山东省制造业碳排放驱动因素研究——基于GDIM方法
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摘要
在大力倡导低碳发展的背景下,面对国际国内碳排放达峰目标的双重压力,实现山东省碳排放2027年达峰目标,制造业的转型发展成为关键。文章以山东省2000-2016年制造业碳排放作为研究对象,采用广义迪氏指数分解法对能源、投资、产值等碳排放演变驱动因素进行分解,并进行综合性、阶段性以及贡献值累积性分析,发现产出规模、能耗规模、投资规模对碳排放具较强的促进作用、碳强度效应较强的抑制作用以及碳效率效应比较微弱的抑制作用。基于此,提出引导制造业投资流向、产业结构能源结构双调并举、碳强度和能源强度实现双降的碳减排措施。
The rapid development of manufacturing in Shandong Province is accompanied by high carbon emissions and high pollution. Under the background of vigorously advocating low-carbon development,in the face of the dual pressure of international and domestic carbon emission peaks,and to achieve the goal of carbon emission in Shandong Province by 2027,the transformation and development of the manufacturing industry has become the sticking point. This paper takes Shandong Province's manufacturing carbon emissions from 2000 to 2016 as the research object. It uses the Generalized Divisia Index method to decompose the evolution drivers of carbon emissions such as energy,investment,and production value. Comprehensive analysis,periodic analysis,and cumulative analysis of contribution values are conducted. It is found that yield,energy consumption and investment have a positive effect on carbon emissions;and carbon intensity effect factors have a strong inhibitory effect;carbon efficiency effect factors have a weak inhibition effect. In response to this,it is proposed to guide the flow of manufacturing investment,implement the dual-tuning of the industrial structure and energy structure,and reduce carbon intensity and energy intensity,so as to achieve carbon reduction.
The rapid development of manufacturing in Shandong Province is accompanied by high carbon emissions and high pollution. Under the background of vigorously advocating low-carbon development,in the face of the dual pressure of international and domestic carbon emission peaks,and to achieve the goal of carbon emission in Shandong Province by 2027,the transformation and development of the manufacturing industry has become the sticking point. This paper takes Shandong Province's manufacturing carbon emissions from 2000 to 2016 as the research object. It uses the Generalized Divisia Index method to decompose the evolution drivers of carbon emissions such as energy,investment,and production value. Comprehensive analysis,periodic analysis,and cumulative analysis of contribution values are conducted. It is found that yield,energy consumption and investment have a positive effect on carbon emissions;and carbon intensity effect factors have a strong inhibitory effect;carbon efficiency effect factors have a weak inhibition effect. In response to this,it is proposed to guide the flow of manufacturing investment,implement the dual-tuning of the industrial structure and energy structure,and reduce carbon intensity and energy intensity,so as to achieve carbon reduction.
引文
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[2]EHRLICH P R,HOLDREN J P.One-dimensional economy[J].Bulletin of the Atomic Scientists,1972,16(2):18-27.
[3]KAYA Y.Impact of carbon dioxide emission on GNPgrowth:interpretation of proposed scenarios[R].Presentation to the Energy and Industry Subgroup,Response Strategies Working Group,IPCC,1989.
[4]GUAN D B,KLAUS H,CHRISTOPHER L,et al.The drivers of Chinese CO2 emissions from 1980 to 2030[J].Global Environmental Change,2008,36(2):626-634.
[5]PETER G,JEFFREY K.Exporting the greenhouse:foreign capital penetration and CO2 emissions 1980-1996[J].Journal of World-Systems Research,2003,65(2):261-275.
[6]TALUKDAR D,MEISNER C M.Does the private sector help or hurt the environment?evidence from carbon dioxide pollution in developing countries[J].World Development,2001,29(5):827-840.
[7]蒋金华.产业集聚对我国制造业碳排放的影响研究[D].长春:吉林大学,2015.
[8]邵帅,张曦,赵兴荣.中国制造业碳排放的经验分解与达峰路径--广义迪氏指数分解和动态情景分析[J].中国工业经济,2017(3):44-63.
[9]王钰,张连城.中国制造业向低碳经济型增长方式转变的影响因素及机制研究--基于STIRPAT模型对制造业28个行业动态面板数据的分析[J].经济学动态,2015(4):35-41.
[10]MOUTINHO V,MOREIRA A C,SILVA P M.The driving forces of change in energy-related CO2 emissions in eastern,western,Northern and Southern Europe:the LMDI approach to decomposition analysis[J].Renewable&Sustainable Energy Reviews,2015,50(3):1485-1499.
[11]JUNG S,AN K,DODBIBA G,et al.Regional energy-related carbon emission characteristics and potential mitigation in eco-industrial parks in South Korea:logarithmic mean divisia index analysis based on the kaya identity[J].Energy,2012,46(1):231-241.
[12]O’MAHONY T,ZHOU P,SWEENEY J.The driving forces of change in energy-related CO2 emissions in ireland:a multi-sectoral decomposition from 1990 to 2007[J].Energy Policy,2012,44(7):256-267.
[13]田雷.吉林省能源碳排放驱动因素与新常态背景下碳排放趋势研究[D].长春:吉林大学,2016.
[14]黄圆圆.福建省制造业分行业碳排放差异及影响因素分析[D].福州:福州大学,2014.
[15]VANINSKY A.Factorial decomposition of CO2 emissions:a generalized Divisia index approach[J].Energy Economics,2014,45(8):1256-1287.
[16]闫庆友,尹洁婷.基于广义迪氏指数分解法的京津冀地区碳排放因素分解[J].科技管理研究,2017,37(19):239-245.