In January 2020, anthropogenic emissions in Northeast Asia reduced due to the COVID-19 outbreak. When outdoor activities of the public were limited, PM2.5 concentrations in China and South Korea between February and March 2020 reduced by − 16.8 μg/m3 and − 9.9 μg/m3 respectively, compared with the average over the previous three years. This study uses air quality modeling and observations over the past four years to separate the influence of reductions in anthropogenic emissions from meteorological changes and emission control policies on this PM2.5 concentration change. Here, we show that the impacts of anthropogenic pollution reduction on PM2.5 were found to be approximately − 16% in China and − 21% in South Korea, while those of meteorology and emission policies were − 7% and − 8% in China, and − 5% and − 4% in South Korea, respectively. These results show that the influence on PM2.5 concentration differs across time and region and according to meteorological conditions and emission control policies. Finally, the influence of reductions in anthropogenic emissions was greater than that of meteorological conditions and emission policies during COVID-19 period.
Abstract. 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.
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