Research On Influencing Factors Of Carbon Emissions In Construction Industry In Jiangxi Province

Global warming,caused by a significant increase in greenhouse gas emissions,has attracted the attention of countries around the world.China’s carbon emissions ranks among the top in the world.The government attaches great importance to carbon emission reduction in order to achieve carbon peaking and carbon neutrality as soon as possible.Because the building industry is a national pillar industry with high emissions and energy consumption,its carbon emissions remain high,accounting for 36% of the country’s overall carbon emissions.In the relevant documents of the IPCC,it is indicated that the construction industry has a certain advantage in all industries depending on its high potential and low cost in terms of emission reduction.Therefore,this paper uses the grey relational analysis method and the STIRPAT model to study the influencing factors of carbon emissions from the construction industry in Jiangxi Province.This paper first establishes a carbon emission measurement model for the whole life cycle of the construction industry,and divides the carbon emissions of the construction industry into the construction stage,the use and maintenance stage of the construction industry,and the maintenance and demolition stages of the construction industry.The construction stage includes the preparation of building materials stage,building material transportation stage and building construction stage.Collect the data of the construction industry in Jiangxi Province from 2004 to 2020,and calculate and analyze the carbon emissions of the construction industry in Jiangxi Province at various stages.Then,on the basis of the calculation model of the whole life cycle of the construction industry and the existing literature,the relevant influencing factors are selected through the calculation model of each stage,and several macro indicators of the construction industry are introduced,and 26 factors related to the carbon emission of the construction industry are selected.Secondly,the grey correlation method is used to analyze the correlation degree of the influencing factors to the carbon emissions of the construction industry in Jiangxi Province,so as to select the STIRPAT model indicators,and then construct the STIRPAT influencing factor analysis model,use the multiple linear regression method to fit the model,and use the ridge regression to eliminate the multicollinearity problem.The conclusions of this study are as follows:(1)Since 2004,the proportion of carbon emissions in the preparation stage of building materials in Jiangxi Province has continued to increase in the total carbon emissions of the construction industry in Jiangxi Province.The proportion of total carbon emissions from the construction industry continued to decline,and by2020,the proportions had changed from 50.0% and 40.42% to 76.25% and 15.49%.The data from the two stages shows that the continuous increase in the scale of the construction industry in Jiangxi Province has led to an increase in the use of building materials,and at the same time,the energy utilization efficiency has increased year by year.(2)Through correlation analysis,it is found that the indicators with the highest correlation in each stage are timber,road freight volume,completed area of construction industry and electricity consumption in the use stage of construction industry.However,considering that the rapid development of the logistics industry in recent years has a great impact on the road freight volume,the water freight volume is selected as the representative influencing factor of the transportation stage.(3)Eight variables of timber,electricity,completed area of buildings in the construction industry,freight volume by water,labor productivity of construction enterprises,GDP,urbanization rate,and added value of the tertiary industry will have a significant positive impact on total carbon emissions.And for each one percent increase,the carbon emissions of the construction industry in Jiangxi Province increased by0.112%,0.098%,0.071%,0.092%,0.065%,0.077%,0.381%,and 0.084%.