the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Differences in anthropogenic greenhouse gas emissions estimates explained
Abstract. We examine differences in global and national greenhouse gas (GHG) emissions estimates and highlight the important role of varying system boundaries and conceptual approaches in driving these variations. Despite consensus among assessments and datasets that GHG emissions continue to increase and are far from aligned with the Paris Agreement goals, estimates can differ significantly. Our review finds three main reasons for these differences. First, datasets vary in their coverage of gases, sectors and countries; second, there are different approaches to defining ‘anthropogenic’ emissions and removals in the land use, land-use change and forestry (LULUCF) sector; and third, the Paris Agreement doesn’t cover all relevant sources of emissions, including the cement carbonation sink and ozone depleting substances. As different assessments have different objectives, they may deal with these issues differently. We highlight three assessment conventions that report or use emissions data: those focused on interpreting national progress, policies and pledges under the Paris Agreement; those consistent with integrated assessment modelling (IAM) benchmarks of emissions under different warming scenarios; and those consistent with climate forcing assessments. Considering annual average emissions over the period 2014 to 2023, we show global totals of 44.7 GtCO2e yr-1 [90 % CI ± 4.6], 53.1 GtCO2e yr-1 [90 % CI ± 5.2], and 54.9 GtCO2e yr-1 [90 % CI ± 5.2] for these three conventions, respectively. We suggest that users of GHG emissions data increase transparency in their decision criteria for choosing datasets and setting the scope of an assessment. The data used in this study to make figures 8–13 is available at: https://doi.org/10.5281/zenodo.15126539 (Lamb, 2025b).
Competing interests: Author FNT is a member of the editorial board of the journal.
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
(1887 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
- CC1: 'primap-hist long name', Mika Pflüger, 30 Apr 2025
- RC1: 'Comment on essd-2025-188', Anonymous Referee #1, 07 May 2025
-
RC2: 'Comment on essd-2025-188', Anonymous Referee #2, 02 Feb 2026
I find this article to be a very useful and tidy overview, providing clarity and guidelines on the use of very widely used datasets for greenhouse gases. I would be happy to see this article published as is, but I do have a few minor suggestion for corrections / improvement:
This article very nicely contrasts the differences between various emissions datasets, where they originate and how large they are. However, many of these datasets are updated on a regular datasets, and differences between different versions of the same dataset can be non-trivial even for data for the same historical years. If possible, I would like some comparison or contrast of the size difference seen here between different datasets and the differences in dataset versions. Is the differences between datasets orders of magnitude larger, or just maybe a smaller factor?
There are a lot of abbreviations here, I think I would prefer if the Global Methane Budget was not abbreviated, as the abbreviation is only used a couple of times, and the full name is used again after the abbreviation is introduced.
I find figure 3 slightly confusing to read, as I don't immediately understand what is covered by the inventories, as the text for that is above the box, and not inside as for GCB and GFED/GFAS. Could presumably be solved with a sentence or two in the caption.
As far as I can see, section 2.2.3 deals exclusively with methane emissions. If this is true, I would like the word "methane" to feature in the section heading, i.e. "Wetlands and freshwater body methane emission" or similar.
In figure 9, I am confused by the sentence on GWP100 use in the caption. This figure shows only CO2 emissions, so no GWP100-based conversion would have needed to be applied, right?
When referring to methane emissions as CO2 equivalent units, especially in the methane only figure (Figure 10), I would like it specified which GWP100 value in Forster et.al. 2021 is used as there are (at least) two different choices.
Then a few typo-fixes:
Line 74: "often poorly transparent" -> "often not transparent"
Line 100: "use by the corresponding emission factor" - > "use by a corresponding emission factor" (as emissions factor choices can vary between datasets, and dataset versions)
Line 213: "LULUCF sector occur are generally" - > "LULUCF sector are generally"
Line 325: "didistinguish" -> "distinguish"
Line 362-364: These two sentences confuse me slightly, as the first states that wetland emissions are considered natural, but then the second still states that some of it is considered anthropogenic anyway. Maybe this is fine and would just benefit from a slight rephrasing.
Line 387: Consider citing also the WMO 2026 report on ozone depletion.
Citation: https://doi.org/10.5194/essd-2025-188-RC2
Data sets
Dataset for Differences in anthropogenic greenhouse gas emissions estimates explained William F. Lamb https://doi.org/10.5281/zenodo.15126540
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 2,497 | 283 | 56 | 2,836 | 59 | 89 |
- HTML: 2,497
- PDF: 283
- XML: 56
- Total: 2,836
- BibTeX: 59
- EndNote: 89
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Line 130: Please note that the full title of the PRIMAP-hist dataset is (and always has been) “The PRIMAP-hist national historical emissions time series”, not “Potsdam Realtime Integrated Model for probabilistic Assessment of emissions Paths”. The “Potsdam…” long name used to be the long form of the PRIMAP model (not the historical emissions output), but we also abandoned that, PRIMAP is simply a name now.