The spatial-temporal evolution analysis of carbon emission of China's thermal power industry based on the three-stage SBM—DEA model

Abstract

Purpose China has proposed two-stage goals of carbon peaking by 2030 and carbon neutralization by 2060. The carbon emission reduction effect of the power industry, especially the thermal power industry, will directly affect the progress of the goal. This paper aims to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency of the thermal power industry and proposes policy suggestions for realizing China’s carbon peak and carbon neutralization goals. Design/methodology/approach This paper evaluates and compares the carbon emission efficiency of the thermal power industry in 29 provinces and regions in China from 2014 to 2019 based on the three-stage slacks-based measure (SBM) of efficiency in data envelopment analysis (DEA) model of undesired output, excluding the influence of environmental factors and random errors. Findings Empirical results show that during the sample period, the carbon emission efficiency of China’s thermal power industry shows a fluctuating upward trend, and the carbon emission efficiency varies greatly among the provincial regions. The carbon emission efficiency of the interregional thermal power industry presents a pattern of “eastern > central > western,” which is consistent with the level of regional economic development. Environmental factors such as economic level and environmental regulation level are conducive to the improvement of carbon emission efficiency of the thermal power industry, but the proportion of thermal power generation and industrial structure is the opposite. Originality/value This paper adopts the three-stage SBM–DEA model of undesired output and takes CO2 as the undesired output to reveal the spatial-temporal characteristics and influencing factors of carbon emission efficiency in China’s thermal power industry. The results provide a more comprehensive perspective for regional comparative evaluation and influencing factors of carbon emission efficiency in China’s thermal power industry.

Efficiency evaluation and redundancy analysis on low carbon economic development in Guangdong Province

“…This was supported and explained by Chen, Yi and Liu, who said that in China, regional economic development is not balanced, the structure of energy consumption varies greatly, so it is necessary to consider the environmental effects as well as statistical noise so as to more accurately assess the carbon emissions efficiency [ 12 ]. They also proposed the combination of SBM and three stage DEA models for that SBM models are widely used in the evaluation of energy environmental efficiency [ 12 , 14 , 16 – 19 ]. Moreover, according to Yu and Yuan, the traditional DEA model that used by many researchers can only process cross-section data and cannot make dynamic comparison, so it is difficult to show the dynamic change of the efficiency of low-carbon economy [ 20 ].…”

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