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Assessing pre-pandemic carbon footprint of diet transitions in UK nations and regions

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DataCite Commons2024-09-10 更新2024-07-29 收录
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https://tandf.figshare.com/articles/dataset/Assessing_pre-pandemic_carbon_footprint_of_diet_transitions_in_UK_nations_and_regions/20418003
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资源简介:
Food supply chains hold significant embodied carbon emissions that need to be mitigated and neutralized. This study aimed to explore the historical Greenhouse Gas (GHG) emissions associated with household food consumption at a local scale i.e. across the eight English regions and the four nations that comprise the United Kingdom (UK). UK EatWell guidelines were used to explore the potential change in emissions and food costs in a scenario of transitions to healthier diets across the study areas. These emissions were calculated based on food consumption data before the advent of the Covid-pandemic i.e. between the years 2001 and 2018. Spatial data analysis was used to explore if the study areas had any significant correlations with respect to the emissions during the study period. The results displayed a potential reduction in GHG emissions for all study areas in the explored scenario. Further impacts include a reduction in household food costs across a majority of the areas during the study period. However, a consistent trend of significant correlations among the study areas was absent. This study concludes that local or regional policymaking should take precedence over national regulations to achieve healthier diets that are both carbon-neutral and affordable for the households.

食品供应链蕴含着大量隐含碳排放,亟需开展减排与中和工作。本研究旨在探究地方尺度下家庭食品消费相关的历史温室气体(Greenhouse Gas, GHG)排放,研究范围覆盖英格兰的8个地区以及组成大不列颠及北爱尔兰联合王国(United Kingdom, UK)的4个构成国。本研究采用英国《EatWell饮食指南》,探究在研究区域内转向健康饮食的情景下,温室气体排放与家庭食品成本的潜在变化。上述排放量的计算基于新冠疫情暴发前的食品消费数据,即2001年至2018年期间的统计数据。本研究采用空间数据分析方法,探究研究区域在研究期内的温室气体排放是否存在显著相关性。研究结果显示,在所探究的情景下,所有研究区域的温室气体排放均存在潜在减排空间。此外,研究期间多数研究区域的家庭食品成本也呈现下降趋势。但各研究区域之间并未呈现出一致的显著相关性趋势。本研究得出结论:若要实现兼顾碳中和与家庭可负担性的健康饮食模式,地方或区域层面的政策制定应优先于国家层面的监管措施。
提供机构:
Taylor & Francis
创建时间:
2022-08-02
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