新冠肺炎疫情对咸阳市空气质量的影响

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Abstract Using a Machine Learning Model (MLM) to decouple meteorological parameters, this paper quantified true impacts of emission reduction by pollution sources resulting from COVID-19 on air quality in Xianyang. Compared with the non-epidemic scenario, the results showed that concentrations of PM_2.5, PM₁₀, SO₂, NO₂, and CO in Xianyang had significantly decreased by 19.3%, 26.0%, 13.4%, 60.1% and 9.1%, respectively, with NO₂ decreasing the most, SO₂ and CO decreasing slightly, and O₃ increased by 50.9% conversely. Under the condition that both primary emission and precursors of secondary particulate matter decreased, the concentration of PM_2.5 dropped lower than expected, and O₃ increased though, showing the complexity of PM_2.5 and O₃ control, in the meanwhile implying that the impact of operating pollution sources during the epidemic on air quality was greater than malfunctioned sources, and official regulations to restrict and suspend production in factories (similar to the impact of the pandemic) had limited improvement on air quality. In the future, emphases should be put on the treatment of operating pollution sources during the pandemic such as scattered coal and biomass combustion, heat production and supply, and crude oil processing and petroleum product manufacturing.

Key words： emission reduction of pollution sources air quality COVID-19 pandemic random forest model

Received: 19 December 2020

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X51

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	DAI Xing-liang
	SONG Guo-jun
	JIANG Xiao-qun
	YU Jing-juan
	FANG Dan-yang

Cite this article:

DAI Xing-liang,SONG Guo-jun,JIANG Xiao-qun等. Impacts of the COVID-19 pandemic on air quality in Xianyang[J]. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(7): 3106-3114.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2021/V41/I7/3106

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