4.8 Article

Air emissions perspective on energy efficiency: An empirical analysis of China's coastal areas

期刊

APPLIED ENERGY
卷 185, 期 -, 页码 604-614

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2016.10.127

关键词

Energy efficiency; Data envelopment analysis; China's coastal areas; Air emissions

资金

  1. National Natural Science Foundation of China [71521002, 71402103]
  2. National Key RD Program [2016YFA0602603]
  3. Natural Science Foundation of Guangdong Province [2015A030313556]
  4. MOE Youth Foundation Project of Humanities and Social Sciences at Universities in China [13YJC630123]
  5. China Postdoctoral Science Foundation [2015M580053, 2016T90042]

向作者/读者索取更多资源

Improving energy efficiency has been recognized as the most effective way to reduce the greenhouse effect and achieve sustainable development. From the perspective of air emissions, this paper adopts data envelopment analysis approach to evaluate the energy efficiency in China's coastal areas over the period of 2000-2012. Carbon dioxide, sulfur dioxide and nitrogen oxide are treated as undesirable outputs of energy consumptions. The proposed global Epsilon-based measure is used to estimate the static energy efficiency with an annual cross-section of data. The weights of the three undesirable outputs are determined according to their treatment costs. A global Malmquist-Luenberger productivity index based on directional distance function is employed to dynamically evaluate the energy efficiency. The results indicate the following in China's coastal areas: (1) the level of economic development is positively related to energy efficiency scores; (2) energy efficiency scores decrease when considering undesirable outputs except Beijing and Hainan; (3) the Circum-Bohai Sea Economic Region greatly improves energy efficiency and has great potential of air emission; (4) the annual growth rate of Malmquist-Luenberger productivity index change is overestimated; (5) energy efficiency improvement is mainly driven by technological improvement, and scale efficiency and management level are the main obstacles. (C) 2016 Elsevier Ltd. All rights reserved.

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