|本期目录/Table of Contents|

[1]史晨茜,刘兰君*,周鹏,等.武汉城市三维形态对PM2.5空间分布的影响及响应研究 [J].武汉工程大学学报,2025,47(06):689-697.[doi:10.19843/j.cnki.CN42-1779/TQ.202412015]
 SHI Chenxi,LIU Lanjun*,ZHOU Peng,et al.Impacts of Wuhan’s three-dimensional urban morphology on PM2.5 spatial distribution and their interactive effects [J].Journal of Wuhan Institute of Technology,2025,47(06):689-697.[doi:10.19843/j.cnki.CN42-1779/TQ.202412015]
点击复制

武汉城市三维形态对PM2.5空间分布的影响及响应研究
(/HTML)
分享到:

《武汉工程大学学报》[ISSN:1674-2869/CN:42-1779/TQ]

卷:
47
期数:
2025年06期
页码:
689-697
栏目:
智能制造
出版日期:
2025-12-31

文章信息/Info

Title:
Impacts of Wuhan’s three-dimensional urban morphology on PM2.5 spatial distribution and their interactive effects
文章编号:
1674 - 2869(2025)06 - 0689 - 09
作者:
史晨茜1刘兰君*1周鹏2林奕晨3许婉清1陈岸1伍嘉诚1
1. 武汉工程大学土木工程与建筑学院,湖北 武汉 430074;
2. 湖北省战略规划中心,湖北 武汉 430071;
3. 永业行规划勘测设计(湖北)有限公司,湖北 武汉 430000

Author(s):
SHI Chenxi1LIU Lanjun*1ZHOU Peng2LIN Yichen3XU Wanqing1CHEN An1WU Jiacheng1
1. School of Civil Engineering and Architecture,Wuhan Institute of Technology,Wuhan 430074,China;
2. Hubei Strategic Planning Center,Wuhan 430071,China;
3. Yongyehang Planning Survey and Design (Hubei) Co.,Ltd,Wuhan 430000,China

关键词:
武汉市主城区城市三维形态PM2.5污染影响因素空间计量分析
Keywords:
main urban area of Wuhanthree-dimensional urban morphologyPM2.5 pollutioninfluencing factors spatial econometric analysis
分类号:
X513
DOI:
10.19843/j.cnki.CN42-1779/TQ.202412015
文献标志码:
A
摘要:
在全球高速城市化发展背景下,城市形态的环境效应已经成为当前的热点研究主题,突破传统二维平面视角的局限,以武汉市主城区为研究对象,以“PM2.5空间格局分析—城市三维形态测度—作用机制挖掘”为研究主线,通过构建普通线性回归模型(OLS)、空间滞后模型(SLM)和空间误差模型(SEM)开展武汉城市三维形态对PM2.5空间分布的影响及响应研究。研究结果表明:武汉市主城区PM2.5浓度整体呈现“西北高东南低”的空间分布趋势,并具有明显的空间自相关特征。对比OLS、SLM和SEM模型的回归结果与检验参数,SEM拟合结果最优。城市形态显著影响PM2.5浓度的空间异质性:路网密度对武汉市主城区PM2.5浓度有显著的正向影响;土地利用混合度、武汉市地区生产总值等城市二维形态对PM2.5浓度具有显著的负效应;交通可达性、高层高密度城市形态、三维绿量、距江距离等城市三维形态对PM2.5浓度具有显著的负效应。通过合理控制城市三维形态,有助于削减城市PM2.5浓度,改善城市环境,实现可持续发展。
Abstract:
With the rapid global urbanization,the environmental effects of urban morphology have emerged as a prominent research focus. This study broke through the limitations of traditional two-dimensional analyses by examining Wuhan’s main urban area through a tripartite framework——“PM2.5 spatial pattern analysis → three-dimensional(3D) urban morphology quantification → mechanistic interpretation”. Using ordinary least squares model(OLS),spatial lag model (SLM),and spatial error model(SEM),we systematically evaluated the impact of 3D urban morphology on PM2.5 spatial distribution. The results demonstrated three key findings regarding PM2.5 distribution in Wuhan’s main urban area:Firstly,PM2.5 concentrations exhibited a distinct spatial pattern characterized by higher levels in northwestern sectors and lower concentrations in southeastern zones,with a statistically significant autocorrelation. Secondly,comparative analysis of regression results and test parameters from OLS,SLM and SEM models indicated that SEM provided the optimal fit. Lastly,the urban morphology significantly affected the spatial heterogeneity of PM2.5 concentration through three distinct mechanisms:(1) Road network density showed a significant positive correlation with PM2.5 levels;(2)Two-dimensional urban morphology indicators—particularly land-use mix diversity and regional GDP density— demonstrated significant negative associations;(3) Three-dimensional urban features including transportation accessibility,high-density building clusters,3D green biomass,and proximity to the Yangtze River all exhibited substantial negative effects. These findings suggest that rational control of three-dimensional urban morphology can effectively reduce the concentration of PM2.5 in the city,improve the urban environment and achieve sustainable development.

参考文献/References:

[1] 叶深,王鹏,黄祎,等.长三角城市群城市空间形态对PM2.5与O3污染空间异质性特征的影响研究[J].生态环境学报,2023,32(10):1771-1784.
[2] 陈明,胡义,戴菲.城市绿地空间形态对PM2.5的消减影响——以武汉市为例[J].风景园林,2019,26(12):74-78.
[3] BADACH J, WOJNOWSKI W, G BICKI J. Spatial aspects of urban air quality management:estimating the impact of micro-scale urban form on pollution dispersion [J]. Computers,Environment and Urban Systems,2023,99:101890.
[4] 孙梦竹,杨昆,杨玉莲,等.基于MODIS的中国PM2.5污染时空分布特征研究[J].环境科学与技术,2017,40(11):53-58.
[5] 韩婧,李元征,李锋.2000—2015年中国PM2.5浓度时空分布特征及其城乡差异[J].生态学报,2019,39(8):2954-2962.
[6] 宋俊.中国PM2.5污染影响因素及健康风险研究[D].济南:山东师范大学,2024.
[7] 刘芮男,寇星霞,高怡,等.近年来云南省PM2.5浓度变化趋势与潜在区域来源分析[J].气候与环境研究,2023,28(5):509-517.
[8] 李飞,董珑,孔少杰,等.我国省域CO2-PM2.5-O3时空关联效应与协同管控对策[J].中国环境科学,2023,43(12):6246-6260.
[9]YANG Y,CHRISTAKOS G. Spatiotemporal characterization of ambient PM2.5 concentrations in Shandong Province (China) [J]. Environmental Science & Technology,2015,49(22):13431-13438.
[10] 陈美娟,刘静,刘利民,等.基于MODIS数据的沈阳市PM2.5反演研究[J].环境科学与技术,2016,39(12):87-93.
[11] 刘迅,廖珊慧,李智恒,等.基于MSPA分析绿地形态空间格局对PM2.5的消退作用——以广州市、深圳市为例[J].生态科学,2024,43(3):186-195.
[12] YU L D, WANG G F, ZHANG R J, et al. Characterization and source apportionment of PM2.5 in an urban environment in Beijing [J]. Aerosol and Air Quality Research,2013,13(2):574-583.
[13] 陈辉,厉青,王中挺,等.利用MODIS资料监测京津冀地区近地面PM2.5方法研究[J].气象与环境学报,2014,30(5):27-37.
[14] 施婷婷,王帅,杨立娟,等.中国华东地区PM2.5浓度时空变化及与景观格局关联研究[J].遥感技术与应用,2024,39(2):435-446.
[15] DENG C X,QIN C Y,LI Z W,et al. Spatiotemporal variations of PM2.5 pollution and its dynamic relationships with meteorological conditions in Beijing-Tianjin-Hebei region [J]. Chemosphere,2022,301:134640.
[16] 徐建辉,江洪.长江三角洲PM2.5质量浓度遥感估算与时空分布特征[J].环境科学,2015,36(9):3119-3127.
[17] HO K F,HO S S H,LEE S C,et al. Summer and winter variations of dicarboxylic acids,fatty acids and benzoic acid in PM2.5 in Pearl Delta River Region,China [J]. Atmospheric Chemistry and Physics,2011,11(5):2197-2208.
[18] 巫燕园,刘逸凡,汤蓉,等.中国特大城市群PM2.5污染及健康负担的时空演变特征[J].南京大学学报(自然科学),2024,60(1):158-167.
[19] 张军,刘磊玉,张腾飞,等.中国城市群PM2.5人口暴露风险时空格局及其驱动机制[J].环境科学,2025,46(8):5000-5012.
[20] HUANG C Y, HU T T,DUAN Y S, et al. Effect of urban morphology on air pollution distribution in high-density urban blocks based on mobile monitoring and machine learning [J]. Building and Environment,2022,219:109173.
[21] 方怡青,曲凌雁.城市空间形态与空气质量相关性研究综述[J].现代城市研究,2018(8):88-94.
[22] YANG J Y,SHI B X,SHI Y,et al. Air pollution dispersal in high density urban areas:research on the triadic relation of wind,air pollution,and urban form [J]. Sustainable Cities and Society,2020,54:101941.
[23] 岳峰,傅凡,戴菲,等.基于遥感反演的特大城市颗粒物浓度与三维绿量相关性研究[J].中国园林,2021,37(3):83-88.

相似文献/References:

备注/Memo

备注/Memo:
收稿日期:2024-12-18
基金项目:国家自然科学基金(52278076);湖北省社科基金一般项目(HBSKJJ20233316)
作者简介:史晨茜,硕士研究生。Email:22304010022@stu.wit.edu.cn
*通信作者:刘兰君,硕士,副教授。Email:11090101@wit.edu.cn

更新日期/Last Update: 2026-01-06