Abstract

Since anthropogenic NOx (NOx=NO+NO2) and CO2 are co-emitted species for anthropogenic sources, some studies have used the NOx emissions retrieved from satellite observations to infer the anthropogenic CO2 emissions. However, these studies did not consider the fact that satellites measure total NO2 concentrations and their inferred emissions encompass both biogenic and anthropogenic sources. In this study, we introduce a method to distinguish soil NOx emissions from satellite-based total NOx emissions. The total NOx emissions are derived by the state-of-the-art inverse algorithm DECSO (Daily Emission estimation Constrained by Satellite Observations, Mijling and van der A, 2012; Ding et al., 2017a) from TROPOMI observations. Using the characteristic seasonal cycle of soil emissions we derive these emissions for representative regions with only biogenic emissions, which are then applied to nearby regions according land-use fractions. To evaluate this approach, we compared the deviation between the tropospheric NO2 concentration observed by satellite and two atmospheric composition model simulations: one using the satellite-derived soil NOx emissions and another with the Copernicus Atmosphere Monitoring Service (CAMS) global soil emissions inventory (CAMS-GLOB-SOIL). Once the soil NOx emissions are derived, they can be subtracted from the total emissions to get anthropogenic NOx emissions. Subsequently anthropogenic CO2 emissions can be estimated using known CO2/NOx factors from bottom-up inventories. The annual CO2 emissions derived from DECSO (called DECSO-CO2) in our study area (large part of Europe) is 3.7 Gt in 2019, which is comparable with the 3.2 Gt of the CAMS CO2 inventory (called CAMS-CO2). The DECSO-CO2 and CAMS-CO2 are comparable for most large sources and cities, but the DECSO-CO2 show a larger number of low emission spots than the CAMS-CO2. The results demonstrate the potential for DECSO to expand its application to other regions in the world with less information on anthropogenic CO2 emissions.

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