AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
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Simulation of SOA Formation from the Photooxidation of Gasoline in the Presence of NOx and Electrolytic Inorganic Aerosol
MYOSEON JANG, Chufan Zhou, Zechen Yu, Sanghee Han, University of Florida
Abstract Number: 500 Working Group: Aerosol Chemistry
Abstract The prediction of secondary organic aerosol (SOA) mass is complex due to variation and complexity in the atmospheric process of hydrocarbons under varying NOx, SO2, sunlight , humidity and temperature in ambient environments. Our laboratory’s recent efforts have improved the state-of-the science-art via the development of the UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model, which features the product stoichiometric coefficients (51 lumping groups) based on volatility (6 groups) and reactivity (8 groups) to consider their emerging chemistry in the aerosol phase. In the model, Glyoxal, methylglyoxal, and IEPOX, which are known to significantly contribute to SOA formation, are explicitly treated. The preexisting UNIPAR vastly improves the accuracy of SOA mass prediction for each precursor owing to the stoichiometric coefficient array set that is dynamically generated under varying NOx and aging conditions but specific to each precursor. The SOA model, however, needs simplification and unification to treat a variety of precursor hydrocarbons appeared in ambient air. In this study, UNIPAR is extended to the simulation of gasoline SOA that is attributed to various hydrocarbons to mimic SOA formation under urban environments. In UNIPAR extension, the model parameters, linked to partitioning of oxygenated organic species in multiphase and their reaction rate constants in aerosol (i.e. oligomerization in organic phase, acid-catalyzed reactions in inorganic aqueous phase, and organosulfate formation), are cohesive for various aromatic precursors. The dynamic stoichiometric coefficient array set, which changes by NOx and aging conditions, is also cohesive to various aromatic precursors in the extended UNIPAR. The consumption of aromatic precursors in gasoline is predicted by using Carbon Bond Mechanism (CB6) and integrated with UNIPAR to predict SOA mass. The feasibility of UNIPAR is demonstrated with chamber data (UF-APHOR), which produce SOA from the photooxidation of gasoline in the presence of electrolytic inorganic aerosol and NOx.