Methane detection and emission estimation from space: Benchmarking PRISMA and EnMAP with the GHGSat constellation

The use of satellite observations to detect and quantify methane emissions from localized sources is constantly increasing. The comparison between results generated by different sensors aboard satellites can be challenging due to differences in spatial and spectral resolution, retrieval approaches, and acquisition timing. In this study, we evaluate the capability of the PRISMA hyperspectral satellite to detect methane plumes and reproduce plume structures, benchmarking its methane detection and estimates against corresponding data provided by the GHGSat constellation. Geolocation refinement is applied to PRISMA imagery, followed by methane retrievals using the MAG1C algorithm. Results show that PRISMA detects almost 60% of the emission sources identified by GHGSat and reproduces the main spatial trends of methane enhancements along the plume. The analysis along the plume centerline highlights consistent patterns of higher methane concentrations near the source, followed by gradual dilution along the plume tail. A multi-sensor comparison, including EnMAP, further illustrates the temporal evolution of a plume by showing the observed methane flux trend over a two hour interval. Overall, the correlation between PRISMA and GHGSat flux estimates showed a Pearson coefficient of 0.95, although PRISMA systematically seems to reveal lower methane enhancements with respect to GHGSat. The results obtained in this work confirm that hyperspectral satellite observations can provide a consistent representation of methane plume dynamics across different sensors, looking forward robust cross-sensor analysis of emission sources.