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<p>The transition to low-carbon energy consumption is vital for the sustainable development of the energy economy. This study analyzes the evolution of the energy structure in 30 Chinese provinces from 2010 to 2022. First, based on the theory of “dual substitution in energy structure,” the low-carbon transition level of energy consumption structure (LCTECS) is measured. Second, GIS spatial analysis techniques are employed to explore the spatial evolution characteristics of LCTECS. Finally, the geographic detector model (GDM) is used for driver factor analysis. The results show that: (1) China’s LCTECS has steadily but slowly increased, with only the eastern region surpassing the national average. (2) LCTECS exhibits positive spatial autocorrelation, forming a stable pattern of “high-high” clustering in the east and “low-low” clustering in the northeast and northwest, with a clear “club effect.” (3) The expansion direction of LCTECS along the “northeast-southwest” axis has strengthened, while the centroid trajectory has shifted from northwest to southeast, with an increasing disparity in development between coastal and inland, indicating a trend of growing regional divergence and spatial polarization. (4) The spatial evolution is significantly influenced by factors such as energy consumption intensity, economic development level, and population density, with these factors generally exhibiting nonlinear or dual-factor interactive effects.</p>

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Research on the evolution of energy structure in China’s Provincial regions based on GIS spatial analysis and the geographic detector model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月11日

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  • Weiwei Fang,
  • Fanlong Zeng

摘要

The transition to low-carbon energy consumption is vital for the sustainable development of the energy economy. This study analyzes the evolution of the energy structure in 30 Chinese provinces from 2010 to 2022. First, based on the theory of “dual substitution in energy structure,” the low-carbon transition level of energy consumption structure (LCTECS) is measured. Second, GIS spatial analysis techniques are employed to explore the spatial evolution characteristics of LCTECS. Finally, the geographic detector model (GDM) is used for driver factor analysis. The results show that: (1) China’s LCTECS has steadily but slowly increased, with only the eastern region surpassing the national average. (2) LCTECS exhibits positive spatial autocorrelation, forming a stable pattern of “high-high” clustering in the east and “low-low” clustering in the northeast and northwest, with a clear “club effect.” (3) The expansion direction of LCTECS along the “northeast-southwest” axis has strengthened, while the centroid trajectory has shifted from northwest to southeast, with an increasing disparity in development between coastal and inland, indicating a trend of growing regional divergence and spatial polarization. (4) The spatial evolution is significantly influenced by factors such as energy consumption intensity, economic development level, and population density, with these factors generally exhibiting nonlinear or dual-factor interactive effects.