Qin Chaoyong, Liang Yizheng, Cao Yun
School of Business, Guangxi University, Nanning, 530004, China.
Key Laboratory of Interdisciplinary Science of Statistics and Management (Guangxi University), Education Department of Guangxi, Nanning, 530004, China.
Sci Rep. 2024 Aug 14;14(1):18873. doi: 10.1038/s41598-024-68989-1.
The power industry's low carbon transition is pivotal for achieving carbon reduction and sustainable development. This study uses the super epsilon-based measurement (Super-EBM) model and the Malmquist index to evaluate the power industry's low carbon transition efficiency using data from 30 provinces in China from 2010 to 2020, and utilizes the Tobit model to comprehensively analyze the factors affecting the low carbon transition of power industry. In addition, this paper examines the spatial differences in the power industry's low carbon transition efficiency as well as its distributional characteristics and dynamic evolutionary patterns. Conclusion is drawn as follows this paper analyzes the regional differences, spatial distribution characteristics and dynamic evolutionary trends of the power industry's low carbon transition. The main conclusions are as follows: (1) The power industry's low carbon transition efficiency in China shows an uptrend, with the western China region having the highest overall level of efficiency, greater fluctuations in the central China region, and more stability in the eastern China region, technological progress is a central factor in increasing total factor productivity, the efficiency of the power industry's low carbon transition is positively influenced by the electricity prices, and negatively influenced by the energy structure, environmental regulations and economic structure; (2) the Intraregional differences and hypervariable density are the main reasons sources of the overall differences in the efficiency of the power industry's low carbon transition; Intraregional differences in the eastern, central, and western China regions are decreasing year by year, but the efficiency of the power industry's low carbon transition in the western China region is still distributed in a multipolar way; (3) The dynamic evolutionary trends of the efficiency distribution of the low carbon transition in power industry is influenced by the type of spatial lag in the neighboring area. Where areas with low efficiency makes it difficult to achieve short-term leapfrog development, and areas with a cluster of high-efficiency provinces are prone to "Siphon Effect". The findings provide a theoretical basis for promoting the efficiency of the power industry's low carbon transition and coordinating the strategic adjustment of economic and environmental green development.
电力行业的低碳转型对于实现碳减排和可持续发展至关重要。本研究运用基于超效率的测度（Super-EBM）模型和Malmquist指数，利用2010年至2020年中国30个省份的数据评估电力行业的低碳转型效率，并运用Tobit模型全面分析影响电力行业低碳转型的因素。此外，本文考察了电力行业低碳转型效率的空间差异及其分布特征和动态演化模式。研究得出以下结论：本文分析了电力行业低碳转型的区域差异、空间分布特征和动态演化趋势。主要结论如下：（1）中国电力行业的低碳转型效率呈上升趋势，西部地区总体效率水平最高，中部地区波动较大，东部地区较为稳定，技术进步是提高全要素生产率的核心因素，电力行业低碳转型效率受电价正向影响，受能源结构、环境规制和经济结构负向影响；（2）区域内差异和超变密度是电力行业低碳转型效率总体差异的主要来源；中国东部、中部和西部地区的区域内差异逐年减小，但西部地区电力行业低碳转型效率仍呈多极分布；（3）电力行业低碳转型效率分布的动态演化趋势受邻域空间滞后类型的影响。效率低的地区难以实现短期跨越式发展，高效省份集聚的地区容易出现“虹吸效应”。研究结果为提高电力行业低碳转型效率、协调经济与环境绿色发展的战略调整提供了理论依据。
