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Impacts of COVID-19 on Air Quality over China: Links with Meteorological Factors and Energy Consumption

机译:Covid-19对中国空气质量的影响:具有气象因素和能耗的环节

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摘要

The stringent control measures in China to curb the spread of Coronavirus disease (COVID-19) have had profound societal and environmental impacts, including changes in energy consumption practices and thereby in air pollutant emissions. In this study, a suite of satellite and numerically assimilated air pollution and meteorological data combined with information on energy consumption practices and nighttime light (NTL) was used to evaluate the effects of these COVID-19 control measures on air quality. These data revealed that control measures reduced aerosols mostly over central and eastern parts of China by countering favorable meteorological conditions for increased aerosols. The control measures reduced short-lived nitrogen dioxide (NO2) with little influence on long-lived carbon monoxide (CO). Consistent with energy production and energy consumption statistics in different sectors, NTL data suggest that high human mobility within the residential sector and reduced activity in other sectors during the implementation of control measures explain small but significant decreases in black carbon and sulfate aerosols, respectively, during this period. Overall, these results provide useful information for policy makers and the scientific community by clarifying the contributions of meteorological factors and energy consumption to changes in air quality. This information can guide the development of air pollution mitigation strategies and provides insight into the air pollution status in China and the potential for long-distance transport.
机译:中国的严格控制措施抑制冠状病毒疾病(Covid-19)的传播具有深刻的社会和环境影响,包括能源消耗实践的变化,从而在空气污染物排放中。在这项研究中,使用了一套卫星和数值同化的空气污染和气象数据与能耗实践和夜间光线(NTL)的信息相结合,用于评估这些Covid-19控制措施对空气质量的影响。这些数据显示,通过对抗气溶胶增加的气象条件,控制措施主要在中国的中央和东部地区减少了气溶胶。控制措施降低了短寿命的氮二氧化氮(NO2),对长寿命的一氧化碳(CO)几乎没有影响。与不同部门的能源生产和能源消耗统计一致,NTL数据表明,在控制措施实施过程中,在居住部门内的高人类流动性和其他部门的活动减少,分别在这一时期。总体而言,这些结果通过澄清气象因素和能源消耗对空气质量变化的贡献提供了决策者和科学界的有用信息。该信息可以指导风污染策略的发展,并向中国的空气污染状况和远程运输潜力提供了深入了解。

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