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Misbehaviour dominates GHG emissions from food loss and waste

Nature Climate Change (2026)Cite this article

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Abstract

Food loss and waste (FLW) generates ~19% of global anthropogenic greenhouse gas emissions, yet its determinants and mitigation potential remain insufficiently understood. To address this, we develop a mechanistic framework that disaggregates FLW emissions into those driven by techno-economic constraints, surplus production and mis-consumption, with the latter two constituting misbehaviour-driven emissions. We show that global misbehaviour-driven emissions amounted to 4.0 Gt of CO2-equivalent emissions in 2021, representing 59% of total FLW emissions, with meat consumption and structural surplus contributing 50% and 15%, respectively. We further quantify country-level FLW emission reduction potentials through behavioural, technological and dietary pathways, finding that behavioural controls provide the greatest reduction potentials globally. However, any single intervention is insufficient to achieve Sustainable Development Goal 12.3 of halving FLW emissions, underscoring the need for integrated strategies. Sub-Saharan Africa is projected to be the largest regional FLW emitter and account for 21% of global misbehaviour-driven emissions and 18% of global techno-economic-constraint-driven emissions by 2050.

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Fig. 1: FLW segments and corresponding emissions.
Fig. 2: National ΣMBC emissions between 2001 and 2021.
Fig. 3: Dependence of ΣMBC on socio-economic factors between 2001 and 2021.
Fig. 4: Mitigation potential and feasibility of national FLW emissions in 2021.
Fig. 5: Predictions of regional FLW emissions by segment under SSP scenarios to 2050.

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Data availability

The data that support the findings of this study are available in Supplementary Information, and Supplementary Data alongside the paper. Most of the datasets used in the analysis are available publicly, such as from the FAOSTAT or World Bank. Food supply raw data are available on the FAOSTAT website and can be accessed at the following link: https://www.fao.org/faostat/en/#home. FLW raw data are available on FAOSTAT website and can be accessed at the following link: https://www.fao.org/platform-food-loss-waste/flw-data/en/. All other data are available from the corresponding authors upon reasonable request. Source data are provided with this paper.

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Acknowledgements

We thank the 2023 Key Achievement Cultivation Plan Project of Nanjing Forestry University for financial support (project number 163108230, K.Y.).

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Authors and Affiliations

  1. Department of Environmental Engineering, College of Ecology and Environment, Nanjing Forestry University, Nanjing, China

    Ke Yin, Jingyu Zhu, Mo Wu, Xue Ling, Maoyao Cai, Shuhan Ren, Xingyu Zhao, Chen Ling & Lei Yu

  2. School of Civil and Environmental Engineering, Nanyang Technological University, Singapore, Singapore

    Jingyu Zhu, Yao Wang & Xunchang Fei

  3. Nanyang Environment and Water Research Institute, Singapore, Singapore

    Jingyu Zhu & Xunchang Fei

  4. Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing, China

    Houhu Zhang

  5. Consultant-Energy Transition Integrated Solutions International, Singapore, Singapore

    Huanhuan Tong

  6. Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland

    Chao He

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  1. Ke Yin
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Contributions

K.Y. conceived the study with substantial input from X.F.; performed the analysis with support from J.Z., M.W., X.L. and M.C.; and drafted the paper. All authors reviewed and edited the paper.

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Correspondence to Ke Yin or Xunchang Fei.

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Extended data

Extended Data Fig. 1 Illustration of FLW emission segments by stakeholders and mitigation pathway.

Comparison of emissions under our framework and the FAO classification, linking driving forces, responsible actors, and targeted interventions.

Extended Data Fig. 2 MBCS-to-ΣMBC ratios under three shared socioeconomic pathways (SSPs).

MBCS-to-ΣMBC ratios under a, SSP1, b, SSP2, and c, SSP5 for SSAF, WA + NAF, CA + SA (excluding India), EA + SEA (excluding China), EU + NAM + OC (excluding the U.S.), China, India, and the U.S. values for 2001–2021 were calculated using FAOSTAT food supply data, and projections for 2025–2050 were derived from SSP-based GDP and population trajectories. See Methods for details.

Source data

Extended Data Fig. 3 Average ΣMBC/Cap and ΣTCC/Cap across regions in 2001-2021.

Six regions are shown: SSAF, WA + NAF, CA + SA, EA + SEA, EU + NAM + OC, and LAM + CAR. Detailed country/region definitions are provided in the caption of Supplementary Fig. 3. Error bars indicate the 5th – 95th percentile range.

Source data

Extended Data Fig. 4 Schematic framework for calculating and projecting emissions from food loss and waste.

FLW denotes food loss and waste; FAO, Food and Agriculture Organization of the United Nations; FLC, food loss embodied GHG emissions during supply; FWC, food waste embodied GHG emissions ascribed to retail and customer; FLWW, FLW emissions ascribed to waste management; LCA, life cycle assessment; and RICE, the Regional Integrated model of Climate and the Economy. Here, p(t) is GDP, L(t) is population, and R(t) is a function of social discount rate (SDR). E denotes a constant elasticity of substitution (CES) function for FLW emissions prediction, associated with FLC in distribution. See Methods (Eqs. 21–23) for details.

Supplementary information

Supplementary Information (download PDF )

Supplementary Figs. 1–18, Tables 1–8 and Discussion.

Reporting Summary (download PDF )

Supplementary Data 1 (download XLSX )

Surplus values across countries from 2000 to 2021.

Supplementary Data 2 (download XLSX )

Percentage changes in food supply across countries under a “halving meat consumption” scenario.

Supplementary Data 3 (download XLSX )

Country-specific carbon emission coefficients.

Supplementary Data 4 (download XLSX )

Population data across countries from 2001 to 2021.

Supplementary Data 5 (download XLSX )

Greenhouse gas mitigation under SDG 12.3.

Source data

Source Data Fig. 2 (download XLSX )

Statistical source data for Fig. 2.

Source Data Fig. 3 (download XLSX )

Statistical source data for Fig. 3.

Source Data Fig. 4 (download XLSX )

Statistical source data for Fig. 4.

Source Data Fig. 5 (download XLSX )

Statistical source data for Fig. 5.

Source Data Extended Data Fig. 2 (download XLSX )

Statistical source data for Extended Data Fig. 2.

Source Data Extended Data Fig. 3 (download XLSX )

Statistical source data for Extended Data Fig. 3.

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Yin, K., Zhu, J., Wu, M. et al. Misbehaviour dominates GHG emissions from food loss and waste. Nat. Clim. Chang. (2026). https://doi.org/10.1038/s41558-026-02596-y

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