You are here:
MODEL DEVELOPMENT - EXPOSURE MODELS
Impact/Purpose:
The overall goal of this task is to evaluate, refine, and disseminate a peer-reviewed state-of-the science probabilistic model for improving estimates of human exposure and dose to multimedia, multipathway pollutants. The primary objectives of this research are the following:
Evaluate and refine the dietary (food and drinking water) exposure module and incorporate it into the SHEDS-Multimedia code.
Evaluate and refine the residential fugacity-based source-to-concentration module and incorporate it into the SHEDS-Multimedia code.
Improve the simulation of longitudinal exposure.
Develop and evaluate procedures for modeling multiple pollutants simultaneously.
Complete the SHEDS-Multimedia version 3 (aggregate) model with interface and documentation; evaluate with available data sets.
Peer review, publish, and make available the SHEDS-Multimedia model and model components.
Description:
Humans are exposed to mixtures of chemicals from multiple pathways and routes. These exposures may result from a single event or may accumulate over time if multiple exposure events occur. The traditional approach of assessing risk from a single chemical and a single route of exposure does not provide a realistic description of exposures and the cumulative risks that result from real-world exposures. Risk assessments within EPA are now evolving toward "cumulative assessments" as mandated by legislation like the Food Quality Protection Act (FQPA) and the Safe Drinking Water Act (SDWA). However, there are considerable uncertainties associated with assessing aggregate exposures and cumulative risks. State-of-the-art predictive models can be used to reduce these uncertainties in describing the physical, chemical, and biological processes that lead to exposure and dose of chemical contaminants. Exposure models predict concentrations of pollants in environmental media as well as describing the activities that bring an individual into contact with the contaminated media.The goal of this research is to refine NERL's Stochastic Human Exposure and Dose Simulation (SHEDS) Model to improve both ease of use and provide additional modeling capabilities. Models development under this task addresses the narrow definition of cumulative risk as defined by FQPA, namely risk from mixtures of chemicals with a common "mode of action.
SHEDS is being developed as a state-of-the-science model to predict and better understand aggregate exposures and cumulative risks. Under this task a user-friendly, documented aggregate SHEDS-Multimedia version will be evaluated, refined, peer reviewed and disseminated. An improved source-to-concentration module will be developed that use fugacity principals to predict fate and transport of primary pollutants and that incorporates indoor chemistry algorithms to predict formation of secondary pollutants. A refined dietary module will be incorporated into the model. Procedures for estimating exposures to mixtures of chemicals and longitudinal exposures over time will be developed to provide inputs for cumulative risk assessments. In conjunction with other tasks, SHEDs and its modules (e.g., dietary module, fugacity module) will also be evaluated against data from field measurement studies (e.g., CTEPP, Jacksonville) and against estimates from other models.
The outcome of this research will be a state-of-the-science probabilistic modeling tool for assisting risk assessors and risk managers in regulatory decision-making when human exposure estimates are required beyond the screening level. The model and model components developed under this task will be applied in support of OPP risk assessment of pyrethroids and n-methyl-carbamates.