• 研究论文 •

近20年来中国能源消费碳排放时空格局动态

1. 1. 湖南科技大学建筑与城乡规划学院,湖南 湘潭 411201
2. 湖南科技大学地理空间信息技术国家地方联合工程实验室,湖南 湘潭 411201
3. 湖南科技大学生命科学学院,湖南 湘潭 411201
• 出版日期:2016-06-23 发布日期:2016-06-23
• 通讯作者: 刘贤赵 E-mail:changchungao@sina.cn;xianzhaoliu@sina.com
• 作者简介:

作者简介：高长春(1989-),男,河南周口人,硕士生,研究方向为RS与GIS应用及区域可持续发展,E-mail: changchungao@sina.cn

• 基金资助:
教育部人文社会科学项目(14YJAZH050);湖南省社会科学基金项目(14YBA170);湖南省研究生科研创新基金项目(CX2016B542)

Spatiotemporal dynamics of carbon emissions by energy consumption in China from 1995 to 2014

Changchun GAO1(), Xianzhao LIU1,2,*(), Chaokui LI2, Yong ZHANG1, Guanghui YU1, Qing SU3, Yanlin TIAN1

1. 1. College of Architecture and Urban Planning, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
2. National-Local Joint Engineering Laboratory of Geo-Spatial Information Technology, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
3. College of Life Science, Hunan University of Science and Technology, Xiangtan 411201, Hunan, China
• Online:2016-06-23 Published:2016-06-23
• Contact: Xianzhao LIU E-mail:changchungao@sina.cn;xianzhaoliu@sina.com
• Supported by:
Humanities and Social Science Project of the Ministry of Education, No.14YJAZH050;Social Science Foundation of Hunan Province, No.14YBA170;Hunan Provincial Innovation Foundation for Postgraduate, No.CX2016B542

CO2等温室气体引起的全球气候变暖是对人类社会可持续发展的严峻挑战。基于IPCC提供的参考方法,在对中国大陆30个省区(不含西藏)能源消费碳排放量估算的基础上,运用ESTDA框架,通过ESDA、LISA时间路径、时空跃迁和标准差椭圆等方法,从时空耦合的角度分析了1995-2014年中国能源消费碳排放时空格局动态性。结果表明：①近20年来中国省域碳排放具有显著的空间正相关性,碳排放空间差异呈先缩小后扩大的趋势;②LISA时间路径分析显示,中国大部分省区的局部空间结构具有较强的稳定性,1995-2001年和2002-2014年2个时段相对长度都小于平均长度的省区均为18个,大部分南方省区在空间依赖方向上的波动性呈增强趋势,而北方大多数省区则保持相对稳定;③出现协同运动的省区由1995-2001年的13个下降到2002-2014年的10个,表明中国碳排放空间格局具有一定的空间整合性,但呈减弱趋势;④中国省域碳排放的局部空间关联模式和集聚特征具有较强的稳定性,表现为一定的路径依赖或空间锁定特征;⑤碳排放重心在113.739°~114.324°E、34.475°~35.036°N之间变动,整体上有向西北方向移动的趋势。中国碳排放空间分布呈东北—西南格局,且有逐步向正北—正南转变的趋势。中国碳减排的重点是加快发展清洁能源与提高能效并重,优化能源结构和促进各省区产业结构转型,制定差异化的省域碳减排政策,建立碳交易制度。

Abstract:

Global warming due to greenhouse gases (such as CO2) emissions posts serious challenges to the sustainable development of the human society. Based on the reference method provided by the Intergovernmental Panel on Climate Change, this study calculated the CO2 emissions of energy consumption in 30 provinces of China (excluding Tibet) from 1995 to 2014. Using exploratory spatial data analysis (ESDA), LISA time path, spatiotemporal transitions, and standard deviation ellipse analysis methods, the authors analyzed the spatiotemporal dynamics of carbon emissions of energy consumption. The results show that: (1) there was a significant positive spatial correlation of carbon emissions of energy consumption in China’s provinces during 1995-2014. The inter-provincial carbon emissions differences first decreased then increased; (2) by means of LISA time path analysis, this study found that the majority of the Chinese provinces had a stable spatial structure of carbon emissions. Eighteen provinces had shorter than average time path lengths in 1995-2001 and 2002-2014. The majority of the southern provinces showed a fluctuating spatial dependence with increasing amplitude over time, while most of the northern provinces showed a relatively stable trend; (3) according to the directional Moran scatter plot, the number of provinces that showed the same trend decreased from 13 in 1995-2001 to 10 in 2002-2014, indicating that the spatial coherence of carbon emissions change at the provincial level had weakened; (4) spatial correlation patterns and clustering of carbon emissions by energy consumption at the provincial level were relatively stable and showed certain degree of path-dependence or lock-in character; (5) carbon emissions gravity center was between 113.739°~114.324°E, 34.475°~35.036°N and was moving to the northwest. The spatial distribution of provincial emissions presented a northeast-southwest pattern, and had the tendency of shifting to a north-south pattern. The focus of carbon emission reduction in China is to accelerate the development of clean energy, improve energy efficiency, promote the optimization and upgrading of energy and industrial structures in all provinces, make differentiated carbon emission reduction policies for different provinces, and establish carbon trading market.