Setting Risk‐Informed Environmental Standards for Bacillus Anthracis Spores

In many cases, human health risk from biological agents is associated with aerosol exposures. Because air concentrations decline rapidly after a release, it may be necessary to use concentrations found in other environmental media to infer future or past aerosol exposures. This article presents an approach for linking environmental concentrations of Bacillus. anthracis (B. anthracis) spores on walls, floors, ventilation system filters, and in human nasal passages with human health risk from exposure to B. anthracis spores. This approach is then used to calculate example values of risk‐informed concentration standards for both retrospective risk mitigation (e.g., prophylactic antibiotics) and prospective risk mitigation (e.g., environmental clean up and reoccupancy). A large number of assumptions are required to calculate these values, and the resulting values have large uncertainties associated with them. The values calculated here suggest that documenting compliance with risks in the range of 10^?4 to 10^?6 would be challenging for small diameter (respirable) spore particles. For less stringent risk targets and for releases of larger diameter particles (which are less respirable and hence less hazardous), environmental sampling would be more promising.     

An Enforceable Indoor Air Quality Standard for Environmental Tobacco Smoke in the Workplace1

Environmental tobacco smoke (ETS)has recently been determined by U.S. environmental and occupational health authorities to be a human carcinogen. We develop a model which permits using atmospheric nicotine measurements to estimate nonsmokers’ETS lung cancer risks in individual workplaces for the first time. We estimate that during the 1980s, the U.S. nonsmoking adult population's median nicotine lung exposure (homes and workplaces combined)was 143 micrograms (μg)of nicotine daily, and that most-exposed adult nonsmokers inhaled 1430 μg/day. These exposure estimates are validated by pharmacokinetic modeling which yields the corresponding steady-state dose of the nicotine metabolite, cotinine. For U.S. adult nonsmokers of working age, we estimate median cotinine values of about 1.0 nanogram per milliliter (ng/ml)in plasma, and 6.2 ng/ml in urine; for most-exposed nonsmokers, we estimate cotinine concentrations of about 10 ng/ml in plasma and 62 ng/ml in urine. These values are consistent to within 15% of the cotinine values observed in contemporaneous clinical epidemiological studies. Corresponding median risk from ETS exposure in U.S. nonsmokers during the 1980s is estimated at about two lung cancer deaths (LCDs)per 1000 at risk, and for most-exposed nonsmokers, about two LCDs per 100. Risks abroad appear similar. Modeling of the lung cancer mortality risk from passive smoking suggests that de minimis [i.e., “acceptable” (10^-6)], risk occurs at an 8-hr time-weighted-average exposure concentration of 7.5 nanograms of ETS nicotine per cubic meter of workplace air for a working lifetime of 40 years. This model is based upon a linear exposure-response relationship validated by physical, clinical, and epidemiological data. From available data, it appears that workplaces without effective smoking policies considerably exceed this de minimis risk standard. For a substantial fraction of the 59 million nonsmoking workers in the U.S., current workplace exposure to ETS also appears to pose risks exceeding the de manifestos risk level above which carcinogens are strictly regulated by the federal government.     

Powerline Frequency Electric and Magnetic Fields: A Pilot Study of Risk Perception

The perception of the potential risk arising from human exposure to 50/60 Hz electric and magnetic fields was studied with a quasi-random sample of 116 well-educated, opinion leaders using the risk perception framework previously developed by Slovic, Fischhoff, and Lichtenstein. These individuals rated exposure to fields from transmission lines and electric blankets on a variety of scales that have been found useful in characterizing people's risk attitudes and perceptions. These judgments allowed us to conjecture about the likely desire for regulation of these potential hazards and the likely response to a publicized problem (e.g., an accident or ominous research finding) involving these two sources of exposure. Various forms of detailed information about 50/60 Hz fields were supplied to respondents. The provision of information produced modest, but statistically significant, changes in perceptions in the direction of greater concern about the risks. In response to questions of public policy, participants desired modest regulatory control of field exposure from transmission lines and little or no control of field exposure from appliances like electric blankets.     

An Integrated Framework for Environmental Multi‐Impact Spatial Risk Analysis

Quantitative risk analysis is being extensively employed to support policymakers and provides a strong conceptual framework for evaluating decision alternatives under uncertainty. Many problems involving environmental risks are, however, of a spatial nature, i.e., containing spatial impacts, spatial vulnerabilities, and spatial risk‐mitigation alternatives. Recent developments in multicriteria spatial analysis have enabled the assessment and aggregation of multiple impacts, supporting policymakers in spatial evaluation problems. However, recent attempts to conduct spatial multicriteria risk analysis have generally been weakly conceptualized, without adequate roots in quantitative risk analysis. Moreover, assessments of spatial risk often neglect the multidimensional nature of spatial impacts (e.g., social, economic, human) that are typically occurring in such decision problems. The aim of this article is therefore to suggest a conceptual quantitative framework for environmental multicriteria spatial risk analysis based on expected multi‐attribute utility theory. The framework proposes: (i) the formal assessment of multiple spatial impacts; (ii) the aggregation of these multiple spatial impacts; (iii) the assessment of spatial vulnerabilities and probabilities of occurrence of adverse events; (iv) the computation of spatial risks; (v) the assessment of spatial risk mitigation alternatives; and (vi) the design and comparison of spatial risk mitigation alternatives (e.g., reductions of vulnerabilities and/or impacts). We illustrate the use of the framework in practice with a case study based on a flood‐prone area in northern Italy.     

Bounding Analysis of Drinking Water Health Risks from a Spill of Hydraulic Fracturing Flowback Water

A bounding risk assessment is presented that evaluates possible human health risk from a hypothetical scenario involving a 10,000‐gallon release of flowback water from horizontal fracturing of Marcellus Shale. The water is assumed to be spilled on the ground, infiltrates into groundwater that is a source of drinking water, and an adult and child located downgradient drink the groundwater. Key uncertainties in estimating risk are given explicit quantitative treatment using Monte Carlo analysis. Chemicals that contribute significantly to estimated health risks are identified, as are key uncertainties and variables to which risk estimates are sensitive. The results show that hypothetical exposure via drinking water impacted by chemicals in Marcellus Shale flowback water, assumed to be spilled onto the ground surface, results in predicted bounds between 10⁻¹⁰ and 10⁻⁶ (for both adult and child receptors) for excess lifetime cancer risk. Cumulative hazard indices (HI_CUMULATIVE) resulting from these hypothetical exposures have predicted bounds (5th to 95th percentile) between 0.02 and 35 for assumed adult receptors and 0.1 and 146 for assumed child receptors. Predicted health risks are dominated by noncancer endpoints related to ingestion of barium and lithium in impacted groundwater. Hazard indices above unity are largely related to exposure to lithium. Salinity taste thresholds are likely to be exceeded before drinking water exposures result in adverse health effects. The findings provide focus for policy discussions concerning flowback water risk management. They also indicate ways to improve the ability to estimate health risks from drinking water impacted by a flowback water spill (i.e., reducing uncertainty).     

A Comparative Cancer Risk Evaluation of MTBE and Other Compounds (Including Naturally Occurring Compounds) in Drinking Water in New Hampshire

Methyl tert-butyl ether (MTBE) was added to gasoline in New Hampshire (NH) between 1995 and 2006 to comply with the oxygenate requirements of the 1990 Amendments to the Clean Air Act. Leaking tanks and spills released MTBE into groundwater, and as a result, MTBE has been detected in drinking water in NH. We conducted a comparative cancer risk assessment and a margin-of-safety (MOS) analysis for several constituents, including MTBE, detected in NH drinking water. Using standard risk assessment methods, we calculated cancer risks from exposure to 12 detected volatile organic compounds (VOCs), including MTBE, and to four naturally occurring compounds (i.e., arsenic, radium-226, radium-228, and radon-222) detected in NH public water supplies. We evaluated exposures to a hypothetical resident ingesting the water, dermally contacting the water while showering, and inhaling compounds volatilizing from water in the home. We then compared risk estimates for MTBE to those of the other 15 compounds. From our analysis, we concluded that the high-end cancer risk from exposure to MTBE in drinking water is lower than the risks from all the other VOCs evaluated and several thousand times lower than the risks from exposure to naturally occurring constituents, including arsenic, radium, and radon. We also conducted an MOS analysis in which we compared toxicological points of departure to the NH maximum contaminant level (MCL) of 13 µg/L. All of the MOSs were greater than or equal to 160,000, indicating a large margin of safety and demonstrating the health-protectiveness of the NH MCL for MTBE.     

An Analysis of the Health Benefits Associated with the Use of MTBE Reformulated Gasoline and Oxygenated Fuels in Reducing Atmospheric Concentrations of Selected Volatile Organic Compounds

To assess the health benefits gained from the use of cleaner burning gasoline, an analysis was conducted of changes in the atmospheric concentration of eight VOCs: acetaldehyde, benzene, 1,3-butadiene, ethylbenzene, formaldehyde, POM, toluene, and xylenes resulting from the use of reformulated gasoline and oxyfuel containing the additive MTBE. Modeled ambient air concentrations of VOCs were used to assess three seasonally-based scenarios: baseline gasoline compared to (a) summer MTBE:RFG, (b) winter MTBE:RFG, and (c) MTBE oxyfuel. The model predicts that the addition of MTBE to RFG or oxyfuel will decrease acetaldehyde, benzene, 1,3-butadiene and POM, but increase formaldehyde tailpipe emissions. The increased formaldehyde emissions, however, will be offset by the reduction of formaldehyde formation in the atmosphere from other VOCs. Using a range of plausible risk estimates, the analysis predicts a positive health benefit, i.e., a decline in cancer incidence associated with use of MTBE:RFG and MTBE oxyfuel. Using EPA cancer risk estimates, reduction in 1,3-butadiene exposure accounts for the greatest health benefit while reduction of benzene exposure accounts for the greatest health benefits based on alternative risk estimates. An analysis of microenvironment monitoring data indicates that most exposures to VOCs are significantly below levels of concern based on established margin-of-safety standards. The analysis does suggest, however, that health effects associated with short-term exposures to acetaldehyde and benzene may warrant further investigation.     

Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.     

Evaluating the Potential for a Helicobacter pylori Drinking Water Guideline

Helicobacter pylori is a microaerophilic, gram‐negative bacterium that is linked to adverse health effects including ulcers and gastrointestinal cancers. The goal of this analysis is to develop the necessary inputs for a quantitative microbial risk assessment (QMRA) needed to develop a potential guideline for drinking water at the point of ingestion (e.g., a maximum contaminant level, or MCL) that would be protective of human health to an acceptable level of risk while considering sources of uncertainty. Using infection and gastric cancer as two discrete endpoints, and calculating dose‐response relationships from experimental data on humans and monkeys, we perform both a forward and reverse risk assessment to determine the risk from current reported surface water concentrations of H. pylori and an acceptable concentration of H. pylori at the point of ingestion. This approach represents a synthesis of available information on human exposure to H. pylori via drinking water. A lifetime risk of cancer model suggests that a MCL be set at <1 organism/L given a 5‐log removal treatment because we cannot exclude the possibility that current levels of H. pylori in environmental source waters pose a potential public health risk. Research gaps include pathogen occurrence in source and finished water, treatment removal rates, and determination of H. pylori risks from other water sources such as groundwater and recreational water.     

A Case Study Comparing Static and Spatially Explicit Ecological Exposure Analysis Methods

Exposure to chemical contaminants must be estimated when performing ecological risk assessments. A previous article proposed a habitat area and quality conditioned population exposure estimator, E[HQ]P, and described an individual-based, random walk, Monte Carlo model (SE3M) to facilitate calculation of E[HQ]P. In this article, E[HQ]P was compared with exposure estimates from a baseline risk assessment that evaluated mink and great blue heron exposure to fluoride at a federal Superfund site. Calculation of E[HQ]P took into consideration a receptor's forage area, movement behavior, population size, and the areal extent and quality of suitable habitat. The baseline assessment used four methods that did (total and unit Tier 2) and did not (total and unit Tier 1) consider habitat area or quality; where "total" included all exposure units on site and "unit" only a given exposure unit. Total Tier 1 estimates were consistently higher than E[HQ]P (e.g., 169.1 mg/kg x d versus 21.6 mg/kg x d). Risk managers using total Tier 1 results for decision making would be unlikely to underestimate exposure; however, implementability of correspondingly lower remedial objectives could be challenging. Unit Tier 1 estimates were higher (e.g., 96.5 mg/kg x d versus 61.6 mg/kg x d) or lower (e.g., 3.5 mg/kg x d versus 51.1 mg/kg x d) than E[HQ]P depending on variations in landscape features. Total Tier 2 and E[HQ]P estimates were similar (e.g., 20.7 mg/kg x d versus 21.6 mg/kg x d) when an ecologically questionable average exposure was assumed. Unit Tier 2 estimates were consistently well below E[HQ]P (e.g., 17.8 mg/kg x d versus 61.6 mg/kg x d) when an average exposure was not assumed. Risk managers using unit Tier 1 or 2 results could be basing their decisions on potentially large underestimates of exposure. By forgoing average exposure assumptions, and explicitly addressing landscape heterogeneity, SE3M appears capable of yielding exposure estimates that are not as potentially misleading to risk managers as those produced with traditional averaging methods.     

Adding dynamics to a static theory: How leader traits evolve and how they are expressed

Leader's traits evolve over time and are expressed differently under different situations. To capture both the evolution and expression of leader traits, we propose a dynamic model. We argue that the evolution of traits consists of changes in intensity and nature. Based on data on five publicly acknowledged Chinese leaders collected from various sources, we identified three patterns (homological, converse, and composite) by which leader traits evolve. We also discovered that leader's traits can be intrinsic or extrinsic. The intrinsic traits change in intensity; whereas the extrinsic traits are replaced by other traits over time. Factors influencing these changes include both internal (e.g., leaders' own learning and introspection) and external (e.g., major social events and subtle cultural influences). The results of our study show that the traits leaders demonstrated under specific situations are composite in nature, which also supports the notion that traits evolve. Based on our finding, we generated a few propositions for future empirical studies.     

Derivation of a Target Level of Lead in Soil at Residential Sites Corresponding to a De Minimis Contribution to Blood Lead Concentration1

Inability to define either a clear toxicologic threshold or a stochastic all-or-nothing (cancer-type) response model for the noncarcinogenic effects of lead (Pb) in young children has posed difficulties for derivation of risk-based target levels of Pb in residential soil. Approaches based on empirical relationships between Pb levels in blood (PbB) and Pb in soil suffer from inability to specify the numerous variables which mediate between these two quantities. Approaches based on achieving a toxicologically de minimis target PbB level (e.g., 10 μg/dl) are subject to large uncertainty in estimating the distribution of existing PbB levels in a specific exposed population and in estimating the relative contribution from nonsoil sources of Pb. The multisource contribution to the distribution of PbB makes this approach unsuited for determination of a target Pb level in a single medium. An alternative approach is presented based on achieving a de minimis contribution to PbB (ΔPbB) from soil. Contributions to Pb exposure from outdoor soil and indoor soil-derived dust (ISDD) are modeled and appropriate values are suggested for input parameters. This analysis predicts that chronic exposure of young children to 200 μg Pb/g (ppm) in residential soil will result in a ΔPbB of 2 μg Pb/dl blood. This concentration of Pb in soil may provide an appropriate target level for residential soil when other significant sources of Pb exposure are present. In other cases, this approach can be used to predict a soil concentration of Pb corresponding to an appropriate non-de minimisΔPbB.     

Health Risk Assessment of a Modern Municipal Waste Incinerator

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 tracer pollutants: 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^–5 g/m³ (20th and 80th percentiles = 1.5·10^–5 and 6.5·10^–5 g/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^–4 g/m³ (0.9.10^–4 – 3.6·10^–4 g/m³) and 8.6·10^–8 (4.3·10^–8–17.3·10^–8); for cadmium they were respectively 8.3·10^–6 g/m³ (4.0·10^–6–17.6·10^–6) and 1.5·10^–8 (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.     

Importance of Uncertainty and Variability to Predicted Risks from Trophic Transfer of PCBs in Dredged Sediments

Biomagnification of organochlorine and other persistent organic contaminants by higher trophic level organisms represents one of the most significant sources of uncertainty and variability in evaluating potential risks associated with disposal of dredged materials. While it is important to distinguish between population variability (e.g., true population heterogeneity in fish weight, and lipid content) and uncertainty (e.g., measurement error), they can be operationally difficult to define separately in probabilistic estimates of human health and ecological risk. We propose a disaggregation of uncertain and variable parameters based on: (1) availability of supporting data; (2) the specific management and regulatory context (in this case, of the U.S. Army Corps of Engineers/U.S. Environmental Protection Agency tiered approach to dredged material management); and (3) professional judgment and experience in conducting probabilistic risk assessments. We describe and quantitatively evaluate several sources of uncertainty and variability in estimating risk to human health from trophic transfer of polychlorinated biphenyls (PCBs) using a case study of sediments obtained from the New York-New Jersey Harbor and being evaluated for disposal at an open water off-shore disposal site within the northeast region. The estimates of PCB concentrations in fish and dietary doses of PCBs to humans ingesting fish are expressed as distributions of values, of which the arithmetic mean or mode represents a particular fractile. The distribution of risk values is obtained using a food chain biomagnification model developed by Gobas by specifying distributions for input parameters disaggregated to represent either uncertainty or variability. Only those sources of uncertainty that could be quantified were included in the analysis. Results for several different two-dimensional Latin Hypercube analyses are provided to evaluate the influence of the uncertain versus variable disaggregation of model parameters. The analysis suggests that variability in human exposure parameters is greater than the uncertainty bounds on any particular fractile, given the described assumptions.     

Issues Related to Time Averaging of Exposure in Modeling Risks Associated with Intermittent Exposures to Lead

Typical exposures to lead often involve a mix of long-term exposures to relatively constant exposure levels (e.g., residential yard soil and indoor dust) and highly intermittent exposures at other locations (e.g., seasonal recreational visits to a park). These types of exposures can be expected to result in blood lead concentrations that vary on a temporal scale with the intermittent exposure pattern. Prediction of short-term (or seasonal) blood lead concentrations arising from highly variable intermittent exposures requires a model that can reliably simulate lead exposures and biokinetics on a temporal scale that matches that of the exposure events of interest. If exposure model averaging times (EMATs) of the model exceed the shortest exposure duration that characterizes the intermittent exposure, uncertainties will be introduced into risk estimates because the exposure concentration used as input to the model must be time averaged to account for the intermittent nature of the exposure. We have used simulation as a means of determining the potential magnitude of these uncertainties. Simulations using models having various EMATs have allowed exploration of the strengths and weaknesses of various approaches to time averaging of exposures and impact on risk estimates associated with intermittent exposures to lead in soil. The International Commission of Radiological Protection (ICRP) model of lead pharmacokinetics in humans simulates lead intakes that can vary in intensity over time spans as small as one day, allowing for the simulation of intermittent exposures to lead as a series of discrete daily exposure events. The ICRP model was used to compare the outcomes (blood lead concentration) of various time-averaging adjustments for approximating the time-averaged intake of lead associated with various intermittent exposure patterns. Results of these analyses suggest that standard approaches to time averaging (e.g., U.S. EPA) that estimate the long-term daily exposure concentration can, in some cases, result in substantial underprediction of short-term variations in blood lead concentrations when used in models that operate with EMATs exceeding the shortest exposure duration that characterizes the intermittent exposure. Alternative time-averaging approaches recommended for use in lead risk assessment more reliably predict short-term periodic (e.g., seasonal) elevations in blood lead concentration that might result from intermittent exposures. In general, risk estimates will be improved by simulation on shorter time scales that more closely approximate the actual temporal dynamics of the exposure.     

An Overview of a Multimedia Benchmarking Analysis for Three Risk Assessment Models: RESRAD, MMSOILS, and MEPAS

Multimedia modelers from the United States Environmental Protection Agency (EPA) and the United States Department of Energy (DOE) collaborated to conduct a detailed and quantitative benchmarking analysis of three multimedia models. The three models—RESRAD (DOE), MMSOILS (EPA), and MEPAS (DOE)—represent analytically-based tools that are used by the respective agencies for performing human exposure and health risk assessments. The study is performed by individuals who participate directly in the ongoing design, development, and application of the models. Model form and function are compared by applying the models to a series of hypothetical problems, first isolating individual modules (e.g., atmospheric, surface water, groundwater) and then simulating multimedia-based risk resulting from contaminant release from a single source to multiple environmental media. Study results show that the models differ with respect to environmental processes included (i.e., model features) and the mathematical formulation and assumptions related to the implementation of solutions. Depending on the application, numerical estimates resulting from the models may vary over several orders-of-magnitude. On the other hand, two or more differences may offset each other such that model predictions are virtually equal. The conclusion from these results is that multimedia models are complex due to the integration of the many components of a risk assessment and this complexity must be fully appreciated during each step of the modeling process (i.e., model selection, problem conceptualization, model application, and interpretation of results).     

Consumer-Phase Salmonella enterica serovar Enteritidis Risk Assessment for Egg-Containing Food Products

We describe a one-dimensional probabilistic model of the role of domestic food handling behaviors on salmonellosis risk associated with the consumption of eggs and egg-containing foods. Six categories of egg-containing foods were defined based on the amount of egg contained in the food, whether eggs are pooled, and the degree of cooking practiced by consumers. We used bootstrap simulation to quantify uncertainty in risk estimates due to sampling error, and sensitivity analysis to identify key sources of variability and uncertainty in the model. Because of typical model characteristics such as nonlinearity, interaction between inputs, thresholds, and saturation points, Sobol's method, a novel sensitivity analysis approach, was used to identify key sources of variability. Based on the mean probability of illness, examples of foods from the food categories ranked from most to least risk of illness were: (1) home-made salad dressings/ice cream; (2) fried eggs/boiled eggs; (3) omelettes; and (4) baked foods/breads. For food categories that may include uncooked eggs (e.g., home-made salad dressings/ice cream), consumer handling conditions such as storage time and temperature after food preparation were the key sources of variability. In contrast, for food categories associated with undercooked eggs (e.g., fried/soft-boiled eggs), the initial level of Salmonella contamination and the log10 reduction due to cooking were the key sources of variability. Important sources of uncertainty varied with both the risk percentile and the food category under consideration. This work adds to previous risk assessments focused on egg production and storage practices, and provides a science-based approach to inform consumer risk communications regarding safe egg handling practices.     

Risk Criteria for Nuclear Power Plants: A Pragmatic Proposal1

Criteria are proposed for both an acceptable upper bound of nuclear power plant risk and a lower bound as a design target. Recognizing that the public risk associated with a power plant can be estimated only by probabilistic analysis of the design features, the spread between the lower design target and the upper bound provides a margin for uncertainty in th probabilistic estimate. The combination of a low probabilistic design target and this margin provides a reasonable expectation that the overall performance will be in the domain of an acceptable risk level. Because the exposure to potential risk is chiefly in the locality of the nuclear station, it is also proposed that compensatory benefits should be provided locally and that these be included as a cost of operation. It is suggested that the upper bound be set at a risk level equivalent to those risks of routine living which are normally accepted, i.e., about 10^-4 deaths per year per person (100 deaths/yr/million). The proposed lower design target is 10^-8 (0.1 deaths/yr/million), about one-hundredth of the minimal risk from the natural hazards all people are exposed to.     

Predicting Future Excess Events in Risk Assessment

Risk characterization in a study population relies on cases of disease or death that are causally related to the exposure under study. The number of such cases, so-called "excess" cases, is not just an indicator of the impact of the risk factor in the study population, but also an important determinant of statistical power for assessing aspects of risk such as age-time trends and susceptible subgroups. In determining how large a population to study and/or how long to follow a study population to accumulate sufficient excess cases, it is necessary to predict future risk. In this study, focusing on models involving excess risk with possible effect modification, we describe a method for predicting the expected magnitude of numbers of excess cases and assess the uncertainty in those predictions. We do this by extending Bayesian APC models for rate projection to include exposure-related excess risk with possible effect modification by, e.g., age at exposure and attained age. The method is illustrated using the follow-up study of Japanese Atomic-Bomb Survivors, one of the primary bases for determining long-term health effects of radiation exposure and assessment of risk for radiation protection purposes. Using models selected by a predictive-performance measure obtained on test data reserved for cross-validation, we project excess counts due to radiation exposure and lifetime risk measures (risk of exposure-induced deaths (REID) and loss of life expectancy (LLE)) associated with cancer and noncancer disease deaths in the A-Bomb survivor cohort.     

Development of a Unit Risk Factor for 1,3-Butadiene Based on an Updated Carcinogenic Toxicity Assessment

The Texas Commission on Environmental Quality (TCEQ) has developed an inhalation unit risk factor (URF) for 1,3-butadiene based on leukemia mortality in an updated epidemiological study on styrene-butadiene rubber production workers conducted by researchers at the University of Alabama at Birmingham. Exposure estimates were updated and an exposure estimate validation study as well as dose-response modeling were conducted by these researchers. This information was not available to the U.S. Environmental Protection Agency when it prepared its health assessment of 1,3-butadiene in 2002. An extensive analysis conducted by TCEQ discusses dose-response modeling, estimating risk for the general population from occupational workers, estimating risk for potentially sensitive subpopulations, effect of occupational exposure estimation error, and use of mortality rates to predict incidence. The URF is 5.0 × 10⁻⁷ per μg/m³ or 1.1 × 10⁻⁶ per ppb and is based on a Cox regression dose-response model using restricted continuous data with age as a covariate, and a linear low-dose extrapolation default approach using the 95% lower confidence limit as the point of departure. Age-dependent adjustment factors were applied to account for possible increased susceptibility for early life exposure. The air concentration at 1 in 100,000 excess leukemia mortality, the no-significant-risk level, is 20 μg/m³ (9.1 ppb), which is slightly lower than the TCEQ chronic reference value of 33 μg/m³ (15 ppb) protective of ovarian atrophy. These values will be used to evaluate ambient air monitoring data so the general public is protected against adverse health effects from chronic exposure to 1,3-butadiene.