风景园林2026，Vol.33Issue(1)：34-46,13.DOI:10.3724/j.fjyl.LA20250571
城市形态对高密度城区PM2.5浓度的影响研究——以干旱区城市乌鲁木齐市主城区为例
Impact of Urban Morphology on PM2.5 Concentrations in High-Density Urban Areas:A Case Study of the Main Urban Area of Urumqi,an Arid-Region City
摘要
Abstract
[Objective]Rapid urbanization in arid regions presents distinctive challenges for air quality management,particularly concerning fine particulate matter(PM2.5).This study aims to systematically quantify the seasonal dynamics of PM2.5 concentrations across different local climate zone(LCZ)types within a high-density arid city.It seeks to elucidate how two-dimensional landscape patterns and three-dimensional urban morphological characteristics jointly influence the spatial distribution of PM2.5,and to identify the dominant drivers and their nonlinear mechanisms in this unique climatic context. [Methods]The main urban area of Urumqi,a representative high-density city in the arid northwest of China,was selected as the case study.A multi-source data fusion framework was constructed,integrating satellite remote sensing data(Sentinel-2 and Landsat 8/9 imagery),vector-based architectural data,ground-based meteorological observations,and high-resolution topographic data.Methodologically,the study proceeded in two main stages within the overarching LCZ framework.First,a random forest(RF)model was employed to generate high-resolution(30-meter)seasonal PM2.5 concentration maps through inversion techniques and to perform a precise LCZ classification for the study area.Second,an eXtreme Gradient Boosting(XGBoost)machine learning regression model,coupled with the SHapley Additive exPlanations(SHAP)interpretability framework,was applied.This advanced analytical approach was used to deconvolve the relative importance and,more importantly,the nonlinear dependence and threshold effects of a comprehensive set of influencing factors.These factors encompassed two-dimensional landscape metrics,three-dimensional urban morphological indicators,elevation,and key meteorological parameters. [Results]The analysis revealed a pronounced seasonal pattern of"higher PM2.5 concentrations in winter and lower in summer"in Urumqi's main urban area,coupled with a spatial distribution characterized by"higher concentrations in the north than in the south,and in built-up areas compared to green spaces".Significant differences in PM2.5 levels were observed among LCZ types.LCZ 10(heavy industry)and the compact built types(LCZ 2,compact mid-rise and LCZ 3,compact low-rise)were identified as persistent high-pollution zones.In contrast,forested LCZ types(LCZ A,dense trees and LCZ B,scattered trees)exhibited a significant capacity to mitigate PM2.5,maintaining consistently low concentrations.Factor importance analysis indicated seasonal shifts in the dominant controls.The NDVI emerged as the most influential factor in summer,demonstrating a linear negative correlation with PM2.5.A threshold effect was observed,with NDVI values greater than 0.25 leading to a marked enhancement of its purifying effect during both seasons.In winter,air temperature and elevation became the predominant factors.Temperatures below-10.2 ℃ strongly favored the formation of temperature inversions,trapping pollutants near the surface.Concurrently,areas with elevations below 800 m,particularly in the northern basin,were prone to forming"cold-air pools"that exacerbated pollution accumulation.Other key nonlinear thresholds were identified:a bare land cohesion index(COHESIONBLG)exceeding 85 in winter led to a sharp increase in dust emission potential;an open group LCZ cohesion index(COHESIONOG)greater than 88 facilitated better pollutant dispersion;and a temperature above 25 ℃ in summer promoted vertical mixing and PM2.5 diffusion.Furthermore,the LCZ compact group consistently showed significantly higher pollution levels than the LCZ open group,highlighting the role of urban morphology in modulating air quality.SHAP analysis further quantified several other key nonlinear thresholds:a Bare Soil/Sand group cohesion index(COHESIONBLG)exceeding 85 in winter led to a sharp increase in dust emission potential;an open group LCZ cohesion index(COHESIONOG)greater than 88 facilitated better pollutant dispersion;and a temperature above 25 ℃ in summer promoted vertical atmospheric mixing and PM2.5 dispersion.Furthermore,the LCZ compact group(LCZ 1-3)consistently exhibited significantly higher pollution levels than the LCZ open group(LCZ 4-6),unequivocally highlighting the decisive role of urban morphology compactness in modulating local air quality. [Conclusion]This study provides a comprehensive and quantitative analysis of the complex interplay between multi-dimensional urban morphology and PM2.5 pollution in an arid,high-density city,leveraging the standardized LCZ framework.It successfully advances the application of the LCZ scheme in arid-region air pollution research,moving beyond qualitative associations to delineate clear seasonal divergences in underlying controlling mechanisms.The principal contribution lies in the innovative integration of explainable machine learning(specifically,XGBoost-SHAP),which enabled precise quantification of critical nonlinear thresholds of key morphological,topographic,and meteorological factors.These findings transcend a merely deeper mechanistic understanding.The findings yield concrete,quantitative scientific evidence that can directly inform the development of precise,LCZ-type-specific and seasonally-adapted PM2.5 management strategies.Consequently,this study offers a robust,evidence-based foundation for optimizing urban spatial planning and urban design in Urumqi and other arid-region cities that face similar air quality challenges.关键词
风景园林/城市形态/局地气候分区/PM2.5/可解释机器学习/非线性阈值/乌鲁木齐Key words
landscape architecture/urban morphology/local climate zone/PM2.5/explainable machine learning/nonlinear threshold/Urumqi分类
建筑与水利引用本文复制引用
刘颂,酒江涛,柳迪子,董婵婵..城市形态对高密度城区PM2.5浓度的影响研究——以干旱区城市乌鲁木齐市主城区为例[J].风景园林,2026,33(1):34-46,13.基金项目
国家自然科学基金"基于生态系统服务权衡与协同的市级生态空间多目标优化研究"(编号52178050) （编号52178050）
