Articles | Volume 21, issue 6
https://doi.org/10.5194/acp-21-5117-2021
© Author(s) 2021. 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-21-5117-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Apr 2021
Research article |
| 01 Apr 2021
| 01 Apr 2021
Systematic detection of local CH4 anomalies by combining satellite measurements with high-resolution forecasts
Jérôme Barré
CORRESPONDING AUTHOR
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Ilse Aben
SRON, Netherlands Institute for Space Research, Utrecht, the Netherlands
Anna Agustí-Panareda
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Gianpaolo Balsamo
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Nicolas Bousserez
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Peter Dueben
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Richard Engelen
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Antje Inness
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Alba Lorente
SRON, Netherlands Institute for Space Research, Utrecht, the Netherlands
Joe McNorton
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Vincent-Henri Peuch
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Gabor Radnoti
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
Roberto Ribas
ECMWF, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, UK
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- High-resolution US methane emissions inferred from an inversion of 2019 TROPOMI satellite data: contributions from individual states, urban areas, and landfills H. Nesser et al. 10.5194/acp-24-5069-2024
- Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm O. Schneising et al. 10.5194/amt-16-669-2023
- Satellites Detect Abatable Super-Emissions in One of the World’s Largest Methane Hotspot Regions I. Irakulis-Loitxate et al. 10.1021/acs.est.1c04873
- Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement A. Agustí-Panareda et al. 10.1038/s41597-022-01228-2
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- Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations T. Scarpelli et al. 10.5194/acp-22-3235-2022
- Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data S. Vanselow et al. 10.5194/acp-24-10441-2024
- Widespread Frequent Methane Emissions From the Oil and Gas Industry in the Permian Basin J. Veefkind et al. 10.1029/2022JD037479
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- The CO2 Human Emissions (CHE) Project: First Steps Towards a European Operational Capacity to Monitor Anthropogenic CO2 Emissions G. Balsamo et al. 10.3389/frsen.2021.707247
- Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Sentinel-2 Imagery T. Ehret et al. 10.1021/acs.est.1c08575
- Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products M. Schneider et al. 10.5194/amt-15-4339-2022
- Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI B. Nathan et al. 10.5194/acp-24-6845-2024
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- Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J. McNorton et al. 10.5194/acp-22-5961-2022
- Monitoring greenhouse gases (GHGs) in China: status and perspective Y. Sun et al. 10.5194/amt-15-4819-2022
- Spatial-Temporal Changes of Methane Content in the Atmosphere for Selected Countries and Regions with High Methane Emission from Rice Cultivation K. Kozicka et al. 10.3390/atmos12111382
- 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
- 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
- Global assessment of oil and gas methane ultra-emitters T. Lauvaux et al. 10.1126/science.abj4351
- Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations D. Varon et al. 10.5194/gmd-15-5787-2022
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- Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: ground-based observations, TROPOMI data, inventory data, and inversions P. Han et al. 10.5194/acp-25-4965-2025
- Methane retrieved from TROPOMI: improvement of the data product and validation of the first 2 years of measurements A. Lorente et al. 10.5194/amt-14-665-2021
28 citations as recorded by crossref.
- La surveillance des émissions anthropiques de CO2 depuis l’espace : un enjeu géopolitique émergent G. Broquet & F. Chevallier 10.4000/12de3
- Quantifying methane emissions from the global scale down to point sources using satellite observations of atmospheric methane D. Jacob et al. 10.5194/acp-22-9617-2022
- Accounting for surface reflectance spectral features in TROPOMI methane retrievals A. Lorente et al. 10.5194/amt-16-1597-2023
- High-resolution US methane emissions inferred from an inversion of 2019 TROPOMI satellite data: contributions from individual states, urban areas, and landfills H. Nesser et al. 10.5194/acp-24-5069-2024
- Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm O. Schneising et al. 10.5194/amt-16-669-2023
- Satellites Detect Abatable Super-Emissions in One of the World’s Largest Methane Hotspot Regions I. Irakulis-Loitxate et al. 10.1021/acs.est.1c04873
- Global nature run data with realistic high-resolution carbon weather for the year of the Paris Agreement A. Agustí-Panareda et al. 10.1038/s41597-022-01228-2
- Reconstructing and quantifying methane emissions from the full duration of a 38-day natural gas well blowout using space-based observations J. Maasakkers et al. 10.1016/j.rse.2021.112755
- Updated Global Fuel Exploitation Inventory (GFEI) for methane emissions from the oil, gas, and coal sectors: evaluation with inversions of atmospheric methane observations T. Scarpelli et al. 10.5194/acp-22-3235-2022
- Automated detection of regions with persistently enhanced methane concentrations using Sentinel-5 Precursor satellite data S. Vanselow et al. 10.5194/acp-24-10441-2024
- Widespread Frequent Methane Emissions From the Oil and Gas Industry in the Permian Basin J. Veefkind et al. 10.1029/2022JD037479
- Quantification of CH4 emissions from waste disposal sites near the city of Madrid using ground- and space-based observations of COCCON, TROPOMI and IASI Q. Tu et al. 10.5194/acp-22-295-2022
- An Effective Quantification of Methane Point-Source Emissions with the Multi-Level Matched Filter from Hyperspectral Imagery M. Liang et al. 10.3390/rs17050843
- On the influence of underlying elevation data on Sentinel-5 Precursor TROPOMI satellite methane retrievals over Greenland J. Hachmeister et al. 10.5194/amt-15-4063-2022
- The CO2 Human Emissions (CHE) Project: First Steps Towards a European Operational Capacity to Monitor Anthropogenic CO2 Emissions G. Balsamo et al. 10.3389/frsen.2021.707247
- Global Tracking and Quantification of Oil and Gas Methane Emissions from Recurrent Sentinel-2 Imagery T. Ehret et al. 10.1021/acs.est.1c08575
- Synergetic use of IASI profile and TROPOMI total-column level 2 methane retrieval products M. Schneider et al. 10.5194/amt-15-4339-2022
- Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI B. Nathan et al. 10.5194/acp-24-6845-2024
- Sensitivity of land-type variations across Canada using S-5p products S. Bhatnagar et al. 10.1016/j.geomat.2025.100048
- Quantification of methane emissions from hotspots and during COVID-19 using a global atmospheric inversion J. McNorton et al. 10.5194/acp-22-5961-2022
- Monitoring greenhouse gases (GHGs) in China: status and perspective Y. Sun et al. 10.5194/amt-15-4819-2022
- Spatial-Temporal Changes of Methane Content in the Atmosphere for Selected Countries and Regions with High Methane Emission from Rice Cultivation K. Kozicka et al. 10.3390/atmos12111382
- 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
- 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
- Global assessment of oil and gas methane ultra-emitters T. Lauvaux et al. 10.1126/science.abj4351
- Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations D. Varon et al. 10.5194/gmd-15-5787-2022
- Quantifying CH4 emissions in hard coal mines from TROPOMI and IASI observations using the wind-assigned anomaly method Q. Tu et al. 10.5194/acp-22-9747-2022
- Spatiotemporal variations in atmospheric CH4 concentrations and enhancements in northern China based on a comprehensive dataset: ground-based observations, TROPOMI data, inventory data, and inversions P. Han et al. 10.5194/acp-25-4965-2025
Latest update: 19 Jun 2025
Short summary
This study presents a new approach to the systematic global detection of anomalous local CH4 concentration anomalies caused by rapid changes in anthropogenic emission levels. The approach utilises both satellite measurements and model simulations, and applies novel data analysis techniques (such as filtering and classification) to automatically detect anomalous emissions from point sources and small areas, such as oil and gas drilling sites, pipelines and facility leaks.
This study presents a new approach to the systematic global detection of anomalous local CH4...
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