Analysis And Prediction On China's Energy-related CO₂ Emission And Transport Energy Consumption Based On Index Decomposition Method

As the largest developing country and the second largest energy consuming countries,as well as the second-largest carbon dioxide's emissions country after the United States,China's energy demand and related carbon dioxide's emissions have been one of the hottest problems disucssed by academe,enviornmental administers and all governrnents in the world.What factors can have some impacts on the change of energy consumption and related CO₂ emission? And how much the contribution of each factor is? Therefore it is very significant to analyze China's energy consumption and related carbon dioxide emissions,which is not only advantageous to China's sustainable development,but also to mitigate the global climate warming.In many industrial sectors,transportation energy consumption rises year by year and it's growth rate is higher than that of the entire society,which has become one of the fastest growing industries.It was note that,because energy consumption of transport and communication gathers an item in our country's statistical system,energy consumption can not be distinguished by transportation mode by fuel type.So it is of great importance to analyze and calculate energy consumption by transportation mode by fuel type,to decompose related factor which influence transportation energy consumption,which is not only one of the main contents of building an economy society,but also the objective requirements of transportation sustainable development.Currently,factor decomposition method is a relatively new method to analyze energy and environmental issues.This aspect's research overseas are quite many,however our country only then just started.Research on environmental issues and sectoral level are less.Thus,based on factor decomposition method this doctoral dissertation development models to quantitatively analyze of China's energy consumption,related carbon dioxide emissions and transportation energy consumption.The main work of this paper is shown as follows.(1) Based on the status quo analysis of China's energy consumption from 1980 to 2006, energy consumption decomposition models are established based on Laspeyres complete decomposition method and LMDI method,respectively,which are used to analyze the factors that influence the change of energy consumption and energy intensity.Then the LMDI method is generalized to an energy forecasting model(LMDIED) that has two funtions(analysis and forecasting). Under two scenarios,that model is used to predict energy demand for 2010,2015 and 2020.(2) Firstly,the terminal energy-related consumption CO₂ emission from 1991 to 2006 is calculated.Next,we analyze the status quo of CO₂ emission from 1991 to 2006.At last, based on Laspeyres complete decomposition method,CO₂ emission decomposition models are established to analyze the factors that influence the change of CO₂ emission and CO₂ emission intensity from whole level and sectoral level,respectively.(3) By analyzing the Chinese transportation development present situation,the transportation energy from 1991 to 2006 by transportation mode by fuel type is calculated.And then,transportation energy consumption decomposition models are established based on LMDI method, which are used to quantitatively analyze the factors that influence the change of transportation energy consumption.Next,energy and exergy effciencies in Chinese transportation sector is analyzed based on exergy method.Currently,city passenger transport energy consumption rises fastly.Based on LMDI method,a decomposition model is developed to to quantitatively analyze the driving forces behind increases in passenger transport energy consumption,which is help to find out the predominant factor that influences transportation energy consumption change.(4)Firstly,a transportation energy demand forecasting model is established based on PLSR method,which is used to predict transportation energy demand for 2020 under two scenarios. Next,the CTEF transportation energy need forecasting model from bottom to top is developed to predict transportation energy demand for 2010,2020 and 2030 under two scenarios. This model concludes four functions:forecasts the transportation energy need;analyzes factor that influences transportation energy need;analyzes energy/exergy efficiency and calculates greenhouse gas emissions.