Abstract

The novel coronavirus (COVID-19) pandemic has provided a distinct opportunity to explore the mechanisms by which human activities affect air quality and pollution emissions. We conduct a quasi-difference-in-differences (DID) analysis of the impacts of lockdown measures on air pollution during the first wave of the COVID-19 pandemic in China. Our study covers 367 cities from the beginning of the lockdown on 23 January 2020 until April 22, two weeks after the lockdown in the epicenter was lifted. Static and dynamic analysis of the average treatment effects on the treated is conducted for the air quality index (AQI) and six criteria pollutants. The results indicate that, first, on average, the AQI decreased by about 7%. However, it was still over the threshold set by the World Health Organization. Second, we detect heterogeneous changes in the level of different pollutants, which suggests heterogeneous impacts of the lockdown on human activities: carbon monoxide (CO) had the biggest drop, about 30%, and nitrogen dioxide (NO2) had the second-biggest drop, 20%. In contrast, ozone (O3) increased by 3.74% due to the changes in the NOx/VOCs caused by the decrease in NOx, the decrease of O3 titration, and particulate matter concentration. Third, air pollution levels rebounded immediately after the number of infections dropped, which indicates a swift recovery of human activities. This study provides insights into the implementation of environmental policies in China and other developing countries.

Highlights

  • At the end of 2019, an unusual coronavirus disease, eventually named COVID-19, was identified in Wuhan, China [1]

  • Our results indicate immense improvements, the air quality was still above the threshold set by the World Health Organization (WHO) and Chinese health standards

  • The decrease is likely attributed to two factors: the seasonal change caused by meteorological conditions and socio-economic factors such as the lockdown measures induced by the COVID-19 pandemic

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Summary

Introduction

At the end of 2019, an unusual coronavirus disease, eventually named COVID-19, was identified in Wuhan, China [1]. Most previous studies only cover a short period, which limits comprehensive interpretation on the shrinkage and on the rebound effect [10]. In this case, the rebound effect is of more concern since it captures the economic recovery from the deadly shock of COVID-19. Through dynamic analysis, we identify the varying impact of the lockdown on air quality, which facilitates our understanding of human responses to the epidemic. To the best of our knowledge, this is the first study that identifies the dynamic impacts of lockdown measures on the environment.

Datasets
Identification Strategy
The Average Effect on Air Pollution
Dynamic Impacts on Air Pollution
Summary Statistics
The Average Effect on Air Quality
Findings
Discussion
Conclusions
Full Text
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