A066-0008
Emissions of atmospheric pollutants during the Covid-19 pandemic: input for atmospheric models

Wednesday, 9 December 2020
Poster
Thierno Doumbia1, Claire Granier1, Sabine Darras2, Nellie Elguindi1, Idir Bouarar3, Benjamin Gaubert4, Nicolas Huneeus5, Yiming Liu6, Brian C McDonald7, Mauricio Osses8, Xiaoqin Shi3, Trissevgeni Stavrakou9, Simone Tilmes10, Tao Wang11 and Guy P Brasseur3, (1)Laboratoire d'Aérologie - Observatoire Midi Pyrénées, Toulouse, France, (2)Observatoire Midi-Pyrenees, Toulouse, France, (3)Max Planck Institute for Meteorology, Hamburg, Germany, (4)National Center for Atmospheric Research, Atmospheric Chemistry Observations & Modeling Laboratory, Boulder, CO, United States, (5)Center for Climate and Resilience Research, Departamento de Geofísica, Universidad de Chile, Santiago, Chile, (6)Sun Yat-sen University, Guangzhou, China, (7)Chemical Sciences Division, NOAA Earth System Research Laboratory, Boulder, CO, United States, (8)Federico Santa Maria Technical University, Valparaiso, Chile, (9)Royal Belgian Institute for Space Aeronomy, Brussels, Belgium, (10)National Center for Atmospheric Research, Atmospheric Chemistry, Observations, and Modeling Laboratory, Boulder, CO, United States, (11)Hong Kong Polytechnic University, Department of Civil and Environmental Engineering, Hong Kong, China
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 have resulted in changes in economic and personal activities in many countries.

Several studies using satellite or surface observations have reported significant decreases in the spatial and temporal distributions of atmospheric pollutants and greenhouse gases. Model studies using global and regional chemistry-transport models have started, in order to analyze observations and to simulate the impact of these lockdowns on the distribution of atmospheric compounds. These modeling studies will also evaluate 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 reduction factors to be applied to global and regional emissions has been developed. This dataset provides the reduction factors on a daily basis starting in January 2020, on a 0.1x0.1 latitude/longitude degree grid.

Activity data have been collected for the transportation, power, industrial and residential sectors. The near real time data for transportation have been obtained from several databases, including Google Mobility Reports, Apple Mobility Trends and Baidu Mitigation Scale Index for China. Changes in energy production and use as well as in industrial activities have been obtained from country and regional databases. Data for the residential sector have been adapted, based on previously published work on greenhouse gases. The reductions on emissions from international shipping are also considered.

Three values of the reduction factors are provided at each grid point for model sensitivity studies, an average, a minimum and maximum value.

We will discuss the data used for the development of the dataset, the global and regional reduction factors, as well as comparisons with satellite and ground-based observations.

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