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Analysis of the spatial association network structure of China's transportation carbon emissions and its driving factors

机译:中国交通碳排放空间关联网络结构及其驱动因素分析

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摘要

Using the social network analysis method, this paper explores the characteristics of the spatial association network structure of China's provincial transportation carbon emissions from 2005 to 2015 and its driving factors. The results are as follows: (1) The spatial association of China's provincial transportation carbon emissions exhibits an intuitive network structure. The degree of closeness which were 0.2253 and 0.2333 in 2005 and 2015 respectively shows an increasing trend on the whole. However, it hit the bottom in 2011, reaching a minimum of 0.2230, which is the "low closeness degree inflection point". (2) The spatial association network presents a significant "core-edge" distribution pattern. Specifically, in the central and eastern regions of China, Henan and Jiangsu have degrees of up to 58.621 and 44.828, which are at the network center. However, some remote regions, like Jilin and Hainan, have degrees of less than 20.000, which are marginalized. (3) The geographical adjacency, the expansion of the difference in R&D investment, and the narrowing of the difference in economic development promote the formation of the interprovincial spatial association. Therefore, in the process of controlling carbon emissions from transportation, the government should focus on the provinces at the network center and pay attention to the impact of the R&D investment on the spatial association of transportation carbon emissions.
机译:本文运用社会网络分析方法,探讨了2005-2015年中国省际交通碳排放的空间关联网络结构特征及其驱动因素。研究结果如下:(1)中国省级交通碳排放的空间关联具有直观的网络结构。整体的亲密度在2005年和2015年分别为0.2253和0.2333。但是,它在2011年触底,最低为0.2230,这是“低接近度拐点”。 (2)空间关联网络呈现出明显的“核心边缘”分布模式。具体而言,在中国的中部和东部地区,河南和江苏的网络中心分别为58.621和44.828。但是,吉林和海南等偏远地区的边缘度低于20.000。 (3)地理上的邻接,R&D投资差异的扩大和经济发展差异的缩小促进了省际空间协会的形成。因此,在控制交通运输碳排放的过程中,政府应重点关注网络中心的省份,并注意研发投入对交通运输碳排放空间关联的影响。

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