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. 2020 Nov 15:743:140879.
doi: 10.1016/j.scitotenv.2020.140879. Epub 2020 Jul 11.

Response of major air pollutants to COVID-19 lockdowns in China

Zhipeng Pei  1 , Ge Han  2 , Xin Ma  3 , Hang Su  4 , Wei Gong  3
Affiliations
Free PMC article

Response of major air pollutants to COVID-19 lockdowns in China

Zhipeng Pei et al. Sci Total Environ. .
Free PMC article

Abstract

COVID-19 suddenly struck Wuhan at the end of 2019 and soon spread to the whole country and the rest of world in 2020. To mitigate the pandemic, China authority has taken unprecedentedly strict measures across the country. That provides a precious window to study how the air quality response to quick decline of anthropogenic emissions in terms of national scale, which would be critical basis to make atmospheric governance policies in the future. In this work, we utilized observations from both remote sensing and in-situ measurements to investigate impacts of COVID-19 lockdown on different air pollutions in different regions of China. It is witnessed that the PM2.5 concentrations exhibited distinct trends in different regions, despite of plunges of NO2 concentrations over the whole country. The steady HCHO concentration in urban area provides sufficient fuels for generations of tropospheric O3, leading to high concentrations of O3, especially when there is not enough NO to consume O3 via the titration effect. Moreover, the SO2 concentration kept steady at a low level regardless of cities. As a conclusion, the COVID-19 lockdown indeed helped reduce NO2 concentration. However, the atmospheric quality in urban areas of China has not improved overall due to lockdown measures. It underscores the significance of comprehensive control of atmospheric pollutants in cleaning air. Reducing VOCs (volatile organic compounds) concentrations in urban areas would be a critical mission for better air quality in the future.

Keywords: Air quality; COVID-19; O(3); PM(2.5); Sentinel-5.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Unlabelled Image
Graphical abstract
Fig. 1
Fig. 1
Map of the study area.
Fig. 2
Fig. 2
Weekly averaged TROPOMI tropospheric NO2 vertical column densities over China.
Fig. 3
Fig. 3
Weekly averaged TROPOMI tropospheric HCHO vertical column densities over China.
Fig. 4
Fig. 4
Weekly averaged PM2.5 concentration during P1 to P5 in 2019 and 2020. Grey columns mark the left vertical axis, representing the weekly averaged PM2.5 concentration. While, orange circles mark the right vertical axis, representing the ration of weekly averaged PM2.5 concentration between 2020 and 2019. A dashed line highlights the ratio of 1. An orange dot above that line indicates an increasing year-on-year PM2.5 concentration and vice versa. Arrows are used to intuitively visualize the year-on-year trend of PM2.5 concentration. Red means rise while green means decline. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Fig. 5
Fig. 5
Weekly averaged O3 concentration during P1 to P5 in 2019 and 2020. Symbols in this figure are the same with those explained in Fig. 4.
Fig. 6
Fig. 6
Weekly averaged NO2 concentration during P1 to P5 in 2019 and 2020. Symbols in this figure are the same with those explained in Fig. 4.
Fig. 7
Fig. 7
Weekly averaged SO2 concentration during P1 to P5 in 2019 and 2020. Symbols in this figure are the same with those explained in Fig. 4.
Fig. 8
Fig. 8
Weekly averaged wind speed during P1 to P5 in 2019 and 2020.
Fig. 9
Fig. 9
Weekly averaged precipitation during P1 to P5 in 2019 and 2020. There was a strong precipitation process during P5 of 2019 in Guangzhou, which resulted in a weekly averaged precipitation of 18.6 mm. To share an identical axis with other conditions, we set a break point in vertical axis at the point of 16 mm because the weekly averaged precipitation in P5 of 2019 in Guangzhou is too large compared with other values.
Fig. 10
Fig. 10
Weekly averaged temperature (in K) during P1 to P5 in 2019 and 2020.
See this image and copyright information in PMC

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