Articles | Volume 22, issue 16
https://doi.org/10.5194/acp-22-10809-2022
© 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-22-10809-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Aug 2022
Research article |
| 26 Aug 2022
| 26 Aug 2022
Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations
Zichong Chen
CORRESPONDING AUTHOR
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA, USA
Daniel J. Jacob
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA, USA
Hannah Nesser
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA, USA
Melissa P. Sulprizio
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA, USA
Alba Lorente
SRON Netherlands Institute for Space Research, Leiden, the Netherlands
Daniel J. Varon
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA, USA
School of Atmospheric Sciences, Sun Yat-sen University, Zhuhai,
Guangdong, China
Lu Shen
Department of Atmospheric and Oceanic Sciences, School of Physics,
Peking University, Beijing, China
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA, USA
Elise Penn
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA, USA
Xueying Yu
Department of Soil, Water, and Climate, University of Minnesota, Saint Paul, MN, USA
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Cited
26 citations as recorded by crossref.
- 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
- 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
- Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al. 10.1038/s41598-023-41914-8
- High-Spatial-Resolution Methane Emissions Calculation Using TROPOMI Data by a Divergence Method S. Li et al. 10.3390/atmos14020388
- Methane emission and influencing factors of China's oil and natural gas sector in 2020–2060: A source level analysis S. Sun et al. 10.1016/j.scitotenv.2023.167116
- Bottom‐Up Evaluation of the Methane Budget in Asia and Its Subregions A. Ito et al. 10.1029/2023GB007723
- 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
- Estimation of Anthropogenic CH4 and CO2 Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots C. Hu et al. 10.1029/2022JD037915
- Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and gas fields tied to activity metrics X. Lu et al. 10.1073/pnas.2217900120
- 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
- Anthropogenic CO2 emission estimates in the Tokyo metropolitan area from ground-based CO2 column observations H. Ohyama et al. 10.5194/acp-23-15097-2023
- 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
- Global warming will largely increase waste treatment CH4 emissions in Chinese megacities: insight from the first city-scale CH4 concentration observation network in Hangzhou, China C. Hu et al. 10.5194/acp-23-4501-2023
- City-level livestock methane emissions in China from 2010 to 2020 M. Du et al. 10.1038/s41597-024-03072-y
- Accounting for surface reflectance spectral features in TROPOMI methane retrievals A. Lorente et al. 10.5194/amt-16-1597-2023
- Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data K. Li et al. 10.1016/j.rse.2024.114039
- 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
- Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al. 10.5194/acp-23-9071-2023
- Reconciling a national methane emission inventory with in-situ measurements Y. Liu et al. 10.1016/j.scitotenv.2023.165896
- Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
- 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
- Practical Guide to Measuring Wetland Carbon Pools and Fluxes S. Bansal et al. 10.1007/s13157-023-01722-2
- Satellite derived trends and variability of CO2 concentrations in the Middle East during 2014–2023 R. Fonseca & D. Francis 10.3389/fenvs.2023.1289142
- An Observing System Simulation Experiment Analysis of How Well Geostationary Satellite Trace‐Gas Observations Constrain NOx Emissions in the US C. Hsu et al. 10.1029/2023JD039323
- A Gridded Inventory of Annual 2012–2018 U.S. Anthropogenic Methane Emissions J. Maasakkers et al. 10.1021/acs.est.3c05138
- Fossil-Fuel and Food Systems Equally Dominate Anthropogenic Methane Emissions in China S. Liu et al. 10.1021/acs.est.2c07933
26 citations as recorded by crossref.
- 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
- 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
- Global observational coverage of onshore oil and gas methane sources with TROPOMI M. Gao et al. 10.1038/s41598-023-41914-8
- High-Spatial-Resolution Methane Emissions Calculation Using TROPOMI Data by a Divergence Method S. Li et al. 10.3390/atmos14020388
- Methane emission and influencing factors of China's oil and natural gas sector in 2020–2060: A source level analysis S. Sun et al. 10.1016/j.scitotenv.2023.167116
- Bottom‐Up Evaluation of the Methane Budget in Asia and Its Subregions A. Ito et al. 10.1029/2023GB007723
- 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
- Estimation of Anthropogenic CH4 and CO2 Emissions in Taiyuan‐Jinzhong Region: One of the World's Largest Emission Hotspots C. Hu et al. 10.1029/2022JD037915
- Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and gas fields tied to activity metrics X. Lu et al. 10.1073/pnas.2217900120
- 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
- Anthropogenic CO2 emission estimates in the Tokyo metropolitan area from ground-based CO2 column observations H. Ohyama et al. 10.5194/acp-23-15097-2023
- 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
- Global warming will largely increase waste treatment CH4 emissions in Chinese megacities: insight from the first city-scale CH4 concentration observation network in Hangzhou, China C. Hu et al. 10.5194/acp-23-4501-2023
- City-level livestock methane emissions in China from 2010 to 2020 M. Du et al. 10.1038/s41597-024-03072-y
- Accounting for surface reflectance spectral features in TROPOMI methane retrievals A. Lorente et al. 10.5194/amt-16-1597-2023
- Developing unbiased estimation of atmospheric methane via machine learning and multiobjective programming based on TROPOMI and GOSAT data K. Li et al. 10.1016/j.rse.2024.114039
- 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
- Automated detection and monitoring of methane super-emitters using satellite data B. Schuit et al. 10.5194/acp-23-9071-2023
- Reconciling a national methane emission inventory with in-situ measurements Y. Liu et al. 10.1016/j.scitotenv.2023.165896
- Methane Retrieval Algorithms Based on Satellite: A Review Y. Jiang et al. 10.3390/atmos15040449
- 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
- Practical Guide to Measuring Wetland Carbon Pools and Fluxes S. Bansal et al. 10.1007/s13157-023-01722-2
- Satellite derived trends and variability of CO2 concentrations in the Middle East during 2014–2023 R. Fonseca & D. Francis 10.3389/fenvs.2023.1289142
- An Observing System Simulation Experiment Analysis of How Well Geostationary Satellite Trace‐Gas Observations Constrain NOx Emissions in the US C. Hsu et al. 10.1029/2023JD039323
- A Gridded Inventory of Annual 2012–2018 U.S. Anthropogenic Methane Emissions J. Maasakkers et al. 10.1021/acs.est.3c05138
- Fossil-Fuel and Food Systems Equally Dominate Anthropogenic Methane Emissions in China S. Liu et al. 10.1021/acs.est.2c07933
Latest update: 16 Apr 2024
Short summary
We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
We quantify methane emissions in China and contributions from different sectors by inverse...
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