High-Resolution Mapping of Nitrogen Oxide Emissions from TROPOMI Retrievals of Tropospheric Nitrogen Dioxide Columns

Satellite-derived spatiotemporal patterns of nitrogen oxide (NO_x) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. We develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NO_x emissions for large cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO₂) retrievals. The accuracy of the coupled method is validated through application to synthetic NO₂ observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R = 0.99, Normalized Mean Bias, NMB = -0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R = 0.88 ± 0.06). We have developed a database utilizing TROPOMI measurements, which reports annual emissions for major cities with a spatial resolution of 0.05°×0.05° spanning the years 2018 to 2021. This database includes 39 US cities as well as other cities where emission estimates may carry significant uncertainties due to data scarcity. Comparisons between the derived TROPOMI-based gridded emissions and bottom-up emission inventories highlight discernible discrepancies in spatial emission patterns for certain cities. This discrepancy implies potential inaccuracies in the allocation of emissions or the omission of sources within bottom-up emission inventories.