Global assessment of oil and gas methane ultra-emitters

An anthropocene-framed transdisciplinary dialog at the chemistry-energy nexus

At the energy-chemistry nexus, key molecules include carbon dioxide (CO2), hydrogen (H2), methane (CH4), and ammonia (NH3). The position of these four molecules and that of the more general family of synthetic macromolecular polymer blends (found in plastics) were cross-analyzed with the planetary boundary framework, and as part of five scientific policy roadmaps for the energy transition. According to the scenarios considered, the use of some of these molecular substances will be drastically modified in the coming years. Ammonia, which is currently almost exclusively synthesized as feedstock for the fertilizer industry, is envisioned as a future carbon-free energy vector. "Green hydrogen" is central to many projected decarbonized chemical processes. Carbon dioxide is forecast to shift from an unavoidable byproduct to a valuable feedstock for the production of carbon-based compounds. In this context, we believe that interdisciplinary elements from history, economics and anthropology are relevant to any attempted cross-analysis. Distinctive and crucial insights drawn from elements of humanities and social sciences have led us to formulate or re-raise open questions and possible blind-spots in main roadmaps, which were developed to guide, inter alia, chemical research toward the energy transition. We consider that these open questions are not sufficiently addressed in the academic arena around chemical research. Nevertheless, they are relevant to our understanding of the current planetary crisis, and to our capacity to properly assess the potential and limitations of chemical research addressing it. This academic perspective was written to share this understanding with the broader academic community. This work is intended not only as a call for a larger interdisciplinary method, to develop a sounder scientific approach to broader scenarios, but also - and perhaps mostly - as a call for the development of radically transdisciplinary routes of research. As scientists with different backgrounds, specialized in different disciplines and actively involved in contributing to shape solutions by means of our research, we bear ethical responsibility for the consequences of our acts, which often lead to consequences well beyond our discipline. Do our research and the knowledge it produces respond, perpetuate or even aggravate the problems encountered by society?

Automatic detection of methane emissions in multispectral satellite imagery using a vision transformer

Curbing methane emissions is among the most effective actions that can be taken to slow down global warming. However, monitoring emissions remains challenging, as detection methods have a limited quantification completeness due to trade-offs that have to be made between coverage, resolution, and detection accuracy. Here we show that deep learning can overcome the trade-off in terms of spectral resolution that comes with multi-spectral satellite data, resulting in a methane detection tool with global coverage and high temporal and spatial resolution. We compare our detections with airborne methane measurement campaigns, which suggests that our method can detect methane point sources in Sentinel-2 data down to plumes of 0.01 km2, corresponding to 200 to 300 kg CH4 h-1 sources. Our model shows an order of magnitude improvement over the state-of-the-art, providing a significant step towards the automated, high resolution detection of methane emissions at a global scale, every few days.

Experimental Study on Enhanced Methane Detection Using an MEMS-Pyroelectric Sensor Integrated with a Wavelet Algorithm

An optical sensing approach that balances portability with cost efficiency has been designed for the reliable monitoring of fugitive methane (CH4) emissions. Employing a LiTaO3-based pyroelectric detector integrated with micro-electro-mechanical systems and a broad infrared source, the developed gas sensor adeptly measured CH4 concentrations with a low limit of detection of about 5.6 ppmv and showed rapid response times with t90 consistently under 3 s. Notably, the novelty of our method lies in its precise control and reduction of CH4 levels, enhanced by wavelet denoising. This technique, optimized through meticulous grid search, effectively mitigated noise interference noticeable at CH4 levels below 10 ppmv. Postdenoising, nonlinear regression analyses based on the modified Beer-Lambert equation returned R2 values of 0.985 and 0.982 for the training and validation sets, respectively. In conclusion, this gas sensor has been shown to be able to meet the requirements for early warning of CH4 leakage on the surface in various carbon capture, utilization, and storage projects such as enhanced oil or gas recovery projects using CO2 injection.

On the Chemical Pathways Influencing the Effective Global Warming Potential of Commercial Hydrofluoroolefin Gases

The enforcement of a global hydrofluorocarbon (HFC) refrigerant phase down led to the introduction of hydrofluoroolefins (HFOs) as a low Global Warming Potential (GWP) substitute, given their low atmospheric lifetime. However, to this date it is not fully clear the long-term atmospheric fate of HFOs primary degradation products: trifluoro acetaldehyde (TFE), trifluoro acetyl fluoride (TFF), and trifluoroacetic acid (TFA). It particularly concerns the possibility of forming HFC-23, a potent global warming agent. Although the atmospheric reaction networks of TFE, TFF, and TFA have a fair level of complexity, the relevant atmospheric chemical pathways are well characterized in the literature, enabling a comprehensive hazard assessment of HFC-23 formation as a secondary HFO breakdown product in diverse scenarios. A lower bound of the HFOs effective GWP in a baseline scenario is found above regulatory thresholds. While further research is crucial to refine climate risk assessments, the existing evidence suggests a non-negligible climate hazard associated with HFOs.

A prospective life cycle assessment of global ammonia decarbonisation scenarios

A prospective life cycle assessment was performed for global ammonia production across 26 regions from 2020 to 2050. The analysis was based on the IEA Ammonia Roadmap and IMAGE electricity scenarios model for three climate scenarios related to a mean surface temperature increase of 3.5 °C, 2.0 °C, and 1.5 °C by 2100. Combining these models with a global perspective and new life cycle inventories improves ammonia's robustness, quality, and applicability in prospective life cycle assessments. It reveals that complete decarbonisation of the ammonia industry by 2050 is unlikely from a life cycle perspective because of residual emissions in the supply chain, even in the most ambitious scenario. However, strong policies in the 1.5 °C scenario could significantly reduce climate impacts by up to 70% per kilogram of ammonia. The cumulative greenhouse gas emissions from the ammonia supply chain between 2020 and 2050 are estimated at 24, 21, and 15 gigatonnes CO2-equivalent for the 3.5 °C, 2.0 °C, and 1.5 °C scenarios, respectively. The paper examines challenges in achieving these scenarios, noting that electrolysis-based (yellow) ammonia, contingent on electricity decarbonisation, offers a cleaner production pathway. However, achieving significant GHG reductions is complex, requiring advancements in technologies with lower readiness, like carbon capture and storage and methane pyrolysis. The study also discusses limitations such as the need to reduce urea demand, potential growth in ammonia as a fuel, reliance on CO2 transport and storage, expansion of renewable energy, raw material scarcity, and the longevity of existing plants. It highlights potential shifts in environmental impacts, such as increased land, metal, and mineral use in scenarios with growing renewable electricity and bioenergy with carbon capture and storage.

Subsidizing Grid-Based Electrolytic Hydrogen Will Increase Greenhouse Gas Emissions in Coal Dominated Power Systems

Clean hydrogen has the potential to serve as an energy carrier and feedstock in decarbonizing energy systems, especially in "hard-to-abate" sectors. Although many countries have implemented policies to promote electrolytic hydrogen development, the impact of these measures on costs of production and greenhouse gas emissions remains unclear. Our study conducts an integrated analysis of provincial levelized costs and life cycle greenhouse gas emissions for all hydrogen production types in China. We find that subsidies are critical to accelerate low carbon electrolytic hydrogen development. Subsidies on renewable-based hydrogen provide cost-effective carbon dioxide equivalent (CO2e) emission reductions. However, subsidies on grid-based hydrogen increase CO2e emissions even compared with coal-based hydrogen because grid electricity in China still relies heavily on coal power and likely will beyond 2030. In fact, CO2e emissions from grid-based hydrogen may increase further if China continues to approve new coal power plants. The levelized costs of renewable energy-based electrolytic hydrogen vary among provinces. Transporting renewable-based hydrogen through pipelines from low- to high-cost production regions reduces the national average levelized cost of renewables-based hydrogen but may increase the risk of hydrogen leakage and the resulting indirect warming effects. Our findings emphasize that policy and economic support for nonfossil electrolytic hydrogen is critical to avoid an increase in CO2e emissions as hydrogen use rises during a clean energy transition.

Increased methane emissions from oil and gas following the Soviet Union's collapse

Global atmospheric methane concentrations rose by 10 to 15 ppb/y in the 1980s before abruptly slowing to 2 to 8 ppb/y in the early 1990s. This period in the 1990s is known as the "methane slowdown" and has been attributed in part to the collapse of the former Soviet Union (USSR) in December 1991, which may have decreased the methane emissions from oil and gas operations. Here, we develop a methane plume detection system based on probabilistic deep learning and human-labeled training data. We use this method to detect methane plumes from Landsat 5 satellite observations over Turkmenistan from 1986 to 2011. We focus on Turkmenistan because economic data suggest it could account for half of the decline in oil and gas emissions from the former USSR. We find an increase in both the frequency of methane plume detections and the magnitude of methane emissions following the collapse of the USSR. We estimate a national loss rate from oil and gas infrastructure in Turkmenistan of more than 10% at times, which suggests the socioeconomic turmoil led to a lack of oversight and widespread infrastructure failure in the oil and gas sector. Our finding of increased oil and gas methane emissions from Turkmenistan following the USSR's collapse casts doubt on the long-standing hypothesis regarding the methane slowdown, begging the question: "what drove the 1992 methane slowdown?"

US oil and gas system emissions from nearly one million aerial site measurements

As airborne methane surveys of oil and gas systems continue to discover large emissions that are missing from official estimates1-4, the true scope of methane emissions from energy production has yet to be quantified. We integrate approximately one million aerial site measurements into regional emissions inventories for six regions in the USA, comprising 52% of onshore oil and 29% of gas production over 15 aerial campaigns. We construct complete emissions distributions for each, employing empirically grounded simulations to estimate small emissions. Total estimated emissions range from 0.75% (95% confidence interval (CI) 0.65%, 0.84%) of covered natural gas production in a high-productivity, gas-rich region to 9.63% (95% CI 9.04%, 10.39%) in a rapidly expanding, oil-focused region. The six-region weighted average is 2.95% (95% CI 2.79%, 3.14%), or roughly three times the national government inventory estimate5. Only 0.05-1.66% of well sites contribute the majority (50-79%) of well site emissions in 11 out of 15 surveys. Ancillary midstream facilities, including pipelines, contribute 18-57% of estimated regional emissions, similarly concentrated in a small number of point sources. Together, the emissions quantified here represent an annual loss of roughly US$1 billion in commercial gas value and a US$9.3 billion annual social cost6. Repeated, comprehensive, regional remote-sensing surveys offer a path to detect these low-frequency, high-consequence emissions for rapid mitigation, incorporation into official emissions inventories and a clear-eyed assessment of the most effective emission-finding technologies for a given region.

Increasing impacts of China's oil and gas demands on global CH4 emissions

The energy sector stands out as a main contributor to increasing global methane (CH4) emissions. Given China's heavy dependence on energy imports, a closer examination of its oil and gas-related CH4 emissions becomes imperative. This study conducts an in-depth analysis of China's contribution to global CH4 emissions stemming from its consumption of crude oil and natural gas since 2000. The results indicate that CH4 emissions from crude oil and natural gas imports rose from 614 Gg in 2000 to 7692 Gg in 2019. When considering domestic production, the demand-induced CH4 emissions in 2019 increased to approximately 10754 Gg (equivalent to 320 Mt CO2-eq and 887 Mt CO2-eq based on global warming potential (GWP) values at the 100-year and 20-year time period), of which 72 % were related to crude oil and natural gas imports. The primary contributor to this increase in CH4 emissions was the expansion of the trade scale. The growth trend of crude oil imports-induced CH4 emissions was also positively influenced by emission intensity and trade structure, but these two drivers had a negative impact on the growth of natural gas imports-induced CH4 emissions. The virtual transfer of CH4 emissions via international oil and gas trade requires urgent policy attention. In collaboration with its trading partners, China should take aggressive actions to achieve meaningful mitigation in CH4 emissions associated with the oil and gas trade.

Geostationary satellite observations of extreme and transient methane emissions from oil and gas infrastructure

We demonstrate geostationary satellite monitoring of large transient methane point sources with the US Geostationary Operational Environmental Satellites (GOES). GOES provides continuous 5- to 10-min coverage of the Americas at 1 to 2 km nadir pixel resolution in two shortwave infrared spectral bands from which large methane plumes can be retrieved. We track the full evolution of an extreme methane release from the El Encino-La Laguna natural gas pipeline in Durango, Mexico on 12 May 2019. The release lasted 3 h at a variable rate of 260 to 550 metric tons of methane per hour and totaled 1,130 to 1,380 metric tons. We report several other detections of transient point sources from oil/gas infrastructure, from which we infer a detection limit of 10 to 100 t h-1. Our results show that extreme releases of methane can last less than an hour, as from deliberate venting, and would thus be difficult to identify and quantify with low-Earth orbit satellites.

High-resolution assessment of coal mining methane emissions by satellite in Shanxi, China

Accurate assessment of coal mine methane (CMM) emissions is a prerequisite for defining baselines and assessing the effectiveness of mitigation measures. Such an endeavor is jeopardized, however, by large uncertainties in current CMM estimates. Here, we assimilated atmospheric methane column concentrations observed by the TROPOMI space borne instrument in a high-resolution regional inversion to estimate CMM emissions in Shanxi, a province representing 15% of the global coal production. The emissions are estimated to be 8.5 ± 0.6 and 8.6 ± 0.6 Tg CH4 yr-1 in 2019 and 2020, respectively, close to upper bound of current bottom-up estimates. Data from more than a thousand of individual mines indicate that our estimated emission factors increase significantly with coal mining depth at prefecture level, suggesting that ongoing deeper mining will increase CMM emission intensity. Our results show robustness of estimating CMM emissions utilizing TROPOMI images and highlight potential of monitoring methane leakages and emissions from satellites.

Assessing the Relative Importance of Satellite-Detected Methane Superemitters in Quantifying Total Emissions for Oil and Gas Production Areas in Algeria

Methane emissions from oil and gas production provide an important contribution to global warming. We investigate 2020 emissions from the largest gas field in Algeria, Hassi R'Mel, and the oil-production-dominated area Hassi Messaoud. We use methane data from the high-resolution (20 m) Sentinel-2 instruments to identify and estimate emission time series for 11 superemitters (including 10 unlit flares). We integrate this information in a transport model inversion that uses methane data from the coarser (7 km × 5.5 km) but higher-precision TROPOMI instrument to estimate emissions from both the 11 superemitters (>1 t/h individually) and the remaining diffuse area source (not detected as point sources with Sentinel-2). Compared to a bottom-up inventory for 2019 that is aligned with UNFCCC-reported emissions, we find that 2020 emissions in Hassi R'Mel (0.16 [0.11-0.22] Tg/yr) are lower by 53 [24-73]%, and emissions in Hassi Messaoud (0.22 [0.13-0.28] Tg/yr) are higher by 79 [4-188]%. Our analysis indicates that a larger fraction of Algeria's methane emissions (∼75%) come from oil production than national reporting suggests (5%). Although in both regions the diffuse area source constitutes the majority of emissions, relatively few satellite-detected superemitters provide a significant contribution (24 [12-40]% in Hassi R'Mel; 49 [27-71]% in Hassi Messaoud), indicating that mitigation efforts should address both. Our synergistic use of Sentinel-2 and TROPOMI can produce a unique and detailed emission characterization of oil and gas production areas.

Semantic segmentation of methane plumes with hyperspectral machine learning models

Methane is the second most important greenhouse gas contributor to climate change; at the same time its reduction has been denoted as one of the fastest pathways to preventing temperature growth due to its short atmospheric lifetime. In particular, the mitigation of active point-sources associated with the fossil fuel industry has a strong and cost-effective mitigation potential. Detection of methane plumes in remote sensing data is possible, but the existing approaches exhibit high false positive rates and need manual intervention. Machine learning research in this area is limited due to the lack of large real-world annotated datasets. In this work, we are publicly releasing a machine learning ready dataset with manually refined annotation of methane plumes. We present labelled hyperspectral data from the AVIRIS-NG sensor and provide simulated multispectral WorldView-3 views of the same data to allow for model benchmarking across hyperspectral and multispectral sensors. We propose sensor agnostic machine learning architectures, using classical methane enhancement products as input features. Our HyperSTARCOP model outperforms strong matched filter baseline by over 25% in F1 score, while reducing its false positive rate per classified tile by over 41.83%. Additionally, we demonstrate zero-shot generalisation of our trained model on data from the EMIT hyperspectral instrument, despite the differences in the spectral and spatial resolution between the two sensors: in an annotated subset of EMIT images HyperSTARCOP achieves a 40% gain in F1 score over the baseline.

Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space

Carbon dioxide and methane emissions are the two primary anthropogenic climate-forcing agents and an important source of uncertainty in the global carbon budget. Uncertainties are further magnified when emissions occur at fine spatial scales (<1 km), making attribution challenging. We present the first observations from NASA's Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer showing quantification and attribution of fine-scale methane (0.3 to 73 tonnes CH4 hour-1) and carbon dioxide sources (1571 to 3511 tonnes CO2 hour-1) spanning the oil and gas, waste, and energy sectors. For selected countries observed during the first 30 days of EMIT operations, methane emissions varied at a regional scale, with the largest total emissions observed for Turkmenistan (731 ± 148 tonnes CH4 hour-1). These results highlight the contributions of current and planned point source imagers in closing global carbon budgets.

Lipidomic diversity and proxy implications of archaea from cold seep sediments of the South China Sea

Cold seeps on the continental margins are characterized by intense microbial activities that consume a large portion of methane by anaerobic methanotrophic archaea (ANME) through anaerobic oxidation of methane (AOM). Although ANMEs are known to contain unique ether lipids that may have an important function in marine carbon cycling, their full lipidomic profiles and functional distribution in particular cold-seep settings are still poorly characterized. Here, we combined the 16S rRNA gene sequencing and lipidomic approaches to analyze archaeal communities and their lipids in cold seep sediments with distinct methane supplies from the South China Sea. The archaeal community was dominated by ANME-1 in the moderate seepage area with strong methane emission. Low seepage area presented higher archaeal diversity covering Lokiarchaeia, Bathyarchaeia, and Thermoplasmata. A total of 55 core lipids (CLs) and intact polar lipids (IPLs) of archaea were identified, which included glycerol dialkyl glycerol tetraethers (GDGTs), hydroxy-GDGTs (OH-GDGTs), archaeol (AR), hydroxyarchaeol (OH-AR), and dihydroxyarchaeol (2OH-AR). Diverse polar headgroups constituted the archaeal IPLs. High concentrations of dissolved inorganic carbon (DIC) with depleted δ13CDIC and high methane index (MI) values based on both CLs (MICL) and IPLs (MIIPL) indicate that ANMEs were active in the moderate seepage area. The ANME-2 and ANME-3 clades were characterized by enhanced glycosidic and phosphoric diether lipids production, indicating their potential role in coupling carbon and phosphurus cycling in cold seep ecosystems. ANME-1, though representing a smaller proportion of total archaea than ANME-2 and ANME-3 in the low seepage area, showed a positive correlation with MIIPL, indicating a different mechanism contributing to the IPL-GDGT pool. This also suggests that MIIPL could be a sensitive index to trace AOM activities performed by ANME-1. Overall, our study expands the understanding of the archaeal lipid composition in the cold seep and improves the application of MI using intact polar lipids that potentially link to extent ANME activities.

Global termite methane emissions have been affected by climate and land-use changes

Termites with symbiotic methanogens are a known source of atmospheric methane (CH4), but large uncertainties remain regarding the flux magnitude. This study estimated global termite CH4 emissions using a framework similar to previous studies but with contemporary datasets and a biogeochemical model. The global termite emission in 2020 was estimated as 14.8 ± 6.7 Tg CH4 year-1, mainly from tropical and subtropical ecosystems, indicating a major natural source from upland regions. Uncertainties associated with estimation methods were assessed. The emission during the historical period 1901-2021 was estimated to have increased gradually (+ 0.7 Tg CH4 year-1) as a result of combined influences of elevated CO2 (via vegetation productivity), climatic warming, and land-use change. Future projections using climate and land-use scenarios (shared socioeconomic pathways [ssp] 126 and 585) also showed increasing trends (+ 0.5 to 5.9 Tg CH4 year-1 by 2100). These results suggest the importance of termite emissions in the global CH4 budget and, thus, in climatic prediction and mitigation.

Global observational coverage of onshore oil and gas methane sources with TROPOMI

Satellite observations have been used to measure methane (CH4) emissions from the oil and gas (O&G) industry, particularly by revealing previously undocumented, very large emission events and basin-level emission estimates. However, most satellite systems use passive remote sensing to retrieve CH4 mixing ratios, which is sensitive to sunlight, earth surface properties, and atmospheric conditions. Accordingly, the reliability of satellites for routine CH4 emissions monitoring varies across the globe. To better understand the potentials and limitations of routine monitoring of CH4 emissions with satellites, we investigated the global observational coverage of the TROPOMI instrument onboard the Sentinel-5P satellite-the only satellite system currently with daily global coverage. A 0.1° × 0.1° gridded global map that indicates the average number of days with valid observations from TROPOMI for 2019-2021 was generated by following the measurement retrieval quality-assurance threshold (≥ 0.5). We found TROPOMI had promising observational coverage over dryland regions (maximum: 58.6%) but limited coverage over tropical regions and high latitudes (minimum: 0%). Cloud cover and solar zenith angle were the primary factors affecting observational coverage at high latitudes, while aerosol optical thickness was the primary factor over dryland regions. To further assess the country-level reliability of satellites for detecting and quantifying CH4 emissions from the onshore O&G sector, we extracted the average annual TROPOMI observational coverage (TOC) over onshore O&G infrastructure for 160 countries. Seven of the top-10 O&G-producing countries had an average annual TOC < 10% (< 36 days per year), which indicates the limited ability to routinely identify large emissions events, track their duration, and quantify emissions rates using inverse modelling. We further assessed the potential performance of the latter by combining TOC and the uncertainties from the global O&G inventory. Results indicate that the accuracy of emissions quantifications of onshore O&G sources using TROPOMI data and inverse modeling will be higher in countries located in dryland and mid-latitude regions and lower in tropical and high-latitude regions. Therefore, current passive-sensing satellites have low potential for frequent monitoring of large methane emissions from O&G sectors in countries located in tropical and high latitudes (e.g., Canada, Russia, Brazil, Norway, and Venezuela). Alternative methods should be considered for routine emissions monitoring in these regions.

National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations

Reducing methane emissions from fossil fuel exploitation (oil, gas, coal) is an important target for climate policy, but current national emission inventories submitted to the United Nations Framework Convention on Climate Change (UNFCCC) are highly uncertain. Here we use 22 months (May 2018-Feb 2020) of satellite observations from the TROPOMI instrument to better quantify national emissions worldwide by inverse analysis at up to 50 km resolution. We find global emissions of 62.7 ± 11.5 (2σ) Tg a-1 for oil-gas and 32.7 ± 5.2 Tg a-1 for coal. Oil-gas emissions are 30% higher than the global total from UNFCCC reports, mainly due to under-reporting by the four largest emitters including the US, Russia, Venezuela, and Turkmenistan. Eight countries have methane emission intensities from the oil-gas sector exceeding 5% of their gas production (20% for Venezuela, Iraq, and Angola), and lowering these intensities to the global average level of 2.4% would reduce global oil-gas emissions by 11 Tg a-1 or 18%.

Evaluation of Uncertainties in the Anthropogenic SO2 Emissions in the USA from the OMI Point Source Catalog

Satellite remote sensing is a promising method of monitoring emissions that may be missing in inventories, but the accuracy of these estimates is often not clear. We demonstrate here a comprehensive evaluation of errors in anthropogenic sulfur dioxide (SO₂) emission estimates from NASA's OMI point source catalog for the contiguous US by comparing emissions from the catalog with high-quality emission inventory data over different dimensions including size of individual sources, aggregate vs individual source errors, and potential bias in individual source estimates over time. For sources that are included in the catalog, we find that errors in aggregate (sum of error for all included sources) are relatively low. Errors for individual sources in any given year can be substantial, however, with over- or underestimates in terms of total error ranging from -80 to 110 kt (roughly 10-90th percentile). We find that these errors are not necessarily random over time and that there can be consistently positive or negative biases for individual sources. We did not find any overall statistical relationship between the degree of isolation of a source and bias, either at a 40 or 70 km scales. For a sub-set of sources where inventory emissions over a radius of 70 km around an OMI detection are larger than twice the emissions within 40 km, the OMI value is consistently overestimated. We find, as expected, that emission sources not included in the catalog are the largest aggregate source of difference between the satellite estimates and inventories, especially in more recent years where source emission magnitudes have been decreasing and note that trends in satellite detections do not necessarily track trends in total emissions. We find that the OMI-based SO₂ emissions are accurate in aggregate, when summed over a number of sources, but must be interpreted more cautiously at the individual source level. Similar analyses would be valuable for other satellite emission estimates; however, in many cases, the appropriate high-quality reference data may need to be generated.

Challenges and opportunities in the global methane cycle

To control the atmospheric methane concentration for Paris Agreement and Global Methane Pledge, it is urgent to elucidate global methane budget, in the context of dangerous high growth rate of atmospheric methane concentration in the past three years (2020-2022). Interdisciplinary research can definitely help answer the open questions about methane budget, as some examples shown in this Special Issue on "Methane emissions, sinks, and mitigation".

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

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 for this desert-based test. 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. Three-quarters (75%) 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 a 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 19-89% of total oil and natural gas system emissions detected in a recent survey of a high-emitting region.

Large increases in methane emissions expected from North America's largest wetland complex

Natural methane (CH₄) emissions from aquatic ecosystems may rise because of human-induced climate warming, although the magnitude of increase is highly uncertain. Using an exceptionally large CH₄ flux dataset (~19,000 chamber measurements) and remotely sensed information, we modeled plot- and landscape-scale wetland CH₄ emissions from the Prairie Pothole Region (PPR), North America's largest wetland complex. Plot-scale CH₄ emissions were driven by hydrology, temperature, vegetation, and wetland size. Historically, landscape-scale PPR wetland CH₄ emissions were largely dependent on total wetland extent. However, regardless of future wetland extent, PPR CH₄ emissions are predicted to increase by two- or threefold by 2100 under moderate or severe warming scenarios, respectively. Our findings suggest that international efforts to decrease atmospheric CH₄ concentrations should jointly account for anthropogenic and natural emissions to maintain climate mitigation targets to the end of the century.

Widespread Frequent Methane Emissions From the Oil and Gas Industry in the Permian Basin

Emissions of methane (CH₄) in the Permian basin (USA) have been derived for 2019 and 2020 from satellite observations of the Tropospheric Monitoring Instrument (TROPOMI) using the divergence method, in combination with a data driven method to estimate the background column densities. The resulting CH₄ emission data, which have been verified using model data with known emissions, have a spatial resolution of approximately 10 km. The CH₄ emissions show moderate spatial correlation with the locations of oil and gas production and drilling activities in the Permian basin, as well as with emissions of nitrogen oxides (NO_x). Analysis of the emission maps and time series indicates that a significant fraction of methane emissions in the Permian basin is from frequent widespread emissions sources, rather than from a few infrequent very large unplanned releases, which is important considering possible CH₄ emission mitigation strategies. In addition to providing spatially resolved emissions, the divergence method also provides the total emissions of the Permian basin and its main sub-basins. The total CH₄ emission of the Permian is estimated as 3.0 ± 0.7 Tg yr^-1 for 2019, which agrees with other independent estimates based on TROPOMI data. For the Delaware sub-basin, it is estimated as 1.4 ± 0.3 Tg yr^-1 for 2019, and for the Midland sub-basin 1.2 ± 0.3 Tg yr^-1. In 2020 the emissions are 9% lower compared to 2019 in the entire Permian basin, and respectively 19% and 27% for the Delaware and Midland sub-basins.

Assessing Detection Efficiencies for Continuous Methane Emission Monitoring Systems at Oil and Gas Production Sites

Continuous monitoring systems, consisting of multiple fixed sensors, are increasingly being deployed at oil and gas production sites to detect methane emissions. While these monitoring systems operate continuously, their efficiency in detecting emissions will depend on meteorological conditions, sensor detection limits, the number of sensors deployed, and sensor placement strategies. This work demonstrates an approach to assess the effectiveness of continuous sensor networks in detecting infinite-duration and fixed-duration emission events. The case studies examine a single idealized source and a group of nine different sources at varying heights and locations on a single pad. Using site-specific meteorological data and dispersion modeling, the emission detection performance is characterized. For these case studies, infinite-duration emission events are detected within 1 h to multiple days, depending on the number of sensors deployed. The percentage of fixed-duration emission events that are detected ranged from less than 10% to more than 90%, depending on the number of sources, emission release height, emission event duration, and the number of sensors deployed. While these results are specific to these case studies, the analysis framework described in this work can be broadly applied in the evaluation of continuous emission monitoring network designs.

Risk of the hydrogen economy for atmospheric methane

Hydrogen (H₂) is expected to play a crucial role in reducing greenhouse gas emissions. However, hydrogen losses to the atmosphere impact atmospheric chemistry, including positive feedback on methane (CH₄), the second most important greenhouse gas. Here we investigate through a minimalist model the response of atmospheric methane to fossil fuel displacement by hydrogen. We find that CH₄ concentration may increase or decrease depending on the amount of hydrogen lost to the atmosphere and the methane emissions associated with hydrogen production. Green H₂ can mitigate atmospheric methane if hydrogen losses throughout the value chain are below 9 ± 3%. Blue H₂ can reduce methane emissions only if methane losses are below 1%. We address and discuss the main uncertainties in our results and the implications for the decarbonization of the energy sector.

Recent Advances Toward Transparent Methane Emissions Monitoring: A Review

Given that anthropogenic greenhouse gas (GHG) emissions must be immediately reduced to avoid drastic increases in global temperature, methane emissions have been placed center stage in the fight against climate change. Methane has a significantly larger warming potential than carbon dioxide. A large percentage of methane emissions are in the form of industry emissions, some of which can now be readily identified and mitigated. This review considers recent advances in methane detection that allow accurate and transparent monitoring, which are needed for reducing uncertainty in source attribution and evaluating progress in emissions reductions. A particular focus is on complementary methods operating at different scales with applications for the oil and gas industry, allowing rapid detection of large point sources and addressing inconsistencies of emissions inventories. Emerging airborne and satellite imaging spectrometers are advancing our understanding and offer new top-down assessment methods to complement bottom-up methods. Successfully merging estimates across scales is vital for increased certainty regarding greenhouse gas emissions and can inform regulatory decisions. The development of comprehensive, transparent, and spatially resolved top-down and bottom-up inventories will be crucial for holding nations accountable for their climate commitments.

Role of space station instruments for improving tropical carbon flux estimates using atmospheric data

The tropics is the nexus for many of the remaining gaps in our knowledge of environmental science, including the carbon cycle and atmospheric chemistry, with dire consequences for our ability to describe the Earth system response to a warming world. Difficulties associated with accessibility, coordinated funding models and economic instabilities preclude the establishment of a dense pan-tropical ground-based atmospheric measurement network that would otherwise help to describe the evolving state of tropical ecosystems and the associated biosphere-atmosphere fluxes on decadal timescales. The growing number of relevant sensors aboard sun-synchronous polar orbiters provide invaluable information over the remote tropics, but a large fraction of the data collected along their orbits is from higher latitudes. The International Space Station (ISS), which is in a low-inclination, precessing orbit, has already demonstrated value as a proving ground for Earth observing atmospheric sensors and as a testbed for new technology. Because low-inclination orbits spend more time collecting data over the tropics, we argue that the ISS and its successors, offer key opportunities to host new Earth-observing atmospheric sensors that can lead to a step change in our understanding of tropical carbon fluxes.

Ethylene industrial emitters seen from space

Volatile organic compounds are emitted abundantly from a variety of natural and anthropogenic sources. However, in excess, they can severely degrade air quality. Their fluxes are currently poorly represented in inventories due to a lack of constraints from global measurements. Here, we track from space over 300 worldwide hotspots of ethylene, the most abundant industrially produced organic compound. We identify specific emitters associated with petrochemical clusters, steel plants, coal-related industries, and megacities. Satellite-derived fluxes reveal that the ethylene emissions of the industrial sources are underestimated or missing in the state-of-the-art Emission Database for Global Atmospheric Research (EDGAR) inventory. This work exposes global emission point-sources of a short-lived carbonated gas, complementing the ongoing large-scale efforts on the monitoring of inorganic pollutants.

On the use of Earth Observation to support estimates of national greenhouse gas emissions and sinks for the Global stocktake process: lessons learned from ESA-CCI RECCAP2

The Global Stocktake (GST), implemented by the Paris Agreement, requires rapid developments in the capabilities to quantify annual greenhouse gas (GHG) emissions and removals consistently from the global to the national scale and improvements to national GHG inventories. In particular, new capabilities are needed for accurate attribution of sources and sinks and their trends to natural and anthropogenic processes. On the one hand, this is still a major challenge as national GHG inventories follow globally harmonized methodologies based on the guidelines established by the Intergovernmental Panel on Climate Change, but these can be implemented differently for individual countries. Moreover, in many countries the capability to systematically produce detailed and annually updated GHG inventories is still lacking. On the other hand, spatially-explicit datasets quantifying sources and sinks of carbon dioxide, methane and nitrous oxide emissions from Earth Observations (EO) are still limited by many sources of uncertainty. While national GHG inventories follow diverse methodologies depending on the availability of activity data in the different countries, the proposed comparison with EO-based estimates can help improve our understanding of the comparability of the estimates published by the different countries. Indeed, EO networks and satellite platforms have seen a massive expansion in the past decade, now covering a wide range of essential climate variables and offering high potential to improve the quantification of global and regional GHG budgets and advance process understanding. Yet, there is no EO data that quantifies greenhouse gas fluxes directly, rather there are observations of variables or proxies that can be transformed into fluxes using models. Here, we report results and lessons from the ESA-CCI RECCAP2 project, whose goal was to engage with National Inventory Agencies to improve understanding about the methods used by each community to estimate sources and sinks of GHGs and to evaluate the potential for satellite and in-situ EO to improve national GHG estimates. Based on this dialogue and recent studies, we discuss the potential of EO approaches to provide estimates of GHG budgets that can be compared with those of national GHG inventories. We outline a roadmap for implementation of an EO carbon-monitoring program that can contribute to the Paris Agreement.

Inefficient and unlit natural gas flares both emit large quantities of methane

Flaring is widely used by the fossil fuel industry to dispose of natural gas. Industry and governments generally assume that flares remain lit and destroy methane, the predominant component of natural gas, with 98% efficiency. Neither assumption, however, is based on real-world observations. We calculate flare efficiency using airborne sampling across three basins responsible for >80% of US flaring and combine these observations with unlit flare prevalence surveys. We find that both unlit flares and inefficient combustion contribute comparably to ineffective methane destruction, with flares effectively destroying only 91.1% (90.2, 91.8; 95% confidence interval) of methane. This represents a fivefold increase in methane emissions above present assumptions and constitutes 4 to 10% of total US oil and gas methane emissions, highlighting a previously underappreciated methane source and mitigation opportunity.

Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the United States

Understanding, prioritizing, and mitigating methane (CH₄) emissions requires quantifying CH₄ budgets from facility scales to regional scales with the ability to differentiate between source sectors. We deployed a tiered observing system for multiple basins in the United States (San Joaquin Valley, Uinta, Denver-Julesburg, Permian, Marcellus). We quantify strong point source emissions (>10 kg CH₄ h^-1) using airborne imaging spectrometers, attribute them to sectors, and assess their intermittency with multiple revisits. We compare these point source emissions to total basin CH₄ fluxes derived from inversion of Sentinel-5p satellite CH₄ observations. Across basins, point sources make up on average 40% of the regional flux. We sampled some basins several times across multiple months and years and find a distinct bimodal structure to emission timescales: the total point source budget is split nearly in half by short-lasting and long-lasting emission events. With the increasing airborne and satellite observing capabilities planned for the near future, tiered observing systems will more fully quantify and attribute CH₄ emissions from facility to regional scales, which is needed to effectively and efficiently reduce methane emissions.

Locating and Quantifying Methane Emissions by Inverse Analysis of Path-Integrated Concentration Data Using a Markov-Chain Monte Carlo Approach

The action to reduce anthropogenic greenhouse gas emissions is severely constrained by the difficulty of locating sources and quantifying their emission rates. Methane emissions by the energy sector are of particular concern. We report results achieved with a new area monitoring approach using laser dispersion spectroscopy to measure path-averaged concentrations along multiple beams. The method is generally applicable to greenhouse gases, but this work is focused on methane. Nineteen calibrated methane releases in four distinct configurations, including three separate blind trials, were made within a flat test area of 175 m by 175 m. Using a Gaussian plume gas dispersion model, driven by wind velocity data, we calculate the data anticipated for hundreds of automatically proposed candidate source configurations. The Markov-chain Monte Carlo analysis finds source locations and emission rates whose calculated path-averaged concentrations are consistent with those measured and associated uncertainties. This approach found the correct number of sources and located them to be within <9 m in more than 75% of the cases. The relative accuracy of the mass emission rate results was highly correlated to the localization accuracy and better than 30% in 70% of the cases. The discrepancies for mass emission rates were <2 kg/h for 95% of the cases.

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 tCH4/h to 600 tCH4/h. We conclude here that the prevalence of ultraemitters (>25tCH4/h) detected globally by Sentinel-5P directly relates to emission occurrences below its detection threshold in the range >2tCH4/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.

Monitoring methane emissions from oil and gas operations‡

The atmospheric concentration of methane has more than doubled since the start of the Industrial Revolution. Methane is the second-most-abundant greenhouse gas created by human activities and a major driver of climate change. This APS-Optica report provides a technical assessment of the current state of monitoring U.S. methane emissions from oil and gas operations, which accounts for roughly 30% of U.S. anthropogenic methane emissions. The report identifies current technological and policy gaps and makes recommendations for the federal government in three key areas: methane emissions detection, reliable and systematized data and models to support mitigation measures, and effective regulation.

Chasing after methane's ultra-emitters

[Figure: see text].