摘要
随着城市化进程加速,高密度开发与交通活动加剧使城市街区尺度空气污染问题日益凸显。文章以合肥市滨湖新区高密度建成区为例,基于卫星反演获取的30个地面点位PM_(2.5)质量浓度估算数据,构建LUR模型;通过双变量相关性分析筛选影响因素,最终选取8个影响因素与PM_(2.5)质量浓度进行多元回归分析,量化各因素的正负影响程度,并据此提出规划建议。研究构建的LUR模型为城市街区PM_(2.5)影响因素的相关性分析提供有效方法与数据支持,对城市微环境治理具有实践意义。
As urbanization accelerates,high-density development and intensified traffic activities have exacerbated air pollution issues at the urban block scale.Taking the high-density built-up area of Binhu New Area,Hefei as a case study,this paper develops a Land Use Regression(LUR)model,using estimated PM_(2.5) mass concentration data from 30 ground-based sampling points derived from satellite inversion.Bivariate correlation analysis was first used to screen potential influencing factors.Ultimately,8 factors were selected for multiple regression analysis against PM_(2.5) mass concentrations,to quantify the magnitude of their positive and negative impacts.Evidencebased planning recommendations were formulated based on the findings.The LUR model established in this study provides an effective methodological and data-driven foundation for analyzing the correlation of PM_(2.5) influencing factors in urban blocks,and holds practical value for urban micro-environment governance.
作者
夏宇轩
伍君奇
罗頔
王薇
XIA Yuxuan;WU Junqi;LUO Di;WANG Wei
出处
《住宅科技》
2025年第12期42-51,60,共11页
Housing Science
基金
国家自然科学基金面上项目“面向病毒气溶胶健康风险防控的公共建筑空间设计研究”(编号:52478016)
安徽省自然科学基金面上项目“地铁站域室内外环境PM2.5浓度分布和扩散规律及其空间关联性研究”(编号:2308085ME182)。
