Quantifying urban, industrial, and background changes in NO<sub>2</sub> during the COVID-19 lockdown period based on TROPOMI satellite observations
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Published:2022-03-31
Issue:6
Volume:22
Page:4201-4236
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Fioletov VitaliORCID, McLinden Chris A.ORCID, Griffin DeboraORCID, Krotkov NickolayORCID, Liu FeiORCID, Eskes HenkORCID
Abstract
Abstract. 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 20σ below the baseline level from the other years.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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