Secondary organic aerosol formation via multiphase reaction of hydrocarbons in urban atmospheres using CAMx integrated with the UNIPAR model

The prediction of secondary organic aerosol (SOA) on regional scales is traditionally performed by using gas-particle partitioning models. In the presence of inorganic salted wet aerosols, aqueous reactions of semivolatile organic compounds can also significantly contribute to SOA formation. The UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model utilizes the explicit gas mechanism to better predict SOA formation from multiphase reactions of hydrocarbons. In this work, the UNIPAR model was incorporated with the Comprehensive Air Quality Model with Extensions (CAMx) to predict the ambient concentration of organic matter (OM) in urban atmospheres during the Korean-United States Air Quality (2016 KORUS-AQ) campaign. The SOA mass predicted with CAMx-UNIPAR changed with varying levels of humidity and emissions and in turn has the potential to improve the accuracy of OM simulations. CAMx-UNIPAR significantly improved the simulation of SOA formation under the wet condition, which often occurred during the KORUS-AQ campaign, through the consideration of aqueous reactions of reactive organic species and gas-aqueous partitioning. The contribution of aromatic SOA to total OM was significant during the low-level transport/haze period (24-31 May 2016) because aromatic oxygenated products are hydrophilic and reactive in aqueous aerosols. The OM mass predicted with CAMx-UNIPAR was compared with that predicted with CAMx integrated with the conventional two-product model (SOAP). Based on estimated statistical parameters to predict OM mass, the performance of CAMx-UNIPAR was noticeably better than that of the conventional CAMx model, although both SOA models underestimated OM compared to observed values, possibly due to missing precursor hydrocarbons such as sesquiterpenes, alkanes, and intermediate volatile organic compounds (VOCs). The CAMx-UNIPAR simulation suggested that in the urban areas of South Korea, terpene and anthropogenic emissions significantly contribute to SOA formation while isoprene SOA minimally impacts SOA formation.

Automated summary

The UNIPAR model was incorporated with the CAMx model to predict the concentration of organic matter in urban atmospheres during the KORUS-AQ campaign. The simulation results showed that considering aqueous reactions can significantly improve the prediction of SOA formation under wet conditions. Aromatic SOA contributed significantly to the total OM during the low-level transport/haze period. The performance of CAMx-UNIPAR was better than that of the conventional CAMx model, although both models underestimated the observed OM.