东北大学学报:自然科学版 ›› 2017, Vol. 38 ›› Issue (2): 300-304.DOI: 10.12068/j.issn.1005-3026.2017.02.030

• 管理科学 • 上一篇    

基于STIRPAT及解耦模型的河北省碳排放影响因素分析

杨沫, 陈凯   

  1. (东北大学 工商管理学院, 辽宁 沈阳110169)
  • 收稿日期:2016-07-15 修回日期:2016-07-15 出版日期:2017-02-15 发布日期:2017-03-03
  • 通讯作者: 杨沫
  • 作者简介:杨沫(1983-),女,河北秦皇岛人,东北大学博士研究生; 陈凯(1961-),男,山西浑源人,东北大学教授,博士生导师.
  • 基金资助:
    国家社会科学基金重大资助项目(15ZDC034).

Influencing Factors of Carbon Emissions in Hebei Province Based on the STIRPAT and Decoupling Models

YANG Mo, CHEN Kai   

  1. School of Business Administration, Northeastern University, Shenyang 110169, China.
  • Received:2016-07-15 Revised:2016-07-15 Online:2017-02-15 Published:2017-03-03
  • Contact: YANG Mo
  • About author:-
  • Supported by:
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摘要: 运用解耦模型分析了2007年—2014年河北省的解耦状态:从增长性耦合到弱解耦,在波动中实现了强解耦.运用STIRPAT模型分析河北省碳排放影响因素,利用灰色模型GM(1,1)预测河北省2015年—2022年碳排放量,结果显示:产业结构对河北省碳排放影响最大;煤炭消费量、人均GDP、城镇人口占比、人口数对河北省碳排放量有促进作用,能源价格和研究与发展经费支出对河北省碳排放量的影响系数较小;能源结构、能源强度对河北省碳排放量有一定的抑制作用.GM(1,1)模型预测结果显示:应当重视河北省碳排放量的发展趋势,正视低碳发展的压力,通过调整各影响因素实现河北省低碳经济.

关键词: STIRPAT模型, 解耦模型, 碳排放, 影响因素, 因子分析, GM(1, 1)

Abstract: The decoupling state of Hebei Province from 2007 to 2014 was analyzed by using the decoupling model, and the results showed that the decoupling state has changed from the growing coupling to the weak decoupling, which finally realizes the strong decoupling in volatility. The influencing factors of carbon emission in Hebei Province were analyzed by using the STIRPAT model, and the carbon emission of 2015-2022 in Hebei Province was predicted by using the grey model GM (1, 1). The results showed: industrial structure has the biggest influence on carbon emission; coal consumption, per capita GDP, urban population proportion and overall population have promoting effect on carbon emission, while energy price and expenditure on R&D have a small influence coefficient on carbon emission; and energy structure and energy intensity have a certain inhibitory effect on carbon emission. The prediction results from the GM (1, 1) model showed that Hebei Province should pay greater attention to the development trend of carbon emission, face the pressure of low carbon development, and achieve low carbon economy in Hebei Province by adjusting all the influencing factors.

Key words: STIRPAT model, decoupling model, carbon emission, influencing factor, factor analysis, GM (1, 1)

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