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从省域和部门视角看 2012 年中国隐含碳转移网络

Research on China's embodied carbon transfer network in 2012 from the perspective of provinces and sectors.

机构信息

College of Management and Economics, Tianjin University, Tianjin, 300072, China.

出版信息

Environ Sci Pollut Res Int. 2020 Nov;27(31):38701-38714. doi: 10.1007/s11356-020-09528-z. Epub 2020 Jul 6.

Abstract

Resource endowment and economic development of different provinces in China vary greatly, resulting in large amount of CO transfers. We need further exploration to help decision makers allocate emission responsibilities reasonably. We construct China's embodied CO transfer network (CTN) in 2012 from the perspective of provinces and sectors based on multi-regional input-output (MRIO) model and complex network analysis. The key CO transfer nodes and paths, final demand decomposition, topological structure, clustering characteristics, and influencing factors are analyzed. The results show that the average CO transfer length from one province (sector) to another is only 1.323 (1.584). The top three net CO importers (45.39% of the total), located in developed eastern coastal area, mainly import CO from energy-rich but underdeveloped provinces such as Heilongjiang. It presents a CO transfer pattern from north to south and from west to east. CO transfer in energy industry is mainly driven by urban household consumption. Non-adjacent provinces with distance greater than 750 km have no significant spillover effect and difference in technology level has the greatest impact on CTN. This work is important for differentiating the roles of provinces and sectors in CTN, guiding the allocation of carbon credits and controlling total CO emissions.

摘要

中国各省份的资源禀赋和经济发展差异很大,导致大量的 CO 排放转移。我们需要进一步探索,以帮助决策者合理分配排放责任。我们基于多区域投入产出(MRIO)模型和复杂网络分析,从省和部门的角度构建了中国 2012 年的隐含 CO 转移网络(CTN)。分析了关键 CO 转移节点和路径、最终需求分解、拓扑结构、聚类特征和影响因素。结果表明,从一个省(部门)到另一个省(部门)的平均 CO 转移长度仅为 1.323(1.584)。前三个净 CO 进口省(占总数的 45.39%)位于发达的东部沿海地区,主要从资源丰富但欠发达的黑龙江等省份进口 CO。呈现出从北到南、从西到东的 CO 转移格局。能源行业的 CO 转移主要由城市家庭消费驱动。距离超过 750 公里的非相邻省份没有显著的溢出效应,技术水平差异对 CTN 的影响最大。这项工作对于区分 CTN 中各省和部门的作用、引导碳信用额的分配和控制总 CO 排放量具有重要意义。

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