| 中国省际电力碳排放关联网络结构及影响因素分析 |
| 摘要点击 368 全文点击 23 投稿时间：2025-07-01 修订日期：2025-10-31 |
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| 中文关键词 电力碳排放 复杂网络 块模型 社会网络分析 二次指派程序（QAP） |
| 英文关键词 power carbon emissions complex network block model social network analysis quadratic assignment procedure（QAP） |
| DOI 10.13227/j.hjkx.202507015 |
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| 中文摘要 |
| 探究中国电力行业省际碳排放空间关联网络及其影响因素，有助于识别区域碳排放角色，推动差异化与协同化的电力碳减排政策制定. 采用网络分析法构建了2007~2022年中国省际电力碳排放关联网络，并结合社会网络分析法和二次指派程序对网络结构特征及其影响因素进行分析. 结果表明：①网络节点特征呈现“集中生产-分散消费”的基本结构，并呈现出规模扩张、格局固化与节点分化加剧并存的演化趋势，具有典型的路径依赖性与“马太效应”. ②网络空间结构呈现出核心-边缘结构强化、空间布局趋向“两横三纵”轴带式结构以及网络连接由“多点连接”向“主干输送”转变的趋势. ③从板块结构演化来看，在特高压工程驱动下，四大板块功能分化显著，北方煤电集团成为核心碳外溢源，板块间交互关系趋于复杂. ④网络的驱动因素方面，特高压工程显著强化了跨省电力碳排放的空间关联；区域邻近性仍具基础作用，但随着远距离输电能力提升，物理距离与空间相邻的重要性明显减弱；产业规模差异影响呈阶段性波动，人均用电量的正向效应持续增强；清洁能源对煤电的替代减排效应已不断增强；环境规制对跨区域电力碳排放影响有限. |
| 英文摘要 |
| Exploring the inter-provincial spatial association network of carbon emissions in China's power sector and its driving factors helps to identify regional carbon emission roles and promote differentiated and coordinated policies for power-related carbon reduction. This study constructs China's inter-provincial power carbon emission networks from 2007 to 2022 using network analysis and further applies social network analysis and the quadratic assignment procedure to examine network structural features and influencing factors. The results show that： ① Network nodes exhibited a “concentrated production-dispersed consumption” pattern， with simultaneous trends of scale expansion， structural solidification， and intensified node differentiation， reflecting typical path dependence and the “Matthew effect.” ② The spatial structure revealed a strengthening core-periphery configuration， an axial layout of “two horizontal and three vertical” transmission corridors， and a shift from “multi-point connections” to “trunk transmission.” ③ Four major blocks could be identified： Block Ⅰ， dominated by consumption-oriented provinces， acted as a carbon sink； Block Ⅱ， centered on Shaanxi， Xinjiang， and Inner Mongolia， consistently functioned as a major carbon source； Block Ⅲ， including Jiangsu， Shanghai， and Zhejiang， was mainly a net receiver； and Block Ⅳ， comprising central and southwestern provinces， formed a relatively independent subsystem. Overall， ultra-high-voltage （UHV） projects weakened intra-block clustering while strengthening inter-block connections， with the northern coal-based power cluster gradually emerging as the national core of carbon outflow. ④ Regarding driving factors， UHV projects significantly enhanced spatial associations of inter-provincial power carbon emissions； regional proximity remained fundamental， but its importance declined with the rise of long-distance transmission； the impact of industrial scale differences fluctuated over time， while the positive effect of per capita electricity consumption continued to strengthen； clean energy substitution has shown an increasing mitigation effect on coal power； and environmental regulation exerted limited influence on cross-regional power carbon emissions. After the launch of the national carbon trading market， the influence mechanism was mainly characterized by the strengthened substitution effect of clean energy and the reappearance of industrial scale disparities， while other factors remained relatively stable. |
