Articles | Volume 22, issue 14
https://doi.org/10.5194/acp-22-9617-2022
© 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/acp-22-9617-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Review article
| Highlight paper
| 
29 Jul 2022
Review article | Highlight paper |
| 29 Jul 2022
| 29 Jul 2022
Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane
Daniel J. Jacob
CORRESPONDING AUTHOR
School of Engineering and Applied Sciences, Harvard University,
Cambridge, 02138, USA
Daniel J. Varon
School of Engineering and Applied Sciences, Harvard University,
Cambridge, 02138, USA
GHGSat, Inc., Montreal, H2W 1Y5, Canada
Daniel H. Cusworth
Arizona Institutes for Resilience, University of Arizona, Tucson,
85721, USA
Carbon Mapper, Pasadena, 91109, USA
Philip E. Dennison
Department of Geography, University of Utah, Salt Lake City, 84112,
USA
Christian Frankenberg
Division of Geological and Planetary Sciences, California Institute
of Technology, Pasadena, 91125, USA
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, 91109, USA
Ritesh Gautam
Environmental Defense Fund, Washington, D.C., 20009, USA
Luis Guanter
Research Institute of Water and Environmental Engineering,
Universitat Politecnica de Valencia, Valencia, 46022, Spain
Environmental Defense Fund, Amsterdam, 1017, The Netherlands
John Kelley
GeoSapient, Inc., Cypress, 77429, USA
Jason McKeever
GHGSat, Inc., Montreal, H2W 1Y5, Canada
Lesley E. Ott
NASA GSFC, Greenbelt, 20771, USA
Benjamin Poulter
NASA GSFC, Greenbelt, 20771, USA
Zhen Qu
School of Engineering and Applied Sciences, Harvard University,
Cambridge, 02138, USA
Andrew K. Thorpe
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, 91109, USA
John R. Worden
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, 91109, USA
Riley M. Duren
Arizona Institutes for Resilience, University of Arizona, Tucson,
85721, USA
Carbon Mapper, Pasadena, 91109, USA
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, 91109, USA
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43 citations as recorded by crossref.
- National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations L. Shen et al. 10.1038/s41467-023-40671-6
- Uvsq-Sat NG, a New CubeSat Pathfinder for Monitoring Earth Outgoing Energy and Greenhouse Gases M. Meftah et al. 10.3390/rs15194876
- Minimum detection limits of the TROPOMI satellite sensor across North America and their implications for measuring oil and gas methane emissions L. Dubey et al. 10.1016/j.scitotenv.2023.162222
- High-resolution assessment of coal mining methane emissions by satellite in Shanxi, China S. Peng et al. 10.1016/j.isci.2023.108375
- Determination of Greenhouse Gas Concentrations from the 16U CubeSat Spacecraft Using Fourier Transform Infrared Spectroscopy V. Mayorova et al. 10.3390/s23156794
- Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al. 10.5194/acp-23-7503-2023
- The role of satellite remote sensing in mitigating and adapting to global climate change S. Zhao et al. 10.1016/j.scitotenv.2023.166820
- Atmospheric remote sensing for anthropogenic methane emissions: Applications and research opportunities S. Zhang et al. 10.1016/j.scitotenv.2023.164701
- Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al. 10.3390/atmos14040758
- S2MetNet: A novel dataset and deep learning benchmark for methane point source quantification using Sentinel-2 satellite imagery A. Radman et al. 10.1016/j.rse.2023.113708
- Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
- Response to Gallagher (2022)—the Australian Tidal Restoration for Blue Carbon method 2022—conservative, robust, and practical C. Lovelock et al. 10.1111/rec.14027
- Impact of transport model resolution and a priori assumptions on inverse modeling of Swiss F-gas emissions I. Katharopoulos et al. 10.5194/acp-23-14159-2023
- Single-blind validation of space-based point-source detection and quantification of onshore methane emissions E. Sherwin et al. 10.1038/s41598-023-30761-2
- Methane and nitrous oxide emissions from municipal wastewater treatment plants in China: A plant-level and technology-specific study H. Li et al. 10.1016/j.ese.2023.100345
- Assessing the Relative Importance of Satellite-Detected Methane Superemitters in Quantifying Total Emissions for Oil and Gas Production Areas in Algeria S. Naus et al. 10.1021/acs.est.3c04746
- Understanding the potential of Sentinel-2 for monitoring methane point emissions J. Gorroño et al. 10.5194/amt-16-89-2023
- Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data A. Vara-Vela et al. 10.5194/gmd-16-6413-2023
- Air pollution accountability research: Moving from a chain to a web S. Ebelt et al. 10.1016/j.gloepi.2023.100128
- Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space A. Thorpe et al. 10.1126/sciadv.adh2391
- Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al. 10.1038/s41598-023-41914-8
- Investigating high methane emissions from urban areas detected by TROPOMI and their association with untreated wastewater B. de Foy et al. 10.1088/1748-9326/acc118
- Modeling global indices for estimating non-photosynthetic vegetation cover P. Dennison et al. 10.1016/j.rse.2023.113715
- 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al. 10.3788/AOS230429
- Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the United States D. Cusworth et al. 10.1073/pnas.2202338119
- Constraining industrial ammonia emissions using hyperspectral infrared imaging L. Noppen et al. 10.1016/j.rse.2023.113559
- Tiered Leak Detection and Repair Programs at Simulated Oil and Gas Production Facilities: Increasing Emission Reduction by Targeting High-Emitting Sources F. Cardoso-Saldaña 10.1021/acs.est.2c08582
- Utilizing Remote Sensing and Data Analytics Techniques to Detect Methane Emissions from the Oil and Gas Industry and Assist with Sustainability Metrics Á. Esparza et al. 10.2118/215818-PA
- Semantic segmentation of methane plumes with hyperspectral machine learning models V. Růžička et al. 10.1038/s41598-023-44918-6
- Monitoring greenhouse gases (GHGs) in China: status and perspective Y. Sun et al. 10.5194/amt-15-4819-2022
- East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis R. Liang et al. 10.5194/acp-23-8039-2023
- Evaluation of Uncertainties in the Anthropogenic SO2 Emissions in the USA from the OMI Point Source Catalog K. Narayan et al. 10.1021/acs.est.2c07056
- Reconciling Methane Emission Measurements for Offshore Oil and Gas Platforms with Detailed Emission Inventories: Accounting for Emission Intermittency Z. Chen et al. 10.1021/acsenvironau.2c00041
- Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al. 10.5194/acp-23-9071-2023
- Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution M. Omara et al. 10.5194/essd-15-3761-2023
- Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison G. McNicol et al. 10.1029/2023AV000956
- 煤炭行业甲烷排放卫星遥感研究进展与展望 秦. Qin Kai et al. 10.3788/AOS231293
- A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases N. Balasus et al. 10.5194/amt-16-3787-2023
- Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action Z. Chen et al. 10.5194/acp-23-5945-2023
- Temperature dependence of the absorption of the R(6) manifold of the 2ν3 band of methane in air in support of the MERLIN mission S. Vasilchenko et al. 10.1016/j.jqsrt.2023.108483
- Evaluating net life-cycle greenhouse gas emissions intensities from gas and coal at varying methane leakage rates D. Gordon et al. 10.1088/1748-9326/ace3db
- Derivation of Emissions From Satellite‐Observed Column Amounts and Its Application to TROPOMI NO2 and CO Observations K. Sun 10.1029/2022GL101102
- Recent Advances Toward Transparent Methane Emissions Monitoring: A Review B. Erland et al. 10.1021/acs.est.2c02136
41 citations as recorded by crossref.
- National quantifications of methane emissions from fuel exploitation using high resolution inversions of satellite observations L. Shen et al. 10.1038/s41467-023-40671-6
- Uvsq-Sat NG, a New CubeSat Pathfinder for Monitoring Earth Outgoing Energy and Greenhouse Gases M. Meftah et al. 10.3390/rs15194876
- Minimum detection limits of the TROPOMI satellite sensor across North America and their implications for measuring oil and gas methane emissions L. Dubey et al. 10.1016/j.scitotenv.2023.162222
- High-resolution assessment of coal mining methane emissions by satellite in Shanxi, China S. Peng et al. 10.1016/j.isci.2023.108375
- Determination of Greenhouse Gas Concentrations from the 16U CubeSat Spacecraft Using Fourier Transform Infrared Spectroscopy V. Mayorova et al. 10.3390/s23156794
- Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al. 10.5194/acp-23-7503-2023
- The role of satellite remote sensing in mitigating and adapting to global climate change S. Zhao et al. 10.1016/j.scitotenv.2023.166820
- Atmospheric remote sensing for anthropogenic methane emissions: Applications and research opportunities S. Zhang et al. 10.1016/j.scitotenv.2023.164701
- Use of Assimilation Analysis in 4D-Var Source Inversion: Observing System Simulation Experiments (OSSEs) with GOSAT Methane and Hemispheric CMAQ S. Voshtani et al. 10.3390/atmos14040758
- S2MetNet: A novel dataset and deep learning benchmark for methane point source quantification using Sentinel-2 satellite imagery A. Radman et al. 10.1016/j.rse.2023.113708
- Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
- Response to Gallagher (2022)—the Australian Tidal Restoration for Blue Carbon method 2022—conservative, robust, and practical C. Lovelock et al. 10.1111/rec.14027
- Impact of transport model resolution and a priori assumptions on inverse modeling of Swiss F-gas emissions I. Katharopoulos et al. 10.5194/acp-23-14159-2023
- Single-blind validation of space-based point-source detection and quantification of onshore methane emissions E. Sherwin et al. 10.1038/s41598-023-30761-2
- Methane and nitrous oxide emissions from municipal wastewater treatment plants in China: A plant-level and technology-specific study H. Li et al. 10.1016/j.ese.2023.100345
- Assessing the Relative Importance of Satellite-Detected Methane Superemitters in Quantifying Total Emissions for Oil and Gas Production Areas in Algeria S. Naus et al. 10.1021/acs.est.3c04746
- Understanding the potential of Sentinel-2 for monitoring methane point emissions J. Gorroño et al. 10.5194/amt-16-89-2023
- Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data A. Vara-Vela et al. 10.5194/gmd-16-6413-2023
- Air pollution accountability research: Moving from a chain to a web S. Ebelt et al. 10.1016/j.gloepi.2023.100128
- Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space A. Thorpe et al. 10.1126/sciadv.adh2391
- Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al. 10.1038/s41598-023-41914-8
- Investigating high methane emissions from urban areas detected by TROPOMI and their association with untreated wastewater B. de Foy et al. 10.1088/1748-9326/acc118
- Modeling global indices for estimating non-photosynthetic vegetation cover P. Dennison et al. 10.1016/j.rse.2023.113715
- 大气甲烷卫星传感器和遥感算法研究综述 何. He Zhuo et al. 10.3788/AOS230429
- Strong methane point sources contribute a disproportionate fraction of total emissions across multiple basins in the United States D. Cusworth et al. 10.1073/pnas.2202338119
- Constraining industrial ammonia emissions using hyperspectral infrared imaging L. Noppen et al. 10.1016/j.rse.2023.113559
- Tiered Leak Detection and Repair Programs at Simulated Oil and Gas Production Facilities: Increasing Emission Reduction by Targeting High-Emitting Sources F. Cardoso-Saldaña 10.1021/acs.est.2c08582
- Utilizing Remote Sensing and Data Analytics Techniques to Detect Methane Emissions from the Oil and Gas Industry and Assist with Sustainability Metrics Á. Esparza et al. 10.2118/215818-PA
- Semantic segmentation of methane plumes with hyperspectral machine learning models V. Růžička et al. 10.1038/s41598-023-44918-6
- Monitoring greenhouse gases (GHGs) in China: status and perspective Y. Sun et al. 10.5194/amt-15-4819-2022
- East Asian methane emissions inferred from high-resolution inversions of GOSAT and TROPOMI observations: a comparative and evaluative analysis R. Liang et al. 10.5194/acp-23-8039-2023
- Evaluation of Uncertainties in the Anthropogenic SO2 Emissions in the USA from the OMI Point Source Catalog K. Narayan et al. 10.1021/acs.est.2c07056
- Reconciling Methane Emission Measurements for Offshore Oil and Gas Platforms with Detailed Emission Inventories: Accounting for Emission Intermittency Z. Chen et al. 10.1021/acsenvironau.2c00041
- Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al. 10.5194/acp-23-9071-2023
- Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution M. Omara et al. 10.5194/essd-15-3761-2023
- Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison G. McNicol et al. 10.1029/2023AV000956
- 煤炭行业甲烷排放卫星遥感研究进展与展望 秦. Qin Kai et al. 10.3788/AOS231293
- A blended TROPOMI+GOSAT satellite data product for atmospheric methane using machine learning to correct retrieval biases N. Balasus et al. 10.5194/amt-16-3787-2023
- Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action Z. Chen et al. 10.5194/acp-23-5945-2023
- Temperature dependence of the absorption of the R(6) manifold of the 2ν3 band of methane in air in support of the MERLIN mission S. Vasilchenko et al. 10.1016/j.jqsrt.2023.108483
- Evaluating net life-cycle greenhouse gas emissions intensities from gas and coal at varying methane leakage rates D. Gordon et al. 10.1088/1748-9326/ace3db
Latest update: 08 Dec 2023
Executive editor
Methane is a greenhouse gas that significantly contributes to global warming.
Its sources are not well constrained as many point sources are missing in
emission inventories that are built based on bottom-up approaches. Emissions
include sources caused by human activities (oil/gas, lifestock) but also natural ones, e.g.
wetlands. The current paper fills this gap by comprehensively reviewing the
capabilities of current and forthcoming satellites as powerful top-down tools
to observe atmospheric methane and quantify emissions.
Their most important application is to quantify anthropogenic
methane sources , where there is substantial interest in identifying hot spots to reduce
emissions, closing the methane budget, and to ensure compliance with
international climate agreements. This paper is of broad interest for the
geoscience community, as it not only presents an overview of the existing
discrepancies in the atmospheric methane budget and emissions but also addresses the
difficulties in defining its emission inventories on various spatial scales.
Methane is a greenhouse gas that significantly contributes to global warming.
Its sources are...
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.
We review the capability of satellite observations of atmospheric methane to quantify methane...
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