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Impacts of Lockdown Policy on Air Quality in Chinese Cities on Different Economic Levels during the COVID-19 Pandemic (preprint)
researchsquare; 2023.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-2501769.v1
ABSTRACT
The sudden outbreak of the Corona Virus Disease 2019 (COVID-19) broke the stable trend of air quality improvement in Chinese cities due to the emergency response measures, such as the lockdown policy. In this study, 333 Chinese cities are divided into six levels by economic factors, such as first-tier, new first-tier, second-tier, third-tier, fourth-tier, and fifth-tier, and the time of each year was defined as pre-lockdown, lockdown and reopen periods. The results show that, during the pre-lockdown period, the concentrations of NO2 and PM2.5 decreased by 10.13% and 6.15%, respectively, compared with the same period averages in 2017–2019. The fifth-tier cities have the minimum reductions of NO2 and PM2.5. The lockdown policy has significantly improved the air quality in Chinese cities during the COVID-19 pandemic. The concentrations of NO2 and PM2.5 decreased by 42.38% and 29.34%, respectively, but the air quality of first-tier cities was least affected by lockdown. During the reopen period, the concentrations of NO2 and PM2.5 decreased by 14.28% and 25.71%, respectively, and the NO2 concentrations in each city are similar for the season. The NO2 and PM2.5 concentrations in 2020 without lockdown were estimated through a multivariate linear regression model. The actual values of both NO2 and PM2.5 concentrations during the lockdown period are lower than the projected values based on the 2017–2019 trend, again indicating that the lockdown policy influences their concentrations.
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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: Virus Diseases / COVID-19 Language: English Year: 2023 Document Type: Preprint

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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: Virus Diseases / COVID-19 Language: English Year: 2023 Document Type: Preprint