Zheng Yandi, Ji Keke
School of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, 430070, China.
China Automotive Technology and Research Center Co., Ltd., Tianjin, 30030, China.
Environ Sci Pollut Res Int. 2025 Apr;32(20):12372-12391. doi: 10.1007/s11356-025-36433-0. Epub 2025 Apr 29.
The scientific determination of the carbon emission reduction potential (CERP) of the transportation industry, as well as the clarification of its spatial correlation structure and its influencing factors, is of great significance to the promotion of transportation carbon emission reduction management. This paper measures the CERP of the transportation industry in 30 provinces in China from 2010 to 2019, taking into account the principles of efficiency and equity. It also explores the spatial correlation network characteristics and influencing factors of the CERP by using social network analysis method and quadratic assignment procedure model. The results show that: (1) the CERP of China's transportation industry is generally high, with an overall pattern of "high in the west and low in the east". (2) The CERP of China's provincial transportation exhibits a complex, multi-layered network correlation, with a hierarchical gradient characterized by "dense in the east and sparse in the west". The hierarchical gradient is characterized by "dense in the east and sparse in the west". The eastern region is at the core, while the western region is at the periphery. (3) Beijing-Tianjin-Hebei and the northeast are "net beneficiaries", while most of the transportation hub provinces in the Yangtze River Delta, South China, and Southwest China are "bidirectional spillover", and most of the inland or remote regions are "net beneficiaries. (4) Spatial adjacency, differences in provincial distances, differences in levels of economic development, differences in transportation structures, differences in levels of informatization, and differences in levels of environmental regulation drive the formation and evolution of spatially connected network structures.
科学测定交通运输业的碳排放 reduction 潜力（CERP），以及厘清其空间关联结构及其影响因素，对于推动交通运输碳排放 reduction 管理具有重要意义。本文基于效率与公平原则，测度了 2010 - 2019 年中国 30 个省份交通运输业的 CERP。同时，运用社会网络分析方法和二次指派程序模型，探究了 CERP 的空间关联网络特征及影响因素。结果表明：（1）中国交通运输业的 CERP 总体较高，呈现“西部高、东部低”的总体格局。（2）中国省级交通运输业的 CERP 呈现出复杂、多层的网络关联，具有“东部密集、西部稀疏”的层级梯度特征。东部地区处于核心地位，而西部地区处于边缘地位。（3）京津冀和东北地区为“净受益区”，而长三角、华南和西南地区的多数交通枢纽省份为“双向溢出”，多数内陆或偏远地区为“净受益区”。（4）空间邻接性、省际距离差异、经济发展水平差异、交通结构差异、信息化水平差异以及环境规制水平差异推动了空间连通网络结构的形成与演化。
