基于LMDI的中国工业能源碳足迹生态压力因素分解研究
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摘要
随着气候危机频发及资源环境问题的日渐严峻,实现工业的低碳转型成为当前的必然选择,而推动工业低碳发展的关键在于对影响工业能源碳足迹的因素做出合理分析。在测算出2000—2015年中国工业38个细分行业能源碳足迹生态压力(EPICF)的基础上,划分出高、中、低压行业,并采用LMDI法对3类行业的EPICF进行因素分解,结果表明:产业结构取代能源强度成为降低高压行业EPICF的主导因素;中压行业减压的关键要素是能源强度、能源结构和产业结构;低压行业减压的重点仍落在降低能源强度上;经济发展始终是中国工业EPICF增长的最大原因;现阶段,森林和草地的人口压力和能源结构因素的作用不大,退耕还林还草和能源结构调整的效果未得到真正发挥。
With the frequent occurrence of the climate crisis and the increasingly serious problems of resources and environment,the realization of low-carbon transformation of industry has become an inevitable choice.The key to promote the low carbon development of industry is to make a reasonable analysis of the factors that affect the energy carbon footprint of industry.Based on the calculation of the ecological pressure intensity of carbon footprint(EPICF) in 38 sectors of China's industry from 2000 to 2015,this paper classifies it into three types,which include high,middle and low pressure industry and decomposes the EPICF of these 3 types of industries by LMDI method.The results show that:Industrial structure which replaces energy intensity has become the leading factor to reduce EPICF in high pressure industry;Energy intensity,energy structure and industrial structure are the three key elements of the medium pressure industry's decompression;The emphasis of decompression in the low pressure industry is still on the reduction of energy intensity;Economic development is always the biggest driving force for China's industrial EPICF growth;At this stage,the contribution of population pressure of forest and grassland and energy structure is not significant,which reflects that the effects of conversion of cropland to forest and grassland and energy structure adjustment have not been brought into full play.
With the frequent occurrence of the climate crisis and the increasingly serious problems of resources and environment,the realization of low-carbon transformation of industry has become an inevitable choice.The key to promote the low carbon development of industry is to make a reasonable analysis of the factors that affect the energy carbon footprint of industry.Based on the calculation of the ecological pressure intensity of carbon footprint(EPICF) in 38 sectors of China's industry from 2000 to 2015,this paper classifies it into three types,which include high,middle and low pressure industry and decomposes the EPICF of these 3 types of industries by LMDI method.The results show that:Industrial structure which replaces energy intensity has become the leading factor to reduce EPICF in high pressure industry;Energy intensity,energy structure and industrial structure are the three key elements of the medium pressure industry's decompression;The emphasis of decompression in the low pressure industry is still on the reduction of energy intensity;Economic development is always the biggest driving force for China's industrial EPICF growth;At this stage,the contribution of population pressure of forest and grassland and energy structure is not significant,which reflects that the effects of conversion of cropland to forest and grassland and energy structure adjustment have not been brought into full play.
引文
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[2]Wackernagel M.Ecological footprint and appropriated carrying capacity:A tool for planning toward sustainability[D].Columbia:The University of British Columbia,1994.
[3]Wackernagel M,Rees W E.Our ecological footprint:Reducing human impact on the earth[M].Gabriola:New Society Publishers,1996.
[4]Wiedmann T,Minx J.A definition of carbon footprint[J].Journal of the Royal Society of Medicine,2007,92(4):193-195.
[5]李智,鞠美庭,刘伟,等.中国1996年-2005年能源生态足迹与效率动态测度与分析[J].资源科学,2007(6):54-60.
[6]董雪旺.国内外碳足迹研究进展述评[J].浙江工商大学学报,2013(2):67-75.
[7]Virtanen Y,Kurppa S,Saarinen M,et al.Carbon footprint of food-approaches from national input-output statistics and a LCA of a food portion[J].Journal of Cleaner Production,2011,19(16):1849-1856.
[8]周国富,宫丽丽.京津冀能源消耗的碳足迹及其影响因素分析[J].经济问题,2014(8):27-31.
[9]赵先贵,肖玲,马彩虹,等.山西省碳足迹动态分析及碳排放等级评估[J].干旱区资源与环境,2014(9):21-26.
[10]闫云凤.京津冀碳足迹演变趋势与空间、产业分布[J].经济与管理研究,2016(11):75-81.
[11]庞军,高笑默,石媛昌,等.基于MRIO模型的中国省级区域碳足迹及碳转移研究[J].环境科学学报,2017(5):2012-2020.
[12]吴德存,刘金平.我国区域间能源及碳足迹空间差异分析[J].统计与决策,2017(6):132-136.
[13]卢俊宇,黄贤金,陈逸,等.基于能源消费的中国省级区域碳足迹时空演变分析[J].地理研究,2013(2):326-336.
[14]张约翰,张平宇.长吉都市区能源碳足迹测度及影响因素研究[J].地理科学,2012(9):1099-1105.
[15]陈操操,刘春兰,汪浩,等.北京市能源消费碳足迹影响因素分析--基于STIRPAT模型和偏小二乘模型[J].中国环境科学,2014(6):1622-1632.
[16]闫云凤.京津冀碳足迹演变趋势与驱动机制研究[J].软科学,2016(8):10-14.
[17]孙强,沈玉志.区域碳足迹耦合度及影响因素研究[J].生态经济,2016(11):75-79.
[18]Van Amstel A.IPCC 2006 Guidelines for national greenhouse gas inventories[M].Washington:Institute for Global Environmental Strategies,2006.
[19]Ang B W,Liu F L.A new energy decomposition method:Perfect in decomposition and consistent in aggregation[J].Energy,2001,26(6):537-548.
[20]Ang B W.The LMDI approach to decomposition analysis:Apractical guide[J].Energy Policy,2005,33(7):867-871.