This project aims to improve chemical transport model predictions of wildfire smoke exposure by enhancing emissions inventories, updating chemical mechanisms, and applying machine learning–based data fusion.
Anaerobic digesters on California dairy farms can significantly reduce methane emissions with minimal impact on air quality. Modeling for the year 2050 in the San Joaquin Valley shows slight changes in PM2.5 and ozone levels, negligible health risks, and no effect on environmental justice disparities, supporting digesters as a low-risk GHG reduction strategy.