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Drivers of GHG emissions from dietary transition patterns in China: Supply versus demand options

He, Pan ORCID:, Cai, Beiming, Baiocchi, Giovanni and Liu, Zhu 2021. Drivers of GHG emissions from dietary transition patterns in China: Supply versus demand options. Journal of Industrial Ecology 25 (3) , pp. 707-719. 10.1111/jiec.13086

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Diets have been changing drastically in China in the recent decades and this change has contributed considerably to greenhouse gas (GHG) emissions. In determining effective mitigation strategies for future emissions, it is necessary to know how emissions related to diet vary over time in overall magnitude and due to compositional changes driven by socioeconomic dynamics. This study evaluates the change in dietary GHG emissions in China during the 1997–2011 period by linking environmentally extended input–output tables with individual daily food intake data. It further decomposes the contribution to GHG emission changes of various socioeconomic driving factors. The results show that GHG emissions related to national diet have been decreasing from 1,180 Mt CO2e to 640 Mt CO2e (a 54% decline), largely due to technical innovation that has reduced the emissions per calorie of food (135% of the total reduction). The change in dietary patterns has had mixed effects, with a decline in calorie intake reducing emissions by 21% while increases in animal‐sourced food consumption have raised emissions by 25%. Our findings stress the importance of technical progress in the historical change in dietary GHG emissions and suggest a focus on behavior changes for future research and policymaking, which has the potential to promote dietary changes toward less animal product consumption. Our findings highlight the importance of both technological and demand‐side behavioral options in reducing the impact of diets on GHG emissions.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Earth and Environmental Sciences
Publisher: Wiley
ISSN: 1088-1980
Date of First Compliant Deposit: 7 October 2020
Date of Acceptance: 8 September 2020
Last Modified: 06 Nov 2023 18:07

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