2025 Theses Doctoral

Automated Model Reduction of Atmospheric Chemical Mechanisms

Wiser, Forwood Cloud

The atmospheric chemistry of volatile organic compounds (VOC) has a major influence onatmospheric pollutants and particle formation. Accurate modeling of this chemistry is essential for air quality models. Complete representations of VOC oxidation chemistry are far too large for spatiotemporal simulations of the atmosphere, necessitating reduced mechanisms.

This work details several new graph theory-based methods for mechanism reduction, optimization, and evaluation. Our newest algorithm, the Automated MOdel REduction 2.0 (AMORE 2.0), efficiently and accurately reduces VOC oxidation mechanisms to a desired size by removing, merging, and rerouting sections of the graph representation of the mechanism. This algorithm can reduce large mechanisms by over 90%, making them usable in atmospheric simulations. This work will improve our ability to accurately model the atmosphere, thereby supporting air quality management and advancing atmospheric chemical science.