School of Economics and Management, North China Electric Power University, Changping, Beijing 102206, China.
School of Economics and Management, North China Electric Power University, Changping, Beijing 102206, China.
Sci Total Environ. 2022 Dec 20;853:158613. doi: 10.1016/j.scitotenv.2022.158613. Epub 2022 Sep 9.
China faces enormous pressure to reduce carbon emissions. Since the agglomeration and driving effect of urban agglomerations have continued to increase, relying on the network relationship within urban agglomerations to coordinate emission reduction becomes an effective way. This paper combines the modified Gravity model and Social Network Analysis method to measure the structure characteristics of carbon emission spatial correlation network of the seven urban agglomerations as a whole and each urban agglomeration in China, analyzes the interaction mechanism between cities and between urban agglomerations, and finally explores the influencing factors of carbon emission spatial correlation through the QAP analysis method. The results are as follows: (1) As for the overall network, overall scale was increasing, but the hierarchical structure had a certain firmness. YRD and PRD urban agglomerations were at the center of the network and received the spillover relationship of MRYR, CC, CP, and HC urban agglomerations. (2) As for the networks of urban agglomerations, the allocation of low-carbon resource elements still needed to be optimized, especially BTH urban agglomeration. Beijing, Shanghai, Nanjing, Wuxi, etc. were at the center of the network. The influencing factors and degree of carbon emission spatial correlation in each urban agglomeration were different.
中国面临着巨大的减排压力。由于城市群的集聚和驱动效应不断增强，依靠城市群内部的网络关系来协调减排成为一种有效途径。本文结合修正的引力模型和社会网络分析方法，测算了中国七大城市群及其各城市群整体的碳排放空间关联网络的结构特征，分析了城市间和城市群间的相互作用机制，最后通过 QAP 分析方法探讨了碳排放空间关联的影响因素。结果表明：（1）就整体网络而言，整体规模不断扩大，但等级结构具有一定的稳定性。长三角和珠三角城市群处于网络中心，接收京津冀、山东半岛、海峡西岸和中原城市群的溢出关系。（2）城市群内部网络方面，低碳资源要素的配置仍需优化，尤其是京津冀城市群。北京、上海、南京、无锡等城市处于网络中心，各城市群的碳排放空间关联的影响因素和程度存在差异。
