Abstract
Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based fCO2 products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2022, EFOS increased by 0.9 % relative to 2021, with fossil emissions at 9.9 ± 0.5 Gt C yr−1 (10.2 ± 0.5 Gt C yr−1 when the cement carbonation sink is not included), and ELUC was 1.2 ± 0.7 Gt C yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.8 Gt C yr−1 (40.7±3.2 Gt CO2 yr−1). Also, for 2022, GATM was 4.6±0.2 Gt C yr−1 (2.18±0.1 ppm yr−1; ppm denotes parts per million), SOCEAN was 2.8±0.4 Gt C yr−1, and SLAND was 3.8±0.8 Gt C yr−1, with a BIM of −0.1 Gt C yr−1 (i.e. total estimated sources marginally too low or sinks marginally too high). The global atmospheric CO2 concentration averaged over 2022 reached 417.1 ± 0.1 ppm. Preliminary data for 2023 suggest an increase in EFOS relative to 2022 of +1.1 % (0.0 % to 2.1 %) globally and atmospheric CO2 concentration reaching 419.3 ppm, 51 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2022, with a near-zero overall budget imbalance, although discrepancies of up to around 1 Gt C yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living-data update documents changes in methods and data sets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2023 (Friedlingstein et al., 2023).
Original language | English (US) |
---|---|
Pages (from-to) | 5301-5369 |
Number of pages | 69 |
Journal | Earth System Science Data |
Volume | 15 |
Issue number | 12 |
DOIs | |
State | Published - 2023 |
ASJC Scopus subject areas
- General Earth and Planetary Sciences
Online availability
- 10.5194/essd-15-5301-2023License: CC BY
Library availability
Discover UIUC Full TextRelated links
Fingerprint
Dive into the research topics of 'Global Carbon Budget 2023'. Together they form a unique fingerprint.Cite this
- APA
- Standard
- Harvard
- Vancouver
- Author
- BIBTEX
- RIS
In: Earth System Science Data, Vol. 15, No. 12, 2023, p. 5301-5369.
Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Global Carbon Budget 2023
AU - Friedlingstein, Pierre
AU - O’Sullivan, Michael
AU - Jones, Matthew W.
AU - Andrew, Robbie M.
AU - Bakker, Dorothee C.E.
AU - Hauck, Judith
AU - Landschützer, Peter
AU - Le Quéré, Corinne
AU - Luijkx, Ingrid T.
AU - Peters, Glen P.
AU - Peters, Wouter
AU - Pongratz, Julia
AU - Schwingshackl, Clemens
AU - Sitch, Stephen
AU - Canadell, Josep G.
AU - Ciais, Philippe
AU - Jackson, Robert B.
AU - Alin, Simone R.
AU - Anthoni, Peter
AU - Barbero, Leticia
AU - Bates, Nicholas R.
AU - Becker, Meike
AU - Bellouin, Nicolas
AU - Decharme, Bertrand
AU - Bopp, Laurent
AU - Brasika, Ida Bagus Mandhara
AU - Cadule, Patricia
AU - Chamberlain, Matthew A.
AU - Chandra, Naveen
AU - Chau, Thi Tuyet Trang
AU - Chevallier, Frédéric
AU - Chini, Louise P.
AU - Cronin, Margot
AU - Dou, Xinyu
AU - Enyo, Kazutaka
AU - Evans, Wiley
AU - Falk, Stefanie
AU - Feely, Richard A.
AU - Feng, Liang
AU - Ford, Daniel J.
AU - Gasser, Thomas
AU - Ghattas, Josefine
AU - Gkritzalis, Thanos
AU - Grassi, Giacomo
AU - Gregor, Luke
AU - Gruber, Nicolas
AU - Gürses, Özgür
AU - Harris, Ian
AU - Hefner, Matthew
AU - Heinke, Jens
AU - Houghton, Richard A.
AU - Hurtt, George C.
AU - Iida, Yosuke
AU - Ilyina, Tatiana
AU - Jacobson, Andrew R.
AU - Jain, Atul
AU - Jarníková, Tereza
AU - Jersild, Annika
AU - Jiang, Fei
AU - Jin, Zhe
AU - Joos, Fortunat
AU - Kato, Etsushi
AU - Keeling, Ralph F.
AU - Kennedy, Daniel
AU - Goldewijk, Kees Klein
AU - Knauer, Jürgen
AU - Korsbakken, Jan Ivar
AU - Körtzinger, Arne
AU - Lan, Xin
AU - Lefèvre, Nathalie
AU - Li, Hongmei
AU - Liu, Junjie
AU - Liu, Zhiqiang
AU - Ma, Lei
AU - Marland, Greg
AU - Mayot, Nicolas
AU - McGuire, Patrick C.
AU - McKinley, Galen A.
AU - Meyer, Gesa
AU - Morgan, Eric J.
AU - Munro, David R.
AU - Nakaoka, Shin Ichiro
AU - Niwa, Yosuke
AU - O’Brien, Kevin M.
AU - Olsen, Are
AU - Omar, Abdirahman M.
AU - Ono, Tsuneo
AU - Paulsen, Melf
AU - Pierrot, Denis
AU - Pocock, Katie
AU - Poulter, Benjamin
AU - Powis, Carter M.
AU - Rehder, Gregor
AU - Resplandy, Laure
AU - Robertson, Eddy
AU - Rödenbeck, Christian
AU - Rosan, Thais M.
AU - Schwinger, Jörg
AU - Séférian, Roland
AU - Smallman, T. Luke
AU - Smith, Stephen M.
AU - Sospedra-Alfonso, Reinel
AU - Sun, Qing
AU - Sutton, Adrienne J.
AU - Sweeney, Colm
AU - Takao, Shintaro
AU - Tans, Pieter P.
AU - Tian, Hanqin
AU - Tilbrook, Bronte
AU - Tsujino, Hiroyuki
AU - Tubiello, Francesco
AU - van der Werf, Guido R.
AU - van Ooijen, Erik
AU - Wanninkhof, Rik
AU - Watanabe, Michio
AU - Wimart-Rousseau, Cathy
AU - Yang, Dongxu
AU - Yang, Xiaojuan
AU - Yuan, Wenping
AU - Yue, Xu
AU - Zaehle, Sönke
AU - Zeng, Jiye
AU - Zheng, Bo
N1 - We thank all people and institutions who provided the data used in this Global Carbon Budget 2023 and the Global Carbon Project members for their input throughout the development of this publication. We thank Nigel Hawtin for producing Figs. 2 and 15. We thank Alex Vermeulen and Hanna Ritchie for hosting the global carbon budget data sets on the ICOS portal and the Our World in Data website, respectively. We thank Ian G. C. Ashton, Sebastian Brune, Fatemeh Cheginig, Sam Ditkovsky, Christian Eth\u00E9, Amanda R. Fay, Lonneke Goddijn-Murphy, T. Holding, Yawen Kong, Fabrice Lacroix, Yi Liu, Damian Loher, Naiqing Pan, Paridhi Rustogi, Shijie Shu, Jamie Shutler, Richard Sims, Phillip Townsend, Jing Wang, Andrew J. Watson, and David K. Woolf for their involvement in the development, use, and analysis of the models and data products used here. We thank Toste Tanhua, Marcos Fontela, Claire Lo Monaco, and Nicolas Metzl, who contributed to the provision of surface ocean CO2 observations for the year 2022 (see Table S6). We also thank Stephen D. Jones of the Ocean Thematic Centre of the EU Integrated Carbon Observation System (ICOS) Research Infrastructure, Eugene Burger of NOAA\u2019s Pacific Marine Environmental Laboratory, and Alex Kozyr of NOAA\u2019s National Centers for Environmental Information for their contribution to surface ocean CO2 data and metadata management. This is PMEL contribution 5550. We thank the scientists, institutions, and funding agencies responsible for the collection and quality control of the data in SOCAT as well as the International Ocean Carbon Coordination Project (IOCCP), the Surface Ocean\u2013Lower Atmosphere Study (SOLAS), and the Integrated Marine Biosphere Research (IMBeR) programme for their support. We thank Nadine Goris and Lavinia Patara for support in calculating observational ocean evaluation metrics. We thank Fortunat Joos, Samar Khatiwala, and Timothy DeVries for providing historical atmospheric and ocean data. We thank data providers ObsPack GLOBALVIEWplus v8.0 and NRT v8.1 for atmospheric CO2 observations. Ingrid T. Luijkx and Wouter Peters thank the CarbonTracker Europe team at Wageningen University, including Remco de Kok, Joram Hooghiem, Linda Kooijmans, and Auke van der Woude. Daniel Kennedy thanks all the scientists, software engineers, and administrators who contributed to the development of CESM2. Josefine Ghattas thanks the whole ORCHIDEE group. Ian Harris thanks the Japan Meteorological Agency (JMA) for producing the Japanese 55-year Reanalysis (JRA-55). Reinel Sospedra-Alfonso thanks Barbara Winter, Woosung Lee, and William J. Merryfield for their contribution to the preparation and production of CanESM5 runs. Patricia Cadule thanks Olivier Torres, Juliette Mignot, Didier Swingedouw, and Laurent Bopp for contributions to the IPSLCM6A-CO2-LR simulations. Yosuke Niwa thanks CSIRO, EC, Empa, FMI, IPEN, JMA, LSCE, NCAR, NIES, NILU, NIWA, NOAA, SIO, and TU/NIPR for providing data for NISMON-CO2. Zhe Jin thanks Xiangjun Tian, Yilong Wang, Hongqin Zhang, Min Zhao, Tao Wang, Jinzhi Ding and Shilong Piao for their contributions to the GONGGA inversion system. Bo Zheng thanks Yawen Kong for running the THU inversion system. Fr\u00E9d\u00E9ric Chevallier thanks Zo\u00E9 Lloret, who maintained the atmospheric transport model for the CAMS inversions. Fr\u00E9d\u00E9ric Chevallier and Thi-Tuyet-Trang Chau thank Marion Gehlen for her contribution to the CMEMS-LSCE-FFNNv2 product. Lian Fang thanks Paul I. Palmer and acknowledges ongoing support from the National Centre for Earth Observation. Junjie Liu thanks the Jet Propulsion Laboratory, California Institute of Technology. Zhiqiang Liu thanks Ning Zeng, Yun Liu, Eugenia Kalnay, and Gassem Asrar for their contributions to the COLA system. Fei Jiang acknowledges ongoing support from the Frontiers Science Center for Critical Earth Material Cycling, Nanjing University. Andy Jacobson thanks the team at NOAA GML, Boulder, Colorado, USA, who provided the CarbonTracker CT2022 and CT-NRT.v2023-3 results from the website at http: //carbontracker.noaa.gov (last access: 9 November 2023). Meike Becker and Are Olsen thank Sparebanken Vest/Agenda Vestlandet for their support for the observations on the Statsraad Lehmkuhl. Margot Cronin thanks Anthony English, Clynt Gregory, and Gordon Furey (P&O Maritime Services) and Tobias Steinhoff and Aodhan Fitzgerald (Marine Institute) for their support. Wiley Evans and Katie Pocock thank the Tula Foundation for funding support. Thanos Gkritzalis and the VLIZ ICOS team are thankful to the crew of the research vessel Simon Stevin for all the support and help they provide. Data providers Nicolas Metzl and Claire LoMonaco thank the French Institut National des Sciences de l\u2019Univers (INSU), Institut Polaire fran\u00E7ais Paul-\u00C9mile Victor (IPEV), Observatoire des sciences de l\u2019univers Ecce Terra (OSU at Sorbonne Universit\u00E9), Institut Fran\u00E7ais de Recherche pour l\u2019Exploitation de la Mer (IFREMER), and French Oceanographic Fleet (FOF) for the Marion Dufresne data set (https://doi.org/10.17600/18001858, Lo Monaco and Metzl, 2022). Bronte Tilbrook and Erik van Ooijen thank Australia\u2019s Integrated Marine Observing System (IMOS) for sourcing of CO2 data. IMOS is enabled by the National Collaborative Research Infrastructure Strategy (NCRIS). FAOSTAT is funded by FAO member states through their contributions to the FAO Regular Programme; data contributions by national experts are greatly acknowledged. The views expressed in this paper are the authors\u2019 only and do not necessarily reflect those of FAO. Finally, we thank all funders who have supported the individual and joint contributions to this work (see details below), as well as the two anonymous reviewers of this paper and the many researchers who have provided feedback. This research was supported by the following sources of funding: the Integrated Marine Observing System (IMOS) (Australia); ICOS Flanders (Belgium); the Research Foundation \u2013 Flanders (grant no. I001821N) (Belgium); the Tula Foundation (Canada); the Chinese Academy of Science Project for Young Scientists in Basic Research (grant no. YSBR-037) (China); the National Key R&D Program of China (grant no. 2020YFA0607504); the National Natural Science Foundation (grant nos. 42141020, 42275128, 42275128, 41921005) (China); Scientific Research Start-up Funds (grant no. QD2021024C) from Tsinghua Shenzhen International Graduate School (China); the Second Tibetan Plateau Scientific Expedition and Research Program (grant no. 2022QZKK0101) (China); the Young Elite Scientists Sponsorship Program by CAST (grant no. YESS20200135) (China); Fundamental Research Funds for the Central Universities (grant no. 090414380031) (China); the Copernicus Atmosphere Monitoring Service, implemented by ECMWF (grant no. CAMS2 55) (European Commission, EC); Copernicus Marine Environment Monitoring Service, implemented by MOi (grant no. CAMS2 55) (EC); H2020 (Horizon 2020) 4C (grant no. 821003) (EC); H2020 ESM2025 \u2013 Earth System Models for the Future (grant no. 101003536) (EC); H2020 EuroSea (grant no. 862626) (EC); H2020 GEORGE (grant no. 101094716) (EC); H2020 JERICOS3 (grant no. 871153) (EC); ICOS France (France); the Institut de Recherche pour le D\u00E9veloppement (IRD) (France); the Federal Ministry of Education and Research (BMBF) (grant no. 03F0885AL1) (Germany); the Federal Ministry of Education and Research, collaborative project C-SCOPE (Towards Marine Carbon Observations 2.0: Socializing, COnnecting, Perfecting and Expanding, project no. 03F0877A) (Germany); the Helmholtz Association ATMO programme (Germany); the Helmholtz Association of German Research Centres (project MOSES; Modular Observation Solutions for Earth Systems) (Germany); ICOS (Integrated Carbon Observation System) Germany (Germany); the Ludwig Maximilians University of Munich, Department of Geography (Germany); the Marine Institute (Ireland); the Arctic Challenge for Sustainability phase II project (ArCS II; grant no. JP-MXD1420318865) (Japan); the Environment Research and Technology Development Fund (grant no. JP-MEERF21S20800) (Japan); the Global Environmental Research Coordination System, Ministry of the Environment (grant no. E2252) (Japan); the Japan Meteorological Agency (Japan); the Ministry of Education, Culture, Sports, Science and Technology, MEXT Program for the Advanced Studies of Climate Change Projection (SENTAN) (grant nos. JPMXD0722680395, JPMXD0722681344) (Japan); the Ministry of Environment, Environmental Restoration and Conservation Agency, Environment Research and Technology Development Fund (grant no. JPMEERF21S20810) (Japan); the National Institute for Environmental Studies (Japan); the Research Council of Norway (N-ICOS-2; grant no. 296012) (Norway); the Swiss National Science Foundation (grant no. 200020-200511) (Switzerland); the National Centre for Atmospheric Science (UK); NERC (Natural Environment Research Council) Independent Research Fellowship (NE/V01417X/1) (UK); NERC (NE/R016518/1) (UK); the Royal Society (grant no. RP\\R1\\191063) (UK); UK Research and Innovation (UKRI) for Horizon Europe (GreenFeedBack; grant no. 10040851) (UK); the NASA Carbon Monitoring System programme (80NSSC21K1059) (USA); the NASA OCO Science Team programme (grant no. 80NM0018F0583) (USA); a National Center for Atmospheric Research (NCAR) cooperative agreement (NSF no. 1852977) (USA); a National Oceanic and Atmospheric Administration (NOAA) cooperative agreement (grant no. NA22OAR4320151) (USA); the National Science Foundation (grant nos. NSF-831361857, OPP-1922922) (USA); NOAA (grant no. NA20OAR4320278) (USA); a NOAA cooperative agreement, the Cooperative Institute for Climate, Ocean, & Ecosystem Studies (CIOCES; grant no. NA20OAR4320271) (USA); a NOAA cooperative agreement, the Cooperative Institute for Marine and Atmospheric Studies (CIMAS), University of Miami (grant no. NA20OAR4320472) (USA); the NOAA Global Ocean Monitoring and Observing Program (grant nos. 100018302, 100007298, NA-03-AR4320179) (USA); and the NOAA Ocean Acidification Program (USA). We also acknowledge support from the following computing facilities: the Adapter Allocation Scheme from the National Computational Infrastructure (NCI) (Australia); the High-Performance Computing Center (HPCC) of Nanjing University (China); GENCI-TGCC (grant nos. A0130102201, A0130106328, A0140107732, A0130107403) (France); CCRT awarded by CEA DRF (grant no. CCRT2023-p24cheva) (France); the HPC cluster Aether at the University of Bremen, financed by DFG within the scope of the Excellence Initiative (Germany); the state of Baden-W\u00FCrttemberg, through bwHPC (Germany); Earth Simulator (ES4) at JAMSTEC (Japan); JAMSTEC\u2019s supercomputer system (Japan); the NIES supercomputer system (Japan); NIES (SX-Aurora) and MRI (Fujitsu server PRIMERGY CX2550M5) (Japan); the ADA HPC cluster at the University of East Anglia (UK); the UK CEDA JASMIN supercomputer (UK); and Cheyenne NCAR HPC resources managed by CISL (https://doi.org/10.5065/D6RX99HX, Hart, 2021) (USA). Financial support. This research was supported by the following sources of funding: the Integrated Marine Observing System (IMOS) (Australia); ICOS Flanders (Belgium); the Research Foundation \u2013 Flanders (grant no. I001821N) (Belgium); the Tula Foundation (Canada); the Chinese Academy of Science Project for Young Scientists in Basic Research (grant no. YSBR-037) (China); the National Key R&D Program of China (grant no. 2020YFA0607504); the National Natural Science Foundation (grant nos. 42141020, 42275128, 42275128, 41921005) (China); Scientific Research Start-up Funds (grant no. QD2021024C) from Tsinghua Shenzhen International Graduate School (China); the Second Tibetan Plateau Scientific Expedition and Research Program (grant no. 2022QZKK0101) (China); the Young Elite Scientists Sponsorship Program by CAST (grant no. YESS20200135) (China); Fundamental Research Funds for the Central Universities (grant no. 090414380031) (China); the Copernicus Atmosphere Monitoring Service, implemented by ECMWF (grant no. CAMS2 55) (European Commission, EC); Copernicus Marine Environment Monitoring Service, implemented by MOi (grant no. CAMS2 55) (EC); H2020 (Horizon 2020) 4C (grant no. 821003) (EC); H2020 ESM2025 \u2013 Earth System Models for the Future (grant no. 101003536) (EC); H2020 EuroSea (grant no. 862626) (EC); H2020 GEORGE (grant no. 101094716) (EC); H2020 JERICO-S3 (grant no. 871153) (EC); ICOS France (France); the Insti-tut de Recherche pour le D\u00E9veloppement (IRD) (France); the Federal Ministry of Education and Research (BMBF) (grant no. 03F0885AL1) (Germany); the Federal Ministry of Education and Research, collaborative project C-SCOPE (Towards Marine Carbon Observations 2.0: Socializing, COnnecting, Perfecting and Expanding, project no. 03F0877A) (Germany); the Helmholtz Association ATMO programme (Germany); the Helmholtz Association of German Research Centres (project MOSES; Modular Observation Solutions for Earth Systems) (Germany); ICOS (Integrated Carbon Observation System) Germany (Germany); the Ludwig Maximilians University of Munich, Department of Geography (Germany); the Marine Institute (Ireland); the Arctic Challenge for Sustainability phase II project (ArCS II; grant no. JP-MXD1420318865) (Japan); the Environment Research and Technology Development Fund (grant no. JP-MEERF21S20800) (Japan); the Global Environmental Research Coordination System, Ministry of the Environment (grant no. E2252) (Japan); the Japan Meteorological Agency (Japan); the Ministry of Education, Culture, Sports, Science and Technology, MEXT Program for the Advanced Studies of Climate Change Projection (SENTAN) (grant nos. JPMXD0722680395, JPMXD0722681344) (Japan); the Ministry of Environment, Environmental Restoration and Conservation Agency, Environment Research and Technology Development Fund (grant no. JPMEERF21S20810) (Japan); the National Institute for Environmental Studies (Japan); the Research Council of Norway (N-ICOS-2; grant no. 296012) (Norway); the Swiss National Science Foundation (grant no. 200020-200511) (Switzerland); the National Centre for Atmospheric Science (UK); NERC (Natural Environment Research Council) Independent Research Fellowship (NE/V01417X/1) (UK); NERC (NE/R016518/1) (UK); the Royal Society (grant no. RP\\R1\\191063) (UK); UK Research and Innovation (UKRI) for Horizon Europe (GreenFeed-Back; grant no. 10040851) (UK); the NASA Carbon Monitoring System programme (80NSSC21K1059) (USA); the NASA OCO Science Team programme (grant no. 80NM0018F0583) (USA); a National Center for Atmospheric Research (NCAR) cooperative agreement (NSF no. 1852977) (USA); a National Oceanic and Atmospheric Administration (NOAA) cooperative agreement (grant no. NA22OAR4320151) (USA); the National Science Foundation (grant nos. NSF-831361857, OPP-1922922) (USA); NOAA (grant no. NA20OAR4320278) (USA); a NOAA cooperative agreement, the Cooperative Institute for Climate, Ocean, & Ecosystem Studies (CIOCES; grant no. NA20OAR4320271) (USA); a NOAA cooperative agreement, the Cooperative Institute for Marine and Atmospheric Studies (CIMAS), University of Miami (grant no. NA20OAR4320472) (USA); the NOAA Global Ocean Monitoring and Observing Program (grant nos. 100018302, 100007298, NA-03-AR4320179) (USA); and the NOAA Ocean Acidification Program (USA). We also acknowledge support from the following computing facilities: the Adapter Allocation Scheme from the National Computational Infrastructure (NCI) (Australia); the High-Performance Computing Center (HPCC) of Nanjing University (China); GENCI-TGCC (grant nos. A0130102201, A0130106328, A0140107732, A0130107403) (France); CCRT awarded by CEA DRF (grant no. CCRT2023-p24cheva) (France); the HPC cluster Aether at the University of Bremen, financed by DFG within the scope of the Excellence Initiative (Germany); the state of Baden-W\u00FCrttemberg, through bwHPC (Germany); Earth Simulator (ES4) at JAMSTEC (Japan); JAMSTEC\u2019s supercomputer system (Japan); the NIES supercomputer system (Japan); NIES (SX-Aurora) and MRI (Fujitsu server PRIMERGY CX2550M5) (Japan); the ADA HPC cluster at the University of East Anglia (UK); the UK CEDA JASMIN supercomputer (UK); and Cheyenne NCAR HPC resources managed by CISL (https://doi.org/10.5065/D6RX99HX, Hart, 2021) (USA).
PY - 2023
Y1 - 2023
N2 - Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based fCO2 products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2022, EFOS increased by 0.9 % relative to 2021, with fossil emissions at 9.9 ± 0.5 Gt C yr−1 (10.2 ± 0.5 Gt C yr−1 when the cement carbonation sink is not included), and ELUC was 1.2 ± 0.7 Gt C yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.8 Gt C yr−1 (40.7±3.2 Gt CO2 yr−1). Also, for 2022, GATM was 4.6±0.2 Gt C yr−1 (2.18±0.1 ppm yr−1; ppm denotes parts per million), SOCEAN was 2.8±0.4 Gt C yr−1, and SLAND was 3.8±0.8 Gt C yr−1, with a BIM of −0.1 Gt C yr−1 (i.e. total estimated sources marginally too low or sinks marginally too high). The global atmospheric CO2 concentration averaged over 2022 reached 417.1 ± 0.1 ppm. Preliminary data for 2023 suggest an increase in EFOS relative to 2022 of +1.1 % (0.0 % to 2.1 %) globally and atmospheric CO2 concentration reaching 419.3 ppm, 51 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2022, with a near-zero overall budget imbalance, although discrepancies of up to around 1 Gt C yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living-data update documents changes in methods and data sets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2023 (Friedlingstein et al., 2023).
AB - Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based fCO2 products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, and Earth system models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2022, EFOS increased by 0.9 % relative to 2021, with fossil emissions at 9.9 ± 0.5 Gt C yr−1 (10.2 ± 0.5 Gt C yr−1 when the cement carbonation sink is not included), and ELUC was 1.2 ± 0.7 Gt C yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 11.1 ± 0.8 Gt C yr−1 (40.7±3.2 Gt CO2 yr−1). Also, for 2022, GATM was 4.6±0.2 Gt C yr−1 (2.18±0.1 ppm yr−1; ppm denotes parts per million), SOCEAN was 2.8±0.4 Gt C yr−1, and SLAND was 3.8±0.8 Gt C yr−1, with a BIM of −0.1 Gt C yr−1 (i.e. total estimated sources marginally too low or sinks marginally too high). The global atmospheric CO2 concentration averaged over 2022 reached 417.1 ± 0.1 ppm. Preliminary data for 2023 suggest an increase in EFOS relative to 2022 of +1.1 % (0.0 % to 2.1 %) globally and atmospheric CO2 concentration reaching 419.3 ppm, 51 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean of and trend in the components of the global carbon budget are consistently estimated over the period 1959–2022, with a near-zero overall budget imbalance, although discrepancies of up to around 1 Gt C yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows the following: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living-data update documents changes in methods and data sets applied to this most recent global carbon budget as well as evolving community understanding of the global carbon cycle. The data presented in this work are available at https://doi.org/10.18160/GCP-2023 (Friedlingstein et al., 2023).
UR - http://www.scopus.com/inward/record.url?scp=85181687307&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85181687307&partnerID=8YFLogxK
U2 - 10.5194/essd-15-5301-2023
DO - 10.5194/essd-15-5301-2023
M3 - Article
AN - SCOPUS:85181687307
SN - 1866-3508
VL - 15
SP - 5301
EP - 5369
JO - Earth System Science Data
JF - Earth System Science Data
IS - 12
ER -