Uncertainties in risk assessment at USDOE facilities

International Nuclear Information System (INIS)

Hamilton, L.D.; Holtzman, S.; Meinhold, A.F.; Morris, S.C.; Rowe, M.D.

1994-01-01

The United States Department of Energy (USDOE) has embarked on an ambitious program to remediate environmental contamination at its facilities. Decisions concerning cleanup goals, choices among cleanup technologies, and funding prioritization should be largely risk-based. Risk assessments will be used more extensively by the USDOE in the future. USDOE needs to develop and refine risk assessment methods and fund research to reduce major sources of uncertainty in risk assessments at USDOE facilities. The terms open-quote risk assessment close-quote and open-quote risk management close-quote are frequently confused. The National Research Council (1983) and the United States Environmental Protection Agency (USEPA, 1991a) described risk assessment as a scientific process that contributes to risk management. Risk assessment is the process of collecting, analyzing and integrating data and information to identify hazards, assess exposures and dose responses, and characterize risks. Risk characterization must include a clear presentation of open-quotes... the most significant data and uncertainties...close quotes in an assessment. Significant data and uncertainties are open-quotes...those that define and explain the main risk conclusionsclose quotes. Risk management integrates risk assessment information with other considerations, such as risk perceptions, socioeconomic and political factors, and statutes, to make and justify decisions. Risk assessments, as scientific processes, should be made independently of the other aspects of risk management (USEPA, 1991a), but current methods for assessing health risks are based on conservative regulatory principles, causing unnecessary public concern and misallocation of funds for remediation

The Uncertainties of Risk Management

DEFF Research Database (Denmark)

Vinnari, Eija; Skærbæk, Peter

2014-01-01

for expanding risk management. More generally, such uncertainties relate to the professional identities and responsibilities of operational managers as defined by the framing devices. Originality/value – The paper offers three contributions to the extant literature: first, it shows how risk management itself......Purpose – The purpose of this paper is to analyse the implementation of risk management as a tool for internal audit activities, focusing on unexpected effects or uncertainties generated during its application. Design/methodology/approach – Public and confidential documents as well as semi......-structured interviews are analysed through the lens of actor-network theory to identify the effects of risk management devices in a Finnish municipality. Findings – The authors found that risk management, rather than reducing uncertainty, itself created unexpected uncertainties that would otherwise not have emerged...

Where do uncertainties reside within environmental risk assessments? Expert opinion on uncertainty distributions for pesticide risks to surface water organisms.

Science.gov (United States)

Skinner, Daniel J C; Rocks, Sophie A; Pollard, Simon J T

2016-12-01

A reliable characterisation of uncertainties can aid uncertainty identification during environmental risk assessments (ERAs). However, typologies can be implemented inconsistently, causing uncertainties to go unidentified. We present an approach based on nine structured elicitations, in which subject-matter experts, for pesticide risks to surface water organisms, validate and assess three dimensions of uncertainty: its level (the severity of uncertainty, ranging from determinism to ignorance); nature (whether the uncertainty is epistemic or aleatory); and location (the data source or area in which the uncertainty arises). Risk characterisation contains the highest median levels of uncertainty, associated with estimating, aggregating and evaluating the magnitude of risks. Regarding the locations in which uncertainty is manifest, data uncertainty is dominant in problem formulation, exposure assessment and effects assessment. The comprehensive description of uncertainty described will enable risk analysts to prioritise the required phases, groups of tasks, or individual tasks within a risk analysis according to the highest levels of uncertainty, the potential for uncertainty to be reduced or quantified, or the types of location-based uncertainty, thus aiding uncertainty prioritisation during environmental risk assessments. In turn, it is expected to inform investment in uncertainty reduction or targeted risk management action. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Risk uncertainty analysis methods for NUREG-1150

International Nuclear Information System (INIS)

Benjamin, A.S.; Boyd, G.J.

1987-01-01

Evaluation and display of risk uncertainties for NUREG-1150 constitute a principal focus of the Severe Accident Risk Rebaselining/Risk Reduction Program (SARRP). Some of the principal objectives of the uncertainty evaluation are: (1) to provide a quantitative estimate that reflects, for those areas considered, a credible and realistic range of uncertainty in risk; (2) to rank the various sources of uncertainty with respect to their importance for various measures of risk; and (3) to characterize the state of understanding of each aspect of the risk assessment for which major uncertainties exist. This paper describes the methods developed to fulfill these objectives

Guidance for treatment of variability and uncertainty in ecological risk assessments of contaminated sites

International Nuclear Information System (INIS)

1998-06-01

Uncertainty is a seemingly simple concept that has caused great confusion and conflict in the field of risk assessment. This report offers guidance for the analysis and presentation of variability and uncertainty in ecological risk assessments, an important issue in the remedial investigation and feasibility study processes. This report discusses concepts of probability in terms of variance and uncertainty, describes how these concepts differ in ecological risk assessment from human health risk assessment, and describes probabilistic aspects of specific ecological risk assessment techniques. The report ends with 17 points to consider in performing an uncertainty analysis for an ecological risk assessment of a contaminated site

Uncertainty: lotteries and risk

OpenAIRE

Ávalos, Eloy

2011-01-01

In this paper we develop the theory of uncertainty in a context where the risks assumed by the individual are measurable and manageable. We primarily use the definition of lottery to formulate the axioms of the individual's preferences, and its representation through the utility function von Neumann - Morgenstern. We study the expected utility theorem and its properties, the paradoxes of choice under uncertainty and finally the measures of risk aversion with monetary lotteries.

Uncertainty quantification in flood risk assessment

Science.gov (United States)

Blöschl, Günter; Hall, Julia; Kiss, Andrea; Parajka, Juraj; Perdigão, Rui A. P.; Rogger, Magdalena; Salinas, José Luis; Viglione, Alberto

2017-04-01

Uncertainty is inherent to flood risk assessments because of the complexity of the human-water system, which is characterised by nonlinearities and interdependencies, because of limited knowledge about system properties and because of cognitive biases in human perception and decision-making. On top of the uncertainty associated with the assessment of the existing risk to extreme events, additional uncertainty arises because of temporal changes in the system due to climate change, modifications of the environment, population growth and the associated increase in assets. Novel risk assessment concepts are needed that take into account all these sources of uncertainty. They should be based on the understanding of how flood extremes are generated and how they change over time. They should also account for the dynamics of risk perception of decision makers and population in the floodplains. In this talk we discuss these novel risk assessment concepts through examples from Flood Frequency Hydrology, Socio-Hydrology and Predictions Under Change. We believe that uncertainty quantification in flood risk assessment should lead to a robust approach of integrated flood risk management aiming at enhancing resilience rather than searching for optimal defense strategies.

GENERAL RISKS AND UNCERTAINTIES OF REPORTING AND MANAGEMENT REPORTING RISKS

Directory of Open Access Journals (Sweden)

CAMELIA I. LUNGU

2011-04-01

Full Text Available Purpose: Highlighting risks and uncertainties reporting based on a literature review research. Objectives: The delimitation of risk management models and uncertainties in fundamental research. Research method: Fundamental research study directed to identify the relevant risks’ models presented in entities’ financial statements. Uncertainty is one of the fundamental coordinates of our world. As showed J.K. Galbraith (1978, the world now lives under the age of uncertainty. Moreover, we can say that contemporary society development could be achieved by taking decisions under uncertainty, though, risks. Growing concern for the study of uncertainty, its effects and precautions led to the rather recent emergence of a new science, science of hazards (les cindyniques - l.fr. (Kenvern, 1991. Current analysis of risk are dominated by Beck’s (1992 notion that a risk society now exists whereby we have become more concerned about our impact upon nature than the impact of nature upon us. Clearly, risk permeates most aspects of corporate but also of regular life decision-making and few can predict with any precision the future. The risk is almost always a major variable in real-world corporate decision-making, and managers that ignore it are in a real peril. In these circumstances, a possible answer is assuming financial discipline with an appropriate system of incentives.

The Stock Market: Risk vs. Uncertainty.

Science.gov (United States)

Griffitts, Dawn

2002-01-01

This economics education publication focuses on the U.S. stock market and the risk and uncertainty that an individual faces when investing in the market. The material explains that risk and uncertainty relate to the same underlying concept randomness. It defines and discusses both concepts and notes that although risk is quantifiable, uncertainty…

Sustainability Risk Evaluation for Large-Scale Hydropower Projects with Hybrid Uncertainty

Directory of Open Access Journals (Sweden)

Weiyao Tang

2018-01-01

Full Text Available As large-scale hydropower projects are influenced by many factors, risk evaluations are complex. This paper considers a hydropower project as a complex system from the perspective of sustainability risk, and divides it into three subsystems: the natural environment subsystem, the eco-environment subsystem and the socioeconomic subsystem. Risk-related factors and quantitative dimensions of each subsystem are comprehensively analyzed considering uncertainty of some quantitative dimensions solved by hybrid uncertainty methods, including fuzzy (e.g., the national health degree, the national happiness degree, the protection of cultural heritage, random (e.g., underground water levels, river width, and fuzzy random uncertainty (e.g., runoff volumes, precipitation. By calculating the sustainability risk-related degree in each of the risk-related factors, a sustainable risk-evaluation model is built. Based on the calculation results, the critical sustainability risk-related factors are identified and targeted to reduce the losses caused by sustainability risk factors of the hydropower project. A case study at the under-construction Baihetan hydropower station is presented to demonstrate the viability of the risk-evaluation model and to provide a reference for the sustainable risk evaluation of other large-scale hydropower projects.

Risk newsboy: approach for addressing uncertainty in developing action levels and cleanup limits

International Nuclear Information System (INIS)

Cooke, Roger; MacDonell, Margaret

2007-01-01

Site cleanup decisions involve developing action levels and residual limits for key contaminants, to assure health protection during the cleanup period and into the long term. Uncertainty is inherent in the toxicity information used to define these levels, based on incomplete scientific knowledge regarding dose-response relationships across various hazards and exposures at environmentally relevant levels. This problem can be addressed by applying principles used to manage uncertainty in operations research, as illustrated by the newsboy dilemma. Each day a newsboy must balance the risk of buying more papers than he can sell against the risk of not buying enough. Setting action levels and cleanup limits involves a similar concept of balancing and distributing risks and benefits in the face of uncertainty. The newsboy approach can be applied to develop health-based target concentrations for both radiological and chemical contaminants, with stakeholder input being crucial to assessing 'regret' levels. Associated tools include structured expert judgment elicitation to quantify uncertainty in the dose-response relationship, and mathematical techniques such as probabilistic inversion and iterative proportional fitting. (authors)

Uncertainties in risk assessment and decision making

International Nuclear Information System (INIS)

Starzec, Peter; Purucker, Tom; Stewart, Robert

2008-02-01

The general concept for risk assessment in accordance with the Swedish model for contaminated soil implies that the toxicological reference value for a given receptor is first back-calculated to a corresponding concentration of a compound in soil and (if applicable) then modified with respect to e.g. background levels, acute toxicity, and factor of safety. This result in a guideline value that is subsequently compared to the observed concentration levels. Many sources of uncertainty exist when assessing whether the risk for a receptor is significant or not. In this study, the uncertainty aspects have been addressed from three standpoints: 1. Uncertainty in the comparison between the level of contamination (source) and a given risk criterion (e.g. a guideline value) and possible implications on subsequent decisions. This type of uncertainty is considered to be most important in situations where a contaminant is expected to be spatially heterogeneous without any tendency to form isolated clusters (hotspots) that can be easily delineated, i.e. where mean values are appropriate to compare to the risk criterion. 2. Uncertainty in spatial distribution of a contaminant. Spatial uncertainty should be accounted for when hotspots are to be delineated and the volume of soil contaminated with levels above a stated decision criterion has to be assessed (quantified). 3. Uncertainty in an ecological exposure model with regard to the moving pattern of a receptor in relation to spatial distribution of contaminant in question. The study points out that the choice of methodology to characterize the relation between contaminant concentration and a pre-defined risk criterion is governed by a conceptual perception of the contaminant's spatial distribution and also depends on the structure of collected data (observations). How uncertainty in transition from contaminant concentration into risk criterion can be quantified was demonstrated by applying hypothesis tests and the concept of

Risk and Uncertainty in Production Economics | Otaha | African ...

African Journals Online (AJOL)

One of the most celebrated and feared concepts in the World today are risk which is the product of uncertainty. Risk and uncertainty are often used interchangeably by many economists as if they are the same thing, but it is not true. While risk can be measured and estimated, and even ensured, uncertainty can not.

Risk Assessment Uncertainties in Cybersecurity Investments

Directory of Open Access Journals (Sweden)

Andrew Fielder

2018-06-01

Full Text Available When undertaking cybersecurity risk assessments, it is important to be able to assign numeric values to metrics to compute the final expected loss that represents the risk that an organization is exposed to due to cyber threats. Even if risk assessment is motivated by real-world observations and data, there is always a high chance of assigning inaccurate values due to different uncertainties involved (e.g., evolving threat landscape, human errors and the natural difficulty of quantifying risk. Existing models empower organizations to compute optimal cybersecurity strategies given their financial constraints, i.e., available cybersecurity budget. Further, a general game-theoretic model with uncertain payoffs (probability-distribution-valued payoffs shows that such uncertainty can be incorporated in the game-theoretic model by allowing payoffs to be random. This paper extends previous work in the field to tackle uncertainties in risk assessment that affect cybersecurity investments. The findings from simulated examples indicate that although uncertainties in cybersecurity risk assessment lead, on average, to different cybersecurity strategies, they do not play a significant role in the final expected loss of the organization when utilising a game-theoretic model and methodology to derive these strategies. The model determines robust defending strategies even when knowledge regarding risk assessment values is not accurate. As a result, it is possible to show that the cybersecurity investments’ tool is capable of providing effective decision support.

Risks, uncertainty, vagueness

International Nuclear Information System (INIS)

Haefele, W.; Renn, O.; Erdmann, G.

1990-01-01

The notion of 'risk' is discussed in its social and technological contexts, leading to an investigation of the terms factuality, hypotheticality, uncertainty, and vagueness, and to the problems of acceptance and acceptability especially in the context of political decision finding. (DG) [de

Climate policy uncertainty and investment risk

Energy Technology Data Exchange (ETDEWEB)

NONE

2007-06-21

Our climate is changing. This is certain. Less certain, however, is the timing and magnitude of climate change, and the cost of transition to a low-carbon world. Therefore, many policies and programmes are still at a formative stage, and policy uncertainty is very high. This book identifies how climate change policy uncertainty may affect investment behaviour in the power sector. For power companies, where capital stock is intensive and long-lived, those risks rank among the biggest and can create an incentive to delay investment. Our analysis results show that the risk premiums of climate change uncertainty can add 40% of construction costs of the plant for power investors, and 10% of price surcharges for the electricity end-users. This publication tells what can be done in policy design to reduce these costs. Incorporating the results of quantitative analysis, this publication also shows the sensitivity of different power sector investment decisions to different risks. It compares the effects of climate policy uncertainty with energy market uncertainty, showing the relative importance of these sources of risk for different technologies in different market types. Drawing on extensive consultation with power companies and financial investors, it also assesses the implications for policy makers, allowing the key messages to be transferred into policy designs. This book is a useful tool for governments to improve climate policy mechanisms and create more certainty for power investors.

Consideration of uncertainties in CCDF risk curves in safety oriented decision making processes

International Nuclear Information System (INIS)

Stern, E.; Tadmor, J.

1988-01-01

In recent years, some of the results of Probabilistic Risk Assessment (i.e. the magnitudes of the various adverse health effects and other effects of potential accidents in nuclear power plants) have usually been presented in Complementary Cumulative Distribution Function curves, widely known as CCDF risk curves. CCDF curves are characteristic of probabilistic accident analyses and consequence calculations, although, in many cases, the codes producing the CCDF curves consist of a mixture of both probabilistic and deterministic calculations. One of the main difficulties in the process of PRA is the problem of uncertainties associated with the risk assessments. The uncertainties, as expressed in CCDF risk curves can be classified into two main categories: (a) uncertainties expressed by the CCDF risk curve itself due to its probabilistic nature and - (b) the uncertainty band of CCDF risk curves. The band consists of a ''family of CCDF curves'' which represents the risks (e.g. early/late fatalities) evaluated at various levels of confidence for a specific Plant-Site Combination (PSC) i.e. a certain nuclear power plant located at a certain site. The reasons why a family of curves rather than a single curve represents the risk of a certain PSC have been discussed. Generally, the uncertainty band of CCDF curves is limited by the 95% (''conservative'') and the 5% curves. In most cases the 50% (median, ''best estimate'') curve is also shown because scientists tend to believe that it represents the ''realistic'' (or real) risk of the plant

Uncertainty in ecological risk assessment: A statistician's view

International Nuclear Information System (INIS)

Smith, E.P.

1995-01-01

Uncertainty is a topic that has different meanings to researchers, modelers, managers and policy makers. The perspective of this presentation will be on the modeling view of uncertainty and its quantitative assessment. The goal is to provide some insight into how a statistician visualizes and addresses the issue of uncertainty in ecological risk assessment problems. In ecological risk assessment, uncertainty arises from many sources and is of different type depending on what is studies, where it is studied and how it is studied. Some major sources and their impact are described. A variety of quantitative approaches to modeling uncertainty are characterized and a general taxonomy given. Examples of risk assessments of lake acidification, power plant impact assessment and the setting of standards for chemicals will be used discuss approaches to quantitative assessment of uncertainty and some of the potential difficulties

Regulatory uncertainty and the associated business risk for emerging technologies

International Nuclear Information System (INIS)

Hoerr, Robert A.

2011-01-01

An oversight system specifically concerned with nanomaterials should be flexible enough to take into account the unique aspects of individual novel materials and the settings in which they might be used, while recognizing that heretofore unrecognized safety issues may require future modifications. This article considers a question not explicitly considered by the project team: what is the risk that uncertainty over how regulatory oversight will be applied to nanomaterials will delay or block the development of this emerging technology, thereby depriving human health of potential and substantial benefits? An ambiguous regulatory environment could delay the availability of valuable new technology and therapeutics for human health by reducing access to investment capital. Venture capitalists list regulatory uncertainty as a major reason not to invest at all in certain areas. Uncertainty is far more difficult to evaluate than risk, which lends itself to quantitative models and can be factored into projections of return on possible investments. Loss of time has a large impact on investment return. An examination of regulatory case histories suggests that an increase in regulatory resting requirement, where the path is well-defined, is far less costly than a delay of a year or more in achieving product approval and market launch.

Regulatory uncertainty and the associated business risk for emerging technologies

Science.gov (United States)

Hoerr, Robert A.

2011-04-01

An oversight system specifically concerned with nanomaterials should be flexible enough to take into account the unique aspects of individual novel materials and the settings in which they might be used, while recognizing that heretofore unrecognized safety issues may require future modifications. This article considers a question not explicitly considered by the project team: what is the risk that uncertainty over how regulatory oversight will be applied to nanomaterials will delay or block the development of this emerging technology, thereby depriving human health of potential and substantial benefits? An ambiguous regulatory environment could delay the availability of valuable new technology and therapeutics for human health by reducing access to investment capital. Venture capitalists list regulatory uncertainty as a major reason not to invest at all in certain areas. Uncertainty is far more difficult to evaluate than risk, which lends itself to quantitative models and can be factored into projections of return on possible investments. Loss of time has a large impact on investment return. An examination of regulatory case histories suggests that an increase in regulatory resting requirement, where the path is well-defined, is far less costly than a delay of a year or more in achieving product approval and market launch.

Analysis of uncertainty in modeling perceived risks

International Nuclear Information System (INIS)

Melnyk, R.; Sandquist, G.M.

2005-01-01

Expanding on a mathematical model developed for quantifying and assessing perceived risks, the distribution functions, variances, and uncertainties associated with estimating the model parameters are quantified. The analytical model permits the identification and assignment of any number of quantifiable risk perception factors that can be incorporated within standard risk methodology. Those risk perception factors associated with major technical issues are modeled using lognormal probability density functions to span the potentially large uncertainty variations associated with these risk perceptions. The model quantifies the logic of public risk perception and provides an effective means for measuring and responding to perceived risks. (authors)

Developing Hydrogeological Site Characterization Strategies based on Human Health Risk

Science.gov (United States)

de Barros, F.; Rubin, Y.; Maxwell, R. M.

2013-12-01

In order to provide better sustainable groundwater quality management and minimize the impact of contamination in humans, improved understanding and quantification of the interaction between hydrogeological models, geological site information and human health are needed. Considering the joint influence of these components in the overall human health risk assessment and the corresponding sources of uncertainty aid decision makers to better allocate resources in data acquisition campaigns. This is important to (1) achieve remediation goals in a cost-effective manner, (2) protect human health and (3) keep water supplies clean in order to keep with quality standards. Such task is challenging since a full characterization of the subsurface is unfeasible due to financial and technological constraints. In addition, human exposure and physiological response to contamination are subject to uncertainty and variability. Normally, sampling strategies are developed with the goal of reducing uncertainty, but less often they are developed in the context of their impacts on the overall system uncertainty. Therefore, quantifying the impact from each of these components (hydrogeological, behavioral and physiological) in final human health risk prediction can provide guidance for decision makers to best allocate resources towards minimal prediction uncertainty. In this presentation, a multi-component human health risk-based framework is presented which allows decision makers to set priorities through an information entropy-based visualization tool. Results highlight the role of characteristic length-scales characterizing flow and transport in determining data needs within an integrated hydrogeological-health framework. Conditions where uncertainty reduction in human health risk predictions may benefit from better understanding of the health component, as opposed to a more detailed hydrogeological characterization, are also discussed. Finally, results illustrate how different dose

Risk assessment under deep uncertainty: A methodological comparison

International Nuclear Information System (INIS)

Shortridge, Julie; Aven, Terje; Guikema, Seth

2017-01-01

Probabilistic Risk Assessment (PRA) has proven to be an invaluable tool for evaluating risks in complex engineered systems. However, there is increasing concern that PRA may not be adequate in situations with little underlying knowledge to support probabilistic representation of uncertainties. As analysts and policy makers turn their attention to deeply uncertain hazards such as climate change, a number of alternatives to traditional PRA have been proposed. This paper systematically compares three diverse approaches for risk analysis under deep uncertainty (qualitative uncertainty factors, probability bounds, and robust decision making) in terms of their representation of uncertain quantities, analytical output, and implications for risk management. A simple example problem is used to highlight differences in the way that each method relates to the traditional risk assessment process and fundamental issues associated with risk assessment and description. We find that the implications for decision making are not necessarily consistent between approaches, and that differences in the representation of uncertain quantities and analytical output suggest contexts in which each method may be most appropriate. Finally, each methodology demonstrates how risk assessment can inform decision making in deeply uncertain contexts, informing more effective responses to risk problems characterized by deep uncertainty. - Highlights: • We compare three diverse approaches to risk assessment under deep uncertainty. • A simple example problem highlights differences in analytical process and results. • Results demonstrate how methodological choices can impact risk assessment results.

Uncertainties in Cancer Risk Coefficients for Environmental Exposure to Radionuclides. An Uncertainty Analysis for Risk Coefficients Reported in Federal Guidance Report No. 13

Energy Technology Data Exchange (ETDEWEB)

Pawel, David [U.S. Environmental Protection Agency; Leggett, Richard Wayne [ORNL; Eckerman, Keith F [ORNL; Nelson, Christopher [U.S. Environmental Protection Agency

2007-01-01

Federal Guidance Report No. 13 (FGR 13) provides risk coefficients for estimation of the risk of cancer due to low-level exposure to each of more than 800 radionuclides. Uncertainties in risk coefficients were quantified in FGR 13 for 33 cases (exposure to each of 11 radionuclides by each of three exposure pathways) on the basis of sensitivity analyses in which various combinations of plausible biokinetic, dosimetric, and radiation risk models were used to generate alternative risk coefficients. The present report updates the uncertainty analysis in FGR 13 for the cases of inhalation and ingestion of radionuclides and expands the analysis to all radionuclides addressed in that report. The analysis indicates that most risk coefficients for inhalation or ingestion of radionuclides are determined within a factor of 5 or less by current information. That is, application of alternate plausible biokinetic and dosimetric models and radiation risk models (based on the linear, no-threshold hypothesis with an adjustment for the dose and dose rate effectiveness factor) is unlikely to change these coefficients by more than a factor of 5. In this analysis the assessed uncertainty in the radiation risk model was found to be the main determinant of the uncertainty category for most risk coefficients, but conclusions concerning the relative contributions of risk and dose models to the total uncertainty in a risk coefficient may depend strongly on the method of assessing uncertainties in the risk model.

Introduction of risk size in the determination of uncertainty factor UFL in risk assessment

International Nuclear Information System (INIS)

Xue Jinling; Lu Yun; Velasquez, Natalia; Hu Hongying; Yu Ruozhen; Liu Zhengtao; Meng Wei

2012-01-01

The methodology for using uncertainty factors in health risk assessment has been developed for several decades. A default value is usually applied for the uncertainty factor UF L , which is used to extrapolate from LOAEL (lowest observed adverse effect level) to NAEL (no adverse effect level). Here, we have developed a new method that establishes a linear relationship between UF L and the additional risk level at LOAEL based on the dose–response information, which represents a very important factor that should be carefully considered. This linear formula makes it possible to select UF L properly in the additional risk range from 5.3% to 16.2%. Also the results remind us that the default value 10 may not be conservative enough when the additional risk level at LOAEL exceeds 16.2%. Furthermore, this novel method not only provides a flexible UF L instead of the traditional default value, but also can ensure a conservative estimation of the UF L with fewer errors, and avoid the benchmark response selection involved in the benchmark dose method. These advantages can improve the estimation of the extrapolation starting point in the risk assessment. (letter)

Gambling in Latin: incorporating uncertainty in risk management

Energy Technology Data Exchange (ETDEWEB)

Gratt, L.B.; Levin, L. (IWG Corporation, San Diego, CA (United States))

1994-08-01

Risk assessment uses assumptions based on differing degrees of conservatism. This complicates the understanding of the uncertainty in the final risk estimate. Uncertainties arise from each component of the risk assessment process: source terms, atmospheric transport, exposure, and dose response. Probabilistic modeling using Monte Carlo and Latin Square sampling techniques (reference to Gambling in Latin) allows for an improved approach to risk assessment and management. 16 refs., 1 fig., 1 tab.

Assessing scenario and parametric uncertainties in risk analysis: a model uncertainty audit

International Nuclear Information System (INIS)

Tarantola, S.; Saltelli, A.; Draper, D.

1999-01-01

In the present study a process of model audit is addressed on a computational model used for predicting maximum radiological doses to humans in the field of nuclear waste disposal. Global uncertainty and sensitivity analyses are employed to assess output uncertainty and to quantify the contribution of parametric and scenario uncertainties to the model output. These tools are of fundamental importance for risk analysis and decision making purposes

Uncertainties and demonstration of compliance with numerical risk standards

International Nuclear Information System (INIS)

Preyssl, C.; Cullingford, M.C.

1987-01-01

When dealing with numerical results of a probabilistic risk analysis performed for a complex system, such as a nuclear power plant, one major objective may be to deal with the problem of compliance or non-compliance with a prefixed risk standard. The uncertainties in the risk results associated with the consequences and their probabilities of occurrence may be considered by representing the risk as a risk band. Studying the area and distance between the upper and lower bound of the risk band provides consistent information on the uncertainties in terms of risk, not by means of scalars only but also by real functions. Criteria can be defined for determining compliance with a numerical risk standard, and the 'weighting functional' method, representing a possible tool for testing compliance of risk results, is introduced. By shifting the upper confidence bound due to redefinition, part of the risk band may exceed the standard without changing the underlying results. Using the concept described it is possible to determine the amount of risk, i.e. uncertainty, exceeding the standard. The mathematical treatment of uncertainties therefore allows probabilistic risk assessment results to be compared. A realistic example illustrates the method. (author)

Uncertainty analysis in the applications of nuclear probabilistic risk assessment

International Nuclear Information System (INIS)

Le Duy, T.D.

2011-01-01

The aim of this thesis is to propose an approach to model parameter and model uncertainties affecting the results of risk indicators used in the applications of nuclear Probabilistic Risk assessment (PRA). After studying the limitations of the traditional probabilistic approach to represent uncertainty in PRA model, a new approach based on the Dempster-Shafer theory has been proposed. The uncertainty analysis process of the proposed approach consists in five main steps. The first step aims to model input parameter uncertainties by belief and plausibility functions according to the data PRA model. The second step involves the propagation of parameter uncertainties through the risk model to lay out the uncertainties associated with output risk indicators. The model uncertainty is then taken into account in the third step by considering possible alternative risk models. The fourth step is intended firstly to provide decision makers with information needed for decision making under uncertainty (parametric and model) and secondly to identify the input parameters that have significant uncertainty contributions on the result. The final step allows the process to be continued in loop by studying the updating of beliefs functions given new data. The proposed methodology was implemented on a real but simplified application of PRA model. (author)

Uncertainty studies and risk assessment for CO2 storage in geological formations

International Nuclear Information System (INIS)

Walter, Lena Sophie

2013-01-01

Carbon capture and storage (CCS) in deep geological formations is one possible option to mitigate the greenhouse gas effect by reducing CO 2 emissions into the atmosphere. The assessment of the risks related to CO 2 storage is an important task. Events such as CO 2 leakage and brine displacement could result in hazards for human health and the environment. In this thesis, a systematic and comprehensive risk assessment concept is presented to investigate various levels of uncertainties and to assess risks using numerical simulations. Depending on the risk and the processes, which should be assessed, very complex models, large model domains, large time scales, and many simulations runs for estimating probabilities are required. To reduce the resulting high computational costs, a model reduction technique (the arbitrary polynomial chaos expansion) and a method for model coupling in space are applied. The different levels of uncertainties are: statistical uncertainty in parameter distributions, scenario uncertainty, e.g. different geological features, and recognized ignorance due to assumptions in the conceptual model set-up. Recognized ignorance and scenario uncertainty are investigated by simulating well defined model set-ups and scenarios. According to damage values, which are defined as a model output, the set-ups and scenarios can be compared and ranked. For statistical uncertainty probabilities can be determined by running Monte Carlo simulations with the reduced model. The results are presented in various ways: e.g., mean damage, probability density function, cumulative distribution function, or an overall risk value by multiplying the damage with the probability. If the model output (damage) cannot be compared to provided criteria (e.g. water quality criteria), analytical approximations are presented to translate the damage into comparable values. The overall concept is applied for the risks related to brine displacement and infiltration into drinking water

Model uncertainty in financial markets : Long run risk and parameter uncertainty

NARCIS (Netherlands)

de Roode, F.A.

2014-01-01

Uncertainty surrounding key parameters of financial markets, such as the in- flation and equity risk premium, constitute a major risk for institutional investors with long investment horizons. Hedging the investors’ inflation exposure can be challenging due to the lack of domestic inflation-linked

Assessing uncertainty and risk in exploited marine populations

International Nuclear Information System (INIS)

Fogarty, M.J.; Mayo, R.K.; O'Brien, L.; Serchuk, F.M.; Rosenberg, A.A.

1996-01-01

The assessment and management of exploited fish and invertebrate populations is subject to several types of uncertainty. This uncertainty translates into risk to the population in the development and implementation of fishery management advice. Here, we define risk as the probability that exploitation rates will exceed a threshold level where long term sustainability of the stock is threatened. We distinguish among several sources of error or uncertainty due to (a) stochasticity in demographic rates and processes, particularly in survival rates during the early fife stages; (b) measurement error resulting from sampling variation in the determination of population parameters or in model estimation; and (c) the lack of complete information on population and ecosystem dynamics. The first represents a form of aleatory uncertainty while the latter two factors represent forms of epistemic uncertainty. To illustrate these points, we evaluate the recent status of the Georges Bank cod stock in a risk assessment framework. Short term stochastic projections are made accounting for uncertainty in population size and for random variability in the number of young surviving to enter the fishery. We show that recent declines in this cod stock can be attributed to exploitation rates that have substantially exceeded sustainable levels

A Framework for Understanding Uncertainty in Seismic Risk Assessment.

Science.gov (United States)

Foulser-Piggott, Roxane; Bowman, Gary; Hughes, Martin

2017-10-11

A better understanding of the uncertainty that exists in models used for seismic risk assessment is critical to improving risk-based decisions pertaining to earthquake safety. Current models estimating the probability of collapse of a building do not consider comprehensively the nature and impact of uncertainty. This article presents a model framework to enhance seismic risk assessment and thus gives decisionmakers a fuller understanding of the nature and limitations of the estimates. This can help ensure that risks are not over- or underestimated and the value of acquiring accurate data is appreciated fully. The methodology presented provides a novel treatment of uncertainties in input variables, their propagation through the model, and their effect on the results. The study presents ranges of possible annual collapse probabilities for different case studies on buildings in different parts of the world, exposed to different levels of seismicity, and with different vulnerabilities. A global sensitivity analysis was conducted to determine the significance of uncertain variables. Two key outcomes are (1) that the uncertainty in ground-motion conversion equations has the largest effect on the uncertainty in the calculation of annual collapse probability; and (2) the vulnerability of a building appears to have an effect on the range of annual collapse probabilities produced, i.e., the level of uncertainty in the estimate of annual collapse probability, with less vulnerable buildings having a smaller uncertainty. © 2017 Society for Risk Analysis.

Scientific uncertainties associated with risk assessment of radiation

International Nuclear Information System (INIS)

Hubert, P.; Fagnani, F.

1989-05-01

The proper use and interpretation of data pertaining to biological effects of ionizing radiations is based on a continuous effort to discuss the various assumptions and uncertainties in the process of risk assessment. In this perspective, it has been considered useful by the Committee to review critically the general scientific foundations that constitute the basic framework of data for the evaluation of health effects of radiation. This review is an attempt to identify the main sources of uncertainties, to give, when possible, an order of magnitude for their relative importance, and to clarify the principal interactions between the different steps of the process of risk quantification. The discussion has been restricted to stochastic effects and especially to cancer induction in man: observations at the cellular levels and animal and in vitro experiments have not been considered. The consequences which might result from abandoning the hypothesis of linearity have not been directly examined in this draft, especially in respect to the concept of collective dose. Since another document dealing with 'Dose-response relationships for radiation-induced cancer' is in preparation, an effort has been made to avoid any overlap by making reference to that document whenever necessary

Scientific uncertainties associated with risk assessment of radiation

Energy Technology Data Exchange (ETDEWEB)

Hubert, P; Fagnani, F

1989-05-01

The proper use and interpretation of data pertaining to biological effects of ionizing radiations is based on a continuous effort to discuss the various assumptions and uncertainties in the process of risk assessment. In this perspective, it has been considered useful by the Committee to review critically the general scientific foundations that constitute the basic framework of data for the evaluation of health effects of radiation. This review is an attempt to identify the main sources of uncertainties, to give, when possible, an order of magnitude for their relative importance, and to clarify the principal interactions between the different steps of the process of risk quantification. The discussion has been restricted to stochastic effects and especially to cancer induction in man: observations at the cellular levels and animal and in vitro experiments have not been considered. The consequences which might result from abandoning the hypothesis of linearity have not been directly examined in this draft, especially in respect to the concept of collective dose. Since another document dealing with 'Dose-response relationships for radiation-induced cancer' is in preparation, an effort has been made to avoid any overlap by making reference to that document whenever necessary.

Methods for Addressing Uncertainty and Variability to Characterize Potential Health Risk From Trichloroethylene-Contaminated Ground Water Beale Air Force Base in California: Integration of Uncertainty and Variability in Pharmacokinetics and Dose-Response; TOPICAL

International Nuclear Information System (INIS)

Bogen, K.T.

1999-01-01

Traditional estimates of health risk are typically inflated, particularly if cancer is the dominant endpoint and there is fundamental uncertainty as to mechanism(s) of action. Risk is more realistically characterized if it accounts for joint uncertainty and interindividual variability after applying a unified probabilistic approach to the distributed parameters of all (linear as well as nonlinear) risk-extrapolation models involved. Such an approach was applied to characterize risks to potential future residents posed by trichloroethylene (TCE) in ground water at an inactive landfill site on Beale Air Force Base in California. Variability and uncertainty were addressed in exposure-route-specific estimates of applied dose, in pharmacokinetically based estimates of route-specific metabolized fractions of absorbed TCE, and in corresponding biologically effective doses estimated under a genotoxic/linear (MA(sub g)) vs. a cytotoxic/nonlinear (MA(sub c)) mechanistic assumption for TCE-induced cancer. Increased risk conditional on effective dose was estimated under MA(sub G) based on seven rodent-bioassay data sets, and under MA, based on mouse hepatotoxicity data. Mean and upper-bound estimates of combined risk calculated by the unified approach were and lt;10(sup -6) and and lt;10(sup -4), respectively, while corresponding estimates based on traditional deterministic methods were and gt;10(sup -5) and and gt;10(sup -4), respectively. It was estimated that no TCE-related harm is likely occur due any plausible residential exposure scenario involving the site. The unified approach illustrated is particularly suited to characterizing risks that involve uncertain and/or diverse mechanisms of action

Statistically based uncertainty assessments in nuclear risk analysis

International Nuclear Information System (INIS)

Spencer, F.W.; Diegert, K.V.; Easterling, R.G.

1987-01-01

Over the last decade, the problems of estimation and uncertainty assessment in probabilistics risk assessment (PRAs) have been addressed in a variety of NRC and industry-sponsored projects. These problems have received attention because of a recognition that major uncertainties in risk estimation exist, which can be reduced by collecting more and better data and other information, and because of a recognition that better methods for assessing these uncertainties are needed. In particular, a clear understanding of the nature and magnitude of various sources of uncertainty is needed to facilitate descision-making on possible plant changes and research options. Recent PRAs have employed methods of probability propagation, sometimes involving the use of Bayes Theorem, and intended to formalize the use of ''engineering judgment'' or ''expert opinion.'' All sources, or feelings, of uncertainty are expressed probabilistically, so that uncertainty analysis becomes simply a matter of probability propagation. Alternatives to forcing a probabilistic framework at all stages of a PRA are a major concern in this paper, however

Risk assessment through drinking water pathway via uncertainty modeling of contaminant transport using soft computing

International Nuclear Information System (INIS)

Datta, D.; Ranade, A.K.; Pandey, M.; Sathyabama, N.; Kumar, Brij

2012-01-01

The basic objective of an environmental impact assessment (EIA) is to build guidelines to reduce the associated risk or mitigate the consequences of the reactor accident at its source to prevent deterministic health effects, to reduce the risk of stochastic health effects (eg. cancer and severe hereditary effects) as much as reasonable achievable by implementing protective actions in accordance with IAEA guidance (IAEA Safety Series No. 115, 1996). The measure of exposure being the basic tool to take any appropriate decisions related to risk reduction, EIA is traditionally expressed in terms of radiation exposure to the member of the public. However, models used to estimate the exposure received by the member of the public are governed by parameters some of which are deterministic with relative uncertainty and some of which are stochastic as well as imprecise (insufficient knowledge). In an admixture environment of this type, it is essential to assess the uncertainty of a model to estimate the bounds of the exposure to the public to invoke a decision during an event of nuclear or radiological emergency. With a view to this soft computing technique such as evidence theory based assessment of model parameters is addressed to compute the risk or exposure to the member of the public. The possible pathway of exposure to the member of the public in the aquatic food stream is the drinking of water. Accordingly, this paper presents the uncertainty analysis of exposure via uncertainty analysis of the contaminated water. Evidence theory finally addresses the uncertainty in terms of lower bound as belief measure and upper bound of exposure as plausibility measure. In this work EIA is presented using evidence theory. Data fusion technique is used to aggregate the knowledge on the uncertain information. Uncertainty of concentration and exposure is expressed as an interval of belief, plausibility

Risk Characterization uncertainties associated description, sensitivity analysis

International Nuclear Information System (INIS)

Carrillo, M.; Tovar, M.; Alvarez, J.; Arraez, M.; Hordziejewicz, I.; Loreto, I.

2013-01-01

The power point presentation is about risks to the estimated levels of exposure, uncertainty and variability in the analysis, sensitivity analysis, risks from exposure to multiple substances, formulation of guidelines for carcinogenic and genotoxic compounds and risk subpopulations

Hazardous waste transportation risk assessment: Benefits of a combined deterministic and probabilistic Monte Carlo approach in expressing risk uncertainty

International Nuclear Information System (INIS)

Policastro, A.J.; Lazaro, M.A.; Cowen, M.A.; Hartmann, H.M.; Dunn, W.E.; Brown, D.F.

1995-01-01

This paper presents a combined deterministic and probabilistic methodology for modeling hazardous waste transportation risk and expressing the uncertainty in that risk. Both the deterministic and probabilistic methodologies are aimed at providing tools useful in the evaluation of alternative management scenarios for US Department of Energy (DOE) hazardous waste treatment, storage, and disposal (TSD). The probabilistic methodology can be used to provide perspective on and quantify uncertainties in deterministic predictions. The methodology developed has been applied to 63 DOE shipments made in fiscal year 1992, which contained poison by inhalation chemicals that represent an inhalation risk to the public. Models have been applied to simulate shipment routes, truck accident rates, chemical spill probabilities, spill/release rates, dispersion, population exposure, and health consequences. The simulation presented in this paper is specific to trucks traveling from DOE sites to their commercial TSD facilities, but the methodology is more general. Health consequences are presented as the number of people with potentially life-threatening health effects. Probabilistic distributions were developed (based on actual item data) for accident release amounts, time of day and season of the accident, and meteorological conditions

From risk management to uncertainty management: a significant change in project management

Institute of Scientific and Technical Information of China (English)

LI Gui-jun; ZHANG Yue-song

2006-01-01

Starting with the meanings of the terms "risk" and "uncertainty,"" he paper compares uncertainty management with risk management in project management. We bring some doubt to the use of "risk" and "uncertainty" interchangeably in project management and deem their scope, methods, responses, monitoring and controlling should be different too. Illustrations are given covering terminology, description, and treatment from different perspectives of uncertainty management and risk management. Furthermore, the paper retains that project risk management (PRM) processes might be modified to facilitate an uncertainty management perspective,and we support that project uncertainty management (PUM) can enlarge its contribution to improving project management performance, which will result in a significant change in emphasis compared with most risk management.

Sensitivity and uncertainty analyses in aging risk-based prioritizations

International Nuclear Information System (INIS)

Hassan, M.; Uryas'ev, S.; Vesely, W.E.

1993-01-01

Aging risk evaluations of nuclear power plants using Probabilistic Risk Analyses (PRAs) involve assessments of the impact of aging structures, systems, and components (SSCs) on plant core damage frequency (CDF). These assessments can be used to prioritize the contributors to aging risk reflecting the relative risk potential of the SSCs. Aging prioritizations are important for identifying the SSCs contributing most to plant risk and can provide a systematic basis on which aging risk control and management strategies for a plant can be developed. However, these prioritizations are subject to variabilities arising from uncertainties in data, and/or from various modeling assumptions. The objective of this paper is to present an evaluation of the sensitivity of aging prioritizations of active components to uncertainties in aging risk quantifications. Approaches for robust prioritization of SSCs also are presented which are less susceptible to the uncertainties

Methods to Quantify Uncertainty in Human Health Risk Assessment

National Research Council Canada - National Science Library

Aurelius, Lea

1998-01-01

...) and other health professionals, such as the Bioenviroumental Engineer, to identify the appropriate use of probabilistic techniques for a site, and the methods by which probabilistic risk assessment...

Political uncertainty and firm risk in China

Directory of Open Access Journals (Sweden)

Danglun Luo

2017-12-01

Full Text Available The political uncertainty surrounded by the turnover of government officials has a major impact on local economies and local firms. This paper investigates the relationship between the turnover of prefecture-city officials and the inherent risk faced by local firms in China. Using data from 1999 to 2012, we find that prefecture-city official turnovers significantly increased firm risk. Our results show that the political risk was mitigated when new prefecture-city officials were well connected with their provincial leaders. In addition, the impact of political uncertainty was more pronounced for regulated firms and firms residing in provinces with low market openness.

Uncertainty studies and risk assessment for CO{sub 2} storage in geological formations

Energy Technology Data Exchange (ETDEWEB)

Walter, Lena Sophie

2013-07-01

Carbon capture and storage (CCS) in deep geological formations is one possible option to mitigate the greenhouse gas effect by reducing CO{sub 2} emissions into the atmosphere. The assessment of the risks related to CO{sub 2} storage is an important task. Events such as CO{sub 2} leakage and brine displacement could result in hazards for human health and the environment. In this thesis, a systematic and comprehensive risk assessment concept is presented to investigate various levels of uncertainties and to assess risks using numerical simulations. Depending on the risk and the processes, which should be assessed, very complex models, large model domains, large time scales, and many simulations runs for estimating probabilities are required. To reduce the resulting high computational costs, a model reduction technique (the arbitrary polynomial chaos expansion) and a method for model coupling in space are applied. The different levels of uncertainties are: statistical uncertainty in parameter distributions, scenario uncertainty, e.g. different geological features, and recognized ignorance due to assumptions in the conceptual model set-up. Recognized ignorance and scenario uncertainty are investigated by simulating well defined model set-ups and scenarios. According to damage values, which are defined as a model output, the set-ups and scenarios can be compared and ranked. For statistical uncertainty probabilities can be determined by running Monte Carlo simulations with the reduced model. The results are presented in various ways: e.g., mean damage, probability density function, cumulative distribution function, or an overall risk value by multiplying the damage with the probability. If the model output (damage) cannot be compared to provided criteria (e.g. water quality criteria), analytical approximations are presented to translate the damage into comparable values. The overall concept is applied for the risks related to brine displacement and infiltration into

Farm decision making under risk and uncertainty.

NARCIS (Netherlands)

Backus, G.B.C.; Eidman, V.R.; Dijkhuizen, A.A.

1997-01-01

Relevant portions of the risk literature are reviewed, relating them to observed behaviour in farm decision-making. Relevant topics for applied agricultural risk research are proposed. The concept of decision making under risk and uncertainty is discussed by reviewing the theory of Subjective

Optimal allocation of resources over health care programmes: dealing with decreasing marginal utility and uncertainty.

Science.gov (United States)

Al, Maiwenn J; Feenstra, Talitha L; Hout, Ben A van

2005-07-01

This paper addresses the problem of how to value health care programmes with different ratios of costs to effects, specifically when taking into account that these costs and effects are uncertain. First, the traditional framework of maximising health effects with a given health care budget is extended to a flexible budget using a value function over money and health effects. Second, uncertainty surrounding costs and effects is included in the model using expected utility. Other approaches to uncertainty that do not specify a utility function are discussed and it is argued that these also include implicit notions about risk attitude.

Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings.

Directory of Open Access Journals (Sweden)

Elise Payzan-LeNestour

Full Text Available Recently, evidence has emerged that humans approach learning using Bayesian updating rather than (model-free reinforcement algorithms in a six-arm restless bandit problem. Here, we investigate what this implies for human appreciation of uncertainty. In our task, a Bayesian learner distinguishes three equally salient levels of uncertainty. First, the Bayesian perceives irreducible uncertainty or risk: even knowing the payoff probabilities of a given arm, the outcome remains uncertain. Second, there is (parameter estimation uncertainty or ambiguity: payoff probabilities are unknown and need to be estimated. Third, the outcome probabilities of the arms change: the sudden jumps are referred to as unexpected uncertainty. We document how the three levels of uncertainty evolved during the course of our experiment and how it affected the learning rate. We then zoom in on estimation uncertainty, which has been suggested to be a driving force in exploration, in spite of evidence of widespread aversion to ambiguity. Our data corroborate the latter. We discuss neural evidence that foreshadowed the ability of humans to distinguish between the three levels of uncertainty. Finally, we investigate the boundaries of human capacity to implement Bayesian learning. We repeat the experiment with different instructions, reflecting varying levels of structural uncertainty. Under this fourth notion of uncertainty, choices were no better explained by Bayesian updating than by (model-free reinforcement learning. Exit questionnaires revealed that participants remained unaware of the presence of unexpected uncertainty and failed to acquire the right model with which to implement Bayesian updating.

New challenges on uncertainty propagation assessment of flood risk analysis

Science.gov (United States)

Martins, Luciano; Aroca-Jiménez, Estefanía; Bodoque, José M.; Díez-Herrero, Andrés

2016-04-01

Natural hazards, such as floods, cause considerable damage to the human life, material and functional assets every year and around the World. Risk assessment procedures has associated a set of uncertainties, mainly of two types: natural, derived from stochastic character inherent in the flood process dynamics; and epistemic, that are associated with lack of knowledge or the bad procedures employed in the study of these processes. There are abundant scientific and technical literature on uncertainties estimation in each step of flood risk analysis (e.g. rainfall estimates, hydraulic modelling variables); but very few experience on the propagation of the uncertainties along the flood risk assessment. Therefore, epistemic uncertainties are the main goal of this work, in particular,understand the extension of the propagation of uncertainties throughout the process, starting with inundability studies until risk analysis, and how far does vary a proper analysis of the risk of flooding. These methodologies, such as Polynomial Chaos Theory (PCT), Method of Moments or Monte Carlo, are used to evaluate different sources of error, such as data records (precipitation gauges, flow gauges...), hydrologic and hydraulic modelling (inundation estimation), socio-demographic data (damage estimation) to evaluate the uncertainties propagation (UP) considered in design flood risk estimation both, in numerical and cartographic expression. In order to consider the total uncertainty and understand what factors are contributed most to the final uncertainty, we used the method of Polynomial Chaos Theory (PCT). It represents an interesting way to handle to inclusion of uncertainty in the modelling and simulation process. PCT allows for the development of a probabilistic model of the system in a deterministic setting. This is done by using random variables and polynomials to handle the effects of uncertainty. Method application results have a better robustness than traditional analysis

Risk Management and Uncertainty in Infrastructure Projects

DEFF Research Database (Denmark)

Harty, Chris; Neerup Themsen, Tim; Tryggestad, Kjell

2014-01-01

The assumption that large complex projects should be managed in order to reduce uncertainty and increase predictability is not new. What is relatively new, however, is that uncertainty reduction can and should be obtained through formal risk management approaches. We question both assumptions...... by addressing a more fundamental question about the role of knowledge in current risk management practices. Inquiries into the predominant approaches to risk management in large infrastructure and construction projects reveal their assumptions about knowledge and we discuss the ramifications these have...... for project and construction management. Our argument and claim is that predominant risk management approaches tends to reinforce conventional ideas of project control whilst undermining other notions of value and relevance of built assets and project management process. These approaches fail to consider...

Risk Aversion, Price Uncertainty and Irreversible Investments

NARCIS (Netherlands)

van den Goorbergh, R.W.J.; Huisman, K.J.M.; Kort, P.M.

2003-01-01

This paper generalizes the theory of irreversible investment under uncertainty by allowing for risk averse investors in the absence of com-plete markets.Until now this theory has only been developed in the cases of risk neutrality, or risk aversion in combination with complete markets.Within a

The explicit treatment of model uncertainties in the presence of aleatory and epistemic parameter uncertainties in risk and reliability analysis

International Nuclear Information System (INIS)

Ahn, Kwang Il; Yang, Joon Eon

2003-01-01

In the risk and reliability analysis of complex technological systems, the primary concern of formal uncertainty analysis is to understand why uncertainties arise, and to evaluate how they impact the results of the analysis. In recent times, many of the uncertainty analyses have focused on parameters of the risk and reliability analysis models, whose values are uncertain in an aleatory or an epistemic way. As the field of parametric uncertainty analysis matures, however, more attention is being paid to the explicit treatment of uncertainties that are addressed in the predictive model itself as well as the accuracy of the predictive model. The essential steps for evaluating impacts of these model uncertainties in the presence of parameter uncertainties are to determine rigorously various sources of uncertainties to be addressed in an underlying model itself and in turn model parameters, based on our state-of-knowledge and relevant evidence. Answering clearly the question of how to characterize and treat explicitly the forgoing different sources of uncertainty is particularly important for practical aspects such as risk and reliability optimization of systems as well as more transparent risk information and decision-making under various uncertainties. The main purpose of this paper is to provide practical guidance for quantitatively treating various model uncertainties that would often be encountered in the risk and reliability modeling process of complex technological systems

Exploring the uncertainties in cancer risk assessment using the integrated probabilistic risk assessment (IPRA) approach.

Science.gov (United States)

Slob, Wout; Bakker, Martine I; Biesebeek, Jan Dirk Te; Bokkers, Bas G H

2014-08-01

Current methods for cancer risk assessment result in single values, without any quantitative information on the uncertainties in these values. Therefore, single risk values could easily be overinterpreted. In this study, we discuss a full probabilistic cancer risk assessment approach in which all the generally recognized uncertainties in both exposure and hazard assessment are quantitatively characterized and probabilistically evaluated, resulting in a confidence interval for the final risk estimate. The methodology is applied to three example chemicals (aflatoxin, N-nitrosodimethylamine, and methyleugenol). These examples illustrate that the uncertainty in a cancer risk estimate may be huge, making single value estimates of cancer risk meaningless. Further, a risk based on linear extrapolation tends to be lower than the upper 95% confidence limit of a probabilistic risk estimate, and in that sense it is not conservative. Our conceptual analysis showed that there are two possible basic approaches for cancer risk assessment, depending on the interpretation of the dose-incidence data measured in animals. However, it remains unclear which of the two interpretations is the more adequate one, adding an additional uncertainty to the already huge confidence intervals for cancer risk estimates. © 2014 Society for Risk Analysis.

Assessment of Risks and Uncertainties in Poultry Farming in Kwara ...

African Journals Online (AJOL)

, identify the risks and uncertainties encountered by the farmers, determines the level of severity of the risks and uncertainties, and identifies the coping strategies employed by the farmers. Primary data obtained from 99 registered poultry ...

Reducing uncertainty in wind turbine blade health inspection with image processing techniques

Science.gov (United States)

Zhang, Huiyi

Structural health inspection has been widely applied in the operation of wind farms to find early cracks in wind turbine blades (WTBs). Increased numbers of turbines and expanded rotor diameters are driving up the workloads and safety risks for site employees. Therefore, it is important to automate the inspection process as well as minimize the uncertainties involved in routine blade health inspection. In addition, crack documentation and trending is vital to assess rotor blade and turbine reliability in the 20 year designed life span. A new crack recognition and classification algorithm is described that can support automated structural health inspection of the surface of large composite WTBs. The first part of the study investigated the feasibility of digital image processing in WTB health inspection and defined the capability of numerically detecting cracks as small as hairline thickness. The second part of the study identified and analyzed the uncertainty of the digital image processing method. A self-learning algorithm was proposed to recognize and classify cracks without comparing a blade image to a library of crack images. The last part of the research quantified the uncertainty in the field conditions and the image processing methods.

Introduction to risk and uncertainty in hydrosystem engineering

CERN Document Server

Goodarzi, Ehsan; Teang Shui, Lee

2013-01-01

Water engineers require knowledge of stochastic, frequency concepts, uncertainty analysis, risk assessment, and the processes that predict unexpected events. This book presents the basics of stochastic, risk and uncertainty analysis, and random sampling techniques in conjunction with straightforward examples which are solved step by step. In addition, appropriate Excel functions are included as an alternative to solve the examples, and two real case studies is presented in the last chapters of book.

Uncertainties in fatal cancer risk estimates used in radiation protection

International Nuclear Information System (INIS)

Kai, Michiaki

1999-01-01

Although ICRP and NCRP had not described the details of uncertainties in cancer risk estimates in radiation protection, NCRP, in 1997, firstly reported the results of uncertainty analysis (NCRP No.126) and which is summarized in this paper. The NCRP report pointed out that there are following five factors which uncertainty possessing: uncertainty in epidemiological studies, in dose assessment, in transforming the estimates to risk assessment, in risk prediction and in extrapolation to the low dose/dose rate. These individual factors were analyzed statistically to obtain the relationship between the probability of cancer death in the US population and life time risk coefficient (% per Sv), which showed that, for the latter, the mean value was 3.99 x 10 -2 /Sv, median, 3.38 x 10 -2 /Sv, GSD (geometrical standard deviation), 1.83 x 10 -2 /Sv and 95% confidential limit, 1.2-8.84 x 10 -2 /Sv. The mean value was smaller than that of ICRP recommendation (5 x 10 -2 /Sv), indicating that the value has the uncertainty factor of 2.5-3. Moreover, the most important factor was shown to be the uncertainty in DDREF (dose/dose rate reduction factor). (K.H.)

Assessment and uncertainty analysis of groundwater risk.

Science.gov (United States)

Li, Fawen; Zhu, Jingzhao; Deng, Xiyuan; Zhao, Yong; Li, Shaofei

2018-01-01

Groundwater with relatively stable quantity and quality is commonly used by human being. However, as the over-mining of groundwater, problems such as groundwater funnel, land subsidence and salt water intrusion have emerged. In order to avoid further deterioration of hydrogeological problems in over-mining regions, it is necessary to conduct the assessment of groundwater risk. In this paper, risks of shallow and deep groundwater in the water intake area of the South-to-North Water Transfer Project in Tianjin, China, were evaluated. Firstly, two sets of four-level evaluation index system were constructed based on the different characteristics of shallow and deep groundwater. Secondly, based on the normalized factor values and the synthetic weights, the risk values of shallow and deep groundwater were calculated. Lastly, the uncertainty of groundwater risk assessment was analyzed by indicator kriging method. The results meet the decision maker's demand for risk information, and overcome previous risk assessment results expressed in the form of deterministic point estimations, which ignore the uncertainty of risk assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

Review of studies related to uncertainty in risk analsis

International Nuclear Information System (INIS)

Rish, W.R.; Marnicio, R.J.

1988-08-01

The Environmental Protection Agency's Office of Radiation Programs (ORP) is responsible for regulating on a national level the risks associated with technological sources of ionizing radiation in the environment. A critical activity of the ORP is analyzing and evaluating risk. The ORP believes that the analysis of uncertainty should be an integral part of any risk assessment; therefore, the ORP has initiated a project to develop framework for the treatment of uncertainty in risk analysis. Summaries of recent studies done in five areas of study are presented

The role of uncertainty analysis in dose reconstruction and risk assessment

International Nuclear Information System (INIS)

Hoffman, F.O.; Simon, S.L.; Thiessen. K.M.

1996-01-01

Dose reconstruction and risk assessment rely heavily on the use of mathematical models to extrapolate information beyond the realm of direct observation. Because models are merely approximations of real systems, their predictions are inherently uncertain. As a result, full disclosure of uncertainty in dose and risk estimates is essential to achieve scientific credibility and to build public trust. The need for formal analysis of uncertainty in model predictions was presented during the nineteenth annual meeting of the NCRP. At that time, quantitative uncertainty analysis was considered a relatively new and difficult subject practiced by only a few investigators. Today, uncertainty analysis has become synonymous with the assessment process itself. When an uncertainty analysis is used iteratively within the assessment process, it can guide experimental research to refine dose and risk estimates, deferring potentially high cost or high consequence decisions until uncertainty is either acceptable or irreducible. Uncertainty analysis is now mandated for all ongoing dose reconstruction projects within the United States, a fact that distinguishes dose reconstruction from other types of exposure and risk assessments. 64 refs., 6 figs., 1 tab

Overview of methods for uncertainty analysis and sensitivity analysis in probabilistic risk assessment

International Nuclear Information System (INIS)

Iman, R.L.; Helton, J.C.

1985-01-01

Probabilistic Risk Assessment (PRA) is playing an increasingly important role in the nuclear reactor regulatory process. The assessment of uncertainties associated with PRA results is widely recognized as an important part of the analysis process. One of the major criticisms of the Reactor Safety Study was that its representation of uncertainty was inadequate. The desire for the capability to treat uncertainties with the MELCOR risk code being developed at Sandia National Laboratories is indicative of the current interest in this topic. However, as yet, uncertainty analysis and sensitivity analysis in the context of PRA is a relatively immature field. In this paper, available methods for uncertainty analysis and sensitivity analysis in a PRA are reviewed. This review first treats methods for use with individual components of a PRA and then considers how these methods could be combined in the performance of a complete PRA. In the context of this paper, the goal of uncertainty analysis is to measure the imprecision in PRA outcomes of interest, and the goal of sensitivity analysis is to identify the major contributors to this imprecision. There are a number of areas that must be considered in uncertainty analysis and sensitivity analysis for a PRA: (1) information, (2) systems analysis, (3) thermal-hydraulic phenomena/fission product behavior, (4) health and economic consequences, and (5) display of results. Each of these areas and the synthesis of them into a complete PRA are discussed

Including model uncertainty in risk-informed decision making

International Nuclear Information System (INIS)

Reinert, Joshua M.; Apostolakis, George E.

2006-01-01

Model uncertainties can have a significant impact on decisions regarding licensing basis changes. We present a methodology to identify basic events in the risk assessment that have the potential to change the decision and are known to have significant model uncertainties. Because we work with basic event probabilities, this methodology is not appropriate for analyzing uncertainties that cause a structural change to the model, such as success criteria. We use the risk achievement worth (RAW) importance measure with respect to both the core damage frequency (CDF) and the change in core damage frequency (ΔCDF) to identify potentially important basic events. We cross-check these with generically important model uncertainties. Then, sensitivity analysis is performed on the basic event probabilities, which are used as a proxy for the model parameters, to determine how much error in these probabilities would need to be present in order to impact the decision. A previously submitted licensing basis change is used as a case study. Analysis using the SAPHIRE program identifies 20 basic events as important, four of which have model uncertainties that have been identified in the literature as generally important. The decision is fairly insensitive to uncertainties in these basic events. In three of these cases, one would need to show that model uncertainties would lead to basic event probabilities that would be between two and four orders of magnitude larger than modeled in the risk assessment before they would become important to the decision. More detailed analysis would be required to determine whether these higher probabilities are reasonable. Methods to perform this analysis from the literature are reviewed and an example is demonstrated using the case study

Review of studies related to uncertainty in risk analsis

Energy Technology Data Exchange (ETDEWEB)

Rish, W.R.; Marnicio, R.J.

1988-08-01

The Environmental Protection Agency's Office of Radiation Programs (ORP) is responsible for regulating on a national level the risks associated with technological sources of ionizing radiation in the environment. A critical activity of the ORP is analyzing and evaluating risk. The ORP believes that the analysis of uncertainty should be an integral part of any risk assessment; therefore, the ORP has initiated a project to develop framework for the treatment of uncertainty in risk analysis. Summaries of recent studies done in five areas of study are presented.

A Quantitative Measure For Evaluating Project Uncertainty Under Variation And Risk Effects

Directory of Open Access Journals (Sweden)

A. Chenarani

2017-10-01

Full Text Available The effects of uncertainty on a project and the risk event as the consequence of uncertainty are analyzed. The uncertainty index is proposed as a quantitative measure for evaluating the uncertainty of a project. This is done by employing entropy as the indicator of system disorder and lack of information. By employing this index, the uncertainty of each activity and its increase due to risk effects as well as project uncertainty changes as a function of time can be assessed. The results are implemented and analyzed for a small turbojet engine development project as the case study. The results of this study can be useful for project managers and other stakeholders for selecting the most effective risk management and uncertainty controlling method.

Risk Assessment and Decision-Making under Uncertainty in Tunnel and Underground Engineering

Directory of Open Access Journals (Sweden)

Yuanpu Xia

2017-10-01

Full Text Available The impact of uncertainty on risk assessment and decision-making is increasingly being prioritized, especially for large geotechnical projects such as tunnels, where uncertainty is often the main source of risk. Epistemic uncertainty, which can be reduced, is the focus of attention. In this study, the existing entropy-risk decision model is first discussed and analyzed, and its deficiencies are improved upon and overcome. Then, this study addresses the fact that existing studies only consider parameter uncertainty and ignore the influence of the model uncertainty. Here, focus is on the issue of model uncertainty and differences in risk consciousness with different decision-makers. The utility theory is introduced in the model. Finally, a risk decision model is proposed based on the sensitivity analysis and the tolerance cost, which can improve decision-making efficiency. This research can provide guidance or reference for the evaluation and decision-making of complex systems engineering problems, and indicate a direction for further research of risk assessment and decision-making issues.

Testing Map Features Designed to Convey the Uncertainty of Cancer Risk: Insights Gained From Assessing Judgments of Information Adequacy and Communication Goals.

Science.gov (United States)

Severtson, Dolores J

2015-02-01

Barriers to communicating the uncertainty of environmental health risks include preferences for certain information and low numeracy. Map features designed to communicate the magnitude and uncertainty of estimated cancer risk from air pollution were tested among 826 participants to assess how map features influenced judgments of adequacy and the intended communication goals. An uncertain versus certain visual feature was judged as less adequate but met both communication goals and addressed numeracy barriers. Expressing relative risk using words communicated uncertainty and addressed numeracy barriers but was judged as highly inadequate. Risk communication and visual cognition concepts were applied to explain findings.

Managing project risks and uncertainties

Directory of Open Access Journals (Sweden)

Mike Mentis

2015-01-01

Full Text Available This article considers threats to a project slipping on budget, schedule and fit-for-purpose. Threat is used here as the collective for risks (quantifiable bad things that can happen and uncertainties (poorly or not quantifiable bad possible events. Based on experience with projects in developing countries this review considers that (a project slippage is due to uncertainties rather than risks, (b while eventuation of some bad things is beyond control, managed execution and oversight are still the primary means to keeping within budget, on time and fit-for-purpose, (c improving project delivery is less about bigger and more complex and more about coordinated focus, effectiveness and developing thought-out heuristics, and (d projects take longer and cost more partly because threat identification is inaccurate, the scope of identified threats is too narrow, and the threat assessment product is not integrated into overall project decision-making and execution. Almost by definition, what is poorly known is likely to cause problems. Yet it is not just the unquantifiability and intangibility of uncertainties causing project slippage, but that they are insufficiently taken into account in project planning and execution that cause budget and time overruns. Improving project performance requires purpose-driven and managed deployment of scarce seasoned professionals. This can be aided with independent oversight by deeply experienced panelists who contribute technical insights and can potentially show that diligence is seen to be done.

Accounting for predictive uncertainty in a risk analysis focusing on radiological contamination of groundwater

International Nuclear Information System (INIS)

Andricevic, R.; Jacobson, R.L.; Daniels, J.I.

1994-12-01

This study focuses on the probabilistic travel time approach for predicting transport of radionuclides by groundwater velocity considering parameter uncertainty. The principal entity in the presented model is a travel time probability density function (pdf) conditioned on the set of parameters used to describe different transport processes like advection, dispersion, sorption, and decay. The model is applied to predict the arrival time of radionuclides in groundwater from the Nevada Test Site (NTS) at possible locations of potential human receptors nearby. Because of the lack of sorption the Tritium is found to provide the largest risk. Inclusion of sorption processes indicate that the parameter uncertainty and especially negative correlation between the mean velocity and the sorption strength is instrumental in evaluating the radionuclides arrival time at the prespecified accessible environment. Our analysis of potential health risks takes into consideration uncertainties in physiological attributes, as well as in committed effective dose and the estimate of physical detriment per unit Committed Effective Dose

Accounting for Households' Perceived Income Uncertainty in Consumption Risk Sharing

NARCIS (Netherlands)

Singh, S.; Stoltenberg, C.A.

2017-01-01

We develop a consumption risk-sharing model that distinguishes households' perceived income uncertainty from income uncertainty as measured by an econometrician. Households receive signals on their future disposable income that can drive a gap between the two uncertainties. Accounting for the

Risk-informed regulation: handling uncertainty for a rational management of safety

International Nuclear Information System (INIS)

Zio, Enrico

2008-01-01

A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated

Uncertainty propagation in probabilistic risk assessment: A comparative study

International Nuclear Information System (INIS)

Ahmed, S.; Metcalf, D.R.; Pegram, J.W.

1982-01-01

Three uncertainty propagation techniques, namely method of moments, discrete probability distribution (DPD), and Monte Carlo simulation, generally used in probabilistic risk assessment, are compared and conclusions drawn in terms of the accuracy of the results. For small uncertainty in the basic event unavailabilities, the three methods give similar results. For large uncertainty, the method of moments is in error, and the appropriate method is to propagate uncertainty in the discrete form either by DPD method without sampling or by Monte Carlo. (orig.)

Health significance and statistical uncertainty. The value of P-value.

Science.gov (United States)

Consonni, Dario; Bertazzi, Pier Alberto

2017-10-27

The P-value is widely used as a summary statistics of scientific results. Unfortunately, there is a widespread tendency to dichotomize its value in "P0.05" ("statistically not significant"), with the former implying a "positive" result and the latter a "negative" one. To show the unsuitability of such an approach when evaluating the effects of environmental and occupational risk factors. We provide examples of distorted use of P-value and of the negative consequences for science and public health of such a black-and-white vision. The rigid interpretation of P-value as a dichotomy favors the confusion between health relevance and statistical significance, discourages thoughtful thinking, and distorts attention from what really matters, the health significance. A much better way to express and communicate scientific results involves reporting effect estimates (e.g., risks, risks ratios or risk differences) and their confidence intervals (CI), which summarize and convey both health significance and statistical uncertainty. Unfortunately, many researchers do not usually consider the whole interval of CI but only examine if it includes the null-value, therefore degrading this procedure to the same P-value dichotomy (statistical significance or not). In reporting statistical results of scientific research present effects estimates with their confidence intervals and do not qualify the P-value as "significant" or "not significant".

Exploiting risk-reward structures in decision making under uncertainty.

Science.gov (United States)

Leuker, Christina; Pachur, Thorsten; Hertwig, Ralph; Pleskac, Timothy J

2018-06-01

People often have to make decisions under uncertainty-that is, in situations where the probabilities of obtaining a payoff are unknown or at least difficult to ascertain. One solution to this problem is to infer the probability from the magnitude of the potential payoff and thus exploit the inverse relationship between payoffs and probabilities that occurs in many domains in the environment. Here, we investigated how the mind may implement such a solution: (1) Do people learn about risk-reward relationships from the environment-and if so, how? (2) How do learned risk-reward relationships impact preferences in decision-making under uncertainty? Across three experiments (N = 352), we found that participants can learn risk-reward relationships from being exposed to choice environments with a negative, positive, or uncorrelated risk-reward relationship. They were able to learn the associations both from gambles with explicitly stated payoffs and probabilities (Experiments 1 & 2) and from gambles about epistemic events (Experiment 3). In subsequent decisions under uncertainty, participants often exploited the learned association by inferring probabilities from the magnitudes of the payoffs. This inference systematically influenced their preferences under uncertainty: Participants who had been exposed to a negative risk-reward relationship tended to prefer the uncertain option over a smaller sure option for low payoffs, but not for high payoffs. This pattern reversed in the positive condition and disappeared in the uncorrelated condition. This adaptive change in preferences is consistent with the use of the risk-reward heuristic. Copyright © 2018 Elsevier B.V. All rights reserved.

The spectre of uncertainty in communicating technological risk

Energy Technology Data Exchange (ETDEWEB)

Broesius, Michael T. [Univ. of California, Livermore, CA (United States)

1993-12-01

The literature does not clearly describe the potential moral and ethical conflicts that can exist between technology sponsors and the technical communicators whose job it is to present potentially risky technology to the non-technical people most likely to be imperiled by such risk. Equally important, the literature does not address the issue of uncertainty -- not the uncertainty likely to be experienced by the community at risk, but the unreliable processes and methodologies used by technology sponsors to define, quantify, and develop strategies to mitigate technological risks. In this paper, the author goes beyond a description of risk communication, the nature of the generally predictable interaction between technology advocates and non-technically trained individuals, and current trends in the field. Although that kind of information is critical to the success of any risk communication activity, and he has included it when necessary to provide background and perspective, without knowing how and why risk assessment is done, it has limited practical applicability outside the sterile, value-free vacuum in which it is usually framed. Technical communicators, particularly those responsible for communicating potential technological risk, must also understand the social, political, economic, statistical, and ethical issues they will invariably encounter.

Uncertainty Instability Risk Analysis of High Concrete Arch Dam Abutments

Directory of Open Access Journals (Sweden)

Xin Cao

2017-01-01

Full Text Available The uncertainties associated with concrete arch dams rise with the increased height of dams. Given the uncertainties associated with influencing factors, the stability of high arch dam abutments as a fuzzy random event was studied. In addition, given the randomness and fuzziness of calculation parameters as well as the failure criterion, hazard point and hazard surface uncertainty instability risk ratio models were proposed for high arch dam abutments on the basis of credibility theory. The uncertainty instability failure criterion was derived through the analysis of the progressive instability failure process on the basis of Shannon’s entropy theory. The uncertainties associated with influencing factors were quantized by probability or possibility distribution assignments. Gaussian random theory was used to generate random realizations for influence factors with spatial variability. The uncertainty stability analysis method was proposed by combining the finite element analysis and the limit equilibrium method. The instability risk ratio was calculated using the Monte Carlo simulation method and fuzzy random postprocessing. Results corroborate that the modeling approach is sound and that the calculation method is feasible.

Risk analysis under uncertainty, the precautionary principle, and the new EU chemicals strategy.

Science.gov (United States)

Rogers, Michael D

2003-06-01

Three categories of uncertainty in relation to risk assessment are defined; uncertainty in effect, uncertainty in cause, and uncertainty in the relationship between a hypothesised cause and effect. The Precautionary Principle (PP) relates to the third type of uncertainty. Three broad descriptions of the PP are set out, uncertainty justifies action, uncertainty requires action, and uncertainty requires a reversal of the burden of proof for risk assessments. The application of the PP is controversial but what matters in practise is the precautionary action (PA) that follows. The criteria by which the PAs should be judged are detailed. This framework for risk assessment and management under uncertainty is then applied to the envisaged European system for the regulation of chemicals. A new EU regulatory system has been proposed which shifts the burden of proof concerning risk assessments from the regulator to the producer, and embodies the PP in all three of its main regulatory stages. The proposals are critically discussed in relation to three chemicals, namely, atrazine (an endocrine disrupter), cadmium (toxic and possibly carcinogenic), and hydrogen fluoride (a toxic, high-production-volume chemical). Reversing the burden of proof will speed up the regulatory process but the examples demonstrate that applying the PP appropriately, and balancing the countervailing risks and the socio-economic benefits, will continue to be a difficult task for the regulator. The paper concludes with a discussion of the role of precaution in the management of change and of the importance of trust in the effective regulation of uncertain risks.

Dealing with uncertainty arising out of probabilistic risk assessment

International Nuclear Information System (INIS)

Solomon, K.A.; Kastenberg, W.E.; Nelson, P.F.

1984-03-01

In addressing the area of safety goal implementation, the question of uncertainty arises. This report suggests that the Nuclear Regulatory Commission (NRC) should examine how other regulatory organizations have addressed the issue. Several examples are given from the chemical industry, and comparisons are made to nuclear power risks. Recommendations are made as to various considerations that the NRC should require in probabilistic risk assessments in order to properly treat uncertainties in the implementation of the safety goal policy. 40 references, 7 figures, 5 tables

Real-Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties

Science.gov (United States)

Zhu, Feilin; Zhong, Ping-An; Sun, Yimeng; Yeh, William W.-G.

2017-12-01

Multiple uncertainties exist in the optimal flood control decision-making process, presenting risks involving flood control decisions. This paper defines the main steps in optimal flood control decision making that constitute the Forecast-Optimization-Decision Making (FODM) chain. We propose a framework for supporting optimal flood control decision making under multiple uncertainties and evaluate risk propagation along the FODM chain from a holistic perspective. To deal with uncertainties, we employ stochastic models at each link of the FODM chain. We generate synthetic ensemble flood forecasts via the martingale model of forecast evolution. We then establish a multiobjective stochastic programming with recourse model for optimal flood control operation. The Pareto front under uncertainty is derived via the constraint method coupled with a two-step process. We propose a novel SMAA-TOPSIS model for stochastic multicriteria decision making. Then we propose the risk assessment model, the risk of decision-making errors and rank uncertainty degree to quantify the risk propagation process along the FODM chain. We conduct numerical experiments to investigate the effects of flood forecast uncertainty on optimal flood control decision making and risk propagation. We apply the proposed methodology to a flood control system in the Daduhe River basin in China. The results indicate that the proposed method can provide valuable risk information in each link of the FODM chain and enable risk-informed decisions with higher reliability.

Uncertainty and risk in wildland fire management: A review

Science.gov (United States)

Matthew P. Thompson; Dave E. Calkin

2011-01-01

Wildland fire management is subject to manifold sources of uncertainty. Beyond the unpredictability of wildfire behavior, uncertainty stems from inaccurate/missing data, limited resource value measures to guide prioritization across fires and resources at risk, and an incomplete scientific understanding of ecological response to fire, of fire behavior response to...

Quantile uncertainty and value-at-risk model risk.

Science.gov (United States)

Alexander, Carol; Sarabia, José María

2012-08-01

This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value-at-Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of "model risk" in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value-at-Risk model risk and compute the required regulatory capital add-on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value-at-Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks. © 2012 Society for Risk Analysis.

Low-dose extrapolation of radiation health risks: some implications of uncertainty for radiation protection at low doses.

Science.gov (United States)

Land, Charles E

2009-11-01

Ionizing radiation is a known and well-quantified human cancer risk factor, based on a remarkably consistent body of information from epidemiological studies of exposed populations. Typical examples of risk estimation include use of Japanese atomic bomb survivor data to estimate future risk from radiation-related cancer among American patients receiving multiple computed tomography scans, persons affected by radioactive fallout, or persons whose livelihoods involve some radiation exposure, such as x-ray technicians, interventional radiologists, or shipyard workers. Our estimates of radiation-related risk are uncertain, reflecting statistical variation and our imperfect understanding of crucial assumptions that must be made if we are to apply existing epidemiological data to particular situations. Fortunately, that uncertainty is also highly quantifiable, and can be presented concisely and transparently. Radiation protection is ultimately a political process that involves consent by stakeholders, a diverse group that includes people who might be expected to be risk-averse and concerned with plausible upper limits on risk (how bad could it be?), cost-averse and concerned with lower limits on risk (can you prove there is a nontrivial risk at current dose levels?), or combining both points of view. How radiation-related risk is viewed by individuals and population subgroups also depends very much on perception of related benefit, which might be (for example) medical, economic, altruistic, or nonexistent. The following presentation follows the lead of National Council on Radiation Protection and Measurements (NCRP) Commentary 14, NCRP Report 126, and later documents in treating radiation protection from the viewpoint of quantitative uncertainty analysis.

Uncertainty and sensitivity analysis of environmental and health risks of nanomaterials

DEFF Research Database (Denmark)

Grieger, Khara Deanne; Hansen, Steffen Foss; Baun, Anders

Scientific uncertainty about the environmental, health and safety issues (EHS) of nanomaterials has been recognized by scientists, regulators, NGO’s as well as industry as a possible barrier towards nanotechnology reaching its full potential. Historically, research efforts tend to be directed...... within EHS knowledge and research for the sake of science itself, it is also crucial that these research efforts are strategically focused and prioritized in order to assist regulators, industry, as well as scientists in the EHS challenges that face them in developing nanomaterials. Therefore, this study...... characterisation of engineered nanoparticles according to several reports. This includes establishing, developing and standardising reference materials, monitoring and detection equipment and estimating human and environmental exposure concentrations. These issues ultimately lead to significant challenges...

Construction of a case for expert judgement of uncertainty in early health effects models

International Nuclear Information System (INIS)

Grupa, J.

1997-11-01

The contribution of ECN to a joint study of the European Commission (EC) and the US Nuclear Regulatory Commission (NRC), in which the uncertainty in risks and consequences of severe accidents at nuclear power plants are evaluated, is described. The procedure used to obtain these uncertainties is called expert judgement. In a formal expert judgement procedure a panel of experts has provided quantitative information about the uncertainty in given observables: a quantity that describes an observation concerning the phenomenon of interest, in this paper the relation between dose and health effects, without information or assumptions about any model describing this phenomenon. The observables are defined in a case structure, a questionnaire provided to all experts. ECN has contributed to the selection of the experts for the early health effects panel, and provided assistance for drafting the case structure for this panel. This paper describes the radiological information provided by ECN and the analyses necessary for constructing the case structure. The deliverables of the expert elicitation are uncertainty distributions of the observables requested in the case structure. The results are intended to be unbiased, i.e. it should be applicable to any model describing the relation between dose and health effects. They will be published by the project team in a joint publication of the NRC and the EC. In this way the resulting uncertainty distributions are available for further work in the joint project and available to a more general public. 2 figs., 4 refs

A review of different perspectives on uncertainty and risk and an alternative modeling paradigm

International Nuclear Information System (INIS)

Samson, Sundeep; Reneke, James A.; Wiecek, Margaret M.

2009-01-01

The literature in economics, finance, operations research, engineering and in general mathematics is first reviewed on the subject of defining uncertainty and risk. The review goes back to 1901. Different perspectives on uncertainty and risk are examined and a new paradigm to model uncertainty and risk is proposed using relevant ideas from this study. This new paradigm is used to represent, aggregate and propagate uncertainty and interpret the resulting variability in a challenge problem developed by Oberkampf et al. [2004, Challenge problems: uncertainty in system response given uncertain parameters. Reliab Eng Syst Safety 2004; 85(1): 11-9]. The challenge problem is further extended into a decision problem that is treated within a multicriteria decision making framework to illustrate how the new paradigm yields optimal decisions under uncertainty. The accompanying risk is defined as the probability of an unsatisfactory system response quantified by a random function of the uncertainty

Uncertainty in exposure of underground miners to radon daughters and the effect of uncertainty on risk estimates

International Nuclear Information System (INIS)

1989-10-01

Studies of underground miners provide the principal basis for assessing the risk from radon daughter exposure. An important problem in all epidemiological studies of underground miners is the reliability of the estimates of the miners' exposures. This study examines the various sources of uncertainty in exposure estimation for the principal epidemiologic studies reported in the literature including the temporal and spatial variability of radon sources and, with the passage of time, changes to both mining methods and ventilation conditions. Uncertainties about work histories and the role of other hard rock mining experience are also discussed. The report also describes two statistical approaches, both based on Bayesian methods, by which the effects on the estimated risk coefficient of uncertainty in exposure (WLM) can be examined. One approach requires only an estimate of the cumulative WLM exposure of a group of miners, an estimate of the number of (excess) lung cancers potentially attributable to that exposure, and a specification of the uncertainty about the cumulative exposure of the group. The second approach is based on a linear regression model which incorporates errors (uncertainty) in the independent variable (WLM) and allows the dependent variable (cases) to be Poisson distributed. The method permits the calculation of marginal probability distributions for either slope (risk coefficient) or intercept. The regression model approach is applied to several published data sets from epidemiological studies of miners. Specific results are provided for each data set and apparent differences in risk coefficients are discussed. The studies of U.S. uranium miners, Ontario uranium miners and Czechoslovakian uranium miners are argued to provide the best basis for risk estimation at this time. In general terms, none of the analyses performed are inconsistent with a linear exposure-effect relation. Based on analyses of the overall miner groups, the most likely ranges

Uncertainty estimation and risk prediction in air quality

International Nuclear Information System (INIS)

Garaud, Damien

2011-01-01

This work is about uncertainty estimation and risk prediction in air quality. Firstly, we build a multi-model ensemble of air quality simulations which can take into account all uncertainty sources related to air quality modeling. Ensembles of photochemical simulations at continental and regional scales are automatically generated. Then, these ensemble are calibrated with a combinatorial optimization method. It selects a sub-ensemble which is representative of uncertainty or shows good resolution and reliability for probabilistic forecasting. This work shows that it is possible to estimate and forecast uncertainty fields related to ozone and nitrogen dioxide concentrations or to improve the reliability of threshold exceedance predictions. The approach is compared with Monte Carlo simulations, calibrated or not. The Monte Carlo approach appears to be less representative of the uncertainties than the multi-model approach. Finally, we quantify the observational error, the representativeness error and the modeling errors. The work is applied to the impact of thermal power plants, in order to quantify the uncertainty on the impact estimates. (author) [fr

The treatment of uncertainties in risk for regulatory decision making

International Nuclear Information System (INIS)

Baybutt, P.; Cox, D.C.; Denning, R.S.; Kurth, R.E.; Fraley, D.W.; Heaberlin, S.W.

1982-01-01

This paper describes research conducted in an ongoing program at Battelle to develop and adapt decision analysis methods for regulatory decision making. A general approach to risk-based decision making is discussed. The nature of uncertainties in risk assessment is described and methods for their inclusion in decision making are proposed. The use of decision analysis methods in regulatory decision making and the consideration of uncertainties is illustrated in a realistic case study

Managing uncertainty: a grounded theory of stigma in transgender health care encounters.

Science.gov (United States)

Poteat, Tonia; German, Danielle; Kerrigan, Deanna

2013-05-01

A growing body of literature supports stigma and discrimination as fundamental causes of health disparities. Stigma and discrimination experienced by transgender people have been associated with increased risk for depression, suicide, and HIV. Transgender stigma and discrimination experienced in health care influence transgender people's health care access and utilization. Thus, understanding how stigma and discrimination manifest and function in health care encounters is critical to addressing health disparities for transgender people. A qualitative, grounded theory approach was taken to this study of stigma in health care interactions. Between January and July 2011, fifty-five transgender people and twelve medical providers participated in one-time in-depth interviews about stigma, discrimination, and health care interactions between providers and transgender patients. Due to the social and institutional stigma against transgender people, their care is excluded from medical training. Therefore, providers approach medical encounters with transgender patients with ambivalence and uncertainty. Transgender people anticipate that providers will not know how to meet their needs. This uncertainty and ambivalence in the medical encounter upsets the normal balance of power in provider-patient relationships. Interpersonal stigma functions to reinforce the power and authority of the medical provider during these interactions. Functional theories of stigma posit that we hold stigmatizing attitudes because they serve specific psychological functions. However, these theories ignore how hierarchies of power in social relationships serve to maintain and reinforce inequalities. The findings of this study suggest that interpersonal stigma also functions to reinforce medical power and authority in the face of provider uncertainty. Within functional theories of stigma, it is important to acknowledge the role of power and to understand how stigmatizing attitudes function to maintain

Probabilistic human health risk assessment of degradation-related chemical mixtures in heterogeneous aquifers: Risk statistics, hot spots, and preferential channels

Science.gov (United States)

Henri, Christopher V.; Fernàndez-Garcia, Daniel; de Barros, Felipe P. J.

2015-06-01

The increasing presence of toxic chemicals released in the subsurface has led to a rapid growth of social concerns and the need to develop and employ models that can predict the impact of groundwater contamination on human health risk under uncertainty. Monitored natural attenuation is a common remediation action in many contamination cases. However, natural attenuation can lead to the production of daughter species of distinct toxicity that may pose challenges in pollution management strategies. The actual threat that these contaminants pose to human health depends on the interplay between the complex structure of the geological media and the toxicity of each pollutant byproduct. This work addresses human health risk for chemical mixtures resulting from the sequential degradation of a contaminant (such as a chlorinated solvent) under uncertainty through high-resolution three-dimensional numerical simulations. We systematically investigate the interaction between aquifer heterogeneity, flow connectivity, contaminant injection model, and chemical toxicity in the probabilistic characterization of health risk. We illustrate how chemical-specific travel times control the regime of the expected risk and its corresponding uncertainties. Results indicate conditions where preferential flow paths can favor the reduction of the overall risk of the chemical mixture. The overall human risk response to aquifer connectivity is shown to be nontrivial for multispecies transport. This nontriviality is a result of the interaction between aquifer heterogeneity and chemical toxicity. To quantify the joint effect of connectivity and toxicity in health risk, we propose a toxicity-based Damköhler number. Furthermore, we provide a statistical characterization in terms of low-order moments and the probability density function of the individual and total risks.

RISK CORRIDORS AND REINSURANCE IN HEALTH INSURANCE MARKETPLACES: Insurance for Insurers

OpenAIRE

LAYTON, TIMOTHY J.; MCGUIRE, THOMAS G.; SINAIKO, ANNA D.

2016-01-01

In order to encourage entry and lower prices, most regulated markets for health insurance include policies that seek to reduce the uncertainty faced by insurers. In addition to risk adjustment of premiums paid to plans, the Health Insurance Marketplaces established by the Affordable Care Act implement reinsurance and risk corridors. Reinsurance limits insurer costs associated with specific individuals, while risk corridors protect against aggregate losses. Both tighten the insurer's distribut...

Risk Management and Uncertainty in Large Complex Public Projects

DEFF Research Database (Denmark)

Neerup Themsen, Tim; Harty, Chris; Tryggestad, Kjell

Governmental actors worldwide are promoting risk management as a rational approach to man-age uncertainty and improve the abilities to deliver large complex projects according to budget, time plans, and pre-set project specifications: But what do we know about the effects of risk management...... on the abilities to meet such objectives? Using Callon’s (1998) twin notions of framing and overflowing we examine the implementation of risk management within the Dan-ish public sector and the effects this generated for the management of two large complex pro-jects. We show how the rational framing of risk...... management have generated unexpected costly outcomes such as: the undermining of the longer-term value and societal relevance of the built asset, the negligence of the wider range of uncertainties emerging during project processes, and constraining forms of knowledge. We also show how expert accountants play...

Modelling and propagation of uncertainties in the German Risk Study

International Nuclear Information System (INIS)

Hofer, E.; Krzykacz, B.

1982-01-01

Risk assessments are generally subject to uncertainty considerations. This is because of the various estimates that are involved. The paper points out those estimates in the so-called phase A of the German Risk Study, for which uncertainties were quantified. It explains the probabilistic models applied in the assessment to their impact on the findings of the study. Finally the resulting subjective confidence intervals of the study results are presented and their sensitivity to these probabilistic models is investigated

What risk assessments of genetically modified organisms can learn from institutional analyses of public health risks.

Science.gov (United States)

Rajan, S Ravi; Letourneau, Deborah K

2012-01-01

The risks of genetically modified organisms (GMOs) are evaluated traditionally by combining hazard identification and exposure estimates to provide decision support for regulatory agencies. We question the utility of the classical risk paradigm and discuss its evolution in GMO risk assessment. First, we consider the problem of uncertainty, by comparing risk assessment for environmental toxins in the public health domain with genetically modified organisms in the environment; we use the specific comparison of an insecticide to a transgenic, insecticidal food crop. Next, we examine normal accident theory (NAT) as a heuristic to consider runaway effects of GMOs, such as negative community level consequences of gene flow from transgenic, insecticidal crops. These examples illustrate how risk assessments are made more complex and contentious by both their inherent uncertainty and the inevitability of failure beyond expectation in complex systems. We emphasize the value of conducting decision-support research, embracing uncertainty, increasing transparency, and building interdisciplinary institutions that can address the complex interactions between ecosystems and society. In particular, we argue against black boxing risk analysis, and for a program to educate policy makers about uncertainty and complexity, so that eventually, decision making is not the burden that falls upon scientists but is assumed by the public at large.

What Risk Assessments of Genetically Modified Organisms Can Learn from Institutional Analyses of Public Health Risks

Directory of Open Access Journals (Sweden)

S. Ravi Rajan

2012-01-01

Full Text Available The risks of genetically modified organisms (GMOs are evaluated traditionally by combining hazard identification and exposure estimates to provide decision support for regulatory agencies. We question the utility of the classical risk paradigm and discuss its evolution in GMO risk assessment. First, we consider the problem of uncertainty, by comparing risk assessment for environmental toxins in the public health domain with genetically modified organisms in the environment; we use the specific comparison of an insecticide to a transgenic, insecticidal food crop. Next, we examine normal accident theory (NAT as a heuristic to consider runaway effects of GMOs, such as negative community level consequences of gene flow from transgenic, insecticidal crops. These examples illustrate how risk assessments are made more complex and contentious by both their inherent uncertainty and the inevitability of failure beyond expectation in complex systems. We emphasize the value of conducting decision-support research, embracing uncertainty, increasing transparency, and building interdisciplinary institutions that can address the complex interactions between ecosystems and society. In particular, we argue against black boxing risk analysis, and for a program to educate policy makers about uncertainty and complexity, so that eventually, decision making is not the burden that falls upon scientists but is assumed by the public at large.

Health risk assessment of exposure to ionizing radiation

International Nuclear Information System (INIS)

Ogata, Hiromitsu

2011-01-01

Risk assessment is an essential process for evaluating the human health effects of exposure to ionizing radiation and for determining acceptable levels of exposure. There are two major components of radiation risk assessment: a measure of exposure level and a measure of disease occurrence. For quantitative estimation of health risks, it is important to evaluate the association between exposure and disease occurrence using epidemiological or experimental data. In these approaches, statistical risk models are used particularly for estimating cancer risks related to exposure to low levels of radiation. This paper presents a summary of basic models and methods of risk assessment for studying exposure-risk relationships. Moreover, quantitative risk estimates are subject to several sources of uncertainty due to inherent limitations in risk assessment studies. This paper also discusses the limitations of radiation risk assessment. (author)

Operational Implementation of a Pc Uncertainty Construct for Conjunction Assessment Risk Analysis

Science.gov (United States)

Newman, Lauri K.; Hejduk, Matthew D.; Johnson, Lauren C.

2016-01-01

Earlier this year the NASA Conjunction Assessment and Risk Analysis (CARA) project presented the theoretical and algorithmic aspects of a method to include the uncertainties in the calculation inputs when computing the probability of collision (Pc) between two space objects, principally uncertainties in the covariances and the hard-body radius. The output of this calculation approach is to produce rather than a single Pc value an entire probability density function that will represent the range of possible Pc values given the uncertainties in the inputs and bring CA risk analysis methodologies more in line with modern risk management theory. The present study provides results from the exercise of this method against an extended dataset of satellite conjunctions in order to determine the effect of its use on the evaluation of conjunction assessment (CA) event risk posture. The effects are found to be considerable: a good number of events are downgraded from or upgraded to a serious risk designation on the basis of consideration of the Pc uncertainty. The findings counsel the integration of the developed methods into NASA CA operations.

Risk Analysis of Reservoir Flood Routing Calculation Based on Inflow Forecast Uncertainty

Directory of Open Access Journals (Sweden)

Binquan Li

2016-10-01

Full Text Available Possible risks in reservoir flood control and regulation cannot be objectively assessed by deterministic flood forecasts, resulting in the probability of reservoir failure. We demonstrated a risk analysis of reservoir flood routing calculation accounting for inflow forecast uncertainty in a sub-basin of Huaihe River, China. The Xinanjiang model was used to provide deterministic flood forecasts, and was combined with the Hydrologic Uncertainty Processor (HUP to quantify reservoir inflow uncertainty in the probability density function (PDF form. Furthermore, the PDFs of reservoir water level (RWL and the risk rate of RWL exceeding a defined safety control level could be obtained. Results suggested that the median forecast (50th percentiles of HUP showed better agreement with observed inflows than the Xinanjiang model did in terms of the performance measures of flood process, peak, and volume. In addition, most observations (77.2% were bracketed by the uncertainty band of 90% confidence interval, with some small exceptions of high flows. Results proved that this framework of risk analysis could provide not only the deterministic forecasts of inflow and RWL, but also the fundamental uncertainty information (e.g., 90% confidence band for the reservoir flood routing calculation.

Evaluating Sources of Risks in Large Engineering Projects: The Roles of Equivocality and Uncertainty

Directory of Open Access Journals (Sweden)

Leena Pekkinen

2015-11-01

Full Text Available Contemporary project risk management literature introduces uncertainty, i.e., the lack of information, as a fundamental basis of project risks. In this study the authors assert that equivocality, i.e., the existence of multiple and conflicting interpretations, can also serve as a basis of risks. With an in-depth empirical investigation of a large complex engineering project the authors identified risk sources having their bases in the situations where uncertainty or equivocality was the predominant attribute. The information processing theory proposes different managerial practices for risk management based on the sources of risks in uncertainty or equivocality.

Quantification of uncertainty in flood risk assessment for flood protection planning: a Bayesian approach

Science.gov (United States)

Dittes, Beatrice; Špačková, Olga; Ebrahimian, Negin; Kaiser, Maria; Rieger, Wolfgang; Disse, Markus; Straub, Daniel

2017-04-01

Flood risk estimates are subject to significant uncertainties, e.g. due to limited records of historic flood events, uncertainty in flood modeling, uncertain impact of climate change or uncertainty in the exposure and loss estimates. In traditional design of flood protection systems, these uncertainties are typically just accounted for implicitly, based on engineering judgment. In the AdaptRisk project, we develop a fully quantitative framework for planning of flood protection systems under current and future uncertainties using quantitative pre-posterior Bayesian decision analysis. In this contribution, we focus on the quantification of the uncertainties and study their relative influence on the flood risk estimate and on the planning of flood protection systems. The following uncertainty components are included using a Bayesian approach: 1) inherent and statistical (i.e. limited record length) uncertainty; 2) climate uncertainty that can be learned from an ensemble of GCM-RCM models; 3) estimates of climate uncertainty components not covered in 2), such as bias correction, incomplete ensemble, local specifics not captured by the GCM-RCM models; 4) uncertainty in the inundation modelling; 5) uncertainty in damage estimation. We also investigate how these uncertainties are possibly reduced in the future when new evidence - such as new climate models, observed extreme events, and socio-economic data - becomes available. Finally, we look into how this new evidence influences the risk assessment and effectivity of flood protection systems. We demonstrate our methodology for a pre-alpine catchment in southern Germany: the Mangfall catchment in Bavaria that includes the city of Rosenheim, which suffered significant losses during the 2013 flood event.

A risk assessment methodology for incorporating uncertainties using fuzzy concepts

International Nuclear Information System (INIS)

Cho, Hyo-Nam; Choi, Hyun-Ho; Kim, Yoon-Bae

2002-01-01

This paper proposes a new methodology for incorporating uncertainties using fuzzy concepts into conventional risk assessment frameworks. This paper also introduces new forms of fuzzy membership curves, designed to consider the uncertainty range that represents the degree of uncertainties involved in both probabilistic parameter estimates and subjective judgments, since it is often difficult or even impossible to precisely estimate the occurrence rate of an event in terms of one single crisp probability. It is to be noted that simple linguistic variables such as 'High/Low' and 'Good/Bad' have the limitations in quantifying the various risks inherent in construction projects, but only represent subjective mental cognition adequately. Therefore, in this paper, the statements that include some quantification with giving specific value or scale, such as 'Close to any value' or 'Higher/Lower than analyzed value', are used in order to get over the limitations. It may be stated that the proposed methodology will be very useful for the systematic and rational risk assessment of construction projects

Recent developments in health risks modeling techniques applied to hazardous waste site assessment and remediation

International Nuclear Information System (INIS)

Mendez, W.M. Jr.

1990-01-01

Remediation of hazardous an mixed waste sites is often driven by assessments of human health risks posed by the exposures to hazardous substances released from these sites. The methods used to assess potential health risk involve, either implicitly or explicitly, models for pollutant releases, transport, human exposure and intake, and for characterizing health effects. Because knowledge about pollutant fate transport processes at most waste sites is quite limited, and data cost are quite high, most of the models currently used to assess risk, and endorsed by regulatory agencies, are quite simple. The models employ many simplifying assumptions about pollutant fate and distribution in the environment about human pollutant intake, and toxicologic responses to pollutant exposures. An important consequence of data scarcity and model simplification is that risk estimates are quite uncertain and estimates of the magnitude uncertainty associated with risk assessment has been very difficult. A number of methods have been developed to address the issue of uncertainty in risk assessments in a manner that realistically reflects uncertainty in model specification and data limitations. These methods include definition of multiple exposure scenarios, sensitivity analyses, and explicit probabilistic modeling of uncertainty. Recent developments in this area will be discussed, along with their possible impacts on remediation programs, and remaining obstacles to their wider use and acceptance by the scientific and regulatory communities

Environmental impact and risk assessments and key factors contributing to the overall uncertainties

International Nuclear Information System (INIS)

Salbu, Brit

2016-01-01

There is a significant number of nuclear and radiological sources that have contributed, are still contributing, or have the potential to contribute to radioactive contamination of the environment in the future. To protect the environment from radioactive contamination, impact and risk assessments are performed prior to or during a release event, short or long term after deposition or prior and after implementation of countermeasures. When environmental impact and risks are assessed, however, a series of factors will contribute to the overall uncertainties. To provide environmental impact and risk assessments, information on processes, kinetics and a series of input variables is needed. Adding problems such as variability, questionable assumptions, gaps in knowledge, extrapolations and poor conceptual model structures, a series of factors are contributing to large and often unacceptable uncertainties in impact and risk assessments. Information on the source term and the release scenario is an essential starting point in impact and risk models; the source determines activity concentrations and atom ratios of radionuclides released, while the release scenario determine the physico-chemical forms of released radionuclides such as particle size distribution, structure and density. Releases will most often contain other contaminants such as metals, and due to interactions, contaminated sites should be assessed as a multiple stressor scenario. Following deposition, a series of stressors, interactions and processes will influence the ecosystem transfer of radionuclide species and thereby influence biological uptake (toxicokinetics) and responses (toxicodynamics) in exposed organisms. Due to the variety of biological species, extrapolation is frequently needed to fill gaps in knowledge e.g., from effects to no effects, from effects in one organism to others, from one stressor to mixtures. Most toxtests are, however, performed as short term exposure of adult organisms

Risk in technical and scientific studies: general introduction to uncertainty management and the concept of risk

International Nuclear Information System (INIS)

Apostolakis, G.E.

2004-01-01

George Apostolakis (MIT) presented an introduction to the concept of risk and uncertainty management and their use in technical and scientific studies. He noted that Quantitative Risk Assessment (QRA) provides support to the overall treatment of a system as an integrated socio-technical system. Specifically, QRA aims to answer the questions: - What can go wrong (e.g., accident sequences or scenarios)? - How likely are these sequences or scenarios? - What are the consequences of these sequences or scenarios? The Quantitative Risk Assessment deals with two major types of uncertainty. An assessment requires a 'model of the world', and this preferably would be a deterministic model based on underlying processes. In practice, there are uncertainties in this model of the world relating to variability or randomness that cannot be accounted for directly in a deterministic model and that may require a probabilistic or aleatory model. Both deterministic and aleatory models of the world have assumptions and parameters, and there are 'state-of-knowledge' or epistemic uncertainties associated with these. Sensitivity studies or eliciting expert opinion can be used to address the uncertainties in assumptions, and the level of confidence in parameter values can be characterised using probability distributions (pdfs). Overall, the distinction between aleatory and epistemic uncertainties is not always clear, and both can be treated mathematically in the same way. Lessons on safety assessments that can be learnt from experience at nuclear power plants are that beliefs about what is important can be wrong if a risk assessment is not performed. Also, precautionary approaches are not always conservative if failure modes are not identified. Nevertheless, it is important to recognize that uncertainties will remain despite a quantitative risk assessment: e.g., is the scenario list complete, are the models accepted as reasonable, and are parameter probability distributions representative of

Sensing risk, fearing uncertainty: Systems science approach to change.

Directory of Open Access Journals (Sweden)

Ivo P Janecka

2014-03-01

Full Text Available BackgroundMedicine devotes its primary focus to understanding change, from cells to network relationships; observations of non-linearity are inescapable. Recent events provide extraordinary examples of major non-linear surprises within the societal system: human genome-from anticipated 100,000+ genes to only 20,000+; junk DNA-initially ignored but now proven to control genetic processes; economic reversals-bursting of bubbles in technology, housing, finance; foreign wars; relentless rise in obesity, neurodegenerative diseases.There are two attributes of systems science that are especially relevant to this research: One- it offers a method for creating a structural context with a guiding path to pragmatic knowledge; and, two- it gives pre-eminence to sensory input capable to register, evaluate, and react to change. Material / MethodPublic domain records of change, during the last fifty years, have been studied in the context of systems science, the dynamic systems model, and various cycles. Results / Conclusions Change is dynamic, ever-present, never isolated, and of variable impact; it reflects innumerable relationships among contextual systems; change can be perceived as risk or uncertainty depending upon how the assessment is made; risk is quantifiable by sensory input and generates a degree of rational optimism; uncertainty is not quantifiable and evokes fear; trust is key to sharing risk; the measurable financial credit can be a proxy for societal trust; expanding credit dilutes trust; when a credit bubble bursts, so will trust; absence of trust paralyzes systems’ relationships leading to disorganized complexity which prevents value creation and heightens the probability of random events; disappearance of value, accompanied by chaos, threatens all systems.From personal health to economic sustainability and collective rationality, most examined components of the societal system were found not to be optimized and trust was not in evidence.

Probabilistic accident consequence uncertainty analysis -- Early health effects uncertainty assessment. Volume 2: Appendices

Energy Technology Data Exchange (ETDEWEB)

Haskin, F.E. [Univ. of New Mexico, Albuquerque, NM (United States); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)

1997-12-01

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA early health effects models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the panel on early health effects, (4) short biographies of the experts, and (5) the aggregated results of their responses.

The characterisation and evaluation of uncertainty in probabilistic risk analysis

International Nuclear Information System (INIS)

Parry, G.W.; Winter, P.W.

1980-10-01

The sources of uncertainty in probabilistic risk analysis are discussed using the event/fault tree methodology as an example. The role of statistics in quantifying these uncertainties is investigated. A class of uncertainties is identified which is, at present, unquantifiable, using either classical or Bayesian statistics. It is argued that Bayesian statistics is the more appropriate vehicle for the probabilistic analysis of rare events and a short review is given with some discussion on the representation of ignorance. (author)

Sensitivity to Uncertainty in Asteroid Impact Risk Assessment

Science.gov (United States)

Mathias, D.; Wheeler, L.; Prabhu, D. K.; Aftosmis, M.; Dotson, J.; Robertson, D. K.

2015-12-01

The Engineering Risk Assessment (ERA) team at NASA Ames Research Center is developing a physics-based impact risk model for probabilistically assessing threats from potential asteroid impacts on Earth. The model integrates probabilistic sampling of asteroid parameter ranges with physics-based analyses of entry, breakup, and impact to estimate damage areas and casualties from various impact scenarios. Assessing these threats is a highly coupled, dynamic problem involving significant uncertainties in the range of expected asteroid characteristics, how those characteristics may affect the level of damage, and the fidelity of various modeling approaches and assumptions. The presented model is used to explore the sensitivity of impact risk estimates to these uncertainties in order to gain insight into what additional data or modeling refinements are most important for producing effective, meaningful risk assessments. In the extreme cases of very small or very large impacts, the results are generally insensitive to many of the characterization and modeling assumptions. However, the nature of the sensitivity can change across moderate-sized impacts. Results will focus on the value of additional information in this critical, mid-size range, and how this additional data can support more robust mitigation decisions.

Nonlinear Uncertainty Propagation of Satellite State Error for Tracking and Conjunction Risk Assessment

Science.gov (United States)

2017-12-18

AFRL-RV-PS- AFRL-RV-PS- TR-2017-0177 TR-2017-0177 NONLINEAR UNCERTAINTY PROPAGATION OF SATELLITE STATE ERROR FOR TRACKING AND CONJUNCTION RISK...Uncertainty Propagation of Satellite State Error for Tracking and Conjunction Risk Assessment 5a. CONTRACT NUMBER FA9453-16-1-0084 5b. GRANT NUMBER...prediction and satellite conjunction analysis. Statistical approach utilizes novel methods to build better uncertainty state characterization in the context

Risk Worth Taking - Entrepreneurial Behaviour When Faced with Risk and Uncertainty

DEFF Research Database (Denmark)

Zichella, Giulio

theory suggests differences in risk taking due to individual characteristics. However, entrepreneurship theory did not provide empirical support for such differences. Using data from a laboratory experiment with simple money games, we observe how individuals from two different groups (entrepreneurial......-oriented, non-entrepreneurial-oriented) react to different degrees of risk and uncertainty when real monetary incentives are involved in each decision. The analysis reveals significant differences between entrepreneurial and non-entrepreneurial-oriented individuals in their decision making. In particular...

Climate change, uncertainty and investment in flood risk reduction

OpenAIRE

Pol, van der, T.D.

2015-01-01

Economic analysis of flood risk management strategies has become more complex due to climate change. This thesis investigates the impact of climate change on investment in flood risk reduction, and applies optimisation methods to support identification of optimal flood risk management strategies. Chapter 2 provides an overview of cost-benefit analysis (CBA) of flood risk management strategies under climate change uncertainty and new information. CBA is applied to determine optimal dike height...

Divide and Conquer: A Valid Approach for Risk Assessment and Decision Making under Uncertainty for Groundwater-Related Diseases

Science.gov (United States)

Sanchez-Vila, X.; de Barros, F.; Bolster, D.; Nowak, W.

2010-12-01

Assessing the potential risk of hydro(geo)logical supply systems to human population is an interdisciplinary field. It relies on the expertise in fields as distant as hydrogeology, medicine, or anthropology, and needs powerful translation concepts to provide decision support and policy making. Reliable health risk estimates need to account for the uncertainties in hydrological, physiological and human behavioral parameters. We propose the use of fault trees to address the task of probabilistic risk analysis (PRA) and to support related management decisions. Fault trees allow decomposing the assessment of health risk into individual manageable modules, thus tackling a complex system by a structural “Divide and Conquer” approach. The complexity within each module can be chosen individually according to data availability, parsimony, relative importance and stage of analysis. The separation in modules allows for a true inter- and multi-disciplinary approach. This presentation highlights the three novel features of our work: (1) we define failure in terms of risk being above a threshold value, whereas previous studies used auxiliary events such as exceedance of critical concentration levels, (2) we plot an integrated fault tree that handles uncertainty in both hydrological and health components in a unified way, and (3) we introduce a new form of stochastic fault tree that allows to weaken the assumption of independent subsystems that is required by a classical fault tree approach. We illustrate our concept in a simple groundwater-related setting.

Can Bayesian Belief Networks help tackling conceptual model uncertainties in contaminated site risk assessment?

DEFF Research Database (Denmark)

Troldborg, Mads; Thomsen, Nanna Isbak; McKnight, Ursula S.

different conceptual models may describe the same contaminated site equally well. In many cases, conceptual model uncertainty has been shown to be one of the dominant sources for uncertainty and is therefore essential to account for when quantifying uncertainties in risk assessments. We present here......A key component in risk assessment of contaminated sites is the formulation of a conceptual site model. The conceptual model is a simplified representation of reality and forms the basis for the mathematical modelling of contaminant fate and transport at the site. A conceptual model should...... a Bayesian Belief Network (BBN) approach for evaluating the uncertainty in risk assessment of groundwater contamination from contaminated sites. The approach accounts for conceptual model uncertainty by considering multiple conceptual models, each of which represents an alternative interpretation of the site...

On the influence of uncertainties in estimating risk aversion and working interest

International Nuclear Information System (INIS)

MacKay, J.A.; Lerche, I.

1996-01-01

The influence of uncertainties in costs, value, success probability, risk tolerance and mandated working interest are evaluated for their impact on assessing probable ranges of uncertainty on risk adjusted value, RAV, using different models. The relative importance of different factors in contributing to the uncertainty in RAV is analyzed, as is the influence of different probability distributions for the intrinsic variables entering the RAV model formulae. Numerical illustrations indicate how the RAV probabilities depend not only on the model functions (Cozzolino, hyperbolic tangent) used to provide RAV estimates, but also on the intrinsic shapes of the probability distributions from which are drawn input parameter values for Monte Carlo simulations. In addition, a mandated range of working interest can be addressed as an extra variable contributing to the probabilistic range of RAV; while negative RAV values for high-cost project can be used to assess the probable buy-out amount one should be prepared to pay depending on corporate risk philosophy. Also, the procedures illustrate how the relative contributions of scientific factors influence uncertainty of reserve assessments, allowing one to determine where to concentrate effort to improve the ranges of uncertainty. (Author)

A new approach to reduce uncertainties in space radiation cancer risk predictions.

Directory of Open Access Journals (Sweden)

Francis A Cucinotta

Full Text Available The prediction of space radiation induced cancer risk carries large uncertainties with two of the largest uncertainties being radiation quality and dose-rate effects. In risk models the ratio of the quality factor (QF to the dose and dose-rate reduction effectiveness factor (DDREF parameter is used to scale organ doses for cosmic ray proton and high charge and energy (HZE particles to a hazard rate for γ-rays derived from human epidemiology data. In previous work, particle track structure concepts were used to formulate a space radiation QF function that is dependent on particle charge number Z, and kinetic energy per atomic mass unit, E. QF uncertainties where represented by subjective probability distribution functions (PDF for the three QF parameters that described its maximum value and shape parameters for Z and E dependences. Here I report on an analysis of a maximum QF parameter and its uncertainty using mouse tumor induction data. Because experimental data for risks at low doses of γ-rays are highly uncertain which impacts estimates of maximum values of relative biological effectiveness (RBEmax, I developed an alternate QF model, denoted QFγAcute where QFs are defined relative to higher acute γ-ray doses (0.5 to 3 Gy. The alternate model reduces the dependence of risk projections on the DDREF, however a DDREF is still needed for risk estimates for high-energy protons and other primary or secondary sparsely ionizing space radiation components. Risk projections (upper confidence levels (CL for space missions show a reduction of about 40% (CL∼50% using the QFγAcute model compared the QFs based on RBEmax and about 25% (CL∼35% compared to previous estimates. In addition, I discuss how a possible qualitative difference leading to increased tumor lethality for HZE particles compared to low LET radiation and background tumors remains a large uncertainty in risk estimates.

Risk, rationality, and regret: responding to the uncertainty of childhood food anaphylaxis.

Science.gov (United States)

Hu, W; Kerridge, I; Kemp, A

2005-06-01

Risk and uncertainty are unavoidable in clinical medicine. In the case of childhood food allergy, the dysphoric experience of uncertainty is heightened by the perception of unpredictable danger to young children. Medicine has tended to respond to uncertainty with forms of rational decision making. Rationality cannot, however, resolve uncertainty and provides an insufficient account of risk. This paper compares the medical and parental accounts of two peanut allergic toddlers to highlight the value of emotions in decision making. One emotion in particular, regret, assists in explaining the actions taken to prevent allergic reactions, given the diffuse nature of responsibility for children. In this light, the assumption that doctors make rational judgments while patients have emotion led preferences is a false dichotomy. Reconciling medical and lay accounts requires acknowledgement of the interrelationship between the rational and the emotional, and may lead to more appropriate clinical decision making under conditions of uncertainty.

Uncertainty assessment of urban pluvial flood risk in a context of climate change adaptation decision making

DEFF Research Database (Denmark)

Arnbjerg-Nielsen, Karsten; Zhou, Qianqian

2014-01-01

uncertainty analysis, which can assess and quantify the overall uncertainty in relation to climate change adaptation to urban flash floods. The analysis is based on an uncertainty cascade that by means of Monte Carlo simulations of flood risk assessments incorporates climate change impacts as a key driver......There has been a significant increase in climatic extremes in many regions. In Central and Northern Europe, this has led to more frequent and more severe floods. Along with improved flood modelling technologies this has enabled development of economic assessment of climate change adaptation...... to increasing urban flood risk. Assessment of adaptation strategies often requires a comprehensive risk-based economic analysis of current risk, drivers of change of risk over time, and measures to reduce the risk. However, such studies are often associated with large uncertainties. The uncertainties arise from...

Integrated Risk-Capability Analysis under Deep Uncertainty : An ESDMA Approach

NARCIS (Netherlands)

Pruyt, E.; Kwakkel, J.H.

2012-01-01

Integrated risk-capability analysis methodologies for dealing with increasing degrees of complexity and deep uncertainty are urgently needed in an ever more complex and uncertain world. Although scenario approaches, risk assessment methods, and capability analysis methods are used, few organizations

Priority setting in health care: disentangling risk aversion from inequality aversion.

Science.gov (United States)

Echazu, Luciana; Nocetti, Diego

2013-06-01

In this paper, we introduce a tractable social welfare function that is rich enough to disentangle attitudes towards risk in health outcomes from attitudes towards health inequalities across individuals. Given this preference specification, we evaluate how the introduction of uncertainty over the severity of illness and over the effectiveness of treatments affects the optimal allocation of healthcare resources. We show that the way in which uncertainty affects the optimal allocation within our proposed specification may differ sharply from that in the standard expected utility framework. Copyright © 2012 John Wiley & Sons, Ltd.

Learning Risk-Taking and Coping with Uncertainty through Experiential, Team-Based Entrepreneurship Education

Science.gov (United States)

Arpiainen, Riitta-Liisa; Kurczewska, Agnieszka

2017-01-01

This empirical study investigates how students' perceptions of risk-taking and coping with uncertainty change while they are exposed to experience-based entrepreneurship education. The aim of the study is twofold. First, the authors set out to identify the dynamics of entrepreneurial thinking among students experiencing risk and uncertainty while…

Hydroclimatic risks and uncertainty in the global power sector

Science.gov (United States)

Gidden, Matthew; Byers, Edward; Greve, Peter; Kahil, Taher; Parkinson, Simon; Raptis, Catherine; Rogelj, Joeri; Satoh, Yusuke; van Vliet, Michelle; Wada, Yoshide; Krey, Volker; Langan, Simon; Riahi, Keywan

2017-04-01

Approximately 80% of the world's electricity supply depends on reliable water resources. Thermoelectric and hydropower plants have been impacted by low flows and floods in recent years, notably in the US, Brazil, France, and China, amongst other countries. The dependence on reliable flows imputes a large vulnerability to the electricity supply system due to hydrological variability and the impacts of climate change. Using an updated dataset of global electricity capacity with global climate and hydrological data from the ISI-MIP project, we present an overview analysis of power sector vulnerability to hydroclimatic risks, including low river flows and peak flows. We show how electricity generation in individual countries and transboundary river basins can be impacted, helping decision-makers identify key at-risk geographical regions. Furthermore, our use of a multi-model ensemble of climate and hydrological models allows us to quantify the uncertainty of projected impacts, such that basin-level risks and uncertainty can be compared.

Improving default risk prediction using Bayesian model uncertainty techniques.

Science.gov (United States)

Kazemi, Reza; Mosleh, Ali

2012-11-01

Credit risk is the potential exposure of a creditor to an obligor's failure or refusal to repay the debt in principal or interest. The potential of exposure is measured in terms of probability of default. Many models have been developed to estimate credit risk, with rating agencies dating back to the 19th century. They provide their assessment of probability of default and transition probabilities of various firms in their annual reports. Regulatory capital requirements for credit risk outlined by the Basel Committee on Banking Supervision have made it essential for banks and financial institutions to develop sophisticated models in an attempt to measure credit risk with higher accuracy. The Bayesian framework proposed in this article uses the techniques developed in physical sciences and engineering for dealing with model uncertainty and expert accuracy to obtain improved estimates of credit risk and associated uncertainties. The approach uses estimates from one or more rating agencies and incorporates their historical accuracy (past performance data) in estimating future default risk and transition probabilities. Several examples demonstrate that the proposed methodology can assess default probability with accuracy exceeding the estimations of all the individual models. Moreover, the methodology accounts for potentially significant departures from "nominal predictions" due to "upsetting events" such as the 2008 global banking crisis. © 2012 Society for Risk Analysis.

Reliability, Resilience, and Vulnerability criteria for the evaluation of Human Health Risks

Science.gov (United States)

Rodak, C. M.; Silliman, S. E.; Bolster, D.

2011-12-01

Understanding the impact of water quality on the health of a general population is challenging due high degrees of uncertainty and variability in hydrological, toxicological and human aspects of the system. Assessment of the impact of changes in water quality of a public water supply is critical to management of that water supply. We propose the use of three different system evaluation criteria: Reliability, Resilience and Vulnerability (RRV) as a tool for assessing the impact of uncertainty in the arrival of contaminant mass through time with respect to human health risks on a variable population. These criteria were first introduced to the water resources community by Hashimoto et al (1982). Most simply one can understand these criteria as the following: Reliability is the likelihood of the system being in a state of success; Resilience is the probability that the system will return to a state of success at t+1 if it is in failure at time step t, and Vulnerability is the severity of failure, which here is defined as the maximum health risk. These concepts are applied to a theoretical example where the water quality at a water supply well varies over time: health impact is considered based on sliding, 30-year windows of exposure to water derived from the well. We apply the methodology, in terms of uncertainty in water quality deviations, to eight simulated breakthrough curves of a contaminant at the well: each curve represents equal mass of contaminant arriving at the well over a 70-year lifetime of the well, but different mass distributions over time. These curves are used to investigate the impact of uncertainty in the distribution through time of the contaminant mass at the well, as well as the initial arrival of the contaminant over the 70-year lifetime of the well. In addition to extending the health risk through time with uncertainty in mass distribution, we incorporate variability in the human population to examine the evolution of the three criteria within

Uncertainty and Decision Making: Examples of Some Possible New Frontiers

Science.gov (United States)

Silliman, S. E.; Rodak, C. M.; Bolster, D.; Saavedra, K.; Evans, W.

2011-12-01

The concept of decision making under uncertainty for groundwater systems represents an exciting area of research and application. In this presentation, three examples are briefly introduced which represent possible new applications of risk and decision making under uncertainty. In the most classic of the three examples, a probabilistic strategy is considered within the context of management / assessment of proposed changes in land-use in the vicinity of a public water-supply well. Focused on health-risk related to contamination at the well, the analysis includes uncertainties in source location / strength, groundwater flow / transport, human exposure, and human health risk. The second example involves application of Probabilistic Risk Assessment (PRA) to the evaluation of development projects in rural regions of developing countries. PRA combined with Fault Tree Analysis provides a structure for analysis of the impact of data uncertainties on the estimation of health risk resulting from failure of multiple components of new water-resource systems. The third is an extension of the concept of "risk compensation" to the analysis of potential long-term risk associated with new water resource projects. Of direct interest here is the appearance of new risk to the public, such as introduction of new disease pathways or new sources of contamination of the source waters. As a result of limitations on conceptual model and/or limitations on data, this type of risk is often difficult to identify / assess, and is therefore not commonly included in formal decision-making efforts: it may however seriously impact the long-term net benefit of a water resource project. The goal of presenting these three examples is to illustrate the breadth of possible application of uncertainty / risk analyses beyond the more classic applications to groundwater remediation and protection.

[Health care economics, uncertainty and physician-induced demand].

Science.gov (United States)

Domenighetti, G; Casabianca, A

1995-10-21

The health care market is a very particular one that is mainly characterized by the absence of information and transparency at every level, particularly between the physician-supplier and the patient-consumer. On this market it is up to the physician to evaluate and define the patient's needs and to decide which are the most effective goods for the patient. The determinants of medical prescription are not only related to the health status of the patient, but also to the payment system (fee for services, salary), to physician density, professional uncertainty, the role and status of the physician in his profession, the legal framework which rules the medical profession, and also the information level of the patient. Agency relationship and professional uncertainty are the most relevant determinants of supplier-induced demand. Professional uncertainty inherent in the practice of a stochastic art such as medicine will "always" give an ethical justification for supplier-induced demand or for the pursuit of "maximal" and/or "defensive" care when market competition is perceived by the physician as a threat to his/her income or employment. Time is ripe for consumers and physicians empowerment in the aim to promote better self-management of health and more thoughtful access to care (for consumers) and more evidences based medicine for physicians.

Health and environmental risks of energy systems

International Nuclear Information System (INIS)

Hamilton, L.D.

1984-01-01

The paper gives four examples of health risk assessments of energy systems: (1) Comparative risk assessment of the health effects of the coal and nuclear fuel cycles. Estimates differ from previous values chiefly by inclusion of ranges of uncertainty, but some coal-cycle numbers were re-estimated. Upper-boundary public disease risks of air pollution from coal-fired plants dominate. Reactors probably account for most of the potential effect of major nuclear accidents. Accidental death rates in electricity generation are low for reactors and higher for coal. (2) Upper-boundary air pollution health risks of existing fossil-fuel-based energy technologies in the United States of America. Preliminary mortality estimates were obtained combining potential impacts of three index pollutants - SO 4 , NO 2 , and CO - as independent measures of risk. Four fuel cycle trajectories leading to three end-uses were analysed. (3) Health risks of acid deposition and other transported air pollutants, carried out as part of an assessment of the US Congress Office of Technology Assessment (OTA) 'Acid Rain and Transported Air Pollutants. (4) Health effects of uranium mill tailings piles. Mortality risk is estimated to be minuscule (8.7x10 -9 average individual lifetime cancer risk from a model mill, compared with 9.5x10 -4 for background radiation). Methods that sum risks over the indefinite future are shown to be unrealistic. As a final example of risk analysis, the cost-effectiveness analysis for proposed EPA standards for radionuclides is shown to be deficient by an analysis concluding that the cost per potential cancer avoided could range from US $70 million to US $140 billion

Information Uncertainty to Compare Qualitative Reasoning Security Risk Assessment Results

Energy Technology Data Exchange (ETDEWEB)

Chavez, Gregory M [Los Alamos National Laboratory; Key, Brian P [Los Alamos National Laboratory; Zerkle, David K [Los Alamos National Laboratory; Shevitz, Daniel W [Los Alamos National Laboratory

2009-01-01

The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. Associated with each predicted risk reasoning result is a quantifiable amount of information uncertainty which can be measured and used to compare the results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. The measured quantities of conflict and non-specificity can ultimately be used to compare qualitative reasoning results which are important in triage studies and ultimately resource allocation. Straight forward extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.

Evaluation of risk impact of changes to Completion Times addressing model and parameter uncertainties

International Nuclear Information System (INIS)

Martorell, S.; Martón, I.; Villamizar, M.; Sánchez, A.I.; Carlos, S.

2014-01-01

This paper presents an approach and an example of application for the evaluation of risk impact of changes to Completion Times within the License Basis of a Nuclear Power Plant based on the use of the Probabilistic Risk Assessment addressing identification, treatment and analysis of uncertainties in an integrated manner. It allows full development of a three tired approach (Tier 1–3) following the principles of the risk-informed decision-making accounting for uncertainties as proposed by many regulators. Completion Time is the maximum outage time a safety related equipment is allowed to be down, e.g. for corrective maintenance, which is established within the Limiting Conditions for Operation included into Technical Specifications for operation of a Nuclear Power Plant. The case study focuses on a Completion Time change of the Accumulators System of a Nuclear Power Plant using a level 1 PRA. It focuses on several sources of model and parameter uncertainties. The results obtained show the risk impact of the proposed CT change including both types of epistemic uncertainties is small as compared with current safety goals of concern to Tier 1. However, what concerns to Tier 2 and 3, the results obtained show how the use of some traditional and uncertainty importance measures helps in identifying high risky configurations that should be avoided in NPP technical specifications no matter the duration of CT (Tier 2), and other configurations that could take part of a configuration risk management program (Tier 3). - Highlights: • New approach for evaluation of risk impact of changes to Completion Times. • Integrated treatment and analysis of model and parameter uncertainties. • PSA based application to support risk-informed decision-making. • Measures of importance for identification of risky configurations. • Management of important safety issues to accomplish safety goals

[Status Quo, Uncertainties and Trends Analysis of Environmental Risk Assessment for PFASs].

Science.gov (United States)

Hao, Xue-wen; Li, Li; Wang, Jie; Cao, Yan; Liu, Jian-guo

2015-08-01

This study systematically combed the definition and change of terms, category and application of perfluoroalkyl and polyfluoroalkyl substances (PFASs) in international academic, focusing on the environmental risk and exposure assessment of PFASs, to comprehensively analyze the current status, uncertainties and trends of PFASs' environmental risk assessment. Overall, the risk assessment of PFASs is facing a complicated situation involving complex substance pedigrees, various types, complex derivative relations, confidential business information and risk uncertainties. Although the environmental risk of long-chain PFASs has been widely recognized, the short-chain PFASs and short-chain fluorotelomers as their alternatives still have many research gaps and uncertainties in environmental hazards, environmental fate and exposure risk. The scope of risk control of PFASs in the international community is still worth discussing. Due to trade secrets and market competition, the chemical structure and risk information of PFASs' alternatives are generally lack of openness and transparency. The environmental risk of most fluorinated and non-fluorinated alternatives is not clear. In total, the international research on PFASs risk assessment gradually transfer from long-chain perfluoroalkyl acids (PFAAs) represented by perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) to short-chain PFAAs, and then extends to other PFASs. The main problems to be solved urgently and researched continuously are: the environmental hazardous assessment indexes, such as bioaccumulation and environmental migration, optimization method, the environmental release and multimedia environmental fate of short-chain PFASs; the environmental fate of neutral PFASs and the transformation and contribution as precursors of short-chain PFASs; the risk identification and assessment of fluorinated and non-fluorinated alternatives of PFASs.

Management of uncertainties and the role of risk in Andra programme

International Nuclear Information System (INIS)

Grevoz, A.

2004-01-01

This paper aims at presenting some aspects of the management of uncertainties in the programmes of Andra for the study of a deep geological repository for high level, long-lived wastes. After presenting very briefly the context of risk-management in the French safety rules, it will discuss how Andra has attempted to link the notions of uncertainties and risk in its 'Dossier 2001' for the clay medium, how this could be made compatible with a deterministic safety approach, what feedback it got from this first exercise, and what are the perspectives for future work. (author)

Environmental impact and risk assessments and key factors contributing to the overall uncertainties.

Science.gov (United States)

Salbu, Brit

2016-01-01

There is a significant number of nuclear and radiological sources that have contributed, are still contributing, or have the potential to contribute to radioactive contamination of the environment in the future. To protect the environment from radioactive contamination, impact and risk assessments are performed prior to or during a release event, short or long term after deposition or prior and after implementation of countermeasures. When environmental impact and risks are assessed, however, a series of factors will contribute to the overall uncertainties. To provide environmental impact and risk assessments, information on processes, kinetics and a series of input variables is needed. Adding problems such as variability, questionable assumptions, gaps in knowledge, extrapolations and poor conceptual model structures, a series of factors are contributing to large and often unacceptable uncertainties in impact and risk assessments. Information on the source term and the release scenario is an essential starting point in impact and risk models; the source determines activity concentrations and atom ratios of radionuclides released, while the release scenario determine the physico-chemical forms of released radionuclides such as particle size distribution, structure and density. Releases will most often contain other contaminants such as metals, and due to interactions, contaminated sites should be assessed as a multiple stressor scenario. Following deposition, a series of stressors, interactions and processes will influence the ecosystem transfer of radionuclide species and thereby influence biological uptake (toxicokinetics) and responses (toxicodynamics) in exposed organisms. Due to the variety of biological species, extrapolation is frequently needed to fill gaps in knowledge e.g., from effects to no effects, from effects in one organism to others, from one stressor to mixtures. Most toxtests are, however, performed as short term exposure of adult organisms

Health care consumerism: incentives, behavior change and uncertainties.

Science.gov (United States)

Domaszewicz, Sander; Havlin, Linda; Connolly, Susan

2010-01-01

Employers affected by the recession's 2009 peak must press for cost containment in 2010, especially in health care benefits. Encouraging employee consumerism--through consumer-directed health plans and other strategies--can be enhanced by incentives, but federal efforts at health care reform add some element of uncertainty to the consumer-directed solution. This article provides some lessons to guide the course of action for employers considering implementing a consumerist approach to improve employee health and control the cost trend.

An evaluation of the treatment of risk and uncertainties in the IPCC reports on climate change.

Science.gov (United States)

Aven, Terje; Renn, Ortwin

2015-04-01

Few global threats rival global climate change in scale and potential consequence. The principal international authority assessing climate risk is the Intergovernmental Panel on Climate Change (IPCC). Through repeated assessments the IPCC has devoted considerable effort and interdisciplinary competence to articulating a common characterization of climate risk and uncertainties. We have reviewed the assessment and its foundation for the Fifth Assessment Reports published in 2013 and 2014, in particular the guidance note for lead authors of the fifth IPCC assessment report on consistent treatment of uncertainties. Our analysis shows that the work carried out by the ICPP is short of providing a theoretically and conceptually convincing foundation on the treatment of risk and uncertainties. The main reasons for our assessment are: (i) the concept of risk is given a too narrow definition (a function of consequences and probability/likelihood); and (ii) the reports lack precision in delineating their concepts and methods. The goal of this article is to contribute to improving the handling of uncertainty and risk in future IPCC studies, thereby obtaining a more theoretically substantiated characterization as well as enhanced scientific quality for risk analysis in this area. Several suggestions for how to improve the risk and uncertainty treatment are provided. © 2014 Society for Risk Analysis.

Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: A comparative study

International Nuclear Information System (INIS)

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2016-01-01

The uncertainties of renewable energy have brought great challenges to power system commitment, dispatches and reserve requirement. This paper presents a comparative study on integration of renewable generation uncertainties into SCUC (stochastic security-constrained unit commitment) considering reserve and risk. Renewable forecast uncertainties are captured by a list of PIs (prediction intervals). A new scenario generation method is proposed to generate scenarios from these PIs. Different system uncertainties are considered as scenarios in the stochastic SCUC problem formulation. Two comparative simulations with single (E1: wind only) and multiple sources of uncertainty (E2: load, wind, solar and generation outages) are investigated. Five deterministic and four stochastic case studies are performed. Different generation costs, reserve strategies and associated risks are compared under various scenarios. Demonstrated results indicate the overall costs of E2 is lower than E1 due to penetration of solar power and the associated risk in deterministic cases of E2 is higher than E1. It implies the superimposed effect of uncertainties during uncertainty integration. The results also demonstrate that power systems run a higher level of risk during peak load hours, and that stochastic models are more robust than deterministic ones. - Highlights: • An extensive comparative study for renewable integration is presented. • A novel scenario generation method is proposed. • Wind and solar uncertainties are represented by a list of prediction intervals. • Unit commitment and dispatch costs are discussed considering reserve and risk.

Deep Uncertainty Surrounding Coastal Flood Risk Projections: A Case Study for New Orleans

Science.gov (United States)

Wong, Tony E.; Keller, Klaus

2017-10-01

Future sea-level rise drives severe risks for many coastal communities. Strategies to manage these risks hinge on a sound characterization of the uncertainties. For example, recent studies suggest that large fractions of the Antarctic ice sheet (AIS) may rapidly disintegrate in response to rising global temperatures, leading to potentially several meters of sea-level rise during the next few centuries. It is deeply uncertain, for example, whether such an AIS disintegration will be triggered, how much this would increase sea-level rise, whether extreme storm surges intensify in a warming climate, or which emissions pathway future societies will choose. Here, we assess the impacts of these deep uncertainties on projected flooding probabilities for a levee ring in New Orleans, LA. We use 18 scenarios, presenting probabilistic projections within each one, to sample key deeply uncertain future projections of sea-level rise, radiative forcing pathways, storm surge characterization, and contributions from rapid AIS mass loss. The implications of these deep uncertainties for projected flood risk are thus characterized by a set of 18 probability distribution functions. We use a global sensitivity analysis to assess which mechanisms contribute to uncertainty in projected flood risk over the course of a 50-year design life. In line with previous work, we find that the uncertain storm surge drives the most substantial risk, followed by general AIS dynamics, in our simple model for future flood risk for New Orleans.

Probabilistic approach for assessing infants' health risks due to ingestion of nanoscale silver released from consumer products.

Science.gov (United States)

Pang, Chengfang; Hristozov, Danail; Zabeo, Alex; Pizzol, Lisa; Tsang, Michael P; Sayre, Phil; Marcomini, Antonio

2017-02-01

Silver nanoparticles (n-Ag) are widely used in consumer products and many medical applications because of their unique antibacterial properties. Their use is raising concern about potential human exposures and health effects. Therefore, it is informative to assess the potential human health risks of n-Ag in order to ensure that nanotechnology-based consumer products are deployed in a safe and sustainable way. Even though toxicity studies clearly show the potential hazard of n-Ag, there have been few attempts to integrate hazard and exposure assessments to evaluate risks. The underlying reason for this is the difficulty in characterizing exposure and the lack of toxicity studies essential for human health risk assessment (HHRA). Such data gaps introduce significant uncertainty into the risk assessment process. This study uses probabilistic methods to assess the relative uncertainty and potential risks of n-Ag exposure to infants. In this paper, we estimate the risks for infants potentially exposed to n-Ag through drinking juice or milk from sippy cups or licking baby blankets containing n-Ag. We explicitly evaluate uncertainty and variability contained in available dose-response and exposure data in order to make the risk characterization process transparent. Our results showed that individual margin of exposures for oral exposure to sippy cups and baby blankets containing n-Ag exhibited minimal risk. Copyright © 2016. Published by Elsevier Ltd.

Development of Risk Uncertainty Factors from Historical NASA Projects

Science.gov (United States)

Amer, Tahani R.

2011-01-01

NASA is a good investment of federal funds and strives to provide the best value to the nation. NASA has consistently budgeted to unrealistic cost estimates, which are evident in the cost growth in many of its programs. In this investigation, NASA has been using available uncertainty factors from the Aerospace Corporation, Air Force, and Booz Allen Hamilton to develop projects risk posture. NASA has no insight into the developmental of these factors and, as demonstrated here, this can lead to unrealistic risks in many NASA Programs and projects (P/p). The primary contribution of this project is the development of NASA missions uncertainty factors, from actual historical NASA projects, to aid cost-estimating as well as for independent reviews which provide NASA senior management with information and analysis to determine the appropriate decision regarding P/p. In general terms, this research project advances programmatic analysis for NASA projects.

Research approaches to address uncertainties in the risk assessment of arsenic in drinking water

International Nuclear Information System (INIS)

Hughes, Michael F.; Kenyon, Elaina M.; Kitchin, Kirk T.

2007-01-01

Inorganic arsenic (iAs), an environmental drinking water contaminant, is a human toxicant and carcinogen. The public health community has developed recommendations and regulations that limit human exposure to iAs in drinking water. Although there is a vast amount of information available to regulators on the exposure, disposition and the health-related effects of iAs, there is still critical information about the toxicology of this metalloid that is needed. This necessary information includes identification of the chemical species of arsenic that is (are) the active toxicant(s), the mode(s) of action for its various toxicities and information on potentially susceptible populations. Because of these unknown factors, the risk assessment of iAs still incorporates default assumptions, leading to uncertainties in the overall assessment. The characteristics of a scientifically defensible risk assessment for iAs are that it must: (1) quantitatively link exposure and target tissue dose of active metabolites to key events in the mode of action for major health effects and (2) identify sources of variation in susceptibility to arsenic-induced health effects and quantitatively evaluate their impact wherever possible. Integration of research to address these goals will better protect the health of iAs-exposed populations

Risk, uncertainty and prophet: The psychological insights of Frank H. Knight

Directory of Open Access Journals (Sweden)

Tim Rakow

2010-10-01

Full Text Available Economist Frank H. Knight (1885--1972 is commonly credited with defining the distinction between decisions under ``risk'' (known chance and decisions under ``uncertainty'' (unmeasurable probability in his 1921 book Risk, Uncertainty and Profit. A closer reading of Knight (1921 reveals a host of psychological insights beyond this risk-uncertainty distinction, many of which foreshadow revolutionary advances in psychological decision theory from the latter half of the 20th century. Knight's description of economic decision making shared much with Simon's (1955, 1956 notion of bounded rationality, whereby choice behavior is regulated by cognitive and environmental constraints. Knight described features of risky choice that were to become key components of prospect theory (Kahneman and Tversky, 1979: the reference dependent valuation of outcomes, and the non-linear weighting of probabilities. Knight also discussed several biases in human decision making, and pointed to two systems of reasoning: one quick, intuitive but error prone, and a slower, more deliberate, rule-based system. A discussion of Knight's potential contribution to psychological decision theory emphasises the importance of a historical perspective on theory development, and the potential value of sourcing ideas from other disciplines or from earlier periods of time.

Advances in Financial Risk Management and Economic Policy Uncertainty: An Overview

NARCIS (Netherlands)

S.M. Hammoudeh (Shawkat); M.J. McAleer (Michael)

2014-01-01

markdownabstract__Abstract__ Financial risk management is difficult at the best of times, but especially so in the presence of economic uncertainty and financial crises. The purpose of this special issue on “Advances in Financial Risk Management and Economic Policy Uncertainty” is to highlight

Allocating risk capital for a brownfields redevelopment project under hydrogeological and financial uncertainty.

Science.gov (United States)

Yu, Soonyoung; Unger, Andre J A; Parker, Beth; Kim, Taehee

2012-06-15

In this study, we defined risk capital as the contingency fee or insurance premium that a brownfields redeveloper needs to set aside from the sale of each house in case they need to repurchase it at a later date because the indoor air has been detrimentally affected by subsurface contamination. The likelihood that indoor air concentrations will exceed a regulatory level subject to subsurface heterogeneity and source zone location uncertainty is simulated by a physics-based hydrogeological model using Monte Carlo realizations, yielding the probability of failure. The cost of failure is the future value of the house indexed to the stochastic US National Housing index. The risk capital is essentially the probability of failure times the cost of failure with a surcharge to compensate the developer against hydrogeological and financial uncertainty, with the surcharge acting as safety loading reflecting the developers' level of risk aversion. We review five methodologies taken from the actuarial and financial literature to price the risk capital for a highly stylized brownfield redevelopment project, with each method specifically adapted to accommodate our notion of the probability of failure. The objective of this paper is to develop an actuarially consistent approach for combining the hydrogeological and financial uncertainty into a contingency fee that the brownfields developer should reserve (i.e. the risk capital) in order to hedge their risk exposure during the project. Results indicate that the price of the risk capital is much more sensitive to hydrogeological rather than financial uncertainty. We use the Capital Asset Pricing Model to estimate the risk-adjusted discount rate to depreciate all costs to present value for the brownfield redevelopment project. A key outcome of this work is that the presentation of our risk capital valuation methodology is sufficiently generalized for application to a wide variety of engineering projects. Copyright © 2012 Elsevier

Some considerations on the treatment of uncertainties in risk assessment for practical decision making

International Nuclear Information System (INIS)

Aven, Terje; Zio, Enrico

2011-01-01

This paper discusses the challenges involved in the representation and treatment of uncertainties in risk assessment, taking the point of view of its use in support to decision making. Two main issues are addressed: (1) how to faithfully represent and express the knowledge available to best support the decision making and (2) how to best inform the decision maker. A general risk-uncertainty framework is presented which provides definitions and interpretations of the key concepts introduced. The framework covers probability theory as well as alternative representations of uncertainty, including interval probability, possibility and evidence theory.

Analysis of parameter uncertainties in the assessment of seismic risk for nuclear power plants

International Nuclear Information System (INIS)

Yucemen, S.M.

1981-04-01

Probabilistic and statistical methods are used to develop a procedure by which the seismic risk at a specific site can be systematically analyzed. The proposed probabilistic procedure provides a consisted method for the modelling, analysis and updating of uncertainties that are involved in the seismic risk analysis for nuclear power plants. Methods are proposed for including these uncertainties in the final value of calculated risks. Two specific case studies are presented in detail to illustrate the application of the probabilistic method of seismic risk evaluation and to investigate the sensitivity of results to different assumptions

Forecasting Investment Risks in Conditions of Uncertainty

Directory of Open Access Journals (Sweden)

Andrenko Elena A.

2017-04-01

Full Text Available The article is aimed at studying the topical problem of evaluation and forecasting risks of investment activity of enterprises in conditions of uncertainty. Generalizing the researches on qualitative and quantitative methods for evaluating investment risks has helped to reveal certain shortcomings of the proposed approaches, to note in most of the publications there are no results as to any practical application, and to allocate promising directions. On the basis of the theory of fuzzy sets, a model of forecasting the expected risk has been proposed, making use of the Gauss membership function, which has certain advantages over the multi-angular membership functions. Dependences of investment risk from the parameters characterizing the investment project have been obtained. Using the formulas obtained, the total risk of investing in innovation project depending on the boundary conditions has been defined. As the researched target, index of profitability has been selected. The model provides the potential investors and developers with forecasting possible scenarios of investment process to make informed managerial decisions about the appropriateness of introduction and implementation of a project.

Too Risk Averse to Stay Honest? Business Corruption, Uncertainty and Attitudes Toward Risk

OpenAIRE

Soreide, T.

2009-01-01

The presence of business-corruption provokes firms to make choices between legal business approaches and illegal bribery. The outcome of a chosen strategy will usually be uncertain at the time the decision is made, and a firm's decision will depend partly on its attitude towards risk. Drawing on empirical results about business corruption, this paper describes the risks, uncertainties and benefits attached to bribery, and specifies their impact on firms' propensity to offer bribes. it then de...

Health and environmental risks of energy systems

International Nuclear Information System (INIS)

Hamilton, L.D.

1984-01-01

This paper gives four examples of health risk assessments of energy systems: (1) Comparative risk assessment of the health effects of the coal and nuclear fuel cycles. Estimates differ from previous values chiefly by inclusion of ranges of uncertainty, but some coal-cycle numbers were re-estimated. Upper-boundary public disease risks of air pollution from coal-fired plants dominate. Reactors probably account for most of the potential effect of major nuclear accidents. Accidental death rates in electricity generation are low for reactors and higher for coal. (2) Upper boundary air pollution health risks of existing fossil-based energy technologies in the United States. Preliminary mortality estimates were obtained combining potential impacts of three index pollutants - SO 4 , NO 2 , and CO - as independent measures of risk. Four fuel cycle trajectories leading to three end-uses were analyzed. Example results: domestic wood burning has substantial potential impact, with an upper boundary exceeding that of coal; upper-boundary air pollution impacts of gas can exceed those of oil, because of NO 2 . (3) Health risks of acid deposition and other transported air pollutants, carried out as part of an assessment of the US Congress Office of Technology Assessment (OTA) Acid Rain and Transported Air Pollutants - Implications for Public Policy. Three scenarios were examined, leading to estimates of 40,000 to 50,000 annual premature deaths, depending on year (1978 vs 2000) and scenario (holding total emissions constant vs 30% reduction). (4) health effects of uranium mill tailings piles. Mortality risk is estimated to be minuscule (8.7 x 10 -9 average individual lifetime cancer risk from a model mill, compared with 9.5 x 10 -4 for background radiation). Methods that sum risks over the indefinite future are shown to be to be unrealistic. 39 references, 7 figures, 15 tables

Risk-sensitive optimal feedback control accounts for sensorimotor behavior under uncertainty.

Directory of Open Access Journals (Sweden)

Arne J Nagengast

2010-07-01

Full Text Available Many aspects of human motor behavior can be understood using optimality principles such as optimal feedback control. However, these proposed optimal control models are risk-neutral; that is, they are indifferent to the variability of the movement cost. Here, we propose the use of a risk-sensitive optimal controller that incorporates movement cost variance either as an added cost (risk-averse controller or as an added value (risk-seeking controller to model human motor behavior in the face of uncertainty. We use a sensorimotor task to test the hypothesis that subjects are risk-sensitive. Subjects controlled a virtual ball undergoing Brownian motion towards a target. Subjects were required to minimize an explicit cost, in points, that was a combination of the final positional error of the ball and the integrated control cost. By testing subjects on different levels of Brownian motion noise and relative weighting of the position and control cost, we could distinguish between risk-sensitive and risk-neutral control. We show that subjects change their movement strategy pessimistically in the face of increased uncertainty in accord with the predictions of a risk-averse optimal controller. Our results suggest that risk-sensitivity is a fundamental attribute that needs to be incorporated into optimal feedback control models.

Uncertainty analysis in vulnerability estimations for elements at risk- a review of concepts and some examples on landslides

Science.gov (United States)

Ciurean, R. L.; Glade, T.

2012-04-01

Decision under uncertainty is a constant of everyday life and an important component of risk management and governance. Recently, experts have emphasized the importance of quantifying uncertainty in all phases of landslide risk analysis. Due to its multi-dimensional and dynamic nature, (physical) vulnerability is inherently complex and the "degree of loss" estimates imprecise and to some extent even subjective. Uncertainty analysis introduces quantitative modeling approaches that allow for a more explicitly objective output, improving the risk management process as well as enhancing communication between various stakeholders for better risk governance. This study presents a review of concepts for uncertainty analysis in vulnerability of elements at risk to landslides. Different semi-quantitative and quantitative methods are compared based on their feasibility in real-world situations, hazard dependency, process stage in vulnerability assessment (i.e. input data, model, output), and applicability within an integrated landslide hazard and risk framework. The resulted observations will help to identify current gaps and future needs in vulnerability assessment, including estimation of uncertainty propagation, transferability of the methods, development of visualization tools, but also address basic questions like what is uncertainty and how uncertainty can be quantified or treated in a reliable and reproducible way.

Examining uncertainties in the linkage between global climate change and potential human health impacts in the western USA -- Hexachlorobenzene (HCB) as a case study

Energy Technology Data Exchange (ETDEWEB)

McKone, T.E.; Daniels, J.I. [Lawrence Livermore National Lab., CA (United States); Goldman, M. [Univ. of California, Davis, CA (United States)

1994-09-30

Industrial societies have altered the earth`s environment in ways that could have important, long-term ecological, economic, and health implications. In this paper the authors define, characterize, and evaluate parameter and outcome uncertainties using a model that links global climate change with predictions of chemical exposure and human health risk in the western region of the US. They illustrate the impact of uncertainty about global climate change on such potential secondary outcomes using as a case study the public health consequences related to the behavior environmentally of hexachlorobenzene (HCB), an ubiquitous multimedia pollutant. They begin by constructing a matrix that reveals the linkage between global environmental change and potential regional human-health effects that might be induced directly and/or indirectly by HCB released into the air and water. This matrix is useful for translating critical uncertainties into terms that can be understood and used by policy makers to formulate strategies against potential adverse irreversible health and economic consequences. Specifically, the authors employ a combined uncertainty/sensitivity analysis to investigate how the HCB that has been released is affected by increasing atmospheric temperature and the accompanying climate alterations that are anticipated and how such uncertainty propagates to affect the expected magnitude and calculational precision of estimates of associated potential human exposures and health effects.

The uncertainty cascade in flood risk assessment under changing climatic conditions - the Biala Tarnowska case study

Science.gov (United States)

Doroszkiewicz, Joanna; Romanowicz, Renata

2016-04-01

Uncertainty in the results of the hydraulic model is not only associated with the limitations of that model and the shortcomings of data. An important factor that has a major impact on the uncertainty of the flood risk assessment in a changing climate conditions is associated with the uncertainty of future climate scenarios (IPCC WG I, 2013). Future climate projections provided by global climate models are used to generate future runoff required as an input to hydraulic models applied in the derivation of flood risk maps. Biala Tarnowska catchment, situated in southern Poland is used as a case study. Future discharges at the input to a hydraulic model are obtained using the HBV model and climate projections obtained from the EUROCORDEX project. The study describes a cascade of uncertainty related to different stages of the process of derivation of flood risk maps under changing climate conditions. In this context it takes into account the uncertainty of future climate projections, an uncertainty of flow routing model, the propagation of that uncertainty through the hydraulic model, and finally, the uncertainty related to the derivation of flood risk maps. One of the aims of this study is an assessment of a relative impact of different sources of uncertainty on the uncertainty of flood risk maps. Due to the complexity of the process, an assessment of total uncertainty of maps of inundation probability might be very computer time consuming. As a way forward we present an application of a hydraulic model simulator based on a nonlinear transfer function model for the chosen locations along the river reach. The transfer function model parameters are estimated based on the simulations of the hydraulic model at each of the model cross-section. The study shows that the application of the simulator substantially reduces the computer requirements related to the derivation of flood risk maps under future climatic conditions. Acknowledgements: This work was supported by the

Emerging Radiation Health-Risk Mitigation Technologies

International Nuclear Information System (INIS)

Wilson, J.W.; Cucinotta, F.A.; Schimmerling, W.

2004-01-01

Past space missions beyond the confines of the Earth's protective magnetic field have been of short duration and protection from the effects of solar particle events was of primary concern. The extension of operational infrastructure beyond low-Earth orbit to enable routine access to more interesting regions of space will require protection from the hazards of the accumulated exposures of Galactic Cosmic Rays (GCR). There are significant challenges in providing protection from the long-duration exposure to GCR: the human risks to the exposures are highly uncertain and safety requirements places unreasonable demands in supplying sufficient shielding materials in the design. A vigorous approach to future radiation health-risk mitigation requires a triage of techniques (using biological and technical factors) and reduction of the uncertainty in radiation risk models. The present paper discusses the triage of factors for risk mitigation with associated materials issues and engineering design methods

County-Level Climate Uncertainty for Risk Assessments: Volume 1.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

2017-06-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

Uncertainties associated with geologic disposal of high-level radioactive waste

International Nuclear Information System (INIS)

Kocher, D.C.; Sjoreen, A.L.; Bard, C.S.; Olsen, C.R.

1982-01-01

This paper focuses on uncertainties associated with models for predicting: (1) groundwater transport of radionuclides between a repository and the biosphere; and (2) long-term collective dose and health effects following release of long-lived radionuclides to the biosphere. We do not present numerical estimates of uncertainties in such predictions. Rather, we emphasize the various sources of uncertainty and attempt to evaluate the extent to which current models and supporting data bases can realistically describe long-term repository performance and health risks. We do not consider uncertainties associated with the long-term performance of engineered barriers at a repository or with human intrusion

Interpretations of alternative uncertainty representations in a reliability and risk analysis context

International Nuclear Information System (INIS)

Aven, T.

2011-01-01

Probability is the predominant tool used to measure uncertainties in reliability and risk analyses. However, other representations also exist, including imprecise (interval) probability, fuzzy probability and representations based on the theories of evidence (belief functions) and possibility. Many researchers in the field are strong proponents of these alternative methods, but some are also sceptical. In this paper, we address one basic requirement set for quantitative measures of uncertainty: the interpretation needed to explain what an uncertainty number expresses. We question to what extent the various measures meet this requirement. Comparisons are made with probabilistic analysis, where uncertainty is represented by subjective probabilities, using either a betting interpretation or a reference to an uncertainty standard interpretation. By distinguishing between chances (expressing variation) and subjective probabilities, new insights are gained into the link between the alternative uncertainty representations and probability.

Emotion and decision-making under uncertainty: Physiological arousal predicts increased gambling during ambiguity but not risk.

Science.gov (United States)

FeldmanHall, Oriel; Glimcher, Paul; Baker, Augustus L; Phelps, Elizabeth A

2016-10-01

Uncertainty, which is ubiquitous in decision-making, can be fractionated into known probabilities (risk) and unknown probabilities (ambiguity). Although research has illustrated that individuals more often avoid decisions associated with ambiguity compared to risk, it remains unclear why ambiguity is perceived as more aversive. Here we examine the role of arousal in shaping the representation of value and subsequent choice under risky and ambiguous decisions. To investigate the relationship between arousal and decisions of uncertainty, we measure skin conductance response-a quantifiable measure reflecting sympathetic nervous system arousal-during choices to gamble under risk and ambiguity. To quantify the discrete influences of risk and ambiguity sensitivity and the subjective value of each option under consideration, we model fluctuating uncertainty, as well as the amount of money that can be gained by taking the gamble. Results reveal that although arousal tracks the subjective value of a lottery regardless of uncertainty type, arousal differentially contributes to the computation of value-that is, choice-depending on whether the uncertainty is risky or ambiguous: Enhanced arousal adaptively decreases risk-taking only when the lottery is highly risky but increases risk-taking when the probability of winning is ambiguous (even after controlling for subjective value). Together, this suggests that the role of arousal during decisions of uncertainty is modulatory and highly dependent on the context in which the decision is framed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Epistemic uncertainties and natural hazard risk assessment - Part 1: A review of the issues

Science.gov (United States)

Beven, K. J.; Aspinall, W. P.; Bates, P. D.; Borgomeo, E.; Goda, K.; Hall, J. W.; Page, T.; Phillips, J. C.; Rougier, J. T.; Simpson, M.; Stephenson, D. B.; Smith, P. J.; Wagener, T.; Watson, M.

2015-12-01

Uncertainties in natural hazard risk assessment are generally dominated by the sources arising from lack of knowledge or understanding of the processes involved. There is a lack of knowledge about frequencies, process representations, parameters, present and future boundary conditions, consequences and impacts, and the meaning of observations in evaluating simulation models. These are the epistemic uncertainties that can be difficult to constrain, especially in terms of event or scenario probabilities, even as elicited probabilities rationalized on the basis of expert judgements. This paper reviews the issues raised by trying to quantify the effects of epistemic uncertainties. Such scientific uncertainties might have significant influence on decisions that are made for risk management, so it is important to communicate the meaning of an uncertainty estimate and to provide an audit trail of the assumptions on which it is based. Some suggestions for good practice in doing so are made.

Health risks of passive smoking.

Science.gov (United States)

Papier, C M; Stellman, S D

1986-01-01

Passive or involuntary smoking is the inhalation of smoke which escapes directly into the air from the lit end of a burning cigarette. This unfiltered smoke contains the same toxic components of the mainstream smoke inhaled directly by the smoker, including numerous carcinogens, many in greater concentrations. It has long been known that exposure to this type of smoke leads to increased respiratory and other adverse health conditions in non-smokers, especially children. During the past five years, evidence has been accumulating that risk of lung cancer is also higher, particularly in non-smoking women whose husbands smoke. Despite uncertainties and differences in interpretation of various cancer studies, there is ample justification for public health measures now in place or proposed, such as restriction or elimination of smoking in the workplace and in public places.

Assessment of volcanic hazards, vulnerability, risk and uncertainty (Invited)

Science.gov (United States)

Sparks, R. S.

2009-12-01

many sources of uncertainty in forecasting the areas that volcanic activity will effect and the severity of the effects. Uncertainties arise from: natural variability, inadequate data, biased data, incomplete data, lack of understanding of the processes, limitations to predictive models, ambiguity, and unknown unknowns. The description of volcanic hazards is thus necessarily probabilistic and requires assessment of the attendant uncertainties. Several issues arise from the probabilistic nature of volcanic hazards and the intrinsic uncertainties. Although zonation maps require well-defined boundaries for administrative pragmatism, such boundaries cannot divide areas that are completely safe from those that are unsafe. Levels of danger or safety need to be defined to decide on and justify boundaries through the concepts of vulnerability and risk. More data, better observations, improved models may reduce uncertainties, but can increase uncertainties and may lead to re-appraisal of zone boundaries. Probabilities inferred by statistical techniques are hard to communicate. Expert elicitation is an emerging methodology for risk assessment and uncertainty evaluation. The method has been applied at one major volcanic crisis (Soufrière Hills Volcano, Montserrat), and is being applied in planning for volcanic crises at Vesuvius.

Risk Analysis for Environmental Health Triage

International Nuclear Information System (INIS)

Bogen, K T

2005-01-01

The Homeland Security Act mandates development of a national, risk-based system to support planning for, response to and recovery from emergency situations involving large-scale toxic exposures. To prepare for and manage consequences effectively, planners and responders need not only to identify zones of potentially elevated individual risk, but also to predict expected casualties. Emergency response support systems now define ''consequences'' by mapping areas in which toxic chemical concentrations do or may exceed Acute Exposure Guideline Levels (AEGLs) or similar guidelines. However, because AEGLs do not estimate expected risks, current unqualified claims that such maps support consequence management are misleading. Intentionally protective, AEGLs incorporate various safety/uncertainty factors depending on scope and quality of chemical-specific toxicity data. Some of these factors are irrelevant, and others need to be modified, whenever resource constraints or exposure-scenario complexities require responders to make critical trade-off (triage) decisions in order to minimize expected casualties. AEGL-exceedance zones cannot consistently be aggregated, compared, or used to calculate expected casualties, and so may seriously misguide emergency response triage decisions. Methods and tools well established and readily available to support environmental health protection are not yet developed for chemically related environmental health triage. Effective triage decisions involving chemical risks require a new assessment approach that focuses on best estimates of likely casualties, rather than on upper plausible bounds of individual risk. If risk-based consequence management is to become a reality, federal agencies tasked with supporting emergency response must actively coordinate to foster new methods that can support effective environmental health triage

Quantifying aggregated uncertainty in Plasmodium falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation.

Science.gov (United States)

Gething, Peter W; Patil, Anand P; Hay, Simon I

2010-04-01

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty--the fidelity of predictions at each mapped pixel--but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers.

Managing structural uncertainty in health economic decision models: a discrepancy approach

OpenAIRE

Strong, M.; Oakley, J.; Chilcott, J.

2012-01-01

Healthcare resource allocation decisions are commonly informed by computer model predictions of population mean costs and health effects. It is common to quantify the uncertainty in the prediction due to uncertain model inputs, but methods for quantifying uncertainty due to inadequacies in model structure are less well developed. We introduce an example of a model that aims to predict the costs and health effects of a physical activity promoting intervention. Our goal is to develop a framewor...

Adaptive Governance, Uncertainty, and Risk: Policy Framing and Responses to Climate Change, Drought, and Flood.

Science.gov (United States)

Hurlbert, Margot; Gupta, Joyeeta

2016-02-01

As climate change impacts result in more extreme events (such as droughts and floods), the need to understand which policies facilitate effective climate change adaptation becomes crucial. Hence, this article answers the question: How do governments and policymakers frame policy in relation to climate change, droughts, and floods and what governance structures facilitate adaptation? This research interrogates and analyzes through content analysis, supplemented by semi-structured qualitative interviews, the policy response to climate change, drought, and flood in relation to agricultural producers in four case studies in river basins in Chile, Argentina, and Canada. First, an epistemological explanation of risk and uncertainty underscores a brief literature review of adaptive governance, followed by policy framing in relation to risk and uncertainty, and an analytical model is developed. Pertinent findings of the four cases are recounted, followed by a comparative analysis. In conclusion, recommendations are made to improve policies and expand adaptive governance to better account for uncertainty and risk. This article is innovative in that it proposes an expanded model of adaptive governance in relation to "risk" that can help bridge the barrier of uncertainty in science and policy. © 2015 Society for Risk Analysis.

An overview of the risk uncertainty assessment process for the Cassini space mission

International Nuclear Information System (INIS)

Wyss, G.D.

1996-01-01

The Cassini spacecraft is a deep space probe whose mission is to explore the planet Saturn and its moons. Since the spacecraft's electrical requirements will be supplied by radioisotope thermoelectric generators (RTGs), the spacecraft designers and mission planners must assure that potential accidents involving the spacecraft do not pose significant human risk. The Cassini risk analysis team is seeking to perform a quantitative uncertainty analysis as a part of the overall mission risk assessment program. This paper describes the uncertainty analysis methodology to be used for the Cassini mission and compares it to the methods that were originally developed for evaluation of commercial nuclear power reactors

Practical consequences of the assessment of different energy health risks

International Nuclear Information System (INIS)

Hamilton, L.D.

1984-01-01

Public authorities must make decisions about energy, and the risks of alternative strategies need to be calculated including health and environmental costs. Information from various sources must be organized into a logical framework for comparing impacts. This must include the widest practicable range of health and environmental damage - public health impact of pollution, role of accidents, disease and hazardous materials in the workplace, and odds for catastrophes. It must put each part of the energy cycle into perspective - giving particular attention to uncertainties in knowledge - to convey what is known, what is uncertain, and the importance of each factor in the overall picture. This paper gives examples of the use of health-impact assessment by decision-makers: (1) comparative risk assessment of the health effects of coal and nuclear fuel cycles used in nuclear power plant siting and licensing hearings, and (2) health risks of acid deposition and other air-transported pollutants, carried out as part of an assessment for the U.S. Congress Office of Technology Assessment. (author)

Worldwide Regulations of Standard Values of Pesticides for Human Health Risk Control: A Review

Science.gov (United States)

Jennings, Aaron

2017-01-01

The impact of pesticide residues on human health is a worldwide problem, as human exposure to pesticides can occur through ingestion, inhalation, and dermal contact. Regulatory jurisdictions have promulgated the standard values for pesticides in residential soil, air, drinking water, and agricultural commodity for years. Until now, more than 19,400 pesticide soil regulatory guidance values (RGVs) and 5400 pesticide drinking water maximum concentration levels (MCLs) have been regulated by 54 and 102 nations, respectively. Over 90 nations have provided pesticide agricultural commodity maximum residue limits (MRLs) for at least one of the 12 most commonly consumed agricultural foods. A total of 22 pesticides have been regulated with more than 100 soil RGVs, and 25 pesticides have more than 100 drinking water MCLs. This research indicates that those RGVs and MCLs for an individual pesticide could vary over seven (DDT drinking water MCLs), eight (Lindane soil RGVs), or even nine (Dieldrin soil RGVs) orders of magnitude. Human health risk uncertainty bounds and the implied total exposure mass burden model were applied to analyze the most commonly regulated and used pesticides for human health risk control. For the top 27 commonly regulated pesticides in soil, there are at least 300 RGVs (8% of the total) that are above all of the computed upper bounds for human health risk uncertainty. For the top 29 most-commonly regulated pesticides in drinking water, at least 172 drinking water MCLs (5% of the total) exceed the computed upper bounds for human health risk uncertainty; while for the 14 most widely used pesticides, there are at least 310 computed implied dose limits (28.0% of the total) that are above the acceptable daily intake values. The results show that some worldwide standard values were not derived conservatively enough to avoid human health risk by the pesticides, and that some values were not computed comprehensively by considering all major human exposure

Worldwide Regulations of Standard Values of Pesticides for Human Health Risk Control: A Review.

Science.gov (United States)

Li, Zijian; Jennings, Aaron

2017-07-22

Abstract : The impact of pesticide residues on human health is a worldwide problem, as human exposure to pesticides can occur through ingestion, inhalation, and dermal contact. Regulatory jurisdictions have promulgated the standard values for pesticides in residential soil, air, drinking water, and agricultural commodity for years. Until now, more than 19,400 pesticide soil regulatory guidance values (RGVs) and 5400 pesticide drinking water maximum concentration levels (MCLs) have been regulated by 54 and 102 nations, respectively. Over 90 nations have provided pesticide agricultural commodity maximum residue limits (MRLs) for at least one of the 12 most commonly consumed agricultural foods. A total of 22 pesticides have been regulated with more than 100 soil RGVs, and 25 pesticides have more than 100 drinking water MCLs. This research indicates that those RGVs and MCLs for an individual pesticide could vary over seven (DDT drinking water MCLs), eight (Lindane soil RGVs), or even nine (Dieldrin soil RGVs) orders of magnitude. Human health risk uncertainty bounds and the implied total exposure mass burden model were applied to analyze the most commonly regulated and used pesticides for human health risk control. For the top 27 commonly regulated pesticides in soil, there are at least 300 RGVs (8% of the total) that are above all of the computed upper bounds for human health risk uncertainty. For the top 29 most-commonly regulated pesticides in drinking water, at least 172 drinking water MCLs (5% of the total) exceed the computed upper bounds for human health risk uncertainty; while for the 14 most widely used pesticides, there are at least 310 computed implied dose limits (28.0% of the total) that are above the acceptable daily intake values. The results show that some worldwide standard values were not derived conservatively enough to avoid human health risk by the pesticides, and that some values were not computed comprehensively by considering all major human

A method for minimum risk portfolio optimization under hybrid uncertainty

Science.gov (United States)

Egorova, Yu E.; Yazenin, A. V.

2018-03-01

In this paper, we investigate a minimum risk portfolio model under hybrid uncertainty when the profitability of financial assets is described by fuzzy random variables. According to Feng, the variance of a portfolio is defined as a crisp value. To aggregate fuzzy information the weakest (drastic) t-norm is used. We construct an equivalent stochastic problem of the minimum risk portfolio model and specify the stochastic penalty method for solving it.

Human health and safety risks management in underground coal mines using fuzzy TOPSIS

Energy Technology Data Exchange (ETDEWEB)

Mahdevari, Satar, E-mail: satar.mahdevari@aut.ac.ir [Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Shahriar, Kourosh [Department of Mining and Metallurgical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Esfahanipour, Akbar [Industrial Engineering Department, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

2014-08-01

The scrutiny of health and safety of personnel working in underground coal mines is heightened because of fatalities and disasters that occur every year worldwide. A methodology based on fuzzy TOPSIS was proposed to assess the risks associated with human health in order to manage control measures and support decision-making, which could provide the right balance between different concerns, such as safety and costs. For this purpose, information collected from three hazardous coal mines namely Hashouni, Hojedk and Babnizu located at the Kerman coal deposit, Iran, were used to manage the risks affecting the health and safety of their miners. Altogether 86 hazards were identified and classified under eight categories: geomechanical, geochemical, electrical, mechanical, chemical, environmental, personal, and social, cultural and managerial risks. Overcoming the uncertainty of qualitative data, the ranking process is accomplished by fuzzy TOPSIS. After running the model, twelve groups with different risks were obtained. Located in the first group, the most important risks with the highest negative effects are: materials falling, catastrophic failure, instability of coalface and immediate roof, firedamp explosion, gas emission, misfire, stopping of ventilation system, wagon separation at inclines, asphyxiation, inadequate training and poor site management system. According to the results, the proposed methodology can be a reliable technique for management of the minatory hazards and coping with uncertainties affecting the health and safety of miners when performance ratings are imprecise. The proposed model can be primarily designed to identify potential hazards and help in taking appropriate measures to minimize or remove the risks before accidents can occur. - Highlights: • Risks associated with health and safety of coal miners were investigated. • A reliable methodology based on Fuzzy TOPSIS was developed to manage the risks. • Three underground mines in Kerman

Human health and safety risks management in underground coal mines using fuzzy TOPSIS

International Nuclear Information System (INIS)

Mahdevari, Satar; Shahriar, Kourosh; Esfahanipour, Akbar

2014-01-01

The scrutiny of health and safety of personnel working in underground coal mines is heightened because of fatalities and disasters that occur every year worldwide. A methodology based on fuzzy TOPSIS was proposed to assess the risks associated with human health in order to manage control measures and support decision-making, which could provide the right balance between different concerns, such as safety and costs. For this purpose, information collected from three hazardous coal mines namely Hashouni, Hojedk and Babnizu located at the Kerman coal deposit, Iran, were used to manage the risks affecting the health and safety of their miners. Altogether 86 hazards were identified and classified under eight categories: geomechanical, geochemical, electrical, mechanical, chemical, environmental, personal, and social, cultural and managerial risks. Overcoming the uncertainty of qualitative data, the ranking process is accomplished by fuzzy TOPSIS. After running the model, twelve groups with different risks were obtained. Located in the first group, the most important risks with the highest negative effects are: materials falling, catastrophic failure, instability of coalface and immediate roof, firedamp explosion, gas emission, misfire, stopping of ventilation system, wagon separation at inclines, asphyxiation, inadequate training and poor site management system. According to the results, the proposed methodology can be a reliable technique for management of the minatory hazards and coping with uncertainties affecting the health and safety of miners when performance ratings are imprecise. The proposed model can be primarily designed to identify potential hazards and help in taking appropriate measures to minimize or remove the risks before accidents can occur. - Highlights: • Risks associated with health and safety of coal miners were investigated. • A reliable methodology based on Fuzzy TOPSIS was developed to manage the risks. • Three underground mines in Kerman

Impact of Hydrogeological Uncertainty on Estimation of Environmental Risks Posed by Hydrocarbon Transportation Networks

Science.gov (United States)

Ciriello, V.; Lauriola, I.; Bonvicini, S.; Cozzani, V.; Di Federico, V.; Tartakovsky, Daniel M.

2017-11-01

Ubiquitous hydrogeological uncertainty undermines the veracity of quantitative predictions of soil and groundwater contamination due to accidental hydrocarbon spills from onshore pipelines. Such predictions, therefore, must be accompanied by quantification of predictive uncertainty, especially when they are used for environmental risk assessment. We quantify the impact of parametric uncertainty on quantitative forecasting of temporal evolution of two key risk indices, volumes of unsaturated and saturated soil contaminated by a surface spill of light nonaqueous-phase liquids. This is accomplished by treating the relevant uncertain parameters as random variables and deploying two alternative probabilistic models to estimate their effect on predictive uncertainty. A physics-based model is solved with a stochastic collocation method and is supplemented by a global sensitivity analysis. A second model represents the quantities of interest as polynomials of random inputs and has a virtually negligible computational cost, which enables one to explore any number of risk-related contamination scenarios. For a typical oil-spill scenario, our method can be used to identify key flow and transport parameters affecting the risk indices, to elucidate texture-dependent behavior of different soils, and to evaluate, with a degree of confidence specified by the decision-maker, the extent of contamination and the correspondent remediation costs.

Media reporting of risk information: Uncertainties and the future

International Nuclear Information System (INIS)

Peltu, M.

1988-01-01

This paper argues that very little is known with a reasonable degree of certainty about how the media influence their audiences. Media effects are mediated through diverse, subtle social interactions and processes. Future changes in the regulatory and technological media environment will create even more uncertainty by changing basic parameters of media/audience interaction. More research is needed to help shed light on these uncertainties and future changes. If this research is to be of relevance to real communicators of real risk, it must fully address the issues of how the media are influenced, not just media impacts. In this context, the role of experts, PR, advertising, and media professionals' motivations are key priorities. (orig.)

Dealing with unquantifiable uncertainties in landslide modelling for urban risk reduction in developing countries

Science.gov (United States)

Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

2016-04-01

Landslides have many negative economic and societal impacts, including the potential for significant loss of life and damage to infrastructure. Slope stability assessment can be used to guide decisions about the management of landslide risk, but its usefulness can be challenged by high levels of uncertainty in predicting landslide occurrence. Prediction uncertainty may be associated with the choice of model that is used to assess slope stability, the quality of the available input data, or a lack of knowledge of how future climatic and socio-economic changes may affect future landslide risk. While some of these uncertainties can be characterised by relatively well-defined probability distributions, for other uncertainties, such as those linked to climate change, no probability distribution is available to characterise them. This latter type of uncertainty, often referred to as deep uncertainty, means that robust policies need to be developed that are expected to perform acceptably well over a wide range of future conditions. In our study the impact of deep uncertainty on slope stability predictions is assessed in a quantitative and structured manner using Global Sensitivity Analysis (GSA) and the Combined Hydrology and Stability Model (CHASM). In particular, we use several GSA methods including the Method of Morris, Regional Sensitivity Analysis and Classification and Regression Trees (CART), as well as advanced visualization tools, to assess the combination of conditions that may lead to slope failure. Our example application is a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates during the hurricane season, steep slopes, and highly weathered residual soils. Rapid unplanned urbanisation and changing climate may further exacerbate landslide risk in the future. Our example shows how we can gain useful information in the presence of deep uncertainty by combining physically based models with GSA in

Uncertainty Analysis of A Flood Risk Mapping Procedure Applied In Urban Areas

Science.gov (United States)

Krause, J.; Uhrich, S.; Bormann, H.; Diekkrüger, B.

In the framework of IRMA-Sponge program the presented study was part of the joint research project FRHYMAP (flood risk and hydrological mapping). A simple con- ceptual flooding model (FLOODMAP) has been developed to simulate flooded areas besides rivers within cities. FLOODMAP requires a minimum of input data (digital el- evation model (DEM), river line, water level plain) and parameters and calculates the flood extent as well as the spatial distribution of flood depths. of course the simulated model results are affected by errors and uncertainties. Possible sources of uncertain- ties are the model structure, model parameters and input data. Thus after the model validation (comparison of simulated water to observed extent, taken from airborne pictures) the uncertainty of the essential input data set (digital elevation model) was analysed. Monte Carlo simulations were performed to assess the effect of uncertain- ties concerning the statistics of DEM quality and to derive flooding probabilities from the set of simulations. The questions concerning a minimum resolution of a DEM re- quired for flood simulation and concerning the best aggregation procedure of a given DEM was answered by comparing the results obtained using all available standard GIS aggregation procedures. Seven different aggregation procedures were applied to high resolution DEMs (1-2m) in three cities (Bonn, Cologne, Luxembourg). Basing on this analysis the effect of 'uncertain' DEM data was estimated and compared with other sources of uncertainties. Especially socio-economic information and monetary transfer functions required for a damage risk analysis show a high uncertainty. There- fore this study helps to analyse the weak points of the flood risk and damage risk assessment procedure.

Framing risk and uncertainty in social science articles on climate change, 1995–2012

OpenAIRE

Shaw, Chris; Hellsten, Iina; Nerlich, Brigitte

2016-01-01

The issue of climate change is intimately linked to notions of risk and uncertainty, concepts that pose challenges to climate science, climate change communication, and science-society interactions. While a large majority of climate scientists are increasingly certain about the causes of climate change and the risks posed by its impacts (see IPCC, 2013 and 2014), public perception of climate change is still largely framed by uncertainty, especially regarding impacts (Poortinga et al., 2011). ...

Assessing risks and uncertainties in forest dynamics under different management scenarios and climate change

Directory of Open Access Journals (Sweden)

Matthias Albert

2015-05-01

Full Text Available Background Forest management faces a climate induced shift in growth potential and increasing current and emerging new risks. Vulnerability analysis provides decision support based on projections of natural resources taking risks and uncertainties into account. In this paper we (1 characterize differences in forest dynamics under three management scenarios, (2 analyse the effects of the three scenarios on two risk factors, windthrow and drought stress, and (3 quantify the effects and the amount of uncertainty arising from climate projections on height increment and drought stress. Methods In four regions in northern Germany, we apply three contrasting management scenarios and project forest development under climate change until 2070. Three climate runs (minimum, median, maximum based on the emission scenario RCP 8.5 control the site-sensitive forest growth functions. The minimum and maximum climate run define the range of prospective climate development. Results The projections of different management regimes until 2070 show the diverging medium-term effects of thinnings and harvests and long-term effects of species conversion on a regional scale. Examples of windthrow vulnerability and drought stress reveal how adaptation measures depend on the applied management path and the decision-maker’s risk attitude. Uncertainty analysis shows the increasing variability of drought risk projections with time. The effect of climate projections on height growth are quantified and uncertainty analysis reveals that height growth of young trees is dominated by the age-trend whereas the climate signal in height increment of older trees is decisive. Conclusions Drought risk is a serious issue in the eastern regions independent of the applied silvicultural scenario, but adaptation measures are limited as the proportion of the most drought tolerant species Scots pine is already high. Windthrow risk is no serious overall threat in any region, but adequate

In uncertainty we trust: a median voter model with risk aversion

Directory of Open Access Journals (Sweden)

Pavel A. Yakovlev

2011-12-01

Full Text Available The principal-agent problem and uncertainty are some of the key factors affecting financial and political markets. Fear of the unknown plays an important role in human decision making, including voting. This article describes a theoretical model where voter risk aversion towards uncertainty gives political incumbents a significant advantage over their challengers, exacerbating the principal-agent problem between voters and legislators. The model presented predicts that a rise in voter uncertainty concerning the challenger allows the incumbent to deviate from the median voter’s policy preference without losing the election. This model reconciles the paradoxical coexistence of ideological shirking and high incumbent reelection rates without abandoning the elegant median voter framework.

Using Statistical and Probabilistic Methods to Evaluate Health Risk Assessment: A Case Study

Directory of Open Access Journals (Sweden)

Hongjing Wu

2014-06-01

Full Text Available The toxic chemical and heavy metals within wastewater can cause serious adverse impacts on human health. Health risk assessment (HRA is an effective tool for supporting decision-making and corrective actions in water quality management. HRA can also help people understand the water quality and quantify the adverse effects of pollutants on human health. Due to the imprecision of data, measurement error and limited available information, uncertainty is inevitable in the HRA process. The purpose of this study is to integrate statistical and probabilistic methods to deal with censored and limited numbers of input data to improve the reliability of the non-cancer HRA of dermal contact exposure to contaminated river water by considering uncertainty. A case study in the Kelligrews River in St. John’s, Canada, was conducted to demonstrate the feasibility and capacity of the proposed approach. Five heavy metals were selected to evaluate the risk level, including arsenic, molybdenum, zinc, uranium and manganese. The results showed that the probability of the total hazard index of dermal exposure exceeding 1 is very low, and there is no obvious evidence of risk in the study area.

Economics versus psychology.Risk, uncertainty and the expected utility theory

OpenAIRE

Schilirò, Daniele

2017-01-01

The present contribution examines the emergence of expected utility theory by John von Neumann and Oskar Morgenstern, the subjective the expected utility theory by Savage, and the problem of choice under risk and uncertainty, focusing in particular on the seminal work “The Utility Analysis of Choices involving Risk" (1948) by Milton Friedman and Leonard Savage to show how the evolution of the theory of choice has determined a separation of economics from psychology.

Risco, incerteza e as possibilidades de ação na saúde ambiental Risk, uncertainty and the possibilities of action in environmental health

Directory of Open Access Journals (Sweden)

Renato Rocha Lieber

2003-06-01

Full Text Available O conceito de risco vem tendo uso crescente no entendimento das relações entre saúde e ambiente. Uma revisão recente do seu emprego¹ mostrou que o risco é próprio da condição humana e que a exclusão da incerteza promove a manutenção do status quo. O problema que se coloca é como propor ações de melhoria na saúde ambiental sob os pressupostos da dúvida e da incerteza que caracterizam a condição de risco. Como proposta de solução, a obra de H. Arendt² prestou-se ao exame dos significados e das implicações da incerteza no campo do pensamento e no campo da ação. Os resultados mostram que o risco se insere na lacuna construída entre o passado e o futuro. Quando esta lacuna passa a ser entendida como espaço de possibilidades, a incerteza, produzida no campo do pensamento fomenta a liberdade e a participação no campo da ação. A valorização da subjetividade e o exercício do juízo promovem a configuração de novos contextos e de novas possibilidades de ação, tanto em relação à natureza como em relação aos homens. Este conhecimento novo se insere na lacuna entre passado e futuro e realimenta o processo. Conclui-se que as ações de "promoção da saúde" devem estar aptas a aceitar resultados não necessariamente idealizados. Na ação livre não existem certezas e a sua relevância não está nos fins que se possa estabelecer, mas no processo do seu exercício.The concept of risk has been increasingly used in the understanding of the relationship between health and environment. A recent review of its use¹ showed that risk belongs to the human condition and that excluding uncertainty promotes maintaining the status quo. The question is how to propose actions to improve environmental health under the assumptions of doubt and uncertainty that characterize the condition of risk. As a proposal for a solution, the work of H. Arendt² examined the meanings and implications of uncertainty in the field of thought and

Principles for decisions involving environmental and health risks

International Nuclear Information System (INIS)

Bengtsson, B.

1989-01-01

Decision making with respect to safety is becoming more and more complex. The risk involved must be taken into account together with numerous other factors such as the benefits, the uncertainties and the public perception. Can the decision maker be aided by some kind of system, general rules of thumb, or broader perspective on similar decisions? This question has been addressed in a joint Nordic project relating to nuclear power. Modern techniques for risk assessment and management have been studied and parallels drawn to such areas as offshore safety and management of genotoxic chemicals in the environment. The topics include synoptic vs. incrementalistic approaches to decision making, health hazards from radiation and genotoxic chemicals, value judgments in decision making, definitions of low risks, risk comparisons, and principles for decision making when risks are involved. (author) 47 refs

Uncertainty as Knowledge: Constraints on Policy Choices Provided by Analysis of Uncertainty

Science.gov (United States)

Lewandowsky, S.; Risbey, J.; Smithson, M.; Newell, B. R.

2012-12-01

Uncertainty forms an integral part of climate science, and it is often cited in connection with arguments against mitigative action. We argue that an analysis of uncertainty must consider existing knowledge as well as uncertainty, and the two must be evaluated with respect to the outcomes and risks associated with possible policy options. Although risk judgments are inherently subjective, an analysis of the role of uncertainty within the climate system yields two constraints that are robust to a broad range of assumptions. Those constraints are that (a) greater uncertainty about the climate system is necessarily associated with greater expected damages from warming, and (b) greater uncertainty translates into a greater risk of the failure of mitigation efforts. These ordinal constraints are unaffected by subjective or cultural risk-perception factors, they are independent of the discount rate, and they are independent of the magnitude of the estimate for climate sensitivity. The constraints mean that any appeal to uncertainty must imply a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.

Integration of expert knowledge and uncertainty in natural risk assessment

Science.gov (United States)

Baruffini, Mirko; Jaboyedoff, Michel

2010-05-01

Natural hazards occurring in alpine regions during the last decades have clearly shown that interruptions of the Swiss railway power supply and closures of the Gotthard highway due to those events have increased the awareness of infrastructure vulnerability also in Switzerland and illustrate the potential impacts of failures on the performance of infrastructure systems. This asks for a high level of surveillance and preservation along the transalpine lines. Traditional simulation models are only partially capable to predict complex systems behaviours and the subsequently designed and implemented protection strategies are not able to mitigate the full spectrum of risk consequences. They are costly, and maximal protection is most probably not economically feasible. In addition, the quantitative risk assessment approaches such as fault tree analysis, event tree analysis and equivalent annual fatality analysis rely heavily on statistical information. Collecting sufficient data to base a statistical probability of risk is costly and, in many situations, such data does not exist; thus, expert knowledge and experience or engineering judgment can be exploited to estimate risk qualitatively. In order to overcome the statistics lack we used models based on expert's knowledge in order to qualitatively predict based on linguistic appreciation that are more expressive and natural in risk assessment. Fuzzy reasoning (FR) can be used providing a mechanism of computing with words (Zadeh, 1965) for modelling qualitative human thought processes in analyzing complex systems and decisions. Uncertainty in predicting the risk levels arises from such situations because no fully-formalized knowledge are available. Another possibility is to use probability based on triangular probability density function (T-PDF) that can be used to follow the same flow-chart as FR. We implemented the Swiss natural hazard recommendations FR and probability using T-PDF in order to obtain hazard zoning and

Bayesian Hierarchical Structure for Quantifying Population Variability to Inform Probabilistic Health Risk Assessments.

Science.gov (United States)

Shao, Kan; Allen, Bruce C; Wheeler, Matthew W

2017-10-01

Human variability is a very important factor considered in human health risk assessment for protecting sensitive populations from chemical exposure. Traditionally, to account for this variability, an interhuman uncertainty factor is applied to lower the exposure limit. However, using a fixed uncertainty factor rather than probabilistically accounting for human variability can hardly support probabilistic risk assessment advocated by a number of researchers; new methods are needed to probabilistically quantify human population variability. We propose a Bayesian hierarchical model to quantify variability among different populations. This approach jointly characterizes the distribution of risk at background exposure and the sensitivity of response to exposure, which are commonly represented by model parameters. We demonstrate, through both an application to real data and a simulation study, that using the proposed hierarchical structure adequately characterizes variability across different populations. © 2016 Society for Risk Analysis.

Trust and truth: uncertainty in health care practice.

Science.gov (United States)

Tyreman, Stephen

2015-06-01

Uncertainty is the ubiquitous presence across health care. It is usually understood in terms of decision making, 'knowing' the correct diagnosis or understanding how the human body works. Using the work of Ludwig Wittgenstein, Georges Canguilhem and Tim Ingold, I outline a story of journeying and habitation, and argue that while uncertainty for practitioners may be about enhancing theoretical knowledge, for patients it is about knowing how to act in a taken-for-granted and largely unconscious way in a world that has become uncertain, and in which the main tool of action, the human body, no longer functions with the certainty it once had. In this situation, the role of the practitioner is first and foremost to recognize the uncertainty that has emerged in the patient's 'habitation' and to reassure them by enabling them to have a new or restored confidence in their body so that they can act with certainty. © 2015 John Wiley & Sons, Ltd.

Uncertainty and Sensitivity of Direct Economic Flood Damages: the FloodRisk Free and Open-Source Software

Science.gov (United States)

Albano, R.; Sole, A.; Mancusi, L.; Cantisani, A.; Perrone, A.

2017-12-01

The considerable increase of flood damages in the the past decades has shifted in Europe the attention from protection against floods to managing flood risks. In this context, the expected damages assessment represents a crucial information within the overall flood risk management process. The present paper proposes an open source software, called FloodRisk, that is able to operatively support stakeholders in the decision making processes with a what-if approach by carrying out the rapid assessment of the flood consequences, in terms of direct economic damage and loss of human lives. The evaluation of the damage scenarios, trough the use of the GIS software proposed here, is essential for cost-benefit or multi-criteria analysis of risk mitigation alternatives. However, considering that quantitative assessment of flood damages scenarios is characterized by intrinsic uncertainty, a scheme has been developed to identify and quantify the role of the input parameters in the total uncertainty of flood loss model application in urban areas with mild terrain and complex topography. By the concept of parallel models, the contribution of different module and input parameters to the total uncertainty is quantified. The results of the present case study have exhibited a high epistemic uncertainty on the damage estimation module and, in particular, on the type and form of the utilized damage functions, which have been adapted and transferred from different geographic and socio-economic contexts because there aren't depth-damage functions that are specifically developed for Italy. Considering that uncertainty and sensitivity depend considerably on local characteristics, the epistemic uncertainty associated with the risk estimate is reduced by introducing additional information into the risk analysis. In the light of the obtained results, it is evident the need to produce and disseminate (open) data to develop micro-scale vulnerability curves. Moreover, the urgent need to push

Uncertainty analysis in estimating Japanese ingestion of global fallout Cs-137 using health risk evaluation model

International Nuclear Information System (INIS)

Shimada, Yoko; Morisawa, Shinsuke

1998-01-01

Most of model estimation of the environmental contamination includes some uncertainty associated with the parameter uncertainty in the model. In this study, the uncertainty was analyzed in a model for evaluating the ingestion of radionuclide caused by the long-term global low-level radioactive contamination by using various uncertainty analysis methods: the percentile estimate, the robustness analysis and the fuzzy estimate. The model is mainly composed of five sub-models, which include their own uncertainty; we also analyzed the uncertainty. The major findings obtained in this study include that the possibility of the discrepancy between predicted value by the model simulation and the observed data is less than 10%; the uncertainty of the predicted value is higher before 1950 and after 1980; the uncertainty of the predicted value can be reduced by decreasing the uncertainty of some environmental parameters in the model; the reliability of the model can definitively depend on the following environmental factors: direct foliar absorption coefficient, transfer factor of radionuclide from stratosphere down to troposphere, residual rate by food processing and cooking, transfer factor of radionuclide in ocean and sedimentation in ocean. (author)

Unquestioned answers or unanswered questions: beliefs about science guide responses to uncertainty in climate change risk communication.

Science.gov (United States)

Rabinovich, Anna; Morton, Thomas A

2012-06-01

In two experimental studies we investigated the effect of beliefs about the nature and purpose of science (classical vs. Kuhnian models of science) on responses to uncertainty in scientific messages about climate change risk. The results revealed a significant interaction between both measured (Study 1) and manipulated (Study 2) beliefs about science and the level of communicated uncertainty on willingness to act in line with the message. Specifically, messages that communicated high uncertainty were more persuasive for participants who shared an understanding of science as debate than for those who believed that science is a search for absolute truth. In addition, participants who had a concept of science as debate were more motivated by higher (rather than lower) uncertainty in climate change messages. The results suggest that achieving alignment between the general public's beliefs about science and the style of the scientific messages is crucial for successful risk communication in science. Accordingly, rather than uncertainty always undermining the effectiveness of science communication, uncertainty can enhance message effects when it fits the audience's understanding of what science is. © 2012 Society for Risk Analysis.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

International Nuclear Information System (INIS)

Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

2011-01-01

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. -- Highlights: → We model uncertainties on energy market prices and wind power production. → A hybrid intelligent approach generates price-wind power scenarios. → Risk aversion is also incorporated in the proposed stochastic programming approach. → A realistic case study, based on a wind farm in Portugal, is provided. → Our approach allows selecting the best solution according to the desired risk exposure level.

Risk assessment calculations using MEPAS, an accepted screening methodology, and an uncertainty analysis for the reranking of Waste Area Groupings at Oak Ridge National Laboratory, Oak Ridge, Tennessee

International Nuclear Information System (INIS)

Shevenell, L.; Hoffman, F.O.; MacIntosh, D.

1992-03-01

The Waste Area Groupings (WAGs) at the Oak Ridge National Laboratory (ORNL) were reranked with respect to on- and off-site human health risks using two different methods. Risks associated with selected contaminants from each WAG for occupants of WAG 2 or an off-site area were calculated using a modified formulation of the Multimedia Environmental Pollutant Assessment System (MEPAS) and a method suitable for screening, referred to as the ORNL/ESD method (the method developed by the Environmental Sciences Division at ORNL) in this report. Each method resulted in a different ranking of the WAGs. The rankings from the two methods are compared in this report. All risk assessment calculations, except the original MEPAS calculations, indicated that WAGs 1; 2, 6, 7 (WAGs 2, 6 and 7 as one combined WAG); and 4 pose the greatest potential threat to human health. However, the overall rankings of the WAGs using constant parameter values in the different methods were inconclusive because uncertainty in parameter values can change the calculated risk associated with particular pathways, and hence, the final rankings. Uncertainty analysis using uncertainties about all model parameters were used to reduce biases associated with parameter selection and to more reliably rank waste sites according to potential risks associated with site contaminants. Uncertainty analysis indicates that the WAGs should be considered for further investigation, or remediation, in the following order: (1) WAG 1; (2) WAGs 2, 6, and 7 (combined); and 4; (3) WAGs 3, 5, and 9; and, (4) WAG 8

Uncertainty, causality and decision: The case of social risks and nuclear risk in particular

International Nuclear Information System (INIS)

Lahidji, R.

2012-01-01

Probability and causality are two indispensable tools for addressing situations of social risk. Causal relations are the foundation for building risk assessment models and identifying risk prevention, mitigation and compensation measures. Probability enables us to quantify risk assessments and to calibrate intervention measures. It therefore seems not only natural, but also necessary to make the role of causality and probability explicit in the definition of decision problems in situations of social risk. Such is the aim of this thesis.By reviewing the terminology of risk and the logic of public interventions in various fields of social risk, we gain a better understanding of the notion and of the issues that one faces when trying to model it. We further elaborate our analysis in the case of nuclear safety, examining in detail how methods and policies have been developed in this field and how they have evolved through time. This leads to a number of observations concerning risk and safety assessments.Generalising the concept of intervention in a Bayesian network allows us to develop a variety of causal Bayesian networks adapted to our needs. In this framework, we propose a definition of risk which seems to be relevant for a broad range of issues. We then offer simple applications of our model to specific aspects of the Fukushima accident and other nuclear safety problems. In addition to specific lessons, the analysis leads to the conclusion that a systematic approach for identifying uncertainties is needed in this area. When applied to decision theory, our tool evolves into a dynamic decision model in which acts cause consequences and are causally interconnected. The model provides a causal interpretation of Savage's conceptual framework, solves some of its paradoxes and clarifies certain aspects. It leads us to considering uncertainty with regard to a problem's causal structure as the source of ambiguity in decision-making, an interpretation which corresponds to a

Risk assessment for improved treatment of health considerations in EIA

International Nuclear Information System (INIS)

Demidova, Olga; Cherp, Aleg

2005-01-01

Environmental Impact Assessment (EIA) and Risk Assessment (RA) processes are rarely used to complement each other despite potential benefits of such integration. This paper proposes a model for procedural and methodological integration of EIA and RA based on reported best practice approaches. The proposed model stipulates 'embedding' RA into EIA and is organized in accordance with the generic stages of the EIA process. The model forms the basis for the proposed Evaluation Package which can be used as a benchmarking tool for evaluating the effectiveness of integration of RA within particular EIAs. The current paper uses the package for evaluating seven Environmental Impact Statements (EISs) of waste incineration facilities in the UK produced between 1990 and 2000. Though RA was found to be an element of these EIAs, its prominence varied considerably from case to case. Systematic application of RA in accordance with the best practice was not observed. Particular omissions were demonstrated in assessing health impacts not directly associated with air emissions, identifying the receptors of health impacts (affected population), interpreting health impacts as health risks, dealing with uncertainties, and risk communications

Communicating Uncertainty about Climate Change for Application to Security Risk Management

Science.gov (United States)

Gulledge, J. M.

2011-12-01

The science of climate change has convincingly demonstrated that human activities, including the release of greenhouse gases, land-surface changes, particle emissions, and redistribution of water, are changing global and regional climates. Consequently, key institutions are now concerned about the potential social impacts of climate change. For example, the 2010 Quadrennial Defense Review Report from the U.S. Department of Defense states that "climate change, energy security, and economic stability are inextricably linked." Meanwhile, insured losses from climate and weather-related natural disasters have risen dramatically over the past thirty years. Although these losses stem largely from socioeconomic trends, insurers are concerned that climate change could exacerbate this trend and render certain types of climate risk non-diversifiable. Meanwhile, the climate science community-broadly defined as physical, biological, and social scientists focused on some aspect of climate change-remains largely focused scholarly activities that are valued in the academy but not especially useful to decision makers. On the other hand, climate scientists who engage in policy discussions have generally permitted vested interests who support or oppose climate policies to frame the discussion of climate science within the policy arena. Such discussions focus on whether scientific uncertainties are sufficiently resolved to justify policy and the vested interests overstate or understate key uncertainties to support their own agendas. Consequently, the scientific community has become absorbed defending scientific findings to the near exclusion of developing novel tools to aid in risk-based decision-making. For example, the Intergovernmental Panel on Climate Change (IPCC), established expressly for the purpose of informing governments, has largely been engaged in attempts to reduce unavoidable uncertainties rather than helping the world's governments define a science-based risk

Risk estimation and decision making: the health effects on populations of exposure to low levels of ionizing radiation

International Nuclear Information System (INIS)

Fabrikant, J.I.

1982-01-01

Presented is a background for an understanding of the potential health effects in populations exposed to low-level radiation. Discussed is the knowledge about the health effects of low-level radiation. Comments on how the risks of radiation-induced cancer and genetically-related ill-health in man may be estimated, the sources of the scientific and epidemiological data, the dose-response models used, and the uncertainties which limit precise estimates of excess risks from radiation. Also discussed are the implications of numerical risk estimation for radiation protection and decision-making for public health policy

Ignoring correlation in uncertainty and sensitivity analysis in life cycle assessment: what is the risk?

Energy Technology Data Exchange (ETDEWEB)

Groen, E.A., E-mail: Evelyne.Groen@gmail.com [Wageningen University, P.O. Box 338, Wageningen 6700 AH (Netherlands); Heijungs, R. [Vrije Universiteit Amsterdam, De Boelelaan 1105, Amsterdam 1081 HV (Netherlands); Leiden University, Einsteinweg 2, Leiden 2333 CC (Netherlands)

2017-01-15

Life cycle assessment (LCA) is an established tool to quantify the environmental impact of a product. A good assessment of uncertainty is important for making well-informed decisions in comparative LCA, as well as for correctly prioritising data collection efforts. Under- or overestimation of output uncertainty (e.g. output variance) will lead to incorrect decisions in such matters. The presence of correlations between input parameters during uncertainty propagation, can increase or decrease the the output variance. However, most LCA studies that include uncertainty analysis, ignore correlations between input parameters during uncertainty propagation, which may lead to incorrect conclusions. Two approaches to include correlations between input parameters during uncertainty propagation and global sensitivity analysis were studied: an analytical approach and a sampling approach. The use of both approaches is illustrated for an artificial case study of electricity production. Results demonstrate that both approaches yield approximately the same output variance and sensitivity indices for this specific case study. Furthermore, we demonstrate that the analytical approach can be used to quantify the risk of ignoring correlations between input parameters during uncertainty propagation in LCA. We demonstrate that: (1) we can predict if including correlations among input parameters in uncertainty propagation will increase or decrease output variance; (2) we can quantify the risk of ignoring correlations on the output variance and the global sensitivity indices. Moreover, this procedure requires only little data. - Highlights: • Ignoring correlation leads to under- or overestimation of the output variance. • We demonstrated that the risk of ignoring correlation can be quantified. • The procedure proposed is generally applicable in life cycle assessment. • In some cases, ignoring correlation has a minimal effect on decision-making tools.

Uncertainty and Risk Management in Cyber Situational Awareness

Science.gov (United States)

Li, Jason; Ou, Xinming; Rajagopalan, Raj

Handling cyber threats unavoidably needs to deal with both uncertain and imprecise information. What we can observe as potential malicious activities can seldom give us 100% confidence on important questions we care about, e.g. what machines are compromised and what damage has been incurred. In security planning, we need information on how likely a vulnerability can lead to a successful compromise to better balance security and functionality, performance, and ease of use. These information are at best qualitative and are often vague and imprecise. In cyber situational awareness, we have to rely on such imperfect information to detect real attacks and to prevent an attack from happening through appropriate risk management. This chapter surveys existing technologies in handling uncertainty and risk management in cyber situational awareness.

Climate uncertainty and implications for U.S. state-level risk assessment through 2050.

Energy Technology Data Exchange (ETDEWEB)

Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.; Tidwell, Vincent Carroll; Stamber, Kevin Louis; Kelic, Andjelka; Backus, George A.; Warren, Drake E.; Zagonel, Aldo A.; Ehlen, Mark Andrew; Klise, Geoffrey T.; Vargas, Vanessa N.

2009-10-01

Decisions for climate policy will need to take place in advance of climate science resolving all relevant uncertainties. Further, if the concern of policy is to reduce risk, then the best-estimate of climate change impacts may not be so important as the currently understood uncertainty associated with realizable conditions having high consequence. This study focuses on one of the most uncertain aspects of future climate change - precipitation - to understand the implications of uncertainty on risk and the near-term justification for interventions to mitigate the course of climate change. We show that the mean risk of damage to the economy from climate change, at the national level, is on the order of one trillion dollars over the next 40 years, with employment impacts of nearly 7 million labor-years. At a 1% exceedance-probability, the impact is over twice the mean-risk value. Impacts at the level of individual U.S. states are then typically in the multiple tens of billions dollar range with employment losses exceeding hundreds of thousands of labor-years. We used results of the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) climate-model ensemble as the referent for climate uncertainty over the next 40 years, mapped the simulated weather hydrologically to the county level for determining the physical consequence to economic activity at the state level, and then performed a detailed, seventy-industry, analysis of economic impact among the interacting lower-48 states. We determined industry GDP and employment impacts at the state level, as well as interstate population migration, effect on personal income, and the consequences for the U.S. trade balance.

Sensitivity of Asteroid Impact Risk to Uncertainty in Asteroid Properties and Entry Parameters

Science.gov (United States)

Wheeler, Lorien; Mathias, Donovan; Dotson, Jessie L.; NASA Asteroid Threat Assessment Project

2017-10-01

A central challenge in assessing the threat posed by asteroids striking Earth is the large amount of uncertainty inherent throughout all aspects of the problem. Many asteroid properties are not well characterized and can range widely from strong, dense, monolithic irons to loosely bound, highly porous rubble piles. Even for an object of known properties, the specific entry velocity, angle, and impact location can swing the potential consequence from no damage to causing millions of casualties. Due to the extreme rarity of large asteroid strikes, there are also large uncertainties in how different types of asteroids will interact with the atmosphere during entry, how readily they may break up or ablate, and how much surface damage will be caused by the resulting airbursts or impacts.In this work, we use our Probabilistic Asteroid Impact Risk (PAIR) model to investigate the sensitivity of asteroid impact damage to uncertainties in key asteroid properties, entry parameters, or modeling assumptions. The PAIR model combines physics-based analytic models of asteroid entry and damage in a probabilistic Monte Carlo framework to assess the risk posed by a wide range of potential impacts. The model samples from uncertainty distributions of asteroid properties and entry parameters to generate millions of specific impact cases, and models the atmospheric entry and damage for each case, including blast overpressure, thermal radiation, tsunami inundation, and global effects. To assess the risk sensitivity, we alternately fix and vary the different input parameters and compare the effect on the resulting range of damage produced. The goal of these studies is to help guide future efforts in asteroid characterization and model refinement by determining which properties most significantly affect the potential risk.

The shape of uncertainty: underwriting decisions in the face of catastrophic risk

International Nuclear Information System (INIS)

Keykhah, M.

1998-01-01

This paper will explore how insurance and re-insurance underwriters price catastrophe risk from natural perils. It will first describe the theoretical nature of pricing risk, and outline studies of underwriting that propose analyzing decision making from a more behavioral than rational choice perspective. The paper then argues that in order to provide the appropriate context for probability (which is the focus of the studies on decision making under uncertainty), it may be helpful to look at the nature of choice within a market and organizational context. Moreover, the nature of probability itself is explored with a review to construct a broader analysis. Finally, it will be argued that the causal framework of the underwriter, in addition to inductive reasoning, provides a shape to uncertainty. (author)

Visualizing the uncertainty in the relationship between seasonal average climate and malaria risk.

Science.gov (United States)

MacLeod, D A; Morse, A P

2014-12-02

Around $1.6 billion per year is spent financing anti-malaria initiatives, and though malaria morbidity is falling, the impact of annual epidemics remains significant. Whilst malaria risk may increase with climate change, projections are highly uncertain and to sidestep this intractable uncertainty, adaptation efforts should improve societal ability to anticipate and mitigate individual events. Anticipation of climate-related events is made possible by seasonal climate forecasting, from which warnings of anomalous seasonal average temperature and rainfall, months in advance are possible. Seasonal climate hindcasts have been used to drive climate-based models for malaria, showing significant skill for observed malaria incidence. However, the relationship between seasonal average climate and malaria risk remains unquantified. Here we explore this relationship, using a dynamic weather-driven malaria model. We also quantify key uncertainty in the malaria model, by introducing variability in one of the first order uncertainties in model formulation. Results are visualized as location-specific impact surfaces: easily integrated with ensemble seasonal climate forecasts, and intuitively communicating quantified uncertainty. Methods are demonstrated for two epidemic regions, and are not limited to malaria modeling; the visualization method could be applied to any climate impact.

Uncertainty Analysis and Overtopping Risk Evaluation of Maroon Dam withMonte Carlo and Latin Hypercube Methods

Directory of Open Access Journals (Sweden)

J. M. Vali Samani

2016-02-01

Full Text Available Introduction: The greatest part of constructed dams belongs to embankment dams and there are many examples of their failures throughout history. About one-third of the world’s dam failures have been caused by flood overtopping, which indicates that flood overtopping is an important factor affecting reservoir projects’ safety. Moreover, because of a poor understanding of the randomness of floods, reservoir water levels during flood seasons are often lowered artificially in order to avoid overtopping and protect the lives and property of downstream residents. So, estimation of dam overtopping risk with regard to uncertainties is more important than achieving the dam’s safety. This study presents the procedure for risk evaluation of dam overtopping due to various uncertaintiess in inflows and reservoir initial condition. Materials and Methods: This study aims to present a practical approach and compare the different uncertainty analysis methods in the evaluation of dam overtopping risk due to flood. For this purpose, Monte Carlo simulation and Latin hypercube sampling methods were used to calculate the overtopping risk, evaluate the uncertainty, and calculate the highest water level during different flood events. To assess these methods from a practical point of view, the Maroon dam was chosen for the case study. Figure. 1 indicates the work procedure, including three parts: 1 Identification and evaluation of effective factors on flood routing and dam overtopping, 2 Data collection and analysis for reservoir routing and uncertainty analysis, 3 Uncertainty and risk analysis. Figure 1- Diagram of dam overtopping risk evaluation Results and Discussion: Figure 2 shows the results of the computed overtopping risks for the Maroon Dam without considering the wind effect, for the initial water level of 504 m as an example. As it is shown in Figure. 2, the trends of the risk curves computed by the different uncertainty analysis methods are similar

Oral-to-inhalation route extrapolation in occupational health risk assessment: A critical assessment

NARCIS (Netherlands)

Rennen, M.A.J.; Bouwman, T.; Wilschut, A.; Bessems, J.G.M.; Heer, C.de

2004-01-01

Due to a lack of route-specific toxicity data, the health risks resulting from occupational exposure are frequently assessed by route-to-route (RtR) extrapolation based on oral toxicity data. Insight into the conditions for and the uncertainties connected with the application of RtR extrapolation

Impacts of representing sea-level rise uncertainty on future flood risks: An example from San Francisco Bay.

Science.gov (United States)

Ruckert, Kelsey L; Oddo, Perry C; Keller, Klaus

2017-01-01

Rising sea levels increase the probability of future coastal flooding. Many decision-makers use risk analyses to inform the design of sea-level rise (SLR) adaptation strategies. These analyses are often silent on potentially relevant uncertainties. For example, some previous risk analyses use the expected, best, or large quantile (i.e., 90%) estimate of future SLR. Here, we use a case study to quantify and illustrate how neglecting SLR uncertainties can bias risk projections. Specifically, we focus on the future 100-yr (1% annual exceedance probability) coastal flood height (storm surge including SLR) in the year 2100 in the San Francisco Bay area. We find that accounting for uncertainty in future SLR increases the return level (the height associated with a probability of occurrence) by half a meter from roughly 2.2 to 2.7 m, compared to using the mean sea-level projection. Accounting for this uncertainty also changes the shape of the relationship between the return period (the inverse probability that an event of interest will occur) and the return level. For instance, incorporating uncertainties shortens the return period associated with the 2.2 m return level from a 100-yr to roughly a 7-yr return period (∼15% probability). Additionally, accounting for this uncertainty doubles the area at risk of flooding (the area to be flooded under a certain height; e.g., the 100-yr flood height) in San Francisco. These results indicate that the method of accounting for future SLR can have considerable impacts on the design of flood risk management strategies.

Impacts of representing sea-level rise uncertainty on future flood risks: An example from San Francisco Bay.

Directory of Open Access Journals (Sweden)

Kelsey L Ruckert

Full Text Available Rising sea levels increase the probability of future coastal flooding. Many decision-makers use risk analyses to inform the design of sea-level rise (SLR adaptation strategies. These analyses are often silent on potentially relevant uncertainties. For example, some previous risk analyses use the expected, best, or large quantile (i.e., 90% estimate of future SLR. Here, we use a case study to quantify and illustrate how neglecting SLR uncertainties can bias risk projections. Specifically, we focus on the future 100-yr (1% annual exceedance probability coastal flood height (storm surge including SLR in the year 2100 in the San Francisco Bay area. We find that accounting for uncertainty in future SLR increases the return level (the height associated with a probability of occurrence by half a meter from roughly 2.2 to 2.7 m, compared to using the mean sea-level projection. Accounting for this uncertainty also changes the shape of the relationship between the return period (the inverse probability that an event of interest will occur and the return level. For instance, incorporating uncertainties shortens the return period associated with the 2.2 m return level from a 100-yr to roughly a 7-yr return period (∼15% probability. Additionally, accounting for this uncertainty doubles the area at risk of flooding (the area to be flooded under a certain height; e.g., the 100-yr flood height in San Francisco. These results indicate that the method of accounting for future SLR can have considerable impacts on the design of flood risk management strategies.

Rethinking Risk: Prospect Theory Application in Health Message Framing Research.

Science.gov (United States)

Harrington, Nancy Grant; Kerr, Anna M

2017-02-01

Although prospect theory conceptualizes risk as uncertainty, health message framing research based on the theory typically conceptualizes risk as severity. This study reports the results of two experiments designed to explore these alternative conceptualizations of risk and their effect on health decision making. Participants (N 1  = 768, N 2  = 532) were randomly assigned to one of four conditions that presented a hypothetical scenario of a sexually transmitted disease (STD) outbreak. The conditions were defined by message prompt (deadly vs. easily curable STD) and response option frame (gain vs. loss). Participants selected which of two programs (certain outcome vs. uncertain outcome) they would prefer to combat the outbreak. Across both experiments, participants expressed strong preferences for certain (low risk) outcomes in the gain-framed conditions and no preferences in the loss-framed conditions. These differences held regardless of the consequence severity of the scenario. We discuss the theoretical and practical implications of these results and offer directions for future research.

The HTA Risk Analysis Chart: Visualising the Need for and Potential Value of Managed Entry Agreements in Health Technology Assessment.

Science.gov (United States)

Grimm, Sabine Elisabeth; Strong, Mark; Brennan, Alan; Wailoo, Allan J

2017-12-01

Recent changes to the regulatory landscape of pharmaceuticals may sometimes require reimbursement authorities to issue guidance on technologies that have a less mature evidence base. Decision makers need to be aware of risks associated with such health technology assessment (HTA) decisions and the potential to manage this risk through managed entry agreements (MEAs). This work develops methods for quantifying risk associated with specific MEAs and for clearly communicating this to decision makers. We develop the 'HTA risk analysis chart', in which we present the payer strategy and uncertainty burden (P-SUB) as a measure of overall risk. The P-SUB consists of the payer uncertainty burden (PUB), the risk stemming from decision uncertainty as to which is the truly optimal technology from the relevant set of technologies, and the payer strategy burden (PSB), the additional risk of approving a technology that is not expected to be optimal. We demonstrate the approach using three recent technology appraisals from the UK National Institute for Health and Clinical Excellence (NICE), each of which considered a price-based MEA. The HTA risk analysis chart was calculated using results from standard probabilistic sensitivity analyses. In all three HTAs, the new interventions were associated with substantial risk as measured by the P-SUB. For one of these technologies, the P-SUB was reduced to zero with the proposed price reduction, making this intervention cost effective with near complete certainty. For the other two, the risk reduced substantially with a much reduced PSB and a slightly increased PUB. The HTA risk analysis chart shows the risk that the healthcare payer incurs under unresolved decision uncertainty and when considering recommending a technology that is not expected to be optimal given current evidence. This allows the simultaneous consideration of financial and data-collection MEA schemes in an easily understood format. The use of HTA risk analysis charts will

Health information seeking and the World Wide Web: an uncertainty management perspective.

Science.gov (United States)

Rains, Stephen A

2014-01-01

Uncertainty management theory was applied in the present study to offer one theoretical explanation for how individuals use the World Wide Web to acquire health information and to help better understand the implications of the Web for information seeking. The diversity of information sources available on the Web and potential to exert some control over the depth and breadth of one's information-acquisition effort is argued to facilitate uncertainty management. A total of 538 respondents completed a questionnaire about their uncertainty related to cancer prevention and information-seeking behavior. Consistent with study predictions, use of the Web for information seeking interacted with respondents' desired level of uncertainty to predict their actual level of uncertainty about cancer prevention. The results offer evidence that respondents who used the Web to search for cancer information were better able than were respondents who did not seek information to achieve a level of uncertainty commensurate with the level of uncertainty they desired.

Residential building codes, affordability, and health protection: a risk-tradeoff approach.

Science.gov (United States)

Hammitt, J K; Belsky, E S; Levy, J I; Graham, J D

1999-12-01

Residential building codes intended to promote health and safety may produce unintended countervailing risks by adding to the cost of construction. Higher construction costs increase the price of new homes and may increase health and safety risks through "income" and "stock" effects. The income effect arises because households that purchase a new home have less income remaining for spending on other goods that contribute to health and safety. The stock effect arises because suppression of new-home construction leads to slower replacement of less safe housing units. These countervailing risks are not presently considered in code debates. We demonstrate the feasibility of estimating the approximate magnitude of countervailing risks by combining the income effect with three relatively well understood and significant home-health risks. We estimate that a code change that increases the nationwide cost of constructing and maintaining homes by $150 (0.1% of the average cost to build a single-family home) would induce offsetting risks yielding between 2 and 60 premature fatalities or, including morbidity effects, between 20 and 800 lost quality-adjusted life years (both discounted at 3%) each year the code provision remains in effect. To provide a net health benefit, the code change would need to reduce risk by at least this amount. Future research should refine these estimates, incorporate quantitative uncertainty analysis, and apply a full risk-tradeoff approach to real-world case studies of proposed code changes.

A risk-based method for planning of bus–subway corridor evacuation under hybrid uncertainties

International Nuclear Information System (INIS)

Lv, Y.; Yan, X.D.; Sun, W.; Gao, Z.Y.

2015-01-01

Emergencies involved in a bus–subway corridor system are associated with many processes and factors with social and economic implications. These processes and factors and their interactions are related to a variety of uncertainties. In this study, an interval chance-constrained integer programming (EICI) method is developed in response to such challenges for bus–subway corridor based evacuation planning. The method couples a chance-constrained programming with an interval integer programming model framework. It can thus deal with interval uncertainties that cannot be quantified with specified probability distribution functions. Meanwhile, it can also reflect stochastic features of traffic flow capacity, and thereby help examine the related violation risk of constraint. The EICI method is applied to a subway incident based evacuation case study. It is solved through an interactive algorithm that does not lead to more complicated intermediate submodels and has a relatively low computational requirement. A number of decision alternatives could be directly generated based on results from the EICI method. It is indicated that the solutions cannot only help decision makers identify desired population evacuation and vehicle dispatch schemes under hybrid uncertainties, but also provide bases for in-depth analyses of tradeoffs among evacuation plans, total evacuation time, and constraint-violation risks. - Highlights: • An inexact model is developed for the bus–subway corridor evacuation management. • It tackles stochastic and interval uncertainties in an integer programming problem. • It can examine violation risk of the roadway flow capacity related constraint. • It will help identify evacuation schemes under hybrid uncertainties

Are Polish firms risk-averting or risk-loving? : evidence on demand uncertainty and the capital-labour ratio in a transition economy

NARCIS (Netherlands)

Lensink, Robert; Murinde, Victor; Green, Christopher J.

1999-01-01

This paper investigates the effect of demand uncertainty on the capital-labour ratio of non-financial firms in Poland in order to infer the firms’ risk behaviour. A generic model is used to characterise a utility maximising firm in a transition economy with demand uncertainty and imperfect

Risk, Uncertainty and Precaution in Science: The Threshold of the Toxicological Concern Approach in Food Toxicology.

Science.gov (United States)

Bschir, Karim

2017-04-01

Environmental risk assessment is often affected by severe uncertainty. The frequently invoked precautionary principle helps to guide risk assessment and decision-making in the face of scientific uncertainty. In many contexts, however, uncertainties play a role not only in the application of scientific models but also in their development. Building on recent literature in the philosophy of science, this paper argues that precaution should be exercised at the stage when tools for risk assessment are developed as well as when they are used to inform decision-making. The relevance and consequences of this claim are discussed in the context of the threshold of the toxicological concern approach in food toxicology. I conclude that the approach does not meet the standards of an epistemic version of the precautionary principle.

Strategy for prioritizing whistleblowing with potential risks related to health services

Directory of Open Access Journals (Sweden)

Rafael Fernandes Barros

2017-11-01

Full Text Available Introduction: The Sanitary Surveillance of Health Services receives daily denunciations that refer to situations of risk that can hardly be measured quantitatively and attribute to some type of specific damage, in a context of great uncertainty. Objective: Considering such situations should be adequately addressed under the health risk paradigm, this work had as objective identifying notions about risk and its forms of analysis in the scope of Sanitary Surveillance of Health Services, as well as the existence of strategies and models in the analysis and treatment of denunciations. Method: An extensive literature review (through the Regional Portal of the BVS, databases SciELO and SciELO Books, and the journal Visa em Debate was conducted. Results: Although the results point to a relatively recent discussion regarding the model of potential risk analysis as an operational concept for the field of health surveillance in health services, there is no description of strategies or models applied to the analysis or treatment of whistleblowing. Thus, it is discussed and proposed a strategy for the initial analysis of reports with potential risk, which seeks to bring minimally objective criteria, in a field marked by enormous subjectivity. Conclusions: We conclude by indicating that the presented strategy is an initial instrument for the management of whistleblowing that must be discussed and adapted to the reality and context of health surveillance agencies.

A new perspective on human health risk assessment: Development of a time dependent methodology and the effect of varying exposure durations

International Nuclear Information System (INIS)

Siirila, Erica R.; Maxwell, Reed M.

2012-01-01

We present a new Time Dependent Risk Assessment (TDRA) that stochastically considers how joint uncertainty and inter-individual variability (JUV) associated with human health risk change as a function of time. In contrast to traditional, time independent assessments of risk, this new formulation relays information on when the risk occurs, how long the duration of risk is, and how risk changes with time. Because the true exposure duration (ED) is often uncertain in a risk assessment, we also investigate how varying the magnitude of fixed size durations (ranging between 5 and 70 years) of this parameter affects the distribution of risk in both the time independent and dependent methodologies. To illustrate this new formulation and to investigate these mechanisms for sensitivity, an example of arsenic contaminated groundwater is used in conjunction with two scenarios of different environmental concentration signals resulting from rate dependencies in geochemical reactions. Cancer risk is computed and compared using environmental concentration ensembles modeled with sorption as 1) a linear equilibrium assumption (LEA) and 2) first order kinetics (Kin). Results show that the information attained in the new time dependent methodology reveals how the uncertainty in other time-dependent processes in the risk assessment may influence the uncertainty in risk. We also show that individual susceptibility also affects how risk changes in time, information that would otherwise be lost in the traditional, time independent methodology. These results are especially pertinent for forecasting risk in time, and for risk managers who are assessing the uncertainty of risk. - Highlights: ► A human health, Time Dependent Risk Assessment (TDRA) methodology is presented. ► TDRA relays information on the magnitude, duration, and fluxes of risk in time. ► Kinetic and equilibrium concentration signals show sensitivity in TDRA results. ► In the TDRA results, individual susceptibility

A new perspective on human health risk assessment: Development of a time dependent methodology and the effect of varying exposure durations

Energy Technology Data Exchange (ETDEWEB)

Siirila, Erica R., E-mail: esiirila@mymail.mines.edu [Hydrologic Science and Engineering Program, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); Department of Geology and Geological Engineering, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); Maxwell, Reed M., E-mail: rmaxwell@mines.edu [Hydrologic Science and Engineering Program, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); Integrated Groundwater Modeling Center (IGWMC), Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States); Department of Geology and Geological Engineering, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401 (United States)

2012-08-01

We present a new Time Dependent Risk Assessment (TDRA) that stochastically considers how joint uncertainty and inter-individual variability (JUV) associated with human health risk change as a function of time. In contrast to traditional, time independent assessments of risk, this new formulation relays information on when the risk occurs, how long the duration of risk is, and how risk changes with time. Because the true exposure duration (ED) is often uncertain in a risk assessment, we also investigate how varying the magnitude of fixed size durations (ranging between 5 and 70 years) of this parameter affects the distribution of risk in both the time independent and dependent methodologies. To illustrate this new formulation and to investigate these mechanisms for sensitivity, an example of arsenic contaminated groundwater is used in conjunction with two scenarios of different environmental concentration signals resulting from rate dependencies in geochemical reactions. Cancer risk is computed and compared using environmental concentration ensembles modeled with sorption as 1) a linear equilibrium assumption (LEA) and 2) first order kinetics (Kin). Results show that the information attained in the new time dependent methodology reveals how the uncertainty in other time-dependent processes in the risk assessment may influence the uncertainty in risk. We also show that individual susceptibility also affects how risk changes in time, information that would otherwise be lost in the traditional, time independent methodology. These results are especially pertinent for forecasting risk in time, and for risk managers who are assessing the uncertainty of risk. - Highlights: Black-Right-Pointing-Pointer A human health, Time Dependent Risk Assessment (TDRA) methodology is presented. Black-Right-Pointing-Pointer TDRA relays information on the magnitude, duration, and fluxes of risk in time. Black-Right-Pointing-Pointer Kinetic and equilibrium concentration signals show

Bridging the gap between academic research and regulatory health risk assessment of Endocrine Disrupting Chemicals.

Science.gov (United States)

Beronius, Anna; Hanberg, Annika; Zilliacus, Johanna; Rudén, Christina

2014-12-01

Regulatory risk assessment is traditionally based primarily on toxicity studies conducted according to standardized and internationally validated test guidelines. However, health risk assessment of endocrine disrupting chemicals (EDCs) is argued to rely on the efficient integration of findings from academic research. The aim of this review was to provide an overview of current developments to facilitate the use of academic research in regulatory risk assessment of chemicals and how certain aspects of study design and reporting are particularly important for the risk assessment process. By bridging the gap between academic research and regulatory health risk assessment of EDCs, scientific uncertainty in risk assessment conclusions can be reduced, allowing for better targeted policy decisions for chemical risk reduction. Copyright © 2014. Published by Elsevier Ltd.

An inexact mixed risk-aversion two-stage stochastic programming model for water resources management under uncertainty.

Science.gov (United States)

Li, W; Wang, B; Xie, Y L; Huang, G H; Liu, L

2015-02-01

Uncertainties exist in the water resources system, while traditional two-stage stochastic programming is risk-neutral and compares the random variables (e.g., total benefit) to identify the best decisions. To deal with the risk issues, a risk-aversion inexact two-stage stochastic programming model is developed for water resources management under uncertainty. The model was a hybrid methodology of interval-parameter programming, conditional value-at-risk measure, and a general two-stage stochastic programming framework. The method extends on the traditional two-stage stochastic programming method by enabling uncertainties presented as probability density functions and discrete intervals to be effectively incorporated within the optimization framework. It could not only provide information on the benefits of the allocation plan to the decision makers but also measure the extreme expected loss on the second-stage penalty cost. The developed model was applied to a hypothetical case of water resources management. Results showed that that could help managers generate feasible and balanced risk-aversion allocation plans, and analyze the trade-offs between system stability and economy.

Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors: Final Scientific/Technical Report

International Nuclear Information System (INIS)

Vierow, Karen; Aldemir, Tunc

2009-01-01

The project entitled, 'Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors', was conducted as a DOE NERI project collaboration between Texas A and M University and The Ohio State University between March 2006 and June 2009. The overall goal of the proposed project was to develop practical approaches and tools by which dynamic reliability and risk assessment techniques can be used to augment the uncertainty quantification process in probabilistic risk assessment (PRA) methods and PRA applications for Generation IV reactors. This report is the Final Scientific/Technical Report summarizing the project.

Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors: Final Scientific/Technical Report

Energy Technology Data Exchange (ETDEWEB)

Vierow, Karen; Aldemir, Tunc

2009-09-10

The project entitled, “Uncertainty Quantification in the Reliability and Risk Assessment of Generation IV Reactors”, was conducted as a DOE NERI project collaboration between Texas A&M University and The Ohio State University between March 2006 and June 2009. The overall goal of the proposed project was to develop practical approaches and tools by which dynamic reliability and risk assessment techniques can be used to augment the uncertainty quantification process in probabilistic risk assessment (PRA) methods and PRA applications for Generation IV reactors. This report is the Final Scientific/Technical Report summarizing the project.

Demonstration uncertainty/sensitivity analysis using the health and economic consequence model CRAC2

International Nuclear Information System (INIS)

Alpert, D.J.; Iman, R.L.; Johnson, J.D.; Helton, J.C.

1985-01-01

This paper summarizes a demonstration uncertainty/sensitivity analysis performed on the reactor accident consequence model CRAC2. The study was performed with uncertainty/sensitivity analysis techniques compiled as part of the MELCOR program. The principal objectives of the study were: 1) to demonstrate the use of the uncertainty/sensitivity analysis techniques on a health and economic consequence model, 2) to test the computer models which implement the techniques, 3) to identify possible difficulties in performing such an analysis, and 4) to explore alternative means of analyzing, displaying, and describing the results. Demonstration of the applicability of the techniques was the motivation for performing this study; thus, the results should not be taken as a definitive uncertainty analysis of health and economic consequences. Nevertheless, significant insights on health and economic consequence analysis can be drawn from the results of this type of study. Latin hypercube sampling (LHS), a modified Monte Carlo technique, was used in this study. LHS generates a multivariate input structure in which all the variables of interest are varied simultaneously and desired correlations between variables are preserved. LHS has been shown to produce estimates of output distribution functions that are comparable with results of larger random samples

Optimal hydro scheduling and offering strategies considering price uncertainty and risk management

International Nuclear Information System (INIS)

Catalão, J.P.S.; Pousinho, H.M.I.; Contreras, J.

2012-01-01

Hydro energy represents a priority in the energy policy of Portugal, with the aim of decreasing the dependence on fossil fuels. In this context, optimal hydro scheduling acquires added significance in moving towards a sustainable environment. A mixed-integer nonlinear programming approach is considered to enable optimal hydro scheduling for the short-term time horizon, including the effect of head on power production, start-up costs related to the units, multiple regions of operation, and constraints on discharge variation. As new contributions to the field, market uncertainty is introduced in the model via price scenarios and risk management is included using Conditional Value-at-Risk to limit profit volatility. Moreover, plant scheduling and pool offering by the hydro power producer are simultaneously considered to solve a realistic cascaded hydro system. -- Highlights: ► A mixed-integer nonlinear programming approach is considered for optimal hydro scheduling. ► Market uncertainty is introduced in the model via price scenarios. ► Risk management is included using conditional value-at-risk. ► Plant scheduling and pool offering by the hydro power producer are simultaneously considered. ► A realistic cascaded hydro system is solved.

Scientific uncertainties and climate risks

International Nuclear Information System (INIS)

Petit, M.

2005-01-01

Human activities have induced a significant change in the Earth's atmospheric composition and, most likely, this trend will increase throughout the coming decades. During the last decades, the mean temperature has actually increased by the expected amount. Moreover, the geographical distribution of the warming, and day-to-night temperature variation have evolved as predicted. The magnitude of those changes is relatively small for the time being, but is expected to increase alarmingly during the coming decades. Greenhouse warming is a representative example of the problems of sustainable development: long-term risks can be estimated on a rational basis from scientific laws alone, but the non-specialist is generally not prepared to understand the steps required. However, even the non-specialist has obviously the right to decide about his way of life and the inheritance that he would like to leave for his children, but it is preferable that he is fully informed before making his decisions. Dialog, mutual understanding and confidence must prevail between Science and Society to avoid irrational actions. Controversy among experts is quite frequent. In the case of greenhouse warming, a commendable collective expertise has drastically reduced possible confusion. The Intergovernmental Panel on Climate Change was created jointly by the World Meteorology Organization (WMO) and the UN Program for the Environment (UNEP). Its reports evaluate the state of knowledge on past and future global climate changes, their impact, and the possibility of controlling anthropogenic emissions. The main targeted readers are, nevertheless, non-specialists, who should be made aware of results deduced from approaches that they may not be able to follow step by step. Moreover, these results, in particular, future projections, are, and will remain, subject to some uncertainty, which a fair description of the state of knowledge must include. Many misunderstandings between writers and readers can

Risk management frameworks for human health and environmental risks.

Science.gov (United States)

Jardine, Cindy; Hrudey, Steve; Shortreed, John; Craig, Lorraine; Krewski, Daniel; Furgal, Chris; McColl, Stephen

2003-01-01

A comprehensive analytical review of the risk assessment, risk management, and risk communication approaches currently being undertaken by key national, provincial/state, territorial, and international agencies was conducted. The information acquired for review was used to identify the differences, commonalities, strengths, and weaknesses among the various approaches, and to identify elements that should be included in an effective, current, and comprehensive approach applicable to environmental, human health and occupational health risks. More than 80 agencies, organizations, and advisory councils, encompassing more than 100 risk documents, were examined during the period from February 2000 until November 2002. An overview was made of the most important general frameworks for risk assessment, risk management, and risk communication for human health and ecological risk, and for occupational health risk. In addition, frameworks for specific applications were reviewed and summarized, including those for (1)contaminated sites; (2) northern contaminants; (3) priority substances; (4) standards development; (5) food safety; (6) medical devices; (7) prescription drug use; (8) emergency response; (9) transportation; (10) risk communication. Twelve frameworks were selected for more extensive review on the basis of representation of the areas of human health, ecological, and occupational health risk; relevance to Canadian risk management needs; representation of comprehensive and well-defined approaches; generalizability with their risk areas; representation of "state of the art" in Canada, the United States, and/or internationally; and extent of usage of potential usage within Canada. These 12 frameworks were: 1. Framework for Environmental Health Risk Management (US Presidential/Congressional Commission on Risk Assessment and Risk Management, 1997). 2. Health Risk Determination: The Challenge of Health Protection (Health and Welfare Canada, 1990). 3. Health Canada Decision

Methodology evaluation of innovative projects under risk and uncertainty

Directory of Open Access Journals (Sweden)

2012-09-01

Full Text Available This article deals with problems connected with the assessment of innovative projects in the context of risk and uncertainty, topical issues of evaluation of innovative projects at the present stage of development of the Russian economy. By the example of the solution of the "crossing the river" is considering the possibility of using hierarchical models to address it. In what follows, and compares the priorities of different groups of factors are given by calculating the overall costs and benefits. The paper provides a rationale for combined use of four aspects: the beneficial aspects of the decision (the benefits and opportunities and negative (costs and risks that may lead to the decision in question.

Probabilistic evaluation of uncertainties and risks in aerospace components

Science.gov (United States)

Shah, A. R.; Shiao, M. C.; Nagpal, V. K.; Chamis, C. C.

1992-01-01

This paper summarizes a methodology developed at NASA Lewis Research Center which computationally simulates the structural, material, and load uncertainties associated with Space Shuttle Main Engine (SSME) components. The methodology was applied to evaluate the scatter in static, buckling, dynamic, fatigue, and damage behavior of the SSME turbo pump blade. Also calculated are the probability densities of typical critical blade responses, such as effective stress, natural frequency, damage initiation, most probable damage path, etc. Risk assessments were performed for different failure modes, and the effect of material degradation on the fatigue and damage behaviors of a blade were calculated using a multi-factor interaction equation. Failure probabilities for different fatigue cycles were computed and the uncertainties associated with damage initiation and damage propagation due to different load cycle were quantified. Evaluations on the effects of mistuned blades on a rotor were made; uncertainties in the excitation frequency were found to significantly amplify the blade responses of a mistuned rotor. The effects of the number of blades on a rotor were studied. The autocorrelation function of displacements and the probability density function of the first passage time for deterministic and random barriers for structures subjected to random processes also were computed. A brief discussion was included on the future direction of probabilistic structural analysis.

Review. Assessing uncertainty and risk in forest planning and decision support systems: review of classical methods and introduction of new approaches

Directory of Open Access Journals (Sweden)

M. Pasalodos-Tato

2013-07-01

Full Text Available Aim: Since forest planning is characterized by long time horizon and it typically involves large areas of land and numerous stakeholders, uncertainty and risk should play an important role when developing forest management plans. The aim of this study is to review different methods to deal with risk and uncertainty in forest planning, listing problems that forest managers may face during the preparation of management plans and trying to give recommendations in regard to the application of each method according to the problem case. The inclusion of risk and uncertainty in decision support systems is also analyzed.Area: It covers the temporal and spatial scale of forest planning, the spatial context, the participation process, the objectives dimensions and the good and services addressed.Material and methods: Several hundreds of articles dealing with uncertainty and risk were identified regarding different forestry-related topics and approaches. Form them, around 170 articles were further reviewed, categorized and evaluated.Main results: The study presents a thorough review and classification of methods and approaches to consider risk and uncertainty in forest planning. Moreover, new approaches are introduced, showing the opportunities that their application present in forest planning.Research highlights: The study can aid forest managers in the decision making process when designing a forest management plan considering risk and uncertainty.Keywords: operations research; optimal alternative; stochastic risk; endogenous risk; stand level; forest level.

Modeling the Near-Term Risk of Climate Uncertainty: Interdependencies among the U.S. States

Science.gov (United States)

Lowry, T. S.; Backus, G.; Warren, D.

2010-12-01

Decisions made to address climate change must start with an understanding of the risk of an uncertain future to human systems, which in turn means understanding both the consequence as well as the probability of a climate induced impact occurring. In other words, addressing climate change is an exercise in risk-informed policy making, which implies that there is no single correct answer or even a way to be certain about a single answer; the uncertainty in future climate conditions will always be present and must be taken as a working-condition for decision making. In order to better understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions, this study estimates the impacts from responses to climate change on U.S. state- and national-level economic activity by employing a risk-assessment methodology for evaluating uncertain future climatic conditions. Using the results from the Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment Report (AR4) as a proxy for climate uncertainty, changes in hydrology over the next 40 years were mapped and then modeled to determine the physical consequences on economic activity and to perform a detailed 70-industry analysis of the economic impacts among the interacting lower-48 states. The analysis determines industry-level effects, employment impacts at the state level, interstate population migration, consequences to personal income, and ramifications for the U.S. trade balance. The conclusions show that the average risk of damage to the U.S. economy from climate change is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs. Further analysis shows that an increase in uncertainty raises this risk. This paper will present the methodology behind the approach, a summary of the underlying models, as well as the path forward for improving the approach.

Mental Health Experiences of Older Adults Living with HIV: Uncertainty, Stigma, and Approaches to Resilience.

Science.gov (United States)

Furlotte, Charles; Schwartz, Karen

2017-06-01

This study describes the mental health experiences of older adults living with HIV in Ottawa. Eleven participants aged 52 to 67 completed in-depth personal interviews. Mental health concerns pervaded the lives of these older adults. We identified three central themes common to the participants' stories: uncertainty, stigma, and resilience. For some of these participants, uncertainty impacting mental health centred on unexpected survival; interpretation of one's symptoms; and medical uncertainty. Participants' experiences of stigma included discrimination in health care interactions; misinformation; feeling stigmatized due to aspects of their physical appearance; compounded stigma; and anticipated stigma. Participants reported using several coping strategies, which we frame as individual approaches to resilience. These strategies include reducing the space that HIV takes up in one's life; making lifestyle changes to accommodate one's illness; and engaging with social support. These findings inform understandings of services for people aging with HIV who may experience mental health concerns.

Perceived risk: rationality, uncertainty and scepticism

International Nuclear Information System (INIS)

Green, C.H.

1981-01-01

The subject is discussed under the headings: introduction; measuring what (deciding which outcomes are to be considered; personal safety, threat to health and safety (threat to society, threat to health)); accuracy of beliefs (distinction between immediate-in-effect hazards and delayed-in-effect hazards); the context of beliefs about risk (evolution of beliefs, changes in beliefs). Some references are made to nuclear power. (U.K.)

Assessing the reliability of dose coefficients for exposure to radioiodine by members of the public, accounting for dosimetric and risk model uncertainties.

Science.gov (United States)

Puncher, M; Zhang, W; Harrison, J D; Wakeford, R

2017-06-26

Assessments of risk to a specific population group resulting from internal exposure to a particular radionuclide can be used to assess the reliability of the appropriate International Commission on Radiological Protection (ICRP) dose coefficients used as a radiation protection device for the specified exposure pathway. An estimate of the uncertainty on the associated risk is important for informing judgments on reliability; a derived uncertainty factor, UF, is an estimate of the 95% probable geometric difference between the best risk estimate and the nominal risk and is a useful tool for making this assessment. This paper describes the application of parameter uncertainty analysis to quantify uncertainties resulting from internal exposures to radioiodine by members of the public, specifically 1, 10 and 20-year old females from the population of England and Wales. Best estimates of thyroid cancer incidence risk (lifetime attributable risk) are calculated for ingestion or inhalation of 129 I and 131 I, accounting for uncertainties in biokinetic model and cancer risk model parameter values. These estimates are compared with the equivalent ICRP derived nominal age-, sex- and population-averaged estimates of excess thyroid cancer incidence to obtain UFs. Derived UF values for ingestion or inhalation of 131 I for 1 year, 10-year and 20-year olds are around 28, 12 and 6, respectively, when compared with ICRP Publication 103 nominal values, and 9, 7 and 14, respectively, when compared with ICRP Publication 60 values. Broadly similar results were obtained for 129 I. The uncertainties on risk estimates are largely determined by uncertainties on risk model parameters rather than uncertainties on biokinetic model parameters. An examination of the sensitivity of the results to the risk models and populations used in the calculations show variations in the central estimates of risk of a factor of around 2-3. It is assumed that the direct proportionality of excess thyroid cancer

Economic–Environmental Sustainability in Building Projects: Introducing Risk and Uncertainty in LCCE and LCCA

Directory of Open Access Journals (Sweden)

Elena Fregonara

2018-06-01

Full Text Available The aim of this paper is to propose a methodology for supporting decision-making in the design stages of new buildings or in the retrofitting of existing heritages. The focus is on the evaluation of economic–environmental sustainability, considering the presence of risk and uncertainty. An application of risk analysis in conjunction with Life-Cycle Cost Analysis (LCCA is proposed for selecting the preferable solution between technological options, which represents a recent and poorly explored context of analysis. It is assumed that there is a presence of uncertainty in cost estimating, in terms of the Life-Cycle Cost Estimates (LCCEs and uncertainty in the technical performance of the life-cycle cost analysis. According to the probability analysis, which was solved through stochastic simulation and the Monte Carlo Method (MCM, risk and uncertainty are modeled as stochastic variables or as “stochastic relevant cost drivers”. Coherently, the economic–financial and energy–environmental sustainability is analyzed through the calculation of a conjoint “economic–environmental indicator”, in terms of the stochastic global cost. A case study of the multifunctional building glass façade project in Northern Italy is proposed. The application demonstrates that introducing flexibility into the input data and the duration of the service lives of components and the economic and environmental behavior of alternative scenarios can lead to opposite results compared to a deterministic analysis. The results give full evidence of the environmental variables’ capacity to significantly perturb the model output.

Margins for geometric uncertainty around organs at risk in radiotherapy

International Nuclear Information System (INIS)

McKenzie, Alan; Herk, Marcel van; Mijnheer, Ben

2002-01-01

Background and purpose: ICRU Report 62 suggests drawing margins around organs at risk (ORs) to produce planning organ at risk volumes (PRVs) to account for geometric uncertainty in the radiotherapy treatment process. This paper proposes an algorithm for drawing such margins, and compares the recommended margin widths with examples from clinical practice and discusses the limitations of the approach. Method: The use of the PRV defined in this way is that, despite the geometric uncertainties, the dose calculated within the PRV by the treatment planning system can be used to represent the dose in the OR with a certain confidence level. A suitable level is where, in the majority of cases (90%), the dose-volume histogram of the PRV will not under-represent the high-dose components in the OR. In order to provide guidelines on how to do this in clinical practice, this paper distinguishes types of OR in terms of the tolerance doses relative to the prescription dose and suggests appropriate margins for serial-structure and parallel-structure ORs. Results: In some instances of large and parallel ORs, the clinician may judge that the complication risk in omitting a margin is acceptable. Otherwise, for all types of OR, systematic, treatment preparation uncertainties may be accommodated by an OR→PRV margin width of 1.3Σ. Here, Σ is the standard deviation of the combined systematic (treatment preparation) uncertainties. In the case of serial ORs or small, parallel ORs, the effects of blurring caused by daily treatment execution errors (set-up and organ motion) should be taken into account. Near a region of high dose, blurring tends to shift the isodoses away from the unblurred edge as shown on the treatment planning system by an amount that may be represented by 0.5σ. This margin may be used either to increase or to decrease the margin already calculated for systematic uncertainties, depending upon the size of the tolerance dose relative to the detailed planned dose

APROBA-Plus: A probabilistic tool to evaluate and express uncertainty in hazard characterization and exposure assessment of substances.

Science.gov (United States)

Bokkers, Bas G H; Mengelers, Marcel J; Bakker, Martine I; Chiu, Weihsueh A; Slob, Wout

2017-12-01

To facilitate the application of probabilistic risk assessment, the WHO released the APROBA tool. This tool applies lognormal uncertainty distributions to the different aspects of the hazard characterization, resulting in a probabilistic health-based guidance value. The current paper describes an extension, APROBA-Plus, which combines the output from the probabilistic hazard characterization with the probabilistic exposure to rapidly characterize risk and its uncertainty. The uncertainty in exposure is graphically compared with the uncertainty in the target human dose, i.e. the dose that complies with the specified protection goals. APROBA-Plus is applied to several case studies, resulting in distinct outcomes and illustrating that APROBA-Plus could serve as a standard extension of routine risk assessments. By visualizing the uncertainties, APROBA-Plus provides a more transparent and informative outcome than the more usual deterministic approaches, so that risk managers can make better informed decisions. For example, APROBA-Plus can help in deciding whether risk-reducing measures are warranted or that a refined risk assessment would first be needed. If the latter, the tool can be used to prioritize possible refinements. APROBA-Plus may also be used to rank substances into different risk categories, based on potential health risks without being compromised by different levels of conservatism that may be associated with point estimates of risk. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessment and presentation of uncertainties in probabilistic risk assessment: how should this be done

International Nuclear Information System (INIS)

Garlick, A.R.; Holloway, N.J.

1987-01-01

Despite continuing improvements in probabilistic risk assessment (PRA) techniques, PRA results, particularly those including degraded core analysis, will have maximum uncertainties of several orders of magnitude. This makes the expression of results, a matter no less important than their estimation. We put forward some ideas on the assessment and expression of highly uncertain quantities, such as probabilities of outcomes of a severe accident. These do not form a consistent set, but rather a number of alternative approaches aimed at stimulating discussion. These include non-probability expressions, such as fuzzy logic or Schafer's support and plausibility which abandon the purely probabilistic expression of risk for a more flexible type of expression, in which other types of measure are possible. The 'risk equivalent plant' concepts represent the opposite approach. Since uncertainty in a risk measure is in itself a form of risk, an attempt is made to define a 'risk equivalent' which is a risk with perfectly defined parameters, regarded (by means of suitable methods of judgement) as 'equally undesirable' with the actual plant. Some guidelines are given on the use of Bayesian methods in data-free or limited data situations. (author)

Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory

Energy Technology Data Exchange (ETDEWEB)

Chen, Qiuwen, E-mail: qchen@rcees.ac.cn [RCEES, Chinese Academy of Sciences, Shuangqinglu 18, Beijing 10085 (China); China Three Gorges University, Daxuelu 8, Yichang 443002 (China); CEER, Nanjing Hydraulics Research Institute, Guangzhoulu 223, Nanjing 210029 (China); Rui, Han; Li, Weifeng; Zhang, Yanhui [RCEES, Chinese Academy of Sciences, Shuangqinglu 18, Beijing 10085 (China)

2014-06-01

Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004–2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial–temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial–temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. - Highlights: • An innovative method is developed to analyze algal bloom risks with uncertainties. • The algal blooms in Taihu Lake showed obvious spatial and temporal patterns. • The lake is mainly characterized as moderate bloom but with high uncertainty. • Severe bloom with low uncertainty appeared occasionally in the northwest part. • The results provide important information to bloom monitoring and management.

Public Health Concern on Fukushima Radiation Risks in Korea and Response Strategies

Energy Technology Data Exchange (ETDEWEB)

Lee, Chaewon [Korea Institute of Radiological and Medical Sciences, 75 Nowon-Ro, Seoul 139-781 (Korea, Republic of)

2014-07-01

This paper reviews the characteristics of public perception on radiation risks by Fukushima Daiichi nuclear power plant accident and aims to suggest the appropriate strategies for minimizing social anxiety and managing the risk effectively on the basis of those features. In South Korea, the nearest country to Japan, fishery sales decreased 20% in 2013 due to consumers' fears over radiation contaminated seafood products. Public health concern is also increasing. The characteristics of public perception on the risk are the key factors of social anxiety, which are 'ongoing hazard' and 'uncertainty'. They can be translated same as the concepts of 'fear' and 'unknown risk', the psychometric factors of risk perception described in Slovic (1989)'s qualitative characteristics. News on a series of hazardous situations such as radioactive water leaks or radioactive steam at Fukushima is continually reported. Noting no expectation of accident settlement in near future, media coverage which has the expression of 'the maximum permissible level of radiation' without any translation of the measured dosimetric quantity causes the public's phobic fear. Uncertainties on health risks of low dose ionizing radiation in humans are not only the causes of fear but the challenges in building trust in risk communications. Rumours appear under ambiguous and uncertain situation with a lack of information. The communications among public authorities, related institutes, experts and the public become very important since the public health concern on radiation contamination turns into attention to the system of inspection, distribution, and regulation of imported food. The public shows deep interest in the safety standard of guidelines used in regulatory policy and safety management, which leads to a desire for participation in policy making process. Situational crisis communication theory can be applied to the situation quoted and

Estimate of the uncertainties in the relative risk of secondary malignant neoplasms following proton therapy and intensity-modulated photon therapy

International Nuclear Information System (INIS)

Fontenot, Jonas D; Bloch, Charles; Followill, David; Titt, Uwe; Newhauser, Wayne D

2010-01-01

Theoretical calculations have shown that proton therapy can reduce the incidence of radiation-induced secondary malignant neoplasms (SMN) compared with photon therapy for patients with prostate cancer. However, the uncertainties associated with calculations of SMN risk had not been assessed. The objective of this study was to quantify the uncertainties in projected risks of secondary cancer following contemporary proton and photon radiotherapies for prostate cancer. We performed a rigorous propagation of errors and several sensitivity tests to estimate the uncertainty in the ratio of relative risk (RRR) due to the largest contributors to the uncertainty: the radiation weighting factor for neutrons, the dose-response model for radiation carcinogenesis and interpatient variations in absorbed dose. The interval of values for the radiation weighting factor for neutrons and the dose-response model were derived from the literature, while interpatient variations in absorbed dose were taken from actual patient data. The influence of each parameter on a baseline RRR value was quantified. Our analysis revealed that the calculated RRR was insensitive to the largest contributors to the uncertainty. Uncertainties in the radiation weighting factor for neutrons, the shape of the dose-risk model and interpatient variations in therapeutic and stray doses introduced a total uncertainty of 33% to the baseline RRR calculation.

Making sense of perceptions of risk of diseases and vaccinations: a qualitative study combining models of health beliefs, decision-making and risk perception

Directory of Open Access Journals (Sweden)

Bond Lyndal

2011-12-01

Full Text Available Abstract Background Maintaining high levels of childhood vaccinations is important for public health. Success requires better understanding of parents' perceptions of diseases and consequent decisions about vaccinations, however few studies have considered this from the theoretical perspectives of risk perception and decision-making under uncertainty. The aim of this study was to examine the utility of subjective risk perception and decision-making theories to provide a better understanding of the differences between immunisers' and non-immunisers' health beliefs and behaviours. Methods In a qualitative study we conducted semi-structured in-depth interviews with 45 Australian parents exploring their experiences and perceptions of disease severity and susceptibility. Using scenarios about 'a new strain of flu' we explored how risk information was interpreted. Results We found that concepts of dread, unfamiliarity, and uncontrollability from the subjective perception of risk and ambiguity, optimistic control and omission bias from explanatory theories of decision-making under uncertainty were useful in understanding why immunisers, incomplete immunisers and non-immunisers interpreted severity and susceptibility to diseases and vaccine risk differently. Immunisers dreaded unfamiliar diseases whilst non-immunisers dreaded unknown, long term side effects of vaccines. Participants believed that the risks of diseases and complications from diseases are not equally spread throughout the community, therefore, when listening to reports of epidemics, it is not the number of people who are affected but the familiarity or unfamiliarity of the disease and the characteristics of those who have had the disease that prompts them to take preventive action. Almost all believed they themselves would not be at serious risk of the 'new strain of flu' but were less willing to take risks with their children's health. Conclusion This study has found that health messages

Making sense of perceptions of risk of diseases and vaccinations: a qualitative study combining models of health beliefs, decision-making and risk perception.

Science.gov (United States)

Bond, Lyndal; Nolan, Terry

2011-12-20

Maintaining high levels of childhood vaccinations is important for public health. Success requires better understanding of parents' perceptions of diseases and consequent decisions about vaccinations, however few studies have considered this from the theoretical perspectives of risk perception and decision-making under uncertainty. The aim of this study was to examine the utility of subjective risk perception and decision-making theories to provide a better understanding of the differences between immunisers' and non-immunisers' health beliefs and behaviours. In a qualitative study we conducted semi-structured in-depth interviews with 45 Australian parents exploring their experiences and perceptions of disease severity and susceptibility. Using scenarios about 'a new strain of flu' we explored how risk information was interpreted. We found that concepts of dread, unfamiliarity, and uncontrollability from the subjective perception of risk and ambiguity, optimistic control and omission bias from explanatory theories of decision-making under uncertainty were useful in understanding why immunisers, incomplete immunisers and non-immunisers interpreted severity and susceptibility to diseases and vaccine risk differently. Immunisers dreaded unfamiliar diseases whilst non-immunisers dreaded unknown, long term side effects of vaccines. Participants believed that the risks of diseases and complications from diseases are not equally spread throughout the community, therefore, when listening to reports of epidemics, it is not the number of people who are affected but the familiarity or unfamiliarity of the disease and the characteristics of those who have had the disease that prompts them to take preventive action. Almost all believed they themselves would not be at serious risk of the 'new strain of flu' but were less willing to take risks with their children's health. This study has found that health messages about the risks of disease which are communicated as though there

Incorporating the Technology Roadmap Uncertainties into the Project Risk Assessment

International Nuclear Information System (INIS)

Bonnema, B.E.

2002-01-01

This paper describes two methods, Technology Roadmapping and Project Risk Assessment, which were used to identify and manage the technical risks relating to the treatment of sodium bearing waste at the Idaho National Engineering and Environmental Laboratory. The waste treatment technology under consideration was Direct Vitrification. The primary objective of the Technology Roadmap is to identify technical data uncertainties for the technologies involved and to prioritize the testing or development studies to fill the data gaps. Similarly, project management's objective for a multi-million dollar construction project includes managing all the key risks in accordance to DOE O 413.3 - ''Program and Project Management for the Acquisition of Capital Assets.'' In the early stages, the Project Risk Assessment is based upon a qualitative analysis for each risk's probability and consequence. In order to clearly prioritize the work to resolve the technical issues identified in the Technology Roadmap, the issues must be cross- referenced to the project's Risk Assessment. This will enable the project to get the best value for the cost to mitigate the risks

Characterizing uncertainty when evaluating risk management metrics: risk assessment modeling of Listeria monocytogenes contamination in ready-to-eat deli meats.

Science.gov (United States)

Gallagher, Daniel; Ebel, Eric D; Gallagher, Owen; Labarre, David; Williams, Michael S; Golden, Neal J; Pouillot, Régis; Dearfield, Kerry L; Kause, Janell

2013-04-01

This report illustrates how the uncertainty about food safety metrics may influence the selection of a performance objective (PO). To accomplish this goal, we developed a model concerning Listeria monocytogenes in ready-to-eat (RTE) deli meats. This application used a second order Monte Carlo model that simulates L. monocytogenes concentrations through a series of steps: the food-processing establishment, transport, retail, the consumer's home and consumption. The model accounted for growth inhibitor use, retail cross contamination, and applied an FAO/WHO dose response model for evaluating the probability of illness. An appropriate level of protection (ALOP) risk metric was selected as the average risk of illness per serving across all consumed servings-per-annum and the model was used to solve for the corresponding performance objective (PO) risk metric as the maximum allowable L. monocytogenes concentration (cfu/g) at the processing establishment where regulatory monitoring would occur. Given uncertainty about model inputs, an uncertainty distribution of the PO was estimated. Additionally, we considered how RTE deli meats contaminated at levels above the PO would be handled by the industry using three alternative approaches. Points on the PO distribution represent the probability that - if the industry complies with a particular PO - the resulting risk-per-serving is less than or equal to the target ALOP. For example, assuming (1) a target ALOP of -6.41 log10 risk of illness per serving, (2) industry concentrations above the PO that are re-distributed throughout the remaining concentration distribution and (3) no dose response uncertainty, establishment PO's of -4.98 and -4.39 log10 cfu/g would be required for 90% and 75% confidence that the target ALOP is met, respectively. The PO concentrations from this example scenario are more stringent than the current typical monitoring level of an absence in 25 g (i.e., -1.40 log10 cfu/g) or a stricter criteria of absence

Dispelling urban myths about default uncertainty factors in chemical risk assessment--sufficient protection against mixture effects?

Science.gov (United States)

Martin, Olwenn V; Martin, Scholze; Kortenkamp, Andreas

2013-07-01

Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an

Flood risk assessment and robust management under deep uncertainty: Application to Dhaka City

Science.gov (United States)

Mojtahed, Vahid; Gain, Animesh Kumar; Giupponi, Carlo

2014-05-01

The socio-economic changes as well as climatic changes have been the main drivers of uncertainty in environmental risk assessment and in particular flood. The level of future uncertainty that researchers face when dealing with problems in a future perspective with focus on climate change is known as Deep Uncertainty (also known as Knightian uncertainty), since nobody has already experienced and undergone those changes before and our knowledge is limited to the extent that we have no notion of probabilities, and therefore consolidated risk management approaches have limited potential.. Deep uncertainty is referred to circumstances that analysts and experts do not know or parties to decision making cannot agree on: i) the appropriate models describing the interaction among system variables, ii) probability distributions to represent uncertainty about key parameters in the model 3) how to value the desirability of alternative outcomes. The need thus emerges to assist policy-makers by providing them with not a single and optimal solution to the problem at hand, such as crisp estimates for the costs of damages of natural hazards considered, but instead ranges of possible future costs, based on the outcomes of ensembles of assessment models and sets of plausible scenarios. Accordingly, we need to substitute optimality as a decision criterion with robustness. Under conditions of deep uncertainty, the decision-makers do not have statistical and mathematical bases to identify optimal solutions, while instead they should prefer to implement "robust" decisions that perform relatively well over all conceivable outcomes out of all future unknown scenarios. Under deep uncertainty, analysts cannot employ probability theory or other statistics that usually can be derived from observed historical data and therefore, we turn to non-statistical measures such as scenario analysis. We construct several plausible scenarios with each scenario being a full description of what may happen

The Roles of Three Types of Knowledge and Perceived Uncertainty in Explaining Risk Perception, Acceptability, and Self-Protective Response—A Case Study on Endocrine Disrupting Surfactants

Directory of Open Access Journals (Sweden)

Hien Ho

2018-02-01

Full Text Available The ubiquitous surfactants nonylphenol (NP and its ethoxylates (NPEOs, which are known as endocrine disrupters, have appeared in the lists of restricted chemical substances, monitoring programs, and environmental quality standards of many countries due to their adverse effects. Recent studies have reported alarming levels of NP, as the final metabolite of NPEOs, in Vietnamese urban waters, whilst response to this issue is negligible. With the aim of addressing how the public perceives and expects to avoid the risk of endocrine disrupting surfactants (EDSs, the study tested the hypothesized roles of specific knowledge, general knowledge, and perceived uncertainty using structural equation modelling. The findings revealed that different types of knowledge played certain roles in explaining risk perception, risk acceptability, and self-protective response, which are distinguished by experience amongst the public. Evidence of the mediating role that perceived uncertainty may play in the decrease of risk perception and the increase of risk unacceptance has been provided. The insights gained from the study may help answer why the public are in favor of taking non-diet-related self-protective measures rather than changing their dietary habits, which illustrates a comparison with the basis of health belief model. The needs for building cognitive capacity amongst the public, particularly pregnant women and young mothers, and risk communication concerning endocrine disrupting contamination linked to reproductive health are highlighted.

Making sense of perceptions of risk of diseases and vaccinations: a qualitative study combining models of health beliefs, decision-making and risk perception

OpenAIRE

Bond Lyndal; Nolan Terry

2011-01-01

Abstract Background Maintaining high levels of childhood vaccinations is important for public health. Success requires better understanding of parents' perceptions of diseases and consequent decisions about vaccinations, however few studies have considered this from the theoretical perspectives of risk perception and decision-making under uncertainty. The aim of this study was to examine the utility of subjective risk perception and decision-making theories to provide a better understanding o...

Experiences of Uncertainty in Men With an Elevated PSA.

Science.gov (United States)

Biddle, Caitlin; Brasel, Alicia; Underwood, Willie; Orom, Heather

2015-05-15

A significant proportion of men, ages 50 to 70 years, have, and continue to receive prostate specific antigen (PSA) tests to screen for prostate cancer (PCa). Approximately 70% of men with an elevated PSA level will not subsequently be diagnosed with PCa. Semistructured interviews were conducted with 13 men with an elevated PSA level who had not been diagnosed with PCa. Uncertainty was prominent in men's reactions to the PSA results, stemming from unanswered questions about the PSA test, PCa risk, and confusion about their management plan. Uncertainty was exacerbated or reduced depending on whether health care providers communicated in lay and empathetic ways, and provided opportunities for question asking. To manage uncertainty, men engaged in information and health care seeking, self-monitoring, and defensive cognition. Results inform strategies for meeting informational needs of men with an elevated PSA and confirm the primary importance of physician communication behavior for open information exchange and uncertainty reduction. © The Author(s) 2015.

A new uncertainty importance measure

International Nuclear Information System (INIS)

Borgonovo, E.

2007-01-01

Uncertainty in parameters is present in many risk assessment problems and leads to uncertainty in model predictions. In this work, we introduce a global sensitivity indicator which looks at the influence of input uncertainty on the entire output distribution without reference to a specific moment of the output (moment independence) and which can be defined also in the presence of correlations among the parameters. We discuss its mathematical properties and highlight the differences between the present indicator, variance-based uncertainty importance measures and a moment independent sensitivity indicator previously introduced in the literature. Numerical results are discussed with application to the probabilistic risk assessment model on which Iman [A matrix-based approach to uncertainty and sensitivity analysis for fault trees. Risk Anal 1987;7(1):22-33] first introduced uncertainty importance measures

Do (un)certainty appraisal tendencies reverse the influence of emotions on risk taking in sequential tasks?

Science.gov (United States)

Bagneux, Virginie; Bollon, Thierry; Dantzer, Cécile

2012-01-01

According to the Appraisal-Tendency Framework (Han, Lerner, & Keltner, 2007), certainty-associated emotions increase risk taking compared with uncertainty-associated emotions. To date, this general effect has only been shown in static judgement and decision-making paradigms; therefore, the present study tested the effect of certainty on risk taking in a sequential decision-making task. We hypothesised that the effect would be reversed due to the kind of processing involved, as certainty is considered to encourage heuristic processing that takes into account the emotional cues arising from previous decisions, whereas uncertainty leads to more systematic processing. One hundred and one female participants were induced to feel one of three emotions (film clips) before performing a decision-making task involving risk (Game of Dice Task; Brand et al., 2005). As expected, the angry and happy participants (certainty-associated emotions) were more likely than the fearful participants (uncertainty-associated emotion) to make safe decisions (vs. risky decisions).

Health risk assessment for nanoparticles: A case for using expert judgment

International Nuclear Information System (INIS)

Kandlikar, Milind; Ramachandran, Gurumurthy; Maynard, Andrew; Murdock, Barbara; Toscano, William A.

2007-01-01

Uncertainties in conventional quantitative risk assessment typically relate to values of parameters in risk models. For many environmental contaminants, there is a lack of sufficient information about multiple components of the risk assessment framework. In such cases, the use of default assumptions and extrapolations to fill in the data gaps is a common practice. Nanoparticle risks, however, pose a new form of risk assessment challenge. Besides a lack of data, there is deep scientific uncertainty regarding every aspect of the risk assessment framework: (a) particle characteristics that may affect toxicity; (b) their fate and transport through the environment; (c) the routes of exposure and the metrics by which exposure ought to be measured; (d) the mechanisms of translocation to different parts of the body; and (e) the mechanisms of toxicity and disease. In each of these areas, there are multiple and competing models and hypotheses. These are not merely parametric uncertainties but uncertainties about the choice of the causal mechanisms themselves and the proper model variables to be used, i.e., structural uncertainties. While these uncertainties exist for PM2.5 as well, risk assessment for PM2.5 has avoided dealing with these issues because of a plethora of epidemiological studies. However, such studies don't exist for the case of nanoparticles. Even if such studies are done in the future, they will be very specific to a particular type of engineered nanoparticle and not generalizable to other nanoparticles. Therefore, risk assessment for nanoparticles will have to deal with the various uncertainties that were avoided in the case of PM2.5. Consequently, uncertainties in estimating risks due to nanoparticle exposures may be characterized as 'extreme'. This paper proposes a methodology by which risk analysts can cope with such extreme uncertainty. One way to make these problems analytically tractable is to use expert judgment approaches to study the degree of

Risk classification and uncertainty propagation for virtual water distribution systems

International Nuclear Information System (INIS)

Torres, Jacob M.; Brumbelow, Kelly; Guikema, Seth D.

2009-01-01

While the secrecy of real water distribution system data is crucial, it poses difficulty for research as results cannot be publicized. This data includes topological layouts of pipe networks, pump operation schedules, and water demands. Therefore, a library of virtual water distribution systems can be an important research tool for comparative development of analytical methods. A virtual city, 'Micropolis', has been developed, including a comprehensive water distribution system, as a first entry into such a library. This virtual city of 5000 residents is fully described in both geographic information systems (GIS) and EPANet hydraulic model frameworks. A risk classification scheme and Monte Carlo analysis are employed for an attempted water supply contamination attack. Model inputs to be considered include uncertainties in: daily water demand, seasonal demand, initial storage tank levels, the time of day a contamination event is initiated, duration of contamination event, and contaminant quantity. Findings show that reasonable uncertainties in model inputs produce high variability in exposure levels. It is also shown that exposure level distributions experience noticeable sensitivities to population clusters within the contaminant spread area. High uncertainties in exposure patterns lead to greater resources needed for more effective mitigation strategies.

Local scale multiple quantitative risk assessment and uncertainty evaluation in a densely urbanised area (Brescia, Italy

Directory of Open Access Journals (Sweden)

S. Lari

2012-11-01

Full Text Available The study of the interactions between natural and anthropogenic risks is necessary for quantitative risk assessment in areas affected by active natural processes, high population density and strong economic activities.

We present a multiple quantitative risk assessment on a 420 km² high risk area (Brescia and surroundings, Lombardy, Northern Italy, for flood, seismic and industrial accident scenarios. Expected economic annual losses are quantified for each scenario and annual exceedance probability-loss curves are calculated. Uncertainty on the input variables is propagated by means of three different methodologies: Monte-Carlo-Simulation, First Order Second Moment, and point estimate.

Expected losses calculated by means of the three approaches show similar values for the whole study area, about 64 000 000 € for earthquakes, about 10 000 000 € for floods, and about 3000 € for industrial accidents. Locally, expected losses assume quite different values if calculated with the three different approaches, with differences up to 19%.

The uncertainties on the expected losses and their propagation, performed with the three methods, are compared and discussed in the paper. In some cases, uncertainty reaches significant values (up to almost 50% of the expected loss. This underlines the necessity of including uncertainty in quantitative risk assessment, especially when it is used as a support for territorial planning and decision making. The method is developed thinking at a possible application at a regional-national scale, on the basis of data available in Italy over the national territory.

Accounting for data uncertainties in comparing risks from energy systems

International Nuclear Information System (INIS)

Hauptmanns, Ulrich

1998-01-01

Data and models for risk comparisons are uncertain and this is true all the more the larger the time horizon contemplated. Statistical methods are presented for dealing with data uncertainties thus providing a broader foundation for decisions. Nevertheless, it has to be borne in mind that no method exists to account for the 'unforeseeable' which is always present in decision making with respect to the far future. (author)

Use of screening techniques to reduce uncertainty in risk assessment at a former manufactured gas plant site

International Nuclear Information System (INIS)

Logan, C.M.; Walden, R.H.; Baker, S.R.; Pekar, Z.; LaKind, J.S.; MacFarlane, I.D.

1995-01-01

Preliminary analysis of risks from a former manufactured gas plant (MGP) site revealed six media associated with potential exposure pathways: soils, air, surface water, groundwater, estuarine sediments, and aquatic biota. Contaminants of concern (COCs) include polycyclic aromatic hydrocarbons, volatile organic hydrocarbons, metals, cyanide, and PCBs. Available chemical data, including site-specific measurements and existing data from other sources (e.g., agency monitoring programs, Chesapeake Bay Program), were evaluated for potential utility in risk assessment. Where sufficient data existed, risk calculations were performed using central tendency and reasonable maximum exposure estimates. Where site-specific data were not available, risks were estimated using conservatively high default assumptions for dose and/or exposure duration. Because of the large number of potential exposure pathways and COCs, a sensitivity analysis was conducted to determine which information most influences risk assessment outcome so that any additional data collection to reduce uncertainty can be cost-effectively targeted. The sensitivity analysis utilized two types of information: (1) the impact that uncertainty in risk input values has on output risk estimates, and (2) the potential improvement in key risk input values, and consequently output values, if better site-specific data were available. A decision matrix using both quantitative and qualitative information was developed to prioritize sampling strategies to minimize uncertainty in the final risk assessment

Experiences of liver health related uncertainty and self-reported stress among people who inject drugs living with hepatitis C virus: a qualitative study.

Science.gov (United States)

Goutzamanis, Stelliana; Doyle, Joseph S; Thompson, Alexander; Dietze, Paul; Hellard, Margaret; Higgs, Peter

2018-04-02

People who inject drugs (PWID) are most at risk of hepatitis C virus infection in Australia. The introduction of transient elastography (TE) (measuring hepatitis fibrosis) and direct acting antiviral medications will likely alter the experience of living with hepatitis C. We aimed to explore positive and negative influences on wellbeing and stress among PWID with hepatitis C. The Treatment and Prevention (TAP) study examines the feasibility of treating hepatitis C mono-infected PWID in community settings. Semi-structured interviews were conducted with 16 purposively recruited TAP participants. Participants were aware of their hepatitis C seropositive status and had received fibrosis assessment (measured by TE) prior to interview. Questions were open-ended, focusing on the impact of health status on wellbeing and self-reported stress. Interviews were voice recorded, transcribed verbatim and thematically analysed, guided by Mishel's (1988) theory of Uncertainty in Illness. In line with Mishel's theory of Uncertainty in Illness all participants reported hepatitis C-related uncertainty, particularly mis-information or a lack of knowledge surrounding liver health and the meaning of TE results. Those with greater fibrosis experienced an extra layer of prognostic uncertainty. Experiences of uncertainty were a key motivation to seek treatment, which was seen as a way to regain some stability in life. Treatment completion alleviated hepatitis C-related stress, and promoted feelings of empowerment and confidence in addressing other life challenges. TE scores seemingly provide some certainty. However, when paired with limited knowledge, particularly among people with severe fibrosis, TE may be a source of uncertainty and increased personal stress. This suggests the need for simple education programs and resources on liver health to minimise stress.

Uncertainties in smart grids behavior and modeling: What are the risks and vulnerabilities? How to analyze them?

Energy Technology Data Exchange (ETDEWEB)

Zio, Enrico, E-mail: enrico.zio@ecp.fr [Ecole Centrale Paris - Supelec, Paris (France); Politecnico di Milano, Milano (Italy); Aven, Terje, E-mail: terje.aven@uis.no [University of Stavanger, Stavanger (Norway)

2011-10-15

This paper looks into the future world of smart grids from a rather different perspective than usual: that of uncertainties and the related risks and vulnerabilities. An analysis of the foreseen constituents of smart grids and of the technological, operational, economical and policy-driven challenges is carried out to identify and characterize the related uncertainties and associated risks and vulnerabilities. The focus is on the challenges posed to the representation and treatment of uncertainties in the performance assessment of such systems, given their complexity and high-level of integration of novel technologies. A general framework of analysis is proposed. - Highlights: > We have looked into the development and operation of smart grids for power distribution. > We have identified a number of uncertainties, which are expected to play an influential role. > We have provided some guidelines to address these issues, based on probability intervals.

Review. Assessing uncertainty and risk in forest planning and decision support systems: review of classical methods and introduction of innovative approaches

Energy Technology Data Exchange (ETDEWEB)

Pasalodos-Tato, M.; Makinen, A.; Garcia-Gonzalez, J.; Borges, J. G.; Lamas, T.; Eriksson, L. O.

2013-09-01

Aim: Since forest planning is characterized by long time horizon and it typically involves large areas of land and numerous stake holders, uncertainty and risk should play an important role when developing forest management plans. The aim of this study is to review different methods to deal with risk and uncertainty in forest planning, listing problems that forest managers may face during the preparation of management plans and trying to give recommendations in regard to the application of each method according to the problem case. The inclusion of risk and uncertainty in decision support systems is also analyzed. Area: It covers the temporal and spatial scale of forest planning, the spatial context, the participation process, the objectives dimensions and the good and services addressed. Material and methods: Several hundreds of articles dealing with uncertainty and risk were identified regarding different forestry-related topics and approaches. Form them, around 170 articles were further reviewed, categorized and evaluated. Main results: The study presents a thorough review and classification of methods and approaches to consider risk and uncertainty in forest planning. Moreover, new approaches are introduced, showing the opportunities that their application presents in forest planning. Research highlights: The study can aid forest managers in the decision making process when designing a forest management plan considering risk and uncertainty. (Author)

Investing in finite-life carbon emissions reduction program under risk and idiosyncratic uncertainty

International Nuclear Information System (INIS)

Fouilloux, Jessica; Moraux, Franck; Viviani, Jean-Laurent

2015-01-01

This paper aims at emphasizing the ability of new frameworks of real option model to highlight key characteristics of industrial Carbon Emissions Reduction Program investment decision. We develop both theoretical arguments and numerical simulations with structural parameters calibrated on real-life data. We find that both radical uncertainty and risk lead to speed-up green investments, compared to the predictions of real option models that are normally used in green investment literature. The conventional “wait and see” attitude, questioned in recent developments of the real option theory, is not validated. In conclusion, our results should foster companies to implement green investments and help governments to define appropriate incentives to encourage green investments. Of particular note, the paper highlights that finance theory is not necessarily an obstacle to green investment decisions. -- Highlights: •We use real option model to identify key features of CERP investment decision. •We determine the optimal carbon price threshold to undertake a CERP. •Investment decision is a non-monotonic function of idiosyncratic uncertainty. •Increasing uncertainty until a moderate level can accelerate investment decision. •Decreasing idiosyncratic risk can accelerate investment decision

Stochastic fuzzy environmental risk characterization of uncertainty and variability in risk assessments: A case study of polycyclic aromatic hydrocarbons in soil at a petroleum-contaminated site in China

International Nuclear Information System (INIS)

Hu, Yan; Wang, Zesen; Wen, Jingya; Li, Yu

2016-01-01

Highlights: • Deal with environmental quality guidelines absence in risk characterization. • Quantitative represention of uncertainty from environmental quality guidelines. • Quantitative represention of variability from contaminant exposure concentrations. • Establishment of stochastic-fuzzy environmental risk characterization approach framework. - Abstract: Better decisions are made using risk assessment models when uncertainty and variability are explicitly acknowledged. Uncertainty caused by a lack of uniform and scientifically supported environmental quality guidelines and variability in the degree of exposure of environmental systems to contaminants are here incorporated in a stochastic fuzzy environmental risk characterization (SFERC) approach. The approach is based on quotient probability distribution and environmental risk level fuzzy membership function methods. The SFERC framework was used to characterize the environmental risks posed by 16 priority polycyclic aromatic hydrocarbons (PAHs) in soil at a typical petroleum-contaminated site in China. This relied on integrating data from the literature and field and laboratory experiments. The environmental risk levels posed by the PAHs under four risk scenarios were determined using the SFERC approach, using “residential land” and “industrial land” environmental quality guidelines under “loose” and “strict” strictness parameters. The results showed that environmental risks posed by PAHs in soil are primarily caused by oil exploitation, traffic emissions, and coal combustion. The SFERC approach is an effective tool for characterizing uncertainty and variability in environmental risk assessments and for managing contaminated sites.

Stochastic fuzzy environmental risk characterization of uncertainty and variability in risk assessments: A case study of polycyclic aromatic hydrocarbons in soil at a petroleum-contaminated site in China

Energy Technology Data Exchange (ETDEWEB)

Hu, Yan [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environment Sciences, Beijing 100012 (China); Wang, Zesen [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Wen, Jingya [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Institute of Hydropower and Environment Research, Beijing 100012 (China); Li, Yu, E-mail: liyuxx8@hotmail.com [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China)

2016-10-05

Highlights: • Deal with environmental quality guidelines absence in risk characterization. • Quantitative represention of uncertainty from environmental quality guidelines. • Quantitative represention of variability from contaminant exposure concentrations. • Establishment of stochastic-fuzzy environmental risk characterization approach framework. - Abstract: Better decisions are made using risk assessment models when uncertainty and variability are explicitly acknowledged. Uncertainty caused by a lack of uniform and scientifically supported environmental quality guidelines and variability in the degree of exposure of environmental systems to contaminants are here incorporated in a stochastic fuzzy environmental risk characterization (SFERC) approach. The approach is based on quotient probability distribution and environmental risk level fuzzy membership function methods. The SFERC framework was used to characterize the environmental risks posed by 16 priority polycyclic aromatic hydrocarbons (PAHs) in soil at a typical petroleum-contaminated site in China. This relied on integrating data from the literature and field and laboratory experiments. The environmental risk levels posed by the PAHs under four risk scenarios were determined using the SFERC approach, using “residential land” and “industrial land” environmental quality guidelines under “loose” and “strict” strictness parameters. The results showed that environmental risks posed by PAHs in soil are primarily caused by oil exploitation, traffic emissions, and coal combustion. The SFERC approach is an effective tool for characterizing uncertainty and variability in environmental risk assessments and for managing contaminated sites.

Cognitive Processes in Decisions Under Risk Are Not the Same As in Decisions Under Uncertainty

Directory of Open Access Journals (Sweden)

Kirsten G Volz

2012-07-01

Full Text Available We deal with risk versus uncertainty, a distinction that is of fundamental importance for cognitive neuroscience yet largely neglected. In a world of risk (small world, all alternatives, consequences, and probabilities are known. In uncertain (large worlds, some of this information is unknown or unknowable. Most of cognitive neuroscience studies exclusively study the neural correlates for decisions under risk (e.g., lotteries, with the tacit implication that understanding these would lead to an understanding of decision making in general. First, we show that normative strategies for decisions under risk do not generalize to uncertain worlds, where simple heuristics are often the more accurate strategies. Second, we argue that the cognitive processes for making decisions in a world of risk are not the same as those for dealing with uncertainty. Because situations with known risks are the exception rather than the rule in human evolution, it is unlikely that our brains are adapted to them. We therefore suggest a paradigm shift towards studying decision processes in uncertain worlds and provide first examples.

Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management.

Science.gov (United States)

Oddo, Perry C; Lee, Ben S; Garner, Gregory G; Srikrishnan, Vivek; Reed, Patrick M; Forest, Chris E; Keller, Klaus

2017-09-05

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies. © 2017 Society for Risk Analysis.

Health risk assessment of dichloromethane (methylene chloride) in California ground water

International Nuclear Information System (INIS)

Bogen, K.T.; Hall, L.C.; Wright, K.; McKone, T.E.

1992-01-01

This document presents an assessment of potential health risks associated with exposure to dichloromethane (DCM) dissolved in California drinking water, focusing primarily on information relevant to a determination of potential cancer risk that may be associated with such exposures to DCM. This assessment is being provided to the California Environmental Protection Agency for the development of drinking-water standards to manage the health risks of DCM exposures. Other assessments required in the risk-management process include analyses of the technical and economic feasibilities of treating water supplies contaminated with DCM. The primary goal of this health-risk assessment is to evaluate scientifically plausible dose-response relationships for observed and potential DCM-induced cancer in order to define dose rates that can be used to establish standards that win protect members of the general public from this chronic toxicity endpoint resulting solely from groundwater-based exposures to DCM, based on information obtained from the scientific literature. The document consists of seven sections, plus one supporting appendix. Each section provides information that can be used to develop DCM drinking-water standards that will safeguard human health. Evaluation of this information in support of specific groundwater safety standards for DCM was not conducted in this report; rather, the basis for selection of alternative standards, along with a narrative description of certain key sources of underlying uncertainty, are presented for evaluation through the regulatory risk-management process

Demonstration uncertainty/sensitivity analysis using the health and economic consequence model CRAC2

International Nuclear Information System (INIS)

Alpert, D.J.; Iman, R.L.; Johnson, J.D.; Helton, J.C.

1984-12-01

The techniques for performing uncertainty/sensitivity analyses compiled as part of the MELCOR program appear to be well suited for use with a health and economic consequence model. Two replicate samples of size 50 gave essentially identical results, indicating that for this case, a Latin hypercube sample of size 50 seems adequate to represent the distribution of results. Though the intent of this study was a demonstration of uncertainty/sensitivity analysis techniques, a number of insights relevant to health and economic consequence modeling can be gleaned: uncertainties in early deaths are significantly greater than uncertainties in latent cancer deaths; though the magnitude of the source term is the largest source of variation in estimated distributions of early deaths, a number of additional parameters are also important; even with the release fractions for a full SST1, one quarter of the CRAC2 runs gave no early deaths; and comparison of the estimates of mean early deaths for a full SST1 release in this study with those of recent point estimates for similar conditions indicates that the recent estimates may be significant overestimations of early deaths. Estimates of latent cancer deaths, however, are roughly comparable. An analysis of the type described here can provide insights in a number of areas. First, the variability in the results gives an indication of the potential uncertainty associated with the calculations. Second, the sensitivity of the results to assumptions about the input variables can be determined. Research efforts can then be concentrated on reducing the uncertainty in the variables which are the largest contributors to uncertainty in results

Human Health Risk Assessment of Pharmaceuticals in Water: Issues and Challenges Ahead

Directory of Open Access Journals (Sweden)

Arun Kumar

2010-11-01

Full Text Available This study identified existing issues related to quantitative pharmaceutical risk assessment (QPhRA, hereafter for pharmaceuticals in water and proposed possible solutions by analyzing methodologies and findings of different published QPhRA studies. Retrospective site-specific QPhRA studies from different parts of the world (U.S.A., United Kingdom, Europe, India, etc. were reviewed in a structured manner to understand different assumptions, outcomes obtained and issues, identified/addressed/raised by the different QPhRA studies. Till date, most of the published studies have concluded that there is no appreciable risk to human health during environmental exposures of pharmaceuticals; however, attention is still required to following identified issues: (1 Use of measured versus predicted pharmaceutical concentration, (2 Identification of pharmaceuticals-of-concern and compounds needing special considerations, (3 Use of source water versus finished drinking water-related exposure scenarios, (4 Selection of representative exposure routes, (5 Valuation of uncertainty factors, and (6 Risk assessment for mixture of chemicals. To close the existing data and methodology gaps, this study proposed possible ways to address and/or incorporation these considerations within the QPhRA framework; however, more research work is still required to address issues, such as incorporation of short-term to long-term extrapolation and mixture effects in the QPhRA framework. Specifically, this study proposed a development of a new “mixture effects-related uncertainty factor” for mixture of chemicals (i.e., mixUFcomposite, similar to an uncertainty factor of a single chemical, within the QPhRA framework. In addition to all five traditionally used uncertainty factors, this uncertainty factor is also proposed to include concentration effects due to presence of different range of concentration levels of pharmaceuticals in a mixture. However, further work is required to

Optimal natural resources management under uncertainty with catastrophic risk

Energy Technology Data Exchange (ETDEWEB)

Motoh, Tsujimura [Graduate School of Economics, Kyoto University, Yoshida-honmochi, Sakyo-ku, Kyoto 606-8501 (Japan)

2004-05-01

We examine an optimal natural resources management problem under uncertainty with catastrophic risk and investigate the optimal rate of use of a natural resource. For this purpose, we use stochastic control theory. We assume that, until a catastrophic event occurs, the stock of the natural resource is governed by a stochastic differential equation. We describe the catastrophic phenomenon as a Poisson process. From this analysis, we show the optimal rate of use of the natural resource in explicit form. Furthermore, we present comparative static results for the optimal rate of use of the natural resource.

Optimal natural resources management under uncertainty with catastrophic risk

International Nuclear Information System (INIS)

Motoh, Tsujimura

2004-01-01

We examine an optimal natural resources management problem under uncertainty with catastrophic risk and investigate the optimal rate of use of a natural resource. For this purpose, we use stochastic control theory. We assume that, until a catastrophic event occurs, the stock of the natural resource is governed by a stochastic differential equation. We describe the catastrophic phenomenon as a Poisson process. From this analysis, we show the optimal rate of use of the natural resource in explicit form. Furthermore, we present comparative static results for the optimal rate of use of the natural resource

Uncertainty Estimation Cheat Sheet for Probabilistic Risk Assessment

Science.gov (United States)

Britton, Paul T.; Al Hassan, Mohammad; Ring, Robert W.

2017-01-01

"Uncertainty analysis itself is uncertain, therefore, you cannot evaluate it exactly," Source Uncertain Quantitative results for aerospace engineering problems are influenced by many sources of uncertainty. Uncertainty analysis aims to make a technical contribution to decision-making through the quantification of uncertainties in the relevant variables as well as through the propagation of these uncertainties up to the result. Uncertainty can be thought of as a measure of the 'goodness' of a result and is typically represented as statistical dispersion. This paper will explain common measures of centrality and dispersion; and-with examples-will provide guidelines for how they may be estimated to ensure effective technical contributions to decision-making.

Dispelling urban myths about default uncertainty factors in chemical risk assessment – sufficient protection against mixture effects?

Science.gov (United States)

2013-01-01

Assessing the detrimental health effects of chemicals requires the extrapolation of experimental data in animals to human populations. This is achieved by applying a default uncertainty factor of 100 to doses not found to be associated with observable effects in laboratory animals. It is commonly assumed that the toxicokinetic and toxicodynamic sub-components of this default uncertainty factor represent worst-case scenarios and that the multiplication of those components yields conservative estimates of safe levels for humans. It is sometimes claimed that this conservatism also offers adequate protection from mixture effects. By analysing the evolution of uncertainty factors from a historical perspective, we expose that the default factor and its sub-components are intended to represent adequate rather than worst-case scenarios. The intention of using assessment factors for mixture effects was abandoned thirty years ago. It is also often ignored that the conservatism (or otherwise) of uncertainty factors can only be considered in relation to a defined level of protection. A protection equivalent to an effect magnitude of 0.001-0.0001% over background incidence is generally considered acceptable. However, it is impossible to say whether this level of protection is in fact realised with the tolerable doses that are derived by employing uncertainty factors. Accordingly, it is difficult to assess whether uncertainty factors overestimate or underestimate the sensitivity differences in human populations. It is also often not appreciated that the outcome of probabilistic approaches to the multiplication of sub-factors is dependent on the choice of probability distributions. Therefore, the idea that default uncertainty factors are overly conservative worst-case scenarios which can account both for the lack of statistical power in animal experiments and protect against potential mixture effects is ill-founded. We contend that precautionary regulation should provide an

Uncertainties in geologic disposal of high-level wastes - groundwater transport of radionuclides and radiological consequences

International Nuclear Information System (INIS)

Kocher, D.C.; Sjoreen, A.L.; Bard, C.S.

1983-01-01

The analysis for radionuclide transport in groundwater considers models and methods for characterizing (1) the present geologic environment and its future evolution due to natural geologic processes and to repository development and waste emplacement, (2) groundwater hydrology, (3) radionuclide geochemistry, and (4) the interactions among these phenomena. The discussion of groundwater transport focuses on the nature of the sources of uncertainty rather than on quantitative estimates of their magnitude, because of the lack of evidence that current models can provide realistic quantitative predictions of radionuclide transport in groundwater for expected repository environments. The analysis for the long-term health risk to man following releases of long-lived radionuclides to the biosphere is more quantitative and involves estimates of uncertainties in (1) radionuclide concentrations in man's exposure environment, (2) radionuclide intake by exposed individuals per unit concentration in the environment, (3) the dose per unit intake, (4) the number of exposed individuals, and (5) the health risk per unit dose. For the important long-lived radionuclides in high-level waste, uncertainties in most of the different components of a calculation of individual and collective dose per unit release appear to be no more than two or three orders of magnitude; these uncertainties are certainly much less than uncertainties in predicting groundwater transport of radionuclides between a repository and the biosphere. Several limitations in current models for predicting the health risk to man per unit release to the biosphere are discussed

How risk and uncertainty is used in Supply Chain Management: a literature study

DEFF Research Database (Denmark)

Bøge Sørensen, Lars

2004-01-01

Keywords Supply Chain Management, Risk Management, Supply Chain Risk ManagementAbstract To comply with Supply Chain Management dogma companies have cut their inventoriesto a minimum, lead times have been shortened, new suppliers have been chosen and the customerportfolio has been reduced. All...... of these activities impose a great deal of risk on the firms,jeopardizing the survival of entire supply chains. In this article the author intends to investigateand document the use and meaning of Risk and Uncertainty within journals publishing material onSupply Chain Management and Logistics. Subsequently...... suggestions for further research areproposed - the integration of Risk Management into the discipline of Supply Chain Design....

A dominance-based approach to map risks of ecological invasions in the presence of severe uncertainty

Science.gov (United States)

Denys Yemshanov; Frank H. Koch; D. Barry Lyons; Mark Ducey; Klaus Koehler

2012-01-01

Aim Uncertainty has been widely recognized as one of the most critical issues in predicting the expansion of ecological invasions. The uncertainty associated with the introduction and spread of invasive organisms influences how pest management decision makers respond to expanding incursions. We present a model-based approach to map risk of ecological invasions that...

Incorporating uncertainties into risk assessment with an application to the exploratory studies facilities at Yucca Mountain

International Nuclear Information System (INIS)

Fathauer, P.M.

1995-08-01

A methodology that incorporates variability and reducible sources of uncertainty into the probabilistic and consequence components of risk was developed. The method was applied to the north tunnel of the Exploratory Studies Facility at Yucca Mountain in Nevada. In this assessment, variability and reducible sources of uncertainty were characterized and propagated through the risk assessment models using a Monte Carlo based software package. The results were then manipulated into risk curves at the 5% and 95% confidence levels for both the variability and overall uncertainty analyses, thus distinguishing between variability and reducible sources of uncertainty. In the Yucca Mountain application, the designation of the north tunnel as an item important to public safety, as defined by 10 CFR 60, was determined. Specifically, the annual frequency of a rock fall breaching a waste package causing an off-site dose of 500 mrem (5x10 -3 Sv) was calculated. The annual frequency, taking variability into account, ranged from 1.9x10 -9 per year at the 5% confidence level to 2.5x10 -9 per year at the 95% confidence level. The frequency range after including all uncertainty was 9.5x10 -10 to 1.8x10 -8 per year. The maximum observable frequency, at the 100% confidence level, was 4.9x10 -8 per year. This is below the 10 -6 per year frequency criteria of 10 CFR 60. Therefore, based on this work, the north tunnel does not fall under the items important to public safety designation for the event studied

TREATING UNCERTAINTIES IN A NUCLEAR SEISMIC PROBABILISTIC RISK ASSESSMENT BY MEANS OF THE DEMPSTER-SHAFER THEORY OF EVIDENCE

OpenAIRE

Lo , Chung-Kung; Pedroni , N.; Zio , Enrico

2014-01-01

International audience; The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk a...

Uncertainty Quantification Reveals the Importance of Data Variability and Experimental Design Considerations for in Silico Proarrhythmia Risk Assessment

Directory of Open Access Journals (Sweden)

Kelly C. Chang

2017-11-01

Full Text Available The Comprehensive in vitro Proarrhythmia Assay (CiPA is a global initiative intended to improve drug proarrhythmia risk assessment using a new paradigm of mechanistic assays. Under the CiPA paradigm, the relative risk of drug-induced Torsade de Pointes (TdP is assessed using an in silico model of the human ventricular action potential (AP that integrates in vitro pharmacology data from multiple ion channels. Thus, modeling predictions of cardiac risk liability will depend critically on the variability in pharmacology data, and uncertainty quantification (UQ must comprise an essential component of the in silico assay. This study explores UQ methods that may be incorporated into the CiPA framework. Recently, we proposed a promising in silico TdP risk metric (qNet, which is derived from AP simulations and allows separation of a set of CiPA training compounds into Low, Intermediate, and High TdP risk categories. The purpose of this study was to use UQ to evaluate the robustness of TdP risk separation by qNet. Uncertainty in the model parameters used to describe drug binding and ionic current block was estimated using the non-parametric bootstrap method and a Bayesian inference approach. Uncertainty was then propagated through AP simulations to quantify uncertainty in qNet for each drug. UQ revealed lower uncertainty and more accurate TdP risk stratification by qNet when simulations were run at concentrations below 5× the maximum therapeutic exposure (Cmax. However, when drug effects were extrapolated above 10× Cmax, UQ showed that qNet could no longer clearly separate drugs by TdP risk. This was because for most of the pharmacology data, the amount of current block measured was <60%, preventing reliable estimation of IC50-values. The results of this study demonstrate that the accuracy of TdP risk prediction depends both on the intrinsic variability in ion channel pharmacology data as well as on experimental design considerations that preclude an

Addressing uncertainties in the ERICA Integrated Approach

International Nuclear Information System (INIS)

Oughton, D.H.; Agueero, A.; Avila, R.; Brown, J.E.; Copplestone, D.; Gilek, M.

2008-01-01

Like any complex environmental problem, ecological risk assessment of the impacts of ionising radiation is confounded by uncertainty. At all stages, from problem formulation through to risk characterisation, the assessment is dependent on models, scenarios, assumptions and extrapolations. These include technical uncertainties related to the data used, conceptual uncertainties associated with models and scenarios, as well as social uncertainties such as economic impacts, the interpretation of legislation, and the acceptability of the assessment results to stakeholders. The ERICA Integrated Approach has been developed to allow an assessment of the risks of ionising radiation, and includes a number of methods that are intended to make the uncertainties and assumptions inherent in the assessment more transparent to users and stakeholders. Throughout its development, ERICA has recommended that assessors deal openly with the deeper dimensions of uncertainty and acknowledge that uncertainty is intrinsic to complex systems. Since the tool is based on a tiered approach, the approaches to dealing with uncertainty vary between the tiers, ranging from a simple, but highly conservative screening to a full probabilistic risk assessment including sensitivity analysis. This paper gives on overview of types of uncertainty that are manifest in ecological risk assessment and the ERICA Integrated Approach to dealing with some of these uncertainties

Model uncertainty in safety assessment

International Nuclear Information System (INIS)

Pulkkinen, U.; Huovinen, T.

1996-01-01

The uncertainty analyses are an essential part of any risk assessment. Usually the uncertainties of reliability model parameter values are described by probability distributions and the uncertainty is propagated through the whole risk model. In addition to the parameter uncertainties, the assumptions behind the risk models may be based on insufficient experimental observations and the models themselves may not be exact descriptions of the phenomena under analysis. The description and quantification of this type of uncertainty, model uncertainty, is the topic of this report. The model uncertainty is characterized and some approaches to model and quantify it are discussed. The emphasis is on so called mixture models, which have been applied in PSAs. Some of the possible disadvantages of the mixture model are addressed. In addition to quantitative analyses, also qualitative analysis is discussed shortly. To illustrate the models, two simple case studies on failure intensity and human error modeling are described. In both examples, the analysis is based on simple mixture models, which are observed to apply in PSA analyses. (orig.) (36 refs., 6 figs., 2 tabs.)

Model uncertainty in safety assessment

Energy Technology Data Exchange (ETDEWEB)

Pulkkinen, U; Huovinen, T [VTT Automation, Espoo (Finland). Industrial Automation

1996-01-01

The uncertainty analyses are an essential part of any risk assessment. Usually the uncertainties of reliability model parameter values are described by probability distributions and the uncertainty is propagated through the whole risk model. In addition to the parameter uncertainties, the assumptions behind the risk models may be based on insufficient experimental observations and the models themselves may not be exact descriptions of the phenomena under analysis. The description and quantification of this type of uncertainty, model uncertainty, is the topic of this report. The model uncertainty is characterized and some approaches to model and quantify it are discussed. The emphasis is on so called mixture models, which have been applied in PSAs. Some of the possible disadvantages of the mixture model are addressed. In addition to quantitative analyses, also qualitative analysis is discussed shortly. To illustrate the models, two simple case studies on failure intensity and human error modeling are described. In both examples, the analysis is based on simple mixture models, which are observed to apply in PSA analyses. (orig.) (36 refs., 6 figs., 2 tabs.).

Framing risk and uncertainty in social science articles on climate change, 1995-2012

NARCIS (Netherlands)

Shaw, C.; Hellsten, I.; Nerlich, B.; Crichton, J.; Candlin, C.N.; Firkins, A.S.

2016-01-01

The issue of climate change is intimately linked to notions of risk and uncertainty, concepts that pose challenges to climate science, climate change communication, and science-society interactions. While a large majority of climate scientists are increasingly certain about the causes of climate

Space Radiation Cancer, Circulatory Disease and CNS Risks for Near Earth Asteroid and Mars Missions: Uncertainty Estimates for Never-Smokers

Science.gov (United States)

Cucinotta, Francis A.; Chappell, Lori J.; Wang, Minli; Kim, Myung-Hee

2011-01-01

The uncertainties in estimating the health risks from galactic cosmic rays (GCR) and solar particle events (SPE) are a major limitation to the length of space missions and the evaluation of potential risk mitigation approaches. NASA limits astronaut exposures to a 3% risk of exposure induced cancer death (REID), and protects against uncertainties in risks projections using an assessment of 95% confidence intervals after propagating the error from all model factors (environment and organ exposure, risk coefficients, dose-rate modifiers, and quality factors). Because there are potentially significant late mortality risks from diseases of the circulatory system and central nervous system (CNS) which are less well defined than cancer risks, the cancer REID limit is not necessarily conservative. In this report, we discuss estimates of lifetime risks from space radiation and new estimates of model uncertainties are described. The key updates to the NASA risk projection model are: 1) Revised values for low LET risk coefficients for tissue specific cancer incidence, with incidence rates transported to an average U.S. population to estimate the probability of Risk of Exposure Induced Cancer (REIC) and REID. 2) An analysis of smoking attributable cancer risks for never-smokers that shows significantly reduced lung cancer risk as well as overall cancer risks from radiation compared to risk estimated for the average U.S. population. 3) Derivation of track structure based quality functions depends on particle fluence, charge number, Z and kinetic energy, E. 4) The assignment of a smaller maximum in quality function for leukemia than for solid cancers. 5) The use of the ICRP tissue weights is shown to over-estimate cancer risks from SPEs by a factor of 2 or more. Summing cancer risks for each tissue is recommended as a more accurate approach to estimate SPE cancer risks. 6) Additional considerations on circulatory and CNS disease risks. Our analysis shows that an individual s

Financial risk management for new technology integration in energy planning under uncertainty

International Nuclear Information System (INIS)

Ahmed, Sajjad; Elsholkami, Mohamed; Elkamel, Ali; Du, Juan; Ydstie, Erik B.; Douglas, Peter L.

2014-01-01

Highlights: • Financial risk associated with over or underproduction of electricity is studied. • A two-stage stochastic model that considers parameter uncertainties is developed. • The model was applied to a real case to meet projected electricity demand of a fleet of generating stations. • Incorporation of financial risk resulted in an increase in electricity cost. • The selection of technologies was the same as that obtained from a deterministic model. - Abstract: This paper proposes a new methodology to include financial risk management in the framework of two-stage stochastic programming for energy planning under uncertainties in demand and fuel price. A deterministic mixed integer linear programming formulation is extended to a two-stage stochastic programming model in order to take into account random parameters that have discrete and finite probabilistic distributions. This was applied to a case study focusing on planning the capacity supply to meet the projected electricity demand for the fleet of electricity generation stations owned and operated by Ontario Power Generation (OPG). The objective of the proposed mathematical model is to minimize cost subject to environmental constraints. The case study is investigated by considering only existing technologies and also by considering the integration of new technologies that help achieve stricter carbon reduction requirements

Distribution of uncertainties at the municipality level for flood risk modelling along the river Meuse: implications for policy-making

Science.gov (United States)

Pirotton, Michel; Stilmant, Frédéric; Erpicum, Sébastien; Dewals, Benjamin; Archambeau, Pierre

2016-04-01

Flood risk modelling has been conducted for the whole course of the river Meuse in Belgium. Major cities, such as Liege (200,000 inh.) and Namur (110,000 inh.), are located in the floodplains of river Meuse. Particular attention has been paid to uncertainty analysis and its implications for decision-making. The modelling chain contains flood frequency analysis, detailed 2D hydraulic computations, damage modelling and risk calculation. The relative importance of each source of uncertainty to the overall results uncertainty has been estimated by considering several alternate options for each step of the analysis: different distributions were considered in the flood frequency analysis; the influence of modelling assumptions and boundary conditions (e.g., steady vs. unsteady) were taken into account for the hydraulic computation; two different landuse classifications and two sets of damage functions were used; the number of exceedance probabilities involved in the risk calculation (by integration of the risk-curves) was varied. In addition, the sensitivity of the results with respect to increases in flood discharges was assessed. The considered increases are consistent with a "wet" climate change scenario for the time horizons 2021-2050 and 2071-2100 (Detrembleur et al., 2015). The results of hazard computation differ significantly between the upper and lower parts of the course of river Meuse in Belgium. In the former, inundation extents grow gradually as the considered flood discharge is increased (i.e. the exceedance probability is reduced), while in the downstream part, protection structures (mainly concrete walls) prevent inundation for flood discharges corresponding to exceedance probabilities of 0.01 and above (in the present climate). For higher discharges, large inundation extents are obtained in the floodplains. The highest values of risk (mean annual damage) are obtained in the municipalities which undergo relatively frequent flooding (upper part of the

Radical uncertainty, non-predictability, antifragility and risk-sharing Islamic finance

Directory of Open Access Journals (Sweden)

Umar Rafi

2016-12-01

Full Text Available Under conditions of radical uncertainty, risk sharing renders financial systems anti-fragile. Our goal in this paper is to show that risk-sharing Islamic finance (RSIF shares the characteristics defined by Taleb for an anti-fragile system, by mapping some characteristics of anti-fragility onto those of risk-sharing Islamic finance. A key insight around which such a connection can be established is by relating the principle of “no risk-no gain”from Islamic finance to the concept of skin-in-the-game from anti-fragility theory. The relationship is then extended to other characteristics of the two frameworks, to show that RSIF overlaps with anti-fragility over many dimensions. The broader case for an antifragile system includes another important characteristic, namely “soul in the game” and concern for social justice. It is the authors’ hope that emerging research on anti-fragility, combined with the emerging research on RSIF, can have a lasting impact on the field of finance by laying the foundations for a compelling case that it is time for humanity to replace the dominant debt-based risk transfer/risk shifting financial system with a system in which everyone shares the risks faced by society. JEL: D81, D89, E44, F34, G32

Uncertainties in radioecological assessment models

International Nuclear Information System (INIS)

Hoffman, F.O.; Miller, C.W.; Ng, Y.C.

1983-01-01

Environmental radiological assessments rely heavily on the use of mathematical models. The predictions of these models are inherently uncertain because models are inexact representations of real systems. The major sources of this uncertainty are related to bias in model formulation and imprecision in parameter estimation. The magnitude of uncertainty is a function of the questions asked of the model and the specific radionuclides and exposure pathways of dominant importance. It is concluded that models developed as research tools should be distinguished from models developed for assessment applications. Furthermore, increased model complexity does not necessarily guarantee increased accuracy. To improve the realism of assessment modeling, stochastic procedures are recommended that translate uncertain parameter estimates into a distribution of predicted values. These procedures also permit the importance of model parameters to be ranked according to their relative contribution to the overall predicted uncertainty. Although confidence in model predictions can be improved through site-specific parameter estimation and increased model validation, health risk factors and internal dosimetry models will probably remain important contributors to the amount of uncertainty that is irreducible. 41 references, 4 figures, 4 tables

Comparison of the effect of hazard and response/fragility uncertainties on core melt probability uncertainty

International Nuclear Information System (INIS)

Mensing, R.W.

1985-01-01

This report proposes a method for comparing the effects of the uncertainty in probabilistic risk analysis (PRA) input parameters on the uncertainty in the predicted risks. The proposed method is applied to compare the effect of uncertainties in the descriptions of (1) the seismic hazard at a nuclear power plant site and (2) random variations in plant subsystem responses and component fragility on the uncertainty in the predicted probability of core melt. The PRA used is that developed by the Seismic Safety Margins Research Program

Understanding and characterisation of the risks to human health from exposure to low levels of radiation

International Nuclear Information System (INIS)

Goodhead, D. T.

2009-01-01

Exposure to ionising radiation can lead to a wide variety of health effects. Cancer is judged to be the main risk from radiation at low doses and low dose rates, and controlling this risk has been the main factor in developing radiation protection practice. Conventional paradigms of radiobiology and radiation carcinogenesis have served to guide extrapolations of epidemiological data on exposed human populations, so as to estimate risks at low doses and low dose rates, to other types of ionising radiation and to non-uniform exposures. These paradigms are founded on a century of experimental and theoretical studies, but nevertheless there remain many uncertainties. Major assumptions and simplifications have been introduced to achieve a practical system of additive doses (and implied risks) for radiation protection. Advancing epidemiological studies and experimental research continue to reduce uncertainties in some areas while, in others, they raise new challenges to the generality and applicability of the conventional paradigms. (authors)

What do experts stakeholders think about chemical risks and uncertainties. An Internet survey

Energy Technology Data Exchange (ETDEWEB)

Assmuth, T.; Lyytimaeki, J.; Hilden, M.; Lindholm, M.; Munier, B.

2007-07-01

This report presents results from a web-based explorative survey on integrated risk assessment. The survey was conducted in the EU-funded project NoMiracle (Novel Methods for Risk Assessment of Cumulative Stressors in Europe) which develops methods for assessing cumulative risks from combined exposures to multiple stressors. The objectives of the survey were to give a general picture of perceptions and views among experts and stakeholders concerning risks, risk assessment and risk management. The survey focused on chemicals with an emphasis on information related to complex risks and uncertainties in a management context. The methodology of the survey combined traditional multiple choice questions and a novel approach that charted the importance of different types of information in two-dimensional graphs describing simultaneously use in regulatory procedures and public discussion. Another part was linked to new methods of presenting risks and explored the ranking of separate and cumulative risks in map grids. The survey was e-mailed to 952 recipients representing researchers, national and EU level administrators, enterprises, NGOs and international organizations, and most EU member states and some other countries. The response rate (26 %) can be considered acceptable but limits the possibilities to make quantitative claims concerning the views held by different groups although it gives an overview of the types of views one encounter among experts. A key finding was the pronounced variability of concepts and views regarding risks and uncertainties, and regarding information and knowledge about these. Opinions on risks and risk assessment, particularly on integrated risk assessment, on related principles, and on the role of experts are genuinely variable. They cannot be reduced to any simple model, and cannot (and need not) be dispelled in a forced manner. The observations should be taken into account in the development and application of novel methods for risk

Environmental health risk assessment and management for global climate change

Science.gov (United States)

Carter, P.

2014-12-01

This environmental health risk assessment and management approach for atmospheric greenhouse gas (GHG) pollution is based almost entirely on IPCC AR5 (2014) content, but the IPCC does not make recommendations. Large climate model uncertainties may be large environmental health risks. In accordance with environmental health risk management, we use the standard (IPCC-endorsed) formula of risk as the product of magnitude times probability, with an extremely high standard of precaution. Atmospheric GHG pollution, causing global warming, climate change and ocean acidification, is increasing as fast as ever. Time is of the essence to inform and make recommendations to governments and the public. While the 2ºC target is the only formally agreed-upon policy limit, for the most vulnerable nations, a 1.5ºC limit is being considered by the UNFCCC Secretariat. The Climate Action Network International (2014), representing civil society, recommends that the 1.5ºC limit be kept open and that emissions decline from 2015. James Hansen et al (2013) have argued that 1ºC is the danger limit. Taking into account committed global warming, its millennial duration, multiple large sources of amplifying climate feedbacks and multiple adverse impacts of global warming and climate change on crops, and population health impacts, all the IPCC AR5 scenarios carry extreme environmental health risks to large human populations and to the future of humanity as a whole. Our risk consideration finds that 2ºC carries high risks of many catastrophic impacts, that 1.5ºC carries high risks of many disastrous impacts, and that 1ºC is the danger limit. IPCC AR4 (2007) showed that emissions must be reversed by 2015 for a 2ºC warming limit. For the IPCC AR5 only the best-case scenario RCP2.6, is projected to stay under 2ºC by 2100 but the upper range is just above 2ºC. It calls for emissions to decline by 2020. We recommend that for catastrophic environmental health risk aversion, emissions decline

Integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management

International Nuclear Information System (INIS)

Catrinu, M.D.; Nordgard, D.E.

2011-01-01

Asset managers in electricity distribution companies generally recognize the need and the challenge of adding structure and a higher degree of formal analysis into the increasingly complex asset management decisions. This implies improving the present asset management practice by making the best use of the available data and expert knowledge and by adopting new methods for risk analysis and decision support and nevertheless better ways to document the decisions made. This paper discusses methods for integrating risk analysis and multi-criteria decision support under uncertainty in electricity distribution system asset management. The focus is on how to include the different company objectives and risk analyses into a structured decision framework when deciding how to handle the physical assets of the electricity distribution network. This paper presents an illustrative example of decision support for maintenance and reinvestment strategies based, using expert knowledge, simplified risk analyses and multi-criteria decision analysis under uncertainty.

Value at risk (VaR in uncertainty: Analysis with parametric method and black & scholes simulations

Directory of Open Access Journals (Sweden)

Humberto Banda Ortiz

2014-07-01

Full Text Available VaR is the most accepted risk measure worldwide and the leading reference in any risk management assessment. However, its methodology has important limitations which makes it unreliable in contexts of crisis or high uncertainty. For this reason, the aim of this work is to test the VaR accuracy when is employed in contexts of volatility, for which we compare the VaR outcomes in scenarios of both stability and uncertainty, using the parametric method and a historical simulation based on data generated with the Black & Scholes model. VaR main objective is the prediction of the highest expected loss for any given portfolio, but even when it is considered a useful tool for risk management under conditions of markets stability, we found that it is substantially inaccurate in contexts of crisis or high uncertainty. In addition, we found that the Black & Scholes simulations lead to underestimate the expected losses, in comparison with the parametric method and we also found that those disparities increase substantially in times of crisis. In the first section of this work we present a brief context of risk management in finance. In section II we present the existent literature relative to the VaR concept, its methods and applications. In section III we describe the methodology and assumptions used in this work. Section IV is dedicated to expose the findings. And finally, in Section V we present our conclusions.

Probabilistic health risk assessment of carcinogenic emissions from a MSW gasification plant.

Science.gov (United States)

Lonati, Giovanni; Zanoni, Francesca

2012-09-01

Health risk assessment due to the atmospheric emissions of carcinogenic pollutants (PCDD/Fs and Cd) from a waste gasification plant is performed by means of a probabilistic approach based on probability density functions for the description of the input data of the model parameters involved in the assessment. These functions incorporate both the epistemic and stochastic uncertainty of the input data (namely, the emission rate of the pollutants) and of all the parameters used for individual exposure assessment through the pathways of inhalation, soil ingestion and dermal contact, and diet. The uncertainty is propagated throughout the evaluation by Monte Carlo technique, resulting in the probability distribution of the individual risk. The median risk levels nearby the plant are in the 10(-8)-10(-10) range, ten-fold lower than the deterministic estimate based on precautionary values for the input data; however, the very upper percentiles (>95th) of the risk distribution can exceed the conventional 10(-6) reference value. The estimated risk is almost entirely determined by the Cd exposure through the diet; the pathways arising from PCDD/Fs exposure are without any practical significance, suggesting that the emission control should focus on Cd in order to reduce the carcinogenic risk. Risk variance decomposition shows the prevailing influence on the estimated risk of the Cd concentration at the emission stack: thus, for a more accurate risk assessment the efforts should focus primarily on the definition of its probability density function. Copyright © 2012 Elsevier Ltd. All rights reserved.

Bayesian uncertainty analyses of probabilistic risk models

International Nuclear Information System (INIS)

Pulkkinen, U.

1989-01-01

Applications of Bayesian principles to the uncertainty analyses are discussed in the paper. A short review of the most important uncertainties and their causes is provided. An application of the principle of maximum entropy to the determination of Bayesian prior distributions is described. An approach based on so called probabilistic structures is presented in order to develop a method of quantitative evaluation of modelling uncertainties. The method is applied to a small example case. Ideas for application areas for the proposed method are discussed

The Health Risk Assessment of Pb and Cr leachated from fly ash monolith landfill

International Nuclear Information System (INIS)

Hung, Ming-Lung; Wu, Sheng-Yao; Chen, Yen-Chuan; Shih, Hsiu-Ching; Yu, Yue-Hwa; Ma, Hwong-wen

2009-01-01

As of 2004, nearly two hundred thousand tons of fly ash monoliths are created each year in Taiwan to confine heavy metals for reducing the leaching quantity by precipitation. However, due to abnormal monolith fracture, poorly liner quality or exceeding usage over designed landfill capacity, serious groundwater pollution of the landfills has been reported. This research focuses on Pb and Cr leaching from monolithic landfill to assess the risk of groundwater pollution in the vicinity. The methodology combines water budget simulations using HELP model with fate and risk simulations using MMSOILS model for 5 kinds of landfill structures and 2 types of leaching models, and calculates the risk distribution over 400 grids in the down gradient direction of groundwater. The results demonstrated that the worst liner quality will cause the largest risk and the most significant exposure pathway is groundwater intake, which accounted for 98% of the total risk. Comparing Pb and Cr concentrations in the groundwater with the drinking water standards, only 14.25% of the total grids are found to be under 0.05 mg/L of Pb, and over 96.5% of the total grids are in the safety range of Cr. It indicates that Pb leaching from fly ash monolithic landfills may cause serious health risks. Without consideration of the parameters uncertainty, the cancer and noncancer risk of Pb with the sanitary landfill method was 4.23E-07 and 0.63, respectively, both under acceptable levels. However, by considering the parameters uncertainty, the non-carcinogenic risk of Pb became 1.43, exceeding the acceptable level. Only under the sealed landfill method was the hazard quotient below 1. It is important to use at least the sealed landfill for fly ash monoliths containing lead to effectively reduce health risks.

Estimation of Uncertainty in Risk Assessment of Hydrogen Applications

DEFF Research Database (Denmark)

Markert, Frank; Krymsky, V.; Kozine, Igor

2011-01-01

Hydrogen technologies such as hydrogen fuelled vehicles and refuelling stations are being tested in practice in a number of projects (e.g. HyFleet-Cute and Whistler project) giving valuable information on the reliability and maintenance requirements. In order to establish refuelling stations the ...... probability and the NUSAP concept to quantify uncertainties of new not fully qualified hydrogen technologies and implications to risk management.......Hydrogen technologies such as hydrogen fuelled vehicles and refuelling stations are being tested in practice in a number of projects (e.g. HyFleet-Cute and Whistler project) giving valuable information on the reliability and maintenance requirements. In order to establish refuelling stations...... the permitting authorities request qualitative and quantitative risk assessments (QRA) to show the safety and acceptability in terms of failure frequencies and respective consequences. For new technologies not all statistical data might be established or are available in good quality causing assumptions...

Contaminated site risk and uncertainty assessment for impacts on surface and groundwater

DEFF Research Database (Denmark)

Thomsen, Nanna Isbak

available between sites and choosing between the need for further investigation or remediation. This is a question of prioritizing the sites that pose the greatest risk, and it is a matter of making decisions under uncertainty. Both tasks require a structured assessment of the risk posed by the contaminated...... sites. In a conventional risk assessment of a contaminated site, risk is evaluated by assessing whether a concentration guideline is exceeded at a specific point of compliance in the water resource of interest. If the guideline is exceeded, it is concluded that the site poses a risk. However......, a contaminated site may pose a threat to multiple water resources, or multiple contaminated sites may threaten a single water resource. For more advanced risk assessments, it is therefore relevant to develop methods that can handle this challenge. In this thesis, four contributions are made to the field...

County-Level Climate Uncertainty for Risk Assessments: Volume 10 Appendix I - Historical Evaporation.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

2017-06-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

County-Level Climate Uncertainty for Risk Assessments: Volume 8 Appendix G - Historical Precipitation.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

2017-06-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

Information Seeking in Uncertainty Management Theory: Exposure to Information About Medical Uncertainty and Information-Processing Orientation as Predictors of Uncertainty Management Success.

Science.gov (United States)

Rains, Stephen A; Tukachinsky, Riva

2015-01-01

Uncertainty management theory outlines the processes through which individuals cope with health-related uncertainty. Information seeking has been frequently documented as an important uncertainty management strategy. The reported study investigates exposure to specific types of medical information during a search, and one's information-processing orientation as predictors of successful uncertainty management (i.e., a reduction in the discrepancy between the level of uncertainty one feels and the level one desires). A lab study was conducted in which participants were primed to feel more or less certain about skin cancer and then were allowed to search the World Wide Web for skin cancer information. Participants' search behavior was recorded and content analyzed. The results indicate that exposure to two health communication constructs that pervade medical forms of uncertainty (i.e., severity and susceptibility) and information-processing orientation predicted uncertainty management success.

An uncertainty inventory demonstration - a primary step in uncertainty quantification

Energy Technology Data Exchange (ETDEWEB)

Langenbrunner, James R. [Los Alamos National Laboratory; Booker, Jane M [Los Alamos National Laboratory; Hemez, Francois M [Los Alamos National Laboratory; Salazar, Issac F [Los Alamos National Laboratory; Ross, Timothy J [UNM

2009-01-01

Tools, methods, and theories for assessing and quantifying uncertainties vary by application. Uncertainty quantification tasks have unique desiderata and circumstances. To realistically assess uncertainty requires the engineer/scientist to specify mathematical models, the physical phenomena of interest, and the theory or framework for assessments. For example, Probabilistic Risk Assessment (PRA) specifically identifies uncertainties using probability theory, and therefore, PRA's lack formal procedures for quantifying uncertainties that are not probabilistic. The Phenomena Identification and Ranking Technique (PIRT) proceeds by ranking phenomena using scoring criteria that results in linguistic descriptors, such as importance ranked with words, 'High/Medium/Low.' The use of words allows PIRT to be flexible, but the analysis may then be difficult to combine with other uncertainty theories. We propose that a necessary step for the development of a procedure or protocol for uncertainty quantification (UQ) is the application of an Uncertainty Inventory. An Uncertainty Inventory should be considered and performed in the earliest stages of UQ.

Use of health effect risk estimates and uncertainty in formal regulatory proceedings: a case study involving atmospheric particulates

International Nuclear Information System (INIS)

Habegger, L.J.; Oezkaynak, A.H.

1984-01-01

Coal combustion particulates are released to the atmosphere by power plants supplying electrical to the nuclear fuel cycle. This paper presents estimates of the public health risks associated with the release of these particulates at a rate associated with the annual nuclear fuel production requirements for a nuclear power plan. Utilization of these risk assessments as a new component in the formal evaluation of total risks from nuclear power plants is discussed. 23 references, 3 tables

A scenario-based modeling approach for emergency evacuation management and risk analysis under multiple uncertainties

Energy Technology Data Exchange (ETDEWEB)

Lv, Y., E-mail: lvyying@hotmail.com [School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Huang, G.H., E-mail: huang@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Guo, L., E-mail: guoli8658@hotmail.com [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Li, Y.P., E-mail: yongping.li@iseis.org [MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Dai, C., E-mail: daichao321@gmail.com [College of Environmental Sciences and Engineering, Peking University, Beijing 100871 (China); Wang, X.W., E-mail: wangxingwei0812@gamil.com [State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875 (China); Sun, W., E-mail: sunwei@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada)

2013-02-15

Highlights: ► An interval-parameter joint-probabilistic integer programming method is developed. ► It is useful for nuclear emergency management practices under uncertainties. ► It can schedule optimal routes with maximizing evacuees during a finite time. ► Scenario-based analysis enhances robustness in controlling system risk. ► The method will help to improve the capability of disaster responses. -- Abstract: Nuclear emergency evacuation is important to prevent radioactive harms by hazardous materials and to limit the accidents’ consequences; however, uncertainties are involved in the components and processes of such a management system. In the study, an interval-parameter joint-probabilistic integer programming (IJIP) method is developed for emergency evacuation management under uncertainties. Optimization techniques of interval-parameter programming (IPP) and joint-probabilistic constrained (JPC) programming are incorporated into an integer linear programming framework, so that the approach can deal with uncertainties expressed as joint probability and interval values. The IJIP method can schedule the optimal routes to guarantee the maximum population evacuated away from the effected zone during a finite time. Furthermore, it can also facilitate post optimization analysis to enhance robustness in controlling system violation risk imposed on the joint-probabilistic constraints. The developed method has been applied to a case study of nuclear emergency management; meanwhile, a number of scenarios under different system conditions have been analyzed. It is indicated that the solutions are useful for evacuation management practices. The result of the IJIP method can not only help to raise the capability of disaster responses in a systematic manner, but also provide an insight into complex relationships among evacuation planning, resources utilizations, policy requirements and system risks.

Probabilistic accident consequence uncertainty analysis -- Late health effects uncertain assessment. Volume 2: Appendices

Energy Technology Data Exchange (ETDEWEB)

Little, M.P.; Muirhead, C.R. [National Radiological Protection Board (United Kingdom); Goossens, L.H.J.; Kraan, B.C.P.; Cooke, R.M. [Delft Univ. of Technology (Netherlands); Harper, F.T. [Sandia National Labs., Albuquerque, NM (United States); Hora, S.C. [Univ. of Hawaii, Hilo, HI (United States)

1997-12-01

The development of two new probabilistic accident consequence codes, MACCS and COSYMA, was completed in 1990. These codes estimate the consequence from the accidental releases of radiological material from hypothesized accidents at nuclear installations. In 1991, the US Nuclear Regulatory Commission and the Commission of the European Communities began cosponsoring a joint uncertainty analysis of the two codes. The ultimate objective of this joint effort was to systematically develop credible and traceable uncertainty distributions for the respective code input variables. A formal expert judgment elicitation and evaluation process was identified as the best technology available for developing a library of uncertainty distributions for these consequence parameters. This report focuses on the results of the study to develop distribution for variables related to the MACCS and COSYMA late health effects models. This volume contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures, (3) the rationales and results for the expert panel on late health effects, (4) short biographies of the experts, and (5) the aggregated results of their responses.

Economic risk-based analysis: Effect of technical and market price uncertainties on the production of glycerol-based isobutanol

DEFF Research Database (Denmark)

Loureiro da Costa Lira Gargalo, Carina; Gernaey, Krist; Sin, Gürkan

2016-01-01

to propagate the market price and technical uncertainties to the economic indicator calculations and to quantify the respective economic risk. The results clearly indicated that under the given market price uncertainties, the probability of obtaining a negative NPV is 0.95. This is a very high probability...

Public Health and Epidemiological Considerations For Avian Influenza Risk Mapping and Risk Assessment

Directory of Open Access Journals (Sweden)

Joseph P. Dudley

2008-12-01

Full Text Available Avian influenza viruses are now widely recognized as important threats to agricultural biosecurity and public health, and as the potential source for pandemic human influenza viruses. Human infections with avian influenza viruses have been reported from Asia (H5N1, H5N2, H9N2, Africa (H5N1, H10N7, Europe (H7N7, H7N3, H7N2, and North America (H7N3, H7N2, H11N9. Direct and indirect public health risks from avian influenzas are not restricted to the highly pathogenic H5N1 "bird flu" virus, and include low pathogenic as well as high pathogenic strains of other avian influenza virus subtypes, e.g., H1N1, H7N2, H7N3, H7N7, and H9N2. Research has shown that the 1918 Spanish Flu pandemic was caused by an H1N1 influenza virus of avian origins, and during the past decade, fatal human disease and human-to-human transmission has been confirmed among persons infected with H5N1 and H7N7 avian influenza viruses. Our ability to accurately assess and map the potential economic and public health risks associated with avian influenza outbreaks is currently constrained by uncertainties regarding key aspects of the ecology and epidemiology of avian influenza viruses in birds and humans, and the mechanisms by which highly pathogenic avian influenza viruses are transmitted between and among wild birds, domestic poultry, mammals, and humans. Key factors needing further investigation from a risk management perspective include identification of the driving forces behind the emergence and persistence of highly pathogenic avian influenza viruses within poultry populations, and a comprehensive understanding of the mechanisms regulating transmission of highly pathogenic avian influenza viruses between industrial poultry farms and backyard poultry flocks. More information is needed regarding the extent to which migratory bird populations to contribute to the transnational and transcontinental spread of highly pathogenic avian influenza viruses, and the potential for wild bird

Qualitative uncertainty analysis in probabilistic safety assessment context

International Nuclear Information System (INIS)

Apostol, M.; Constantin, M; Turcu, I.

2007-01-01

In Probabilistic Safety Assessment (PSA) context, an uncertainty analysis is performed either to estimate the uncertainty in the final results (the risk to public health and safety) or to estimate the uncertainty in some intermediate quantities (the core damage frequency, the radionuclide release frequency or fatality frequency). The identification and evaluation of uncertainty are important tasks because they afford credit to the results and help in the decision-making process. Uncertainty analysis can be performed qualitatively or quantitatively. This paper performs a preliminary qualitative uncertainty analysis, by identification of major uncertainty in PSA level 1- level 2 interface and in the other two major procedural steps of a level 2 PSA i.e. the analysis of accident progression and of the containment and analysis of source term for severe accidents. One should mention that a level 2 PSA for a Nuclear Power Plant (NPP) involves the evaluation and quantification of the mechanisms, amount and probabilities of subsequent radioactive material releases from the containment. According to NUREG 1150, an important task in source term analysis is fission products transport analysis. The uncertainties related to the isotopes distribution in CANDU NPP primary circuit and isotopes' masses transferred in the containment, using SOPHAEROS module from ASTEC computer code will be also presented. (authors)

Brine migration resulting from CO2 injection into saline aquifers – An approach to risk estimation including various levels of uncertainty

DEFF Research Database (Denmark)

Walter, Lena; Binning, Philip John; Oladyshkin, Sergey

2012-01-01

resulting from displaced brine. Quantifying risk on the basis of numerical simulations requires consideration of different kinds of uncertainties and this study considers both, scenario uncertainty and statistical uncertainty. Addressing scenario uncertainty involves expert opinion on relevant geological......Comprehensive risk assessment is a major task for large-scale projects such as geological storage of CO2. Basic hazards are damage to the integrity of caprocks, leakage of CO2, or reduction of groundwater quality due to intrusion of fluids. This study focuses on salinization of freshwater aquifers...... for large-scale 3D models including complex physics. Therefore, we apply a model reduction based on arbitrary polynomial chaos expansion combined with probabilistic collocation method. It is shown that, dependent on data availability, both types of uncertainty can be equally significant. The presented study...

How to manage project opportunity and risk why uncertainty management can be a much better approach than risk management

CERN Document Server

Ward, Stephen

2011-01-01

Since I wrote the Foreword for the second edition of this book, risk management processes have become much more widely used, but controversy about what should be done and how best to do it has grown. Managing risk is a risky business. Chapman and Ward provide an in-depth explanation of why it is important to understand and manage underlying uncertainty in all its forms, in order to realise opportunities more fully and enhance corporate performance. They show what best practice should look like. The implications go well beyond the conventional wisdom of project risk management, providing an enl

On treatment of uncertainty in system planning

International Nuclear Information System (INIS)

Flage, R.; Aven, T.

2009-01-01

In system planning and operation considerable efforts and resources are spent to reduce uncertainties, as a part of project management, uncertainty management and safety management. The basic idea seems to be that uncertainties are purely negative and should be reduced. In this paper we challenge this way of thinking, using a common industry practice as an example. In accordance with this industry practice, three uncertainty interval categories are used: ±40% intervals for the feasibility phase, ±30% intervals for the concept development phase and ±20% intervals for the engineering phase. The problem is that such a regime could easily lead to a conservative management regime encouraging the use of existing methods and tools, as new activities and novel solutions and arrangements necessarily mean increased uncertainties. In the paper we suggest an alternative approach based on uncertainty and risk descriptions, but having no predefined uncertainty reduction structures. The approach makes use of risk assessments and economic optimisation tools such as the expected net present value, but acknowledges the need for broad risk management processes which extend beyond the analyses. Different concerns need to be balanced, including economic aspects, uncertainties and risk, and practicability

Water shortage risk assessment considering large-scale regional transfers: a copula-based uncertainty case study in Lunan, China.

Science.gov (United States)

Gao, Xueping; Liu, Yinzhu; Sun, Bowen

2018-06-05

The risk of water shortage caused by uncertainties, such as frequent drought, varied precipitation, multiple water resources, and different water demands, brings new challenges to the water transfer projects. Uncertainties exist for transferring water and local surface water; therefore, the relationship between them should be thoroughly studied to prevent water shortage. For more effective water management, an uncertainty-based water shortage risk assessment model (UWSRAM) is developed to study the combined effect of multiple water resources and analyze the shortage degree under uncertainty. The UWSRAM combines copula-based Monte Carlo stochastic simulation and the chance-constrained programming-stochastic multiobjective optimization model, using the Lunan water-receiving area in China as an example. Statistical copula functions are employed to estimate the joint probability of available transferring water and local surface water and sampling from the multivariate probability distribution, which are used as inputs for the optimization model. The approach reveals the distribution of water shortage and is able to emphasize the importance of improving and updating transferring water and local surface water management, and examine their combined influence on water shortage risk assessment. The possible available water and shortages can be calculated applying the UWSRAM, also with the corresponding allocation measures under different water availability levels and violating probabilities. The UWSRAM is valuable for mastering the overall multi-water resource and water shortage degree, adapting to the uncertainty surrounding water resources, establishing effective water resource planning policies for managers and achieving sustainable development.

Analysis of algal bloom risk with uncertainties in lakes by integrating self-organizing map and fuzzy information theory.

Science.gov (United States)

Chen, Qiuwen; Rui, Han; Li, Weifeng; Zhang, Yanhui

2014-06-01

Algal blooms are a serious problem in waters, which damage aquatic ecosystems and threaten drinking water safety. However, the outbreak mechanism of algal blooms is very complex with great uncertainty, especially for large water bodies where environmental conditions have obvious variation in both space and time. This study developed an innovative method which integrated a self-organizing map (SOM) and fuzzy information diffusion theory to comprehensively analyze algal bloom risks with uncertainties. The Lake Taihu was taken as study case and the long-term (2004-2010) on-site monitoring data were used. The results showed that algal blooms in Taihu Lake were classified into four categories and exhibited obvious spatial-temporal patterns. The lake was mainly characterized by moderate bloom but had high uncertainty, whereas severe blooms with low uncertainty were observed in the northwest part of the lake. The study gives insight on the spatial-temporal dynamics of algal blooms, and should help government and decision-makers outline policies and practices on bloom monitoring and prevention. The developed method provides a promising approach to estimate algal bloom risks under uncertainties. Copyright © 2014 Elsevier B.V. All rights reserved.

Communicating Low-Probability High-Consequence Risk, Uncertainty and Expert Confidence: Induced Seismicity of Deep Geothermal Energy and Shale Gas.

Science.gov (United States)

Knoblauch, Theresa A K; Stauffacher, Michael; Trutnevyte, Evelina

2018-04-01

Subsurface energy activities entail the risk of induced seismicity including low-probability high-consequence (LPHC) events. For designing respective risk communication, the scientific literature lacks empirical evidence of how the public reacts to different written risk communication formats about such LPHC events and to related uncertainty or expert confidence. This study presents findings from an online experiment (N = 590) that empirically tested the public's responses to risk communication about induced seismicity and to different technology frames, namely deep geothermal energy (DGE) and shale gas (between-subject design). Three incrementally different formats of written risk communication were tested: (i) qualitative, (ii) qualitative and quantitative, and (iii) qualitative and quantitative with risk comparison. Respondents found the latter two the easiest to understand, the most exact, and liked them the most. Adding uncertainty and expert confidence statements made the risk communication less clear, less easy to understand and increased concern. Above all, the technology for which risks are communicated and its acceptance mattered strongly: respondents in the shale gas condition found the identical risk communication less trustworthy and more concerning than in the DGE conditions. They also liked the risk communication overall less. For practitioners in DGE or shale gas projects, the study shows that the public would appreciate efforts in describing LPHC risks with numbers and optionally risk comparisons. However, there seems to be a trade-off between aiming for transparency by disclosing uncertainty and limited expert confidence, and thereby decreasing clarity and increasing concern in the view of the public. © 2017 Society for Risk Analysis.

The Effect of Social Trust on Citizens’ Health Risk Perception in the Context of a Petrochemical Industrial Complex

Directory of Open Access Journals (Sweden)

Vicente Tortosa-Edo

2013-01-01

Full Text Available Perceived risk of environmental threats often translates into psychological stress with a wide range of effects on health and well-being. Petrochemical industrial complexes constitute one of the sites that can cause considerable pollution and health problems. The uncertainty around emissions results in a perception of risk for citizens residing in neighboring areas, which translates into anxiety and physiological stress. In this context, social trust is a key factor in managing the perceived risk. In the case of industrial risks, it is essential to distinguish between trust in the companies that make up the industry, and trust in public institutions. In the context of a petrochemical industrial complex located in the port of Castellón (Spain, this paper primarily discusses how trust — both in the companies located in the petrochemical complex and in the public institutions — affects citizens’ health risk perception. The research findings confirm that while the trust in companies negatively affects citizens’ health risk perception, trust in public institutions does not exert a direct and significant effect. Analysis also revealed that trust in public institutions and health risk perception are essentially linked indirectly (through trust in companies.

The Effect of Social Trust on Citizens’ Health Risk Perception in the Context of a Petrochemical Industrial Complex

Science.gov (United States)

López-Navarro, Miguel Ángel; Llorens-Monzonís, Jaume; Tortosa-Edo, Vicente

2013-01-01

Perceived risk of environmental threats often translates into psychological stress with a wide range of effects on health and well-being. Petrochemical industrial complexes constitute one of the sites that can cause considerable pollution and health problems. The uncertainty around emissions results in a perception of risk for citizens residing in neighboring areas, which translates into anxiety and physiological stress. In this context, social trust is a key factor in managing the perceived risk. In the case of industrial risks, it is essential to distinguish between trust in the companies that make up the industry, and trust in public institutions. In the context of a petrochemical industrial complex located in the port of Castellón (Spain), this paper primarily discusses how trust—both in the companies located in the petrochemical complex and in the public institutions—affects citizens’ health risk perception. The research findings confirm that while the trust in companies negatively affects citizens’ health risk perception, trust in public institutions does not exert a direct and significant effect. Analysis also revealed that trust in public institutions and health risk perception are essentially linked indirectly (through trust in companies). PMID:23337129

Disruptive event uncertainties in a perturbation approach to nuclear waste repository risk analysis

Energy Technology Data Exchange (ETDEWEB)

Harvey, T.F.

1980-09-01

A methodology is developed for incorporating a full range of the principal forecasting uncertainties into a risk analysis of a nuclear waste repository. The result of this methodology is a set of risk curves similar to those used by Rasmussen in WASH-1400. The set of curves is partially derived from a perturbation approach to analyze potential disruptive event sequences. Such a scheme could be useful in truncating the number of disruptive event scenarios and providing guidance to those establishing data-base development priorities.

Risk-based flood protection planning under climate change and modeling uncertainty: a pre-alpine case study

Directory of Open Access Journals (Sweden)

B. Dittes

2018-05-01

Full Text Available Planning authorities are faced with a range of questions when planning flood protection measures: is the existing protection adequate for current and future demands or should it be extended? How will flood patterns change in the future? How should the uncertainty pertaining to this influence the planning decision, e.g., for delaying planning or including a safety margin? Is it sufficient to follow a protection criterion (e.g., to protect from the 100-year flood or should the planning be conducted in a risk-based way? How important is it for flood protection planning to accurately estimate flood frequency (changes, costs and damage? These are questions that we address for a medium-sized pre-alpine catchment in southern Germany, using a sequential Bayesian decision making framework that quantitatively addresses the full spectrum of uncertainty. We evaluate different flood protection systems considered by local agencies in a test study catchment. Despite large uncertainties in damage, cost and climate, the recommendation is robust for the most conservative approach. This demonstrates the feasibility of making robust decisions under large uncertainty. Furthermore, by comparison to a previous study, it highlights the benefits of risk-based planning over the planning of flood protection to a prescribed return period.

Risk-based flood protection planning under climate change and modeling uncertainty: a pre-alpine case study

Science.gov (United States)

Dittes, Beatrice; Kaiser, Maria; Špačková, Olga; Rieger, Wolfgang; Disse, Markus; Straub, Daniel

2018-05-01

Planning authorities are faced with a range of questions when planning flood protection measures: is the existing protection adequate for current and future demands or should it be extended? How will flood patterns change in the future? How should the uncertainty pertaining to this influence the planning decision, e.g., for delaying planning or including a safety margin? Is it sufficient to follow a protection criterion (e.g., to protect from the 100-year flood) or should the planning be conducted in a risk-based way? How important is it for flood protection planning to accurately estimate flood frequency (changes), costs and damage? These are questions that we address for a medium-sized pre-alpine catchment in southern Germany, using a sequential Bayesian decision making framework that quantitatively addresses the full spectrum of uncertainty. We evaluate different flood protection systems considered by local agencies in a test study catchment. Despite large uncertainties in damage, cost and climate, the recommendation is robust for the most conservative approach. This demonstrates the feasibility of making robust decisions under large uncertainty. Furthermore, by comparison to a previous study, it highlights the benefits of risk-based planning over the planning of flood protection to a prescribed return period.

Assessing the near-term risk of climate uncertainty : interdependencies among the U.S. states.

Energy Technology Data Exchange (ETDEWEB)

Loose, Verne W.; Lowry, Thomas Stephen; Malczynski, Leonard A.; Tidwell, Vincent Carroll; Stamber, Kevin Louis; Reinert, Rhonda K.; Backus, George A.; Warren, Drake E.; Zagonel, Aldo A.; Ehlen, Mark Andrew; Klise, Geoffrey T.; Vargas, Vanessa N.

2010-04-01

Policy makers will most likely need to make decisions about climate policy before climate scientists have resolved all relevant uncertainties about the impacts of climate change. This study demonstrates a risk-assessment methodology for evaluating uncertain future climatic conditions. We estimate the impacts of climate change on U.S. state- and national-level economic activity from 2010 to 2050. To understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions to mitigate the course of climate change, we focus on precipitation, one of the most uncertain aspects of future climate change. We use results of the climate-model ensemble from the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) as a proxy for representing climate uncertainty over the next 40 years, map the simulated weather from the climate models hydrologically to the county level to determine the physical consequences on economic activity at the state level, and perform a detailed 70-industry analysis of economic impacts among the interacting lower-48 states. We determine the industry-level contribution to the gross domestic product and employment impacts at the state level, as well as interstate population migration, effects on personal income, and consequences for the U.S. trade balance. We show that the mean or average risk of damage to the U.S. economy from climate change, at the national level, is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs.

Influence of air quality model resolution on uncertainty associated with health impacts

Directory of Open Access Journals (Sweden)

T. M. Thompson

2012-10-01

Full Text Available We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx, we ran a modeling episode with meteorological inputs simulating conditions as they occurred during August through September 2006 (a period representative of conditions leading to high ozone, and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between the 2, 4 and 12 km resolution runs, but the 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements motivated by Executive Order 12866 as it applies to the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2, 4 or 12 km resolution. On average, when modeling at 36 km resolution, an estimated 5 deaths per week during the May through September ozone

Probabilistic risk analysis and fault trees: Initial discussion of application to identification of risk at a wellhead

Science.gov (United States)

Rodak, C.; Silliman, S.

2012-02-01

Wellhead protection is of critical importance for managing groundwater resources. While a number of previous authors have addressed questions related to uncertainties in advective capture zones, methods for addressing wellhead protection in the presence of uncertainty in the chemistry of groundwater contaminants, the relationship between land-use and contaminant sources, and the impact on health of the receiving population are limited. It is herein suggested that probabilistic risk analysis (PRA) combined with fault trees (FT) provides a structure whereby chemical transport can be combined with uncertainties in source, chemistry, and health impact to assess the probability of negative health outcomes in the population. As such, PRA-FT provides a new strategy for the identification of areas of probabilistically high human health risk. Application of this approach is demonstrated through a simplified case study involving flow to a well in an unconfined aquifer with heterogeneity in aquifer properties and contaminant sources.

Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models

Directory of Open Access Journals (Sweden)

Koen Degeling

2017-12-01

Full Text Available Abstract Background Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Methods Two approaches, 1 using non-parametric bootstrapping and 2 using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Results Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500, the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25, yielding infeasible modeling outcomes. Conclusions Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.

Accounting for parameter uncertainty in the definition of parametric distributions used to describe individual patient variation in health economic models.

Science.gov (United States)

Degeling, Koen; IJzerman, Maarten J; Koopman, Miriam; Koffijberg, Hendrik

2017-12-15

Parametric distributions based on individual patient data can be used to represent both stochastic and parameter uncertainty. Although general guidance is available on how parameter uncertainty should be accounted for in probabilistic sensitivity analysis, there is no comprehensive guidance on reflecting parameter uncertainty in the (correlated) parameters of distributions used to represent stochastic uncertainty in patient-level models. This study aims to provide this guidance by proposing appropriate methods and illustrating the impact of this uncertainty on modeling outcomes. Two approaches, 1) using non-parametric bootstrapping and 2) using multivariate Normal distributions, were applied in a simulation and case study. The approaches were compared based on point-estimates and distributions of time-to-event and health economic outcomes. To assess sample size impact on the uncertainty in these outcomes, sample size was varied in the simulation study and subgroup analyses were performed for the case-study. Accounting for parameter uncertainty in distributions that reflect stochastic uncertainty substantially increased the uncertainty surrounding health economic outcomes, illustrated by larger confidence ellipses surrounding the cost-effectiveness point-estimates and different cost-effectiveness acceptability curves. Although both approaches performed similar for larger sample sizes (i.e. n = 500), the second approach was more sensitive to extreme values for small sample sizes (i.e. n = 25), yielding infeasible modeling outcomes. Modelers should be aware that parameter uncertainty in distributions used to describe stochastic uncertainty needs to be reflected in probabilistic sensitivity analysis, as it could substantially impact the total amount of uncertainty surrounding health economic outcomes. If feasible, the bootstrap approach is recommended to account for this uncertainty.

Human health risk assessment methodology for the UMTRA Ground Water Project

International Nuclear Information System (INIS)

1994-11-01

This document presents the method used to evaluate human risks associated with ground water contamination at inactive uranium processing sites. The intent of these evaluations is to provide the public and remedial action decision-makers with information about the health risks that might be expected at each site in a manner that is easily understood. The method (1) develops probabilistic distributions for exposure variables where sufficient data exist, (2) simulates predicted exposure distributions using Monte Carlo techniques, and (3) develops toxicity ranges that reflect human data when available, animal data if human data are insufficient, regulatory levels, and uncertainties. Risk interpretation is based on comparison of the potential exposure distributions with the derived toxicity ranges. Graphic presentations are an essential element of the semiquantitative interpretation and are expected to increase understanding by the public and decision-makers

The costs of uncertainty: regulating health and safety in the Canadian uranium industry

International Nuclear Information System (INIS)

Robinson, I.

1982-04-01

Federalism, and particularly federal/provincial jurisdictional relationships, have led to considerable uncertainty in the regulation of occupational health and safety and of environmental protection in the Canadian uranium mining industry. The two principal uranium producing provinces in Canada are Saskatchewan and Ontario. Since 1978, in an attempt to avoid constitutional issues, both these provinces and the federal government as well have proceeded unilaterally with health and safety reforms for the industry. In Saskatchewan this has resulted in areas of overlapping jurisdiction, which have led to uncertainty over the legal enforceability of the provincial regulations. In Ontario, the province has left significant gaps in the protection of both workers and the environment. Little progress can be expected in eliminating these gaps and overlaps until the current administrative and jurisdictional arrangements are understood

Human health risk assessment screening approach for evaluating contaminants at source control and integrator operable units

International Nuclear Information System (INIS)

Blaylock, B.G.; Frank, M.L.; Hoffman, F.O.; Miller, P.D.; White, R.K.; Purucker, S.T.; Redfearn, A.

1992-10-01

A more streamlined approach is proposed for executing the Remedial Investigation/Feasibility Study Process. This approach recognizes the uncertainties associated with the process, particularly regarding the derivation of human health risk estimates. The approach is tailored for early identification of sites and contaminants of immediate concern, early remediation of such sites, and early identification of low-risk sites that can be eliminated from further investigations. The purpose is to hasten the clean-up process and do so in a cost-effective manner

Optimizing an Investment Solution in Conditions of Uncertainty and Risk as a Multicriterial Task

Directory of Open Access Journals (Sweden)

Kotsyuba Oleksiy S.

2017-10-01

Full Text Available The article is concerned with the methodology for optimizing investment decisions in conditions of uncertainty and risk. The subject area of the study relates, first of all, to real investment. The problem of modeling an optimal investment solution is considered to be a multicriterial task. Also, the constructive part of the publication is based on the position that the multicriteriality of objectives of investment projecting is the result, first, of the complex nature of the category of economic attractiveness (efficiency of real investment, and secondly, of the need to take into account the risk factor, which is a vector measure, in the preparation of an investment solution. An attempt has been made to develop an instrumentarium to optimize investment decisions in a situation of uncertainty and the risk it engenders, based on the use of roll-up of the local criteria. As a result of its implementation, a model has been proposed, which has the advantage that it takes into account, to a greater extent than is the case for standardized roll-up options, the contensive and formal features of the local (detailed criteria.

County-Level Climate Uncertainty for Risk Assessments: Volume 17 Appendix P - Forecast Soil Moisture

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

2017-04-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

County-Level Climate Uncertainty for Risk Assessments: Volume 26 Appendix Y - Historical Ridging Rate.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lowry, Thomas Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Shannon M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Walker, La Tonya Nicole [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roberts, Barry L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Malczynski, Leonard A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-05-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

County-Level Climate Uncertainty for Risk Assessments: Volume 27 Appendix Z - Forecast Ridging Rate.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

2017-06-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

County-Level Climate Uncertainty for Risk Assessments: Volume 14 Appendix M - Historical Surface Runoff.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

2017-06-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

County-Level Climate Uncertainty for Risk Assessments: Volume 12 Appendix K - Historical Rel. Humidity.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

2017-06-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

County-Level Climate Uncertainty for Risk Assessments: Volume 16 Appendix O - Historical Soil Moisture.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A.; Lowry, Thomas Stephen; Jones, Shannon M; Walker, La Tonya Nicole; Roberts, Barry L; Malczynski, Leonard A.

2017-06-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

County-Level Climate Uncertainty for Risk Assessments: Volume 15 Appendix N - Forecast Surface Runoff.

Energy Technology Data Exchange (ETDEWEB)

Backus, George A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Lowry, Thomas Stephen [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Jones, Shannon M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Walker, La Tonya Nicole [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Roberts, Barry L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Malczynski, Leonard A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-05-01

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

Blockchain to Rule the Waves - Nascent Design Principles for Reducing Risk and Uncertainty in Decentralized Environments

DEFF Research Database (Denmark)

Nærland, Kristoffer; Müller-Bloch, Christoph; Beck, Roman

2017-01-01

Many decentralized, inter-organizational environments such as supply chains are characterized by high transactional uncertainty and risk. At the same time, blockchain technology promises to mitigate these issues by introducing certainty into economic transactions. This paper discusses the findings...... of a Design Science Research project involving the construction and evaluation of an information technology artifact in collaboration with Maersk, a leading international shipping company, where central documents in shipping, such as the Bill of Lading, are turned into a smart contract on blockchain. Based...... on our insights from the project, we provide first evidence for preliminary design principles for applications that aim to mitigate the transactional risk and uncertainty in decentralized environments using blockchain. Both the artifact and the first evidence for emerging design principles are novel...

Frequency and prioritization of patient health risks from a structured health risk assessment.

Science.gov (United States)

Phillips, Siobhan M; Glasgow, Russell E; Bello, Ghalib; Ory, Marcia G; Glenn, Beth A; Sheinfeld-Gorin, Sherri N; Sabo, Roy T; Heurtin-Roberts, Suzanne; Johnson, Sallie Beth; Krist, Alex H

2014-01-01

To describe the frequency and patient-reported readiness to change, desire to discuss, and perceived importance of 13 health risk factors in a diverse range of primary care practices. Patients (n = 1,707) in 9 primary care practices in the My Own Health Report (MOHR) trial reported general, behavioral, and psychosocial risk factors (body mass index [BMI], health status, diet, physical activity, sleep, drug use, stress, anxiety or worry, and depression). We classified responses as "at risk" or "healthy" for each factor, and patients indicated their readiness to change and/or desire to discuss identified risk factors with providers. Patients also selected 1 of the factors they were ready to change as most important. We then calculated frequencies within and across these factors and examined variation by patient characteristics and across practices. On average, patients had 5.8 (SD = 2.12; range, 0-13) unhealthy behaviors and mental health risk factors. About 55% of patients had more than 6 risk factors. On average, patients wanted to change 1.2 and discuss 0.7 risks. The most common risks were inadequate fruit/vegetable consumption (84.5%) and overweight/obesity (79.6%). Patients were most ready to change BMI (33.3%) and depression (30.7%), and most wanted to discuss depression (41.9%) and anxiety or worry (35.2%). Overall, patients rated health status as most important. Implementing routine comprehensive health risk assessments in primary care will likely identify a high number of behavioral and psychosocial health risks. By soliciting patient priorities, providers and patients can better manage counseling and behavior change. © 2014 Annals of Family Medicine, Inc.

Assessment of uncertainties in risk analysis of chemical establishments. The ASSURANCE project. Final summary report

DEFF Research Database (Denmark)

Lauridsen, K.; Kozine, Igor; Markert, Frank

2002-01-01

and led the comparison of results in order to reveal the causes for differences between the partners' results. The results of the project point to an increased awareness of the potential uncertainties in riskanalyses and highlight a number of important sources of such uncertainties. In the hazard......This report summarises the results obtained in the ASSURANCE project (EU contract number ENV4-CT97-0627). Seven teams have performed risk analyses for the same chemical facility, an ammonia storage. The EC's Joint Research Centre at Ispra and RisøNational Laboratory co-ordinated the exercise...

Treating Uncertainties in A Nuclear Seismic Probabilistic Risk Assessment by Means of the Distemper-Safer Theory of Evidence

International Nuclear Information System (INIS)

Lo, Chungkung; Pedroni, N.; Zio, E.

2014-01-01

The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i. e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest

Treating Uncertainties in A Nuclear Seismic Probabilistic Risk Assessment by Means of the Distemper-Safer Theory of Evidence

Energy Technology Data Exchange (ETDEWEB)

Lo, Chungkung [Chair on Systems Science and the Energetic Challenge, Paris (France); Pedroni, N.; Zio, E. [Politecnico di Milano, Milano (Italy)

2014-02-15

The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i. e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest.

Exploration Health Risks: Probabilistic Risk Assessment

Science.gov (United States)

Rhatigan, Jennifer; Charles, John; Hayes, Judith; Wren, Kiley

2006-01-01

Maintenance of human health on long-duration exploration missions is a primary challenge to mission designers. Indeed, human health risks are currently the largest risk contributors to the risks of evacuation or loss of the crew on long-duration International Space Station missions. We describe a quantitative assessment of the relative probabilities of occurrence of the individual risks to human safety and efficiency during space flight to augment qualitative assessments used in this field to date. Quantitative probabilistic risk assessments will allow program managers to focus resources on those human health risks most likely to occur with undesirable consequences. Truly quantitative assessments are common, even expected, in the engineering and actuarial spheres, but that capability is just emerging in some arenas of life sciences research, such as identifying and minimize the hazards to astronauts during future space exploration missions. Our expectation is that these results can be used to inform NASA mission design trade studies in the near future with the objective of preventing the higher among the human health risks. We identify and discuss statistical techniques to provide this risk quantification based on relevant sets of astronaut biomedical data from short and long duration space flights as well as relevant analog populations. We outline critical assumptions made in the calculations and discuss the rationale for these. Our efforts to date have focussed on quantifying the probabilities of medical risks that are qualitatively perceived as relatively high risks of radiation sickness, cardiac dysrhythmias, medically significant renal stone formation due to increased calcium mobilization, decompression sickness as a result of EVA (extravehicular activity), and bone fracture due to loss of bone mineral density. We present these quantitative probabilities in order-of-magnitude comparison format so that relative risk can be gauged. We address the effects of

Inexact stochastic risk-aversion optimal day-ahead dispatch model for electricity system management with wind power under uncertainty

International Nuclear Information System (INIS)

Ji, Ling; Huang, Guo-He; Huang, Lu-Cheng; Xie, Yu-Lei; Niu, Dong-Xiao

2016-01-01

High penetration of wind power generation and deregulated electricity market brings a great challenge to the electricity system operators. It is crucial to make optimal strategy among various generation units and spinning reserve for supporting the system safety operation. By integrating interval two-stage programming and stochastic robust programming, this paper proposes a novel robust model for day-ahead dispatch and risk-aversion management under uncertainties. In the proposed model, the uncertainties are expressed as interval values with different scenario probability. The proposed method requires low computation, and still retains the complete information. A case study is to validate the effectiveness of this approach. Facing the uncertainties of future demand and electricity price, the system operators need to make optimal dispatch strategy for thermal power units and wind turbine, and arrange proper spinning reserve and flexible demand response program to mitigate wind power forecasting error. The optimal strategies provide the system operators with better trade-off between the maximum benefits and the minimum system risk. In additional, two different market rules are compared. The results show that extra financial penalty for the wind power dispatch deviation is another efficient way to enhance the risk consciousness of decision makers and lead to more conservative strategy. - Highlights: • An inexact two-stage stochastic robust programming model for electricity system with wind power penetration. • Uncertainties expressed as discrete intervals and probability distributions. • Demand response program was introduced to adjust the deviation in real-time market. • Financial penalty for imbalance risk from wind power generation was evaluated.

Mean-variance model for portfolio optimization with background risk based on uncertainty theory

Science.gov (United States)

Zhai, Jia; Bai, Manying

2018-04-01

The aim of this paper is to develop a mean-variance model for portfolio optimization considering the background risk, liquidity and transaction cost based on uncertainty theory. In portfolio selection problem, returns of securities and assets liquidity are assumed as uncertain variables because of incidents or lacking of historical data, which are common in economic and social environment. We provide crisp forms of the model and a hybrid intelligent algorithm to solve it. Under a mean-variance framework, we analyze the portfolio frontier characteristic considering independently additive background risk. In addition, we discuss some effects of background risk and liquidity constraint on the portfolio selection. Finally, we demonstrate the proposed models by numerical simulations.

Cyanobacterial toxins: risk management for health protection

International Nuclear Information System (INIS)

Codd, Geoffrey A.; Morrison, Louise F.; Metcalf, James S.

2005-01-01

This paper reviews the occurrence and properties of cyanobacterial toxins, with reference to the recognition and management of the human health risks which they may present. Mass populations of toxin-producing cyanobacteria in natural and controlled waterbodies include blooms and scums of planktonic species, and mats and biofilms of benthic species. Toxic cyanobacterial populations have been reported in freshwaters in over 45 countries, and in numerous brackish, coastal, and marine environments. The principal toxigenic genera are listed. Known sources of the families of cyanobacterial toxins (hepato-, neuro-, and cytotoxins, irritants, and gastrointestinal toxins) are briefly discussed. Key procedures in the risk management of cyanobacterial toxins and cells are reviewed, including derivations (where sufficient data are available) of tolerable daily intakes (TDIs) and guideline values (GVs) with reference to the toxins in drinking water, and guideline levels for toxigenic cyanobacteria in bathing waters. Uncertainties and some gaps in knowledge are also discussed, including the importance of exposure media (animal and plant foods), in addition to potable and recreational waters. Finally, we present an outline of steps to develop and implement risk management strategies for cyanobacterial cells and toxins in waterbodies, with recent applications and the integration of Hazard Assessment Critical Control Point (HACCP) principles

Economic policy uncertainty, credit risks and banks lending decisions: Evidence from Chinese commercial banks

Institute of Scientific and Technical Information of China (English)

Qinwei Chi; Wenjing Li

2017-01-01

Using data for Chinese commercial banks from 2000 to 2014, this paper examines the effects of economic policy uncertainty(EPU) on banks’ credit risks and lending decisions. The results reveal significantly positive connections among EPU and non-performing loan ratios, loan concentrations and the normal loan migration rate. This indicates that EPU increases banks’ credit risks and negatively influences loan size, especially for joint-equity banks. Given the increasing credit risks generated by EPU, banks can improve operational performance by reducing loan sizes. Further research indicates that the effects of EPU on banks’ credit risks and lending decisions are moderated by the marketization level, with financial depth moderating the effect on banks’ credit risks and strengthening it on lending decisions.

Health and environmental risk governance in the french context. The role of scientific expertise and economic analysis

International Nuclear Information System (INIS)

Courvalin, C.; Boisson, P.; Dab, W.; Cohen de Lara, M.; Godard, O.; Heriard Dubreuil, G.; Hervouet, V.

1998-01-01

Full text of publication follows: increasing public concern as regards health and environmental risks makes it necessary, for public policies and regulation of risk assessment and management to comply with multiple and often non consistent expectations from the public in a rapidly changing environment. Evolution of risk assessment and management is currently observed as a consequence of this context. Whereas the former technical approaches were playing down the existence of residual risk as well as scientific uncertainties, current reflections rather aim at empowering the stakeholders of hazardous activities in the decision-making process in order to build up social trust and public confidence. This paper will present the conclusions of a work group entrusted by the French authorities with the task of proposing recommendations in order to update the risk assessment and management current approaches in the field of energy producing and consuming. The conclusions of this work are based on the analysis of three major issues as regards environmental health risks: climate change, atmospheric pollution, and radiation protection. It is also based on the 1997 report of the US Congress Commission on risk assessment and management. The report points out the difficulty for the French 'command and control' regulatory tradition to comply with public demand for transparency and more democratic involvement in the decision-making process. The conclusion presents various recommendations as regards the role of scientific expertise, the use of economic analysis and the decision-making process in risk assessment and management. The conclusion particularly emphasises key aspects of the decision-making process such as: the necessity of contextualizing risk assessment, the taking into account of scientific uncertainties and the need for stakeholders' involvement. (authors)

Health risks in perspective: Judging health risks of energy technologies

Energy Technology Data Exchange (ETDEWEB)

Rowe, M.D.

1992-09-18

Almost daily, Americans receive reports from the mass news media about some new and frightening risk to health and welfare. Most such reports emphasize the newsworthiness of the risks -- the possibility of a crisis, disagreements among experts, how things happened, who is responsible for fixing them, how much will it cost, conflict among parties involved, etc. As a rule, the magnitudes of the risks, or the difficulty of estimating those magnitudes, have limited newsworthiness, and so they are not mentioned. Because of this emphasis in the news media, most people outside the risk assessment community must judge the relative significance of the various risks to which we all are exposed with only that information deemed newsworthy by reporters. This information is biased and shows risks in isolation. There is no basis for understanding and comparing the relative importance of risks among themselves, or for comparing one risk, perhaps a new or newly-discovered one, in the field of all risks. The purpose of this report is to provide perspective on the various risks to which we are routinely exposed. It serves as a basis for understanding the meaning of quantitative risk estimates and for comparing new or newly-discovered risks with other, better-understood risks. Specific emphasis is placed on health risks of energy technologies.

Health and environmental risk-related impacts of actinide burning on high-level waste disposal

International Nuclear Information System (INIS)

Forsberg, C.W.

1992-05-01

The potential health and environmental risk-related impacts of actinide burning for high-level waste disposal were evaluated. Actinide burning, also called waste partitioning-transmutation, is an advanced method for radioactive waste management based on the idea of destroying the most toxic components in the waste. It consists of two steps: (1) selective removal of the most toxic radionuclides from high-level/spent fuel waste and (2) conversion of those radionuclides into less toxic radioactive materials and/or stable elements. Risk, as used in this report, is defined as the probability of a failure times its consequence. Actinide burning has two potential health and environmental impacts on waste management. Risks and the magnitude of high-consequence repository failure scenarios are decreased by inventory reduction of the long-term radioactivity in the repository. (What does not exist cannot create risk or uncertainty.) Risk may also be reduced by the changes in the waste characteristics, resulting from selection of waste forms after processing, that are superior to spent fuel and which lower the potential of transport of radionuclides from waste form to accessible environment. There are no negative health or environmental impacts to the repository from actinide burning; however, there may be such impacts elsewhere in the fuel cycle

Identifying Selected Behavioral Determinants of Risk and Uncertainty on the Real Estate Market

Directory of Open Access Journals (Sweden)

Brzezicka Justyna

2014-07-01

Full Text Available Various market behaviors can be characterized as risky or uncertain, thus their observation is important to the real estate market system. The extensive use of behavioral factors facilitates their implementation and studies in relation to the real estate market system. The behavioral approach has established its own instrumentation which enables elements of risk and uncertainty to be quantified.

Application of a Novel Dose-Uncertainty Model for Dose-Uncertainty Analysis in Prostate Intensity-Modulated Radiotherapy

International Nuclear Information System (INIS)

Jin Hosang; Palta, Jatinder R.; Kim, You-Hyun; Kim, Siyong

2010-01-01

Purpose: To analyze dose uncertainty using a previously published dose-uncertainty model, and to assess potential dosimetric risks existing in prostate intensity-modulated radiotherapy (IMRT). Methods and Materials: The dose-uncertainty model provides a three-dimensional (3D) dose-uncertainty distribution in a given confidence level. For 8 retrospectively selected patients, dose-uncertainty maps were constructed using the dose-uncertainty model at the 95% CL. In addition to uncertainties inherent to the radiation treatment planning system, four scenarios of spatial errors were considered: machine only (S1), S1 + intrafraction, S1 + interfraction, and S1 + both intrafraction and interfraction errors. To evaluate the potential risks of the IMRT plans, three dose-uncertainty-based plan evaluation tools were introduced: confidence-weighted dose-volume histogram, confidence-weighted dose distribution, and dose-uncertainty-volume histogram. Results: Dose uncertainty caused by interfraction setup error was more significant than that of intrafraction motion error. The maximum dose uncertainty (95% confidence) of the clinical target volume (CTV) was smaller than 5% of the prescribed dose in all but two cases (13.9% and 10.2%). The dose uncertainty for 95% of the CTV volume ranged from 1.3% to 2.9% of the prescribed dose. Conclusions: The dose uncertainty in prostate IMRT could be evaluated using the dose-uncertainty model. Prostate IMRT plans satisfying the same plan objectives could generate a significantly different dose uncertainty because a complex interplay of many uncertainty sources. The uncertainty-based plan evaluation contributes to generating reliable and error-resistant treatment plans.