Login / Signup

Strategies for refinement of occupational inhalation exposure evaluation in the EPA TSCA risk evaluation process.

Heather N LynchLaura HallettClaire M HamajiAndrew Maier
Published in: Toxicology and industrial health (2023)
The focus on occupational exposures in the first published risk evaluations of existing chemicals by the Environmental Protection Agency (EPA) under the amended Toxic Substances Control Act (TSCA) puts a welcome spotlight on protecting the health of workers in the United States. Because new, fit-for-purpose occupational exposure assessment methodologies were developed by EPA, the objective of this analysis was to evaluate these methodologies in light of other existing occupational risk assessment frameworks. We focused our analysis on three chlorinated chemicals (methylene chloride, carbon tetrachloride, perchloroethylene). The EPA's methods were evaluated relative to peer-reviewed and professional organizations' guidelines for conducting site- and facility-based exposure assessment. Analyses of several key phases in the EPA approach were conducted to evaluate the effect of alternative approaches on exposure estimates. The revised exposure estimates using these alternative approaches yielded substantially different exposure estimates from those in the TSCA risk evaluations for these chemicals. The results also demonstrated the importance of utilizing a tiered approach to exposure estimation that includes collecting qualitative data, defining similar exposure groups, and integrating well-parameterized models with empirical data. These approaches aid in preventing mischaracterization of exposures and generating exposure estimates representative of current industrial practices. Collaboration among industry, EPA, and other government agencies to develop a harmonized approach to exposure assessment would improve the methodological rigor of, and increase stakeholder confidence in, the results of TSCA risk evaluations.
Keyphrases
  • healthcare
  • primary care
  • heavy metals
  • wastewater treatment
  • mental health
  • machine learning
  • social media
  • data analysis