Analysis Of Factors Affecting China's Transportation Energy Consumption And Potential For Energy Conservation And Emission Reduction

With the acceleration of industrialization and urbanization in China,the energy consumption of transportation in China has increased rapidly and the proportion to total energy consumption has also increased significantly.Traffic energy consumption has been ranked second in energy consumption for various industries for many years,second only to industrial use,the total energy consumption of 10%-20%.From the perspective of energy consumption structure,the main consumption source is oil,accounting for more than 90%of the traffic total energy consumption,and the average annual growth rate is about 10%.Transportation has become China's key area of energy-saving emission reduction.Therefore,it is very important to analyze and extract the main factors that influence the energy consumption of transportation industry,forecast the energy consumption of the transportation industry and explore the way of energy saving,which is of great significance for promoting transportation energy saving,energy utilization and energy security.Based on the analysis of traffic energy consumption at home and abroad and the current development situation of transportation,firstly,Bayesian structural equation model(BSEM)is constructed to explore the mechanism of the influence factors on traffic energy consumption.MCMC-Gibbs method was used to expand the sample data from 1990 to 2013.The Bayesian method was used to explore the interaction between latent variables and traffic energy consumption,including the total economic activity,technological progress and transportation structure.Secondly,the path-analysis method was used to extract the main influence factors of traffic energy consumption.Then,based on the extracted core factors,the VAR model is established to study the dynamic time delay relationship between energy consumption and the main factors,and to analyze the impulse response of endogenous variables to traffic energy consumption.Then,Gibbs sampling is used to construct the BVAR model based on Bayesian estimation to predict the traffic energy consumption in China from 2016 to 2020,and the model predictions are good.Finally,the energy consumption and carbon emission of China's transportation are forecasted based on scenario analysis,and the potential of energy saving and emission reduction is estimated.The conclusions of this paper include:(1)The Bayesian Structural Equation Model(BSEM)measures the direct and combined effects of various factors.It is found that the transportation structure is the most important factor affecting the transportation energy consumption when considering the indirect effects caused by the interaction between the latent variables of the factors,followed by technological progress,and finally the total economic activity.(2)The results of path analysis show that the main factors influencing the energy consumption of transportation are the total turnover of transportation,the per capita disposable income of urban households,the energy consumption per unit turnover,the proportion of investment in fixed assets in the transportation industry,Turnover accounted for 5 variables.The transportation volume is the main factor leading to the increase of transportation energy consumption.The per capita disposable income of urban residents,energy consumption per unit of turnover,and the proportion of highway civil aviation turnover have effect on transportation consumption mainly by the total traffic volume.(3)The impulse response analysis of the VAR model shows that the transportation turnover has a significant promoting effect and long lasting effect on the traffic energy consumption.The effect of energy consumption per unit of transportation on traffic energy consumption is gradual.In the short term,the energy consumption will be increased due to the "rebound effect" and the long-term technological progress will inhibit the increase of energy consumption.(4)The prediction results of BVAR model based on Bayesian estimation show that if China's transportation structure is not optimized during the "thirth Five-Year Plan"period and the transportation energy intensity develop naturally,the energy consumption in transportation will reach 65392.30?65703.66 ten thousand tons of standard coal in 2020,compared with an increase of 119.858%?120.904%in 2010.(5)Scenario analysis predict energy consumption and carbon emissions of transportation in China from 2016 to 2030.Forecast results show that the transportation industry has a greater pressure on energy-saving and emission reduction,which means the industry has great potential in energy-saving and emission reduction.By 2020,the energy-saving potential is 59.1723 million tons of standard coal,the energy-saving rate is 11.98%,and the energy-saving potential is 38686.672 million tons of standard coal in 2030,the saving rate is 44.45%.The emission reduction potential is 31.31 million tons in 2020,the emission reduction rate is 4.47%,the emission reduction potential is 230.275 million tons in 2030 and the emission reduction rate is 12.7%.