Multi-Day Photochemical Evolution of Organic Aerosol from Biomass Burning Emissions

Abstract

Biomass burning is an important source of primary and secondary organic aerosol (POA, SOA, and together, OA) to the atmosphere. The photochemical evolution of biomass burning OA, especially over long photochemical ages, is highly complex and there are large uncertainties in how this evolution is represented in models. Recently, Lim et al. (2019) performed and reported on photooxidation experiments of biomass burning emissions using a small environmental chamber (~150 L) to study the OA evolution over multiple equivalent days of photochemical aging. In this work, we use a kinetic, process-level model (SOM-TOMAS; Statistical Oxidation Model-TwO Moment Aerosol Sectional) to simulate the photochemical evolution of OA in 18 chamber experiments performed on emissions from 10 different fuels. A base version of the model was able to simulate the time-dependent evolution of the OA mass concentration and its oxygen-to-carbon ratio (O:C) at short photochemical ages (0.5 to 1 equivalent days). At longer photochemical ages (>1 equivalent day), the model exhibited poor skill in predicting the OA mass concentration and significantly underestimated the OA O:C. The OA after several equivalent days of photochemical aging was slightly dominated by SOA (57%, on average) with the remainder being POA (43%, on average). Semi-volatile organic compounds, oxygenated aromatics, and heterocyclics accounted for the majority (89%, on average) of the SOA formed. Experimental artifacts (i.e., particle and vapor wall losses) were found to be much more important in influencing the OA evolution than other processes (i.e., dilution, heterogeneous chemistry, and oligomerization reactions). Adjustments to the kinetic model seemed to improve model performance only marginally indicating that the model was missing precursors, chemical pathways, or both, especially to explain the observed enhancement in OA mass and O:C over longer photochemical ages. While far from ideal, this work contributes to a process-level understanding of biomass burning OA that is relevant for its extended evolution at regional and global scales.