Chinese Industrial Energy Efficiency Evaluation Considering Carbon Emissions

Cao Ming, W. Xiaoping
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引用次数: 6

Abstract

Data envelopment analysis (DEA) is effective to evaluate energy efficiency, but few studies use this technique considering carbon emissions. This paper measures Chinese industrial sector¡¯s energy efficiency considering carbon emissions based on the slack-based measure (SBM) model in1997-2008. The results show that Chinese industrial energy efficiency is relatively low, the average scores (SBM-based)fluctuated between 0.26 and 0.35, and the trend is decreasing gradually. By Comparative analysis, prove that SBM model considering undesirable outputs can better assess energy efficiency and the level of industrial low-carbon development, the last six sectors¡¯ energy efficiency are extremely low and have great potentiality for improvement.
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考虑碳排放的中国工业能源效率评价
数据包络分析(DEA)是一种有效的能源效率评价方法,但很少有研究使用该方法来考虑碳排放。本文采用基于松弛测度(slack-based measure, SBM)模型对1997-2008年考虑碳排放的中国工业部门能源效率进行了测度。结果表明:我国工业能效水平相对较低,平均得分(基于中小企业)在0.26 ~ 0.35之间波动,且呈逐渐下降趋势;通过对比分析,证明考虑不良产出的SBM模型能更好地评价能源效率和工业低碳发展水平,后6个行业的能源效率极低,有很大的提升潜力。
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