Wei Yujie, Zhao Tao, Zhang Xiaoping, Tian Qi, Zhang Fan
College of Management and Economics, Tianjin University, Tianjin, 300072, China.
Research Institute of Management Science, Business School, Hohai University, Nanjing, 211100, China.
Sci Rep. 2025 May 29;15(1):18794. doi: 10.1038/s41598-025-99021-9.
In this study, an improved gravity model and social network analysis (SNA) are applied to analysis CO emissions in China's power sector, uniquely incorporating electricity and fossil fuel trade flows. It further explores the dynamic effect of energy transition on networks using a panel model, and clarifies the provincial roles in emission abatement and resource allocation. According to the findings, significant regional heterogeneities in CO emissions from 2007 to 2022 can be observed. Coal-dependent provinces, such as Inner Mongolia and Shanxi, face high emissions and challenging transitions, while developed areas such as Beijing and Shanghai have decreased emissions through clean energy integration and enhanced power efficiency. Network analysis identifies Beijing and Jiangsu as central to resource management, empowered by robust policy and information-sharing capabilities, while most provinces demonstrate weaker coordination owing to constrained intermediary functions. In addition, the study observes that energy transitions increase network density (0.3512) and contacts (0.3545) yet decrease efficiency (- 0.1464), suggesting technical and coordinative obstacles. An increasing degree of transition strengthens interprovincial CO connections, establishing provinces experiencing more rapid transitions as critical nodes. Greater closeness centrality (0.0186) signifies shorter collaborative pathways, accelerating the transition. These findings derive practical guidance for regional power collaborations and sustainable growth, offering novel perspectives for a green transition toward carbon neutrality.
在本研究中，一种改进的引力模型和社会网络分析（SNA）被应用于分析中国电力部门的一氧化碳排放，独特地纳入了电力和化石燃料贸易流。它进一步使用面板模型探索能源转型对网络的动态影响，并阐明各省在减排和资源分配中的作用。根据研究结果，可以观察到2007年至2022年一氧化碳排放存在显著的区域异质性。依赖煤炭的省份，如内蒙古和山西，面临高排放和具有挑战性的转型，而北京和上海等发达地区通过整合清洁能源和提高电力效率实现了排放减少。网络分析确定北京和江苏在资源管理方面处于核心地位，它们拥有强大的政策和信息共享能力，而大多数省份由于中介功能受限，协调能力较弱。此外，研究观察到能源转型增加了网络密度（0.3512）和联系（0.3545），但降低了效率（-0.1464），这表明存在技术和协调障碍。转型程度的提高加强了省际一氧化碳联系，使转型较快的省份成为关键节点。更高的接近中心性（0.0186）意味着更短的协作路径，加速了转型。这些发现为区域电力合作和可持续增长提供了实际指导，为向碳中和的绿色转型提供了新的视角。
