摘要
由于我国空气污染状况的日趋恶化,研究空气污染的形成因素并制定相应的污染治理政策对于我国生态文明建设有着重要的意义。基于STIRPAT环境效应分析模型,文中利用空间分析工具对选取的31个样本区域的PM2.5排放污染进行了空间探索性分析与空间计量检验。空间探索性分析结果表明:通过计算全局空间Moran’s I指数测算出样本区域PM2.5排放污染具有较强的空间自相关性,局部空间聚集检验则显示出样本区域PM2.5排放污染除具有自相关性外还表现出一定的空间异质性。进一步的空间计量检验结果显示样本区域GDP总量的增长将使得PM2.5污染继续恶化,而提高样本区域人均GDP水平则能有效的降低污染水平。样本区域在能耗上的空间交互影响也较为明显,对于选取的三个能耗指标,煤炭消耗的增加无论对于区域自身还是邻接区域都已成为加剧PM2.5排放污染的主要因素,原油消耗的增长只对邻接区域污染水平产生了影响,而电力消耗的提高缓解了区域自身的PM2.5排放污染但加剧了邻接区域的污染。由于空间溢出效应的影响,样本区域PM2.5污染表现出了很强的空间相关性,这就要求在相关污染治理政策的制定上要充分考虑到空间因素的影响,不仅要从经济发展方式和能源消耗结构的改变等环节入手,同时还要加强省域之间的协调促进,最终实现对污染的有效治理。
Due to the increasingly worse air pollution situation in China, the research of air pollution factors and the formulating of corresponding policies about pollution are of great significance for the construction of ecological civilization in China. Based on STIRPAT model, we carried out exploratory spatial analysis and spatial econometric analysis on PM2. 5 pollution of China' s 31 sample regions. Spatial analysis results show that the PM2. 5 emissions in sample regions in the global space with strong positive spatial autocorrelation;at the same time, in addition to a global positive spatial autocorrelation also, PM2. 5 emissions showed a certain spatial heterogeneity. The spatial econometric test showed that the growth of the total GDP deteriorated the PM2. 5 emission pollution, and improving the level of GDP per capita can effectively reduce the level of pollution. Regional spatial interaction of regions had a significant impact on energy consumption; when it comes to the index of energy consumption, increased coal consumption for both regional or neighboring regions has become the main factor for increasing PM2. 5 emission, oil consumption growth only affected the regional pollution level of the adjacent, while the increase of power consumption eased regional PM2. 5 emission in its own region but exacerbated the emission in the neigh boring regions. Based on the above conclusions, in order to effectivly control PM2. 5 pollution, China should change economic development mode and energy consumption structure, and strengthen coordination of provincial PM2. 5 emissions.
出处
《中国人口·资源与环境》
CSSCI
CSCD
北大核心
2015年第9期153-159,共7页
China Population,Resources and Environment
基金
中央高校基本科研基金项目"中国绿色低碳城镇化研究"(编号:2015AD005)