For the best predictive power, large-scale atmospheric chemistry models should reflect the most current scientific understanding. However, bridging the molecular-level detail provided by laboratory and theoretical chemistry studies, and computationally limited large-scale atmospheric models, presents technical challenges. I will discuss our recent work developing a novel, graph theory-based, Automated Model Reduction approach (AMORE) and applying it to the gas-phase isoprene oxidation mechanism. The resulting reduced model, AMORE-Isoprene, performs favorably compared to existing isoprene oxidation models of similar size when tested against the full-sized mechanism and chamber data in the F0AM box model environment. AMORE-Isoprene has also been included in the new CMAQ chemical mechanism, CRACMM, resulting in improved simulations of ozone and formaldehyde compared to ambient observations.

Atmospheric chemistry, from lab to large-scale models: Bridging scales and managing complexity

Where thousands of chemistry professionals meet to share ideas and advance scientific and technical knowledge. Spring 2023 abstracts, posters, and presentations will launch at the end of March.

ACS Spring 2023

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.