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

• Main Authors: Fei Ma, Yixuan Wang, Kum Fai Yuen, Wenlin Wang, Xiaodan Li, Yuan Liang
• Format: Article
• Language: English
• Published: MDPI AG 2019-06-01
• Series: International Journal of Environmental Research and Public Health
• Subjects: transportation carbon emission; gravity model; social network; QAP regression analysis
• Online Access: https://www.mdpi.com/1660-4601/16/12/2154

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 (<i>ANTCE</i>) using a gravity model with China&#8217;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 <i>ANTCE</i> network of inter-provincial transportation carbon emissions to examine the overall association structure. There were three key findings. First, the tightness of China&#8217;s <i>ANTCE</i> network is growing, and its complexity and robustness are gradually increasing. Second, China&#8217;s <i>ANTCE</i> network shows a structural characteristic of &#8220;dense east and thin west.&#8221; 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 <i>ANTCE</i> network. The research findings provide a theoretical foundation for the development of policies that may better coordinate carbon emission mitigation in regional transportation.