地理科学 ›› 2016, Vol. 36 ›› Issue (4): 491-501.doi: 10.13249/j.cnki.sgs.2016.04.002

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中国交通CO2排放时空格局演变及其影响因素——基于2000~2012年30个省(市)面板数据的分析

杨文越1, 李涛2, 曹小曙1,3()   

  1. 1.中山大学地理科学与规划学院,广东 广州 510275
    2.广东财经大学地理与旅游学院,广东 广州 510320
    3.陕西师范大学交通地理与空间规划研究所,陕西 西安 710119
  • 收稿日期:2015-02-07 修回日期:2015-08-20 出版日期:2016-07-21 发布日期:2016-07-21
  • 作者简介:

    作者简介:杨文越(1988-),男,广东韶关人,博士研究生,研究方向为城市交通地理与土地利用。E-mail:yangwenyue900780@163.com

  • 基金资助:
    国家自然科学基金项目(41171139,41130747)中央高校基本科研业务费专项资金(GK201303006)资助

The Evolution of Spatial-temporal Characteristics and Influence Factors of CO2 Emissions from Transport in China: A Panel Data Analysis of 30 Provinces in China from 2000 to 2012

Wenyue Yang1, Tao Li2, Xiaoshu Cao1,3()   

  1. 1.School of Geography Science and Planning, Sun Yat-sen University, Guangzhou 510275, Guangdong, China
    2. School of Geography & Tourism, Guangdong University of Finance & Economics, Guangzhou 510320,Guangdong, China
    3. Institute of Transport Geography and Spatial Planning, Shaanxi Normal University, Xi’an 710119,Shannxi, China
  • Received:2015-02-07 Revised:2015-08-20 Online:2016-07-21 Published:2016-07-21
  • Supported by:
    National Natural Science Foundation of China(41171139,41130747)The Fundamental Research Funds for the Central Universities(GK201303006 )

摘要:

通过构建交通CO2排放模型对2000~2012年中国30个省(市)的交通CO2排放时空演变特征进行了分析。并采取“由大到小”逐步回归的建模方式,在传统的固定效应模型(面板数据模型)基础上引入时间固定效应,构建了双向固定效应模型对中国交通CO2排放的社会经济、城市形态、交通发展等方面的影响因素进行研究。结果表明:2000~2012年期间,中国交通CO2排放总量和人均交通CO2排放量分别以9.29%和8.69%的年均增速增长,前者的区域差异呈先增后减趋势,后者的区域差异则首先呈周期性波动,而后一直保持减少趋势。人均GDP和城镇居民家庭人均可支配收入对人均交通CO2排放具有显著的正向效应,表明社会经济发展和居民收入水平提高是交通CO2排放增长的主要驱动因素。城市人口密度对交通CO2排放亦具有显著的正向效应,这意味着未来中国应加强对城市人口密度的规划控制,以避免因人口过度集聚而额外增加产生交通CO2排放。公共交通发展水平对交通CO2排放增长具有显著的负向效应,但小汽车拥有率对交通CO2排放的影响并不显著。

关键词: 交通CO2排放, 时空特征, 面板数据, 双向固定效益模型, 中国

Abstract:

This article attempted to analyze the spatial-temporal evolution and regional differences of carbon emissions from transport in China over the period 2000-2012 based on the transport carbon-emission model. Moreover, a two-way fixed effect model was developed to study the factors in terms of socioeconomic, urban form and transport development that influenced transport carbon emissions in China through the regression method of "general to specific". The results indicated that China’s total and per capita CO2 emissions from transport were growing at 9.29% and 8.69% a year respectively, appearing the different characteristics of stages. The regional differences of the total CO2 emissions from transport first increased and then decreased, while the regional differences of the per capita CO2 emissions from transport first had a cyclical fluctuation and then kept decreasing. Provinces with higher total CO2 emissions from transport were mainly concentrated in the eastern coastal region which had a prosperous economy and a large population, while provinces with higher per capita CO2 emissions from transport were predominantly concentrated in developed regions such as Shanghai, Beijing and Tianjin as well as some western provinces with lower population density. In the aspect of socioeconomic influential factors, per capita GDP and per capita disposable income of urban households both had significant positive effect on per capita CO2 emissions from transport, which indicated that the development of social economy and the increase in residents' income level were main drivers of transport CO2 emissions growth. The urbanization level also had a positive effect, but it was not statistically significant. In addition, industrial structure was the least significant factor. In the aspect of urban form influential factors, urban population density also had a significant positive effect on transport CO2 emissions, which was contrary to the conclusions of study abroad. Moreover, the city size also had a positive effect, but it was not statistically significant. In the aspect of transport development, the effect of urban road density was positive and was more significant than urban road ratio and highway density. The effect of public transport development was significantly negative. However, the effect of car ownership was not statistically significant. Finally, the effect of time was negative to transport CO2 emissions, which reflected that the effect of some unobserved factors for controlling the growth of transport CO2 emissions in China was gradually appearing.The better understanding of the relationship between socio-economy, urban form, transport development and transport CO2 emissions will help China to curb transport CO2 emissions growth and construct city space environment towards low-carbon and sustainable.

Key words: transport CO2 emissions, spatial-temporal characteristics, panel data, two-way fixed effect model, China

中图分类号: 

  • K901