Published: December 5, 2023

Citation: Friedlingstein et al., Global Carbon Budget 2023. https://doi.org/10.5194/essd-15-5301-2023

Data: Global Carbon Project. (2023). Supplemental data of Global Carbon Budget 2023 (Version 1.1) [Data set]. Global Carbon Project. https://doi.org/10.18160/gcp-2023

Changelog:

• 2022 total anthropogenic CO₂ emissions (including the cement carbonation sink): 11.1±0.8 GtC/year (40.7±3.2 GtCO₂/year).
• 2022 fossil CO₂ emissions increased by 0.9% to 10.2±0.5 GtC/year (9.9 ± 0.5 GtC/year when the cement carbonation sink is included)
• 2022 global atmospheric CO₂ concentration: 417.1 ± 0.1 ppm
• remaining carbon budget for a 50% likelihood to limit global warming to 1.5, 1.7, and 2°C has reduced to 75 GtC (275 GtCO₂), 175 GtC (625 GtCO₂), and 315 GtC (1150 GtCO₂)

Global Carbon Budget 2023

ICOS Archive

• Summary
• Global Carbon Budget
• Historical Budget
• Fossil Emissions by Category
• Land-Use Change Emissions
• Ocean Sink
• Terrestrial Sink
• Cement Carbonation Sink

Terrestrial CO₂ sink (positive values represent a flux from the atmosphere to the land)

Cite individual estimates as:

• CABLE-POP Haverd, V., Smith, B., Nieradzik, L., Briggs, P. R., Woodgate, W., Trudinger, C. M., Canadell, J. G., and Cuntz, M.: A new version of the CABLE land surface model (Subversion revision r4601) incorporating land use and land cover change, woody vegetation demography, and a novel optimisation-based approach to plant coordination of photosynthesis, Geosci. Model Dev., 11, 2995-3026, 2018.
• CLASSIC Melton, J. R., Arora, V. K., Wisernig-cojoc, E., Seiler, C., Fortier, M. and Chan, E.: CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme ( CLASS ) and the Canadian Terrestrial Ecosystem Model ( CTEM ) – Part 1: Model framework and site-level performance, , 2825–2850, 2020.
• CLM5.0 Lawrence, D., Fisher, R., Koven, C., Oleson, K., Swenson, S., et al.: The Community Land Model version 5: Description of new features, benchmarking, and impact of forcing uncertainty, JAMES, accepted, 2019
• DLEM Tian, H., G. Chen, C. Lu, X. Xu, D. J. Hayes, W. Ren, S. Pan, D.N. Huntzinger, S.C. Wofsy: North American terrestrial CO₂ uptake largely offset by CH4 and N2O emissions: Toward a full accounting of the greenhouse gas budget, Climatic Change, 129:423-426, 2015
• ED Ma, L., Hurtt, G., Ott, L., Sahajpal, R., Fisk, J., Lamb, R., Tang, H., Flanagan, S., Chini, L., Chatterjee, A., and Sullivan, J.: Global evaluation of the Ecosystem Demography model (ED v3.0), Geosci. Model Dev., 15, 1971–1994, https://doi.org/10.5194/gmd-15-1971-2022, 2022.
• ELM Yang, X., Thornton, P., Ricciuto, D., Wang, Y., and Hoffman, F.: Global evaluation of terrestrial biogeochemistry in the Energy Exascale Earth System Model (E3SM) and the role of the phosphorus cycle in the historical terrestrial carbon balance, Biogeosciences, 20, 2813–2836, https://doi.org/10.5194/bg-20-2813-2023, 2023.
• IBIS Yuan WP, Liu D, Dong WJ, Liu SG, Zhou GS, Yu GR, Zhao TB, Feng JM, Ma ZG, Chen JQ, Chen Y, Chen SP, Han SJ, Huang JP, Li LH, Liu HZ, Liu SM, Ma MG, Wang YF, Xia JZ, Xu WF, Zhang Q, Zhao XQ, Zhao L. 2014. Multiyear precipitation reduction strongly decreases carbon uptake over northern China. Journal of Geophysical Research: Biogeosciences, 119, 881-896.
• ISAM Shu, S., Jain, A. K., Koven, C. D., and Mishra, U.: Estimation of Permafrost SOC Stock and Turnover Time Using a Land Surface Model With Vertical Heterogeneity of Permafrost Soils, Global Biogeochem. Cy., 34, e2020GB006585, https://doi.org/10.1029/2020GB006585, 2020.
• ISBA-CTRIP Delire, C., Séférian, R., Decharme, B., Alkama, R., Calvet, J.-C., Carrer, D., Gibelin, A.-L., Joetzjer, E., Morel, X., Rocher, M., and Tzanos, D.: The Global Land Carbon Cycle Simulated With ISBA-CTRIP: Improvements Over the Last Decade, J. Adv. Model. Earth Syst., 12, e2019MS001886, https://doi.org/10.1029/2019MS001886, 2020.
• JSBACH Reick, C. H., Gayler, V., Goll, D., Hagemann, S., Heidkamp, M., Nabel, J. E. M. S., Raddatz, T., Roeckner, E., Schnur, R., and Wilkenskjeld, S.: JSBACH 3 - The land component of the MPI Earth System Model: documentation of version 3.2, https://doi.org/10.17617/2.3279802, 2021.
• JULES-ES Wiltshire, A.,Burke, E., Chadburn, S., Jones, C., Cox, P., Davies-Barnard, T., Friedlingstein, P., Harper, A., Liddicoat, S., Sitch, S., Zaehle, S
• LPJ-GUESS Smith, B., Warlind, D., Arneth, A., Hickler, T., Leadley, P., Siltberg, J., and Zaehle, S.: Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model, Biogeosciences, 11, 2027-2054, 2014.
• LPJwsl Poulter, B., Frank, D. C., Hodson, E. L., and Zimmermann, N. E.: Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO₂ airborne fraction, Biogeosciences, 8, 2027-2036, 2011.
• LPJml Schaphoff, S., von Bloh, W., Rammig, A., Thonicke, K., Biemans, H., Forkel, M., Gerten, D., Heinke, J., Jägermeyr, J., Knauer, J., Langerwisch, F., Lucht, W., Müller, C., Rolinski, S., and Waha, K.: LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description, Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018, 2018.
• LPX-Bern Lienert, S. and Joos, F.: A Bayesian ensemble data assimilation to constrain model parameters and land-use carbon emissions, Biogeosciences, 15, 2909-2930, 2018.
• OCNv2 Zaehle, S. and Friend, A. D.: Carbon and nitrogen cycle dynamics in the O-CN land surface model: 1. Model description, site-scale evaluation, and sensitivity to parameter estimates, Global Biogeochemical Cycles, 24, GB1005, 2010
• ORCHIDEEv3 Vuichard, N., Messina, P., Luyssaert, S., Guenet, B., Zaehle, S., Ghattas, J., Ipsl, L. and Paris-saclay, U.: Accounting for carbon and nitrogen interactions in the global terrestrial ecosystem model ORCHIDEE ( trunk version , rev 4999 ): multi-scale evaluation of gross primary production, , 4751–4779, 2019.
• SDGVM Walker, A. P., Quaife, T., van Bodegom, P. M., De Kauwe, M. G., Keenan, T. F., Joiner, J., Lomas, M. R., MacBean, N., Xu, C. G., Yang, X. J., and Woodward, F. I.: The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (V-cmax) on global gross primary production, New Phytologist, 215, 1370-1386, 2017.
• VISIT Kato, E., Kinoshita, T., Ito, A., Kawamiya, M. and Yamagata, Y.: Evaluation of spatially explicit emission scenario of land-use change and biomass burning using a process-based biogeochemical model, J. Land Use Sci., 8(1), 104–122, doi:10.1080/1747423x.2011.628705, 2013.
• YIBs Yue, X. and Unger, N.: The Yale Interactive terrestrial Biosphere model version 1.0: description , evaluation and implementation into NASA GISS, , 2399–2417, doi:10.5194/gmd-8-2399-2015, 2015.

GCB

Individual Models

Unit GtC/year