西南石油大学学报(社会科学版) ›› 2020, Vol. 22 ›› Issue (2): 11-20.DOI: 10.11885/j.issn.1674-5094.2019.09.26.03

• 能源发展研究 • 上一篇    下一篇

山东省碳排放驱动因素的效应

公维凤, 戚晓红, 王玥   

  1. 曲阜师范大学经济学院, 山东 日照 276826
  • 收稿日期:2019-09-26 出版日期:2020-03-01 发布日期:2020-03-01
  • 通讯作者: 戚晓红(1995-),女(汉族),山东临沂人,硕士研究生,研究方向:能源经济。
  • 作者简介:公维凤(1979-),女(汉族),山东临沂人,副教授,博士,研究方向:能源经济。
  • 基金资助:
    国家自然科学基金项目“宏微观联动视角下区域碳排放达峰机制及实现路径研究”(71804089);教育部人文社科基金项目“区域碳排放联动达峰的实现路径研究:以环渤海经济区为例”(18YJCZH034)。

Effects of the Driving Factors of Carbon Emission in Shandong Province

GONG Weifeng, QI Xiaohong, WANG Yue   

  1. School of Economics, Qufu Normal University, Rizhao Shandong, 276826, China
  • Received:2019-09-26 Online:2020-03-01 Published:2020-03-01

摘要: 作为我国的经济强省,山东省经济发展主要依靠以煤炭为主导的能源密集型产业。近年来,为了实现经济绿色发展,山东省相继出台了一系列低碳发展政策。利用LMDI方法进行因素分解,以探究山东省碳排放驱动因素的效应。结果表明:经济产出效应、能源消费结构效应、产业结构效应会促进碳排放量的增长,而能源强度效应则会抑制碳排放量的增长。其中,经济产出效应是影响山东省碳排放的最主要因素。同时,灰色模型预测未来山东省碳排放量将会增加。鉴于此,应通过优化能源消费结构、对高碳行业通过新旧动能转换实现产业结构转型、提升公民环保意识等措施,促进山东省早日实现减排达峰的目标,最终实现绿色可持续发展。

关键词: 碳排放, 驱动因素, LMDI方法, 灰色理论, Verhulst模型

Abstract: Shandong, a large economic province in China, relies mainly on coal-based energy-intensive industries for its economic development. Carbon emission problem has become increasingly prominent has aggravated air pollution in the province. In order to achieve green economic development, Shandong Province has issued a series of low-carbon development programs and policies. The LMDI method is used for decomposition analysis of the effects of the driving factors of carbon emission in Shandong Province. The results show that economic output, energy consumption structure and industrial structure are factors that promote the growth of carbon emissions, and energy intensity will inhibit the growth of carbon emissions. In addition, the gray Verhulst model is used to predict the overall trend of carbon emissions in Shandong Province in the future. Based on the above analyses,policy recommendations are proposed for the development and implementation of energy conservation and emission reduction.

Key words: carbon emission, driving factor, LMDI method, gray theory, Verhulst model

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