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Study On The Influencing Factors Of Building Carbon Emission In Chongqing Based On The Model Of STIRPAT

Posted on:2019-08-23Degree:MasterType:Thesis
Country:ChinaCandidate:Z H HuangFull Text:PDF
GTID:2371330566977516Subject:Management science and engineering
Abstract/Summary:PDF Full Text Request
The rapid process of urbanization and industrialization has resulted in excessive carbon emissions.At present,carbon emissions are widely considered as the main causes of climate change which affects human development in some dimensions including economy,society and ecology.China is the lagest greenhouse gas emission country in the world.The energy consumed by building in China presents appromitate 1/5 of the overall energy consumed by the whole country.Therefore,building operation is one of the most potential areas to reduce carbon emissions.In this study,Chongqing city is taken as an example to analyze which factors have effect on building carbon emissions,and predict the carbon emissions of buildings in Chongqing city in the period of 2015-2030.Using the literature review method,this study chose the principle of environmental impact evaculation(STIRPAT)to establishe an evaluation model for analyzing influencing factors of building carbon emission in Chongqing city,and this study chose scenario analysis method to predict building carbon emission of Chongqi in the future period of 2015-2030.Through the literature review method and the selection principle of influencing factors of building carbon emission in Chongqing city,this study selected five factors including the number of resident population,urbanization rate,per capita GDP,per capita third industrial added value and building carbon emission per unit floor area.Then though the application of environment impact assessment model(STIRPAT)and ridge regression method,this study established the model of the influencing factors of carbon emission in Chongqing city.Finally,the scenario analysis method and the STIRPAT prediction model were employed to predict the amount of building carbon emission in Chongqing city from 2015 to 2030.This study set three scenario including benchmark scenario,pessimistic scenario and optimistic scenario to predict the changing trend of buinding carbon emission of Chongqing city in the three different scenario from 2016 to 2030.The main results of this study are as follows: 1)This study calculated building carbon emission of the stage of building operation in Chongqing city during the period of 2005-2014 years.This study indicates that the quantity of building carbon emission in Chongqing city had a rising trend;2)The number of resident population has the greatest impact on building carbon emission in Chongqing city,which is fellowed by the influencing factors of urbanization rate,per capita GDP,per capita third industrial added value and building carbon emission per unit floor area;3)in the benchmark scenario,pessimistic scenario and optimistic scenario,the amount of building carbon emissions in Chongqing city from 2015 to 2030 are showing a growth trend,but the three growth rates are similiar.The growth rates of building carbon emissions in Chongqing city from large to small are pessimistic scenario,benchmark scenario,and optimistic scenario;4)Influencing factors study and scenario-based prediction of building carbon emission in Chongqing city based on the model of STIRPAT indicated that the Chongqing city government can reduce building carbon emission by reducing the size of coefficients of the five influencing factors and 5)this study suggests the Chongqing goverance take efforts to reduce building carbon emission from the perspective of reducing the size of coefficients of these five influencing factors.The results of this research not only can be used as useful references for Chongqing municipal government in formulating building emission reduction measueras,but also can provide more materials for enriching the research about carbon emissions.
Keywords/Search Tags:Building carbon emissions, Chongqing, STIRPAT model, Influencing factors, Carbon emissions prediction analisis
PDF Full Text Request
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