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http://dx.doi.org/10.5572/KOSAE.2009.25.4.339

Prediction Approaches of Personal Exposure from Ambient Air Pollution Using Spatial Analysis: A Pilot Study Using Ulsan Cohort Data  

Son, Ji-Young (Department of Public Health, Hanyang University)
Kim, Yoon-Shin (Department of Public Health, Hanyang University)
Cho, Yong-Sung (Department of Epidemiology, School of Public Health, UCLA)
Lee, Jong-Tae (Department of Environmental Health, College of Health Science, Korea University)
Publication Information
Journal of Korean Society for Atmospheric Environment / v.25, no.4, 2009 , pp. 339-346 More about this Journal
Abstract
The objectives of this study were to introduce spatial interpolation methods which have been applied in recent papers, to apply three methods (nearest monitor, inverse distance weighting, kriging) to domestic data (Ulsan cohort) as an example of estimating the personal exposure levels. We predicted the personal exposure estimates of 2,102 participants in Ulsan cohort using spatial interpolation methods based on information of their residential address. We found that there was a similar tendency among the estimates of each method. The correlation coefficients between predictions from pairs of interpolation methods (except for the correlation coefficient between nearest montitor and kriging of CO and $SO_2$) were generally high (r=0.84 to 0.96). Even if there are some limitations such as location and density of monitoring station, spatial interpolation methods can reflect spatial aspects of air pollutant and spatial heterogeneity in individual level so that they provide more accurate estimates than monitor data alone. But they may still result in misclassification of exposure. To minimize misclassification for better estimates, we need to consider individual characteristics such as daily activity pattern.
Keywords
Personal exposure; Prediction; Spatial interpolation; Air pollution;
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Times Cited By KSCI : 1  (Citation Analysis)
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