Environmental fate assessors in the U.S. Environmental Protection Agency’s Office of Pollution Prevention and Toxics (EPA/OPPT) routinely use predictive models to make determinations on environmental fate and transport endpoints for new chemical substances. These determinations impact exposure estimates used for assessing potential risks to humans and environmental receptors. The role of environmental partitioning is pivotal in assessing the fate and transport of new chemicals in environmental media, such as soil, water, and air. Fate assessors in EPA/OPPT routinely use the in-house developed EPI Suite™ models. The specific module within EPI Suite™ that estimates partitioning of chemicals in different media is the steady-state Level III Fugacity Model, LEV3EPI™, adapted from Donald Mackay’s research group. The LEV3EPI™ model utilizes estimated inputs on an organic chemical’s physico-chemical (p-chem) characteristics, degradation rates, and bioaccumulative behavior. Outputs from this model are used with other modules in EPI Suite™, such as the STPWIN™ module. The STPWIN™ estimates the removal of an organic chemical from a sewage treatment plant (STP) by biodegradation, volatilization, and sorption during wastewater treatment. Collectively, the EPISuite™ fugacity-based model estimates on overall environmental persistence time are used with assessing the PBT potential of chemicals. This poster describes how LEV3EPI™ is used as a predictive platform for fugacity multi-media modeling of organic chemicals in EPA/OPPT’s exposure assessment process to inform persistence and removal in STPs: first how LEV3EPI™ calculates the necessary parameters used as inputs for the fugacity models, and how the outputs provide estimates of release and partitioning of organic chemicals to environmental media; second, showing ongoing developments of LEV3EPI™ and will focus on data flow between the p-chem estimation in EPI Suite™ and LEV3EPI™. Finally, two example outputs will be shown, which are representative of an internal evaluation performed on the complete datasets of two different chemical classes. The evaluation of the outputs from KOCWIN™ estimates on these chemical classes indicates more consistent results if the soil KOC value is based on the KOW/KOWWIN™ approach as opposed to the past default data flow of using the molecular connectivity index (MCI) based approach for determine KOC. The result of this data flow will be incorporated into a future update of EPI Suite™.

Use of EPI Suite™ fugacity model in assessing environmental fate

2019 Fall National Meeting

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