Articles | Volume 22, issue 19
https://doi.org/10.5194/acp-22-13183-2022
https://doi.org/10.5194/acp-22-13183-2022
Research article
 | 
14 Oct 2022
Research article |  | 14 Oct 2022

Four-dimensional variational assimilation for SO2 emission and its application around the COVID-19 lockdown in the spring 2020 over China

Yiwen Hu, Zengliang Zang, Xiaoyan Ma, Yi Li, Yanfei Liang, Wei You, Xiaobin Pan, and Zhijin Li

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Cited articles

Al-qaness, M. A. A., Fan, H., Ewees, A. A., Yousri, D., and Abd Elaziz, M.: Improved ANFIS model for forecasting Wuhan City Air Quality and analysis COVID-19 lockdown impacts on air quality, Environ. Res., 194, 110607, https://doi.org/10.1016/j.envres.2020.110607, 2021. 
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Chen, D., Liu, Z., Ban, J., and Chen, M.: The 2015 and 2016 wintertime air pollution in China: SO2 emission changes derived from a WRF-Chem/EnKF coupled data assimilation system , Atmos. Chem. Phys., 19, 8619–8650, https://doi.org/10.5194/acp-19-8619-2019, 2019. 
Chen, Y., Yang, K., Zhou, D., Qin, J., and Guo, X.: Improving the Noah Land Surface Model in Arid Regions with an Appropriate Parameterization of the Thermal Roughness Length, J. Hydrometeorol., 11, 995–1006, https://doi.org/10.1175/2010JHM1185.1, 2010. 
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Short summary
This study developed a four-dimensional variational assimilation (4DVAR) system based on WRF–Chem to optimise SO2 emissions. The 4DVAR system was applied to obtain the SO2 emissions during the early period of the COVID-19 pandemic over China. The results showed that the 4DVAR system effectively optimised emissions to describe the actual changes in SO2 emissions related to the COVID lockdown, and it can thus be used to improve the accuracy of forecasts.
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