Exposure Modelling Approaches to Support Environmental Decision-Making in Multiple Contexts: A Review of Select Case Examples at the U.S. EPA
On this page:
Currently, jurisdictions and individuals are challenged to consider the full range of information required to manage and use chemicals in a way that protects and promotes public health. Research to apply and demonstrate approaches that leverage disparate information by combining both mechanistic and data-driven modeling to characterize human exposure to environmental stressors is critical for credible decision-making. For example, there are persistent environmental contaminants that are contributing to many human health outcomes, including lead (Pb) and perfluoroalkyl substances (PFAS). For Pb, much is known about its sources, and it has largely been eliminated from production of consumer goods in the U.S., but historical contamination still poses a human exposure risk. In contrast, despite some phase-out of some legacy PFAS, alternate chemicals within the same class of compounds are being introduced into product streams. We are conducting applied research on these two high priority chemicals using the latest modeling techniques to inform decisions at the national, regional, and local scale. EPA’s Stochastic Human Exposure and Dose Simulation model for Pb (SHEDS-Pb) — a probabilistic, mechanistic human exposure model combined with a Pb deterministic biokinetic and uptake model — was developed and applied to estimate aggregate children’s exposures and blood lead levels (BLL) from drinking water, dust, and soil to support EPA regulatory Pb decisions. On a regional level, we developed an advanced geospatial statistical approach using children’s BLL to identify high Pb exposure locations at the census tract scale for two U.S. states. The resolution of results at this scale can help the most impacted communities target Pb actions for public health protection. For PFAS, limited existing fish tissue PFAS occurrence data, publicly available geospatial data, and census information were used to develop predictive models to identify potential areas of PFAS contamination. These findings are informing additional fish sampling in the Northwestern U.S. that will help EPA Regional partners better focus efforts to reduce human exposure to PFAS in impacted communities. These examples demonstrate our commitment to using state-of-the-science information and exposure tools to: characterize the scope and magnitude of the most important environmental health problems; develop new information to fill the most critical gaps; and advance methods and tools to inform public policy.