A two-tiered attribution structural decomposition analysis to reveal drivers at both sub-regional and sectoral levels: A case study of energy consumption in the Jing-Jin-Ji region

A two-tiered attribution structural decomposition analysis to reveal drivers at both sub-regional and sectoral levels: A case study of energy consumption in the Jing-Jin-Ji region
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揭示次区域和部门层面驱动因素的两层归因结构分解分析:以京津冀地区能源消费为例

DOI:
10.1016/j.jclepro.2018.12.167
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发表时间:
2019-03
影响因子:
11.1
通讯作者:
Zhu Bing
Zhu Bing
中科院分区:
环境科学与生态学1区
文献类型:
--
作者:
Yu Yadong;Liang Sai;Zhou Wenji;Ren Hongtao;Kharrazi Ali;Zhu Bing

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结构分解分析(SDA)是研究环境压力驱动力的一种常用方法。通过归因分析,SDA可以进一步将EP的驱动力分解为经济部门或次区域,并提供更详细的循证决策。然而,目前的归因分析研究还没有得到充分的发展,只有一个层次,即,它们将环保的驱动力分解到次区域或经济部门层面。在这项研究中,我们介绍了一种SDA的方法与两个层次的归因分析,这是能够1)探索的驱动力,在多个区域的水平和2)进一步分解的驱动力的环境保护到子区域和经济部门。基于该方法,对2007-2012年京津冀地区能源消费变化的驱动力进行了分析。本案例研究的结果表明,技术变革、最终需求结构和最终需求构成对该地区能源消费变化的贡献率分别为-129%,12%和-3%,而富裕程度、生产结构、人口总数和人口结构对该地区能源消费变化的贡献率分别为129%,77%,38%和2%。从分区域和经济部门层面的贡献来看,河北省和化工及金属冶炼和压延行业的贡献最为突出。通过本案例研究,我们分析了两层归因SDA方法的优势和局限性,并提出了关键的政策建议和未来的研究方向。
Structural decomposition analysis (SDA) is a very commonly used method for exploring the driving forces of environmental pressure (EP). Enhanced with attribution analysis, SDA can further decompose the driving forces of EP into economic sectors or sub-regions and provide more detailed evidence-based policymaking. However, current studies of SDA with attribution analysis have not been sufficiently developed and are only one-tiered, i.e., they decompose the driving forces of EP into either a sub-regional or an economic sectoral level. In this study, we introduce a method of SDA with a two-tiered attribution analysis, which is capable of 1) exploring the driving force of environmental pressure at a multi-regional level and 2) further decomposing the driving forces of EP into both sub-regions and economic sectors. Based on this method, we explore the driving forces for the change of energy consumption in the Jing-Jin-Ji region during the period of 2007–2012. Results of this case study indicate that technological change, final demand structure, and final demand composition respectively contributed −129%, 12%, and −3% while affluence, production structure, total population, and population structure respectively contributed 129%, 77%, 38%, and 2% to energy consumption change in the region. In terms of sub-regional and economic sectoral level contributions, Hebei province and the chemical and smelting and rolling of metals industries were the most prominent contributors. Through this case study, we situate the strengths and limitations of the two-tiered attribution SDA method and propose key policy suggestions and future research directions.
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