Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99644
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dc.contributorDepartment of Civil and Environmental Engineeringen_US
dc.creatorDoumbia, Ten_US
dc.creatorGranier, Cen_US
dc.creatorElguindi, Nen_US
dc.creatorBouarar, Ien_US
dc.creatorDarras, Sen_US
dc.creatorBrasseur, Gen_US
dc.creatorGaubert, Ben_US
dc.creatorLiu, Yen_US
dc.creatorShi, Xen_US
dc.creatorStavrakou, Ten_US
dc.creatorTilmes, Sen_US
dc.creatorLacey, Fen_US
dc.creatorDeroubaix, Aen_US
dc.creatorWang, Ten_US
dc.date.accessioned2023-07-18T03:12:29Z-
dc.date.available2023-07-18T03:12:29Z-
dc.identifier.issn1866-3508en_US
dc.identifier.urihttp://hdl.handle.net/10397/99644-
dc.language.isoenen_US
dc.publisherCopernicus GmbHen_US
dc.rights© Author(s) 2021.en_US
dc.rightsThis work is distributed under the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Doumbia, T., Granier, C., Elguindi, N., Bouarar, I., Darras, S., Brasseur, G., Gaubert, B., Liu, Y., Shi, X., Stavrakou, T., Tilmes, S., Lacey, F., Deroubaix, A., and Wang, T.: Changes in global air pollutant emissions during the COVID-19 pandemic: a dataset for atmospheric modeling, Earth Syst. Sci. Data, 13, 4191–4206 is available at https://doi.org/10.5194/essd-13-4191-2021.en_US
dc.titleChanges in global air pollutant emissions during the COVID-19 pandemic : a dataset for atmospheric modelingen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage4191en_US
dc.identifier.epage4206en_US
dc.identifier.volume13en_US
dc.identifier.issue8en_US
dc.identifier.doi10.5194/essd-13-4191-2021en_US
dcterms.abstractIn order to fight the spread of the global COVID-19 pandemic, most of the world's countries have taken control measures such as lockdowns during a few weeks to a few months. These lockdowns had significant impacts on economic and personal activities in many countries. Several studies using satellite and surface observations have reported important changes in the spatial and temporal distributions of atmospheric pollutants and greenhouse gases. Global and regional chemistry-transport model studies are being performed in order to analyze the impact of these lockdowns on the distribution of atmospheric compounds. These modeling studies aim at evaluating the impact of the regional lockdowns at the global scale. In order to provide input for the global and regional model simulations, a dataset providing adjustment factors (AFs) that can easily be applied to current global and regional emission inventories has been developed. This dataset provides, for the January–August 2020 period, gridded AFs at a 0.1×0.1 latitude–longitude degree resolution on a daily or monthly basis for the transportation (road, air and ship traffic), power generation, industry and residential sectors. The quantification of AFs is based on activity data collected from different databases and previously published studies. A range of AFs are provided at each grid point for model sensitivity studies. The emission AFs developed in this study are applied to the CAMS global inventory (CAMS-GLOB-ANT_v4.2_R1.1), and the changes in emissions of the main pollutants are discussed for different regions of the world and the first 6 months of 2020. Maximum decreases in the total emissions are found in February in eastern China, with an average reduction of 20 %–30 % in NOx, NMVOCs (non-methane volatile organic compounds) and SO2 relative to the reference emissions. In the other regions, the maximum changes occur in April, with average reductions of 20 %–30 % for NOx, NMVOCs and CO in Europe and North America and larger decreases (30 %–50 %) in South America. In India and African regions, NOx and NMVOC emissions are reduced on average by 15 %–30 %. For the other species, the maximum reductions are generally less than 15 %, except in South America, where large decreases in CO and BC (black carbon) are estimated. As discussed in the paper, reductions vary highly across regions and sectors due to the differences in the duration of the lockdowns before partial or complete recovery. The dataset providing a range of AFs (average and average ± standard deviation) is called CONFORM (COvid-19 adjustmeNt Factors fOR eMissions) (https://doi.org/10.25326/88; Doumbia et al., 2020). It is distributed by the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) database (https://eccad.aeris-data.fr/, last access: 23 August 2021).en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationEarth system science data, 2021, v. 13, no. 8, p. 4191-4206en_US
dcterms.isPartOfEarth system science dataen_US
dcterms.issued2021-
dc.identifier.scopus2-s2.0-85114037362-
dc.identifier.eissn1866-3516en_US
dc.description.validate202307 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS-
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextAERIS; HORIZON 2020 research and innovation action; South-Eastern European Data Services; National Science Foundation; National Center for Atmospheric Research; European Space Agencyen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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