Association of per- and polyfluoroalkyl substance exposure with fatty liver disease risk in US adults.

Background & Aims: Per- and polyfluoroalkyl substances (PFAS) are widespread pollutants with demonstrated hepatotoxicity. Few studies have examined the association between PFAS and fatty liver disease (FLD) risk in an adult population. Methods: In this cross-sectional study of participants from the 2017-2018 National Health and Nutrition Examination Survey, serum PFAS were measured, and FLD cases were ascertained by vibration-controlled transient elastography. Logistic regression models were used to examine the association between circulating PFAS levels and FLD risk. Analyses were stratified into non-alcoholic FLD and alcoholic FLD risk groups by alcohol intake status, as well as controlling for other risk factors, including personal demographics, lifestyle factors, and related health factors. Results: Among 1,135 eligible participants, 446 had FLD. For FLD risk, the multivariable-adjusted odds ratio per log-transformed SD increase (ORSD) in perfluorohexane sulfonate (PFHxS) was 1.13 (95% CI 1.01-1.26). The association between PFHxS and FLD appeared stronger among individuals with obesity or high-fat diets (both p interaction <0.05). When limiting the analysis to 212 heavy drinkers (≥2 drinks/day for women and ≥3 drinks/day for men), significantly higher risk of alcoholic FLD was found for higher levels of perfluorooctanoic acid (ORSD 1.79; 95% CI 1.07-2.99), PFHxS (ORSD 2.06; 95% CI 1.17-3.65), and perfluoroheptane sulfonic acid (ORSD 1.44; 95% CI 1.00-2.07), and marginally significant higher risk for total PFAS (ORSD 2.12; 95% CI 0.99-4.54). In never or light drinkers, we did not observe any significant association between PFAS and non-alcoholic FLD. Significant positive associations were found for PFAS with aspartate aminotransferase, gamma-glutamyl transaminase, total bilirubin, and albumin (ß ranged from 0.008 to 0.101, all p <0.05). Conclusions: Higher serum PFAS was moderately associated with FLD risk and worse liver function in the general population, and among those with independent risk factors, including heavy alcohol intake, obesity, or high-fat diets, PFAS increased the risk. These results suggest synergistic effects on hepatic steatosis between PFAS exposures as measured through biomonitoring data and lifestyle risk factors in a nationally representative US population. Impact and Implications: The per- and polyfluoroalkyl substances (PFAS) may convey higher risk for chronic liver disease in humans. Among 1,135 US adults in the 2017-2018 National Health and Nutrition Examination Survey, we found that higher serum PFAS was associated with higher fatty liver disease risk and worse liver function, especially among those with liver disease risk factors, including heavy alcohol intake, obesity, or high-fat diets. Continuously monitoring PFAS in the population and examining how they potentiate risk to the liver are essential.

A Systematic Framework for Collecting Site-Specific Sampling and Survey Data to Support Analyses of Health Impacts from Land-Based Pollution in Low- and Middle-Income Countries.

The rise of small-scale and localized economic activities in low- and middle-income countries (LMICs) has led to increased exposures to contaminants associated with these processes and the potential for resulting adverse health effects in exposed communities. Risk assessment is the process of building models to predict the probability of adverse outcomes based on concentration-response functions and exposure scenarios for individual contaminants, while epidemiology uses statistical methods to explore associations between potential exposures and observed health outcomes. Neither approach by itself is practical or sufficient for evaluating the magnitude of exposures and health impacts associated with land-based pollution in LMICs. Here we propose a more pragmatic framework for designing representative studies, including uniform sampling guidelines and household surveys, that draws from both methodologies to better support community health impact analyses associated with land-based pollution sources in LMICs. Our primary goal is to explicitly link environmental contamination from land-based pollution associated with specific localized economic activities to community exposures and health outcomes at the household level. The proposed framework was applied to the following three types of industries that are now widespread in many LMICs: artisanal scale gold mining (ASGM), used lead-acid battery recycling (ULAB), and small tanning facilities. For each activity, we develop a generalized conceptual site model (CSM) that describes qualitative linkages from chemical releases or discharges, environmental fate and transport mechanisms, exposure pathways and routes, populations at risk, and health outcomes. This upfront information, which is often overlooked, is essential for delineating the contaminant zone of influence in a community and identifying relevant households for study. We also recommend cost-effective methods for use in LMICs related to environmental sampling, biological monitoring, survey questionnaires, and health outcome measurements at contaminated and unexposed reference sites. Future study designs based on this framework will facilitate consistent, comparable, and standardized community exposure, risk, and health impact assessments for land-based pollution in LMICs. The results of these studies can also support economic burden analyses and risk management decision-making around site cleanup, risk mitigation, and public health education.

Risk Analysis Approaches to Evaluating Health Impacts from Land-Based Pollution in Low- and Middle-Income Countries.

Risk analysis offers a useful framework for evaluating and managing environmental health risks across different settings. In this Perspective, we question whether the principles and practice of risk analysis could be beneficial in the context of land-based pollution in low- and middle-income countries (LMICs) to better support risk-based decision making. Specifically, potential health and economic impacts from land-based pollution in LMICs has become an increasing issue of concern due to widespread environmental contamination from active and legacy operations, particularly informal activities that are becoming increasingly dispersed throughout communities, such as used lead acid battery recycling, artisanal and small-scale gold mining, and small-scale tanneries. However, the overall magnitude and scale of the public health problem arising from these sources remains highly uncertain and poorly characterized and cannot be compared to land-based pollution in high-income countries due to unique factors. This lack of knowledge has negatively affected the political priority and level of funding for risk mitigation actions targeting land-based pollution in these countries. Our primary objective is to raise further awareness of this emerging issue among risk analysts and decisionmakers and to advocate for more robust and focused research. Here, we highlight the types of industries and activities contributing to land-based pollution in LMICs and describe key findings and knowledge and data gaps that have hindered a fuller understanding of this issue. We also discuss how several risk assessment and risk management approaches might be useful in this resource-constrained context. We conclude that a combination of risk analysis approaches may be worthwhile, but more work is needed to determine which methods or tools will be most informative, technically feasible, and cost-effective for identifying, prioritizing, and mitigating land-based pollution in LMICs. Affected researchers, funding agencies, and local or national governments will need to work together to develop improved study designs and risk mitigation strategies.

Integrating Metapopulation Dynamics into a Bayesian Network Relative Risk Model: Assessing Risk of Pesticides to Chinook Salmon (Oncorhynchus tshawytscha) in an Ecological Context.

The population level is often the biological endpoint addressed in ecological risk assessments (ERAs). However, ERAs tend to ignore the metapopulation structure, which precludes an understanding of how population viability is affected by multiple stressors (e.g., toxicants and environmental conditions) at large spatial scales. Here we integrate metapopulation model simulations into a regional-scale, multiple stressors risk assessment (Bayesian network relative risk model [BN-RRM]) of organophosphate (OP) exposure, water temperature, and DO impacts on Chinook salmon (Oncorhynchus tshawytscha). A matrix metapopulation model was developed for spring Chinook salmon in the Yakima River Basin (YRB), Washington, USA, including 3 locally adapted subpopulations and hatchery fish that interact with those subpopulations. Three metapopulation models (an exponential model, a ceiling density-dependent model, and an exponential model without dispersal) were integrated into the BN-RRM to evaluate the effects of population model assumptions on risk calculations. Risk was defined as the percent probability that the abundance of a subpopulation would decline from their initial abundance (500 000). This definition of risk reflects the Puget Sound Partnership's management goal of achieving "no net loss" of Chinook abundance. The BN-RRM model results for projection year 20 showed that risk (in % probability) from OPs and environmental stressors was higher for the wild subpopulations-the American River (50.9%-97.7%) and Naches (39.8%-84.4%) spring Chinook-than for the hatchery population (CESRF 18.5%-46.5%) and the Upper Yakima subpopulation (21.5%-68.7%). Metapopulation risk was higher in summer (58.1%-68.7%) than in winter (33.6%-53.2%), and this seasonal risk pattern was conserved at the subpopulation level. To reach the management goal in the American River spring Chinook subpopulation, the water temperature conditions in the Lower Yakima River would need to decrease. We demonstrate that 1) relative risk can vary across a metapopulation's spatial range, 2) dispersal among patches impacts subpopulation abundance and risk, and 3) local adaptation within a salmon metapopulation can profoundly impact subpopulation responses to equivalent stressors. Integr Environ Assess Manag 2021;17:95-109. © 2020 SETAC.

Evolving Science and Practice of Risk Assessment.

Managing public health risks from environmental contaminants has historically relied on a risk assessment process defined by the regulatory context in which these risks are assessed. Risk assessment guidance follows a straightforward, chemical-by-chemical approach to inform regulatory decisions around the question "what is the risk-based concentration protective of human and ecological health outcomes?" Here we briefly summarize regulatory risk assessment in the context of innovative risk assessment approaches based on an evolving understanding of the underlying scientific disciplines that support risk analysis more broadly. We discuss scientific versus regulatory tensions in the application of these approaches for future risk assessments, and challenges in translating our improved understanding of the underlying scientific complexity to the regulatory landscape to better inform decision making that extends beyond conventional regulatory mandates.

Evaluation of dredged sediment for aquatic placement: interpreting contaminant bioaccumulation.

The potential bioaccumulation of sediment-associated contaminants is one of the primary concerns associated with the aquatic placement of dredged sediment. Laboratory bioaccumulation tests with representative infaunal organisms exposed to dredged sediment and reference sediment are used to assess the potential for contaminant-related bioaccumulation impacts. Dredged sediment testing and evaluation guidance provides statistical inferences and numerous assessment factors (e.g., the magnitude of difference (MOD)) to interpret results; however, detailed information for applying these factors is lacking. Therefore, the focus of this work was to provide context for the application of the MOD as a line of evidence for evaluating bioaccumulation risk associated with dredged material placement in aquatic environments by considering variance (as coefficient of variation (CV)), MOD, and statistical differences associated with bioaccumulation bioassay tissue concentrations in three case studies. Based on peer-reviewed data and dredged material monitoring data, relatively low within-sample variability (CVs < 50%) of tissue concentrations can be achieved for commonly assessed constituents (e.g., polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs), metals, and butyl tins). Thus, statistical comparisons were generally able to detect significant differences (p < 0.05; α = 0.05) across tissue concentrations with relatively low MODs (< 2-fold difference). Based on the observed variance, MOD, and statistical differences associated with bioaccumulation bioassay tissue concentrations, a 2-fold MOD can provide an additional line of evidence to evaluate bioaccumulative risk when statistical significance is observed. These results indicated that a judicious consideration of the sample variance and MOD is a useful factor when discerning meaningful differences among contaminant tissue concentrations.

Integration of Chlorpyrifos Acetylcholinesterase Inhibition, Water Temperature, and Dissolved Oxygen Concentration into a Regional Scale Multiple Stressor Risk Assessment Estimating Risk to Chinook Salmon.

We estimated the risk to populations of Chinook salmon (Oncorhynchus tshawytscha) due to chlorpyrifos (CH), water temperature (WT), and dissolved oxygen concentration (DO) in 4 watersheds in Washington State, USA. The watersheds included the Nooksack and Skagit Rivers in the Northern Puget Sound, the Cedar River in the Seattle-Tacoma corridor, and the Yakima River, a tributary of the Columbia River. The Bayesian network relative risk model (BN-RRM) was used to conduct this ecological risk assessment and was modified to contain an acetylcholinesterase (AChE) inhibition pathway parameterized using data from CH toxicity data sets. The completed BN-RRM estimated risk at a population scale to Chinook salmon employing classical matrix modeling runs up to 50-y timeframes. There were 3 primary conclusions drawn from the model-building process and the risk calculations. First, the incorporation of an AChE inhibition pathway and the output from a population model can be combined with environmental factors in a quantitative fashion. Second, the probability of not meeting the management goal of no loss to the population ranges from 65% to 85%. Environmental conditions contributed to a larger proportion of the risk compared to CH. Third, the sensitivity analysis describing the influence of the variables on the predicted risk varied depending on seasonal conditions. In the summer, WT and DO were more influential than CH. In the winter, when the seasonal conditions are more benign, CH was the driver. Fourth, in order to reach the management goal, we calculated the conditions that would increase juvenile survival, adult survival, and a reduction in toxicological effects. The same process in this example should be applicable to the inclusion of multiple pesticides and to more descriptive population models such as those describing metapopulations. Integr Environ Assess Manag 2019;00:1-15. © 2019 SETAC.

Ecosystem Resilience on Human Terms.

Linked socioecological systems consist of economies in societies in nature and make explicit the relationship between the natural environment and human well-being using the language of ecosystem services. A growth-based economy within a constrained biophysical planet (e.g., human activities) has led to a need for ecosystem resilience. Valuation of ecosystem services using the language of economics appears insufficient in the face of human activity. All ecosystems are resilient but will demonstrate that resilience in unexpected and potentially unwanted ways, particularly as human pressures and influences lead to tipping points of extinction (e.g., complete die-off of coral reefs) in these linked socioecological systems. Structured approaches for evaluating the risks, benefits, and impacts of human activities exist but are not effectively applied and when applied, focus on downstream outcomes rather than on upstream actions (e.g., responding to climate change impacts rather than addressing causes of climate change). Ecosystem resilience in the face of unprecedented environmental challenges may not result in the hoped-for set of ecosystem services. Integr Environ Assess Manag 2018;14:598-600. © 2018 SETAC.

Results of a national survey of high-frequency fish consumers in the United States.

Exposure to contaminants in fish may be associated with adverse health outcomes even as fish consumption is generally considered beneficial. Risk assessments conducted to support regulatory analyses rely on quantitative fish consumption estimates. Here we report the results of a national survey of high-frequency fish consumers (n = 2099) based on a survey population statistically representative of ~17.6 million U.S. individuals consuming three or more fish meals per week. The survey was conducted during 2013 using an on-line survey instrument. Total fish consumption averaged 111g/day from market, restaurant and self-caught sources. Depending on the season, the incidence of individuals reporting consumption of self-caught species ranged between 10-12% of our high-frequency fish consuming demographic, averaging approximately 30g/day and comprising 23% of total fish consumption from all sources of fish. Recreational or self-caught consumption rates vary regionally and are poorly understood, particularly for high-frequency consumers, making it difficult to support national-scale assessments. A divergence between sport-fishing and harvesting of fish as a food-staple is apparent in survey results given differences in consumption patterns with income and education. Highest consumption rates were reported for low income respondents more likely to harvest fish as a food staple. By contrast, the incidence of self-caught fish consumption was higher with income and education although overall consumption rates were lower. Regional differences were evident, with respondents from the East-South Central and New England regions reporting lowest consumption rates from self-caught fish on the order of 12-16g/day and those from Mountain, Pacific and Mid-Atlantic regions reporting highest rates ranging from 44 to 59g/day. Respondent-specific consumption rates together with national-level data on fish tissue concentrations of PCBs, MeHg, and PFOS suggest that 10-58% of respondents reporting self-caught fish consumption are exposed to concentrations of these contaminants that exceed threshold levels for health effects based on a target hazard index of one, representing 2.3M to 19M individuals. The results of this nationwide survey of high-frequency fish consumers highlights regional and demographic differences in self-caught and total fish consumption useful for policy analysis with implications for distributional differences in potential health impacts in the context of both contaminant exposures as well as protective effects.

Spatially explicit bioaccumulation modeling in aquatic environments: Results from 2 demonstration sites.

Bioaccumulation models quantify the relationship between sediment and water exposure concentrations and resulting tissue levels of chemicals in aquatic organisms and represent a key link in the suite of tools used to support decision making at contaminated sediment sites. Predicted concentrations in the aquatic food web provide exposure estimates for human health and ecological risk assessments, which, in turn, provide risk-based frameworks for evaluating potential remedial activities and other management alternatives based on the fish consumption pathway. Despite the widespread use of bioaccumulation models to support remedial decision making, concerns remain about the predictive power of these models. A review of the available literature finds the increased mathematical complexity of typical bioaccumulation model applications is not matched by the deterministic exposure concentrations used to drive the models. We tested a spatially explicit exposure model (FishRand) at 2 nominally contaminated sites and compared results to estimates of bioaccumulation based on conventional, nonspatial techniques, and monitoring data. Differences in predicted fish tissue concentrations across applications were evident, although these demonstration sites were only mildly contaminated and would not warrant management actions on the basis of fish consumption. Nonetheless, predicted tissue concentrations based on the spatially explicit exposure characterization consistently outperformed conventional, nonspatial techniques across a variety of model performance metrics. These results demonstrate the improved predictive power as well as greater flexibility in evaluating the impacts of food web exposure and fish foraging behavior in a heterogeneous exposure environment. Integr Environ Assess Manag 2017;13:1023-1037. © 2017 SETAC.

Ecosystem services in risk assessment and management.

The ecosystem services (ES) concept holds much promise for environmental decision making. Even so, the concept has yet to gain full traction in the decisions and policies of environmental agencies in the United States, Europe, and elsewhere. In this paper we examine the opportunities for and implications of including ES in risk assessments and the risk management decisions that they inform. We assert that use of ES will: 1) lead to more comprehensive environmental protection; 2) help to articulate the benefits of environmental decisions, policies, and actions; 3) better inform the derivation of environmental quality standards; 4) enable integration of human health and ecological risk assessment; and 5) facilitate horizontal integration of policies, regulations, and programs. We provide the technical basis and supporting rationale for each assertion, relying on examples taken from experiences in the United States and European Union. Specific recommendations are offered for use of ES in risk assessment and risk management, and issues and challenges to advancing use of ES are described together with some of the science needed to improve the value of the ES concept to environmental protection. Integr Environ Assess Manag 2017;13:62-73. © 2016 SETAC.

Exposure to Mixtures of Metals and Neurodevelopmental Outcomes: A Multidisciplinary Review Using an Adverse Outcome Pathway Framework.

Current risk assessment guidance calls for an individual chemical-by-chemical approach that fails to capture potential interactive effects of exposure to environmental mixtures and genetic variability. We conducted a review of the literature on relationships between prenatal and early life exposure to mixtures of lead (Pb), arsenic (As), cadmium (Cd), and manganese (Mn) with neurodevelopmental outcomes. We then used an adverse outcome pathway (AOP) framework to integrate lines of evidence from multiple disciplines based on evolving guidance developed by the Organization for Economic Cooperation and Development (OECD). Toxicological evidence suggests a greater than additive effect of combined exposures to As-Pb-Cd and to Mn with any other metal, and several epidemiologic studies also suggest synergistic effects from binary combinations of Pb-As, Pb-Cd, and Pb-Mn. The exposure levels reported in these epidemiologic studies largely fall at the high-end (e.g., 95th percentile) of biomonitoring data from the National Health and Nutrition Examination Survey (NHANES), suggesting a small but significant potential for high-end exposures. This review integrates multiple data sources using an AOP framework and provides an initial application of the OECD guidance in the context of potential neurodevelopmental toxicity of several metals, recognizing the evolving nature of regulatory interpretation and acceptance.

A Systematic Review of Carcinogenic Outcomes and Potential Mechanisms from Exposure to 2,4-D and MCPA in the Environment.

Chlorophenoxy compounds, particularly 2,4-dichlorophenoxyacetic acid (2,4-D) and 4-chloro-2-methylphenoxy)acetic acid (MCPA), are amongst the most widely used herbicides in the United States for both agricultural and residential applications. Epidemiologic studies suggest that exposure to 2,4-D and MCPA may be associated with increased risk non-Hodgkins lymphoma (NHL), Hodgkin's disease (HD), leukemia, and soft-tissue sarcoma (STS). Toxicological studies in rodents show no evidence of carcinogenicity, and regulatory agencies worldwide consider chlorophenoxies as not likely to be carcinogenic or unclassifiable as to carcinogenicity. This systematic review assembles the available data to evaluate epidemiologic, toxicological, pharmacokinetic, exposure, and biomonitoring studies with respect to key cellular events noted in disease etiology and how those relate to hypothesized modes of action for these constituents to determine the plausibility of an association between exposure to environmentally relevant concentrations of 2,4-D and MCPA and lymphohematopoietic cancers. The combined evidence does not support a genotoxic mode of action. Although plausible hypotheses for other carcinogenic modes of action exist, a comparison of biomonitoring data to oral equivalent doses calculated from bioassay data shows that environmental exposures are not sufficient to support a causal relationship. Genetic polymorphisms exist that are known to increase the risk of developing NHL. The potential interaction between these polymorphisms and exposures to chlorophenoxy compounds, particularly in occupational settings, is largely unknown.

Public health impacts of secondary particulate formation from aromatic hydrocarbons in gasoline.

BACKGROUND: Aromatic hydrocarbons emitted from gasoline-powered vehicles contribute to the formation of secondary organic aerosol (SOA), which increases the atmospheric mass concentration of fine particles (PM2.5). Here we estimate the public health burden associated with exposures to the subset of PM2.5 that originates from vehicle emissions of aromatics under business as usual conditions. METHODS: The PM2.5 contribution from gasoline aromatics is estimated using the Community Multiscale Air Quality (CMAQ) modeling system and the results are compared to ambient measurements from the literature. Marginal PM2.5 annualized concentration changes are used to calculate premature mortalities using concentration-response functions, with a value of mortality reduction approach used to monetize the social cost of mortality impacts. Morbidity impacts are qualitatively discussed. RESULTS: Modeled aromatic SOA concentrations from CMAQ fall short of ambient measurements by approximately a factor of two nationwide, with strong regional differences. After accounting for this model bias, the estimated public health impacts from exposure to PM2.5 originating from aromatic hydrocarbons in gasoline lead to a central estimate of approximately 3800 predicted premature mortalities nationwide, with estimates ranging from 1800 to over 4700 depending on the specific concentration-response function used. These impacts are associated with total social costs of $28.2B, and range from $13.6B to $34.9B in 2006$. CONCLUSIONS: These preliminary quantitative estimates indicate particulates from vehicular emissions of aromatic hydrocarbons demonstrate a nontrivial public health burden. The results provide a baseline from which to evaluate potential public health impacts of changes in gasoline composition.

Decision analytic strategies for integrating ecosystem services and risk assessment.

Ecosystem services as a concept and guiding principle are enjoying wide popularity and endorsement from high-level policy thinkers to industry as support for sustainability goals continue to grow. However, explicit incorporation of ecosystem services into decision making still lacks practical implementation at more local scales and faces significant regulatory and technical constraints. Risk assessment represents an example of a regulatory process for which guidance exists that makes it challenging to incorporate ecosystem service endpoints. Technical constraints exist in the quantification of the relationships between ecological functions and services and endpoints valued by humans, and the complexity of those interactions with respect to bundling and stacking. In addition, ecosystem services, by their very definition, represent an anthropogenic construct with no inherent ecological value, which, in practical terms, requires a far more inclusionary decision making process explicitly incorporating a greater diversity of stakeholder values. Despite these constraints, it is possible, given a commitment to sustainable decision making, to simplify the process based on strategic outcomes (e.g., identifying desired end-states in general terms). Decision analytic techniques provide a mechanism for evaluating tradeoffs across key ecosystem services valued by stakeholders and to develop criteria drawn from the entire spectrum of stakeholders in evaluating potential alternatives. This article highlights several examples of ways in which ecosystem service endpoints can be incorporated into the decision-making process.

Evaluation of the public health impacts of traffic congestion: a health risk assessment.

BACKGROUND: Traffic congestion is a significant issue in urban areas in the United States and around the world. Previous analyses have estimated the economic costs of congestion, related to fuel and time wasted, but few have quantified the public health impacts or determined how these impacts compare in magnitude to the economic costs. Moreover, the relative magnitudes of economic and public health impacts of congestion would be expected to vary significantly across urban areas, as a function of road infrastructure, population density, and atmospheric conditions influencing pollutant formation, but this variability has not been explored. METHODS: In this study, we evaluate the public health impacts of ambient exposures to fine particulate matter (PM2.5) concentrations associated with a business-as-usual scenario of predicted traffic congestion. We evaluate 83 individual urban areas using traffic demand models to estimate the degree of congestion in each area from 2000 to 2030. We link traffic volume and speed data with the MOBILE6 model to characterize emissions of PM2.5 and particle precursors attributable to congestion, and we use a source-receptor matrix to evaluate the impact of these emissions on ambient PM2.5 concentrations. Marginal concentration changes are related to a concentration-response function for mortality, with a value of statistical life approach used to monetize the impacts. RESULTS: We estimate that the monetized value of PM2.5-related mortality attributable to congestion in these 83 cities in 2000 was approximately $31 billion (2007 dollars), as compared with a value of time and fuel wasted of $60 billion. In future years, the economic impacts grow (to over $100 billion in 2030) while the public health impacts decrease to $13 billion in 2020 before increasing to $17 billion in 2030, given increasing population and congestion but lower emissions per vehicle. Across cities and years, the public health impacts range from more than an order of magnitude less to in excess of the economic impacts. CONCLUSIONS: Our analyses indicate that the public health impacts of congestion may be significant enough in magnitude, at least in some urban areas, to be considered in future evaluations of the benefits of policies to mitigate congestion.

Evaluation of sources of uncertainty in risk assessments conducted for the US Army using a case study approach.

We identify, categorize, and score sources of uncertainty in human health and ecological risk assessments conducted for several US Army sites to identify better analytical practices and opportunities for targeted research to improve risk estimates. The reviewed assessments are from reports completed within the past 8 y and were obtained from the US Army Environmental Technical Information Center (ETIC) at Aberdeen Proving Ground, Maryland, USA. Most of the risk assessments incorporated only qualitative uncertainty analysis to demonstrate the conservatism of selected data and predictive models. Food chain transfer (e.g., concentrations of contaminants across trophic levels) dominated quantifiable sources of uncertainty across the risk assessments evaluated. Factors related to dermal exposures ranked high for human health, and effects assessment for ecological endpoints.

Estimation of fugitive lead emission rates from secondary lead facilities using hierarchical Bayesian models.

Fugitive emissions from secondary lead recovery facilities are difficult to estimate and can vary significantly from site to site. A methodology is presented for estimating fugitive emissions using back inference from observed ambient concentrations at nearby monitors, in conjunction with an atmospheric transport and dispersion model. Observed concentrations are regressed against unit source-monitor transfer terms computed by the model, and the fitted parameters of the regression equation include the background ambient lead concentration, the fugitive lead emission rate, and (when stack emissions are assumed to be unknown) the stack lead emission rate. The methodology is implemented at three sites, one each in Florida, Texas, and New York. A hierarchical Bayesian method is used to estimate the parameters of the model, allowing inferences to be made for both site-specific values and multisite (national) distributions of fugitive emissions and background concentrations. Informed prior distributions must be specified for the background lead concentrations and for fugitive and stack emission rates in order to obtain stable estimates. Sensitivity analyses with alternative priors indicate that posterior estimates of background concentrations and fugitive emission rates are relatively insensitive to the assumed priors, although estimated stack emission rates can vary with alternative priors, especially for the New York facility, where the stack emission rate is highly uncertain and poorly resolved by the model. The fugitive lead emission rates estimated for the sites are comparable to, or in some cases (especially Texas and New York) likely larger than the stack emissions that are determined for these facilities. An aggregate predictive distribution is derived for the average fugitive lead emission rate from secondary lead smelting facilities, with a median value of 9.2 x 10(-7) g Pb/m2/sec, and a 90% credible interval from 2.1 x 10(-7)-5.3 x 10(-6) g Pb/m2/sec. This wide range reflects both the variation in fugitive lead emissions from site to site and the high degree of uncertainty resulting from an estimate based on only a very small sample of sites. As such, the primary contribution of this study is methodological, demonstrating how information from multiple sites can be combined and considered simultaneously for the estimation of fugitive emission rates, but recognizing that additional sites must be included to obtain a more precise characterization.

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.

The use of spatial modeling in an aquatic food web to estimate exposure and risk.

This paper quantitatively evaluates interactions among foraging behavior, habitat preferences, site characteristics and the spatial distribution of contaminants in estimating PCB exposure concentrations for winter flounder at a hypothetical open water dredged material disposal site in the coastal waters of New York and New Jersey (NY-NJ). The models implemented in this study include a spatial submodel to account for spatial and temporal characteristics of fish exposure and a probabilistic adaptation of the Gobas bioaccumulation model to account for temporal variation in concentrations of polychlorinated biphenyls (PCBs) in sediment and water. We estimated the geographic distribution of an offshore winter flounder subpopulation based on species biology, including such variables as foraging area, habitat size, disposal site size and migration characteristics. We incorporated these variables together with an estimate of differential attraction to a management site within a spatially explicit model to assess the range of expected PCB exposures to a winter flounder population. The output of this modeling effort, flounder PCB tissue concentrations, provides exposure point concentrations for estimates of human health risk through ingestion of locally caught flounder. The risks obtained for the spatially non-explicit case are as much as one order of magnitude higher than those obtained after incorporating spatial and temporal characteristics of winter flounder foraging and seasonal migration. Incorporating spatial and temporal variables in food chain models can help support sediment management decisions by providing a quantitative expression of the confidence in risk estimates.