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| 6 Aug 2026 | |
| Reports |
Satellites and other remote sensing technologies can now detect methane plumes that were previously invisible, identifying leaks at oil and gas facilities, landfills, and coal mines worldwide. As these capabilities move from research into operational use, ensuring that measurements are reliable and comparable across different instruments and analytical approaches becomes essential. Annmarie Eldering, Senior Fellow at the Data Foundation's Center for Climate and Environmental Data, led this intercomparison study as the second in a series examining how different analytical teams interpret identical satellite measurements.
The first study released by the Data Foundation used NASA's EMIT instrument to test whether teams could agree with each other on detecting plumes, identifying the location of the start of the plume, and quantifying emissions. This study goes a step further, using data from the German Aerospace Center's EnMAP instrument alongside controlled release experiments, where known quantities of methane were deliberately emitted and then measured. That design makes it possible to assess not just whether analysts agree, but whether they are getting the right answers. It also extends the analysis to emission rates roughly 10 times lower than those examined in the EMIT study. A significant fraction or emissions (and leaks) occur at these lower emission rates. This study improves trust in technology to detect and quantify these lower emissions rates and expands the evidence base to a broader range of real-world sources.
As more organizations develop detection and quantification capabilities, understanding these methodological differences is important for building confidence in the data and for enabling the use of multiple datasets together. To support this rapidly growing field, the Data Foundation launched the Methane Plume Remote Sensing Measurements Technical Working Group (MP TWG) to support the rapidly growing field of remote sensing for the detection and quantification of methane emissions. By fostering collaboration across the technical community, the MP TWG aims to increase consistency across products and results, improve understanding of what drives measurement error, and advance a well-constructed validation strategy that builds trust in the data.
