The rapid development of the economy and the implementation of environmental policies adapted in India have led to fast changes of regional SO2 emissions. We present a monthly SO2 emission inventory for India covering December 2018 to November 2023 based on the Tropospheric Monitoring Instrument (TROPOMI) Level-2 COBRA SO2 dataset, using an improved flux-divergence method and estimated local SO2 lifetime, which includes both its chemical loss and dry deposition. We update the methodology to use the daily CAMS model output estimates of the hydroxyl-radical distribution as well as the measured dry deposition velocity to account for the variability in the tropospheric SO2 lifetime. It is the first effort to derive the local SO2 lifetime for application in the divergence method. The results show the application of the local SO2 lifetime improves the accuracy of SO2 emissions estimation when compared to calculations using a constant lifetime. Our improved flux-divergence method reduced the spreading of the point-source emissions compared to the standard flux-divergence method. Our derived averaged SO2 emissions covering the recent 5 years are about 5.2 Tg yr−1 with a monthly mean uncertainty of 40 %, which is lower than the bottom-up emissions of 11.0 Tg yr−1 from CAMS-GLOB-ANT v5.3. The total emissions from the 92 largest point-source emissions are estimated to be 2.9 Tg yr−1, lower than the estimation of 5.2 Tg yr−1 from the global SO2 catalog MSAQSO2LV4. We claim that the variability in the SO2 lifetime is important to account for in estimating top-down SO2 emissions.

An improved divergence method has been developed to estimate annual methane (CH4) emissions from TROPOspheric Monitoring Instrument (TROPOMI) observations. It has been applied to the period of 2018 to 2021 over the Middle East, where the orography is complicated, and the mean mixing ratio of methane (XCH4) might be affected by albedos or aerosols over some locations. To adapt to extreme changes of terrain over mountains or coasts, winds are used with their divergent part removed. A temporal filter is introduced to identify highly variable emissions and to further exclude fake sources caused by retrieval artifacts. We compare our results to widely used bottom-up anthropogenic emission inventories: Emissions Database for Global Atmospheric Research (EDGAR), Community Emissions Data System (CEDS), and Global Fuel Exploitation Inventory (GFEI) over several regions representing various types of sources. The NOx emissions are from EDGAR and Daily Emissions Constrained by Satellite Observations (DECSO), and the industrial heat sources identified by Visible Infrared Imaging Radiometer Suite (VIIRS) are further used to better understand our resulting methane emissions. Our results indicate possibly large underestimations of methane emissions in metropolises like Tehran (up to 50 %) and Isfahan (up to 70 %) in Iran. The derived annual methane emissions from oil/gas production near the Caspian Sea in Turkmenistan are comparable to GFEI but more than 2 times higher than EDGAR and CEDS in 2019. Large discrepancies in the distribution of methane sources in Riyadh and its surrounding areas are found between EDGAR, CEDS, GFEI, and our emissions. The methane emission from oil/gas production to the east of Riyadh seems to be largely overestimated by EDGAR and CEDS, while our estimates as well as GFEI and DECSO NOx indicate much lower emissions from industrial activities. On the other hand, regions like Iran, Iraq, and Oman are dominated by sources from oil and gas exploitation that probably include more irregular releases of methane, with the result that our estimates, which include only invariable sources, are lower than the bottom-up emission inventories.