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Measurement of China's green low-carbon development level and research on its spatial correlation network characteristics based on complex network theory
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Published:   2026-06-05
Publication Date:   2026-06-05
Online:   2026-06-05
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Abstract:

Against the background of China’s “dual carbon” goals, scientifically measuring the level of green and low-carbon development and revealing its spatial association characteristics are of great significance for promoting coordinated regional green transformation. Taking 30 provinces in China from 2011 to 2023 as the research sample, this study constructs a comprehensive evaluation index system for green and low-carbon development from the economic, social, and ecological dimensions. The entropy-weighted TOPSIS method is employed to measure the green and low-carbon development level of each province, while kernel density estimation is used to depict its dynamic distribution characteristics. On this basis, an interprovincial spatial association network is constructed using an improved gravity model, and social network analysis is applied to systematically examine the structural characteristics of the spatial network of green and low-carbon development from both overall and individual perspectives. The results show that: (1) During the study period, China’s overall level of green and low-carbon development exhibits a steady upward trend; (2) The kernel density curves shift rightward and become increasingly concentrated, indicating continuous improvement in green and low-carbon development and a mitigation of interprovincial differentiation; (3) The spatial association network structure of green and low-carbon development remains relatively stable, featuring a low network density yet high connectivity efficiency, and has gradually exhibited small-world characteristics; (4) Economically developed eastern provinces occupy core positions in the network over the long term, exerting strong spillover and intermediary effects, and the overall network displays a pronounced “core–periphery” structure. These findings provide empirical evidence and policy implications for optimizing regional collaborative pathways toward green and low-carbon development and for advancing the achievement of China’s “dual carbon” goals.

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Basic Information:

China Classification Code:F124.5

Citation Information:

[1]LIU Jiabao,GUO Jialin.Measurement of China's green low-carbon development level and research on its spatial correlation network characteristics based on complex network theory[J].Journal of Nantong University (Natural Science Edition)().

Fund Information:

安徽省自然科学基金面上项目(2508085MA017)

Published:  

2026-06-05

Publication Date:  

2026-06-05

Online:  

2026-06-05

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