摘要
为探索中国省域碳排放的空间演化规律,以二氧化碳为测度指标,利用空间统计方法和自回归积分滑动平均模型分析了碳排放的空间格局演化特征及其未来变化趋势,最后运用空间杜宾面板数据模型分析了影响碳排放的主要因素。结果表明:(1)中国省域碳排放空间格局总体上较为稳定,HH类型省域主要分布于中国北方地区,LL类型省域主要分布于中国的西部地区,中国省域碳排放在空间上的集聚性和集群效应增强。碳排放的重点调控区域包括长江经济带、京津冀地区、山东、河南、山西、陕西、宁夏、内蒙古和辽宁等。(2)1997-2007年中国省域碳排放标准差椭圆的中心向西南移动,2007-2012年向西北移动;碳排放沿X轴呈分散趋势,沿Y轴呈集中趋势;转角大致在21.516 0°~30.852 6°之间变化;碳排放的空间密集化程度增加,空间分布形态呈现"圆化"趋势,空间相似性降低。(3)2013-2020年碳排放标准差椭圆的中心主要在中牟县内移动;碳排放空间格局呈现一定的空间拉伸趋势;转角大致在20.661 3°~22.482 7°之间变化;形状指数总体上呈轻微增加趋势,空间分布形态呈现"圆化"趋势,空间格局相对稳定。(4)空间面板模型的结果表明,碳排放强度、人口总量、产业结构和经济水平是影响中国省域能源消费碳排放空间格局演化的主要因素。其中,降低碳排放强度是控制碳排放量的重要途径,产业结构和人口总量对碳排放量表现出了明显的空间溢出效应。
Taking carbon dioxide as measure index, using spatial statistical method and autoregressive integrated moving average model, the paper analyzed the characters of spatial pattern and its future trends; Finally, using spatial Durbin panel data model, we analyzed the main influencing factors of carbon emissions. The results are shown as follows. （1）HH types of provinces are mainly distributed in the north of China, the LL types of provinces are mainly distributed in the western of China, the spatial clustering and cluster effects of carbon emissions significantly enhance in China. In general, spatial pattern of China＇s provincial carbon emissions is relatively stable, the key regulatory areas of carbon emissions include the Yangtze River Economic Region, Beijing Tianjin Hebei Region, Shandong, Henan, Shanxi, Shaanxi, Ningxia, Inner Mongolia and Liaoning. （2）The standard deviation ellipse center of China＇s provincial carbon emission moved to the southwest over the period 1997-2007, it moved to the northwest during 2007-2012. Carbon emissions show a decentralization trend along the X axis and a concentrate trend along the Y axis. Angle changes between 2t.516 0 degrees and 30.852 6 degrees. The spatial intensive of carbon emission increases, the spatial distribution of carbon emissions shows a ＂circular＂ tendency, and the spatial similarity decreases. （3）The standard deviation ellipse center of China＇s provincial carbon emission lied in Zhongmou County during 2013-2020; Spatial pattern of carbon emissions exhibits a spatial stretching trend; Angle changes between 20.661 3 degrees and 22.482 7 degrees. The shape index shows a slight increasing trend, the spatial distribution of carbon emissions shows a ＂circular＂ tendency, and the spatial pattern is relatively stable. （4）The results of the spatial panel model show that the carbon intensity, the total population, the industrial structure and the economic level are the main factors that affect the spatial pattern of carbon emissions in the pr
出处
《生态经济》
北大核心
2017年第3期46-52,共7页
Ecological Economy
基金
国家自然基金项目(41571162)
中国清洁发展机制基金赠款项目(2012065)
中国清洁发展机制基金赠款项目(1214073)
关键词
碳排放
空间格局
标准差椭圆
自回归积分滑动平均模型
空间杜宾面板数据模型
carbon emissions
spatial pattern
standard deviational ellipses
autoregressive integrated moving average model
spatial Durbin panel data model
