The carbon reduction potential by improving technical efficiency from energy sources to final services in China: An extended Kaya identity analysis

被引：40
作者：
Lin, Yuancheng [1 ,2 ]
Ma, Linwei [1 ,2 ]
Li, Zheng [1 ]
Ni, Weidou [1 ]
机构：
[1] Tsinghua Univ, Tsinghua BP Clean Energy Res & Educ Ctr, Dept Energy & Power Engn, State Key Lab Power Syst, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Tsinghua Rio Tinto Joint Res Ctr Resources, Int Joint Lab Low Carbon Clean Energy Innovat, Lab Low Carbon Energy, Beijing 100084, Peoples R China
来源：
ENERGY | 2023年 / 263卷
基金：
中国国家自然科学基金;
关键词：
Energy efficiency improvement; Carbon neutrality; Energy system; Kaya identity; Passive system; Sankey diagram; INDEX DECOMPOSITION ANALYSIS; LMDI DECOMPOSITION; CO2; EMISSION; EXERGY; CONSUMPTION; INDICATORS; CONSISTENT; INDUSTRY; PERFECT; DEMAND;
D O I：
10.1016/j.energy.2022.125963
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
Improving energy efficiency is one of the most reliable ways toward carbon neutrality. Most previous studies have focused on how to reduce energy intensity; however, it is not enough to provide an overview of how many carbon emissions can be reduced by technical efficiency improvements underlying energy systems. To fill this gap, this study extended the common Kaya identity to systematically evaluate the carbon reduction potential from technical efficiency improvements of various technical conversion components within the energy system at a granular level. The extended Kaya identity includes technical efficiency factors of electricity efficiency, con-version efficiency, and passive efficiency. It provides a comprehensive framework to evaluate current perfor-mance, historical contributions, and future potential of technical efficiency improvements. The case of China reveals that: Currently, only around 5% of energy sources were delivered to final services. By improving tech-nical efficiency to high levels, 59% carbon reduction can be achieved during the future energy transition, even when the economy is still growing. In the past, electricity efficiency and conversion efficiency have significantly reduced carbon emissions. Future policymakers should pay more attention to passive systems to provide more final services, such as improved room insulation, streamlined vehicle designs, and smart energy management.
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页数：14
相关论文
共 71 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]   Index decomposition analysis for comparing emission scenarios: Applications and challenges [J].
Ang, B. W. ;
Goh, Tian .
ENERGY ECONOMICS, 2019, 83 :74-87
[3]   LMDI decomposition approach: A guide for implementation [J].
Ang, B. W. .
ENERGY POLICY, 2015, 86 :233-238
[4]   The LMDI approach to decomposition analysis: a practical guide [J].
Ang, BW .
ENERGY POLICY, 2005, 33 (07) :867-871
[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]   Perfect decomposition techniques in energy and environmental analysis [J].
Ang, BW ;
Liu, FL ;
Chew, EP .
ENERGY POLICY, 2003, 31 (14) :1561-1566
[8]   Factorizing changes in energy and environmental indicators through decomposition [J].
Ang, BW ;
Zhang, FQ ;
Choi, KH .
ENERGY, 1998, 23 (06) :489-495
[9]   A survey of index decomposition analysis in energy and environmental studies [J].
Ang, BW ;
Zhang, FQ .
ENERGY, 2000, 25 (12) :1149-1176
[10]   A new energy decomposition method: perfect in decomposition and consistent in aggregation [J].
Ang, BW ;
Liu, FL .
ENERGY, 2001, 26 (06) :537-548
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