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Multi-region input-output analysis of embodied emissions and intensities: Spatial aggregation by linking regional and global datasets

机译:多区域输入 - 体现排放和强度的分析:通过链接区域和全球数据集的空间聚合

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摘要

The multi-region input-output (MRIO) model has been widely adopted to capture feedback effects in energy/ emission studies. For regional emission studies, linking regional and global datasets is essential to capture both interregional and international feedback effects. However, this will lead to spatial aggregation. This paper deals with spatial aggregation issues in the MRIO analysis of regional embodied emissions/intensities when linking regional and global datasets. When such data are available for two different years, there are also spatial aggregation issues in the structural decomposition analysis (SDA) that may be conducted to investigate the driving forces of changes of regional embodied emissions/intensities between the two years. In this paper, we discuss four such spatial aggregation schemes with different data requirements. An empirical study linking the data of China's 30 regions and 43 world countries for 2007 and 2012 and analyzing the impacts of spatial aggregation on China's regional embodied emissions and intensities and their driving forces between these two years is presented. The study shows the impacts of spatial aggregation on the regional results. It is found that the spatial aggregation has a greater impact on the sectoral results than the regional results. Implications of the findings on regional emission studies are discussed.
机译:多区域输入输出(MRIO)模型已被广泛采用以捕获能量/排放研究中的反馈效果。对于区域排放研究,联系区域和全球数据集对于捕获区域间和国际反馈效果至关重要。但是,这将导致空间聚集。本文涉及区域体现排放/强度在联系区域和全球数据集时的空间聚合问题。当这些数据有两个不同年份时,结构分解分析(SDA)也存在空间聚集问题,以调查两年间区域体现排放/强度变化的驱动力。在本文中,我们讨论了具有不同数据要求的四种这样的空间聚合方案。提出了一种与2007年和2012年43世纪43世界国家的数据相关的实证研究,并提出了对中国区域体现和强度的影响,分析了这两年之间的空间汇总对中国区域体现和强度及其驱动力。该研究表明了空间汇总对区域结果的影响。发现空间聚集对部门结果产生了更大的影响而不是区域结果。讨论了调查结果对区域排放研究的影响。

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