ALBERT

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: 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: 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: 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.

Notes: The aim of this study was to determine the impact on risk perceptions of disclosing genetic test results used to estimate the risk of Alzheimer's disease (AD). Adult children (n= 149) of people with AD were randomized to one of two groups—Intervention group: lifetime risk estimates of AD based on age, gender, family history, and Apolipoprotein E (APOE) genotype; Control group: lifetime risk estimates of AD based on the same risk factors excluding APOE genotype. Perceptions of personal risk (PPR) for AD were assessed six weeks after risk assessments. PPR were correlated with actual lifetime risk estimates (r= 0.501; p 〈 0.0001). After controlling for lifetime risks communicated to participants, age, and number of affected relatives, PPR scores among those with an ɛ4-positive test result (the test result associated with increased AD susceptibility) (adjusted mean: 3.4 (SD: 0.7)) were not different from the PPR scores in the Control group (adjusted mean: 3.4 (SD: 0.7) (F(1,91)= 1.98; p= 0.162). Again, controlling for lifetime risk estimates, age, and number of affected relatives, the PPR score of those receiving an ɛ4-negative test result was significantly lower (adjusted mean: 3.1 (SD: 0.8)) than those in the Control group (adjusted mean: 3.4 (SD: 0.7) (F(1,95)= 6.23; p= 0.014). Perceptions of risk of developing AD are influenced by genetic test disclosure in those receiving ɛ4-negative, but not those receiving ɛ4-positive test results. Despite the reduced perceptions of risk in the former group, there was no evidence of false reassurance (i.e., perceiving risks as equal to or lower than population risks of AD), although this possibility should be assessed in other testing contexts.

Notes: Society often sets social standards that define thresholds of damage to society or the environment above which compensation must be paid to the state or other parties. In this article, we analyze the interdependence between the use of social standards and investment evaluation under dynamic uncertainty where a negative externality above a threshold established by society requires an assessment and payment of damages. Under uncertainty, the party considering implementing a project or new technology must not only assess when the project is economically efficient to implement but when to abandon a project that could potentially exceed the social standard. Using real-option theory and simple models, we demonstrate how such a social standard can be integrated into cost-benefit analysis through the use of a development option and a liability option coupled with a damage function. Uncertainty, in fact, implies that both parties interpret the social standard as a target for safety rather than an inflexible barrier that cannot be overcome. The larger is the uncertainty, in fact, the greater will be the tolerance for damages in excess of the social standard from both parties.

Notes: There is increasing interest in being able to express the consequences of exposure to potentially toxic compounds in monetary terms in order to evaluate potential cost-benefit relationships of controlling exposure. Behavioral effects of acute toluene exposure could be subjected to cost-benefit analysis if the effects of toluene were quantitatively compared to those of ethanol ingestion, which has been monetized for applied contexts. Behavioral effects of toluene and ethanol were quantified by meta-analysis of studies from the peer-reviewed literature describing their effects on choice reaction time (reaction time in a test requiring a subject to choose among two or more alternatives before responding). The internal doses of these compounds were estimated by a general physiological and toxicokinetic (GPAT) simulation from exposure parameters provided in the reports. The reported effects were converted to a common metric (proportion of baseline) and related to the estimated internal doses of toluene and ethanol, from which dose-effect equations were fitted. The estimated effect of toluene was compared to the estimated effect of ethanol on the same dependent variable by deriving a dose-equivalence equation (DEE) to express the dose of toluene as an equivalent dose of ethanol on the basis of equal effect magnitude. A nomogram was constructed by GPAT simulation to relate the environmental exposure concentration of toluene to the equivalent effect magnitude of a range of ethanol internal doses. Behavioral effects and their evaluation are determined by internal doses, which in turn are determined by a variety of variables. In addition to concentration and duration of exposure, which determine internal dose by pharmacokinetic processes, the activity level of exposed persons is a major factor. This analysis provides a continuous function of the consequences of toluene exposure expressed as ethanol-equivalent doses within confidence limits. The resulting function has the potential to estimate the monetary values of behavioral deficits caused by a range of exposures to toluene from existing monetized information on ethanol.

Notes: Clostridium perfringens is a pathogen that mainly causes food poisoning outbreaks when large quantities of food are prepared. Therefore, a model was developed to predict the effect of different cooling procedures on the growth of this pathogen during cooling of food: Dutch pea soup. First, a growth rate model based on interpretable parameters was used to predict growth during linear cooling of pea soup. Second, a temperature model for cooling pea soup was constructed by fitting the model to experimental data published earlier. This cooling model was used to estimate the effect of various cooling environments on average cooling times, taking into account the effect of stirring and product volume. The growth model systematically overestimated growth of C. perfringens during cooling in air, but this effect was limited to less than 0.5 log N/ml and this was considered to be acceptable for practical purposes. It was demonstrated that the growth model for C. perfringens combined with the cooling model for pea soup could be used to sufficiently predict growth of C. perfringens in different volume sizes of pea soup during cooling in air as well as the effect of stirring, different cooling temperatures, and various cooling environments on the growth of C. perfringens in pea soup. Although fine-tuning may be needed to eliminate inaccuracies, it was concluded that the combined model could be a useful tool for designing good manufacturing practices (GMP) procedures.

Notes: The management of microbial risk in food products requires the ability to predict growth kinetics of pathogenic microorganisms in the event of contamination and growth initiation. Useful data for assessing these issues may be found in the literature or from experimental results. However, the large number and variety of data make further development difficult. Statistical techniques, such as meta-analysis, are then useful to realize synthesis of a set of distinct but similar experiences. Moreover, predictive modeling tools can be employed to complete the analysis and help the food safety manager to interpret the data. In this article, a protocol to perform a meta-analysis of the outcome of a relational database, associated with quantitative microbiology models, is presented. The methodology is illustrated with the effect of temperature on pathogenic Escherichia coli and Listeria monocytogenes, growing in culture medium, beef meat, and milk products. Using a database and predictive models, simulations of growth in a given product subjected to various temperature scenarios can be produced. It is then possible to compare food products for a given microorganism, according to its growth ability in these products, and to compare the behavior of bacteria in a given foodstuff. These results can assist decisions for a variety of questions on food safety.

Notes: The uncertainty associated with estimates should be taken into account in quantitative risk assessment. Each input's uncertainty can be characterized through a probabilistic distribution for use under Monte Carlo simulations. In this study, the sampling uncertainty associated with estimating a low proportion on the basis of a small sample size was considered. A common application in microbial risk assessment is the estimation of a prevalence, proportion of contaminated food products, on the basis of few tested units. Three Bayesian approaches (based on beta(0, 0), beta 〈inlineGraphic alt="inline image" href="urn:x-wiley:02724332:RISA565:RISA_565_mu1" location="equation/RISA_565_mu1.gif"/〉, and beta(l, 1)) and one frequentist approach (based on the frequentist confidence distribution) were compared and evaluated on the basis of simulations. For small samples, we demonstrated some differences between the four tested methods. We concluded that the better method depends on the true proportion of contaminated products, which is by definition unknown in common practice. When no prior information is available, we recommend the beta 〈inlineGraphic alt="inline image" href="urn:x-wiley:02724332:RISA565:RISA_565_mu2" location="equation/RISA_565_mu2.gif"/〉 prior or the confidence distribution. To illustrate the importance of these differences, the four methods were used in an applied example. We performed two-dimensional Monte Carlo simulations to estimate the proportion of cold smoked salmon packs contaminated by Listeria monocytogenes, one dimension representing within-factory uncertainty, modeled by each of the four studied methods, and the other dimension representing variability between companies.

Notes: A poultry-processing model for a quantitative microbiological risk assessment (QMRA) of campylobacter is presented, which can also be applied to other QMRAs involving poultry processing. The same basic model is applied in each consecutive stage of industrial processing. It describes the effects of inactivation and removal of the bacteria, and the dynamics of cross-contamination in terms of the transfer of campylobacter from the intestines to the carcass surface and the environment, from the carcasses to the environment, and from the environment to the carcasses. From the model it can be derived that, in general, the effect of inactivation and removal is dominant for those carcasses with high initial bacterial loads, and cross-contamination is dominant for those with low initial levels. In other QMRA poultry-processing models, the input-output relationship between the numbers of bacteria on the carcasses is usually assumed to be linear on a logarithmic scale. By including some basic mechanistics, it is shown that this may not be realistic. As nonlinear behavior may affect the predicted effects of risk mitigations; this finding is relevant for risk management. Good knowledge of the variability of bacterial loads on poultry entering the process is important. The common practice in microbiology to only present geometric mean of bacterial counts is insufficient: arithmetic mean are more suitable, in particular, to describe the effect of cross-contamination. The effects of logistic slaughter (scheduled processing) as a risk mitigation strategy are predicted to be small. Some additional complications in applying microbiological data obtained in processing plants are discussed.

Notes: A linear population risk model used by the U.S. Food and Drug Administration (FDA) Center for Veterinary Medicine (CVM) estimates the risk of human cases of campylobacteriosis caused by fluoroquinolone-resistant Campylobacter. Among the cases of campylobacteriosis attributed to domestically produced chicken, the fluoroquinolone resistance is assumed to result from the use of fluoroquinolones in poultry in the United States. Properties of the linear population risk model are contrasted with those of a farm-to-fork model commonly used for microbial risk assessments. The utility of the linear population model for the purpose for which it was used by CVM is discussed.

Notes: A mathematical model is presented, which addresses individual hygiene practices during food preparation and consumption patterns in private homes. Further, the model links food preparers and consumers based on their relationship to household types. For different age and gender groups, the model estimates (i) the probability of ingesting a meal where precautions have not been taken to avoid the transfer of microorganisms from raw food to final meal (a risk meal), exemplified by the event that the cutting board was not washed during food preparation, and (ii) the probability of ingesting a risk meal in a private home, where chicken was the prepared food item (a chicken risk meal). Chicken was included in the model, as chickens are believed to be the major source of human exposure to the foodborne pathogen Campylobacter. Monte Carlo simulations showed that the probability of ingesting a risk meal was highest for young males (aged 18–29 years) and lowest for the elderly above 60 years of age. Children aged 0–4 years had a higher probability of ingesting a risk meal than children aged 5–17 years. This difference between age and gender groups was ascribed to the variations in the hygiene levels of food preparers. By including the probability of ingesting a chicken meal at home, simulations revealed that all age groups, except the group above 60 years of age, had approximately the same probability of ingesting a chicken risk meal, the probability of females being slightly higher than that of males. The simulated results show that the probability of ingesting a chicken risk meal at home does not only depend on the hygiene practices of the persons preparing the food, but also on the consumption patterns of consumers, and the relationship between people preparing and ingesting food. This finding supports the need of including information on consumer behavior and preparation hygiene in the consumer phase of exposure assessments.

Notes: When the transportation risk posed by shipments of hazardous chemical and radioactive materials is being assessed, it is necessary to evaluate therisks associated with both vehicle emissions and cargo-related risks. Diesel exhaust and fugitive dust emissions from vehicles transporting hazardous shipments lead to increased air pollution, which increases the risk of latent fatalities in the affected population along the transport route. The estimated risk from these vehicle-related sources can often be as large or larger than the estimated risk associated with the material being transported. In this paper, data from the U.S. Environmental Protection Agency's Motor Vehicle-Related Air Toxics Study are first used to develop latent cancer fatality estimates per kilometer of travel in rural and urban areas forall diesel truck classes. These unit risk factors are based on studies investigating the carcinogenic nature of diesel exhaust. With the same methodology, the current per-kilometer latent fatality risk factor used in transportation risk assessments for heavy diesel trucks in urban areas is revised and the analysis expanded to provide risk factors for rural areas and all diesel truck classes. These latter fatality estimates may include, but are not limited to, cancer fatalities and are based primarily on the most recent epidemiological data available on mortality rates associated with ambient air PM-10 concentrations.

Notes: Risk assessors often use different probability plots as a way to assessthe fit of a particular distribution or model by comparing the plotted points to a straight line and to obtain estimates of the parameters in parametric distributions or models. When empirical data do not fall in a sufficiently straight line on a probability plot, and when no other single parametricdistribution provides an acceptable (graphical) fit to the data, the risk assessor may consider a mixture model with two component distributions. Animated probability plots are a way to visualize the possible behaviors of mixture models with two component distributions. When no single parametric distribution provides an adequate fit to an empirical dataset, animated probability plots can help an analyst pick some plausible mixture models for the data based on their qualitative fit. After using animations during exploratory data analysis, the analyst must then use other statistical tools, including but not limited to: Maximum Likelihood Estimation (MLE) to find the optimal parameters, Goodness of Fit (GoF) tests, and a variety of diagnostic plots to check the adequacy of the fit. Using a specific example with two LogNormal components, we illustrate the use of animated probability plots asa tool for exploring the suitability of a mixture model with two component distributions. Animations work well with other types of probability plots, and they may be extended to analyze mixture models with three or more component distributions.

Notes: For carcinogens, this paper provides a quantitative examination of the roles of potency and weight-of-evidence (WOE) in setting permissible exposure limits (PELs) at the U.S. Occupational Safety and Health Administration (OSHA) and threshold limit values (TLVs) at the private American Conference of Governmental Industrial Hygienists (ACGIH). On normative grounds, both of these factors should influence choices about the acceptable level of exposures. Our major objective is to examine whether and in what ways these factors have been considered by these organizations. A lesser objective is to identify outliers, which might be candidates for further regulatory scrutiny. Our sample (N=48) includes chemicals for which EPA has estimated a unit risk as a measure of carcinogenic potency and for which OSHA or the ACGIH has a PEL or TLV. Different assessments of the strength of the evidence of carcinogenicity were obtained from EPA, ACGIH, and the International Agency for Research on Cancer. We found that potency alone explains 49% of the variation in PELs and 62% of the variation in TLVs. For the ACGIH, WOE plays a much smaller role than potency. TLVs set by the ACGIH since 1989 appear to be stricter than earlier TLVs. We suggest that this change represents evidence that the ACGIH had responded to criticisms leveled at it in the late 1980s for failing to adopt sufficiently protective standards. The models developed here identify 2-nitropropane, ethylene dibromide, and chromium as having OSHA PELs significantly higher than predicted on the basis of potency and WOE.

Notes: Much has been written about the development and application of quantitative methods for estimating under uncertainty the long-term radiological performance of underground disposal of radioactive wastes. Until recently, interest has been focused almost entirely on the technical challenges regardless of the role of the organization responsible for these analyses. Now the dialogue between regulators, the repository developer or operator, and other interested parties in the decision-making process receives increasing attention, especially in view of some current difficulties in obtaining approvals to construct or operate deep facilities for intermediate or high-level wastes. Consequently, it is timely to consider the options for regulators’review and evaluation of safety submissions, at the various stages in the site selection to repository closure process, and to consider, especially, the role for performance assessment (PA) within the programs of a regulator both before and after delivery of such a submission. The origins and broad character of present regulations in the European Union (EU) and in the OECD countries are outlined and some regulatory PA reviewed. The issues raised are discussed, especially in regard to the interpretation of regulations, the dangers from the desire for simplicity in argument, the use of regulatory PA to review and challenge the PA in the safety case, and the effects of the relationship between proponent and regulator. Finally, a very limited analysis of the role of PA in public hearings is outlined and recommendations are made, together with proposals for improving the mechanisms for international collaboration on technical issues of regulatory concern.

Notes: In this paper the problem of high-level nuclear waste disposal is viewed as a five-stage, cascaded decision problem. The first four of these decisions having essentially been made, the work of recent years has been focused on the fifth stage, which concerns specifics of the repository design. The probabilistic performance assessment (PPA) work is viewed as the outcome prediction for this stage, and the site characterization work as the information gathering option. This brief examination of the proposed Yucca Mountain repository through a decision analysis framework resulted in three conclusions: (1) A decision theory approach to the process of selecting and characterizing Yucca Mountain would enhance public understanding of the issues and solutions to high-level waste management; (2) engineered systems are an attractive alternative to offset uncertainties in the containment capability of the natural setting and should receive greater emphasis in the design of the repository; and (3) a strategy of “waste management” should be adopted, as opposed to “waste disposal,” as it allows for incremental confirmation and confidence building of a permanent solution to the high-level waste problem.

Notes: Physiologically-based toxicokinetic (PBTK) models are widely used to quantify whole-body kinetics of various substances. However, since they attempt to reproduce anatomical structures and physiological events, they have ahigh number of parameters. Their identification from kinetic data alone is often impossible, and other information about the parameters is needed to render the model identifiable. The most commonly used approach consists of independently measuring, or taking fom literature sources, some of the parameters, fixing them in the kinetic model, and then performing model identification on a reduced number of less certain parameters. This results in a substantial reduction of the degrees of freedom of the model. In this study, we show that this method results in final estimates of the free parameters whose precision is overestimated. We then compared this approach with an empirical Bayes approach, which takes into account not only the mean value, but also the error associated with the independently determined parameters. Blood and breath 2H8- toluene washout curves, obtained in17 subjects, were analyzed with a previously presented PBTK model suitable for person-specific dosimetry. Model parameters with the greatest effect onpredicted levels were alveolar ventilation rate QPC, fat tissue fraction VFC, blood air partition coefficient Kb, fraction of cardiac output to fat Qa/co and rate of extrahepatic metabolismVmax.p. Differences in the measured and Bayesian-fitted values of QPC, VFc and Kb were significant (p 〈 0.05), andthe precision of the fitted values Vmax.p and Qa/co went from 11 ± 5% to 75 ± 170% (NS) and from 8 ± 2% to 9 ± 2% (p 〈 0.05) respectively. The empirical Bayes approach did not result in less reliable parameter estimates: rather, it pointed out that the precision of parameter estimates can be overly optimistic when other parameters in the model, eitherdirectly measured or taken from literature sources, are treated as known without error. In conclusion, an empirical Bayes approach to parameter estimation resulted in a better model fit, different final parameter estimates, and more realistic parameter precisions.

Notes: The US Department of Transportation was interested in the risks associated with transporting Hydrazine in tanks with and without relief devices. Hydrazine is both highly toxic and flammable, as well as corrosive. Consequently, there was a conflict as to whether a relief device should be used or not. Data were not available on the impact of relief devices on release probabilities or the impact of Hydrazine on the likelihood of fires and explosions. In this paper, a Monte Carlo sensitivity analysis of the unknown parameters was used to assess the risks associated with highway transport of Hydrazine. To help determine whether or not relief devices should be used, fault trees and event trees were used to model the sequences of events that could lead to adverse consequences during transport of Hydrazine. The event probabilities in the event trees were derived as functions of the parameters whose effects were not known. The impacts of these parameters on the riskof toxic exposures, fires, and explosions were analyzed through a Monte Carlo sensitivity analysis and analyzed statistically through an analysis of variance. The analysis allowed the determination of which of the unknown parameters had a significant impact on the risks. It also provided the necessary support to a critical transportation decision even though the values of several key parameters were not known.

Notes: During the modernization of the municipal waste incinerator (MWI, maximum capacity of 180,000 tons per year) of Metropolitan Grenoble (405,000 inhabitants), in France, a risk assessment was conducted, based on four tracerpollutants: two volatile organic compounds (benzene and 1,1,1 trichloroethane) and two heavy metals (nickel and cadmium, measured in particles). A Gaussian plume dispersion model, applied to maximum emissions measured at the MWI stacks, was used to estimate the distribution of these pollutants in the atmosphere throughout the metropolitan area. A random sample telephone survey (570 subjects) gathered data on time-activity patterns, according to demographic characteristics of the population. Life-long exposure was assessed as a time-weighted average of ambient air concentrations. Inhalation alone was considered because, in the Grenoble urban setting, other routes of exposure are not likely. A Monte Carlo simulation was used to describe probability distributions of exposures and risks. The median of the life-long personal exposures distribution to MWI benzene was 3.2 · 10−5μg/m3 (20th and 80th percentiles = 1.5 · 10−5 and 6.5 · 10−5μg/m3), yielding a 2.6 · 10−10 carcinogenic risk (1.2 · 10−10 - 5.4 · 10−10). For nickel, the corresponding life-time exposure and cancer risk were 1.8 ·10−4μg/m3 (0.9 ·10−4 - 3.6 ·10−4μg/m3) and 8.6 · 10−8 (4.3 · 10−8 - 17.3 ·10−8); for cadmium they were respectively 8.3 ·10−6μg/m3 (4.0 ·10−6 - 17.6 ·10−6) and 1.5 · (7.2 · 10−9 - 3.1. · 10−8). Inhalation exposure to cadmium emitted by the MWI represented less than 1% of the WHO Air Quality Guideline (5 ng/m3), while there was a margin of exposure of more than 109 between the NOAEL (150 ppm) and exposure estimates to trichloroethane. Neither dioxins nor mercury, a volatile metal, were measured. This could lessen the attributable life-long risks estimated. The minute (VOCs and cadmium) to moderate (nickel) exposure and risk estimates are in accord with other studies on modern MWIs meeting recent emission regulations, however.

Notes: Methods of quantitative risk assessment for toxic responses that are measured on a continuous scale are not well established. Although risk-assessment procedures that attempt to utilize the quantitative information in such data have been proposed, there is no general agreement that these procedures are appreciably more efficient than common quantal dose-response procedures that operate on dichotomized continuous data. This paper points out an equivalence between the dose-response models of the nonquantal approach of Kodell and West(1)) and a quantal probit procedure, and provides results from a Monte Carlo simulation study to compare coverage probabilities of statistical lower confidence limits on dose corresponding to specified additional risk based on applying the two procedures to continuous data from a dose-response experiment. The nonquantal approach is shown to be superior, in terms of both statistical validity and statistical efficiency.

Notes: This paper discusses a successful public involvement effort that addressed and resolved several highly controversial water management issues involving environmental and flood risks associated with an electrical generation facility in British Columbia. It begins with a discussion of concepts for designing public involvement, summarizing research that indicates why individuals and groups may find it difficult to make complex choices. Reasons for public involvement, and the range of current practices are discussed. Next, four principles for designing group decision process are outlined, emphasizing decision-aiding concepts that include “value-focused thinking” and “adaptive management.” The next sections discuss the Alouette River Stakeholder Committee process in terms of objectives, participation, process, methods for structuring values and creating alternatives, information sources, and results. Discussion and conclusions complete the paper.

Notes: During the 1980s, seismic research suggested that Oregon and the City of Portland had a higher risk of a major earthquake than had previously been assumed. In 1993, the State of Oregon adopted a new version of the Oregon Structural Specialty Code, which changed the designation of western Oregon from seismic zone 2b to seismic zone 3. The City of Portland established a program and a Task Force on Seismic Strengthening of Buildings to recommend actions that would encourage upgrading of city buildings. A survey of adult city residents was conducted in April, 1996 to determine public attitudes and opinions about earthquake risks, management and mitigation of earthquake hazards, priorities for protection by strengthening buildings, evaluations of strategies for informing the public about earthquake risks, and support for specific options the city might take to protect citizens against earthquake events. Social and demographic information on individuals and households was also collected. Respondents provided ratings for a wide range of social and environmental risks, provided information on priorities for strengthening key buildings and infrastructure facilities, and answered hypothetical questions about voting for bond measures to pay for city earthquake mitigation programs. Respondents recognized significant risk from earthquakes and supported programs to protect people, especially vulnerable residents such as children and the sick. There was strong support for protecting emergency response capabilities. There was much less support for using public funds to reduce the risks associated with privately owned buildings. There were also some strong pockets of resistance to publicly funded mitigation programs in response to the hypothetical bond measures.

Notes: From a comprehensive search of the literature, the hormesis phenomenon was found to occur over a wide range of chemicals, taxonomic groups, and endpoints. By use of computer searches and extensive cross-referencing, nearly 3000 potentially relevant articles were identified. Evidence of chemical and radiation hormesis was judged to have occurred in approximately 10oO of these by use of a priori criteria. These criteria included study design features (e.g., number of doses, dose range), dose-response relationship, statistical analysis, and reproducibility of results. Numerous biological endpoints were assessed, with growth responses the most prevalent, followed by metabolic effects, reproductive responses, longevity, and cancer. Hormetic responses were generally observed to be of limited magnitude with an average maximum stimulation of 30 to 60 percent over that of the controls. This maximum usually occurred 4- to 5-fold below the NOAEL for a particular endpoint. The present analysis suggests that hormesis is a reproducible and generalizable biological phenomenon and is a fundamental component of many, if not most, dose-response relationships. The relatively infrequent observation of homesis in the literature is believed to be due primarily to experimental design considerations, especially with respect to the number and range of doses and endpoint selection. Because of regulatory considerations, most toxicologic studies have been carried out at high doses above the low-dose region where the hormesis phenomenon occurs.

Notes: As the use of digital computers for instrumentation and control of safety-critical systems has increased, there has been a growing debate over the issue of whether probabilistic risk assessment techniques can be applied to these systems. This debate has centered on the issue of whether software failures can be modeled probabilistically. This paper describes a “context-based” approach to software risk assessment that explicitly recognizes the fact that the behavior of software is not probabilistic. The source of the perceived uncertainty in its behavior results from both the input to the software as well as the application and environment in which the software is operating. Failures occur as the result of encountering some context for which the software was not properly designed, as opposed to the software simply failing “randomly.” The paper elaborates on the concept of “error-forcing context” as it applies to software. It also illustrates a methodology which utilizes event trees, fault trees, and the Dynamic Flowgraph Methodology (DFM) to identify “error-forcing contexts” for software in the form of fault tree prime implicants.

Notes: Australian state and federal agencies use a broad range of methods for setting conservation priorities for species at risk. Some of these are based on rule sets developed by the International Union for the Conservation ofNature, while others use point scoring protocols to assess threat. All of them ignore uncertainty in the data. In this study, we assessed the conservation status of 29 threatened vascular plants from Tasmania and New South Wales using a variety of methods including point scoring and rule-based approaches. In addition, several methods for dealing with uncertainty in the data were applied to each of the prioritysetting schemes. The results indicatethat the choice of a protocol for setting priorities and the choice of the way in which uncertainty is treated may make important differences to the resulting assessments of risk. The choice among methods needs to be rationalized within the management context in which it is to be applied. These methods are not a substitute for more formal risk assessment.

Notes: This paper describes a multi-stakeholder process designed to assess thepotential health risks associated with adverse air quality in an urban industrial neighborhood. The paper briefly describes the quantitative health risk assessment conducted by scientific experts, with input by a grassroots community group concerned about the impacts of adverse air quality on theirhealth and quality of life. In this case, rather than accept the views of the scientific experts, the community used their powers of perception toadvantage by successfully advocating for a professionally conducted community health survey. This survey was designed to document, systematically and rigorously, the health risk perceptions community members associated with exposure to adverse air quality in their neighborhood. This paper describes theinstitutional and community contexts within which the research is situated as well as the design, administration, analysis, and results of the community health survey administered to 402 households living in an urban industrial neighborhood in Hamilton, Ontario, Canada. These survey results served tolegitimate the community's concerns about air quality and tohelp broaden operational definitions of ‘health.’ In addition, the resultsof both healthrisk assessment exercises served to keep issues of air quality on the localpolitical agenda. Implications of these findings for our understanding of theenvironmental justice process as well as the ability of communitiesto influence environmental health policy are discussed.

Notes: Psychometric data on risk perceptions are often collected using the method developed by Slovic, Fischhoff, and Lichtenstein, where an array of risk issues are evaluated with respect to a number of risk characteristics, such as how dreadful, catastrophic or involuntary exposure to each risk is. The analysis of these data has often been carried out at an aggregate level, where mean scores for all respondents are compared between risk issues. However, this approach may conceal important variation between individuals, and individual analyses have also been performed for single risk issues. This paper presents a new methodological approach using a technique called multilevel modelling for analysing individual and aggregated responses simultaneously, to produce unconditional and unbiased results at both individual and aggregate levels of the data. Two examples are given using previously published data sets on risk perceptions collected by the authors, and results between the traditional and new approaches compared. The discussion focuses on the implications of and possibilities provided by the new methodology.

Notes: The use of uncertainty factors in the standard method for deriving acceptable intake or exposure limits for humans, such as the Reference Dose (RfD), may be viewed as a conservative method of taking various uncertainties into account. As an obvious alternative, the use of uncertainty distributions instead of uncertainty factors is gaining attention. This paper presents a comprehensive discussion of a general framework that quantifies both the uncertainties in the no-adverse-effect level in the animal (using a benchmark-like approach) and the uncertainties in the various extrapolation steps involved (using uncertainty distributions). This approach results in an uncertainty distribution for the no-adverse-effect level in the sensitive human subpopulation, reflecting the overall scientific uncertainty associated with that level. A lower percentile of this distribution may be regarded as an acceptable exposure limit (e.g., RfD) that takes account of the various uncertainties in a nonconservative fashion. The same methodology may also be used as a tool to derive a distribution for possible human health effects at a given exposure level. We argue that in a probabilistic approach the uncertainty in the estimated no-adverse-effect-level in the animal should be explicitly taken into account. Not only is this source of uncertainty too large to be ignored, it also has repercussions for the quantification of the other uncertainty distributions.

Notes: This research explores public judgments about the threat-reducing potential of experts, individual behavior, and government spending. The data are responses of a national sample of 1225 to mail surveys that include measures of several dimensions of public judgments about violent crime, automobile accidents, hazardous chemical waste, air pollution, water pollution, global warming, AIDS, heart disease, and cancer. Beliefs about who can best mitigate threats are specific to classes of threats. In general, there is little faith that experts can do much about violent crime and automobile accidents, moderate faith in their ability to address problems of global warming, and greater expectations for expert solutions to the remaining threats. People judge individual behavior as effective in reducing the threats of violent crime, AIDS, heart disease, and automobile accidents but less so for the remaining threats. Faith in more government spending is highest for AIDS and the other two health items, lowest for the trio of violent crime, automobile accidents, and global warming, and moderate for the remaining threats. For most threats, people are not distributed at the extremes in judging mitigators. Strong attitudinal and demographic cleavages are also lacking, although some interesting relationships occur. This relative lack of sharp cleavages and the generally moderate opinion indicate ample opportunity for public education and risk communication.

Notes: Recreational and subsistence hunters and anglers consume a wide range of species, including birds, mammals, fish and shellfish, some of which represent significant exposure pathways for environmental toxic agents. This study focuses on the Department of Energy's (DOE'S) Savannah River Site (SRS), a former nuclear weapons production facility in South Carolina. The potential risk of contaminant intake from consuming mourning doves (Zenaida macroura), the most popular United States game bird, was examined under various risk scenarios. For all of these scenarios we used the mean tissue concentration of six metals (lead, mercury, cadmium, selenium, chromium, manganese) and radiocesium, in doves collected on and near SRS. We also estimated risk to a child consuming doves that had the maximum contaminant level. We used the cancer slope factor for radiocesium, the Environmental Protection Agencies UptakeBiokinetic model for lead, and published reference doses for the other metals. As a result of our risk assessments we recommend management of water levels in contaminated reservoirs so that lake bed sediments are not exposed to use by gamebirds and other terrestrial wildlife. Particularly, measures should be taken to insure that the hunting public does not have access to such a site. Our data also indicate that doves on popular hunting areas are exposed to excess lead, suggesting that banning lead shot for doves, as has been done for waterfowl, is desirable.

Notes: Exposure duration is an important component in determining long-term dose rates associated with exposure to environmental contaminants. Surveys of exposed populations collect information on individuals' past behaviors, including the durations of a behavior up to the time of the survey. This paper presents an empirical approach for determining the distribution of total durations that is consistent with the distribution past durations obtained from surveys. This approach is appropriate where the rates of beginning and ending a behavior are relatively constant over time. The approach allows the incorporation of information on the distribution of age in a population into the determination of the distribution of durations. The paper also explores the impact of “longevity” bias on survey data. A case study of the application of this approach to two angler populations is also provided. The results of the case study have characteristics similar to the results reported by Israeli and Nelson (Risk Anal. 12, 65-72 (1992)) from their analytical model of residential duration. Specifically, the average period of time for the total duration in the entire population is shorter than the average period of time reported for historical duration in the surveyed individuals.

Notes: Information format can influence the extent to which target audiences understand and respond to risk-related information. This study examined four elements of risk information presentation format. Using printed materials, we examined target audience perceptions about: (a) reading level; (b) use of diagrams vs. text; (c) commanding versus cajoling tone; and (d) use of qualitative vs. quantitative information presented in a risk ladder. We used the risk communication topic of human health concerns related to eating noncommercial Great Lakes fish affected by chemical contaminants. Results from the comparisons of specific communication formats indicated that multiple formats are required to meet the needs of a significant percent of anglers for three of the four format types examined. Advisory text should be reviewed to ensure the reading level is geared to abilities of the target audience. For many audiences, a combination of qualitative and quantitative information, and a combination of diagrams and text may be most effective. For most audiences, a cajoling rather than commanding tone better provides them with the information they need to make a decision about fish consumption. Segmenting audiences regarding information needs and communication formats may help clarify which approaches to take with each audience.

Notes: Using exploratory data analysis, probability plots, scatterplots, and computer animations to rotate and visualize the data, we fit a trivariate Normal distribution to data for the height, the natural logarithm of body weight, and the body fat for 646 men between the ages of 50 and 80 years as reported by the medical staff of the U.S. Veterans Administration's “Normative Aging Study” in Boston, MA. Although these data do not include any children, women, or young men, the measurements represent the best data that we could find through a 4-year search. We believe that these data are well measured and reliable for men in the specified age range and that these data reveal an interesting statistical pattern for use in probabilistic PBPK models.

Notes: Significant research work has been completed in the development of risk-based inservice inspection (ISI) and testing (IST) technology for nuclear power plant applications through the ASME Center For Research and Technology Development. This paper provides technology that has been developed for these engineering applications. The technology includes risk-based ranking methods, beginning with the use of plant probabilistic risk assessment (PRA), for the determination of risk-significant and less risk-significant components for inspection and the determination of similar populations for pumps and valves for inservice testing. Decision analysis methods are outlined for developing ISI and IST programs. This methodology integrates nondestructive examination data, structural reliability/risk assessment results, PRA results, failure data, and expert opinion to evaluate the effectiveness of ISI programs. Similarly, decision analysis uses the output of failure mode and causes analysis in combination with data, expert opinion, and PRA results to evaluate the effectiveness of IST programs. Results of pilot applications of these ASME methods to actual nuclear plant systems and components are summarized. The results of this work are already being used to develop recommended changes in ISI and IST requirements by the ASME Section XI and the ASME Operation and Maintenance Code organizations. A perspective on Code and regulatory adoption is also outlined. Finally, the potential benefits to the nuclear industry in terms of safety, person-rem exposure, and costs are summarized.

Notes: Probabilistic Seismic Hazard Analysis (PSHA) is a methodology that estimates the likelihood that various levels of earthquake-caused ground motions will be exceeded at a given location in a given future time period. Due to large uncertainties in all of the geosciences data and in their modeling, multiple model interpretations are often possible. This leads to disagreements among the experts, which in the past has led to disagreement on the selection of a ground motion for design at a given site. This paper reports on a project, co-sponsored by the U.S. Nuclear Regulatory Commission, the U.S. Department of Energy, and the Electric Power Research Institute, that was undertaken to review the state-of-the-art and improve on the overall stability of the PSHA process, by providing methodological guidance on how to perform a PSHA. The project reviewed past studies and examined ways to improve on the present state-of-the-art. In analyzing past PSHA studies, the most important conclusion is that differences in PSHA results are commonly due to process rather than technical differences. Thus, the project concentrated heavily on developing process recommendations, especially on the use of multiple experts, and this paper reports on those process recommendations. The problem of facilitating and integrating the judgments of a diverse group of experts is analyzed in detail. The authors believe that the concepts and process principles apply just as well to non-earthquake fields such as volcanic hazard, flood risk, nuclear-plant safety, and climate change.

Notes: Trichloroacetic acid (TCA) is major metabolite of trichloroethylene (TRI) thought to contribute to its hepatocarcinogenic effects in mice. Recent studies have shown that peak blood concentrations of TCA in rats do not occur until approximately 12 hours following an oral dose of TRI. However, blood concentrations of TRI reach maximum within an hour and are nondetectable after 2 hours.(1) The results of study which examined the enterohepatic recirculation (EHC) of the principle TRI metabolited(2) was used to develop physiologically-based pharmacokinetic model for TRI, which includes enterohepatic recirculation of its metabolites. The model quantitatively predicts the uptake, distribution and elimination of TRI, trichloroethanol, trichloroethanol-glucuronide, and TCA and includes production of metabolites through the enterohepatic recirculation pathway. Physiologic parameters used in the model were obtained from the literature.(3.4) Parameters for TRI metabolism were taken from Fisher et al.(5) Other kinetic parameters were found in the literature or estimated from experimental data.(2) The model was calibrated to data from experiments of an earlier study where TRI was orally administered(2) Verification of the model was conducted using data on the enterohepatic recirculation of TCEOH and TCA(2) chloral hydrate data (infusion doses) from Merdink,(1) and TRI data from Templin(l) and Larson and Bull.(1)

Notes: Estimates were made of the numbers of liver carcinogens in 390 long-term bioassays conducted by the National Toxicology Program (NTP). These estimates were obtained from examination of the global pattern of p-values obtained from statistical tests applied to individual bioassays. Representative estimates of the number of liver carcinogens (90% confidence interval in parentheses) obtained in our analysis compared to NTP's determination are as follows: female rats—49 (23, 76), NTP = 30; male rats—88 (59, 116), NTP = 35; female mice—131 (105, 157), NTP = 81; male mice—100 (73, 126), NTP = 61; overall—166 (135, 197), NTP = 108. The estimator from which these estimates were obtained is biased low by an unknown amount. Consequently, this study provides persuasive evidence of the existence of more rodent liver carcinogens than were identified by the NTP.

Notes: We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.

Notes: This report describes the use of Bayesian networks (BNs) to model statistical loss distributions in financial operational risk scenarios. Its focus is on modeling “long” tail, or unexpected, loss events using mixtures of appropriate loss frequency and severity distributions where these mixtures are conditioned on causal variables that model the capability or effectiveness of the underlying controls process. The use of causal modeling is discussed from the perspective of exploiting local expertise about process reliability and formally connecting this knowledge to actual or hypothetical statistical phenomena resulting from the process. This brings the benefit of supplementing sparse data with expert judgment and transforming qualitative knowledge about the process into quantitative predictions. We conclude that BNs can help combine qualitative data from experts and quantitative data from historical loss databases in a principled way and as such they go some way in meeting the requirements of the draft Basel II Accord (Basel, 2004) for an advanced measurement approach (AMA).

Notes: The number of collisions and fatalities at rail-highway intersections in the United States has declined significantly over the past 30 years, despite considerable increases in the volume of rail and highway traffic. This article disaggregates the improvement into its constituent causes. Negative binomial regressions are conducted on a pooled data set for 49 states from 1975 to 2001. The analysis concludes that about two-fifths of the decrease is due to factors such as reduced drunk driving and improved emergency medical response that have improved safety on all parts of the highway network. The installation of gates and/or flashing lights accounts for about a fifth of the reduction. The development in the 1970s and early 1980s of the Operation Lifesaver public education campaign, and the installation of additional lights on locomotives in the mid 1990s, each led to about a seventh of the reduction. Finally, about a tenth is due to closure of crossings resulting from line abandonments or consolidation of little-used crossings.

Notes: The value of a statistical life (VSL) is a key input for estimating the benefits of policies that save lives. Several recent studies have obtained estimates of the VSL from contingent valuation surveys, i.e., by asking people to say how much they would pay to reduce their risk of dying. This article examines statistical factors that may influence the estimates of the VSL obtained from such surveys. We examine the importance of distributional assumptions, the choice of the welfare statistics of interest, the procedure for computing them, outliers, undesirable response effects, and internal validity of the willingness-to-pay (WTP) responses. We illustrate the importance of these factors using dichotomous-choice and open-ended WTP data from four recent contingent valuation surveys.

Notes: Safety systems are important components of high-consequence systems that are intended to prevent the unintended operation of the system and thus the potentially significant negative consequences that could result from such an operation. This presentation investigates and illustrates formal procedures for assessing the uncertainty in the probability that a safety system will fail to operate as intended in an accident environment. Probability theory and evidence theory are introduced as possible mathematical structures for the representation of the epistemic uncertainty associated with the performance of safety systems, and a representation of this type is illustrated with a hypothetical safety system involving one weak link and one strong link that is exposed to a high temperature fire environment. Topics considered include (1) the nature of diffuse uncertainty information involving a system and its environment, (2) the conversion of diffuse uncertainty information into the mathematical structures associated with probability theory and evidence theory, and (3) the propagation of these uncertainty structures through a model for a safety system to obtain representations in the context of probability theory and evidence theory of the uncertainty in the probability that the safety system will fail to operate as intended. The results suggest that evidence theory provides a potentially valuable representational tool for the display of the implications of significant epistemic uncertainty in inputs to complex analyses.

Notes: Recent studies demonstrating a concentration dependence of elimination of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) suggest that previous estimates of exposure for occupationally exposed cohorts may have underestimated actual exposure, resulting in a potential overestimate of the carcinogenic potency of TCDD in humans based on the mortality data for these cohorts. Using a database on U.S. chemical manufacturing workers potentially exposed to TCDD compiled by the National Institute for Occupational Safety and Health (NIOSH), we evaluated the impact of using a concentration- and age-dependent elimination model (CADM) (Aylward et al., 2005) on estimates of serum lipid area under the curve (AUC) for the NIOSH cohort. These data were used previously by Steenland et al. (2001) in combination with a first-order elimination model with an 8.7-year half-life to estimate cumulative serum lipid concentration (equivalent to AUC) for these workers for use in cancer dose-response assessment. Serum lipid TCDD measurements taken in 1988 for a subset of the cohort were combined with the NIOSH job exposure matrix and work histories to estimate dose rates per unit of exposure score. We evaluated the effect of choices in regression model (regression on untransformed vs. ln-transformed data and inclusion of a nonzero regression intercept) as well as the impact of choices of elimination models and parameters on estimated AUCs for the cohort. Central estimates for dose rate parameters derived from the serum-sampled subcohort were applied with the elimination models to time-specific exposure scores for the entire cohort to generate AUC estimates for all cohort members. Use of the CADM resulted in improved model fits to the serum sampling data compared to the first-order models. Dose rates varied by a factor of 50 among different combinations of elimination model, parameter sets, and regression models. Use of a CADM results in increases of up to five-fold in AUC estimates for the more highly exposed members of the cohort compared to estimates obtained using the first-order model with 8.7-year half-life. This degree of variation in the AUC estimates for this cohort would affect substantially the cancer potency estimates derived from the mortality data from this cohort. Such variability and uncertainty in the reconstructed serum lipid AUC estimates for this cohort, depending on elimination model, parameter set, and regression model, have not been described previously and are critical components in evaluating the dose-response data from the occupationally exposed populations.

Notes: Approaches to risk assessment have been shown to vary among regulatory agencies and across jurisdictional boundaries according to the different assumptions and justifications used. Approaches to screening-level risk assessment from six international agencies were applied to an urban case study focusing on benzo[a]pyrene (B[a]P) exposure and compared in order to provide insight into the differences between agency methods, assumptions, and justifications. Exposure estimates ranged four-fold, with most of the dose stemming from exposure to animal products (8–73%) and plant products (24–88%). Total cancer risk across agencies varied by two orders of magnitude, with exposure to air and plant and animal products contributing most to total cancer risk, while the air contribution showed the greatest variability (1–99%). Variability in cancer risk of 100-fold was attributed to choices of toxicological reference values (TRVs), either based on a combination of epidemiological and animal data, or on animal data. The contribution and importance of the urban exposure pathway for cancer risk varied according to the TRV and, ultimately, according to differences in risk assessment assumptions and guidance. While all agency risk assessment methods are predicated on science, the study results suggest that the largest impact on the differential assessment of risk by international agencies comes from policy and judgment, rather than science.

Notes: In this article, we describe a straightforward method for solving the probability of at least one malignant cell by time t, and the associated hazard function, in the general (i.e., nonhomogeneous) two-stage Moolgavkar-Venzon-Knudson (MVK) model of cancer. The method consists of solving four coupled ordinary differential equations derived from the Kolmogorov backward equations for this process. The relationship of this method to previously proposed solutions is discussed.

Notes: To estimate the critical dose of lead inducing anemia in humans, the effects of lead on hemoglobin (Hb) and hematocrit (Hct) levels and red blood cell (RBC) count were examined in 388 male lead-exposed workers with blood lead (BPb) levels of 0.05–5.5 (mean 1.3) μmol/L by using the benchmark dose (BMD) approach. The BPb level was significantly related to Hb (regression coefficient β=–0.276), RBC (β=–11.35), and Hct (β=–0.563) among the workers (p 〈 0.001) when controlling for age and working status. The average BPb levels were significantly higher in the workers with anemia (1.85 μmol/L), based on the WHO criteria, than in those without anemia (1.26 μmol/L). The benchmark dose levels of BPb (i.e., lower 95% confidence limits of BMD), calculated from the K-power model set at an abnormal probability of 5% in unexposed workers and an excess risk of 5% in exposed workers were estimated to be 0.94 μmol/L (19.5 μg/dl) for Hb, 0.94 μmol/L (19.4 μg/dl) for RBC, and 1.43 μmol/L (29.6 μg/dl) for Hct. These findings suggest that reduction in hematopoietic indicators may be initiated at BPbs below the level currently considered without effect.

Notes: The U.S. Department of Agriculture (USDA) tests a subset of cattle slaughtered in the United States for bovine spongiform encephalitis (BSE). Knowing the origin of cattle (U.S. vs. Canadian) at testing could enable new testing or surveillance policies based on the origin of cattle testing positive. For example, if a Canadian cow tests positive for BSE, while no U.S. origin cattle do, the United States could subject Canadian cattle to more stringent testing. This article illustrates the application of a value-of-information (VOI) framework to quantify and compare potential economic costs to the United States of implementing tracking cattle origins to the costs of not doing so. The potential economic value of information from a tracking program is estimated to exceed its costs by more than five-fold if such information can reduce future losses in export and domestic markets and reduce future testing costs required to reassure or win back customers. Sensitivity analyses indicate that this conclusion is somewhat robust to many technical, scientific, and market uncertainties, including the current prevalence of BSE in the United States and/or Canada and the likely reactions of consumers to possible future discoveries of BSE in the United States and/or Canada. Indeed, the potential value of tracking information is great enough to justify locating and tracking Canadian cattle already in the United States when this can be done for a reasonable cost. If aggressive tracking and testing can win back lost exports, then the VOI of a tracking program may increase to over half a billion dollars per year.

Notes: In the Mexico City metropolitan area, poor air quality is a public health concern. Diesel vehicles contribute significantly to the emissions that are most harmful to health. Harmful diesel emissions can be reduced by retrofitting vehicles with one of several technologies, including diesel particulate filters. We quantified the social costs and benefits, including health benefits, of retrofitting diesel vehicles in Mexico City with catalyzed diesel particulate filters, actively regenerating diesel particulate filters, or diesel oxidation catalysts, either immediately or in 2010, when capital costs are expected to be lower. Retrofit with either type of diesel particulate filter or an oxidation catalyst is expected to provide net benefits to society beginning immediately and in 2010. At current prices, retrofit with an oxidation catalyst provides greatest net benefits. However, as capital costs decrease, retrofit with diesel particulate filters is expected to provide greater net benefits. In both scenarios, retrofit of older, dirtier vehicles that circulate only within the city provides greatest benefits, and retrofit with oxidation catalysts provides greater health benefits per dollar spent than retrofit with particulate filters. Uncertainty about the magnitude of net benefits of a retrofit program is significant. Results are most sensitive to values used to calculate benefits, such as the concentration-response coefficient, intake fraction (a measure of exposure), and the monetary value of health benefits.

Notes: In their regulations, the U.S. Environmental Protection Agency and the U.S. Nuclear Regulatory Commission permit the omission of features, events, or processes with probabilities of 〈10−4 in 104 yr (e.g., a constant frequency of 〈10−8 per yr) in assessments of the performance of radioactive waste disposal systems. Igneous intrusion (or “volcanism”) of a geologic repository at Yucca Mountain for radioactive waste is one disruptive event that has a probability with a range of uncertainty that straddles this regulatory criterion and is considered directly in performance assessment calculations. A self-sustained nuclear chain reaction (or “criticality”) is another potentially disruptive event to consider, although it was never found to be important when evaluating the efficacy of radioactive waste disposal since the early 1970s. The thesis of this article is that the consideration of the joint event—volcanism and criticality—occurring in any 10,000-year period following closure can be eliminated from performance calculations at Yucca Mountain. The probability of the joint event must be less than the fairly well-accepted but low probability of volcanism. Furthermore, volcanism does not “remove” or “fail” existing hydrologic or geochemical constraints at Yucca Mountain that tend to prevent concentration of fissile material. Prior to general corrosion failure of waste packages, the mean release of fissile mass caused by a low-probability, igneous intrusive event is so small that the probability of a critical event is remote, even for highly enriched spent nuclear fuel owned by the U.S. Department of Energy. After widespread failure of packages occurs, the probability of the joint event is less than the probability of criticality because of the very small influence of volcanism on the mean fissile mass release. Hence, volcanism plays an insignificant role in inducing criticality over any 104-yr period. We also argue that the Oklo reactors serve as a natural analogue and provide a rough bound on probability of criticality given favorable hydrologic or geochemical conditions on the scale of the repository that is less than 0.10. Because the product of this bound with the probability of volcanism represents the probability of the joint event and the product is less than 10−4 in 104 yr, consideration of the joint event can be eliminated from performance calculations.

Notes: Decision analysis is recognized as the right way to make risk management decisions, using probabilistic techniques to assess the accident risk. It is also accepted that the decisions that individuals in the organization make affect the likelihood of an accident and thus managerial and organizational factors should be included in the risk modeling process. However, decision analytic techniques have not been used to understand the decisions that are made by these individuals. The initial domain for this research is marine transportation. We use the framework of value-focused thinking in order to understand safety decisions made within our research partner organization, a major domestic oil tanker operator. We describe the results of interviews held with managers and employees from this organization. Through these interviews, we sought to understand the values these experts apply in their roles within the organization and the objectives they seek to achieve to contribute to its overall safety performance. The end result is a framework that not only portrays the fundamental objectives of safe operations for various roles in the organization, but also interconnects these different decision contexts. We believe that this approach is fundamentally different from those used in previous work and that this is an interesting application of value-focused thinking.

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 Retraction. In the framework of the APHEIS program (Air Pollution and Health: A European Information System), a health impact assessment of air pollution in 26 European cities was performed for particles of an aerodynamic diameter less than or equal to 10 μm (PM10). For short-term effects, it was based on overall estimates from the APHEA-2 project (Air Pollution and Health: A European Approach). These city-specific risk assessments require city-specific concentration-response functions, raising the question of which concentration-response is most appropriate. Estimates from city-specific models are more specific, but have greater uncertainty than those provided from multicity analyses. We compared several estimates derived from the city-specific analyses in cities that were part of the APHEA-2 project, as well as in a city that was not included in APHEA-2 but was part of the APHEIS project. These estimates were: the estimates from a local regression model, the adjusted estimates based on two significant effect modifiers identified through meta-regression models, and the city-specific empirical Bayes (shrunken) estimates and their underlying distribution. The shrunken and adjusted estimates were used to improve the estimation of city-specific concentration-response function. From these different estimates, attributable numbers of deaths per year were calculated. The advantages and limits of the different approaches are discussed through real data and in a simulation study.

Notes: The weather forecast says that there is a “30% chance of rain,” and we think we understand what it means. This quantitative statement is assumed to be unambiguous and to convey more information than does a qualitative statement like “It might rain tomorrow.” Because the forecast is expressed as a single-event probability, however, it does not specify the class of events it refers to. Therefore, even numerical probabilities can be interpreted by members of the public in multiple, mutually contradictory ways. To find out whether the same statement about rain probability evokes various interpretations, we randomly surveyed pedestrians in five metropolises located in countries that have had different degrees of exposure to probabilistic forecasts––Amsterdam, Athens, Berlin, Milan, and New York. They were asked what a “30% chance of rain tomorrow” means both in a multiple-choice and a free-response format. Only in New York did a majority of them supply the standard meteorological interpretation, namely, that when the weather conditions are like today, in 3 out of 10 cases there will be (at least a trace of) rain the next day. In each of the European cities, this alternative was judged as the least appropriate. The preferred interpretation in Europe was that it will rain tomorrow “30% of the time,” followed by “in 30% of the area.” To improve risk communication with the public, experts need to specify the reference class, that is, the class of events to which a single-event probability refers.

Notes: A method for estimating long-term exposures from short-term measurements is validated using data from a recent EPA study of exposure to fine particles. The method was developed a decade ago but long-term exposure data to validate it did not exist until recently. In this article, exposure data from repeated visits to 37 persons over 1 year (up to 28 measurements per person) are used to test the model. Both fine particle mass and elemental concentrations measured indoors, outdoors, and on the person are examined. To provide the most stringent test of the method, only two single-day distributions are randomly selected for each element to predict the long-term distributions. The precision of the method in estimating the long-term geometric mean and geometric standard deviation appears to be of the order of 10%, with no apparent bias. The precision in estimating the 99th percentile ranges from 19% to 48%, again without obvious bias. The precision can be improved by selecting a number of pairs of single-day distributions instead of just one pair. Occasionally, the method fails to provide an estimate for the long-term distribution. In that case, a repeat of the random selection procedure can provide an estimate. Although the method assumes a log-normal distribution, most of the distributions tested failed the chi-square test for log-normality. Therefore, the method appears suitable for application to distributions that depart from log-normality.

Notes: Combining DNA variation data and risk assessment procedures offers important diagnostic and monitoring tools for evaluating the relative success of exotic species invasions. Risk assessment may allow us to understand how the numbers of founding individuals, genetic variants, population sources, and introduction events affect successful establishment and spread. This is particularly important in habitats that are “hotbeds” for invasive species—such as the North American Great Lakes. This study compares genetic variability and its application to risk assessment within and among three Eurasian groups and five species that successfully invaded the Great Lakes during the mid 1980s through early 1990s; including zebra and quagga mussels, round and tubenose gobies, and the ruffe. DNA sequences are compared from exotic and native populations in order to evaluate the role of genetic diversity in invasions. Close relatives are also examined, since they often invade in concert and several are saline tolerant and are likely to spread to North American estuaries. Results show that very high genetic diversity characterizes the invasions of all five species, indicating that they were founded by very large numbers of propagules and underwent no founder effects. Genetic evidence points to multiple invasion sources for both dreissenid and goby species, which appears related to especially rapid spread and widespread colonization success in a variety of habitats. In contrast, results show that the ruffe population in the Great Lakes originated from a single founding population source from the Elbe River drainage. Both the Great Lakes and the Elbe River populations of ruffe have similar genetic diversity levels—showing no founder effect, as in the other invasive species. In conclusion, high genetic variability, large numbers of founders, and multiple founding sources likely significantly contribute to the risk of an exotic species introduction's success and persistence.