Severe air pollution events not avoided by reduced anthropogenic activities during COVID-19 outbreak

Abstract

Due to the pandemic of coronavirus disease 2019 in China, almost all avoidable activities in China are prohibited since Wuhan announced lockdown on January 23, 2020. With reduced activities, severe air pollution events still occurred in the North China Plain, causing discussions regarding why severe air pollution was not avoided. The Community Multi-scale Air Quality model was applied during January 01 to February 12, 2020 to study PM_2.5 changes under emission reduction scenarios. The estimated emission reduction case (Case 3) better reproduced PM_2.5. Compared with the case without emission change (Case 1), Case 3 predicted that PM_2.5 concentrations decreased by up to 20% with absolute decreases of 5.35, 6.37, 9.23, 10.25, 10.30, 12.14, 12.75, 14.41, 18.00 and 30.79 μg/m³ in Guangzhou, Shanghai, Beijing, Shijiazhuang, Tianjin, Jinan, Taiyuan, Xi'an, Zhengzhou, Wuhan, respectively. In high-pollution days with PM_2.5 greater than 75 μg/m³, the reductions of PM_2.5 in Case 3 were 7.78, 9.51, 11.38, 13.42, 13.64, 14.15, 14.42, 16.95 and 22.08 μg/m³ in Shanghai, Jinan, Shijiazhuang, Beijing, Taiyuan, Xi'an, Tianjin, Zhengzhou and Wuhan, respectively. The reductions in emissions of PM_2.5 precursors were ~2 times of that in concentrations, indicating that meteorology was unfavorable during simulation episode. A further analysis shows that benefits of emission reductions were overwhelmed by adverse meteorology and severe air pollution events were not avoided. This study highlights that large emissions reduction in transportation and slight reduction in industrial would not help avoid severe air pollution in China, especially when meteorology is unfavorable. More efforts should be made to completely avoid severe air pollution.

Keywords: COVID-19; China; Emission reduction; Meteorology; Severe air pollution.

Graphical abstract

Fig. 1

Locations of domains and major cities (red point), Wuhan is marked as yellow star and Hubei province is in blue. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Fig. 2

Predicted daily PM_2.5 and its components with observed daily PM_2.5 in 10 major cities in Case 3. Units are µg/m³.

Fig. 3

Predicted PM_2.5 and its major components and the changes between cases in unit of µg/m³ during January 20 to February 12, 2020. SO₄ is sulfate, NO₃ is a nitrate, NH₄ is ammonium, EC is elemental carbon, POA is primary organic aerosol, SOA is secondary organic aerosol and OTHER is the sum of inexplicit components.

Fig. 4

Predicted daily PM_2.5 with components and observed PM_2.5 in 10 major cities of three scenarios during January 20 to February 12, 2020. Units are µg/m³.

Fig. 5

Averaged predicted daily PM_2.5 with components and observed PM_2.5 in 10 major cities of three scenarios on high-pollution days (>75 µg/m³, left column) and low-pollution days (right column). The number of days in high (H) and low (L) pollution days are marked after the city names. Units are µg/m³.

Fig. 6

Relative changes in concentrations of primary PM_2.5 (PPM) and secondary components, and in emissions of related precursors in Case 3 to Case 1 in four cities.

Fig. 7

Estimated contributions of meteorology and anthropogenic emissions changes to averaged PM_2.5 concentrations in selected cities during January 20 to February 12, 2020. Units are µg/m³. Guangzhou is not included as it had no high-pollution days during the episode.