江苏省能源消费结构对碳排放影响的效应与趋势——基于LMDI和Logistics模型的实证研究
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摘要
近年来,江苏省能源消费持续增长且以煤为主的能源结构尚未改变,由此引起碳排放量也在逐年增加.主要研究碳排放系数、碳排放的影响因素以及不同能源结构下的碳排放预测.首先对碳排放系数进行计算,然后基于LMDI模型对影响江苏省碳排放的因素进行分析,最后运用1ogistics模型对不同能源结构下的碳排放进行预测.结果发现能源消费过度依赖煤炭是导致碳排放增加的主要因素,天然气每替代煤炭2%或新能源每替代煤炭1%,2030年江苏省碳排放峰值将下降1%.
In recent years,sustained growth of energy consumption and give priority to with coal energy structure have not changed in Jiangsu province,the resulting carbon emissions are also increasing year by year.This paper mainly study carbon emission coefficient,the influence factors of carbon emissions and carbon emissions under different energy structure prediction.First of all,calculating the carbon emissions coefficient,and then based on LMDI model to analyze the influencing factors of carbon emissions in Jiangsu province,the Logistics model is used to predict carbon emissions under different energy structure.The results show that coal is the main factor to the rise in carbon emissions,natural gas every alternative coal2%or new energy replacing coal 1%,peak will fall 1%of carbon emissions in Jiangsu province in 2030.
In recent years,sustained growth of energy consumption and give priority to with coal energy structure have not changed in Jiangsu province,the resulting carbon emissions are also increasing year by year.This paper mainly study carbon emission coefficient,the influence factors of carbon emissions and carbon emissions under different energy structure prediction.First of all,calculating the carbon emissions coefficient,and then based on LMDI model to analyze the influencing factors of carbon emissions in Jiangsu province,the Logistics model is used to predict carbon emissions under different energy structure.The results show that coal is the main factor to the rise in carbon emissions,natural gas every alternative coal2%or new energy replacing coal 1%,peak will fall 1%of carbon emissions in Jiangsu province in 2030.
引文
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[4]李宏岳,陈然.低碳经济与产业结构调整[J].经济问题探索,2011(1):66-71.
[5]王雨.推进我国能源战略转型的路径选择[J].当代经济研究,2014(3):67-70.
[6]Li Yingjian,Li Jiezhi,Qiu Qi,Xu Yafei.Energy auditing and energy conservation potential for glass works[J].Applied Energy,2010,87:2438-2446.
[7]Zhao Xiaoli,Ma Chunbo,Hong Dongyue.Why did China's energy intensity increase during 1998-2006:Decomposition and policy analysis[J].Energy Policy,2010,38:1379-1388.
[8]D.Charlier,Anna Risch.Evaluation of the impact of environmental public policy measures on energy consumption and greenhouse gas emissions in the French residential sector[J].Energy Policy,2012,46:170-184.
[9]Wu Zhibin,Xu Jiuping.Predicting and optimization of energy consumption using system dynamicsfuzzy multiple objective programming in world heritage areas[J].Energy,2013,49:19-31.
[10]Li Ke,Lin Boqiang.The nonlinear impacts of industrial structure on China's energy intensity[J].Energy,2014,69:258-265.
[11]Zeng Lin,Xu Ming,Liang Sai,Zeng Siyu,Zhang Tianzhu.Revisiting drivers of energy intensity in China during 1997-2007:A structural decomposition analysis[J].Energy Policy,2014,67:640-647.
[12]Peter Mulder,Henri Groot.Dutch sectorial energy intensity developments in international perspective,1987-2005[J].Energy Policy,2013,52:501-512.
[13]国家统计局能源统计司.中国能源统计年鉴(1995-2013)[M].北京:中国统计出版社,(1996-2014).
[14]李国璋,王双.中国能源强度变动的区域因素分解分析——基于LMDI分解方法[J].财经研究,2008(08).
[15]江苏省统计局.江苏统计年鉴2014[M].北京:中国统计出版社,2014.
目录