DOI: 10.1016/j.atmosenv.2015.02.018
Scopus记录号: 2-s2.0-84925430823
论文题名: Development of a land-use regression model for ultrafine particles in Toronto, Canada
作者: Sabaliauskas K ; , Jeong C ; -H ; , Yao X ; , Reali C ; , Sun T ; , Evans G ; J
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 110 起始页码: 84
结束页码: 92
语种: 英语
英文关键词: Diurnal variation
; Land use regression
; Spatiotemporal variation
; Ultrafine particles
Scopus关键词: Housing
; Population statistics
; Regression analysis
; Diurnal variation
; Land use regression
; Land-use regression models
; Monitoring locations
; Population densities
; Predictor variables
; Spatio-temporal variation
; Ultrafine particle
; Land use
; atmospheric pollution
; concentration (composition)
; diurnal variation
; land use change
; particle size
; pollution monitoring
; residential location
; spatial distribution
; spatiotemporal analysis
; Article
; atmospheric dispersion
; Canada
; circadian rhythm
; concentration (parameters)
; highway
; industrial area
; land use
; land use regression
; particle size
; particulate matter
; pollution monitoring
; population density
; predictor variable
; priority journal
; regression analysis
; residential area
; ultrafine particle
; Canada
; Ontario [Canada]
; Toronto
Scopus学科分类: Environmental Science: Water Science and Technology
; Earth and Planetary Sciences: Earth-Surface Processes
; Environmental Science: Environmental Chemistry
英文摘要: This study applies land-use regression (LUR) to characterize the spatial distribution of ultrafine particles (UFP) in a large city. Particle number (PN) concentrations were measured in residential areas around Toronto, Canada, between June and August 2008. A combination of fixed and mobile monitoring was used to assess spatial gradients between and within communities. The fixed monitoring locations included a central site, two downtown sites, and four residential sites located 6-15km from the downtown core. The mobile data included average PN concentrations collected on 112 road segments from 10 study routes that were repeated on three separate days. The mobile data was used to create the land-use regression model while the fixed sites were used for validation purposes. The predictor variables that best described the spatial variation of PN concentration (R2=0.72, validated R2=0.68) included population density within 300m, total resource and industrial area within 1000m, total residential area within 3000m, and major roadway and highway length within 3000m. The LUR model successfully predicted the afternoon peak PN concentration (slope=0.96, R2=0.86) but over-predicted the 24-haverage PN concentration (slope=1.28, R2=0.72) measured at seven fixed monitoring sites. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81767
Appears in Collections: 气候变化事实与影响
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作者单位: Southern Ontario Centre for Atmospheric Aerosol Research, Department of Chemical Engineering and Applied Chemistry, University of Toronto, Canada
Recommended Citation:
Sabaliauskas K,, Jeong C,-H,et al. Development of a land-use regression model for ultrafine particles in Toronto, Canada[J]. Atmospheric Environment,2015-01-01,110