Abstract View
Air Quality Impact During and After the COVID-19 Lockdown in Global Cities
Shaojun Zhang, Jiajun Gu, K. Max Zhang, BO YANG, Yuejie Wang, Yifan Wen, Ye Wu, Jiming Hao, Cornell University
Abstract Number: 610
Working Group: Urban Aerosols
Abstract
The pandemic of coronavirus disease 2019 (COVID-19) resulted in the stringent lockdown worldwide to reduce the infection rate. We adopted a fixed-meteorology technique based on machine learning techniques to analyze the air quality impacts from the COVID-19 lockdown for 10 metropolitan areas globally. Compared with the without lockdown scenario, we estimated that the lockdown reduced ambient NO2 concentrations by 36% to 53% during the most restrictive periods with the Level-1 public health emergence response control actions in China. The traffic analysis during the same periods confirmed that traffic emission changes were a major factor in the substantial NO2 reduction but also associated with increased O3 concentrations. In China, the lockdown also reduced PM2.5 concentrations, though heavy pollution episodes occurred during certain days due to the enhanced formation of secondary aerosol. The analysis implies that the air pollution levels are likely to rebound quickly as the as the economy reopens.