SO2 emission estimates using satellite observations from TROPOMI and OMI and the global chemistry transport model LMDz-INCA

Sulfur dioxide (SO₂) is released into the Earth’s atmosphere through natural and anthropogenic processes and the latter category amounts to the majority of the global SO₂ emissions. Satellite SO₂ observations have been used to monitor SO₂ emissions at different regional and global scales and to detect large-point sources of SO₂ emissions of diverse origins. In this study, we conducted atmospheric inversions at the global scale to estimate daily SO₂ emissions at 1.26^o×2.5^o (latitude×longitude) spatial resolution over polluted regions for two years 2020 and 2021 using satellite SO₂ total vertical column densities (TVCDs) obtained by the Sentinel 5p TROPOspheric Monitoring Instrument (TROPOMI) and AURA Ozone Monitoring Instrument (OMI). We used the global chemistry coupled transport model LMDz-INCA with 1.26^o×2.5^o (latitude×longitude) horizontal resolution and 79 hybrid σ-p vertical levels extending to the stratosphere to simulate the model SO₂ TVCDs. The model uses a priori monthly global anthropogenic emission inventories from the open-source Community Emissions Data System (CDES). As the TROPOMI operational offline L2 SO₂ data product has high noise levels, we used the TROPOMI COBRA SO₂ data product in this study which has comparatively smaller noise. First, we evaluated the SO₂ TVCDs from the LMDz-INCA model simulations for a reference year 2019 with the observed SO₂ TVCDs from TROPOMI and OMI. The daily average (10-day running average) of the model simulated SO₂ TVCDs over the major polluted regions like India, China, and the Middle East, and over less polluted regions like South Africa, and South America mostly follow the trend of the observed SO₂ TVCDs from both TROPOMI and OMI. The model overestimates SO2 TVCDs over India and the Middle East and underestimates them over China, South Africa, and South America. For Europe and North America, the noise levels in the daily averaged TVCDs from both TROPOMI and OMI are too high for a meaningful comparison. In order to estimate anthropogenic SO₂ emissions, we used a recently developed inversion approach (Zheng et al., 2020), which was previously used to estimate anthropogenic NO_x emissions over China. We performed the model simulation for 2019 with 40% reduced anthropogenic SO₂ emission to calculate the gridded local sensitivities of the TVCDs to the change in the anthropogenic SO₂ emissions. The inversion approach combines these gridded local sensitivities and the relative change of the observed satellites and the modelled TVCDs to derive the relative change of anthropogenic SO₂ emissions from the reference year 2019 to the inversion years 2020 and 2021. The estimated total SO₂ emissions from TROPOMI and OMI observations for 2020 and 2021 are mostly higher compared to the reference year total emissions over the world and over the selected regions. The total SO₂ emissions from TROPOMI and OMI observations at the common model grids for both inversion years are consistent with each other.