| In order to response the international pressure of carbon emissions reduction and adapt to theway change of domestic economic growth, the chinese government proposes some of measuresincluding slowing down the economic growth rate moderately, and raising the proportion of the addedvalue of service industry, and optimizing the industrial structure, and reducing energy intensity andcarbon intensity greatly, and optimizing energy consumption structure in the “12th Five-Year PlanOutline”. In order to achieve the rate of energy intensity reduction by16%and the rate of carbonemission intensity reduction by17%, the government drew up the comprehensive work plans aboutenergy conservation and the comprehensive work plans about emission reduction during the “12thFive-Year” period. The government set the target of the rate of provincial energy intensity reductionand provincial carbon intensity reduction. In guarantee of steady economic growth at the same time,how to reduce the cost of emissions reduction and energy conservation, and to improve the efficiencyof energy utilization, and to optimize energy consumption structure, and to reduce energy intensityand carbon intensity, and to slow down the growth rate of energy consumption and carbon emissions,and to promote further decoupling of carbon emission and economic growth, and to search theoptimal economic growth path, become a major issues of the long run developing strategy.In this paper, the futrue change trend of energy intensity and carbon emissions intensity and thechange trend of the influence factors of the double intensity were predicted. The evolution historytrend of energy consumption structure and industrial structure and the planning constraints were allconsidered. Parametric programming and multi-objective programming ideas were combined with.How the adjustment of energy consumption structure and industrial structure, and energy intensity ofthe whole nation and every province affect the low-carbon economic growth path were analyzed.（1）The influence factors of energy intensity and carbon emissions intensity of the whole nationwere analyzed. The futrue change trend of the double intensity and their influence factors werepredicted based on the history data. The futrue change trend of energy consumption structure andindustrial structure of the nation were predicted. The futrue change trend of energy consumptionstructure and energy intensity of every province were also predicted.The results show that, the national industrial structure would be optimized following historicalevolution trajectory. The proportion of added value of first industry and secondary industry wouldboth drop from2010to2015. The proportion of added value of third industry would rise from2010to2015, which could not reach47%. The industrial structure need to be adjusted further during the “12thFive-Year” period. The rate of energy intensity reduction of some provinces could reach the target of“12th Five-Year Planning”. If don’t consider the medium and long-term energy plan but based on thehistorical evolution from2010to2015, the energy consumption structure of the whole nation wouldbe optimized. The proportion of coal consumption and oil consumption would both drop respectively.The proportion of gas consumption and non-fossil energy consumption would both rise respectively. The proportion of non-fossil energy consumption could not reach the target in the “12th Five-YearPlanning”.（2）The multi-objective programming models of the industrial economic growth under therestriction of double intensity were established. It also analyzed the impact of industrial energyconsumption intensity, energy consumption structure and carbon dioxide emissions intensityadjustment on the economic growth path. The results show that, the economic growth rate ofagriculture, industry and construction would all slow down if the changing tendency of energyintensity of each industry and the changing tendency of primary energy consumption structure from2010to2015follow the tendency from2005to2010in the first multi-objective scenario.Nevertheless, the economic growth rate of other sectors would be improved. On the basis of the firstmulti-objective scenario, lessening the reduction rate of energy consumption intensity of constructionand industry, and enlarging the reduction rate of other industrial energy consumption intensity couldimprove the economic growth rate of agriculture and construction. Optimizing energy consumptionstructure could decelerate the pressure of reducing energy consumption intensity of industry andconstruction. The share of non-fossil energy in its energy mix would reach11.4%by2015. Based onthe optimization of energy consumption structure, lessening the reduction rate of energy consumptionintensity of construction and industry further more has little effect on the economic growth of allsectors, but could increase energy consumption and carbon dioxide emissions of the whole nation. Inall scenarios, the share of service industry would all reach47%by2015, but the additional potential toincrease it would be small. The decoupling relationship between energy consumption and economicgrowth of the whole nation and every sector would be in weak decoupling relationship. Thedecoupling relationship between carbon dioxide emissions and economic growth of the whole nationwould also be in weak decoupling relationship.（3）An optimal model of provincial economic growth under the restriction of double intensitywas established form the global optimal angle. Under the constraint of energy intensity and carbonemissions intensity of the nation, the optimal path of provincial economic growth was found. Thedecoupling relationship between carbon dioxide emissions and economic growth of each provincewas predicted. If each provincial government achieves the target of energy intensity and carbondioxide emissions intensity in two blue prints, the economic growth rate of Shanxi, Ningxia, InnerMongolia and Huizhou would be reduced, but the economic growth rate of other provinces would bepromoted. Increasing economic growth rate of Beijing, Hebei, Shanghai, Zhejiang, and Guangdong isbenefit to promote economic development of Shanxi, Inner Mongolia, and Huizhou. But theenergy-carbon intensity of several provinces would be increased. From2010to2015, the nationalenergy intensity and carbon emissions intensity respectively would be about down18.19%and19.56%. The decoupling relationship between energy consumption and economic growth of Hainanand Qinghai would be a growth connection, but the decoupling relationship of energy consumptionand economic growth of other provinces would be all weak decoupling. The decoupling relationshipof carbon dioxide emissions and economic growth of Hainan would be a growth connection, but this decoupling relationship of other provinces would be all weak decoupling. The results show that theeffect of energy conservation and emission reduction would be remarkable along the optimaleconomic growth path. The growth rate of carbon dioxide emissions would be lower than the growthrate of energy consumption in each province. It means that energy consumption structure of eachprovince would be gradually optimizing.（4）The evolution history trend of provincial energy intensity and energy consumption structureand planning constraints were all considered. The multi-objective optimization models of provincialenergy consumption structure were established. The optimal adjustment of provincial energyconsumption structure were analyzed in the three scenarios. The first scenario is just realizingprovincial energy intensity reduction goals. The second scenario is the predictive value of theprovincial energy intensity reduction to follow evolution history trend. The third scenario of isadjusting provincial energy intensity reduction. The optimal rate of provincial energy intensityreduction and provincial energy intensity reduction were searched. The decoupling relationshipbetween carbon dioxide emissions and economic growth of each province was also predicted.The energy consumption structure of the whole nation would be optimized. The proportion ofcoal consumption, oil consumption, and gas consumption would drop respectively. The proportion ofnon-fossil energy consumption would rise. But the proportion of non-fossil energy consumption couldnot reach the target in the “12th Five-Year Planning”. The optimal proportion of non-fossil energyconsumption of all provinces were upper limit of its expansion constraints, But the optimal proportionof coal consumption of most of provinces were lower limit of its expansion constraints. These resultsmeans that the non-fossil energy consumption should rise as far as possible, but the pace of optimizeenergy consumption structure of these provinces could not fast in the short term.The pace of optimize energy consumption structure of shanghai, shandong, hunan, hainan,guizhou, yunnan, qinghai, ningxia, xinjiang need be speeded up. The pace of optimize energyconsumption structure of Heilongjiang, Jilin, Inner Mongolia, henan, Hubei, Shanxi need slow down.The optimal rate of energy intensity reduction and carbon intensity reduction existed regionaldifferences. The optimal rate of energy intensity reduction of beijing, shanxi, Inner Mongolia, jilin,heilongjiang, anhui, and Shandong were more than20%. However, The optimal rate of energyintensity reduction of Qinghai and Xinjiang were less than2%.The optimal rate of carbon emissions intensity reduction of each province was more than thetarget of planning constraints. The optimal rate of carbon emissions intensity reduction of Tianjin,Zhejiang, Guangdong, Gansu, Qinghai, and Xinjiang was just its target. However, The optimal rate ofcarbon emissions intensity reduction of other provinces was more than its target. |
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