DOI: 10.1016/j.atmosenv.2015.01.049
Scopus记录号: 2-s2.0-84921900755
论文题名: Two-week NO2 maps for the City of Zurich, Switzerland, derived by statistical modelling utilizing data from a routine passive diffusion sampler network
作者: Mueller M ; D ; , Wagner M ; , Barmpadimos I ; , Hueglin C
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 106 起始页码: 1
结束页码: 10
语种: 英语
英文关键词: Air quality assessment
; Generalized Additive Models
; Geoinformation
; Nitrogen dioxide
; Statistical modelling
; Urban environment
Scopus关键词: Air quality
; Diffusion
; Nitrogen oxides
; Regression analysis
; Statistical methods
; Air quality assessment
; Generalized additive model
; Geo-information
; Nitrogen dioxides
; Statistical modelling
; Urban environments
; Passive networks
; nitrogen dioxide
; air quality
; assessment method
; atmospheric modeling
; atmospheric pollution
; concentration (composition)
; data set
; diffusion
; emission
; nitrogen dioxide
; point source pollution
; public health
; spatial resolution
; urban pollution
; air quality
; algorithm
; Article
; diffusion
; exhaust gas
; explanatory variable
; generalized additive model
; heating
; passive diffusion network
; priority journal
; regression analysis
; Switzerland
; topography
; urban area
; Switzerland
; Zurich [Switzerland]
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: We developed a method to generate two-week NO2 concentration maps with a high spatial resolution (10m by 10m) for the city of Zurich, Switzerland, based on statistical modelling. Our models utilize data from a dense passive diffusion sampler network consisting of 49 sites that measured 14-day mean NO2 concentrations in the year 2008. The regression analysis is based on Generalized Additive Models (GAMs) and a stepwise forward selection algorithm that leads to models relying on a small number of explanatory variables (2-3). The explanatory variables included in the regression analysis are spatially resolved information on traffic and heating systems related NOX and NO2 emissions, respectively, sky view factors, and topography (elevation). Deviance explained of the 26 models ranges from 0.66 to 0.79. 81% of the modelled and 77% of the predicted NO2 concentrations, respectively, deviate less than 25% from the observations. The modelling approach outlined in this paper augments the value of point measurements obtained from urban routine passive diffusion sampler networks by providing spatially resolved concentration fields. The derived maps allow a detailed assessment of NO2 levels in cities and can be used in applications such as public health protection. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81868
Appears in Collections: 气候变化事实与影响
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作者单位: Empa, Swiss Federal Laboratories for Materials Science and Technology, Ueberlandstrasse 129, Duebendorf, Switzerland; SCOR Switzerland AG, General-Guisan-Quai 26, Zurich, Switzerland
Recommended Citation:
Mueller M,D,, Wagner M,et al. Two-week NO2 maps for the City of Zurich, Switzerland, derived by statistical modelling utilizing data from a routine passive diffusion sampler network[J]. Atmospheric Environment,2015-01-01,106