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    宋国宝

    • 副教授     博士生导师   硕士生导师
    • 性别:男
    • 毕业院校:北京师范大学
    • 学位:博士
    • 所在单位:环境学院
    • 学科:环境科学. 环境工程
    • 办公地点:环境学院B715室
    • 联系方式:大连理工大学 环境学院 工业生态与环境工程教育部重点实验室, 邮编116024 邮件:gb.song@dlut.edu.cn
    • 电子邮箱:gb.song@dlut.edu.cn

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    Climatic burden of eating at home against away-from-home: A novel Bayesian Belief Network model for the mechanism of eating-out in urban China

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    论文类型:期刊论文

    发表时间:2019-02-10

    发表刊物:SCIENCE OF THE TOTAL ENVIRONMENT

    收录刊物:SCIE、PubMed、SSCI、Scopus

    卷号:650

    期号:Pt 1

    页面范围:224-232

    ISSN号:0048-9697

    关键字:Eat away-from-home; Carbon footprint; Climate change; Urbanization; Socioeconomic transitioning; Bayesian Belief Network

    摘要:Dietary patterns of eating away-from-home (AFH) considerably differ from those of eating at home in urban China, thus generating varied carbon footprints. However, few studies have investigated the effect of eating places on diet-related climatic burden, and few have modelled the mechanism under the condition of eating-out because the decision of consumers on whether to eat AFH or at home is determined by multiple non-linear socioeconomic factors. Here, we compared the carbon footprints of eating at home and AFH using household survey data from 12 Chinese provinces, and developed a Bayesian Belief Network (BBN) model to identify key factors of eating AFH. Our findings show that eating AFH leads to higher climatic burdens though respondents consume less food on average than when eating at home. However, in urban areas, the carbon footprint generated increases more rapidly from eating at-home than when eating AFH. The BBN model was found to have strong capability to predict the possibility of eating out with an accuracy of 89%. Although diet patterns and embedded carbon footprint vary considerably across provinces from northeastern to southwestern China, sufficient evidence could not be found to support the influence of geographic factors on the decision of respondents to eat AFH at large scale. Instead, individual occupation and income were found to be the two key contributors. Thus, merely estimating the carbon footprint of food consumption is currently not sufficient, but social and economic elements need to be quantitatively considered to differentiate the eating-place effect on diet-related climatic burden. (C) 2018 Elsevier B.V. All rights reserved.