High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns
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- Morgan State Univ., Baltimore, MD (United States). Goddard Earth Sciences Technology and Research (GESTAR) II; NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
- Max Planck Society, Mainz (Germany). Max Planck Inst. for Chemistry
- NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
- NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States); Science Systems and Applications Inc., Lanham, MD (United States)
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States). Joint Global Change Research Institute
- George Mason Univ., Fairfax, VA (United States)
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 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 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 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 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. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.
- Research Organization:
- Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE; National Aeronautics and Space Administration (NASA)
- Grant/Contract Number:
- AC05-76RL01830; 80NSSC19K0980
- OSTI ID:
- 2336734
- Report Number(s):
- PNNL-SA-186789
- Journal Information:
- Atmospheric Chemistry and Physics (Online), Vol. 24, Issue 6; ISSN 1680-7324
- Publisher:
- Copernicus Publications, EGUCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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