomass. Both methods showed that the model's performance is satisfactory when applied to the three selected vegetation types.

  13. Flood Hazard Mapping by Using Geographic Information System and Hydraulic Model: Mert River, Samsun, Turkey

    Directory of Open Access Journals (Sweden)

    Vahdettin Demir

    2016-01-01

    Full Text Available In this study, flood hazard maps were prepared for the Mert River Basin, Samsun, Turkey, by using GIS and Hydrologic Engineering Centers River Analysis System (HEC-RAS. In this river basin, human life losses and a significant amount of property damages were experienced in 2012 flood. The preparation of flood risk maps employed in the study includes the following steps: (1 digitization of topographical data and preparation of digital elevation model using ArcGIS, (2 simulation of flood lows of different return periods using a hydraulic model (HEC-RAS, and (3 preparation of flood risk maps by integrating the results of (1 and (2.

  14. Vertical Integration of Geographic Information Sciences: A Recruitment Model for GIS Education

    Science.gov (United States)

    Yu, Jaehyung; Huynh, Niem Tu; McGehee, Thomas Lee

    2011-01-01

    An innovative vertical integration model for recruiting to GIS education was introduced and tested following four driving forces: curriculum development, GIS presentations, institutional collaboration, and faculty training. Curriculum development was a useful approach to recruitment, student credit hour generation, and retention-rate improvement.…

  15. Research-Based Program Development: Refining the Service Model for a Geographic Alliance

    Science.gov (United States)

    Rutherford, David J.; Lovorn, Carley

    2018-01-01

    Research conducted in 2013 identified the perceptions that K-12 teachers and administrators hold with respect to: (1) the perceived needs in education, (2) the professional audiences that are most important to reach, and (3) the service models that are most effective. The specific purpose of the research was to refine and improve the services that…

  16. Extending Geographic Weights of Evidence Models for Use in Location Based Services

    Science.gov (United States)

    Sonwalkar, Mukul Dinkar

    2012-01-01

    This dissertation addresses the use and modeling of spatio-temporal data for the purposes of providing applications for location based services. One of the major issues in dealing with spatio-temporal data for location based services is the availability and sparseness of such data. Other than the hardware costs associated with collecting movement…

  17. To assess and control global change in agriculture through ecosystem models integrated into geographic information systems

    International Nuclear Information System (INIS)

    Ponti, L.; Iannetta, M.; Gutierrez, A.P.

    2015-01-01

    The transfer of ENEA PBDM (physiologically based demographic models) GIS technology, represents an opportunity to address global change in agriculture on an ecological basis in a local context, be able to provide European governmental agencies the necessary scientific basis for developing effective policies for adaptation to global change, including climate change [it

  18. Econometric model for age- and population-dependent radiation exposures

    International Nuclear Information System (INIS)

    Sandquist, G.M.; Slaughter, D.M.; Rogers, V.C.

    1991-01-01

    The economic impact associated with ionizing radiation exposures in a given human population depends on numerous factors including the individual's mean economic status as a function age, the age distribution of the population, the future life expectancy at each age, and the latency period for the occurrence of radiation-induced health effects. A simple mathematical model has been developed that provides an analytical methodology for estimating the societal econometrics associated with radiation effects are to be assessed and compared for economic evaluation

  19. Modelling of aircrew radiation exposure during solar particle events

    Science.gov (United States)

    Al Anid, Hani Khaled

    show a very different response during anisotropic events, leading to variations in aircrew radiation doses that may be significant for dose assessment. To estimate the additional exposure due to solar flares, a model was developed using a Monte-Carlo radiation transport code, MCNPX. The model transports an extrapolated particle spectrum based on satellite measurements through the atmosphere using the MCNPX analysis. This code produces the estimated flux at a specific altitude where radiation dose conversion coefficients are applied to convert the particle flux into effective and ambient dose-equivalent rates. A cut-off rigidity model accounts for the shielding effects of the Earth's magnetic field. Comparisons were made between the model predictions and actual flight measurements taken with various types of instruments used to measure the mixed radiation field during Ground Level Enhancements 60 and 65. An anisotropy analysis that uses neutron monitor responses and the pitch angle distribution of energetic solar particles was used to identify particle anisotropy for a solar event in December 2006. In anticipation of future commercial use, a computer code has been developed to implement the radiation dose assessment model for routine analysis. Keywords: Radiation Dosimetry, Radiation Protection, Space Physics.

  20. A Unifying Model for the Analysis of Phenotypic, Genetic and Geographic Data

    DEFF Research Database (Denmark)

    Guillot, Gilles; Rena, Sabrina; Ledevin, Ronan

    2012-01-01

    Recognition of evolutionary units (species, populations) requires integrating several kinds of data such as genetic or phenotypic markers or spatial information, in order to get a comprehensive view concerning the dierentiation of the units. We propose a statistical model with a double original...... advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography; and (ii) it allows one to analyze genetic and phenotypic data within a unied model and inference framework, thus...... an intricate case of inter- and intra-species dierentiation based on an original data-set of georeferenced genetic and morphometric markers obtained on Myodes voles from Sweden. A computer program is made available as an extension of the R package Geneland....

  1. Water quality control in Third River Reservoir (Argentina using geographical information systems and linear regression models

    Directory of Open Access Journals (Sweden)

    Claudia Ledesma

    2013-08-01

    Full Text Available Water quality is traditionally monitored and evaluated based upon field data collected at limited locations. The storage capacity of reservoirs is reduced by deposits of suspended matter. The major factors affecting surface water quality are suspended sediments, chlorophyll and nutrients. Modeling and monitoring the biogeochemical status of reservoirs can be done through data from remote sensors. Since the improvement of sensors’ spatial and spectral resolutions, satellites have been used to monitor the interior areas of bodies of water. Water quality parameters, such as chlorophyll-a concentration and secchi disk depth, were found to have a high correlation with transformed spectral variables derived from bands 1, 2, 3 and 4 of LANDSAT 5TM satellite. We created models of estimated responses in regard to values of chlorophyll-a. To do so, we used population models of single and multiple linear regression, whose parameters are associated with the reflectance data of bands 2 and 4 of the sub-image of the satellite, as well as the data of chlorophyll-a obtained in 25 selected stations. According to the physico-chemical analyzes performed, the characteristics of the water in the reservoir of Rio Tercero, correspond to somewhat hard freshwater with calcium bicarbonate. The water was classified as usable as a source of plant treatment, excellent for irrigation because of its low salinity and low residual sodium carbonate content, but unsuitable for animal consumption because of its low salt content.

  2. Integration of a Hydrological Model within a Geographical Information System: Application to a Forest Watershed

    Directory of Open Access Journals (Sweden)

    Dimitris Fotakis

    2014-03-01

    Full Text Available Watershed simulation software used for operational purposes must possess both dependability of results and flexibility in parameter selection and testing. The UBC watershed model (UBCWM contains a wide spectrum of parameters expressing meteorological, geological, as well as ecological watershed characteristics. The hydrological model was coupled to the MapInfo GIS and the software created was named Watershed Mapper (WM. WM is endowed with several features permitting operational utilization. These include input data and basin geometry visualization, land use/cover and soil simulation, exporting of statistical results and thematic maps and interactive variation of disputed parameters. For the application of WM two hypothetical scenarios of forest fires were examined in a study watershed. Four major rainfall events were selected from 12-year daily precipitation data and the corresponding peak flows were estimated for the base line data and hypothetical scenarios. A significant increase was observed as an impact of forest fires on peak flows. Due to its flexibility the combined tool described herein may be utilized in modeling long-term hydrological changes in the context of unsteady hydrological analyses.

  3. Inferring the past and present connectivity across the range of a North American leaf beetle: combining ecological niche modeling and a geographically explicit model of coalescence.

    Science.gov (United States)

    Dellicour, Simon; Fearnley, Shannon; Lombal, Anicée; Heidl, Sarah; Dahlhoff, Elizabeth P; Rank, Nathan E; Mardulyn, Patrick

    2014-08-01

    The leaf beetle Chrysomela aeneicollis occurs across Western North America, either at high elevation or in small, isolated populations along the coast, and thus has a highly fragmented distribution. DNA sequence data (three loci) were collected from five regions across the species range. Population connectivity was examined using traditional ecological niche modeling, which suggested that gene flow could occur among regions now and in the past. We developed geographically explicit coalescence models of sequence evolution that incorporated a two-dimensional representation of the hypothesized ranges suggested by the niche-modeling estimates. We simulated sequence data according to these models and compared them to observed sequences to identify most probable scenarios regarding the migration history of C. aeneicollis. Our results disagreed with initial niche-modeling estimates by clearly rejecting recent connectivity among regions, and were instead most consistent with a long period of range fragmentation, extending well beyond the last glacial maximum. This application of geographically explicit models of coalescence has highlighted some limitations of the use of climatic variables for predicting the present and past range of a species and has explained aspects of the Pleistocene evolutionary history of a cold-adapted organism in Western North America. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

  4. Equality in Maternal and Newborn Health: Modelling Geographic Disparities in Utilisation of Care in Five East African Countries.

    Directory of Open Access Journals (Sweden)

    Corrine W Ruktanonchai

    Full Text Available Geographic accessibility to health facilities represents a fundamental barrier to utilisation of maternal and newborn health (MNH services, driving historically hidden spatial pockets of localized inequalities. Here, we examine utilisation of MNH care as an emergent property of accessibility, highlighting high-resolution spatial heterogeneity and sub-national inequalities in receiving care before, during, and after delivery throughout five East African countries.We calculated a geographic inaccessibility score to the nearest health facility at 300 x 300 m using a dataset of 9,314 facilities throughout Burundi, Kenya, Rwanda, Tanzania and Uganda. Using Demographic and Health Surveys data, we utilised hierarchical mixed effects logistic regression to examine the odds of: 1 skilled birth attendance, 2 receiving 4+ antenatal care visits at time of delivery, and 3 receiving a postnatal health check-up within 48 hours of delivery. We applied model results onto the accessibility surface to visualise the probabilities of obtaining MNH care at both high-resolution and sub-national levels after adjusting for live births in 2015.Across all outcomes, decreasing wealth and education levels were associated with lower odds of obtaining MNH care. Increasing geographic inaccessibility scores were associated with the strongest effect in lowering odds of obtaining care observed across outcomes, with the widest disparities observed among skilled birth attendance. Specifically, for each increase in the inaccessibility score to the nearest health facility, the odds of having skilled birth attendance at delivery was reduced by over 75% (0.24; CI: 0.19-0.3, while the odds of receiving antenatal care decreased by nearly 25% (0.74; CI: 0.61-0.89 and 40% for obtaining postnatal care (0.58; CI: 0.45-0.75.Overall, these results suggest decreasing accessibility to the nearest health facility significantly deterred utilisation of all maternal health care services. These

  5. Equality in Maternal and Newborn Health: Modelling Geographic Disparities in Utilisation of Care in Five East African Countries.

    Science.gov (United States)

    Ruktanonchai, Corrine W; Ruktanonchai, Nick W; Nove, Andrea; Lopes, Sofia; Pezzulo, Carla; Bosco, Claudio; Alegana, Victor A; Burgert, Clara R; Ayiko, Rogers; Charles, Andrew Sek; Lambert, Nkurunziza; Msechu, Esther; Kathini, Esther; Matthews, Zoë; Tatem, Andrew J

    2016-01-01

    Geographic accessibility to health facilities represents a fundamental barrier to utilisation of maternal and newborn health (MNH) services, driving historically hidden spatial pockets of localized inequalities. Here, we examine utilisation of MNH care as an emergent property of accessibility, highlighting high-resolution spatial heterogeneity and sub-national inequalities in receiving care before, during, and after delivery throughout five East African countries. We calculated a geographic inaccessibility score to the nearest health facility at 300 x 300 m using a dataset of 9,314 facilities throughout Burundi, Kenya, Rwanda, Tanzania and Uganda. Using Demographic and Health Surveys data, we utilised hierarchical mixed effects logistic regression to examine the odds of: 1) skilled birth attendance, 2) receiving 4+ antenatal care visits at time of delivery, and 3) receiving a postnatal health check-up within 48 hours of delivery. We applied model results onto the accessibility surface to visualise the probabilities of obtaining MNH care at both high-resolution and sub-national levels after adjusting for live births in 2015. Across all outcomes, decreasing wealth and education levels were associated with lower odds of obtaining MNH care. Increasing geographic inaccessibility scores were associated with the strongest effect in lowering odds of obtaining care observed across outcomes, with the widest disparities observed among skilled birth attendance. Specifically, for each increase in the inaccessibility score to the nearest health facility, the odds of having skilled birth attendance at delivery was reduced by over 75% (0.24; CI: 0.19-0.3), while the odds of receiving antenatal care decreased by nearly 25% (0.74; CI: 0.61-0.89) and 40% for obtaining postnatal care (0.58; CI: 0.45-0.75). Overall, these results suggest decreasing accessibility to the nearest health facility significantly deterred utilisation of all maternal health care services. These results

  6. Assess and control global change in agriculture through ecosystem models integrated in geographic information systems

    International Nuclear Information System (INIS)

    Ponti, Luigi; Gutierrez, Andrew Paul; Iannetta, Massimo

    2015-01-01

    ENEA has created, in collaboration with the University of California at Berkeley, the Global Change Biology project that, for the first time, has made available in Europe a technology that can be It used to interpret and effectively manage change Global agriculture. The aim of the project was to provide tools to summarize, manage and analyze data Ecological on the effects of global change in agricultural systems, using traditional Mediterranean crops (Eg. Vineyards and olive) as model systems (http: // cordis.europa.eu/project/rcn/89728_en.html). [it

  7. Remote sensing, geographical information systems, and spatial modeling for analyzing public transit services

    Science.gov (United States)

    Wu, Changshan

    Public transit service is a promising transportation mode because of its potential to address urban sustainability. Current ridership of public transit, however, is very low in most urban regions, particularly those in the United States. This woeful transit ridership can be attributed to many factors, among which poor service quality is key. Given this, there is a need for transit planning and analysis to improve service quality. Traditionally, spatially aggregate data are utilized in transit analysis and planning. Examples include data associated with the census, zip codes, states, etc. Few studies, however, address the influences of spatially aggregate data on transit planning results. In this research, previous studies in transit planning that use spatially aggregate data are reviewed. Next, problems associated with the utilization of aggregate data, the so-called modifiable areal unit problem (MAUP), are detailed and the need for fine resolution data to support public transit planning is argued. Fine resolution data is generated using intelligent interpolation techniques with the help of remote sensing imagery. In particular, impervious surface fraction, an important socio-economic indicator, is estimated through a fully constrained linear spectral mixture model using Landsat Enhanced Thematic Mapper Plus (ETM+) data within the metropolitan area of Columbus, Ohio in the United States. Four endmembers, low albedo, high albedo, vegetation, and soil are selected to model heterogeneous urban land cover. Impervious surface fraction is estimated by analyzing low and high albedo endmembers. With the derived impervious surface fraction, three spatial interpolation methods, spatial regression, dasymetric mapping, and cokriging, are developed to interpolate detailed population density. Results suggest that cokriging applied to impervious surface is a better alternative for estimating fine resolution population density. With the derived fine resolution data, a multiple

  8. Modelling nonpoint source pollution of MUDA river basin using GIS (Geographic Information System)

    International Nuclear Information System (INIS)

    Nyon Yong Chik; Taher Buyong

    2000-01-01

    The management of our rivers is under increasing pressure to conserve and sustain as it remains the focus of human civilization and subjected to increasing demand from man and its activities. Integrated river basin management represents comprehensive form of terrestrial water resources management while GIS is a promising tool to be used in the management strategy. In efforts to display the true capabilities of GIS in analysing nonpoint source pollution (NPS), an assessment of NPS was carried out at MUDA river basin using Arc View 3.0 Spatial Analyst. Expected Mean Concentration (EMC) which is associated with land use was used to predict the amount of pollutants constituents. A runoff grid was then processed to model the flow domain. Finally, the modelling of the pollutant loads downstreams towards the basin outlet is achieved by flow direction and accumulation analysis of the product of EMC and runoff grid. A user interface was programmed to display each application data theme via a pop-up window. In addition, users will be able to enter EMG values for the corresponding land use through an application dialog developed in Visual Basic. (Author)

  9. Interface between the model of quality QUALZE and a geographic information system

    International Nuclear Information System (INIS)

    Betancur, T; Sierra C, J.H.

    1998-01-01

    For the decision making related to the adequate utilization of a natural resource, is required count on versatile mechanisms that permit a rapid access the information related to the conditions of the system on the one which is intended to act, so that they could be analyzed and be designed political of managing and control that guarantee the preservation of the resource. A model is a design tool that permits to represent the simplified way reality and if is built of adequate way possesses a value predictive enormously useful for the managing of a natural resource. The water, essential element for the life, it has suffered deterioration in its quality, on account of man activities that they have established the irrational use of the water. The principal objective of the mathematical current models of water is to produce a tool that has the capacity to simulate the hydrological behavior and the quality of an aquatic system. The power to simulate the behavior of a water current permits to predict the changes that will have, when vary the element exhausts that affect its conditions

  10. Geographic information system for SILMU and the modelling of soil carbon flows

    International Nuclear Information System (INIS)

    Alm, J.; Lempinen, R.

    1994-01-01

    Integration of the various research themes incorporated as a single programme is a demanding task both scientifically and technically. To provide a tool for regionally based analysis and display of the results, a general purpose research database was configured in the GIS laboratory of the university of Joensuu, starting in 1992. In addition of the database system itself, a service node for GIS analysis and other possible uses of regional data was also established. The database can be used to store various background datasets, such as land use, soil maps, topography and regionally interpolated 1961-1990 climate parameters. These data can be combined and connected to other datasets and models provided by any SILMU research group

  11. Model for Determining Geographical Distribution of Heat Saving Potentials in Danish Building Stock

    DEFF Research Database (Denmark)

    Petrovic, Stefan; Karlsson, Kenneth Bernard

    2014-01-01

    Since the global oil crisis in the 1970s, Denmark has followed a path towards energy independency by continuously improving its energy efficiency and energy conservation. Energy efficiency was mainly tackled by introducing a high number of combined heat and power plants in the system, while energy...... conservation was predominantly approached by implementing heat saving measures. Today, with the goal of 100% renewable energy within the power and heat sector by the year 2035, reductions in energy demand for space heating and the preparation of domestic hot water remain at the top of the agenda in Denmark....... A highly detailed model for determining heat demand, possible heat savings and associated costs in the Danish building stock is presented. Both scheduled and energy-saving renovations until year 2030 have been analyzed. The highly detailed GIS-based heat atlas for Denmark is used as a container for storing...

  12. External exposure model for various geometries of contaminated materials

    International Nuclear Information System (INIS)

    LePoire, D.; Kamboj, S.; Yu, C.

    1996-01-01

    A computational model for external exposure was developed for the U.S. Department of Energy's residual radioactive material guideline computer code (RESRAD) on the basis of dose coefficients from Federal Guidance Report No. 12 and the point-kernel method. This model includes the effects of different materials and exposure distances, as well as source geometry (cover thickness, source depth, area, and shape). A material factor is calculated on the basis of the point-kernel method using material-specific photon cross-section data and buildup factors. This present model was incorporated into RESRAD-RECYCLE (a RESRAD family code used for computing radiological impacts of metal recycling) and is being incorporated into RESRAD-BUILD (a DOE recommended code for computing impacts of building decontamination). The model was compared with calculations performed with the Monte Carlo N-Particle Code (MCNP) and the Microshield code for three different source geometries, three different radionuclides ( 234 U, 238 U, and 60 Co, representing low, medium, and high energy, respectively), and five different source materials (iron, copper, aluminum, water, and soil). The comparison shows that results of this model are in very good agreement with MCNP calculations (within 5% for 60 Co and within 30% for 238 U and 234 U for all materials and source geometries). Significant differences (greater than 100%) were observed with Microshield for thin 234 U sources

  13. Geographic information systems-based expert system modelling for shoreline sensitivity to oil spill disaster in Rivers State, Nigeria

    Directory of Open Access Journals (Sweden)

    Olanrewaju Lawal

    2017-07-01

    Full Text Available In the absence of adequate and appropriate actions, hazards often result in disaster. Oil spills across any environment are very hazardous; thus, oil spill contingency planning is pertinent, supported by Environmental Sensitivity Index (ESI mapping. However, a significant data gap exists across many low- and middle-income countries in aspect of environmental monitoring. This study developed a geographic information system (GIS-based expert system (ES for shoreline sensitivity to oiling. It focused on the biophysical attributes of the shoreline with Rivers State as a case study. Data on elevation, soil, relative wave exposure and satellite imageries were collated and used for the development of ES decision rules within GIS. Results show that about 70% of the shoreline are lined with swamp forest/mangroves/nympa palm, and 97% have silt and clay as dominant sediment type. From the ES, six ranks were identified; 61% of the shoreline has a rank of 9 and 19% has a rank of 3 for shoreline sensitivity. A total of 568 km out of the 728 km shoreline is highly sensitive (ranks 7–10. There is a clear indication that the study area is a complex mixture of sensitive environments to oil spill. GIS-based ES with classification rules for shoreline sensitivity represents a rapid and flexible framework for automatic ranking of shoreline sensitivity to oiling. It is expected that this approach would kick-start sensitivity index mapping which is comprehensive and openly available to support disaster risk management around the oil producing regions of the country.

  14. Predictive modeling of terrestrial radiation exposure from geologic materials

    Science.gov (United States)

    Haber, Daniel A.

    Aerial gamma ray surveys are an important tool for national security, scientific, and industrial interests in determining locations of both anthropogenic and natural sources of radioactivity. There is a relationship between radioactivity and geology and in the past this relationship has been used to predict geology from an aerial survey. The purpose of this project is to develop a method to predict the radiologic exposure rate of the geologic materials in an area by creating a model using geologic data, images from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), geochemical data, and pre-existing low spatial resolution aerial surveys from the National Uranium Resource Evaluation (NURE) Survey. Using these data, geospatial areas, referred to as background radiation units, homogenous in terms of K, U, and Th are defined and the gamma ray exposure rate is predicted. The prediction is compared to data collected via detailed aerial survey by our partner National Security Technologies, LLC (NSTec), allowing for the refinement of the technique. High resolution radiation exposure rate models have been developed for two study areas in Southern Nevada that include the alluvium on the western shore of Lake Mohave, and Government Wash north of Lake Mead; both of these areas are arid with little soil moisture and vegetation. We determined that by using geologic units to define radiation background units of exposed bedrock and ASTER visualizations to subdivide radiation background units of alluvium, regions of homogeneous geochemistry can be defined allowing for the exposure rate to be predicted. Soil and rock samples have been collected at Government Wash and Lake Mohave as well as a third site near Cameron, Arizona. K, U, and Th concentrations of these samples have been determined using inductively coupled mass spectrometry (ICP-MS) and laboratory counting using radiation detection equipment. In addition, many sample locations also have

  15. An Atlas of ShakeMaps and population exposure catalog for earthquake loss modeling

    Science.gov (United States)

    Allen, T.I.; Wald, D.J.; Earle, P.S.; Marano, K.D.; Hotovec, A.J.; Lin, K.; Hearne, M.G.

    2009-01-01

    We present an Atlas of ShakeMaps and a catalog of human population exposures to moderate-to-strong ground shaking (EXPO-CAT) for recent historical earthquakes (1973-2007). The common purpose of the Atlas and exposure catalog is to calibrate earthquake loss models to be used in the US Geological Survey's Prompt Assessment of Global Earthquakes for Response (PAGER). The full ShakeMap Atlas currently comprises over 5,600 earthquakes from January 1973 through December 2007, with almost 500 of these maps constrained-to varying degrees-by instrumental ground motions, macroseismic intensity data, community internet intensity observations, and published earthquake rupture models. The catalog of human exposures is derived using current PAGER methodologies. Exposure to discrete levels of shaking intensity is obtained by correlating Atlas ShakeMaps with a global population database. Combining this population exposure dataset with historical earthquake loss data, such as PAGER-CAT, provides a useful resource for calibrating loss methodologies against a systematically-derived set of ShakeMap hazard outputs. We illustrate two example uses for EXPO-CAT; (1) simple objective ranking of country vulnerability to earthquakes, and; (2) the influence of time-of-day on earthquake mortality. In general, we observe that countries in similar geographic regions with similar construction practices tend to cluster spatially in terms of relative vulnerability. We also find little quantitative evidence to suggest that time-of-day is a significant factor in earthquake mortality. Moreover, earthquake mortality appears to be more systematically linked to the population exposed to severe ground shaking (Modified Mercalli Intensity VIII+). Finally, equipped with the full Atlas of ShakeMaps, we merge each of these maps and find the maximum estimated peak ground acceleration at any grid point in the world for the past 35 years. We subsequently compare this "composite ShakeMap" with existing global

  16. A model of the European electricity market. What can we learn from a geographical expansion to EU20?

    International Nuclear Information System (INIS)

    Lise, W.; Hobbs, B.F.

    2005-09-01

    This paper presents the static computational game theoretic COMPETES (COmprehensive Market Power in Electricity Transmission and Energy Simulator) model version 2.0. This model can be used to study various policy question regarding economic and environmental effects of a fully opened European electricity market. The COMPETES model can take strategic interaction among electricity producing firms into account. The strategic behaviour of generation companies can be reflected in the conjectures each company holds regarding the supply response of rival companies. These response functions simulate expectations concerning how rivals will change their electricity sales when prices change; these expectations determine the perceived profitability of capacity withholding and other strategies. In addition, COMPETES can solve the market outcome under price and quantity competition. COMPETES can also represent different systems of transmission pricing, among them fixed transmission tariffs, congestion-based pricing of physical transmission, and auction pricing of interface capacity between countries. CO2 costs can be brought in as an exogenous variable. In this paper the COMPETES model is calibrated to twenty European countries, EU20 for short, namely Austria, Belgium, Czech Republic, Denmark, Finland, France, Germany, Hungary, Italy, Luxembourg, Netherlands, Norway, Poland, Portugal, Slovakia, Slovenia, Spain, Sweden, Switzerland, UK/England and Wales. These countries have been chosen because they are geographically adjoined, their electricity networks are well connected (UCTE, Nord Pool, UK), they are members of the European Union (except for Norway and Switzerland) and data is quite reliable (which would for instance not be the case for the Balkan countries). The level of detail in the COMPETES model is quite extensive. The model contains various characteristics of 7531 power plants in the EU20 area (acquired from the database on World Energy Power Plants). These

  17. Predictive Models and Tools for Screening Chemicals under TSCA: Consumer Exposure Models 1.5

    Science.gov (United States)

    CEM contains a combination of models and default parameters which are used to estimate inhalation, dermal, and oral exposures to consumer products and articles for a wide variety of product and article use categories.

  18. Modelling long-term fire occurrence factors in Spain by accounting for local variations with geographically weighted regression

    Science.gov (United States)

    Martínez-Fernández, J.; Chuvieco, E.; Koutsias, N.

    2013-02-01

    Humans are responsible for most forest fires in Europe, but anthropogenic factors behind these events are still poorly understood. We tried to identify the driving factors of human-caused fire occurrence in Spain by applying two different statistical approaches. Firstly, assuming stationary processes for the whole country, we created models based on multiple linear regression and binary logistic regression to find factors associated with fire density and fire presence, respectively. Secondly, we used geographically weighted regression (GWR) to better understand and explore the local and regional variations of those factors behind human-caused fire occurrence. The number of human-caused fires occurring within a 25-yr period (1983-2007) was computed for each of the 7638 Spanish mainland municipalities, creating a binary variable (fire/no fire) to develop logistic models, and a continuous variable (fire density) to build standard linear regression models. A total of 383 657 fires were registered in the study dataset. The binary logistic model, which estimates the probability of having/not having a fire, successfully classified 76.4% of the total observations, while the ordinary least squares (OLS) regression model explained 53% of the variation of the fire density patterns (adjusted R2 = 0.53). Both approaches confirmed, in addition to forest and climatic variables, the importance of variables related with agrarian activities, land abandonment, rural population exodus and developmental processes as underlying factors of fire occurrence. For the GWR approach, the explanatory power of the GW linear model for fire density using an adaptive bandwidth increased from 53% to 67%, while for the GW logistic model the correctly classified observations improved only slightly, from 76.4% to 78.4%, but significantly according to the corrected Akaike Information Criterion (AICc), from 3451.19 to 3321.19. The results from GWR indicated a significant spatial variation in the local

  19. Quantifying geographic variation in the climatic drivers of midcontinent wetlands with a spatially varying coefficient model.

    Science.gov (United States)

    Roy, Christian

    2015-01-01

    The wetlands in the Prairie Pothole Region and in the Great Plains are notorious for their sensitivity to weather variability. These wetlands have been the focus of considerable attention because of their ecological importance and because of the expected impact of climate change. Few models in the literature, however, take into account spatial variation in the importance of wetland drivers. This is surprising given the importance spatial heterogeneity in geomorphology and climatic conditions have in the region. In this paper, I use spatially-varying coefficients to assess the variation in ecological drivers in a number of ponds observed over a 50-year period (1961-2012). I included the number of ponds observed the year before on a log scale, the log of total precipitation, and mean maximum temperature during the four previous seasons as explanatory variables. I also included a temporal component to capture change in the number of ponds due to anthropogenic disturbance. Overall, fall and spring precipitation were most important in pond abundance in the west, whereas winter and summer precipitation were the most important drivers in the east. The ponds in the east of the survey area were also more dependent on pond abundance during the previous year than those in the west. Spring temperature during the previous season influenced pond abundance; while the temperature during the other seasons had a limited effect. The ponds in the southwestern part of the survey area have been increasing independently of climatic conditions, whereas the ponds in the northeast have been steadily declining. My results underline the importance of accounting the spatial heterogeneity in environmental drivers, when working at large spatial scales. In light of my results, I also argue that assessing the impacts of climate change on wetland abundance in the spring, without more accurate climatic forecasting, will be difficult.

  20. Quantifying geographic variation in the climatic drivers of midcontinent wetlands with a spatially varying coefficient model.

    Directory of Open Access Journals (Sweden)

    Christian Roy

    Full Text Available The wetlands in the Prairie Pothole Region and in the Great Plains are notorious for their sensitivity to weather variability. These wetlands have been the focus of considerable attention because of their ecological importance and because of the expected impact of climate change. Few models in the literature, however, take into account spatial variation in the importance of wetland drivers. This is surprising given the importance spatial heterogeneity in geomorphology and climatic conditions have in the region. In this paper, I use spatially-varying coefficients to assess the variation in ecological drivers in a number of ponds observed over a 50-year period (1961-2012. I included the number of ponds observed the year before on a log scale, the log of total precipitation, and mean maximum temperature during the four previous seasons as explanatory variables. I also included a temporal component to capture change in the number of ponds due to anthropogenic disturbance. Overall, fall and spring precipitation were most important in pond abundance in the west, whereas winter and summer precipitation were the most important drivers in the east. The ponds in the east of the survey area were also more dependent on pond abundance during the previous year than those in the west. Spring temperature during the previous season influenced pond abundance; while the temperature during the other seasons had a limited effect. The ponds in the southwestern part of the survey area have been increasing independently of climatic conditions, whereas the ponds in the northeast have been steadily declining. My results underline the importance of accounting the spatial heterogeneity in environmental drivers, when working at large spatial scales. In light of my results, I also argue that assessing the impacts of climate change on wetland abundance in the spring, without more accurate climatic forecasting, will be difficult.

  1. Maxent modeling for predicting the potential geographical distribution of two peony species under climate change.

    Science.gov (United States)

    Zhang, Keliang; Yao, Linjun; Meng, Jiasong; Tao, Jun

    2018-09-01

    Paeonia (Paeoniaceae), an economically important plant genus, includes many popular ornamentals and medicinal plant species used in traditional Chinese medicine. Little is known about the properties of the habitat distribution and the important eco-environmental factors shaping the suitability. Based on high-resolution environmental data for current and future climate scenarios, we modeled the present and future suitable habitat for P. delavayi and P. rockii by Maxent, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results showed that the moderate and high suitable areas for P. delavayi and P. rockii encompassed ca. 4.46×10 5 km 2 and 1.89×10 5 km 2 , respectively. Temperature seasonality and isothermality were identified as the most critical factors shaping P. delavayi distribution, and UVB-4 and annual precipitation were identified as the most critical for shaping P. rockii distribution. Under the scenario with a low concentration of greenhouse gas emissions (RCP2.6), the range of both species increased as global warming intensified; however, under the scenario with higher concentrations of emissions (RCP8.5), the suitable habitat range of P. delavayi decreased while P. rockii increased. Overall, our prediction showed that a shift in distribution of suitable habitat to higher elevations would gradually become more significant. The information gained from this study should provide a useful reference for implementing long-term conservation and management strategies for these species. Copyright © 2018. Published by Elsevier B.V.

  2. Inhalation Exposure Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    K. Rautenstrauch

    2004-09-10

    This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception.

  3. Inhalation Exposure Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    K. Rautenstrauch

    2004-01-01

    This analysis is one of 10 reports that support the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents development of input parameters for the biosphere model that are related to atmospheric mass loading and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the total system performance assessment (TSPA) for a Yucca Mountain repository. Inhalation Exposure Input Parameters for the Biosphere Model is one of five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the Technical Work Plan for Biosphere Modeling and Expert Support (BSC 2004 [DIRS 169573]). This analysis report defines and justifies values of mass loading for the biosphere model. Mass loading is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Mass loading values are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air inhaled by a receptor and concentrations in air surrounding crops. Concentrations in air to which the receptor is exposed are then used in the inhalation submodel to calculate the dose contribution to the receptor from inhalation of contaminated airborne particles. Concentrations in air surrounding plants are used in the plant submodel to calculate the concentrations of radionuclides in foodstuffs contributed from uptake by foliar interception

  4. Modeling emission rates and exposures from outdoor cooking

    Science.gov (United States)

    Edwards, Rufus; Princevac, Marko; Weltman, Robert; Ghasemian, Masoud; Arora, Narendra K.; Bond, Tami

    2017-09-01

    Approximately 3 billion individuals rely on solid fuels for cooking globally. For a large portion of these - an estimated 533 million - cooking is outdoors, where emissions from cookstoves pose a health risk to both cooks and other household and village members. Models that estimate emissions rates from stoves in indoor environments that would meet WHO air quality guidelines (AQG), explicitly don't account for outdoor cooking. The objectives of this paper are to link health based exposure guidelines with emissions from outdoor cookstoves, using a Monte Carlo simulation of cooking times from Haryana India coupled with inverse Gaussian dispersion models. Mean emission rates for outdoor cooking that would result in incremental increases in personal exposure equivalent to the WHO AQG during a 24-h period were 126 ± 13 mg/min for cooking while squatting and 99 ± 10 mg/min while standing. Emission rates modeled for outdoor cooking are substantially higher than emission rates for indoor cooking to meet AQG, because the models estimate impact of emissions on personal exposure concentrations rather than microenvironment concentrations, and because the smoke disperses more readily outdoors compared to indoor environments. As a result, many more stoves including the best performing solid-fuel biomass stoves would meet AQG when cooking outdoors, but may also result in substantial localized neighborhood pollution depending on housing density. Inclusion of the neighborhood impact of pollution should be addressed more formally both in guidelines on emissions rates from stoves that would be protective of health, and also in wider health impact evaluation efforts and burden of disease estimates. Emissions guidelines should better represent the different contexts in which stoves are being used, especially because in these contexts the best performing solid fuel stoves have the potential to provide significant benefits.

  5. Data model management, with the use of artificial intelligence, for a geographic information system in the energetic sector

    Directory of Open Access Journals (Sweden)

    Nayi Sánchez Fleitas

    2016-09-01

    Full Text Available A Geographic Information System (GIS, named SIGOBE v 3.0, for the electric sector is development. The Integral Management System of the ECIE (SIGECIE and the Integrated Network Management System (SIGERE databases are taxed alfanumeric information. Studies determined the need for a model for data management, contributing to the GIS development, on a conceptual schema domain capable of responding to different user requests, through automatic query as support decision making. To provide the GIS with a conceptual basis an ontology is determined, which will be expressed by logical descriptive, to generate the traits of a case-based reasoning that allows automation of consultations. The final quality of GIS was verified according to the quality standards of the ISO-9126:2002 standard. The proposed model and its functionality contributes to: facilitate decision-making at different levels, perform risk analysis to have the defects of electrical installations, reduce the time of failure to the key areas of the country, organize the travel of trucks more efficiently and locate electrical faults more accurately.

  6. SAS macro programs for geographically weighted generalized linear modeling with spatial point data: applications to health research.

    Science.gov (United States)

    Chen, Vivian Yi-Ju; Yang, Tse-Chuan

    2012-08-01

    An increasing interest in exploring spatial non-stationarity has generated several specialized analytic software programs; however, few of these programs can be integrated natively into a well-developed statistical environment such as SAS. We not only developed a set of SAS macro programs to fill this gap, but also expanded the geographically weighted generalized linear modeling (GWGLM) by integrating the strengths of SAS into the GWGLM framework. Three features distinguish our work. First, the macro programs of this study provide more kernel weighting functions than the existing programs. Second, with our codes the users are able to better specify the bandwidth selection process compared to the capabilities of existing programs. Third, the development of the macro programs is fully embedded in the SAS environment, providing great potential for future exploration of complicated spatially varying coefficient models in other disciplines. We provided three empirical examples to illustrate the use of the SAS macro programs and demonstrated the advantages explained above. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  7. Modelling the sequential geographical exploitation and potential collapse of marine fisheries through economic globalization, climate change and management alternatives

    Directory of Open Access Journals (Sweden)

    Gorka Merino

    2011-07-01

    Full Text Available Global marine fisheries production has reached a maximum and may even be declining. Underlying this trend is a well-understood sequence of development, overexploitation, depletion and in some instances collapse of individual fish stocks, a pattern that can sequentially link geographically distant populations. Ineffective governance, economic considerations and climate impacts are often responsible for this sequence, although the relative contribution of each factor is contentious. In this paper we use a global bioeconomic model to explore the synergistic effects of climate variability, economic pressures and management measures in causing or avoiding this sequence. The model shows how a combination of climate-induced variability in the underlying fish population production, particular patterns of demand for fish products and inadequate management is capable of driving the world’s fisheries into development, overexploitation, collapse and recovery phases consistent with observations. Furthermore, it demonstrates how a sequential pattern of overexploitation can emerge as an endogenous property of the interaction between regional environmental fluctuations and a globalized trade system. This situation is avoidable through adaptive management measures that ensure the sustainability of regional production systems in the face of increasing global environmental change and markets. It is concluded that global management measures are needed to ensure that global food supply from marine products is optimized while protecting long-term ecosystem services across the world’s oceans.

  8. Evaluation Models for E-Learning Platform in Riyadh City Universities (RCU with Applied of Geographical Information System (GIS

    Directory of Open Access Journals (Sweden)

    Abdulaziz I. Alharrah

    2014-12-01

    Full Text Available E-learning that integrates digital knowledge content, network and information technology has become an emerging learning method. As the e-learning platform approach is becoming an important tool to allow the flexibility and quality requested by such a kind of learning process. There is a new kind of problem faced by organizations consisting in the selection of the most suitable e-learning platform. This paper proposes evaluation model for E-Learning platform in Riyadh City universities (RCU with Applied Geographic Information System (GIS. The E-Learning platform solution selection is a multiple criteria decision-making problem that needs to be addressed objectively taking into consideration the relative weights of the criteria for any organization. We formulate the quoted multi criteria problem as a decision hierarchy to be solved using GIS. AGIS-based evaluation index system and web-based evaluating platform were established. In this paper we will show the general evaluation strategy and some obtained results using our model to evaluate some existing commercial platforms.The results of evaluation model are outlined as follows: Total weights of the proposed framework in management feature is 20.25/25, in collaborative feature is 9.2/10, in adaption learning path is 6.8/10 and in interactive learning object is 5/5. The total weights of all features are 41.25/50. In this study an evaluation model was applied on Riyadh City universities like KSU, IMAMU, NAUSS, YU and FU. Then, the results were compared with each other. The total weighs of KSU was 41. While the total weights of FU, IMAMU, YU and NAUSS was 40, 37, 36 and 32, respectively. Evaluation process shows that the proposed framework satisfied the objectives with applied GIS.

  9. Lyssavirus infection: 'low dose, multiple exposure' in the mouse model.

    Science.gov (United States)

    Banyard, Ashley C; Healy, Derek M; Brookes, Sharon M; Voller, Katja; Hicks, Daniel J; Núñez, Alejandro; Fooks, Anthony R

    2014-03-06

    The European bat lyssaviruses (EBLV-1 and EBLV-2) are zoonotic pathogens present within bat populations across Europe. The maintenance and transmission of lyssaviruses within bat colonies is poorly understood. Cases of repeated isolation of lyssaviruses from bat roosts have raised questions regarding the maintenance and intraspecies transmissibility of these viruses within colonies. Furthermore, the significance of seropositive bats in colonies remains unclear. Due to the protected nature of European bat species, and hence restrictions to working with the natural host for lyssaviruses, this study analysed the outcome following repeat inoculation of low doses of lyssaviruses in a murine model. A standardized dose of virus, EBLV-1, EBLV-2 or a 'street strain' of rabies (RABV), was administered via a peripheral route to attempt to mimic what is hypothesized as natural infection. Each mouse (n=10/virus/group/dilution) received four inoculations, two doses in each footpad over a period of four months, alternating footpad with each inoculation. Mice were tail bled between inoculations to evaluate antibody responses to infection. Mice succumbed to infection after each inoculation with 26.6% of mice developing clinical disease following the initial exposure across all dilutions (RABV, 32.5% (n=13/40); EBLV-1, 35% (n=13/40); EBLV-2, 12.5% (n=5/40)). Interestingly, the lowest dose caused clinical disease in some mice upon first exposure ((RABV, 20% (n=2/10) after first inoculation; RABV, 12.5% (n=1/8) after second inoculation; EBLV-2, 10% (n=1/10) after primary inoculation). Furthermore, five mice developed clinical disease following the second exposure to live virus (RABV, n=1; EBLV-1, n=1; EBLV-2, n=3) although histopathological examination indicated that the primary inoculation was the most probably cause of death due to levels of inflammation and virus antigen distribution observed. All the remaining mice (RABV, n=26; EBLV-1, n=26; EBLV-2, n=29) survived the tertiary and

  10. Determinants of Dentists' Geographic Distribution.

    Science.gov (United States)

    Beazoglou, Tryfon J.; And Others

    1992-01-01

    A model for explaining the geographic distribution of dentists' practice locations is presented and applied to particular market areas in Connecticut. Results show geographic distribution is significantly related to a few key variables, including demography, disposable income, and housing prices. Implications for helping students make practice…

  11. Use of geographically weighted logistic regression to quantify spatial variation in the environmental and sociodemographic drivers of leptospirosis in Fiji: a modelling study.

    Science.gov (United States)

    Mayfield, Helen J; Lowry, John H; Watson, Conall H; Kama, Mike; Nilles, Eric J; Lau, Colleen L

    2018-05-01

    Leptospirosis is a globally important zoonotic disease, with complex exposure pathways that depend on interactions between human beings, animals, and the environment. Major drivers of outbreaks include flooding, urbanisation, poverty, and agricultural intensification. The intensity of these drivers and their relative importance vary between geographical areas; however, non-spatial regression methods are incapable of capturing the spatial variations. This study aimed to explore the use of geographically weighted logistic regression (GWLR) to provide insights into the ecoepidemiology of human leptospirosis in Fiji. We obtained field data from a cross-sectional community survey done in 2013 in the three main islands of Fiji. A blood sample obtained from each participant (aged 1-90 years) was tested for anti-Leptospira antibodies and household locations were recorded using GPS receivers. We used GWLR to quantify the spatial variation in the relative importance of five environmental and sociodemographic covariates (cattle density, distance to river, poverty rate, residential setting [urban or rural], and maximum rainfall in the wettest month) on leptospirosis transmission in Fiji. We developed two models, one using GWLR and one with standard logistic regression; for each model, the dependent variable was the presence or absence of anti-Leptospira antibodies. GWLR results were compared with results obtained with standard logistic regression, and used to produce a predictive risk map and maps showing the spatial variation in odds ratios (OR) for each covariate. The dataset contained location information for 2046 participants from 1922 households representing 81 communities. The Aikaike information criterion value of the GWLR model was 1935·2 compared with 1254·2 for the standard logistic regression model, indicating that the GWLR model was more efficient. Both models produced similar OR for the covariates, but GWLR also detected spatial variation in the effect of each

  12. Annual individual hygienic assessment of natural exposure doses of the Altai territory model areas population

    Directory of Open Access Journals (Sweden)

    N. Yu. Potseluev

    2016-01-01

    Full Text Available The goal is to determine ionizing radiation natural sources exposure regularities of Altai Territory model areas population. The materials and methods. 11376 radon measurements, 1247 gamma radiation meas-urements in an open area and in residential and office buildings were performed, selection of 189 drinking water tests was carried out. Results. Complex radiation and hygienic examination of the region with the most large municipalities number with model areas allocation was conducted. The assessment of the Altai Territory population’s individual annual radiation doses from natural radionuclides has revealed a number of the regularities depending on the terrain’s ecological and geographical type. Following the research results, ranging the region territories taking into account of annual effective doses of the population from natural sources for 2009-2015 was carried out. The annual individual effective dose of the Altai Territory upland areas population presented by the highest values and ranges from 7.36 mSv / year to 8.19 mSv / year. Foothill regions of Altai and in Salair ridge are characterized by increased population exposure from natural sources. Here the dose ranges from 5.09 mSv / year to 6.22 mSv / year. Steppe and forest-steppe territories are characterized by the lowest level of the natural radiation which is ranging from 3.23 mSv / year to 4.11 mSv / year, that doesn’t exceed the all-Russian levels. Most of the hygienic radon equivalent equilibrium volume activity standards exceedances were registered in mountain and foothill areas buildings. A number of radon anomalies is revealed also in steppe areas. Med exceedances ranged from 203 ± 17.8 Bq / m3 to 480 ± 37.9 Bq / m3. Given the fact that most of these buildings belong to the administrative or educational institutions with an eight-hour working day, the dose of radiation for people there can be up to 10 mSv / year. Conclusion. Spreading of individual annual effective

  13. A review of geographic variation and Geographic Information Systems (GIS) applications in prescription drug use research.

    Science.gov (United States)

    Wangia, Victoria; Shireman, Theresa I

    2013-01-01

    While understanding geography's role in healthcare has been an area of research for over 40 years, the application of geography-based analyses to prescription medication use is limited. The body of literature was reviewed to assess the current state of such studies to demonstrate the scale and scope of projects in order to highlight potential research opportunities. To review systematically how researchers have applied geography-based analyses to medication use data. Empiric, English language research articles were identified through PubMed and bibliographies. Original research articles were independently reviewed as to the medications or classes studied, data sources, measures of medication exposure, geographic units of analysis, geospatial measures, and statistical approaches. From 145 publications matching key search terms, forty publications met the inclusion criteria. Cardiovascular and psychotropic classes accounted for the largest proportion of studies. Prescription drug claims were the primary source, and medication exposure was frequently captured as period prevalence. Medication exposure was documented across a variety of geopolitical units such as countries, provinces, regions, states, and postal codes. Most results were descriptive and formal statistical modeling capitalizing on geospatial techniques was rare. Despite the extensive research on small area variation analysis in healthcare, there are a limited number of studies that have examined geographic variation in medication use. Clearly, there is opportunity to collaborate with geographers and GIS professionals to harness the power of GIS technologies and to strengthen future medication studies by applying more robust geospatial statistical methods. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. Comparison of height-diameter models based on geographically weighted regressions and linear mixed modelling applied to large scale forest inventory data

    Energy Technology Data Exchange (ETDEWEB)

    Quirós Segovia, M.; Condés Ruiz, S.; Drápela, K.

    2016-07-01

    Aim of the study: The main objective of this study was to test Geographically Weighted Regression (GWR) for developing height-diameter curves for forests on a large scale and to compare it with Linear Mixed Models (LMM). Area of study: Monospecific stands of Pinus halepensis Mill. located in the region of Murcia (Southeast Spain). Materials and Methods: The dataset consisted of 230 sample plots (2582 trees) from the Third Spanish National Forest Inventory (SNFI) randomly split into training data (152 plots) and validation data (78 plots). Two different methodologies were used for modelling local (Petterson) and generalized height-diameter relationships (Cañadas I): GWR, with different bandwidths, and linear mixed models. Finally, the quality of the estimated models was compared throughout statistical analysis. Main results: In general, both LMM and GWR provide better prediction capability when applied to a generalized height-diameter function than when applied to a local one, with R2 values increasing from around 0.6 to 0.7 in the model validation. Bias and RMSE were also lower for the generalized function. However, error analysis showed that there were no large differences between these two methodologies, evidencing that GWR provides results which are as good as the more frequently used LMM methodology, at least when no additional measurements are available for calibrating. Research highlights: GWR is a type of spatial analysis for exploring spatially heterogeneous processes. GWR can model spatial variation in tree height-diameter relationship and its regression quality is comparable to LMM. The advantage of GWR over LMM is the possibility to determine the spatial location of every parameter without additional measurements. Abbreviations: GWR (Geographically Weighted Regression); LMM (Linear Mixed Model); SNFI (Spanish National Forest Inventory). (Author)

  15. SHEDS-HT: An Integrated Probabilistic Exposure Model for Prioritizing Exposures to Chemicals with Near-Field and Dietary Sources

    Science.gov (United States)

    United States Environmental Protection Agency (USEPA) researchers are developing a strategy for highthroughput (HT) exposure-based prioritization of chemicals under the ExpoCast program. These novel modeling approaches for evaluating chemicals based on their potential for biologi...

  16. Forecasting the regional distribution and sufficiency of physicians in Japan with a coupled system dynamics-geographic information system model.

    Science.gov (United States)

    Ishikawa, Tomoki; Fujiwara, Kensuke; Ohba, Hisateru; Suzuki, Teppei; Ogasawara, Katsuhiko

    2017-09-12

    In Japan, the shortage of physicians has been recognized as a major medical issue. In our previous study, we reported that the absolute shortage will be resolved in the long term, but maldistribution among specialties will persist. To address regional shortage, several Japanese medical schools increased existing quota and established "regional quotas." This study aims to assist policy makers in designing effective policies; we built a model for forecasting physician numbers by region to evaluate future physician supply-demand balances. For our case study, we selected Hokkaido Prefecture in Japan, a region displaying disparities in healthcare services availability between urban and rural areas. We combined a system dynamics (SD) model with geographic information system (GIS) technology to analyze the dynamic change in spatial distribution of indicators. For Hokkaido overall and for each secondary medical service area (SMSA) within the prefecture, we analyzed the total number of practicing physicians. For evaluating absolute shortage and maldistribution, we calculated sufficiency levels and Gini coefficient. Our study covered the period 2010-2030 in 5-year increments. According to our forecast, physician shortage in Hokkaido Prefecture will largely be resolved by 2020. Based on current policies, we forecast that four SMSAs in Hokkaido will continue to experience physician shortages past that date, but only one SMSA would still be understaffed in 2030. The results show the possibility that diminishing imbalances between SMSAs would not necessarily mean that regional maldistribution would be eliminated, as seen from the sufficiency levels of the various SMSAs. Urgent steps should be taken to place doctors in areas where our forecasting model predicts that physician shortages could occur in the future.

  17. Modeling the geographic distribution of Ixodes scapularis and Ixodes pacificus (Acari: Ixodidae) in the contiguous United States

    Science.gov (United States)

    Hahn, Micah; Jarnevich, Catherine S.; Monaghan, Andrew J.; Eisen, Rebecca J.

    2016-01-01

    In addition to serving as vectors of several other human pathogens, the black-legged tick, Ixodes scapularis Say, and western black-legged tick, Ixodes pacificus Cooley and Kohls, are the primary vectors of the spirochete (Borrelia burgdorferi ) that causes Lyme disease, the most common vector-borne disease in the United States. Over the past two decades, the geographic range of I. pacificus has changed modestly while, in contrast, the I. scapularis range has expanded substantially, which likely contributes to the concurrent expansion in the distribution of human Lyme disease cases in the Northeastern, North-Central and Mid-Atlantic states. Identifying counties that contain suitable habitat for these ticks that have not yet reported established vector populations can aid in targeting limited vector surveillance resources to areas where tick invasion and potential human risk are likely to occur. We used county-level vector distribution information and ensemble modeling to map the potential distribution of I. scapularis and I. pacificus in the contiguous United States as a function of climate, elevation, and forest cover. Results show that I. pacificus is currently present within much of the range classified by our model as suitable for establishment. In contrast, environmental conditions are suitable for I. scapularis to continue expanding its range into northwestern Minnesota, central and northern Michigan, within the Ohio River Valley, and inland from the southeastern and Gulf coasts. Overall, our ensemble models show suitable habitat for I. scapularis in 441 eastern counties and for I. pacificus in 11 western counties where surveillance records have not yet supported classification of the counties as established.

  18. High Throughput Exposure Modeling of Semi-Volatile Chemicals in Articles of Commerce (ACS)

    Science.gov (United States)

    Risk due to chemical exposure is a function of both chemical hazard and exposure. Near-field exposures to chemicals in consumer products are identified as the main drivers of exposure and yet are not well quantified or understood. The ExpoCast project is developing a model that e...

  19. Geographically Weighted Regression Models in Estimating Median Home Prices in Towns of Massachusetts Based on an Urban Sustainability Framework

    Directory of Open Access Journals (Sweden)

    Yaxiong Ma

    2018-03-01

    Full Text Available Housing is a key component of urban sustainability. The objective of this study was to assess the significance of key spatial determinants of median home price in towns in Massachusetts that impact sustainable growth. Our analysis investigates the presence or absence of spatial non-stationarity in the relationship between sustainable growth, measured in terms of the relationship between home values and various parameters including the amount of unprotected forest land, residential land, unemployment, education, vehicle ownership, accessibility to commuter rail stations, school district performance, and senior population. We use the standard geographically weighted regression (GWR and Mixed GWR models to analyze the effects of spatial non-stationarity. Mixed GWR performed better than GWR in terms of Akaike Information Criterion (AIC values. Our findings highlight the nature and spatial extent of the non-stationary vs. stationary qualities of key environmental and social determinants of median home price. Understanding the key determinants of housing values, such as valuation of green spaces, public school performance metrics, and proximity to public transport, enable towns to use different strategies of sustainable urban planning, while understanding urban housing determinants—such as unemployment and senior population—can help modify urban sustainable housing policies.

  20. A State-of-the-Art Review on the Integration of Building Information Modeling (BIM and Geographic Information System (GIS

    Directory of Open Access Journals (Sweden)

    Xin Liu

    2017-02-01

    Full Text Available The integration of Building Information Modeling (BIM and Geographic Information System (GIS has been identified as a promising but challenging topic to transform information towards the generation of knowledge and intelligence. Achievement of integrating these two concepts and enabling technologies will have a significant impact on solving problems in the civil, building and infrastructure sectors. However, since GIS and BIM were originally developed for different purposes, numerous challenges are being encountered for the integration. To better understand these two different domains, this paper reviews the development and dissimilarities of GIS and BIM, the existing integration methods, and investigates their potential in various applications. This study shows that the integration methods are developed for various reasons and aim to solve different problems. The parameters influencing the choice can be summarized and named as “EEEF” criteria: effectiveness, extensibility, effort, and flexibility. Compared with other methods, semantic web technologies provide a promising and generalized integration solution. However, the biggest challenges of this method are the large efforts required at early stage and the isolated development of ontologies within one particular domain. The isolation problem also applies to other methods. Therefore, openness is the key of the success of BIM and GIS integration.

  1. Modelling of chosen selectable factors of the develop of tourism with geographic IT and fuzzy sets using

    Directory of Open Access Journals (Sweden)

    Jitka Machalová

    2011-01-01

    Full Text Available The tourism is the significant tool of prosperity not only of the well-known touristic regions, but it is significant potential developing element of not so developed provincial regions. Develop and placements of tourism are dependent on factors (conditions that influence its use in concrete regions. These factors are classified into selectable, localisation, and realisation (localisation and realisation factors issue was published as a part of solution of the research plan of FBE No. MSM 6215648904, part 03. The selectable factors determine the possibilities of the region to develop tourism in demand function. The landscape character and the environment appertain to these objective presumptions. But these presumptions were subjective perceived. The aim of this paper is to make methodology of evaluation of introduced selectable factors. Geographic information technology will be use for spatial modelling. Theory of fuzzy sets, with its ability to catch the vagueness, will be use for defining of fuzzygeoelements and for the making several fuzzylayers. The fuzzylayers will be come into map algebra for whole formulation of these selectable factors. The methodology will be verified on territory micro region Babi lom (south of Moravia.

  2. Geographic Access Modeling of Emergency Obstetric and Neonatal Care in Kigoma Region, Tanzania: Transportation Schemes and Programmatic Implications.

    Science.gov (United States)

    Chen, Yi No; Schmitz, Michelle M; Serbanescu, Florina; Dynes, Michelle M; Maro, Godson; Kramer, Michael R

    2017-09-27

    Access to transportation is vital to reducing the travel time to emergency obstetric and neonatal care (EmONC) for managing complications and preventing adverse maternal and neonatal outcomes. This study examines the distribution of travel times to EmONC in Kigoma Region, Tanzania, using various transportation schemes, to estimate the proportion of live births (a proxy indicator of women needing delivery care) with poor geographic access to EmONC services. The 2014 Reproductive Health Survey of Kigoma Region identified 4 primary means of transportation used to travel to health facilities: walking, cycling, motorcycle, and 4-wheeled motor vehicle. A raster-based travel time model was used to map the 2-hour travel time catchment for each mode of transportation. Live birth density distributions were aggregated by travel time catchments, and by administrative council, to estimate the proportion of births with poor access. Of all live births in Kigoma Region, 13% occurred in areas where women can reach EmONC facilities within 2 hours on foot, 33% in areas that can be reached within 2 hours only by motorized vehicles, and 32% where it is impossible to reach EmONC facilities within 2 hours. Over 50% of births in 3 of the 8 administrative councils had poor estimated access. In half the councils, births with poor access could be reduced to no higher than 12% if all female residents had access to motorized vehicles. Significant differences in geographic access to EmONC in Kigoma Region, Tanzania, were observed both by location and by primary transportation type. As most of the population may only have good EmONC access when using mechanized or motorized vehicles, bicycles and motorcycles should be incorporated into the health transportation strategy. Collaboration between private transportation sectors and obstetric service providers could improve access to EmONC services among most populations. In areas where residents may not access EmONC facilities within 2 hours

  3. Indicators of residential traffic exposure: Modelled NOX, traffic proximity, and self-reported exposure in RHINE III

    Science.gov (United States)

    Carlsen, Hanne Krage; Bäck, Erik; Eneroth, Kristina; Gislason, Thorarinn; Holm, Mathias; Janson, Christer; Jensen, Steen Solvang; Johannessen, Ane; Kaasik, Marko; Modig, Lars; Segersson, David; Sigsgaard, Torben; Forsberg, Bertil; Olsson, David; Orru, Hans

    2017-10-01

    Few studies have investigated associations between self-reported and modelled exposure to traffic pollution. The objective of this study was to examine correlations between self-reported traffic exposure and modelled (a) NOX and (b) traffic proximity in seven different northern European cities; Aarhus (Denmark), Bergen (Norway), Gothenburg, Umeå, and Uppsala (Sweden), Reykjavik (Iceland), and Tartu (Estonia). We analysed data from the RHINE III (Respiratory Health in Northern Europe, http://www.rhine.nu)

  4. Modeling species’ realized climatic niche space and predicting their response to global warming for several western forest species with small geographic distributions

    Science.gov (United States)

    Marcus V. Warwell; Gerald E. Rehfeldt; Nicholas L. Crookston

    2010-01-01

    The Random Forests multiple regression tree was used to develop an empirically based bioclimatic model of the presence-absence of species occupying small geographic distributions in western North America. The species assessed were subalpine larch (Larix lyallii), smooth Arizona cypress (Cupressus arizonica ssp. glabra...

  5. Crossing physical simulations of snow conditions and a geographic model of ski area to assess ski resorts vulnerability

    Science.gov (United States)

    François, Hugues; Spandre, Pierre; Morin, Samuel; George-Marcelpoil, Emmanuelle; Lafaysse, Matthieu; Lejeune, Yves

    2016-04-01

    In order to face climate change, meteorological variability and the recurrent lack of natural snow on the ground, ski resorts adaptation often rely on technical responses. Indeed, since the occurrence of episodes with insufficient snowfalls in the early 1990's, snowmaking has become an ordinary practice of snow management, comparable to grooming, and contributes to optimise the operation of ski resorts. It also participates to the growth of investments and is associated with significant operating costs, and thus represents a new source of vulnerability. The assessment of the actual effects of snowmaking and of snow management practices in general is a real concern for the future of the ski industry. The principal model use to simulate snow conditions in resorts, Ski Sim, has also been moving this way. Its developers introduced an artificial input of snow on ski area to complete natural snowfalls and considered different organisations of ski lifts (lower and upper zones). However the use of a degree-day model prevents them to consider the specific properties of artificial snow and the impact of grooming on the snowpack. A first proof of concept in the French Alps has shown the feasibility and the interest to cross the geographic model of ski areas and the output of the physically-based reanalysis of snow conditions SAFRAN - Crocus (François et al., CRST 2014). Since these initial developments, several ways have been explored to refine our model. A new model of ski areas has been developed. Our representation is now based on gravity derived from a DEM and ski lift localisation. A survey about snow management practices also allowed us to define criteria in order to model snowmaking areas given ski areas properties and tourism infrastructures localisation. We also suggest to revisit the assessment of ski resort viability based on the "one hundred days rule" based on natural snow depth only. Indeed, the impact of snow management must be considered so as to propose

  6. Mapping the Global Potential Geographical Distribution of Black Locust (Robinia Pseudoacacia L. Using Herbarium Data and a Maximum Entropy Model

    Directory of Open Access Journals (Sweden)

    Guoqing Li

    2014-11-01

    Full Text Available Black locust (Robinia pseudoacacia L. is a tree species of high economic and ecological value, but is also considered to be highly invasive. Understanding the global potential distribution and ecological characteristics of this species is a prerequisite for its practical exploitation as a resource. Here, a maximum entropy modeling (MaxEnt was used to simulate the potential distribution of this species around the world, and the dominant climatic factors affecting its distribution were selected by using a jackknife test and the regularized gain change during each iteration of the training algorithm. The results show that the MaxEnt model performs better than random, with an average test AUC value of 0.9165 (±0.0088. The coldness index, annual mean temperature and warmth index were the most important climatic factors affecting the species distribution, explaining 65.79% of the variability in the geographical distribution. Species response curves showed unimodal relationships with the annual mean temperature and warmth index, whereas there was a linear relationship with the coldness index. The dominant climatic conditions in the core of the black locust distribution are a coldness index of −9.8 °C–0 °C, an annual mean temperature of 5.8 °C–14.5 °C, a warmth index of 66 °C–168 °C and an annual precipitation of 508–1867 mm. The potential distribution of black locust is located mainly in the United States, the United Kingdom, Germany, France, the Netherlands, Belgium, Italy, Switzerland, Australia, New Zealand, China, Japan, South Korea, South Africa, Chile and Argentina. The predictive map of black locust, climatic thresholds and species response curves can provide globally applicable guidelines and valuable information for policymakers and planners involved in the introduction, planting and invasion control of this species around the world.

  7. Inhalation Exposure Input Parameters for the Biosphere Model

    Energy Technology Data Exchange (ETDEWEB)

    M. A. Wasiolek

    2003-09-24

    This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air

  8. Inhalation Exposure Input Parameters for the Biosphere Model

    International Nuclear Information System (INIS)

    M. A. Wasiolek

    2003-01-01

    This analysis is one of the nine reports that support the Environmental Radiation Model for Yucca Mountain Nevada (ERMYN) biosphere model. The ''Biosphere Model Report'' (BSC 2003a) describes in detail the conceptual model as well as the mathematical model and its input parameters. This report documents a set of input parameters for the biosphere model, and supports the use of the model to develop biosphere dose conversion factors (BDCFs). The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for a Yucca Mountain repository. This report, ''Inhalation Exposure Input Parameters for the Biosphere Model'', is one of the five reports that develop input parameters for the biosphere model. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling, and the plan for development of the biosphere abstraction products for TSPA, as identified in the ''Technical Work Plan: for Biosphere Modeling and Expert Support'' (BSC 2003b). It should be noted that some documents identified in Figure 1-1 may be under development at the time this report is issued and therefore not available at that time. This figure is included to provide an understanding of how this analysis report contributes to biosphere modeling in support of the license application, and is not intended to imply that access to the listed documents is required to understand the contents of this analysis report. This analysis report defines and justifies values of mass loading, which is the total mass concentration of resuspended particles (e.g., dust, ash) in a volume of air. Measurements of mass loading are used in the air submodel of ERMYN to calculate concentrations of radionuclides in air surrounding crops and concentrations in air inhaled by a receptor. Concentrations in air to which the

  9. Use of an aggregate exposure model to estimate consumer exposure to fragrance ingredients in personal care and cosmetic products.

    Science.gov (United States)

    Safford, B; Api, A M; Barratt, C; Comiskey, D; Daly, E J; Ellis, G; McNamara, C; O'Mahony, C; Robison, S; Smith, B; Thomas, R; Tozer, S

    2015-08-01

    Ensuring the toxicological safety of fragrance ingredients used in personal care and cosmetic products is essential in product development and design, as well as in the regulatory compliance of the products. This requires an accurate estimation of consumer exposure which, in turn, requires an understanding of consumer habits and use of products. Where ingredients are used in multiple product types, it is important to take account of aggregate exposure in consumers using these products. This publication investigates the use of a newly developed probabilistic model, the Creme RIFM model, to estimate aggregate exposure to fragrance ingredients using the example of 2-phenylethanol (PEA). The output shown demonstrates the utility of the model in determining systemic and dermal exposure to fragrances from individual products, and aggregate exposure. The model provides valuable information not only for risk assessment, but also for risk management. It should be noted that data on the concentrations of PEA in products used in this article were obtained from limited sources and not the standard, industry wide surveys typically employed by the fragrance industry and are thus presented here to illustrate the output and utility of the newly developed model. They should not be considered an accurate representation of actual exposure to PEA. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. PBDE exposure from food in Ireland: optimising data exploitation in probabilistic exposure modelling.

    Science.gov (United States)

    Trudel, David; Tlustos, Christina; Von Goetz, Natalie; Scheringer, Martin; Hungerbühler, Konrad

    2011-01-01

    Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants added to plastics, polyurethane foam, electronics, textiles, and other products. These products release PBDEs into the indoor and outdoor environment, thus causing human exposure through food and dust. This study models PBDE dose distributions from ingestion of food for Irish adults on congener basis by using two probabilistic and one semi-deterministic method. One of the probabilistic methods was newly developed and is based on summary statistics of food consumption combined with a model generating realistic daily energy supply from food. Median (intermediate) doses of total PBDEs are in the range of 0.4-0.6 ng/kg(bw)/day for Irish adults. The 97.5th percentiles of total PBDE doses lie in a range of 1.7-2.2 ng/kg(bw)/day, which is comparable to doses derived for Belgian and Dutch adults. BDE-47 and BDE-99 were identified as the congeners contributing most to estimated intakes, accounting for more than half of the total doses. The most influential food groups contributing to this intake are lean fish and salmon which together account for about 22-25% of the total doses.

  11. An investigation by LA-ICP-MS of possum tooth enamel as a model for identifying childhood geographical locations of historical and archaeological human remains from New Zealand

    International Nuclear Information System (INIS)

    Cameron, N.E.; Balks, M.; Littler, R.; Manley-Harris, M.; Te Awekotuku, N.

    2012-01-01

    LA-ICP-MS (laser ablation-inductively coupled plasma-mass spectrometry) has been used to analyse enamel from the teeth of brushtail possum (Trichosurus vulpecula) in order to model a method for identifying the childhood geographical origin of human remains within New Zealand. The model application of the method is promising for establishing locations of historical and archaeological human remains, including preserved heads, upoko tuhi. (author). 30 refs., 5 figs., 6 tabs.

  12. NEPR Geographic Zone Map 2015

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This geographic zone map was created by interpreting satellite and aerial imagery, seafloor topography (bathymetry model), and the new NEPR Benthic Habitat Map...

  13. Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images.

    Science.gov (United States)

    Ji, Zexuan; Chen, Qiang; Niu, Sijie; Leng, Theodore; Rubin, Daniel L

    2018-01-01

    To automatically and accurately segment geographic atrophy (GA) in spectral-domain optical coherence tomography (SD-OCT) images by constructing a voting system with deep neural networks without the use of retinal layer segmentation. An automatic GA segmentation method for SD-OCT images based on the deep network was constructed. The structure of the deep network was composed of five layers, including one input layer, three hidden layers, and one output layer. During the training phase, the labeled A-scans with 1024 features were directly fed into the network as the input layer to obtain the deep representations. Then a soft-max classifier was trained to determine the label of each individual pixel. Finally, a voting decision strategy was used to refine the segmentation results among 10 trained models. Two image data sets with GA were used to evaluate the model. For the first dataset, our algorithm obtained a mean overlap ratio (OR) 86.94% ± 8.75%, absolute area difference (AAD) 11.49% ± 11.50%, and correlation coefficients (CC) 0.9857; for the second dataset, the mean OR, AAD, and CC of the proposed method were 81.66% ± 10.93%, 8.30% ± 9.09%, and 0.9952, respectively. The proposed algorithm was capable of improving over 5% and 10% segmentation accuracy, respectively, when compared with several state-of-the-art algorithms on two data sets. Without retinal layer segmentation, the proposed algorithm could produce higher segmentation accuracy and was more stable when compared with state-of-the-art methods that relied on retinal layer segmentation results. Our model may provide reliable GA segmentations from SD-OCT images and be useful in the clinical diagnosis of advanced nonexudative AMD. Based on the deep neural networks, this study presents an accurate GA segmentation method for SD-OCT images without using any retinal layer segmentation results, and may contribute to improved understanding of advanced nonexudative AMD.

  14. Benchmarking of computer codes and approaches for modeling exposure scenarios

    International Nuclear Information System (INIS)

    Seitz, R.R.; Rittmann, P.D.; Wood, M.I.; Cook, J.R.

    1994-08-01

    The US Department of Energy Headquarters established a performance assessment task team (PATT) to integrate the activities of DOE sites that are preparing performance assessments for the disposal of newly generated low-level waste. The PATT chartered a subteam with the task of comparing computer codes and exposure scenarios used for dose calculations in performance assessments. This report documents the efforts of the subteam. Computer codes considered in the comparison include GENII, PATHRAE-EPA, MICROSHIELD, and ISOSHLD. Calculations were also conducted using spreadsheets to provide a comparison at the most fundamental level. Calculations and modeling approaches are compared for unit radionuclide concentrations in water and soil for the ingestion, inhalation, and external dose pathways. Over 30 tables comparing inputs and results are provided

  15. Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials

    Energy Technology Data Exchange (ETDEWEB)

    Malchow, Russell L. [National Security Technologies, LLC; Haber, Daniel University of Nevada, Las Vegas; Burnley, Pamela [University of Nevada, Las Vegas; Marsac, Kara [University of Nevada, Las Vegas; Hausrath, Elisabeth [University of Nevada, Las Vegas; Adcock, Christopher [University of Nevada, Las Vegas

    2015-01-01

    Aerial gamma ray surveys are important for those working in nuclear security and industry for determining locations of both anthropogenic radiological sources and natural occurrences of radionuclides. During an aerial gamma ray survey, a low flying aircraft, such as a helicopter, flies in a linear pattern across the survey area while measuring the gamma emissions with a sodium iodide (NaI) detector. Currently, if a gamma ray survey is being flown in an area, the only way to correct for geologic sources of gamma rays is to have flown the area previously. This is prohibitively expensive and would require complete national coverage. This project’s goal is to model the geologic contribution to radiological backgrounds using published geochemical data, GIS software, remote sensing, calculations, and modeling software. K, U and Th are the three major gamma emitters in geologic material. U and Th are assumed to be in secular equilibrium with their daughter isotopes. If K, U, and Th abundance values are known for a given geologic unit the expected gamma ray exposure rate can be calculated using the Grasty equation or by modeling software. Monte Carlo N-Particle Transport software (MCNP), developed by Los Alamos National Laboratory, is modeling software designed to simulate particles and their interactions with matter. Using this software, models have been created that represent various lithologies. These simulations randomly generate gamma ray photons at energy levels expected from natural radiologic sources. The photons take a random path through the simulated geologic media and deposit their energy at the end of their track. A series of nested spheres have been created and filled with simulated atmosphere to record energy deposition. Energies deposited are binned in the same manner as the NaI detectors used during an aerial survey. These models are used in place of the simplistic Grasty equation as they take into account absorption properties of the lithology which the

  16. Research about social, curricular and geographical transversality of a teaching and learning history model based on ojbects as primary sources and classroom museums

    Directory of Open Access Journals (Sweden)

    Glória Solé

    2017-01-01

    Full Text Available The article’s starting point is the problem of perception and understanding of history –which is essential to create a critical citizenship- by future citizens (primary school students as well as future educators (teachers training university students. The article proposes two models of teaching and learning history and its development in two case studies adapted to different ages and geographical contexts (case 1: teachers training degree students of a Spanish university and case 2: Portuguese primary education pupils. Results of the development of the teaching and learning model in both contexts are presented at the same time that the social, curricular and geographical transversality of the model proposed is exposed.

  17. Modelling and simulation of concrete leaching under outdoor exposure conditions

    International Nuclear Information System (INIS)

    Schiopu, Nicoleta; Tiruta-Barna, Ligia; Jayr, Emmanuel; Mehu, Jacques; Moszkowicz, Pierre

    2009-01-01

    Recently, a demand regarding the assessment of release of dangerous substances from construction products was raised by European Commission which has issued the Mandate M/366 addressed to CEN. This action is in relation with the Essential Requirement No. 3 'Hygiene, Health and Environment' of the Construction Products Directive (89/106/EC). The potential hazard for environment and health may arise in different life cycle stages of a construction product. During the service life stage, the release of substances due to contact with the rain water is the main potential hazard source, as a consequence of the leaching phenomenon. The objective of this paper is to present the development of a coupled chemical-transport model for the case of a concrete based construction product, i.e. concrete paving slabs, exposed to rain water under outdoor exposure conditions. The development of the model is based on an iterative process of comparing the experimental results with the simulated results up to an acceptable fit. The experiments were conducted at laboratory scale (equilibrium and dynamic leaching tests) and field scale. The product was exposed for one year in two types of leaching scenarios under outdoor conditions, 'runoff' and 'stagnation', and the element release was monitored. The model was calibrated using the experimental data obtained at laboratory scale and validated against measured field data, by taking into account the specific rain water balance and the atmospheric CO 2 uptake as input parameters. The numerical tool used in order to model and simulate the leaching behaviour was PHREEQC, coupled with the Lawrence Livermore National Laboratory (LLNL) thermodynamic data base. The simulation results are satisfying and the paper demonstrates the feasibility of the modelling approach for the leaching behaviour assessment of concrete type construction materials

  18. Modeled exposure assessment via inhalation and dermal pathways to airborne semivolatile organic compounds (SVOCs) in residences.

    Science.gov (United States)

    Shi, Shanshan; Zhao, Bin

    2014-05-20

    Exposure to airborne semivolatile organic compounds (SVOCs) in indoor and outdoor environments of humans may lead to adverse health risks. Thus, we established a model to evaluate exposure to airborne SVOCs. In this model, SVOCs phase-specific concentrations were estimated by a kinetic partition model accounting for particle dynamics. The exposure pathways to airborne SVOCs included inhalation exposure to gas- and particle-phases, dermal exposure by direct gas-to-skin pathway and dermal exposure by direct particle deposition. Exposures of defined "reference people" to two typical classifications of SVOCs, one generated from both indoor and outdoor sources, represented by polycyclic aromatic hydrocarbons (PAHs), and the other generated mainly from only indoor sources, represented by di 2-ethylhexyl phthalate (DEHP), were analyzed as an example application of the model. For PAHs with higher volatility, inhalation exposure to gas-phase, ranging from 6.03 to 16.4 ng/kg/d, accounted for the most of the exposure to the airborne phases. For PAHs with lower volatility, inhalation exposure to particle-phase, ranging from 1.48 to 1.53 ng/kg/d, was the most important exposure pathway. As for DEHP, dermal exposure via direct gas-to-skin pathway was 460 ng/kg/d, which was the most striking exposure pathway when the barrier effect of clothing was neglected.

  19. A BAYESIAN SPATIAL AND TEMPORAL MODELING APPROACH TO MAPPING GEOGRAPHIC VARIATION IN MORTALITY RATES FOR SUBNATIONAL AREAS WITH R-INLA.

    Science.gov (United States)

    Khana, Diba; Rossen, Lauren M; Hedegaard, Holly; Warner, Margaret

    2018-01-01

    Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005-2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and county-specific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software R-INLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation.

  20. Comparison of modeled estimates of inhalation exposure to aerosols during use of consumer spray products.

    Science.gov (United States)

    Park, Jihoon; Yoon, Chungsik; Lee, Kiyoung

    2018-05-30

    In the field of exposure science, various exposure assessment models have been developed to complement experimental measurements; however, few studies have been published on their validity. This study compares the estimated inhaled aerosol doses of several inhalation exposure models to experimental measurements of aerosols released from consumer spray products, and then compares deposited doses within different parts of the human respiratory tract according to deposition models. Exposure models, including the European Center for Ecotoxicology of Chemicals Targeted Risk Assessment (ECETOC TRA), the Consumer Exposure Model (CEM), SprayExpo, ConsExpo Web and ConsExpo Nano, were used to estimate the inhaled dose under various exposure scenarios, and modeled and experimental estimates were compared. The deposited dose in different respiratory regions was estimated using the International Commission on Radiological Protection model and multiple-path particle dosimetry models under the assumption of polydispersed particles. The modeled estimates of the inhaled doses were accurate in the short term, i.e., within 10 min of the initial spraying, with a differences from experimental estimates ranging from 0 to 73% among the models. However, the estimates for long-term exposure, i.e., exposure times of several hours, deviated significantly from the experimental estimates in the absence of ventilation. The differences between the experimental and modeled estimates of particle number and surface area were constant over time under ventilated conditions. ConsExpo Nano, as a nano-scale model, showed stable estimates of short-term exposure, with a difference from the experimental estimates of less than 60% for all metrics. The deposited particle estimates were similar among the deposition models, particularly in the nanoparticle range for the head airway and alveolar regions. In conclusion, the results showed that the inhalation exposure models tested in this study are suitable

  1. A Bayesian kriging model for estimating residential exposure to air pollution of children living in a high-risk area in Italy

    Directory of Open Access Journals (Sweden)

    Ana M. Vicedo-Cabrera

    2013-11-01

    Full Text Available A core challenge in epidemiological analysis of the impact of exposure to air pollution on health is assessment of the individual exposure for subjects at risk. Geographical information systems (GIS-based pollution mapping, such as kriging, has become one of the main tools for evaluating individual exposure to ambient pollutants. We applied universal Bayesian kriging to estimate the residential exposure to gaseous air pollutants for children living in a high-risk area (Milazzo- Valle del Mela in Sicily, Italy. Ad hoc air quality monitoring campaigns were carried out: 12 weekly measurements for sulphur dioxide (SO2 and nitrogen dioxide (NO2 were obtained from 21 passive dosimeters located at each school yard of the study area from November 2007 to April 2008. Universal Bayesian kriging was performed to predict individual exposure levels at each residential address for all 6- to 12-years-old children attending primary school at various locations in the study area. Land use, altitude, distance to main roads and population density were included as covariates in the models. A large geographical heterogeneity in air quality was recorded suggesting complex exposure patterns. We obtained a predicted mean level of 25.78 (±10.61 μg/m3 of NO2 and 4.10 (±2.71 μg/m3 of SO2 at 1,682 children’s residential addresses, with a normalised root mean squared error of 28% and 25%, respectively. We conclude that universal Bayesian kriging approach is a useful tool for the assessment of realistic exposure estimates with regard to ambient pollutants at home addresses. Its prediction uncertainty is highly informative and can be used for both designing subsequent campaigns and for improved modelling of epidemiological associations.

  2. Source apportionment of soil heavy metals using robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR) receptor model.

    Science.gov (United States)

    Qu, Mingkai; Wang, Yan; Huang, Biao; Zhao, Yongcun

    2018-06-01

    The traditional source apportionment models, such as absolute principal component scores-multiple linear regression (APCS-MLR), are usually susceptible to outliers, which may be widely present in the regional geochemical dataset. Furthermore, the models are merely built on variable space instead of geographical space and thus cannot effectively capture the local spatial characteristics of each source contributions. To overcome the limitations, a new receptor model, robust absolute principal component scores-robust geographically weighted regression (RAPCS-RGWR), was proposed based on the traditional APCS-MLR model. Then, the new method was applied to the source apportionment of soil metal elements in a region of Wuhan City, China as a case study. Evaluations revealed that: (i) RAPCS-RGWR model had better performance than APCS-MLR model in the identification of the major sources of soil metal elements, and (ii) source contributions estimated by RAPCS-RGWR model were more close to the true soil metal concentrations than that estimated by APCS-MLR model. It is shown that the proposed RAPCS-RGWR model is a more effective source apportionment method than APCS-MLR (i.e., non-robust and global model) in dealing with the regional geochemical dataset. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. Applicability of western chemical dietary exposure models to the Chinese population.

    Science.gov (United States)

    Zhao, Shizhen; Price, Oliver; Liu, Zhengtao; Jones, Kevin C; Sweetman, Andrew J

    2015-07-01

    A range of exposure models, which have been developed in Europe and North America, are playing an increasingly important role in priority setting and the risk assessment of chemicals. However, the applicability of these tools, which are based on Western dietary exposure pathways, to estimate chemical exposure to the Chinese population to support the development of a risk-based environment and exposure assessment, is unclear. Three frequently used modelling tools, EUSES, RAIDAR and ACC-HUMANsteady, have been evaluated in terms of human dietary exposure estimation by application to a range of chemicals with different physicochemical properties under both model default and Chinese dietary scenarios. Hence, the modelling approaches were assessed by considering dietary pattern differences only. The predicted dietary exposure pathways were compared under both scenarios using a range of hypothetical and current emerging contaminants. Although the differences across models are greater than those between dietary scenarios, model predictions indicated that dietary preference can have a significant impact on human exposure, with the relatively high consumption of vegetables and cereals resulting in higher exposure via plants-based foodstuffs under Chinese consumption patterns compared to Western diets. The selected models demonstrated a good ability to identify key dietary exposure pathways which can be used for screening purposes and an evaluative risk assessment. However, some model adaptations will be required to cover a number of important Chinese exposure pathways, such as freshwater farmed-fish, grains and pork. Copyright © 2015 Elsevier Inc. All rights reserved.

  4. Strategies for Controlling Item Exposure in Computerized Adaptive Testing with the Generalized Partial Credit Model

    Science.gov (United States)

    Davis, Laurie Laughlin

    2004-01-01

    Choosing a strategy for controlling item exposure has become an integral part of test development for computerized adaptive testing (CAT). This study investigated the performance of six procedures for controlling item exposure in a series of simulated CATs under the generalized partial credit model. In addition to a no-exposure control baseline…

  5. Bivariate Left-Censored Bayesian Model for Predicting Exposure: Preliminary Analysis of Worker Exposure during the Deepwater Horizon Oil Spill.

    Science.gov (United States)

    Groth, Caroline; Banerjee, Sudipto; Ramachandran, Gurumurthy; Stenzel, Mark R; Sandler, Dale P; Blair, Aaron; Engel, Lawrence S; Kwok, Richard K; Stewart, Patricia A

    2017-01-01

    In April 2010, the Deepwater Horizon oil rig caught fire and exploded, releasing almost 5 million barrels of oil into the Gulf of Mexico over the ensuing 3 months. Thousands of oil spill workers participated in the spill response and clean-up efforts. The GuLF STUDY being conducted by the National Institute of Environmental Health Sciences is an epidemiological study to investigate potential adverse health effects among these oil spill clean-up workers. Many volatile chemicals were released from the oil into the air, including total hydrocarbons (THC), which is a composite of the volatile components of oil including benzene, toluene, ethylbenzene, xylene, and hexane (BTEXH). Our goal is to estimate exposure levels to these toxic chemicals for groups of oil spill workers in the study (hereafter called exposure groups, EGs) with likely comparable exposure distributions. A large number of air measurements were collected, but many EGs are characterized by datasets with a large percentage of censored measurements (below the analytic methods' limits of detection) and/or a limited number of measurements. We use THC for which there was less censoring to develop predictive linear models for specific BTEXH air exposures with higher degrees of censoring. We present a novel Bayesian hierarchical linear model that allows us to predict, for different EGs simultaneously, exposure levels of a second chemical while accounting for censoring in both THC and the chemical of interest. We illustrate the methodology by estimating exposure levels for several EGs on the Development Driller III, a rig vessel charged with drilling one of the relief wells. The model provided credible estimates in this example for geometric means, arithmetic means, variances, correlations, and regression coefficients for each group. This approach should be considered when estimating exposures in situations when multiple chemicals are correlated and have varying degrees of censoring. © The Author 2017

  6. Physiologically based pharmacokinetic toolkit to evaluate environmental exposures: Applications of the dioxin model to study real life exposures

    Energy Technology Data Exchange (ETDEWEB)

    Emond, Claude, E-mail: claude.emond@biosmc.com [BioSimulation Consulting Inc, Newark, DE (United States); Ruiz, Patricia; Mumtaz, Moiz [Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, Atlanta, GA (United States)

    2017-01-15

    Chlorinated dibenzo-p-dioxins (CDDs) are a series of mono- to octa-chlorinated homologous chemicals commonly referred to as polychlorinated dioxins. One of the most potent, well-known, and persistent member of this family is 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). As part of translational research to make computerized models accessible to health risk assessors, we present a Berkeley Madonna recoded version of the human physiologically based pharmacokinetic (PBPK) model used by the U.S. Environmental Protection Agency (EPA) in the recent dioxin assessment. This model incorporates CYP1A2 induction, which is an important metabolic vector that drives dioxin distribution in the human body, and it uses a variable elimination half-life that is body burden dependent. To evaluate the model accuracy, the recoded model predictions were compared with those of the original published model. The simulations performed with the recoded model matched well with those of the original model. The recoded model was then applied to available data sets of real life exposure studies. The recoded model can describe acute and chronic exposures and can be useful for interpreting human biomonitoring data as part of an overall dioxin and/or dioxin-like compounds risk assessment. - Highlights: • The best available dioxin PBPK model for interpreting human biomonitoring data is presented. • The original PBPK model was recoded from acslX to the Berkeley Madonna (BM) platform. • Comparisons were made of the accuracy of the recoded model with the original model. • The model is a useful addition to the ATSDR's BM based PBPK toolkit that supports risk assessors. • The application of the model to real-life exposure data sets is illustrated.

  7. Risk assessment of exposure to aflatoxin B1 and ochratoxin A through consumption of different Pistachio (Pistacia vera L.) cultivars collected from four geographical regions of Iran.

    Science.gov (United States)

    Taghizadeh, Seyedeh Faezeh; Rezaee, Ramin; Davarynejad, Gholamhossein; Asili, Javad; Nemati, Seyed Hossein; Goumenou, Marina; Tsakiris, Ioannis; Tsatsakis, Aristides M; Shirani, Kobra; Karimi, Gholamreza

    2018-07-01

    Iran is one of the main suppliers of pistachio for the European market accounting for over 90% of its demands; hence, efficient analytical methods are required for detection of mycotoxins contamination in pistachio kernels before exporting them. In this study, aflatoxin B1 (AFB1) and ochratoxin A (OTA) levels in five pistachio cultivars collected from four sites of Iran, were measured by HPLC. Based on the results, risk assessment for AFB1 and OTA residues was done. The highest mean concentrations of AFB1 and OTA were found in Ahmad-aghaei (4.33 and 2.19 ng/g, respectively) and Akbari (4.08 and 1.943 ng/g, respectively) cultivars from Rafsanjan, Iran. Even the highest concentrations of AFB1 and OTA in analyzed samples were lower than the corresponding maximum limits set by EU authorities. The hazard index (HI) value for consumers of Iranian pistachio is below one. It could be concluded that consumption of pistachio cultivated in these regions poses no health risk of mycotoxins exposure. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. A study of spatial resolution in pollution exposure modelling

    Directory of Open Access Journals (Sweden)

    Gustafsson Susanna

    2007-06-01

    Full Text Available Abstract Background This study is part of several ongoing projects concerning epidemiological research into the effects on health of exposure to air pollutants in the region of Scania, southern Sweden. The aim is to investigate the optimal spatial resolution, with respect to temporal resolution, for a pollutant database of NOx-values which will be used mainly for epidemiological studies with durations of days, weeks or longer periods. The fact that a pollutant database has a fixed spatial resolution makes the choice critical for the future use of the database. Results The results from the study showed that the accuracy between the modelled concentrations of the reference grid with high spatial resolution (100 m, denoted the fine grid, and the coarser grids (200, 400, 800 and 1600 meters improved with increasing spatial resolution. When the pollutant values were aggregated in time (from hours to days and weeks the disagreement between the fine grid and the coarser grids were significantly reduced. The results also illustrate a considerable difference in optimal spatial resolution depending on the characteristic of the study area (rural or urban areas. To estimate the accuracy of the modelled values comparison were made with measured NOx values. The mean difference between the modelled and the measured value were 0.6 μg/m3 and the standard deviation 5.9 μg/m3 for the daily difference. Conclusion The choice of spatial resolution should not considerably deteriorate the accuracy of the modelled NOx values. Considering the comparison between modelled and measured values we estimate that an error due to coarse resolution greater than 1 μg/m3 is inadvisable if a time resolution of one day is used. Based on the study of different spatial resolutions we conclude that for urban areas a spatial resolution of 200–400 m is suitable; and for rural areas the spatial resolution could be coarser (about 1600 m. This implies that we should develop a pollutant

  9. Exposure Modeling for Polychlorinated Biphenyls in School Buildings

    Science.gov (United States)

    There is limited research on characterizing exposures from PCB sources for occupants of school buildings. PCB measurement results from six schools were used to estimate potential exposure distributions for four age groups (4-5, 6-10, 11-14, 14-18 year-olds) using the Stochastic...

  10. Air Pollution Exposure Modeling for Epidemiology Studies and Public Health

    Science.gov (United States)

    Air pollution epidemiology studies of ambient fine particulate matter (PM2.5) often use outdoor concentrations as exposure surrogates. These surrogates can induce exposure error since they do not account for (1) time spent indoors with ambient PM2.5 levels attenuated from outdoor...

  11. Modelling of occupational exposure to inhalable nickel compounds.

    Science.gov (United States)

    Kendzia, Benjamin; Pesch, Beate; Koppisch, Dorothea; Van Gelder, Rainer; Pitzke, Katrin; Zschiesche, Wolfgang; Behrens, Thomas; Weiss, Tobias; Siemiatycki, Jack; Lavoué, Jerome; Jöckel, Karl-Heinz; Stamm, Roger; Brüning, Thomas

    2017-07-01

    The aim of this study was to estimate average occupational exposure to inhalable nickel (Ni) using the German exposure database MEGA. This database contains 8052 personal measurements of Ni collected between 1990 and 2009 in adjunct with information on the measurement and workplace conditions. The median of all Ni concentrations was 9 μg/m 3 and the 95th percentile was 460 μg/m 3 . We predicted geometric means (GMs) for welders and other occupations centered to 1999. Exposure to Ni in welders is strongly influenced by the welding process applied and the Ni content of the used welding materials. Welding with consumable electrodes of high Ni content (>30%) was associated with 10-fold higher concentrations compared with those with a low content (exposure levels (GMs ≥20 μg/m 3 ) were observed in gas metal and shielded metal arc welders using welding materials with high Ni content, in metal sprayers, grinders and forging-press operators, and in the manufacture of batteries and accumulators. The exposure profiles are useful for exposure assessment in epidemiologic studies as well as in industrial hygiene. Therefore, we recommend to collect additional exposure-specific information in addition to the job title in community-based studies when estimating the health risks of Ni exposure.

  12. PAH exposure through soil ingestion: Combining digestion models and bioassays

    Energy Technology Data Exchange (ETDEWEB)

    Wiele, T.R. van de; Verstraete, W. [Ghent University (BE).Laboratory Microbial Ecology and Technology (LabMET); Siciliano, S.D. [University of Saskatchewan (Canada). Department of Soil Science

    2003-07-01

    Exposure to environmental contaminants through soil ingestion is an important issue in current health risk assessment. Polycyclic aromatic hydrocarbons (PAH) or their metabolites pose risks to humans due to their toxic, mutagenic, carcinogenic or even (anti)estrogenic properties. PAH mobilization from a soil matrix (49.1{+-}1.5 mg PAH/kg DW) was assessed using a Simulator of the Human Intestinal Microbial Ecosystem (SHIME). PAH GC-MS analysis was performed on the pellet and supernatant of SHIME digests and gave 101, 92, 89 and 97% recovery for water, stomach, duodenal and colon digests, respectively. PAH release was highest for the water extract (0.51%) and the stomach digestion (0.44%). Lower mobilized fractions in the duodenum (0.13%) and colon (0.30%) digests could be attributed to PAH complexation with bile salts, dissolved organic matter or colon microbiota. The digestion model provides us with relevant information to what extent soil bound PAHs are mobilized in the gastrointestinal tract and thus reach the gut wall, prior to absorption. (orig.)

  13. Minimizing Surface Exposure to Climate Extremity in Coastal Megacities by Structure Remodelling using Integral Geographic Information System: Lessons from Greater Mumbai Metropolitan

    Science.gov (United States)

    Tiwari, A.

    2016-12-01

    Coastal metropolitans in South Asia represent the most densely populated and congested urban spaces ranking among the largest urban settlements of the planet. These megacities are characterized by inadequate infrastructure, lack of mitigation tools, and weak resilience of urban ecosystems. Additionally, climate change has increased vulnerability of poor and marginalized population living in rapidly growing coastal megacities to increased frequency, severity and intensity of extreme weather events. This has adversely affected local counter strategies and adaptation tools, transforming such events into hazards with the inability to respond and mitigate. Study aimed to develop a participatory framework for risk reduction in Greater Mumbai Metropolitan by Structure Remodeling (SR) in integral GIS. Research utilized terrain analysis tools and vulnerability mapping, and identified risk susceptible fabric and checked its scope for SR without: 1.adding to its (often) complex fragmentation, and 2.without interference with the ecosystem services accommodated by it. Surfaces available included paved ground, streetscapes commercial facades, rooftops,public spaces, open as well as dark spaces. Remodeling altered certain characteristics in the intrinsic or extrinsic cross-section profile or in both (if suitable) with infrastructure measures (grey, green, blue) that collectively involved ecosystem services and maintained natural hydrological connection. This method fairly reduced exposure of vulnerable surface and minimized risk to achieve extremity-neutral state. Harmonizing with public perception and incorporating priorities of local authorities, the method is significant as it rises above the fundamental challenges arising during management of (often) conflicting perspectives and interests of multiplicity of stakeholders involved at various levels in urban climate governance while ensuring inclusive solutions with reduced vulnerability and increased resilience. Additionally

  14. Bayesian geostatistical modelling of malaria and lymphatic filariasis infections in Uganda: predictors of risk and geographical patterns of co-endemicity

    Directory of Open Access Journals (Sweden)

    Pedersen Erling M

    2011-10-01

    Full Text Available Abstract Background In Uganda, malaria and lymphatic filariasis (causative agent Wuchereria bancrofti are transmitted by the same vector species of Anopheles mosquitoes, and thus are likely to share common environmental risk factors and overlap in geographical space. In a comprehensive nationwide survey in 2000-2003 the geographical distribution of W. bancrofti was assessed by screening school-aged children for circulating filarial antigens (CFA. Concurrently, blood smears were examined for malaria parasites. In this study, the resultant malariological data are analysed for the first time and the CFA data re-analysed in order to identify risk factors, produce age-stratified prevalence maps for each infection, and to define the geographical patterns of Plasmodium sp. and W. bancrofti co-endemicity. Methods Logistic regression models were fitted separately for Plasmodium sp. and W. bancrofti within a Bayesian framework. Models contained covariates representing individual-level demographic effects, school-level environmental effects and location-based random effects. Several models were fitted assuming different random effects to allow for spatial structuring and to capture potential non-linearity in the malaria- and filariasis-environment relation. Model-based risk predictions at unobserved locations were obtained via Bayesian predictive distributions for the best fitting models. Maps of predicted hyper-endemic malaria and filariasis were furthermore overlaid in order to define areas of co-endemicity. Results Plasmodium sp. parasitaemia was found to be highly endemic in most of Uganda, with an overall population adjusted parasitaemia risk of 47.2% in the highest risk age-sex group (boys 5-9 years. High W. bancrofti prevalence was predicted for a much more confined area in northern Uganda, with an overall population adjusted infection risk of 7.2% in the highest risk age-group (14-19 year olds. Observed overall prevalence of individual co

  15. A study on the use and modeling of geographical information system for combating forest crimes: an assessment of crimes in the eastern Mediterranean forests.

    Science.gov (United States)

    Pak, Mehmet; Gülci, Sercan; Okumuş, Arif

    2018-01-06

    This study focuses on the geo-statistical assessment of spatial estimation models in forest crimes. Used widely in the assessment of crime and crime-dependent variables, geographic information system (GIS) helps the detection of forest crimes in rural regions. In this study, forest crimes (forest encroachment, illegal use, illegal timber logging, etc.) are assessed holistically and modeling was performed with ten different independent variables in GIS environment. The research areas are three Forest Enterprise Chiefs (Baskonus, Cinarpinar, and Hartlap) affiliated to Kahramanmaras Forest Regional Directorate in Kahramanmaras. An estimation model was designed using ordinary least squares (OLS) and geographically weighted regression (GWR) methods, which are often used in spatial association. Three different models were proposed in order to increase the accuracy of the estimation model. The use of variables with a variance inflation factor (VIF) value of lower than 7.5 in Model I and lower than 4 in Model II and dependent variables with significant robust probability values in Model III are associated with forest crimes. Afterwards, the model with the lowest corrected Akaike Information Criterion (AIC c ), and the highest R 2 value was selected as the comparison criterion. Consequently, Model III proved to be more accurate compared to other models. For Model III, while AIC c was 328,491 and R 2 was 0.634 for OLS-3 model, AIC c was 318,489 and R 2 was 0.741 for GWR-3 model. In this respect, the uses of GIS for combating forest crimes provide different scenarios and tangible information that will help take political and strategic measures.

  16. Mathematical model quantifies multiple daylight exposure and burial events for rock surfaces using luminescence dating

    International Nuclear Information System (INIS)

    Freiesleben, Trine; Sohbati, Reza; Murray, Andrew; Jain, Mayank; Al Khasawneh, Sahar; Hvidt, Søren; Jakobsen, Bo

    2015-01-01

    Interest in the optically stimulated luminescence (OSL) dating of rock surfaces has increased significantly over the last few years, as the potential of the method has been explored. It has been realized that luminescence-depth profiles show qualitative evidence for multiple daylight exposure and burial events. To quantify both burial and exposure events a new mathematical model is developed by expanding the existing models of evolution of luminescence–depth profiles, to include repeated sequential events of burial and exposure to daylight. This new model is applied to an infrared stimulated luminescence-depth profile from a feldspar-rich granite cobble from an archaeological site near Aarhus, Denmark. This profile shows qualitative evidence for multiple daylight exposure and burial events; these are quantified using the model developed here. By determining the burial ages from the surface layer of the cobble and by fitting the new model to the luminescence profile, it is concluded that the cobble was well bleached before burial. This indicates that the OSL burial age is likely to be reliable. In addition, a recent known exposure event provides an approximate calibration for older daylight exposure events. This study confirms the suggestion that rock surfaces contain a record of exposure and burial history, and that these events can be quantified. The burial age of rock surfaces can thus be dated with confidence, based on a knowledge of their pre-burial light exposure; it may also be possible to determine the length of a fossil exposure, using a known natural light exposure as calibration. - Highlights: • Evidence for multiple exposure and burial events in the history of a single cobble. • OSL rock surface dating model improved to include multiple burial/exposure cycles. • Application of the new model quantifies burial and exposure events.

  17. Modelling ecological and human exposure to POPs in Venice lagoon - Part II: Quantitative uncertainty and sensitivity analysis in coupled exposure models.

    Science.gov (United States)

    Radomyski, Artur; Giubilato, Elisa; Ciffroy, Philippe; Critto, Andrea; Brochot, Céline; Marcomini, Antonio

    2016-11-01

    The study is focused on applying uncertainty and sensitivity analysis to support the application and evaluation of large exposure models where a significant number of parameters and complex exposure scenarios might be involved. The recently developed MERLIN-Expo exposure modelling tool was applied to probabilistically assess the ecological and human exposure to PCB 126 and 2,3,7,8-TCDD in the Venice lagoon (Italy). The 'Phytoplankton', 'Aquatic Invertebrate', 'Fish', 'Human intake' and PBPK models available in MERLIN-Expo library were integrated to create a specific food web to dynamically simulate bioaccumulation in various aquatic species and in the human body over individual lifetimes from 1932 until 1998. MERLIN-Expo is a high tier exposure modelling tool allowing propagation of uncertainty on the model predictions through Monte Carlo simulation. Uncertainty in model output can be further apportioned between parameters by applying built-in sensitivity analysis tools. In this study, uncertainty has been extensively addressed in the distribution functions to describe the data input and the effect on model results by applying sensitivity analysis techniques (screening Morris method, regression analysis, and variance-based method EFAST). In the exposure scenario developed for the Lagoon of Venice, the concentrations of 2,3,7,8-TCDD and PCB 126 in human blood turned out to be mainly influenced by a combination of parameters (half-lives of the chemicals, body weight variability, lipid fraction, food assimilation efficiency), physiological processes (uptake/elimination rates), environmental exposure concentrations (sediment, water, food) and eating behaviours (amount of food eaten). In conclusion, this case study demonstrated feasibility of MERLIN-Expo to be successfully employed in integrated, high tier exposure assessment. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Exposure opportunity models for Agent Orange, dioxin, and other military herbicides used in Vietnam, 1961-1971.

    Science.gov (United States)

    Stellman, Steven D; Stellman, Jeanne M

    2004-07-01

    Nearly 19.5 million gallons of herbicides were sprayed on the Republic of Vietnam between 1961 and 1971 for military purposes. Amounts of spray and patterns of applications are available in an electronic file called HERBS that contains records of 9141 defoliation missions, including detailed coordinates of US Air Force Ranch Hand aircraft flight paths, along with chemical agent and gallonage sprayed. Two classes of models for use in epidemiological and environmental studies that utilize the HERBS data for estimating relative exposure opportunity indices are presented: a discrete "hits" model that counts instances of proximity in time and space to known herbicide applications, and a continuous exposure opportunity index, E4, that takes into account type and amount of herbicide sprayed, distance from spray application, and time interval when exposure may have occurred. Both direct spraying and indirect exposure to herbicide (or dioxin) that may have remained in the local environment are considered, using a conservative first-order model for environmental disappearance. A correction factor for dermal versus respiratory routes of entry has been incorporated. E4 has a log-normal distribution that spans six orders of magnitude, thus providing a substantial amount of discrimination between sprayed and unsprayed areas. The models improve on earlier ones by making full use of the geometry of the HERBS spray flight paths of Ranch Hand aircraft. To the extent possible so many decades after the War, the models have been qualitatively validated by comparison with recent dioxin soil and biota samples from heavily contaminated areas of Vietnam, and quantitatively validated against adipose dioxin obtained in epidemiological studies of Vietnamese. These models are incorporated within a geographic information system (GIS) that may be used, as one would expect, to identify locations such as hamlets, villages, and military installations sprayed by herbicide. In a novel application

  19. The Potential Neurotoxic Effects of Low-Dose Sarin Exposure in a Guinea Pig Model

    Science.gov (United States)

    2002-01-01

    1 THE POTENTIAL NEUROTOXIC EFFECTS OF LOW-DOSE SARIN EXPOSURE IN A GUINEA PIG MODEL Melinda R. Roberson, PhD, Michelle B. Schmidt...Proving Ground, MD 21010 USA ABSTRACT This study is assessing the effects in guinea pigs of repeated low-dose exposure to the nerve...COVERED - 4. TITLE AND SUBTITLE The Potential Neurotoxic Effects Of Low-Dose Sarin Exposure In A Guinea Pig Model 5a. CONTRACT NUMBER 5b

  20. Stochastic modeling of near-field exposure to parabens in personal care products

    DEFF Research Database (Denmark)

    Csiszar, Susan A.; Ernstoff, Alexi; Fantke, Peter

    2017-01-01

    Exposure assessment is a key step in determining risks to chemicals in consumer goods, including personal care products (PCPs). Exposure models can be used to estimate exposures to chemicals in the absence of biomonitoring data and as tools in chemical risk prioritization and screening. We apply...... a PCP exposure model based on the product intake fraction (PiF), which is defined as the fraction of chemical in a product that is taken in by the exposed population, to estimate chemical intake based on physicochemical properties and PCP usage characteristics. The PiF can be used to estimate route...... and pathway-specific exposures during both the use and disposal stages of a product. As a case study, we stochastically quantified population level exposures to parabens in PCPs, and compared estimates with biomarker values. We estimated exposure based on the usage of PCPs in the female US population, taking...

  1. Vacuum System and Modeling for the Materials Plasma Exposure Experiment

    International Nuclear Information System (INIS)

    Lumsdaine, Arnold; Meitner, Steve; Graves, Van; Bradley, Craig; Stone, Chris

    2017-01-01

    Understanding the science of plasma-material interactions (PMI) is essential for the future development of fusion facilities. The design of divertors and first walls for the next generation of long-pulse fusion facilities, such as a Fusion Nuclear Science Facility (FNSF) or a DEMO, requires significant PMI research and development. In order to meet this need, a new linear plasma facility, the Materials Plasma Exposure Experiment (MPEX) is proposed, which will produce divertor relevant plasma conditions for these next generation facilities. The device will be capable of handling low activation irradiated samples and be able to remove and replace samples without breaking vacuum. A Target Exchange Chamber (TEC) which can be disconnected from the high field environment in order to perform in-situ diagnostics is planned for the facility as well. The vacuum system for MPEX must be carefully designed in order to meet the requirements of the different heating systems, and to provide conditions at the target similar to those expected in a divertor. An automated coupling-decoupling (“autocoupler”) system is designed to create a high vacuum seal, and will allow the TEC to be disconnected without breaking vacuum in either the TEC or the primary plasma materials interaction chamber. This autocoupler, which can be actuated remotely in the presence of the high magnetic fields, has been designed and prototyped, and shows robustness in a variety of conditions. The vacuum system has been modeled using a simplified finite element analysis, and indicates that the design goals for the pressures in key regions of the facility are achievable.

  2. Development of a Lethal Intranasal Exposure Model of Ebola Virus in the Cynomolgus Macaque

    Directory of Open Access Journals (Sweden)

    Kendra J. Alfson

    2017-10-01

    Full Text Available Ebola virus (EBOV is a filovirus that can cause Ebola virus disease (EVD. No approved vaccines or therapies exist for filovirus infections, despite an urgent need. The development and testing of effective countermeasures against EBOV requires use of animal models and a thorough understanding of how the model aligns with EVD in humans. The majority of published studies report outcomes of parenteral exposures for emulating needle stick transmission. However, based on data from EVD outbreaks, close contact exposures to infected bodily fluid seems to be one of the primary routes of EBOV transmission. Thus, further work is needed to develop models that represent mucosal exposure. To characterize the outcome of mucosal exposure to EBOV, cynomolgus macaques were exposed to EBOV via intranasal (IN route using the LMA® mucosal atomization device (LMA® MAD. For comparison, four non-human primates (NHPs were exposed to EBOV via intramuscular (IM route. This IN exposure model was uniformly lethal and correlated with a statistically significant delay in time to death when compared to exposure via the IM route. This more closely reflects the timeframes observed in human infections. An IN model of exposure offers an attractive alternative to other models as it can offer insight into the consequences of exposure via a mucosal surface and allows for screening countermeasures via a different exposure route.

  3. A Comparison of Item Exposure Control Procedures with the Generalized Partial Credit Model

    Science.gov (United States)

    Sanchez, Edgar Isaac

    2008-01-01

    To enhance test security of high stakes tests, it is vital to understand the way various exposure control strategies function under various IRT models. To that end the present dissertation focused on the performance of several exposure control strategies under the generalized partial credit model with an item pool of 100 and 200 items. These…

  4. A Comparison of Exposure Control Procedures in CAT Systems Based on Different Measurement Models for Testlets

    Science.gov (United States)

    Boyd, Aimee M.; Dodd, Barbara; Fitzpatrick, Steven

    2013-01-01

    This study compared several exposure control procedures for CAT systems based on the three-parameter logistic testlet response theory model (Wang, Bradlow, & Wainer, 2002) and Masters' (1982) partial credit model when applied to a pool consisting entirely of testlets. The exposure control procedures studied were the modified within 0.10 logits…

  5. Mapping and modelling the geographical distribution of soil-transmitted helminthiases in Peninsular Malaysia: implications for control approaches

    Directory of Open Access Journals (Sweden)

    Romano Ngui

    2014-05-01

    Full Text Available Soil-transmitted helminth (STH infections in Malaysia are still highly prevalent, especially in rural and remote communities. Complete estimations of the total disease burden in the country has not been performed, since available data are not easily accessible in the public domain. The current study utilised geographical information system (GIS to collate and map the distribution of STH infections from available empirical survey data in Peninsular Malaysia, highlighting areas where information is lacking. The assembled database, comprising surveys conducted between 1970 and 2012 in 99 different locations, represents one of the most comprehensive compilations of STH infections in the country. It was found that the geographical distribution of STH varies considerably with no clear pattern across the surveyed locations. Our attempt to generate predictive risk maps of STH infections on the basis of ecological limits such as climate and other environmental factors shows that the prevalence of Ascaris lumbricoides is low along the western coast and the southern part of the country, whilst the prevalence is high in the central plains and in the North. In the present study, we demonstrate that GIS can play an important role in providing data for the implementation of sustainable and effective STH control programmes to policy-makers and authorities in charge.

  6. Geographical information systems

    DEFF Research Database (Denmark)

    Möller, Bernd

    2004-01-01

    The chapter gives an introduction to Geographical Information Systems (GIS) with particular focus on their application within environmental management.......The chapter gives an introduction to Geographical Information Systems (GIS) with particular focus on their application within environmental management....

  7. Clinical and pathological manifestations of cardiovascular disease in rat models: the influence of acute ozone exposure

    Science.gov (United States)

    This paper shows that rat models of cardiovascular diseases have differential degrees of underlying pathologies at a young age. Rodent models of cardiovascular diseases (CVD) and metabolic disorders are used for examining susceptibility variations to environmental exposures. How...

  8. Modeling the Cumulative Effects of Social Exposures on Health: Moving beyond Disease-Specific Models

    Directory of Open Access Journals (Sweden)

    Heather L. White

    2013-03-01

    Full Text Available The traditional explanatory models used in epidemiology are “disease specific”, identifying risk factors for specific health conditions. Yet social exposures lead to a generalized, cumulative health impact which may not be specific to one illness. Disease-specific models may therefore misestimate social factors’ effects on health. Using data from the Canadian Community Health Survey and Canada 2001 Census we construct and compare “disease-specific” and “generalized health impact” (GHI models to gauge the negative health effects of one social exposure: socioeconomic position (SEP. We use logistic and multinomial multilevel modeling with neighbourhood-level material deprivation, individual-level education and household income to compare and contrast the two approaches. In disease-specific models, the social determinants under study were each associated with the health conditions of interest. However, larger effect sizes were apparent when outcomes were modeled as compound health problems (0, 1, 2, or 3+ conditions using the GHI approach. To more accurately estimate social exposures’ impacts on population health, researchers should consider a GHI framework.

  9. Geographic Media Literacy

    Science.gov (United States)

    Lukinbeal, Chris

    2014-01-01

    While the use of media permeates geographic research and pedagogic practice, the underlying literacies that link geography and media remain uncharted. This article argues that geographic media literacy incorporates visual literacy, information technology literacy, information literacy, and media literacy. Geographic media literacy is the ability…

  10. TREXMO: A Translation Tool to Support the Use of Regulatory Occupational Exposure Models.

    Science.gov (United States)

    Savic, Nenad; Racordon, Dimitri; Buchs, Didier; Gasic, Bojan; Vernez, David

    2016-10-01

    Occupational exposure models vary significantly in their complexity, purpose, and the level of expertise required from the user. Different parameters in the same model may lead to different exposure estimates for the same exposure situation. This paper presents a tool developed to deal with this concern-TREXMO or TRanslation of EXposure MOdels. TREXMO integrates six commonly used occupational exposure models, namely, ART v.1.5, STOFFENMANAGER(®) v.5.1, ECETOC TRA v.3, MEASE v.1.02.01, EMKG-EXPO-TOOL, and EASE v.2.0. By enabling a semi-automatic translation between the parameters of these six models, TREXMO facilitates their simultaneous use. For a given exposure situation, defined by a set of parameters in one of the models, TREXMO provides the user with the most appropriate parameters to use in the other exposure models. Results showed that, once an exposure situation and parameters were set in ART, TREXMO reduced the number of possible outcomes in the other models by 1-4 orders of magnitude. The tool should manage to reduce the uncertain entry or selection of parameters in the six models, improve between-user reliability, and reduce the time required for running several models for a given exposure situation. In addition to these advantages, registrants of chemicals and authorities should benefit from more reliable exposure estimates for the risk characterization of dangerous chemicals under Regulation, Evaluation, Authorisation and restriction of CHemicals (REACH). © The Author 2016. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

  11. Estimating Margin of Exposure to Thyroid Peroxidase Inhibitors Using High-Throughput in vitro Data, High-Throughput Exposure Modeling, and Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling

    Science.gov (United States)

    Leonard, Jeremy A.; Tan, Yu-Mei; Gilbert, Mary; Isaacs, Kristin; El-Masri, Hisham

    2016-01-01

    Some pharmaceuticals and environmental chemicals bind the thyroid peroxidase (TPO) enzyme and disrupt thyroid hormone production. The potential for TPO inhibition is a function of both the binding affinity and concentration of the chemical within the thyroid gland. The former can be determined through in vitro assays, and the latter is influenced by pharmacokinetic properties, along with environmental exposure levels. In this study, a physiologically based pharmacokinetic (PBPK) model was integrated with a pharmacodynamic (PD) model to establish internal doses capable of inhibiting TPO in relation to external exposure levels predicted through exposure modeling. The PBPK/PD model was evaluated using published serum or thyroid gland chemical concentrations or circulating thyroxine (T4) and triiodothyronine (T3) hormone levels measured in rats and humans. After evaluation, the model was used to estimate human equivalent intake doses resulting in reduction of T4 and T3 levels by 10% (ED10) for 6 chemicals of varying TPO-inhibiting potencies. These chemicals were methimazole, 6-propylthiouracil, resorcinol, benzophenone-2, 2-mercaptobenzothiazole, and triclosan. Margin of exposure values were estimated for these chemicals using the ED10 and predicted population exposure levels for females of child-bearing age. The modeling approach presented here revealed that examining hazard or exposure alone when prioritizing chemicals for risk assessment may be insufficient, and that consideration of pharmacokinetic properties is warranted. This approach also provides a mechanism for integrating in vitro data, pharmacokinetic properties, and exposure levels predicted through high-throughput means when interpreting adverse outcome pathways based on biological responses. PMID:26865668

  12. Modeling Of In-Vehicle Human Exposure to Ambient Fine Particulate Matter

    Science.gov (United States)

    Liu, Xiaozhen; Frey, H. Christopher

    2012-01-01

    A method for estimating in-vehicle PM2.5 exposure as part of a scenario-based population simulation model is developed and assessed. In existing models, such as the Stochastic Exposure and Dose Simulation model for Particulate Matter (SHEDS-PM), in-vehicle exposure is estimated using linear regression based on area-wide ambient PM2.5 concentration. An alternative modeling approach is explored based on estimation of near-road PM2.5 concentration and an in-vehicle mass balance. Near-road PM2.5 concentration is estimated using a dispersion model and fixed site monitor (FSM) data. In-vehicle concentration is estimated based on air exchange rate and filter efficiency. In-vehicle concentration varies with road type, traffic flow, windspeed, stability class, and ventilation. Average in-vehicle exposure is estimated to contribute 10 to 20 percent of average daily exposure. The contribution of in-vehicle exposure to total daily exposure can be higher for some individuals. Recommendations are made for updating exposure models and implementation of the alternative approach. PMID:23101000

  13. Simulation of Population-Based Commuter Exposure to NO2 Using Different Air Pollution Models

    Directory of Open Access Journals (Sweden)

    Martina S. Ragettli

    2014-05-01

    Full Text Available We simulated commuter routes and long-term exposure to traffic-related air pollution during commute in a representative population sample in Basel (Switzerland, and evaluated three air pollution models with different spatial resolution for estimating commute exposures to nitrogen dioxide (NO2 as a marker of long-term exposure to traffic-related air pollution. Our approach includes spatially and temporally resolved data on actual commuter routes, travel modes and three air pollution models. Annual mean NO2 commuter exposures were similar between models. However, we found more within-city and within-subject variability in annual mean (±SD NO2 commuter exposure with a high resolution dispersion model (40 ± 7 µg m−3, range: 21–61 than with a dispersion model with a lower resolution (39 ± 5 µg m−3; range: 24–51, and a land use regression model (41 ± 5 µg m−3; range: 24–54. Highest median cumulative exposures were calculated along motorized transport and bicycle routes, and the lowest for walking. For estimating commuter exposure within a city and being interested also in small-scale variability between roads, a model with a high resolution is recommended. For larger scale epidemiological health assessment studies, models with a coarser spatial resolution are likely sufficient, especially when study areas include suburban and rural areas.

  14. An assessment of geographical distribution of different plant functional types over North America simulated using the CLASS-CTEM modelling framework

    Science.gov (United States)

    Shrestha, Rudra K.; Arora, Vivek K.; Melton, Joe R.; Sushama, Laxmi

    2017-10-01

    The performance of the competition module of the CLASS-CTEM (Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model) modelling framework is assessed at 1° spatial resolution over North America by comparing the simulated geographical distribution of its plant functional types (PFTs) with two observation-based estimates. The model successfully reproduces the broad geographical distribution of trees, grasses and bare ground although limitations remain. In particular, compared to the two observation-based estimates, the simulated fractional vegetation coverage is lower in the arid southwest North American region and higher in the Arctic region. The lower-than-observed simulated vegetation coverage in the southwest region is attributed to lack of representation of shrubs in the model and plausible errors in the observation-based data sets. The observation-based data indicate vegetation fractional coverage of more than 60 % in this arid region, despite only 200-300 mm of precipitation that the region receives annually, and observation-based leaf area index (LAI) values in the region are lower than one. The higher-than-observed vegetation fractional coverage in the Arctic is likely due to the lack of representation of moss and lichen PFTs and also likely because of inadequate representation of permafrost in the model as a result of which the C3 grass PFT performs overly well in the region. The model generally reproduces the broad spatial distribution and the total area covered by the two primary tree PFTs (needleleaf evergreen trees, NDL-EVG; and broadleaf cold deciduous trees, BDL-DCD-CLD) reasonably well. The simulated fractional coverage of tree PFTs increases after the 1960s in response to the CO2 fertilization effect and climate warming. Differences between observed and simulated PFT coverages highlight model limitations and suggest that the inclusion of shrubs, and moss and lichen PFTs, and an adequate representation of permafrost will help improve

  15. An assessment of geographical distribution of different plant functional types over North America simulated using the CLASS–CTEM modelling framework

    Directory of Open Access Journals (Sweden)

    R. K. Shrestha

    2017-10-01

    Full Text Available The performance of the competition module of the CLASS–CTEM (Canadian Land Surface Scheme and Canadian Terrestrial Ecosystem Model modelling framework is assessed at 1° spatial resolution over North America by comparing the simulated geographical distribution of its plant functional types (PFTs with two observation-based estimates. The model successfully reproduces the broad geographical distribution of trees, grasses and bare ground although limitations remain. In particular, compared to the two observation-based estimates, the simulated fractional vegetation coverage is lower in the arid southwest North American region and higher in the Arctic region. The lower-than-observed simulated vegetation coverage in the southwest region is attributed to lack of representation of shrubs in the model and plausible errors in the observation-based data sets. The observation-based data indicate vegetation fractional coverage of more than 60 % in this arid region, despite only 200–300 mm of precipitation that the region receives annually, and observation-based leaf area index (LAI values in the region are lower than one. The higher-than-observed vegetation fractional coverage in the Arctic is likely due to the lack of representation of moss and lichen PFTs and also likely because of inadequate representation of permafrost in the model as a result of which the C3 grass PFT performs overly well in the region. The model generally reproduces the broad spatial distribution and the total area covered by the two primary tree PFTs (needleleaf evergreen trees, NDL-EVG; and broadleaf cold deciduous trees, BDL-DCD-CLD reasonably well. The simulated fractional coverage of tree PFTs increases after the 1960s in response to the CO2 fertilization effect and climate warming. Differences between observed and simulated PFT coverages highlight model limitations and suggest that the inclusion of shrubs, and moss and lichen PFTs, and an adequate representation of

  16. ConsExpo - Consumer Exposure and Uptake Models -Program Manual

    NARCIS (Netherlands)

    Delmaar JE; Park MVDZ; Engelen JGM van; SIR

    2006-01-01

    This report provides guidance to the use of ConsExpo 4.0, successor to ConsExpo 3.0, a computer program that was developed to assist in the exposure assessment of compounds in non-food consumer products. The wide range of available consumer products is associated with an even wider variation in

  17. Mathematical Models of Human Hematopoiesis Following Acute Radiation Exposure

    Science.gov (United States)

    2014-05-01

    response of 11 subjects from Chernobyl 1986 . . . . . . 104 B.8 Chernobyl case studies: Platelet data . . . . . . . . . . . . . . . . . . . . . . 105 B...9 Chernobyl case studies: Granulocyte data . . . . . . . . . . . . . . . . . . . 106 B.10 Chernobyl case studies: Lymphocyte data...information for use in nuclear disaster preparedness planning. Understanding how biological systems change after radiation exposure provides insight on the

  18. Determining the validity of exposure models for environmental epidemiology : predicting electromagnetic fields from mobile phone base stations

    NARCIS (Netherlands)

    Beekhuizen, Johan|info:eu-repo/dai/nl/34472641X

    2014-01-01

    One of the key challenges in environmental epidemiology is the exposure assessment of large populations. Spatial exposure models have been developed that predict exposure to the pollutant of interest for large study sizes. However, the validity of these exposure models is often unknown. In this

  19. Modeling of groundwater potential of the sub-basin of Siriri river, Sergipe state, Brazil, based on Geographic Information System and Remote Sensing

    Directory of Open Access Journals (Sweden)

    Washington Franca Rocha

    2011-08-01

    Full Text Available The use of Geographic Information System (GIS and Remote Sensing for modeling groundwater potential give support for the analysis and decision-making processes about water resource management in watersheds. The objective of this work consisted in modeling the groundwater water potential of Siriri river sub-basin, Sergipe state, based on its natural environment (soil, land use, slope, drainage density, lineament density, rainfall and geology using Remote Sensing and Geographic Information System as an integration environment. The groundwater potential map was done using digital image processing procedures of ENVI 4.4 software and map algebra of ArcGIS 9.3®. The Analytical Hierarchy Method was used for modeling the weights definition of the different criteria (maps. Loads and weights of the different classes were assigned to each map according to their influence on the overall objective of the work. The integration of these maps in a GIS environment and the AHP technique application allowed the development of the groundwater potential map in five classes: very low, low, moderate, high, very high. The average flow rates of wells confirm the potential of aquifers Sapucari, Barriers and Maruim since they are the most exploited in this sub-basin, with average flows of 78,113 L/h, 19,332 L/h and 12,085 L/h, respectively.

  20. Bisphenol A induces steatosis in HepaRG cells using a model of perinatal exposure

    OpenAIRE

    Bucher , Simon; Jalili , Pégah; Le Guillou , Dounia; Begriche , Karima; Rondel , Karine; Martinais , Sophie; Zalko , Daniel; Corlu , Anne; Robin , Marie-Anne; Fromenty , Bernard

    2017-01-01

    International audience; Human exposure to bisphenol A (BPA) could favor obesity and related metabolic disorders such as hepatic steatosis. Investigations in rodents have shown that these deleterious effects are observed not only when BPA is administered during the adult life but also with different protocols of perinatal exposure. Whether perinatal BPA exposure could pose a risk in human is currently unknown, and thus appropriate in vitro models could be important to tackle this major issue. ...

  1. CalTOX, a multimedia total exposure model for hazardous-waste sites

    International Nuclear Information System (INIS)

    McKone, T.E.

    1993-06-01

    CalTOX has been developed as a spreadsheet model to assist in health-risk assessments that address contaminated soils and the contamination of adjacent air, surface water, sediments, and ground water. The modeling effort includes a multimedia transport and transformation model, exposure scenario models, and efforts to quantify and reduce uncertainty in multimedia, multiple-pathway exposure models. This report provides an overview of the CalTOX model components, lists the objectives of the model, describes the philosophy under which the model was developed, identifies the chemical classes for which the model can be used, and describes critical sensitivities and uncertainties. The multimedia transport and transformation model is a dynamic model that can be used to assess time-varying concentrations of contaminants introduced initially to soil layers or for contaminants released continuously to air or water. This model assists the user in examining how chemical and landscape properties impact both the ultimate route and quantity of human contact. Multimedia, multiple pathway exposure models are used in the CalTOX model to estimate average daily potential doses within a human population in the vicinity of a hazardous substances release site. The exposure models encompass twenty-three exposure pathways. The exposure assessment process consists of relating contaminant concentrations in the multimedia model compartments to contaminant concentrations in the media with which a human population has contact (personal air, tap water, foods, household dusts soils, etc.). The average daily dose is the product of the exposure concentrations in these contact media and an intake or uptake factor that relates the concentrations to the distributions of potential dose within the population

  2. Mathematical model quantifies multiple daylight exposure and burial events for rock surfaces using luminescence dating

    DEFF Research Database (Denmark)

    Freiesleben, Trine Holm; Sohbati, Reza; Murray, Andrew

    2015-01-01

    Interest in the optically stimulated luminescence (OSL) dating of rock surfaces has increased significantly over the last few years, as the potential of the method has been explored. It has been realized that luminescence-depth profiles show qualitative evidence for multiple daylight exposure...... and burial events. To quantify both burial and exposure events a new mathematical model is developed by expanding the existing models of evolution of luminescenceedepth profiles, to include repeated sequential events of burial and exposure to daylight. This new model is applied to an infrared stimulated...... events. This study confirms the suggestion that rock surfaces contain a record of exposure and burial history, and that these events can be quantified. The burial age of rock surfaces can thus be dated with confidence, based on a knowledge of their pre-burial light exposure; it may also be possible...

  3. Simulation model of lung cancer incidence related to smoking and radon daughter exposure

    International Nuclear Information System (INIS)

    Stolowijk, J.A.J.

    1990-01-01

    A mathematical model of lung cancer and radon daughter exposure is presented. It is aimed to provide a quantitative estimate in the form of dose-effect relationship. The nature of the cigarette smoking and radon exposure interaction it is shown to be a multiplicative or sub-multiplicative function rather than a simpler model in which the effect of the two exposures would be summed. The model was written in the SAS programming language. An annotated listing of the program is given. 4 refs

  4. Use of biocidal products (insect sprays and electro-vaporizer) in indoor areas--exposure scenarios and exposure modeling.

    Science.gov (United States)

    Berger-Preiss, Edith; Koch, Wolfgang; Gerling, Susanne; Kock, Heiko; Appel, Klaus E

    2009-09-01

    Five commercially available insect sprays were applied in a model room. Spraying was performed in accordance with the manufacturers' instructions and in an overdosed manner in order to simulate worst-case conditions or an unforeseeable misuse. In addition, we examined electro-vaporizers. The Respicon aerosol monitoring system was applied to determine inhalation exposure. During normal spraying (10 seconds) and during the following 2-3 minutes, exposure concentrations ranged from 70 to 590 microg/m3 for the pyrethroids tetramethrin, d-phenothrin, cyfluthrin, bioallethrin, and the pyrethrins. Calculated inhalable doses were 2-16 microg. A concentration of approximately 850 microg chlorpyrifos/m(3) (inhalable dose: approximately 20 microg) was determined when the "Contra insect fly spray" was applied. Highest exposure concentrations (1100-2100 microg/m3) were measured for piperonyl butoxide (PBO), corresponding to an inhalation intake of 30-60microg. When simulating worst-case conditions, exposure concentrations of 200-3400microg/m3 and inhalable doses of 10-210microg were determined for the various active substances. Highest concentrations (4800-8000 microg/m3) were measured for PBO (inhalable: 290-480 microg). By applying the electro-vaporizer "Nexa Lotte" plug-in mosquito killer concentrations for d-allethrin were in the range of 5-12microg/m3 and 0.5-2 microg/m3 for PBO while with the "Paral" plug-in mosquito killer concentrations of 0.4-5microg/m3 for pyrethrins and 1-7 microg/m3 for PBO were measured. Potential dermal exposures were determined using exposure pads. Between 80 and 1000microg active substance (tetramethrin, phenothrin, cyfluthrin, bioallethrin, pyrethrins, chlorpyrifos) were deposited on the clothing of the total body surface area of the spray user. Highest levels (up to 3000 microg) were determined for PBO. Worst-case uses of the sprays led to 5-9 times higher concentrations. Also a 2-hour stay nearby an operating electro-vaporizer led to a

  5. Using geographic information systems

    International Nuclear Information System (INIS)

    Winsor, R.W.

    1997-01-01

    A true Geographic Information System (GIS) is a computer mapping system with spatial analysis ability and cartographic accuracy that will offer many different projections. GIS has evolved to become an everyday tool for a wide range of users including oil companies, worldwide. Other systems are designed to allow oil and gas companies to keep their upstream data in the same format. Among these are the Public Petroleum Data Model developed by Gulf Canada, Digitech and Applied Terravision Systems of Calgary, the system developed and marketed by the Petrotechnical Open Software Corporation in the United States, and the Mercury projects by IBM. These have been developed in an effort to define an industry standard. The advantages and disadvantages of open and closed systems were discussed. Factors to consider when choosing a GIS system such as overall performance, area of use and query complexity, were reviewed. 3 figs

  6. Probabilistic estimation of residential air exchange rates for population-based human exposure modeling

    Science.gov (United States)

    Residential air exchange rates (AERs) are a key determinant in the infiltration of ambient air pollution indoors. Population-based human exposure models using probabilistic approaches to estimate personal exposure to air pollutants have relied on input distributions from AER meas...

  7. Multi-pathway exposure modelling of chemicals in cosmetics with application to shampoo

    DEFF Research Database (Denmark)

    Ernstoff, Alexi S.; Fantke, Peter; Csiszar, Susan A.

    2016-01-01

    We present a novel multi-pathway, mass balance based, fate and exposure model compatible with life cycle and high-throughput screening assessments of chemicals in cosmetic products. The exposures through product use as well as post-use emissions and environmental media were quantified based...

  8. Multi-pathway exposure modelling of chemicals in cosmetics with application to shampoo

    Science.gov (United States)

    We present a novel multi-pathway, mass balance based, fate and exposure model compatible with life cycle and high-throughput screening assessments of chemicals in cosmetic products. The exposures through product use as well as post-use emissions and environmental media were quant...

  9. Harmonization of future needs for dermal exposure assessment and modeling : a workshop report

    NARCIS (Netherlands)

    Marquart, H.; Maidment, S.; Mcclaflin, J.L.; Fehrenbacher, M.C.

    2001-01-01

    Dermal exposure assessment and modeling is still in early phases of development. This article presents the results of a workshop organized to harmonize the future needs in this field. Methods for dermal exposure assessment either assess the mass of contaminant that is transferred to the skin, or the

  10. EPA's SHEDS-multimedia model: children's cumulative pyrethroid exposure estimates and evaluation against NHANES biomarker data

    Science.gov (United States)

    The U.S. EPA's SHEDS-Multimedia model was applied to enhance the understanding of children's exposures and doses to multiple pyrethroid pesticides, including major contributing chemicals and pathways. This paper presents combined dietary and residential exposure estimates and cum...

  11. An Exploratory Study: Assessment of Modeled Dioxin Exposure in Ceramic Art Studios (Final Report, 2008)

    Science.gov (United States)

    EPA announced the availability of the final report, An Exploratory Study: Assessment of Modeled Dioxin Exposure in Ceramic Art Studios. This report investigates the potential dioxin exposure to artists/hobbyists who use ball clay to make pottery and related products. Derm...

  12. A framework for widespread replication of a highly spatially resolved childhood lead exposure risk model.

    Science.gov (United States)

    Kim, Dohyeong; Galeano, M Alicia Overstreet; Hull, Andrew; Miranda, Marie Lynn

    2008-12-01

    Preventive approaches to childhood lead poisoning are critical for addressing this longstanding environmental health concern. Moreover, increasing evidence of cognitive effects of blood lead levels system-based childhood lead exposure risk models, especially if executed at highly resolved spatial scales, can help identify children most at risk of lead exposure, as well as prioritize and direct housing and health-protective intervention programs. However, developing highly resolved spatial data requires labor-and time-intensive geocoding and analytical processes. In this study we evaluated the benefit of increased effort spent geocoding in terms of improved performance of lead exposure risk models. We constructed three childhood lead exposure risk models based on established methods but using different levels of geocoded data from blood lead surveillance, county tax assessors, and the 2000 U.S. Census for 18 counties in North Carolina. We used the results to predict lead exposure risk levels mapped at the individual tax parcel unit. The models performed well enough to identify high-risk areas for targeted intervention, even with a relatively low level of effort on geocoding. This study demonstrates the feasibility of widespread replication of highly spatially resolved childhood lead exposure risk models. The models guide resource-constrained local health and housing departments and community-based organizations on how best to expend their efforts in preventing and mitigating lead exposure risk in their communities.

  13. Geographical information system based model of land suitability for good yield of rice in prachuap khiri khan province, thailand

    International Nuclear Information System (INIS)

    Hussain, W.; Sohaib, O.

    2012-01-01

    Correct assessment of land is a major issue in agricultural sector to use possible capability of any land, to raise cultivation and production of rice. Geographical Information System (GIS) provides broad techniques for suitable land classifications. This study is GIS based on land suitability analysis for rice farming in Prachuap Khiri Khan Province, Thailand, where the main livelihood of people is rice farming. This analysis was conducted considering the relationship of rice production with various data layers of elevation, slope, soil pH, rainfall, fertilizer use and land use. ArcView GIS 3.2 software is used to consider each layer according to related data to weight every coefficient, ranking techniques are used. It was based on determining correlation of rice production and these variables. This analysis showed a positive correlation with these variables in varying degrees depending on the magnitude and quality of these factors. By combining both data layers of GIS and weighted linear combination, various suitable lands have been developed for cultivation of rice. Integrated suitable assessment map and current land were compared to find suitable land in Prachuap Khiri Khan Province of Thailand. As a result of this comparison, we get a land which is suitable for optimum utilization for rice production in Prachuap Khiri Khan Province. (author)

  14. Use of topographic and climatological models in a geographical data base to improve Landsat MSS classification for Olympic National Park

    Science.gov (United States)

    Cibula, William G.; Nyquist, Maurice O.

    1987-01-01

    An unsupervised computer classification of vegetation/landcover of Olympic National Park and surrounding environs was initially carried out using four bands of Landsat MSS data. The primary objective of the project was to derive a level of landcover classifications useful for park management applications while maintaining an acceptably high level of classification accuracy. Initially, nine generalized vegetation/landcover classes were derived. Overall classification accuracy was 91.7 percent. In an attempt to refine the level of classification, a geographic information system (GIS) approach was employed. Topographic data and watershed boundaries (inferred precipitation/temperature) data were registered with the Landsat MSS data. The resultant boolean operations yielded 21 vegetation/landcover classes while maintaining the same level of classification accuracy. The final classification provided much better identification and location of the major forest types within the park at the same high level of accuracy, and these met the project objective. This classification could now become inputs into a GIS system to help provide answers to park management coupled with other ancillary data programs such as fire management.

  15. Environmental tobacco smoke in designated smoking areas in the hospitality industry: exposure measurements, exposure modelling and policy assessment.

    Science.gov (United States)

    McNabola, A; Eyre, G J; Gill, L W

    2012-09-01

    Tobacco control policy has been enacted in many jurisdictions worldwide banning smoking in the workplace. In the hospitality sector many businesses such as bars, hotels and restaurants have installed designated smoking areas on their premises and allowance for such smoking areas has been made in the tobacco control legislation of many countries. An investigation was carried out into the level of exposure to environmental tobacco smoke (ETS) present in 8 pubs in Ireland which included designated smoking areas complying with two different definitions of a smoking area set out in Irish legislation. In addition, ETS exposure in a pub with a designated smoking area not in compliance with the legislation was also investigated. The results of this investigation showed that the two differing definitions of a smoking area present in pubs produced similar concentrations of benzene within smoking areas (5.1-5.4 μg/m(3)) but differing concentrations within the 'smoke-free' areas (1.42-3.01 μg/m(3)). Smoking areas in breach of legislative definitions were found to produce the highest levels of benzene in the smoking area (49.5 μg/m(3)) and 'smoke-free' area (7.68 μg/m(3)). 3D exposure modelling of hypothetical smoking areas showed that a wide range of ETS exposure concentrations were possible in smoking areas with the same floor area and same smoking rate but differing height to width and length to width ratios. The results of this investigation demonstrate that significant scope for improvement of ETS exposure concentrations in pubs and in smoking areas may exist by refining and improving the legislative definitions of smoking areas in law. Copyright © 2012 Elsevier Ltd. All rights reserved.

  16. Merging Models and Biomonitoring Data to Characterize Sources andPathways of Human Exposure to Organophosphorous Pesticides in the SalinasValley of California

    Energy Technology Data Exchange (ETDEWEB)

    McKone, Thomas E.; Castorina, Rosemary; Kuwabara, Yu; Harnly,Martha E.; Eskenazi, Brenda; Bradman, Asa

    2006-06-01

    By drawing on human biomonitoring data and limited environmental samples together with outputs from the CalTOX multimedia, multipathway source-to-dose model, we characterize cumulative intake of organophosphorous (OP) pesticides in an agricultural region of California. We assemble regional OP pesticide use, environmental sampling, and biological tissue monitoring data for a large and geographically dispersed population cohort of 592 pregnant Latina women in California (the CHAMACOS cohort). We then use CalTOX with regional pesticide usage data to estimate the magnitude and uncertainty of exposure and intake from local sources. We combine model estimates of intake from local sources with food intake based on national residue data to estimate for the CHAMACOS cohort cumulative median OP intake, which corresponds to expected levels of urinary dialkylphosphate (DAP) metabolite excretion for this cohort. From these results we develop premises about relative contributions from different sources and pathways of exposure. We evaluate these premises by comparing the magnitude and variation of DAPs in the CHAMACOS cohort with the whole U.S. population using data from the National Health and Nutrition Evaluation Survey (NHANES). This comparison supports the premise that in both populations diet is the common and dominant exposure pathway. Both the model results and biomarker comparison supports the observation that the CHAMACOS population has a statistically significant higher intake of OP pesticides that appears as an almost constant additional dose among all participants. We attribute the magnitude and small variance of this intake to non-dietary exposure in residences from local sources.

  17. A Comparison of Two Strategies for Building an Exposure Prediction Model.

    Science.gov (United States)

    Heiden, Marina; Mathiassen, Svend Erik; Garza, Jennifer; Liv, Per; Wahlström, Jens

    2016-01-01

    Cost-efficient assessments of job exposures in large populations may be obtained from models in which 'true' exposures assessed by expensive measurement methods are estimated from easily accessible and cheap predictors. Typically, the models are built on the basis of a validation study comprising 'true' exposure data as well as an extensive collection of candidate predictors from questionnaires or company data, which cannot all be included in the models due to restrictions in the degrees of freedom available for modeling. In these situations, predictors need to be selected using procedures that can identify the best possible subset of predictors among the candidates. The present study compares two strategies for selecting a set of predictor variables. One strategy relies on stepwise hypothesis testing of associations between predictors and exposure, while the other uses cluster analysis to reduce the number of predictors without relying on empirical information about the measured exposure. Both strategies were applied to the same dataset on biomechanical exposure and candidate predictors among computer users, and they were compared in terms of identified predictors of exposure as well as the resulting model fit using bootstrapped resamples of the original data. The identified predictors were, to a large part, different between the two strategies, and the initial model fit was better for the stepwise testing strategy than for the clustering approach. Internal validation of the models using bootstrap resampling with fixed predictors revealed an equally reduced model fit in resampled datasets for both strategies. However, when predictor selection was incorporated in the validation procedure for the stepwise testing strategy, the model fit was reduced to the extent that both strategies showed similar model fit. Thus, the two strategies would both be expected to perform poorly with respect to predicting biomechanical exposure in other samples of computer users. © The

  18. A hybrid modeling with data assimilation to evaluate human exposure level

    Science.gov (United States)

    Koo, Y. S.; Cheong, H. K.; Choi, D.; Kim, A. L.; Yun, H. Y.

    2015-12-01

    Exposure models are designed to better represent human contact with PM (Particulate Matter) and other air pollutants such as CO, SO2, O3, and NO2. The exposure concentrations of the air pollutants to human are determined by global and regional long range transport of global and regional scales from Europe and China as well as local emissions from urban and road vehicle sources. To assess the exposure level in detail, the multiple scale influence from background to local sources should be considered. A hybrid air quality modeling methodology combing a grid-based chemical transport model with a local plume dispersion model was used to provide spatially and temporally resolved air quality concentration for human exposure levels in Korea. In the hybrid modeling approach, concentrations from a grid-based chemical transport model and a local plume dispersion model are added to provide contributions from photochemical interactions, long-range (regional) transport and local-scale dispersion. The CAMx (Comprehensive Air quality Model with Extensions was used for the background concentrations from anthropogenic and natural emissions in East Asia including Korea while the road dispersion by vehicle emission was calculated by CALPUFF model. The total exposure level of the pollutants was finally assessed by summing the background and road contributions. In the hybrid modeling, the data assimilation method based on the optimal interpolation was applied to overcome the discrepancies between the model predicted concentrations and observations. The air quality data from the air quality monitoring stations in Korea. The spatial resolution of the hybrid model was 50m for the Seoul Metropolitan Ares. This example clearly demonstrates that the exposure level could be estimated to the fine scale for the exposure assessment by using the hybrid modeling approach with data assimilation.

  19. Modeling and Characterization of the Uplink and Downlink Exposure in Wireless Networks

    Directory of Open Access Journals (Sweden)

    Anis Krayni

    2017-01-01

    Full Text Available This paper deals with a new methodology to assess the exposure induced by both uplink and downlink of a cellular network using 3D electromagnetic simulations. It aims to analyze together the exposure induced by a personal device (uplink exposure and that induced by a base station (downlink exposure. The study involved the major parameters contributing to variability and uncertainty in exposure assessment, such as the user’s posture, the type of wireless device, and the propagation environment. Our approach is relying basically on the modeling of the power radiated by the personal device and the ambient electric field, while taking into account the effects of human body shadowing and the propagation channel fluctuations. The exposure assessment as well as the human-wave interactions has been simulated using the finite difference in time domain method (FDTD. In uplink scenarios, four FDTD simulations were performed with a child model, used in two postures (sitting and standing and in two usage scenarios (voice and data, which aimed to examine the exposure induced by a mobile phone and a tablet emitting, respectively, at 900 MHz and 1940 MHz. In the downlink scenario, a series of FDTD simulations of an exposure to a single plane wave and multiplane waves have been conducted, and an efficient metamodeling of the exposure using the Polynomial Chaos approach has been developed.

  20. Multi-scale spatial modeling of human exposure from local sources to global intake

    DEFF Research Database (Denmark)

    Wannaz, Cedric; Fantke, Peter; Jolliet, Olivier

    2018-01-01

    Exposure studies, used in human health risk and impact assessments of chemicals are largely performed locally or regionally. It is usually not known how global impacts resulting from exposure to point source emissions compare to local impacts. To address this problem, we introduce Pangea......, an innovative multi-scale, spatial multimedia fate and exposure assessment model. We study local to global population exposure associated with emissions from 126 point sources matching locations of waste-to-energy plants across France. Results for three chemicals with distinct physicochemical properties...... occur within a 100 km radius from the source. This suggests that, by neglecting distant low-level exposure, local assessments might only account for fractions of global cumulative intakes. We also study ~10,000 emission locations covering France more densely to determine per chemical and exposure route...

  1. Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

    International Nuclear Information System (INIS)

    Teng, S.; Tebby, C.; Barcellini-Couget, S.; De Sousa, G.; Brochot, C.; Rahmani, R.; Pery, A.R.R.

    2016-01-01

    Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.

  2. Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models

    Energy Technology Data Exchange (ETDEWEB)

    Teng, S.; Tebby, C. [Models for Toxicology and Ecotoxicology Unit, INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Barcellini-Couget, S. [ODESIA Neosciences, Sophia Antipolis, 400 route des chappes, 06903 Sophia Antipolis (France); De Sousa, G. [INRA, ToxAlim, 400 route des Chappes, BP, 167 06903 Sophia Antipolis, Cedex (France); Brochot, C. [Models for Toxicology and Ecotoxicology Unit, INERIS, Parc Technologique Alata, BP 2, 60550 Verneuil-en-Halatte (France); Rahmani, R. [INRA, ToxAlim, 400 route des Chappes, BP, 167 06903 Sophia Antipolis, Cedex (France); Pery, A.R.R., E-mail: alexandre.pery@agroparistech.fr [AgroParisTech, UMR 1402 INRA-AgroParisTech Ecosys, 78850 Thiverval Grignon (France); INRA, UMR 1402 INRA-AgroParisTech Ecosys, 78850 Thiverval Grignon (France)

    2016-08-15

    Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro – in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. - Highlights: • We could predict cell response over repeated exposure to mixtures of cosmetics. • Compounds acted independently on the cells. • Metabolic interactions impacted exposure concentrations to the compounds.

  3. Airports Geographic Information System -

    Data.gov (United States)

    Department of Transportation — The Airports Geographic Information System maintains the airport and aeronautical data required to meet the demands of the Next Generation National Airspace System....

  4. A model to establish the monetary value of the man-sievert for public exposure

    International Nuclear Information System (INIS)

    Schneider, T.; Schieber, C.; Eeckhoudt, L.; Godfroid, P.

    2000-01-01

    The implementation of cost-benefit analysis for the optimisation of radiation protection relies on the adoption of a monetary value of the man-sievert. From the economic point of view, the monetary value of the man-sievert can be seen as a function reflecting the individual and collective preferences associated with the level of exposures and the specificity of the exposure situations. It must thus integrate several dimensions: one dimension, which is independent of the exposure situation, is related to the potential health effects associated with the level of exposure; other dimensions are related to social and equity consideration, reflecting the characteristics of exposure situation: distribution of individual exposures, individual and social risk perception,... In the case of occupational exposure, CEPN has developed a model to define the monetary values of the man-sievert according to the level of individual exposure. This model has been used by some European nuclear utilities for setting their own values to be used in the process of radiological protection optimisation for workers. The question arising now concerns the establishment of this value for public exposure. For this purpose, we have considered one of the main differences between public and worker exposures: i.e. the existence of compensation systems for the radiation induced health effects if they occur for the workers. In the case of public exposure, such systems do not exist, mainly due to the absence of a permanent individual monitoring of exposures and to the low level of individual exposure. A theoretical model was developed to evaluate the willingness to pay to reduce the probability of occurrence of a radiation induced health effects (i.e. to reduce the level of exposure). It shows that, because of the absence of a compensation system for the public, this willingness to pay should be higher when the probability is reduced for the public than for the workers. The result of the numerical

  5. Assessment of Aircrew Radiation Exposure by further measurements and model development

    International Nuclear Information System (INIS)

    Lewis, B. J.; Desormeaux, M.; Green, A. R.; Bennett, L. G. I.; Butler, A.; McCall, M.; Saez Vergara, J. C.

    2004-01-01

    A methodology is presented for collecting and analysing exposure measurements from galactic cosmic radiation using a portable equipment suite and encapsulating these data into a semi-empirical model/Predictive Code for Aircrew Radiation Exposure (PCAIRE) for the assessment of aircrew radiation exposure on any flight over the solar cycle. The PCAIRE code has been validated against integral route dose measurements at commercial aircraft altitudes during experimental flights made by various research groups over the past 5 y with code predictions typically within ±20% of the measured data. An empirical correlation, based on ground-level neutron monitoring data, is detailed further for estimation of aircrew exposure from solar particle events. The semi-empirical models have been applied to predict the annual and career exposure of a flight crew member using actual flight roster data, accounting for contributions from galactic radiation and several solar energetic-particle events over the period 1973-2002. (authors)

  6. A changing climate: impacts on human exposures to O3 using an integrated modeling methodology

    Science.gov (United States)

    Predicting the impacts of changing climate on human exposure to air pollution requires future scenarios that account for changes in ambient pollutant concentrations, population sizes and distributions, and housing stocks. An integrated methodology to model changes in human exposu...

  7. 76 FR 53454 - Exposure Modeling Public Meeting; Notice of Public Meeting

    Science.gov (United States)

    2011-08-26

    ... Exposure Modeling Public Meeting will be held for presentation and discussion of current issues related to... Exponential Concentration Decline with Application to Riparian-Aquatic Pesticide Ecotoxicity. 4. Pesticide...

  8. Geographical Clusters and Predictors of Rabies in Three Southeastern States.

    Science.gov (United States)

    Reilly, Sara; Sanderson, Wayne T; Christian, W Jay; Browning, Steven R

    2017-06-01

    The rabies virus causes progressive encephalomyelitis that is fatal in nearly 100% of untreated cases. In the United States, wildlife act as the primary reservoir for rabies; prevention, surveillance, and control costs remain high. The purpose of this study is to understand the current distribution of wildlife rabies in three southeastern states, with particular focus on raccoons as the primary eastern reservoir, as well as identify demographic and geographic factors which may affect the risk of human exposure. This ecologic study obtained county-level rabies surveillance data from state health departments and the United States Department of Agriculture Wildlife services for North Carolina, Virginia, and West Virginia from 2010 to 2013. A spatial statistical analysis was performed to identify county clusters with high or low rates of raccoon rabies in the three states. Potential demographic and geographic factors associated with these varying rates of rabies were assessed using a multivariable negative binomial regression model. In North Carolina, raccoons constituted 50% of positive tests, in Virginia, 49%, and in West Virginia, 50%. Compared to persons residing in West Virginia counties, persons in North Carolina counties had 1.67 times the risk of exposure (p rabies exposure. Further research is needed to better understand the effect of the oral rabies vaccine program in controlling the risk of human exposure to raccoon rabies.

  9. Modeling the spatio-temporal dynamics of porcine reproductive & respiratory syndrome cases at farm level using geographical distance and pig trade network matrices.

    Science.gov (United States)

    Amirpour Haredasht, Sara; Polson, Dale; Main, Rodger; Lee, Kyuyoung; Holtkamp, Derald; Martínez-López, Beatriz

    2017-06-07

    Porcine reproductive and respiratory syndrome (PRRS) is one of the most economically devastating infectious diseases for the swine industry. A better understanding of the disease dynamics and the transmission pathways under diverse epidemiological scenarios is a key for the successful PRRS control and elimination in endemic settings. In this paper we used a two step parameter-driven (PD) Bayesian approach to model the spatio-temporal dynamics of PRRS and predict the PRRS status on farm in subsequent time periods in an endemic setting in the US. For such purpose we used information from a production system with 124 pig sites that reported 237 PRRS cases from 2012 to 2015 and from which the pig trade network and geographical location of farms (i.e., distance was used as a proxy of airborne transmission) was available. We estimated five PD models with different weights namely: (i) geographical distance weight which contains the inverse distance between each pair of farms in kilometers, (ii) pig trade weight (PT ji ) which contains the absolute number of pig movements between each pair of farms, (iii) the product between the distance weight and the standardized relative pig trade weight, (iv) the product between the standardized distance weight and the standardized relative pig trade weight, and (v) the product of the distance weight and the pig trade weight. The model that included the pig trade weight matrix provided the best fit to model the dynamics of PRRS cases on a 6-month basis from 2012 to 2015 and was able to predict PRRS outbreaks in the subsequent time period with an area under the ROC curve (AUC) of 0.88 and the accuracy of 85% (105/124). The result of this study reinforces the importance of pig trade in PRRS transmission in the US. Methods and results of this study may be easily adapted to any production system to characterize the PRRS dynamics under diverse epidemic settings to more timely support decision-making.

  10. Not to put too fine a point on it - does increasing precision of geographic referencing improve species distribution models for a wide-ranging migratory bat?

    Science.gov (United States)

    Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.

    2015-01-01

    Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.

  11. Mixed geographically weighted regression (MGWR) model with weighted adaptive bi-square for case of dengue hemorrhagic fever (DHF) in Surakarta

    Science.gov (United States)

    Astuti, H. N.; Saputro, D. R. S.; Susanti, Y.

    2017-06-01

    MGWR model is combination of linear regression model and geographically weighted regression (GWR) model, therefore, MGWR model could produce parameter estimation that had global parameter estimation, and other parameter that had local parameter in accordance with its observation location. The linkage between locations of the observations expressed in specific weighting that is adaptive bi-square. In this research, we applied MGWR model with weighted adaptive bi-square for case of DHF in Surakarta based on 10 factors (variables) that is supposed to influence the number of people with DHF. The observation unit in the research is 51 urban villages and the variables are number of inhabitants, number of houses, house index, many public places, number of healthy homes, number of Posyandu, area width, level population density, welfare of the family, and high-region. Based on this research, we obtained 51 MGWR models. The MGWR model were divided into 4 groups with significant variable is house index as a global variable, an area width as a local variable and the remaining variables vary in each. Global variables are variables that significantly affect all locations, while local variables are variables that significantly affect a specific location.

  12. Modelling the seasonal variation of vitamin D due to sun exposure.

    Science.gov (United States)

    Diffey, B L

    2010-06-01

    The current interest in vitamin D as a preventive agent in many chronic diseases has led to a reappraisal of adequate sun exposure. Yet just what constitutes adequacy remains to be clearly defined and validated. To do this requires an understanding of how behaviour outdoors during the year translates into seasonal changes in vitamin D status. To develop a model for estimating the changes in serum 25-hydroxyvitamin D [25(OH)D] levels as a consequence of sun exposure throughout the year. A novel mathematical model is described that incorporates the changes in serum 25(OH)D following a single, whole-body exposure to solar ultraviolet radiation with daily sun exposure in order to estimate the annual variation in serum 25(OH)D. The model yields results that agree closely with measured data from a large population-based study. Application of the model showed that current advice about 10-20 min of daily sun exposure during the summer months does little in the way of boosting overall 25(OH)D levels, while sufficient sun exposure that could achieve a worthwhile benefit would compromise skin health. There is little in the way of public health advice concerning the benefits of sun exposure that can be given as an effective means of maintaining adequate vitamin D levels throughout the year. Instead it would seem safer and more effective to fortify more foods with vitamin D and/or to consider the use of supplements during the winter months. Messages concerning sun exposure should remain focused on the detrimental effects of excessive sun exposure and should avoid giving specific advice on what might be 'optimal' sun exposure. © 2010 The Authors. Journal Compilation © 2010 British Association of Dermatologists.

  13. Indoor aerosol modeling for assessment of exposure and respiratory tract deposited dose

    Science.gov (United States)

    Hussein, Tareq; Wierzbicka, Aneta; Löndahl, Jakob; Lazaridis, Mihalis; Hänninen, Otto

    2015-04-01

    Air pollution is one of the major environmental problems that influence people's health. Exposure to harmful particulate matter (PM) occurs both outdoors and indoors, but while people spend most of their time indoors, the indoor exposures tend to dominate. Moreover, higher PM concentrations due to indoor sources and tightness of indoor environments may substantially add to the outdoor originating exposures. Empirical and real-time assessment of human exposure is often impossible; therefore, indoor aerosol modeling (IAM) can be used as a superior method in exposure and health effects studies. This paper presents a simple approach in combining available aerosol-based modeling techniques to evaluate the real-time exposure and respiratory tract deposited dose based on particle size. Our simple approach consists of outdoor aerosol data base, IAM simulations, time-activity pattern data-base, physical-chemical properties of inhaled aerosols, and semi-empirical deposition fraction of aerosols in the respiratory tract. These modeling techniques allow the characterization of regional deposited dose in any metric: particle mass, particle number, and surface area. The first part of this presentation reviews recent advances in simple mass-balance based modeling methods that are needed in analyzing the health relevance of indoor exposures. The second part illustrates the use of IAM in the calculations of exposure and deposited dose. Contrary to previous methods, the approach presented is a real-time approach and it goes beyond the exposure assessment to provide the required information for the health risk assessment, which is the respiratory tract deposited dose. This simplified approach is foreseen to support epidemiological studies focusing on exposures originating from both indoor and outdoor sources.

  14. A four factor model for estimating human radiation exposure to radon daughters in the home

    International Nuclear Information System (INIS)

    McCullough, R.S.; Letourneau, E.G.; Waight, P.J.

    1981-01-01

    This model is intended to represent the exposure received by individuals who spend any part of their day in a private home. Variables are defined to represent (1) different human groups, (2) basement and other levels in a house, (3) the four seasons of the year, and (4) activities within the home. The model is extremely flexible and appears to be applicable to other exposure circumstances. The number and definition of each of the variables can be changed easily. (author)

  15. The multimedia models for the evaluation of exposure bond to the atmospheric emissions of classified installations

    International Nuclear Information System (INIS)

    Bonnard, R.

    2001-12-01

    Risk assessment and environmental impacts studies are realized to preserve the public health. Today one of the most used approach is the use of an atmospheric dispersion model to assess the risks. The data are then injected in a calculation software of exposure bond to polluted soils, to evaluate the risks of non direct exposure. This report details and evaluates the models corresponding to the need: the methodology for assessing Health Risks associated with multiple pathways of exposure to combustor, human health risk assessment proto col for hazardous waste combustion facilities, EUSES, CALTOX, MEPAS, MEND-TOX, RESRAD, MMSOILS, FRAMES-HWIR, PC-GEMS and TRIM. (A.L.B.)

  16. Coloring geographical threshold graphs

    Energy Technology Data Exchange (ETDEWEB)

    Bradonjic, Milan [Los Alamos National Laboratory; Percus, Allon [Los Alamos National Laboratory; Muller, Tobias [EINDHOVEN UNIV. OF TECH

    2008-01-01

    We propose a coloring algorithm for sparse random graphs generated by the geographical threshold graph (GTG) model, a generalization of random geometric graphs (RGG). In a GTG, nodes are distributed in a Euclidean space, and edges are assigned according to a threshold function involving the distance between nodes as well as randomly chosen node weights. The motivation for analyzing this model is that many real networks (e.g., wireless networks, the Internet, etc.) need to be studied by using a 'richer' stochastic model (which in this case includes both a distance between nodes and weights on the nodes). Here, we analyze the GTG coloring algorithm together with the graph's clique number, showing formally that in spite of the differences in structure between GTG and RGG, the asymptotic behavior of the chromatic number is identical: {chi}1n 1n n / 1n n (1 + {omicron}(1)). Finally, we consider the leading corrections to this expression, again using the coloring algorithm and clique number to provide bounds on the chromatic number. We show that the gap between the lower and upper bound is within C 1n n / (1n 1n n){sup 2}, and specify the constant C.

  17. Assessing the cumulative impacts of geographically isolated wetlands on watershed hydrology using the SWAT model coupled with improved wetland modules.

    Science.gov (United States)

    Lee, S; Yeo, I-Y; Lang, M W; Sadeghi, A M; McCarty, G W; Moglen, G E; Evenson, G R

    2018-06-07

    Despite recognizing the importance of wetlands in the Coastal Plain of the Chesapeake Bay Watershed (CBW) in terms of ecosystem services, our understanding of wetland functions has mostly been limited to individual wetlands and overall catchment-scale wetland functions have rarely been investigated. This study is aimed at assessing the cumulative impacts of wetlands on watershed hydrology for an agricultural watershed within the Coastal Plain of the CBW using the Soil and Water Assessment Tool (SWAT). We employed two improved wetland modules for enhanced representation of physical processes and spatial distribution of riparian wetlands (RWs) and geographically isolated wetlands (GIWs). This study focused on GIWs as their hydrological impacts on watershed hydrology are poorly understood and GIWs are poorly protected. Multiple wetland scenarios were prepared by removing all or portions of the baseline GIW condition indicated by the U.S. Fish and Wildlife Service National Wetlands Inventory geospatial dataset. We further compared the impacts of GIWs and RWs on downstream flow (i.e., streamflow at the watershed outlet). Our simulation results showed that GIWs strongly influenced downstream flow by altering water transport mechanisms in upstream areas. Loss of all GIWs reduced both water routed to GIWs and water infiltrated into the soil through the bottom of GIWs, leading to an increase in surface runoff of 9% and a decrease in groundwater flow of 7% in upstream areas. These changes resulted in increased variability of downstream flow in response to extreme flow conditions. GIW loss also induced an increase in month to month variability of downstream flow and a decrease in the baseflow contribution to streamflow. Loss of all GIWs was shown to cause a greater fluctuation of downstream flow than loss of all RWs for this study site, due to a greater total water storage capacity of GIWs. Our findings indicate that GIWs play a significant role in controlling hydrological

  18. Exposure assessment of mobile phone base station radiation in an outdoor environment using sequential surrogate modeling.

    Science.gov (United States)

    Aerts, Sam; Deschrijver, Dirk; Joseph, Wout; Verloock, Leen; Goeminne, Francis; Martens, Luc; Dhaene, Tom

    2013-05-01

    Human exposure to background radiofrequency electromagnetic fields (RF-EMF) has been increasing with the introduction of new technologies. There is a definite need for the quantification of RF-EMF exposure but a robust exposure assessment is not yet possible, mainly due to the lack of a fast and efficient measurement procedure. In this article, a new procedure is proposed for accurately mapping the exposure to base station radiation in an outdoor environment based on surrogate modeling and sequential design, an entirely new approach in the domain of dosimetry for human RF exposure. We tested our procedure in an urban area of about 0.04 km(2) for Global System for Mobile Communications (GSM) technology at 900 MHz (GSM900) using a personal exposimeter. Fifty measurement locations were sufficient to obtain a coarse street exposure map, locating regions of high and low exposure; 70 measurement locations were sufficient to characterize the electric field distribution in the area and build an accurate predictive interpolation model. Hence, accurate GSM900 downlink outdoor exposure maps (for use in, e.g., governmental risk communication and epidemiological studies) are developed by combining the proven efficiency of sequential design with the speed of exposimeter measurements and their ease of handling. Copyright © 2013 Wiley Periodicals, Inc.

  19. Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools

    Science.gov (United States)

    O'Donnell, Michael S.; Aldridge, Cameron L.; Doherty, Kevin E.; Fedy, Bradley C.

    2015-01-01

    With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-selection studies to identify prioritization efforts for species of conservation concern to increase understanding and help guide habitat-conservation efforts. Recently, the authors undertook a large-scale collaborative effort that developed habitat-selection models for Greater Sage-grouse (Centrocercus urophasianus) across large landscapes in Wyoming, USA and for multiple life-stages (nesting, late brood-rearing, and winter). We developed these habitat models using resource selection functions, based upon sage-grouse telemetry data collected for localized studies and within each life-stage. The models allowed us to characterize and spatially predict seasonal sage-grouse habitat use in Wyoming. Due to the quantity of models, the diversity of model predictors (in the form of geographic information system data) produced by analyses, and the variety of potential applications for these data, we present here a resource that complements our published modeling effort, which will further support land managers.

  20. Simple intake and pharmacokinetic modeling to characterize exposure of Americans to perfluoroctanoic acid, PFOA.

    Science.gov (United States)

    Lorber, Matthew; Egeghy, Peter P

    2011-10-01

    Models for assessing intakes of perfluorooctanoic acid, PFOA, are described and applied. One model is based on exposure media concentrations and contact rates. This model is applied to general population exposures for adults and 2-year old children. The other model is a simple one-compartment, first-order pharmacokinetic (PK) model. Parameters for this model include a rate of elimination of PFOA and a blood volume of distribution. The model was applied to data from the National Health and Nutritional Examination Survey, NHANES, to backcalculate intakes. The central tendency intake estimate for adults and children based on exposure media concentrations and contact rates were 70 and 26 ng/day, respectively. The central tendency adult intake derived from NHANES data was 56 and 37 ng/day for males and females, respectively. Variability and uncertainty discussions regarding the intake modeling focus on lack of data on direct exposure to PFOA used in consumer products, precursor compounds, and food. Discussions regarding PK modeling focus on the range of blood measurements in NHANES, the appropriateness of the simple PK model, and the uncertainties associated with model parameters. Using the PK model, the 10th and 95th percentile long-term average adult intakes of PFOA are 15 and 130 ng/day.

  1. Modelling the exposure induced by a criticality excursion in solution

    International Nuclear Information System (INIS)

    Kerouanton, David; Delgovea, Laure; Castaniera, Eric; Raimondia, Nicolas

    2008-01-01

    During a criticality accident, significant exposure is generated by 4 radiation origins: radiation directly induced by fissions (prompt neutrons and gamma), gamma radiations induced by (n, γ) reactions in crossed materials (capture gamma) and gamma radiations emitted by fission products. Due to boiling of the solution, a fraction of fissions products is airborne and is deposited in the ventilation shafts. 5.10 18 fissions are considered in a dissolution tank containing uranyl nitrate by using the deterministic ATTILA radiation transport code. Instantaneous radiations rates are evaluated as a function of the distance and compared with data available in the literature. Dose rates induced behind various shielding materials such as concrete, steel or glass are assessed. In all cases, relative contributions of prompt or capture radiations is detailed. (author)

  2. Hydrological simulation of Sperchios River basin in Central Greece using the MIKE SHE model and geographic information systems

    Science.gov (United States)

    Paparrizos, Spyridon; Maris, Fotios

    2017-05-01

    The MIKE SHE model is able to simulate the entire stream flow which includes direct and basic flow. Many models either do not simulate or use simplistic methods to determine the basic flow. The MIKE SHE model takes into account many hydrological data. Since this study was directed towards the simulation of surface runoff and infiltration into saturated and unsaturated zone, the MIKE SHE is an appropriate model for reliable conclusions. In the current research, the MIKE SHE model was used to simulate runoff in the area of Sperchios River basin. Meteorological data from eight rainfall stations within the Sperchios River basin were used as inputs. Vegetation as well as geological data was used to perform the calibration and validation of the physical processes of the model. Additionally, ArcGIS program was used. The results indicated that the model was able to simulate the surface runoff satisfactorily, representing all the hydrological data adequately. Some minor differentiations appeared which can be eliminated with the appropriate adjustments that can be decided by the researcher's experience.

  3. A review of models for near-field exposure pathways of chemicals in consumer products

    DEFF Research Database (Denmark)

    Huang, Lei; Ernstoff, Alexi; Fantke, Peter

    2017-01-01

    able to quantify the multiple transfers of chemicals from products used near-field to humans. The present review therefore aims at an in-depth overview of modeling approaches for near-field chemical release and human exposure pathways associated with consumer products. It focuses on lower......-tier, mechanistic models suitable for life cycle assessments (LCA), chemical alternative assessment (CAA) and high-throughput screening risk assessment (HTS). Chemicals in a product enter the near-field via a defined “compartment of entry”, are transformed or transferred to adjacent compartments, and eventually end......Exposure to chemicals in consumer products has been gaining increasing attention, with multiple studies showing that near-field exposures from products is high compared to far-field exposures. Regarding the numerous chemical-product combinations, there is a need for an overarching review of models...

  4. Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

    Science.gov (United States)

    2015-02-01

    Computational and Information Sciences Directorate Battlefield Environment Division (ATTN: RDRL- CIE -M) White Sands Missile Range, NM 88002-5501 8. PERFORMING...meteorological parameters, which became our focus. We found that elevation accounts for a significant portion of the variance in the model error. The...found that elevation accounts for a significant portion of the variance in the model error of surface temperature and relative humidity predictions

  5. Indoor PM2.5 exposure in London's domestic stock: Modelling current and future exposures following energy efficient refurbishment

    Science.gov (United States)

    Shrubsole, C.; Ridley, I.; Biddulph, P.; Milner, J.; Vardoulakis, S.; Ucci, M.; Wilkinson, P.; Chalabi, Z.; Davies, M.

    2012-12-01

    Simulations using CONTAM (a validated multi-zone indoor air quality (IAQ) model) are employed to predict indoor exposure to PM2.5 in London dwellings in both the present day housing stock and the same stock following energy efficient refurbishments to meet greenhouse gas emissions reduction targets for 2050. We modelled interventions that would contribute to the achievement of these targets by reducing the permeability of the dwellings to 3 m3 m-2 h-1 at 50 Pa, combined with the introduction of mechanical ventilation and heat recovery (MVHR) systems. It is assumed that the current mean outdoor PM2.5 concentration of 13 μg m-3 decreased to 9 μg m-3 by 2050 due to emission control policies. Our primary finding was that installation of (assumed perfectly functioning) MVHR systems with permeability reduction are associated with appreciable reductions in PM2.5 exposure in both smoking and non-smoking dwellings. Modelling of the future scenario for non-smoking dwellings show a reduction in annual average indoor exposure to PM2.5 of 18.8 μg m-3 (from 28.4 to 9.6 μg m-3) for a typical household member. Also of interest is that a larger reduction of 42.6 μg m-3 (from 60.5 to 17.9 μg m-3) was shown for members exposed primarily to cooking-related particle emissions in the kitchen (cooks). Reductions in envelope permeability without mechanical ventilation produced increases in indoor PM2.5 concentrations; 5.4 μg m-3 for typical household members and 9.8 μg m-3 for cooks. These estimates of changes in PM2.5 exposure are sensitive to assumptions about occupant behaviour, ventilation system usage and the distributions of input variables (±72% for non-smoking and ±107% in smoking residences). However, if realised, they would result in significant health benefits.

  6. Shared and unshared exposure measurement error in occupational cohort studies and their effects on statistical inference in proportional hazards models

    Science.gov (United States)

    Laurier, Dominique; Rage, Estelle

    2018-01-01

    Exposure measurement error represents one of the most important sources of uncertainty in epidemiology. When exposure uncertainty is not or only poorly accounted for, it can lead to biased risk estimates and a distortion of the shape of the exposure-response relationship. In occupational cohort studies, the time-dependent nature of exposure and changes in the method of exposure assessment may create complex error structures. When a method of group-level exposure assessment is used, individual worker practices and the imprecision of the instrument used to measure the average exposure for a group of workers may give rise to errors that are shared between workers, within workers or both. In contrast to unshared measurement error, the effects of shared errors remain largely unknown. Moreover, exposure uncertainty and magnitude of exposure are typically highest for the earliest years of exposure. We conduct a simulation study based on exposure data of the French cohort of uranium miners to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the shape of the exposure-response curve in proportional hazards models. Our results indicate that uncertainty components shared within workers cause more bias in risk estimation and a more severe attenuation of the exposure-response relationship than unshared exposure uncertainty or exposure uncertainty shared between individuals. These findings underline the importance of careful characterisation and modeling of exposure uncertainty in observational studies. PMID:29408862

  7. A geographical information system-based web model of arbovirus transmission risk in the continental United States of America

    Directory of Open Access Journals (Sweden)

    Sarah K. Konrad

    2012-11-01

    Full Text Available A degree-day (DD model of West Nile virus capable of forecasting real-time transmission risk in the continental United States of America up to one week in advance using a 50-km grid is available online at https://sites. google.com/site/arbovirusmap/. Daily averages of historical risk based on temperatures for 1994-2003 are available at 10- km resolution. Transmission risk maps can be downloaded from 2010 to the present. The model can be adapted to work with any arbovirus for which the temperature-related parameters are known, e.g. Rift Valley fever virus. To more effectively assess virus establishment and transmission, the model incorporates “compound risk” maps and forecasts, which includes livestock density as a parameter.

  8. Modeling the distribution of Schistosoma mansoni and host snails in Uganda using satellite sensor data and Geographical Information Systems

    DEFF Research Database (Denmark)

    Stensgaard, Anna-Sofie; Jørgensen, A; Kabatereine, N B

    2005-01-01

    The potential value of MODIS satellite sensor data on Normalized Difference Vegetation Index (NDVI) and land surface temperatures (LST) for describing the distribution of the Schistosoma mansoni-"Biomphalaria pfeifferi"/Biomphalaria sudanica parasite-snail system in inland Uganda, were tested...... by developing annual and seasonal composite models, and iteratively analysing for their relationship with parasite and snail distribution. The dry season composite model predicted an endemic area that produced the best fit with the distribution of schools with > or =5% prevalence. NDVI values of 151-174, day...

  9. Effects of copper nanoparticle exposure on host defense in a murine pulmonary infection model

    Directory of Open Access Journals (Sweden)

    Grassian Vicki H

    2011-09-01

    Full Text Available Abstract Background Human exposure to nanoparticles (NPs and environmental bacteria can occur simultaneously. NPs induce inflammatory responses and oxidative stress but may also have immune-suppressive effects, impairing macrophage function and altering epithelial barrier functions. The purpose of this study was to assess the potential pulmonary effects of inhalation and instillation exposure to copper (Cu NPs using a model of lung inflammation and host defense. Methods We used Klebsiella pneumoniae (K.p. in a murine lung infection model to determine if pulmonary bacterial clearance is enhanced or impaired by Cu NP exposure. Two different exposure modes were tested: sub-acute inhalation (4 hr/day, 5 d/week for 2 weeks, 3.5 mg/m3 and intratracheal instillation (24 hr post-exposure, 3, 35, and 100 μg/mouse. Pulmonary responses were evaluated by lung histopathology plus measurement of differential cell counts, total protein, lactate dehydrogenase (LDH activity, and inflammatory cytokines in bronchoalveolar lavage (BAL fluid. Results Cu NP exposure induced inflammatory responses with increased recruitment of total cells and neutrophils to the lungs as well as increased total protein and LDH activity in BAL fluid. Both inhalation and instillation exposure to Cu NPs significantly decreased the pulmonary clearance of K.p.-exposed mice measured 24 hr after bacterial infection following Cu NP exposure versus sham-exposed mice also challenged with K.p (1.4 × 105 bacteria/mouse. Conclusions Cu NP exposure impaired host defense against bacterial lung infections and induced a dose-dependent decrease in bacterial clearance in which even our lowest dose demonstrated significantly lower clearance than observed in sham-exposed mice. Thus, exposure to Cu NPs may increase the risk of pulmonary infection.

  10. Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models.

    Science.gov (United States)

    Teng, S; Tebby, C; Barcellini-Couget, S; De Sousa, G; Brochot, C; Rahmani, R; Pery, A R R

    2016-08-15

    Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro - in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. Development of a LiDAR derived digital elevation model (DEM) as Input to a METRANS geographic information system (GIS).

    Science.gov (United States)

    2011-05-01

    This report describes an assessment of digital elevation models (DEMs) derived from : LiDAR data for a subset of the Ports of Los Angeles and Long Beach. A methodology : based on Monte Carlo simulation was applied to investigate the accuracy of DEMs ...

  12. A review of air exchange rate models for air pollution exposure assessments.

    Science.gov (United States)

    Breen, Michael S; Schultz, Bradley D; Sohn, Michael D; Long, Thomas; Langstaff, John; Williams, Ronald; Isaacs, Kristin; Meng, Qing Yu; Stallings, Casson; Smith, Luther

    2014-11-01

    A critical aspect of air pollution exposure assessments is estimation of the air exchange rate (AER) for various buildings where people spend their time. The AER, which is the rate of exchange of indoor air with outdoor air, is an important determinant for entry of outdoor air pollutants and for removal of indoor-emitted air pollutants. This paper presents an overview and critical analysis of the scientific literature on empirical and physically based AER models for residential and commercial buildings; the models highlighted here are feasible for exposure assessments as extensive inputs are not required. Models are included for the three types of airflows that can occur across building envelopes: leakage, natural ventilation, and mechanical ventilation. Guidance is provided to select the preferable AER model based on available data, desired temporal resolution, types of airflows, and types of buildings included in the exposure assessment. For exposure assessments with some limited building leakage or AER measurements, strategies are described to reduce AER model uncertainty. This review will facilitate the selection of AER models in support of air pollution exposure assessments.

  13. Hybrid Air Quality Modeling Approach for use in the Hear-road Exposures to Urban air pollutant Study(NEXUS)

    Science.gov (United States)

    The paper presents a hybrid air quality modeling approach and its application in NEXUS in order to provide spatial and temporally varying exposure estimates and identification of the mobile source contribution to the total pollutant exposure. Model-based exposure metrics, associa...

  14. Modelling Dietary Exposure to Chemical Components in Heat-Processed Meats

    DEFF Research Database (Denmark)

    Georgiadis, Stylianos; Jakobsen, Lea Sletting; Nielsen, Bo Friis

    Several chemical compounds that potentially increase the risk of developing cancer in humans are formed during heat processing of meat. Estimating the overall health impact of these compounds in the population requires accurate estimation of the exposure to the chemicals, as well as the probabili.......g. the Poisson-Lognormal approach, are promising tools to address this obstacle. The exposure estimates can then be applied to dose-response models to quantify the cancer risk.......Several chemical compounds that potentially increase the risk of developing cancer in humans are formed during heat processing of meat. Estimating the overall health impact of these compounds in the population requires accurate estimation of the exposure to the chemicals, as well as the probability...... that different levels of exposure result in disease. The overall goal of this study was to evaluate the impact of variability of exposure patterns and uncertainty of exposure data in burden of disease estimates. We focus on the first phase of burden of disease modelling, i.e. the estimation of exposure...

  15. Comparison of spatiotemporal prediction models of daily exposure of individuals to ambient nitrogen dioxide and ozone in Montreal, Canada.

    Science.gov (United States)

    Buteau, Stephane; Hatzopoulou, Marianne; Crouse, Dan L; Smargiassi, Audrey; Burnett, Richard T; Logan, Travis; Cavellin, Laure Deville; Goldberg, Mark S

    2017-07-01

    In previous studies investigating the short-term health effects of ambient air pollution the exposure metric that is often used is the daily average across monitors, thus assuming that all individuals have the same daily exposure. Studies that incorporate space-time exposures of individuals are essential to further our understanding of the short-term health effects of ambient air pollution. As part of a longitudinal cohort study of the acute effects of air pollution that incorporated subject-specific information and medical histories of subjects throughout the follow-up, the purpose of this study was to develop and compare different prediction models using data from fixed-site monitors and other monitoring campaigns to estimate daily, spatially-resolved concentrations of ozone (O 3 ) and nitrogen dioxide (NO 2 ) of participants' residences in Montreal, 1991-2002. We used the following methods to predict spatially-resolved daily concentrations of O 3 and NO 2 for each geographic region in Montreal (defined by three-character postal code areas): (1) assigning concentrations from the nearest monitor; (2) spatial interpolation using inverse-distance weighting; (3) back-extrapolation from a land-use regression model from a dense monitoring survey, and; (4) a combination of a land-use and Bayesian maximum entropy model. We used a variety of indices of agreement to compare estimates of exposure assigned from the different methods, notably scatterplots of pairwise predictions, distribution of differences and computation of the absolute agreement intraclass correlation (ICC). For each pairwise prediction, we also produced maps of the ICCs by these regions indicating the spatial variability in the degree of agreement. We found some substantial differences in agreement across pairs of methods in daily mean predicted concentrations of O 3 and NO 2 . On a given day and postal code area the difference in the concentration assigned could be as high as 131ppb for O 3 and 108ppb

  16. Children's Lead Exposure: A Multimedia Modeling Analysis to Guide Public Health Decision-Making.

    Science.gov (United States)

    Zartarian, Valerie; Xue, Jianping; Tornero-Velez, Rogelio; Brown, James

    2017-09-12

    Drinking water and other sources for lead are the subject of public health concerns around the Flint, Michigan, drinking water and East Chicago, Indiana, lead in soil crises. In 2015, the U.S. Environmental Protection Agency (EPA)'s National Drinking Water Advisory Council (NDWAC) recommended establishment of a "health-based, household action level" for lead in drinking water based on children's exposure. The primary objective was to develop a coupled exposure-dose modeling approach that can be used to determine what drinking water lead concentrations keep children's blood lead levels (BLLs) below specified values, considering exposures from water, soil, dust, food, and air. Related objectives were to evaluate the coupled model estimates using real-world blood lead data, to quantify relative contributions by the various media, and to identify key model inputs. A modeling approach using the EPA's Stochastic Human Exposure and Dose Simulation (SHEDS)-Multimedia and Integrated Exposure Uptake and Biokinetic (IEUBK) models was developed using available data. This analysis for the U.S. population of young children probabilistically simulated multimedia exposures and estimated relative contributions of media to BLLs across all population percentiles for several age groups. Modeled BLLs compared well with nationally representative BLLs (0-23% relative error). Analyses revealed relative importance of soil and dust ingestion exposure pathways and associated Pb intake rates; water ingestion was also a main pathway, especially for infants. This methodology advances scientific understanding of the relationship between lead concentrations in drinking water and BLLs in children. It can guide national health-based benchmarks for lead and related community public health decisions. https://doi.org/10.1289/EHP1605.

  17. The Validity and Applicability of Using a Generic Exposure Assessment Model for Occupational Exposure to Nano-Objects and Their Aggregates and Agglomerates

    NARCIS (Netherlands)

    Bekker, Cindy; Voogd, Eef; Fransman, Wouter; Vermeulen, Roel

    2016-01-01

    BACKGROUND: Control banding can be used as a first-tier assessment to control worker exposure to nano-objects and their aggregates and agglomerates (NOAA). In a second tier, more advanced modelling approaches are needed to produce quantitative exposure estimates. As currently no general quantitative

  18. The validity and applicability of using a generic exposure assessment model for occupational exposure to nano-objects and their aggregates and agglomerates

    NARCIS (Netherlands)

    Bekker, C.; Voogd, E.; Fransman, W.; Vermeulen, R.

    2016-01-01

    Background: Control banding can be used as a first-tier assessment to control worker exposure to nano-objects and their aggregates and agglomerates (NOAA). In a second tier, more advanced modelling approaches are needed to produce quantitative exposure estimates. As currently no general quantitative

  19. Modeling personal exposure to traffic related air pollutants

    NARCIS (Netherlands)

    Montagne, D.R.

    2015-01-01

    The first part of this thesis is about the VE3SPA project. Land use regression (LUR) models are often used to predict the outdoor air pollution at the home address of study participants, to study long-term effects of air pollution. While several studies have documented that PM2.5 mass measured at a

  20. Could natural selection change the geographic range limits of light brown apple moth (Lepidoptera, Tortricidae) in North America?

    Science.gov (United States)

    Amy C. Morey; Robert C. Venette; William D. Hutchison

    2013-01-01

    We artificially selected for increased freeze tolerance in the invasive light brown apple moth. Our results suggest that, by not accounting for adaptation to cold, current models of potential geographic distributions could underestimate the areas at risk of exposure to this species.

  1. ADDRESSING HUMAN EXPOSURE TO AIR POLLUTANTS AROUND BUILDINGS IN URBAN AREAS WITH COMPUTATIONAL FLUID DYNAMICS (CFD) MODELS

    Science.gov (United States)

    Computational Fluid Dynamics (CFD) simulations provide a number of unique opportunities for expanding and improving capabilities for modeling exposures to environmental pollutants. The US Environmental Protection Agency's National Exposure Research Laboratory (NERL) has been c...

  2. Improved heat transfer modeling of the eye for electromagnetic wave exposures.

    Science.gov (United States)

    Hirata, Akimasa

    2007-05-01

    This study proposed an improved heat transfer model of the eye for exposure to electromagnetic (EM) waves. Particular attention was paid to the difference from the simplified heat transfer model commonly used in this field. From our computational results, the temperature elevation in the eye calculated with the simplified heat transfer model was largely influenced by the EM absorption outside the eyeball, but not when we used our improved model.

  3. Modeling Human Exposure Levels to Airborne Volatile Organic Compounds by the Hebei Spirit Oil Spill

    OpenAIRE

    Kim, Jong Ho; Kwak, Byoung Kyu; Ha, Mina; Cheong, Hae-Kwan; Yi, Jongheop

    2012-01-01

    Objectives The goal was to model and quantify the atmospheric concentrations of volatile organic compounds (VOCs) as the result of the Hebei Spirit oil spill, and to predict whether the exposure levels were abnormally high or not. Methods We developed a model for calculating the airborne concentration of VOCs that are produced in an oil spill accident. The model was applied to a practical situation, namely the Hebei Spirit oil spill. The accuracy of the model was verified by comparing the res...

  4. Atmospheric Dispersion Modelling and Spatial Analysis to Evaluate Population Exposure to Pesticides from Farming Processes

    Directory of Open Access Journals (Sweden)

    Sofia Costanzini

    2018-01-01

    Full Text Available This work originates from an epidemiological study aimed to assess the correlation between population exposure to pesticides used in agriculture and adverse health effects. In support of the population exposure evaluation two models implemented by the authors were applied: a GIS-based proximity model and the CAREA atmospheric dispersion model. In this work, the results of the two models are presented and compared. Despite the proximity analysis is widely used for these kinds of studies, it was investigated how meteorology could affect the exposure assessment. Both models were applied to pesticides emitted by 1519 agricultural fields and considering 2584 receptors distributed over an area of 8430 km2. CAREA output shows a considerable enhancement in the percentage of exposed receptors, from the 4% of the proximity model to the 54% of the CAREA model. Moreover, the spatial analysis of the results on a specific test site showed that the effects of meteorology considered by CAREA led to an anisotropic exposure distribution that differs considerably from the symmetric distribution resulting by the proximity model. In addition, the results of a field campaign for the definition and planning of ground measurement of concentration for the validation of CAREA are presented. The preliminary results showed how, during treatments, pesticide concentrations distant from the fields are significantly higher than background values.

  5. A Model of International Communication Media Appraisal and Exposure: A Comprehensive Test in Belize.

    Science.gov (United States)

    Johnson, J. David; Oliveira, Omar Souki

    A study constituted the fifth phase of a programmatic research effort designed to develop and test a model of international communications media exposure and appraisal. The model posits that three variables--editorial tone, communication potential, and utility--have positive determinant effects on these dependent variables. Research was carried…

  6. An in-premise model for Legionella exposure during showering events

    Science.gov (United States)

    An exposure model was constructed to predict the critical Legionella densities in an engineered water system that might result in infection from inhalation of aerosols containing the pathogen while showering. The model predicted the Legionella densities in the shower air, water ...

  7. Matrix Population Model for Estimating Effects from Time-Varying Aquatic Exposures: Technical Documentation

    Science.gov (United States)

    The Office of Pesticide Programs models daily aquatic pesticide exposure values for 30 years in its risk assessments. However, only a fraction of that information is typically used in these assessments. The population model employed herein is a deterministic, density-dependent pe...

  8. Developing, Applying, and Evaluating Models for Rapid Screening of Chemical Exposures

    DEFF Research Database (Denmark)

    Arnot, J.; Shin, H.; Ernstoff, Alexi

    2015-01-01

    provides an introduction to underlying principles of some models used for exposure- and risk-based HTS for chemical prioritization for human health, including tools used in the ExpoDat project (USEtox, RAIDAR, CalTox) and other initiatives (SHEDS-HT). Case study examples of HTS include(i) model...

  9. COMPARING THE UTILITY OF MULTIMEDIA MODELS FOR HUMAN AND ECOLOGICAL EXPOSURE ANALYSIS: TWO CASES

    Science.gov (United States)

    A number of models are available for exposure assessment; however, few are used as tools for both human and ecosystem risks. This discussion will consider two modeling frameworks that have recently been used to support human and ecological decision making. The study will compare ...

  10. MODELING OF NATURAL VULNERABILITY TO EROSION THROUGH THE GEOGRAPHIC INFORMATION SYSTEMS IN MORRO DO CHAPÉU-BA

    Directory of Open Access Journals (Sweden)

    Jocimara Souza Britto Lobão

    2005-05-01

    Full Text Available The environment is always in permanent change keeping its proper dynamics with its own rhythms.However, when the people move themselves occupying specific locations, some transformations can take place, constituting threats for the environment and for the manhimself. These changes are related to the enviroment degradation, which has erosion as one of its most significant processes.To understand this dynamic, it is necessary to model the environment in a way that is possible to identify areas with different degrees of natural vulnerability to erosion and thus provide actions that relieve these impacts.The erosive processes are part of the lithosphere modeling system and have its intensity degree more stable or more intense according to the sum of several physical variables (lithology, leveling, landscape, rainfall and hydrography, biological variables (ecosystem- the type of the original and second growth vegetation and anthropogenic variables (the type of human occupation and mining activities.The impact of the rain on the soil has its effects reduced because of the vegetation and so the pedogenesis is benefited and the erosive processes minimized. On the other hand, if there is no vegetation or if this is insuficient, morphogenesis becomes more intense and theerosive processes enhanced.

  11. Modeling flight attendants' exposure to secondhand smoke in commercial aircraft: historical trends from 1955 to 1989.

    Science.gov (United States)

    Liu, Ruiling; Dix-Cooper, Linda; Hammond, S Katharine

    2015-01-01

    Flight attendants were exposed to elevated levels of secondhand smoke (SHS) in commercial aircraft when smoking was allowed on planes. During flight attendants' working years, their occupational SHS exposure was influenced by various factors, including the prevalence of active smokers on planes, fliers' smoking behaviors, airplane flight load factors, and ventilation systems. These factors have likely changed over the past six decades and would affect SHS concentrations in commercial aircraft. However, changes in flight attendants' exposure to SHS have not been examined in the literature. This study estimates the magnitude of the changes and the historic trends of flight attendants' SHS exposure in U.S. domestic commercial aircraft by integrating historical changes of contributing factors. Mass balance models were developed and evaluated to estimate flight attendants' exposure to SHS in passenger cabins, as indicated by two commonly used tracers (airborne nicotine and particulate matter (PM)). Monte Carlo simulations integrating historical trends and distributions of influence factors were used to simulate 10,000 flight attendants' exposure to SHS on commercial flights from 1955 to 1989. These models indicate that annual mean SHS PM concentrations to which flight attendants were exposed in passenger cabins steadily decreased from approximately 265 μg/m(3) in 1955 and 1960 to 93 μg/m(3) by 1989, and airborne nicotine exposure among flight attendants also decreased from 11.1 μg/m(3) in 1955 to 6.5 μg/m(3) in 1989. Using duration of employment as an indicator of flight attendants' cumulative occupational exposure to SHS in epidemiological studies would inaccurately assess their lifetime exposures and thus bias the relationship between the exposure and health effects. This historical trend should be considered in future epidemiological studies.

  12. A Model of Medical Countermeasures for Vesicant Exposure

    Science.gov (United States)

    2015-10-01

    lipophilic, can diffuse readily through the intracellular spaces of the stratum corneum, which are filled with lipids such as sebum, oils , waxes, as...does not decontaminate his skin or his eyes. The resulting injury to the eyes, lungs, and skin are shown in Figure 8-1. Figure 8-1. Eye, Lung, and...R.Vijayaraghavan, & S.C.Pant. (2011). Designing of mouse model: A new approach for studying sulphur mustard-induced skin lesions. Burns . Meier, H. M. (1998

  13. Assessment of Brown Bear\\'s (Ursus arctos syriacus Winter Habitat Using Geographically Weighted Regression and Generalized Linear Model in South of Iran

    Directory of Open Access Journals (Sweden)

    A. A. Zarei

    2016-03-01

    Full Text Available Winter dens are one of the important components of brown bear's (Ursus arctos syriacus habitat, affecting their reproduction and survival. Therefore identification of factors affecting the habitat selection and suitable denning areas in the conservation of our largest carnivore is necessary. We used Geographically Weighted Logistic Regression (GWLR and Generalized Linear Model (GLM for modeling suitability of denning habitat in Kouhkhom region in Fars province. In the present research, 20 dens (presence locations and 20 caves where signs of bear were not found (absence locations were used as dependent variables and six environmental factors were used for each location as independent variables. The results of GLM showed that variables of distance to settlements, altitude, and distance to water were the most important parameters affecting suitability of the brown bear's denning habitat. The results of GWLR showed the significant local variations in the relationship between occurrence of brown bear dens and the variable of distance to settlements. Based on the results of both models, suitable habitats for denning of the species are impassable areas in the mountains and inaccessible for humans.

  14. How many studies are necessary to compare niche-based models for geographic distributions? Inductive reasoning may fail at the end.

    Science.gov (United States)

    Terribile, L C; Diniz-Filho, J A F; De Marco, P

    2010-05-01

    The use of ecological niche models (ENM) to generate potential geographic distributions of species has rapidly increased in ecology, conservation and evolutionary biology. Many methods are available and the most used are Maximum Entropy Method (MAXENT) and the Genetic Algorithm for Rule Set Production (GARP). Recent studies have shown that MAXENT perform better than GARP. Here we used the statistics methods of ROC - AUC (area under the Receiver Operating Characteristics curve) and bootstrap to evaluate the performance of GARP and MAXENT in generate potential distribution models for 39 species of New World coral snakes. We found that values of AUC for GARP ranged from 0.923 to 0.999, whereas those for MAXENT ranged from 0.877 to 0.999. On the whole, the differences in AUC were very small, but for 10 species GARP outperformed MAXENT. Means and standard deviations for 100 bootstrapped samples with sample sizes ranging from 3 to 30 species did not show any trends towards deviations from a zero difference in AUC values of GARP minus AUC values of MAXENT. Ours results suggest that further studies are still necessary to establish under which circumstances the statistical performance of the methods vary. However, it is also important to consider the possibility that this empirical inductive reasoning may fail in the end, because we almost certainly could not establish all potential scenarios generating variation in the relative performance of models.

  15. Geographic Information System and Remote Sensing Approach with Hydrologic Rational Model for Flood Event Analysis in Jakarta

    Science.gov (United States)

    Aditya, M. R.; Hernina, R.; Rokhmatuloh

    2017-12-01

    Rapid development in Jakarta which generates more impervious surface has reduced the amount of rainfall infiltration into soil layer and increases run-off. In some events, continuous high rainfall intensity could create sudden flood in Jakarta City. This article used rainfall data of Jakarta during 10 February 2015 to compute rainfall intensity and then interpolate it with ordinary kriging technique. Spatial distribution of rainfall intensity then overlaid with run-off coefficient based on certain land use type of the study area. Peak run-off within each cell resulted from hydrologic rational model then summed for the whole study area to generate total peak run-off. For this study area, land use types consisted of 51.9 % industrial, 37.57% parks, and 10.54% residential with estimated total peak run-off 6.04 m3/sec, 0.39 m3/sec, and 0.31 m3/sec, respectively.

  16. Modeling the transmitted and stored energy in multilayer protective clothing under low-level radiant exposure

    International Nuclear Information System (INIS)

    Su, Yun; He, Jiazhen; Li, Jun

    2016-01-01

    Highlights: • A numerical model from heating source to skin tissues through multilayer fabric system is developed. • The numerical model is comprehensively validated with experimental data. • The model is used to investigate the relationship between the transmitted and stored energy and the influencing factors. - Abstract: A finite difference model was introduced to simulate the transmitted and stored energy in firefighters' protective clothing exposed to low-level thermal radiation. The model domain consists of a three-layer fire-resistant fabric system (outer shell, moisture barrier, and thermal liner), the human skin, and the air gap between clothing and the skin. The model accounted for the relationship between the transmitted heat during the exposure and the discharged heat during the cooling-down period. The numerical model predictions were compared with experimental data. Additionally, the parameters that affect the transmitted and stored energy of protective clothing were investigated. The results demonstrate that for the typical multilayer firefighter protective clothing, the transmitted heat during exposure and the discharged heat after exposure totally determine the skin burn under low-level heat exposure, especially for third-degree skin burns. The findings obtained in this study can be used to engineer fabric systems that provide better protection for the stored thermal burn.

  17. Geographical variation and the determinants of domestic endotoxin levels in mattress dust in Europe

    NARCIS (Netherlands)

    Chen, C.M.; Thiering, E.; Doekes, G.; Zock, J.P.; Bakolis, I.; Norbäck, D.; Sunyer, J.; Villani, S.; Verlato, G.; Täubel, M.; Jarvis, D.

    2012-01-01

    Endotoxin exposures have manifold effects on human health. The geographical variation and determinants of domestic endotoxin levels in Europe have not yet been extensively described. To investigate the geographical variation and determinants of domestic endotoxin concentrations in mattress dust in

  18. On the influence of the exposure model on organ doses

    International Nuclear Information System (INIS)

    Drexler, G.; Eckerl, H.

    1988-01-01

    Based on the design characteristics of the MIRD-V phantom, two sex-specific adult phantoms, ADAM and EVA were introduced especially for the calculation of organ doses resulting from external irradiation. Although the body characteristics of all the phantoms are in good agreement with those of the reference man and woman, they have some disadvantages related to the location and shape of organs and the form of the whole body. To overcome these disadvantages related to the location and shape of organs and form of the whole body. To overcome these disadvantages related to the location and shape of organs and the form of the whole body. To overcome these disadvantages and to obtain more realistic phantoms, a technique based on computer tomographic data (voxel-phantom) was developed. This technique allows any physical phantom or real body to be converted into computer files. The improvements are of special importance with regard to the skeleton, because a better modeling of the bone surfaces and separation of hard bone and bone marrow can be achieved. For photon irradiation, the sensitivity of the model on organ doses or the effective dose equivalent is important for operational radiation protection

  19. SAR exposure from UHF RFID reader in adult, child, pregnant woman, and fetus anatomical models.

    Science.gov (United States)

    Fiocchi, Serena; Markakis, Ioannis A; Ravazzani, Paolo; Samaras, Theodoros

    2013-09-01

    The spread of radio frequency identification (RFID) devices in ubiquitous applications without their simultaneous exposure assessment could give rise to public concerns about their potential adverse health effects. Among the various RFID system categories, the ultra high frequency (UHF) RFID systems have recently started to be widely used in many applications. This study addresses a computational exposure assessment of the electromagnetic radiation generated by a realistic UHF RFID reader, quantifying the exposure levels in different exposure scenarios and subjects (two adults, four children, and two anatomical models of women 7 and 9 months pregnant). The results of the computations are presented in terms of the whole-body and peak spatial specific absorption rate (SAR) averaged over 10 g of tissue to allow comparison with the basic restrictions of the exposure guidelines. The SAR levels in the adults and children were below 0.02 and 0.8 W/kg in whole-body SAR and maximum peak SAR levels, respectively, for all tested positions of the antenna. On the contrary, exposure of pregnant women and fetuses resulted in maximum peak SAR(10 g) values close to the values suggested by the guidelines (2 W/kg) in some of the exposure scenarios with the antenna positioned in front of the abdomen and with a 100% duty cycle and 1 W radiated power. Copyright © 2013 Wiley Periodicals, Inc.

  20. Estimation of occupational and nonoccupational nitrogen dioxide exposure for Korean taxi drivers using a microenvironmental model

    International Nuclear Information System (INIS)

    Son, Busoon; Yang, Wonho; Breysse, Patrick; Chung, Taewoong; Lee, Youngshin

    2004-01-01

    Occupational and nonoccupational personal nitrogen dioxide (NO 2 ) exposures were measured using passive samplers for 31 taxi drivers in Asan and Chunan, Korea. Exposures were also estimated using a microenvironmental time-weighted average model based on indoor, outdoor and inside the taxi area measurements. Mean NO 2 indoor and outdoor concentrations inside and outside the taxi drivers' houses were 24.7±10.7 and 23.3±8.3 ppb, respectively, with a mean indoor to outdoor NO 2 ratio of 1.1. Mean personal NO 2 exposure of taxi drivers was 30.3±9.7 ppb. Personal NO 2 exposures for drivers were more strongly correlated with interior vehicle NO 2 levels (r=0.89) rather than indoor residential NO 2 levels (r=0.74) or outdoor NO 2 levels (r=0.71). The main source of NO 2 exposure for taxi drivers was considered to be occupational driving. Interestingly, the NO 2 exposures for drivers' using LPG-fueled vehicles (26.3±1.3 ppb) were significantly lower than those (38.1±1.3 ppb) using diesel-fueled vehicle (P 2 exposure with indoor and outdoor NO 2 levels of the residence, and interior vehicle NO 2 levels (P 2 levels because they drive diesel-using vehicles outdoors in Korea

  1. Modeling human exposure to hazardous-waste sites: a question of completeness

    International Nuclear Information System (INIS)

    Daniels, J.I.; McKone, T.E.

    1991-01-01

    In risk analysis, we use human-exposure assessments to translate contaminant sources into quantitative estimates of the amount of contaminant that comes in contact with human-environment boundaries, that is, the lungs, the gastrointestinal tract, and the skin surface of individuals within a specified population. An assessment of intake requires that we determine how much crosses these boundaries. Exposure assessments often rely implicitly in the assumption that exposure can be linked by simple parameters to ambient concentration in air, water, and soil. However, more realistic exposure models require that we abandon such simple assumptions. To link contaminant concentrations in water, air, or soil with potential human intakes, we constrict pathway-exposure factors (PEFs). For each PEF we combine information in environmental partitioning as well as human anatomy, physiology, and patterns into an algebraic term that converts concentrations of contaminants (in mg/L water, mg/m 3 air, and mg/kg soil) into a daily intake per unit body weight in mg/kg-d for a specific rout of exposure such as inhalation, ingestion, or dermal uptake. Using examples involving human exposure to either a radionuclide (tritium, 3 H) or a toxic organic chemical (tetrachloroethylene, PCE) in soil, water, and air, we illustrate the use of PEFs and consider the implications for risk assessment. (au)

  2. The preparation of landslide map by Landslide Numerical Risk Factor (LNRF model and Geographic Information System (GIS

    Directory of Open Access Journals (Sweden)

    Ali Mohammadi Torkashvand

    2014-12-01

    Full Text Available One of the risks to threaten mountainous areas is that hillslope instability caused damage to lands. One of the most dangerous instabilities is mass movement and much movement occurs due to slip. The aim of this study is zonation of landslide hazards in a basin of the Ardebil province, the eastern slopes of Sabalan, Iran. Geological and geomorphologic conditions, climate and type of land use have caused susceptibility of this watershed to landslides. Firstly, maps of the main factors affecting landslide occurrence including slope, distance from faults, lithology, elevation and precipitation were prepared and digitized. Then, by using interpretation of aerial photos and satellite images and field views, the ground truth map of landslides was prepared. Each basic layer (factor and landslide map were integrated to compute the numeric value of each factor with the help of a Landslide Numerical Risk Factor (LNRF model and landslide occurrence percent obtained in different units from each of the maps. Finally, with overlapping different data layers, a landslide hazard zonation map was prepared. Results showed that 67.85% of the basin has high instability, 7.76% moderate instability and 24.39% low instability.

  3. Predictive models for the assessment of occupational exposure to chemicals: A new challenge for employers

    Directory of Open Access Journals (Sweden)

    Jan Piotr Gromiec

    2013-10-01

    Full Text Available Employers are obliged to carry out and document the risk associated with the use of chemical substances. The best but the most expensive method is to measure workplace concentrations of chemicals. At present no "measureless" method for risk assessment is available in Poland, but predictive models for such assessments have been developed in some countries. The purpose of this work is to review and evaluate the applicability of selected predictive methods for assessing occupational inhalation exposure and related risk to check the compliance with Occupational Exposure Limits (OELs, as well as the compliance with REACH obligations. Based on the literature data HSE COSHH Essentials, EASE, ECETOC TRA, Stoffenmanager, and EMKG-Expo-Tool were evaluated. The data on validation of predictive models were also examined. It seems that predictive models may be used as a useful method for Tier 1 assessment of occupational exposure by inhalation. Since the levels of exposure are frequently overestimated, they should be considered as "rational worst cases" for selection of proper control measures. Bearing in mind that the number of available exposure scenarios and PROC categories is limited, further validation by field surveys is highly recommended. Predictive models may serve as a good tool for preliminary risk assessment and selection of the most appropriate risk control measures in Polish small and medium size enterprises (SMEs providing that they are available in the Polish language. This also requires an extensive training of their future users. Med Pr 2013;64(5:699–716

  4. Modeled occupational exposures to gas-phase medical laser-generated air contaminants.

    Science.gov (United States)

    Lippert, Julia F; Lacey, Steven E; Jones, Rachael M

    2014-01-01

    Exposure monitoring data indicate the potential for substantive exposure to laser-generated air contaminants (LGAC); however the diversity of medical lasers and their applications limit generalization from direct workplace monitoring. Emission rates of seven previously reported gas-phase constituents of medical laser-generated air contaminants (LGAC) were determined experimentally and used in a semi-empirical two-zone model to estimate a range of plausible occupational exposures to health care staff. Single-source emission rates were generated in an emission chamber as a one-compartment mass balance model at steady-state. Clinical facility parameters such as room size and ventilation rate were based on standard ventilation and environmental conditions required for a laser surgical facility in compliance with regulatory agencies. All input variables in the model including point source emission rates were varied over an appropriate distribution in a Monte Carlo simulation to generate a range of time-weighted average (TWA) concentrations in the near and far field zones of the room in a conservative approach inclusive of all contributing factors to inform future predictive models. The concentrations were assessed for risk and the highest values were shown to be at least three orders of magnitude lower than the relevant occupational exposure limits (OELs). Estimated values do not appear to present a significant exposure hazard within the conditions of our emission rate estimates.

  5. Evaluation of Refuge Life Risk using Geographical and Social Grid-Models with Satellite-Based House Ratio and Flood Depth by Tsunami Simulation

    Science.gov (United States)

    Kaneko, D.; Hosoyamada, T.

    2017-12-01

    The authors have developed social and geographical models for evaluating and applying life risk to the Kamakura coast near the south-western part of the metropolitan areas of Tokyo. The coastline close to the seismic center of the South Kanto earthquake is in the riskiest belt in the metropolitan area with a high possibility of house collapse and tsunami run-up. Kamakura is an important historical city, visited by many tourists who are not familiar with seismic dangers. There is a high probability of loss of human life during an evacuation of the city during tsunami waves. To evaluate the distribution of life risk characteristics in the area, models for citizens and sightseers are developed that includes social data such as population density, wooden-house ratio, and geographical evacuation distance and tsunami-flooding depth. The population of Kamakura City is 174,050 and the risk of tsunami evacuation is high in the area from the southern part of Kamakura Station to Zaimokuza block, where the population is approximately 15,310 people. There are about 26,000 tourists visiting this area on weekdays and about 100,000 sightseers visiting the area on Saturdays and Sundays. On weekdays the population per mesh will increase by half of the 2,000 inhabitants. On Saturdays and Sundays the population density will be 4 thousand who will double those of the inhabitants. A disaster prevention hill is proposed as a tsunami countermeasure on the coast of Kamakura City. The hill is covered by pine forest with a high-standard road, evacuation center, and sightseeing parking lots embedded in the hilly bank. In normal times, tourists and citizens use this area as a seaside pine park. Long concrete box structures strengthen the hill inside the mound, which has two levels, the lower equipped with high-standard-width roads on the ground level. The parking areas will resolve daily traffic congestion issues along the Kamakura main streets. The evaluation of over-flooding tsunamis and

  6. Updating flood maps efficiently using existing hydraulic models, very-high-accuracy elevation data, and a geographic information system; a pilot study on the Nisqually River, Washington

    Science.gov (United States)

    Jones, Joseph L.; Haluska, Tana L.; Kresch, David L.

    2001-01-01

    A method of updating flood inundation maps at a fraction of the expense of using traditional methods was piloted in Washington State as part of the U.S. Geological Survey Urban Geologic and Hydrologic Hazards Initiative. Large savings in expense may be achieved by building upon previous Flood Insurance Studies and automating the process of flood delineation with a Geographic Information System (GIS); increases in accuracy and detail result from the use of very-high-accuracy elevation data and automated delineation; and the resulting digital data sets contain valuable ancillary information such as flood depth, as well as greatly facilitating map storage and utility. The method consists of creating stage-discharge relations from the archived output of the existing hydraulic model, using these relations to create updated flood stages for recalculated flood discharges, and using a GIS to automate the map generation process. Many of the effective flood maps were created in the late 1970?s and early 1980?s, and suffer from a number of well recognized deficiencies such as out-of-date or inaccurate estimates of discharges for selected recurrence intervals, changes in basin characteristics, and relatively low quality elevation data used for flood delineation. FEMA estimates that 45 percent of effective maps are over 10 years old (FEMA, 1997). Consequently, Congress has mandated the updating and periodic review of existing maps, which have cost the Nation almost 3 billion (1997) dollars. The need to update maps and the cost of doing so were the primary motivations for piloting a more cost-effective and efficient updating method. New technologies such as Geographic Information Systems and LIDAR (Light Detection and Ranging) elevation mapping are key to improving the efficiency of flood map updating, but they also improve the accuracy, detail, and usefulness of the resulting digital flood maps. GISs produce digital maps without manual estimation of inundated areas between

  7. Spatial-temporal modeling of the association between air pollution exposure and preterm birth: identifying critical windows of exposure.

    Science.gov (United States)

    Warren, Joshua; Fuentes, Montserrat; Herring, Amy; Langlois, Peter

    2012-12-01

    Exposure to high levels of air pollution during the pregnancy is associated with increased probability of preterm birth (PTB), a major cause of infant morbidity and mortality. New statistical methodology is required to specifically determine when a particular pollutant impacts the PTB outcome, to determine the role of different pollutants, and to characterize the spatial variability in these results. We develop a new Bayesian spatial model for PTB which identifies susceptible windows throughout the pregnancy jointly for multiple pollutants (PM(2.5) , ozone) while allowing these windows to vary continuously across space and time. We geo-code vital record birth data from Texas (2002-2004) and link them with standard pollution monitoring data and a newly introduced EPA product of calibrated air pollution model output. We apply the fully spatial model to a region of 13 counties in eastern Texas consisting of highly urban as well as rural areas. Our results indicate significant signal in the first two trimesters of pregnancy with different pollutants leading to different critical windows. Introducing the spatial aspect uncovers critical windows previously unidentified when space is ignored. A proper inference procedure is introduced to correctly analyze these windows. © 2012, The International Biometric Society.

  8. Frequency of sucrose exposure on the cariogenicity of a biofilm-caries model

    Science.gov (United States)

    Díaz-Garrido, Natalia; Lozano, Carla; Giacaman, Rodrigo A.

    2016-01-01

    Objective: Although sucrose is considered the most cariogenic carbohydrate in the human diet, the question of how many exposures are needed to induce damage on the hard dental tissues remains unclear. To approach this question, different frequencies of daily sucrose exposure were tested on a relevant biological caries model. Materials and Methods: Biofilms of the Streptococcus mutans were formed on enamel slabs and exposed to cariogenic challenges with 10% sucrose for 5 min at 0, 1, 3, 5, 8, or 10 times per day. After 5 days, biofilms were retrieved to analyze biomass, protein content, viable bacteria, and polysaccharide formation. Enamel demineralization was evaluated by percentage of microhardness loss (percentage surface hardness loss [%SHL]). Results: Biomass, protein content, polysaccharide production, acidogenicity of the biofilm, and %SHL proportionally increased with the number of daily exposures to sucrose (P 0.05). Conclusions: Higher sucrose exposure seems to increase cariogenicity, in a frequency-dependent manner, by the modification of bacterial virulent properties. PMID:27403051

  9. EXPURT - a model for evaluating exposure from radioactive material deposited in the urban environment

    International Nuclear Information System (INIS)

    Crick, M.J.; Brown, J.

    1990-06-01

    This model, EXPURT (EXPosure from Urban Radionuclide Transfer), is described in detail. The model simulates the movement of activity deposited on various surfaces in the urban environment and, by taking into account the shielding properties of buildings and the habits of the population, evaluates the external doses to members of the population living in such urban environments, as a function of time after deposition. One of the other advantages of EXPURT over simpler models is that it can be used to assess the possible dose reductions that might be achieved by various decontamination techniques; for example, it can estimate the effectiveness of decontaminating roof surfaces alone in reducing exposure to individuals living in an urban environment. Sensitivity/uncertainty studies have been performed whereby those parameters contributing most to remaining uncertainty in the model's predictions of dose and dose rates were identified. Predictions of the EXPURT model were compared with those from a simpler external dose model in use at NRPB. (author)

  10. Estimating overall exposure effects for the clustered and censored outcome using random effect Tobit regression models.

    Science.gov (United States)

    Wang, Wei; Griswold, Michael E

    2016-11-30

    The random effect Tobit model is a regression model that accommodates both left- and/or right-censoring and within-cluster dependence of the outcome variable. Regression coefficients of random effect Tobit models have conditional interpretations on a constructed latent dependent variable and do not provide inference of overall exposure effects on the original outcome scale. Marginalized random effects model (MREM) permits likelihood-based estimation of marginal mean parameters for the clustered data. For random effect Tobit models, we extend the MREM to marginalize over both the random effects and the normal space and boundary components of the censored response to estimate overall exposure effects at population level. We also extend the 'Average Predicted Value' method to estimate the model-predicted marginal means for each person under different exposure status in a designated reference group by integrating over the random effects and then use the calculated difference to assess the overall exposure effect. The maximum likelihood estimation is proposed utilizing a quasi-Newton optimization algorithm with Gauss-Hermite quadrature to approximate the integration of the random effects. We use these methods to carefully analyze two real datasets. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  11. An Agent-Based Modeling Framework for Simulating Human Exposure to Environmental Stresses in Urban Areas

    Directory of Open Access Journals (Sweden)

    Liang Emlyn Yang

    2018-04-01

    Full Text Available Several approaches have been used to assess potential human exposure to environmental stresses and achieve optimal results under various conditions, such as for example, for different scales, groups of people, or points in time. A thorough literature review in this paper identifies the research gap regarding modeling approaches for assessing human exposure to environment stressors, and it indicates that microsimulation tools are becoming increasingly important in human exposure assessments of urban environments, in which each person is simulated individually and continuously. The paper further describes an agent-based model (ABM framework that can dynamically simulate human exposure levels, along with their daily activities, in urban areas that are characterized by environmental stresses such as air pollution and heat stress. Within the framework, decision-making processes can be included for each individual based on rule-based behavior in order to achieve goals under changing environmental conditions. The ideas described in this paper are implemented in a free and open source NetLogo platform. A basic modeling scenario of the ABM framework in Hamburg, Germany, demonstrates its utility in various urban environments and individual activity patterns, as well as its portability to other models, programs, and frameworks. The prototype model can potentially be extended to support environmental incidence management through exploring the daily routines of different groups of citizens, and comparing the effectiveness of different strategies. Further research is needed to fully develop an operational version of the model.

  12. GEOGRAPHIC INFORMATION SYSTEM-BASED MODELING AND ANALYSIS FOR SITE SELECTION OF GREEN MUSSEL, Perna viridis, MARICULTURE IN LADA BAY, PANDEGLANG, BANTEN PROVINCE

    Directory of Open Access Journals (Sweden)

    I Nyoman Radiarta

    2011-06-01

    Full Text Available Green mussel is one of important species cultured in Lada Bay, Pandeglang. To provide a necessary guidance regarding green mussel mariculture development, finding suitable site is an important step. This study was conducted to identify suitable site for green mussel mariculture development using geographic information system (GIS based models. Seven important parameters were grouped into two submodels, namely environmental (water temperature, salinity, suspended solid, dissolve oxygen, and bathymetry and infrastructural (distance to settlement and pond aquaculture. A constraint data was used to exclude the area from suitability maps that cannot be allowed to develop green mussel mariculture, including area of floating net fishing activity and area near electricity station. Analyses of factors and constraints indicated that about 31% of potential area with bottom depth less than 25 m had the most suitable area. This area was shown to have an ideal condition for green mussel mariculture in this study region. This study shows that GIS model is a powerful tool for site selection decision making. The tool can be a valuable tool in solving problems in local, regional, and/or continent areas.

  13. Simvastatin Exposure and Rotator Cuff Repair in a Rat Model.

    Science.gov (United States)

    Deren, Matthew E; Ehteshami, John R; Dines, Joshua S; Drakos, Mark C; Behrens, Steve B; Doty, Stephen; Coleman, Struan H

    2017-03-01

    Simvastatin is a common medication prescribed for hypercholesterolemia that accelerates local bone formation. It is unclear whether simvastatin can accelerate healing at the tendon-bone interface after rotator cuff repair. This study was conducted to investigate whether local and systemic administration of simvastatin increased tendon-bone healing of the rotator cuff as detected by maximum load to failure in a controlled animal-based model. Supraspinatus tendon repair was performed on 120 Sprague-Dawley rats. Sixty rats had a polylactic acid membrane overlying the repair site. Of these, 30 contained simvastatin and 30 did not contain medication. Sixty rats underwent repair without a polylactic acid membrane. Of these, 30 received oral simvastatin (25 mg/kg/d) and 30 received a regular diet. At 4 weeks, 5 rats from each group were killed for histologic analysis. At 8 weeks, 5 rats from each group were killed for histologic analysis and the remaining 20 rats were killed for biomechanical analysis. One rat that received oral simvastatin died of muscle necrosis. Average maximum load to failure was 35.2±6.2 N for those receiving oral simvastatin, 36.8±9.0 N for oral control subjects, 39.5±12.8 N for those receiving local simvastatin, and 39.1±9.3 N for control subjects with a polylactic acid membrane. No statistically significant differences were found between any of the 4 groups (P>.05). Qualitative histologic findings showed that all groups showed increased collagen formation and organization at 8 weeks compared with 4 weeks, with no differences between the 4 groups at each time point. The use of systemic and local simvastatin offered no benefit over control groups. [Orthopedics. 2017; 40(2):e288-e292.]. Copyright 2016, SLACK Incorporated.

  14. The evolution of cooperation on geographical networks

    Science.gov (United States)

    Li, Yixiao; Wang, Yi; Sheng, Jichuan

    2017-11-01

    We study evolutionary public goods game on geographical networks, i.e., complex networks which are located on a geographical plane. The geographical feature effects in two ways: In one way, the geographically-induced network structure influences the overall evolutionary dynamics, and, in the other way, the geographical length of an edge influences the cost when the two players at the two ends interact. For the latter effect, we design a new cost function of cooperators, which simply assumes that the longer the distance between two players, the higher cost the cooperator(s) of them have to pay. In this study, network substrates are generated by a previous spatial network model with a cost-benefit parameter controlling the network topology. Our simulations show that the greatest promotion of cooperation is achieved in the intermediate regime of the parameter, in which empirical estimates of various railway networks fall. Further, we investigate how the distribution of edges' geographical costs influences the evolutionary dynamics and consider three patterns of the distribution: an approximately-equal distribution, a diverse distribution, and a polarized distribution. For normal geographical networks which are generated using intermediate values of the cost-benefit parameter, a diverse distribution hinders the evolution of cooperation, whereas a polarized distribution lowers the threshold value of the amplification factor for cooperation in public goods game. These results are helpful for understanding the evolution of cooperation on real-world geographical networks.

  15. Social-geographic approaches to application of economic-mathematical modeling in predicting the place of Ukrainian farming economies in food market commoditization

    Directory of Open Access Journals (Sweden)

    Valeriy Rudenko

    2017-11-01

    Full Text Available Social-geographic analysis of farmery with application of economic-mathematical modeling allowed for prediction of farming economies’ role in food market commoditization. The equation of potential demand was suggested. Actual consumption and its recommended rates with respect to meat and meat products, milk and milk products, eggs, fish and fish products, bread and cereal products, potatoes, vegetables, fruits and berries, etc, were compared. Cartographic model of Ukrainian domestic food market’s potential capacity (within good-money relations was developed. The low level of purchasing power, especially in rural population, makes a high percentage of foodstuffs be beyond the goods-money relations. In rural areas, they (inclusive of farmers produce and consume a significant portion of foodstuffs that escaped the goods-money relations, or such foodstuffs were given to them by the relatives. We regard that in the process of assessment of the capacity of domestic food market, this share of products should also be taken into account. The assessment also necessitates consideration of the number of urban and rural population in Ukrainian regions; manufacturing of certain types of agricultural production; needs in this or that type of product as prescribed by minimal and rational consumption rates. When predicting, with the use of economic-mathematical modeling, the places of farming economies in commoditization of food market, it is reasonable to apply the parameters of time series of the number of farming economies and the areas of lands used by them with consideration of the dynamics of population number and the level of its (population self-provision with agricultural production. Application of predictive linear models shows that the share of production manufactured by farming economies will be most essential before 2020 on the market of potatoes and vegetables (reaching 15 %. Despite the predicted double increase in animal production, its share

  16. Significant geographic gradients in particulate sulfate over Japan determined from multiple-site measurements and a chemical transport model: Impacts of transboundary pollution from the Asian continent

    Science.gov (United States)

    Aikawa, Masahide; Ohara, Toshimasa; Hiraki, Takatoshi; Oishi, Okihiro; Tsuji, Akihiro; Yamagami, Makiko; Murano, Kentaro; Mukai, Hitoshi

    2010-01-01

    We found a significant geographic gradient (longitudinal and latitudinal) in the sulfate (SO 42-) concentrations measured at multiple sites over the East Asian Pacific Rim region. Furthermore, the observed gradient was well reproduced by a regional chemical transport model. The observed and modeled SO 42- concentrations were higher at the sites closer to the Asian continent. The concentrations of SO 42- from China as calculated by the model also showed the fundamental features of the longitudinal/latitudinal gradient. The proportional contribution of Chinese SO 42- to the total in Japan throughout the year was above 50-70% in the control case, using data for Chinese sulfur dioxide (SO 2) emission from the Regional Emission Inventory in Asia (40-60% in the low Chinese emissions case, using Chinese SO 2 emissions data from the State Environmental Protection Administration of China), with a winter maximum of approximately 65-80%, although the actual concentrations of SO 42- from China were highest in summer. The multiple-site measurements and the model analysis strongly suggest that the SO 42- concentrations in Japan were influenced by the outflow from the Asian continent, and this influence was greatest in the areas closer to the Asian continent. In contrast, we found no longitudinal/latitudinal gradient in SO 2 concentrations; instead SO 2 concentrations were significantly correlated with local SO 2 emissions. Our results show that large amounts of particulate sulfate are transported over long distances from the East Asian Pacific Rim region, and consequently the SO 42- concentrations in Japan are controlled by the transboundary outflow from the Asian continent.

  17. Exposure assessment and modeling of particulate matter for asthmatic children using personal nephelometers

    Science.gov (United States)

    Wu, Chang-Fu; Delfino, Ralph J.; Floro, Joshua N.; Quintana, Penelope J. E.; Samimi, Behzad S.; Kleinman, Michael T.; Allen, Ryan W.; Sally Liu, L.-J.

    It has been shown that acute exposures to particulate matter (PM) may exacerbate asthma in children. However, most epidemiological studies have relied on time-integrated PM measurements taken at a centrally located stationary monitoring sites. In this article, we characterized children's short-term personal exposures to PM 2.5 (PM with aerodynamic diameters size-selective inlet was used to estimate real-time PM 2.5 concentrations on 20 asthmatic children, inside and outside of their residences, and at a central site. The personal and indoor pDRs were operated passively, while the home outdoor and central site instruments were operated actively. The subjects received 29.2% of their exposures at school, even though they only spent 16.4% of their time there. More precise personal clouds were estimated for the home-indoor and home-outdoor microenvironments where PM concentrations were measured. The personal cloud increased with increasing activity levels and was higher during outdoor activities than during indoor activities. We built models to predict personal PM exposures based on either microenvironmental or central-site PM 2.5 measurements, and evaluated the modeled exposures against the actual personal measurements. A multiple regression model with central site PM concentration as the main predictor had a better prediction power ( R2=0.41) than a three-microenvironmental model ( R2=0.11). We further constructed a source-specific exposure model utilizing the time-space-activity information and the particle infiltration efficiencies (mean=0.72±0.15) calculated from a recursive mass balance model. It was estimated that the mean hourly personal exposures resulting from ambient, indoor-generated, and personal activity PM 2.5 were 11.1, 5.5, and 10.0 μg/m 3, respectively, when the modeling error was minimized. The high PM 2.5 exposure to personal activities reported in our study is likely due to children's more active lifestyle as compared with older adult subjects in

  18. Dermal Exposure Assessment to Pesticides in Farming Systems in Developing Countries: Comparison of Models

    Directory of Open Access Journals (Sweden)

    Camilo Lesmes Fabian

    2015-04-01

    Full Text Available In the field of occupational hygiene, researchers have been working on developing appropriate methods to estimate human exposure to pesticides in order to assess the risk and therefore to take the due decisions to improve the pesticide management process and reduce the health risks. This paper evaluates dermal exposure models to find the most appropriate. Eight models (i.e., COSHH, DERM, DREAM, EASE, PHED, RISKOFDERM, STOFFENMANAGER and PFAM were evaluated according to a multi-criteria analysis and from these results five models (i.e., DERM, DREAM, PHED, RISKOFDERM and PFAM were selected for the assessment of dermal exposure in the case study of the potato farming system in the Andean highlands of Vereda La Hoya, Colombia. The results show that the models provide different dermal exposure estimations which are not comparable. However, because of the simplicity of the algorithm and the specificity of the determinants, the DERM, DREAM and PFAM models were found to be the most appropriate although their estimations might be more accurate if specific determinants are included for the case studies in developing countries.

  19. Accounting for misclassification in electronic health records-derived exposures using generalized linear finite mixture models.

    Science.gov (United States)

    Hubbard, Rebecca A; Johnson, Eric; Chubak, Jessica; Wernli, Karen J; Kamineni, Aruna; Bogart, Andy; Rutter, Carolyn M

    2017-06-01

    Exposures derived from electronic health records (EHR) may be misclassified, leading to biased estimates of their association with outcomes of interest. An example of this problem arises in the context of cancer screening where test indication, the purpose for which a test was performed, is often unavailable. This poses a challenge to understanding the effectiveness of screening tests because estimates of screening test effectiveness are biased if some diagnostic tests are misclassified as screening. Prediction models have been developed for a variety of exposure variables that can be derived from EHR, but no previous research has investigated appropriate methods for obtaining unbiased association estimates using these predicted probabilities. The full likelihood incorporating information on both the predicted probability of exposure-class membership and the association between the exposure and outcome of interest can be expressed using a finite mixture model. When the regression model of interest is a generalized linear model (GLM), the expectation-maximization algorithm can be used to estimate the parameters using standard software for GLMs. Using simulation studies, we compared the bias and efficiency of this mixture model approach to alternative approaches including multiple imputation and dichotomization of the predicted probabilities to create a proxy for the missing predictor. The mixture model was the only approach that was unbiased across all scenarios investigated. Finally, we explored the performance of these alternatives in a study of colorectal cancer screening with colonoscopy. These findings have broad applicability in studies using EHR data where gold-standard exposures are unavailable and prediction models have been developed for estimating proxies.

  20. A Comparison of Item Selection Techniques and Exposure Control Mechanisms in CATs Using the Generalized Partial Credit Model.

    Science.gov (United States)

    Pastor, Dena A.; Dodd, Barbara G.; Chang, Hua-Hua

    2002-01-01

    Studied the impact of using five different exposure control algorithms in two sizes of item pool calibrated using the generalized partial credit model. Simulation results show that the a-stratified design, in comparison to a no-exposure control condition, could be used to reduce item exposure and overlap and increase pool use, while degrading…

  1. CHILDREN'S RESIDENTIAL EXPOSURE TO CHLORPYRIFOS: APPLICATION OF CPPAES FIELD MEASUREMENTS OF CHLORPYRIFOS AND TCPY WITHIN MENTOR/SHEDS PESTICIDES MODEL

    Science.gov (United States)

    The comprehensive individual field-measurements on non-dietary exposure collected in the Children's-Post-Pesticide-Application-Exposure-Study (CPPAES) were used within MENTOR/SHEDS-Pesticides, a physically based stochastic human exposure and dose model. In this application, howev...

  2. A PROBABILISTIC EXPOSURE ASSESSMENT FOR CHILDREN WHO CONTACT CCA-TREATED PLAYSETS AND DECKS USING THE STOCHASTIC HUMAN EXPOSURE AND DOSE SIMULATION (SHEDS) MODEL FOR THE WOOD PRESERVATIVE EXPOSURE SCENARIO

    Science.gov (United States)

    The U.S. Environmental Protection Agency has conducted a probabilistic exposure and dose assessment on the arsenic (As) and chromium (Cr) components of Chromated Copper Arsenate (CCA) using the Stochastic Human Exposure and Dose Simulation model for wood preservatives (SHEDS-Wood...

  3. Modeling The Inhalation Exposure Pathway In Performance Assessment Of Geologic Radioactive Waste Repository At Yucca Mountain

    International Nuclear Information System (INIS)

    M.A. Wasiolek

    2006-01-01

    Inhalation exposure pathway modeling has recently been investigated as one of the tasks of the BIOPROTA Project (BIOPROTA 2005). BIOPROTA was set up to address the key uncertainties in long term assessments of contaminant releases into the environment arising from radioactive waste disposal. Participants of this international Project include national authorities and agencies, both regulators and operators, with responsibility for achieving safe and acceptable radioactive waste management. The objective of the inhalation task was to investigate the calculation of doses arising from inhalation of particles suspended from soils within which long-lived radionuclides, particularly alpha emitters, had accumulated. It was recognized that site-specific conditions influence the choice of conceptual model and input parameter values. Therefore, one of the goals of the task was to identify the circumstances in which different processes included in specific inhalation exposure pathway models were important. This paper discusses evaluation of processes and modeling assumptions specific to the proposed repository at Yucca Mountain as compared to the typical approaches and other models developed for different assessments and project specific contexts. Inhalation of suspended particulates that originate from contaminated soil is an important exposure pathway, particularly for exposure to actinides such as uranium, neptunium and plutonium. Radionuclide accumulation in surface soil arises from irrigation of soil with contaminated water over many years. The level of radionuclide concentration in surface soil depends on the assumed duration of irrigation. Irrigation duration is one of the parameters used on biosphere models and it depends on a specific assessment context. It is one of the parameters addressed in this paper from the point of view of assessment context for the proposed repository at Yucca Mountain. The preferred model for the assessment of inhalation exposure uses

  4. Examining the Pathologic Adaptation Model of Community Violence Exposure in Male Adolescents of Color

    Science.gov (United States)

    Gaylord-Harden, Noni K.; So, Suzanna; Bai, Grace J.; Henry, David B.; Tolan, Patrick H.

    2017-01-01

    The current study examined a model of desensitization to community violence exposure—the pathologic adaptation model—in male adolescents of color. The current study included 285 African American (61%) and Latino (39%) male adolescents (W1 M age = 12.41) from the Chicago Youth Development Study to examine the longitudinal associations between community violence exposure, depressive symptoms, and violent behavior. Consistent with the pathologic adaptation model, results indicated a linear, positive association between community violence exposure in middle adolescence and violent behavior in late adolescence, as well as a curvilinear association between community violence exposure in middle adolescence and depressive symptoms in late adolescence, suggesting emotional desensitization. Further, these effects were specific to cognitive-affective symptoms of depression and not somatic symptoms. Emotional desensitization outcomes, as assessed by depressive symptoms, can occur in male adolescents of color exposed to community violence and these effects extend from middle adolescence to late adolescence. PMID:27653968

  5. Heavy Metal Exposure and Metabolic Syndrome: Evidence from Human and Model System Studies.

    Science.gov (United States)

    Planchart, Antonio; Green, Adrian; Hoyo, Cathrine; Mattingly, Carolyn J

    2018-03-01

    Metabolic syndrome (MS) describes the co-occurrence of conditions that increase one's risk for heart disease and other disorders such as diabetes and stroke. The worldwide increase in the prevalence of MS cannot be fully explained by lifestyle factors such as sedentary behavior and caloric intake alone. Environmental exposures, such as heavy metals, have been implicated, but results are conflicting and possible mechanisms remain unclear. To assess recent progress in determining a possible role between heavy metal exposure and MS, we reviewed epidemiological and model system data for cadmium (Cd), lead (Pb), and mercury (Hg) from the last decade. Data from 36 epidemiological studies involving 17 unique countries/regions and 13 studies leveraging model systems are included in this review. Epidemiological and model system studies support a possible association between heavy metal exposure and MS or comorbid conditions; however, results remain conflicting. Epidemiological studies were predominantly cross-sectional and collectively, they highlight a global interest in this question and reveal evidence of differential susceptibility by sex and age to heavy metal exposures. In vivo studies in rats and mice and in vitro cell-based assays provide insights into potential mechanisms of action relevant to MS including altered regulation of lipid and glucose homeostasis, adipogenesis, and oxidative stress. Heavy metal exposure may contribute to MS or comorbid conditions; however, available data are conflicting. Causal inference remains challenging as epidemiological data are largely cross-sectional; and variation in study design, including samples used for heavy metal measurements, age of subjects at which MS outcomes are measured; the scope and treatment of confounding factors; and the population demographics vary widely. Prospective studies, standardization or increased consistency across study designs and reporting, and consideration of molecular mechanisms informed by model

  6. Lung cancer attributable to indoor radon exposure in France using different risk models

    International Nuclear Information System (INIS)

    Catelinois, O.C.; Laurier, D.L.; Rogel, A.R.; Billon, S.B.; Tirmarche, M.T.; Hemon, Dh.; Verger, P.V.

    2006-01-01

    allowing to perform a sensibility analysis according to the geographical level of calculation. Uncertainties associated to risk coefficients and exposures have been quantified and it impact on risk estimates is calculated. The estimated number of deaths attributable to domestic radon exposure ranges from 1,234 (90 % uncertainty interval (UI): 593 2,156) to 3,108 (90 % UI: 2,996 3,221). The corresponding risk fractions range from 5 % (90 % UI: 2 % - 9 %) to 12.4 % (90 % UI: 11.9 % - 12.8 %). This work provides an adaptation of the classical risk assessment method integrating each of its step such as a discussion about the choice of the dose - response relationship. The data analysis considers the interaction between ionizing radiation and other risk factors and a quantification of uncertainties. This work provides new results showing the importance of the choice of the dose-response relationship and of the quantification of uncertainties in risk assessment. (authors)

  7. Personal Exposure to Mixtures of Volatile Organic Compounds: Modeling and Further Analysis of the RIOPA Data

    Science.gov (United States)

    Batterman, Stuart; Su, Feng-Chiao; Li, Shi; Mukherjee, Bhramar; Jia, Chunrong

    2015-01-01

    INTRODUCTION Emission sources of volatile organic compounds (VOCs) are numerous and widespread in both indoor and outdoor environments. Concentrations of VOCs indoors typically exceed outdoor levels, and most people spend nearly 90% of their time indoors. Thus, indoor sources generally contribute the majority of VOC exposures for most people. VOC exposure has been associated with a wide range of acute and chronic health effects; for example, asthma, respiratory diseases, liver and kidney dysfunction, neurologic impairment, and cancer. Although exposures to most VOCs for most persons fall below health-based guidelines, and long-term trends show decreases in ambient emissions and concentrations, a subset of individuals experience much higher exposures that exceed guidelines. Thus, exposure to VOCs remains an important environmental health concern. The present understanding of VOC exposures is incomplete. With the exception of a few compounds, concentration and especially exposure data are limited; and like other environmental data, VOC exposure data can show multiple modes, low and high extreme values, and sometimes a large portion of data below method detection limits (MDLs). Field data also show considerable spatial or interpersonal variability, and although evidence is limited, temporal variability seems high. These characteristics can complicate modeling and other analyses aimed at risk assessment, policy actions, and exposure management. In addition to these analytic and statistical issues, exposure typically occurs as a mixture, and mixture components may interact or jointly contribute to adverse effects. However most pollutant regulations, guidelines, and studies remain focused on single compounds, and thus may underestimate cumulative exposures and risks arising from coexposures. In addition, the composition of VOC mixtures has not been thoroughly investigated, and mixture components show varying and complex dependencies. Finally, although many factors are

  8. Evaluation of three physiologically based pharmacokinetic (PBPK) modeling tools for emergency risk assessment after acute dichloromethane exposure

    NARCIS (Netherlands)

    Boerleider, R. Z.; Olie, J. D N; van Eijkeren, J. C H; Bos, P. M J; Hof, B. G H; de Vries, I.; Bessems, J. G M; Meulenbelt, J.; Hunault, C. C.

    2015-01-01

    Introduction: Physiologically based pharmacokinetic (PBPK) models may be useful in emergency risk assessment, after acute exposure to chemicals, such as dichloromethane (DCM). We evaluated the applicability of three PBPK models for human risk assessment following a single exposure to DCM: one model

  9. Measurements of indoor and outdoor natural radiation exposure rates in model houses

    International Nuclear Information System (INIS)

    Matsuda, Hideharu; Fukaya, Mitsuharu; Minato, Susumu

    1990-01-01

    Natural gamma-ray and cosmic-ray exposure rates were measured indoors and outdoors for 94 model houses of four housing centers in Nagoya to obtain basic data for estimation of the population dose. Influence of the structure of houses on indoor exposure rates and relationship between indoor and outdoor natural gamma-ray exposure rates were studied. Exposure rates were measured with a 1.5'' φ x 4'' NaI (Tl) scintillation counter and a 6''φ spherical plastic scintillation counter. The mean indoor natural gamma-ray exposure rate in ferro-concrete buildings was about 40% higher than that in fireproof wooden houses, about 60% higher than that in light-weight steel-framed buildings, in fireproof wooden houses, it was also about 10% higher than in light-weight steel-framed building. The ratio of indoor to outdoor natural gamma-ray exposure rate was found to be about 0.95±0.15, 0.77±0.10, and 0.72±0.13 for ferro-concrete buildings, fireproof wooden houses and light-weight steel-framed buildings, respectively. The mean indoor cosmic-ray exposure rate in ferro-concrete buildings was 2.8 μR/h, about 18% lower than the outdoors. The indoor cosmic-ray exposure rate in fireproof wooden houses and light-weight steel-framed buildings were 3.2 μR/h, about 6% lower than the outdoors. (author)

  10. A Bayesian Approach for Summarizing and Modeling Time-Series Exposure Data with Left Censoring.

    Science.gov (United States)

    Houseman, E Andres; Virji, M Abbas

    2017-08-01

    Direct reading instruments are valuable tools for measuring exposure as they provide real-time measurements for rapid decision making. However, their use is limited to general survey applications in part due to issues related to their performance. Moreover, statistical analysis of real-time data is complicated by autocorrelation among successive measurements, non-stationary time series, and the presence of left-censoring due to limit-of-detection (LOD). A Bayesian framework is proposed that accounts for non-stationary autocorrelation and LOD issues in exposure time-series data in order to model workplace factors that affect exposure and estimate summary statistics for tasks or other covariates of interest. A spline-based approach is used to model non-stationary autocorrelation with relatively few assumptions about autocorrelation structure. Left-censoring is addressed by integrating over the left tail of the distribution. The model is fit using Markov-Chain Monte Carlo within a Bayesian paradigm. The method can flexibly account for hierarchical relationships, random effects and fixed effects of covariates. The method is implemented using the rjags package in R, and is illustrated by applying it to real-time exposure data. Estimates for task means and covariates from the Bayesian model are compared to those from conventional frequentist models including linear regression, mixed-effects, and time-series models with different autocorrelation structures. Simulations studies are also conducted to evaluate method performance. Simulation studies with percent of measurements below the LOD ranging from 0 to 50% showed lowest root mean squared errors for task means and the least biased standard deviations from the Bayesian model compared to the frequentist models across all levels of LOD. In the application, task means from the Bayesian model were similar to means from the frequentist models, while the standard deviations were different. Parameter estimates for covariates

  11. Human Exposure Assessment for Air Pollution.

    Science.gov (United States)

    Han, Bin; Hu, Li-Wen; Bai, Zhipeng

    2017-01-01

    Assessment of human exposure to air pollution is a fundamental part of the more general process of health risk assessment. The measurement methods for exposure assessment now include personal exposure monitoring, indoor-outdoor sampling, mobile monitoring, and exposure assessment modeling (such as proximity models, interpolation model, air dispersion models, and land-use regression (LUR) models). Among these methods, personal exposure measurement is considered to be the most accurate method of pollutant exposure assessment until now, since it can better quantify observed differences and better reflect exposure among smaller groups of people at ground level. And since the great differences of geographical environment, source distribution, pollution characteristics, economic conditions, and living habits, there is a wide range of differences between indoor, outdoor, and individual air pollution exposure in different regions of China. In general, the indoor particles in most Chinese families comprise infiltrated outdoor particles, particles generated indoors, and a few secondary organic aerosol particles, and in most cases, outdoor particle pollution concentrations are a major contributor to indoor concentrations in China. Furthermore, since the time, energy, and expense are limited, it is difficult to measure the concentration of pollutants for each individual. In recent years, obtaining the concentration of air pollutants by using a variety of exposure assessment models is becoming a main method which could solve the problem of the increasing number of individuals in epidemiology studies.

  12. A MODEL OF PARTNERSHIP PROJECT FOR HEALTH AND COMMUNITY DEVELOPMENT BETWEEN UNIVERSITY OF PITESTI AND A RURAL POPULATION, FROM A DISADVANTAGED GEOGRAPHICAL AREA

    Directory of Open Access Journals (Sweden)

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