Articles | Volume 13, issue 3
https://doi.org/10.5194/essd-13-1073-2021
© 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/essd-13-1073-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A comparative study of anthropogenic CH4 emissions over China based on the ensembles of bottom-up inventories
Xiaohui Lin
CORRESPONDING AUTHOR
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing, China
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing, China
Monica Crippa
European Commission, Joint Research Centre (JRC), Ispra, Italy
Shushi Peng
Sino-French Institute for Earth System Science, College of Urban and
Environmental Sciences, Peking University, Beijing, China
Pengfei Han
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Ning Zeng
Department of Atmospheric and Oceanic Science, and Earth System
Science Interdisciplinary Center, University of Maryland, College Park,
Maryland, USA
Lijun Yu
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing, China
Guocheng Wang
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing, China
Viewed
Total article views: 4,023 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 Aug 2020)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
2,861 | 1,040 | 122 | 4,023 | 425 | 109 | 158 |
- HTML: 2,861
- PDF: 1,040
- XML: 122
- Total: 4,023
- Supplement: 425
- BibTeX: 109
- EndNote: 158
Total article views: 3,550 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 15 Mar 2021)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
2,616 | 823 | 111 | 3,550 | 300 | 92 | 137 |
- HTML: 2,616
- PDF: 823
- XML: 111
- Total: 3,550
- Supplement: 300
- BibTeX: 92
- EndNote: 137
Total article views: 473 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 Aug 2020)
HTML | XML | Total | Supplement | BibTeX | EndNote | |
---|---|---|---|---|---|---|
245 | 217 | 11 | 473 | 125 | 17 | 21 |
- HTML: 245
- PDF: 217
- XML: 11
- Total: 473
- Supplement: 125
- BibTeX: 17
- EndNote: 21
Viewed (geographical distribution)
Total article views: 4,023 (including HTML, PDF, and XML)
Thereof 3,714 with geography defined
and 309 with unknown origin.
Total article views: 3,550 (including HTML, PDF, and XML)
Thereof 3,306 with geography defined
and 244 with unknown origin.
Total article views: 473 (including HTML, PDF, and XML)
Thereof 408 with geography defined
and 65 with unknown origin.
Country | # | Views | % |
---|
Country | # | Views | % |
---|
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Cited
26 citations as recorded by crossref.
- Mitigating climate change by abating coal mine methane: A critical review of status and opportunities C. Karacan et al. 10.1016/j.coal.2024.104623
- Historical trend of China's CH4 concentrations and emissions during 2003–2020 based on satellite observations, and their implications D. Chen et al. 10.1016/j.apr.2022.101615
- Influence of Surface Methane on Tropospheric Ozone Concentrations and Cereal Yield in Asia K. Tatsumi 10.3390/agronomy13102586
- Rio (1992) to Glasgow (2021): Three decades of inadequate mitigation of climate change and its slow onset effects I. Stavi 10.3389/fenvs.2022.999788
- Agriculture related methane emissions embodied in China's interprovincial trade H. Pan et al. 10.1016/j.rser.2023.113850
- An integrated view of correlated emissions of greenhouse gases and air pollutants in China X. Lin et al. 10.1186/s13021-023-00229-x
- Natural Gas Leakage Ratio Determined from Flux Measurements of Methane in Urban Beijing Y. Huangfu et al. 10.1021/acs.estlett.4c00573
- Fossil-Fuel and Food Systems Equally Dominate Anthropogenic Methane Emissions in China S. Liu et al. 10.1021/acs.est.2c07933
- 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
- China's methane emissions derived from the inversion of GOSAT observations with a CMAQ and EnKS-based regional data assimilation system X. Kou et al. 10.1016/j.apr.2024.102333
- The Chinese Carbon-Neutral Goal: Challenges and Prospects N. Zeng et al. 10.1007/s00376-021-1313-6
- Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
- The effect of quarantine policy on pollution emission and the usage of private transportation in urban areas Y. Hong & K. Lu 10.1038/s41598-024-66685-8
- Spatial and Temporal Variations of Atmospheric CH4 in Monsoon Asia Detected by Satellite Observations of GOSAT and TROPOMI H. Song et al. 10.3390/rs15133389
- Decreasing methane emissions from China’s coal mining with rebounded coal production J. Gao et al. 10.1088/1748-9326/ac38d8
- Temporal variation and grade categorization of methane emission from LNG fueling stations Y. Wang et al. 10.1038/s41598-022-23334-2
- Decadal Methane Emission Trend Inferred from Proxy GOSAT XCH4 Retrievals: Impacts of Transport Model Spatial Resolution S. Zhu et al. 10.1007/s00376-022-1434-6
- Seamless mapping of long-term (2010–2020) daily global XCO2 and XCH4 from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatiotemporally self-supervised fusion method Y. Wang et al. 10.5194/essd-15-3597-2023
- Paving the way for sustainable agriculture: An analysis of evolution and driving forces of methane emissions reduction in China Z. Xu et al. 10.1016/j.resconrec.2023.107392
- Retrieval of dominant methane (CH4) emission sources, the first high-resolution (1–2 m) dataset of storage tanks of China in 2000–2021 F. Chen et al. 10.5194/essd-16-3369-2024
- Effect of Surface Methane Controls on Ozone Concentration and Rice Yield in Asia K. Tatsumi 10.3390/atmos14101558
- City-level livestock methane emissions in China from 2010 to 2020 M. Du et al. 10.1038/s41597-024-03072-y
- Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region W. Hu et al. 10.1007/s40789-024-00700-1
- Quantification of Central and Eastern China's atmospheric CH4 enhancement changes and its contributions based on machine learning approach X. Ai et al. 10.1016/j.jes.2023.03.010
- Spatiotemporal investigation of near-surface CH4 and factors influencing CH4 over South, East, and Southeast Asia M. Khaliq et al. 10.1016/j.scitotenv.2024.171311
- 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
26 citations as recorded by crossref.
- Mitigating climate change by abating coal mine methane: A critical review of status and opportunities C. Karacan et al. 10.1016/j.coal.2024.104623
- Historical trend of China's CH4 concentrations and emissions during 2003–2020 based on satellite observations, and their implications D. Chen et al. 10.1016/j.apr.2022.101615
- Influence of Surface Methane on Tropospheric Ozone Concentrations and Cereal Yield in Asia K. Tatsumi 10.3390/agronomy13102586
- Rio (1992) to Glasgow (2021): Three decades of inadequate mitigation of climate change and its slow onset effects I. Stavi 10.3389/fenvs.2022.999788
- Agriculture related methane emissions embodied in China's interprovincial trade H. Pan et al. 10.1016/j.rser.2023.113850
- An integrated view of correlated emissions of greenhouse gases and air pollutants in China X. Lin et al. 10.1186/s13021-023-00229-x
- Natural Gas Leakage Ratio Determined from Flux Measurements of Methane in Urban Beijing Y. Huangfu et al. 10.1021/acs.estlett.4c00573
- Fossil-Fuel and Food Systems Equally Dominate Anthropogenic Methane Emissions in China S. Liu et al. 10.1021/acs.est.2c07933
- 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
- China's methane emissions derived from the inversion of GOSAT observations with a CMAQ and EnKS-based regional data assimilation system X. Kou et al. 10.1016/j.apr.2024.102333
- The Chinese Carbon-Neutral Goal: Challenges and Prospects N. Zeng et al. 10.1007/s00376-021-1313-6
- Methane emissions from China: a high-resolution inversion of TROPOMI satellite observations Z. Chen et al. 10.5194/acp-22-10809-2022
- The effect of quarantine policy on pollution emission and the usage of private transportation in urban areas Y. Hong & K. Lu 10.1038/s41598-024-66685-8
- Spatial and Temporal Variations of Atmospheric CH4 in Monsoon Asia Detected by Satellite Observations of GOSAT and TROPOMI H. Song et al. 10.3390/rs15133389
- Decreasing methane emissions from China’s coal mining with rebounded coal production J. Gao et al. 10.1088/1748-9326/ac38d8
- Temporal variation and grade categorization of methane emission from LNG fueling stations Y. Wang et al. 10.1038/s41598-022-23334-2
- Decadal Methane Emission Trend Inferred from Proxy GOSAT XCH4 Retrievals: Impacts of Transport Model Spatial Resolution S. Zhu et al. 10.1007/s00376-022-1434-6
- Seamless mapping of long-term (2010–2020) daily global XCO2 and XCH4 from the Greenhouse Gases Observing Satellite (GOSAT), Orbiting Carbon Observatory 2 (OCO-2), and CAMS global greenhouse gas reanalysis (CAMS-EGG4) with a spatiotemporally self-supervised fusion method Y. Wang et al. 10.5194/essd-15-3597-2023
- Paving the way for sustainable agriculture: An analysis of evolution and driving forces of methane emissions reduction in China Z. Xu et al. 10.1016/j.resconrec.2023.107392
- Retrieval of dominant methane (CH4) emission sources, the first high-resolution (1–2 m) dataset of storage tanks of China in 2000–2021 F. Chen et al. 10.5194/essd-16-3369-2024
- Effect of Surface Methane Controls on Ozone Concentration and Rice Yield in Asia K. Tatsumi 10.3390/atmos14101558
- City-level livestock methane emissions in China from 2010 to 2020 M. Du et al. 10.1038/s41597-024-03072-y
- Merging TROPOMI and eddy covariance observations to quantify 5-years of daily CH4 emissions over coal-mine dominated region W. Hu et al. 10.1007/s40789-024-00700-1
- Quantification of Central and Eastern China's atmospheric CH4 enhancement changes and its contributions based on machine learning approach X. Ai et al. 10.1016/j.jes.2023.03.010
- Spatiotemporal investigation of near-surface CH4 and factors influencing CH4 over South, East, and Southeast Asia M. Khaliq et al. 10.1016/j.scitotenv.2024.171311
- 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
Latest update: 13 Dec 2024
Short summary
CH4 is a potent greenhouse gas, and China’s anthropogenic CH4 emissions account for a large proportion of global total emissions. However, the existing estimates either focus on a specific sector or lag behind real time by several years. We collected and analyzed 12 datasets and compared them to reveal the spatiotemporal changes and their uncertainties. We further estimated the emissions from 1990–2019, and the estimates showed a robust trend in recent years when compared to top-down results.
CH4 is a potent greenhouse gas, and China’s anthropogenic CH4 emissions account for a large...
Altmetrics
Final-revised paper
Preprint