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中国能源消费碳排放的时空差异及驱动因素研究
引用本文:张馨.中国能源消费碳排放的时空差异及驱动因素研究[J].干旱区地理,2018,41(5):1115-1122.
作者姓名:张馨
作者单位:陕西省社会科学院经济研究所, 陕西 西安 710065
基金项目:国家社科基金青年项目(15CJY034)
摘    要:随着气候变化日益加剧,碳排放及其影响越来越受到人们的关注。针对我国30个省区2000-2015年终端能源消费产生的碳排放进行核算,分析中国能源消费碳排放的区域特征和时空差异,并通过STIRPAT模型和面板数据模型相结合的方法从碳排放量和碳排放强度两个视角对碳排放的驱动因素进行分析。研究发现,从全国层面来看,人口规模、人均GDP、能源强度以及城市化水平对碳排放量产生正向的驱动作用,即每提升1%,碳排放量将分别增加1.046 9%、0.938 6%、0.722 6%、0.411 6%,而产业结构对碳排放具有负向的驱动效应。对于碳排放强度而言,人均GDP和产业结构均产生负向的抑制作用。从区域层面来看,通过经济水平分组,东、中、西部三大区域由于经济发展水平的差异,各个因素对碳排放的影响也有所不同并表现出一定的规律性;城市化水平分组表现出随着城市化水平的提高,碳排放量也随之降低。通过研究,可为我国合理制定CO2减排的区域差异化政策提供参考依据。

关 键 词:碳排放  STIRPAT模型  面板数据  驱动因素  
收稿时间:2018-03-21

Spatial-temporal differences and driving factors of carbon emission from energy consumption in China
ZHANG Xin.Spatial-temporal differences and driving factors of carbon emission from energy consumption in China[J].Arid Land Geography,2018,41(5):1115-1122.
Authors:ZHANG Xin
Institution:Institute of Economics, Shaanxi Academy of Social Sciences, Xi'an 710065, Shaanxi, China
Abstract:With the accelerating climate change,the carbon emission and its influence are paid more and more attention.This paper calculated the carbon emissions from energy consumption covered 30 provinces from 2000 to 2015,and analyzed the regional characteristics and spatial-temporal differences of carbon emissions in China.Based on the STIRPAT model and panel data model,the driving factors of carbon emissions were analyzed from two perspectives of carbon emissions and carbon intensity.The study found that,at the national level,the population scale,per capita GDP,energy intensity and urbanization level have positive driving effect,and 1% increase in each factor,the carbon emissions will be increased by 1.046 9%,0.938 6%,0.722 6%,0.411 6%,respectively.However the industrial structure has negative effect on carbon emissions.For carbon intensity,per capita GDP and industrial structure have negative inhibitory effect.At the regional level,three economic regions of the East,Middle and West regions of China were defined by grouping the individual areas based on their economic level.Due to the difference of economic development level,the effects of each factor on carbon emissions were also different and show a certain regularity.The grouping by urbanization level showed that carbon emissions have been decreased along with the increase of urbanization level.This study provided a reference for the government to make a reasonable and differentiated policy about CO2 emission reduction based on the region.
Keywords:carbon emission  STIRPAT model  panel data  driving factors  
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