【作者】 高洁；

【导师】 王建伟；

【作者基本信息】 长安大学 ， 交通运输规划与管理， 2013， 博士

【摘要】 交通运输碳排放量的持续增长严重影响了社会经济的发展效率和居民的出行质量，建设低碳交通运输体系已成为中国政府应对气候变化和环境污染的主要手段。建设低碳交通运输体系的关键是对交通运输碳排放的控制。然而由于交通运输碳排放时空特征复杂，影响因素众多且影响机理不明，使得交通运输碳减排难度较大。目前尚缺乏对交通运输碳排放特征和演变机理的系统性研究，无法为交通运输碳减排目标设定、低碳交通运输体系规划及交通运输碳减排政策设置提供决策依据。因此，研究交通运输碳排放特征及演变机理已成为关键且紧迫的问题。本文以交通运输碳排放为对象，重点研究其时空特征、影响因素及演变模型。论文主要研究成果如下：（1）将交通运输碳排放时间特征划分为短期特征与长期特征，研究了短期与长期特征的计算方法。基于脱钩弹性指数模型，将交通运输碳排放总量及碳排放结构作为变量，建立了交通运输碳排放短期波动特征计算模型。基于R/S分形理论，将交通运输碳排放量及碳排放效率作为交通运输碳排放时间序列演变状态变量，建立了交通运输碳排放时间序列的Hurst指数计算方法。实证研究表明：中国交通运输碳排放存在随机性波动和趋势性波动特征，短期波动状态较为复杂，长期时间序列存在自相似性及状态持续性的分形特征。（2）研究了交通运输碳排放空间分布的差异程度、差异来源及收敛性特征。采用标准差和变异系数测算交通运输碳排放空间分布的绝对差异和相对差异，建立了以交通运输增加值为权重的交通运输碳排放Theil指数模型及一阶分解模型，构建了交通运输碳排放强度差异收敛性检验的面板回归模型。通过模型计算获得了中国交通运输碳排放空间差异程度及来源，并表明交通运输碳排放强度差异具有β收敛性特征。（3）建立了交通运输碳排放量因素分解模型，从因素分解的维度研究了运输结构、道路运输规模及道路运输碳排放等内部因素以及经济发展水平、人口规模等外部因素对交通运输碳排放量演变的影响。实证研究表明：结构因素对中国交通运输碳排放量增长的拉动作用仅次于规模因素；在技术因素中，道路运输能源强度明显抑制交通运输碳排放量的增长，交通运输能源碳排放因子的抑制作用较弱。（4）建立了向量自回归模型、脉冲函数和方差分解模型，从影响因素动态作用的维度研究了交通运输碳排放与交通运输增长之间的动态关系及作用特征，分析了相互冲击所带来的动态效应及相互冲击时各自的贡献率和重要程度。实证研究表明：交通运输周转量与交通运输碳排放之间的相互冲击只存在短期响应，短期内碳排放增长的冲击对交通运输周转量增长有负的影响作用；交通运输周转量在第一期只受到自身波动的影响，交通运输碳排放对其冲击的效应在第二期才表现出来；交通运输周转量对交通运输碳排放的预测贡献率在第一期就已经显现出来，具有直接的、基础性的影响。（5）基于EKC分析了交通运输碳排放随经济发展、交通运输发展演变的阶段性过程；在此基础上，将交通运输碳减排政策参数作为控制变量，建立了交通运输碳排放量演变模型，研究了交通运输碳排放具有的一般性演变规律，通过模拟获得了不同碳减排政策控制强度下的交通运输碳排放演变曲线及碳减排量的变化规律。在政策控制参数μ和δ的影响下，交通运输碳排放量演变均呈现“S”型增长特征；政策控制参数通过对碳排放演变曲线速率和峰值点的影响获得不同的碳减排量；参数μ对交通运输碳排放量演变曲线增长速度的影响比参数δ更加显著。（6）将运输结构细化为运输方式之间的不同作用，提出了基于运输量转移的交通运输碳排放演变动力学模型，研究了运输量转移对交通运输碳排放量演变的影响机理，通过模拟获得了不同运输量转移情形下的交通运输碳排放演变规律。交通运输碳排放量演变与不同碳排放特征的交通运输方式之间的运输量转移程度密切相关；高碳运输方式在前期对交通运输碳排放量演变的影响显著，低碳交通运输方式在后期对交通运输碳排放量的影响明显。更多还原

【Abstract】 The continuing growth of transport carbon emissions has serious impact on thedevelopment efficiency of social economy and the quality of residents travel. Developinglow-carbon transportation has become the main measure of Chinese government to tackleclimate change and environmental pollution. Controlling the transport carbon emissions is thekey to build a low-carbon transport system. However, the spatial-temporal characteristics oftransport carbon emissions is very complex，and there are so many factors to affect thetransport carbon emissions，and the influence mechanism of these factors is not very clear，which makes it very difficult to reduce the carbon emissions of transportation. Currently, it islack of comprehensive researches about the feature and the evolution mechanism of transportcarbon emissions, unable to provide decision basis for setting carbon reduction targets,planning a low-carbon transportation system and developing carbon reduction policies.Therefore, a study of the feature and the evolution mechanism of transport carbon emissionshas become a critical and urgent issue. The dissertation took transport carbon emissions as theobject of study, studied the spatial-temporal characteristics, influence factors and evolutionmodels of transport carbon emissions.The main contributions of this dissertation are as follows:(1) Divided the time characteristics of transport carbon emissions into short-termcharacteristics and long-term characteristics and put forward a calculation method to studythese characteristics. Based on the elastic decoupling index model, took the total carbonemissions of transportation and the energy structure of carbon emissions as variables,established a calculation model used to measure the short-term fluctuations characteristics oftransport carbon emissions. Based on the R/S fractal theory, took the carbon emissions oftransportation and the efficiency of Carbon emissions as variables of time series evolution ofcarbon emissions, put forward a calculation method of Hurst Index. Empirical analysis showsthat: transport carbon emissions of china exists deterministic and stochastic characteristics, itsshort-term fluctuations state is very complex, while there are fractal characteristics ofself-similarity and persistence in the long run.(2) Studied the degree, source and convergence characteristics of spatial distributiondifference of transport carbon emissions. Using the standard deviation and variationcoefficient estimated the absolute difference and relative difference of transport carbonemissions in spatial distribution, established a Theil index model and a first-orderdecomposition model of transport carbon emissions whose weight depends on the added valueof transportation，established a panel regression model used to examine the convergence oftransport carbon intensity difference. Through computation, obtained the degree and source ofspatial distribution difference of transport carbon emissions, found that transport carbonintensity difference has convergence characteristics of β.(3)Based on the KAYA identities, established a factor decomposition model oftransportation carbon emissions. Using factor decomposition studied how the internal factors(such as Scale of road transport, Road transport energy consumption carbon emissions,Transport intensity and Transport structure) and external factors (such as Economic development and Population size) affect the evolution of transport carbon emissions.Empirical analysis shows that: the pulling effect on China’s transport carbon emissions growthcaused by structural factors is only not as obvious as the pulling effect caused by scale factors;among the technical factors, road transport energy intensity could significantly suppress thegrowth of transport carbon emissions, while the inhibition caused by the transportation energycarbon emission factor is relatively weak.(4) Analysis the period characteristics of transportation emissions based on EKC.Established a vector autoregression model, an impulse function and a variance decompositionmodel, analyzed the mutual dynamic effects caused by mutual impact and its contribution andimportance. Based on the dynamic effect of influence factors, studied the dynamicrelationship between transport carbon emissions and transport growth and analyzed itscharacteristic. Empirical analysis shows that: mutual impact between transport-kilometers andtransport carbon emissions exists only in the short term, the growth of carbon emissions has anegative influence on the growth of transport-kilometers in the short term.Transport-kilometers affected only by the fluctuation itself in the first period, the impacteffect caused by transport carbon emissions appears only in the second period. While thetransport-kilometers has a direct and fundamental impact on the transport carbon emissionsand its contribution rate has appeared in the first period.(5) Based on the EKC curve and logistic model, took the parameters of transport carbonreduction policy as control variable, established an evolution model of transport carbonemissions and analyzed the general evolution law of transport carbon emissions. Throughsimulation, obtained the evolution curve of transport carbon emissions and changing rule ofcarbon emission reductions：under the influence of policy control parameters (μ&δ), transportcarbon emissions changes with a "S" type growth characteristics; different policy controlparameters affect the rate and peak point of the carbon evolution curve in different degrees, asa result, the carbon emission reductions is different. Parameter μ has more significant effectson the evolution curve growth rate of transport carbon emissions than parameters δ.(6) Regarded transportation structure as the interaction between different modes oftransport, put forward an evolution dynamics model of transport carbon emissions which isbased on traffic transfer and analyzed the influence mechanism which the traffic transferaffects the evolution of transport carbon emissions. Through simulation, obtained thechanging rule of carbon emission reduction with different transfer of traffic: the evolution oftransport carbon emissions has relationship with the degree of transfer of traffic; thehigh-carbon modes of transport has significant effect on the evolution of transport carbonemissions in the earlier stage, while the low-carbon modes of transport has significant effecton the evolution of transport carbon emissions in the late period.更多还原