基于STIRPAT模型的区域交通运输碳排放影响因素分析

发布时间：2018-06-03 21:30

本文选题：交通运输 + 碳排放　；参考：《北京交通大学》2017年硕士论文

【摘要】：在生态环境恶化和可再生能源紧张的背景下,气候变暖已发展成为全球范围内十大突出的环境问题之首。据IPCC研究显示,二氧化碳等温室气体排放量的不断增长使其成为气候变暖的主要影响原因。交通运输作为国民经济支柱性产业,在国民经济迅猛发展的同时拉动交通运输业发展水平提高,但中国也为之付出了较为严重的生态环境破坏和碳排放量增加的代价,进而使交通运输业发展成为仅次于工业领域的第二大能源消费和碳排放部门。由于我国区域经济存在差异性,交通运输碳排放也表现出区域不均衡的特点,因此从区域角度分析交通运输行业的碳排放与其影响因素之间的关系,对于国家实现节能减排目标具有重要意义。本文选取2000——2014年《中国统计年鉴》、《中国能源统计年鉴》的省级数据,综合考虑经济水平、交通运输发展水平及交通运输碳排放水平,将人口规模、产业结构、部门能源消费结构、客货运周转量引入改进的STIRPAT模型进行影响因素分析,并结合环境库兹涅茨曲线,选取城市化率、GDP和部门能源利用效率进行曲线关系判断分析。通过对全国系统交通运输碳排放量进行收敛性分析发现,在全国系统中存在阶段性收敛,但在整体水平下不收敛,由于区域异质性的存在验证了划分区域进行影响因素研究的必要性。本文基于尺度空间理论,将大多应用在经济金融领域的多尺度空间聚类算法应用在交通运输领域,进行中国30个省域多因素面板数据的区域划分,结果与实际情况大致吻合。并在聚类结果基础上通过面板数据回归模型进行交通运输碳排放相关影响因素的弹性分析,从而识别交通运输碳排放分区域变化规律及特点,基于交通运输碳排放实证研究,分别从产业结构比重、部门能源消费结构、城市化率、经济发展水平、客货运周转量、部门能源利用效率方面提出制定“共同但有差别”的交通运输节能减排政策。
[Abstract]:Under the background of the deterioration of ecological environment and the shortage of renewable energy, climate warming has become one of the top ten outstanding environmental problems in the world. Increasing emissions of greenhouse gases, such as carbon dioxide, are the main cause of global warming, according to IPCC. As a pillar industry of the national economy, the transportation industry develops rapidly and promotes the development level of the transportation industry. However, China has also paid the price of serious ecological environment damage and carbon emission increase. Thus, transportation industry has become the second largest energy consumption and carbon emission sector after industry. Because of the difference of regional economy in our country, the carbon emission of transportation also shows the characteristics of regional imbalance, so the relationship between the carbon emissions of transportation industry and its influencing factors is analyzed from the regional perspective. It is of great significance for the country to achieve the goal of energy saving and emission reduction. This paper selects the provincial data of China Statistical Yearbook and China Energy Statistics Yearbook from 2000 to 2014, and synthetically considers the economic level, transportation development level and transportation carbon emission level. The structure of energy consumption and the turnover of passenger and freight are introduced into the improved STIRPAT model to analyze the influencing factors, and the relationship between urbanization rate and energy efficiency is analyzed according to the environmental Kuznets curve. By analyzing the convergence of carbon emissions from national transportation, it is found that there is phase convergence in the national system, but it does not converge at the overall level. Because of the existence of regional heterogeneity, it is necessary to study the influencing factors of dividing regions. Based on the theory of scale space, this paper applies the multi-scale spatial clustering algorithm, which is mostly applied in the field of economy and finance, to the area of transportation, and divides the multi-factor panel data of 30 provinces in China. The results are in good agreement with the actual situation. Based on the clustering results, the elastic analysis of related factors of transport carbon emissions is carried out through panel data regression model, so as to identify the characteristics of transport carbon emissions, based on the empirical study of transport carbon emissions. From the aspects of industrial structure proportion, sector energy consumption structure, urbanization rate, economic development level, passenger and freight transport turnover, energy use efficiency of the department, the paper puts forward a "common but different" policy of energy saving and emission reduction in transportation.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：X73

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