Articles | Volume 22, issue 10
https://doi.org/10.5194/acp-22-6811-2022
© 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-22-6811-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 May 2022
Research article |
| 25 May 2022
| 25 May 2022
The 2019 methane budget and uncertainties at 1° resolution and each country through Bayesian integration Of GOSAT total column methane data and a priori inventory estimates
John R. Worden
CORRESPONDING AUTHOR
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Daniel H. Cusworth
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Arizona Institutes for Resilience, University of Arizona, Tucson, AZ, USA
School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
Yuzhong Zhang
School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
Institute of Advanced Technology, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
A. Anthony Bloom
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Shuang Ma
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Brendan K. Byrne
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Tia Scarpelli
School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
Joannes D. Maasakkers
SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
David Crisp
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
Riley Duren
Arizona Institutes for Resilience, University of Arizona, Tucson, AZ, USA
Daniel J. Jacob
School of Engineering and Applied Science, Harvard University, Cambridge, MA, USA
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Cited
23 citations as recorded by crossref.
- Direct measurement of methane emissions from the upstream oil and gas sector: Review of measurement results and technology advances (2018–2022) X. Yang et al. 10.1016/j.jclepro.2023.137693
- A global review of methane policies reveals that only 13% of emissions are covered with unclear effectiveness M. Olczak et al. 10.1016/j.oneear.2023.04.009
- 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
- Assessment of methane emissions from oil, gas and coal sectors across inventories and atmospheric inversions K. Tibrewal et al. 10.1038/s43247-023-01190-w
- City-scale methane emissions from the midstream oil and gas industry: A satellite survey of the Zhoushan archipelago X. Yang et al. 10.1016/j.jclepro.2024.141673
- National CO2budgets (2015–2020) inferred from atmospheric CO2observations in support of the global stocktake B. Byrne et al. 10.5194/essd-15-963-2023
- A high-resolution satellite-based map of global methane emissions reveals missing wetland, fossil fuel, and monsoon sources X. Yu et al. 10.5194/acp-23-3325-2023
- 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
- 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
- A Gridded Inventory of Annual 2012–2018 U.S. Anthropogenic Methane Emissions J. Maasakkers et al. 10.1021/acs.est.3c05138
- 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
- Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
- The greenhouse gas budget for China's terrestrial ecosystems X. Wang et al. 10.1093/nsr/nwad274
- Assessing the methane mitigation potential of innovative management in US rice production C. Reavis et al. 10.1088/1748-9326/ad0925
- Country-level methane emissions and their sectoral trends during 2009–2020 estimated by high-resolution inversion of GOSAT and surface observations R. Janardanan et al. 10.1088/1748-9326/ad2436
- 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
- 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
- Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space A. Thorpe et al. 10.1126/sciadv.adh2391
- Changes in tropospheric air quality related to the protection of stratospheric ozone in a changing climate S. Madronich et al. 10.1007/s43630-023-00369-6
- Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
- Numerical analysis of CH4 concentration distributions over East Asia with a regional chemical transport model L. Qin et al. 10.1016/j.atmosenv.2023.120207
- Bottom‐Up Evaluation of the Methane Budget in Asia and Its Subregions A. Ito et al. 10.1029/2023GB007723
- 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
22 citations as recorded by crossref.
- Direct measurement of methane emissions from the upstream oil and gas sector: Review of measurement results and technology advances (2018–2022) X. Yang et al. 10.1016/j.jclepro.2023.137693
- A global review of methane policies reveals that only 13% of emissions are covered with unclear effectiveness M. Olczak et al. 10.1016/j.oneear.2023.04.009
- 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
- Assessment of methane emissions from oil, gas and coal sectors across inventories and atmospheric inversions K. Tibrewal et al. 10.1038/s43247-023-01190-w
- City-scale methane emissions from the midstream oil and gas industry: A satellite survey of the Zhoushan archipelago X. Yang et al. 10.1016/j.jclepro.2024.141673
- National CO2budgets (2015–2020) inferred from atmospheric CO2observations in support of the global stocktake B. Byrne et al. 10.5194/essd-15-963-2023
- A high-resolution satellite-based map of global methane emissions reveals missing wetland, fossil fuel, and monsoon sources X. Yu et al. 10.5194/acp-23-3325-2023
- 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
- 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
- A Gridded Inventory of Annual 2012–2018 U.S. Anthropogenic Methane Emissions J. Maasakkers et al. 10.1021/acs.est.3c05138
- 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
- Verifying Methane Inventories and Trends With Atmospheric Methane Data J. Worden et al. 10.1029/2023AV000871
- The greenhouse gas budget for China's terrestrial ecosystems X. Wang et al. 10.1093/nsr/nwad274
- Assessing the methane mitigation potential of innovative management in US rice production C. Reavis et al. 10.1088/1748-9326/ad0925
- Country-level methane emissions and their sectoral trends during 2009–2020 estimated by high-resolution inversion of GOSAT and surface observations R. Janardanan et al. 10.1088/1748-9326/ad2436
- 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
- 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
- Attribution of individual methane and carbon dioxide emission sources using EMIT observations from space A. Thorpe et al. 10.1126/sciadv.adh2391
- Changes in tropospheric air quality related to the protection of stratospheric ozone in a changing climate S. Madronich et al. 10.1007/s43630-023-00369-6
- Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
- Numerical analysis of CH4 concentration distributions over East Asia with a regional chemical transport model L. Qin et al. 10.1016/j.atmosenv.2023.120207
- Bottom‐Up Evaluation of the Methane Budget in Asia and Its Subregions A. Ito et al. 10.1029/2023GB007723
Latest update: 24 Apr 2024
Short summary
This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely...
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