Impact Plan ML

Project Aerosol

We use machine learning techniques to detect methane plumes in satellite data. The first project focused on detection of methane plumes in TROPOMI data. We use machine learning techniques to scan through millions of methane observations to find methane plumes originating from super-emitters. When combined with targeted high-resolution observations, this allows us to pinpoint large leaks, enabling mitigation activities (see IMEO Mars). This work is described in Schuit et al, 2023, and forms the basis for our weekly plume detections that you can find at our dedicated page.

In the next step of the project, we will apply machine learning to other (high-resolution) satellite datasets.

All methane plumes detected in 2021 TROPOMI data, grouped into one of the four dominant anthropogenic source types based on bottom-up emission inventories (Schuit et. al., 2023)


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