Routine estimate of global 10-day mean maps of the anthropogenic NOx, SO2 and NH3 emissions over land since 2019 based on satellite observations

Ammonia (NH3), nitrogen oxides (NOx) and sulfur dioxide (SO2) are key precursors of secondary inorganic aerosols and strongly influence air quality, nitrogen deposition and ecosystem health. Yet bottom-up emission inventories and the temporal profiles for these species remain highly uncertain and often inconsistent across regions and sectors. Here we present a global dataset of anthropogenic NOx, SO2 and NH3 emissions over land, providing estimates of the daily 10-day mean emission fields since 2019 at 1.27° × 2.5° resolution. Emissions are derived from an atmospheric transport and chemistry inverse modelling system based on the global chemistry transport model LMDZ-INCA and a finite-difference mass-balance (FDMB) inversion approach. We account for satellite retrieval operators by consistently applying averaging kernels to the modeled NO2, SO2 and NH3 fields prior to model–observation comparison and emissions inversion. For NOx and SO2, we assimilate tropospheric NO2 columns from TROPOMI, with OMI-based NOx inversions used for consistency checks. For NH3, we use IASI total columns. The TROPOMI- and OMI-based NOx inversions show similar large-scale spatial patterns but differ regionally in magnitude, and generally indicate higher NOx emissions than bottom-up inventories over major source regions such as China and India. The TROPOMI-based SO2 inversions suggest lower anthropogenic SO2 emissions than bottom-up inventories at the global scale and across most major source regions, with global totals remaining relatively stable over 2019–2023. For NH3, the IASI-based inversion reveals persistent hotspots over South and East Asia—especially India and China—where inferred emissions exceed estimates from inventories, with pronounced seasonal peaks in high-emitting regions. Our dataset provides retrieval-consistent, time-resolved constraints on major aerosol precursors and implies systematic discrepancies between bottom-up inventories and satellite-constrained emissions over major source regions. The presentation details the methodological choices ensuring the routine estimates of such global maps of emissions, the relevance of their relatively high resolution, and investigations for a joint inversion of the three species to strengthen the consistency of the overall dataset.