Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Imagery.

Methane (CH) emission estimates from top-down studies over oil and gas basins have revealed systematic underestimation of CH emissions in current national inventories. Sparse but extremely large amounts of CH 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 imagery to detect and quantify more than 1200 CH emissions. In combination with emission estimates from airborne and 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 directly relates to emission occurrences below its detection threshold in the range >2/h, which correspond to large emitters covered by . 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.