DOI: 10.1016/j.atmosenv.2015.10.042
Scopus记录号: 2-s2.0-84945546115
论文题名: Development of long-term spatiotemporal models for ambient ozone in six metropolitan regions of the United States: The MESA Air study
作者: Wang M ; , Keller J ; P ; , Adar S ; D ; , Kim S ; -Y ; , Larson T ; V ; , Olives C ; , Sampson P ; D ; , Sheppard L ; , Szpiro A ; A ; , Vedal S ; , Kaufman J ; D
刊名: Atmospheric Environment
ISSN: 0168-2563
EISSN: 1573-515X
出版年: 2015
卷: 123 起始页码: 79
结束页码: 87
语种: 英语
英文关键词: Geo-statistical model
; MESA Air
; Multi-city
; Ozone
; Spatio-temporal
Scopus关键词: Forecasting
; Land use
; Ambient ozone concentration
; Epidemiological studies
; Multi-city
; Spatio temporal
; Spatio-temporal variation
; Spatiotemporal patterns
; Statistical modeling
; Temporal and spatial variability
; Ozone
; ozone
; air quality
; concentration (composition)
; database
; kriging
; long-term change
; metropolitan area
; model validation
; ozone
; public health
; spatiotemporal analysis
; ambient air
; Article
; community
; controlled study
; environmental exposure
; home
; human
; kriging
; land use
; ozone layer
; priority journal
; spatiotemporal analysis
; United States
; United States
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: Background: Current epidemiologic studies rely on simple ozone metrics which may not appropriately capture population ozone exposure. For understanding health effects of long-term ozone exposure in population studies, it is advantageous for exposure estimation to incorporate the complex spatiotemporal pattern of ozone concentrations at fine scales. Objective: To develop a geo-statistical exposure prediction model that predicts fine scale spatiotemporal variations of ambient ozone in six United States metropolitan regions. Methods: We developed a modeling framework that estimates temporal trends from regulatory agency and cohort-specific monitoring data from MESA Air measurement campaigns and incorporates land use regression with universal kriging using predictor variables from a large geographic database. The cohort-specific data were measured at home and community locations. The framework was applied in estimating two-week average ozone concentrations from 1999 to 2013 in models of each of the six MESA Air metropolitan regions. Results: Ozone models perform well in both spatial and temporal dimensions at the agency monitoring sites in terms of prediction accuracy. City-specific leave-one (site)-out cross-validation R2 accounting for temporal and spatial variability ranged from 0.65 to 0.88 in the six regions. For predictions at the home sites, the R2 is between 0.60 and 0.91 for cross-validation that left out 10% of home sites in turn. The predicted ozone concentrations vary substantially over space and time in all the metropolitan regions. Conclusion: Using the available data, our spatiotemporal models are able to accurately predict long-term ozone concentrations at fine spatial scales in multiple regions. The model predictions will allow for investigation of the long-term health effects of ambient ozone concentrations in future epidemiological studies. © 2015 Elsevier Ltd. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/81336
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA, United States; Department of Biostatistics, University of Washington, Seattle, WA, United States; Department of Epidemiology, University of Michigan, Ann Arbor, MI, United States; Institute of Health and Environment, Seoul National University, Seoul, South Korea; Department of Civil and Environmental Engineering, College of Engineering, University of Washington, Seattle, WA, United States; Department of Statistics, University of Washington, Seattle, WA, United States
Recommended Citation:
Wang M,, Keller J,P,et al. Development of long-term spatiotemporal models for ambient ozone in six metropolitan regions of the United States: The MESA Air study[J]. Atmospheric Environment,2015-01-01,123