PNNL

Abstract

Satellite-derived spatiotemporal patterns of nitrogen oxide (NOx) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we couple the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NOx emissions across US 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 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 then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05°×0.05° from 2018 to 2021. This database demonstrates a strong correlation (R = 0.90) with the national emission inventory (NEI) but reveals some bias (NMB = -0.24). There are noticeable differences in the spatial patterns of emissions in some cities, which suggests potential misallocation of emissions and/or missing sources in bottom-up emission inventories.