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The Evolution of the Spatial Association Effect of Carbon Emissions in Transportation: A Social Network Perspective

机译:社会网络视角下的交通碳排放空间关联效应的演变

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摘要

The association effect between provincial transportation carbon emissions has become an important issue in regional carbon emission management. This study explored the relationship and development trends associated with regional transportation carbon emissions. A social network method was used to analyze the structural characteristics of the spatial association of transportation carbon emissions. Indicators for each of the structural characteristics were selected from three dimensions: The integral network, node network, and spatial clustering. Then, this study established an association network for transportation carbon emissions (ANTCE) using a gravity model with China’s provincial data during the period of 2007 to 2016. Further, a block model (a method of partitioning provinces based on the information of transportation carbon emission) was used to group the ANTCE network of inter-provincial transportation carbon emissions to examine the overall association structure. There were three key findings. First, the tightness of China’s ANTCE network is growing, and its complexity and robustness are gradually increasing. Second, China’s ANTCE network shows a structural characteristic of “dense east and thin west.” That is, the transportation carbon emissions of eastern provinces in China are highly correlated, while those of central and western provinces are less correlated. Third, the eastern provinces belong to the two-way spillover or net benefit block, the central regions belong to the broker block, and the western provinces belong to the net spillover block. This indicates that the transportation carbon emissions in the western regions are flowing to the eastern and central regions. Finally, a regression analysis using a quadratic assignment procedure (QAP) was used to explore the spatial association between provinces. We found that per capita gross domestic product (GDP) and fixed transportation investments significantly influence the association and spillover effects of the ANTCE network. The research findings provide a theoretical foundation for the development of policies that may better coordinate carbon emission mitigation in regional transportation.
机译:省交通碳排放之间的关联效应已经成为区域碳排放管理中的重要问题。这项研究探索了与区域交通碳排放量相关的关系和发展趋势。运用社会网络方法分析了交通碳排放空间关联的结构特征。从三个维度中选择了每个结构特征的指标:整体网络,节点网络和空间聚类。然后,本研究利用引力模型与中国省际数据在2007年至2016年之间建立了运输碳排放关联网络(ANTCE)。此外,采用了区块模型(一种基于运输碳排放信息的省份划分方法) )用于对跨省运输碳排放的ANTCE网络进行分组,以检查整体关联结构。有三个主要发现。首先,中国ANTCE网络的紧密程度在不断提高,其复杂性和稳健性也在逐步提高。其次,中国的ANTCE网络显示出“密集的东部和稀薄的西部”的结构特征。也就是说,中国东部省份的交通碳排放高度相关,而中部和西部省份的交通碳排放相关性较低。第三,东部省份属于双向溢出或净收益区,中部地区属于中间商区,西部省份属于净溢出区。这表明西部地区的运输碳排放正在流向东部和中部地区。最后,使用二次分配程序(QAP)进行回归分析,以探索各省之间的空间关联。我们发现人均国内生产总值(GDP)和固定交通投资显着影响ANTCE网络的关联和溢出效应。研究结果为制定政策提供了理论基础,这些政策可以更好地协调区域交通中的碳减排。

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