Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 12
Articles | Volume 18, issue 12
https://doi.org/10.5194/gmd-18-3607-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3607-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 12
Model description paper
 | 
18 Jun 2025
Model description paper |  | 18 Jun 2025

Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods

Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet

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Short summary
We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
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