the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Global consumption-based deforestation carbon emissions and regional hotspots: 2001–2015
Abstract. The consumption-based carbon emissions dataset for deforestation is essential for developing effective emission reduction policies by offering an alternative perspective. Although previous studies have provided national-scale data on deforestation emission footprints, the global scale data with detailed and continuous spatial information is still lacking. Here, we created a global consumption-based carbon emissions gridded dataset for deforestation at a 1 km resolution for 2001–2015, integrating spatial data on road networks, deforestation, and forest carbon fluxes with country-level statistics on global trade. Our dataset reveals that trade-related carbon emissions induced by deforestation were 25.3 Gt CO2e, constituting 31.0 % of global carbon emissions due to deforestation. Additionally, the top 20 countries are responsible for most of the consumption-based carbon emissions which contribute to over 80 % of the global total. While high-income countries are responsible for 68.8 % of hidden deforestation emissions in trade, the ones in lower-income counties are rising due to the notable consumption in higher-income areas. This new dataset help addresses the previous data gap in consumption-based global deforestation emissions, aiding the formulation of consumer-side emission reduction strategies and expanding the approaches for mitigating carbon emissions due to anthropogenic activities. Datasets are available at https://doi.org//10.6084/m9.figshare.28091879 (Tang et al., 2024).
Competing interests: Some authors are members of the editorial board of journal 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 preprint. The responsibility to include appropriate place names lies with the authors.- Preprint
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RC1: 'Comment on essd-2024-619', Anonymous Referee #1, 13 May 2025
I had a quick look at this paper to see if it was worth reviewing.
Whilst the issue/data is important, I was dismayed to see that the paper only presents partial results, and not actually the data needed for such a study.
i.e. the authors point to the uniqueness of the data that they estimate, but then only present a few key derived results, rather than the underlying data that they estimate and which they allude to in the study.
As such, there is no point reviewing the work for a dataset descriptor, as, in my mind, they do not adequately describe, or present data. The data description in the methods is also rather brief.
You might like to check why the authors claim to present a global dataset at grid scale, but only provide results for 8 regions at a very aggregated level.Citation: https://doi.org/10.5194/essd-2024-619-RC1 -
RC2: 'Comment on essd-2024-619', Anonymous Referee #2, 13 May 2025
This manuscript addresses a timely and relevant topic by estimating global consumption-based deforestation carbon emissions using an enhanced SMRIO model and claims to produce a 1 km-resolution global dataset covering 2001–2015. While the analytical framework appears sound and the topic aligns with the scope of ESSD, I have several concerns regarding the adequacy of the dataset description.
The primary issue is that the manuscript does not sufficiently demonstrate or present the dataset it claims to contribute. The results focus largely on aggregated regional or country-level summaries, with only a few case-specific maps (e.g., USA and China) shown. Despite repeated references to the availability of a global gridded dataset, the authors provide no sample visualizations, tables, or excerpts from the actual 1 km data product—either in the main text or in the supplementary material. This lack of transparency makes it difficult to evaluate the data's completeness, coverage, and usability. Furthermore, no metadata or format specifications (e.g., content of the TIFF files on figshare) are included.
While the study has potential and the methodology is well documented, the presentation falls short of ESSD standards for dataset documentation and accessibility. I encourage the authors to revise the manuscript substantially to provide representative samples, clearer metadata, and concrete evidence of the claimed dataset before resubmission.
Citation: https://doi.org/10.5194/essd-2024-619-RC2
Status: closed
-
RC1: 'Comment on essd-2024-619', Anonymous Referee #1, 13 May 2025
I had a quick look at this paper to see if it was worth reviewing.
Whilst the issue/data is important, I was dismayed to see that the paper only presents partial results, and not actually the data needed for such a study.
i.e. the authors point to the uniqueness of the data that they estimate, but then only present a few key derived results, rather than the underlying data that they estimate and which they allude to in the study.
As such, there is no point reviewing the work for a dataset descriptor, as, in my mind, they do not adequately describe, or present data. The data description in the methods is also rather brief.
You might like to check why the authors claim to present a global dataset at grid scale, but only provide results for 8 regions at a very aggregated level.Citation: https://doi.org/10.5194/essd-2024-619-RC1 -
RC2: 'Comment on essd-2024-619', Anonymous Referee #2, 13 May 2025
This manuscript addresses a timely and relevant topic by estimating global consumption-based deforestation carbon emissions using an enhanced SMRIO model and claims to produce a 1 km-resolution global dataset covering 2001–2015. While the analytical framework appears sound and the topic aligns with the scope of ESSD, I have several concerns regarding the adequacy of the dataset description.
The primary issue is that the manuscript does not sufficiently demonstrate or present the dataset it claims to contribute. The results focus largely on aggregated regional or country-level summaries, with only a few case-specific maps (e.g., USA and China) shown. Despite repeated references to the availability of a global gridded dataset, the authors provide no sample visualizations, tables, or excerpts from the actual 1 km data product—either in the main text or in the supplementary material. This lack of transparency makes it difficult to evaluate the data's completeness, coverage, and usability. Furthermore, no metadata or format specifications (e.g., content of the TIFF files on figshare) are included.
While the study has potential and the methodology is well documented, the presentation falls short of ESSD standards for dataset documentation and accessibility. I encourage the authors to revise the manuscript substantially to provide representative samples, clearer metadata, and concrete evidence of the claimed dataset before resubmission.
Citation: https://doi.org/10.5194/essd-2024-619-RC2
Data sets
Consumption-based Carbon Emissions for Deforestation (2001–2015) Dongmei Tang, Yuanzhi Yao, and Xia Li https://doi.org/10.6084/m9.figshare.28091879
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