ALBERT

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: Food-related illness in the United States is estimated to affect over six million people per year and cost the economy several billion dollars. These illnesses and costs could be reduced if minimum infectious doses were established and used as the basis of regulations and monitoring. However, standard methodologies for dose-response assessment are not yet formulated for microbial risk assessment. The objective of this study was to compare dose response models for food-borne pathogens and determine which models were most appropriate for a range of pathogens. The statistical models proposed in the literature and chosen for comparison purposes were log-normal,(19) log-logistic,(17) exponential,(7,9,17)ß-Poisson(7,9,18) and Welbull-Gamma.(3) These were fit to four data sets also taken from published literature, Shigella fiexneri,(9,12,13)Shigella dysenteriae,(9,11)Campylobacter jejuni,(15,16) and Salmonella typhosa,(7,14) usingthe method of maximum likelihood. The Weibull-gamma, the only model with three parameters, was also the only model capable of fitting all the data sets examined using the maximum likelihood estimation for comparisons. Infectious doses were also calculated using each model. Within any given data set, the infectious dose estimated to affect one percent of the population ranged from one order of magnitude to as much as nine orders of magnitude, illustrating the differences in extrapolation of the dose response models. More data are needed to compare models and examine extrapolation from high to low doses for food-borne pathogens.

Notes: Environmental managers are increasingly charged with involving the public in the development and modification of policies regarding risks to huma health and the environment. Involving the public in environmental decision making first requires a broad understanding of how and why the public perceives various risks. The Savannah River Stakeholder Study was conducted withthe purpose of investigating individual, economic, and social characteristics of risk perceptions among those living near the Savannah River Nuclear Weapons Site. A number of factors were found to impact risk perceptions among those living near the site. One's estimated proximity to the site and relative river location surfaced as strong determinants of risk perceptions among SRS residents. Additionally, living in a quality neighborhood and demonstrating a willingness to accept health risks for economic gain strongly abated heightened risk perceptions.

Notes: Five atmospheric transport models were evaluated for use in Phase I1 ofthe Historical Public Exposures Studies at the Rocky Flats Plant. Models included a simple straight-line Gaussian plume model (ISCST2), several integrated puff models (RATCHET, TRIAD, and INPUFF2), and a complex terrain mode (TRAC). Evaluations were based on how well model predictions compared with sulfur hexafluoride tracer measurements taken in the vicinity of Rocky Flats in February 1991. Twelve separate tracer experiments were conducted, eac lasting 9 hr and measured at 140 samplers in arcs 8 and 16 km from the release point at Rocky Flats. Four modeling objectives were defined based on the endpoints of the overall study: (1) the unpaired maximum hourly average concentration, (2) paired time-averaged concentration, (3) unpaired time-averaged concentration, and (4) arc-integrated concentration. Performance measures were used to evaluate models and focused on the geometric mean and standard deviation of the predicted-to-observed ratio and the correlation coefficient between predicted and observed concentrations. No one model consistently outperformed the others in all modeling objectives and performance measures. About 75% of the maximum hourly concentration predictions were within a factor of 5 of the observations. About 64% of the paired and 80% of the unpaired time-averaged model predictions were within a factor of 5 of theobservations. The overall performance of the RATCHET model was somewhat better than the other models. All models appeared to experience difficulty defining plume trajectories, which was attributed to the influence of multilayered flow initiated by terrain complexities and the diurnal flow patterns characteristic of the Colorado Front Range.

Notes: Calculation of accident dose-risk estimates with the RADTRAN code requires input data describing the population likely to be affected by the plumeof radioactive material (RAM) released in a hypothetical transportation accident. In the existing model, population densities within 1/2 mile (0.8 km)of the route centerline are tabulated in three ranges (Rural, Suburban, andUrban). These population densities may be of questionable validity since the plume in the RADTRAN analysis is assumed to extend out to 120 km from thehypothetical accident site. We present a GIs-based population model which accounts for the actual distribution of population under a potential plume, and compare accident-risk estimates based on the resulting population densities with those based on the existing model. Results for individual points along a route differ greatly, but the cumulative accident risks for a sample route of a few hundred kilometers are found to be comparable, if not identical. We conclude, therefore, that for estimation of aggregate accident risks over typical routes of several hundred kilometers, the existing, simpler RADTRAN model is sufficiently detailed and accurate.

Notes: This paper discusses a number of the key challenges to the acceptance and aplication of probabilistic risk analysis (PRA). Those challenges include:(a) the extensive reliance on subjective judgment in PRA, requiring the development of guidance for the use of PRA in risk-informed regulation, and possibly the development of “robust” or “reference” prior distributions to minimize the reliance on judgment; and (b) the treatment of human perfor-mance in PRA, including not only human errorperse but also management and organizational factors more broadly. All of these areas are seen as presentinginteresting research challenges at the interface between engineering and other disciplines.

Notes: Rational decision making requires that the total uncertainty about a variate of interest (a predictand) be quantified in terms of a probability distribution, conditional on all available information and knowledge. Supposethe state-of-knowledge is embodied in a deterministic model, which is imperfect and outputs only an estimate of the predictand. Fundamentals are presented of two Bayesian methods for producing a probabilistic forecast via anydeterministic model. The Bayesian Processor of Forecast (BPF) quantifies the total uncertainty in terms of a posterior distribution, conditional on model output. The Bayesian Forecasting System (BFS) decomposes the total uncertainty into input uncertainty and model uncertainty, which are characterized independently and then integrated into a predictive distribution. The BFS is compared with Monte Carlo simulation and “ensemble forecasting” technique, none of which can alone produce a probabilistic forecast that quantifies the total uncertainty, but each can serve as a component of the BFS.

Notes: This article describes an application of a method for assessing risks associated with the introduction of an organism into a new environment. The test organism was a binucleate Rhizoctonia fungal isolate that has potential for commercial development as a biological control agent for damping-off diseases in bedding plants. A test sample of host plant species was selected using the centrifugal phylogenetic host range principles, but with an emphasis on economic species. The effect of the fungus on the plant was measured for each species and expressed on a logarithmic scale. The effects on weights of shoots and roots per container were not normally distributed, nor were the effects on the number of plants standing (those which survived). Statements about the effect on the number standing and the shoot weight per container involved using the observed (empirical) distribution. This is illustrated with an example. Problems were encountered in defining the population of species at risk, and in deciding how this population should be formally sampled. The limitations of the method are discussed.

Notes: The heuristic-systematic information processing model (HSM) holds that individuals will use one or both of these modes of information processing when attempting to evaluate information in order to arrive at a judgment. Systematic processing is defined by effortful scrutiny and comparison of information, whereas heuristic processing is defined by the use of cues to amve more easily at a judgment. Antecedents to the two processing modes include information sufficiency, motivation, and self-efficacy. Structural equation modeling is used to examine competing configuration of this model and to evaluate the model as appropriate for predicting risk judgment. The model also is evaluated across three groups that vary with respect to their level of concern. These analyses are executed within a case study involving an epidemiological investigation of a suspected cancer cluster. The analysis confirms the HSM's theoretically proposed structure and shows it to be a useful vehicle for evaluating risk judgment. In the overall analysis, antecedent variables generally function as specified by theory. Systematic processing is predicted by greater motivation. Heuristic processing is predicted by information sufficiency. Self-efficacy is a significant predictor of both processing modes. And heuristic processing is shown to be associated with judgment of less risk. However, when the analysis is contrasted across three groups (those concerned about cancer, not concerned and uncertain) it is shown that the model is significantly more robust for the uncertain group. This finding may have implications for the use of the HSM in risk research specifically, and in field research generally.

Notes: South Carolina has issued fish consumption advisories for the Savannah River based on mercury and radionuclide levels. We examine differences in fishing rates and fish consumption of 258 people interviewed while fishing along the Savannah River, as a function of age, education, ethnicity, employment history, and income, and test the assumption that the average consumption of fish is less than the recreational value of 19 kg/year assumed by risk assessors. Ethnicity and education contributed significantly to explaining variations in number of fish meals per month, serving size, and total quantity of fish consumed per year. Blacks fished more often, ate more fish meals of slightly larger serving sizes, and consumed more fish per year than did Whites. Although education and income were correlated, education contributed most significantly to behavior; people who did not graduate from high school ate fish more often, ate more fish per year, and ate more whole fish than people who graduated from high school. Computing consumption of fish for each person individually indicates that (1) people who eat fish more often also eat larger portions, (2) a substantial number of people consume more than the amount of fish used to compute risk to recreational fishermen, (3) some people consume more than the subsistence level default assumption (50 kglyear) and (4) Blacks consume more fish per year than Whites, putting them at greater risk from contaminants in fish. Overall, ethnicity, age, and education contributed to variations in fishing behavior and consumption.

Notes: The association between daily fluctuations in ambient particulate matter and daily variations in nonaccidental mortality have been extensively investigated. Although it is now widely recognized that such an association exists, the form of the concentration-response model is still in question. Linear, no threshold and linear threshold models have been most commonly examined. In this paper we considered methods to detect and estimate threshold concentrations using time series data of daily mortality rates and air pollution concentrations. Because exposure is measured with error, we also considered the influence of measurement error in distinguishing between these two completing model specifications. The methods were illustrated on a 15-year daily time series of nonaccidental mortality and particulate air pollution data in Toronto, Canada. Nonparametric smoothed representations of the association between mortality and air pollution were adequate to graphically distinguish between these two forms. Weighted nonlinear regression methods for relative risk models were adequate to give nearly unbiased estimates of threshold concentrations even under conditions of extreme exposure measurement error. The uncertainty in the threshold estimates increased with the degree of exposure error. Regression models incorporating threshold concentrations could be clearly distinguished from linear relative risk models in the presence of exposure measurement error. The assumption of a linear model given that a threshold model was the correct form usually resulted in overestimates in the number of averted premature deaths, except for low threshold concentrations and large measurement error.

Notes: Facility-specific information on pollution was obtained for 36 coke plants and 46 oil refineries in the United States and matched with information on populations surrounding these 82 facilities. These data were analyzed to determine whether environmental inequities were present, whether they were more economic or racial in nature, and whether the racial composition of nearby communities has changed significantly since plants began operations. The Census tracts near coke plants have a disproportionate share of poor and nonwhite residents. Multivariate analyses suggest that existing inequities are primarily economic in nature. The findings for oil refineries are not strongly supportive of the environmental inequity hypothesis. Rank ordering of facilities by race, poverty, and pollution produces limited (although not consistent) evidence that the more risky facilities tend to be operating in communities with above-median proportions of nonwhite residents (near coke plants) and Hispanic residents (near oil refineries). Over time, the racial makeup of many communities near facilities has changed significantly, particularly in the case of coke plants sited in the early 1900s. Further risk-oriented studies of multiple manufacturing facilities in various industrial sectors of the economy are recommended.

Notes: We investigated the way results of human health risk assessments are used, and the theory used to describe those methods, sometimes called the “NAS paradigm.” Contrary to a key tenet of that theory, current methods have strictly limited utility. The characterizations now considered standard, Safety Indices such as “Acceptable Daily Intake,”“Reference Dose,” and so on, usefully inform only decisions that require a choice between two policy alternatives (e.g., approve a food additive or not), decided solely on the basis of a finding of safety. Riskis characterized as the quotient of one of these Safety Indices divided by an estimate of exposure: a quotient greater than one implies that the situation may be considered safe. Such decisions are very widespread, both in the U. S. federal government and elsewhere. No current method is universal; different policies lead to different practices, for example, in California's “Proposition 65,” where statutory provisions specify some practices. Further, an important kind of human health risk assessment is not recognized by this theory: this kind characterizes risk as likelihood of harm, given estimates of exposure consequent to various decision choices. Likelihood estimates are necessary whenever decision makers have many possible decision choices and must weigh more than two societal values, such as in EPA's implementation of “conventional air pollutants.” These estimates can not be derived using current methods; different methods are needed. Our analysis suggests changes needed in both the theory and practice of human health risk assessment, and how what is done is depicted.

Notes: The prominent role of animal bioassay evidence in environmental regulatory decisions compels a careful characterization of extrapolation uncertainties. In noncancer risk assessment, uncertainty factors are incorporated to account for each of several extrapolations required to convert a bioassay outcome into a putative subthreshold dose for humans. Measures of relative toxicity taken between different dosing regimens, different endpoints, or different species serve as a reference for establishing the uncertainty factors. Ratios of no observed adverse effect levels (NOAELs) have been used for this purpose; statistical summaries of such ratios across sets of chemicals are widely used to guide the setting of uncertainty factors. Given the poor statistical properties of NOAELs, the informativeness of these summary statistics is open to question. To evaluate this, we develop an approach to “calibrate” the ability of NOAEL ratios to reveal true properties of a specified distribution for relative toxicity. A priority of this analysis is to account for dependencies of NOAEL ratios on experimental design and other exogenous factors. Our analysis of NOAEL ratio summary statistics finds (1) that such dependencies are complex and produce pronounced systematic errors and (2) that sampling error associated with typical sample sizes (50 chemicals) is nonnegligible. These uncertainties strongly suggest that NOAEL ratio summary statistics cannot be taken at face value; conclusions based on such ratios reported in well over a dozen published papers should be reconsidered.

Notes: We compare the regulatory implications of applying the traditional (linearized) and exact two-stage dose-response models to animal carcinogenic data. We analyze dose-response data from six studies, representing five different substances, and we determine the “goodness- of-fit” of each model as well as the 95% confidence lower limit ofthe dose corresponding to a target excess risk of 10-5 (the target risk doseTRD). For the two concave datasets, we find that the exact model gives a substantially better fit to the data than the traditional model, and that the exact model gives aTRD that is an order of magnitude lower than that given by the traditional model. In the other cases, the exact model gives a fit equivalent to or better than the traditional model. We also show that although the exact two-stage model may exhibit dose-response concavity at moderate dose levels, it is always linear or sublinear, and never supralinear, in the low-dose limit. Because regulatory concern is almost always confined to the low-dose region extrapolation, supralinear behavior seems not to be of regulatory concern in the exact two-stage model. Finally, we find that when performing this low-dose extrapolation in cases of dose-response concavity, extrapolating the model fit leads to a more conservative TRD than taking a linear extrapolation from 10% excess risk. We conclude with a set of recommendations.

Notes: The characterization and treatment of uncertainty poses special challenges when modeling indeterminate or complex coupled systems such as those involved in the interactions between human activity, climate and the ecosystem. Uncertainty about model structure may become as, or more important than, uncertainty about parameter values. When uncertainty grows so large that prediction or optimization no longer makes sense, it may still be possible to use the model as a “behavioral test bed” to examine the relative robustness of alternative observational and behavioral strategies. When modelsmust be run into portions of their phase space that are not well understood, different submodels may become unreliable at different rates. A common example involves running a time stepped model far into the future. Several strategies can be used to deal with such situations. The probability of model failure can be reported as a function of time. Possible alternative “surprises” can be assigned probabilities, modeled separately, and combined. Finally, through the use of subjective judgments, one may be able to combine, and over time shift between models, moving from more detailed to progressively simpler order-of-magnitude models, and perhaps ultimately, on to simple bounding analysis.

Notes: In any model the values of estimates for various parameters are obtained from different sources each with its own level of uncertainty. When the probability distributions of the estimates are obtained as opposed to point values only, the measurement uncertainties in the parameter estimates may be addressed. However, the sources used for obtaining the data and the models used to select appropriate distributions are of differing degrees of uncertainty. A hierarchy of different sources of uncertainty based upon one's ability to validate data and models empirically is presented. When model parameters are aggregated with different levels of the hierarchy represented, this implies distortion or degradation in the utility and validity of the models used. Means to identify and deal with such heterogeneous data sourcesare explored, and a number of approaches to addressing this problem is presented. One approach, using Range/confidence Estimates coupled with an Information Value Analysis Process, is presented as an example.

Notes: Variability arises due to differences in the value of a quantity among different members of a population. Uncertainty arises due to lack of knowledge regarding the true value of a quantity for a given member of a population. We describe and evaluate two methods for quantifying both variability and uncertainty. These methods, bootstrapsimulation and a likelihood-based method, are applied to three datasets. The datasetsinclude a synthetic sample of 19 values from a Lognormal distribution, a sample of nine values obtained from measurements of the PCB concentration in leafy produce, and asample of five values for the partitioning of chromium in the flue gas desulfurization system of coal-fired power plants. For each of these datasets, we employ the two methods to characterize uncertainty in the arithmetic mean and standard deviation, cumulative distribution functions based upon fitted parametric distributions, the 95th percentile of variability, and the 63rd percentile of uncertainty for the 81st percentile of variability. The latter is intended to show that it is possible to describe anypoint within the uncertain frequency distribution by specifying an uncertainty percentile and a Variability percentile. Using the bootstrap method, we compare results based upon use of the method of matching moments and the method of maximum likelihood for fitting distributions to data. Our results indicate that with only 5-19 data pointsas in the datasets we have evaluated, there is substantial uncertainty based upon random sampling error. Both the boostrap and likelihood-based approaches yield comparable uncertainty estimates in most cases.

Notes: Evaluating alternatives for restoring the Everglades involves analysis of a complex ecological and economic system for which current knowledge is limited. Uncertain benefits and impacts are analyzed probabilistically in this paper, following otherwise accepted principles of net present value (NPV) analysis. Ecological benefits and impacts were considered in monetary terms. Probabilities for selected uncertain parameters were found by maximizing entropy. The first ecological risk conceptual model for the Everglades ecosystem was developed to show ecological interactions. “Current Plans” for restoration involve discharge of phosphorus-enriched water from artificial wetlands to relatively pristine Everglades marshes for 3–10 years, risking conversion of the ecosystem to a eutrophic cattail marsh. For two of the three areas studied, alternative “Bypass Plans” were shown to avoid the loss of up to 3000 acres of sawgrass marsh at a cost that is probabilistically justified by the value of the ecosystem preserved. Sensitivity of the results to projected ecological changes, eutrophic marsh valuation, natural marsh valuation, and future values as represented in the discount rate, was examined.

Notes: The motivation of the present work is to provide an auxiliary tool for the decision-maker (DM) faced with predictive model uncertainty. The tool is especially suited for the allocation of R&Dresources. When taking decisions under uncertainties, making use of the output from mathematical or computational models, the DM might be helped if the uncertainty in model predictions be decomposed in a quantitative-rather than qualitativefashion, apportioning uncertainty according to source. This would allow optimal use of resources to reduce the imprecision in the prediction. For complex models, such a decomposition of the uncertainty into constituent elements could be impractical as such, due to the large number of parameters involved. If instead parameters could be grouped into logical subsets, then the analysis could be more useful, also because the decision maker might likely have different perceptions (and degrees of acceptance) for different kinds of uncertainty. For instance, the decomposition in groups could involve one subset of factors for each constituent module of the model; or one set for the weights, and one for the factors in a multicriteria analysis; or phenomenological parameters of the model vs. factors driving the model configuratiodstructure aggregation level, etc.); finally, one might imagine that a partition of the uncertainty could be sought between stochastic (or aleatory) and subjective (or epistemic) uncertainty. The present note shows how to compute rigorous decomposition of the output's variance with grouped parameters, and how this approach may be beneficial for the efficiency and transparency of the analysis.

Notes: The concept of vulnerability of complex industrial systems is defined and discussed in relation to risk and system survivability. The discussion is illustrated by referring to a number of previous industrial accidents. The various risk factors, or threats, influencing an industrial system's vulnerability are classified and discussed. Both internal and external threats are covered. The general scope of vulnerability analysis is compared to traditional risk analysis approaches and main differences are illustrated. A general procedure for vulnerability analysis in two steps, including building of scenarios and preparation of relevant worksheets, is described and discussed.

Notes: The current safety criteria for a high hazard dam focus on protecting the dam during a large flood. While protecting the dam does help to protect downstream people and property, the two objectives are not the same. Instead, the criteria should focus on lowering property damage (including damage to the dam) and preventing flood deaths.High hazard dams must survive a design flood in the current safety criteria. However, experts don't agree on the size of the peak flow that meets this criteria.Statistical hydrologists have proposed an alternative to using professional judgment to specify the design flood. Unfortunately, peak flow distributions cannot be estimated with confidence for extreme floods given available data.A major safety goal is to prevent deaths from floods. Preventing deaths is a major reason for constructing the spillway to handle extreme floods so that the dam doesn't fail due to overtopping. However, even if the dam doesn't fail, the spilled floods could cause many deaths. A better approach is to warn people to get them out of harm's way if a flood is coming.Retrofitting existing dams that could pass a “probable maximum flood” (PMF) when built is almost never a good use of funds. Instead, funds would be spent better by focusing on preventing damage from small floods, lowering the damage from medium-sized floods, and warning people in the event of a flood that could pose risks to life.

Notes: This paper describes and illustrates the architecture of computer-based Dynamic Risk Management Systems (DRMS) designed to assist real-time risk management decisions for complex physical systems, for example, engineered systems such as offshore platforms or medical systems such as patient treatment in Intensive Care Units. A key characteristic of the DRMSs that we describe is that they are hybrid, combining the powers of Probabilistic Risk Analysis methods and heuristic Artificial Intelligence techniques. A control module determines whether the situation corresponds to a specific rule or regulation, and is clear enough or urgent enough for an expert system to make an immediate recommendation without further analysis of the risks involved. Alternatively, if time permits and if the uncertainties justify it, a risk and decision analysis module formulates and evaluates options, including that of gathering further information. This feature is particularly critical since, most of the time, the physical system is only partially observable, i.e., the signals observed may not permit unambiguous characterization of its state. The DRMS structure is also dynamic in that, for a given time window (e.g., 1 day or 1 hour), it anticipates the physical system's state (and, when appropriate, performs a risk analysis) accounting for its evolution, its mode of operations, the predicted external loads and problems, and the possible changes in the set of available options. Therefore, we specifically address the issue of dynamic information gathering for decision-making purposes. The concepts are illustrated focusing on the risk and decision analysis modules for a particular case of real-time risk management on board offshore oil platforms, namely of two types of gas compressor leaks, one progressive and one catastrophic. We describe briefly the DRMS proof-of-concept produced at Stanford, and the prototype (ARMS) that is being constructed by Bureau Veritas (Paris) based on these concepts.

Notes: Identifying the causes of accidents is a necessary prerequisite for preventive action. Some research suggests however that the analysis of accidents does not only differ between experts and laymen but that it is also linked to certain characteristics inherent in the analyst and in the social group to which he belongs: beliefs, value systems, norms, experiences in common, attitudes, roles, social and technical practices, etc. Culturally determined bias seems to affect the perception of risk and the causes of accidents. This article presents a certain number of thoughts and results based upon research carried out on causal attributions of traffic accidents in The Ivory Coast (West Africa) and discusses the importance of culture in risk-taking and accident prevention. It shows in particular that fatalistic beliefs and mystical practices influence the perception of accidents and consequently incite one to take more risks and neglect safety measures.

Notes: Since substantial bias can result from assigning some type of mean exposure to a group, risk assessments based on epidemiological data should avoid the grouping of data whenever possible. However, ungrouped data are frequently unavailable, and the question arises as to whether an arithmetic or geometric mean is the most appropriate summary measure of exposure. It is argued in this paper that one should use the type of mean for which the total risk that would result if every member of the population was exposed to the mean level is as close as possible to the actual total population risk. Using this criterion an arithmetic mean is always preferred over a geometric mean whenever the dose response is convex. In each of several data sets examined in this paper for which the dose response was not convex, an arithmetic mean was still preferred based on this criterion.

Notes: Developmental anomalies resulting from prenatal toxicity can be manifested in terms of both malformations among surviving offspring and prenatal death. Although these two endpoints have traditionally been analyzed separately in the assessment of risk, multivariate methods of risk characterization have recently been proposed. We examined this and other issues in developmental toxicity risk assessment by evaluating the accuracy and precision of estimates of the effective dose (ED05) and the benchmark dose (BMD05) using computer simulation. Our results indicated that different variance structures (Dirichlet-trinomial and generalized linear model) used to characterize overdispersion yielded comparable results when fitting joint dose response models based on generalized estimating equations. (The choice of variance structure in separate modeling was also not critical.) However, using the Rao-Scott transformation to eliminate overdispersion tended to produce estimates of the ED05 with reduced bias and mean squared error. Because joint modeling ensures that the ED05 for overall toxicity (based on both malformations and prenatal death) is always less than the ED05 for either malformations or prenatal death, joint modeling is preferred to separate modeling for risk assessment purposes.

Notes: Nineteen Senior Managers of a major chemical company in the United Kingdom participated in a survey to determine their attitudes, beliefs, and perceptions regarding risks from chemicals. Similar surveys had previously been conducted with toxicologists and members of the general public in the United States and Canada. In general, the Senior Managers tended to judge risks to be quite small for most chemicals. Moreover, they had lower risk perceptions than did members of the British Toxicological Society and even far lower perceptions of risk than a comparison group of members of the Canadian public. The managers held views that were similar to British toxicologists working in industry and government and dissimilar to the views of toxicologists working in academia. The observed differences between views of managers, toxicologists, and the public must be recognized and understood in order to facilitate communication and constructive efforts to manage chemical risks.

Notes: The construction industry is both the largest civilian industry and the most unique in terms of fragmentation and its approach to controlling risk. Structural specifications establish nominal safety factors and design criteria for engineered structures such as buildings, bridges, dams, and power facilities. The goal is satisfactory strength capacity to safely and economically meet the demands of structural performance. Structures must resist the highly uncertain effects of combined gravity, earthquakes, wind, and snow loads supported by natural and human-made materials. The public's expectation is that structures should last a long time and have low lifetime risk of structural failure. Historically, specifications have contained safety factors which evolved from past experiences and provided adequate safety or low risk. Due to pressures of economy and the need to optimize structural performance, structural specifications have recently been developed and accepted by industry based on structural reliability and risk-assessment principles. This paper reviews developments of probabilistic applications in structural specifications including specification format, database, implementation examples, target risk levels, present research activities, and future goals for establishing optimal risk-design procedures.

Notes: Importance measures have been useful in the process of extracting insights from risk analyses. Importance measures have also been suggested for use in component classification. However, there are difficulties of interpretation associated with component classification based on importance measures. This paper briefly reviews an alternative method, “Top Event Prevention Analysis,” and, based on a simple example, compares its key characteristics to those of conventional applications of importance measures. The methods are compared with respect to the task of formulating a safety case for a complex and potentially hazardous facility, in which component classification plays an important role. A key subtask is identification of a collection of design elements that is necessary and sufficient to achieve the desired level of protection of the public, the workers, and the environment. At the design stage, identifying this set helps to determine what elements to include in the final design. Separately, a similar selection process could be used in order to justify limiting the scope of regulatory oversight to a subset of design elements, on which a safety case is to be based. This step could be taken during initial review of a design, or later as part of an effort to justify relief from regulatory requirements that are burdensome but provide little actual risk reduction.〈section xml:id="abs1-1"〉〈title type="main"〉SUMMARYA safety case should arguably be based on a collection of design elements that combine to provide satisfactory plant response to important safety challenges, and provide this response with the desired reliability (achieved through redundancy and diversity in design, and programmatic support activities as necessary in implementation). The key property of such a collection resides in the set as a whole, and not in any single element: the implications of including or not including any given design element in the collection depend strongly on what other design elements are included. Given a logic model that comprehensively addresses plant response, reflecting all components under consideration, and a defense-in-depth safety standard of the kind discussed above, TEPA is capable of choosing prevention sets: subsets of components that have the desired defense-in-depth property, and are suitable candidates for serving as the nucleus of a safety case.Single-event importance measures cannot capture considerations like this, except perhaps as part of an arduous iterative reformulation of a logic model to successively remove and restore combinations of events in a trial-and-error approach to a self-consistent design solution. No method of applying conventional importance measures has been shown to produce solutions that are feasible in the sense of completing pathsets, nor is one expected. Interpreting the upper portion of a ranked list of components as a safety case would therefore be a misapplication of the importance measure concept.However, given a prevention set, one could apply importance measures to fine-tune the allocation of resources within this set. That is, one could compute importances within a model that took credit only for elements of the prevention set, and reason from there. Even in this case, some iteration might be required in order to achieve a self-consistent allocation (one for which the reliability credit taken for each component is commensurate with the resources allocated to it). In order to draw valid conclusions in an application of this type, one must recall that all importance measures are predicated on credit for all modeled components; it is invalid to infer that components can be dropped from a safety case on grounds of low calculated importance. In short, application of importance measures is valid when (a) the selection problem has been solved by other means, (b) the importances are calculated with credit only for selected components, and (c) the resources allocated to each component are commensurate with the level of credit taken for the component (e.g., credit for a component's availability is backed up by an appropriate test schedule.).A byproduct of this work is the observation that whether or not TEPA itself is applied to choose prevention sets, a useful litmus test to be applied to a safety case is simply whether it is based on a union of complete success paths. As discussed above, thinking of the safety case in this way has other benefits, in helping to identify unmodeled components and in helping to specify the demands that must be met by each component, so that programmatic activities necessary to ensure its function can be identified and carried out. This formulation of the safety case helps in thinking about the relationship between component performance and resources allocated to that component. Understanding this relationship is essential to optimizing the use of safety resources.The number of combinations (possible prevention sets) that must be examined grows very rapidly as the number of design elements and minimal cutsets increases. Therefore, many realistic problems will be very demanding computationally. To some extent, this could be considered a drawback of TEPA, but it should be understood that the underlying problem is combinatorially very difficult, and actual solutions to it should not be expected to come easily in all cases. Fortunately, as illustrated by the practical applications summarized above, many real large-scale problems have specific features that permit their solution by adaptations of the general approach.

Notes: This paper raises two questions, i.e., Are some people more prone to perceive hazards than others embedded in the same dangerous working environment?, and—if so—Is it possible to find distinguishing characteristics allowing us to profile this worker segment? A survey study was conducted among catering personnel working on a drilling platform at the continental shelf in the North sea. It was observed that some people more than others perceived hazards in their working environment. By contrasting the extreme groups, i.e., the high and low hazards perceivers it was found that sociodemographics, e.g., gender, marital status, age and working experience possessed no descriptive power. However, the findings revealed that the worker segment prone to perceive high hazards also reported higher degree of burnout, anxiety and depression than did the low hazards perceivers. They (the high hazards perceivers) were also less satisfied with their stay on the platform, and they reported more health problems as well. The findings indicate that hazards perceptions of hazards go beyond mere “cold cognition,” also tapping into negatively feelings and emotional states. Theoretical and practical implications are highlighted.

Notes: This paper presents estimates of daily average per capita fish consumption by age and gender for the 48 conterminous states. The estimated consumption rates are reported for three fish habitats: freshwater/estuarine fish, marine fish, and all fish. The estimates were generated from the combined 1989, 1990, and 1991 Continuing Survey of Food Intake by Individuals (CSFII), a national food consumption survey conducted by the United States Department of Agriculture (USDA). Point and interval estimates of per capita fish consumption were generated from the empirical distribution of daily average per capita consumption. The point estimates include the mean, 50th, 75th, 90th, 95th, and 99th percentiles. Ninety percent confidence intervals are provided for the estimated mean and 90% bootstrap intervals are provided for percentile estimates. Information in a recipe file provided by USDA was used to calculate the amount of fish in recipes which contain fish. The estimated consumption rates are based on the weight of fish in its prepared or “as consumed” condition. The estimated mean consumption rate for all fish for the U.S. population of the 48 conterminous states was 15.65 grams/person/day (C.I.:14.67–16.63) of which 4.71 grams/person/day (C.I.:4.17–5.25) was freshwater/estuarine fish and 10.94 grams/person/day (C.I.: 10.14–11.73) was marine fish.

Notes: The combination of radon and smoking produces a synergistic risk of lung cancer. Lay understanding of this risk was examined from the perspectives of mental models theory, the psychometric approach to risk perception, and optimistic bias. As assessed by interview, participants (N= 50) had more extensive mental models for the risks of smoking than for the risks of radon or the combination of radon and smoking; 32% knew little or nothing about radon. Despite reading an informational brochure, their risk-perception ratings of the three hazards showed no perception of the synergy between smoking and radon risk, although the combined hazard was rated as less familiar but more controllable than the average of the single hazards (p 〈 .01). No evidence of optimistic bias for the health consequences of radon, or the combination of radon and smoking was observed. Participants appeared to be combining the single-hazard risks subadditively to arrive at their combined-hazard risk perceptions. Further research on the integration of perceived risks would be beneficial for designing optimal communications about synergistic risk.

Notes: This paper investigates the role that performance-based regulations can play in linking a firm's environmental, health, and safety concerns with their corporate strategy. The specific focus is on the performance standards required by the Clean Air Act Amendments (CAAA) which require firms that store or use certain chemicals to develop a Risk Management Plan (RMP) for reducing the likelihood and impact of accidents at their plants. Data from a series of case studies and interviews of executives in chemical firms reveal that proactive companies integrated many of the requirements of the CAAA into their management systems prior to the regulatory requirements. Most of these firms tend to be large ones. Small firms often lack the resources to implement these regulations and hence have tended to have a more difficult time with compliance.

Notes: Suppose that a residential neighborhood may have been contaminated by anearby abandoned hazardous waste site. The suspected contamination consistsof elevated soil concentrations of chemicals that are also found in the absence of site-related contamination. How should a risk manager decide which residential properties to sample and which ones to clean? This paper introduces an adaptive spatial sampling approach which uses initial observations to guide subsequent search. Unlike some recent model-based spatial data analysis methods, it does not require any specific statistical model for the spatial distribution of hazards, but instead constructs an increasingly accurate nonparametric approximation to it as sampling proceeds. Possible cost-effective sampling and cleanup decision rules are described by decision parameters such as the number of randomly selected locations used to initialize the process, the number of highest-concentration locations searched around, the number of samples taken at each location, a stopping rule, and a remediation action threshold. These decision parameters are optimized by simulating the performance of each decision rule. The simulation is performed using the data collected so far to impute multiple probable values ofunknown soil concentration distributions during each simulation run. This optimized adaptive spatial sampling technique has been applied to real data using error probabilities for wrongly cleaning or wrongly failing to clean each location (compared to the action that would be taken if perfect information were available) as evaluation criteria. It provides a practical approach for quantifying trade-offs between these different types of errors and expected cost. It also identifies strategies that are undominated with respect to all of these criteria.

Notes: A call for risk assessment approaches that better characterize and quantify uncertainty has been made by the scientific and regulatory community. This paper responds to that call by demonstrating a distributional approachthat draws upon human data to derive potency estimates and to identify and quantify important sources of uncertainty. The approach is rooted in the science of decision analysis and employs an influence diagram, a decision tree, probabilistic weights, and a distribution of point estimates of carcinogenic potency. Its results estimate the likelihood of different carcinogenicrisks (potencies) for a chemical under a specific scenario. For this exercise, human data on formaldehyde were employed to demonstrate the approach. Sensitivity analyses were performed to determine the relative impact of specific levels and alternatives on the potency distribution. The resulting potency estimates are compared with the results of an exercise using animal data on formaldehyde. The paper demonstrates that distributional risk assessment is readily adapted to situations in which epidemiologic data serve as the basis for potency estimates. Strengths and weaknesses of the distributional approach are discussed. Areas for further application and research are recommended.

Notes: The paper applies classical statistical principles to yield new tools for risk assessment and makes new use of epidemiological data for human riskassessment. An extensive clinical and epidemiological study of workers engaged in the manufacturing and formulation of aldrin and dieldrin provides occupational hygiene and biological monitoring data on individual exposures over the years of employment and provides unusually accurate measures of individual lifetime average daily doses. In the cancer dose-response modeling, each worker is treated as a separate experimental unit with his own unique dose. Maximum likelihood estimates of added cancer risk are calculated for multistage, multistage-Weibull, and proportional hazards models. Distributional characterizations of added cancer risk are based on bootstrap and relative likelihood techniques. The cancer mortality data on these male workerssuggest that low-dose exposures to aldrin and dieldrin do not significantlyincrease human cancer risk and may even decrease the human hazard rate for all types of cancer combined at low doses (e.g., 1μg/kg/day). The apparent hormetic effect in the best fitting dose-response models for this data set is statistically significant. The decrease in cancer risk at low doses ofaldrin and dleldrin is in sharp contrast to the U.S. Environmental Protection Agency's upper bound on cancer potency based on mouse liver tumors. The EPA's upper bound implies that lifetime average daily doses of 0.0000625 and 0.00625 pμg/kg body weight/day would correspond to increased cancer risks of 0.000001 and O.OOO1, respectively. However, the best estimate from the Pernis epidemiological data is that there is no increase in cancer risk in these workers at these doses or even at doses as large as 2 μg/kg/day.

Notes: Ethylene oxide (EO) research has significantly increased since the 1980s, when regulatory risk assessments were last completed on the basis of theanimal cancer chronic bioassays. In tandem with the new scientific understanding, there have been evolutionary changes in regulatory risk assessment guidelines, that encourage flexibility and greater use of scientific information. The results of an updated meta-analysis of the findings from 10 unique EO study cohorts from five countries, including nearly 33,000 workers, and over 800 cancers are presented, indicating that EO does not cause increased risk of cancers overall or of brain, stomach or pancreatic cancers. The findings for leukemia and non-Hodgkin's lymphoma (NHL) are inconclusive. Two studies with the requisite attributes of size, individual exposure estimates and follow up are the basis for dose-response modeling and added lifetime risk predictions under environmental and occupational exposure scenariosand a variety of plausible alternative assumptions. A point of departure analysis, with various margins of exposure, is also illustrated using human data. The two datasets produce remarkably similar leukemia added risk predictions, orders of magnitude lower than prior animal-based predictions under conservative, default assumptions, with risks on the order of 1 × 10−6 or lower for exposures in the low ppb range. Inconsistent results for “lymphoid” tumors, a non-standard grouping using histologic information from death certificates, are discussed. This assessment demonstrates the applicability of the current risk assessment paradigm to epidemiological data.

Notes: The human toxicity potential, a weighting scheme used to evaluate toxicemissions for life cycle assessment and toxics release inventories, is based on potential dose calculations and toxicity factors. This paper evaluatesthe variance in potential dose calculations that can be attributed to the uncertainty in chemical-specific input parameters as well as the variabilit in exposure factors and landscape parameters. A knowledge of the uncertainty allows us to assess the robustness of a decision based on the toxicity potential; a knowledge of the sources of uncertainty allows us to focus our resources if we want to reduce the uncertainty. The potential dose of 236 chemicals was assessed. The chemicals were grouped by dominant exposure route, and a Monte Carlo analysis was conducted for one representative chemical in each group. The variance is typically one to two orders of magnitude. For comparison, the point estimates in potential dose for 236 chemicals span ten orders of magnitude. Most of the variance in the potential dose is due to chemical-specific input parameters, especially half-lives, although exposure factors such as fish intake and the source of drinking water can be important for chemicals whose dominant exposure is through indirect routes. Landscape characteristics are generally of minor importance.

Notes: To assess soil and groundwater quality two generic (i.e. multifunctional) risk-based standards, Target and Intervention Value, have been developed, in the framework of the Dutch Soil Protection Act. These standards allow soil and groundwater to be classified as clean, slightly contaminated or seriously contaminated. The Target Value is basedon potential risks to ecosysystems, while the Intervention Value is based oqpotential risks to humans and ecosystems. In the case of serious soil contamination the site has, in principle, to be remediated, making it necessary to determine the remediation urgency on the basis of actual (i.e. site-specific) risks to humans and ecosystems and, besides, actual risks due to contaminant migration.

Notes: The Waste Isolation Pilot Plant (WIPP) is a geological repository for disposal ofU.S. defense transuranic radioactive waste. Built and operated by the U.S. Departmentof Energy (DOE), it is located in the Permian age salt beds in southeastern New Mexico at a depth of 655 m. Performance assessment for the repository's compliance with the 10,000-year containment standards was completed in 1996 and the U.S. Environmental Protection Agency (EPA) certified in 1998 that the repository meets compliance with the EPA standards 40 CFR 191 and 40 CFR 194. The Environmental Evaluation Group (EEG) review of the DOE'S application for certification identified a number of issues. These related to the scenarios, conceptual models, and values of the input parameters used in the calculations. It is expected that these issues will be addressed and resolved during the first 5-year recertification process that began with the first receipt of waste at WIPP on March 26, 1999, and scheduled to be completed in March 2004.

Notes: The estimation of health risks from exposure to a mixture of chemical carcinogens is generally based on the combination of information from several available single compound studies. The current practice of directly summing the upper bound risk estimates of individual carcinogenic components as an upper bound on the total risk of a mixture is known to be generally too conservative. Gaylor and Chen (1996, Risk Analysis) proposed a simple procedure to compute an upper bound on the total risk using only the upper confidence limits and central risk estimates of individual carcinogens. The Gaylor-Chen procedure was derived based on an underlying assumption of the normality for the distributions of individual risk estimates. In this paper we evaluated the Gaylor-Chen approach in terms of the coverage probability. The performance of the Gaylor-Chen approach in terms the coverages of the upper confidence limits on the true risks of individual carcinogens. In general, if the coverage probabilities for the individual carcinogens are all approximately equal to the nominal level, then the Gaylor-Chen approach shouldperform well. However, the Gaylor-Chen approach can be conservative or anti-conservative if some or all individual upper confidence limit estimates are conservative or anti-conservative.

Notes: Political context may play a large role in influencing the efficiency of environmental and health regulations. This case study uses data from a 1989 update of the Occupational Safety and Health Administration (OSHA) Permissible Exposure Limits (PELS) program to determine the relative effects of legislative mandates, costly acquisition of information by the agency, and pressure applied by special interest groups upon exposure standards. The empirical analysis suggests that federal agencies successfully thwart legislative attempts to limit agency discretion, and that agencies exercise bounded rationality by placing greater emphasis on more easily obtained information. The 1989 PEL were less significantly related to more costly information, contained “safety factors” for chemicals presenting relatively more ambiguous risks, and the proposed standard stringencies showed evidence of beinginfluenced by vying industry and labor interests.

Notes: Monte Carlo methods in risk assessment are finding increasingly widespread application. With the recognition that inputs may be correlated, the incorporation of such correlations into the simulation has become important. Most implementations rely upon the method of Iman and Conover for generating correlated random variables. In this work, alternative methods using copulas are presented for deriving correlated random variables. It is further shown that the particular algorithm or assumption used may have a substantial effect on the output results, due to differences in higher order bivariate moments.

Notes: In this paper, we review methods for assessing and managing the risk of extreme events, where “extreme events” are defined to be rare, severe, and outside the normal range of experience of the system in question. First, we discuss several systematic approaches for identifying possible extreme events. We then discuss some issues related to risk assessment of extreme events, including what type of output is needed (e.g., a single probability vs. a probability distribution), and alternatives to the probabilistic approach. Next, we present a number of probabilistic methods. These include : guidelines for eliciting informative probability distributions from experts; maximum entropy distributions; extreme value theory; other approaches for constructing prior distributions (such as reference or noninformative priors); the use of modeling and decomposition to estimate the probability (or distribution) of interest; and bounding methods. Finally, we briefly discuss several approaches for managing the risk of extreme events, and conclude with recommendations and directions for future research.

Notes: It is common in catastrophic food-contamination events that consumers fail to adjust instantaneously to a normal consumption level. One explanation is that consumers only gradually accept new positive information as being trustworthy. The gradual establishment of the trustworthiness of the released information depends on both positive and negative media coverage over time. We examine the individual “trust” effects by extending the prospective reference theory (Viscusi, 1989) to include a dynamic adjustment process of risk perception. Conditions that allow aggregation of changes in risk perceptions across individuals are described. The proposed model describes a general updating process of risk perceptions to media coverage and can be applied to explain the temporal impact of media coverage on consumption of a broad range of goods (food or nonfood). A case study of milk contamination is conducted to demonstrate consumer demand adjustment process to a temporarily unfavorable shock. The results suggest that effects of positive and negative information to adjustment of consumption and risk perception are asymmetric over time.

Notes: The scaling of administered doses to achieve equal degrees of toxic effect in different species has been relatively poorly examined for noncancer toxicity, either empirically or theoretically. We investigate empirical patterns in the correspondence of single oral dose LD, values across several mammalian species for a large number of chemicals based on data reported in the RTECSQ database maintained by the National Institute for Occupational Safety and Health. We find a good correspondence of LD, values across species when the dose levels are expressed in terms of mgadministered per kg of body mass. Our findings contrast with earlier analyses that support scaling doses by the 3/4-power of body mass to achieve equal subacute toxicity of antineoplastic agents. We suggest that, especially for severe toxicity, single- and repeated-dosing regimes may have different cross-species scaling properties, as they may depend on standing levels of defenses and rate of regeneration of defenses, respectively.

Notes: This paper reviews existing data on the variability in parameters relevant for health risk analyses. We cover both exposure-related parameters andparameters related to individual susceptibility to toxicity. The toxicity/susceptibility data base under construction is part of a longer term research effort to lay the groundwork for quantitative distributional analyses of non-cancer toxic risks. These data are broken down into a variety of parameter types that encompass different portions of the pathway from external exposure to the production of biological responses. The discrete steps in this pathway, as we now conceive them, are:〈list xml:id="l2" style="custom"〉•Contact Rate (Breathing rates per body weight; fish consumption per bodyweight)•Uptake or Absorption as a Fraction of Intake or Contact Rate•General Systemic Availability Net of First Pass Elimination and Dilutionvia Distribution Volume (e.g., intial blood concentration per mg/kg of uptake)•Systemic Elimination (half life or clearance)•Active Site Concentration per Systemic Blood or Plasma Concentration•Physiological Parameter Change per Active Site Concentration (expressed as the dose required to make a given percentage change in different people, or the dose required to achieve some proportion of an individual's maximum response to the drug or toxicant)•Functional Reserve Capacity-Change in Baseline Physiological Parameter Needed to Produce a Biological Response or Pass a Criterion of Abnormal FunctionComparison of the amounts of variability observed for the different parameter types suggests that appreciable variability is associated with the final step in the process-differences among people in “functional reserve capacity.” This has the implication that relevant information for estimatingeffective toxic susceptibility distributions may be gleaned by direct studies of the population distributions of key physiological parameters in people that are not exposed to the environmental and occupational toxicants thatare thought to perturb those parameters. This is illustrated with some recent observations of the population distributions of Low Density Lipoprotein Cholesterol from the second and third National Health and Nutrition Examination Surveys.

Notes: Proposed in this article is one possible framework for classifying multiple types of ethical issues in risk communication research and practice to help continue a discussion initiated in 1990 by Morgan and Lave. Some of the questions that each stage of the process for planning risk communication strategies appears to pose for ethics are discussed (e.g., selecting issues to be communicated, knowing the issue, dealing with constraints). Also discussed briefly are some issues raised by the possibility that risk communicators aspire to the status of a profession. The purpose is to foster discussion rather than issue a conclusive statement on the topic, because its very nature makes a definitive pronouncement indefensible.

Notes: The ultimate goal of the research reported in this series of three articles is to derive distributions of doses of selected environmental tobacco smoke (ETS)-related chemicals for nonsmoking workers. This analysis uses data from the 16-City Study collected with personal monitors over the course of one workday in workplaces where smoking occurred. In this article, we describe distributions of ETS chemical concentrations and the characteristicsof those distributions (e.g., whether the distribution was log normal for agiven constituent) for the workplace exposure. Next, we present population parameters relevant for estimating dose distributions and the methods used for estimating those dose distributions. Finally, we derive distributions of doses of selected ETS-related constituents obtained in the workplace for people in smoking work environments. Estimating dose distributions providedinformation beyond the usual point estimate of dose and showed that the preponderance of individuals exposed to ETS in the workplace were exposed at the low end of the dose distribution curve. The results of this analysis include estimations of hourly maxima and time-weighted average (TWA) doses of nicotine from workplace exposures to ETS (extrapolated from 1 day to 1 week) and doses derived from modeled lung burdens of ultraviolet-absorbing particulate matter (UVPM) and solanesol resulting from workplace exposures to ETS (extrapolated from 1 day to 1 year).

Notes: Through surveys of students and junior professionals and interviews with business and government executives, we studied Chinese choices and fairness perceptions in risky health and safety decisions. The survey responses were compared with American responses from an earlier study by Keller and Sarin.The survey results show that the American and Chinese respondents had similar fairness perceptions, but the Chinese did not make decisions that were consistent with their fairness perceptions, whereas the Americans did. We found that the middle-age Chinese professionals tended to make choices that were more different from the Americans than were the choices of the young Chinese management students. It is likely that these discrepancies were caused by cultural differences, with the younger Chinese tending to face a stronger Western influence.The insights from the survey results were enriched by interviews that revealed fairness perceptions of Chinese business and government executives.A framework to interpret cultural influences on decision making was also proposed.

Notes: The risk of catastrophic failures, for example in the aviation and aerospace industries, can be approached from different angles (e.g., statistics when they exist, or a detailed probabilistic analysis of the system). Each new accident carries information that has already been included in the experience base or constitutes new evidence that can be used to update a previous assessment of the risk. In this paper, we take a different approach and consider the risk and the updating from the investor's point of view. Based on the market response to past airplane accidents, we examine which ones have created a “surprise response” and which ones are considered part of the risk of the airline business as previously assessed. To do so, we quantify the magnitude and the timing of the observed market response to catastrophic accidents, and we compare it to an estimate of the response that would be expected based on the true actual cost of the accident including direct and indirect costs (“full-cost information” response). First, we develop a method based on stock market data to measure the actual market response to an accident and we construct an estimate of the “full-cost information” response to such an event. We then compare the two figures for the immediate and the long-term response of the market for the affected firm, as well as for the whole industry group to which the firm belongs. As an illustration, we analyze a sample of ten fatal accidents experienced by major US domestic airlines during the last seven years. In four cases, we observed an abnormal market response. In these instances, it seems that the shareholders may have updated their estimates of the probability of a future accident in the affected airlines or more generally of the firm's future business prospects. This market reaction is not always easy to explain much less to anticipate, a fact which management should bear in mind when planning a firm's response to such an event.

Notes: This paper describes the application of two multimedia models, PRESTO and MMSOILS, to predict contaminant migration from a landfill that contains an organic chemical (methylene chloride) and a radionuclide (uranium-238). Exposure point concentrations and human health risks are predicted, and distributions of those predictions are generated using Monte Carlo techniques. Analysis of exposure point concentrations shows that predictions of uranium-238 in groundwater differ by more than one order of magnitude between models. These differences occur mainly because PRESTO simulates uranium-238 transport through the groundwater using a one-dimensional algorithm and vertically mixes the plume over an effective mixing depth, whereas MMSOILS uses a three-dimensional algorithm and simulates a plume that resides near the surface of the aquifer.A sensitivity analysis, using stepwise multiple linear regression, is performed to evaluate which of the random variables are most important in producing the predicted distributions of exposure point concentrations and health risks. The sensitivity analysis shows that the predicted distributions can be accurately reproduced using a small subset of the random variables. Simple regression techniques are applied, for comparison, to the same scenarios, and results are similar. The practical implication of this analysis is the ability to distinguish between important versus unimportant random variables in terms of their sensitivity to selected endpoints.

Notes: A sample of 323 residents of New Jersey stratified by neighborhood quality (excellent, good, fair, poor) was gathered to determine if trust in science and technology to protect public health and environment at the societal scale was associated with trust of the local officials, such as the mayor, health officer, developers, mass media, and legislators who are guardians of the local environment. Societal (trust of science and technology) and neighborhood (mayor, health officer) dimensions of trust were found. These societal and neighborhood trust dimen-sions were weakly correlated. Respondents were divided into four trust-of-authority groups: high societal-high neighborhood, low societal-low neighborhood, high societal-low neigh-borhood, and low societal-high neighborhood. High societal-high neighborhood trust re-spondents were older, had lived in the neighborhoods for many years, were not troubled much by neighborhood or societal environmental threats, and had a strong sense of control over their environment. In strong contrast, low societal-low neighborhood trust respondents were relatively young, typically had lived in their present neighborhood for a short time, were troubled by numerous neighborhood and societal environmental threats, did not practice many personal public health practices, and felt little control over their environment.

Notes: Recreational and subsistence angling are important aspects of urban culture for much of North America where people are concentrated near the coasts or major rivers. Yet there are fish and shellfish advisories for many estuaries, rivers, and lakes, and these are not always heeded. This paper examines fishing behavior, sources of information, perceptions, and compliance with fishing advisories as a function of ethnicity for people fishing in the Newark Bay Complex of the New York-New Jersey Harbor. We test the null hypothesis that there were no ethnic differences in sources of information, perceptions of the safety of fish consumption, and compliance with advisories. There were ethnic differences in consumption rates, sources of information about fishing, knowledge about the safety of the fish, awareness of fishing advisories or of the correct advisories, and knowledge about risks for increased cancer and to unborn and young children. In general, the knowledge base was much lower for Hispanics, was intermediate for blacks, and was greatest for whites. When presented with a statement about the potential risks from eating fish, there were no differences in their willingness to stop eating fish or to encourage pregnant women to stop. These results indicate a willingness to comply with advisories regardless of ethnicity, but a vast difference in the base knowledge necessary to make informed risk decisions about the safety of fish and shellfish. Although the overall median income level of the population was in the $25,000-34,999 income category, for Hispanics it was on the border between $15,OOO-24,999 and $25,000-34,999.

Notes: Water pollution from agricultural pesticides continues to be a public concern. Given that the use of such pesticides on the farm is largely governed by voluntary behavior, it is important to understand what drives farmer behavior. Health belief models in public health and social psychology argue that persons who have adverse health experiences are likely to undertake preventive behavior. An analogous hypothesis set was tested here: farmers who believe they have had adverse health experiences from pesticides are likely to have heightened concerns about pesticides and are more likely to take greater precautions in dealing with pesticides. This work is based on an original survey of a population of 2700 corn and soybean growers in Maryland, New York, and Pennsylvania using the U.S. Department of Agriculture data base. It was designed as a mail survey with telephone follow-up, and resulted in a 60 percent response rate. Farm operators report experiencing adverse health problems they believe are associated with pesticides that is equivalent to an incidence rate that is higher than the reported incidence of occupational pesticide poisonings, but similar to the reported incidence of all pesticide poisonings. Farmers who report experiencing such problems have more heightened concerns about water pollution from fertilizers and pesticides, and illness and injury from mixing, loading, and applying pesticides than farmers who have not experienced such problems. Farmers who report experiencing such problems also are more likely to report using alternative pest management practices than farmers who do not report having such problems. This implies that farmers who have had such experiences do care about the effects of application and do engage in alternative means of pest management, which at least involve the reduction in pesticide use.

Notes: The approximate solution of the two-stage clonal expansion model of cancer may substantially deviate from the exact solution, and may therefore lead to erroneous conclusions in particular applications. However, for time-varying parameters the exact solution (method of characteristics) is not easy to implement, hampering the accessibility of the model to nonmathematicians. Based on intuitive reasoning, Clewell et al. (1995) proposed an improved approximate solution that is easy to implement whatever time-varying behavior the parameters may have. Here we provide the mathematical foundation for the approximation suggested by Clewell et al. (1995) and show that, after a slight modification, it is in fact an exact solution for the case of time-constant parameters. We were not able to prove that it is an exact solution for time-varying parameters as well. However, several computer simulations showed that the numerical results do not differ from the exact solution as proposed by Moolgavkar and Luebeck (1990). The advantage of this alternative solution is that the hazard rate of the first malignant cell can be evaluated by numerically integrating a single differential equation.