Articles | Volume 18, issue 11
https://doi.org/10.5194/gmd-18-3311-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-3311-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
04 Jun 2025
Model description paper |
| 04 Jun 2025
| 04 Jun 2025
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
Daniel J. Varon
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
Melissa Sulprizio
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
Hannah Nesser
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Zichong Chen
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
Nicholas Balasus
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
Sarah E. Hancock
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
James D. East
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
Todd A. Mooring
Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA
Alexander Oort Alonso
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
Joannes D. Maasakkers
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Ilse Aben
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Sabour Baray
Environment and Climate Change Canada, Toronto, ON, Canada
Kevin W. Bowman
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
John R. Worden
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California, USA
Felipe J. Cardoso-Saldaña
ExxonMobil Technology and Engineering Company, Spring, TX, USA
Emily Reidy
ExxonMobil Technology and Engineering Company, Spring, TX, USA
Daniel J. Jacob
School of Engineering and Applied Science, Harvard University, Cambridge, Massachusetts, USA
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Cited
14 citations as recorded by crossref.
- Technical note: 12 km resolution capability for the global GEOS-Chem model of atmospheric composition X. Wang et al. https://doi.org/10.5194/acp-26-6857-2026
- Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates J. East et al. https://doi.org/10.1038/s41467-025-67122-8
- Quantifying urban and landfill methane emissions in the United States using TROPOMI satellite data X. Wang et al. https://doi.org/10.1126/sciadv.adz9308
- Seasonality and Declining Intensity of Methane Emissions from the Permian and Nearby US Oil and Gas Basins D. Varon et al. https://doi.org/10.1021/acs.est.5c08745
- Simulating out-of-sample atmospheric transport to enable flux inversions N. Dadheech & A. Turner https://doi.org/10.5194/acp-26-427-2026
- Advances in Satellite-Based Monitoring of Urban Emission Sources and Air Quality: A Review S. Naderi et al. https://doi.org/10.1007/s11270-025-09009-4
- Recent advances in TROPOMI-based methane source detection: a systematic review R. Liu et al. https://doi.org/10.1080/15481603.2026.2650822
- Attributing 2019–2024 methane growth using TROPOMI satellite observations M. He et al. https://doi.org/10.1126/sciadv.adz9007
- Predicting and correcting the influence of boundary conditions in regional inverse analyses H. Nesser et al. https://doi.org/10.5194/gmd-18-9279-2025
- 2019–2024 trends in African livestock and wetland emissions as contributors to the global methane rise N. Balasus et al. https://doi.org/10.5194/acp-26-4601-2026
- Continental-scale spatiotemporal assessment of atmospheric methane over Australia: Hotspot persistence and priority-area screening A. Ghahremanlou et al. https://doi.org/10.1016/j.atmosenv.2026.121992
- Estimating Methane Emissions by Integrating Satellite Regional Emissions Mapping and Point-Source Observations: Case Study in the Permian Basin M. Gao & Z. Xing https://doi.org/10.3390/rs17183143
- German methane fluxes estimated top-down using ICON–ART – Part 2: Inversion results for 2021 V. Bruch et al. https://doi.org/10.5194/acp-25-17187-2025
- A Bayesian inversion of TROPOMI methane observations over South Africa: Implications for bottom-up inventories K. Maliehe et al. https://doi.org/10.1016/j.scitotenv.2026.181650
14 citations as recorded by crossref.
- Technical note: 12 km resolution capability for the global GEOS-Chem model of atmospheric composition X. Wang et al. https://doi.org/10.5194/acp-26-6857-2026
- Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates J. East et al. https://doi.org/10.1038/s41467-025-67122-8
- Quantifying urban and landfill methane emissions in the United States using TROPOMI satellite data X. Wang et al. https://doi.org/10.1126/sciadv.adz9308
- Seasonality and Declining Intensity of Methane Emissions from the Permian and Nearby US Oil and Gas Basins D. Varon et al. https://doi.org/10.1021/acs.est.5c08745
- Simulating out-of-sample atmospheric transport to enable flux inversions N. Dadheech & A. Turner https://doi.org/10.5194/acp-26-427-2026
- Advances in Satellite-Based Monitoring of Urban Emission Sources and Air Quality: A Review S. Naderi et al. https://doi.org/10.1007/s11270-025-09009-4
- Recent advances in TROPOMI-based methane source detection: a systematic review R. Liu et al. https://doi.org/10.1080/15481603.2026.2650822
- Attributing 2019–2024 methane growth using TROPOMI satellite observations M. He et al. https://doi.org/10.1126/sciadv.adz9007
- Predicting and correcting the influence of boundary conditions in regional inverse analyses H. Nesser et al. https://doi.org/10.5194/gmd-18-9279-2025
- 2019–2024 trends in African livestock and wetland emissions as contributors to the global methane rise N. Balasus et al. https://doi.org/10.5194/acp-26-4601-2026
- Continental-scale spatiotemporal assessment of atmospheric methane over Australia: Hotspot persistence and priority-area screening A. Ghahremanlou et al. https://doi.org/10.1016/j.atmosenv.2026.121992
- Estimating Methane Emissions by Integrating Satellite Regional Emissions Mapping and Point-Source Observations: Case Study in the Permian Basin M. Gao & Z. Xing https://doi.org/10.3390/rs17183143
- German methane fluxes estimated top-down using ICON–ART – Part 2: Inversion results for 2021 V. Bruch et al. https://doi.org/10.5194/acp-25-17187-2025
- A Bayesian inversion of TROPOMI methane observations over South Africa: Implications for bottom-up inventories K. Maliehe et al. https://doi.org/10.1016/j.scitotenv.2026.181650
Saved (final revised paper)
Latest update: 08 Jun 2026
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.
Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating...
