ArticleCarbon balance and management2026
Analyzing the carbon emission efficiency and influencing factors of China's thermal power generation sector based on super-SBM and ESTDA models.
Article in Carbon balance and management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- High-Order Interactions Reshape the Carbon Emission Efficiency Network Across Chinese Regions.Entropy (Basel, Switzerland) · 2026Article
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6 authors.
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Abstract
The progress of carbon emission reduction and the effectiveness of the energy transition in the thermal power generation industry (TPI) directly impact both the quality of the implementation of China's dual carbon goals and the broader landscape of sustainable development. To precisely analyze the core patterns of low-carbon transformation in the industry, this study overcame the limitations of existing research on the thermal power sector's carbon emission efficiency (TPCEE) indicator system. These limitations include insufficient industry adaptability, an inadequate characterization of efficiency evolution dynamics, and an insufficient representation of regional differences. It innovatively constructed a TPCEE indicator system, focusing on the spatiotemporal evolution mechanisms and influencing factors of TPCEE. An integrated research framework of "efficiency measurement, spatiotemporal analysis, influencing factor exploration" was established. In addition, based on panel data from 30 Chinese provinces covering the period 2005-2022, empirical research was conducted using the Super-SBM model, exploratory spatiotemporal data analysis, and the Tobit model. The findings indicated that: (1) the TPCEE showed an overall fluctuating downward trend during the period of 2005-2022, and high-TPCEE areas were located primarily in North China and coastal provinces, while low-TPCEE regions were scattered in Northwest, Northeast, Central, and Southwest China. (2) Given the probability of spatiotemporal coalescence exceeding 70%, the spatial structure of the TPCEE was comparatively stable, showing distinct path dependence. (3) At the national level, the industrial structure, power generation mix, energy intensity, and degree of government intervention contributed to overall efficiency improvements. From a regional perspective, the impact of these factors on the TPCEE exhibited significant regional heterogeneity. The government may use the results as a foundation for building regional energy-saving and emission-reduction plans, as well as to encourage low-carbon transition and sustainable development in the Chinese TPI.
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