Top‐Down Estimates of U.S. NO <sub> <i>x</i> </sub> Emissions Using TEMPO and TROPOMI NO <sub>2</sub> Remote Sensing Observations With WRF‐Chem/Chem‐DART

Abstract The operation of geostationary (GEO) instruments such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) provides unprecedented hourly nitrogen dioxide (NO 2 ) observations compared to the once‐daily data from a low‐Earth orbit (LEO) platform like the TROPOspheric Monitoring Instrument (TROPOMI). This study investigates the performance and challenges of using TEMPO versus TROPOMI measurements to constrain anthropogenic nitrogen oxides (NO x ) emissions. The accuracy of TEMPO and TROPOMI NO 2 tropospheric columns are assessed using Pandora observations, finding a low bias of 9%–12.3% in TEMPO, and TROPOMI data during August 2023, while TEMPO midday and late afternoon observations are less of low bias. Top‐down NO x emissions derived by midday TEMPO and TROPOMI data are generally consistent over urban areas, being 5%–20% lower than bottom‐up emissions provided by the 2021 GReenhouse gas And Air Pollutants Emissions System (GRA 2 PES), and align with 2023 GRA 2 PES emissions, demonstrating the reliability of using satellite data for timely updates of bottom‐up inventories. However, assimilating additional morning/late afternoon TEMPO data leads to the poorest top‐down NO x emissions, likely resulting from larger negative measurement biases. NO x emission inversions effectively mitigate NO x overprediction, though the top‐down NO x emissions might be over‐corrected in urban cores. NO x emissions optimization also improves ozone forecasts by reducing the model's positive biases, especially when assimilating midday TEMPO data. Our study suggests that TEMPO midday observations provide better constraints on the magnitude and spatiotemporal variation of anthropogenic NO x emissions than TROPOMI, while morning TEMPO v3 data should be used cautiously due to potential negative impact on NO x emissions inversion.

Authors

Institutions

Publication Details

Journal
Journal of Geophysical Research Atmospheres
Published
2026-01-19
DOI
https://doi.org/10.1029/2025jd044223
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Top‐Down Estimates of U.S. NO x Emissions Using TEMPO and TROPOMI NO 2 Remote Sensing Observations With WRF‐Chem/Chem‐DART

Gonzalo González Abad, D. K. Henze, Arthur P. Mizzi, Chelsea E. Stockwell et al.
Journal of Geophysical Research Atmospheres
Atmospheric and Environmental Gas Dynamics
article

Top‐Down Estimates of U.S. NO x Emissions Using TEMPO and TROPOMI NO 2 Remote Sensing Observations With WRF‐Chem/Chem‐DART

Gonzalo González Abad, D. K. Henze, Arthur P. Mizzi, Chelsea E. Stockwell, Caroline R. Nowlan, Kristen Zuraski, Brian McDonald, Colin Harkins, Meng Li, Jian He, Chuanyu Xu, Chia‐Hua Hsu, Fangjun Li, Rebecca H. Schwantes, Eleanor M. Waxman, Shobha Kondragunta, Congmeng Lyu, Jeff Peischl, Owen R. Cooper, R. Bradley Pierce, Siyuan Wang, Andrew W. Rollins, Carsten Warneke, Xiong Liu
article en

Abstract

Abstract The operation of geostationary (GEO) instruments such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) provides unprecedented hourly nitrogen dioxide (NO 2 ) observations compared to the once‐daily data from a low‐Earth orbit (LEO) platform like the TROPOspheric Monitoring Instrument (TROPOMI). This study investigates the performance and challenges of using TEMPO versus TROPOMI measurements to constrain anthropogenic nitrogen oxides (NO x ) emissions. The accuracy of TEMPO and TROPOMI NO 2 tropospheric columns are assessed using Pandora observations, finding a low bias of 9%–12.3% in TEMPO, and TROPOMI data during August 2023, while TEMPO midday and late afternoon observations are less of low bias. Top‐down NO x emissions derived by midday TEMPO and TROPOMI data are generally consistent over urban areas, being 5%–20% lower than bottom‐up emissions provided by the 2021 GReenhouse gas And Air Pollutants Emissions System (GRA 2 PES), and align with 2023 GRA 2 PES emissions, demonstrating the reliability of using satellite data for timely updates of bottom‐up inventories. However, assimilating additional morning/late afternoon TEMPO data leads to the poorest top‐down NO x emissions, likely resulting from larger negative measurement biases. NO x emission inversions effectively mitigate NO x overprediction, though the top‐down NO x emissions might be over‐corrected in urban cores. NO x emissions optimization also improves ozone forecasts by reducing the model's positive biases, especially when assimilating midday TEMPO data. Our study suggests that TEMPO midday observations provide better constraints on the magnitude and spatiotemporal variation of anthropogenic NO x emissions than TROPOMI, while morning TEMPO v3 data should be used cautiously due to potential negative impact on NO x emissions inversion.

Journal of Geophysical Research AtmospheresVol. 131(2)
Ames Research Center (US), University of Wisconsin–Madison (US), Cooperative Institute for Research in Environmental Sciences (US), University of Colorado Boulder (US), Bay Area Environmental Research Institute (US), Geospatial Research (United Kingdom) (GB), Center for Astrophysics Harvard & Smithsonian (US), NOAA Chemical Sciences Laboratory (US), NOAA Center for Satellite Applications and Research (US), Science and Technology Corporation (Norway) (NO)
Sustainable cities and communities
Openalex Percentile: Top 87%
Atmospheric and Environmental Gas Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.