Articles | Volume 15, issue 23
https://doi.org/10.5194/amt-15-7155-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-7155-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Dec 2022
Research article |
| 13 Dec 2022
| 13 Dec 2022
Detecting and quantifying methane emissions from oil and gas production: algorithm development with ground-truth calibration based on Sentinel-2 satellite imagery
Zhan Zhang
Department of Energy Resources Engineering, Stanford University,
Stanford, California 94305, United States
Evan D. Sherwin
Department of Energy Resources Engineering, Stanford University,
Stanford, California 94305, United States
Daniel J. Varon
School of Engineering and Applied Science, Harvard University,
Cambridge, Massachusetts 02138, United States
GHGSat, Inc., Montréal, H2W 1Y5, Canada
Adam R. Brandt
CORRESPONDING AUTHOR
Department of Energy Resources Engineering, Stanford University,
Stanford, California 94305, United States
Related authors
Evan D. Sherwin, Sahar H. El Abbadi, Philippine M. Burdeau, Zhan Zhang, Zhenlin Chen, Jeffrey S. Rutherford, Yuanlei Chen, and Adam R. Brandt
Atmos. Meas. Tech., 17, 765–782, https://doi.org/10.5194/amt-17-765-2024, https://doi.org/10.5194/amt-17-765-2024, 2024
Short summary
Short summary
Countries and companies increasingly rely on a growing fleet of satellites to find large emissions of climate-warming methane, particularly from oil and natural gas systems across the globe. We independently assessed the performance of nine such systems by releasing controlled, undisclosed amounts of methane as satellites passed overhead. The tested systems produced reliable detection and quantification results, including the smallest-ever emission detected from space in such a test.
Audrey McManemin, Catherine Juéry, Vincent Blandin, James L. France, Philippine Burdeau, and Adam R. Brandt
EGUsphere, https://doi.org/10.5194/egusphere-2025-3793, https://doi.org/10.5194/egusphere-2025-3793, 2025
This preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).
Short summary
Short summary
This experiment tested the ability of different technologies to detect and measure methane emissions. Participating teams used satellites, drones, and other systems to estimate methane leak rates without knowing the true rate. Some systems were more accurate than others, and wind and other environmental conditions made measurements harder. Our findings help improve these tools and support efforts to track and reduce methane emissions as new environmental rules take shape in Europe and beyond.
Hannah Nesser, Kevin W. Bowman, Matthew D. Thill, Daniel J. Varon, Cynthia A. Randles, Ashutosh Tewari, Felipe J. Cardoso-Saldaña, Emily Reidy, Joannes D. Maasakkers, and Daniel J. Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2025-2850, https://doi.org/10.5194/egusphere-2025-2850, 2025
Short summary
Short summary
Regional analyses of atmospheric trace gases can improve knowledge of fluxes and their trends at high resolution but rely on the specification of boundary conditions at the domain edges. Biases in the often-uncertain boundary conditions propagate to the inferred fluxes. We develop a framework to explain how errors in the boundary conditions influence the optimized fluxes, derive two metrics to estimate this influence, and compare two methods to correct for the biases.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
Short summary
Short summary
Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Riley Duren, Daniel Cusworth, Alana Ayasse, Kate Howell, Alex Diamond, Tia Scarpelli, Jinsol Kim, Kelly O'neill, Judy Lai-Norling, Andrew Thorpe, Sander R. Zandbergen, Lucas Shaw, Mark Keremedjiev, Jeff Guido, Paul Giuliano, Malkam Goldstein, Ravi Nallapu, Geert Barentsen, David R. Thompson, Keely Roth, Daniel Jensen, Michael Eastwood, Frances Reuland, Taylor Adams, Adam Brandt, Eric A. Kort, James Mason, and Robert O. Green
EGUsphere, https://doi.org/10.5194/egusphere-2025-2275, https://doi.org/10.5194/egusphere-2025-2275, 2025
Short summary
Short summary
We describe the Carbon Mapper emissions monitoring system including methane and carbon dioxide observations from the constellation of Tanager hyperspectral satellites, a global monitoring strategy optimized for enabling mitigation impact at the scale of individual facilities, and a data platform that delivers timely and transparent information for diverse stakeholders. We present early findings from Tanager-1 including the use of our data to locate and repair a leaking oil and gas pipeline.
Drew C. Pendergrass, Daniel J. Jacob, Nicholas Balasus, Lucas Estrada, Daniel J. Varon, James D. East, Megan He, Todd A. Mooring, Elise Penn, Hannah Nesser, and John R. Worden
EGUsphere, https://doi.org/10.5194/egusphere-2025-1554, https://doi.org/10.5194/egusphere-2025-1554, 2025
Short summary
Short summary
We use satellite observations of atmospheric methane, a potent greenhouse gas, to calculate emissions from both human and natural sources. We find that methane emissions surged in 2020 and 2021 before declining in 2022 and 2023. We attribute the surge in large part to emissions from eastern Africa, which experienced large methane-generating floods. We argue that previous work has attributed the methane surge to human-caused emissions (rather than wetlands) because of poor mapping in the tropics.
Shutao Zhao, Yuzhong Zhang, Shuang Zhao, Xinlu Wang, and Daniel J. Varon
Atmos. Chem. Phys., 25, 4035–4052, https://doi.org/10.5194/acp-25-4035-2025, https://doi.org/10.5194/acp-25-4035-2025, 2025
Short summary
Short summary
We target the challenge of detecting methane super-emitters in oil and gas fields, which is critical for mitigating climate change. Traditional satellite-based detectors struggle due to interference from complex surfaces. We developed a novel method using deep transfer learning that improves detection efficiency and accuracy by reducing artifacts and adapting methane knowledge to different regions. Application revealed significant methane emissions, demonstrating the potential of our method.
Sarah E. Hancock, Daniel J. Jacob, Zichong Chen, Hannah Nesser, Aaron Davitt, Daniel J. Varon, Melissa P. Sulprizio, Nicholas Balasus, Lucas A. Estrada, María Cazorla, Laura Dawidowski, Sebastián Diez, James D. East, Elise Penn, Cynthia A. Randles, John Worden, Ilse Aben, Robert J. Parker, and Joannes D. Maasakkers
Atmos. Chem. Phys., 25, 797–817, https://doi.org/10.5194/acp-25-797-2025, https://doi.org/10.5194/acp-25-797-2025, 2025
Short summary
Short summary
We quantify 2021 methane emissions in South America at up to 25 km × 25 km resolution using satellite methane observations. We find a 55 % upward adjustment to anthropogenic emission inventories, including those reported to the UN Framework Convention on Climate Change under the Paris Agreement. Our estimates match inventories for Brazil, Bolivia, and Paraguay but are much higher for other countries. Livestock emissions (65 % of anthropogenic emissions) show the largest discrepancies.
Jonathan F. Dooley, Kenneth Minschwaner, Manvendra K. Dubey, Sahar H. El Abbadi, Evan D. Sherwin, Aaron G. Meyer, Emily Follansbee, and James E. Lee
Atmos. Meas. Tech., 17, 5091–5111, https://doi.org/10.5194/amt-17-5091-2024, https://doi.org/10.5194/amt-17-5091-2024, 2024
Short summary
Short summary
Methane is a powerful greenhouse gas originating from both natural and human activities. We describe a new uncrewed aerial system (UAS) designed to measure methane emission rates over a wide range of scales. This system has been used for direct quantification of point sources and distributed emitters over scales of up to 1 km. The system uses simultaneous measurements of methane and ethane to distinguish between different kinds of natural and human-related emission sources.
Brian Nathan, Joannes D. Maasakkers, Stijn Naus, Ritesh Gautam, Mark Omara, Daniel J. Varon, Melissa P. Sulprizio, Lucas A. Estrada, Alba Lorente, Tobias Borsdorff, Robert J. Parker, and Ilse Aben
Atmos. Chem. Phys., 24, 6845–6863, https://doi.org/10.5194/acp-24-6845-2024, https://doi.org/10.5194/acp-24-6845-2024, 2024
Short summary
Short summary
Venezuela's Lake Maracaibo region is notoriously hard to observe from space and features intensive oil exploitation, although production has strongly decreased in recent years. We estimate methane emissions using 2018–2020 TROPOMI satellite observations with national and regional transport models. Despite the production decrease, we find relatively constant emissions from Lake Maracaibo between 2018 and 2020, indicating that there could be large emissions from abandoned infrastructure.
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
Atmos. Meas. Tech., 17, 2777–2787, https://doi.org/10.5194/amt-17-2777-2024, https://doi.org/10.5194/amt-17-2777-2024, 2024
Short summary
Short summary
We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 502 ± 464 t h−1.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
Short summary
Short summary
Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Evan D. Sherwin, Sahar H. El Abbadi, Philippine M. Burdeau, Zhan Zhang, Zhenlin Chen, Jeffrey S. Rutherford, Yuanlei Chen, and Adam R. Brandt
Atmos. Meas. Tech., 17, 765–782, https://doi.org/10.5194/amt-17-765-2024, https://doi.org/10.5194/amt-17-765-2024, 2024
Short summary
Short summary
Countries and companies increasingly rely on a growing fleet of satellites to find large emissions of climate-warming methane, particularly from oil and natural gas systems across the globe. We independently assessed the performance of nine such systems by releasing controlled, undisclosed amounts of methane as satellites passed overhead. The tested systems produced reliable detection and quantification results, including the smallest-ever emission detected from space in such a test.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
Short summary
Short summary
We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Berend J. Schuit, Joannes D. Maasakkers, Pieter Bijl, Gourav Mahapatra, Anne-Wil van den Berg, Sudhanshu Pandey, Alba Lorente, Tobias Borsdorff, Sander Houweling, Daniel J. Varon, Jason McKeever, Dylan Jervis, Marianne Girard, Itziar Irakulis-Loitxate, Javier Gorroño, Luis Guanter, Daniel H. Cusworth, and Ilse Aben
Atmos. Chem. Phys., 23, 9071–9098, https://doi.org/10.5194/acp-23-9071-2023, https://doi.org/10.5194/acp-23-9071-2023, 2023
Short summary
Short summary
Using two machine learning models, which were trained on TROPOMI methane satellite data, we detect 2974 methane plumes, so-called super-emitters, in 2021. We detect methane emissions globally related to urban areas or landfills, coal mining, and oil and gas production. Using our monitoring system, we identify 94 regions with frequent emissions. For 12 locations, we target high-resolution satellite instruments to enlarge and identify the exact infrastructure responsible for the emissions.
Drew C. Pendergrass, Daniel J. Jacob, Hannah Nesser, Daniel J. Varon, Melissa Sulprizio, Kazuyuki Miyazaki, and Kevin W. Bowman
Geosci. Model Dev., 16, 4793–4810, https://doi.org/10.5194/gmd-16-4793-2023, https://doi.org/10.5194/gmd-16-4793-2023, 2023
Short summary
Short summary
We have built a tool called CHEEREIO that allows scientists to use observations of pollutants or gases in the atmosphere, such as from satellites or surface stations, to update supercomputer models that simulate the Earth. CHEEREIO uses the difference between the model simulations of the atmosphere and real-world observations to come up with a good guess for the actual composition of our atmosphere, the true emissions of various pollutants, and whatever else they may want to study.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
Short summary
Short summary
We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
Short summary
Short summary
We use TROPOMI satellite observations to quantify weekly methane emissions from the US Permian oil and gas basin from May 2018 to October 2020. We find that Permian emissions are highly variable, with diverse economic and activity drivers. The most important drivers during our study period were new well development and natural gas price. Permian methane intensity averaged 4.6 % and decreased by 1 % per year.
Zichong Chen, Daniel J. Jacob, Ritesh Gautam, Mark Omara, Robert N. Stavins, Robert C. Stowe, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Drew C. Pendergrass, and Sarah Hancock
Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
Short summary
Short summary
We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
Javier Gorroño, Daniel J. Varon, Itziar Irakulis-Loitxate, and Luis Guanter
Atmos. Meas. Tech., 16, 89–107, https://doi.org/10.5194/amt-16-89-2023, https://doi.org/10.5194/amt-16-89-2023, 2023
Short summary
Short summary
We present a methane flux rate retrieval methodology using the Sentinel-2 mission, validating the algorithm for different scenes and plumes. The detection limit is 1000–2000 kg h−1 for homogeneous scenes and temporally invariant surfaces and above 5000 kg h−1 for heterogeneous ones. Dominant quantification errors are wind-related or plume mask-related. For heterogeneous scenes, the surface structure underlying the methane plume can become a dominant source of uncertainty.
Lu Shen, Ritesh Gautam, Mark Omara, Daniel Zavala-Araiza, Joannes D. Maasakkers, Tia R. Scarpelli, Alba Lorente, David Lyon, Jianxiong Sheng, Daniel J. Varon, Hannah Nesser, Zhen Qu, Xiao Lu, Melissa P. Sulprizio, Steven P. Hamburg, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 11203–11215, https://doi.org/10.5194/acp-22-11203-2022, https://doi.org/10.5194/acp-22-11203-2022, 2022
Short summary
Short summary
We use 22 months of TROPOMI satellite observations to quantity methane emissions from the oil (O) and natural gas (G) sector in the US and Canada at the scale of both individual basins as well as country-wide aggregates. We find that O/G-related methane emissions are underestimated in these inventories by 80 % for the US and 40 % for Canada, and 70 % of the underestimate in the US is from five O/G basins, including Permian, Haynesville, Anadarko, Eagle Ford, and Barnett.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
Short summary
Short summary
We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
Short summary
Short summary
We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
Short summary
Short summary
Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
Elena Sánchez-García, Javier Gorroño, Itziar Irakulis-Loitxate, Daniel J. Varon, and Luis Guanter
Atmos. Meas. Tech., 15, 1657–1674, https://doi.org/10.5194/amt-15-1657-2022, https://doi.org/10.5194/amt-15-1657-2022, 2022
Short summary
Short summary
This study seeks to present the as-yet-unknown potential use of WorldView-3 for the mapping of methane point source emissions. The proposed retrieval methodology is based on the idea that the spectral channels not affected by methane can be used to predict the methane-affected band through regression analysis. The results show the precise location of 26 independent point emissions over different methane hotspot regions worldwide, which prove the game-changing potential that this mission entails.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
Short summary
Short summary
The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
Daniel J. Varon, Dylan Jervis, Jason McKeever, Ian Spence, David Gains, and Daniel J. Jacob
Atmos. Meas. Tech., 14, 2771–2785, https://doi.org/10.5194/amt-14-2771-2021, https://doi.org/10.5194/amt-14-2771-2021, 2021
Short summary
Short summary
Satellites can detect methane emissions by measuring sunlight reflected from the Earth's surface and atmosphere. Here we show that the European Space Agency's Sentinel-2 twin satellites can be used to monitor anomalously large methane point sources around the world, with global coverage every 2–5 days and 20 m spatial resolution. We demonstrate this previously unreported capability through high-frequency Sentinel-2 monitoring of two strong methane point sources in Algeria and Turkmenistan.
Dylan Jervis, Jason McKeever, Berke O. A. Durak, James J. Sloan, David Gains, Daniel J. Varon, Antoine Ramier, Mathias Strupler, and Ewan Tarrant
Atmos. Meas. Tech., 14, 2127–2140, https://doi.org/10.5194/amt-14-2127-2021, https://doi.org/10.5194/amt-14-2127-2021, 2021
Short summary
Short summary
We describe how the GHGSat-D demonstration satellite is designed and operated in order to measure greenhouse gas emissions from different types of industrial facilities. The distinguishing features of GHGSat-D, or
Claire, are its compact size (< 15 kg) and high spatial resolution (< 50 m). We give a mathematical model of the instrument and describe the techniques used to infer a methane concentration from a measurement of the sunlight that has reflected off the Earth's surface.
Cited articles
Alvarez, R. A., Zavala-Araiza, D., Lyon, D. R., Allen, D. T., Barkley, Z. R., Brandt, A. R., Davis, K. J., Herndon, S. C., Jacob, D. J., Karion, A., Kort, E. A., Lamb, B. K., Lauvaux, T., Maasakkers, J. D., Marchese, A. J., Omara, M., Pacala, S. W., Peischl, J., Robinson, A. L., Shepson, P. B., Sweeney, C., Townsend-Small, A., Wofsy, S. C., and Hamburg, S. P.: Assessment of methane emissions from the US oil and gas supply chain,
Science, 361, 186–188, https://doi.org/10.1126/science.aar7204, 2018.
Brandt, A. R., Heath, G. A., Kort, E. A., O'Sullivan, F., Pétron, G.,
Jordaan, S. M., Tans, P., Wilcox, J., Gopstein, A. M., Arent, D., Wofsy, S.,
Brown, N. J., Bradley, R., Stucky, G. D., Eardley, D., and Harriss, R.:
Methane leaks from North American natural gas systems, Science, 343,
733–735, https://doi.org/10.1126/science.1247045, 2014.
Chen, Y., Sherwin, E. D., Berman, E. S., Jones, B. B., Gordon, M. P.,
Wetherley, E. B., Kort, E. A., and Brandt, A. R.: Quantifying Regional
Methane Emissions in the New Mexico Permian Basin with a Comprehensive
Aerial Survey, Environ. Sci. Technol., 56, 4317–4323,
https://doi.org/10.1021/acs.est.1c06458, 2022.
Cusworth, D. H., Jacob, D. J., Varon, D. J., Chan Miller, C., Liu, X., Chance, K., Thorpe, A. K., Duren, R. M., Miller, C. E., Thompson, D. R., Frankenberg, C., Guanter, L., and Randles, C. A.: Potential of next-generation imaging spectrometers to detect and quantify methane point sources from space, Atmos. Meas. Tech., 12, 5655–5668, https://doi.org/10.5194/amt-12-5655-2019, 2019.
Cusworth, D. H., Duren, R. M., Thorpe, A. K., Olson-Duvall, W., Heckler, J.,
Chapman, J. W., Eastwood, M. L., Helmlinger, M. C., Green, R. O., Asner, G.
P., Dennison, P. E., and Miller, C. E.: Intermittency of large methane
emitters in the Permian Basin, Environ. Sci. Technol.
Lett., 8, 567–573, https://doi.org/10.1021/acs.estlett.1c00173, 2021.
Ehret, T., De Truchis, A., Mazzolini, M., Morel, J.-M., D'aspremont, A.,
Lauvaux, T., Duren, R., Cusworth, D., and Facciolo, G.: Global tracking and
quantification of oil and gas methane emissions from recurrent sentinel-2
imagery, Environ. Sci. Technol., 355 56, 10517–10529,
https://doi.org/10.1021/acs.est.1c08575, 2022.
Frankenberg, C., Thorpe, A. K., Thompson, D. R., Hulley, G., Kort, E. A.,
Vance, N., Borchardt, J., Krings, T., Gerilowski, K., Sweeney, C., Conley,
S., Bue, B. D., Aubrey, A. D., Hook, S., and Green, R. O.: Airborne methane
remote measurements reveal heavy-tail flux distribution in Four Corners
region, P. Natl. Acad. Sci. USA, 113, 9734–9739,
https://doi.org/10.1073/pnas.1605617113, 2016.
Hausmann, P., Sussmann, R., and Smale, D.: Contribution of oil and natural gas production to renewed increase in atmospheric methane (2007–2014): top–down estimate from ethane and methane column observations, Atmos. Chem. Phys., 16, 3227–3244, https://doi.org/10.5194/acp-16-3227-2016, 2016.
Hu, H., Landgraf, J., Detmers, R., Borsdorff, T., Aan de Brugh, J., Aben,
I., Butz, A., and Hasekamp, O.: Toward global mapping of methane with
TROPOMI: First results and intersatellite comparison to GOSAT, Geophys.
Res. Lett., 45, 3682–3689, https://doi.org/10.1002/2018GL077259, 2018.
IEA: Global Methane Tracker 2022, Tech. rep., IEA,
https://www.iea.org/reports/global-methane-tracker-2022, last access: 6 July 2022.
Irakulis-Loitxate, I., Guanter, L., Maasakkers, J. D., Zavala-Araiza, D.,
and Aben, I.: Satellites Detect Abatable SuperEmissions in One of the
World's Largest Methane Hotspot Regions, Environ. Sci. Technol., 56, 2143–2152, https://doi.org/10.1021/acs.est.1c04873, 2022.
Jacob, D. J., Turner, A. J., Maasakkers, J. D., Sheng, J., Sun, K., Liu, X., Chance, K., Aben, I., McKeever, J., and Frankenberg, C.: Satellite observations of atmospheric methane and their value for quantifying methane emissions, Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, 2016.
Karion, A., Sweeney, C., Pétron, G., Frost, G., Michael Hardesty, R.,
Kofler, J., Miller, B. R., Newberger, T., Wolter, S., Banta, R., Brewer, A.,
Dlugokencky, E., Lang, P., Montzka, S. A., Schnell, R., Tans, P., Trainer,
M., Zamora, R., and Conley, S.: Methane emissions estimate from airborne
measurements over a western United States natural gas field, Geophys.
Res. Lett., 40, 4393–4397, https://doi.org/10.1002/grl.50811, 2013.
Lauvaux, T., Giron, C., Mazzolini, M., d'Aspremont, A., Duren, R., Cusworth,
D., Shindell, D., and Ciais, P.: Global assessment of oil and gas methane
ultra-emitters, Science, 375, 557–561, https://doi.org/10.1126/science.abj4351, 2022.
MacKay, K., Lavoie, M., Bourlon, E., Atherton, E., O'Connell, E., Baillie,
J., Fougère, C., and Risk, D.: Methane emissions from upstream oil and
gas production in Canada are underestimated, Sci. Rep., 11, 1–8,
https://doi.org/10.1038/s41598-021-87610-3, 2021.
Phiri, D., Simwanda, M., Salekin, S., Nyirenda, V. R., Murayama, Y., and
Ranagalage, M.: Sentinel-2 data for land cover/use mapping: A review, Remote
Sens., 12, 2291, https://doi.org/10.3390/rs12142291, 2020.
Rutherford, J. S., Sherwin, E. D., Ravikumar, A. P., Heath, G. A.,
Englander, J., Cooley, D., Lyon, D., Omara, M., Langfitt, Q., and Brandt, A.
R.: Closing the methane gap in US oil and natural gas production emissions
inventories, Nat. Commun., 12, 1–12, https://doi.org/10.1038/s41467-021-25017-4, 2021.
Rutherford, J. S., Sherwin, E. D., Chen, Y., and Brandt, A. R.: Controlled
release experimental methods: 2021 Stanford controlled releases in TX and
AZ,
https://eao.stanford.edu/sites/g/files/sbiybj22256/files/media/file/Method_description_Setup_and_Uncertainty_v18.pdf, last access: 30 August 2022.
Sánchez-García, E., Gorroño, J., Irakulis-Loitxate, I., Varon, D. J., and Guanter, L.: Mapping methane plumes at very high spatial resolution with the WorldView-3 satellite, Atmos. Meas. Tech., 15, 1657–1674, https://doi.org/10.5194/amt-15-1657-2022, 2022.
Sherwin, E. D., Chen, Y., Ravikumar, A. P., and Brandt, A. R.: Single-blind
test of airplane-based hyperspectral methane detection via controlled
releases, Elem. Sci. Anth., 9, 00063, https://doi.org/10.1525/elementa.2021.00063, 2021.
Thompson, D., Thorpe, A., Frankenberg, C., Green, R., Duren, R., Guanter,
L., Hollstein, A., Middleton, E., Ong, L., and Ungar, S.: Space-based remote
imaging spectroscopy of the Aliso Canyon CH4 superemitter, Geophys.
Res. Lett., 43, 6571–6578, https://doi.org/10.1002/2016GL069079, 2016.
US NOAA: The High-Resolution Rapid Refresh (HRRR), U.S. NOAA [data set],
https://rapidrefresh.noaa.gov/hrrr/ (last access: 15 March 2022), 2021.
Varon, D. J., Jacob, D. J., McKeever, J., Jervis, D., Durak, B. O. A., Xia, Y., and Huang, Y.: Quantifying methane point sources from fine-scale satellite observations of atmospheric methane plumes, Atmos. Meas. Tech., 11, 5673–5686, https://doi.org/10.5194/amt-11-5673-2018, 2018.
Varon, D. J., Jacob, D. J., Jervis, D., and McKeever, J.: Quantifying
time-averaged methane emissions from individual coal mine vents with
GHGSat-D satellite observations, Environ. Sci. Technol., 54,
10246–10253, https://doi.org/10.1021/acs.est.0c01213, 2020.
Varon, D. J., Jervis, D., McKeever, J., Spence, I., Gains, D., and Jacob, D. J.: High-frequency monitoring of anomalous methane point sources with multispectral Sentinel-2 satellite observations, Atmos. Meas. Tech., 14, 2771–2785, https://doi.org/10.5194/amt-14-2771-2021, 2021.
Veefkind, J., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter,
G., Claas, J., Eskes, H., de Haan, J., Kleipool, Q., van Weele, M.,
Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P.,
Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P.: TROPOMI on
the ESA Sentinel-5 Precursor: A GMES mission for global observations of the
atmospheric composition for climate, air quality and ozone layer
applications, Remote Sens. Environ., 120, 70–83,
https://doi.org/10.1016/j.rse.2011.09.027, 2012.
Zavala-Araiza, D., Lyon, D. R., Alvarez, R. A., Davis, K. J., Harriss, R.,
Herndon, S. C., Karion, A., Kort, E. A., Lamb, B. K., Lan, X., Marchese, A.
J., Pacala, S. W., Robinson, A. L., Shepson, P. B., Sweeney, C., Talbot, R.,
Townsend-Small, A., Yacovitch, T. I., Zimmerle, D. J., and Hamburg, S. P.:
Reconciling divergent estimates of oil and gas methane emissions,
P. Natl. Acad. Sci. USA, 112, 15597–15602,
https://doi.org/10.1073/pnas.1522126112, 2015.
Short summary
This work developed a multi-band–multi-pass–multi-comparison-date Sentinel-2 methane retrieval algorithm, and the method was calibrated by data from a controlled release test. To our knowledge, this is the first study that validates the performance of a Sentinel-2 methane detection algorithm by calibration with a ground-truth testing. It illustrates the potential for additional validation with systematic future experiments wherein algorithms can be tuned to meet different detection expectations.
This work developed a multi-band–multi-pass–multi-comparison-date Sentinel-2 methane retrieval...
