Sectoral energy-environmental efficiency and its influencing factors in China: Based on S-U-SBM model and panel regression model

被引:32
|
作者
Xiao, Chengming [1 ]
Wang, Zhen [1 ]
Shi, Weifang [2 ]
Deng, Liangchun [3 ]
Wei, Liyuan [1 ]
Wang, Yanwen [1 ]
Peng, Sha [1 ]
机构
[1] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China
[2] Huazhong Agr Univ, Coll Resource & Environm, Wuhan 430070, Hubei, Peoples R China
[3] Ctr Environm Progress, Wuhan 430079, Hubei, Peoples R China
基金
中国国家自然科学基金;
关键词
Energy-environmental efficiency; Undesirable outputs; Super-SBM model; Panel regression; SLACKS-BASED MEASURE; DATA ENVELOPMENT ANALYSIS; UNDESIRABLE OUTPUTS; INDUSTRIAL SECTORS; EMISSIONS; PRODUCTIVITY; ECONOMIES;
D O I
10.1016/j.jclepro.2018.02.033
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Energy use is often accompanied with air emissions including SOx, NOx, CO2, etc. It is essential to consider both the energy and environmental performance of various sectors to ensure better policy making. This study considered air pollution by calculating energy-environmental efficiency (EEE) at the sectoral level. A few studies have previously applied the slack-based measure (SBM) model to multi sector EEE assessments. Despite the advantages of SBM model, potential improvements have rarely been proposed. Therefore, a super-efficiency SBM model with undesirable outputs (S-U-SBM) was used to evaluate the EEE of 31 sectors in China. The policy implications of improving EEE, in microcosmic (potential improvement) and macroscopic (influencing factors) terms, were considered. The results indicated that for all sectors there was an overall trend of increasing EEE from 1995 to 2009, except for Rent and Other Business Activities, and Health and Social Work. The average annual potential for energy saving and emission-reducing measures in all sectors was 1.396 x 10(17) J and 7.0780 x 10(7) tons, respectively. Chemicals and Chemical Materials had the highest potential to save energy and reduce emissions. A panel regression indicated that the relationship between EEE and gross output was U-shaped for all industry, but had an inverted-U shape for heavy industry. Sectoral size, technology, and the proportion of energy demand satisfied by coal significantly influenced EEE. (C) 2018 Elsevier Ltd. All rights reserved.
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页码:545 / 552
页数:8
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