Spatial–temporal variations and influencing factors of air quality in China’s major cities during COVID-19 lockdown

Environmental Science and Pollution Research https://doi.org/10.1007/s11356-022-23927-4 RESEARCH ARTICLE Spatial–temporal variations and influencing factors of air quality in China’s major cities during COVID‑19 lockdown Xinlin Yan1 · Tao Sun1 Received: 6 July 2022 / Accepted: 27 October 2022 © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract To control the spread of COVID-19, the Chinese government announced a “lockdown” policy, and the citizens’ activities were restricted. This study selected three standard air quality indexes, AQI, PM2.5, and PM10, of 2017–2021 in 40 major cities in six regions in China to analyze their changes, spatial–temporal distributions, and socioeconomic influencing factors. Compared with 2019, the values of AQI, PM2.5, and PM10 decreased, and the days with AQI levels “AQI ≤ 100” increased during the “lockdown” in 2020. Due to different degrees of industrialization, the concentration of air pollutants shows significant regional characteristics. The AQI values before and after the “lockdown” in 2020 show significant spatial autocorrelation, and the cities’ AQI values in the north present high autocorrelation, and the cities in the south are in low autocorrelation. From the data at the national level, carbon emission intensity (CEI), per capita energy consumption (PEC), per capita GDP (PCG), industrialization rate (IR), and proportion of construction value added (PCVA) have the greatest impact on AQI. This study gives regulators confidence that if the government implements regionalized air quality improvement policies according to the characteristics of each region in China and reasonably plans socioeconomic activities, it is expected to improve China’s air quality sustainably. Keywords COVID-19 · Lockdown · Air quality · Spatial autocorrelation · Influencing factors · Environmental governance policy Introduction In December 2019, the first case of unknown pneumonia appeared in Wuhan, China, and then the virus causing pneumonia spread rapidly in China and even around the world and was named COVID-19 by WHO (WHO 2020). Due to the spread of COVID-19 from Wuhan to other provinces in China, the Chinese government announced the “lockdown” of Wuhan on January 23, 2020. Subsequently, all provinces’ governments announced the launch of the firstclass response to major national public health events and began implementing epidemic restriction measures nationwide. These government restrictions include residents being Responsible Editor: Philippe Garrigues * Tao Sun 1 College of Economics and Management, Nanjing University of Aeronautics and Astronautics, No. 29, Jiangjun Avenue, Nanjing 211106, Jiangsu, China restricted from going out; large gatherings being banned; schools, shopping centers, construction sites, and factories being temporarily suspended; and traffic and transportation being controlled. Since the “lockdown” started during the Chinese lunar new year, traffic control restricted a large number of population movements, which affected the economic activities of the whole country, but also provided an opportunity for China’s air pollution research. Studies have shown that air quality will change during significant events. During the 2008 Olympic Games and the 2014 APEC summit, Beijing issued policies to restrict factory production and transportation in order to improve air quality (Chen et al. 2013). During the annual plenary session of the National People’s Congress and the National Committee of the Chinese People’s Political Consultative Conference from 2013 to 2016, due to the temporary implementation of strict air quality governance measures at the annual meeting, the air quality index AQI decreased by 5.7%. During the APEC meeting in 2014, the AQI index decreased by 35.9% due to the most stringent air governance measures issued by the China central government, and the values of 13 Vol.:(0123456789) Environmental Science and Pollution Research M2.5, PM10, SO2, NO2, and CO decreased by 41.3%, 48.2%, P 56.5%, 38.9%, and 35.5% respectively (Li et al. 2017). The G20 Summit in Hangzhou in 2016 proved that the holding of large-scale events is related to the changes of air quality (Li et al. 2019). However, the impact of the COVID-19 “lockdown” is unmatched by the previous major events in China. Recent studies in many countries have shown that the “lockdown” caused by the spread of COVID-19 and the reduction of traffic and industrial activities have a positive impact on the environment (Li et al. 2020). The study found that the AQI, PM2.5, and PM10 of major cities in India decreased significantly during the one month of “lockdown” (Naqvi et al. 2021; Das et al. 2021; Yadav et al. 2020). Anthropogenic emissions reduce processes that promote secondary aerosol formation through measurements of aerosol composition during COVID-19 (Sun et al. 2020). The study found that PM2.5 emission levels are strongly linked to the deaths of people infected with COVID-19, with regions dominated by fossil fuel emissions significantly affecting the number of COVID19 cases (Sahu et al. 2021; Ali et al. 2021). Based on the conventional pollutant monitoring data for 4 years and 3 months in the same period from 2018 to 2021, this paper analyzes air quality indexes in 40 major cities in China before, during, and after the “lockdown” in 2020. On this basis, the spatial effect test model of air quality and test model of air quality influencing factors are established to study the differences of socioeconomic factors on air quality both national and regional wide. The research results are helpful in understanding the evidence of the impact of human social activities on air quality during the period of strict policy restrictions, as well as the regional characteristics of air pollution, and provide a reference for formulating related air pollution governance policies and measures. Materials and methods Data sources and processing This paper selects the data of monitoring points of 40 major cities in China, which spatially covers the developed cities in all provinces and regions in China. We collected daily air pollution data from China’s national environmental monitoring center from December to March 2017–2021 and selected air quality indexes AQI, PM2.5, and PM10. Due to the characteristics of regional transmission of air pollutants, the air pollutants concentration of each city will be affected by the surrounding cities (Li et al. 2017). In this study, 40 major cities are divided into six regions according to their economic development level, industrial and energy structure, urban agglomeration development characteristics, regional climate characteristics, and geographical location (Miao et al. 2019; Xu et al. 2021; Hao et al. 2018; Luo et al. 2021; Zhu et al. 2018; Wei et al. 2020; Li et al. 2021); details are shown in Table 1. January 23, 2020, the 29th of the lunar calendar, is the day before the Ch (...truncated)