Contributions to sector-level carbon intensity change: An integrated decomposition analysis

被引:169
作者
Wang, Qunwei [1 ]
Hang, Ye [1 ,2 ]
Su, Bin [2 ]
Zhou, Peng [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Econ & Management, 29 Jiangjun Ave, Nanjing 211106, Jiangsu, Peoples R China
[2] Natl Univ Singapore, Energy Studies Inst, 29 Heng Mui Keng Terrace, Singapore 119620, Singapore
基金
中国国家自然科学基金;
关键词
Sector-level carbon intensity; Production-theoretical decomposition analysis; Index decomposition method; Attribution analysis; China; DIVISIA INDEX DECOMPOSITION; INPUT-OUTPUT-ANALYSIS; CO2 EMISSION TRENDS; ENERGY INTENSITY; DRIVING FORCES; ELECTRICITY-GENERATION; DIOXIDE EMISSIONS; CHINA; PRODUCTIVITY; ATTRIBUTION;
D O I
10.1016/j.eneco.2017.12.014
中图分类号
F [经济];
学科分类号
02 ;
摘要
Exploring the factors driving sector-level carbon intensity change is important to inform targeted emission reduction policies. This paper proposes an integrated decomposition approach, combining production-theoretical decomposition analysis (PDA), index decomposition analysis (IDA) and attribution analysis (AA). The proposed approach can decompose sector-level carbon intensity change into nine driving factors, including two new pre-defined factors (i.e. the potential regional output structure effect and the output gap effect). This provides more detailed information about the influence of production technology related components, i.e. technical efficiency and technological change, and the contribution of each region to the individual driving factor. Industrial sectors across 30 provinces in China are used to demonstrate the integrated decomposition approach. The decomposition and attribution results show that the desirable output technological change effect is the dominant factor in decreasing industrial carbon intensity, of which Hebei, Shandong, Jiangsu, Liaoning and Henan are the main contributors. The potential energy intensity effect reduces industrial carbon intensity remarkably as well, mainly due to Henan, Liaoning, Shandong, Hunan and Inner Mongolia. Provinces are classifies into four performance groups based on the attribution results. Targeted industrial carbon intensity reduction policies should be implemented in different groups of provinces. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码:12 / 25
页数:14
相关论文
共 69 条
[1]   Handling zero values in the logarithmic mean Divisia index decomposition approach [J].
Ang, B. W. ;
Liu, Na .
ENERGY POLICY, 2007, 35 (01) :238-246
[2]   A spatial-temporal decomposition approach to performance assessment in energy and emissions [J].
Ang, B. W. ;
Su, Bin ;
Wang, H. .
ENERGY ECONOMICS, 2016, 60 :112-121
[3]   LMDI decomposition approach: A guide for implementation [J].
Ang, B. W. .
ENERGY POLICY, 2015, 86 :233-238
[4]   Multi-country comparisons of energy performance: The index decomposition analysis approach [J].
Ang, B. W. ;
Xu, X. Y. ;
Su, Bin .
ENERGY ECONOMICS, 2015, 47 :68-76
[5]  
Ang BW, 1997, ENERGY J, V18, P59
[6]   Decomposition analysis for policymaking in energy: which is the preferred method? [J].
Ang, BW .
ENERGY POLICY, 2004, 32 (09) :1131-1139
[7]   Factorizing changes in energy and environmental indicators through decomposition [J].
Ang, BW ;
Zhang, FQ ;
Choi, KH .
ENERGY, 1998, 23 (06) :489-495
[8]   A survey of index decomposition analysis in energy and environmental studies [J].
Ang, BW ;
Zhang, FQ .
ENERGY, 2000, 25 (12) :1149-1176
[9]  
[Anonymous], 2011, MOD EC SCI
[10]  
[Anonymous], J CLEAN PROD