Energy intensity and energy conservation potential in China: A regional comparison perspective

被引:133
作者
Dong, Kangyin [1 ,2 ]
Sun, Renjin [1 ,3 ]
Hochman, Gal [2 ]
Li, Hui [4 ,5 ,6 ]
机构
[1] China Univ Petr, Sch Business Adm, Beijing 102249, Peoples R China
[2] Rutgers State Univ, Dept Agr Food & Resource Econ, New Brunswick, NJ 08901 USA
[3] China Univ Petr, China State Key Lab Heavy Oil Proc, Beijing 102249, Peoples R China
[4] Beijing Inst Technol, Sch Management & Econ, Beijing 100081, Peoples R China
[5] Beijing Inst Technol, Ctr Energy & Environm Policy Res, Beijing 100081, Peoples R China
[6] Beijing Key Lab Energy Econ & Environm Management, Beijing 100081, Peoples R China
关键词
Energy intensity; Energy conservation potential; Regional analysis; China; PANEL-DATA EVIDENCE; CO2; EMISSIONS; DECOMPOSITION ANALYSIS; HETEROGENEOUS PANELS; STEEL-INDUSTRY; NATURAL-GAS; URBANIZATION; CONSUMPTION; EFFICIENCY; PROVINCES;
D O I
10.1016/j.energy.2018.05.053
中图分类号
O414.1 [热力学];
学科分类号
摘要
Increasing energy demand and the associated environmental pressures have ignited the Chinese government's concerns regarding energy conservation. Using provincial-level panel data covering the period of 2000-2015, this study first identifies the drivers of energy intensity across China's regions, employing a series of econometric techniques allowing for cross-sectional dependence and slope homogeneity. Based on the estimation results and scenario analysis, this study forecasts the possible energy conservation potential at the regional level by 2030. The panel augmented mean group (AMG) estimator provides similar estimation results for the three regions: economic structure and urbanization rate are the deterministic factors increasing energy intensity, while R&D investment and relative energy price reduce it. The results of scenario analysis indicate that, under the advanced scenario, the energy conservation potential in the eastern, central, and western regions in 2030 will be 1,209.53 million tons of coal equivalent (tce), 664.23 million tce, and 774.48 million tce, respectively. At the national level, the advanced scenario can save 2,648.24 million tce of energy consumption by 2030, accounting for 43.3% of the energy demand under the business-as-usual (BAU) scenario. Finally, these findings offer several targeted policy suggestions for reducing energy intensity and promoting energy conservation potential at the national and regional levels. (C) 2018 Elsevier Ltd. All rights reserved.
引用
收藏
页码:782 / 795
页数:14
相关论文
共 59 条
[1]  
[Anonymous], 2009, SOC RES
[2]  
[Anonymous], 2016, China energy statistical yearbook (CESY)
[3]   Energy access scenarios to 2030 for the power sector in sub-Saharan Africa [J].
Bazilian, Morgan ;
Nussbaumer, Patrick ;
Rogner, Hans-Holger ;
Brew-Hammond, Abeeku ;
Foster, Vivien ;
Pachauri, Shonali ;
Williams, Eric ;
Howells, Mark ;
Niyongabo, Philippe ;
Musaba, Lawrence ;
Gallachoir, Brian O. ;
Radka, Mark ;
Kammen, Daniel M. .
UTILITIES POLICY, 2012, 20 (01) :1-16
[4]   The impact of urbanization on energy intensity: Panel data evidence considering cross-sectional dependence and heterogeneity [J].
Bilgili, Faik ;
Kocak, Emrah ;
Bulut, Umit ;
Kuloglu, Ayhan .
ENERGY, 2017, 133 :242-256
[5]   A parametric approach to the estimation of cointegration vectors in panel data [J].
Breitung, J .
ECONOMETRIC REVIEWS, 2005, 24 (02) :151-173
[6]   THE LAGRANGE MULTIPLIER TEST AND ITS APPLICATIONS TO MODEL-SPECIFICATION IN ECONOMETRICS [J].
BREUSCH, TS ;
PAGAN, AR .
REVIEW OF ECONOMIC STUDIES, 1980, 47 (01) :239-253
[7]  
CPSY, 2016, CHIN PROV STAT YB
[8]   A review of China's energy consumption structure and outlook based on a long-range energy alternatives modeling tool [J].
Dong, Kang-Yin ;
Sun, Ren-Jin ;
Li, Hui ;
Jiang, Hong-Dian .
PETROLEUM SCIENCE, 2017, 14 (01) :214-227
[9]   Do natural gas and renewable energy consumption lead to less CO2 emission? Empirical evidence from a panel of BRICS countries [J].
Dong, Kangyin ;
Sun, Renjin ;
Hochman, Gal .
ENERGY, 2017, 141 :1466-1478
[10]   Impact of natural gas consumption on CO2 emissions: Panel data evidence from China's provinces [J].
Dong, Kangyin ;
Sun, Renjin ;
Hochman, Gal ;
Zeng, Xiangang ;
Li, Hui ;
Jiang, Hongdian .
JOURNAL OF CLEANER PRODUCTION, 2017, 162 :400-410