Potential energy conservation and CO2 emissions reduction related to China's road transportation

被引:58
作者
Lu, Quanying [1 ]
Chai, Jian [2 ,5 ]
Wang, Shouyang [1 ,3 ]
Zhang, Zhe George [4 ,5 ]
Sun, Xiaojie Christine [6 ]
机构
[1] Univ Chinese Acad Sci, Sch Econ & Management, 80 Zhongguancun East Rd, Beijing 100190, Peoples R China
[2] Xidian Univ, Sch Econ & Management, 266 Xinglong Sect Xifeng Rd, Xian 710126, Shaanxi, Peoples R China
[3] Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Beijing 100190, Peoples R China
[4] Simon Fraser Univ, Beedie Sch Business, Burnaby, BC, Canada
[5] Western Washington Univ, Coll Business & Econ, Dept Decis Sci, Washington, DC USA
[6] Calif State Univ Los Angeles, Sch Business & Econ, Los Angeles, CA 90032 USA
基金
中国国家自然科学基金;
关键词
BSEM; Energy conservation; Emissions reduction; Path analysis; Road transportation; Scenario analysis; FREIGHT TRANSPORTATION; PASSENGER TRANSPORT; EMPIRICAL-EVIDENCE; NEURAL-NETWORK; CLIMATE-CHANGE; CONSUMPTION; EFFICIENCY; DEMAND; SECTOR; MODEL;
D O I
10.1016/j.jclepro.2019.118892
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
As the largest mode in China's transportation industry, road transportation is the vital part to achieve a goal of congestion and emissions reduction. We analyzed the future development of energy consumption and CO2 emissions associated with road transportation. First, a Bayesian structural equation model (BSEM) was developed to explore the internal relations of total demand, structure, and technology as factors impacting the road transportation system. Second, the core influence factors were screened using path analysis. Finally, a scenario analysis model was established to analyze potential energy conservation and CO2 emissions reduction under different conditions. The results show that total demand has the largest direct effect among all influencing factors; however, if we consider indirect influences arising from interactions between latent variables, then traffic structure becomes the most important factor with a combined impact coefficient of -1.63. The respective potential energy conservation and CO2 emissions reduction of road transportation are projected to be approximately 65,237.61 ktoe (37.33% rate) and 41 million tons (8.38%) during the 13th Five-Year Plan period (2016-2020) and reach approximately 91,923.63 ktoe (51.67%) and 68 million tons (12.66%) by 2025. Our results imply that to achieve China's energy conservation and emissions reduction goals, quantity and structure should be emphasized in the short term, whereas technology is critical over the long term. (C) 2019 Elsevier Ltd. All rights reserved.
引用
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页数:14
相关论文
共 66 条
[1]   Energy intensity in road freight transport of heavy goods vehicles in Spain [J].
Andres, Lidia ;
Padilla, Emilio .
ENERGY POLICY, 2015, 85 :309-321
[2]   Accounting frameworks for tracking energy efficiency trends [J].
Ang, B. W. ;
Mu, A. R. ;
Zhou, P. .
ENERGY ECONOMICS, 2010, 32 (05) :1209-1219
[3]  
[Anonymous], 2015, CHINA CCEAN STAT YB
[4]   Bayesian factor analysis for multilevel binary observations [J].
Ansari, A ;
Jedidi, K .
PSYCHOMETRIKA, 2000, 65 (04) :475-496
[5]  
Cai B.-F., 2011, Energy China, V33, P26, DOI 10.3969/j.issn.1003-2355.2011.04.006
[6]  
Chai J, 2015, CHINA MANAGEMENT SCI, V23, P386
[7]   Fuel efficiency and emission in China's road transport sector: Induced effect and rebound effect [J].
Chai, Jian ;
Yang, Ying ;
Wang, Shouyang ;
Lai, Kin Keung .
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2016, 112 :188-197
[8]   Analysis of road transportation energy consumption demand in China [J].
Chai, Jian ;
Lu, Quan-Ying ;
Wang, Shou-Yang ;
Lai, Kin Keung .
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2016, 48 :112-124
[9]   Aviation fuel demand development in China [J].
Chai, Jian ;
Zhang, Zhong-Yu ;
Wang, Shou-Yang ;
Lai, Kin Keung ;
Liu, John .
ENERGY ECONOMICS, 2014, 46 :224-235
[10]   Transport and climate change: a review [J].
Chapman, Lee .
JOURNAL OF TRANSPORT GEOGRAPHY, 2007, 15 (05) :354-367