山西省土地利用的碳排放效率及其优化策略
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摘要
土地利用既是人类社会经济发展的基础,同时也是全球第二大温室气体排放源。随着温室效应日益严重,低碳减排尤其是土地利用过程中的低碳减排逐渐成为人们关注的焦点。近年来,我国经济持续快速增长的同时也造成了碳排放的迅速增加,为了兼顾经济的发展和低碳减排,需要对土地利用碳排放效率进行测算和优化。以土地利用的碳排放技术效率、总效率和规模效率为指标,在数据包络分析(DEA)平台下,运用CCR模式与BCC模式测算了山西省各地级市土地利用过程中能源消耗造成的碳排放的各项效率指标,并对非DEA有效地区的投入产出进行了低碳优化。结果表明,山西省11个地级市中,只有长治和朔州2个市的土地利用碳排放总效率有效。对非DEA有效地区的投入产出进行低碳优化后,得到大同、阳泉、晋城和忻州4个市需要减少地均煤类消耗;太原、晋中市需要降低地均油类消耗;运城、临汾和吕梁市在降低煤耗和油耗的同时,还需对高碳低效的工业用地进行升级转换,积极发展低碳产业。同时,各市都需增加对第一产业和第三产业的投入。研究结果可以为山西省乃至全国的土地利用碳排放效率测算提供参考,同时对相关的低碳减排工作起到了一定的借鉴作用,有利于提高山西省乃至全国的土地低碳利用效率。
The land use is the basis of human social and economic development, at the same time, it is also the second biggest source of the global greenhouse gas emissions. With the greenhouse effect more and more serious, low carbon emission reduction,especially in the process of land use, the reduction of low carbon emissions gradually becomes the focus of people's attention. In the recent years, the continued rapid growth of China economy also has led to the rapid increase in carbon emissions. In order to take into account the development of economy and the reduction of low carbon emission, it is necessary to figure out and optimize the land utilization efficiency of carbon emissions. In this paper, it took the technical effciency, total efficiency and scale efficiency of carbon emissions from land use as the index. Under the platform of DEA, based on the model of CCR and BCC, the various efficiency indicators of carbon emission from energy consumption in the process of land use in Shanxi province were calculated in this paper, and the low-carbon optimization of input and output in non DEA effective area was carried out. The results showed that among the eleven cities of Shanxi province, only the total efficiency of carbon emissions in Changzhi and Shuozhou was effective. After low-carbon optimization of input and output in non-DEA effective areas, four cities, Datong, Yangquan, Jincheng and Xinzhou, needed to reduce average coal consumption,while Taiyuan and Jinzhong needed to reduce the average of ground oil consumption. To reduce coal and fuel consumption at the same time, it was necessary to upgrade the high carbon inefficient industrial land, and actively develop low-carbon industry in Yuncheng,Linfen and Lüliang. At the same time, all cities needed to pay more attention to increasing the investment of the first and third industries.The results of this paper can provide reference for the efficiency of the land use in Shanxi province and even the whole country, and also play a certain reference role for the related low carbon emission reduction work. What's more, the results will help improve the efficiency of land use in Shanxi province and even the whole country.
The land use is the basis of human social and economic development, at the same time, it is also the second biggest source of the global greenhouse gas emissions. With the greenhouse effect more and more serious, low carbon emission reduction,especially in the process of land use, the reduction of low carbon emissions gradually becomes the focus of people's attention. In the recent years, the continued rapid growth of China economy also has led to the rapid increase in carbon emissions. In order to take into account the development of economy and the reduction of low carbon emission, it is necessary to figure out and optimize the land utilization efficiency of carbon emissions. In this paper, it took the technical effciency, total efficiency and scale efficiency of carbon emissions from land use as the index. Under the platform of DEA, based on the model of CCR and BCC, the various efficiency indicators of carbon emission from energy consumption in the process of land use in Shanxi province were calculated in this paper, and the low-carbon optimization of input and output in non DEA effective area was carried out. The results showed that among the eleven cities of Shanxi province, only the total efficiency of carbon emissions in Changzhi and Shuozhou was effective. After low-carbon optimization of input and output in non-DEA effective areas, four cities, Datong, Yangquan, Jincheng and Xinzhou, needed to reduce average coal consumption,while Taiyuan and Jinzhong needed to reduce the average of ground oil consumption. To reduce coal and fuel consumption at the same time, it was necessary to upgrade the high carbon inefficient industrial land, and actively develop low-carbon industry in Yuncheng,Linfen and Lüliang. At the same time, all cities needed to pay more attention to increasing the investment of the first and third industries.The results of this paper can provide reference for the efficiency of the land use in Shanxi province and even the whole country, and also play a certain reference role for the related low carbon emission reduction work. What's more, the results will help improve the efficiency of land use in Shanxi province and even the whole country.
引文
[1]杜克锐,邹楚沅.我国碳排放效率地区差异、影响因素及收敛性分析:基于随机前沿模型和面板单位根的实证研究[J].浙江社会科学,2011(11):32-43.
[2]赖力.中国土地利用的碳排放效应研究[D].南京:南京大学,2010.
[3]曲福田,卢娜,冯淑怡.土地利用变化对碳排放的影响[J].中国人口·资源与环境,2011(10):76-83.
[4]韩召迎,孟亚利,刘丽平,等.基于区域土地利用变化的能源碳足迹改进算法及应用[J].农业工程学报,2012(9):190-195.
[5]游和远,吴次芳.农地集约利用的碳排放效率分析与低碳优化[J].农业工程学报,2014(2):224-234.
[6]吕可文,苗长虹,尚文英.工业能源消耗碳排放行业差异研究:以河南省为例[J].经济地理,2012(12):15-20.
[7]张梅,赖力,黄贤金,等.中国区域土地利用类型转变的碳排放强度研究[J].资源科学,2013(4):792-799.
[8]赵荣钦,陈志刚,黄贤金,等.南京大学土地利用碳排放研究进展[J].地理科学,2012(12):1473-1480.
[9]游和远,吴次芳,沈萍.土地利用结构与能源消耗碳排放的关联测度及其特征解释[J].中国土地科学,2010(11):4-9.
[10]赵荣钦,黄贤金,钟太洋,等.区域土地利用结构的碳效应评估及低碳优化[J].农业工程学报,2013(17):220-229.
[11]李颖,黄贤金,甄峰.江苏省区域不同土地利用方式的碳排放效应分析[J].农业工程学报,2008(Z2):102-107.
[12]R DDER W,REUCHER E.Advanced X-efficiencies for CCR-and BCC-models-towards Peer-based DEA controlling[J].European Journal of Operational Research,2012,219(2):467-476.
[13]马霜.基于DEA方法的我国商业银行效率的比较研究[D].成都:西南财经大学,2012.
[14]MENG W,ZHANG D Q,QI L,et al.Two-level DEA approaches in research evaluation[J].Omega,2008,36(6):950-957.
[15]EDERER NIKOLAUS.Evaluating capital and operating cost efficiency of offshore wind farms:A DEA approach[J].Renewable and Sustainable Energy Reviews,2015,42:1034-1046.
[16]BANKER R D,CHARNES A,COOPER W W.Some models for estimating technical and scale inefficiencies in data envelopment analysis[J].Management Science,1984,30(9):1078-1092.
[17]REINHARD STIJN,KNOX LOVELL C A,THIJSSEN GEERT J.Environmental efficiency with multiple environmentally detrimental variables;estimated with SFA and DEA[J].European Journal of Operational Research,2000,121(2):287-303.
[18]HAILU ATAKELTY,VEEMAN TERRENCE S.Non-parametric productivity analysis with undesirable outputs:an application to the canadian pulp and paper industry[J].American Journal of A-gricultural Economics,2003,85(85):1075-1077.
[19]BUONANNO PAOLO,CARRARO CARLO,GALEOTTI MARZIO.Endogenous induced technical change and the costs of Kyoto[J].Resource and Energy Economics,2003,25(1):11-34.
[20]国家统计局工业交通统计司.中国能源统计年鉴2008[M].北京:中国统计出版社,2009.
[21]山西省统计局.山西统计年鉴2010[M].北京:中国统计出版社,2010.
[22]LBRECHT JOHAN,FRAN OIS DELPHINE,SCHOORS KOEN.Ashapley decomposition of carbon emissions without residuals[J].Energy Policy,2002,30(9):727-736.
[23]IPCC.Climate change 2007:the physical science basis:contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change[M].Cambridge:Cambridge University Press,2007:539-542
[24]ZHANG M,MU H L,NING Y D,et al.Decomposition of energy-related CO2emission over 1991-2006 in China[J].Ecological Economics,2009,68(7):2122-2128.
[25]王铮,朱永彬.我国各省区碳排放量状况及减排对策研究[J].中国科学院院刊,2008(2):109-115.
[26]COOPER WILLIAM W,TONE KAORU,SEIFORD LAWRENCEM.Data envelopment analysis:A comprehensive text with models,applications references,and DEA-Solver software with cdrom[J].Journal of the Operational Research Society,2001,52(12):145-156.
[27]TONE KAORU.A slacks-based measure of efficiency in data envelopment analysis[J].European Journal of Operational Research,2001,130(3):498-509.
[28]国务院发展研究中心.2050中国能源和碳排放报告[M].北京:科学出版社,2009.
[29]张伟,朱启贵,李汉文.能源使用、碳排放与我国全要素碳减排效率[J].经济研究,2013(10):138-150.
[30]张苗,甘臣林,陈银蓉,等.中国城市建设用地开发强度的碳排放效率分析与低碳优化[J].资源科学,2016(2):265-275.
[2]赖力.中国土地利用的碳排放效应研究[D].南京:南京大学,2010.
[3]曲福田,卢娜,冯淑怡.土地利用变化对碳排放的影响[J].中国人口·资源与环境,2011(10):76-83.
[4]韩召迎,孟亚利,刘丽平,等.基于区域土地利用变化的能源碳足迹改进算法及应用[J].农业工程学报,2012(9):190-195.
[5]游和远,吴次芳.农地集约利用的碳排放效率分析与低碳优化[J].农业工程学报,2014(2):224-234.
[6]吕可文,苗长虹,尚文英.工业能源消耗碳排放行业差异研究:以河南省为例[J].经济地理,2012(12):15-20.
[7]张梅,赖力,黄贤金,等.中国区域土地利用类型转变的碳排放强度研究[J].资源科学,2013(4):792-799.
[8]赵荣钦,陈志刚,黄贤金,等.南京大学土地利用碳排放研究进展[J].地理科学,2012(12):1473-1480.
[9]游和远,吴次芳,沈萍.土地利用结构与能源消耗碳排放的关联测度及其特征解释[J].中国土地科学,2010(11):4-9.
[10]赵荣钦,黄贤金,钟太洋,等.区域土地利用结构的碳效应评估及低碳优化[J].农业工程学报,2013(17):220-229.
[11]李颖,黄贤金,甄峰.江苏省区域不同土地利用方式的碳排放效应分析[J].农业工程学报,2008(Z2):102-107.
[12]R DDER W,REUCHER E.Advanced X-efficiencies for CCR-and BCC-models-towards Peer-based DEA controlling[J].European Journal of Operational Research,2012,219(2):467-476.
[13]马霜.基于DEA方法的我国商业银行效率的比较研究[D].成都:西南财经大学,2012.
[14]MENG W,ZHANG D Q,QI L,et al.Two-level DEA approaches in research evaluation[J].Omega,2008,36(6):950-957.
[15]EDERER NIKOLAUS.Evaluating capital and operating cost efficiency of offshore wind farms:A DEA approach[J].Renewable and Sustainable Energy Reviews,2015,42:1034-1046.
[16]BANKER R D,CHARNES A,COOPER W W.Some models for estimating technical and scale inefficiencies in data envelopment analysis[J].Management Science,1984,30(9):1078-1092.
[17]REINHARD STIJN,KNOX LOVELL C A,THIJSSEN GEERT J.Environmental efficiency with multiple environmentally detrimental variables;estimated with SFA and DEA[J].European Journal of Operational Research,2000,121(2):287-303.
[18]HAILU ATAKELTY,VEEMAN TERRENCE S.Non-parametric productivity analysis with undesirable outputs:an application to the canadian pulp and paper industry[J].American Journal of A-gricultural Economics,2003,85(85):1075-1077.
[19]BUONANNO PAOLO,CARRARO CARLO,GALEOTTI MARZIO.Endogenous induced technical change and the costs of Kyoto[J].Resource and Energy Economics,2003,25(1):11-34.
[20]国家统计局工业交通统计司.中国能源统计年鉴2008[M].北京:中国统计出版社,2009.
[21]山西省统计局.山西统计年鉴2010[M].北京:中国统计出版社,2010.
[22]LBRECHT JOHAN,FRAN OIS DELPHINE,SCHOORS KOEN.Ashapley decomposition of carbon emissions without residuals[J].Energy Policy,2002,30(9):727-736.
[23]IPCC.Climate change 2007:the physical science basis:contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change[M].Cambridge:Cambridge University Press,2007:539-542
[24]ZHANG M,MU H L,NING Y D,et al.Decomposition of energy-related CO2emission over 1991-2006 in China[J].Ecological Economics,2009,68(7):2122-2128.
[25]王铮,朱永彬.我国各省区碳排放量状况及减排对策研究[J].中国科学院院刊,2008(2):109-115.
[26]COOPER WILLIAM W,TONE KAORU,SEIFORD LAWRENCEM.Data envelopment analysis:A comprehensive text with models,applications references,and DEA-Solver software with cdrom[J].Journal of the Operational Research Society,2001,52(12):145-156.
[27]TONE KAORU.A slacks-based measure of efficiency in data envelopment analysis[J].European Journal of Operational Research,2001,130(3):498-509.
[28]国务院发展研究中心.2050中国能源和碳排放报告[M].北京:科学出版社,2009.
[29]张伟,朱启贵,李汉文.能源使用、碳排放与我国全要素碳减排效率[J].经济研究,2013(10):138-150.
[30]张苗,甘臣林,陈银蓉,等.中国城市建设用地开发强度的碳排放效率分析与低碳优化[J].资源科学,2016(2):265-275.