globalchange  > 气候变化事实与影响
CSCD记录号: CSCD:6090444
论文题名:
中国碳排放强度的时空演进及跃迁机制
其他题名: Research on spatial and temporal evolution of carbon emission intensity and its transition mechanism in China
作者: 赵桂梅1; 赵桂芹2; 陈丽珍1; 孙华平1
刊名: 中国人口·资源与环境
ISSN: 1002-2104
出版年: 2017
卷: 27, 期:10, 页码:47-52
语种: 中文
中文关键词: 碳排放强度 ; 时空格局演进 ; 探索性时空分析 ; 驱动因素 ; 跃迁机制
英文关键词: carbon emission intensity ; temporal spatial pattern evolution ; exploratory temporal and spatial analysis ; driving factors ; transition mechanism
WOS学科分类: ENVIRONMENTAL SCIENCES
WOS研究方向: Environmental Sciences & Ecology
中文摘要: 面对气候变化所带来的生存危机以及环境治理的复杂状况,对中国碳排放强度时空演进的动态监测与预警治理的研究是实现碳排放强度下降目标的关键。文章测算19972015年中国大陆30个省区碳排放强度的空间面板数据,采用探索性时空数据分析( ESTDA)方法对中国碳排放强度的空间相关性、集聚特征及其时空跃迁进行空间统计分析,借助分位数回归与时空跃迁嵌套模型,揭示在时间和空间推移的双重作用下中国各省区碳排放强度的时空跃迁机制。研究结果表明: ①中国30个省区的碳排放强度在时空分布上并不是完全随机状态,各个省区碳排放强度之间具有显著的空间相关性特征,碳排放强度的变动趋势会受到其相临近省区碳排放强度的影响,省域间的碳排放强度在空间分布上呈现集聚与分异并存的时空演进特征。②中国碳排放强度空间集聚趋势增强,具有高度的凝固性和较低的流动性,10个高碳排放强度省区碳排放强度的稳定性将成为制约中国碳排放强度整体跃迁的重点省区,相关省区的跃迁性将成为驱动中国碳排放强度整体跃迁的关键省区。③各省区的碳排放强度空间集聚过程中存在时空跃迁的驱动模式和制约模式,分位数回归模型能够很好地解释各驱动因素对碳排放强度时空跃迁的驱动机制,不同响应阶段的驱动因素的分位数与碳排放强度时空跃迁类型之间具有很强的嵌套性。④根据各省区碳排放强度时空演进及其跃迁机制的分析结果,进一步提出加强对关键省区碳排放强度的有效监测与治理,加大碳排放的约束力度等差异化的碳减排调控措施。
英文摘要: In face of the crisis of survival and the complicated situations of environmental governance both caused by climate changes, the key solution to reduce the intensity of carbon emissions is to study the dynamic monitoring and early warning control of the spatiotemporal evolution of the carbon intensity in China. This paper estimated the spatial panel data of the carbon intensity in 30 provinces in China during 1997-2015,and did spatial statistical analysis of the spatial correlation,agglomeration characteristics and space-time transition of the carbon intensity by the means of exploratory spatio-temporal data analysis ( ESTDA). It also adopted quantile regression and the space-time transition nested models to reveal the spatiotemporal transition mechanism of the carbon intensity in the Chinese provinces under the dual functions of time and space. The results show that: ①The carbon intensity of the 30 provinces in China is not completely random in the spatial and temporal distribution. There are distinct spatial correlation characteristics between the carbon intensity of the provinces,and the change trend of the carbon intensity in the various provinces is affected by that in the adjacent provinces. The carbon intensity among provinces embodies the spatio-temporal evolution characteristics,bothagglomeration' anddifferentiation'in the spatial distribution.②The spatial agglomeration of the carbon intensity in China is on the increase,with high solidification and low liquidity. The stability of the 10 provinces with high carbon intensity will critically restrict the overall transition of carbon intensity in China. In the contrast,the transition of related provinces will critically drive the overall transition of carbon intensity in China. ③There are driving modes and control modes of the space-time transition in the process of spatial agglomeration of the carbon intensity in the different provinces. The quantile regression model can well explain the driving mechanism caused by different driving factors in the space-time transition of carbon intensity. There are strong nesting between the quantile of the driving factors and the different types of space-time transition about the carbon intensity in the different stages of the response. ④ According to the results of carbon intensity evolution and transition mechanism in the different provinces,we should put forward further different control measures to reduce the carbon emissions,such as strengthening the effective monitoring and management of key provincial carbon intensity and further restricting the carbon emissions.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/153553
Appears in Collections:气候变化事实与影响

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作者单位: 1.江苏大学财经学院, 镇江, 江苏 212013, 中国
2.江苏大学京江学院, 镇江, 江苏 212013, 中国

Recommended Citation:
赵桂梅,赵桂芹,陈丽珍,等. 中国碳排放强度的时空演进及跃迁机制[J]. 中国人口·资源与环境,2017-01-01,27(10):47-52
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