United States Environmental Protection Agency (USEPA) researchers are developing a strategy for high-throughput (HT) exposure-based prioritization of chemicals under the ExpoCast program. These novel modeling approaches for evaluating chemicals based on their potential for biologically relevant human exposures will inform toxicity testing and prioritization for chemical risk assessment. Based on probabilistic methods and algorithms developed for The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals (SHEDS-MM), a new mechanistic modeling approach has been developed to accommodate high-throughput (HT) assessment of exposure potential. In this SHEDS-HT model, the residential and dietary modules of SHEDS-MM have been operationally modified to reduce the user burden, input data demands, and run times of the higher-tier model, while maintaining critical features and inputs that influence exposure. The model has been implemented in R; the modeling framework links chemicals to consumer product categories or food groups (and thus exposure scenarios) to predict HT exposures and intake doses. Initially, SHEDS-HT has been applied to 2507 organic chemicals associated with consumer products and agricultural pesticides. These evaluations employ data from recent USEPA efforts to characterize usage (prevalence, frequency, and magnitude), chemical composition, and exposure scenarios for a wide range of consumer products. In modeling indirect exposures from near-field sources, SHEDS-HT employs a fugacity-based module to estimate concentrations in indoor environmental media. The concentration estimates, along with relevant exposure factors and human activity data, are then used by the model to rapidly generate probabilistic population distributions of near-field indirect exposures via dermal, nondietary ingestion, and inhalation pathways. Pathway-specific estimates of near-field direct exposures from consumer products are also modeled. Population dietary exposures for a variety of chemicals found in foods are combined with the corresponding chemical-specific near-field exposure predictions to produce aggregate population exposure estimates. The estimated intake dose rates (mg/kg/day) for the 2507 chemical case-study spanned 13 orders of magnitude. SHEDS-HT successfully reproduced the pathway-specific exposure results of the higher-tier SHEDS-MM for a case-study pesticide and produced median intake doses significantly correlated (p<0.0001, R2=0.39) with medians inferred using biomonitoring data for 39 chemicals from the National Health and Nutrition Examination Survey (NHANES). Based on the favorable performance of SHEDS-HT with respect to these initial evaluations, we believe this new tool will be useful for HT prediction of chemical exposure potential.

A major field study was conducted in Boise, Idaho, during the heating season of 1986 to 1987 as part of the Integrated Air Cancer Project. Filter samples were systematically collected in residences and in the ambient air across the community to characterize the particle-bound pollutants. The extractable organic matter (EOM) from the filter samples was apportioned to its source of origin, either residential wood combustion (RWC) or mobile sources (MS). Two composite samples, with apportioned contributions from RWC and MS, were prepared from the Boise ambient samples and tested for tumor-initiation potency. A comparative potency lung cancer risk estimate has been made based on the two ambient composite samples from this airshed. In addition, a microenvironmental exposure model was developed from the Boise data and from national survey data to estimate the exposure to EOM from RWC and MS. In this paper, the microenvironmental model is extrapolated to provide an estimate of the average annual exposure and dose in Boise to EOM from RWC and MS. The annual model considers actual pollutant levels in Boise, historical changes in RWC usage and meteorological dilution factors and the likely activities in the various microenvironmental zones and their resultant inhalation rates. Combined with the lifetime risk estimates, the average annual dose suggests a risk of about 4 x 10(-4) based upon the composite ambient samples. Despite the fact that RWC accounts for 73% of the EOM on an annual average basis, it accounts for only about 20% of the estimated lifetime risk.

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