| 中国省际碳达峰碳中和能力空间关联网络及影响因素 |
| 摘要点击 568 全文点击 29 投稿时间：2024-11-12 修订日期：2025-01-30 |
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| 中文关键词 碳达峰碳中和 空间关联网络 影响因素 二次指派程序方法（QAP） 社会网络分析（SNA） |
| 英文关键词 carbon peak and carbon neutrality spatial correlation network influencing factor quadratic assignment procedure（QAP） social network analysis（SNA） |
| DOI 10.13227/j.hjkx.20260205 |
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| 中文摘要 |
| 碳达峰碳中和是气候变化研究的关键议题之一. 构建“五碳一体”框架，测度了2010~2021年中国各省的碳达峰碳中和能力，并采用社会网络分析方法和二次指派程序方法（QAP）揭示其空间关联网络的结构特征与影响因素. 结果表明：①各省碳达峰碳中和能力稳步提升. 在能力分布上，呈现出东部最强、中部次之、西部较弱和东北最弱的格局；②碳达峰碳中和能力的提升主要依赖于资源增效减碳、经济结构脱碳和生态系统固碳；③碳达峰碳中和能力的空间关联网络结构稳定，密度和效率较高，东部省域处于核心地位，跨区域合作增强；④碳达峰碳中和能力的空间关联网络可划分为净受益、经纪人和净溢出这3种板块，各板块内部联系较少，板块间联系紧密；⑤环境规制、新质生产力、城镇化水平、绿色发明专利、数字经济、财政分权、地理邻接和文化传播显著影响碳达峰碳中和能力空间关联网络的形成和发展，而产业结构对其影响不显著. |
| 英文摘要 |
| Carbon peaking and carbon neutrality are key issues in climate change research. This study constructed a novel Five-in-One Carbon （5C） Framework to evaluate the provincial carbon peak and carbon neutrality capabilities （CPCN） in China from 2010 to 2021. Additionally， social network analysis （SNA） and quadratic assignment procedure （QAP） methods were used to reveal the structural characteristics and influencing factors of the CPCN spatial correlation network. The results indicated that： ① Provincial CPCN steadily increased over the study period. In terms of CPCN distribution， the eastern region was the strongest， followed by the central region， while the western region was weaker， and the northeastern region was the weakest. ② CPCN improvements primarily relied on enhancing resource efficiency， decarbonizing economic structure， and carbon sequestration in ecosystems. ③ The network structure of CPCN was stable with high density and efficiency， with eastern provinces occupying core positions and enhanced cross-regional cooperation. ④ The spatial correlation network of CPCN could be divided into three types of plates： net benefits， brokers， and net spillovers， characterized by limited internal connections within plates and close inter-plate correlations. ⑤ Environmental regulation， new quality productive forces， urbanization level， green innovation patents， digital economy， fiscal decentralization， geographical adjacency， and cultural dissemination significantly influenced the formation and development of the spatial correlation network of CPCN， whereas industrial structure had no significant impact. |
