Process-Level Representation of Organic Aerosols in a Regional Climate Model (WRF-Chem): Processes, Parameterizations, and Predictions for GoAmazon

Charles He, Kelsey Bilsback, ManishKumar Shrivastava, Rahul Zaveri, Christopher Cappa, John Seinfeld, Jeffrey R. Pierce, SHANTANU JATHAR, Colorado State University

     Abstract Number: 361
     Working Group: Remote and Regional Atmospheric Aerosol

Abstract
Organic aerosol (OA) in the atmosphere exerts large impacts on air quality, human health and climate. However, OA predictions always bear large uncertainties, which likely stem from the limited representation of important physical and chemical processes in current 3D models. Prominently, these processes can include the multigenerational aging of precursors to form secondary OA (SOA), formation of highly oxygenated molecules from autoxidation reactions, phase state-limited gas/particle partitioning, heterogeneous oxidation, and particle-phase oligomerization. In previous work, we developed a computationally efficient SOA model (simpleSOM-MOSAIC) to simulate these processes within a kinetic framework. In this study, we integrated simpleSOM-MOSAIC into a regional climate model (WRF-Chem) to investigate the impact of process-level modeling on OA formation and evolution, utilizing the GoAmazon campaign as a case study. The base model, including all kinetic processes, was able to capture the elevated concentration of the OA in the downwind plume of Manaus, and ongoing work will compare model predictions with measurements along a flight track crossing the plume. Monoterpenes remained the primary contributor to SOA formation (>90%) in all simulations due to large emissions and high SOA mass yields. Individual process contributions suggested that the semi-solid phase state reduced SOA formation by 5-15% due to slowed partitioning, compared to instantaneous equilibrium; heterogeneous oxidation reduced SOA formation by 5-10% through fragmentation and evaporation; and oligomerization increased SOA formation by 10-15% through shifts in gas/particle equilibrium, resulting in an oligomer fraction of 20%. Thus, these processes had substantial impacts on the SOA burden. The model can also predict SOA O:C ratio, evolution of the particle size distribution, and the volatility distribution. Overall, this study advocates for the kinetic simulation of SOA-governing processes for improved prediction of its concentration and properties and assessment of its environmental and climate impacts.