An inversion model based on GEOS-Chem for estimating global and China's terrestrial carbon fluxes in 2019

被引:10
|
作者
Wu, Chong -Yuan [1 ]
Zhang, Xiao-Ye [1 ,2 ]
Guo, Li-Feng [1 ]
Zhong, Jun -Ting [1 ]
Wang, De-Ying [1 ]
Miao, Chang -Hong [3 ]
Gao, Xiang [4 ]
Zhang, Xi-Liang [5 ]
机构
[1] Chinese Acad Meteorol Sci, Monitoring & Assessment Ctr GHGs & Carbon, Key Lab Atmospher Chem China Meteorol Adm, Beijing 100081, Peoples R China
[2] Zhejiang Inst Meteorol Sci, Zhejiang Meteorol Bur, Hangzhou 310017, Peoples R China
[3] Henan Univ, Lab Climate Change Mitigat & Carbon Neutral, Zhengzhou 450001, Peoples R China
[4] Zhejiang Univ, State Environm Protect Ctr Coal Fired Air Pollut C, State Key Lab Clean Energy Utilizat, Hangzhou 310027, Peoples R China
[5] Tsinghua Univ, Inst Energy Environm & Econ, Beijing 100084, Peoples R China
关键词
CO2; Data assimilation; EnSRF; GEOS-Chem; Terrestrial carbon fluxes; ENSEMBLE DATA ASSIMILATION; ATMOSPHERIC CO2; DIOXIDE EXCHANGE; IN-SITU; EMISSIONS; IMPACT; SINKS; LAND; RETRIEVALS; ECOSYSTEMS;
D O I
10.1016/j.accre.2023.01.001
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories added the method of assimilating atmospheric CO2 concentrations to invert carbon sources and sinks; however, many global carbon inversion models are not publicly available. In addition, our regional assimilation inversion system, CCMVS-R (China Carbon Monitoring, Verification and Supporting for Regional), needs a global carbon inversion model with higher assimilation efficiency to provide boundary conditions. Here, an inversion model based on the global atmospheric chemistry model GEOS-Chem and a more accurate and easier-to-implement ensemble square root Kalman filter (EnSRF) algorithm is con-structed and used to infer global and China's carbon fluxes in 2019. Atmospheric CO2 concentrations from ObsPack sites and five additional CO2 observational sites from China's Greenhouse Gas Observation Network (CGHGNET) were used for data assimilation to improve the estimate. The inverted annual global terrestrial and oceanic carbon uptake is 2.12 and 2.53 Pg C per year, respectively, accounting for 21.1% and 25.1% of global fossil fuel CO2 emissions. The remaining 5.41 Pg C per year in the atmosphere is consistent with the global atmospheric CO2 growth rates of 5.44 Pg C per year reported by the National Oceanic and Atmospheric Administration (NOAA), showing that the inversion model can provide a reasonable estimate of global-scale natural carbon sinks. The inverted terrestrial carbon sink of China is 0.37 Pg C per year, accounting for approximately 13% of China's fossil CO2 emissions.
引用
收藏
页码:49 / 61
页数:13
相关论文
共 50 条
  • [21] Estimating surface carbon fluxes based on a local ensemble transform Kalman filter with a short assimilation window and a long observation window: an observing system simulation experiment test in GEOS-Chem 10.1
    Liu, Yun
    Kalnay, Eugenia
    Zeng, Ning
    Asrar, Ghassem
    Chen, Zhaohui
    Jia, Binghao
    GEOSCIENTIFIC MODEL DEVELOPMENT, 2019, 12 (07) : 2899 - 2914
  • [22] Impact of net-zero emissions on atmospheric CO2 concentration in China: Ideal simulations based on the GEOS-Chem model
    Tan, Jingye
    Wang, Jun
    Mao, Huiqin
    Wang, Hengmao
    Liu, Zhiqiang
    Wang, Meirong
    Yan, Ran
    Wang, Xunmei
    Jiang, Fei
    SCIENCE CHINA-EARTH SCIENCES, 2025, 68 (03) : 867 - 881
  • [23] Assessment of the Impacts of Different Carbon Sources and Sinks on Atmospheric CO2 Concentrations Based on GEOS-Chem
    Qu, Ge
    Zhou, Jia
    Shi, Yusheng
    Yang, Yongliang
    Su, Mengqian
    Wu, Wen
    Zhou, Zhitao
    REMOTE SENSING, 2025, 17 (06)
  • [24] FTIR time series of stratospheric NO2 over Hefei, China, and comparisons with OMI and GEOS-Chem model data
    Yin, Hao
    Sun, Youwen
    Liu, Cheng
    Zhang, Lin
    Lu, Xiao
    Wang, Wei
    Shan, Changgong
    Hu, Qihou
    Tian, Yuan
    Zhang, Chengxin
    Su, Wenjing
    Zhang, Huifang
    Palm, Mathias
    Notholt, Justus
    Liu, Jianguo
    OPTICS EXPRESS, 2019, 27 (16): : A1225 - A1240
  • [25] Regional CO pollution and export in China simulated by the high-resolution nested-grid GEOS-Chem model
    Chen, D.
    Wang, Y.
    McElroy, M. B.
    He, K.
    Yantosca, R. M.
    Le Sager, P.
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2009, 9 (11) : 3825 - 3839
  • [26] Atmospheric Aerosol Distribution in 2016-2017 over the Eastern European Region Based on the GEOS-Chem Model
    Milinevsky, Gennadi
    Miatselskaya, Natallia
    Grytsai, Asen
    Danylevsky, Vassyl
    Bril, Andrey
    Chaikovsky, Anatoli
    Yukhymchuk, Yulia
    Wang, Yuke
    Liptuga, Anatoliy
    Kyslyi, Volodymyr
    Turos, Olena
    Serozhkin, Yuriy
    ATMOSPHERE, 2020, 11 (07)
  • [27] Global and regional carbon budget for 2015-2020 inferred from OCO-2 based on an ensemble Kalman filter coupled with GEOS-Chem
    Kong, Yawen
    Zheng, Bo
    Zhang, Qiang
    He, Kebin
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2022, 22 (16) : 10769 - 10788
  • [28] Invert global and China's terrestrial carbon fluxes over 2019-2021 based on assimilating richer atmospheric CO 2 observations
    Li, Jiaying
    Zhang, Xiaoye
    Guo, Lifeng
    Zhong, Junting
    Wang, Deying
    Wu, Chongyuan
    Li, Fugang
    Li, Ming
    SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 929
  • [29] Development and evaluation of the unified tropospheric-stratospheric chemistry extension (UCX) for the global chemistry-transport model GEOS-Chem
    Eastham, Sebastian D.
    Weisenstein, Debra K.
    Barrett, Steven R. H.
    ATMOSPHERIC ENVIRONMENT, 2014, 89 : 52 - 63
  • [30] Global Temperature Dependency of Biogenic HCHO Columns Observed From Space: Interpretation of TROPOMI Results Using GEOS-Chem Model
    Li, Xicheng
    Zhu, Lei
    De Smedt, Isabelle
    Sun, Wenfu
    Chen, Yuyang
    Shu, Lei
    Wang, Dakang
    Liu, Song
    Pu, Dongchuan
    Li, Juan
    Zuo, Xiaoxing
    Fu, Weitao
    Li, Yali
    Zhang, Peng
    Yan, Zhuoxian
    Fu, Tzung-May
    Shen, Huizhong
    Wang, Chen
    Ye, Jianhuai
    Yang, Xin
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2024, 129 (21)