建筑碳排放影响因素分析及情景预测

Analysis of influencing factors and scenario prediction of building carbon emission

为了解建筑碳排放的影响因素,以江苏省2005—2019年的建筑碳排放数据为研究对象,采用STIRPAT模型对影响建筑碳排放因素进行分析,并以常住人口、城镇化率、人均GDP、第三产业增加值、钢材产量、平均运输里程、建筑企业劳动生产率等为建筑全生命周期各阶段的主要影响因素,利用GA-BP神经网络模型对该省2020—2030年的建筑碳排放进行预测.实验结果表明:常住人口、城镇化率、钢材产量、平均运输里程以及建筑企业劳动生产率的提高会增加建筑碳排放;而人均GDP和第三产业增加值的上升有利于建筑碳排放量的减少.预测结果显示,江苏省建筑全生命周期碳排放在2012年已达到峰值,表明未来江苏省建筑碳排放总体呈下降趋势.该文结果为江苏省建筑业碳减排工作提供理论依据,同时江苏省作为建筑业大省,其在建筑业发展及碳减排工作推进中的经验也将为其他省份提供宝贵的参考价值.

In order to understand the influencing factors of construction carbon emission,the construction carbon emission data of Jiangsu Province from 2005—2019 is used as the research object.The STIRPAT model is used to analyze the factors affecting the carbon emission of buildings,and the main influencing factors are permanent resident population,urbanization rate,per capita GDP,added value of tertiary industry,steel output,average transportation mileage,labor productivity of construction enterprises,etc.The GA-BP neural network model is used to predict the building carbon emissions in the Province from 2020 to 2030.The experimental results show that the increase in resident population,urbanization rate,steel production,average transportation mileage and labour productivity of construction enterprises will increase construction carbon emissions,while the increase in GDP per capita and value added of the tertiary industry will reduce construction carbon emissions.The prediction results show that the life-cycle carbon emissions of construction in Jiangsu Province reached its peak in 2012,indicating a general downward trend in future construction carbon emissions in Jiangsu province.The results of this paper provide a theoretical basis for the carbon emission reduction work of the construction industry in Jiangsu Province.At the same time,the experience of Jiangsu Province in the development of the construction industry and the promotion of carbon emission reduction work will also provide valuable reference value for other provinces.