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 (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

Abstract. The frequency and intensity of summer droughts and heat waves in Western Europe have been increasing, raising concerns about the emergence of fire hazard in less fire prone areas. This exposure of old-growth forests hosting unadapted tree species may cause disproportionately large biomass losses compared to those observed in frequently burned Mediterranean ecosystems. Therefore, analyzing fire seasons from the perspective of exposed burned areas alone is insufficient, we must also consider impacts on biomass loss. In this study, we focus on the exceptional 2022 summer fire season in France and use very high-resolution (10 m) satellite data to calculate the burned area, tree height at the national level, and the subsequent ecological impact based on biomass loss during fires. Our high resolution semi-automated detection estimated 42,520 ha of burned area, compared to the 66,393 ha estimated by the European automated remote sensing detection system (EFFIS), including 48,330 ha actually occurring in forests. We show that Mediterranean forests had a lower biomass loss than in previous years, whereas there was a drastic increase in burned area and biomass loss over the Atlantic pine forests and temperate forests. High biomass losses in the Atlantic pine forests were driven by the large burned area (28,600 ha in 2022 vs. 494 ha yr−1 in 2006–2021 period) but mitigated by a low exposed tree biomass mostly located on intensive management areas. Conversely, biomass loss in temperate forests was abnormally high due to both a 15-fold increase in burned area compared to previous years (3,300 ha in 2022 vs. 216 ha in the 2006–2021 period) and a high tree biomass of the forests which burned. Overall, the biomass loss (i.e. wood biomass dry weight) was 0.25 Mt in Mediterranean forests and shrublands, 1.74 Mt in the Atlantic pine forest, and 0.57 Mt in temperate forests, amounting to a total loss of 2.553 Mt, equivalent to a 17 % increase of the average natural mortality of all French forests, as reported by the national inventory. A comparison of biomass loss between our estimates and global biomass/burned areas data indicates that higher resolution improves the identification of small fire patches, reduces the commission errors with a more accurate delineation of the perimeter of each fire, and increases the biomass affected. This study paves the way for the development of low-latency, high-accuracy assessment of biomass losses and fire patch contours to deliver a more informative impact-based characterization of each fire year.

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.