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,

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.

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

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.

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.

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.

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.

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...

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.

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

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.

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.

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.

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 ...

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.

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.

Geographical variation in the prevalence of sensitization to common aeroallergens in adults

DEFF Research Database (Denmark)

Newson, R B; van Ree, R; Forsberg, B

2014-01-01

BACKGROUND: Geographical variation in the prevalence of sensitization to aeroallergens may reflect differences in exposure to risk factors such as having older siblings, being raised on a farm or other unidentified exposures. OBJECTIVE: We wanted to measure geographical variation in skin prick te...

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

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.

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.

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.

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%.

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.

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

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 ...

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....

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

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.

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.

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.

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

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

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.

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.

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...

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

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.

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.

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

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.

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...

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

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.

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

[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.

[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.

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.

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.

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.

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.

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

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.

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

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...

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.

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

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

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...

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

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.

Socio-economic exposure to natural disasters

International Nuclear Information System (INIS)

Marin, Giovanni; Modica, Marco

2017-01-01

Even though the correct assessment of risks is a key aspect of the risk management analysis, we argue that limited effort has been devoted in the assessment of comprehensive measures of economic exposure at very low scale. For this reason, we aim at providing a series of suitable methodologies to provide a complete and detailed list of the exposure of economic activities to natural disasters. We use Input-Output models to provide information about several socio-economic variables, such as population density, employment density, firms' turnover and capital stock, that can be seen as direct and indirect socio-economic exposure to natural disasters. We then provide an application to the Italian context. These measures can be easily incorporated into risk assessment models to provide a clear picture of the disaster risk for local areas. - Highlights: • Ex ante assessment of economic exposure to disasters at very low geographical scale • Assessment of the cost of natural disasters in ex-post perspective • IO model and spatial autocorrelation to get information on socio-economic variables • Indicators supporting risk assessment and risk management models

Socio-economic exposure to natural disasters

Energy Technology Data Exchange (ETDEWEB)

Marin, Giovanni, E-mail: giovanni.marin@uniurb.it [Department of Economics, Society, Politics, University of Urbino ' Carlo Bo' , via Aurelio Saffi, 2, 61029 Urbino (Italy); IRCrES - CNR, Research Institute on Sustainable Economic Growth, Via Corti 12, 20133 - Milano (Italy); SEEDS, Ferrara (Italy); Modica, Marco, E-mail: marco.modica@ircres.cnr.it [IRCrES - CNR, Research Institute on Sustainable Economic Growth, Via Corti 12, 20133 - Milano (Italy); SEEDS, Ferrara (Italy)

2017-05-15

Even though the correct assessment of risks is a key aspect of the risk management analysis, we argue that limited effort has been devoted in the assessment of comprehensive measures of economic exposure at very low scale. For this reason, we aim at providing a series of suitable methodologies to provide a complete and detailed list of the exposure of economic activities to natural disasters. We use Input-Output models to provide information about several socio-economic variables, such as population density, employment density, firms' turnover and capital stock, that can be seen as direct and indirect socio-economic exposure to natural disasters. We then provide an application to the Italian context. These measures can be easily incorporated into risk assessment models to provide a clear picture of the disaster risk for local areas. - Highlights: • Ex ante assessment of economic exposure to disasters at very low geographical scale • Assessment of the cost of natural disasters in ex-post perspective • IO model and spatial autocorrelation to get information on socio-economic variables • Indicators supporting risk assessment and risk management models.

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

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.

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'.

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.

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

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

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.

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.…

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.

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.

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

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.

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...

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…

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.

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.

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.

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.

Outdoor ultraviolet exposure of children and adolescents

International Nuclear Information System (INIS)

Diffey, B.L.; Gibson, C.J.

1996-01-01

The weekday and weekend outdoor ultraviolet exposure of young people from primary and secondary schools in three geographically distinct regions of England was determined over a 3-month period in summer. Ultraviolet exposure was measured using personal film badges worn by each young person and time spent outdoors, in hourly intervals, assessed using exposure records. In each area a class of 9-10 year-old children from a primary school and a class of 14-15-year-old adolescents from a secondary school took part, giving a total of 180 subjects. We found that primary school children received higher outdoor ultraviolet exposure than young people in secondary schools, and geographical differences in exposure could not be accounted for solely by differences in ambient ultraviolet. There was little difference between the exposure of males and females. Children and adolescents did not behave as homogeneous groups with regard to exposure. (Author)

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.

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

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/

Road traffic air and noise pollution exposure assessment - A review of tools and techniques.

Science.gov (United States)

Khan, Jibran; Ketzel, Matthias; Kakosimos, Konstantinos; Sørensen, Mette; Jensen, Steen Solvang

2018-09-01

Road traffic induces air and noise pollution in urban environments having negative impacts on human health. Thus, estimating exposure to road traffic air and noise pollution (hereafter, air and noise pollution) is important in order to improve the understanding of human health outcomes in epidemiological studies. The aims of this review are (i) to summarize current practices of modelling and exposure assessment techniques for road traffic air and noise pollution (ii) to highlight the potential of existing tools and techniques for their combined exposure assessment for air and noise together with associated challenges, research gaps and priorities. The study reviews literature about air and noise pollution from urban road traffic, including other relevant characteristics such as the employed dispersion models, Geographic Information System (GIS)-based tool, spatial scale of exposure assessment, study location, sample size, type of traffic data and building geometry information. Deterministic modelling is the most frequently used assessment technique for both air and noise pollution of short-term and long-term exposure. We observed a larger variety among air pollution models as compared to the applied noise models. Correlations between air and noise pollution vary significantly (0.05-0.74) and are affected by several parameters such as traffic attributes, building attributes and meteorology etc. Buildings act as screens for the dispersion of pollution, but the reduction effect is much larger for noise than for air pollution. While, meteorology has a greater influence on air pollution levels as compared to noise, although also important for noise pollution. There is a significant potential for developing a standard tool to assess combined exposure of traffic related air and noise pollution to facilitate health related studies. GIS, due to its geographic nature, is well established and has a significant capability to simultaneously address both exposures. Copyright �

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)

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)

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.

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.

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.

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.

Representation of geographic terrain surface using global indexing

DEFF Research Database (Denmark)

Kolar, Jan

2004-01-01

. Unlike cartographic maps, 3D models can capture the geometry of geographic features without flattening the environment, without cartographic projection?can avoid geometric distortion. More interestingly, however, 3D models can be composed into a single model spanning the whole world; it can be navigated...... visually in order to access information and data in the same geometric space as we navigate ourselves in our real environment.   This article attempts to narrow down the overhead of problems in visualization of 3D geographic information and intends to identify fundamental issues common to other systems......A global 3D geographic model a feasible solution for its visualization and management remains a challenging vision. The existence of a reusable platform would provide an unprecedented potential for development of applications related to geography and facilitate comprehension of geographic data...

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.

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.

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

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

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

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

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

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

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.

Uniform Variation in Genetic-Traits of a Marine Bivalve Related to Starvation, Pollution and Geographic Clines

NARCIS (Netherlands)

Hummel, H.; Bogaards, R.H.; Amiard-Triquet, C.; Bachelet, G.; Desprez, M.; Marchand, J.; Rybarczyk, H.; Sylvand, B.; De Wit, Y.; De Wolf, L.

1995-01-01

Consistent patterns of genetic variation in the marine bivalve Macoma balthica (L.) were found after exposure to low levels of copper, starvation, and along geographic dines. The geographic dines were related to temperature and salinity. Genetic differences were primarily found in the LAP (Leucine

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.

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...

Recruitment and Retention Strategies for Environmental Exposure Studies: Lessons from the Detroit Exposure and Aerosol Research Study

Science.gov (United States)

The Environmental Protection Agency’s Detroit Exposure and Aerosol Research Study (DEARS) was a complex 3-year personal exposure study. The six geographically defined areas in the Detroit (Wayne County), Michigan, area used as study locations are ethnically diverse; the majority ...

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

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

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.

Geographical Inequality in Tobacco Control in China: Multilevel Evidence From 98 058 Participants.

Science.gov (United States)

Astell-Burt, Thomas; Zhang, Mei; Feng, Xiaoqi; Wang, Limin; Li, Yichong; Page, Andrew; Zhou, Maigeng; Wang, Linhong

2018-05-03

We investigated the spatial patterning and correlates of tobacco smoking, exposure to secondhand smoke, smoking in public places, workplace smoking prohibition, pro- and counter-tobacco advertisements in mainland China. Choropleth maps and multilevel models were used to assess geographical variation and correlates of the aforementioned outcome variables for 98 058 participants across 31 provinces of China in 2010. Current tobacco smoking prevalence was higher in the central provinces for men and in the north eastern provinces and Tibet for women. Secondhand smoke was higher for both genders in Qinghai and Hunan provinces. Workplace tobacco restrictions was higher in the north and east, whereas smoking in public places was more common in the west, central, and far northeast. Protobacco advertising was observed in public places more often by men (18.5%) than women (13.1%). Men (35.5%) were also more likely to sight counter-tobacco advertising in public places than women (30.1%). Awareness of workplace tobacco restrictions was more common in affluent urban areas. Lower awareness of workplace tobacco restrictions was in less affluent urban and rural areas. Sightings of tobacco smoking in public places was highest in restaurants (80.4% for men, 75.0% for women) and also commonly reported in less affluent urban and rural areas. Exposure to secondhand smoke was lower among women (but not men) where workplace tobacco restrictions was more common and higher regardless of gender in areas where smoking in public places was more commonly observed. Geographical and gender-sensitive targeting of tobacco prevention and control initiatives are warranted. This study demonstrates spatial patterning of China's 300 million smokers across the country that are different for men and women. Many of the factors that influence tobacco use, such as pro- and counter-advertising, also vary geographically. Workplace smoking restrictions are more commonly reported among individuals with higher

The spatial distribution of known predictors of autism spectrum disorders impacts geographic variability in prevalence in central North Carolina

Directory of Open Access Journals (Sweden)

Hoffman Kate

2012-10-01

Full Text Available Abstract Background The causes of autism spectrum disorders (ASD remain largely unknown and widely debated; however, evidence increasingly points to the importance of environmental exposures. A growing number of studies use geographic variability in ASD prevalence or exposure patterns to investigate the association between environmental factors and ASD. However, differences in the geographic distribution of established risk and predictive factors for ASD, such as maternal education or age, can interfere with investigations of ASD etiology. We evaluated geographic variability in the prevalence of ASD in central North Carolina and the impact of spatial confounding by known risk and predictive factors. Methods Children meeting a standardized case definition for ASD at 8 years of age were identified through records-based surveillance for 8 counties biennially from 2002 to 2008 (n=532. Vital records were used to identify the underlying cohort (15% random sample of children born in the same years as children with an ASD, n=11,034, and to obtain birth addresses. We used generalized additive models (GAMs to estimate the prevalence of ASD across the region by smoothing latitude and longitude. GAMs, unlike methods used in previous spatial analyses of ASD, allow for extensive adjustment of individual-level risk factors (e.g. maternal age and education when evaluating spatial variability of disease prevalence. Results Unadjusted maps revealed geographic variation in surveillance-recognized ASD. Children born in certain regions of the study area were up to 1.27 times as likely to be recognized as having ASD compared to children born in the study area as a whole (prevalence ratio (PR range across the study area 0.57-1.27; global P=0.003. However, geographic gradients of ASD prevalence were attenuated after adjusting for spatial confounders (adjusted PR range 0.72-1.12 across the study area; global P=0.052. Conclusions In these data, spatial variation of ASD

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

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.)

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.

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

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....

Application of geographic information systems to waste minimization efforts at the national laboratories

International Nuclear Information System (INIS)

Lyttle, T.W.; Smith, D.M.; Burns, M.; Weinrach, J.B.

1993-01-01

At Los Alamos National Laboratory (LANL), facility waste streams tend to be small but highly diverse. Initial characterization of such waste streams is often difficult in part due to a lack of tools to assist the generators themselves in completing such assessments. A methodology has been developed at LANL to allow process knowledgeable field personnel to develop baseline waste generation assessments and to evaluate potential waste minimization technology. This Process Waste Assessment (PWA) system is an application constructed within the Process Modeling System and currently being integrated with the InFoCAD Geographic Information System (GIS). The Process Modeling System (PMS) is an object-oriented, mass balance-based, discrete-event simulation framework written using the Common Lisp Object System (CLOS). Analytical capabilities supported within the PWA system include: complete mass balance specifications, historical characterization of selected waste stream and generation of facility profiles for materials consumption, resource utilization and worker exposure. Development activities include integration with the LANL facilities management Geographic Information System (GIS) and provisions for a Best Available Technologies (BAT) database. The environments used to develop these assessment tools will be discussed in addition to a review of initial implementation results

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.

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

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.

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.

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

Surveying and Mapping Geographical Information from the Perspective of Geography

Directory of Open Access Journals (Sweden)

LÜ Guonian

2017-10-01

Full Text Available It briefly reviewed the history of geographic information content development since the existence of geographic information system. It pointed out that the current definition of geographic information is always the extension from the "spatial+ attributes" basic mapping framework of geographic information. It is increasingly difficult to adapt to the analysis and application of spatial-temporal big data. From the perspective of geography research subject and content, it summarized systematically that the content and extension of the "geographic information" that geography needs. It put forward that a six-element expression model of geographic information, including spatial location, semantic description, attribute characteristics, geometric form, evolution process, and objects relationship.Under the guidance of the laws of geography, for geographical phenomenon of spatial distribution, temporal pattern and evolution process, the interaction mechanism of the integrated expression, system analysis and efficient management, it designed that a unified GIS data model which is expressed by six basic elements, a new GIS data structure driven by geographical rules and interaction, and key technologies of unstructured spatio-temporal data organization and storage. It provided that a theoretical basis and technical support for the shift from the surveying and mapping geographic information to the scientific geographic information, and it can help improving the organization, management, analysis and expression ability of the GIS of the geographical laws such as geographical pattern, evolution process, and interaction between elements.

Risk of cancer in the vicinity of municipal solid waste incinerators: importance of using a flexible modelling strategy

Directory of Open Access Journals (Sweden)

Goria Sarah

2009-05-01

Full Text Available Abstract Background We conducted an ecological study in four French administrative departments and highlighted an excess risk in cancer morbidity for residents around municipal solid waste incinerators. The aim of this paper is to show how important are advanced tools and statistical techniques to better assess weak associations between the risk of cancer and past environmental exposures. Methods The steps to evaluate the association between the risk of cancer and the exposure to incinerators, from the assessment of exposure to the definition of the confounding variables and the statistical analysis carried out are detailed and discussed. Dispersion modelling was used to assess exposure to sixteen incinerators. A geographical information system was developed to define an index of exposure at the IRIS level that is the geographical unit we considered. Population density, rural/urban status, socio-economic deprivation, exposure to air pollution from traffic and from other industries were considered as potential confounding factors and defined at the IRIS level. Generalized additive models and Bayesian hierarchical models were used to estimate the association between the risk of cancer and the index of exposure to incinerators accounting for the confounding factors. Results Modelling to assess the exposure to municipal solid waste incinerators allowed accounting for factors known to influence the exposure (meteorological data, point source characteristics, topography. The statistical models defined allowed modelling extra-Poisson variability and also non-linear relationships between the risk of cancer and the exposure to incinerators and the confounders. Conclusion In most epidemiological studies distance is still used as a proxy for exposure. This can lead to significant exposure misclassification. Additionally, in geographical correlation studies the non-linear relationships are usually not accounted for in the statistical analysis. In studies of

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.

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

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

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.

Urbanization and traffic related exposures as risk factors for Schizophrenia

DEFF Research Database (Denmark)

Pedersen, Carsten Bøcker; Mortensen, Preben Bo

2006-01-01

: The geographical distance from place of residence to nearest major road had a significant effect. The highest risk was found in children living 500-1000 metres from nearest major road (RR=1.30 (95% Confidence Interval: 1.17-1.44). However, when we accounted for the degree of urbanization, the geographical distance...... that traffic related exposures affect schizophrenia risk and that this potential effect is responsible for the urban-rural differences. The geographical distance from place of residence to nearest major road was used as a proxy variable for traffic related exposures. We used a large population-based sample......BACKGROUND: Urban birth or upbringing increase schizophrenia risk. Though unknown, the causes of these urban-rural differences have been hypothesized to include, e.g., infections, diet, toxic exposures, social class, or an artefact due to selective migration. METHODS: We investigated the hypothesis...

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.

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....

Urbanization and traffic related exposures as risk factors for Schizophrenia

DEFF Research Database (Denmark)

Pedersen, Carsten Bøcker; Mortensen, Preben Bo

2006-01-01

to nearest major road had no significant effect. CONCLUSIONS: The cause(s) or exposure(s) responsible for the urban-rural differences in schizophrenia risk were closer related to the degree of urbanization than to the geographical distance to nearest major road. Traffic related exposures might thus be less......BACKGROUND: Urban birth or upbringing increase schizophrenia risk. Though unknown, the causes of these urban-rural differences have been hypothesized to include, e.g., infections, diet, toxic exposures, social class, or an artefact due to selective migration. METHODS: We investigated the hypothesis...... that traffic related exposures affect schizophrenia risk and that this potential effect is responsible for the urban-rural differences. The geographical distance from place of residence to nearest major road was used as a proxy variable for traffic related exposures. We used a large population-based sample...

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

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.

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

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

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...

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.

Application of geographic information systems to waste minimization efforts at Los Alamos National Laboratory

International Nuclear Information System (INIS)

Lyttle, T.W.; Smith, D.M.; Burns, M.; Weinrach, J.B.

1993-01-01

At Los Alamos National Laboratory (LANL), facility waste streams tend to be small but highly diverse. Initial characterization of such waste streams is often difficult in part due to a lack of tools to assist the generators themselves in completing such assessments. A methodology has been developed at LANL to allow process knowledgeable field personnel to develop baseline waste generation assessments and to evaluate potential waste minimization technology. This Process Waste Assessment (PWA) system is an application constructed within the Process Modeling System and currently being integrated with the InFoCAD Geographic Information System (GIS) . The Process Modeling System (PMS) is an object-oriented, mass balance-based, discrete-event simulation framework written using the Common Lisp Object System (CLOS) . Analytical capabilities supported within the PWA system include: complete mass balance specifications, historical characterization of selected waste streams and generation of facility profiles for materials consumption, resource utilization and worker exposure. Development activities include integration with the LANL facilities management Geographic Information System (GIS) and provisions for a Best Available Technologies (BAT) database. The environments used to develop these assessment tools will be discussed in addition to a review of initial implementation results

Non-occupational exposure to ionizing radiation

International Nuclear Information System (INIS)

Snihs, J.O.

1985-01-01

An overview of non-occupational exposure is presented. The special problems in connection with assessments of collective doses (time, geographical extension, cut-off, uncertainties) are discussed. Examples of methods and principles for monitoring and dose assessments used for various sources of radiation are given and data on public exposure are presented and discussed. (author)

A Geographic Method for High Resolution Spatial Heat Planning

DEFF Research Database (Denmark)

Nielsen, Steffen

2014-01-01

more detailed modelling that takes the geographic placement of buildings and the differences among DH systems into account. In the present article, a method for assessing the costs of DH expansions has been developed. The method was applied in a geographic information system (GIS) model that consists...... are considering distribution costs based on the geographic properties of each area and assessing transmission costs based on an iterative process that examines expansion potentials gradually. The GIS model is only applicable to a Danish context, but the method itself can be applied to other countries....... of three parts and assesses the costs of heat production, distribution, and transmission. The model was also applied to an actual case in order to show how it can be used. The model shows many improvements in the method for the assessment of distribution costs and transmission costs. Most notable...

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.

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.

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.

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...

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.

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.

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.

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.

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.

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, ...

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.

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...

IASM: Individualized activity space modeler

Science.gov (United States)

Hasanzadeh, Kamyar

2018-01-01

Researchers from various disciplines have long been interested in analyzing and describing human mobility patterns. Activity space (AS), defined as an area encapsulating daily human mobility and activities, has been at the center of this interest. However, given the applied nature of research in this field and the complexity that advanced geographical modeling can pose to its users, the proposed models remain simplistic and inaccurate in many cases. Individualized Activity Space Modeler (IASM) is a geographic information system (GIS) toolbox, written in Python programming language using ESRI's Arcpy module, comprising four tools aiming to facilitate the use of advanced activity space models in empirical research. IASM provides individual-based and context-sensitive tools to estimate home range distances, delineate activity spaces, and model place exposures using individualized geographical data. In this paper, we describe the design and functionality of IASM, and provide an example of how it performs on a spatial dataset collected through an online map-based survey.

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

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

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

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

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...

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.

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

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

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.

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...

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...

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...

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.

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.

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

Assessment of population exposure to particulate matter pollution in Chongqing, China

International Nuclear Information System (INIS)

Wang Shuxiao; Zhao Yu; Chen Gangcai; Wang Fei; Aunan, Kristin; Hao Jiming

2008-01-01

To determine the population exposure to PM 10 in Chongqing, China, we developed an indirect model by combining information on the time activity patterns of various demographic subgroups with estimates of the PM 10 concentrations in different microenvironments (MEs). The spatial and temporal variations of the exposure to PM 10 were illustrated in a geographical information system (GIS). The population weighted exposure (PWE) for the entire population was 229, 155 and 211 μg/m 3 , respectively, in winter, summer and as the annual average. Indoor PM 10 level at home was the largest contributor to the PWE, especially for the rural areas where high pollution levels were found due to solid fuels burning. Elder people had higher PM 10 exposure than adults and youth, due to more time spent in indoor MEs. The highest health risk due to particulate was found in the city zone and northeast regions, suggesting that pollution abatement should be prioritized in these areas. - Using an indirect microenvironment model, the population weighted exposure (PWE) to PM 10 in Chongqing was estimated to be 211 μg/m 3 with significant contribution from indoor pollution

Assessment of population exposure to particulate matter pollution in Chongqing, China

Energy Technology Data Exchange (ETDEWEB)

Wang Shuxiao [Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084 (China)], E-mail: shxwang@tsinghua.edu.cn; Zhao Yu [Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084 (China); Chen Gangcai; Wang Fei [Institute of Environmental Science and Technology of Chongqing, Chongqing 630020 (China); Aunan, Kristin [Center for International Climate and Environmental Research, P.O. Box 1129, Blindern, 0318 Oslo (Norway); Hao Jiming [Department of Environmental Science and Engineering, Tsinghua University, Beijing 100084 (China)

2008-05-15

To determine the population exposure to PM{sub 10} in Chongqing, China, we developed an indirect model by combining information on the time activity patterns of various demographic subgroups with estimates of the PM{sub 10} concentrations in different microenvironments (MEs). The spatial and temporal variations of the exposure to PM{sub 10} were illustrated in a geographical information system (GIS). The population weighted exposure (PWE) for the entire population was 229, 155 and 211 {mu}g/m{sup 3}, respectively, in winter, summer and as the annual average. Indoor PM{sub 10} level at home was the largest contributor to the PWE, especially for the rural areas where high pollution levels were found due to solid fuels burning. Elder people had higher PM{sub 10} exposure than adults and youth, due to more time spent in indoor MEs. The highest health risk due to particulate was found in the city zone and northeast regions, suggesting that pollution abatement should be prioritized in these areas. - Using an indirect microenvironment model, the population weighted exposure (PWE) to PM{sub 10} in Chongqing was estimated to be 211 {mu}g/m{sup 3} with significant contribution from indoor pollution.

Geographical data structures supporting regional analysis

International Nuclear Information System (INIS)

Edwards, R.G.; Durfee, R.C.

1978-01-01

In recent years the computer has become a valuable aid in solving regional environmental problems. Over a hundred different geographic information systems have been developed to digitize, store, analyze, and display spatially distributed data. One important aspect of these systems is the data structure (e.g. grids, polygons, segments) used to model the environment being studied. This paper presents eight common geographic data structures and their use in studies of coal resources, power plant siting, population distributions, LANDSAT imagery analysis, and landuse analysis

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.

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.

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...

The GeoGraph 3D Computational Laboratory

National Research Council Canada - National Science Library

Dibble, Catherine; Feldman, Philip G

2003-01-01

.... Even recent progress in social network modeling has not yet offered us any capability to model dynamic processes among mobile agents who interact at all scales on small-world and scale-free geographic networks...

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.

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.

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.

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

Chronic particulate exposure, mortality and cardiovascular outcomes in the nurses health study

Science.gov (United States)

Adverse health effects of exposures to acute air pollution have been well studied. Fewer studies have examined effects of chronic exposure. Previous studies used exposure estimates for narrow time periods and were limited by the geographic distribution of pollution monitors. This...

Personality Homophily and Geographic Distance in Facebook.

Science.gov (United States)

Noë, Nyala; Whitaker, Roger M; Allen, Stuart M

2018-05-24

Personality homophily remains an understudied aspect of social networks, with the traditional focus concerning sociodemographic variables as the basis for assortativity, rather than psychological dispositions. We consider the effect of personality homophily on one of the biggest constraints to human social networks: geographic distance. We use the Big five model of personality to make predictions for each of the five facets: Openness to experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. Using a network of 313,669 Facebook users, we investigate the difference in geographic distance between homophilous pairs, in which both users scored similarly on a particular facet, and mixed pairs. In accordance with our hypotheses, we find that pairs of open and conscientious users are geographically further apart than mixed pairs. Pairs of extraverts, on the other hand, tend to be geographically closer together. We find mixed results for the Neuroticism facet, and no significant effects for the Agreeableness facet. The results are discussed in the context of personality homophily and the impact of geographic distance on social connections.

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

Blood trace metals in a sporadic amyotrophic lateral sclerosis geographical cluster.

Science.gov (United States)

De Benedetti, Stefano; Lucchini, Giorgio; Del Bò, Cristian; Deon, Valeria; Marocchi, Alessandro; Penco, Silvana; Lunetta, Christian; Gianazza, Elisabetta; Bonomi, Francesco; Iametti, Stefania

2017-06-01

Amyotrophic lateral sclerosis (ALS) is a fatal disorder with unknown etiology, in which genetic and environmental factors interplay to determine the onset and the course of the disease. Exposure to toxic metals has been proposed to be involved in the etiology of the disease either through a direct damage or by promoting oxidative stress. In this study we evaluated the concentration of a panel of metals in serum and whole blood of a small group of sporadic patients, all living in a defined geographical area, for which acid mine drainage has been reported. ALS prevalence in this area is higher than in the rest of Italy. Results were analyzed with software based on artificial neural networks. High concentrations of metals (in particular Se, Mn and Al) were associated with the disease group. Arsenic serum concentration resulted lower in ALS patients, but it positively correlated with disease duration. Comet assay was performed to evaluate endogenous DNA damage that resulted not different between patients and controls. Up to now only few studies considered geographically well-defined clusters of ALS patients. Common geographical origin among patients and controls gave us the chance to perform metallomic investigations under comparable conditions of environmental exposure. Elaboration of these data with software based on machine learning processes has the potential to be extremely useful to gain a comprehensive view of the complex interactions eventually leading to disease, even in a small number of subjects.

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

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

Occupational Exposure to Pesticides With Occupational Sun Exposure Increases the Risk for Cutaneous Melanoma.

Science.gov (United States)

Fortes, Cristina; Mastroeni, Simona; Segatto M, Marjorie; Hohmann, Clarissa; Miligi, Lucia; Bakos, Lucio; Bonamigo, Renan

2016-04-01

The objective of the study was to examine the association between occupational exposure to pesticides and cutaneous melanoma, controlling for all possible confounders. A pooled analysis of two case-control studies was conducted in two different geographic areas (Italy and Brazil). Detailed pesticides exposure histories were obtained. Ever use of any pesticide was associated with a high risk of cutaneous melanoma (odds ratio 2.58; 95% confidence interval 1.18-5.65) in particular exposure to herbicides (glyphosate) and fungicides (mancozeb, maneb), after controlling for confounding factors. When subjects were exposed to both pesticides and occupational sun exposure, the risk increased even more (odds ratio 4.68; 95% confidence interval 1.29-17.0). The study suggests an augmented risk of cutaneous melanoma among subjects with exposure to pesticides, in particular among those exposed to occupational sun exposure.

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…

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...

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

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)

Geographic disparity in kidney transplantation under KAS.

Science.gov (United States)

Zhou, Sheng; Massie, Allan B; Luo, Xun; Ruck, Jessica M; Chow, Eric K H; Bowring, Mary G; Bae, Sunjae; Segev, Dorry L; Gentry, Sommer E

2017-12-12

The Kidney Allocation System fundamentally altered kidney allocation, causing a substantial increase in regional and national sharing that we hypothesized might impact geographic disparities. We measured geographic disparity in deceased donor kidney transplant (DDKT) rate under KAS (6/1/2015-12/1/2016), and compared that with pre-KAS (6/1/2013-12/3/2014). We modeled DSA-level DDKT rates with multilevel Poisson regression, adjusting for allocation factors under KAS. Using the model we calculated a novel, improved metric of geographic disparity: the median incidence rate ratio (MIRR) of transplant rate, a measure of DSA-level variation that accounts for patient casemix and is robust to outlier values. Under KAS, MIRR was 1.75 1.81 1.86 for adults, meaning that similar candidates across different DSAs have a median 1.81-fold difference in DDKT rate. The impact of geography was greater than the impact of factors emphasized by KAS: having an EPTS score ≤20% was associated with a 1.40-fold increase (IRR =  1.35 1.40 1.45 , P geographic disparities with KAS (P = .3). Despite extensive changes to kidney allocation under KAS, geography remains a primary determinant of access to DDKT. © 2017 The American Society of Transplantation and the American Society of Transplant Surgeons.

Formal Ontologies and Uncertainty. In Geographical Knowledge

Directory of Open Access Journals (Sweden)

Matteo Caglioni

2014-05-01

Full Text Available Formal ontologies have proved to be a very useful tool to manage interoperability among data, systems and knowledge. In this paper we will show how formal ontologies can evolve from a crisp, deterministic framework (ontologies of hard knowledge to new probabilistic, fuzzy or possibilistic frameworks (ontologies of soft knowledge. This can considerably enlarge the application potential of formal ontologies in geographic analysis and planning, where soft knowledge is intrinsically linked to the complexity of the phenomena under study.  The paper briefly presents these new uncertainty-based formal ontologies. It then highlights how ontologies are formal tools to define both concepts and relations among concepts. An example from the domain of urban geography finally shows how the cause-to-effect relation between household preferences and urban sprawl can be encoded within a crisp, a probabilistic and a possibilistic ontology, respectively. The ontology formalism will also determine the kind of reasoning that can be developed from available knowledge. Uncertain ontologies can be seen as the preliminary phase of more complex uncertainty-based models. The advantages of moving to uncertainty-based models is evident: whether it is in the analysis of geographic space or in decision support for planning, reasoning on geographic space is almost always reasoning with uncertain knowledge of geographic phenomena.

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.

Assessment of long-term spatio-temporal radiofrequency electromagnetic field exposure.

Science.gov (United States)

Aerts, Sam; Wiart, Joe; Martens, Luc; Joseph, Wout

2018-02-01

As both the environment and telecommunications networks are inherently dynamic, our exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) at an arbitrary location is not at all constant in time. In this study, more than a year's worth of measurement data collected in a fixed low-cost exposimeter network distributed over an urban environment was analysed and used to build, for the first time, a full spatio-temporal surrogate model of outdoor exposure to downlink Global System for Mobile Communications (GSM) and Universal Mobile Telecommunications System (UMTS) signals. Though no global trend was discovered over the measuring period, the difference in measured exposure between two instances could reach up to 42dB (a factor 12,000 in power density). Furthermore, it was found that, taking into account the hour and day of the measurement, the accuracy of the surrogate model in the area under study was improved by up to 50% compared to models that neglect the daily temporal variability of the RF signals. However, further study is required to assess the extent to which the results obtained in the considered environment can be extrapolated to other geographic locations. Copyright © 2017 Elsevier Inc. All rights reserved.

Large scale air pollution estimation method combining land use regression and chemical transport modeling in a geostatistical framework.

Science.gov (United States)

Akita, Yasuyuki; Baldasano, Jose M; Beelen, Rob; Cirach, Marta; de Hoogh, Kees; Hoek, Gerard; Nieuwenhuijsen, Mark; Serre, Marc L; de Nazelle, Audrey

2014-04-15

In recognition that intraurban exposure gradients may be as large as between-city variations, recent air pollution epidemiologic studies have become increasingly interested in capturing within-city exposure gradients. In addition, because of the rapidly accumulating health data, recent studies also need to handle large study populations distributed over large geographic domains. Even though several modeling approaches have been introduced, a consistent modeling framework capturing within-city exposure variability and applicable to large geographic domains is still missing. To address these needs, we proposed a modeling framework based on the Bayesian Maximum Entropy method that integrates monitoring data and outputs from existing air quality models based on Land Use Regression (LUR) and Chemical Transport Models (CTM). The framework was applied to estimate the yearly average NO2 concentrations over the region of Catalunya in Spain. By jointly accounting for the global scale variability in the concentration from the output of CTM and the intraurban scale variability through LUR model output, the proposed framework outperformed more conventional approaches.

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.

IMPROVEMENT OF THE F-PERCEPTORY APPROACH THROUGH MANAGEMENT OF FUZZY COMPLEX GEOGRAPHIC OBJECTS

Directory of Open Access Journals (Sweden)

B. Khalfi

2015-08-01

Full Text Available In the real world, data is imperfect and in various ways such as imprecision, vagueness, uncertainty, ambiguity and inconsistency. For geographic data, the fuzzy aspect is mainly manifested in time, space and the function of objects and is due to a lack of precision. Therefore, the researchers in the domain emphasize the importance of modeling data structures in GIS but also their lack of adaptation to fuzzy data. The F-Perceptory approachh manages the modeling of imperfect geographic information with UML. This management is essential to maintain faithfulness to reality and to better guide the user in his decision-making. However, this approach does not manage fuzzy complex geographic objects. The latter presents a multiple object with similar or different geographic shapes. So, in this paper, we propose to improve the F-Perceptory approach by proposing to handle fuzzy complex geographic objects modeling. In a second step, we propose its transformation to the UML modeling.

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.

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.

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.

Relation of whole blood carboxyhemoglobin concentration to ambient carbon monoxide exposure estimated using regression.

Science.gov (United States)

Rudra, Carole B; Williams, Michelle A; Sheppard, Lianne; Koenig, Jane Q; Schiff, Melissa A; Frederick, Ihunnaya O; Dills, Russell

2010-04-15

Exposure to carbon monoxide (CO) and other ambient air pollutants is associated with adverse pregnancy outcomes. While there are several methods of estimating CO exposure, few have been evaluated against exposure biomarkers. The authors examined the relation between estimated CO exposure and blood carboxyhemoglobin concentration in 708 pregnant western Washington State women (1996-2004). Carboxyhemoglobin was measured in whole blood drawn around 13 weeks' gestation. CO exposure during the month of blood draw was estimated using a regression model containing predictor terms for year, month, street and population densities, and distance to the nearest major road. Year and month were the strongest predictors. Carboxyhemoglobin level was correlated with estimated CO exposure (rho = 0.22, 95% confidence interval (CI): 0.15, 0.29). After adjustment for covariates, each 10% increase in estimated exposure was associated with a 1.12% increase in median carboxyhemoglobin level (95% CI: 0.54, 1.69). This association remained after exclusion of 286 women who reported smoking or being exposed to secondhand smoke (rho = 0.24). In this subgroup, the median carboxyhemoglobin concentration increased 1.29% (95% CI: 0.67, 1.91) for each 10% increase in CO exposure. Monthly estimated CO exposure was moderately correlated with an exposure biomarker. These results support the validity of this regression model for estimating ambient CO exposures in this population and geographic setting.

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.

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.

Assessment of population exposure to particulate matter pollution in Chongqing, China.

Science.gov (United States)

Wang, Shuxiao; Zhao, Yu; Chen, Gangcai; Wang, Fei; Aunan, Kristin; Hao, Jiming

2008-05-01

To determine the population exposure to PM(10) in Chongqing, China, we developed an indirect model by combining information on the time activity patterns of various demographic subgroups with estimates of the PM(10) concentrations in different microenvironments (MEs). The spatial and temporal variations of the exposure to PM(10) were illustrated in a geographical information system (GIS). The population weighted exposure (PWE) for the entire population was 229, 155 and 211 microg/m(3), respectively, in winter, summer and as the annual average. Indoor PM(10) level at home was the largest contributor to the PWE, especially for the rural areas where high pollution levels were found due to solid fuels burning. Elder people had higher PM(10) exposure than adults and youth, due to more time spent in indoor MEs. The highest health risk due to particulate was found in the city zone and northeast regions, suggesting that pollution abatement should be prioritized in these areas.

Assessment of population exposure to particulate matter pollution in Chongqing, China

Energy Technology Data Exchange (ETDEWEB)

Shuxiao Wang; Yu Zhao; Gangcai Chen; Fei Wang; Aunan Kristin; Jiming Hao [Tsinghua University, Beijing (China). Department of Environmental Science and Engineering

2008-05-15

To determine the population exposure to PM10 in Chongqing, China, we developed an indirect model by combining information on the time activity patterns of various demographic subgroups with estimates of the PM10 concentrations in different microenvironments (MEs). The spatial and temporal variations of the exposure to PM10 were illustrated in a geographical information system (GIS). The population weighted exposure (PWE) for the entire population was 229, 155 and 211 {mu}g/m{sup 3}, respectively, in winter, summer and as the annual average. Indoor PM10 level at home was the largest contributor to the PWE, especially for the rural areas where high pollution levels were found due to solid fuels burning. Elder people had higher PM10 exposure than adults and youth, due to more time spent in indoor MEs. The highest health risk due to particulate was found in the city zone and northeast regions, suggesting that pollution abatement should be prioritized in these areas.

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

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

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.

Dietary exposure to aflatoxin and fumonisin among Tanzanian children as determined using biomarkers of exposure

Science.gov (United States)

Shirima, Candida P.; Kimanya, Martin E.; Kinabo, Joyce L.; Routledge, Michael N.; Srey, Chou; Wild, Christopher P.; Gong, Yun Yun

2014-01-01

Scope The study aims to evaluate the status of dietary exposure to aflatoxin and fumonisin in young Tanzanian children, using previously validated biomarkers of exposure. Methods and results A total of 148 children aged 12 to 22 months, were recruited from three geographically distant villages in Tanzania; Nyabula, Kigwa and Kikelelwa. Plasma aflatoxin-albumin adducts (AF-alb) and urinary fumonisin B1 (UFB1) were measured by ELISA and LC-MS, respectively. AF-alb was detectable in 84% of children, was highest in fully weaned children (pfumonisin through contaminated diet, although the level of exposure varies markedly between the three villages studied. PMID:23776058

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.

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

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.

The research on data organization technology in the highway geographic information system

Science.gov (United States)

Tian, Zhihui; Wu, Fang; Zeng, Yuhuai

2008-10-01

Data are the basis of GIS. It has direct impact on the efficiency and function of a Highway Geographic Information System (HGIS), because of the characteristics of data model and data organization of the traffic geographic information system such as spatial property, multi-path network, linearity. This paper discussed the data property of HGIS, studied and presented the HGIS spatial data on multi-source and model. Also, it described and verified highway geographical feature of special subject data's linearity, dynamic and multiple-path network property in HGIS.

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

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

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.

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

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

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)

Exposure and risk calculations for disposal of wastes having minimal radioactivity

International Nuclear Information System (INIS)

Fields, D.E.

1984-01-01

The US Nuclear Regulatory Commission is currently considering revision of rules 10 CFR 20 and 10 CFR 61, which cover disposal of solid wastes containing minimal activity radioactivity. In support of these revised rules, we have evaluated the consequences of disposing of four waste streams at four types of disposal areas located in three different geographic regions. Consequences are expressed in terms of human exposures and associated health effects. Each geographic region has its own climate and geology. Example waste streams, waste disposal methods, and geographic regions chosen for this study are clearly specified. The PRESTO-II methodology was used to evaluate radionuclide transport and health effects. This methodology was developed to assess radiological impacts to a static local population for a 1000-year period following disposal. The modeling of pathways and processes of migration from the trench to exposed populations included the following considerations: groundwater transport, overland flow, erosion, surface water dilution, resuspension, atmospheric transport, deposition, inhalation, and ingestion of contaminated beef, milk, crops, and water. 9 references, 2 figures, 3 tables

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.

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.

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 ...

GIDEON: a comprehensive Web-based resource for geographic medicine

Directory of Open Access Journals (Sweden)

Berger Stephen A

2005-04-01

Full Text Available Abstract GIDEON (Global Infectious Diseases and Epidemiology Network is a web-based computer program designed for decision support and informatics in the field of Geographic Medicine. The first of four interactive modules generates a ranked differential diagnosis based on patient signs, symptoms, exposure history and country of disease acquisition. Additional options include syndromic disease surveillance capability and simulation of bioterrorism scenarios. The second module accesses detailed and current information regarding the status of 338 individual diseases in each of 220 countries. Over 50,000 disease images, maps and user-designed graphs may be downloaded for use in teaching and preparation of written materials. The third module is a comprehensive source on the use of 328 anti-infective drugs and vaccines, including a listing of over 9,500 international trade names. The fourth module can be used to characterize or identify any bacterium or yeast, based on laboratory phenotype. GIDEON is an up-to-date and comprehensive resource for Geographic Medicine.

Geographical Mobility of Danish Dual-Earner Couples

DEFF Research Database (Denmark)

Deding, Mette; Filges, Trine

In this paper, we analyse the empirical relationship between geographical residence mobility and geographical job mobility for Danish dual-earner couples. Based on register data from Statistics Denmark from 1999 and 2000, we estimate three probabilities, taking the interdependence between...... the work region matters for the determination of the residence region. Furthermore, although the model stresses the importance of looking at both spouses, we do not find marked differences between the men and the women. Thus, our results do not indicate that one spouse is more important than the other...

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...

Using ecosystem modelling techniques in exposure assessments of radionuclides - an overview

International Nuclear Information System (INIS)

Kumblad, L.

2005-01-01

The risk to humans from potential releases from nuclear facilities is evaluated in safety assessments. Essential components of these assessments are exposure models, which estimate the transport of radionuclides in the environment, the uptake in biota, and transfer to humans. Recently, there has been a growing concern for radiological protection of the whole environment, not only humans, and a first attempt has been to employ model approaches based on stylized environments and transfer functions to biota based exclusively on bioconcentration factors (BCF). They are generally of a non-mechanistic nature and involve no knowledge of the actual processes involved, which is a severe limitation when assessing real ecosystems. in this paper, the possibility of using an ecological modelling approach as a complement or an alternative to the use of BCF-based models is discussed. The paper gives an overview of ecological and ecosystem modelling and examples of studies where ecosystem models have been used in association to ecological risk assessment studies for other pollutants than radionuclides. It also discusses the potential to use this technique in exposure assessments of radionuclides with a few examples from the safety assessment work performed by the Swedish nuclear fuel and waste management company (SKB). Finally there is a comparison of the characteristics of ecosystem models and traditionally exposure models for radionuclides used to estimate the radionuclide exposure of biota. The evaluation of ecosystem models already applied in safety assessments has shown that the ecosystem approach is possible to use to assess exposure to biota, and that it can handle many of the modelling problems identified related to BCF-models. The findings in this paper suggest that both national and international assessment frameworks for protection of the environment from ionising radiation would benefit from striving to adopt methodologies based on ecologically sound principles and

Geographical influences of an emerging network of gang rivalries

Science.gov (United States)

Hegemann, Rachel A.; Smith, Laura M.; Barbaro, Alethea B. T.; Bertozzi, Andrea L.; Reid, Shannon E.; Tita, George E.

2011-10-01

We propose an agent-based model to simulate the creation of street gang rivalries. The movement dynamics of agents are coupled to an evolving network of gang rivalries, which is determined by previous interactions among agents in the system. Basic gang data, geographic information, and behavioral dynamics suggested by the criminology literature are integrated into the model. The major highways, rivers, and the locations of gangs’ centers of activity influence the agents’ motion. We use a policing division of the Los Angeles Police Department as a case study to test our model. We apply common metrics from graph theory to analyze our model, comparing networks produced by our simulations and an instance of a Geographical Threshold Graph to the existing network from the criminology literature.

Long-term exposure to gaseous air pollutants and cardio-respiratory mortality in Brisbane, Australia

Directory of Open Access Journals (Sweden)

Xiao Yu Wang

2009-05-01

Full Text Available This study examines the association of long-term exposure to gaseous air pollution with cardio-respiratory mortality in Brisbane, Australia, in the period 1996-2004. The pollutant concentrations were estimated using geographical information system (GIS techniques at the statistical local area (SLA level. The generalized estimating equations model was used to investigate the impact of nitrogen dioxide (NO2, ozone (O3 and sulphur dioxide (SO2 on mortality due to cardio-respiratory disease after adjusting for a range of potential confounders. An increase of 4.7% (95% confidence interval = 0.7-8.9% in cardio-respiratory mortality for 1 part per billion (ppb increment in annual average concentration of SO2 was estimated. However, there was no significant association between long-term exposures to NO2 or O3 and death due to cardio-respiratory disease. The results indicate that the annual average concentration of SO2 is associated with cardio-respiratory mortality at the SLA level and this association appears to vary with the geographical area.

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)

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.

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

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

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.

The Effect of Geographic Units of Analysis on Measuring Geographic Variation in Medical Services Utilization

Directory of Open Access Journals (Sweden)

Agnus M. Kim

2016-07-01

Full Text Available Objectives: We aimed to evaluate the effect of geographic units of analysis on measuring geographic variation in medical services utilization. For this purpose, we compared geographic variations in the rates of eight major procedures in administrative units (districts and new areal units organized based on the actual health care use of the population in Korea. Methods: To compare geographic variation in geographic units of analysis, we calculated the age–sex standardized rates of eight major procedures (coronary artery bypass graft surgery, percutaneous transluminal coronary angioplasty, surgery after hip fracture, knee-replacement surgery, caesarean section, hysterectomy, computed tomography scan, and magnetic resonance imaging scan from the National Health Insurance database in Korea for the 2013 period. Using the coefficient of variation, the extremal quotient, and the systematic component of variation, we measured geographic variation for these eight procedures in districts and new areal units. Results: Compared with districts, new areal units showed a reduction in geographic variation. Extremal quotients and inter-decile ratios for the eight procedures were lower in new areal units. While the coefficient of variation was lower for most procedures in new areal units, the pattern of change of the systematic component of variation between districts and new areal units differed among procedures. Conclusions: Geographic variation in medical service utilization could vary according to the geographic unit of analysis. To determine how geographic characteristics such as population size and number of geographic units affect geographic variation, further studies are needed.

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.

Cognitive decline, mortality, and organophosphorus exposure in aging Mexican Americans.

Science.gov (United States)

Paul, Kimberly C; Ling, Chenxiao; Lee, Anne; To, Tu My; Cockburn, Myles; Haan, Mary; Ritz, Beate

2018-01-01

Cognitive impairment is a major health concern among older Mexican Americans, associated with significant morbidity and mortality, and may be influenced by environmental exposures. To investigate whether agricultural based ambient organophosphorus (OP) exposure influences 1) the rate of cognitive decline and mortality and 2) whether these associations are mediated through metabolic or inflammatory biomarkers. In a subset of older Mexican Americans from the Sacramento Area Latino Study on Aging (n = 430), who completed modified mini-mental state exams (3MSE) up to 7 times (1998-2007), we examined the relationship between estimated ambient OP exposures and cognitive decline (linear repeated measures model) and time to dementia or being cognitively impaired but not demented (CIND) and time to mortality (cox proportional hazards model). We then explored metabolic and inflammatory biomarkers as potential mediators of these relationships (additive hazards mediation). OP exposures at residential addresses were estimated with a geographic information system (GIS) based exposure assessment tool. Participants with high OP exposure in the five years prior to baseline experienced faster cognitive decline (β = 0.038, p = 0.02) and higher mortality over follow-up (HR = 1.91, 95% CI = 1.12, 3.26). The direct effect of OP exposure was estimated at 241 (95% CI = 27-455) additional deaths per 100,000 person-years, and the proportion mediated through the metabolic hormone adiponectin was estimated to be 4% 1.5-19.2). No other biomarkers were associated with OP exposure. Our study provides support for the involvement of OP pesticides in cognitive decline and mortality among older Mexican Americans, possibly through biologic pathways involving adiponectin. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

The geosystems of complex geographical atlases

Directory of Open Access Journals (Sweden)

Jovanović Jasmina

2012-01-01

Full Text Available Complex geographical atlases represent geosystems of different hierarchical rank, complexity and diversity, scale and connection. They represent a set of large number of different pieces of information about geospace. Also, they contain systematized, correlative and in the apparent form represented pieces of information about space. The degree of information revealed in the atlas is precisely explained by its content structure and the form of presentation. The quality of atlas depends on the method of visualization of data and the quality of geodata. Cartographic visualization represents cognitive process. The analysis converts geospatial data into knowledge. A complex geographical atlas represents information complex of spatial - temporal coordinated database on geosystems of different complexity and territorial scope. Each geographical atlas defines a concrete geosystem. Systemic organization (structural and contextual determines its complexity and concreteness. In complex atlases, the attributes of geosystems are modeled and pieces of information are given in systematized, graphically unique form. The atlas can be considered as a database. In composing a database, semantic analysis of data is important. The result of semantic modeling is expressed in structuring of data information, in emphasizing logic connections between phenomena and processes and in defining their classes according to the degree of similarity. Accordingly, the efficiency of research of needed pieces of information in the process of the database use is enabled. An atlas map has a special power to integrate sets of geodata and present information contents in user - friendly and understandable visual and tactile way using its visual ability. Composing an atlas by systemic cartography requires the pieces of information on concrete - defined geosystems of different hierarchical level, the application of scientific methods and making of adequate number of analytical, synthetic

Integrative real-time geographic visualization of energy resources

International Nuclear Information System (INIS)

Sorokine, A.; Shankar, M.; Stovall, J.; Bhaduri, B.; King, T.; Fernandez, S.; Datar, N.; Omitaomu, O.

2009-01-01

'Full text:' Several models forecast that climatic changes will increase the frequency of disastrous events like droughts, hurricanes, and snow storms. Responding to these events and also to power outages caused by system errors such as the 2003 North American blackout require an interconnect-wide real-time monitoring system for various energy resources. Such a system should be capable of providing situational awareness to its users in the government and energy utilities by dynamically visualizing the status of the elements of the energy grid infrastructure and supply chain in geographic contexts. We demonstrate an approach that relies on Google Earth and similar standard-based platforms as client-side geographic viewers with a data-dependent server component. The users of the system can view status information in spatial and temporal contexts. These data can be integrated with a wide range of geographic sources including all standard Google Earth layers and a large number of energy and environmental data feeds. In addition, we show a real-time spatio-temporal data sharing capability across the users of the system, novel methods for visualizing dynamic network data, and a fine-grain access to very large multi-resolution geographic datasets for faster delivery of the data. The system can be extended to integrate contingency analysis results and other grid models to assess recovery and repair scenarios in the case of major disruption. (author)

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....

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.

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)

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.

Human Mercury Exposure in Yanomami Indigenous Villages from the Brazilian Amazon.

Science.gov (United States)

Vega, Claudia M; Orellana, Jesem D Y; Oliveira, Marcos W; Hacon, Sandra S; Basta, Paulo C

2018-05-23

In the Brazilian Amazon, where the majority of Yanomami villages are settled, mercury (Hg) exposure due to artisanal small-scale gold mining (ASGM) has been reported since the 1980s. This study assessed mercury exposure in the Yanomami reserve and whether the level of contamination was related to the ASGM geographical location. It was conducted using a cross-sectional study of 19 villages. Direct interviews were performed and hair samples were used as a bioindicator of Hg exposure. The Prevalence-Ratio (PR) was estimated as an indicator of association between ASGM geographical locations and human exposure to mercury. Mercury levels (239 hair samples) ranged between 0.4 and 22.1 μg·g -1 and presented substantial differences amongst the villages. In the Waikas-Aracaça region, where current ASGM was reported, we observed the highest Hg concentrations (median = 15.5 μg·g -1 ). Almost all participants presented with hair-Hg levels >6 μg·g -1 (prevalence = 92.3%). In the Paapiu region, we observed the lowest concentrations (median = 3.2 μg·g -1 ; prevalence = 6.7%). Our findings showed that the Waikas Ye'kuana and Waikas Aracaca villages presented with 4.4 (PR = 4.4; Confidence Interval (CI) 95% = 2.2⁻9.0) and 14.0 (PR = 14.0; CI 95% = 7.9⁻24.9) times higher prevalence of hair-Hg concentration, respectively, compared with Paapiu. Considering seasonal variation of Hg-exposure, the lowest concentrations were observed during the wet season (June⁻September) and the highest in the dry season (December⁻April). Our study suggests that there is an association between mercury exposure and ASGM geographical locations.

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

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

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

Fine particulate air pollution and premature atrial contractions: The REasons for Geographic And Racial Differences in Stroke study.

Science.gov (United States)

O'Neal, Wesley T; Soliman, Elsayed Z; Efird, Jimmy T; Judd, Suzanne E; Howard, Virginia J; Howard, George; McClure, Leslie A

2017-05-01

Several reports have suggested that particulate matter (PM) exposure increases the risk for atrial arrhythmias. However, data from large-scale epidemiologic studies supporting this hypothesis are lacking. We examined the association of PM <2.5 μm in diameter (PM 2.5 ) concentration with premature atrial contractions (PACs) in 26,609 (mean age=65±9.4 years; 55% female; 41% black) participants from the REGARDS (REasons for Geographic And Racial Differences in Stroke) study. Estimates of short- (2 weeks) and long-term (1 year) PM 2.5 exposure were computed before each participant's baseline visit using geographic information system data on the individual level at the coordinates of study participants' residences. PACs were identified from baseline electrocardiograms. A total of 2140 (8.2%) participants had evidence of PACs on the baseline electrocardiogram. Short-term PM 2.5 (per 10 μg/m 3 ) exposure was not associated with PACs (OR=1.09, 95% CI=0.98, 1.23). Increases in long-term PM 2.5 (per 10 μg/m 3 ) were associated with PACs (OR=1.40, 95% CI=1.10, 1.78). Interactions were not detected for short- and long-term PM 2.5 exposure by age, sex, or race. Long- but not short-term PM 2.5 exposure is associated with PACs. This suggests a role for long-term PM 2.5 exposure in initiating supraventricular arrhythmias that are triggered by PACs.

Steps towards optimization of medical exposures

International Nuclear Information System (INIS)

Araujo, A.M.C.; Drexler, G.; Oliveira, S.M.V.

1992-01-01

Data about ionizing radiation sources used in medical applications and obtained through and IRD/CNEN National Programme together with Brazilian health authorities are discussed. The data presentation follows, as close as possible, suggestions given by the United Nations Scientific Committee on effects of Atomic Radiation (UNSCEAR). This study uses the geographic country division into five regions. The results have been also analyzed for each region. Due to many demographic, social and economic differences among these regions, some modifications are proposed to the UNSCEAR collection data model, to be used in developing countries with similar situations. This programme has two main aims : (1) to investigate radiation source and radiation protection status in Brazil, in order to give assistance to Brazilian health authorities to plan regional radiation control programmes and training for medical staffs : (2) to implement the system of protection in medical exposures, following the 1990 ICRP recommendations. This includes the justification of a practice in medical exposures, the optimization protection and the possible application of dose constraints. (author)

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.

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

Geographic Ontologies, Gazetteers and Multilingualism

Directory of Open Access Journals (Sweden)

Robert Laurini

2015-01-01

Full Text Available Different languages imply different visions of space, so that terminologies are different in geographic ontologies. In addition to their geometric shapes, geographic features have names, sometimes different in diverse languages. In addition, the role of gazetteers, as dictionaries of place names (toponyms, is to maintain relations between place names and location. The scope of geographic information retrieval is to search for geographic information not against a database, but against the whole Internet: but the Internet stores information in different languages, and it is of paramount importance not to remain stuck to a unique language. In this paper, our first step is to clarify the links between geographic objects as computer representations of geographic features, ontologies and gazetteers designed in various languages. Then, we propose some inference rules for matching not only types, but also relations in geographic ontologies with the assistance of gazetteers.

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.

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

CalTOX, a multimedia total exposure model for hazardous-waste sites; Part 1, Executive summary

Energy Technology Data Exchange (ETDEWEB)

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.

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.

The shape and temporal dynamics of phylogenetic trees arising from geographic speciation.

Science.gov (United States)

Pigot, Alex L; Phillimore, Albert B; Owens, Ian P F; Orme, C David L

2010-12-01

Phylogenetic trees often depart from the expectations of stochastic models, exhibiting imbalance in diversification among lineages and slowdowns in the rate of lineage accumulation through time. Such departures have led to a widespread perception that ecological differences among species or adaptation and subsequent niche filling are required to explain patterns of diversification. However, a key element missing from models of diversification is the geographical context of speciation and extinction. In this study, we develop a spatially explicit model of geographic range evolution and cladogenesis, where speciation arises via vicariance or peripatry, and explore the effects of these processes on patterns of diversification. We compare the results with those observed in 41 reconstructed avian trees. Our model shows that nonconstant rates of speciation and extinction are emergent properties of the apportioning of geographic ranges that accompanies speciation. The dynamics of diversification exhibit wide variation, depending on the mode of speciation, tendency for range expansion, and rate of range evolution. By varying these parameters, the model is able to capture many, but not all, of the features exhibited by birth-death trees and extant bird clades. Under scenarios with relatively stable geographic ranges, strong slowdowns in diversification rates are produced, with faster rates of range dynamics leading to constant or accelerating rates of apparent diversification. A peripatric model of speciation with stable ranges also generates highly unbalanced trees typical of bird phylogenies but fails to produce realistic range size distributions among the extant species. Results most similar to those of a birth-death process are reached under a peripatric speciation scenario with highly volatile range dynamics. Taken together, our results demonstrate that considering the geographical context of speciation and extinction provides a more conservative null model of

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...

Specifying Geographic Information - Ontology, Knowledge Representation, and Formal Constraints

DEFF Research Database (Denmark)

Christensen, Jesper Vinther

2007-01-01

as in the private sector. The theoretical background is the establishment of a representational system, which ontologically comprises a representation of notions in the "real world" and notions which include the representation of these. Thus, the thesis leans towards a traditional division between modeling...... of domains and conceptualization of these. The thesis contributes a formalization of what is understood by domain models and conceptual models, when the focus is on geographic information. Moreover, it is shown how specifications for geographic information are related to this representational system...... of requirements and rules, building on terms from the domain and concept ontologies. In combination with the theoretical basis the analysis is used for developing an underlying model of notions, which defines the individual elements in a specification and the relations between them. In the chapters of the thesis...

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.

Experimental effects of climate messages vary geographically

Science.gov (United States)

Zhang, Baobao; van der Linden, Sander; Mildenberger, Matto; Marlon, Jennifer R.; Howe, Peter D.; Leiserowitz, Anthony

2018-05-01

Social science scholars routinely evaluate the efficacy of diverse climate frames using local convenience or nationally representative samples1-5. For example, previous research has focused on communicating the scientific consensus on climate change, which has been identified as a `gateway' cognition to other key beliefs about the issue6-9. Importantly, although these efforts reveal average public responsiveness to particular climate frames, they do not describe variation in message effectiveness at the spatial and political scales relevant for climate policymaking. Here we use a small-area estimation method to map geographical variation in public responsiveness to information about the scientific consensus as part of a large-scale randomized national experiment (n = 6,301). Our survey experiment finds that, on average, public perception of the consensus increases by 16 percentage points after message exposure. However, substantial spatial variation exists across the United States at state and local scales. Crucially, responsiveness is highest in more conservative parts of the country, leading to national convergence in perceptions of the climate science consensus across diverse political geographies. These findings not only advance a geographical understanding of how the public engages with information about scientific agreement, but will also prove useful for policymakers, practitioners and scientists engaged in climate change mitigation and adaptation.

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.

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.

Study of geographical trends of polycyclic aromatic hydrocarbons using pine needles

Science.gov (United States)

Amigo, José Manuel; Ratola, Nuno; Alves, Arminda

2011-10-01

In this work, pine needles were used as polycyclic aromatic hydrocarbons (PAHs) markers to study the PAHs distribution over several geographical locations in Portugal and over time. Four pine needle sampling campaigns (winter, spring, summer and autumn 2007) were carried out in 29 sites, covering the major urban centres, some industrial points, smaller cities, rural areas and remote locations. Needles from Pinus pinaster Ait. and Pinus pinea L. trees were collected from 2005 and 2006 shoots, corresponding to one up to three years of exposure. Spatial trends of the incidence of PAHs indicate an increase from the remote to the urban and industrial sites. The mean values for the sum of 16 PAHs ranged from 96 ± 30 ng g -1 (dry weight) for remote sites to 866 ± 304 ng g -1 (dw) for industrial sites for P. pinaster needles and from 188 ± 117 ng g -1 (dw) for rural sites to 337 ± 153 ng g -1 (dw) for urban sites for P. pinea. Geographic information system tools and principal component analysis revealed that the contamination patterns of PAHs are somehow related to several socio-geographic parameters of the sampling sites. The geographical trend for the PAHs is similar between seasons in terms of PAH levels, but some diverse behaviour is found on the separation of lighter and heavier PAHs. Differences between P. pinaster and P. pinea needles are stronger in terms of PAH uptake loads than in the site type fingerprints.

Non-professional user`s understanding of Geographic Information

DEFF Research Database (Denmark)

Arleth, Mette

2003-01-01

of digital media, including online access to a variety of GI-based services; maps, online Geographic information systems, interactive 3D models etc. However, can we expect that a citizen, who has no relevant professional basis for understanding the concept geographic information, be able to use GI......-based online services and comprehend the information contents? Using the Gi-based online services qualitatively in the participatory process obviously requires knowledge of the non-professional user`s understanding and use of GI. This paper discusses the needs for research into this field as well as relevant...

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

Human Mercury Exposure in Yanomami Indigenous Villages from the Brazilian Amazon

Directory of Open Access Journals (Sweden)

Claudia M. Vega

2018-05-01

Full Text Available In the Brazilian Amazon, where the majority of Yanomami villages are settled, mercury (Hg exposure due to artisanal small-scale gold mining (ASGM has been reported since the 1980s. This study assessed mercury exposure in the Yanomami reserve and whether the level of contamination was related to the ASGM geographical location. It was conducted using a cross-sectional study of 19 villages. Direct interviews were performed and hair samples were used as a bioindicator of Hg exposure. The Prevalence-Ratio (PR was estimated as an indicator of association between ASGM geographical locations and human exposure to mercury. Mercury levels (239 hair samples ranged between 0.4 and 22.1 μg·g−1 and presented substantial differences amongst the villages. In the Waikas-Aracaça region, where current ASGM was reported, we observed the highest Hg concentrations (median = 15.5 μg·g−1. Almost all participants presented with hair-Hg levels >6 μg·g−1 (prevalence = 92.3%. In the Paapiu region, we observed the lowest concentrations (median = 3.2 μg·g−1; prevalence = 6.7%. Our findings showed that the Waikas Ye’kuana and Waikas Aracaca villages presented with 4.4 (PR = 4.4; Confidence Interval (CI 95% = 2.2–9.0 and 14.0 (PR = 14.0; CI 95% = 7.9–24.9 times higher prevalence of hair-Hg concentration, respectively, compared with Paapiu. Considering seasonal variation of Hg-exposure, the lowest concentrations were observed during the wet season (June–September and the highest in the dry season (December–April. Our study suggests that there is an association between mercury exposure and ASGM geographical locations.

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...

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.

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.

Transport link scanner: simulating geographic transport network expansion through individual investments

Science.gov (United States)

Jacobs-Crisioni, C.; Koopmans, C. C.

2016-07-01

This paper introduces a GIS-based model that simulates the geographic expansion of transport networks by several decision-makers with varying objectives. The model progressively adds extensions to a growing network by choosing the most attractive investments from a limited choice set. Attractiveness is defined as a function of variables in which revenue and broader societal benefits may play a role and can be based on empirically underpinned parameters that may differ according to private or public interests. The choice set is selected from an exhaustive set of links and presumably contains those investment options that best meet private operator's objectives by balancing the revenues of additional fare against construction costs. The investment options consist of geographically plausible routes with potential detours. These routes are generated using a fine-meshed regularly latticed network and shortest path finding methods. Additionally, two indicators of the geographic accuracy of the simulated networks are introduced. A historical case study is presented to demonstrate the model's first results. These results show that the modelled networks reproduce relevant results of the historically built network with reasonable accuracy.

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.

AN ENCODING METHOD FOR COMPRESSING GEOGRAPHICAL COORDINATES IN 3D SPACE

Directory of Open Access Journals (Sweden)

C. Qian

2017-09-01

Full Text Available This paper proposed an encoding method for compressing geographical coordinates in 3D space. By the way of reducing the length of geographical coordinates, it helps to lessen the storage size of geometry information. In addition, the encoding algorithm subdivides the whole space according to octree rules, which enables progressive transmission and loading. Three main steps are included in this method: (1 subdividing the whole 3D geographic space based on octree structure, (2 resampling all the vertices in 3D models, (3 encoding the coordinates of vertices with a combination of Cube Index Code (CIC and Geometry Code. A series of geographical 3D models were applied to evaluate the encoding method. The results showed that this method reduced the storage size of most test data by 90 % or even more under the condition of a speed of encoding and decoding. In conclusion, this method achieved a remarkable compression rate in vertex bit size with a steerable precision loss. It shall be of positive meaning to the web 3d map storing and transmission.

Soil-transmitted helminth prevalence and infection intensity among geographically and economically distinct Shuar communities in the Ecuadorian Amazon.

Science.gov (United States)

Cepon-Robins, Tara J; Liebert, Melissa A; Gildner, Theresa E; Urlacher, Samuel S; Colehour, Alese M; Snodgrass, J Josh; Madimenos, Felicia C; Sugiyama, Lawrence S

2014-10-01

Soil-transmitted helminth (STH) infections can result in a variety of negative health outcomes (e.g., diarrhea, nutritional deficiencies). Market integration (MI; participation in market-based economies) has been suggested to alter levels of STH exposure due to associated changes in diet, sanitation, and behavior, but the effects are complicated and not well understood. Some effects of economic development result in decreased exposure to certain pathogens, and other factors can lead to higher pathogen exposure. With geographic location used as a proxy, the present study investigates the effects of economic development on parasite load among an indigenous population at multiple points along the spectrum of MI. This research has many implications for public health, including an increased understanding of how social and economic changes alter disease risk around the world and how changing parasite load affects other health outcomes (i.e., allergy, autoimmunity). Specifically, this study examines the prevalence of intestinal helminths among the Shuar, an indigenous group in the Morona-Santiago region of Ecuador, from 2 geographically/economically separated areas, with the following objectives: (1) report STH infection prevalence and intensity among Shuar; (2) explore STH infection prevalence and intensity as it relates to age distribution in the Shuar population; (3) compare STH infection patterns in geographically and economically separated Shuar communities at different levels of MI. Kato-Katz thick smears were made from fresh stool samples and examined to determine STH presence/intensity. Results indicate that 65% of the 211 participants were infected with at least 1 STH. Twenty-five percent of the sample had coinfections with at least 2 species of helminth. Infection was more common among juveniles (<15 yr) than adults. Infection prevalence and intensity was highest among more isolated communities with less market access. This study documents preliminary

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.

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.

GEOGRAPHIC NAMES INFORMATION SYSTEM (GNIS) ...

Science.gov (United States)

The Geographic Names Information System (GNIS), developed by the U.S. Geological Survey in cooperation with the U.S. Board on Geographic Names (BGN), contains information about physical and cultural geographic features in the United States and associated areas, both current and historical, but not including roads and highways. The database also contains geographic names in Antarctica. The database holds the Federally recognized name of each feature and defines the location of the feature by state, county, USGS topographic map, and geographic coordinates. Other feature attributes include names or spellings other than the official name, feature designations, feature class, historical and descriptive information, and for some categories of features the geometric boundaries. The database assigns a unique feature identifier, a random number, that is a key for accessing, integrating, or reconciling GNIS data with other data sets. The GNIS is our Nation's official repository of domestic geographic feature names information.

Inhale while Dreaming: Human Exposure to Pollutants while Sleeping

DEFF Research Database (Denmark)

Corsi, Richard; Spilak, Michal; Boor, E., Brandon

2012-01-01

of indoor pollutants, e.g., flame retardants to isocyanates. As such, there is a need for increased dialogue on this subject, end-point relevant research, and action to reduce exposures to high-risk contaminants for most of humanity. This workshop will involve an opening 5–minute presentation related...... discussion related to practical implications of new findings as well as past studies, geographic variations in emissions from mattresses and beddings, methods for reducing population exposures, and suggestions for future research that has practical endpoints and that can lead to reduced exposures....

Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China.

Science.gov (United States)

Shi, Benyun; Tan, Qi; Zhou, Xiao-Nong; Liu, Jiming

2015-05-27

Geographic variations of an infectious disease characterize the spatial differentiation of disease incidences caused by various impact factors, such as environmental, demographic, and socioeconomic factors. Some factors may directly determine the force of infection of the disease (namely, explicit factors), while many other factors may indirectly affect the number of disease incidences via certain unmeasurable processes (namely, implicit factors). In this study, the impact of heterogeneous factors on geographic variations of Plasmodium vivax incidences is systematically investigate in Tengchong, Yunnan province, China. A space-time model that resembles a P. vivax transmission model and a hidden time-dependent process, is presented by taking into consideration both explicit and implicit factors. Specifically, the transmission model is built upon relevant demographic, environmental, and biophysical factors to describe the local infections of P. vivax. While the hidden time-dependent process is assessed by several socioeconomic factors to account for the imported cases of P. vivax. To quantitatively assess the impact of heterogeneous factors on geographic variations of P. vivax infections, a Markov chain Monte Carlo (MCMC) simulation method is developed to estimate the model parameters by fitting the space-time model to the reported spatial-temporal disease incidences. Since there is no ground-truth information available, the performance of the MCMC method is first evaluated against a synthetic dataset. The results show that the model parameters can be well estimated using the proposed MCMC method. Then, the proposed model is applied to investigate the geographic variations of P. vivax incidences among all 18 towns in Tengchong, Yunnan province, China. Based on the geographic variations, the 18 towns can be further classify into five groups with similar socioeconomic causality for P. vivax incidences. Although this study focuses mainly on the transmission of P. vivax

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.

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.

An Allometric Algorithm for Fractal-Based Cobb-Douglas Function of Geographical Systems

Directory of Open Access Journals (Sweden)

Hongyu Luo

2014-01-01

Full Text Available The generalized Cobb-Douglas production function has been derived from a general input-output relation based on fractality assumptions. It was proved to be a useful self-affine model for geographical analysis. However, the ordinary least square calculation is always an ineffectual method for the Cobb-Douglas modeling because of the multicollinearity in the logarithmic linear regression. In this paper, a novel approach is proposed to build the geographical Cobb-Douglas models. Combining the concept of allometric scaling with the linear regression technique, we obtain a simple algorithm that can be employed to estimate the parameters of the Cobb-Douglas function. As a case, the algorithm and models are applied to the public transportation of China’s cities, and the results validate the allometric algorithm. A conclusion can be drawn that the allometric analysis is an effective way of modeling geographical systems with the general Cobb-Douglas function. This study is significant for integrating the notions of allometry, fractals, and scaling into a new framework to form a quantitative methodology of spatial analysis.

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.

Correlates and geographic patterns of knowledge that physical activity decreases cancer risk.

Science.gov (United States)

Ramírez, A Susana; Finney Rutten, Lila J; Vanderpool, Robin C; Moser, Richard P; Hesse, Bradford W

2013-04-01

While many lifestyle-related cancer risk factors including tobacco use, poor diet, and sun exposure are well recognized by the general public, the role of physical activity in decreasing cancer risk is less recognized. Studies have demonstrated gender-, race/ethnicity-, and age-based disparities in cancer risk factor knowledge; however, beliefs and geographic factors that may be related to knowledge are under-examined. In this study, we analyzed data from the 2008 Health Information National Trends Survey to determine correlates of knowledge of the relationship between physical activity and reduced cancer risk in the adult US population. We generated geographic information system maps to examine the geographic distribution of this knowledge. Results revealed that there is confusion among US adults about the relationship between physical activity and cancer risk: Respondents who believed that cancer is not preventable had significantly lower odds of knowing that physical activity reduces cancer risk (p physical activity reduces cancer risk (p physical activity guidelines were also significantly more likely to know that physical activity reduces cancer risk (p physical inactivity. Correlates of cancer risk factor knowledge point to opportunities for targeted interventions.

Exploring the Utility of Model-based Meteorology Data for Heat-Related Health Research and Surveillance

Science.gov (United States)

Vaidyanathan, A.; Yip, F.

2017-12-01

Context: Studies that have explored the impacts of environmental exposure on human health have mostly relied on data from weather stations, which can be limited in geographic scope. For this assessment, we: (1) evaluated the performance of the meteorological data from the North American Land Data Assimilation System Phase 2 (NLDAS) model with measurements from weather stations for public health and specifically for CDC's Environmental Public Health Tracking Program, and (2) conducted a health assessment to explore the relationship between heat exposure and mortality, and examined region-specific differences in heat-mortality (H-M) relationships when using model-based estimates in place of measurements from weather stations.Methods: Meteorological data from the NLDAS Phase 2 model was evaluated against measurements from weather stations. A time-series analysis was conducted, using both station- and model-based data, to generate H-M relationships for counties in the U.S. The county-specific risk information was pooled to characterize regional relationships for both station- and model-based data, which were then compared to identify degrees of overlap and discrepancies between results generated using the two data sources. Results: NLDAS-based heat metrics were in agreement with those generated using weather station data. In general, the H-M relationship tended to be non-linear and varied by region, particularly the heat index value at which the health risks become positively significant. However, there was a high degree of overlap between region-specific H-M relationships generated from weather stations and the NLDAS model.Interpretation: Heat metrics from NLDAS model are available for all counties in the coterminous U.S. from 1979-2015. These data can facilitate health research and surveillance activities exploring health impacts associated with long-term heat exposures at finer geographic scales.Conclusion: High spatiotemporal coverage of environmental health data

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 ...

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.

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...

Volunteered Geographic Information in Wikipedia

Science.gov (United States)

Hardy, Darren

2010-01-01

Volunteered geographic information (VGI) refers to the geographic subset of online user-generated content. Through Geobrowsers and online mapping services, which use geovisualization and Web technologies to share and produce VGI, a global digital commons of geographic information has emerged. A notable example is Wikipedia, an online collaborative…

Predicting geographically distributed adult dental decay in the greater Auckland region of New Zealand.

Science.gov (United States)

Rocha, C M; Kruger, E; Whyman, R; Tennant, M

2014-06-01

To model the geographic distribution of current (and treated) dental decay on a high-resolution geographic basis for the Auckland region of New Zealand. The application of matrix-based mathematics to modelling adult dental disease-based on known population risk profiles to provide a detailed map of the dental caries distribution for the greater Auckland region. Of the 29 million teeth in adults in the region some 1.2 million (4%) are suffering decay whilst 7.2 million (25%) have previously suffered decay and are now restored. The model provides a high-resolution picture of where the disease burden lies geographically and presents to health planners a method for developing future service plans.

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.

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.

Geographic Names Information System (GNIS) for Lousiana, Geographic NAD83, USGS (2007) [GNIS_LA_USGS_2007

Data.gov (United States)

Louisiana Geographic Information Center — The Geographic Names Information System (GNIS) is the Federal standard for geographic nomenclature. The U.S. Geological Survey developed the GNIS for the U.S. Board...

Towns conquer: a gamified application to collect geographical names (vernacular names/toponyms)

OpenAIRE

Castellote, Jesus; Huerta, Joaquin; Pescador, Javier; Brown, Michael

2013-01-01

Ponència presentada a 16th AGILE Conference on Geographic Information Science, Geographic Information Science at the Heart of Europe, 14-17 May 2013, Leuven, Belgium The traditional model for geospatial crowd sourcing asks the public to use their free time collecting geospatial data for no obvious reward. This model has shown to work very well on projects such as Open Street Map, but comes with some clear disadvantages such as reliance on small communities ...

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.

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

Development of planning level transportation safety tools using Geographically Weighted Poisson Regression.

Science.gov (United States)

Hadayeghi, Alireza; Shalaby, Amer S; Persaud, Bhagwant N

2010-03-01

A common technique used for the calibration of collision prediction models is the Generalized Linear Modeling (GLM) procedure with the assumption of Negative Binomial or Poisson error distribution. In this technique, fixed coefficients that represent the average relationship between the dependent variable and each explanatory variable are estimated. However, the stationary relationship assumed may hide some important spatial factors of the number of collisions at a particular traffic analysis zone. Consequently, the accuracy of such models for explaining the relationship between the dependent variable and the explanatory variables may be suspected since collision frequency is likely influenced by many spatially defined factors such as land use, demographic characteristics, and traffic volume patterns. The primary objective of this study is to investigate the spatial variations in the relationship between the number of zonal collisions and potential transportation planning predictors, using the Geographically Weighted Poisson Regression modeling technique. The secondary objective is to build on knowledge comparing the accuracy of Geographically Weighted Poisson Regression models to that of Generalized Linear Models. The results show that the Geographically Weighted Poisson Regression models are useful for capturing spatially dependent relationships and generally perform better than the conventional Generalized Linear Models. Copyright 2009 Elsevier Ltd. All rights reserved.

Impacts of Scale on Geographic Analysis of Health Data: An Example of Obesity Prevalence

Directory of Open Access Journals (Sweden)

Jay Lee

2014-10-01

Full Text Available The prevalence of obesity has increased dramatically in recent decades. It is an important public health issue as it causes many other chronic health conditions, such as hypertension, cardiovascular diseases, and type II diabetics. Obesity affects life expectancy and even the quality of lives. Eventually, it increases social costs in many ways due to increasing costs of health care and workplace absenteeism. Using the spatial patterns of obesity prevalence as an example; we show how different geographic units can reveal different degrees of detail in results of analysis. We used both census tracts and census block groups as units of geographic analysis. In addition; to reveal how different geographic scales may impact on the analytic results; we applied geographically weighted regression to model the relationships between obesity rates (dependent variable and three independent variables; including education attainment; unemployment rates; and median family income. Though not including an exhaustive list of explanatory variables; this regression model provides an example for revealing the impacts of geographic scales on analysis of health data. With obesity data based on reported heights and weights on driver’s licenses in Summit County, Ohio, we demonstrated that geographically weighted regression reveals varying spatial trends between dependent and independent variables that conventional regression models such as ordinary least squares regression cannot. Most importantly, analyses carried out with different geographic scales do show very different results. With these findings, we suggest that, while possible, smaller geographic units be used to allow better understanding of the studies phenomena.

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

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

Changes at the National Geographic Society

Science.gov (United States)

Schwille, Kathleen

2016-01-01

For more than 125 years, National Geographic has explored the planet, unlocking its secrets and sharing them with the world. For almost thirty of those years, National Geographic has been committed to K-12 educators and geographic education through its Network of Alliances. As National Geographic begins a new chapter, they remain committed to the…

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…

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

Geographical information systems and computer cartography

CERN Document Server

Jones, Chris B

2014-01-01

A concise text presenting the fundamental concepts in Geographical Information Systems (GIS), emphasising an understanding of techniques in management, analysis and graphic display of spatial information. Divided into five parts - the first part reviews the development and application of GIS, followed by a summary of the characteristics and representation of geographical information. It concludes with an overview of the functions provided by typical GIS systems. Part Two introduces co-ordinate systems and map projections, describes methods for digitising map data and gives an overview of remote sensing. Part Three deals with data storage and database management, as well as specialised techniques for accessing spatial data. Spatial modelling and analytical techniques for decision making form the subject of Part Four, while the final part is concerned with graphical representation, emphasising issues of graphics technology, cartographic design and map generalisation.

Real-Time Aircraft Cosmic Ray Radiation Exposure Predictions from the NAIRAS Model

Science.gov (United States)

Mertens, C. J.; Tobiska, W.; Kress, B. T.; Xu, X.

2012-12-01

The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting commercial aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Thus, the NAIRAS model addresses an important national need with broad societal, public health and economic benefits. There is also interest in extending NAIRAS to the LEO environment to address radiation hazard issues for the emerging commercial spaceflight industry. The processes responsible for the variability in the solar wind, interplanetary magnetic field, solar energetic particle spectrum, and the dynamical response of the magnetosphere to these space environment inputs, strongly influence the composition and energy distribution of the atmospheric ionizing radiation field. Real-time observations are required at a variety of locations within the geospace environment. The NAIRAS model is driven by real-time input data from ground-, atmospheric-, and space-based platforms. During the development of the NAIRAS model, new science questions and observational data gaps were identified that must be addressed in order to obtain a more reliable and robust operational model of atmospheric radiation exposure. The focus of this talk is to present the current capabilities of the NAIRAS model, discuss future developments in aviation radiation modeling and instrumentation, and propose strategies and methodologies of bridging known gaps in current modeling and observational capabilities.

OGC Geographic Information Service Deductive Semantic Reasoning Based on Description Vocabularies Reduction

Directory of Open Access Journals (Sweden)

MIAO Lizhi

2015-09-01

Full Text Available As geographic information interoperability and sharing developing, more and more interoperable OGC (open geospatial consortium Web services (OWS are generated and published through the internet. These services can facilitate the integration of different scientific applications by searching, finding, and utilizing the large number of scientific data and Web services. However, these services are widely dispersed and hard to be found and utilized with executive semantic retrieval. This is especially true when considering the weak semantic description of geographic information service data. Focusing on semantic retrieval and reasoning of the distributed OWS resources, a deductive and semantic reasoning method is proposed to describe and search relevant OWS resources. Specifically, ①description words are extracted from OWS metadata file to generate GISe ontology-database and instance-database based on geographic ontology according to basic geographic elements category, ②a description words reduction model is put forward to implement knowledge reduction on GISe instance-database based on rough set theory and generate optimized instances database, ③utilizing GISe ontology-database and optimized instance-database to implement semantic inference and reasoning of geographic searching objects is used as an example to demonstrate the efficiency, feasibility and recall ration of the proposed description-word-based reduction model.

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

Modeling personal particle-bound polycyclic aromatic hydrocarbon (pb-pah) exposure in human subjects in Southern California.

Science.gov (United States)

Wu, Jun; Tjoa, Thomas; Li, Lianfa; Jaimes, Guillermo; Delfino, Ralph J

2012-07-11

Exposure to polycyclic aromatic hydrocarbon (PAH) has been linked to various adverse health outcomes. Personal PAH exposures are usually measured by personal monitoring or biomarkers, which are costly and impractical for a large population. Modeling is a cost-effective alternative to characterize personal PAH exposure although challenges exist because the PAH exposure can be highly variable between locations and individuals in non-occupational settings. In this study we developed models to estimate personal inhalation exposures to particle-bound PAH (PB-PAH) using data from global positioning system (GPS) time-activity tracking data, traffic activity, and questionnaire information. We conducted real-time (1-min interval) personal PB-PAH exposure sampling coupled with GPS tracking in 28 non-smoking women for one to three sessions and one to nine days each session from August 2009 to November 2010 in Los Angeles and Orange Counties, California. Each subject filled out a baseline questionnaire and environmental and behavior questionnaires on their typical activities in the previous three months. A validated model was used to classify major time-activity patterns (indoor, in-vehicle, and other) based on the raw GPS data. Multiple-linear regression and mixed effect models were developed to estimate averaged daily and subject-level PB-PAH exposures. The covariates we examined included day of week and time of day, GPS-based time-activity and GPS speed, traffic- and roadway-related parameters, meteorological variables (i.e. temperature, wind speed, relative humidity), and socio-demographic variables and occupational exposures from the questionnaire. We measured personal PB-PAH exposures for 180 days with more than 6 h of valid data on each day. The adjusted R2 of the model was 0.58 for personal daily exposures, 0.61 for subject-level personal exposures, and 0.75 for subject-level micro-environmental exposures. The amount of time in vehicle (averaging 4.5% of total

Modeling personal particle-bound polycyclic aromatic hydrocarbon (pb-pah exposure in human subjects in Southern California

Directory of Open Access Journals (Sweden)

Wu Jun

2012-07-01

Full Text Available Abstract Background Exposure to polycyclic aromatic hydrocarbon (PAH has been linked to various adverse health outcomes. Personal PAH exposures are usually measured by personal monitoring or biomarkers, which are costly and impractical for a large population. Modeling is a cost-effective alternative to characterize personal PAH exposure although challenges exist because the PAH exposure can be highly variable between locations and individuals in non-occupational settings. In this study we developed models to estimate personal inhalation exposures to particle-bound PAH (PB-PAH using data from global positioning system (GPS time-activity tracking data, traffic activity, and questionnaire information. Methods We conducted real-time (1-min interval personal PB-PAH exposure sampling coupled with GPS tracking in 28 non-smoking women for one to three sessions and one to nine days each session from August 2009 to November 2010 in Los Angeles and Orange Counties, California. Each subject filled out a baseline questionnaire and environmental and behavior questionnaires on their typical activities in the previous three months. A validated model was used to classify major time-activity patterns (indoor, in-vehicle, and other based on the raw GPS data. Multiple-linear regression and mixed effect models were developed to estimate averaged daily and subject-level PB-PAH exposures. The covariates we examined included day of week and time of day, GPS-based time-activity and GPS speed, traffic- and roadway-related parameters, meteorological variables (i.e. temperature, wind speed, relative humidity, and socio-demographic variables and occupational exposures from the questionnaire. Results We measured personal PB-PAH exposures for 180 days with more than 6 h of valid data on each day. The adjusted R2 of the model was 0.58 for personal daily exposures, 0.61 for subject-level personal exposures, and 0.75 for subject-level micro-environmental exposures. The amount

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...

Progress in Space Weather Modeling and Observations Needed to Improve the Operational NAIRAS Model Aircraft Radiation Exposure Predictions

Science.gov (United States)

Mertens, C. J.; Kress, B. T.; Wiltberger, M. J.; Tobiska, W.; Xu, X.

2011-12-01

The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting commercial aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Thus, the NAIRAS model addresses an important national need with broad societal, public health and economic benefits. The processes responsible for the variability in the solar wind, interplanetary magnetic field, solar energetic particle spectrum, and the dynamical response of the magnetosphere to these space environment inputs, strongly influence the composition and energy distribution of the atmospheric ionizing radiation field. During the development of the NAIRAS model, new science questions were identified that must be addressed in order to obtain a more reliable and robust operational model of atmospheric radiation exposure. Addressing these science questions require improvements in both space weather modeling and observations. The focus of this talk is to present these science questions, the proposed methodologies for addressing these science questions, and the anticipated improvements to the operational predictions of atmospheric radiation exposure. The overarching goal of this work is to provide a decision support tool for the aviation industry that will enable an optimal balance to be achieved between minimizing health risks to passengers and aircrew while simultaneously minimizing costs to the airline companies.

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

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...

Radio frequency exposure in mobile phone users: Implications for exposure assessment in epidemiological studies

International Nuclear Information System (INIS)

Morrissey, J. J.

2007-01-01

The majority of epidemiological studies investigating correlations between long-term low-level radiofrequency (RF) exposure from mobile phones and health endpoints have followed a case-control design, requiring reconstruction of individual RF exposure. To date, these have employed 'time of use' as an exposure surrogate from questionnaire information or billing records. The present study demonstrates such an approach may not account for variability in mobile phone transmit power, which can be roughly correlated with RF exposure. This variability exists (a) during a single call, (b) between separate calls, (c) between averaged values from individuals within a local study group and (d) between average values from groups in different geographical locations. The present data also suggest an age-related influence on talk time, as well as significant inaccuracy (45-60%) in recalling 'time of use'. Evolving technology and changing use behaviours may add additional complexities. Collectively, these data suggest efforts to identify dose response and statistical correlations between mobile phone use and subtle health endpoints may be significantly challenged. (authors)

Geographical National Condition and Complex System

Directory of Open Access Journals (Sweden)

WANG Jiayao

2016-01-01

Full Text Available The significance of studying the complex system of geographical national conditions lies in rationally expressing the complex relationships of the “resources-environment-ecology-economy-society” system. Aiming to the problems faced by the statistical analysis of geographical national conditions, including the disunity of research contents, the inconsistency of range, the uncertainty of goals, etc.the present paper conducted a range of discussions from the perspectives of concept, theory and method, and designed some solutions based on the complex system theory and coordination degree analysis methods.By analyzing the concepts of geographical national conditions, geographical national conditions survey and geographical national conditions statistical analysis, as well as investigating the relationships between theirs, the statistical contents and the analytical range of geographical national conditions are clarified and defined. This investigation also clarifies the goals of the statistical analysis by analyzing the basic characteristics of the geographical national conditions and the complex system, and the consistency between the analysis of the degree of coordination and statistical analyses. It outlines their goals, proposes a concept for the complex system of geographical national conditions, and it describes the concept. The complex system theory provides new theoretical guidance for the statistical analysis of geographical national conditions. The degree of coordination offers new approaches on how to undertake the analysis based on the measurement method and decision-making analysis scheme upon which the complex system of geographical national conditions is based. It analyzes the overall trend via the degree of coordination of the complex system on a macro level, and it determines the direction of remediation on a micro level based on the degree of coordination among various subsystems and of single systems. These results establish

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...

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...

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

Emplacement of ideas. The development of geographical thought in Brazil in the early 20th century

Directory of Open Access Journals (Sweden)

Lia Osorio Machado

1998-06-01

Full Text Available This paper looks at the circulation of modern geographical ideas in Brazil. The focus is on the relationship between geographical source models and the target model of domestic modernization. Three corresponding "mechanisms" provided the translation from one to the other: gradualism, adaptation and essentialism.

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.

A national prediction model for PM2.5 component exposures and measurement error-corrected health effect inference.

Science.gov (United States)

Bergen, Silas; Sheppard, Lianne; Sampson, Paul D; Kim, Sun-Young; Richards, Mark; Vedal, Sverre; Kaufman, Joel D; Szpiro, Adam A

2013-09-01

Studies estimating health effects of long-term air pollution exposure often use a two-stage approach: building exposure models to assign individual-level exposures, which are then used in regression analyses. This requires accurate exposure modeling and careful treatment of exposure measurement error. To illustrate the importance of accounting for exposure model characteristics in two-stage air pollution studies, we considered a case study based on data from the Multi-Ethnic Study of Atherosclerosis (MESA). We built national spatial exposure models that used partial least squares and universal kriging to estimate annual average concentrations of four PM2.5 components: elemental carbon (EC), organic carbon (OC), silicon (Si), and sulfur (S). We predicted PM2.5 component exposures for the MESA cohort and estimated cross-sectional associations with carotid intima-media thickness (CIMT), adjusting for subject-specific covariates. We corrected for measurement error using recently developed methods that account for the spatial structure of predicted exposures. Our models performed well, with cross-validated R2 values ranging from 0.62 to 0.95. Naïve analyses that did not account for measurement error indicated statistically significant associations between CIMT and exposure to OC, Si, and S. EC and OC exhibited little spatial correlation, and the corrected inference was unchanged from the naïve analysis. The Si and S exposure surfaces displayed notable spatial correlation, resulting in corrected confidence intervals (CIs) that were 50% wider than the naïve CIs, but that were still statistically significant. The impact of correcting for measurement error on health effect inference is concordant with the degree of spatial correlation in the exposure surfaces. Exposure model characteristics must be considered when performing two-stage air pollution epidemiologic analyses because naïve health effect inference may be inappropriate.

Proposed retention model for human inhalation exposure to 241AmO2

International Nuclear Information System (INIS)

Mewhinney, J.A.; Griffith, W.C.; Muggenburg, B.A.

1980-01-01

A dosimetry model based on a four-year study in Beagle dogs was developed to predict patterns of absorbed radiation doses for people exposed by inhalation to 241 AmO 2 . Following a single inhalation exposure to one of three sizes of monodisperse or a polydisperse aerosol of 241 AmO 2 , pairs of dogs were sacrificed at 8, 32, 64 and 256 days, and 2 and 4 years. For about 80% of the initial lung burden, the retention halftimes were 11, 18, 26 and 27 days for the 0.75, 1.5 and 3.0 μm aerodynamic diameter and the 1.8 μm activity median aerodynamic diameter aerosols, respectively. For the remaining 20% of the initial lung burden, the retention halftimes were between 200 to 300 days with no apparent particle size influence. Additional 241 Am metabolic studies reported in the literature using inhalation exposure or injection of the citrate complex were synthesized in the model as were eleven reported cases of human inhalation exposure. This model is compared to the ICRP II and TGLD lung models, both developed by analogy to Pu metabolism. The proposed model differs from these latter models in two important areas: (a) lung retention of 241 AmO 2 could not be adapted to the classifications used in these models, and (b) the fractional translocation from lung to other organs is 2 to 8 times larger. These factors considerably alter the predicted radiation dose distribution among organs and lead to the conclusion that derived radiation protection standards for 241 AmO 2 inhalation exposure should be modified. (author)

An introduction to the indirect exposure assessment approach: modeling human exposure using microenvironmental measurements and the recent National Human Activity Pattern Survey.

Science.gov (United States)

Klepeis, N E

1999-01-01

Indirect exposure approaches offer a feasible and accurate method for estimating population exposures to indoor pollutants, including environmental tobacco smoke (ETS). In an effort to make the indirect exposure assessment approach more accessible to people in the health and risk assessment fields, this paper provides examples using real data from (italic>a(/italic>) a week-long personal carbon monoxide monitoring survey conducted by the author; and (italic>b(/italic>) the 1992 to 1994 National Human Activity Pattern Survey (NHAPS) for the United States. The indirect approach uses measurements of exposures in specific microenvironments (e.g., homes, bars, offices), validated microenvironmental models (based on the mass balance equation), and human activity pattern data obtained from questionnaires to predict frequency distributions of exposure for entire populations. This approach requires fewer resources than the direct approach to exposure assessment, for which the distribution of monitors to a representative sample of a given population is necessary. In the indirect exposure assessment approach, average microenvironmental concentrations are multiplied by the total time spent in each microenvironment to give total integrated exposure. By assuming that the concentrations encountered in each of 10 location categories are the same for different members of the U.S. population (i.e., the NHAPS respondents), the hypothetical contribution that ETS makes to the average 24-hr respirable suspended particle exposure for Americans working their main job is calculated in this paper to be 18 microg/m3. This article is an illustrative review and does not contain an actual exposure assessment or model validation. Images Figure 3 Figure 4 PMID:10350522

Geographical influence of heat stress on milk production of Holstein ...

African Journals Online (AJOL)

To model the influence of heat stress on milk production of Holstein dairy herds on pasture in South Africa, the maximum entropy (Maxent) modelling technique was used in a novel approach to model and map optimal milk-producing areas. Geographical locations of farms with top milk-producing Holstein herds on pasture ...

Geographic approaches to quantifying the risk environment: a focus on syringe exchange program site access and drug-related law enforcement activities

Science.gov (United States)

Cooper, Hannah LF; Bossak, Brian; Tempalski, Barbara; Des Jarlais, Don C.; Friedman, Samuel R.

2009-01-01

The concept of the “risk environment” – defined as the “space … [where] factors exogenous to the individual interact to increase the chances of HIV transmission” – draws together the disciplines of public health and geography. Researchers have increasingly turned to geographic methods to quantify dimensions of the risk environment that are both structural and spatial (e.g., local poverty rates). The scientific power of the intersection between public health and geography, however, has yet to be fully mined. In particular, research on the risk environment has rarely applied geographic methods to create neighbourhood-based measures of syringe exchange programs (SEPs) or of drug-related law enforcement activities, despite the fact that these interventions are widely conceptualized as structural and spatial in nature and are two of the most well-established dimensions of the risk environment. To strengthen research on the risk environment, this paper presents a way of using geographic methods to create neighbourhood-based measures of (1) access to SEP sites and (2) exposure to drug-related arrests, and then applies these methods to one setting (New York City). NYC-based results identified substantial cross-neighbourhood variation in SEP site access and in exposure to drug-related arrest rates (even within the subset of neighbourhoods nominally experiencing the same drug-related police strategy). These geographic measures – grounded as they are in conceptualizations of SEPs and drug-related law enforcement strategies – can help develop new arenas of inquiry regarding the impact of these two dimensions of the risk environment on injectors’ health, including exploring whether and how neighbourhood-level access to SEP sites and exposure to drug-related arrests shape a range of outcomes among local injectors. PMID:18963907

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...

Agent Orange exposure and risk of death in Korean Vietnam veterans: Korean Veterans Health Study.

Science.gov (United States)

Yi, Sang-Wook; Ryu, So-Yeon; Ohrr, Heechoul; Hong, Jae-Seok

2014-12-01

Agent Orange (AO) was a mixture of phenoxy herbicides, containing several dioxin impurities including 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD). Various military herbicides, including AO, were sprayed by the US military and allied forces for military purposes during the Vietnam War. This study was performed to identify the associations between the AO exposure and mortality in Korean Vietnam veterans. From 1 January 1992 to 31 December 2005, 180 639 Korean Vietnam veterans were followed up for vital status and cause of death. The AO exposure index was based on the proximity of the veteran's unit to AO-sprayed areas, using a geographical information system-based model. The adjusted hazard ratios and 95% confidence intervals were calculated by Cox's proportional hazard model. The mortality from all causes of death was elevated with AO exposure. The deaths due to all sites of cancers combined and some specific cancers, including cancers of the stomach, small intestine, liver, larynx, lung, bladder and thyroid gland, as well as chronic myeloid leukaemia, were positively associated with AO exposure. The deaths from angina pectoris, chronic obstructive pulmonary disease and liver disease including liver cirrhosis were also increased with an increasing AO exposure. Overall, this study suggests that AO/TCDD exposure may account for mortality from various diseases even several decades after exposure. Further research is needed to better understand the long-term effects of AO/TCDD exposure on human health. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

Model for screening-level assessment of near-field human exposure to neutral organic chemicals released indoors.

Science.gov (United States)

Zhang, Xianming; Arnot, Jon A; Wania, Frank

2014-10-21

Screening organic chemicals for hazard and risk to human health requires near-field human exposure models that can be readily parametrized with available data. The integration of a model of human exposure, uptake, and bioaccumulation into an indoor mass balance model provides a quantitative framework linking emissions in indoor environments with human intake rates (iRs), intake fractions (iFs) and steady-state concentrations in humans (C) through consideration of dermal permeation, inhalation, and nondietary ingestion exposure pathways. Parameterized based on representative indoor and adult human characteristics, the model is applied here to 40 chemicals of relevance in the context of human exposure assessment. Intake fractions and human concentrations (C(U)) calculated with the model based on a unit emission rate to air for these 40 chemicals span 2 and 5 orders of magnitude, respectively. Differences in priority ranking based on either iF or C(U) can be attributed to the absorption, biotransformation and elimination processes within the human body. The model is further applied to a large data set of hypothetical chemicals representative of many in-use chemicals to show how the dominant exposure pathways, iF and C(U) change as a function of chemical properties and to illustrate the capacity of the model for high-throughput screening. These simulations provide hypotheses for the combination of chemical properties that may result in high exposure and internal dose. The model is further exploited to highlight the role human contaminant uptake plays in the overall fate of certain chemicals indoors and consequently human exposure.

A suggested guideline for exposure control from natural radioactivity in future buildings

International Nuclear Information System (INIS)

Nambi, K.S.V.; Shukla, V.K.

1991-01-01

Naturally occurring radionuclides in building materials are one of the sources of radiation exposure to the population. Their concentrations vary by about 2 to 3 orders of magnitude at different geographical locations. This paper proposes three control methodologies for keeping the population exposure as low as reasonably achievable. Tentative recommendations are also included. (author). 11 refs., 3 tabs., 2 appendixes

No association between exposure to perfluorinated compounds and congenital cryptorchidism

DEFF Research Database (Denmark)

Lind, Dorte Vesterholm; Christensen, Jeppe Hagstrup; Virtanen, Helena E

2014-01-01

Geographical differences in occurrence of diseases in male reproductive organs including malformation in reproductive tract have been reported between Denmark and Finland. The reason for these differences is unknown, but differences in exposure to chemicals with endocrine disrupting abilities have...

How Geographic Maps Increase Recall of Instructional Text.

Science.gov (United States)

Kulhavy, Raymond W.; And Others

1993-01-01

Reviews research on how geographic maps influence the recall of associated text and describes a theoretical model of map-text learning based on dual-coding theory and working memory operations. Instructional implications are explained, and recommendations for instructional applications are given. (Contains 84 references.) (LRW)

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.

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.

Dispersal Kernel Determines Symmetry of Spread and Geographical Range for an Insect

International Nuclear Information System (INIS)

Holland, J.D.

2009-01-01

The distance from a source patch that dispersing insects reach depends on the number of dispersers, or random draws from a probability density function called a dispersal kernel, and the shape of that kernel. This can cause asymmetrical dispersal between habitat patches that produce different numbers of dispersers. Spatial distributions based on these dynamics can explain several ecological patterns including mega populations and geographic range boundaries. I hypothesized that a locally extirpated long horned beetle, the sugar maple borer, has a new geographical range shaped primarily by probabilistic dispersal distances. I used data on occurrence from Ontario, Canada to construct a model of geographical range in Indiana, USA based on maximum dispersal distance scaled by habitat area. This model predicted the new range boundary within 500 m very accurately. This beetle may be an ideal organism for exploring spatial dynamics driven by dispersal.

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...

Oil well fires of Operation Desert Storm--defining troop exposures and determining health risks.

Science.gov (United States)

Heller, Jack M

2011-07-01

During Operation Desert Storm, in February 1991, Iraqi troops began burning Kuwaiti oil wells. Almost immediately there was concern about possible adverse health effects in U.S. personnel exposed to crude oil combustion products. Combustions products were predicted from the known composition of Kuwaiti crude oil. Monitoring sites were established in Saudi Arabia and Kuwait; about 5,000 environmental samples were studied. Data collected were used to develop health risk assessments for the geographic areas sampled. This initial approach to assessing risk had to be greatly expanded when Congress passed Public Law 102-190, requiring development of means to calculate environmental exposures for individual U.S. service members. To estimate daily exposure levels for the entire area over 10 months for all U.S. troops, air dispersion modeling was used in conjunction with satellite imagery and geographic information system technology. This methodology made it possible to separate the risk caused by oil fire smoke from the total risk from all sources for each service member. The U.S. military responses to health concerns related to the oil well fires and to Public Law 102-190 were reviewed. Consideration was given to changes in technology, practices, and policies over the last two decades that might impact a similar contemporary response.

Geographic profiling and animal foraging.

Science.gov (United States)

Le Comber, Steven C; Nicholls, Barry; Rossmo, D Kim; Racey, Paul A

2006-05-21

Geographic profiling was originally developed as a statistical tool for use in criminal cases, particularly those involving serial killers and rapists. It is designed to help police forces prioritize lists of suspects by using the location of crime scenes to identify the areas in which the criminal is most likely to live. Two important concepts are the buffer zone (criminals are less likely to commit crimes in the immediate vicinity of their home) and distance decay (criminals commit fewer crimes as the distance from their home increases). In this study, we show how the techniques of geographic profiling may be applied to animal data, using as an example foraging patterns in two sympatric colonies of pipistrelle bats, Pipistrellus pipistrellus and P. pygmaeus, in the northeast of Scotland. We show that if model variables are fitted to known roost locations, these variables may be used as numerical descriptors of foraging patterns. We go on to show that these variables can be used to differentiate patterns of foraging in these two species.

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

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.

Respiratory Health - Exposure Measurements and Modeling in the Fragrance and Flavour Industry.

Science.gov (United States)

Angelini, Eric; Camerini, Gerard; Diop, Malick; Roche, Patrice; Rodi, Thomas; Schippa, Christine; Thomas, Thierry

2016-01-01

Although the flavor and fragrance industry is about 150 years old, the use of synthetic materials started more than 100 years ago, and the awareness of the respiratory hazard presented by some flavoring substances emerged only recently. In 2001, the US National Institute of Occupational Safety and Health (NIOSH) identified for the first time inhalation exposure to flavoring substances in the workplace as a possible occupational hazard. As a consequence, manufacturers must comply with a variety of workplace safety requirements, and management has to ensure the improvement of health and safety of the employees exposed to hazardous volatile organic compounds. In this sensitive context, MANE opened its facilities to an intensive measuring campaign with the objective to better estimate the real level of hazardous respiratory exposure of workers. In this study, exposure to 27 hazardous volatile substances were measured during several types of handling operations (weighing-mixing, packaging, reconditioning-transferring), 430 measurement results were generated, and were exploited to propose an improved model derived from the well-known ECETOC-TRA model. The quantification of volatile substances in the working atmosphere involved three main steps: adsorption of the chemicals on a solid support, thermal desorption, followed by analysis by gas chromatography-mass spectrometry. Our approach was to examine experimental measures done in various manufacturing workplaces and to define correction factors to reflect more accurately working conditions and habits. Four correction factors were adjusted in the ECETOC-TRA to integrate important exposure variation factors: exposure duration, percentage of the substance in the composition, presence of collective protective equipment and wearing of personal protective equipment. Verification of the validity of the model is based on the comparison of the values obtained after adaptation of the ECETOC-TRA model, according to various exposure

Respiratory Health - Exposure Measurements and Modeling in the Fragrance and Flavour Industry.

Directory of Open Access Journals (Sweden)

Eric Angelini

Full Text Available Although the flavor and fragrance industry is about 150 years old, the use of synthetic materials started more than 100 years ago, and the awareness of the respiratory hazard presented by some flavoring substances emerged only recently. In 2001, the US National Institute of Occupational Safety and Health (NIOSH identified for the first time inhalation exposure to flavoring substances in the workplace as a possible occupational hazard. As a consequence, manufacturers must comply with a variety of workplace safety requirements, and management has to ensure the improvement of health and safety of the employees exposed to hazardous volatile organic compounds. In this sensitive context, MANE opened its facilities to an intensive measuring campaign with the objective to better estimate the real level of hazardous respiratory exposure of workers. In this study, exposure to 27 hazardous volatile substances were measured during several types of handling operations (weighing-mixing, packaging, reconditioning-transferring, 430 measurement results were generated, and were exploited to propose an improved model derived from the well-known ECETOC-TRA model. The quantification of volatile substances in the working atmosphere involved three main steps: adsorption of the chemicals on a solid support, thermal desorption, followed by analysis by gas chromatography-mass spectrometry. Our approach was to examine experimental measures done in various manufacturing workplaces and to define correction factors to reflect more accurately working conditions and habits. Four correction factors were adjusted in the ECETOC-TRA to integrate important exposure variation factors: exposure duration, percentage of the substance in the composition, presence of collective protective equipment and wearing of personal protective equipment. Verification of the validity of the model is based on the comparison of the values obtained after adaptation of the ECETOC-TRA model, according to

An assessment of air pollutant exposure methods in Mexico City, Mexico.

Science.gov (United States)

Rivera-González, Luis O; Zhang, Zhenzhen; Sánchez, Brisa N; Zhang, Kai; Brown, Daniel G; Rojas-Bracho, Leonora; Osornio-Vargas, Alvaro; Vadillo-Ortega, Felipe; O'Neill, Marie S

2015-05-01

Geostatistical interpolation methods to estimate individual exposure to outdoor air pollutants can be used in pregnancy cohorts where personal exposure data are not collected. Our objectives were to a) develop four assessment methods (citywide average (CWA); nearest monitor (NM); inverse distance weighting (IDW); and ordinary Kriging (OK)), and b) compare daily metrics and cross-validations of interpolation models. We obtained 2008 hourly data from Mexico City's outdoor air monitoring network for PM10, PM2.5, O3, CO, NO2, and SO2 and constructed daily exposure metrics for 1,000 simulated individual locations across five populated geographic zones. Descriptive statistics from all methods were calculated for dry and wet seasons, and by zone. We also evaluated IDW and OK methods' ability to predict measured concentrations at monitors using cross validation and a coefficient of variation (COV). All methods were performed using SAS 9.3, except ordinary Kriging which was modeled using R's gstat package. Overall, mean concentrations and standard deviations were similar among the different methods for each pollutant. Correlations between methods were generally high (r=0.77 to 0.99). However, ranges of estimated concentrations determined by NM, IDW, and OK were wider than the ranges for CWA. Root mean square errors for OK were consistently equal to or lower than for the IDW method. OK standard errors varied considerably between pollutants and the computed COVs ranged from 0.46 (least error) for SO2 and PM10 to 3.91 (most error) for PM2.5. OK predicted concentrations measured at the monitors better than IDW and NM. Given the similarity in results for the exposure methods, OK is preferred because this method alone provides predicted standard errors which can be incorporated in statistical models. The daily estimated exposures calculated using these different exposure methods provide flexibility to evaluate multiple windows of exposure during pregnancy, not just trimester or

A geographical analysis of the Swedish wood fuel market

International Nuclear Information System (INIS)

Roos, Anders; Bohlin, Folke; Hektor, Bo; Hillring, Bengt; Parikka, Matti

2000-01-01

The geographical variation in Swedish wood fuel market characteristics for the district heating sector has been studied using Geographical Information Systems (GIS) and cross-sectional Tobit analysis. The results indicate that local availability and competition for wood fuels influence the wood fuel consumption at inland heating plants. The factors affecting the decision to use wood fuel at heating plants close to seaports, however, were not captured by the model, suggesting that coastal location reduces dependency on the local wood fuel market. The effects of changes in local wood fuel availability on wood fuel use by an inland heating plant are presented and discussed

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.

Review of the chronic exposure pathways models in MACCS [MELCOR Accident Consequence Code System] and several other well-known probabilistic risk assessment models

International Nuclear Information System (INIS)

Tveten, U.

1990-06-01

The purpose of this report is to document the results of the work performed by the author in connection with the following task, performed for US Nuclear Regulatory Commission, (USNRC) Office of Nuclear Regulatory Research, Division of Systems Research: MACCS Chronic Exposure Pathway Models: Review the chronic exposure pathway models implemented in the MELCOR Accident Consequence Code System (MACCS) and compare those models to the chronic exposure pathway models implemented in similar codes developed in countries that are members of the OECD. The chronic exposures concerned are via: the terrestrial food pathways, the water pathways, the long-term groundshine pathway, and the inhalation of resuspended radionuclides pathway. The USNRC has indicated during discussions of the task that the major effort should be spent on the terrestrial food pathways. There is one chapter for each of the categories of chronic exposure pathways listed above

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

Enzymatic digestive activity and absorption efficiency in Tagelus dombeii upon Alexandrium catenella exposure

Science.gov (United States)

Fernández-Reiriz, M. J.; Navarro, J. M.; Cisternas, B. A.; Babarro, J. M. F.; Labarta, U.

2013-12-01

We analyzed absorption efficiency (AE) and digestive enzyme activity (amylase, cellulase complex, and laminarinase) of the infaunal bivalve Tagelus dombeii originating from two geographic sites, Corral-Valdivia and Melinka-Aysén, which have different long-term paralytic shellfish poisoning (PSP) exposure rates. We report the effects of past feeding history (origin) on T. dombeii exposed to a mixed diet containing the toxic dinoflagellate Alexandrium catenella and another dinoflagellate-free control diet over a 12-day period in the laboratory. Absorption efficiency values of T. dombeii individuals that experienced PSP exposure in their habitat (Melinka-Aysén) remained unchanged during exposure to toxic food in the laboratory. In contrast, T. dombeii from a non-PSP exposure field site (Corral-Valdivia) showed a significant reduction in AE with toxic exposure time. This study established that the amylase and cellulase complexes were the most important enzymes in the digestive glands of Tagelus from both sites. The temporal evolution of enzymatic activity under toxic diet was fitted to exponential (amylase and cellulase) and to a logarithmic (laminarinase) models. In all fits, we found significant effect of origin in the model parameters. At the beginning of the experiment, higher enzymatic activity was observed for clams from Corral-Valdivia. The amylase activity decreased with time exposure for individuals from Corral and increased for individuals from Melinka. Cellulase activity did not vary over time for clams from Corral, but increased for individuals from Melinka and laminarinase activity decreased over time for individuals from Corral and remained unchanged over time for Melinka. A feeding history of exposure to the dinoflagellate A. catenella was reflected in the digestive responses of both T. dombeii populations.

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...

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

Comparison of the near field/far field model and the advanced reach tool (ART) model V1.5: exposure estimates to benzene during parts washing with mineral spirits.

Science.gov (United States)

LeBlanc, Mallory; Allen, Joseph G; Herrick, Robert F; Stewart, James H

2018-03-01

The Advanced Reach Tool V1.5 (ART) is a mathematical model for occupational exposures conceptually based on, but implemented differently than, the "classic" Near Field/Far Field (NF/FF) exposure model. The NF/FF model conceptualizes two distinct exposure "zones"; the near field, within approximately 1m of the breathing zone, and the far field, consisting of the rest of the room in which the exposure occurs. ART has been reported to provide "realistic and reasonable worst case" estimates of the exposure distribution. In this study, benzene exposure during the use of a metal parts washer was modeled using ART V1.5, and compared to actual measured workers samples and to NF/FF model results from three previous studies. Next, the exposure concentrations expected to be exceeded 25%, 10% and 5% of the time for the exposure scenario were calculated using ART. Lastly, ART exposure estimates were compared with and without Bayesian adjustment. The modeled parts washing benzene exposure scenario included distinct tasks, e.g. spraying, brushing, rinsing and soaking/drying. Because ART can directly incorporate specific types of tasks that are part of the exposure scenario, the present analysis identified each task's determinants of exposure and performance time, thus extending the work of the previous three studies where the process of parts washing was modeled as one event. The ART 50th percentile exposure estimate for benzene (0.425ppm) more closely approximated the reported measured mean value of 0.50ppm than the NF/FF model estimates of 0.33ppm, 0.070ppm or 0.2ppm obtained from other modeling studies of this exposure scenario. The ART model with the Bayesian analysis provided the closest estimate to the measured value (0.50ppm). ART (with Bayesian adjustment) was then used to assess the 75th, the 90th and 95th percentile exposures, predicting that on randomly selected days during this parts washing exposure scenario, 25% of the benzene exposures would be above 0.70ppm; 10

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

Prevalence of Residential Dampness and Mold Exposure in a University Student Population

Directory of Open Access Journals (Sweden)

Mathieu Lanthier-Veilleux

2016-02-01

Full Text Available The impact of residential dampness or mold on respiratory health is well established but few studies have focused on university students. This study aims to: (a describe the prevalence of exposure to residential dampness or mold in university students according to socio-geographic factors and (b identify associated housing characteristics. A web survey was conducted in 2014 among the 26,676 students registered at the Université de Sherbrooke (QC, Canada. Residential dampness and mold being closely intertwined, they were considered as a single exposure and assessed using a validated questionnaire. Exposure was compared according to socio-geographic and housing characteristics using chi-square tests and logistic regressions. Among the 2097 participants included in the study (response rate: 8.1%, over 80% were tenants. Residential exposure to dampness or mold was frequent (36.0%, 95% CI: 33.9–38.1. Marked differences for this exposure were noted according to home ownership (39.7% vs. 25.5% among tenants and owners respectively; OR = 1.92%, 95% CI: 1.54–2.38. Campus affiliation, household composition and the number of residents per building were associated with exposure to dampness or mold (p < 0.01, while sex and age were not. Exposure was also associated with older buildings, and buildings in need of renovations and lacking proper ventilation (p < 0.001. This study highlights the potential risk of university students suffering from mold-related health effects given their frequent exposure to this agent. Further research is needed to fully evaluate the mold-related health impact in this at risk group.

Modeling approaches for characterizing and evaluating environmental exposure to engineered nanomaterials in support of risk-based decision making.

Science.gov (United States)

Hendren, Christine Ogilvie; Lowry, Michael; Grieger, Khara D; Money, Eric S; Johnston, John M; Wiesner, Mark R; Beaulieu, Stephen M

2013-02-05

As the use of engineered nanomaterials becomes more prevalent, the likelihood of unintended exposure to these materials also increases. Given the current scarcity of experimental data regarding fate, transport, and bioavailability, determining potential environmental exposure to these materials requires an in depth analysis of modeling techniques that can be used in both the near- and long-term. Here, we provide a critical review of traditional and emerging exposure modeling approaches to highlight the challenges that scientists and decision-makers face when developing environmental exposure and risk assessments for nanomaterials. We find that accounting for nanospecific properties, overcoming data gaps, realizing model limitations, and handling uncertainty are key to developing informative and reliable environmental exposure and risk assessments for engineered nanomaterials. We find methods suited to recognizing and addressing significant uncertainty to be most appropriate for near-term environmental exposure modeling, given the current state of information and the current insufficiency of established deterministic models to address environmental exposure to engineered nanomaterials.

Patterns of geographic expansion of Aedes aegypti in the Peruvian Amazon.

Directory of Open Access Journals (Sweden)

Sarah Anne Guagliardo

2014-08-01

Full Text Available In the Peruvian Amazon, the dengue vector Aedes aegypti is abundant in large urban centers such as Iquitos. In recent years, it has also been found in a number of neighboring rural communities with similar climatic and socioeconomic conditions. To better understand Ae. aegypti spread, we compared characteristics of communities, houses, and containers in infested and uninfested communities.We conducted pupal-demographic surveys and deployed ovitraps in 34 communities surrounding the city of Iquitos. Communities surveyed were located along two transects: the Amazon River and a 95 km highway. We calculated entomological indices, mapped Ae. aegypti presence, and developed univariable and multivariable logistic regression models to predict Ae. aegypti presence at the community, household, or container level.Large communities closer to Iquitos were more likely to be infested with Ae. aegypti. Within infested communities, houses with Ae. aegypti had more passively-filled containers and were more often infested with other mosquito genera than houses without Ae. aegypti. For containers, large water tanks/drums and containers with solar exposure were more likely to be infested with Ae. aegypti. Maps of Ae. aegypti presence revealed a linear pattern of infestation along the highway, and a scattered pattern along the Amazon River. We also identified the geographical limit of Ae. aegypti expansion along the highway at 19.3 km south of Iquitos.In the Peruvian Amazon, Ae. aegypti geographic spread is driven by human transportation networks along rivers and highways. Our results suggest that urban development and oviposition site availability drive Ae. aegypti colonization along roads. Along rivers, boat traffic is likely to drive long-distance dispersal via unintentional transport of mosquitoes on boats.

5 CFR 536.303 - Geographic conversion.

Science.gov (United States)

2010-01-01

... after geographic conversion is the employee's existing payable rate of basic pay in effect immediately before the action. (b) Geographic conversion when a retained rate employee's official worksite is changed... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Geographic conversion. 536.303 Section...

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)

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.

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

Geographic Medical History: Advances in Geospatial Technology Present New Potentials in Medical Practice

Science.gov (United States)

Faruque, F. S.; Finley, R. W.

2016-06-01

Genes, behaviour, and the environment are known to be the major risk factors for common diseases. When the patient visits a physician, typical questions include family history (genes) and lifestyle of the patient (behaviour), but questions concerning environmental risk factors often remain unasked. It is ironic that 25 centuries ago Hippocrates, known as the father of medicine, noted the importance of environmental exposure in medical investigation as documented in his classic work, "Airs, Waters, Places", yet the practice of routinely incorporating environmental risk factors is still not in place. Modern epigenetic studies have found that unhealthy lifestyle and environmental factors can cause changes to our genes that can increase disease risk factors. Therefore, attempting to solve the puzzle of diseases using heredity and lifestyle alone will be incomplete without accounting for the environmental exposures. The primary reason why environmental exposure has not yet been a routine part of the patient's medical history is mostly due to our inability to provide clinicians useful measures of environmental exposures suitable for their clinical practices. This presentation will discuss advances in geospatial technology that show the potential to catalyse a paradigm shift in medical practice and health research by allowing environmental risk factors to be documented as the patient's "Geographic Medical History". In order to accomplish this we need information on: a) relevant spatiotemporal environmental variables, and b) location of the individual in that person's dynamic environment. Common environmental agents that are known to interact with genetic make-up include air pollutants, mold spores, pesticides, etc. Until recently, the other component, location of an individual was limited to a static representation such as residential or workplace location. Now, with the development of mobile technology, changes in an individual's location can be tracked in real time if

GEOGRAPHIC MEDICAL HISTORY: ADVANCES IN GEOSPATIAL TECHNOLOGY PRESENT NEW POTENTIALS IN MEDICAL PRACTICE

Directory of Open Access Journals (Sweden)

F. S. Faruque

2016-06-01

Full Text Available Genes, behaviour, and the environment are known to be the major risk factors for common diseases. When the patient visits a physician, typical questions include family history (genes and lifestyle of the patient (behaviour, but questions concerning environmental risk factors often remain unasked. It is ironic that 25 centuries ago Hippocrates, known as the father of medicine, noted the importance of environmental exposure in medical investigation as documented in his classic work, “Airs, Waters, Places”, yet the practice of routinely incorporating environmental risk factors is still not in place. Modern epigenetic studies have found that unhealthy lifestyle and environmental factors can cause changes to our genes that can increase disease risk factors. Therefore, attempting to solve the puzzle of diseases using heredity and lifestyle alone will be incomplete without accounting for the environmental exposures. The primary reason why environmental exposure has not yet been a routine part of the patient’s medical history is mostly due to our inability to provide clinicians useful measures of environmental exposures suitable for their clinical practices. This presentation will discuss advances in geospatial technology that show the potential to catalyse a paradigm shift in medical practice and health research by allowing environmental risk factors to be documented as the patient’s “Geographic Medical History”. In order to accomplish this we need information on: a relevant spatiotemporal environmental variables, and b location of the individual in that person’s dynamic environment. Common environmental agents that are known to interact with genetic make-up include air pollutants, mold spores, pesticides, etc. Until recently, the other component, location of an individual was limited to a static representation such as residential or workplace location. Now, with the development of mobile technology, changes in an individual’s location

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...

The association of LUR modeled PM2.5 elemental composition with personal exposure

International Nuclear Information System (INIS)

Montagne, Denise; Hoek, Gerard; Nieuwenhuijsen, Mark; Lanki, Timo; Pennanen, Arto; Portella, Meritxell; Meliefste, Kees; Wang, Meng; Eeftens, Marloes; Yli-Tuomi, Tarja; Cirach, Marta; Brunekreef, Bert

2014-01-01

Background and aims: Land use regression (LUR) models predict spatial variation of ambient concentrations, but little is known about the validity in predicting personal exposures. In this study, the association of LUR modeled concentrations of PM 2.5 components with measured personal concentrations was determined. The elements of interest were copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V) and zinc (Zn). Methods: In Helsinki (Finland), Utrecht (the Netherlands) and Barcelona (Spain) five participants from urban background, five from suburban background and five from busy street sites were selected in each city (15 participants per city). Outdoor, indoor and personal 96-hour PM 2.5 samples were collected by the participants over periods of two weeks in three different seasons (winter, summer and spring/autumn) and the overall average was calculated. Elemental composition was measured by ED-XRF spectrometry. The LUR models for the average ambient concentrations of each element were developed by the ESCAPE project. Results: LUR models predicted the within-city variation of average outdoor Cu and Fe concentrations moderately well (range in R 2 27–67% for Cu and 24–54% for Fe). The outdoor concentrations of the other elements were not well predicted. The LUR modeled concentration only significantly correlated with measured personal Fe exposure in Utrecht and Ni and V in Helsinki. The LUR model predictions did not correlate with measured personal Cu exposure. After excluding observations with an indoor/outdoor ratio of > 1.5, modeled Cu outdoor concentrations correlated with indoor concentrations in Helsinki and Utrecht and personal concentrations in Utrecht. The LUR model predictions were associated with measured outdoor, indoor and personal concentrations for all elements when the data for the three cities was pooled. Conclusions: Within-city modeled variation of elemental composition of PM 2.5 did not predict measured