Assessment of Sectoral NO<sub><i>x</i></sub> Emission Reductions During COVID‐19 Lockdown Using Combined Satellite and Surface Observations and Source‐Oriented Model Simulations
Mingjie Kang, Jie Zhang, Zhen Cheng, Song Guo, Fangcheng Su, Jianlin Hu, Hongliang Zhang, Qi Ying
Abstract
Abstract Large emission reductions of anthropogenic nitrogen oxides (NO x ) due to the coronavirus disease 2019 (COVID‐19) lockdown policies in China have been extensively reported since the outbreak, while assessments of sectoral emission changes during that period are still limited. In this study, a source‐oriented community multiscale air quality (CMAQ) model was applied to quantify NO 2 concentrations from major emission sectors. A new optimization approach was employed to obtain the sectorial emission reductions using satellite and ground‐level observations as constraints. The optimized emissions significantly improved the model performance of NO 2 during the lockdown period. February NO x emission changes varied with regions and sectors, with relatively larger reductions in transportation (286.6 kt) and industrial sources (260.1 kt). The maximum amount of NO x emission reduction occurred in the North China Plain (230.6 kt). Our work presents a quick and reliable technique for assessing sector‐specific emission changes due to short‐term emission control policies.