Research Of Carbon Emission Mechanism . - Atlantis Press

International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)Research of Carbon Emission MechanismCoupling Model and Empirical Case---A CaseStudy of BeijingJianyu Jin1Xiaoliu Shen1Jinjianyu zz@163.comshenxiaoliu@163.comLifeng Duan1joe is here@yahoo.cnTing Cao1ct.undersea@gmail.com(1. School of computer and technology North China Electric Power University, Beijing, China)take the CO2 emission mechanism as the major study direction.Abstract—At present, CO2 emissions in China has beenranking second in the world, 75% of it coming from energyCO2 emission mechanism studies the process, feature andconsumption. Effective control of CO2 emission has become antrend of CO2 emission as well as effects of various factors onurgent problem, and analysis on the impact of factors affectingCO2 emission and on its change. emission mechanism study isCO2 emissions will inevitably become the primary solution to thisin-deep study of CO2 emission source and level, is key step ofproblem. Kaya model is constructed by the product of multipleCO2 emission reduction, and directly relate to the set ofinfluencing factors, which associates the CO2 emission quantitystrategic policies and measures in CO2 emission reduction,with living standards, economic growth, population size and perwhile atcapita GDP. This study is based on the coupling of Kaya modeldevelopment of low-carbon economy[2].and LMDI model which is built to comb Beijing’s evolutionthe same time is of important significance for theII.mechanism of carbon emissions from 2001 and 2010, andMODEL CONSTRUCTIONrespectively builds CO2 emission factor separation model andKaya model, which was put forward by Japan scholarenergy consumption factor separation and superposition modelYoichi Kaya and used as one of the main models in CO2to comb the evolution mechanism of Beijing’s CO2 emission indriving factors analysis, is one of the most widely useddifferent angle of life and production department from 2001 tomodel[3]. Using the product of multiple factors to construct2010. The results show that the living standard, economic growth,Kaya model, the influencing factors such as living standard,population size factors have become the main factors affectingeconomic growth, population scale and Per Capita GDP canthe CO2 emissions, and the effect of energy intensity, industrialbe associated with CO2 emission.structure, energy on CO2 emissions has reached a bottleneck.LMDI (logarithmic mean division index) model satisfies theMeanwhile the results of this study can provide policyfactors reversible, and is able to eliminate residual term, thatrecommendations for other provinces and cities to reduce CO2overcomes the existence of residual term after decompositionemissions.and unsuitable decomposition in residual term and make themodel more persuasive and widely used[5].Index Terms—CO2 emission, Kaya model, logarithmic meanGiven this, this article chose the coupling of Kaya modelDivision index model, The Coupling Model, energy consumption,an LMDI model to combs the mechanism of CO2 emission inI.INTRODUCTIONBeijing.Nowadays reducing the CO2 emission is the mainA.measures to mitigate climate warming for CO2 is the mainfactor of global climate warmingThe factorization model of CO2 emissionCO2 emission factorization model:[1]. To make sure theC emission reduction being reasonable and effective, we must 2013. The authors - Published by Atlantis Press Cii262 ES Fiii(1)

C CE CS CF(2)Q G / N , I j G j / G , M j EP , j / G j ,where, t0 CE ln( Ei / Ei )i t0 CS ln( Si / Si )i C ln( F t / F 0 )Fii i E N 1 In( N it / N i0 ) j E In(Qit / Qi0 ) Q j t0 EI In( I i / I i )j E In( M it / M i0 ) M j (3)Si Ei / E, Fi Ci / D (Cit Ci0 ) / ln(Cit / Ci0 ) CF —energy(7) ( E tp , j E p0, j ) / In( E tp , j / E p0, j )carbon emission intensity effect, E —totalwhere,j 1, 2,3Q - Per Capita GDP, usingenergy consumption, Ei —the consumption of energy i , S irespectively indicate for industrial sector j , G - GDP， G j—proportion of energy i in total energy, CS —energy-production value of industrial sector j ,structural effect, D —GDP, i 1 for coal, i 2 for oil, i 3consumption of industrial sector j , EQ , EN 1 , EM , EIfor gas, Ci —the carbon dioxide emissions of energy iconsumption,E p , j -energyrespectively indicate economic growth, population scale,t —current time period, 0—basic period, Cenergy consumption intensity and industrial structure.—the change of the carbon dioxide emissions between currenttime period and basic period, Fi —carbon emissions intensity,Life factor decomposition extension model： ER NP 0t ER ER ER EN 2 E p CE —energy consumption effect.(8)where,B.Energy consumption decomposition model(9)P ER / N EN 2 ln( N / N ) t0 EP ln( p / p ) ( ERt ER0 ) / In( ERt / ER0 )tThe total energy consumption E is divided intoproduction energy consumption EP and life energyconsumption ER :0(10)(4)P —per capita consumption, ER —energy consumptionEP - production energy consumption, ER - life energyduring the relative time， EN 2 —population size influenceE EP ER EP , j ERjconsumption, E p , j - energy consumption of the industrialsectorfactor in life department, EP —living level influence factor.j in production. This build production factorsextension model and life extension model, and establish thecorresponding relationship with N 、 Q 、 I 、 M 、 P .C.Energy consumption decomposition extension model inThe superposition of production department and lifeproduction department:department influence establishes the factor superpositionEP EP , j NQI j M jjCO2 emission factor superposition modelmodel:(5)j EP EN 1 EQ EI EM C CN CQ CI CM CP CS CF(6)where, CN EN 1 EN 2 / E / CFwhere, CQ ( EQ / E ) CE263(11)

( EP / E ) CEIII. CARBON EMISSION MECHANISM ANALYSISA.analysis on results of Beijing CO2 emissions modelB.both multilevel complemented and accommodated and201020092008the living energy consumption factor has less effect in CO2.EP and ER all increased, but the amplification of ER is73%, the proportion of oil is 9%, and the proportion of naturalgas rise to 18%, but coal is still occupies a high proportionrelatively small for its lower influence, while the growth rateof EP is in fleetness increasing tendency for its largeramong the three. Coal has the highest emission coefficientand the largest proportion among three kinds of energy,influence on E , especially before 2007. The growth ratefollowed by oil and gas. In order to reduce the emission ofslowed down after 2007 under the influence of the policy onCO2, we must upgrade the industrial structure[6 7].energy white paper which released by the state council inFrom the Fig.1 we can see that in the first five years, theDecember 2007.emission of CO2 in Beijing is in a rapid increase trend. ButAmong the changes of E form 2001 to 2010, thecontribution of change EP is about 82% 86%, and is13% 17% for change ER . This is related to the respectivelythen it is in a year-by-year decreasing trend from 2005 to2010. The change of energy consumption and energy structureis positive, that increased the CO2 emission. And with theproportion of EP and ER in Beijing. From 2001 to 2010,upgrade of energy structure, contribution rate is also firstly inincreasing trend and then in decreasing trend. CS isEP keep sharing above 80% in E , though there isnegative and restrains CO2 emission, while the contributiondecreasing in every years, and the sharing rate of ER israte is also negative, that means the energy structure has littlekeeping slow increasing.energy consumption/10000tonseffect on CO2 emissions.CO2/10000tons2007increasing trend during the ten years from 2001 to 2010, andten years from 2001 to 2010, the proportion of coal fells toC400020000-20002006According to Fig.3, the total consumption of energy is inassisting with oil, gas, coal and renewable sources. During theCSAnalysis on the result of energy consumption separationmodelharmoniously developed. The system is electric-oriented,CEYearFig.2. the change trend of Beijing’s energy structure during 2001 2010Beijing proposed an energy-supplying system, which is600002005factor.natural gas0.52004 CM -energy consumption intensity factor, CP -living leveloil2003 CQ -economic growth factor， CI - industrial structure factor,coal12002energy consumption/10000tonsIn the equations, C is for the current changes in CO2emissions relative to the base period, CN -population factor,2001 CI ( EI / E ) CE , CP10000Total Energy ConsumptionProduction energy consumptionLife energy consumption50000YearYearFig.3. Results of Beijing energy consumption separation model form 2001 toFig.1. model decomposition results of CO2 emissions in Beijing from 2001 to20102010264

TABLE.1. Results of Beijing energy consumption separation model formCDP on CO2 emission is decreasing year by year, especially2001 to 2010YearConsumption contributionConsumptionine policies during this ten years. So, during the period of2001 2010, the industry structure changes make EPof productioncontribution of lifereduced. From the Fig.4, we can find that the population scale0.8673430.132657in living department continued increasing since 2001. Beijing20020.8683550.131645is the political and economic center of our country and20030.8535720.146428Beijing's pouring into employment makes the living energy20040.8537360.146264consumption increasing, that turn out to be the increasing of20050.8525190.147481CO2 90.17683120102009200820072006YearFig.5. Changing trend of Beijing’s energy intensity in each industry fromeffect.1000EN1EQEIEM2001 to 2010EPprimary industry5000.8secondary industrytertiary industry0.6ratioenergy consumption/10000tons2005of other factors is relatively smaller. And M take a negativeeffect on CO2 emission while other factors take a positive02004proportion in the production department, and the proportion2003the per capita energy consumption factor occupies a large52002In Fig.4, we can find that among the numerous factors,primary industrysecondary industrytertiary industry2001energy consumption/10000tons200100.40.20-500YearFig.4. Accumulation of consumption separation model’s results from 2001 toYearFig.6. the proportion change tendency of industrial structure of Beijing form20102001 to 2010Fig.5 is the Beijing energy intensity change trend chart.From this chart we can see that the energy intensity of firstForm Fig.7 we can see that the population scale factor inindustry and third industry all in decreasing tendency, but in aproduction department occupies a steady contribution tolow rate, and decline in second industry is larger than theenergy consumption which is in positive increasing trend. Andother two industries, so changes in industry structure make theEP reduced. During the ten years from 2001 to2010 present inthe influence degree is gradually increased with the rapidFig.6, the output ratio of the first and second industry is inhave made a great influence in energy consumption, and havedecreasing tendency, while the third industry’s output ratio isled the total energy consumption to in a significant growthin increasing tendency. Fig.5 presents the changing trend oftrend. Though the contribution of it in 2005 and 2010 hasBeijing’s energy intensity in each industry from 2001 to 2010.some ups-and-downs, it still occupies a relatively largerWe can see that the influence degree of industry structure andproportion on the whole.growth of contribute rate after 2008. Changes in living level265