the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Global Carbon Budget 2025
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 synthesise datasets and methodologies 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. Emissions from land-use change (ELUC) are estimated by bookkeeping models based on land-use and land-use change data. Atmospheric CO2 concentration is measured at surface stations, and the global atmospheric CO2 growth rate (GATM) is computed from the annual changes in concentration. The global net uptake of CO2 by the ocean (SOCEAN, called the ocean sink) is estimated with global ocean biogeochemistry models and observation-based fCO2-products. The global net uptake of CO2 by the land (SLAND, called the land sink) is estimated with dynamic global vegetation models. Additional lines of evidence on land and ocean sinks are provided by atmospheric inversions, atmospheric oxygen measurements, ocean interior observation-based estimates, and Earth System Models. The sum of all sources and sinks results in the carbon budget imbalance (BIM), a measure of imperfect data and incomplete understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ.
For the year 2024, EFOS increased by 1.1 % relative to 2023, with fossil emissions at 10.3 ± 0.5 GtC yr−1 (including the cement carbonation sink, 0.2 GtC/yr), ELUC was 1.3 ± 0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.6 ± 0.9 GtC yr−1 (42.4 ± 3.2 GtCO2 yr−1). Also, for 2024, GATM was 7.9 ± 0.2 GtC yr−1 (3.73 ± 0.1 ppm yr−1), 2.2 GtC above the 2023 growth rate. SOCEAN was 3.4 ± 0.4 GtC yr−1 and SLAND was 1.9 ± 1.1 GtC yr−1, leaving a large negative BIM (−1.7 GtC yr−1), suggesting that the total sink or GATM is strongly overestimated in 2024. The global atmospheric CO2 concentration averaged over 2024 reached 422.8 ± 0.1 ppm. Preliminary data for 2025 suggest an increase in EFOS relative to 2024 of +1.1 % (0.2 % to 2.2 %) globally, and atmospheric CO2 concentration increasing by 2.3 ppm reaching 425.7 ppm, 52 % above the pre-industrial level (around 278 ppm in 1750). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2024, with a near-zero overall budget imbalance, although discrepancies of up to around 1 GtC yr−1 persist for the representation of annual to decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use change 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 mean ocean sink.
This living data update documents changes in methods and datasets 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-2025 (Friedlingstein et al., 2025c).
Competing interests: At least one of the authors is a member of the editorial board of Earth System Science Data.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
(6080 KB) - Metadata XML
-
Supplement
(21932 KB) - BibTeX
- EndNote
Status: open (until 01 Mar 2026)
- RC1: 'Comment on essd-2025-659', Anonymous Referee #1, 11 Jan 2026 reply
-
CC1: 'Comment on essd-2025-659', Fabio Berzaghi, 02 Feb 2026
reply
Dear Authors,
I have a comment of Fig 6d, which I already emailed to the lead authors. The caption states that "positive values of SOCEAN and SLAND represent a flux from the atmosphere to the ocean or the land (carbon sink)." The geographic patterns are similar to the Global Carbon Budget 2023. Line 1519 is mentioned "During 2015-2024 the land sink is positive in all regions (Figure 6d) with the exception of eastern Brazil, Bolivia, northern Venezuela, Southwest USA, central Europe and Central Asia, North and South Africa, and eastern Australia..." I think this makes sense as the right interpretation. However, in the 2023 Budget, the red areas (negative values) were interpreted as C sinks "Uptake due to land-use change occurs, particularly in Europe, partly related to expanding forest area as a consequence of the forest transition in the 19th and 20th centuries and subsequent regrowth of forest". This makes me wonder which interpretation of the results is the correct one. In fact, I would expect that reforestation in Europe has lead to net sink. But in 2025 this was interpreted as a result of the negative effect of climate change.
Does this mean that the 2023 description of results from this figure was completely wrong and opposite of what the color scale was showing? Or is the 2025 paper the correct interpretation of the results?
A small notes on units, I have noticed that the units have been changed from KgC to gC. I understand that for certain figures it might be better to change units for better visualization, but I am not sure why Kg (or tonnes) which are a SI base unit are not more commonly used in the geosciences. Sometimes grams are used to express very large quantities.
Many thanks for your fantastic and useful work.
Citation: https://doi.org/10.5194/essd-2025-659-CC1 -
CC2: 'Reply on CC1', Clemens Schwingshackl, 04 Feb 2026
reply
Dear Fabio,
Thank you for your comment on Figure 6. I’ll try to sort out the misunderstanding.
The figure shows maps for land-use emissions (ELUC; in panel b) and for the natural land sink (SLAND; in panel d).
The sentence “During 2015-2024 the land sink is positive in all regions (Figure 6d) with the exception of eastern Brazil, Bolivia, northern Venezuela, Southwest USA, central Europe and Central Asia, North and South Africa, and eastern Australia...” refers to SLAND, that is Fig. 6d.
Instead, the sentence “Uptake due to land-use change occurs, particularly in Europe, partly related to expanding forest area as a consequence of the forest transition in the 19th and 20th centuries and subsequent regrowth of forest” (from GCB2023) refers to ELUC, that is Fig.6b. (In GCB2025, a revised version of this sentence reads as “Uptake due to land-use change occurs in several regions of the world (Figure 6b) particularly due to re/afforestation.”)
Both sentences are correct, as they refer to different components of the budget: SLAND and ELUC. For SLAND, you can also find a split of effects from increasing atmospheric CO2 concentrations and changes in climate in Figure 12, where the negative effects of climate change on SLAND become evident.
Note also that the colorbars are reversed for ELUC and SLAND: For ELUC, positive numbers denote emissions to the atmosphere, while for SLAND positive numbers denote removals from the atmosphere (in accordance with the budget Equation (1), page 11).
I hope this clarifies your question.
Citation: https://doi.org/10.5194/essd-2025-659-CC2 -
CC4: 'Reply on CC2', Fabio Berzaghi, 05 Feb 2026
reply
Citation: https://doi.org/
10.5194/essd-2025-659-CC4 -
CC5: 'Reply on CC4', Fabio Berzaghi, 05 Feb 2026
reply
BTW, I am not able to access Price & Warren 2016 Literature Review of the Potential of “Blue Carbon” Activities to Reduce Emissions, the link seems to be broken. Are you able to retrieve it?
Best,
Fabio
Citation: https://doi.org/10.5194/essd-2025-659-CC5
-
CC5: 'Reply on CC4', Fabio Berzaghi, 05 Feb 2026
reply
-
CC4: 'Reply on CC2', Fabio Berzaghi, 05 Feb 2026
reply
-
CC3: 'Reply on CC1', Mike O'Sullivan, 04 Feb 2026
reply
Hi Fabio,
Thanks for the query about units. I tried this year to improve the clarity of the colorbars across panels. In the 2023 version of Figure 6, there is a scaling factor for each panel which ensured no long decimals under the colorbar. For this year, I simplified things by removing this scaling factor, but then to ensure the values under the colorbar were not too long, I changed the unit from kgC to gC. As you say, both gC and kgC are commonly used in C cycle science.
Cheers,
Mike
Citation: https://doi.org/10.5194/essd-2025-659-CC3
-
CC2: 'Reply on CC1', Clemens Schwingshackl, 04 Feb 2026
reply
Data sets
Data Supporting the Global Carbon Budget 2025 P. Friedlingstein et al. https://doi.org/10.18160/GCP-2025
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 12,607 | 4,595 | 143 | 17,345 | 463 | 138 | 174 |
- HTML: 12,607
- PDF: 4,595
- XML: 143
- Total: 17,345
- Supplement: 463
- BibTeX: 138
- EndNote: 174
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
The global carbon budget provides an important contribution to both science and policy by updating annually information about emissions and sinks of CO2 and their trends. This year’s budget is no exception, with valuable insights including recent increasing trends in AGR in spite of a small increase in EFOS and that cannot be explained by the current models, and highlighting persisting uncertainty in SLand in the northern extra tropics. A notable new development is the inclusion of the RSS correction, which results in a weaker, but possibly more realistic, land sink. The report follows previous years’ structure and content, and is well written and well referenced. Nevertheless, I would like to point out a few aspects that can be improved or that need further clarification or discussion.
1) General comments
1.1) RSS correction
This is an important new addition to the budget, since the DGVM protocol used in previous budgets assumed no legacy emissions from land-use prior to 1850, implying a stronger land sink than what is plausible.
However, in many figures and tables, it is not clear whether the land component fluxes show include or not this correction, making it difficult for the reader to appreciate its impact in all relevant components of the budget.
1.2) Next-year projections
This budget, like previous ones, provides an estimate of the values of emissions and sinks for the next year, in this case 2025. These projections are based in very different methods, that rely on many assumptions and which are not consistent with each other (the ESM projections being the most self-consistent). Since next-year projections have been now given for several budgets, it would be important to discuss how much confidence can be attributed to these projections: how have previous projections performed? Are the respective uncertainty ranges provided here realistic?
2) Specific comments
Abstract
Lines 193-204: I understand the need to describe briefly the datasets used, but since the budget follows the same approach as previous years, I would recommend shortening this description, in order to rather highlight the new additions (for example the RSS correction) and provide more depth on the new insights from this year’s update (for example the very large value of BIM for 2024).
Lines 205-213: it would be helpful to report percent increase for all budget terms.
Lines 216-220: it would seem important to add here some insight about possible causes for the land BIM in 2024.
Introduction
Please state briefly in the introduction what the novel aspects of this year’s budget are (for example the RSS correction), compared to previous ones.
Lines 367-382: these sentences would probably fit better right in the beginning of the introduction, before stating the current budget’s approach.
Results
The use of sign to indicate an increase/decrease “by” is not always consistent but it is needed for clarity. For example, in Lines 996-1006 +3.6 is given for India, but – sign in “EU27 by” and “USA by” is missing. Many other instances can be found throughout the text across all sections, I note some lines here, but a careful editing is needed. Lines: 1011, 1014-1015, 1028, 1039, 1042, 1048, 1055, 1057-61, 1078, 1205 (35TgC “up”), 1228, 1246, 1262, 1302, 1417, 1422, 1432, 1444, 1950-51.
Fossil fuel
Lines 1026: please state briefly what information and assumptions the projections are based on.
Land use change
Lines 1068-1069: clarify which period is covered by vegetation biomass observations.
Lines 1096-1099: it is the first instance when fluxes, rather than emissions are mentioned. It would be helpful for non-expert readers to state the sign convention here.
Lines 1103-1114: this is relevant for decision making, but it overlooks the fact that these models do not represent processes that can reduce the land sink, especially disturbance fluxes, as noted by Roebroek et al. (2023) among others. Please state limitations and assumptions underlying the values given here.
Lines 1111: it is unclear if here you refer to a potential re/afforestation sink, or current CDR.
Lines 1151: clarify here you mean nature-based CDR, right?
Lines 1160: are RECCAP2 the estimates that are shown in Figure 15?
Lines 1194-1196: I find this confusing, since BM models do not include fire emissions due to natural drivers such as El Niño droughts. Shouldn’t this be rather part of the SLand discussion? And do DGVMs capture these emissions?
Atmospheric CO2
Lines 1271: is r for pearson correlation?
Lines 1295-1299: this is an important point. What would be the implications for 2023, then?
Lines 1301: briefly clarify what the “GCB regression method” is based on.
Lines 1303: give reference to “neutral ENSO year”.
Ocean sink
Lines 1365: remove . after Tropical Pacific
Lines 1382: is there a reason uncertainty ranges given using different notations (+- vs [ ] )? If so, clarify.
Lines 1415-1420: it would be more informative to have this point being discussed along with discrepancies between models and observation-based products. Here makes comparison more difficult.
Lines 1443: briefly explain what predictors are used by the FFNN.
Lines 1489-1491: since there seems to be a linear relationship between the two, would it make sense to apply a correction to fCO2? I do not have a strong opinion, but I am curious if the authors have considered this.
Land sink
Lines 1497-98: does the RSS correction affect only the mean values (bias), or are there carry-over effects that could result in different IAV and trends? Please clarify that the RSS correction was only applied to the DGVM multimodel mean, not to the individual DGVM estimates (as far as I understand).
Lines 1505-1506: give value of the residual sink here too.
Lines 1560: is it unclear if the values given here include the RSS correction, please clarify.
Lines 1571-1573: how about fires?
Lines 1574-1586: do the models representing fires estimate a weaker sink?
Partitioning of the fluxes
Lines 1683-1687: it is worth mentioning that, however, the northern land flux does not seem to contribute much to the BIM in 2024.
Lines 1717-1721: are there implications for the BIM value in 2024 that can be drawn from this comparison?
Lines 1753-1795: this is a very informative addition. However, RECCAP2 provides estimates of regional budgets using additional datasets (possibly with higher confidence that global products). Therefore, it would be worth comparing the estimates here with the values provided by RECCAP2 for each region, or at least highlight those regions where results from RECCAP2 indicate large discrepancies between global datasets and refined regional products.
Closing the global carbon cycle
Lines 1873: th should be superscript
Lines 1876: with “historical” do you mean “pre-industrial”? Does this refer to the RSS correction?
Lines 1891-1893: is this only because of the RSS correction, or are there other reasons?
Lines 1894-1898: the discussion of the disagreements in AGR between the surface network and satellite-based GRESO should be linked here. What is the effect of these disagreements on BIM for 2024?
Lines 1910-1913: I understand a full attribution is out of scope in this already long report, but Bastos et al. (2021) showed that the BIM strongly correlated with differences between inversions and global models, so maybe something could be said about the BIM based on Figure 14? At first glance some of the peaks in BIM in Figure 4 seem to correspond to large differences between inversions and GCB estimates of the total and land fluxes shown in Figure 14, especially in the tropics.
Lines 2024-2032: for traceability, it would be useful to have a table reporting major corrections/updates to the data and their implications.
Lines 2057-2082: there are several satellite-based biomass products that now allow to derive at least some components of ELUC, for example Xu et al. (2021). Are these planned to be incorporated in future budgets, if not, what are the limitations?
Lines 2011-2116: provide values for the estimates by atmospheric inversions, oxygen-based estimates and Randerson et al. (2025) for comparison.
Figures and Tables
Figure 13: do the DGVM estimates shown here include the RSS correction? Please clarify or, ideally, include both the uncorrected and corrected estimates.
Figure 14: does the gray shade for DGVMs correspond to the land-flux with or without RSS correction?
Figure 15 has very poor quality, please increase resolution.
Data availability
I agree that making the data available will contribute to greater understanding and new scientific insights of how the carbon cycle works, as stated in Section 7. However, in that spirit, why are gridded data provided openly for atmospheric inversions only, and not for the other datasets underlying the budget, especially those used in the main figures? Providing all gridded data openly would contribute to speed up understanding of uncertainties and knowledge gaps, by making it accessible to the broader scientific community. Furthermore, this hampers reproducibility of some of the main results of this paper (Figures 6, 11, 12, 15), and does not seem to fully align with ESSD core principles as stated in the journal’s page.
Supplement
It is difficult to extract from the supplementary information the key aspects of the protocol used for DGVM and BM models (starting year, period covered, forcing, adjustments, etc.), since they are referred to in between lengthy descriptions of specific aspects of the datasets. These lengthy descriptions are useful since they contain very relevant information, but I would suggest summarizing the modelling protocol and adjustments performed in a table (similar to Table S2 for GOBMs).
Line 857: I suggest adding a subsection header for the RSS correction here (or highlight as a paragraph), making it easier for the readers to find the relevant information.
References cited
Caspar T. J. Roebroek et al. Releasing global forests from human management: How much more carbon could be stored? Science380, 749-753(2023). DOI:10.1126/science.add5878
James T. Randerson et al.The weak land carbon sink hypothesis. Sci.Adv.11, eadr5489(2025). DOI:10.1126/sciadv.adr5489
Bastos, A et al. (2020), Sources of uncertainty in regional and global terrestrial CO2 exchange estimates. Global Biogeochemical Cycles, 34, e2019GB006393. https://doi.org/10.1029/2019GB006393
Liang Xu et al. Changes in global terrestrial live biomass over the 21st century.Sci. Adv.7,eabe9829(2021).DOI:10.1126/sciadv.abe9829