DOI: 10.1016/j.atmosenv.2015.08.009
Scopus记录号: 2-s2.0-84940398712
论文题名: Improving spatial nitrogen dioxide prediction using diffusion tubes: A case study in West Central Scotland
作者: Pannullo F ; , Lee D ; , Waclawski E ; , Leyland A ; H
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 118 语种: 英语
英文关键词: Bayesian fusion modelling and prediction
; Nitrogen dioxide
; Spatial prediction
Scopus关键词: Atmospheric movements
; Diffusion
; Forecasting
; Health
; Nitrogen
; Nitrogen oxides
; Pollution
; Atmospheric dispersion modeling
; Atmospheric dispersion models
; Epidemiological studies
; Measure concentration
; Modelling and predictions
; Nitrogen dioxides
; Pollution concentration
; Spatial prediction
; Pollution detection
; nitrogen dioxide
; air quality
; Bayesian analysis
; concentration (composition)
; data assimilation
; dispersion
; epidemiology
; equipment
; health risk
; nitrogen dioxide
; pollution monitoring
; prediction
; spatial variation
; Article
; atmospheric dispersion
; automation
; diffusion
; priority journal
; United Kingdom
; validation study
; Scotland
; United Kingdom
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: It has been well documented that air pollution adversely affects health, and epidemiological pollution-health studies utilise pollution data from automatic monitors. However, these automatic monitors are small in number and hence spatially sparse, which does not allow an accurate representation of the spatial variation in pollution concentrations required for these epidemiological health studies. Nitrogen dioxide (NO2) diffusion tubes are also used to measure concentrations, and due to their lower cost compared to automatic monitors are much more prevalent. However, even combining both data sets still does not provide sufficient spatial coverage of NO2 for epidemiological studies, and modelled concentrations on a regular grid from atmospheric dispersion models are also available. This paper proposes the first modelling approach to using all three sources of NO2 data to make fine scale spatial predictions for use in epidemiological health studies. We propose a geostatistical fusion model that regresses combined NO2 concentrations from both automatic monitors and diffusion tubes against modelled NO2 concentrations from an atmospheric dispersion model in order to predict fine scale NO2 concentrations across our West Central Scotland study region. Our model exhibits a 47% improvement in fine scale spatial prediction of NO2 compared to using the automatic monitors alone, and we use it to predict NO2 concentrations across West Central Scotland in 2006. © 2015 The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81566
Appears in Collections: 气候变化事实与影响
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作者单位: MRC CSO Social and Public Health Science Unit, University of Glasgow, 200 Renfield Street, Glasgow, United Kingdom; School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom; Public Health, University of Glasgow, United Kingdom
Recommended Citation:
Pannullo F,, Lee D,, Waclawski E,et al. Improving spatial nitrogen dioxide prediction using diffusion tubes: A case study in West Central Scotland[J]. Atmospheric Environment,2015-01-01,118