Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Sentinel-2 Imagery

Methane (CH₄) emission estimates from top-down studies over oil and gas basins have revealed systematic underestimation of CH₄ emissions in current national inventories. Sparse but extremely large amounts of CH₄ from oil and gas production activities have been detected across the globe, resulting in a significant increase of the overall oil and gas contribution. However, attribution to specific facilities remains a major challenge unless high-spatial-resolution images provide sufficient granularity within the oil and gas basin. In this paper, we monitor known oil and gas infrastructures across the globe using recurrent Sentinel-2 imagery to detect and quantify more than 1200 CH₄ emissions. In combination with emission estimates from airborne and Sentinel-5P measurements, we demonstrate the robustness of the fit to a power law from 0.1 $$/h to 600 $$/h. We conclude here that the prevalence of ultraemitters (>25$$/h) detected globally by Sentinel-5P directly relates to emission occurrences below its detection threshold in the range >2$$/h, which correspond to large emitters covered by Sentinel-2. We also verified that this relation is also valid at a more local scale for two specific countries, namely, Algeria and Turkmenistan, and the Permian basin in the United States.