An overview of human exposure modeling activities at the USEPA's National Exposure Research Laboratory.

The computational modeling of human exposure to environmental pollutants is one of the primary activities of the US Environmental Protection Agency (USEPA)s National Exposure Research Laboratory (NERL). Assessment of human exposures is a critical part of the overall risk assessment paradigm. In exposure assessment, we analyze the source-to-dose sequence of processes, in which pollutants are released from sources into the environment, where they may move through multiple environmental media, and to human receptors via multiple pathways. Exposure occurs at the environment-human interface, where pollutants are contacted in the course of human activities. Exposure may result in a dose, by which chemicals enter the body through multiple portals of entry, primarily inhalation, ingestion, and dermal absorption. Within the body, absorbed pollutants are distributed to, metabolized within, and eliminated from various organs and tissues, where they may cause toxicologic responses or adverse health effects. The NERL's modeling efforts are directed at improving our understanding of this sequence of processes, by characterizing the various factors influencing exposures and dose, and their associated variabilities and uncertainties. Modeling at the NERL is one of three essential programmatic elements, along with measurements and methods development. These are pursued interactively to advance our understanding of exposure-related processes. Exposure models are developed and run using the best currently available measurement data to simulate and predict population exposure and dose distributions, and to identify the most important factors and their variabilities and uncertainties. This knowledge is then used to guide the development of improved methods and measurements needed to obtain better data to improve the assessment and reduce critical uncertainties. These models and measurement results are tools that can be used in risk assessments and in risk management decisions in order to reduce harmful exposures. Current areas of the NERL's exposure modeling emphasis include: Pollutant concentrations in ambient (outdoor) air using the Third Generation Air Quality Modeling System's Community Multiscale Air Quality model (Models-3/CMAQ); Air flow and pollutant concentrations at local and microenvironmental scales using computational fluid dynamics (CFD); Human inhalation exposure to airborne particulate matter, air toxics, and multipathway exposure to pesticides, using the Stochastic Human Exposure and Dose Simulation (SHEDS) model; Human and ecological exposure and risk assessments of hazardous waste sites using Framework for Risk Analysis in Multimedia Environmental Systems--Multimedia, Multipathway, Multireceptor Risk Assessment (FRAMES-3MRA), one of many software programs available from the NERL's Center for Exposure Assessment Modeling (CEAM); Physiologically based pharmacokinetic (PBPK) modeling of pesticides and volatile organic compounds (VOCs) in the Exposure-Related Dose-Estimating Model (ERDEM). A brief historical overview of the NERL's evolution of human exposure models is presented, with examples of the present state-of-the-science represented by SHEDS and FRAMES-3MRA.

A modeling framework for estimating children's residential exposure and dose to chlorpyrifos via dermal residue contact and nondietary ingestion.

To help address the Food Quality Protection Act of 1996, a physically based probabilistic model has been developed to quantify and analyze dermal and nondietary ingestion exposure and dose to pesticides. The Residential Stochastic Human Exposure and Dose Simulation Model for Pesticides (Residential-SHEDS) simulates the exposures and doses of children contacting residues on surfaces in treated residences and on turf in treated residential yards. The simulations combine sequential time-location-activity information from children's diaries with microlevel videotaped activity data, probability distributions of measured surface residues and exposure factors, and pharmacokinetic rate constants. Model outputs include individual profiles and population statistics for daily dermal loading, mass in the blood compartment, ingested residue via nondietary objects, and mass of eliminated metabolite, as well as contributions from various routes, pathways, and media. To illustrate the capabilities of the model framework, we applied Residential-SHEDS to estimate children's residential exposure and dose to chlorpyrifos for 12 exposure scenarios: 2 age groups (0-4 and 5-9 years); 2 indoor pesticide application methods (broadcast and crack and crevice); and 3 postindoor application time periods (< 1, 1-7, and 8-30 days). Independent residential turf applications (liquid or granular) were included in each of these scenarios. Despite the current data limitations and model assumptions, the case study predicts exposure and dose estimates that compare well to measurements in the published literature, and provides insights to the relative importance of exposure scenarios and pathways.

Modeling indoor air concentrations near emission sources in imperfectly mixed rooms.

Assessments of exposure to indoor air pollutants usually employ spatially well-mixed models which assume homogeneous concentrations throughout a building or room. However, practical experience and experimental data indicate that concentrations are not uniform in rooms containing point sources of emissions; concentrations tend to be greater in close proximity to the source than they are further from it. This phenomenon could account for the observation that "personal air" monitors frequently yield higher concentrations than nearby microenvironmental monitors (i.e., the so-called "personal cloud" effect). In this project, we systematically studied the concentrations of a tracer gas at various distances from its emission source in a controlled-environment, room-size chamber under a variety of ventilation conditions. Measured concentrations in the proximity of the source deviated significantly above the predictions of a conventional well-mixed single-compartment mass balance model. The deviation was found to be a function of distance from the source and total room air flow rate. At typical air flow rates, the average concentration at arm's length (approximately 0.4 meters) from the source exceeds the theoretical well-mixed concentration by a ratio of about 2:1. However, this ratio is not constant; the monitored concentration appears to vary randomly from near the theoretical value to several times above it. Concentration data were fitted to a two-compartment model with the source located in a small virtual compartment within the room compartment. These two compartments were linked with a stochastic air transfer rate parameter. The resulting model provides a more realistic simulation of exposure concentrations than does the well-mixed model for assessing exposure to emissions from active sources. Parameter values are presented for using the enhanced model in a variety of typical situations.