Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 18, issue 23
Articles | Volume 18, issue 23
https://doi.org/10.5194/amt-18-7497-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-18-7497-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 23
Research article
 | 
09 Dec 2025
Research article |  | 09 Dec 2025

Development and validation of satellite-derived surface NO2 estimates using machine learning versus traditional approaches in North America

Debora Griffin, Colin Hempel, Chris McLinden, Shailesh Kumar Kharol, Colin Lee, Andre Fogal, Christopher Sioris, Mark Shephard, and Yuan You

Data sets

Air Quality System Data Mart U.S. Environmental Protection Agency https://www.epa.gov/outdoor-air-quality-data

Hourly NO$_2$ surface concentrations National Air Pollution Surveillance Program https://www.canada.ca/en/environment-climate-change/services/air-pollution/monitoring-networks-data/national-air-pollution-program.html

TROPOMI NO2 surface concentrations D. Griffin et al. https://hpfx.collab.science.gc.ca/~deg001/surfaceNO2

TROPOMI Level 2 Nitrogen Dioxide total column products, Version 02 Copernicus Sentinel-5P https://doi.org/10.5270/S5P-9bnp8q8

Model code and software

TROPOMI NO2 surface concentrations python code D. Griffin et al. https://doi.org/10.5281/zenodo.17653066

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Short summary
NO2 surface concentrations are obtained across North America using satellite data and machine learning, and compared to traditional approaches to determine surface NO2 from satellite observations.
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