Carbon emission efficiency of thermal power in different regions of China and spatial correlations

Jin Zhu, Huaping Sun (), Dequn Zhou, Lin Peng and Chuanwang Sun
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Jin Zhu: Nanjing University of Aeronautics and Astronautics
Huaping Sun: Jiangsu University
Dequn Zhou: Nanjing University of Aeronautics and Astronautics
Lin Peng: Jiangsu University

Mitigation and Adaptation Strategies for Global Change, 2020, vol. 25, issue 7, No 3, 1242 pages

Abstract: Abstract In China, the power industry contributes significantly to carbon emissions, reducing carbon emissions in this industry is conducive to China's adaptation and mitigation of climate change. Researches on green and low-carbon power have attracted increasing attention. In this paper, we analyze and compare the carbon emissions from thermal power sector in 30 Chinese provinces, divided into three main regions. Based on the panel data over the period 2002–2016, we use a slacks-based measurement (SBM) model to measure the carbon emission efficiency of China’s power sector. The results show that the carbon emission efficiency of the system is relatively low, with marked differences among regions. Based on the Moran’s I, we further found spatial heterogeneity in carbon emission efficiency of provincial power sector. Policies for adaptation and mitigation of climate change should have regional differences. Interregional collaboration also plays a key role in adapting to and mitigating climate change. For China, it is an important issue to develop clean coal-fired power generation and vigorously develop renewable energy. From a global perspective, energy transformation needs to be continuously promoted. Promoting low-carbon transformation of global energy system requires deep technical cooperation and synergy. Global mitigation strategy should focus on the orientation of structural reform and constantly optimize the energy structure.

Keywords: Carbon emission efficiency; Thermal power sector; SBM model; Spatial correlation (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s11027-019-09901-5

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