京津冀建筑业碳排放区域差异及影响因素研究
Study on Regional Differences and Influencing Factors of Carbon Emissions in the Construction Industry of Beijing Tianjin Hebei
石振武 1毕爱琦 1王金茹1
作者信息
- 1. 东北林业大学 土木与交通学院,黑龙江 哈尔滨 150040
- 折叠
摘要
以京津冀地区为研究对象,构建建筑业全过程碳排放测算模型分析京津冀地区建筑业碳排放的区域差异,利用STIRPAT模型进一步探讨人口总量、城镇化水平、人均 GDP、建筑产业结构效应、能源结构效应、能源消耗强度、劳动生产率 7个因素对京、津、冀建筑业碳排放的影响.结果表明:京津冀地区建筑业碳排放总量大体呈现先增后减再稳定的态势,各因素对京津冀建筑业碳排放的影响存在地区差异,除劳动生产率抑制建筑业碳排放增长,其余6个因素均起促进作用,其中城镇化水平对北京市和天津市的促进作用最强,人口总量对河北省的促进作用最强.基于此,根据各地区碳排放影响因素的影响情况制定差异化减排对策.
Abstract
Taking the Beijing Tianjin Hebei region as the research object,the whole-process carbon emission calculation model of the construction industry was constructed to analyze the regional differences in carbon emissions of the construction industry in the Beijing-Tianjin-Hebei region.The STIRPAT model was used to further explore the impact of seven factors,including population,urbanization level,per capita GDP,construction industrial structure effect,energy structure effect,energy consumption intensity and labor productivity,on the carbon emissions of construction industries in Beijing Tianjin Hebei.The results show that the total carbon emissions of the construction industry in the Beijing-Tianjin-Hebei,generally show a trend of first increasing,then decreasing,and then stabilizing.There are regional differences in the impact of various factors on the carbon emissions of the construction industry in the Beijing-Tianjin-Hebei region.In addition to the labor productivity inhibiting the growth of carbon emissions of the construction industry,the other six factors all play a role in promoting.Among them,the level of urbanization has the strongest promoting effect on Beijing and Tianjin,respectively.The total population has the strongest promoting effect on Hebei Province.Based on this,differentiated emission reduction measures are formulated according to the influence of carbon emission factors in each region.
关键词
建筑业碳排放/STIRPAT模型/影响因素/劳动生产率Key words
construction industry carbon emission/STIRPAT model/influence factor/labor productivity引用本文复制引用
基金项目
黑龙江省自然科学基金(YQ2020G001)
黑龙江省交通运输厅重点科技项目(J-20181215)
出版年
2024
NETL
NSTL
万方数据