Abstract

The prediction of Secondary Organic Aerosol (SOA) in 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 explicit gas chemistry to better predict SOA mass from multiphase reactions. 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 the CAMx-UNIPAR model changed with varying levels of humidity and emissions and in turn, has the potential to improve the accuracy of OM simulations. The CAMx-UNIPAR model 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 the CAMx-UNIPAR model was compared with that predicted with the CAMx model 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 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 VOCs. The CAMx-UNIPAR model 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.

Highlights

  • The formation of secondary organic aerosol (SOA) has gained substantial interest from researchers because of its important impact on climate change (IPCC, 2015;Seinfeld and Pandis, 2016), urban visibility (Chen et al, 2012;Ren et al, 2018), and human health (Requia et al, 2018)

  • The conventional SOA module in regional models has no feature for SOA formation via aqueous phase reactions of different oxygenated products formed from various HCs

  • The organic matter (OM) mass predicted with the CAMx-UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model was compared with the that predicted with the CAMx model integrated with the conventional two product model (Odum et al, 1996)

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Summary

Introduction

The formation of secondary organic aerosol (SOA) has gained substantial interest from researchers because of its important impact on climate change (IPCC, 2015;Seinfeld and Pandis, 2016), urban visibility (Chen et al, 2012;Ren et al, 2018), and human health (Requia et al, 2018). Aerosol phase Reaction (UNIPAR) model, which utilizes explicit gas chemistry to predict SOA mass based on multiphase reactions. During this campaign, inorganic salted aerosols present at four locations across three cities (Seoul, Deajeon, and 65 Gwangju) were wet for the majority of days due to high humidity levels during the night-time and humidity levels above the efflorescent humidity level during the daytime. Inorganic salted aerosols present at four locations across three cities (Seoul, Deajeon, and 65 Gwangju) were wet for the majority of days due to high humidity levels during the night-time and humidity levels above the efflorescent humidity level during the daytime In this way, field data accurately portrayed the importance of aqueous phase reactions to predict SOA burdens in ambient air. The organic matter (OM) mass predicted with the CAMx-UNIPAR model was compared with the that predicted with the CAMx model integrated with the conventional two product model (Odum et al, 1996)

Integration of UNIPAR with CAMx
Simulation domain and model configurations
Results and discussion
Impact of aqueous reactions on SOA mass
SOA compositions and spatial distribution
May – 12 June
Full Text
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