A Framework and Case Study for Exposure Assessment in the Voluntary Children''s Chemical Evaluation Program

A conceptual framework is presented for conducting exposure assessments under the U.S. EPA's Voluntary Children's Chemical Evaluation Program (VCCEP). The VCCEP is a voluntary program whereby companies that manufacture chemicals of potential concern are asked to conduct hazard, exposure, and risk assessments for the chemicals. The VCCEP is unique in its risk-based, tiered approach, and because it focuses on children and requires a comprehensive consideration of all reasonably foreseeable exposure pathways for a particular chemical. The consideration of all potential exposure pathways for some commonly used chemicals presents a daunting challenge for the exposure assessor. This article presents a framework for managing this complicated process, and illustrates the application of the framework with a hypothetical case study. The framework provides guidance for interpreting multiple sources of exposure information and developing a plausible list of exposure pathways for a chemical. Furthermore, the framework provides a means to process all the available information to eliminate pathways of negligible concern from consideration. Finally, the framework provides guidance for utilizing the tiered approach of VCCEP to efficiently conduct an assessment by first using simple, screening-level approaches and then, if necessary, using more complex, refined exposure assessment methods. The case study provides an illustration of the major concepts.     

VCCEP Pilot: Progress on Evaluating Children''s Risks and Data Needs

The Voluntary Children's Chemical Evaluation Program (VCCEP) is designed to provide information to the public on children's potential health risks associated with chemical exposures. The key question of the VCCEP is whether the potential hazards, exposures, and risks to children have been adequately characterized, and, if not, what additional data are necessary. To answer this question, manufacturers or importers of 23 chemicals were asked by the U. S. Environmental Protection Agency (U.S. EPA) to sponsor their chemicals in the first tier of a pilot program. These chemicals were selected for evaluation because they have been found as contaminants in human tissue or fluids (adipose tissue, blood, breath, breast milk, or urine); food and water children may eat and drink; or air children may breathe (including residential or school air). Under the VCCEP framework, sponsoring companies agree to prepare Tier 1 hazard, exposure, and risk assessments on the individual chemicals, and identify the need for additional data. These assessment documents are submitted to the U.S. EPA and subsequently undergo review by experts in an independent peer consultation meeting that is open to the public. Following this peer consultation process, the U.S. EPA reviews each submission and makes a data-needs determination, which may include requesting further data collection or generation by the sponsor. Sponsoring companies then decide whether to volunteer for the next tier and collect or generate the requested data. The purpose of this article is to describe the VCCEP process and to review and present the key findings from the first set of chemicals that have been fully or partially evaluated under the pilot program (vinylidene chloride, decabromodiphenyl ether, pentabromodiphenyl ether, octabromodiphenyl ether, acetone, methyl ethyl ketone, decane, undecane, and dodecane). Specifically, we provide a brief summary of the sponsors' submissions, the peer consultation panels' discussions, and the U.S. EPA's data-needs decisions. Although we do not attempt to conduct independent analyses of the underlying data, we do identify a number of common themes that have emerged during implementation of the pilot program and discuss several key issues that could become important in the future. The information presented here should be useful for various parties interested in the progress of the VCCEP and the results of the initial (Tier 1) children's assessments.     

A Tiered Approach for Risk‐Benefit Assessment of Foods

Risk‐benefit analyses are introduced as a new paradigm for old problems. However, in many cases it is not always necessary to perform a full comprehensive and expensive quantitative risk‐benefit assessment to solve the problem, nor is it always possible, given the lack of required date. The choice to continue from a more qualitative to a full quantitative risk‐benefit assessment can be made using a tiered approach. In this article, this tiered approach for risk‐benefit assessment will be addressed using a decision tree. The tiered approach described uses the same four steps as the risk assessment paradigm: hazard and benefit identification, hazard and benefit characterization, exposure assessment, and risk‐benefit characterization, albeit in a different order. For the purpose of this approach, the exposure assessment has been moved upward and the dose‐response modeling (part of hazard and benefit characterization) is moved to a later stage. The decision tree includes several stop moments, depending on the situation where the gathered information is sufficient to answer the initial risk‐benefit question. The approach has been tested for two food ingredients. The decision tree presented in this article is useful to assist on a case‐by‐case basis a risk‐benefit assessor and policymaker in making informed choices when to stop or continue with a risk‐benefit assessment.     

An Approach for Optimal Allocation of Safety Resources: Using the Knapsack Problem to Take Aggregated Cost‐Efficient Preventive Measures

On the basis of the combination of the well‐known knapsack problem and a widely used risk management technique in organizations (that is, the risk matrix), an approach was developed to carry out a cost‐benefits analysis to efficiently take prevention investment decisions. Using the knapsack problem as a model and combining it with a well‐known technique to solve this problem, bundles of prevention measures are prioritized based on their costs and benefits within a predefined prevention budget. Those bundles showing the highest efficiencies, and within a given budget, are identified from a wide variety of possible alternatives. Hence, the approach allows for an optimal allocation of safety resources, does not require any highly specialized information, and can therefore easily be applied by any organization using the risk matrix as a risk ranking tool.     

Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies

Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system‐based for high‐consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward‐looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high‐consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents.     

The Benefits and Costs of Disclosing Information about Risks: What Do We Know about Right‐to‐Know?

Following the attacks of September 11, 2001, the Environmental Protection Agency and other government agencies removed information from their web sites that they feared could invite attacks on critical public and private infrastructure. Accordingly, the benefits and costs of environmental information disclosure programs have come under increasing scrutiny. This article describes a framework for examining these benefits and costs and illustrates the framework through brief case studies of two information disclosure programs: risk management planning and materials accounting. The article outlines what we know and still need to find out about information disclosure programs in order to appropriately balance benefits and costs.     

Risk Analysis for Biological Hazards: What We Need to Know about Invasive Species

Risk analysis for biological invasions is similar to other types of natural and human hazards. For example, risk analysis for chemical spills requires the evaluation of basic information on where a spill occurs; exposure level and toxicity of the chemical agent; knowledge of the physical processes involved in its rate and direction of spread; and potential impacts to the environment, economy, and human health relative to containment costs. Unlike typical chemical spills, biological invasions can have long lag times from introduction and establishment to successful invasion, they reproduce, and they can spread rapidly by physical and biological processes. We use a risk analysis framework to suggest a general strategy for risk analysis for invasive species and invaded habitats. It requires: (1) problem formation (scoping the problem, defining assessment endpoints); (2) analysis (information on species traits, matching species traits to suitable habitats, estimating exposure, surveys of current distribution and abundance); (3) risk characterization (understanding of data completeness, estimates of the "potential" distribution and abundance; estimates of the potential rate of spread; and probable risks, impacts, and costs); and (4) risk management (containment potential, costs, and opportunity costs; legal mandates and social considerations and information science and technology needs).     

Characterizing Risk for Cumulative Risk Assessments

In assessing environmental health risks, the risk characterization step synthesizes information gathered in evaluating exposures to stressors together with dose–response relationships, characteristics of the exposed population, and external environmental conditions. This article summarizes key steps of a cumulative risk assessment (CRA) followed by a discussion of considerations for characterizing cumulative risks. Cumulative risk characterizations differ considerably from single chemical‐ or single source‐based risk characterization. CRAs typically focus on a specific population instead of a pollutant or pollutant source and should include an evaluation of all relevant sources contributing to the exposures in the population and other factors that influence dose–response relationships. Second, CRAs may include influential environmental and population‐specific conditions, involving multiple chemical and nonchemical stressors. Third, a CRA could examine multiple health effects, reflecting joint toxicity and the potential for toxicological interactions. Fourth, the complexities often necessitate simplifying methods, including judgment‐based and semi‐quantitative indices that collapse disparate data into numerical scores. Fifth, because of the higher dimensionality and potentially large number of interactions, information needed to quantify risk is typically incomplete, necessitating an uncertainty analysis. Three approaches that could be used for characterizing risks in a CRA are presented: the multiroute hazard index, stressor grouping by exposure and toxicity, and indices for screening multiple factors and conditions. Other key roles of the risk characterization in CRAs are also described, mainly the translational aspect of including a characterization summary for lay readers (in addition to the technical analysis), and placing the results in the context of the likely risk‐based decisions.     

Assessing the Benefits and Costs of Homeland Security Research: A Risk-Informed Methodology with Applications for the U.S. Coast Guard

This article describes a methodology for risk-informed benefit–cost analyses of homeland security research products. The methodology is field-tested with 10 research products developed for the U.S. Coast Guard. Risk-informed benefit–cost analysis is a tool for risk management that integrates elements of risk analysis, decision analysis, and benefit–cost analysis. The cost analysis methodology includes a full-cost accounting of research projects, starting with initial fundamental research costs and extending to the costs of implementation of the research products and, where applicable, training, maintenance, and upgrade costs. The benefits analysis methodology is driven by changes in costs and risks leading to five alternative models: cost savings at the same level of security, increased security at the same cost, signal detection improvements, risk reduction by deterrence, and value of information. The U.S. Coast Guard staff selected 10 research projects to test and generalize the methodology. Examples include tools to improve the detection of explosives, reduce the costs of harbor patrols, and provide better predictions of hurricane wind speeds and floods. Benefits models and estimates varied by research project and many input parameters of the benefit estimates were highly uncertain, so risk analysis for sensitivity testing and simulation was important. Aggregating across the 10 research products, we found an overall median net present value of about $385 million, with a range from $54 million (5th percentile) to $877 million (95th percentile). Lessons learned are provided for future applications.     

“The Dose Makes the Poison”: Informing Consumers About the Scientific Risk Assessment of Food Additives

Intensive risk assessment is required before the approval of food additives. During this process, based on the toxicological principle of “the dose makes the poison,? maximum usage doses are assessed. However, most consumers are not aware of these efforts to ensure the safety of food additives and are therefore sceptical, even though food additives bring certain benefits to consumers. This study investigated the effect of a short video, which explains the scientific risk assessment and regulation of food additives, on consumers’ perceptions and acceptance of food additives. The primary goal of this study was to inform consumers and enable them to construct their own risk‐benefit assessment and make informed decisions about food additives. The secondary goal was to investigate whether people have different perceptions of food additives of artificial (i.e., aspartame) or natural origin (i.e., steviolglycoside). To attain these research goals, an online experiment was conducted on 185 Swiss consumers. Participants were randomly assigned to either the experimental group, which was shown a video about the scientific risk assessment of food additives, or the control group, which was shown a video about a topic irrelevant to the study. After watching the video, the respondents knew significantly more, expressed more positive thoughts and feelings, had less risk perception, and more acceptance than prior to watching the video. Thus, it appears that informing consumers about complex food safety topics, such as the scientific risk assessment of food additives, is possible, and using a carefully developed information video is a successful strategy for informing consumers.     

Bioeconomics of Managing the Spread of Exotic Pest Species with Barrier Zones

Exotic pests are serious threats to North American ecosystems; thus, economic analysis of decisions about eradication, stopping, or slowing their spread may be critical to ecosystem management. The proposed bioeconomic model assumes that the rate of population expansion can be reduced (even to negative values in a case of eradication) if certain management actions are taken along the population front. The area of management can be viewed as a dynamic barrier zone that moves together with the population front. The lower is the target rate of spread, the higher would be both benefits and costs of the project. The problem is to find the optimal target rate of spread at which the present value of net benefits from managing population spread reaches its maximum value. If a population spreads along an infinite habitat strip, the target rate of spread is optimal if the slope of the cost function versus the rate of spread is equal to the ratio of the average pest-related damage per unit time and unit area to the discount rate. In a more complex model where the potential area of expansion is limited, two local maxima of net benefits may exist: one for eradication and another for slowing the spread. If both maxima are present, their heights are compared and the strategy that corresponds to a higher value of net benefits is selected. The optimal strategy changes from eradication to slowing the spread and finally to doing nothing as the area occupied by the species increases. The model shows that slowing the spread of pest species generates economic benefits even if a relatively small area remains uninfested. The cost of slowing the spread can be estimated from a model of population expansion via establishment of isolated colonies beyond the moving front. The model is applied to managing the spread of the gypsy moth (Lymantria dispar) populations in the United States.     

Evaluating and improving risk formulas for allocating limited budgets to expensive risk-reduction opportunities

Simple risk formulas, such as risk = probability × impact, or risk = exposure × probability × consequence, or risk = threat × vulnerability × consequence, are built into many commercial risk management software products deployed in public and private organizations. These formulas, which we call risk indices, together with risk matrices, “heat maps,” and other displays based on them, are widely used in applications such as enterprise risk management (ERM), terrorism risk analysis, and occupational safety. But, how well do they serve to guide allocation of limited risk management resources? This article evaluates and compares different risk indices under simplifying conditions favorable to their use (statistically independent, uniformly distributed values of their components; and noninteracting risk‐reduction opportunities). Compared to an optimal (nonindex) approach, simple indices produce inferior resource allocations that for a given cost may reduce risk by as little as 60% of what the optimal decisions would provide, at least in our simple simulations. This article suggests a better risk reduction per unit cost index that achieves 98–100% of the maximum possible risk reduction on these problems for all budget levels except the smallest, which allow very few risks to be addressed. Substantial gains in risk reduction achieved for resources spent can be obtained on our test problems by using this improved index instead of simpler ones that focus only on relative sizes of risk (or of components of risk) in informing risk management priorities and allocating limited risk management resources. This work suggests the need for risk management tools to explicitly consider costs in prioritization activities, particularly in situations where budget restrictions make careful allocation of resources essential for achieving close‐to‐maximum risk‐reduction benefits.     

Traffic‐Based Labor Planning in Retail Stores

Staffing decisions are crucial for retailers since staffing levels affect store performance and labor‐related expenses constitute one of the largest components of retailers’ operating costs. With the goal of improving staffing decisions and store performance, we develop a labor‐planning framework using proprietary data from an apparel retail chain. First, we propose a sales response function based on labor adequacy (the labor to traffic ratio) that exhibits variable elasticity of substitution between traffic and labor. When compared to a frequently used function with constant elasticity of substitution, our proposed function exploits information content from data more effectively and better predicts sales under extreme labor/traffic conditions. We use the validated sales response function to develop a data‐driven staffing heuristic that incorporates the prediction loss function and uses past traffic to predict optimal labor. In counterfactual experimentation, we show that profits achieved by our heuristic are within 0.5% of the optimal (attainable if perfect traffic information was available) under stable traffic conditions, and within 2.5% of the optimal under extreme traffic variability. We conclude by discussing implications of our findings for researchers and practitioners.     

Aligning Chemical Assessment Tools Across the Hazard-Risk Continuum

With the growing number and diversity of hazard and risk assessment algorithms, models, databases, and frameworks for chemicals and their applications, risk assessors and managers are challenged to select the appropriate tool for a given need or decision. Some decisions require relatively simple tools to evaluate chemical hazards (e.g., toxicity), such as labeling for safe occupational handling and transport of chemicals. Others require assessment tools that provide relative comparisons among chemical properties, such as selecting the optimum chemical for a particular use among a group of candidates. Still other needs warrant full risk characterization, coupling both hazard and exposure considerations. Examples of these include new chemical evaluations for commercialization, evaluations of existing chemicals for novel uses, and assessments of the adequacy of risk management provisions. Even well-validated tools can be inappropriately applied, with consequences as severe as misguided chemical management, compromised credibility of the tool and its developers and users, and squandered resources. This article describes seven discrete categories of tools based on their information content, function, and the type of outputs produced. It proposes a systematic framework to assist users in selecting hazard and risk assessment tools for given applications. This analysis illustrates the importance of careful selection of assessment tools to achieve responsible chemical assessment communication and sound risk management.     

Is Epidemiology the Key to Cumulative Risk Assessment?

Although cumulative risk assessment by definition evaluates the joint effects of chemical and nonchemical stressors, studies to date have not considered both dimensions, in part because toxicological studies cannot capture many stressors of interest. Epidemiology can potentially include all relevant stressors, but developing and extracting the necessary information is challenging given some of the inherent limitations of epidemiology. In this article, I propose a conceptual framework within which epidemiological studies could be evaluated for their inclusion into cumulative risk assessment, including a problem formulation/planning and scoping step that focuses on stressors meaningful for risk management decisions, extension of the chemical mixtures framework to include nonchemical stressors, and formal consideration of vulnerability characteristics of the population. In the long term, broadening the applicability and informativeness of cumulative risk assessment will require enhanced communication and collaboration between epidemiologists and risk assessors, in which the structure of social and environmental epidemiological analyses may be informed in part by the needs of cumulative risk assessment.     

Dealing with the White Death: Avalanche Risk Management for Traffic Routes

This article discusses mitigation strategies to protect traffic routes from snow avalanches. Up to now, mitigation of snow avalanches on many roads and railways in the Alps has relied on avalanche sheds, which require large initial investments resulting in high opportunity costs. Therefore, avalanche risk managers have increasingly adopted organizational mitigation measures such as warning systems and closure policies instead. The effectiveness of these measures is, however, greatly dependent on human decisions. In this article, we present a method for optimizing avalanche mitigation for traffic routes in terms of both their risk reduction impact and their net benefit to society. First, we introduce a generic framework for assessing avalanche risk and for quantifying the impact of mitigation. This allows for sound cost-benefit comparisons between alternative mitigation strategies. Second, we illustrate the framework with a case study from Switzerland. Our findings suggest that site-specific characteristics of avalanche paths, as well as the economic importance of a traffic route, are decisive for the choice of optimal mitigation strategies. On routes endangered by few avalanche paths with frequent avalanche occurrences, structural measures are most efficient, whereas reliance on organizational mitigation is often the most appropriate strategy on routes endangered by many paths with infrequent or fuzzy avalanche risk. Finally, keeping a traffic route open may be very important for tourism or the transport industry. Hence, local economic value may promote the use of a hybrid strategy that combines organizational and structural measures to optimize the resource allocation of avalanche risk mitigation.     

Catastrophe Risk Models for Evaluating Disaster Risk Reduction Investments in Developing Countries

Major natural disasters in recent years have had high human and economic costs, and triggered record high postdisaster relief from governments and international donors. Given the current economic situation worldwide, selecting the most effective disaster risk reduction (DRR) measures is critical. This is especially the case for low‐ and middle‐income countries, which have suffered disproportionally more economic and human losses from disasters. This article discusses a methodology that makes use of advanced probabilistic catastrophe models to estimate benefits of DRR measures. We apply such newly developed models to generate estimates for hurricane risk on residential structures on the island of St. Lucia, and earthquake risk on residential structures in Istanbul, Turkey, as two illustrative case studies. The costs and economic benefits for selected risk reduction measures are estimated taking account of hazard, exposure, and vulnerability. We conclude by emphasizing the advantages and challenges of catastrophe model‐based cost‐benefit analyses for DRR in developing countries.     

Flood Risk,Flood Mitigation,and Location Choice: Evaluating the National Flood Insurance Program's Community Rating System

Climate change is expected to worsen the negative effects of natural disasters like floods. The negative impacts, however, can be mitigated by individuals’ adjustments through migration and relocation behaviors. Previous literature has identified flood risk as one significant driver in relocation decisions, but no prior study examines the effect of the National Flood Insurance Program's voluntary program—the Community Rating System (CRS)—on residential location choice. This article fills this gap and tests the hypothesis that flood risk and the CRS‐creditable flood control activities affect residential location choices. We employ a two‐stage sorting model to empirically estimate the effects. In the first stage, individuals’ risk perception and preference heterogeneity for the CRS activities are considered, while mean effects of flood risk and the CRS activities are estimated in the second stage. We then estimate heterogeneous marginal willingness to pay (WTP) for the CRS activities by category. Results show that age, ethnicity and race, educational attainment, and prior exposure to risk explain risk perception. We find significant values for the CRS‐creditable mitigation activities, which provides empirical evidence for the benefits associated with the program. The marginal WTP for an additional credit point earned for public information activities, including hazard disclosure, is found to be the highest. Results also suggest that water amenities dominate flood risk. Thus, high amenity values may increase exposure to flood risk, and flood mitigation projects should be strategized in coastal regions accordingly.     

Design of Developmental Toxicity Studies for Assessing Joint Effects of Dose and Duration

In the assessment of developmental and reproductive effects, the timing and duration of exposures to chemical compounds or other environmental contaminants are of particular interest, as the gestational cycle is known to have periods of increased sensitivity. The goal of this research is to identify optimal experimental designs for conducting developmental toxicity studies when the effects of both exposure level and duration of exposure are of interest. The elements of the study design considered in this evaluation are the allocation of animals to dose-duration exposure groups and the determination of the most efficient intermediate exposure levels. The optimality of various designs is assessed via the accuracy of the estimated excess risk as well as testing criteria. Simulation studies are conducted to compare these criteria and determine optimal design strategies under various underlying dose-response patterns. Asymptotic results are also derived to lend support to the simulation studies.