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. 2021 Sep;17(5):1014-1024.
doi: 10.1002/ieam.4399. Epub 2021 Mar 15.

Observations on the particle pollution of the cities in China in the Coronavirus 2019 closure: Characteristics and lessons for environmental management

Hong Yao  1   2 , Guangyuan Niu  1   2 , Qingxiang Zhang  1   2 , Qinyu Jiang  1   2 , Wei Lu  1   2 , Huan Liu  1   2 , Tianhua Ni  3
Affiliations

Observations on the particle pollution of the cities in China in the Coronavirus 2019 closure: Characteristics and lessons for environmental management

Hong Yao et al. Integr Environ Assess Manag. 2021 Sep.

Abstract

Particulate matter in the air seriously affects human health and has been a hot topic of discussion. Because of the coronavirus disease 2019 (COVID-19) lockdown in cities in China, sources of particulate matter, including gasoline-burning vehicles, dust-producing building sites, and coal-fired factories, almost all ceased at the end of January 2020. It was not until early April that outdoor activities recovered. Ten cities were selected as observation sites during the period from 19 December 2019 to 30 April 2020, covering the periods of preclosure, closure, and gradual resumption. A total of 11 720 groups of data were obtained, and 4 indicators were used to assess the characteristics of the particle pollution in the period. The quality of the atmospheric environment was visibly influenced by human activities in those 5 mo. The concentrations of particulate matter with particle sizes below 10 µm (PM10) decreased slightly in February and March and then began to increase slowly after April with the gradual recovery of production. The concentrations of particulate matter with particle sizes below 2.5 µm (PM2.5) decreased greatly in most regions, especially in northern cities, during closure and maintained a relatively stable level in the following 3 mo. The trends of PM10 and PM2.5 indicated that the reduced human activities during the COVID-19 lockdown decreased the concentrations of particulate matter in the air, and the difference between the PM10 and PM2.5 trends might be due to the different sources of the 2 particles and their different aerodynamics. However, during closure, the particulate matter pollution in the cities remained at a high level, which indicated that some ignored factors other than outdoor production activities, automobile exhaust, and construction site dust might have contributed greatly to the PM10 and PM2.5 concentrations, and the tracing of the particulate matter should be given further attention in environmental management. Integr Environ Assess Manag 2021;17:1014-1024. © 2021 SETAC.

Keywords: COVID-19 lockdown; China; PM10; PM2.5.

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Figures

Figure 1
Figure 1
Ten cities observing PM10 and PM2.5 concentrations during the COVID‐19 closure. PM2.5 = particulate matter with particle sizes below 2.5 µm; PM10 = particulate matter with particle sizes below 10 µm.
Figure 2
Figure 2
Scatter plots of the PM10 and PM2.5 concentrations from 12 December 2019 to 30 April 2020. BJ = Beijing; CD = Chendu; GY = Guiyang; GZ = Guangzhou; HB = Harbin; HH = Hohhot; NT = Nantong; PM2.5 = particulate matter with particle sizes below 2.5 µm; PM10 = particulate matter with particle sizes below 10 µm; SH = Shanghai; TY = Taiyuan; UQ = Urumqi.
Figure 3
Figure 3
Spatial distribution of the monthly average PM10 and PM2.5 concentrations. Cpm2.5 = the PM2.5 concentration; Cpm10 = the PM10 concentration; PM2.5 = particulate matter with particle sizes below 2.5 µm; PM10 = particulate matter with particle sizes below 10 µm.
Figure 4
Figure 4
City‐average PM10 and PM2.5 concentrations at various moments of the day. PM2.5 = particulate matter with particle sizes below 2.5 µm; PM10 = particulate matter with particle sizes below 10 µm.
Figure 5
Figure 5
Daily PM10 and PM2.5 concentrations in the 10 cities. BJ = Beijing; CD = Chendu; GY = Guiyang; GZ = Guangzhou; HB = Harbin; HH = Hohhot; NT = Nantong; PM2.5 = particulate matter with particle sizes below 2.5 µm; PM10 = particulate matter with particle sizes below 10 µm; SH = Shanghai; TY = Taiyuan; UQ = Urumqi.
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