Global Assessment of Oil and Gas Methane Ultra-Emitters

Lauvaux, Thomas; Giron, Clément; Mazzolini, Matthieu; d’Aspremont, Alexandre; Duren, Riley; Cusworth, Daniel H.; Shindell, D. T.; Ciais, Philippe

doi:10.31223/x5ns54

Cited by 20 publications

(39 citation statements)

References 31 publications

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“…Methane emissions mainly originate from venting natural gas at extraction wells and natural gas leaks or releases during pipeline transport. These sources and emitted quantities reflect common procedures of the natural gas industry and the status of its infrastructure -both exhibit high geographical variability, in which so-called "super-emitters" play an important role 38 . In some countries (e.g., Norway, Netherlands, UK) the natural gas industry demonstrates that near-zero leakage rates are possible; yet, huge regional differences remain with some countries having average leakage rates of 1.5%-2.5% (e.g., USA, Russia) and higher (e.g., Algeria, Libya) 39 .…”

Section: Life-cycle Ghg Emissions Of Blue Hydrogenmentioning

confidence: 99%

On the cost competitiveness of blue and green hydrogen

Ueckerdt

Verpoort

Anantharaman

et al. 2022

Preprint

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Hydrogen is indispensable for climate change mitigation; yet, it is unclear to what extent blue hydrogen from natural gas with carbon capture and storage will complement green hydrogen from renewable electricity. Today, green hydrogen costs are higher than those of blue hydrogen, and, despite huge cost reduction potential, it is uncertain when cost parity will be achieved. However, by combining data on costs and life-cycle emissions, we show that hydrogen’s competitiveness is increasingly determined by carbon costs associated with different life-cycle emissions across fuels. To become competitive, green hydrogen requires > 90% renewable electricity input, whereas blue hydrogen requires > 90% net CO2 capture rates and close-to-zero methane leakage. For a broad parameter range, we show that by 2035-40, green hydrogen can become the cheapest hydrogen option. Low-emission blue hydrogen may play a valuable role in bridging the scarcity of green hydrogen; yet, depending on regional circumstances it may have a limited window of competitiveness.

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Section: Life-cycle Ghg Emissions Of Blue Hydrogenmentioning

confidence: 99%

On the cost competitiveness of blue and green hydrogen

Ueckerdt

Verpoort

Anantharaman

et al. 2022

Preprint

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“…For example, the TROPOMI instrument of the Sentinel-5P satellite achieves global coverage with daily revisit time, but primarily detects emissions of 10 metric tons of methane per hour or greater (hereafter t/h, measured on mass of methane basis unless otherwise stated). This is due to the large effective pixel size of the TROPOMI instrument, roughly 7x7 km 8 . Sentinel-2 and Landsat 8 passively cover nearly the entire world's landmass with per-satellite revisit times of 10 and 16 days, respectively, with teams reanalyzing these data advertising minimum detection limits of 1-3 t/h 5,13 .…”

Section: Single-blind Testingmentioning

confidence: 99%

Single-blind validation of space-based point-source methane emissions detection and quantification

Sherwin¹,

Rutherford²,

Chen³

et al. 2023

Preprint

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Satellites are increasingly seen as a tool for identifying large greenhouse gas point sources for mitigation, but independent verification of satellite performance is needed for acceptance and use by policy makers and stakeholders. We conduct to our knowledge the first single-blind controlled methane release testing of satellite-based methane emissions detection and quantification, with five independent teams analyzing data from one to five satellites each. Teams correctly identified 71% of all emissions, ranging from 0.20 [0.19, 0.21] metric tons per hour (t/h) to 7.2 [6.8, 7.6] t/h. Over three-quarters (78%) of quantified estimates fell within ±50% of the metered value, comparable to airplane-based remote sensing technologies. The relatively wide-area Sentinel-2 and Landsat 8 satellites detected emissions as low as 1.4 [1.3, 1.5, 95% confidence interval] t/h, while GHGSat’s targeted system quantified an 0.20 [0.19, 0.21] t/h emission to within 13%. While the fraction of global methane emissions detectable by satellite remains unknown, we estimate that satellite networks could see 18-81% of total oil and natural gas system emissions detected in a recent survey of a high-emitting basin.

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“…The level 2 (L2) product provides a quantification of methane and is already being used by private and public actors to identify and track incidents leading to large methane emissions (Lauvaux et al, 2021). However, these detections are manually identified.…”

Section: Introductionmentioning

confidence: 99%

“…Statistical modeling allows us to control the number of false positives. To validate the method, we compare our detections with a recently proposed dataset (Lauvaux et al, 2021) of manually annotated plumes on the Sentinel-5P L2 methane product. We also compare our detection rate to the detection rate of the method proposed by (Ouerghi et al, 2021) which is also an automatic detection method.…”

Section: Introductionmentioning

confidence: 99%

Automatic Methane Plumes Detection in Time Series of Sentinel-5p L1b Images

Ouerghi

Ehret

Franchis

et al. 2022

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Reducing methane emissions is essential to tackle climate change. Here, we address the problem of detecting automatically large methane leaks using hyperspectral data from the Level 1B product of the Sentinel-5P satellite. To do this, two features of TROPOMI (TROPOspheric Monitoring Instrument), the Sentinel-5P satellite sensor, are exploited. The first one is the fine spectral sampling of the data which allows to isolate features of the methane absorption spectrum in the shortwave infrared wavelength range (SWIR). The second one is the daily coverage of the whole Earth which allows to perform time series analysis. Our method involves three main steps: i) a pixel reconstruction, ii) an angle correction and iii) a plume detection with a time series. In the first step, a simplified absorption model is inverted to recover, for each pixel, a coefficient representative of the presence of methane which we call the methane coefficient. In the second step, a correction is made to the methane coefficient to take into account the viewing angle of the satellite. In the third step, the obtained coefficient is normalized spatially and then the detection is carried out pixel by pixel, by looking for anomalies in a time series. We validate our method by comparing the detected plumes against a recently published dataset of plumes manually detected in the Sentinel-5P L2 methane product. We then show how our method can complement the Sentinel-5P L2 methane product for the detection of methane plumes.

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Global Assessment of Oil and Gas Methane Ultra-Emitters

Cited by 20 publications

References 31 publications

On the cost competitiveness of blue and green hydrogen

On the cost competitiveness of blue and green hydrogen

Single-blind validation of space-based point-source methane emissions detection and quantification

Automatic Methane Plumes Detection in Time Series of Sentinel-5p L1b Images

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