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In order to study the relationship between transportation carbon emissions and economic growth, driving factors of carbon emissions, we established elastic decoupling model and LMDI decomposition analysis model of transport sector. Taking Beijing Tianjin Hebei region as an example, the empirical study was carried out.Results showed that Tianjin and Hebei were in weak decoupling state, Beijing was in expanded negative decoupling state. And the transportation output scale effect in Beijing, Tianjin and Hebei was the main factor to boost the growth of carbon emissions.Energy intensity effect has led to the reduction of carbon emissions in the transport sector in Tianjin and Hebei, but has led to the increase of transport carbon emissions in Beijing.In terms of the energy structure effect, the transportation energy structure effect of Beijing, Tianjin and Hebei have weak positive contributions or negative contribution to the overall of carbon emissions. Introduction Resolving the contradiction between economic growth and carbon emissions properly is an important task for all countries.The establishment of low carbon transportation system has an important effect on China's response to climate change and carbon emission reduction targets [1]. Therefore, it is urgent and significant to study the decoupling relationship between carbon emissions and economic growth and driving factors of carbon emissions in China's transportation industry. Decoupling theory is used to measure the relationship between material consumption and economic growth in the process of industrial development. Tapio [1] put forward the theory of elasticity decoupling. The decoupling of carbon emissions and economic growth in the transportation industry was decoupled from the economic growth. Yang [2] used the Tapio elastic decoupling model to analyze the relationship between carbon emissions and economic growth in China's transportation industry.In terms of application and study of carbon emissions structure decomposition, Ma Yueyue et al [3] used LMDI decomposition method to analyze the influence factors of carbon emissions in China logistics industry.But little research focuses on decoupling relationship between carbon emissions and economic growth, and driving factors of carbon emission of transportation industry in Beijing, Tianjin and Hebei. Beijing, Tianjin and Hebei region is one of core city circle, and also our country's political, cultural, scientific and technological center, whose transportation industry is also facing a huge energy saving and emission reduction challenges and pressure. Therefore, it is of great significance to carry out the empirical analysis on the carbon emissions decoupling effect and driving factors. Materials and Methodology In order to ensure the accuracy of carbon emissions accounting of the transportation, took 21 kinds of energy as the statistical object to calculate the carbon emissions (D) of the transport industry, see Equation (1). 44 12 i i i i D A B C N = × × × × ∑ (1) 3rd International Conference on Education, Management, Arts, Economics and Social Science (ICEMAESS 2015) © 2016. The authors Published by Atlantis Press 596 D stands for carbon emissions of energy consumption in the transport industry; Ai stands for the consumption of EnergyI; Bi stands for standard coal coefficient of EnergyI; Ci stands for carbon emission coefficient of I; Ni stands for fuel oxidation rate of Energy I. The decoupling between carbon emissions and economic growth is carbon emissions are not increased with the growth of the economy, but even appear the decline trend.Based on the Tapio elastic decoupling model, the elasticity decoupling model of the relationship between transportation industry carbon emissions and economic growth wasput forward, as shown in the formula (2). 2, 2 2 ( / ) / ( / ) CO IGDP t CO CO IGDP IGDP = D D (2) Tco2, IGDP is elasticity decoupling value of carbon emissions from transportation industry and transport industry GDP(One hundred million yuan);In order to eliminate the factor of price variation,transport industry's total production value was calculated with the constant price. This paper used extended Kaya identity and Logarithmic Mean DivisiaIndex(LMDI) to study driving factors of carbon emission. i i i i i C E E C IGDP f s n g E E IGDP = × × × = × × × ∑ ∑ (3) Ci stands for the amount of carbon emissions from the consumption of Energy I; Ei stands for the amount of consumption of Energy I; E stands for total energy consumption; IGDP stands for gross product of transport industry; fi=Ci/Ei respects for carbon intensity effect; si=Ei/E respects for the proportion of Energy I in total energy and it is used to explain the structure of energy consumption; n=E/IGDP stands for energy consumption intensity; g stands for influence of industrial scale on carbon emissions in transportation industry Using LMDI model to decompose formula (3), change of carbon emissions from the period t to t+1 period (△C)in Beijing, Tianjin and Hebei region can be expressed as the formula (4). 1 t t f s n g C C C C C C C + D = − = D + D + D + D (4)

Carbon Emissions and Economic Development in Transport Industry - An Empirical Research Based on Decoupling Theory and Structure Decomposition Model