Relationship between neighborhood land use structure and the spatiotemporal pattern of PM2.5 at the microscale: Evidence from the central area of Guangzhou, China. (February 2022)

• Record Type: Journal Article
• Authors: Song, Jie; Zhou, Suhong; Peng, Yinong; Xu, Jianbin; Lin, Rongping
• Is Part Of: Environment & planning. Volume 49:Number 2(2022)
• Page Start: 485
• Page End: 500
• Publication Date: 2022-02
• Subjects: PM2.5 -- spatiotemporal pattern -- neighborhood -- land use structure -- microscale; City planning -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.11605
• DOI: 10.1177/23998083211007866
• Languages: English
• ISSNs: 2399-8083

Abstract

Fine particulate matter (PM2.5 ) is harmful to human health. Although the relationship between urban land use and PM2.5 has been studied in recent years, there has been little consideration of the relationship between land use structure and PM2.5 spatiotemporal patterns at the microscale. Based on mobile monitoring PM2.5 data and point of interest data, this paper explored their relationship with a classification and regression tree model. The results showed that PM2.5 exhibits spatiotemporal heterogeneity at the microscale. The neighborhoods' land use structure can explain 60.4% of the PM2.5 spatiotemporal patterns. Transportation and ecology are the two most significant land use types that correlated with PM2.5 spatiotemporal patterns. Fourteen rules of neighborhood land use structures with different land use types are identified land use structure which leads to different spatiotemporal patterns of PM2.5 . The higher the PM2.5 risk, the stronger the correlation with neighborhood land use structure is. The classification and regression tree model can be effectively used to judge the relationship between neighborhood land use structure and PM2.5 spatiotemporal patterns. The results provide a basis for developing appropriate measures, based on local conditions, to predict PM2.5 pollution levels at the microscale, and reduce the risk of neighborhood exposure to PM2.5 .