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• 管理科学 •    下一篇

中国碳排放影响因素分析和趋势预测??——基于STIRPAT 和GM(1,1)模型的实证研究

佟昕1,陈凯2   

  1. 1. 东北大学 工商管理学院
    2. 东北大学 工商管理学院 东北大学秦皇岛分校经贸学院
  • 收稿日期:2014-05-12 修回日期:2014-06-23 出版日期:2015-02-15 发布日期:2014-11-07
  • 通讯作者: 佟昕
  • 基金资助:
    经济理论体系融合创新研究;区域创新体系知识溢出机制和协同创新模式研究

China Carbon Emission Factors Analysis and Trend Forecasting:Empirical Study Based on STIRPAT and GM (1,1) Model

  • Received:2014-05-12 Revised:2014-06-23 Online:2015-02-15 Published:2014-11-07

摘要: 本文采用STIRPAT模型首次全面地对影响中国2000~2011年碳排放的因素进行分析,并利用灰色模型GM(1,1)预测了中国2012~2020年碳排放量。研究结果显示:城镇化率、经济增长、产业结构、能源价格、人口、能源结构和外贸强度对碳排放量有一定的促进作用,技术进步对碳排放量具有较强的抑制作用;其中对中国碳排放量增加影响较大的因素是人口和产业结构;利用GM(1,1)预测模型可以得出中国2020年碳排放量将为2011年的222.54%。因此,应该理性看待中国碳排放问题,加快低碳经济发展模式转变

关键词: 碳排放, STIRPAT模型, GM(1,1)模型, carbon emissions, STIRPAT model, GM (1,1) model

Abstract: In this paper, first comprehensive analyzed the factors that influence Chinese carbon emissions used on STIRPAT model and predict China from 2012 to 2020 carbon emissions based of gray model GM (1,1). The results show that: the rate of urbanization, economic growth, industrial structure, energy prices, population, energy structure and foreign trade carbon emissions intensity has some role in promoting technological progress on carbon emissions has a strong inhibitory effect; which for China a large increase in carbon emissions factors affecting the population and industrial structure; utilize GM (1,1) prediction model can be drawn Chinese carbon emissions in 2020 will be 2011 of 222.54%. Therefore, it should be a rational view of China's carbon emissions, reduce carbon emissions to promote and achieve emission reduction targets, should accelerate the optimization of industrial structure and energy consumption structure, and actively develop the use of clean energy, accelerate the conversion of the energy-intensive export industries depend , vigorously popularize low-carbon development and propaganda work.