Articles | Volume 15, issue 14
https://doi.org/10.5194/gmd-15-5787-2022
© 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/gmd-15-5787-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
27 Jul 2022
Model description paper |
| 27 Jul 2022
| 27 Jul 2022
Integrated Methane Inversion (IMI 1.0): a user-friendly, cloud-based facility for inferring high-resolution methane emissions from TROPOMI satellite observations
Daniel J. Varon
CORRESPONDING AUTHOR
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Daniel J. Jacob
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Melissa Sulprizio
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Lucas A. Estrada
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
William B. Downs
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Lu Shen
Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China
Sarah E. Hancock
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Hannah Nesser
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Elise Penn
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
Zichong Chen
School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA
School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
Alba Lorente
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Ashutosh Tewari
ExxonMobil Technology and Engineering Company, Annandale, New Jersey, USA
Cynthia A. Randles
ExxonMobil Technology and Engineering Company, Annandale, New Jersey, USA
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Cited
30 citations as recorded by crossref.
- Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al.
- Seasonality and Declining Intensity of Methane Emissions from the Permian and Nearby US Oil and Gas Basins D. Varon et al.
- Predicting and correcting the influence of boundary conditions in regional inverse analyses H. Nesser et al.
- 2019–2024 trends in African livestock and wetland emissions as contributors to the global methane rise N. Balasus et al.
- Data driven analysis of atmospheric methane concentrations as function of geographic, land cover type and season C. Karoff & A. Vara-Vela
- Quantifying CO emissions from boreal wildfires by assimilating TROPOMI and TCCON observations S. Voshtani et al.
- German methane fluxes estimated top-down using ICON–ART – Part 2: Inversion results for 2021 V. Bruch et al.
- North–south inhomogeneous variations of methane emissions observed by TROPOMI over China S. Yu et al.
- Recent advances in TROPOMI-based methane source detection: a systematic review R. Liu et al.
- Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al.
- Simulating out-of-sample atmospheric transport to enable flux inversions N. Dadheech & A. Turner
- 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.
- Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates J. East et al.
- A Bayesian inversion of TROPOMI methane observations over South Africa: Implications for bottom-up inventories K. Maliehe et al.
- Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al.
- Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI B. Nathan et al.
- Evaluation of the methane full-physics retrieval applied to TROPOMI ocean sun glint measurements A. Lorente et al.
- Estimating Methane Emissions by Integrating Satellite Regional Emissions Mapping and Point-Source Observations: Case Study in the Permian Basin M. Gao & Z. Xing
- CHEEREIO 1.0: a versatile and user-friendly ensemble-based chemical data assimilation and emissions inversion platform for the GEOS-Chem chemical transport model D. Pendergrass et al.
- Quantifying urban and landfill methane emissions in the United States using TROPOMI satellite data X. Wang et al.
- Attributing 2019–2024 methane growth using TROPOMI satellite observations M. He et al.
- 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 L. Estrada et al.
- Landfill methane emission: a case study using inversion methods, satellite and CRDS-based observations T. Silva et al.
- State of the Art in Monitoring Methane Emissions from Arctic–boreal Wetlands and Lakes M. Mahdianpari et al.
- Reconciling Bottom–Up and Top–Down Approaches to Quantify Sub-Regional Methane Emissions with Improved Inventory and Three-Year High-Resolution Satellite Measurements C. He et al.
- Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins L. Shen et al.
- Quantifying Methane Emissions Using Satellite Data: Application of the Integrated Methane Inversion (IMI) Model to Assess Danish Emissions A. Vara-Vela et al.
- Satellite quantification of methane emissions from South American countries: a high-resolution inversion of TROPOMI and GOSAT observations S. Hancock et al.
- High-resolution regional inversion reveals overestimation of anthropogenic methane emissions in China S. Feng et al.
- High-resolution greenhouse gas flux inversions using a machine learning surrogate model for atmospheric transport N. Dadheech et al.
30 citations as recorded by crossref.
- Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al.
- Seasonality and Declining Intensity of Methane Emissions from the Permian and Nearby US Oil and Gas Basins D. Varon et al.
- Predicting and correcting the influence of boundary conditions in regional inverse analyses H. Nesser et al.
- 2019–2024 trends in African livestock and wetland emissions as contributors to the global methane rise N. Balasus et al.
- Data driven analysis of atmospheric methane concentrations as function of geographic, land cover type and season C. Karoff & A. Vara-Vela
- Quantifying CO emissions from boreal wildfires by assimilating TROPOMI and TCCON observations S. Voshtani et al.
- German methane fluxes estimated top-down using ICON–ART – Part 2: Inversion results for 2021 V. Bruch et al.
- North–south inhomogeneous variations of methane emissions observed by TROPOMI over China S. Yu et al.
- Recent advances in TROPOMI-based methane source detection: a systematic review R. Liu et al.
- Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al.
- Simulating out-of-sample atmospheric transport to enable flux inversions N. Dadheech & A. Turner
- 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.
- Worldwide inference of national methane emissions by inversion of satellite observations with UNFCCC prior estimates J. East et al.
- A Bayesian inversion of TROPOMI methane observations over South Africa: Implications for bottom-up inventories K. Maliehe et al.
- Continuous weekly monitoring of methane emissions from the Permian Basin by inversion of TROPOMI satellite observations D. Varon et al.
- Assessing methane emissions from collapsing Venezuelan oil production using TROPOMI B. Nathan et al.
- Evaluation of the methane full-physics retrieval applied to TROPOMI ocean sun glint measurements A. Lorente et al.
- Estimating Methane Emissions by Integrating Satellite Regional Emissions Mapping and Point-Source Observations: Case Study in the Permian Basin M. Gao & Z. Xing
- CHEEREIO 1.0: a versatile and user-friendly ensemble-based chemical data assimilation and emissions inversion platform for the GEOS-Chem chemical transport model D. Pendergrass et al.
- Quantifying urban and landfill methane emissions in the United States using TROPOMI satellite data X. Wang et al.
- Attributing 2019–2024 methane growth using TROPOMI satellite observations M. He et al.
- 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 L. Estrada et al.
- Landfill methane emission: a case study using inversion methods, satellite and CRDS-based observations T. Silva et al.
- State of the Art in Monitoring Methane Emissions from Arctic–boreal Wetlands and Lakes M. Mahdianpari et al.
- Reconciling Bottom–Up and Top–Down Approaches to Quantify Sub-Regional Methane Emissions with Improved Inventory and Three-Year High-Resolution Satellite Measurements C. He et al.
- Satellite quantification of oil and natural gas methane emissions in the US and Canada including contributions from individual basins L. Shen et al.
- Quantifying Methane Emissions Using Satellite Data: Application of the Integrated Methane Inversion (IMI) Model to Assess Danish Emissions A. Vara-Vela et al.
- Satellite quantification of methane emissions from South American countries: a high-resolution inversion of TROPOMI and GOSAT observations S. Hancock et al.
- High-resolution regional inversion reveals overestimation of anthropogenic methane emissions in China S. Feng et al.
- High-resolution greenhouse gas flux inversions using a machine learning surrogate model for atmospheric transport N. Dadheech et al.
Saved (final revised paper)
Latest update: 14 May 2026
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.
Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally...
