我国能源消费碳足迹时空迁移及影响因素研究

发布时间：2018-06-02 16:09

本文选题：碳足迹 + 时空迁移　；参考：《安徽财经大学》2016年硕士论文

【摘要】：随着每年全球气候大会的召开,全球气候变化问题已逐渐成为当前国际社会关注的热点,各国政府不断强调节能减排、保护环境,低碳经济的发展是必然的趋势。《京都议定书》的签订更是强调了发达国家与发展中国家在国际社会承担减排的义务。我国是最大的发展中国家,科学技术远不及发达国家,经济的发展需要依赖传统能源,环境问题与能源危机目前亟待解决。我国也是一个能源消耗大国,在全球低碳减排的大背景下,我国有义务为环境的友好发展做贡献。基于上述因素,本研究以能源终端消费量为基础,测算了我国30个省域单元的碳足迹。分别从时间演化和空间分布角度来分析省域碳足迹的时空迁移,并基于STIRPAT模型和EKC曲线,阐述对我国能源消费碳足迹的影响因素。实证结果显示:第一,我国的碳足迹居世界第一,环境压力问题亟需解决。从2003年到2014年,我国碳足迹总量的增长率为557%,平均每年的变化强度为25.96%,省域的之间的碳足迹增长有明显的差异性并逐步扩大。碳足迹在空间上存在自相关性,表现出明显集聚特性,区域碳足迹的影响不仅来自于本身还与周边区域息息相关。在空间分布上,东部地区碳足迹普遍高于西部地区,但是它们之间的差异逐渐减少。第二,基于STIRPAT模型的实证结果显示,对环境压力的影响程度从高到低依次是人口数量、第二产业所占比重、第三产业产业所占比重、高新产业占比、人均GDP。人口数量对碳足迹的影响最高,弹性系数高达14.8867。整体上看,我国东部人口高于西部,其生产生活所依靠的能源也在与日俱增,环境压力随之增加。我国人均GDP每增加1%,碳足迹增加0.5188%。在空间分布上,东部沿海省市人均GDP均高于内陆地区,前者对碳足迹的贡献必然高于后者。总体来说,人均GDP是碳足迹的一个重要影响因素,同时也会增加空间分布的不均衡特质。第二产业比重每增加一个百分点,碳足迹减少2.0846个百分点,也就是说第二产业占比越高,减排作用越大。高新产业占比对环境压力的影响是正向的,弹性系数为1.4267。目前我国的高新技术产业的研究成果真正应用于提升环境质量领域的少之又少,反而会增加环境压力。基于以上分析,碳足迹的区域差异性特征日益凸显,且区域间相互影响,人口、富裕、技术等因素也对空间差异有一定的影响。第三,人均GDP对碳足迹的影响程度最小,弹性为0.5188,环境与经济发展之间的关系已经慢慢变弱。本研究基于环境库兹涅茨分析,探索人均碳足迹与人均GDP的关系,实证结果显示,两者之间呈“N”型曲线关系。
[Abstract]:With the holding of the global climate conference every year, the global climate change has gradually become the focus of attention of the international community. The governments of various countries continue to emphasize energy conservation and emission reduction, and protect the environment. The development of low-carbon economy is an inevitable trend, and the signing of Kyoto Protocol emphasizes the obligation of developed and developing countries to reduce emissions in the international community. China is the largest developing country, science and technology is far from developed countries, economic development needs to rely on traditional energy, environmental problems and energy crisis need to be solved. China is also a large energy consuming country. Under the background of global low carbon emission reduction, China has the obligation to contribute to the friendly development of the environment. Based on the above factors, the carbon footprint of 30 provincial units in China was calculated on the basis of energy terminal consumption. The temporal and spatial migration of provincial carbon footprint is analyzed from the angle of time evolution and spatial distribution. Based on the STIRPAT model and EKC curve, the influencing factors on the carbon footprint of energy consumption in China are discussed. The empirical results show that: first, our carbon footprint ranks first in the world, environmental pressure needs to be solved. From 2003 to 2014, the total growth rate of China's carbon footprint is 5577.The average annual change intensity is 25.96. The growth of carbon footprint between provinces has obvious difference and gradually expands. There is an autocorrelation of carbon footprint in space, showing obvious agglomeration characteristics. The influence of regional carbon footprint is not only from itself but also from the surrounding area. In the spatial distribution, the carbon footprint of the eastern region is generally higher than that of the western region, but the difference between them decreases gradually. Secondly, the empirical results based on STIRPAT model show that the degree of influence on environmental pressure from high to low is population, the proportion of secondary industry, the proportion of tertiary industry, the proportion of high-tech industry, per capita. The impact of population size on the carbon footprint is the highest, with a coefficient of elasticity as high as 14.8867. As a whole, the population of eastern China is higher than that of western China. China's per capita GDP increases by 1 and the carbon footprint increases by 0. 5188. In spatial distribution, the per capita GDP of eastern coastal provinces is higher than that of inland areas, and the contribution of the former to the carbon footprint is bound to be higher than that of the latter. Overall, GDP per capita is an important factor in carbon footprint, and it also increases the disequilibrium of spatial distribution. For every percentage point increase in the secondary industry, the carbon footprint is reduced by 2.0846 percentage points, which means that the higher the ratio of the secondary industry is, the greater the emission reduction effect will be. The effect of the proportion of high-tech industry on environmental pressure is positive, the elastic coefficient is 1.4267. At present, the research results of high and new technology industry in our country are seldom used in the field of improving environmental quality, but will increase the environmental pressure. Based on the above analysis, the regional differences of carbon footprint are increasingly prominent, and regional interaction, population, wealth, technology and other factors also have a certain impact on spatial differences. Third, the impact of GDP per capita on carbon footprint is the least, with elasticity of 0.5188, and the relationship between environment and economic development has gradually weakened. Based on the environmental Kuznets analysis, this study explores the relationship between per capita carbon footprint and per capita GDP. The empirical results show that there is a "N" curve relationship between the two.
【学位授予单位】：安徽财经大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：X24;F426.2

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