基于SBM-DEA模型的工业碳减排潜力与影响因素分析
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摘要
践行绿色发展理念,推进工业碳减排是湖南省实施"一带一部"战略的有效途径。运用非期望产出超效率SBM-DEA模型对湖南省14个市州2007—2016年的工业碳减排潜力进行测算,运用面板数据模型对碳减排压力大中小地区的碳减排影响因素进行分析。结果表明:因地域因素、产业结构、工业结构等差异,湖南各市州工业二氧化碳排放量和碳减排潜力各不相同;长沙等3市州,工业节能减排成效好、减排潜力小;长沙要加速科技发展带动经济发展,张家界和湘西州要加强绿色旅游业发展;湘潭等5市州,二氧化碳排放量较多,工业碳排放潜力大;湘潭、常德、益阳、郴州、娄底,要优化产业结构,推动资本要素高质量深化发展;株洲等6市,工业碳减排潜力居中;株洲、衡阳、邵阳、岳阳、永州、怀化,要通过技术改造、产业转型升级等举措达到节能减排效果。
Implementing the concept of green development and promoting industrial carbon emission reduction are effective ways for Hunan Province to implement the "one belt, one department" strategy. In this paper, the unexpected output super-efficiency SBM-DEA model is applied to calculate the industrial carbon emission reducing potential of 14 cities in Hunan Province from 2007 to 2016. The panel data model is used to analyze the influencing factors of carbon emission reduction in small and medium-sized areas under pressure of carbon emission reduction. The results show that due to regional factors, industrial structure, manufacturing structure and other differences, the industrial carbon dioxide emissions and carbon emission reduction potential of Hunan provinces are different. In Changsha and other three cities,there is a good effect of industrial energy conservation andemission reduction, and the emission reduction potential is small; Changsha should accelerate the development of science and technology to promote economic development,Zhangjiajie and Xiangxi region should strengthen green tourism development; Xiangtan and other 5 cities have more carbon dioxide emissions and larger industrial carbon emissions; Xiangtan, Changde, Yiyang, Chenzhou, Loudi, should optimize the industrial structure, to promote the high quality and deepening development of capital elements; Zhuzhou and other six cities, industrial carbon emission reduction potential are in the middle; Zhuzhou, Hengyang, Shaoyang,Yueyang, Yongzhou, Huaihua should through technological reformation, industrial transformation and upgrading to achieve the goal of energy saving and emission reduction.
Implementing the concept of green development and promoting industrial carbon emission reduction are effective ways for Hunan Province to implement the "one belt, one department" strategy. In this paper, the unexpected output super-efficiency SBM-DEA model is applied to calculate the industrial carbon emission reducing potential of 14 cities in Hunan Province from 2007 to 2016. The panel data model is used to analyze the influencing factors of carbon emission reduction in small and medium-sized areas under pressure of carbon emission reduction. The results show that due to regional factors, industrial structure, manufacturing structure and other differences, the industrial carbon dioxide emissions and carbon emission reduction potential of Hunan provinces are different. In Changsha and other three cities,there is a good effect of industrial energy conservation andemission reduction, and the emission reduction potential is small; Changsha should accelerate the development of science and technology to promote economic development,Zhangjiajie and Xiangxi region should strengthen green tourism development; Xiangtan and other 5 cities have more carbon dioxide emissions and larger industrial carbon emissions; Xiangtan, Changde, Yiyang, Chenzhou, Loudi, should optimize the industrial structure, to promote the high quality and deepening development of capital elements; Zhuzhou and other six cities, industrial carbon emission reduction potential are in the middle; Zhuzhou, Hengyang, Shaoyang,Yueyang, Yongzhou, Huaihua should through technological reformation, industrial transformation and upgrading to achieve the goal of energy saving and emission reduction.
引文
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[22]孙作人,周德群,周鹏,等.基于环境ZSG-DEA的我国省区节能指标分配[J].系统工程,2012,30(1):84-90.
[23]邓集文,牛慧铭.中国城市环境邻避风险的生成逻辑--基于案例嵌入的分析[J].中南林业科技大学学报(社会科学版),2018,12(5):1-7.
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[25]杨青山,张郁,李雅军.基于DEA的东北地区城市群环境效率评价[J].经济地理,2012,32(9):51-55+60.
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[29]刘翔,陈晓红.我国低碳经济发展效率的动态变化及碳减排潜力分析[J].系统工程,2017,35(5):92-100.
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[31]张军,吴桂英,张吉鹏.中国省际物质资本存量估算:1952-2000[J].经济研究,2004(10):35-44.
[32]王兵,王秋彬.工业行业能源效率与工业结构优化升级--年省际面板数据的实证研究[J].数量经济技术经济研究,2010(10):49-62.
[31]许士春,何正霞,龙如银.环境政策工具比较:--基于企业减排的视角[J].系统工程理论与实践,2012,32(11):2351-2362.
[2]段蒙,项定先,卢腾飞,等.武汉市钢铁行业碳减排潜力及成本分析[J].中国人口·资源与环境,2016,26(5):41-44.
[3]吴常艳,黄贤金,揣小伟.基于EIO-LCA的江苏省产业结构调整与碳减排潜力分析[J].中国人口·资源与环境,2015(4):43-51.
[4]张巍.陕西省工业碳减排潜力估算[J].能源技术与管理,2017,42(5):1-3.
[5]王勇,毕莹,王恩东.中国工业碳排放达峰的情景预测与减排潜力评估[J].中国人口.资源与环境,2017,27(10):131-140.
[6]韩中合,祁超,刘明浩.基于要素价格替代弹性的碳排放潜力测算研究[J].中国人口.资源与环境,2016(5):32-36.
[7]冉锦成,马惠兰,苏洋.西北五省农业碳排放测算及碳排放潜力研究[J].江西农业大学学报,2017,39(3):623-632.
[8]郭炳男,曹国勇.中国各省份碳排放效率与减排潜力测度研究[J].生态经济,2017,33(8):20-24.
[9]李灵杰,吴群琪.中国省域交通运输经济发展与碳排放的联合动态性分析[J].西安财经学院学报,2017,30(6):44-49.
[10]邓吉祥,刘晓,王铮.中国碳排放的区域差异及演变特征分析与因素分解[J].自然资源学报,2014,29(2):189-200.
[11]Mika Kortelainen,Dynamic Environmental Performance Analysis:A Malmquist Index Approach.Ecological Economics[J].2007,64(1):23-30.
[12]Luciano Charlita De Freitas,Shinji Kaneko.Decomposing the decoupling of CO2 emission and economic growth in Brazil[J].Ecological Economic,2011,70(8):1 459-1 469.
[13]Zhang Xiaoqing,Ren Jianlan.The relationship between carbon dioxide emissions and industrial structure adjustment in shandong province[J].Energy Procedia,2011(5):1 121-1 125.
[14]陈诗一.中国碳排放强度的波动下降模式及经济解释[J].世界经济,2011(4):36-43.
[15]查建平,唐方方,郑浩生.什么因素多大程度上影响到工业碳排放绩效---来自中国(2003~2010)省级工业面板数据的证据[J].经济理论与经济管理,2013(1):78-84.
[16]杜立民.中国二氧化碳排放的影响因素:基于省级面板数据的研究[J].南方经济,2010(11):21-25.
[17]李艳梅,张雷,程晓凌.中国碳排放变化的因素分解与减排途径分析[J].资源科学,2010,32(2):218-222.
[18]程叶青,王哲野,张守志,等.中国能源消费碳排放强度及其影响因素的空间计量[J].地理学报,2013,68(10):1418-1431.
[19]朱勤,彭希哲,陆志明,等.人口与消费对碳排放影响的分析模型与实证[J].中国人口·资源与环境,2010,20(2):98-102.
[20]孙建卫,赵荣钦,黄贤金,等.1995-2005年中国碳排放核算及其因素分解研究[J].自然资源学报,2010,25(8):1284-1295.
[21]郑凌霄,周敏.技术进步对中国碳排放的影响--基于变参数模型的实证分析[J].科技管理研究,2014(11):215-220.
[22]孙作人,周德群,周鹏,等.基于环境ZSG-DEA的我国省区节能指标分配[J].系统工程,2012,30(1):84-90.
[23]邓集文,牛慧铭.中国城市环境邻避风险的生成逻辑--基于案例嵌入的分析[J].中南林业科技大学学报(社会科学版),2018,12(5):1-7.
[24]李海东,汪斌,熊贝贝,等.基于改进的ISBM-DEA模型的区域环境效率实证研究[J].系统工程,2012,30(7):86-93.
[25]杨青山,张郁,李雅军.基于DEA的东北地区城市群环境效率评价[J].经济地理,2012,32(9):51-55+60.
[26]江三良,刘涵.技术进步对中国区域环境质量的影响研究--基于污染排放的视角[J].中南林业科技大学学报(社会科学版),2017,11(1):5-11.
[27]Tone K.A slacks-based measure of super-efficiency in data envelopment analysis[J].European Journal of Operational Research,2001,143(1):32-41.
[28]Tone K,Sahoo B K.Degree of scale economies and congestion:Aunified DEA approach[J].European Journal of Operational Research,2004,158(3):755-772.
[29]刘翔,陈晓红.我国低碳经济发展效率的动态变化及碳减排潜力分析[J].系统工程,2017,35(5):92-100.
[30]Andersen Petersen N C.A procedure for ranking efficient units in data envelopment analysis[J].Management Science,1993,39(10):1261-1265.
[31]张军,吴桂英,张吉鹏.中国省际物质资本存量估算:1952-2000[J].经济研究,2004(10):35-44.
[32]王兵,王秋彬.工业行业能源效率与工业结构优化升级--年省际面板数据的实证研究[J].数量经济技术经济研究,2010(10):49-62.
[31]许士春,何正霞,龙如银.环境政策工具比较:--基于企业减排的视角[J].系统工程理论与实践,2012,32(11):2351-2362.