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中国区域产业CO2排放影响因素研究:不同经济增长阶段的视角

潘文卿等   

  • 出版日期:2017-03-15 发布日期:2017-03-27

A Study on Factors of Regional Industrial Carbon Emission in China: Based On the Perspective of Different Economic Growth Stages

Pan Wenqing et al.   

  • Online:2017-03-15 Published:2017-03-27

摘要: 本文运用LMDI方法,采用“三层完全分解法”,对中国1997—2014年的CO2排放总量进行分解,探讨中国8大区域的CO2排放特征及其对全国碳排放的贡献,并从能源结构、能源强度、产业结构、人均产出、人口结构及人口总量6大因素对CO2排放进行因素分析。文章基于CO2排放增长与经济增长联系紧密的基本特征,分4个阶段考察了区域CO2排放特征与各因素的影响差异。研究发现:8大区域中,京津地区和南部沿海对全国碳排放增长的贡献最小,中部地区和北部沿海的贡献最大,西北地区的贡献呈上升趋势;影响CO2排放的因素中,人均产出的变动为主要助长性因素,能源强度的变化为主要抑制性因素,能源结构变动的助长性逐年减弱,并在近年成为抑制性因素;2007年之后,随着经济增长的放缓,产业结构也由助长性因素转为制约性因素。据此,本文给出了中国需要协调区域发展、优化区域产业布局,升级产业结构、改善能源使用的技术与结构、提高能源利用效率等相关政策建议。

关键词: CO2排放, 能源消费, 区域结构, 产业结构, 经济增长

Abstract: Using the LMDI method and “Three Tier Complete Decomposition”, this paper decomposes the total Carbon Emission of China from 1997 to 2014, and discusses the contributions of 8 regions in China, due to 6 factors, which are Energy Structure, Energy Intensity, Industrial Structure, Per Capita GDP, Population Structure and Population. Based on the tide connection between Carbon Emission Growth and Economic Development, this paper divides the whole period into 4 parts, and analyzes the differences of features of regional carbon emission and factor influences. The conclusions are: Among the 8 regions, Bei-Jing and Tian-jin District and the Northeast District have the least contributions to the whole country’s carbon emission growth, and the Central District and the Northwest District have the largest contributions with an uplifting trend. Among the 6 factors influencing carbon emission, Per Capital GDP is the main driving factor while the Energy Intensity is the main suppressing factor. Accordingly, this paper provides policy proposals, including coordinating inter-regional developments, optimizing regional sector distributions, upgrading industrial structures, improving the technology and structure of energy using, and developing the efficiency of energy using.

Key words: Carbon Emission, Energy Consumption, Regional Structure, Industrial Structure, Economic Growth.