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김선영,이선주,음영섭,Hae-Jin Choi,신혜섭,류형곤,김호 환경독성보건학회 2014 환경독성보건학회지 Vol.29 No.-
Objectives Cohort studies of associations between air pollution and health have usedexposure prediction approaches to estimate individual-level concentrations. A commonprediction method used in Korean cohort studies is ordinary kriging. In this study, performanceof ordinary kriging models for long-term particulate matter less than or equal to10 μm in diameter (PM10) concentrations in seven major Korean cities was investigatedwith a focus on spatial prediction ability. Methods We obtained hourly PM10 data for 2010 at 226 urban-ambient monitoring sitesin South Korea and computed annual average PM10 concentrations at each site. Giventhe annual averages, we developed ordinary kriging prediction models for each of theseven major cities and for the entire country by using an exponential covariance referencemodel and a maximum likelihood estimation method. For model evaluation, cross-validationwas performed and mean square error and R-squared (R2) statistics were computed. Results Mean annual average PM10 concentrations in the seven major cities ranged between45.5 and 66.0 μg/m3 (standard deviation=2.40 and 9.51 μg/m3, respectively). Cross-validated R2 values in Seoul and Busan were 0.31 and 0.23, respectively, whereasthe other five cities had R2 values of zero. The national model produced a higher crossvalidatedR2 (0.36) than those for the city-specific models. Conclusions In general, the ordinary kriging models performed poorly for the seven majorcities and the entire country of South Korea, but the model performance was better inthe national model. To improve model performance, future studies should examine differentprediction approaches that incorporate PM10 source characteristics.
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