How do pollutants change post-pandemic? Evidence from changes in five key pollutants in nine Chinese cities most affected by the COVID-19

Abstract

Under the COVID-19 global pandemic, China has weakened the large-scale spread of the epidemic through lockdown and other measures. At the same time, with the recovery of social production activities, China has become the only country which achieves positive growth in 2020 in the major economies. It entered the post pandemic period. These measures improved the local environmental quality. However, whether this improvement can be sustained is also a problem that needs to be solved. So, this study investigated the changes of five air pollutants (PM2.5, PM10, NO₂, SO₂, and CO) in the nine cities most severely affected by the pandemic in China during the lockdown and post pandemic period. We emphasized that when analyzing the changes of environmental quality during the epidemic, we must consider not only the impact of the day and short-term changesbut also the cumulative lag effect and sustainable development. Through a combination of qualitative and quantitative methods, it is found that the concentration of pollutants decreased significantly during the lockdown compared to the situation before the epidemic. PM10 and NO₂ are falling most, which downs 39% and 46% respectively. During the lockdown period, the pollutant concentrations response to the pandemic has a lag of 3-7 days. More specifically, in the cities related to single pollutants, the impact on the pollutant shows a significant correlation when the measures are delayed for seven days. In the cities that are related to multiple pollutants, the correlation is usually highest in 3-5 days. This means that the impact of policy measures on the environment lasted for 3-5 days. Besides, Wuhan, Jingmen and Jingzhou have seen the most obvious improvement. However, this improvement did not last. In the post pandemic period, the pollutants rebounded, the growth rates of PM10 and NO₂ reached 44% and 87% in September. When compared with the changes of pollutants concentration in the same period from 2017 to 2019, the decline rate has also been significantly slower, even higher than the average concentration of previous years. The research not only contributes to China's economic "green recovery" plan during the post epidemic period, but also provides references for environmental governance during economic recovery in other countries.

Keywords: Air pollution; Hysteresis; Lockdown; Post pandemic period; Rebound.

Graphical abstract

Fig. 1

COVID-19 measures and impact.

Fig. 2

Steps of the analysis process.

Fig. 3

Hysteresis processing diagram.

Fig. 4

The changes of COVID-19 daily newly confirmed cases.

Fig. 5

Comparison chart of air pollutant content in 2019–2020.

Fig. 5

Comparison chart of air pollutant content in 2019–2020.

Fig. 5

Comparison chart of air pollutant content in 2019–2020.

Fig. 6

Correlation and hysteresis of COVID-19 and environmental pollutants in different cities.

Fig. 7

The dynamic relationship between COVID-19 and pollutants.

Fig. 8

The range of changes in air pollutant concentrations from January to September 2020.

Fig. 8

The range of changes in air pollutant concentrations from January to September 2020.

Fig. 8

The range of changes in air pollutant concentrations from January to September 2020.

Fig. 9

The year-on-year changes in air pollutants in 2020, 2017–2019 (a: The changes in air pollutants concentrations in 2020 and the 2017–2019 average; b: Comparison of the two-stage rebound value in 2020 and 2017–2019).