中国终端能源消费碳排放分配研究
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摘要
为了缓解国内发展需求与国际碳减排压力的矛盾，规避国际社会突然施加绝对碳减排压力的风险，中国需要逐步向碳排放量绝对控制进行过渡，开展省域碳排放量分配研究，是中国由碳排放量持续增长向逐步承担碳减排量的友好过渡。
本研究在对国内外碳排放影响因素、碳排放分配原则及碳排放分配方法进行综述分析的基础上，通过构建碳排放量分配体系，计算碳排放分配系数来体现各省市碳减排责任差异性；采用“定基数、分增量”的方法来保障在稳定发展的前提下进行碳排放量分配，从而构建了基于信息熵的多因子混合加权分配模型（IEMMA），分析了在不同侧重原则的五种情景下各省市碳排放量分配情况。另外，基于传统三部门方法，结合中国碳排放部门的特点构建了中国部门法（CSA），通过预设不同省市各部门活动水平收敛值和强度收敛值来进行各省市碳排放量分配研究。最后在统一碳排放分配目标年和碳排放分配总量的前提下，对两种分配方法的分配结果进行了比较分析。
本论文分别从自上而下的宏观调控角度和自下而上的终端需求角度构建碳排放分配模型，进行省域间碳排放权责分配的探索，提出了将碳排放绝对量分配到各省市的方法。这两种分配方法均能有效减弱碳排放分配量对经济发展水平的依赖性，与各省市碳强度控制相比，本文所构建的方法更有利于对碳排放量进行有效控制。
Global Climate Change has become an indisputable fact that it’s the inevitablerequirement of the sustainable development of human beings to stabilize theatmospheric greenhouse gas concentrations at an appropriate level and preventdramatic climate change on human damage. Controlling the total greenhouse gas isnot only the important measure of global response to climate change but also thecommon responsibility of all countries in the world. According to the "common butdifferentiated" responsibilities of the Kyoto Protocol, as a developing country, Chinadoes not assume the absolute amount of carbon reduction temporarily. With theimprovement of China's industrialization level and the economic development, in thenear future, the continuous growth of the terminal energy consumption carbonemissions in China is inevitable, and then China will increase the pressure ofinternational carbon emission reduction. Meanwhile, China does not exclude thepossibility of beginning to assume the absolute amount of carbon reduction after2020. In order to alleviate the contradiction between domestic development demandand international carbon emission reduction pressure and to avoid the risk of thesudden pressure imposing absolute carbon emission reduction from the internationalcommunity, China needs to control the carbon emissions from the current measuresgradually transition to the absolute control.
Study on allocation methods of carbon emissions from final energyconsumption in province will help us to excavated each province’s carbon reductionpotential and improve its carbon reduction ability. At the same time, allocation ofcarbon emissions is good for us to accomplish our carbon intensity targets which wehave promised. On the other hand, China has carried out the pilot project for carbonemission trading, and the allocation of carbon emission is the basis of carbonemission trading. Meanwhile allocating the specific carbon emissions to provincescan achieve its low-carbon transition at an early date and it will beneficial to form arelatively stable carbon reduction system.
On the basis of analyzing the carbon emission influence factors, the allocationprinciple and allocation methods of carbon emission at home and abroad, this study has carried on the exploration of carbon allocation methods in province whichcombined with the related research of resources allocation and pollutants distribution.The study builds IEMMA from top-down and CSA from bottom-up respectively toresearch the allocation methods of each province in China.
Firstly, based on the principle of "set the base, points incremental", combininginformation entropy theory and linear weighted sum method to calculate carbonallocation coefficient of each province, we build the index system of allocation, andpropose the information entropy and multiple-factor mixed weighting allocationmethod (IEMMA).
According to the various province’s carbon intensity decline index which hadreleased in12th Five-Year Plan, combined with the GDP growth forecast we cancalculate each province’s carbon emissions in2015under the target of carbonintensity control. Compared with the allocation results from the IEMMA model in2015, we can analyze the differences and similarities of the two methods. The studyshows that IEMMA’s allocation method conforms to the historical emission rules ofeach province, meanwhile, and gains good matching with the allocation results ofcarbon intensity control in the12th Five-Year Plan. Therefore, IEMMA can be usedto assign carbon emissions within province.
Furthermore, combining with the practical situation of China, this paperimproves Triptique Approach into CSA which includes primary industry, secondaryindustry, tertiary industry, and life department. Based on predicting activity levelsand carbon emissions intensity levels of different sections, this paper forecasts thetotal allocation amount in the demand perspective with, by CSA.
After building two allocation methods of carbon emissions, the two allocationresults are compared to analyze their advantages and disadvantages. In order toensure the two allocation results are comparable, it's neccessary to standardize thetarget year and the total allocation of carbon emissions. In this study, the target yearis2020which is also the carbon intensity control target year that China has promised.In2020，the total increment of carbon emissions, gained by CSA, is2.94billiontonnes of CO2, which is in the carbon increment scope of CO2emissions per GDPreduced by40–50%on the same economic development level of China. The resulthas certain guiding significance for China to achieve carbon intensity target.
Based on the increment control target of2.94billion tones of CO2, researchesthe allocation with CSA and IEMMA. This paper also compares the allocationcharacteristics in province and the similarities and differences of two aforementionedmethods. IEMMA which is from the top-down with the angles of carbon reductionresponsibility and regional development right analyzes macroscopically theallocation of carbon emissions that bases the total amount control of differentprinciples and puts particular emphasis on scenarios. But CSA which bases eachprovince’s the demand and the convergence level of intensity, puts forward thecarbon emissions targets of each province excluding the sectors and offers thesufficient space of carbon reduction responsibility to the sectors.
From an overall viewpoint, this two allocation methods have certaincoordination. The difference of carbon emission allocation results among provincesis small under the different allocation methods. In addition to Inner Mongolia, Henanand Sichuan province, the difference of the two allocation methods of distribution ofcarbon value among other provinces are within the100million tons of carbondioxide, and the difference is within20%. From the specific allocation results, theprovinces, of which the growth of carbon emission accumulation in the11thfive-year period is much larger, can be assigned to more carbon emissions quotas inthe CSA allocation method than the IEMMA allocation method.
Study shows that overall two allocation methods have certain coordination andsmall difference. The result of IEMMA of all provinces is consistent with the carbonemissions history. And the CSA tend to reflect the space requirements of eachprovince for carbon emissions.
本研究在对国内外碳排放影响因素、碳排放分配原则及碳排放分配方法进行综述分析的基础上，通过构建碳排放量分配体系，计算碳排放分配系数来体现各省市碳减排责任差异性；采用“定基数、分增量”的方法来保障在稳定发展的前提下进行碳排放量分配，从而构建了基于信息熵的多因子混合加权分配模型（IEMMA），分析了在不同侧重原则的五种情景下各省市碳排放量分配情况。另外，基于传统三部门方法，结合中国碳排放部门的特点构建了中国部门法（CSA），通过预设不同省市各部门活动水平收敛值和强度收敛值来进行各省市碳排放量分配研究。最后在统一碳排放分配目标年和碳排放分配总量的前提下，对两种分配方法的分配结果进行了比较分析。
本论文分别从自上而下的宏观调控角度和自下而上的终端需求角度构建碳排放分配模型，进行省域间碳排放权责分配的探索，提出了将碳排放绝对量分配到各省市的方法。这两种分配方法均能有效减弱碳排放分配量对经济发展水平的依赖性，与各省市碳强度控制相比，本文所构建的方法更有利于对碳排放量进行有效控制。
Global Climate Change has become an indisputable fact that it’s the inevitablerequirement of the sustainable development of human beings to stabilize theatmospheric greenhouse gas concentrations at an appropriate level and preventdramatic climate change on human damage. Controlling the total greenhouse gas isnot only the important measure of global response to climate change but also thecommon responsibility of all countries in the world. According to the "common butdifferentiated" responsibilities of the Kyoto Protocol, as a developing country, Chinadoes not assume the absolute amount of carbon reduction temporarily. With theimprovement of China's industrialization level and the economic development, in thenear future, the continuous growth of the terminal energy consumption carbonemissions in China is inevitable, and then China will increase the pressure ofinternational carbon emission reduction. Meanwhile, China does not exclude thepossibility of beginning to assume the absolute amount of carbon reduction after2020. In order to alleviate the contradiction between domestic development demandand international carbon emission reduction pressure and to avoid the risk of thesudden pressure imposing absolute carbon emission reduction from the internationalcommunity, China needs to control the carbon emissions from the current measuresgradually transition to the absolute control.
Study on allocation methods of carbon emissions from final energyconsumption in province will help us to excavated each province’s carbon reductionpotential and improve its carbon reduction ability. At the same time, allocation ofcarbon emissions is good for us to accomplish our carbon intensity targets which wehave promised. On the other hand, China has carried out the pilot project for carbonemission trading, and the allocation of carbon emission is the basis of carbonemission trading. Meanwhile allocating the specific carbon emissions to provincescan achieve its low-carbon transition at an early date and it will beneficial to form arelatively stable carbon reduction system.
On the basis of analyzing the carbon emission influence factors, the allocationprinciple and allocation methods of carbon emission at home and abroad, this study has carried on the exploration of carbon allocation methods in province whichcombined with the related research of resources allocation and pollutants distribution.The study builds IEMMA from top-down and CSA from bottom-up respectively toresearch the allocation methods of each province in China.
Firstly, based on the principle of "set the base, points incremental", combininginformation entropy theory and linear weighted sum method to calculate carbonallocation coefficient of each province, we build the index system of allocation, andpropose the information entropy and multiple-factor mixed weighting allocationmethod (IEMMA).
According to the various province’s carbon intensity decline index which hadreleased in12th Five-Year Plan, combined with the GDP growth forecast we cancalculate each province’s carbon emissions in2015under the target of carbonintensity control. Compared with the allocation results from the IEMMA model in2015, we can analyze the differences and similarities of the two methods. The studyshows that IEMMA’s allocation method conforms to the historical emission rules ofeach province, meanwhile, and gains good matching with the allocation results ofcarbon intensity control in the12th Five-Year Plan. Therefore, IEMMA can be usedto assign carbon emissions within province.
Furthermore, combining with the practical situation of China, this paperimproves Triptique Approach into CSA which includes primary industry, secondaryindustry, tertiary industry, and life department. Based on predicting activity levelsand carbon emissions intensity levels of different sections, this paper forecasts thetotal allocation amount in the demand perspective with, by CSA.
After building two allocation methods of carbon emissions, the two allocationresults are compared to analyze their advantages and disadvantages. In order toensure the two allocation results are comparable, it's neccessary to standardize thetarget year and the total allocation of carbon emissions. In this study, the target yearis2020which is also the carbon intensity control target year that China has promised.In2020，the total increment of carbon emissions, gained by CSA, is2.94billiontonnes of CO2, which is in the carbon increment scope of CO2emissions per GDPreduced by40–50%on the same economic development level of China. The resulthas certain guiding significance for China to achieve carbon intensity target.
Based on the increment control target of2.94billion tones of CO2, researchesthe allocation with CSA and IEMMA. This paper also compares the allocationcharacteristics in province and the similarities and differences of two aforementionedmethods. IEMMA which is from the top-down with the angles of carbon reductionresponsibility and regional development right analyzes macroscopically theallocation of carbon emissions that bases the total amount control of differentprinciples and puts particular emphasis on scenarios. But CSA which bases eachprovince’s the demand and the convergence level of intensity, puts forward thecarbon emissions targets of each province excluding the sectors and offers thesufficient space of carbon reduction responsibility to the sectors.
From an overall viewpoint, this two allocation methods have certaincoordination. The difference of carbon emission allocation results among provincesis small under the different allocation methods. In addition to Inner Mongolia, Henanand Sichuan province, the difference of the two allocation methods of distribution ofcarbon value among other provinces are within the100million tons of carbondioxide, and the difference is within20%. From the specific allocation results, theprovinces, of which the growth of carbon emission accumulation in the11thfive-year period is much larger, can be assigned to more carbon emissions quotas inthe CSA allocation method than the IEMMA allocation method.
Study shows that overall two allocation methods have certain coordination andsmall difference. The result of IEMMA of all provinces is consistent with the carbonemissions history. And the CSA tend to reflect the space requirements of eachprovince for carbon emissions.
引文
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