ALBERT

Notes: For continuous data, risk is defined here as the proportion of animals with values above a large percentile, e.g., the 99th percentile or below the 1st percentile, for the distribution of values among control animals. It is known that reducing the standard deviation of measurements through improved experimental techniques will result in less stringent (higher) doses for the lower confidence limit on the benchmark dose that is estimated to produce a specified risk of animals with abnormal levels for a biological effect. Thus, a somewhat larger (less stringent) lower confidence limit is obtained that may be used as a point of departure for low-dose risk assessment. It is shown in this article that it is important for the benchmark dose to be based primarily on the standard deviation among animals, sa, apart from the standard deviation of measurement errors, sm, within animals. If the benchmark dose is incorrectly based on the overall standard deviation among average values for animals, which includes measurement error variation, the benchmark dose will be overestimated and the risk will be underestimated. The bias increases as sm increases relative to sa. The bias is relatively small if sm is less than one-third of sa, a condition achieved in most experimental designs.

Notes: For diseases with more than one risk factor, the sum of probabilistic estimates of the number of cases caused by each individual factor may exceed the total number of cases observed, especially when uncertainties about exposure and dose response for some risk factors are high. In this study, we outline a method of bounding the fraction of lung cancer fatalities not due to specific well-studied causes. Such information serves as a “reality check” for estimates of the impacts of the minor risk factors, and, as such, complements the traditional risk analysis. With lung cancer as our example, we allocate portions of the observed lung cancer mortality to known causes (such as smoking, residential radon, and asbestos fibers) and describe the uncertainty surrounding those estimates. The interactions among the risk factors are also quantified, to the extent possible. We then infer an upper bound on the residual mortality due to “other” causes, using a consistency constraint on the total number of deaths, the maximum uncertainty principle, and the mathematics originally developed of imprecise probabilities.

Notes: A strong inverse correlation was observed between the polycyclic aromatic hydrocarbon (PAH) mass fraction desorbed, a surrogate measure of bioavailability, and relative carcinogenicity, as quantified by potency equivalency factors (PEFs), for two study sediments from the New York/New Jersey Harbor estuary. Because compounds with the highest toxicity, such as dibenz(a,h)anthracene and benzo(a)pyrene (BAP), also tended to be the least rapidly and least extensively desorbed, the U.S. Environmental Protection Agency (EPA) default guidance may dramatically overestimate risk from exposure to PAH-contaminated soils or sediments. A “relative risk index” (RRI) was developed to account for the combined effects of compound-specific bioavailability and toxic potency in estimating excess cancer risk. Using this approach, estimated excess cancer risk may be diminished by as much as a factor of 159 times versus default EPA guidance. Also, the hierarchy of estimated risk between study sediments and among treatment fractions of study sediments differed using the two approaches, implying that the default approach may inaccurately determine site clean-up priorities. The percentage contribution of each potentially carcinogenic priority PAH to total excess cancer risk was computed under various scenarios. In each case, the contribution of BAP to total excess cancer risk was remarkably invariable, for example, ranging from 48% to 52% in one sediment, and 44% to 54% in the other, over four different exposure durations. These results suggest that BAP may be an excellent indexing compound for gauging relative exposure risk across sediments. Other important contributors to total excess cancer risk were benz(a)anthracene and dibenz(a,h)anthracene. Together, these three compounds comprised nearly 90% of total excess cancer risk from all PAHs in every scenario. This integrated RRI approach may enable regulators to more accurately gauge relative risks and make more informed sediment management decisions.

Notes: The effectiveness of a probabilistic risk assessment (PRA) depends on the quality and relevance of the output from exposure and risk models, which, in turn, depends on the critical inputs to the assessment. These critical inputs are often in the form of probabilistic exposure factor distributions that are derived for the given risk scenario. Deriving probabilistic distributions for model inputs can be time consuming and subjective. The absence of a standard approach for developing these distributions can result in PRAs that are inconsistent and difficult to review by regulatory agencies. We present an approach that reduces subjectivity in the distribution development process without limiting the flexibility needed to prepare relevant PRAs. The approach requires two steps. First, we analyze data pooled at a population scale to (i) identify the most robust demographic descriptors within the population for a given exposure factor, (ii) partition the data into subsets based on these variables, and (iii) construct archetypal distributions for each subpopulation. Second, we sample from these archetypal distributions according to site- or scenario-specific conditions to simulate exposure factor values and use these values to construct the scenario-specific input distribution. The archetypal distributions developed through Step 1 provide a consistent basis for developing scenario-specific distributions so risk assessors will not have to repeatedly collect and analyze raw data for each new assessment. We demonstrate the approach for two commonly used exposure factors—body weight (BW) and exposure duration (ED)—using data that are representative of the U.S. population. For these factors we provide a first set of subpopulation-based archetypal distributions and demonstrate methods for using these distributions to construct relevant scenario-specific probabilistic exposure factor distributions.

Notes: When stricken by a terrorist attack, a war, or a natural disaster, an economic unit or a critical infrastructure may suffer significant loss of productivity. More importantly, due to interdependency or interconnectedness, this initial loss may propagate into other systems and eventually lead to much greater derivative loss. This belongs to what is known as a cascading effect. It is demonstrated in this article that the cascading effect and the derivative loss can be significantly reduced by effective risk management. This is accomplished by deliberately distributing the initial inoperability to other systems so that the total loss (or inoperability) is minimized. The optimal distribution strategy is found by a linear programming technique. The same risk management can also be applied to situations where objectives need to be prioritized. A case study featuring 12 economic sectors illustrates the theory. The result suggests that using the same amount of resources, minimizing risk (inoperability) of infrastructures will generally give rise to highest payoff, whereas overlooking it may result in greatest total loss. The framework developed in this work uses a steady-state approach that applies primarily to managing situations where the attack is catastrophic resulting in very long recovery time.

Notes: Trust in risk managers appears to be an important antecedent of public acceptance for many hazards. However, such trust may be fragile since research suggests that negative performance information has a greater impact than positive performance information (Slovic, 1993). Closer examination of these findings suggests two potential moderators of this valence-related asymmetry—information specificity and hazard risk potential. First, we predicted that the asymmetry would be less evident for low versus high specificity information (risk management policies vs. concrete events). Second, we predicted that it would also be less evident for a low- versus high-risk hazard (pharmaceutical vs. nuclear industry). Study 1 reanalyzed Slovic's original trust asymmetry data for the nuclear industry. In line with Prediction 1, trust asymmetry was less evident for policy than event-related information. Using a new set of items with more clearly defined levels of specificity, Study 2 replicated and extended these findings for the high-risk hazard (nuclear power). In line with Prediction 2, trust asymmetry was even less evident for the low-risk hazard (pharmaceuticals). Positive policies in this industry actually had a greater impact on trust than negative ones, in contrast to previous findings. Results support an information diagnosticity account of earlier findings and suggest that trust in risk managers may be more robust than previously believed.

Notes: Much attention has been addressed to the question of whether Europe or the United States adopts a more precautionary stance to the regulation of potential environmental, health, and safety risks. Some commentators suggest that Europe is more risk-averse and precautionary, whereas the United States is seen as more risk-taking and optimistic about the prospects for new technology. Others suggest that the United States is more precautionary because its regulatory process is more legalistic and adversarial, while Europe is more lax and corporatist in its regulations. The flip-flop hypothesis claims that the United States was more precautionary than Europe in the 1970s and early 1980s, and that Europe has become more precautionary since then. We examine the levels and trends in regulation of environmental, health, and safety risks since 1970. Unlike previous research, which has studied only a small set of prominent cases selected nonrandomly, we develop a comprehensive list of almost 3,000 risks and code the relative stringency of regulation in Europe and the United States for each of 100 risks randomly selected from that list for each year from 1970 through 2004. Our results suggest that: (a) averaging over risks, there is no significant difference in relative precaution over the period, (b) weakly consistent with the flip-flop hypothesis, there is some evidence of a modest shift toward greater relative precaution of European regulation since about 1990, although (c) there is a diversity of trends across risks, of which the most common is no change in relative precaution (including cases where Europe and the United States are equally precautionary and where Europe or the United States has been consistently more precautionary). The overall finding is of a mixed and diverse pattern of relative transatlantic precaution over the period.

Notes: This article tests the hypothesis that the exposure to the threat to societies posed by the introduction of new technologies is associated with a normalization of risk perception. Data collected in 2000 by the International Social Survey Programme (ISSP) on environmental issues were used to explore this hypothesis. Representative samples from 25 countries were employed to assess the national levels of perceived threat to the environment associated with a series of technologies and activities. These values were correlated with economic indicators (mainly from the World Bank) of the diffusion of each of the technologies or activities in each country. Results indicate a negative association of risk perception with the level of technological prevalence (societal normalization effect) and a positive association with the rate of growth of the technology (societal sensitivity effect). These results indicate that the most acute levels of perceived environmental risk are found in those countries where the level of technological prevalence is low but where there has recently been substantial technological development. Environmental awareness is a mediator of the relationship between risk perception and the indices of technological diffusion. This result means that: (1) societal normalization of risk is not a direct consequence of prevalence of the technology, but is driven by awareness of technological development and that (2) societal sensitivity to risk is associated with lower levels of environmental awareness.

Notes: This article investigates whether the choice experiment approach can be used to assess people's preferences and the determinants of these preferences in order to estimate the costs and benefits of different configurations of the transport of hazardous materials by rail. Changes in the exposure to hazardous materials that people are subjected to are used rather than changes in accident risk. To the best knowledge of the author, this has not been done before in a study of people's preferences toward hazardous materials. A mail survey, carried out in two cities in Sweden, is used to obtain tentative estimates of the willingness to pay for a reduction in exposure as well as the willingness to accept an increase in exposure. Special attention is given to viability, since the complexity of the activity studied, transport of hazardous materials, and the method used pose particular challenges. The response rate and tests of validity and consistency indicate that this method can be applied. Moreover, the results suggest that studies of this kind may provide guidance on changes in the transport of hazardous materials, especially because policymakers may influence the attributes presented here. Referring to the exposure of hazardous materials highlights the importance of providing the respondents with adequate information regarding hazardous transports. An important finding is that the amount of background information may have some effect on the stated preferences.

Notes: This article presents a Listeria monocytogenes growth model in milk at the farm bulk tank stage. The main objective was to judge the feasibility and value to risk assessors of introducing a complex model, including a complete thermal model, within a microbial quantitative risk assessment scheme. Predictive microbiology models are used under varying temperature conditions to predict bacterial growth. Input distributions are estimated based on data in the literature, when it is available. If not, reasonable assumptions are made for the considered context. Previously published results based on a Bayesian analysis of growth parameters are used. A Monte Carlo simulation that forecasts bacterial growth is the focus of this study. Three scenarios that take account of the variability and uncertainty of growth parameters are compared. The effect of a sophisticated thermal model taking account of continuous variations in milk temperature was tested by comparison with a simplified model where milk temperature was considered as constant. Limited multiplication of bacteria within the farm bulk tank was modeled. The two principal factors influencing bacterial growth were found to be tank thermostat regulation and bacterial population growth parameters. The dilution phenomenon due to the introduction of new milk was the main factor affecting the final bacterial concentration. The results show that a model that assumes constant environmental conditions at an average temperature should be acceptable for this process. This work may constitute a first step toward exposure assessment for L. monocytogenes in milk. In addition, this partly conceptual work provides guidelines for other risk assessments where continuous variation of a parameter needs to be taken into account.

Notes: Limited time and resources usually characterize environmental decision making at policy organizations such as the U.S. Environmental Protection Agency. In these climates, addressing uncertainty, usually considered a flaw in scientific analyses, is often avoided. However, ignoring uncertainties can result in unpleasant policy surprises. Furthermore, it is important for decisionmakers to know how defensible a chosen policy option is over other options when the uncertainties of the data are considered. The purpose of this article is to suggest an approach that is unique from other approaches in that it considers uncertainty in two specific ways—the uncertainty of stakeholder values within a particular decision context and data uncertainty in the light of the decision-contextual data–values relationship. It is the premise of this article that the interaction between data and stakeholder values is critical to how the decision options are viewed and determines the effect of data uncertainty on the relative acceptability of the decision options, making the understanding of this interaction important to decisionmakers and other stakeholders. This approach utilizes the recently developed decision analysis framework and process, multi-criteria integrated resource assessment (MIRA). This article will specifically address how MIRA can be used to help decisionmakers better understand the importance of uncertainty on the specific (i.e., decision contextual) environmental policy options that they are deliberating.

Notes: Species invasions are extremely common and are vastly outpacing the ability of resource agencies to address each invasion, one species at a time. Management actions that target the whole landscape or ecosystem may provide more cost-effective protection against the establishment of invasive species than a species-by-species approach. To explore what ecosystem-level actions might effectively reduce invasions, we developed a multispecies, multihabitat metapopulation model. We assume that species that successfully establish themselves outside their native range tend to be habitat generalists and that a tradeoff exists between competitive ability and habitat breadth, such that habitat specialists are competitively superior to habitat generalists. In this model, habitat destruction, fragmentation, and short-term disturbances all favor invasion by habitat generalists, despite the inferior competitive abilities of generalist species. Our model results illustrate that providing relatively undisturbed habitat and preventing further habitat degradation and fragmentation can provide a highly cost-effective defense against invasive species.

Notes: In November 2001, the Monterey Institute of International Studies convened a workshop on bioterrorism threat assessment and risk management. Risk assessment practitioners from various disciplines, but without specialized knowledge of terrorism, were brought together with security and intelligence threat analysts to stimulate an exchange that could be useful to both communities. This article, prepared by a subset of the participants, comments on the workshop's findings and their implications and makes three recommendations, two short term (use of threat assessment methodologies and vulnerability analysis) and one long term (application of quantitative risk assessment and modeling), regarding the practical application of risk assessment methods to bioterrorism issues.

Notes: This article presents an approach to the problem of terrorism risk assessment and management by adapting the framework of the risk filtering, ranking, and management method. The assessment is conducted at two levels: (1) the system level, and (2) the asset-specific level. The system-level risk assessment attempts to identify and prioritize critical infrastructures from an inventory of system assets. The definition of critical infrastructures offered by Presidential Decision Directive 63 was used to determine the set of attributes to identify critical assets—categorized according to national, regional, and local impact. An example application is demonstrated using information from the Federal Highway Administration National Bridge Inventory for the State of Virginia. Conversely, the asset-specific risk assessment performs an in-depth analysis of the threats and vulnerabilities of a specific critical infrastructure. An illustration is presented to offer some insights in risk scenario identification and prioritization, multiobjective evaluation of management options, and extreme-event analysis for critical infrastructure protection.

Notes: The article considers point processes most commonly used in reliability and risk analysis. Short-term and long-term behavior for the point processes used as models for repairable systems1 are introduced. As opposed to the long term, the term short term implies that a process is observed during an interval limited by a time close to the mean (or the median) of the respective underlying distribution. A new simple upper bound is proposed on the cumulative intensity function of the renewal process and G-renewal process with an increasing failure rate underlying distribution. The new bound is compared with some known bounds for the renewal process. Finally, a formal definition of “a boundary point” between the short-term repairable system behavior and long-term behavior is introduced. This point can also be used as a lower time limit beyond which the “long-term” Barlow and Proschan bound for the renewal process with NBUE underlying distribution could be effectively applied.

Notes: The U.S. Environmental Protection Agency has begun discussions to consider its assessment of asbestos toxicity related to mineral form and fiber size. Brake workers are typically exposed to short chrysotile fibers. To explore the mesothelioma risk among brake workers, considering other occupational exposures to asbestos, data from a study that was published previously were obtained and the analysis was extended. The National Cancer Institute provided data from a case-control study of mesothelioma. Because many participants with a history of brake work also had employment in other asbestos-related occupations, mesothelioma cases and controls were compared for a history of brake work, controlling for employment in eight occupations with potential asbestos exposure. A stratified analysis was also performed excluding those with any of the eight occupations. Possible interactions between brake work and other occupational exposures related to risk of mesothelioma were also examined. The odds ratio (OR) for employment in brake installation or repair was 0.71 (95% CI: 0.30–1.60) when controlled for insulation or shipbuilding. When a history of employment in any of the eight occupations with potential asbestos exposure was controlled, the OR was 0.82 (95% CI: 0.36–1.80). ORs did not increase with increasing duration of brake work. Exclusion of those with any of the eight exposures resulted in an OR of 0.62 (95% CI: 0.01–4.71) for occupational brake work. There was no evidence of an interaction between brake work and other occupational exposures. These latter analyses were based on small numbers of exposed cases. The results are consistent with the existing literature indicating that brake work does not increase the risk of mesothelioma and adds to the evidence that fiber type and size are important determinants of mesothelioma risk.

Notes: Sensitivity analysis (SA) methods are a valuable tool for identifying critical control points (CCPs), which is one of the important steps in the hazard analysis and CCP approach that is used to ensure safe food. There are many SA methods used across various disciplines. Furthermore, food safety process risk models pose challenges because they often are highly nonlinear, contain thresholds, and have discrete inputs. Therefore, it is useful to compare and evaluate SA methods based upon applications to an example food safety risk model. Ten SA methods were applied to a draft Vibrio parahaemolyticus (Vp) risk assessment model developed by the Food and Drug Administration. The model was modified so that all inputs were independent. Rankings of key inputs from different methods were compared. Inputs such as water temperature, number of oysters per meal, and the distributional assumption for the unrefrigerated time were the most important inputs, whereas time on water, fraction of pathogenic Vp, and the distributional assumption for the weight of oysters were the least important inputs. Most of the methods gave a similar ranking of key inputs even though the methods differed in terms of being graphical, mathematical, or statistical, accounting for individual effects or joint effect of inputs, and being model dependent or model independent. A key recommendation is that methods be further compared by application on different and more complex food safety models. Model independent methods, such as ANOVA, mutual information index, and scatter plots, are expected to be more robust than others evaluated.

Notes: Perceptions of risks associated with mobile phones, base stations, and other sources of electromagnetic fields (EMF) were examined. Data from a telephone survey conducted in the German- and French-speaking parts of Switzerland are presented (N= 1,015). Participants assessed both risks and benefits associated with nine different sources of EMF. Trust in the authorities regulating these hazards was assessed as well. In addition, participants answered a set of questions related to attitudes toward EMF and toward mobile phone base stations. According to respondents' assessments, high-voltage transmission lines are the most risky source of EMF. Mobile phones and mobile phone base stations received lower risk ratings. Results showed that trust in authorities was positively associated with perceived benefits and negatively associated with perceived risks. People who use their mobile phones frequently perceived lower risks and higher benefits than people who use their mobile phones infrequently. People who believed they lived close to a base station did not significantly differ in their level of risks associated with mobile phone base stations from people who did not believe they lived close to a base station. Regarding risk regulation, a majority of participants were in favor of fixing limiting values based on the worst-case scenario. Correlations suggest that belief in paranormal phenomena is related to level of perceived risks associated with EMF. Furthermore, people who believed that most chemical substances cause cancer also worried more about EMF than people who did not believe that chemical substances are that harmful. Practical implications of the results are discussed.

Notes: Experts contend that weather and climate forecasts could have an important role in risk management strategies for community water systems. Yet, most water managers make minimal use of these forecasts. This research explores the determinants of the use of weather and climate forecasts by surveying managers of community water systems in two eastern American states (South Carolina and the Susquehanna River Basin of Pennsylvania). Assessments of the reliability of weather and climate forecasts are not driving their use as water managers who find forecasts reliable are no more likely to use them than are managers who find them unreliable. Although larger systems and those depending on surface water are more likely to use forecasts for some (but not all) purposes, the strongest determinant of forecast use is risk perceptions. Water managers who expect to face problems from weather events in the next decade are much more likely to use forecasts than are water managers who expect few problems. Their expectations of future problems are closely linked with past experience: water managers who have had problems with specific types of weather events (e.g., flood emergencies) in the last 5 years are likely to expect to experience problems in the next decade. Feeling at risk, regardless of the specific source of that weather-related risk, stimulates a decision to use weather and climate forecasts.

Notes: Previous studies have shown that the fatality rate among hazardous waste remediation workers is likely to exceed the fatality rate averted among the public by remediation. The implication is that much hazardous waste remediation is inappropriate on a strictly risk-based basis. Such analyses ignore the fact that the same hazardous waste workers would be engaged in other work with similar or perhaps greater safety risks, and that in any case the single greatest cause of occupational fatalities is traffic accidents, hence distance traveled may be a more important predictor than type of work performed.

Notes: Chemical risk protection in the workplace relies partly on informing workers about possible risks using material safety data sheets (MSDS). This article reports on phase 2 of a project (phase 1 reported in Cox et al.), which employed a mental models approach to improve on data sheets as communicative interventions for perchloroethylene in dry cleaning and rosin-based solder flux in the electronics industry within small businesses in the United Kingdom (small enterprises (SEs) 〈 25 employees in the workplace). It focuses on the efficacy of a multimethod evaluation strategy to assess (1) the capacity of a mental models approach to yield contextually relevant data for intervention design and (2) the effectiveness of the strategy itself in validating the mental models data. The evaluation was conducted using postal questionnaires and semi-structured verbal protocols to provide responses to the alternative intervention content and to prioritize risk messages. User discussion groups were then employed, particularly as a means of establishing whether contextual information could be obtained that would differ qualitatively from the kind elicited through individual (semi) structured methods. We conclude that the mental models approach as part of an iterative process including systematic multimethod evaluation is successful in supporting the design of relevant communications to the users of chemicals. The overall viability of communicative interventions in the context of health and safety in small businesses remains in question. Future research might aim to develop a more holistic approach to interventions in complex occupational contexts.

Notes: This article develops a decision-theoretic methodology for the risk-adjusted mission value (RAMV) for selecting between alternative missions in the presence of uncertainty in the outcomes of the missions. This methodology permits trading off mission risk for mission value, something that probabilistic risk analysis cannot do unless it explicitly incorporates both mission value and risk aversion of the project management. The methodology, in its complete implementation, is consistent with the decision theory known as expected utility theory, although it differs from conventional decision theory in that the probabilities and all but one of the utilities are not those of the decision maker. The article also introduces a new interpretation of risk aversion. The methodology is consistent with the elementary management concept concerning division of labor. An example is presented for selecting between discrete alternatives—four landing sites on Mars. A second example is presented for selecting among a set of continuous alternatives—a comet flyby distance. The methodology is developed within the context of scientific missions, but the methodology is equally applicable to any situation requiring outcome value judgments, probability judgments, and risk aversion judgments by different constituencies.

Notes: Multimodal distribution functions that result from Monte Carlo simulations can be interpreted by superimposing joint probability density functions onto the contour space of the simulated calculations. The method is demonstrated by analysis of the pathway of a radioactive groundwater contaminant using an analytical solution to the transport equation. Simulated concentrations at a fixed time and distance produce multimodal histograms, which are understood with reference to the parameter space for the two random variables—velocity and dispersivity. Numerical integration under the joint density function up to the contour of the analytical solution gives the probability of contaminant exceeding a target concentration. This technique is potentially more efficient than Monte Carlo simulation for low probability events. Visualization of parameter space is restricted to two random variables. Nevertheless, analyzing the two most pertinent random variables in a simulation might still offer insights into the multimodal nature of output histograms.

Notes: In Australia-Salmon, the WTO Appellate Body found Australia to be in violation of the WTO SPS Agreement based on the inconsistency of the “appropriate level of protection” underlying various SPS measures. Article 5.5 of the SPS Agreement prohibits arbitrary or unjustifiable distinctions in “appropriate levels of protection” if such distinctions result in discrimination or a disguised restriction on international trade. In Australia-Salmon, Canada challenged Australia's import ban on salmon. Australia permitted the entry of other fish products that were known to host some of the same diseases cited by Australia in justifying its salmon import ban. The distinction in the “appropriate levels of protection” between Australia's regulation of salmon and its treatment of these other fish products was found to be “arbitrary or unjustified” and to have “resulted in a restriction on international trade.”Australia-Salmon was the first WTO decision to find an Article 5.5 violation. Canada successfully made a “weakest link” argument to undercut Australia's regulatory justification. The decision rests on the relationship between the risk purportedly justifying the salmon import ban and the risk seemingly ignored in Australia's treatment of other fish products—the regulatory “situations” compared concerned the identical pathogens with the identical potential consequences. As such, Australia-Salmon may be an example of a category of regulatory “chains” that are peculiarly exposed to Article 5.5 challenge. In responding to the Appellate Body's ruling, Australia reduced its limits on salmon and imposed new restrictions on the other fish products. The outcome suggests that a challenge of one SPS measure under Article 5.5 may lead to the imposition of new restrictions on other imported products—an unexpected result for the free trade regime.

Notes: Various methods exist to calculate confidence intervals for the benchmark dose in risk analysis. This study compares the performance of three such methods in fitting nonlinear dose-response models: the delta method, the likelihood-ratio method, and the bootstrap method. A data set from a developmental toxicity test with continuous, ordinal, and quantal dose-response data is used for the comparison of these methods. Nonlinear dose-response models, with various shapes, were fitted to these data. The results indicate that a few thousand runs are generally needed to get stable confidence limits when using the bootstrap method. Further, the bootstrap and the likelihood-ratio method were found to give fairly similar results. The delta method, however, resulted in some cases in different (usually narrower) intervals, and appears unreliable for nonlinear dose-response models. Since the bootstrap method is more time consuming than the likelihood-ratio method, the latter is more attractive for routine dose-response analysis. In the context of a probabilistic risk assessment the bootstrap method has the advantage that it directly links to Monte Carlo analysis.

Notes: This study investigated the prevalence of both accurate and erroneous earthquake-related beliefs among a sample of Southern California college students and the relationship between their endorsement of earthquake beliefs and adoption of seismic hazard adjustments. In addition, the study examined the effects of an experimental earthquake education program and the impact of need for cognition on this program. The data revealed a significant degree of agreement with earthquake myths, a generally low level of correlation between earthquake beliefs and the level of hazard adjustments, and a significant effect of hazard information on the endorsement of accurate earthquake beliefs and increases in hazard adjustment. Compared with the “Earthquake Facts (Only)” format, an “Earthquake Myths versus Facts” format was slightly more useful for dispelling erroneous beliefs. Further, there was a tendency for those who were high in need for cognition to have higher levels of hazard adjustment. Finally, there was weak support for the hypothesis that those who were low in need for cognition would develop more accurate earthquake beliefs and higher levels of hazard adjustment in the “Earthquake Myths versus Facts” information condition.

Notes: Recent research finds that perceived risk is closely associated with race and gender. In surveys of the American public a subset of white males stand out for their uniformly low perceptions of environmental health risks, while most nonwhite and nonmale respondents reveal higher perceived risk. Such findings have been attributed to the advantageous position of white males in American social life. This article explores the linked possibility that this demographic pattern is driven not simply by the social advantages or disadvantages embodied in race or gender, but by the subjective experience of vulnerability and by sociopolitical evaluations pertaining to environmental injustice. Indices of environmental (in)justice and social vulnerability were developed as part of a U.S. National Risk Survey (n= 1,192) in order to examine their effect on perceived risk. It was found that those who regarded themselves as vulnerable and supported belief statements consistent with the environmental justice thesis offered higher risk ratings across a range of hazards. Multivariate analysis indicates that our measures of vulnerability and environmental (in)justice predict perceived risk but do not account for all of the effects of race and gender. The article closes with a discussion of the implications of these findings for further work on vulnerability and risk, risk communication, and risk management practices generally.

Notes: A common problem in ethics is that people often desire an end but fail to take the means necessary to achieve it. Employers and employees may desire the safety end mandated by performance standards for pollution control, but they may fail to employ the means, specification standards, necessary to achieve this end. This article argues that current (de jure) performance standards, for lowering employee exposures to ionizing radiation, fail to promote de facto worker welfare, in part because employers and employees do not follow the necessary means (practices known as specification standards) to achieve the end (performance standards) of workplace safety. To support this conclusion, the article argues that (1) safety requires attention to specification, as well as performance, standards; (2) coal-mine specification standards may fail to promote performance standards; (3) nuclear workplace standards may do the same; (4) choosing appropriate means to the end of safety requires attention to the ways uncertainties and variations in exposure may mask violations of standards; and (5) correcting regulatory inattention to differences between de jure and de facto is necessary for achievement of ethical goals for safety.

Notes: Expanding a limited empirical base on effects of risk comparisons, a pilot experiment explored how varying elements of such comparisons might influence public response. The scenario used was a hypothetical trial of an asbestos-installing firm for putting students and staff at a junior high school at “unreasonable risk,” first used by Slovic et al. (1990). Study participants played the role of jurors in the trial, asked to rate the risk, the firm's guilt, whether it should be made liable for future health effects, whether the school should be occupied in its current condition, and whether the asbestos should be removed at a cost of $3 million. Opportunity samples of New Jersey residents (n= 309) received information intended to vary four comparison attributes: number of dimensions of comparison; single versus multiple ways of expressing mortality; a narrative to explain and justify the risk comparison; and the hypothetical role of the participant (juror vs. parent). The dependent variable was a hazard scale constructed from four of the five postcomparison judgments. ANOVA found format variations swamped in their effect by concern about asbestos, with the absence of a narrative and the parental role being the only attributes that increased negative risk reactions. Multiple regression analyses found that multidimensionality, narrative, role, and the presence of any risk comparison at all had significant effects when these (plus death formats) were the only independent variables. However, only multidimensionality (which increased negative reactions) retained significance when asbestos concern, risk beliefs (no safe level of exposure to a carcinogen; any exposure leads to cancer), and demographic variables were added to the analysis. Concern and risk beliefs alone explained 33% of variance in hazard scores; adding demographics and risk comparison variables only raised explained variance to 36% (having children at home and being exposed to multidimensional risk comparisons raised scores; age and income lowered them). The results underline the potentially small effect of risk comparison information on risk views (at least between subjects), but offer some insight into aspects of message design left unexplored in empirical literature to date.

Notes: Recent articles by Busza et al. (BJSW) and Dar et al. (DDH) argue that astrophysical data can be used to establish small bounds on the risk of a “killer strangelet” catastrophe scenario in the RHIC and ALICE collider experiments. The case for the safety of the experiments set out by BJSW does not rely solely on these bounds, but on theoretical arguments, which BJSW find sufficiently compelling to firmly exclude any possibility of catastrophe.Nonetheless, DDH and other commentators (initially including BJSW) suggested that these empirical bounds alone do give sufficient reassurance. This seems unsupportable when the bounds are expressed in terms of expectation value—a good measure, according to standard risk analysis arguments. For example, DDH's main bound, pcatastrophe 〈 2 × 10−8, implies only that the expectation value of the number of deaths is bounded by 120; BJSW's most conservative bound implies the expectation value of the number of deaths is bounded by 60,000.This article reappraises the DDH and BJSW risk bounds by comparing risk policy in other areas. For example, it is noted that, even if highly risk-tolerant assumptions are made and no value is placed on the lives of future generations, a catastrophe risk no higher than ≈10−15 per year would be required for consistency with established policy for radiation hazard risk minimization. Allowing for risk aversion and for future lives, a respectable case can be made for requiring a bound many orders of magnitude smaller.In summary, the costs of small risks of catastrophe have been significantly underestimated by BJSW (initially), by DDH, and by other commentators. Future policy on catastrophe risks would be more rational, and more deserving of public trust, if acceptable risk bounds were generally agreed upon ahead of time and if serious research on whether those bounds could indeed be guaranteed was carried out well in advance of any hypothetically risky experiment, with the relevant debates involving experts with no stake in the experiments under consideration.

Notes: Despite many claims for and against the use of risk comparisons in risk communication, few empirical studies have explored their effect. Even fewer have examined the public's relative preferences among different kinds of risk comparisons. Two studies, published in this journal in 1990 and 2003, used seven measures of “acceptability” to examine public reaction to 14 examples of risk comparisons, as used by a hypothetical factory manager to explain risks of his ethylene oxide plant. This study examined the effect on preferences of scenarios involving low or high conflict between the factory manager and residents of the hypothetical town (as had the 2003 study), and inclusion of a claim that the comparison demonstrated the risks' acceptability. It also tested the Finucane et al. (2000) affect hypothesis that information emphasizing low risks—as in these risk comparisons—would raise benefits estimates without changing risk estimates. Using similar but revised scenarios, risk comparison examples (10 instead of 14), and evaluation measures, an opportunity sample of 303 New Jersey residents rated the comparisons, and the risks and benefits of the factory. On average, all comparisons received positive ratings on all evaluation measures in all conditions. Direct and indirect measures showed that the conflict manipulation worked; overall, No-Conflict and Conflict scenarios evoked scores that were not significantly different. The attachment to each risk comparison of a risk acceptability claim (“So our factory's risks should be acceptable to you.”) did not worsen ratings relative to conditions lacking this claim. Readers who did or did not see this claim were equally likely to infer an attempt to persuade them to accept the risk from the comparison. As in the 2003 article, there was great individual variability in inferred rankings of the risk comparisons. However, exposure to the risk comparisons did not reduce risk estimates significantly (while raising benefit estimates), and Conflict-Claim respondents found the risk of the hypothetical factory less acceptable than No-Conflict respondents. Results suggest that neither risk comparisons nor risk acceptability claims are automatically anathema to audiences, but they may have tiny or unintended effects on audience judgments about risky situations.

Notes: It is believed that food hygiene precautions in domestic kitchens are an important strategy in efforts to reduce the incidence of sporadic food poisoning, but recent research has shown that people who have suffered food poisoning handle the same types of foods and adopt similar food hygiene precautions in their kitchens to the rest of the population. This suggests the need to examine other factors. A case-control study of sporadic Salmonella food poisoning was conducted to investigate several domestic kitchen risk factors. Measures of perception of risk, knowledge, and control associated with food poisoning in case and control respondents are reported here. It was found that perceived personal risk from food poisoning in the home was less than perceived risk to other people. In contrast, ratings of personal knowledge about food poisoning and personal control over food poisoning in the home were seen to be greater than other people's knowledge and control. There were no differences between the cases and the controls in their ratings of knowledge about food poisoning or their control over food poisoning. However, cases perceived their personal risk from food poisoning to be higher than controls. Both case and control samples exhibited optimistic bias but this was reduced in the case sample, suggesting that experience with food poisoning may reduce optimistic bias.

Notes: Recent events have increased awareness of the risk posed by terrorist attacks. Bacillus anthracis has resurfaced in the 21st century as a deadly agent of bioterrorism because of its potential for causing massive civilian casualties. This analysis presents the results of a computer simulation of the dispersion of anthrax spores in a typical 50-story, high-rise building after an intentional release during a bioterrorist incident. The model simulates aerosol dispersion in the case of intensive, small-scale convection, which equalizes the concentration of anthrax spores over the building volume. The model can be used to predict the time interval required for spore dispersion throughout a building after a terrorist attack in a high-rise building. The analysis reveals that an aerosol release of even a relatively small volume of anthrax spores during a terrorist incident has the potential to quickly distribute concentrations that are infectious throughout the building.

Notes: Human health risk assessments use point values to develop risk estimates and thus impart a deterministic character to risk, which, by definition, is a probability phenomenon. The risk estimates are calculated based on individuals and then, using uncertainty factors (UFs), are extrapolated to the population that is characterized by variability. Regulatory agencies have recommended the quantification of the impact of variability in risk assessments through the application of probabilistic methods.In the present study, a framework that deals with the quantitative analysis of uncertainty (U) and variability (V) in target tissue dose in the population was developed by applying probabilistic analysis to physiologically-based toxicokinetic models. The mechanistic parameters that determine kinetics were described with probability density functions (PDFs). Since each PDF depicts the frequency of occurrence of all expected values of each parameter in the population, the combined effects of multiple sources of U/V were accounted for in the estimated distribution of tissue dose in the population, and a unified (adult and child) intraspecies toxicokinetic uncertainty factor UFH-TK was determined.The results show that the proposed framework accounts effectively for U/V in population toxicokinetics. The ratio of the 95th percentile to the 50th percentile of the annual average concentration of the chemical at the target tissue organ (i.e., the UFH-TK) varies with age. The ratio is equivalent to a unified intraspecies toxicokinetic UF, and it is one of the UFs by which the NOAEL can be divided to obtain the RfC/RfD. The 10-fold intraspecies UF is intended to account for uncertainty and variability in toxicokinetics (3.2×) and toxicodynamics (3.2×). This article deals exclusively with toxicokinetic component of UF.The framework provides an alternative to the default methodology and is advantageous in that the evaluation of toxicokinetic variability is based on the distribution of the effective target tissue dose, rather than applied dose. It allows for the replacement of the default adult and children intraspecies UF with toxicokinetic data-derived values and provides accurate chemical-specific estimates for their magnitude. It shows that proper application of probability and toxicokinetic theories can reduce uncertainties when establishing exposure limits for specific compounds and provide better assurance that established limits are adequately protective. It contributes to the development of a probabilistic noncancer risk assessment framework and will ultimately lead to the unification of cancer and noncancer risk assessment methodologies.

Notes: The treatment of uncertainties associated with modeling and risk assessment has recently attracted significant attention. The methodology and guidance for dealing with parameter uncertainty have been fairly well developed and quantitative tools such as Monte Carlo modeling are often recommended. However, the issue of model uncertainty is still rarely addressed in practical applications of risk assessment. The use of several alternative models to derive a range of model outputs or risks is one of a few available techniques. This article addresses the often-overlooked issue of what we call “modeler uncertainty,” i.e., difference in problem formulation, model implementation, and parameter selection originating from subjective interpretation of the problem at hand. This study uses results from the Fruit Working Group, which was created under the International Atomic Energy Agency (IAEA) BIOMASS program (BIOsphere Modeling and ASSessment). Model-model and model-data intercomparisons reviewed in this study were conducted by the working group for a total of three different scenarios. The greatest uncertainty was found to result from modelers' interpretation of scenarios and approximations made by modelers. In scenarios that were unclear for modelers, the initial differences in model predictions were as high as seven orders of magnitude. Only after several meetings and discussions about specific assumptions did the differences in predictions by various models merge. Our study shows that parameter uncertainty (as evaluated by a probabilistic Monte Carlo assessment) may have contributed over one order of magnitude to the overall modeling uncertainty. The final model predictions ranged between one and three orders of magnitude, depending on the specific scenario. This study illustrates the importance of problem formulation and implementation of an analytic-deliberative process in risk characterization.

Notes: This article presents the results of an analysis of the accident history data reported under section 112(r) of the Clean Air Act Amendments. These data provide a fairly complete record of the consequences of reportable accidental releases occurring during the time frame 1995–1999 in the U.S. chemical industry and covering 77 toxic and 63 flammable substances subject to the provisions of section 112(r). As such, these results are of fundamental interest to the affected communities, regulators, and insurers, as well as to owners and managers in the chemical industry. The results show the statistical associations between accident frequency and severity and a number of characteristics of reporting facilities, including their size, the hazardousness of the processes and chemicals inventoried, and the regulatory programs (in addition to section 112(r)) to which these facilities are subject. The results are interpreted in light of economic drivers of protective activity and regulatory priorities for monitoring and enforcement.

Notes: Unlike other waste streams, municipal solid waste (MSW) is collected manually, and MSW collection has recently been found to be among the highest-risk occupations in the United States. However, as for other occupational groups, actual total injury rates, including the great majority of injuries not compensated and those compensated by other insurance, are not known. In this article a predictive Bayesian method of assessing total injury rates from available information without computation is presented, and used to assess the actual numbers of musculoskeletal and dermal injuries requiring clinical care of MSW workers in Florida. Closed-form predictive Bayesian distributions that narrow progressively in response to information, representing both uncertainty and variability, are presented. Available information included workers' compensation (WC) data, worker population data, and safety records for one private and one public collection agency. Subjective input comprised epidemiological and medical judgment based on a review of 165 articles. The number of injuries was assessed at 3,146 annually in Florida, or 54 ± 18 injuries per 100 workers per year with 95% confidence. Further, WC data indicate that the injury rate is 50% higher for garbage collectors specifically, indicating a rate of approximately 80 per 100 workers. Results, though subject to uncertainty in worker numbers and classification and reporting bias, agreed closely with a survey of 251 MSW collectors, of whom 75% reported being injured (and 70% reported illness) within the past 12 months. The approach is recommended for assessment of total injury rates and, where sufficient information exists, for the more difficult assessment of occupational disease rates.

Notes: Statistical fatigue life of a ductile alloy specimen is traditionally divided into three stages, namely, crack nucleation, small crack growth, and large crack growth. Crack nucleation and small crack growth show a wide variation and hence a big spread on cycles versus crack length graph. Relatively, large crack growth shows a lesser variation. Therefore, different models are fitted to the different stages of the fatigue evolution process, thus treating different stages as different phenomena. With these independent models, it is impossible to predict one phenomenon based on the information available about the other phenomenon. Experimentally, it is easier to carry out crack length measurements of large cracks compared to nucleating cracks and small cracks. Thus, it is easier to collect statistical data for large crack growth compared to the painstaking effort it would take to collect statistical data for crack nucleation and small crack growth. This article presents a fracture mechanics-based stochastic model of fatigue crack growth in ductile alloys that are commonly encountered in mechanical structures and machine components. The model has been validated by Ray (1998) for crack propagation by various statistical fatigue data. Based on the model, this article proposes a technique to predict statistical information of fatigue crack nucleation and small crack growth properties that uses the statistical properties of large crack growth under constant amplitude stress excitation. The statistical properties of large crack growth under constant amplitude stress excitation can be obtained via experiments.

Notes: An occupational risk assessment for manganese (Mn) was performed based on benchmark dose analysis of data from two epidemiological studies providing dose-response information regarding the potential neurological effects of exposure to airborne Mn below the current Occupational Safety and Health Administration (OSHA) Permissible Exposure Level (PEL) of 5 mg Mn/m3. Based on a review of the scientific evidence regarding the toxicity of Mn, it was determined that the most appropriate measure of exposure to airborne Mn for the subclinical effects measured in these studies is recent (rather than historical or cumulative) concentration of Mn in respirable (rather than total) particulate. For each of the studies analyzed, the individual exposure and response data from the original study had been made available by the investigators. From these two studies benchmark concentrations calculated for eight endpoints ranged from 0.09 to 0.27 mg Mn/m3. From our evaluation of these results, and considering the fact that the subtle, subclinical effects represented by the neurological endpoints tested in these studies do not represent material impairment, we believe an appropriate occupational exposure guideline for manganese would be in the range of 0.1 to 0.3 mg Mn/m3, based on the respirable particulate fraction only, and expressed as an 8-hour time-weighted average.

Notes: The Safe Drinking Water Act Amendments of 1996 required U.S. utilities to report on drinking water quality to their customers annually, beginning in fall 1999, on the assumption that such reports would alert them to quality problems and perhaps mobilize pressure for improvement. A random sample of New Jersey customers read alternative versions of a water quality report, in an experiment on reactions to water quality information under U.S. Environmental Protection Agency (USEPA) rules. Experiment design was 2 × 3 + 1: two versions each—one with, one without, a violation of a health standard—of a report that was (1) Qualitative (without water quality numbers, thus not meeting USEPA rules); (2) Basic, with minimal information meeting the rules; or (3) Extended, adding reading aids and utility performance information; plus a control instrument without any hypothetical report. Results of ANOVA suggest the reports will have less effect than hoped or feared. These manipulations were successful: people reading the Qualitative versions were less likely to say that the report gave the amounts of substances found in the water, and those reading Violation versions were more likely to report a violation of a health standard. The main differences in responses to the report involved the judged adequacy of the information, and to a lesser extent responses on a Concern scale (constructed from measures of concern, judged risk, clean-up intentions, distrust of utility information, and doubt that the utility was doing all it could to improve water quality). Overall judgments of water quality and utility performance did not change, either relative to the controls or in before versus after responses. Qualitative reports performed worse than others, confirming the decision to have utilities report actual contaminant levels. Extended reports did only slightly better than the Basic versions on these measures. Many respondents had trouble identifying the presence or absence of substance amounts or violations, despite their seeming obviousness (e.g., in a “bottom line” summary on the front page of each report), suggesting many were not processing this information carefully. However, the pattern of responses for those who accurately identified the presence or absence of substance amounts or violations did not differ substantially from that for the group as a whole. Generic risk beliefs (serious local environmental problems; lack of control over risks to one's health) dominated demographic variables, attitudes toward utility water quality or trustworthiness, and the content and format of water quality reports in influencing concern about drinking water quality. Previous empirical and theoretical evidence for lack of change in public risk attitudes due to one-time or infrequent communications—e.g., role of personal experience, perseverance of prior trust or distrust—seems to be confirmed for annual water quality reports.

Notes: Polluted soils have become a public health problem. While population exposure to soil pollutants is generally quantified using multimedia models, their estimations have not been validated, and studies that attempted to do so are scarce. The objective of the SOLEX study was to compare the predictions of pyrene exposure levels (converted into 1 hydroxypyrene) computed by several models with the results of urinary 1-hydropyrene (1-HOP) assays among 110 employees working at three sites polluted during their past use as manufactured gas plants. Four models were used: AERIS (Canada), CalTOX (California, USA), CLEA (UK), and HESP (The Netherlands). Three occupational exposure scenarios—with office, mixed, and outdoor workers—were constructed, based upon job activities during two measurement campaigns, one in winter and one in summer. The exposure levels estimated by the four models could differ markedly (from 7 up to 80 times) according to the exposure scenario. Also, the predominant exposure routes differed according to the model (direct soil ingestion for HESP and CalTOX, inhalation for AERIS, and dermal absorption for CLEA). The predictions of CalTOX are consistent with the 1-HOP measurements for all the scenarios. For HESP, the consistency is observed for the scenarios, office and mixed, for which the pyrene level in the soil is low. AERIS and CLEA yield results that are systematically above the 1-HOP measurements. This study confirms that validation of the models is crucial and points out to the need to proceed to assess components of the models that are the most influential using appropriate statistical analysis in combination with true field data.

Notes: The wide-scale use of methyl tertiary butyl ether (MTBE) in gasoline has resulted in substantial public controversy and action to ban or control its use due to perceived impacts on water quality. Because oxygenates are still required under federal law, considerable research has focused on ethanol as a substitute for MTBE. In this article, we summarize the currently available literature on the air and water quality risks and benefits of MTBE versus ethanol as alternative fuel oxygenates. We find that MTBE-fuel blends are likely to have substantial air quality benefits; ethanol-fuel blends appear to offer similar benefits, but these may be at least partially negated because of ethanol's propensity to increase emissions and ambient concentrations of some air contaminants. Releases of gasoline containing either MTBE or ethanol could have an impact on some drinking water sources, although the impacts associated with MTBE tend to relate to aesthetics (i.e., taste and odor), whereas the impacts associated with ethanol generally relate to health risk (i.e., greater exposure to gasoline constituents such as benzene). It is likely that these water quality impacts will be outweighed by the air quality benefits associated with MTBE and perhaps ethanol use, which affect a much larger population. A lack of data on environmental exposures and associated health impacts hinders the completion of a comprehensive quantitative risk-benefit analysis, and the available air and water quality data should be evaluated in a broader risk-management context, which considers the potential life-cycle impacts, costs, and feasibility associated with alternative fuel oxygenates.

Notes: A sample of 3,201 Danes was subjected to personal interviews in which they were asked to state their preferences for risk-reducing health care interventions based on information on absolute risk reduction (ARR) and relative risk reduction (RRR). The aim of the study was to measure the relative weighting of different types of risk information under various circumstances. The effect of presenting questions, and of explicitly formulating RRR, was analyzed. A preference for increases in RRR was demonstrated. There was a stronger inclination to choose the intervention that offered the highest RRR if RRR was explicitly stated. Individuals with more than 10 years of schooling also demonstrated a preference for increased ARR, but only when facing individually framed choices. In a social choice context, preferences for RRR remained intact, but the magnitude of ARR had no impact on choices. Results imply that social framing may induce a propensity to prefer interventions that target high-risk populations. Those respondents who had received ≤10 years of schooling demonstrated preferences for RRR but not ARR, and no impact of social framing was observed.

Notes: The relationship between trust and risk perception was investigated, within and across four European countries (Sweden, Spain, United Kingdom, and France). Survey data were collected in 1996; total number of respondents was approximately 1,000 (United Kingdom and Spain), 1,350 (France), and 2,050 (Sweden). Trust was a significant predictor of perceived risk within countries, but the strength of the relationship varied from weak (Spain and France) to moderate (United Kingdom and Sweden). General trust was also a significant source of variation in perceived risk among countries, but much of the variation in perceived risk remained unexplained. Correlations between trust and risk perception also varied depending on the type of risk (i.e., nuclear risks were more influenced by trust) and trust measure (i.e., general trust explained perceived risk better than specific trust). It is concluded that trust may be an element in models explaining risk perception, but it is not as powerful as often argued in the risk perception literature.

Notes: Despite many claims for and against the use of risk comparisons in risk communication, few empirical studies have explored their effect. Only one study, published by Roth et al. in this journal in 1990, has tested the 1988 predictions by Covello et al. as to the public's relative preferences for 14 kinds of risk comparisons as they might be used by a factory manager to explain risks of his ethylene oxide plant. That study found no correlations between the Covello predictions and seven different measures of “acceptability” of Covello's examples of each type of comparison. However, two critics of the Roth study, as well as its own authors, suggested that a scenario involving local risks, a conflict-ridden situation, and a plant manager unknown to the townspeople might better evoke Covello-like preferences than the distant, calm, friends-involving scenario used by Roth. The research reported here replicated the Roth study using the same scenario, risk comparison examples, and evaluation measures, and added a second scenario intended to replicate the conditions suggested by critics. Over 200 New Jersey residents answered the study questionnaire. The replication scenario reproduced Roth's results, and the conflict scenario also evoked no rankings correlated with Covello's predictions. Furthermore, neither agreement nor disagreement with five statements representing “conflict”—respondents' reports that the industrial-plant scenario made them angry, they lived near industry, they were concerned about industrial risks, people in their home town were angry about industrial pollution, and they worried “frequently” about long-term effects of pollution—correlated with Covello's predictions. Over half of all ratings ascribed to the comparisons in aggregate were positive, and most detailed comments offered by respondents also were positive, despite many criticisms and suggestions for their improvement. The wide variability in individuals' rankings also undermines the notion of any single ranking of preferred comparisons. These findings have implications for use of risk comparisons, but also reveal the inaccuracy of the field's assumptions about public reaction to industrial risk information, including risk comparison.

Notes: The effect of specification of the target on risk evaluation was examined. A whole set of hazards, covering most of the domains, were considered: common individual hazards, outdoor activities, medical care, public transportation, energy production, pollutants, sex, deviance, and addictions. Three human targets were introduced: personal health risk (including personal risk of death), health risk for people in the country, and health risk for people in the world. The basic design was a between-subjects design. The first hypothesis was that risk judgments made in the “world” condition should be higher than risk judgments made in the “country” condition, and risk judgments made in this condition should be higher than risk judgments made in the “personal” condition. This is what was observed. The second hypothesis was that the target effect should differ as a function of the kind of hazards considered. This also is what was observed. In two domains— pollutants, and deviance, sex, and addictions—the target effect was important. It corresponded to about one-tenth of the response scale. In the four remaining domains, the target effect was unimportant or absent.

Notes: Dissemination of risk information is ubiquitous in contemporary society. We explore how individuals react in everyday life to health-risk information, based on what they report in personal interviews. Health-risk information was without exception recognized as unstable and inconsistent. This conformity, however, did not extend to the narratives regarding how health-risk information should be handled. Two opposite positions (ideal-typical strategies) are presented. Either you tend to process and evaluate new information or you tend to ignore it as a whole. Our attempt to reveal the underlying rationality in these two very different approaches involved the exploration of three different avenues of interpretation and brings together two scientific paradigms—economics and sociology—that provide the framework for our analysis. First, we suggest that a greater long-term experience of explicit choice implies that this kind of action becomes more natural and less resource consuming, whereas a reliance on habits in daily life—a natural adjustment to a lack of resources—makes it is more costly to bother about new information. Second, with fewer resources in the short run, fewer opportunities to mitigate bad outcomes, and greater exposure to social and material risks, one is less likely to devote resources to deal with health-risk information. Third, there are several possible links between a low propensity to take account of risk information and a high relative importance of genuine uncertainty in one's life. These theoretical perspectives provide a viable set of hypotheses regarding mechanisms that may contribute to social differences in the response to health-risk information.

Notes: European directives require that all veterinary medicines be assessed to determine the harmful effects that their use may have on the environment. Fundamental to this assessment is the calculation of the predicted environmental concentration (PEC), which is dependent on the type of drug, its associated treatment characteristics, and the route by which residues enter the environment. Deterministic models for the calculation of the PEC have previously been presented. In this article, the inclusion of variability and uncertainty within such models is introduced. In particular, models for the calculation of the PEC for residues excreted directly onto pasture by grazing animals are considered and comparison of deterministic and stochastic results suggest that uncertainty and variability cannot be ignored.

Notes: In risk assessment, no observed exposure level (NOAEL) and benchmark dose (BMD) are usually derived either from epidemiological studies in humans or from animal experiments. In many in vitro studies, concentration-effect/response curves have been analyzed using different mathematical models finalized to the identification of EC50. In the present article, we propose a model to fit dose-response curves in vitro. The BMD approach has been used to compare the cell viability (MTT assay) of different rat (C6 and PC12, glial and neuronal, respectively) and human cell lines (D384 and SK-N-MC, glial and neuronal, respectively) after 24-hour exposure to the following neurotoxic substances: manganese chloride (MnCl2), methyl-mercury (Me-Hg), and the enantiomers of styrene oxide (SO). For all rat and human cell lines, the potency of the examined compounds was: MnCl2 〈 S-SO 〈 R-SO 〈 Me-Hg. A preliminary comparison with in vivo toxicity data for these substances gave rise to consistent results. Whereas a reasonable agreement between in vitro and in vivo data has been found for Mn and styrene oxide, a wide scatter of LOAEL has been reported for Me-Hg and these appear to be either much higher or lower than the BMD for the MTT assay we observed invitro.

Notes: This article examines the role of climatic and hydrological variability in assessing the cumulative risk of flood events in Poland over a T-year period. In a broad sense flood-risk estimation combines a frequency analysis of extreme hydrological phenomena with an evaluation of flood-induced damages. The damage from floods depends on the critical values of the river discharges. The probabilistic flood analysis usually includes an estimation of the expected annual probability of the critical discharge Qcr being exceeded and the equivalent long-term risk of it being exceeded over the next T years. If, however, the process is nonstationary, the T-year risk of flood damage may depend importantly on the variation of hydrological processes. As a possible explanation for the variations observed in snowmelt-induced floods in Polish rivers, this article investigates the possible impact of the North Atlantic Oscillation (NAO) on surface air temperature T and precipitation P. The spatial distribution of the correlation coefficients between NAO and T, as well as NAO and P, show very significant differences in the NAO impact on meteorological variables in various parts of Europe. To assess the implications of NAO variations on spring flood discharges, a simple model of Snow Cover Water Equivalent (SCWE) was applied to selected Polish river catchments. The conclusion of this analysis is that the yearly maximum of SCWE values significantly decreases with increasing NAO. This leads to a temporal redistribution of winter and spring runoff. The question of spring flood characteristics being stationary or nonstationary may therefore be linked with stochastic properties of the NAO index time series.

Notes: We examine the opportunities for using catastrophe-linked securities (or equivalent forms of nondebt contingent capital) to reduce the total costs of funding infrastructure projects in emerging economies. Our objective is to elaborate on methods to reduce the necessity for unanticipated (emergency) project funding immediately after a natural disaster. We also place the existing explanations of sovereign-level contingent capital into a catastrophic risk management framework. In doing so, we address the following questions. (1) Why might catastrophe-linked securities be useful to a sovereign nation, over and above their usefulness for insurers and reinsurers? (2) Why are such financial instruments ideally suited for protecting infrastructure projects in emerging economies, under third-party sponsorship, from low-probability, high-consequence events that occur as a result of natural disasters? (3) How can the willingness to pay of a sovereign government in an emerging economy (or its external project sponsor), who values timely completion of infrastructure projects, for such instruments be calculated? To supplement our treatment of these questions, we use a multilayer spreadsheet-based model (in Microsoft Excel format) to calculate the overall cost reductions possible through the judicious use of catastrophe-based financial tools. We also report on numerical comparative statics on the value of contingent-capital financing to avoid project disruption based on varying costs of capital, probability and consequences of disasters, the feasibility of strategies for mid-stage project abandonment, and the timing of capital commitments to the infrastructure investment. We use these results to identify high-priority applications of catastrophe-linked securities so that maximal protection can be realized if the total number of catastrophe instruments is initially limited. The article concludes with potential extensions to our model and opportunities for future research.

Notes: Risk perceptions have, to a great extent, been studied exclusively as individual cognitive mechanisms in which individuals collect, process, and form perceptions as atomized units unconnected to a social system. These individual-level theories do not, however, help explain how perception of risk may vary between communities or within a single community. One alternative approach is based on a network theory of contagion. This approach, emerging largely from organizational and community social network studies, suggests that it is the relational aspects of individuals and the resulting networks and self-organizing systems that influence individual perceptions and build “groups or communities of like-minded” individuals. These social units, it is argued, behave as attitude, knowledge, or behavioral structures. The study reported in this article tests one aspect of this theoretical perspective. The central hypothesis proposes the existence of risk perception networks—relational groupings of individuals who share, and perhaps create, similar risk perceptions. To test this idea, data were collected from individuals involved in a community environmental conflict over a hazardous waste site cleanup. The statistical analysis used a matrix of relational social linkages to compare with a matrix of individual risk perceptions. The analysis confirmed the hypothesis suggesting that social linkages in communities may play an important role in focusing risk perceptions.

Notes: We adopted a comparative approach to evaluate and extend a generic methodology to analyze the different sets of beliefs held about chemical hazards in the workplace. Our study mapped existing knowledge structures about the risks associated with the use of perchloroethylene and rosin-based solder flux in differing workplaces. “Influence diagrams” were used to represent beliefs held by chemical experts; “user models” were developed from data elicited from open-ended interviews with the workplace users of the chemicals. The juxtaposition of expert and user understandings of chemical risks enabled us to identify knowledge gaps and misunderstandings and to reinforce appropriate sets of safety beliefs and behavior relevant to chemical risk communications. By designing safety information to be more relevant to the workplace context of users, we believe that employers and employees may gain improved knowledge about chemical hazards in the workplace, such that better chemical risk management, self-protection, and informed decision making develop over time.

Notes: The growing international trade in live wildlife has the potential to result in continuing establishment of nonnative animal populations in the United States. Snakes may pose particularly high risks as potentially invasive species, as exemplified by the decimation of Guam's vertebrate fauna by the accidentally introduced brown tree snake. Herein, ecological and commercial predictors of the likelihood of establishment of invasive populations were used to model risk associated with legal commercial imports of 23 species of boas, pythons, and relatives into the United States during the period 1989–2000. Data on ecological variables were collected from multiple sources, while data on commercial variables were collated from import records maintained by the U.S. Fish and Wildlife Service. Results of the risk-assessment models indicate that species including boa constrictors (Boa constrictor), ball pythons (Python regius), and reticulated pythons (P. reticulatus) may pose particularly high risks as potentially invasive species. Recommendations for reducing risk of establishment of invasive populations of snakes and/or pathogens include temporary quarantine of imports to increase detection rates of nonnative pathogens, increasing research attention to reptile pathogens, reducing the risk that nonnative snakes will reach certain areas with high numbers of federally listed species (such as the Florida Keys), and attempting to better educate individuals purchasing reptiles.

Notes: This study examines the perceived risks to forest biodiversity and perceived effectiveness of biodiversity conservation strategies among the general public. It tests the hypotheses that perceived risk to forest biodiversity is influenced by cognitive factors (value orientation and knowledge) and social-cultural factors (such as gender and environmental membership) and that risk perceptions influence other cognitive constructs such as support for natural resource policy and management. Data were collected from a sample of the general public (n= 596) in British Columbia, Canada by mail survey in 2001. Results show that insects and disease were perceived as the greatest risk. Educating the public and industry about biodiversity issues was perceived as a more effective conservation strategy than restricting human uses of the forest. Value orientation was a better predictor of perceptions of risk and perceived effectiveness of conservation strategies than knowledge indicators or social-cultural variables. Examining the indirect effects of social-cultural variables, however, revealed that value orientation may amplify the effect of these variables and suggests that alternative paths of influence should be included. Perceived risk showed an inconsistent association with perceived effectiveness of conservation strategies.

Notes: A unique multidisciplinary perspective on the risk literature is used to establish a fresh and provocative argument regarding the epistemological understanding and definition of risk. Building on economic conceptualizations that distinguish risk from uncertainty and argue that risk is an ordered application of knowledge to the unknown, the survey identifies each of the disciplines as having a particular knowledge approach with which they confront the unknown so as to order its randomness and convert it into a risk proposition. This epistemological approach suggests the concept of risk can act as a mirror, reflecting the preoccupations, strengths, and weaknesses of each discipline as they grapple with uncertainty. The conclusion suggests that the different disciplines can, and desirably should, act in concert toward a cumulative appreciation of risk that progresses our understanding of the concept. One way in which the article challenges risk experts to join disciplinary forces in a collaborative effort is to holistically appreciate and articulate the concept of political risk calculation.

Notes: By displaying a risk reduction of 50% graphically rather than numerically, Stone, Yates, and Parker significantly increased professed risk-avoidant behavior. The current experiments replicated this effect at various risk ratios. Specifically, participants were willing to spend more money to reduce a risk when the risk information was displayed by asterisks rather than by numbers for risk-reduction ratios ranging from 3% to 97%. Transforming the amount participants were willing to spend to logarithms significantly improved a linear fit to the data, suggesting that participants convert this variable within the decision-making process. Moreover, a log-linear model affords an exceptional fit to both the graphical and numerical data, suggesting that a graphical presentation elicits the same decision-making mechanism as does the numerical display. In addition, the data also suggest that each person removed from harm is weighted more by some additional factor in the graphical compared to the numerical presentations.

Notes: Seven driving attitude scales representing driving behaviors and beliefs about driving were created and initially validated using 257 undergraduate students (168 females, 89 males) in Study 1. However, the Speeding Attitude Scale (SAS) accounted for most of the strength of the intercorrelations among these scales and discriminant classification analyses showed that SAS dominated the other scales as a sufficient explanation for having speeding tickets. Study 2, using 180 students (75 males, 105 females), replicated findings regarding the significant but low correlation between SAS and speeding tickets, and was significantly correlated with Zuckerman's Sensation Seeking Scale (SSS). Replication also showed that males had higher SAS scores and more speeding tickets. Accidents were typically a function of sex, increasing age, and variables related to recent accident history. Objective sources of speeding attitude confirmation may enhance the future validity of the SAS. Potential interventions for being a safe passenger and attitudinal control in the training of young drivers were discussed.

Notes: The prospect of industrial accidents motivated the U.S. Congress to require in the Clean Air Act of 1990 that manufacturing facilities develop Risk Management Plans (RMP) to submit to the U.S. Environmental Protection Agency (USEPA) by July 1999. Industry worried that the requirement to communicate to the public a “worst-case scenario” would arouse unnecessary and counterproductive fears among industry neighbors. We report here the results of focus groups and surveys with such neighbors, focusing particularly upon their reactions to messages about a hypothetical worst-case scenario and management of these risks by industry, government, and other parties. Our findings confirmed our hypotheses that citizens would be skeptical of the competence and trustworthiness of these managers and that this stance would color their views of industrial-facility accident risks. People with job ties to industry or who saw industrial benefits to the community as exceeding its risks had more positive views of industrial risks, but still expressed great concern about the risk and doubt about accident management. Notwithstanding these reactions, overall respondents welcomed this and other related information, which they wanted their local industries to supply. Respondents were not more reassured by additional text describing management of accidents by government and industry. However, respondents did react very positively to the concept of community oversight to review plant safety. Claims about the firm's moral obligation or financial self-interest in preventing accidents were also received positively. Further research on innovative communication and management of accident risks is warranted by these results, even before recent terrorist attacks made this topic more salient.

Notes: Enabling people to make an informed choice on whether to change consumption behavior is ultimately the objective of any fish consumption advisory. This will occur only if people are aware of the advisory, know and understand the advisory information, and believe the information to be true. Interactive, meaningful communication and the opportunity to participate in the process to develop and review advisories are key to achieving these attributes. A case study was undertaken in a community in Alberta, Canada (where an existing advisory was under consideration for review) to determine public awareness, knowledge, compliance, communication effectiveness, information needs, and desire for involvement related to the advisory. The information obtained from this case study was used to develop 14 guiding principles as a foundation for the incorporation of public participation and risk communication into the process of developing and reviewing fish consumption advisories.

Notes: Quantitative risk assessment (QRA) models are used to estimate the risks of transporting dangerous goods and to assess the merits of introducing alternative risk reduction measures for different transportation scenarios and assumptions. A comprehensive QRA model recently was developed in Europe for application to road tunnels. This model can assess the merits of a limited number of “native safety measures.” In this article, we introduce a procedure for extending its scope to include the treatment of a number of important “nonnative safety measures” of interest to tunnel operators and decisionmakers. Nonnative safety measures were not included in the original model specification. The suggested procedure makes use of expert judgment and Monte Carlo simulation methods to model uncertainty in the revised risk estimates. The results of a case study application are presented that involve the risks of transporting a given volume of flammable liquid through a 10-km road tunnel.

Notes: This article investigates how accurately experts (underwriters) and lay persons (university students) judge the risks posed by life-threatening events. Only one prior study (Slovic, Fischhoff, & Lichtenstein, 1985) has previously investigated the veracity of expert versus lay judgments of the magnitude of risk. In that study, a heterogeneous grouping of 15 experts was found to judge, using marginal estimations, a variety of risks as closer to the true annual frequencies of death than convenience samples of the lay population. In this study, we use a larger, homogenous sample of experts performing an ecologically valid task. We also ask our respondents to assess frequencies and relative frequencies directly, rather than ask for a “risk” estimate—a response mode subject to possible qualitative attributions—as was done in the Slovic et al. study. Although we find that the experts outperformed lay persons on a number of measures, the differences are small, and both groups showed similar global biases in terms of: (1) overestimating the likelihood of dying from a condition (marginal probability) and of dying from a condition given that it happens to you (conditional probability), and (2) underestimating the ratios of marginal and conditional likelihoods between pairs of potentially lethal events. In spite of these scaling problems, both groups showed quite good performance in ordering the lethal events in terms of marginal and conditional likelihoods. We discuss the nature of expertise using a framework developed by Bolger and Wright (1994), and consider whether the commonsense assumption of the superiority of expert risk assessors in making magnitude judgments of risk is, in fact, sensible.

Notes: Probability models incorporating a deterministic versus stochastic infectious dose are described for estimating infection risk due to airborne pathogens that infect at low doses. Such pathogens can be occupational hazards or candidate agents for bioterrorism. Inputs include parameters for the infectious dose model, distribution parameters for ambient pathogen concentrations, the breathing rate, the duration of an exposure period, the anticipated number of exposure periods, and, if a respirator device is used, distribution parameters for respirator penetration values. Application of the models is illustrated with a hypothetical scenario involving exposure to Coccidioides immitis, a fungus present in soil in areas of the southwestern United States. Inhaling C. immitis spores causes a respiratory tract infection and is a recognized occupational hazard in jobs involving soil dust exposure in endemic areas. An uncertainty analysis is applied to risk estimation in the context of selecting respiratory protection with a desired degree of efficacy.

Notes: Linear, no-threshold relationships are typically reported for time series studies of air pollution and mortality. Since regulatory standards and economic valuations typically assume some threshold level, we evaluated the fundamental question of the impact of exposure misclassification on the persistence of underlying personal-level thresholds when personal data are aggregated to the population level in the assessment of exposure-response relationships. As an example, we measured personal exposures to two particle metrics, PM2.5 and sulfate (SO42−), for a sample of lung disease patients and compared these with exposures estimated from ambient measurements. Previous work has shown that ambient:personal correlations for PM2.5 are much lower than for SO42−, suggesting that ambient PM2.5 measurements misclassify exposures to PM2.5. We then developed a method by which the measured:estimated exposure relationships for these patients were used to simulate personal exposures for a larger population and then to estimate individual-level mortality risks under different threshold assumptions. These individual risks were combined to obtain the population risk of death, thereby exhibiting the prominence (and the value) of the threshold in the relationship between risk and estimated exposure. Our results indicated that for poorly classified exposures (PM2.5 in this example) population-level thresholds were apparent at lower ambient concentrations than specified common personal thresholds, while for well-classified exposures (e.g., SO42−), the apparent thresholds were similar to these underlying personal thresholds. These results demonstrate that surrogate metrics that are not highly correlated with personal exposures obscure the presence of thresholds in epidemiological studies of larger populations, while exposure indicators that are highly correlated with personal exposures can accurately reflect underlying personal thresholds.

Notes: The impacts of fish consumption advisories on recreational and subsistence fishing, particularly in fresh waters, have been examined extensively. By contrast, little attention has focused on organized recreational fishing, such as from party and charter boats, and particularly for salt water fish. We interviewed 93 New Jersey boat captains to determine their knowledge about fish consumption advisories, and whether, in their opinion, clients knew of fish consumption advisories, and whether they thought advisories had an effect on recreational fishing and their businesses. Advisories were ranked by captains as a moderate influence on the success of their business, less so than number of fish caught, strength of the economy, overfishing by commercial boats, and management regulations. Only one boat captain had not heard warnings about eating fish, but what captains said they had heard was mixed in its accuracy and completeness. Clients expect captains to know about fish, and about half of boat captains said clients had asked about the safety of eating fish. Captains who felt advisories were affecting their businesses tended to fish for species without high levels of mercury (except for bluefish) or PCBs, the primary contaminants of concern for state advisories and federal advice. However, these captains worked closer to areas (e.g., Raritan Bay complex and New York Harbor) subject to advisories than did other captains, and were more prone to say that management regulations (e.g., fish size, creel limits, seasons) and marketing and advertising by the industry or state were strong influences on the success of their seasons. Comparing captains who thought advisories had some or great effect (60%) versus those reporting “no effect” (40%), there was no difference in the mean percentage of trips targeting high mercury species such as swordfish and shark. Many captains said they would or might post advisories, but 42% of the boat captains said they would not post consumption warnings if the state provided them. The significant portion (at least 15%) of saltwater fishing supported by these businesses suggests that these captains are an important conduit for future risk communication.

Notes: This article begins with a review of the regulation of chemicals in Sweden over the past 30 years, focusing particularly on the 1997 Government Environmental Quality Bill, which called for a toxic-free society by the year 2020. The second part of the article analyzes why Sweden has taken this route. The third and final section discusses Sweden's present role in formulating present EU chemical regulation, such as the recent EU Chemical White Paper, and hypothesizes future impacts of Swedish chemical regulations on the EU itself.

Notes: To quantify the health benefits of environmental policies, economists generally require estimates of the reduced probability of illness or death. For policies that reduce exposure to carcinogenic substances, these estimates traditionally have been obtained through the linear extrapolation of experimental dose-response data to low-exposure scenarios as described in the U.S. Environmental Protection Agency's Guidelines for Carcinogen Risk Assessment (1986). In response to evolving scientific knowledge, EPA proposed revisions to the guidelines in 1996. Under the proposed revisions, dose-response relationships would not be estimated for carcinogens thought to exhibit nonlinear modes of action. Such a change in cancer-risk assessment methods and outputs will likely have serious consequences for how benefit-cost analyses of policies aimed at reducing cancer risks are conducted. Any tendency for reduced quantification of effects in environmental risk assessments, such as those contemplated in the revisions to EPA's cancer-risk assessment guidelines, impedes the ability of economic analysts to respond to increasing calls for benefit-cost analysis. This article examines the implications for benefit-cost analysis of carcinogenic exposures of the proposed changes to the 1986 Guidelines and proposes an approach for bounding dose-response relationships when no biologically based models are available. In spite of the more limited quantitative information provided in a carcinogen risk assessment under the proposed revisions to the guidelines, we argue that reasonable bounds on dose-response relationships can be estimated for low-level exposures to nonlinear carcinogens. This approach yields estimates of reduced illness for use in a benefit-cost analysis while incorporating evidence of nonlinearities in the dose-response relationship. As an illustration, the bounding approach is applied to the case of chloroform exposure.

Notes: The increased use of stakeholder processes in environmental decision making has raised concerns about the quality of decisions these processes produce. Some claim that stakeholders make inadequate use of scientific information and analysis and are all too ready to sacrifice technical quality for political expediency. This article looks to the case study record to examine the quality of the decisions from stakeholder-based processes. The data for the analysis come from a “case survey,” in which researchers coded information from 239 published case studies of stakeholder involvement in environmental decision making. These cases reflect a diversity of planning, management, and implementation activities carried out by environmental and natural resource agencies at many levels of government. Overall, the case-study record suggests that there should be little concern that stakeholder processes are resulting in low-quality decisions. The majority of cases contain evidence of stakeholders improving decisions over the status quo; adding new information, ideas, and analysis; and having adequate access to technical and scientific resources. Indeed, data suggest that it is the more intensive stakeholder processes—precisely those that have aroused recent concern—that are more likely to result in higher-quality decisions.

Notes: Research on risk perception aims to explain how people perceive risks in order to better communicate about them. Most of this research has tended to view people as passive risk perceivers. However, if confronted with an unknown risk, people can also actively seek information. The main purpose of this study was to investigate what kind of risk information people desire when confronted with an unknown risk and how this desire for information relates to the main dimensions underlying risk perception. Nine focus-group interviews were conducted. The main results of the focus groups were backed up by a paper-and-pencil questionnaire that was distributed among a random sample of 500 households in the Netherlands. Overall, people desire information with which they can determine the personal relevance of the risk confronting them. This pattern is similar to appraisal steps described by health behavior models. The focus-group results provide a dynamic picture of the way risk aspects might interact to create a final risk judgment.

Notes: In 2001, the U.S. Environmental Protection Agency derived a reference dose (RfD) for methylmercury, which is a daily intake that is likely to be without appreciable risk of deleterious effects during a lifetime. This derivation used a series of benchmark dose (BMD) analyses provided by a National Research Council (NRC) panel convened to assess the health effects of methylmercury. Analyses were performed for a number of endpoints from three large longitudinal cohort studies of the neuropsychological consequences of in utero exposure to methylmercury: the Faroe Islands, Seychelles Islands, and New Zealand studies. Adverse effects were identified in the Faroe Islands and New Zealand studies, but not in the Seychelles Islands. The NRC also performed an integrative analysis of all three studies. The EPA applied a total uncertainty factor (UF) of 10 for intrahuman toxicokinetic and toxicodynamic variability and uncertainty. Dose conversion from cord blood mercury concentrations to maternal methylmercury intake was performed using a one-compartment model. Derivation of potential RfDs from a number of endpoints from the Faroe Islands study converged on 0.1 μg/kg/day, as did the integrative analysis of all three studies. EPA identified several areas for which further information or analyses is needed. Perhaps the most immediately relevant is the ratio of cord:maternal blood mercury concentration, as well as the variability around this ratio. EPA assumed in its dose conversion that the ratio was 1.0; however, available data suggest it is perhaps 1.5–2.0. Verification of a deviation from unity presumably would be translated directly into comparable reduction in the RfD. Other areas that EPA identified as significant areas requiring further attention are cardiovascular consequences of methylmercury exposure and delayed neurotoxicity during aging as a result of previous developmental or adult exposure.

Notes: Risk estimates for food-borne infection will usually depend heavily on numbers of microorganisms present on the food at the time of consumption. As these data are seldom available directly, attention has turned to predictive microbiology as a means of inferring exposure at consumption. Codex guidelines recommend that microbiological risk assessment should explicitly consider the dynamics of microbiological growth, survival, and death in foods. This article describes predictive models and resources for modeling microbial growth in foods, and their utility and limitations in food safety risk assessment. We also aim to identify tools, data, and knowledge sources, and to provide an understanding of the microbial ecology of foods so that users can recognize model limits, avoid modeling unrealistic scenarios, and thus be able to appreciate the levels of confidence they can have in the outputs of predictive microbiology models. The microbial ecology of foods is complex. Developing reliable risk assessments involving microbial growth in foods will require the skills of both microbial ecologists and mathematical modelers. Simplifying assumptions will need to be made, but because of the potential for apparently small errors in growth rate to translate into very large errors in the estimate of risk, the validity of those assumptions should be carefully assessed. Quantitative estimates of absolute microbial risk within narrow confidence intervals do not yet appear to be possible. Nevertheless, the expression of microbial ecology knowledge in “predictive microbiology” models does allow decision support using the tools of risk assessment.

Notes: Probabilistic risk analysis (PRA) can be an effective tool to assess risks and uncertainties and to set priorities among safety policy options. Based on systems analysis and Bayesian probability, PRA has been applied to a wide range of cases, three of which are briefly presented here: the maintenance of the tiles of the space shuttle, the management of patient risk in anesthesia, and the choice of seismic provisions of building codes for the San Francisco Bay Area. In the quantification of a risk, a number of problems arise in the public sector where multiple stakeholders are involved. In this article, I describe different approaches to the treatments of uncertainties in risk analysis, their implications for risk ranking, and the role of risk analysis results in the context of a safety decision process. I also discuss the implications of adopting conservative hypotheses before proceeding to what is, in essence, a conditional uncertainty analysis, and I explore some implications of different levels of ``conservatism'' for the ranking of risk mitigation measures.

Notes: Universal need for, or reactions to, risk communications should not be assumed; potential differences across demographic groups in environmental risk beliefs, attitudes, and behaviors could affect risk levels or opportunities for risk reduction. This article reports relevant findings from a survey experiment involving 1,100 potential jurors in Philadelphia concerning public responses to outdoor air pollution and air quality information. Flynn et al. (1994) and Finucane et al. (2000) found significant differences in risk ratings for multiple hazards, and in generic risk beliefs, between white men (or a subset) and all others (white women, nonwhite men, and nonwhite women). This study examined whether white men had significantly different responses to air pollution and air pollution information. An opportunity sample of volunteers from those awaiting potential jury duty in city courts (matching census estimates for white versus nonwhite proportions, but more female than the city's adult population and more likely to have children) filled out questionnaires distributed quasi-randomly. On most measures there were no statistically significant differences among white men (N = 192), white women (N = 269), nonwhite men (N = 165), and nonwhite women (N = 272). Nonwhites overall (particularly women) reported more concern about and sensitivity to air pollution than whites, and were more concerned by (even overly sensitive to) air pollution information provided as part of the experiment. Nonwhites also were more likely (within-gender comparisons) to report being active outdoors for at least four hours a day, a measure of potential exposure to air pollution, and to report intentions to reduce such outdoor activity after reading air pollution information. Differences between men and women were less frequent than between whites and nonwhites; the most distinctive group was nonwhite women, followed by white men. Flynn et al. (1994) and Finucane et al. (2000) found a far larger proportion of significant differences, with white men as most distinctive, probably due to use of different measures, study design, and population samples. However, all three studies broadly confirm the existence of gender and race interactions in risk beliefs and attitudes (particularly for white men and nonwhite women) that deserve more attention from researchers.

Notes: Promotion or criticism of risk comparisons in risk communication has far exceeded empirical tests of their effects. Slovic et al. (1990) experimented with a hypothetical jury trial in which an asbestos-installing firm was accused of subjecting school occupants to unreasonable risk. A risk comparison sharply reduced subjects' estimates of risk and judgments that the firm was guilty, but a critique of the risk comparison had risk estimates and guilt judgments rebounding to the original (without risk comparison) level. Slovic et al. concluded that risk comparisons' effects were highly unstable, at least in conflict-ridden situations such as a jury trial. The present study replicates and extends this important study, using the same stimuli and questions. The respective effects of the risk comparison and the critique recurred, although much less sharply than in Slovic et al. Moreover, judgments of guilt, risk, and other aspects of the case seemed shaped more by demographics and beliefs about risk generically (e.g., about the likelihood of cancer after exposure to a carcinogen) than by either risk comparison or critique. A variant design, in which the defense's expert witness dismissed potential criticisms of the risk comparison, appeared to “inoculate” people against shifting their views after seeing the critique. Overall, these results show that risk comparisons might change some beliefs about risks in conflict and that “inoculation” can reduce vulnerability to criticism. However, the results also show strong limits on effects of both comparisons and their critiques: they shifted only a minority of judgments and had small effects relative to people's social locations and prior risk beliefs.

Notes: While quantitative estimates of risk have been a standard practice in cancer risk assessment for many years, no similar practice is evident in noncancer risk assessment. We use two recent examples involving methylmercury and arsenic to illustrate the negative impact of this discrepancy on risk communication and cost-benefit analysis. We argue for a more balanced treatment of cancer and noncancer risks and suggest an approach for reaching this goal.

Notes: Experimental animal studies often serve as the basis for predicting risk of adverse responses in humans exposed to occupational hazards. A statistical model is applied to exposure-response data and this fitted model may be used to obtain estimates of the exposure associated with a specified level of adverse response. Unfortunately, a number of different statistical models are candidates for fitting the data and may result in wide ranging estimates of risk. Bayesian model averaging (BMA) offers a strategy for addressing uncertainty in the selection of statistical models when generating risk estimates. This strategy is illustrated with two examples: applying the multistage model to cancer responses and a second example where different quantal models are fit to kidney lesion data. BMA provides excess risk estimates or benchmark dose estimates that reflects model uncertainty.

Notes: Following a comprehensive evaluation of the health risks of radon, the U.S. National Research Council (US-NRC) concluded that the radon inside the homes of U.S. residents is an important cause of lung cancer. To assess lung cancer risks associated with radon exposure in Canadian homes, we apply the new (US-NRC) techniques, tailoring assumptions to the Canadian context. A two-dimensional uncertainty analysis is used to provide both population-based (population attributable risk, PAR; excess lifetime risk ratio, ELRR; and life-years lost, LYL) and individual-based (ELRR and LYL) estimates. Our primary results obtained for the Canadian population reveal mean estimates for ELRR, PAR, and LYL are 0.08, 8%, and 0.10 years, respectively. Results are also available and stratified by smoking status (ever versus never). Conveniently, the three indices (ELRR, PAR, and LYL) reveal similar output uncertainty (geometric standard deviation, GSD ≈ 1.3), and in the case of ELRR and LYL, comparable variability and uncertainty combined (GSD ≈ 4.2). Simplifying relationships are identified between ELRR, LYL, PAR, and the age-specific excess rate ratio (ERR), which suggest a way to scale results from one population to another. This insight is applied in scaling our baseline results to obtain gender-specific estimates, as well as in simplifying and illuminating sensitivity analysis.

Notes: Air pollution is a current and growing concern for Canadians, and there is evidence that ambient levels that meet current exposure standards may be associated with mortality and morbidity in Toronto, Canada. Evaluating exposure is an important step in understanding the relationship between particulate matter (PM) exposure and health outcomes. This report describes the PEARLS model (Particulate Exposure from Ambient to Regional Lung by Subgroup), which predicts exposure distributions for 11 age-gender population subgroups in Toronto to PM2.5 (PM with a median aerodynamic diameter of 2.5 μm or less) using Monte Carlo simulation techniques. The model uses physiological and activity pattern characteristics of each subgroup to determine region-specific lung exposure to PM2.5, which is defined as the mass of PM2.5 deposited per unit time to each of five lung regions (two extrathoracic, bronchial, bronchiolar, and alveolar). The modeling results predict that children, toddlers, and infants have the broadest distributions of exposure, and the greatest chance of experiencing extreme exposures in the alveolar region of the lung. Importance analysis indicates that the most influential model variables are air exchange rate into indoor environments, time spent outdoors, and time spent at high activity levels. Additionally, a “critical point” was defined and introduced to the PEARLS to investigate the effects of possible threshold-pathogenic phenomena on subgroup exposure patterns. The analysis indicates that the subgroups initially predicted to be most highly exposed were likely to have the highest proportion of their population exposed above the critical point. Substantial exposures above the critical point were predicted in all subgroups for ambient concentrations of PM2.5 commonly observed in Toronto after continuous exposure of 24 hours or more.

Notes: It has been shown that bathroom-type water uses dominate personal exposure to water-borne contaminants in the home. Therefore, in assessing exposure of specific population groups to the contaminants in the water, understanding population water-use behavior for bathroom activities as a function of demographic characteristics is vital to realistic exposure estimates. In this article, shower and bath frequencies and durations are analyzed, presented, and compared for various demographic groups derived from analyses of the National Human Activities Pattern Survey (NHAPS) database and the Residential End Uses of Water Study (REUWS) database as well as from a review of current literature. Analysis showed that age and level of education significantly influenced shower and bath frequency and duration. The frequency of showering and bathing reported in NHAPS agreed reasonably well with previous studies; however, durations of these events were found to be significantly longer. Showering frequency reported in REUWS was slightly less than that reported for NHAPS; however, durations of showers reported in REUWS are consistent with other studies. After considering the strengths and weaknesses of each data set and comparing their results to previous studies, it is concluded that NHAPS provides more reliable frequency data, while REUWS provides more reliable duration data. The shower- and bath-use behavior parameters recommended in this article can aid modelers in appropriately specifying water-use behavior as a function of demographic group in order to conduct reasonable assessments of exposure to contaminants that enter the home via the water supply.

Notes: Information about two uncertainties is superadditive in value if the value of information for resolving both uncertainties together exceeds the sum of the value of information for resolving each uncertainty alone. For the two-act linear loss decision problem with normal priors, conditions are derived for which the expected value of perfect information about two independent risks is superadditive. An approximate condition is also presented. The level of additivity of information value has implications for how risk-management resources should be allocated to acquisition of information. Several applications show how a variety of decision problems can reduce to the basic problem, and how the general results obtained here can be translated simply to prescriptions for specific situations.

Notes: Reference values, including an oral reference dose (RfD) and an inhalation reference concentration (RfC), were derived for propylene glycol methyl ether (PGME), and an oral RfD was derived for its acetate (PGMEA). These values were based on transient sedation observed in F344 rats and B6C3F1 mice during a two-year inhalation study. The dose-response relationship for sedation was characterized using internal dose measures as predicted by a physiologically-based pharmacokinetic (PBPK) model for PGME and its acetate. PBPK modeling was used to account for changes in rodent physiology and metabolism due to aging and adaptation, based on data collected during Weeks 1, 2, 26, 52, and 78 of a chronic inhalation study. The peak concentration of PGME in richly perfused tissues (i.e., brain) was selected as the most appropriate internal dose measure based on a consideration of the mode of action for sedation and similarities in tissue partitioning between brain and other richly perfused tissues. Internal doses (peak tissue concentrations of PGME) were designated as either no-observed-adverse-effect levels (NOAELs) or lowest-observed-adverse-effect levels (LOAELs) based on the presence or the absence of sedation at each time point, species, and sex in the two-year study. Distributions of the NOAEL and LOAEL values expressed in terms of internal dose were characterized using an arithmetic mean and standard deviation, with the mean internal NOAEL serving as the basis for the reference values, which was then divided by appropriate uncertainty factors. Where data were permitting, chemical-specific adjustment factors were derived to replace default uncertainty factor values of 10. Nonlinear kinetics, which was predicted by the model in all species at PGME concentrations exceeding 100 ppm, complicate interspecies, and low-dose extrapolations. To address this complication, reference values were derived using two approaches that differ with respect to the order in which these extrapolations were performed: (1) default approach of interspecies extrapolation to determine the human equivalent concentration (PBPK modeling) followed by uncertainty factor application, and (2) uncertainty factor application followed by interspecies extrapolation (PBPK modeling). The resulting reference values for these two approaches are substantially different, with values from the latter approach being seven-fold higher than those from the former approach. Such a striking difference between the two approaches reveals an underlying issue that has received little attention in the literature regarding the application of uncertainty factors and interspecies extrapolations to compounds where saturable kinetics occur in the range of the NOAEL. Until such discussions have taken place, reference values based on the former approach are recommended for risk assessments involving human exposures to PGME and PGMEA.

Notes: In the process of screening a soil against a certain contaminant, we define the health-risk-based preliminary remediation goal (PRG) as the contaminant concentration above which some remedial action may be required. Thus, PRG is the first standard (or guidance) for judging a site. An overestimated PRG (a too-large value) may cause us to miss some contaminated sites that can threaten human health and the environment. An underestimated PRG (a too-small value), on the other hand, may lead to unnecessary cleanup and waste tremendous resources. The PRGs for soils are often calculated on the assumption that the contaminant concentration in soil does not change with time. However, that concentration usually decreases with time as a result of different chemical and transport mechanisms. The static assumption thus exaggerates the long-term exposure dose and results in a too-small PRG. We present a box model that considers all important transport processes and obeys the law of mass conservation. We can use the model as a tool to estimate the transient contaminant concentrations in air, soil, and ground water. Using these concentrations in conjunction with appropriate health-risk parameters, we may estimate the PRGs for different contaminants. As an example, we calculated the tritium PRG for residential soils. The result is quite different from, but within the range of, the two versions of the corresponding PRG previously recommended by the U.S. EPA.

Notes: The extreme importance of critical infrastructures to modern society is widely recognized. These infrastructures are complex and interdependent. Protecting the critical infrastructures from terrorism presents an enormous challenge. Recognizing that society cannot afford the costs associated with absolute protection, it is necessary to identify and prioritize the vulnerabilities in these infrastructures. This article presents a methodology for the identification and prioritization of vulnerabilities in infrastructures. We model the infrastructures as interconnected digraphs and employ graph theory to identify the candidate vulnerable scenarios. These scenarios are screened for the susceptibility of their elements to a terrorist attack, and a prioritized list of vulnerabilities is produced. The prioritization methodology is based on multiattribute utility theory. The impact of losing infrastructure services is evaluated using a value tree that reflects the perceptions and values of the decisionmaker and the relevant stakeholders. These results, which are conditional on a specified threat, are provided to the decisionmaker for use in risk management. The methodology is illustrated through the presentation of a portion of the analysis conducted on the campus of the Massachusetts Institute of Technology.

Notes: This study assesses the fire safety risks associated with compressed natural gas (CNG) vehicle systems, comprising primarily a typical school bus and supporting fuel infrastructure. The study determines the sensitivity of the results to variations in component failure rates and consequences of fire events. The components and subsystems that contribute most to fire safety risk are determined. Finally, the results are compared to fire risks of the present generation of diesel-fueled school buses. Direct computation of the safety risks associated with diesel-powered vehicles is possible because these are mature technologies for which historical performance data are available. Because of limited experience, fatal accident data for CNG bus fleets are minimal. Therefore, this study uses the probabilistic risk assessment (PRA) approach to model and predict fire safety risk of CNG buses. Generic failure data, engineering judgments, and assumptions are used in this study. This study predicts the mean fire fatality risk for typical CNG buses as approximately 0.23 fatalities per 100-million miles for all people involved, including bus passengers. The study estimates mean values of 0.16 fatalities per 100-million miles for bus passengers only. Based on historical data, diesel school bus mean fire fatality risk is 0.091 and 0.0007 per 100-million miles for all people and bus passengers, respectively. One can therefore conclude that CNG buses are more prone to fire fatality risk by 2.5 times that of diesel buses, with the bus passengers being more at risk by over two orders of magnitude. The study estimates a mean fire risk frequency of 2.2 × 10−5 fatalities/bus per year. The 5% and 95% uncertainty bounds are 9.1 × 10−6 and 4.0 × 10−5, respectively. The risk result was found to be affected most by failure rates of pressure relief valves, CNG cylinders, and fuel piping.

Notes: Laypeople's perceptions of health and safety risks have been widely studied, but only a few studies have addressed perceptions of ecological hazards. We assembled a list of 39 attributes of ecological hazards from the literatures on comparative risk assessment, ecological health, environmental conservation and management, environmental psychology, and risk perception. In Study 1, 125 laypeople evaluated 83 hazards on subsets of this attribute set. Factor analysis of attribute ratings (averaged over participants) revealed six oblique factors: ecological impacts, human impacts, human benefits, aesthetic impacts, scientific understanding, and controllability. These factors predicted mean judgments of overall riskiness, ecological riskiness, acceptability, and regulatory strictness. In Study 2, 30 laypeople each evaluated 34 hazards on 17 attributes and 3 dependent variables. Aggregate-level factor analysis of these data replicated the appropriate portion of the factor solution and yielded similar regression results. Parallel analyses at the individual-participant level yielded factors that explained less variance in judgments of overall riskiness, ecological riskiness, and acceptability. However, the decrease in explanatory power was much less than is often reported for disaggregate-level analyses of psychometric data. This discrepancy illustrates the importance of distinguishing between the level of analysis (aggregate versus disaggregate) and the focus of analysis (distinctions among hazards versus distinctions among participants). In a hybrid analysis, aggregate-level factor scores predicted individual participants' riskiness judgments reasonably well. Psychometric studies such as these provide a sound empirical basis for selecting attributes of ecological hazards for use in comparative risk assessment.

Notes: Government and private sector organizations are increasingly turning to the use of maps and other visual models to provide a depiction of environmental hazards and the potential risks they represent to humans and ecosystems. Frequently, the graphic presentation is tailored to address a specific contaminant, its location and possible exposure pathways, and potential receptors. Its format is usually driven by the data available, choice of graphics technology, and the audience being served. A format that is effective for displaying one contaminant at one scale at one site, however, may be ineffective in accurately portraying the circumstances surrounding a different contaminant at the same site, or the same contaminant at a different site, because of limitations in available data or the graphics technology being used. This is the daunting challenge facing the U.S. Department of Energy (DOE), which is responsible for the nation's legacy wastes from nuclear weapons research, testing, and production at over 100 sites in the United States. In this article, we discuss the development and use of integrated geospatial mapping and conceptual site models to identify hazards and evaluate alternative long-term environmental clean-up strategies at DOE sites located across the United States. While the DOE probably has the greatest need for such information, the Department of Defense and other public and private responsible parties for many large and controversial National Priority List or Superfund sites would benefit from a similar approach.

Notes: The research team interviewed over 90 Finnish battalion members in Kosovo, visited 22 units or posts, registered its observations, and made any necessary measurements. Key persons were asked to list the most important risks for occupational safety and health in their area of responsibility. Altogether, 106 accidents and 40 cases of disease resulted in compensation claims in 2000. The risks to the peacekeeping force were about twice those of the permanent staff of military trainees in Finland. Altogether, 21 accidents or cases of disease resulted in sick leave for at least 3 months after service. One permanent injury resulted from an explosion. Biological, chemical, and physical factors caused 8 to 9 occupational illnesses each. Traffic accidents, operational factors, and munitions and mines were evaluated to be the three most important risk factors, followed by occupational hygiene, living conditions (mold, fungi, dust), and general hygiene. Possible fatal risks, such as traffic accidents and munitions and explosives, received a high ranking in both the subjective and the objective evaluations. One permanent injury resulted from an explosion, and two traffic accidents involved a fatality, although not of a peacekeeper. The reduction of sports and military training accidents, risk-control programs, and, for some tasks, better personal protection is considered a development challenge for the near future.