摘要
揭示PM_(2.5)浓度与交通、人口、土地利用等因素的关系对突破PM_(2.5)管理难题起着关键性作用。以往研究大多仅考虑单类影响因素,忽略多类因素的综合作用,且相关研究主要从二维尺度分析城市发展与PM_(2.5)的关系,较少关注三维格局的影响。为解决上述不足,基于广州、深圳的PM_(2.5)监测数据分析PM_(2.5)浓度总体概况和时空分布,进而通过随机森林回归剖析交通、二维土地利用与景观格局、三维空间格局等因素对PM_(2.5)浓度的影响。结果表明:(1)当道路交通为研究区空气污染的主要污染源时,PM_(2.5)浓度变化曲线主要呈双峰状,在中午及晚高峰后两个小时左右达到峰值;(2)二维土地利用与景观格局中的的结构特征与破碎度对PM_(2.5)浓度影响显著,其中不透水面的ED、LSI作用明显;(3)三维空间格局主要通过影响气流运动影响PM_(2.5)的传播,各影响因素与PM_(2.5)浓度呈密切相关。研究结果可辅助规划部门针对PM_(2.5)的影响因素制定相关政策,提高城市环境舒适度,缓解城市发展与污染的矛盾。
Understanding multidimensional relationships between PM_(2.5)concentrations and driving factors(e.g.,transportation,population,land use)is crucial for pollution control.Previous studies have typically examined single-dimensional influences while neglecting synergistic effects between factors.Moreover,research has predominantly analyzed urban development and PM_(2.5)relationships at two-dimensional scales,with limited attention to three-dimensional urban form impacts.Using monitoring data from Guangzhou and Shenzhen,this study explores the characterizes spatiotemporal PM_(2.5)patterns,and quantifies transportation,2D/3D land use impacts via random forest regression.The results show that:(1)the single-day pollution change curve is double-peaked when transportation is the primary source of air pollution in the study area,and the peak emission is reached about two hours after noon and evening rush hour;(2)as for the two-dimensional land use pattern,structural characteristics and fragmentation exert a significant influence on PM_(2.5)concentration,of which ED and LSI on impervious surface have obvious effect;(3)the three-dimensional land use pattern mainly affects the diffusion of PM_(2.5)by affecting the airflow movement,and all three-dimensional factors are closely correlated with the degree of pollution.These results provide mechanistic insights for targeted PM_(2.5)mitigation policies,supporting sustainable urban development while addressing environment-development conflicts.
作者
林锦耀
杨柳
胡悦
温宥越
肖钺
LIN Jinyao;YANG Liu;HU Yue;WEN Youyue;XIAO Yue(School of Geography and Remote Sensing,Guangzhou University,Guangzhou 510006,China;South China Institute of Environmental Science,Ministry of Ecology and Environment,Guangzhou 510535,China;National Key Laboratory of Urban Ecological Environment Simulation and Protection,Guangzhou 510535,China)
出处
《生态科学》
北大核心
2025年第2期143-153,共11页
Ecological Science
基金
教育部人文社会科学研究青年基金(23YJCZH125)
广东省基础与应用基础研究基金青年提升项目(2023A1515030300)
广东省哲学社会科学规划学科共建项目(GD23XSH11)。
