High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns

Bibliographic Details
Title: High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns
Authors: F. Liu, S. Beirle, J. Joiner, S. Choi, Z. Tao, K. E. Knowland, S. J. Smith, D. Q. Tong, S. Ma, Z. T. Fasnacht, T. Wagner
Source: Atmospheric Chemistry and Physics, Vol 24, Pp 3717-3728 (2024)
Publisher Information: Copernicus Publications, 2024.
Publication Year: 2024
Collection: LCC:Physics
LCC:Chemistry
Subject Terms: Physics, QC1-999, Chemistry, QD1-999
More Details: 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1680-7316
1680-7324
Relation: https://acp.copernicus.org/articles/24/3717/2024/acp-24-3717-2024.pdf; https://doaj.org/toc/1680-7316; https://doaj.org/toc/1680-7324
DOI: 10.5194/acp-24-3717-2024
Access URL: https://doaj.org/article/0b8c6825eaa64cb08c1f3282381ec39a
Accession Number: edsdoj.0b8c6825eaa64cb08c1f3282381ec39a
Database: Directory of Open Access Journals
More Details
ISSN:16807316
16807324
DOI:10.5194/acp-24-3717-2024
Published in:Atmospheric Chemistry and Physics
Language:English