Assessment of a Bayesian multivariate interpolation approach for health impact studies

作     者：Sun, WM Le, ND Zidek, JV Burnett, R 

作者机构：STAT Canada Ottawa ON K1A 0T6 Canada British Columbia Canc Agcy Canc Control Res Unit Vancouver BC Canada Univ British Columbia Dept Stat Vancouver BC V5Z 1M9 Canada Hlth Canada Ottawa ON Canada 

出 版 物：《ENVIRONMETRICS》 (环境计量学)

年 卷 期：1998年第9卷第5期

页      面：565-586页

核心收录：

学科分类：0830[工学-环境科学与工程（可授工学、理学、农学学位）] 08[工学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 

主　　题：air pollution Bayesian spatial interpolation EM algorithm ozone sulphate nitrate sulphur dioxide 

摘      要：Health impact studies of air pollution often require estimates of pollutant concentrations at locations where monitoring data are not available, using the concentrations observed at other monitoring stations and possibly at different time periods. Recently, a Bayesian approach for such a temporal and spatial interpolation problem has been proposed by Le, Sun and Zidek (1997). One special feature of the method is that it does not require all sites to monitor the same set of pollutants. This feature is particularly relevant in environmental health studies where pollution data are often pooled together from several monitoring networks which may or may not monitor the same set of pollutants. The methodology is applied to the data in the Province of Ontario, where monthly average concentrations for summer months of nitrogen dioxide (NO2 in mu g/m(3)), ozone (O-3 in ppb), sulphur dioxide (SO2 in mu g/m(3)) and sulfate ion (SO4 in mu g/m(3)) are available for the period from January 1 of 1983 to December 31 of 1988 at 31 ambient monitoring sites. Detailed descriptions of spatial interpolation for air pollutant concentrations at 37 approximate centroids of Public Health Units in Ontario using all available data are presented. The methodology is empirically assessed by a cross-validation study where each of the 31 sites is successively removed and the remaining sites are used to predict its concentration levels. The methodology seems to perform well. (C) 1998 John Wiley & Sons, Ltd.