Preprints
https://doi.org/10.5194/essd-2025-188
https://doi.org/10.5194/essd-2025-188
24 Apr 2025
 | 24 Apr 2025
Status: this preprint is currently under review for the journal ESSD.

Differences in anthropogenic greenhouse gas emissions estimates explained

William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster

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 preprint. The responsibility to include appropriate place names lies with the authors.
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William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster

Status: open (until 31 May 2025)

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William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster

Data sets

Dataset for Differences in anthropogenic greenhouse gas emissions estimates explained William F. Lamb https://doi.org/10.5281/zenodo.15126540

William Lamb, Robbie Andrew, Matthew Jones, Zebedee Nicholls, Glen Peters, Chris Smith, Marielle Saunois, Giacomo Grassi, Julia Pongratz, Steven Smith, Francesco Tubiello, Monica Crippa, Matthew Gidden, Pierre Friedlingstein, Jan Minx, and Piers Forster
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Short summary
This study explores why global greenhouse gas (GHG) emissions estimates vary. Key reasons include different coverage of gases and sectors, varying definitions of anthropogenic land use change emissions, and the Paris Agreement not covering all emission sources. The study highlights three main ways emissions data is reported, each with different objectives and resulting in varying global emission totals. It emphasizes the need for transparency in choosing datasets and setting assessment scopes.
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