|Table of Contents|

Dynamic situation combination decomposition model of urban traffic energy consumption(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2013年03期
Page:
94-100
Research Field:
交通运输规划与管理
Publishing date:

Info

Title:
Dynamic situation combination decomposition model of urban traffic energy consumption
Author(s):
SUN Qi-peng1;  JIA Shi-wei2;  ZHU Lei1;  XU Cheng1
1.School of Economics and Management, Chang'an University, Xi'an 710064, Shaanxi, China; 2.School of Sciences, Beijing University of Posts and Telecommunications, Beijing 100876, China
Keywords:
urban traffic energy consumption;  LMDI model;  dynamic situation combination;  energy consumption contribution;  motor vehicle population;  100-kilometer fuel consumption;  annual driving distance
PACS:
U491
DOI:
-
Abstract:
The existing urban traffic structure was analyzed. The motor vehicle population, 100-kilometer fuel consumption and annual driving distance were taken as influence factors, the rate of influence factor was introduced as parameter, and the dynamic situation combination decomposition model of urban traffic energy consumption was set up by using logarithmic mean Divisia index(LMDI)model. Based on the change conditions of 3 influence factors, 12 situation combination modes were designed, and the change trends of urban traffic energy consumption under different situation combination modes were analyzed. Analysis result shows that the maximum increase amount of total energy consumption is 1.749 2×106 t standard coal, the energy consumption rates of 3 influence factors are 91.79%, -9.57%, 17.78% respectively. The minimum increase amount of total energy consumption is 5.506×105 t standard coal, the energy consumption rates of 3 influence factors are 128.10%, -52.34%, 24.24% respectively. Based on the increase speed of motor vehicle population, the 12 situation combination modes can be divided into 3 schemes such as low-speed increase scheme, middle-speed increase scheme and high-speed increase scheme. The maximum increase amounts of energy consumption for 3 schemes are 8.702×105, 1.309 7×106, 1.749 2×106 t standard coal, the minimum values are 5.506×105, 9.408×105, 1.345 5×106 t standard coal. 3 tabs, 5 figs, 15 refs.

References:

[1] 黄建中.1980年代以来我国特大城市居民出行特征分析[J].城市规划学刊,2005(3):71-75. HUANG Jian-zhong. Analysis on the characteristics of resident trip in Chinese mega-cities since 1980's[J]. Urban Planning Forum, 2005(3): 71-75.(in Chinese)
[2] 张 明,穆海林.基于LMDI分解方法的中国特大城市客运能源消耗研究[J].北京大学学报:自然科学版,2010,46(3):483-486. ZHANG Ming, MU Hai-lin. Research on the change of motorized passenger transport energy consumption in selected Chinese cities based on LMDI method[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2010, 46(3): 483-486.(in Chinese)
[3] ZHANG Zhong-xiang. Decoupling China's carbon emissions increase from economic growth: an economic analysis and policy implications[J]. World Development, 2000, 28(4): 739-752.
[4] FAN Ying, LIU Lan-cui, WU Gang, et al. Change in carbon intensity in China: empirical findings from 1980-2003[J]. Ecological Economics, 2007, 62(3/4): 683-691.
[5] VINUYA F, DIFURIO F, SANDOVAL E. A decomposition analysis of CO2 emissions in the United States[J]. Applied Economics Letters, 2010, 17(10): 925-931.
[6] ANG B W, ZHANG F Q. A survey of index decomposition analysis in energy and environmental analysis[J]. Energy, 2000, 25(12): 1149-1176.
[7] ANG B W. Decomposition analysis for policy making in energy: which is the preferred method?[J]. Energy Policy, 2004, 32(9): 1131-1139.
[8] SORRELL S, LEHTONEN M, STADLETON L, et al. Decoupling of road freight energy use from economic growth in the United Kingdom[J]. Energy Policy, 2013, 41(2): 84-97.
[9] BALEZENTIS A, BALEZENTIS T, STREIMIKIENE D. The energy intensity in Lithuania during 1995-2009: a LMDI approach[J]. Energy Policy, 2011, 39(11): 7322-7334.
[10] 李 政,付 峰,高 丹.中国特大城市客运交通能源需求变化的因素分析[J].清华大学学报:自然科学版,2008,48(11):1945-1948. LI Zheng, FU Feng, GAO Dan. Decomposition analysis of motorized passenger transport energy demand changes in selected Chinese cities[J]. Journal of Tsinghua University: Science and Technology, 2008, 48(11): 1945-1948.(in Chinese)
[11] 汪宏韬.基于LMDI的上海市能源消费碳排放实证分析[J].环境与资源,2010,20(5):143-146. WANG Hong-tao. Logarithmic mean divisia index model and the carbon emission mechanism of energy sector in Shanghai[J]. Resources and Environment, 2010, 20(5): 143-146.(in Chinese)
[12] 朱松丽.北京、上海城市交通能耗和温室气体排放比较[J].城市交通,2010,8(3):58-63. ZHU Song-li. Comparison of transportation energy consumption and greenhouse gas emission between Beijing and Shanghai[J]. Urban Transport of China, 2010, 8(3): 58-63.(in Chinese)
[13] 贾顺平,毛保华,刘 爽,等.中国交通运输能源消耗水平测算与分析[J].交通运输系统工程与信息,2010,10(1):22-27. JIA Shun-ping, MAO Bao-hua, LIU Shuang, et al. Calculation and analysis of transportation energy consumption level in China[J]. Journal of Transportation Systems Engineering and Information Technology, 2010, 10(1): 22-27.(in Chinese)
[14] EOM J Y, SCHIPPER L. Trends in passenger transport energy use in South Korea[J]. Energy Policy, 2010, 38(7): 3598-3607.
[15] ANG B W. The LMDI approach to decomposition analysis: a practical guide[J]. Energy Policy, 2005, 33(7): 867-871.

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Last Update: 2013-07-30