新冠肺炎疫情对咸阳市空气质量的影响

利用机器学习模型控制气象因素影响，定量分析了疫情期间污染源减排对咸阳空气质量的影响.结果表明，与未发生疫情情景相比，疫情期间咸阳PM_2.5、PM₁₀、SO₂、NO₂和CO浓度分别下降19.3%、26.0%、13.4%、60.1%和9.1%，NO₂降幅最大，SO₂和CO降幅较小，O₃浓度不降反而上升50.9%.在一次排放和二次生成前体物都下降的情况下，PM_2.5降幅低于预期，O₃浓度不降反升，反映出PM_2.5和O₃治理的复杂性，暗示了剩余污染源对咸阳空气质量影响较大，而停产限产政策（与疫情影响类似）对咸阳空气质量改善有限，未来应重点关注散煤和生物质燃烧、热力生产和供应、原油加工及石油制品制造等剩余污染源的治理.

Impacts of the COVID-19 pandemic on air quality in Xianyang

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.