Process-Level Quantification on Opposite PM2.5 Changes during the COVID-19 Lockdown over the North China Plain

Abstract

By using an improved process-level quantification method implemented in the WRF-Chem model, we provide a quantitative analysis on contribution of each physical/chemical process to PM_2.5 change from before to during the COVID-19 lockdown and further identify a dominant process responsible for inverse PM_2.5 changes over the southern and northern North China Plain (NCP). From before to during the lockdown period, the PM_2.5 concentration over the southern NCP decreased by 61.0 μg m^–3; a weakened aerosol chemistry production process mainly resulting from emission mitigation of precursors was identified to be the leading process for the PM_2.5 decrease. However, the northern NCP suffered from an unexpected PM_2.5 increase of 10.0 μg m^–3, which was primarily attributed to a weakened advection dilution process induced by decreased wind speed. The improved process analysis method, superior to the traditional one, can be applied to any two periods rather than two instantaneous time points, and therefore it exerts a new contribution to understand the pollution evolution mechanism from a process-level quantitative perspective.