A lightweight NO2-to-NOx conversion model for quantifying NOx emissions of point sources from NO2 satellite observations

Meier, Sandro; Koene, Erik F. M.; Krol, Maarten; Brunner, Dominik; Damm, Alexander; Kuhlmann, Gerrit

doi:https://doi.org/10.5194/acp-24-7667-2024

Articles | Volume 24, issue 13

https://doi.org/10.5194/acp-24-7667-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-24-7667-2024

© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 24, issue 13

Research article

|

05 Jul 2024

Research article |

| 05 Jul 2024

A lightweight NO₂-to-NO_x conversion model for quantifying NO_x emissions of point sources from NO₂ satellite observations

Sandro Meier, Erik F. M. Koene, Maarten Krol, Dominik Brunner, Alexander Damm, and Gerrit Kuhlmann

Supplement

https://doi.org/10.5194/acp-24-7667-2024-supplement

Data sets

CoCO2 WP4.1 Library of Plumes Erik Koene and Dominik Brunner https://doi.org/10.5281/zenodo.7448144

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

ERA5 hourly data on single levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.adbb2d47

Model code and software

The ddeq Python library for point source quantification from remote sensing images (version 1.0) (https://gitlab.com/empa503/remote-sensing/ddeq) Gerrit Kuhlmann et al. https://doi.org/10.5194/gmd-17-4773-2024

Download

Article (4384 KB)
Full-text XML

Short summary

Nitrogen oxides (NO_x = NO + NO₂) are important air pollutants. This study addresses the challenge of accurately estimating NO_x emissions from NO₂ satellite observations. We develop a realistic model to convert NO₂ to NO_x by using simulated plumes from various power plants. We apply the model to satellite NO₂ observations, significantly reducing biases in estimated NO_x emissions. The study highlights the potential for a consistent, high-resolution estimation of NO_x emissions using satellite data.