11 Jan 2021

11 Jan 2021

Review status: a revised version of this preprint is currently under review for the journal ESSD.

Changes in global air pollutant emissions during the COVID-19 pandemic: a dataset for atmospheric chemistry modeling

Thierno Doumbia1, Claire Granier1,2, Nellie Elguindi1, Idir Bouarar3, Sabine Darras4, Guy Brasseur3,5, Benjamin Gaubert5, Yiming Liu6, Xiaoqin Shi3, Trissevgeni Stavrakou7, Simone Tilmes5, Forrest Lacey5, Adrien Deroubaix3, and Tao Wang6 Thierno Doumbia et al.
  • 1Laboratoire d'Aérologie, Toulouse, France
  • 2NOAA Chemical Sciences Laboratory and CIRES/University of Colorado, Boulder, CO, USA
  • 3Max-Planck Institute for Meteorology, Hamburg, Germany
  • 4Observatoire Midi-Pyrénées, Toulouse, France
  • 5Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO, USA
  • 6Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
  • 7Royal Belgian Royal Institute for Space Aeronomy, Brussels, Belgium

Abstract. In order to fight the spread of the global COVID-19 pandemic, most of the world 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 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 is 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 six months of 2020. Maximum decreases in the emissions are found in February in Eastern China, with an average reduction of 20–30 % in NOx, NMVOCs 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 NMVOCs emissions are reduced by 15–30 %. For the others species, the maximum reductions are generally less than 15 %, except in South America, where large decreases in CO and BC 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 adjustmeNt Factor fOR eMissions) ( It is distributed by the Emissions of atmospheric Compounds and Compilation of Ancillary Data (ECCAD) database (

Thierno Doumbia et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2020-348', Yang Song, 11 Jan 2021
  • RC2: 'Comment on essd-2020-348', Pengfei Han, 09 Feb 2021

Thierno Doumbia et al.

Thierno Doumbia et al.


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