High resolution quantification of SO₂ emissions over India based on TROPOMI observations

Abstract. India is a country with high sulfur dioxide (SO₂) emissions mainly resulting from the large number of coal-fired thermal power plants. SO₂ column observations from the Sentinel-5P Tropospheric Monitoring Instrument (TROPOMI) satellite instrument, in combination with inverse modelling techniques can be used to derive observation-based SO₂ emission estimates. The flux-divergence emission estimation method is sensitive to point source emissions and is well-suited for estimating SO₂ emissions in India. However, the flux-divergence method combined with satellite observations spreads out the calculated emissions to grid cells in the neighborhood of the point source. This spreading effect weakens the signal of point sources at their exact location, making it harder to quantify the exact emissions. In this paper, we describe a deconvolution algorithm to reverse the spreading and sharpen the emission signals. Our deconvolution algorithm ensures mass conservation of the emissions. We apply the deconvolution algorithm on gridded SO₂ emissions at a high spatial resolution of 0.025° × 0.025° (2.5 km × 2.5 km) derived from TROPOMI observations with a typical mean footprint size of 6 km. After the deconvolution, the effective spatial resolution of emissions is enhanced to match the grid cell resolutions. The point source emissions significantly increase at their exact locations and emissions in the neighbor grid cells become lower. In our inventory, about 80 % of coal-based power plants with a capacity above 100 MW are detected at the correct location, while the remaining 20 % fall below the noise level. The detected power plants account for 99 % of India’s total coal-based power generation. We also identify 7 previously unreported SO₂ point sources, including coal-based thermal power plants, cement plants, copper industry, and crude oil facility. This deconvolution algorithm improves emission detection and can also be used for other pollutants emitted by point sources to enhance the accuracy of emission inventories.