The Prediction Of Carbon Intensity And Analysis Of Carbon Abatement In The Pearl River Delta

As a result of global warming,the deterioration of environment become more and more serious.Reduction of specific emissions has been proposed as a national target,which was assigned to each province to be a constraint index in China.Especially,Guangdong Province,one of the most developed area in China,is taking the lead in energy conservation and emissions reduction.The carbon intensity should decline by 20.5% during the period of the thirteenth Five-Year Plan,and the Pearl River Delta is supposed to achieve this goal first.Thus,discussion of whether the Pearl River Delta could succeed in finding efficient pathway and take the lead in completing this target is of great theoretical and practical significance to promote energy conservation and develop low-carbon economy.This thesis includes three following parts of research contents:First,the geographical endowment,economic development and energy consumption in the Pearl River Delta region were analyzed.The carbon intensity and total amount of carbon emission of Pearl River Delta between 2005 and 2015 were estimated by using the coefficient method to study the spatial-temporal evolution of carbon emission and carbon intensity.The result shows that the percentage of economic aggregate and energy consumption in the Pearl River Delta region increased by 242% and 96% respectively from 2005 to 2015,and the economic growth rate was slightly higher than the growth rate of energy consumption.The amount of carbon emission from the Pearl River Delta increased from 3,438,600,000 tons to 6,74 8,900,000 tons,and the carbon intensity dropped from 1.89 tons / ten thousand Yuan to 1.13 tons / ten thousand Yuan,experiencing a drop of 40.2%.Under the effect of unbalanced economic development in the Pearl River Delta region,the amount of carbon emission in central region was lower than that in remote region,however the distributions of carbon intensity were exactly different.Secondly,we figured out the influencing factors of carbon intensity by grey correlation analysis.Thus,three grey prediction models of GM(1,1),GM(1,N)and GA-GM(1,N)were established.And the trend of carbon intensity in the Pearl River Delta region from 2005 to 2020 was predicted by the scenario analysis method.The result shows that the GA-GM(1,N)model optimized by genetic algorithm has the best prediction effect among the three models,and the minimum prediction error can reach 0.04%.With the existing policy conditions,the whole Pearl River Delta and Guangzhou can achieve the goal of reducing carbon intensity by 20.5%.When the level of economic development is higher than expected,Shenzhen,Dongguan and Zhongshan can accomplish the task of emission reduction,but other cities is going to experience significant pressure.Finally,the decoupling state of carbon emissions and economic development in the Pearl River Delta region was analyzed by Tapio decoupling mode,and driving factors were decomposed in two stages combined with Kaya identity and LMDI decomposition.The result shows that per capita GDP and energy intensity have great impact on decoupling relationship between carbon emission and economic growth in the Pearl River Delta is mainly influence,and population size shows relatively weaker influence.Among them,the per capita GDP and population size are the restraining factors to realize the decoupling of carbon emissions,and the energy intensity has a significant effect.The improvement of the decoupling state in the Pearl River Delta region is realized mainly through the improvement of energy efficiency and the adjustment of the industrial structure.The mean absolute percentage error(MAPE)is applied to measure the accuracy of prediction.The results show that,of the three models,GA-GM(1,N)produces the best carbon intensity forecasts,with MAPEs of 0.4–1.4% and 0.04–0.4% in the development and testing periods respectively.This indicates that the optimization of the genetic algorithm is effective.The realization of carbon reduction targets in different cities is also explored by combining grey models with scenario analysis.Only Guangzhou could achieve its reduction target under all scenarios,and it can serve as a reference for other cities.