Changes in Air Quality during the Period of COVID-19 in China

Xin Xu, Shupei Huang (), Feng An and Ze Wang ()
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Xin Xu: School of Economics and Management, China University of Geosciences (Beijing), Beijing 100083, China
Shupei Huang: School of Economics and Management, China University of Geosciences (Beijing), Beijing 100083, China
Feng An: School of Economics and Management, University of Science and Technology Beijing, Beijing 100083, China
Ze Wang: International Academic Center of Complex Systems, Beijing Normal University, Zhuhai 519087, China

IJERPH, 2022, vol. 19, issue 23, 1-17

Abstract: This paper revisits the heterogeneous impacts of COVID-19 on air quality. For different types of Chinese cities, we analyzed the different degrees of improvement in the concentrations of six air pollutants (PM2.5, PM10, SO 2 , NO 2 , CO, and O 3 ) during COVID-19 by analyzing the predictivity of air quality. Specifically, we divided the sample into three groups: cities with severe outbreaks, cities with a few confirmed cases, and cities with secondary outbreaks. Ensemble empirical mode decomposition (EEMD), recursive plots (RPs), and recursive quantitative analysis (RQA) were used to analyze these heterogeneous impacts and the predictivity of air quality. The empirical results indicated the following: (1) COVID-19 did not necessarily improve air quality due to factors such as the rebound effect of consumption, and its impacts on air quality were short-lived. After the initial outbreak, NO 2 , CO, and PM2.5 emissions declined for the first 1–3 months. (2) For the cities with severe epidemics, air quality was improved, but for the cities with second outbreaks, air quality was first enhanced and then deteriorated. For the cities with few confirmed cases, air quality first deteriorated and then improved. (3) COVID-19 changed the stability of the air quality sequence. The predictability of the air quality index (AQI) declined in cities with serious epidemic situations and secondary outbreaks, but for the cities with a few confirmed cases, the AQI achieved a stable state sooner. The conclusions may facilitate the analysis of differences in air quality evolution characteristics and fluctuations before and after outbreaks from a quantitative perspective.

Keywords: air quality; predictability; COVID-19 pandemic; ensemble empirical mode decomposition; recursive quantitative analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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