基于STIRPAT模型的中国碳排放EKC验证及影响因素分析
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摘要
研究基于改进的STIRPAT模型和中国1971-2015年时间序列数据,验证了碳排放经典环境库兹涅茨曲线假说在中国的存在性,定量分析了经济规模、能源强度、能源结构、产业结构和人口结构等变量对碳排放总量和人均碳排放量的影响。结果表明:中国碳排放量拐点要早于人均碳排放拐点出现,这主要是由于经济发展与碳排放有逐步脱钩的趋势,居民生活消费碳排放增加趋势明显。各变量对碳排放总量和人均碳排放的影响系数都为正,对碳排放总量和人均碳排放都有正向促进作用。GDP是碳排放总量和人均碳排放首要影响因素。降低能源强度,提高能源效率是降低碳排放量,兑现我国在国际社会的碳减排承诺最为有效和可行的举措。
Based on the improved STIRPAT model and time series data from 1971 to 2015 in China,the existence of the classical environmental Kuznets Curve Hypothesis of carbon emission in China was verified,and the economic scale,energy intensity,energy structure,industrial structure and population structure were quantitatively analyzed of their impact on total carbon emissions and per capita carbon emissions.The results show that China's carbon emission inflection point is earlier than the per capita carbon emission inflection point,which is mainly due to the gradual decoupling of economic development and carbon emissions,and the increase in household consumption carbon emissions is obvious.The variables have a positive impact on total carbon emissions and per capita carbon emissions,and positively contribute to total carbon emissions and per capita carbon emissions.GDP is the primary factor affecting total carbon emissions and per capita carbon emissions.Reducing energy intensity and improving energy efficiency are the most effective and feasible measures to reduce carbon emissions and fulfill China's carbon emission reduction commitments in the international community.
Based on the improved STIRPAT model and time series data from 1971 to 2015 in China,the existence of the classical environmental Kuznets Curve Hypothesis of carbon emission in China was verified,and the economic scale,energy intensity,energy structure,industrial structure and population structure were quantitatively analyzed of their impact on total carbon emissions and per capita carbon emissions.The results show that China's carbon emission inflection point is earlier than the per capita carbon emission inflection point,which is mainly due to the gradual decoupling of economic development and carbon emissions,and the increase in household consumption carbon emissions is obvious.The variables have a positive impact on total carbon emissions and per capita carbon emissions,and positively contribute to total carbon emissions and per capita carbon emissions.GDP is the primary factor affecting total carbon emissions and per capita carbon emissions.Reducing energy intensity and improving energy efficiency are the most effective and feasible measures to reduce carbon emissions and fulfill China's carbon emission reduction commitments in the international community.
引文
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[2]卫平,周亚细.城市化、能源消费与碳排放——基于STIRPAT模型的跨国面板数据实证研究[J].生态经济,2014,30(9):14-18.
[3]徐安.基于STIRPAT模型的沿黄省份城市化对碳排放的影响分析[Z].黄河流域资源环境与生态文明建设学术研讨会交流材料,2011.
[4]冯玲,吝涛,赵千钧.城镇居民生活能耗与碳排放动态特征分析[J].中国人口·资源与环境,2011,21(5):93-100.
[5]郭朝先.国碳排放因素分解:基于LMDI分解技术[J].中国人口·资源与环境,2010,20(12):4-9.