Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2857-2024
© Author(s) 2024. 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-16-2857-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A global surface CO2 flux dataset (2015–2022) inferred from OCO-2 retrievals using the GONGGA inversion system
Zhe Jin
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Xiangjun Tian
CORRESPONDING AUTHOR
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 101408, China
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Hongqin Zhang
Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
Min Zhao
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Tao Wang
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Jinzhi Ding
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Shilong Piao
State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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Cited
9 citations as recorded by crossref.
- To what extent does the CO2 diurnal cycle impact flux estimates derived from global and regional inversions? S. Munassar et al. 10.5194/acp-25-639-2025
- Improved estimates of net ecosystem exchanges in mega-countries using GOSAT and OCO-2 observations L. Zhang et al. 10.1038/s43247-024-01910-w
- Observation of greenhouse gas vertical profiles in the boundary layer of the Mount Qomolangma region using a multirotor UAV Y. Zhou et al. 10.5194/amt-18-1609-2025
- A Top-Down Method for Estimating Regional Fossil Fuel Carbon Emissions Based on Satellite XCO2 Retrievals L. Zhang et al. 10.3390/rs17030447
- Global 20-year time series of XCO2 concentrations derived from satellite observations and interpolations to analyze XCO2 anomalies caused by wildfires W. Wefers et al. 10.1016/j.atmosres.2025.108408
- The decline in tropical land carbon sink drove high atmospheric CO2 growth rate in 2023 Y. Gui et al. 10.1093/nsr/nwae365
- CO2 flux emissions at two urban sites in Beijing and responses to human activity H. Liu et al. 10.1016/j.pce.2024.103791
- Towards verifying and improving estimations of China's CO2 and CH4 budgets using atmospheric inversions Y. Wang et al. 10.1093/nsr/nwaf090
- A global surface CO2 flux dataset (2015–2022) inferred from OCO-2 retrievals using the GONGGA inversion system Z. Jin et al. 10.5194/essd-16-2857-2024
8 citations as recorded by crossref.
- To what extent does the CO2 diurnal cycle impact flux estimates derived from global and regional inversions? S. Munassar et al. 10.5194/acp-25-639-2025
- Improved estimates of net ecosystem exchanges in mega-countries using GOSAT and OCO-2 observations L. Zhang et al. 10.1038/s43247-024-01910-w
- Observation of greenhouse gas vertical profiles in the boundary layer of the Mount Qomolangma region using a multirotor UAV Y. Zhou et al. 10.5194/amt-18-1609-2025
- A Top-Down Method for Estimating Regional Fossil Fuel Carbon Emissions Based on Satellite XCO2 Retrievals L. Zhang et al. 10.3390/rs17030447
- Global 20-year time series of XCO2 concentrations derived from satellite observations and interpolations to analyze XCO2 anomalies caused by wildfires W. Wefers et al. 10.1016/j.atmosres.2025.108408
- The decline in tropical land carbon sink drove high atmospheric CO2 growth rate in 2023 Y. Gui et al. 10.1093/nsr/nwae365
- CO2 flux emissions at two urban sites in Beijing and responses to human activity H. Liu et al. 10.1016/j.pce.2024.103791
- Towards verifying and improving estimations of China's CO2 and CH4 budgets using atmospheric inversions Y. Wang et al. 10.1093/nsr/nwaf090
Latest update: 30 Aug 2025
Short summary
An accurate estimate of spatial distribution and temporal evolution of CO2 fluxes is a critical foundation for providing information regarding global carbon cycle and climate mitigation. Here, we present a global carbon flux dataset for 2015–2022, derived by assimilating satellite CO2 observations into the GONGGA inversion system. This dataset will help improve the broader understanding of global carbon cycle dynamics and their response to climate change.
An accurate estimate of spatial distribution and temporal evolution of CO2 fluxes is a critical...
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