A Process-Level 3D Atmospheric Model for Secondary Organic Aerosol: Model Development and Applications to the GoAmazon Field Campaign
Abstract
Secondary organic aerosol (SOA), which arises from the oxidation of volatile organic compounds (VOCs), has important implications for climate, air quality, and human health. SOA processes are often simplified in models to improve computational efficiency; however, this limits the ability of models to predict key aerosol properties accurately (e.g., mass, size, composition). Recently, we developed a computationally efficient process-level model called simpleSOM-MOSAIC that simulates the oxidation chemistry, thermodynamics, and microphysics of SOA. In previous work, we used simpleSOM-MOSAIC, in box-model form, to simulate -pinene photooxidation in environmental chambers using data from chamber experiments at the California Institute of Technology. We found that the model could reproduce SOA mass yields, O:C ratios, and volatility distributions across various conditions. To further expand the utility of simpleSOM-MOSAIC, we are integrating our process-level model for SOA into the WRF-Chem 3D atmospheric model. The updated model will include (1) multigenerational gas-phase chemistry for a set of key precursors (e.g., monoterpenes, aromatics, and IVOCs), (2) phase-state-influenced kinetic gas/particle partitioning, (3) heterogeneous chemistry, (4) oligomerization reactions, and (5) corrections for chamber experiment artifacts. We plan to use the updated version of WRF-Chem to better understand the contribution of aerosol precursors and processes to SOA formation during the GoAmazon campaign, with a specific focus on aerosol phase state. GoAmazon is of particular interest for SOA formation, because the region is influenced by emissions from both anthropogenic and biogenic sources. We plan to make our model publicly available and anticipate that our implementation of simpleSOM-MOSAIC in WRF-Chem will lead to a better understanding of in-situ SOA data across a variety of projects and applications.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFM.A15F1690B