Decomposition and trend analyses of energy consumption and CO2 emission from the road traffic system in Taiwan

博士 === 國立成功大學 === 環境工程學系碩博士班 === 96 === In this study, the decomposition analysis was adopted to explore the relative impacts of different factors on the aggregate energy consumption from the road transportation system and the private vehicles in Taiwan from 1990 to 2005. Also, the results from this...

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Bibliographic Details
Main Authors: I-Jing Lu, 盧怡靜
Other Authors: Sue J. Lin
Format: Others
Language:en_US
Published: 2008
Online Access:http://ndltd.ncl.edu.tw/handle/76835748710908388779
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Summary:博士 === 國立成功大學 === 環境工程學系碩博士班 === 96 === In this study, the decomposition analysis was adopted to explore the relative impacts of different factors on the aggregate energy consumption from the road transportation system and the private vehicles in Taiwan from 1990 to 2005. Also, the results from this method were then compared with the grey relation analysis (GRA). System dynamics model was constructed as a case study for passenger cars to simulate how vehicular operation, vehicular energy consumption and energy-related CO2 variations will be affected by the demographics, fuel price and economical growth. In order to project the future trends for the fleet size, traffic energy consumption and CO2 emissions from the road transportation system, the grey forecasting model, GM(1,1), was developed. Finally, the factors for the traffic CO2 emission increase in Germany, Japan, South Korea and Taiwan were examined to be helpful references for transportation-related CO2 emission reduction and enhancing vehicular energy efficiency in Taiwan. The major findings of this study are summarized as follows: 1.According to the results of decomposition methodology, the rapid growths of economy and vehicle kilometers per unit vehicle were two key factors for the rise of vehicular fuel demand, whereas the energy intensity had a considerable positive effect on energy conservation. As for the road transportation system, the index of economically active population intensity was another important component for energy decrease. The comparisons between passenger cars and motorcycles suggested that the increasing of vehicular structure share had a positive effect on the increase of fuel demand. 2.Results from the grey relation analysis revealed that the increase in vehicular fuel consumption can be attributed to the fleet size and growth of economy. The factor of GEK exhibited a positive grey relation as the length of vehicle kilometers grew higher than its energy requirement. In comparison to the other factors, the influence of the fuel price and economically active population were obscure since the growth patterns of the compared series and the reference series were inconsistent. 3.According to the simulation of the system dynamics model, the amount of passenger cars in 2025 will be 8.0 million vehicles, which is higher than that of in 1990 by 5.7 million vehicles. Accompanying the growth of fleet size, the vehicular fuel consumption and energy-related CO2 emission increase by 14.2 million kiloliters and 30.8 million metric tons during 1990-2025. The scenario analysis indicates that the restriction on the use of private vehicles has relatively notable effect on energy conservation and emission decrease and follows by the impact of higher fuel price, 3% of LPG vehicles and fuel tax. 4.Results by grey forecasting model showed that the energy demand and CO2 emitted by the road transportation system continued to rise at the annual growth rate of 3.25% and 3.23% over the next 18 years, respectively. Besides, the simulation of different economic development scenario were analyzed because of the economic driving force is an important factor for the increase of transportation demand and vehicular fuel consumption. It revealed that the upper and lower bound values of the number of motor vehicles in 2025 varies from 30.2 to 36.3 million vehicles, with the traffic energy requirement lies between 25.8 million kiloliters to 31.0 million kiloliters. The corresponding emission of CO2 will be 61.1 and 73.4 million metric tons in the low and high scenario profile, respectively. 5.Decomposition analysis in each countries suggested that the rapid growths of economy and vehicle ownership were two major factors for the rapid increase of traffic CO2 emission, whereas the index of population intensity contributed significantly to emission decrease. Also, the vehicular fuel consumption per ten thousand vehicle factor contributed a considerable emission decrease in all countries, except Taiwan.