Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins

Shen, Lu; Gautam, Ritesh; Omara, Mark; Zavala-Araiza, Daniel; Maasakkers, Joannes D.; Scarpelli, Tia R.; Lorente, Alba; Lyon, David; Sheng, Jianxiong; Varon, Daniel J.; Nesser, Hannah; Qu, Zhen; Lu, Xiao; Sulprizio, Melissa P.; Hamburg, Steven P.; Jacob, Daniel J.

doi:10.5194/acp-2022-155

Cited by 14 publications

(15 citation statements)

References 25 publications

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“…GOSAT data are too sparse. TROPOMI has been used to quantify emissions from oil and gas production fields including the Permian Basin (Zhang et al, 2020), other fields in the US and Canada (Shen et al, 2022), and the Mexican Sureste Basin (Shen et al, 2021), revealing large underestimates in the bottom-up inventories. It has also been used to quantify total methane emissions from China and to attribute them to source sectors (Z. .…”

Section: Global and Regional Observations With Area Flux Mappersmentioning

confidence: 99%

Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane

et al. 2022

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Abstract. We review the capability of current and scheduled satellite observations of atmospheric methane in the shortwave infrared (SWIR) to quantify methane emissions from the global scale down to point sources. We cover retrieval methods, precision and accuracy requirements, inverse and mass balance methods for inferring emissions, source detection thresholds, and observing system completeness. We classify satellite instruments as area flux mappers and point source imagers, with complementary attributes. Area flux mappers are high-precision (<1 %) instruments with 0.1–10 km pixel size designed to quantify total methane emissions on regional to global scales. Point source imagers are fine-pixel (<60 m) instruments designed to quantify individual point sources by imaging of the plumes. Current area flux mappers include GOSAT (2009–present), which provides a high-quality record for interpretation of long-term methane trends, and TROPOMI (2018–present), which provides global continuous daily mapping to quantify emissions on regional scales. These instruments already provide a powerful resource to quantify national methane emissions in support of the Paris Agreement. Current point source imagers include the GHGSat constellation and several hyperspectral and multispectral land imaging sensors (PRISMA, Sentinel-2, Landsat-8/9, WorldView-3), with detection thresholds in the 100–10 000 kg h−1 range that enable monitoring of large point sources. Future area flux mappers, including MethaneSAT, GOSAT-GW, Sentinel-5, GeoCarb, and CO2M, will increase the capability to quantify emissions at high resolution, and the MERLIN lidar will improve observation of the Arctic. The averaging times required by area flux mappers to quantify regional emissions depend on pixel size, retrieval precision, observation density, fraction of successful retrievals, and return times in a way that varies with the spatial resolution desired. A similar interplay applies to point source imagers between detection threshold, spatial coverage, and return time, defining an observing system completeness. Expanding constellations of point source imagers including GHGSat and Carbon Mapper over the coming years will greatly improve observing system completeness for point sources through dense spatial coverage and frequent return times.

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Section: Global and Regional Observations With Area Flux Mappersmentioning

confidence: 99%

Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane

et al. 2022

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“…DOFS ∼ 1 would be a minimum requirement to achieve any solid information on emissions in the region of interest, and more may be desirable if multiple pieces of information are desired on the emission fields within the region. Shen et al (2022) required DOFS > 2 to reliably estimate basin-wide emissions from oil and gas basins in North America. If the user deems the DOFS to be insufficient, a cure is to increase the number of observations by lengthening the observation Figure 3.…”

Section: Imi Preview: Assessing Information Content Before Performing...mentioning

confidence: 99%

“…It enables no-cost error analysis by producing an ensemble of solutions to explore the sensitivity to inversion parameters. The algorithm is fully documented in the literature Maasakkers et al, 2019Zhang et al, 2021;Lu et al, 2022), including applications to TROPOMI data (Zhang et al, 2020;Qu et al, 2021;Shen et al, 2021Shen et al, , 2022Z. Chen et al, 2022).…”

Section: Conclusion and Future Developmentsmentioning

confidence: 99%

“…The retrieval success rate averages only 3 % because of clouds and dark and heterogeneous surfaces (Hasekamp et al, 2019), but the data density is still at least 2 orders of magnitude higher than for GOSAT (Qu et al, 2021). TROPOMI data have been used in regional inversions at up to 25 km resolution (Zhang et al, 2020;Shen et al, 2021Shen et al, , 2022Z. Chen et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations

et al. 2022

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Abstract. We present a user-friendly, cloud-based facility for quantifying methane emissions with 0.25∘ × 0.3125∘ (≈ 25 km × 25 km) resolution by inverse analysis of satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI). The facility is built on an Integrated Methane Inversion optimal estimation workflow (IMI 1.0) and supported for use on the Amazon Web Services (AWS) cloud. It exploits the GEOS-Chem chemical transport model and TROPOMI data already resident on AWS, thus avoiding cumbersome big-data download. Users select a region and period of interest, and the IMI returns an analytical solution for the Bayesian optimal estimate of period-average emissions on the 0.25∘ × 0.3125∘ grid including error statistics, information content, and visualization code for inspection of results. The inversion uses an advanced research-grade algorithm fully documented in the literature. An out-of-the-box inversion with rectilinear grid and default prior emission estimates can be conducted with no significant learning curve. Users can also configure their inversions to infer emissions for irregular regions of interest, swap in their own prior emission inventories, and modify inversion parameters. Inversion ensembles can be generated at minimal additional cost once the Jacobian matrix for the analytical inversion has been constructed. A preview feature allows users to determine the TROPOMI information content for their region and time period of interest before actually performing the inversion. The IMI is heavily documented and is intended to be accessible by researchers and stakeholders with no expertise in inverse modelling or high-performance computing. We demonstrate the IMI's capabilities by applying it to estimate methane emissions from the US oil-producing Permian Basin in May 2018.

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“…Individual transactions involving natural gas, even at high volumes, can be sourced from a small number of high-producing assets, and there can be significant design, operational and maintenance variation that impacts emissions even within a basin or sub-basin [14], [44]- [46]. In this context, multi-scale measurements of methane emissions have demonstrated the need for a robust approach to improve emissions inventories.…”

Section: Discussionmentioning

confidence: 99%

Multi-scale Methane Measurements at Oil and Gas Facilities Reveal Necessary Framework for Improved Emissions Accounting

Wang

Daniels

Hammerling

et al. 2022

Preprint

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Methane mitigation from the oil and gas (O&G) sector represents a key near-term global climate action opportunity. The effectiveness of mitigation strategies rests on the ability to quantify spatially and temporally varying methane emissions more accurately than existing approaches. Advances in technologies have enabled improvements in methane emissions measurements and monitoring, In this work, we demonstrate a quantification, monitoring, reporting, and verification framework that pairs snapshot measurements with continuous emissions monitoring systems (CEMS) to reconcile measurements with inventory estimates and account for intermittent emissions events. We find site-level emissions exhibit significant intra-day and daily emissions variation. Snapshot measurements of methane can span over three orders of magnitude and may have limited application in developing annualized inventory estimates. Consequently, while official inventories underestimate methane emissions on average, emissions at individual facilities can be lower than inventory estimates. Using CEMS, we characterize distributions of frequency and duration of intermittent emission events. Technologies that allow high sampling frequency such as CEMS, paired with a mechanistic understanding of facility-level events is key to accurate accounting of short-duration, episodic, and high-volume events that are often missed in snapshot surveys, and to scale snapshot measurements to annualized emissions estimates.

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Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins

Cited by 14 publications

References 25 publications

Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane

Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane

Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations

Multi-scale Methane Measurements at Oil and Gas Facilities Reveal Necessary Framework for Improved Emissions Accounting

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