ACPD Atmospheric Chemistry and Physics Discussions ACPD Atmos. Chem. Phys. Discuss. 1680-7375 Göttingen, Germany 10.5194/acp-2020-760 Improvement of inorganic aerosol component in PM<sub>2.5</sub> by constraining aqueous-phase formation of sulfate in cloud with satellite retrievals: WRF-Chem simulations Sha Tong https://orcid.org/0000-0002-6490-387X 1 Ma Xiaoyan https://orcid.org/0000-0003-4485-8431 1 Wang Jun https://orcid.org/0000-0002-7334-0490 2 Tian Rong 1 Zhao Jianqi 1 Cao Fang 3 Zhang Yan-Lin https://orcid.org/0000-0002-8722-8635 3 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China Department of Chemical and Biochemical Engineering/Center for Global and Regional Environmental Research, The University of Iowa, Iowa City, IA, USA Yale–NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change (ILCEC)/Jiangsu Provincial Key Laboratory of Agricultural Meteorology, College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044, China 31 08 2020 2020 1 54 Copyright: © 2020 Tong Sha et al. 2020 This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ This article is available from https://acp.copernicus.org/preprints/acp-2020-760/ The full text article is available as a PDF file from https://acp.copernicus.org/preprints/acp-2020-760/acp-2020-760.pdf

<p>High concentrations of PM<sub>2.5</sub> in China have caused severe visibility degradation and health problem. However, it is still a big challenge to accurately predict PM<sub>2.5</sub> and its chemical components in the numerical model. In this study, we compared the inorganic aerosol components of PM<sub>2.5</sub> (sulfate, nitrate, and ammonium (SNA)) simulated by WRF-Chem with in-situ data during a heavy haze-fog event (November 2018) in Nanjing. The comparisons show that the model underestimates the sulfate concentrations by 81&thinsp;% and fails to reproduce the significant increase of sulfate concentrations from early morning to noon, which corresponds to the timing of fog dissipation, suggesting that the model underestimates the aqueous-phase formation of sulfate in clouds. In addition, the model overestimates both nitrate and ammonium concentrations by 184&thinsp;% and 57&thinsp;%, respectively. These ultimately result in the simulated SNA 77.2&thinsp;% higher than the observations. However, as the important aqueous-phase reactors, cloud water are simultaneously underestimated by the model. Therefore, the modeled cloud water was constrained based on the MODIS Liquid Water Path (LWP) observations. Results show that the simulation with MODIS-corrected cloud water amount increases the sulfate by a factor of 3, decreases NMB by 53.5&thinsp;%, and can reproduce its diurnal cycles, i.e. the peak concentration at noon. Also, the model absolute bias of nitrate decreases from 184&thinsp;% to 50&thinsp;%, especially for the nocturnal concentrations, which suggests the MODIS-constrained simulation improved the diurnal pattern. Although the simulated ammonium is still higher than the observation, corrected cloud water lead to the decrease of the modeled bias of SNA from 77.2&thinsp;% to 14.1&thinsp;%. The strong sensitivity of simulated SNA concentration to the cloud water provides an explanation for the bias of SNA simulation. Hence, the uncertainties of cloud water can lead to model bias in simulating SNA, and can be reduced by constraining the model with satellite observations.</p>

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