地理科学进展 ›› 2016, Vol. 35 ›› Issue (2): 204-213.doi: 10.18306/dlkxjz.2016.02.007

• 研究论文| 区域与城市 • 上一篇    下一篇

中国低碳城市评价与空间格局分析

吴健生1,2(), 许娜1,*(), 张曦文1   

  1. 1. 北京大学深圳研究生院,城市人居环境科学与技术重点实验室,广东 深圳 518055
    2. 北京大学城市与环境学院,地表过程与模拟教育部重点实验室,北京 100871
  • 收稿日期:2015-08-01 接受日期:2015-09-01 出版日期:2016-02-10 发布日期:2016-02-10
  • 通讯作者: 许娜 E-mail:wujs@pkusz.edu.cn;xuna2013@sz.pku.edu.cn
  • 作者简介:

    作者简介:吴健生(1965-),男,湖南新化人,教授,主要从事城市景观生态和GIS研究,E-mail:wujs@pkusz.edu.cn

  • 基金资助:
    国家自然科学基金项目(41271101)

Evaluation of low-carbon city and spatial pattern analysis in China

Jiansheng WU1,2(), Na XU1,*(), Xiwen ZHANG1   

  1. 1. Key Laboratory for Urban Habitat Environmental Science and Technology, Shenzhen Graduate School, Peking University, Shenzhen 518055, Guangdong, China
    2. Key Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
  • Received:2015-08-01 Accepted:2015-09-01 Online:2016-02-10 Published:2016-02-10
  • Contact: Na XU E-mail:wujs@pkusz.edu.cn;xuna2013@sz.pku.edu.cn
  • Supported by:
    National Natural Science Foundation of China, No.41271101]

摘要:

城市是人类生产和消费活动最为集中的区域,带来了大量的能源消耗和碳排放,低碳城市受到国内外学者广泛探讨。本文从低碳开发、低碳经济、低碳环境、城市规模与能源消耗5个方面22个指标构建了低碳城市评价体系,引入遥感影像中的DMSP-OLS夜间灯光数据集与PM2.5浓度反演影像;利用因子分析、聚类分析及空间相关性分析,将2006年及2010年284个地级及以上城市按照低碳水平分为低碳、相对低碳、相对高碳、高碳四类城市;根据驱动力分为环境主导型、居民主导型、城镇化主导型及产业主导型四种城市类型;空间上识别出京津冀、长三角、山东省及珠三角地区具有低碳城市发展集聚效应;低碳城市发展水平受城市行政等级、产业转型等因素影响。

关键词: 低碳城市, 因子分析, 聚类分析, GIS空间分析, DMSP-OLS夜间灯光, PM2.5浓度

Abstract:

:Cities are the most concentrated area of production and consumption activities of the human race, which brings about great amounts of energy consumption and carbon emissions. Therefore, low-carbon city is widely discussed by scholars around the world. In this study, 22 indicators in five areas, including low-carbon development, low-carbon economy, low-carbon environment, city size, and energy consumption, were used to establish an evaluation system for low-carbon city. Remote sensing images of the DMSP-OLS Nighttime Light sets and PM2.5 concentration inversion image were innovatively included in these indicators. Using factor analysis, cluster analysis, and spatial correlation analysis, 284 cities in China were classified as low-carbon cities, comparatively low-carbon cities, comparatively high-carbon cities, and high-carbon cities in 2006 and 2010. The result shows that the low-carbon status of these cities generally improved in 2010 as compared to 2006. According to the driving forces of city development, these cities were divided into four types: environment-oriented, people-oriented, urbanization-dominated, and industry-dominated. Spatially, the Beijing-Tianjin-Hebei area, the Yangtze River Delta region, Shandong Province, and the Pearl River Delta region had the aggregated effect of low-carbon city development. Chongqing, Chengdu, and Wuhan were distinguished from the periphery cities that had lower level of low-carbon development and belonged to the hotspot cities of advanced low-carbon development in Southwest China. Low-carbon development of cities is affected by the administrative level and industrial transformation of cities, among other factors.

Key words: low-carbon city, factor analysis, cluster analysis, GIS spatial analysis, DMSP-OLS nighttime light, PM2.5 concentration