Methane emissions from oil and gas (O&G) production and transmission represent a considerable contribution to climate change. These emissions comprise sporadic releases of large amounts of methane during maintenance operations or equipment failures not accounted for in current inventory estimates. We collected and analyzed hundreds of very large releases from atmospheric methane images sampled by the TROPOspheric Monitoring Instrument (TROPOMI) between 2019 and 2020. Ultra-emitters are primarily detected over the largest O&G basins throughout the world. With a total contribution equivalent to 8 to 12% (~8 million metric tons of methane per year) of the global O&G production methane emissions, mitigation of ultra-emitters is largely achievable at low costs and would lead to robust net benefits in billions of US dollars for the six major O&G-producing countries when considering societal costs of methane.

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.

Methane emissions from oil and gas (O&G) production and transmission represent a significant contribution to climate change. These emissions comprise sporadic releases of large amounts of methane during maintenance operations or equipment failures not accounted for in current inventory estimates. We collected and analyzed hundreds of very large releases from atmospheric methane images sampled by the TROPOspheric Monitoring Instrument (TROPOMI) over 2019 and 2020 to quantify emissions from O&G ultra-emitters. Ultra-emitters are primarily detected over the largest O&G basins of the world, following a power-law relationship with noticeable variations across countries but similar regression slopes. With a total contribution equivalent to 8-12% (~8 MtCH4.yr -1 ) of the global O&G production methane emissions, mitigation of ultra-emitters is largely achievable at low costs and would lead to robust net benefits in billions of US dollars for the six major producing countries when incorporating recent estimates of societal costs of methane.

Methane (CH 4 ) emissions estimates from top-down studies over oil and gas basins have revealed systematic under-estimation of CH 4 emissions in current national inventories. Sparse but extremely large amounts of CH 4 from oil and gas production activities have been detected across the globe, resulting in a significant increase of the overall O&G contribution. However, attribution to specific facilities remains a major challenge unless high-resolution images provide the sufficient granularity within O&G 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 800 CH 4 leaks.In combination with leak emissions estimates from airborne and Sentinel-5P measurements, we demonstrate the robustness of the fit to a power law from 100 kg CH 4 /hr to 600 t CH 4 /hr. We conclude here that the prevalence of ultra-emitters (>25t CH 4 /hr) detected globally by Sentinel-5P directly relates to leak occurrences below its detection

Methane emissions monitoring is essential to control methane pollution. In this paper, we propose an automatic practical methodology using time series to estimate the quantity of methane in a given plume using a multispectral satellite like Sentinel-2. Sentinel-2 proposes a low revisit time, a good spatial resolution and a low acquisition cost. Contrary to previous methods, the proposed approach does not require a manual selection of an optimal reference image. We compared its performance on an oil-and-gas site in Kazakhstan. This is the first step toward an automatic global monitoring system for methane plume detection and quantification with these satellites.