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Atmospheric Impacts of COVID-19 on NOx and VOC Levels over China Based on TROPOMI and IASI Satellite Data and Modeling

Authors :
Trissevgeni Stavrakou
Jean-François Müller
Maite Bauwens
Thierno Doumbia
Nellie Elguindi
Sabine Darras
Claire Granier
Isabelle De Smedt
Christophe Lerot
Michel Van Roozendael
Bruno Franco
Lieven Clarisse
Cathy Clerbaux
Pierre-François Coheur
Yiming Liu
Tao Wang
Xiaoqin Shi
Benjamin Gaubert
Simone Tilmes
Guy Brasseur
Source :
Atmosphere, Vol 12, Iss 8, p 946 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

China was the first country to undergo large-scale lockdowns in response to the pandemic in early 2020 and a progressive return to normalization after April 2020. Spaceborne observations of atmospheric nitrogen dioxide (NO2) and oxygenated volatile organic compounds (OVOCs), including formaldehyde (HCHO), glyoxal (CHOCHO), and peroxyacetyl nitrate (PAN), reveal important changes over China in 2020, relative to 2019, in response to the pandemic-induced shutdown and the subsequent drop in pollutant emissions. In February, at the peak of the shutdown, the observed declines in OVOC levels were generally weaker (less than 20%) compared to the observed NO2 reductions (−40%). In May 2020, the observations reveal moderate decreases in NO2 (−15%) and PAN (−21%), small changes in CHOCHO (−3%) and HCHO (6%). Model simulations using the regional model MAGRITTEv1.1 with anthropogenic emissions accounting for the reductions due to the pandemic explain to a large extent the observed changes in lockdown-affected regions. The model results suggest that meteorological variability accounts for a minor but non-negligible part (~−5%) of the observed changes for NO2, whereas it is negligible for CHOCHO but plays a more substantial role for HCHO and PAN, especially in May. The interannual variability of biogenic and biomass burning emissions also contribute to the observed variations, explaining e.g., the important column increases of NO2 and OVOCs in February 2020, relative to 2019. These changes are well captured by the model simulations.

Details

Language :
English
ISSN :
20734433
Volume :
12
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Atmosphere
Publication Type :
Academic Journal
Accession number :
edsdoj.80bde817a7c64788ba38d0b03a342562
Document Type :
article
Full Text :
https://doi.org/10.3390/atmos12080946