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Changes in global food consumption increase GHG emissions despite efficiency gains along global supply chains


Greenhouse gas (GHG) emissions related to food consumption complement production-based or territorial accounts by capturing carbon leaked through trade. Here we evaluate global consumption-based food emissions between 2000 and 2019 and underlying drivers using a physical trade flow approach and structural decomposition analysis. In 2019, emissions throughout global food supply chains reached 30 ±9% of anthropogenic GHG emissions, largely triggered by beef and dairy consumption in rapidly developing countries—while per capita emissions in developed countries with a high percentage of animal-based food declined. Emissions outsourced through international food trade dominated by beef and oil crops increased by ~1 Gt CO2 equivalent, mainly driven by increased imports by developing countries. Population growth and per capita demand increase were key drivers to the global emissions increase (+30% and +19%, respectively) while decreasing emissions intensity from land-use activities was the major factor to offset emissions growth (−39%). Climate change mitigation may depend on incentivizing consumer and producer choices to reduce emissions-intensive food products.

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Fig. 1: GHG emissions throughout global supply chains from consumption of food products by country in 2000 and 2019.
Fig. 2: Per capita GHG emissions of food consumption by country in 2000 and 2019.
Fig. 3: GHG emissions embodied in domestic supply and international trade of food of major countries in 2000, 2010 and 2019.
Fig. 4: Patterns of emissions flows embodied in trade.
Fig. 5: Contributions of five driving factors to changes in GHG emissions from food consumption.

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Data availability

The LULUC, agricultural and beyond-farm emissions data are curated by the FAO and freely available from FAOSTAT77. Population data used in this study are obtained from World Population Prospects of the United Nations83. Data of monetary values for transport and food-related sectors are obtained from the GTAP database74. Supplementary methods, discussion, figures, tables and datasets used in the analysis can be found in the Supplementary Information files. More detailed results are available from the corresponding authors on reasonable request. Source data are provided with this paper.

Code availability

Code developed for data processing in MATLAB is available in the Supplementary Information files.


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We thank T. Kastner for providing the code for the PTF approach. We thank the support from Greenpeace Germany for the initial data analysis, modelling and discussions as part of the project ‘Outsourced Environmental Degradation of the EU’. This research is also supported by the National Natural Science Foundation of China (72243004, 72174111), the Shandong Natural Science Foundation of China (ZR2021MG013), the major programme of the National Social Science Foundation of China (21ZDA065), the United Kingdom Research and Innovation (UoB Policy Support Fund PSF-16). For the purpose of open access, a CC BY public copyright licence is applied to any Author Accepted Manuscript arising from this submission. Y.L., Y.H., D.W. and Y.Z. acknowledge the funding support by the China Scholarship Council Ph.D. programme.

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Y.L., Y.S. and K.H. designed the research. Y.L. performed the analysis with support from Y.H., D.W. and Y.Z. on analytical approaches and visualization. Y.L. led the writing with efforts from H.Z., Y.S. and K.H. Y.S. and K.H. supervised and coordinated the overall research. All co-authors reviewed and commented on the manuscript.

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Correspondence to Yuli Shan or Klaus Hubacek.

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Nature Food thanks Francesco Tubiello and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Li, Y., Zhong, H., Shan, Y. et al. Changes in global food consumption increase GHG emissions despite efficiency gains along global supply chains. Nat Food 4, 483–495 (2023).

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