气候变化领域集成服务门户(CCPortal): Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations

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DOI	10.5194/acp-22-4201-2022
	Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations
	Fioletov, Vitali; McLinden, Chris A.; Griffin, Debora; Krotkov, Nickolay; Liu, Fei; Eskes, Henk
发表日期	2022
ISSN	1680-7316
EISSN	1680-7324
起始页码	4201
结束页码	4236
卷号	22 期号:6 页码:36
英文摘要	The COVID-19 lockdown had a large impact on anthropogenic emissions of air pollutants and particularly on nitrogen dioxide (NO2). While the overall NO2 decline over some large cities is well-established, understanding the details remains a challenge since multiple source categories contribute. In this study, a new method of isolation of three components (background NO2, NO2 from urban sources, and NO2 from industrial point sources) is applied to estimate the impact of the COVID-19 lockdown on each of them. The approach is based on fitting satellite data by a statistical model with empirical plume dispersion functions driven by a meteorological reanalysis. Population density and surface elevation data as well as coordinates of industrial sources were used in the analysis. The tropospheric NO2 vertical column density (VCD) values measured by the Tropospheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor over 261 urban areas for the period from 16 March to 15 June 2020 were compared with the average VCD values for the same period in 2018 and 2019. While the background NO2 component remained almost unchanged, the urban NO2 component declined by -18 % to -28 % over most regions. India, South America, and a part of Europe (particularly, Italy, France, and Spain) demonstrated a -40 % to -50 % urban emission decline. In contrast, the decline over urban areas in China, where the lockdown was over during the analysed period, was, on average, only -4.4 +/- 8 %. Emissions from large industrial sources in the analysed urban areas varied greatly from region to region from -4.8 +/- 6 % for China to -40 +/- 10 % for India. Estimated changes in urban emissions are correlated with changes in Google mobility data (the correlation coefficient is 0.62) confirming that changes in traffic were one of the key elements in the decline in urban NO2 emissions. No correlation was found between changes in background NO2 and Google mobility data. On the global scale, the background and urban components were remarkably stable in 2018, 2019, and 2021, with averages of all analysed areas all being within +/- 2.5 % and suggesting that there were no substantial drifts or shifts in TROPOMI data. The 2020 data are clearly an outlier: in 2020, the mean background component for all analysed areas (without China) was -6.0 % +/- 1.2 % and the mean urban component was -26.7 +/- 2.6 % or 20 sigma below the baseline level from the other years.
学科领域	Environmental Sciences; Meteorology & Atmospheric Sciences
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
WOS记录号	WOS:000776275800001
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/273860
作者单位	Environment & Climate Change Canada; National Aeronautics & Space Administration (NASA); NASA Goddard Space Flight Center; Royal Netherlands Meteorological Institute
推荐引用方式 GB/T 7714	Fioletov, Vitali,McLinden, Chris A.,Griffin, Debora,et al. Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations[J],2022,22(6):36.
APA	Fioletov, Vitali,McLinden, Chris A.,Griffin, Debora,Krotkov, Nickolay,Liu, Fei,&Eskes, Henk.(2022).Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations.ATMOSPHERIC CHEMISTRY AND PHYSICS,22(6),36.
MLA	Fioletov, Vitali,et al."Quantifying urban, industrial, and background changes in NO2 during the COVID-19 lockdown period based on TROPOMI satellite observations".ATMOSPHERIC CHEMISTRY AND PHYSICS 22.6(2022):36.