自然资源学报 ›› 2013, Vol. 28 ›› Issue (7): 1106-1116.doi: 10.11849/zrzyxb.2013.07.003

• 资源利用与管理 • 上一篇    下一篇

影响中国碳排放绩效的区域特征研究——基于熵值法的聚类分析

王媛1, 程曦1, 殷培红2, 张雪花3   

  1. 1. 天津大学 环境科学与工程学院, 天津 30007;
    2. 环境保护部 环境与经济政策研究中心, 北京 100029;
    3. 天津工业大学 环境经济研究所, 天津 300387
  • 收稿日期:2012-06-26 修回日期:2013-01-04 出版日期:2013-07-20 发布日期:2013-07-20
  • 通讯作者: 殷培红(1968-),女,北京人,副研究员,博士,主要研究环境演变与资源环境管理。E-mail:peihong_y@163.com E-mail:peihong_y@163.com
  • 作者简介:王媛(1977-),女,天津人,副教授,博士,主要研究资源与环境管理。E-mail:w_yuan77@163.com
  • 基金资助:

    教育部人文社会科学基金"中国贸易隐含碳转移变化与国际产业分工"(11YJCZH177);国家社科基金"全碳效率"测度与区域生态经济评价研究(12BJY025);国家自然科学基金"基于全球生产网络的中国对外贸易中CO2 转移排放研究"(41201591)。

Research on Regional Characteristics of China’s Carbon Emission Performance Based on Entropy Method and Cluster Analysis

WANG Yuan1, CHENG Xi1, YIN Pei-hong2, ZHANG Xue-hua3   

  1. 1. School of Environmental Sciencing and Engineering, Tianjin University, Tianjin 300072, China;
    2. Policy Research Center for Environment and Economy, The Ministry of Environmental Protection, Beijing 100029, China;
    3. Department of Environmental Economics, Tianjin Polytechnic University, Tianjin 300387, China
  • Received:2012-06-26 Revised:2013-01-04 Online:2013-07-20 Published:2013-07-20

摘要:

论文选择影响碳排放绩效的主要指标,基于熵值法确定各指标权重,采用系统聚类分析的方法,以中国省域为研究对象,将全国分为7类区域。分析结果显示:区域分工特征是造成目前中国省级碳排放绩效区域差异的主要影响因素,其次是高碳产业工艺特征和能源结构特征,而经济结构对解释省级碳排放绩效区域差异的贡献有限。北方地区高碳产品生产份额高且工艺水平相对低,能源消费中极高的煤炭比例加重了负面影响,造成其二氧化碳排放绩效水平低,特别是华北地区;近年来东南沿海地区高碳产业也逐步增加,但由于其工艺先进,在一定程度上抵消了高碳产品份额高的负面影响;中西部地区目前高碳产品份额虽然低于东部地区,但工艺水平也低,造成了其低水平的二氧化碳排放绩效。由于各省历史发展、自然资源禀赋、区域分工角色等因素不同,且遵从经济宏观发展客观规律和经济区位理论,除了少数发达地区之外,中国其他区域短时间内很难改变其经济和能源结构,低碳政策制定的重点应放在提高高碳产业工艺水平方面。

关键词: 环境科学, 碳排放绩效, 熵值法, 区域差异, 聚类分析

Abstract:

The main influencing factors of carbon emission performance include economic structure, energy consumption structure, regional division of work and technical level of high-carbon industry. Although these indicators are in a certain degree of influence on CO2 emissions per unit of GDP, it is difficult to measure the contribution of each indicator. In this paper, we selected the four main indicators mentioned, according to the entropy method to measure the weight of each indicator, applying multi-indicators cluster analysis methods under the index system, and dividing the whole country into 7 typical areas. The analysis result shows: the characteristic of the regional division of work, which has the largest weight of 0.4567, is the main factor resulting in regional differences in China’s provincial carbon emissions performance, then the energy structure and the technical characteristics of high carbon industry take the second place. The indicator of economic structure, with a weight of 0.0971, has a limited contribution to explain the regional differences at the provincial level of carbon emissions. In northern regions, the high share of high-carbon production market and low technical level results in low carbon emission performance. Especially in North China, the high proportion of coal in the energy consumption has a negative effect on carbon emission performance; in southeast coastal areas, due to its advanced technology, the negative effect from high share of high-carbon production has been offset to some degree; although the share of high-carbon production in central and western China is much lower than in the eastern regions at present, yet the technical level is low. The carbon emission performance decreased with a backward technical level. There are differences among the historical development of provinces; natural resource endowment and regional division of work, complying with the macroeconomic development of objective laws and economic location theory, in addition to a small number of developed areas, the other regions in China are difficult to change their economic and energy structure in a short period of time. The low-carbon policies should be focused on improving the technical level of high-carbon industries.

Key words: environmental science, carbon emission performance, entropy method, regional differences, cluster analysis

中图分类号: 

  • X321