Search

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.

Nationally reported greenhouse gas inventories are a core component of the Paris Agreement's transparency framework. Comparisons with emission estimates derived from atmospheric observations help identify improvements to reduce uncertainties and increase the confidence in reported values. To facilitate comparisons over the contiguous United States, we present a 0.1° × 0.1° gridded inventory of annual 2012-2018 anthropogenic methane emissions, allocated to 26 individual source categories, with scale-dependent error estimates. Our inventory is consistent with the U.S. Environmental Protection Agency (EPA) Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI), submitted to the United Nations in 2020. Total emissions and patterns (spatial/temporal) reflect the activity and emission factor data underlying the GHGI, including many updates relative to a previous gridded version of the GHGI that has been extensively compared with observations. These underlying data are not generally available in global gridded inventories, and comparison to EDGAR version 6 shows large spatial differences, particularly for the oil and gas sectors. We also find strong regional variability across all sources in annual 2012-2018 spatial trends, highlighting the importance of understanding regional- and facility-level activities. Our inventory represents the first time series of gridded GHGI methane emissions and enables robust comparisons of emissions and their trends with atmospheric observations.

The United States is the world's largest oil/gas methane emitter according to current national reports. Reducing these emissions is a top priority in the US government's climate action plan. Here, we use a 2010 to 2019 high-resolution inversion of surface and satellite observations of atmospheric methane to quantify emission trends for individual oil/gas production regions in North America and relate them to production and infrastructure. We estimate a mean US oil/gas methane emission of 14.8 (12.4 to 16.5) Tg a -1 for 2010 to 2019, 70% higher than reported by the US Environmental Protection Agency. While emissions in Canada and Mexico decreased over the period, US emissions increased from 2010 to 2014, decreased until 2017, and rose again afterward. Increases were driven by the largest production regions (Permian, Anadarko, Marcellus), while emissions in the smaller production regions generally decreased. Much of the year-to-year emission variability can be explained by oil/gas production rates, active well counts, and new wells drilled, with the 2014 to 2017 decrease driven by reduction in new wells and the 2017 to 2019 surge driven by upswing of production. We find a steady decrease in the oil/gas methane intensity (emission per unit methane gas production) for almost all major US production regions. The mean US methane intensity decreased from 3.7% in 2010 to 2.5% in 2019. If the methane intensity for the oil/gas supply chain continues to decrease at this pace, we may expect a 32% decrease in US oil/gas emissions by 2030 despite projected increases in production.

As atmospheric methane concentrations increase at record pace, it is critical to identify individual emission sources with high potential for mitigation. Here, we leverage the synergy between satellite instruments with different spatiotemporal coverage and resolution to detect and quantify emissions from individual landfills. We use the global surveying Tropospheric Monitoring Instrument (TROPOMI) to identify large emission hot spots and then zoom in with high-resolution target-mode observations from the GHGSat instrument suite to identify the responsible facilities and characterize their emissions. Using this approach, we detect and analyze strongly emitting landfills (3 to 29 t hour -1 ) in Buenos Aires, Delhi, Lahore, and Mumbai. Using TROPOMI data in an inversion, we find that city-level emissions are 1.4 to 2.6 times larger than reported in commonly used emission inventories and that the landfills contribute 6 to 50% of those emissions. Our work demonstrates how complementary satellites enable global detection, identification, and monitoring of methane superemitters at the facility level.

We aim to reduce uncertainties in CH 2 O and other volatile organic carbon (VOC) emissions through assimilation of remote sensing data. We first update a three-dimensional (3D) chemical transport model, GEOS-Chem with the KORUSv5 anthropogenic emission inventory and inclusion of chemistry for aromatics and C 2 H 4 , leading to modest improvements in simulation of CH 2 O (normalized mean bias (NMB): -0.57 to -0.51) and O 3 (NMB: -0.25 to -0.19) compared against DC-8 aircraft measurements during KORUS-AQ; the mixing ratio of most VOC species are still underestimated. We next constrain VOC emissions using CH 2 O observations from two satellites (OMI and OMPS) and the DC-8 aircraft during KORUS-AQ. To utilize data from multiple platforms in a consistent manner, we develop a two-step Hybrid Iterative Finite Difference Mass Balance and four-dimensional variational inversion system (Hybrid IFDMB-4DVar). The total VOC emissions throughout the domain increase by 47%. The a posteriori simulation reduces the low biases of simulated CH 2 O (NMB: -0.51 to -0.15), O 3 (NMB: -0.19 to -0.06), and VOCs. Alterations to the VOC speciation from the 4D-Var inversion include increases of biogenic isoprene emissions in Korea and anthropogenic emissions in Eastern China. We find that the IFDMB method alone is adequate for reducing the low biases of VOCs in general; however, 4D-Var provides additional refinement of high-resolution emissions and their speciation. Defining reasonable emission errors and choosing optimal regularization parameters are crucial parts of the inversion system. Our new hybrid inversion framework can be applied for future air quality campaigns, maximizing the value of integrating measurements from current and upcoming geostationary satellite instruments., (© 2022 The Authors.)

Reduction of fossil fuel-related methane emissions has been identified as an essential means for climate change mitigation, but emission source identification remains elusive for most oil and gas production basins in the world. We combine three complementary satellite data sets to survey single methane emission sources on the west coast of Turkmenistan, one of the largest methane hotspots in the world. We found 29 different emitters, with emission rates >1800 kg/h, active in the 2017-2020 time period, although older satellite data show that this type of emission has been occurring for decades. We find that all sources are linked to extraction fields mainly dedicated to crude oil production, where 24 of them are inactive flares venting gas. The analysis of time series suggests a causal relationship between the decrease in flaring and the increase in venting. At the regional level, 2020 shows a substantial increase in the number of methane plume detections concerning previous years. Our results suggest that these large venting point sources represent a key mitigation opportunity as they emanate from human-controlled facilities, and that new satellite methods promise a revolution in the detection and monitoring of methane point emissions worldwide.

Two years of satellite observations were used to quantify methane emissions from coal mines in Queensland, the largest coal-producing state in Australia. The six analyzed surface and underground coal mines are estimated to emit 570 ± 98 Gg a -1 in 2018-2019. Together, they account for 7% of the national coal production while emitting 55 ± 10% of the reported methane emission from coal mining in Australia. Our results indicate that for two of the three locations, our satellite-based estimates are significantly higher than reported to the Australian government. Most remarkably, 40% of the quantified emission came from a single surface mine (Hail Creek) located in a methane-rich coal basin. Our findings call for increased monitoring and investment in methane recovery technologies for both surface and underground mines.

Southeast Australia experienced intensive and geographically extensive wildfires during the 2019-2020 summer season 1,2 . The fires released substantial amounts of carbon dioxide into the atmosphere 3 . However, existing emission estimates based on fire inventories are uncertain 4 , and vary by up to a factor of four for this event. Here we constrain emission estimates with the help of satellite observations of carbon monoxide 5 , an analytical Bayesian inversion 6 and observed ratios between emitted carbon dioxide and carbon monoxide 7 . We estimate emissions of carbon dioxide to be 715 teragrams (range 517-867) from November 2019 to January 2020. This is more than twice the estimate derived by five different fire inventories 8-12 , and broadly consistent with estimates based on a bottom-up bootstrap analysis of this fire episode 13 . Although fires occur regularly in the savannas in northern Australia, the recent episodes were extremely large in scale and intensity, burning unusually large areas of eucalyptus forest in the southeast 13 . The fires were driven partly by climate change 14,15 , making better-constrained emission estimates particularly important. This is because the build-up of atmospheric carbon dioxide may become increasingly dependent on fire-driven climate-carbon feedbacks, as highlighted by this event 16 ., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Industrial emissions play a major role in the global methane budget. The Permian basin is thought to be responsible for almost half of the methane emissions from all U.S. oil- and gas-producing regions, but little is known about individual contributors, a prerequisite for mitigation. We use a new class of satellite measurements acquired during several days in 2019 and 2020 to perform the first regional-scale and high-resolution survey of methane sources in the Permian. We find an unexpectedly large number of extreme point sources (37 plumes with emission rates >500 kg hour -1 ), which account for a range between 31 and 53% of the estimated emissions in the sampled area. Our analysis reveals that new facilities are major emitters in the area, often due to inefficient flaring operations (20% of detections). These results put current practices into question and are relevant to guide emission reduction efforts., (Copyright © 2021 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Using new satellite observations and atmospheric inverse modeling, we report methane emissions from the Permian Basin, which is among the world's most prolific oil-producing regions and accounts for >30% of total U.S. oil production. Based on satellite measurements from May 2018 to March 2019, Permian methane emissions from oil and natural gas production are estimated to be 2.7 ± 0.5 Tg a -1 , representing the largest methane flux ever reported from a U.S. oil/gas-producing region and are more than two times higher than bottom-up inventory-based estimates. This magnitude of emissions is 3.7% of the gross gas extracted in the Permian, i.e., ~60% higher than the national average leakage rate. The high methane leakage rate is likely contributed by extensive venting and flaring, resulting from insufficient infrastructure to process and transport natural gas. This work demonstrates a high-resolution satellite data-based atmospheric inversion framework, providing a robust top-down analytical tool for quantifying and evaluating subregional methane emissions., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Methane emissions due to accidents in the oil and natural gas sector are very challenging to monitor, and hence are seldom considered in emission inventories and reporting. One of the main reasons is the lack of measurements during such events. Here we report the detection of large methane emissions from a gas well blowout in Ohio during February to March 2018 in the total column methane measurements from the spaceborne Tropospheric Monitoring Instrument (TROPOMI). From these data, we derive a methane emission rate of 120 ± 32 metric tons per hour. This hourly emission rate is twice that of the widely reported Aliso Canyon event in California in 2015. Assuming the detected emission represents the average rate for the 20-d blowout period, we find the total methane emission from the well blowout is comparable to one-quarter of the entire state of Ohio's reported annual oil and natural gas methane emission, or, alternatively, a substantial fraction of the annual anthropogenic methane emissions from several European countries. Our work demonstrates the strength and effectiveness of routine satellite measurements in detecting and quantifying greenhouse gas emission from unpredictable events. In this specific case, the magnitude of a relatively unknown yet extremely large accidental leakage was revealed using measurements of TROPOMI in its routine global survey, providing quantitative assessment of associated methane emissions.

Methane emissions from the U.S. oil and natural gas supply chain were estimated by using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO 2 from natural gas combustion. Substantial emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems., (Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

We present a gridded inventory of US anthropogenic methane emissions with 0.1° × 0.1° spatial resolution, monthly temporal resolution, and detailed scale-dependent error characterization. The inventory is designed to be consistent with the 2016 US Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) for 2012. The EPA inventory is available only as national totals for different source types. We use a wide range of databases at the state, county, local, and point source level to disaggregate the inventory and allocate the spatial and temporal distribution of emissions for individual source types. Results show large differences with the EDGAR v4.2 global gridded inventory commonly used as a priori estimate in inversions of atmospheric methane observations. We derive grid-dependent error statistics for individual source types from comparison with the Environmental Defense Fund (EDF) regional inventory for Northeast Texas. These error statistics are independently verified by comparison with the California Greenhouse Gas Emissions Measurement (CALGEM) grid-resolved emission inventory. Our gridded, time-resolved inventory provides an improved basis for inversion of atmospheric methane observations to estimate US methane emissions and interpret the results in terms of the underlying processes.