Daily, seasonal, and spatial patterns of PM10 in Seoul, Korea

Various analyses of the complex behavior in ambient air pollutants have been conducted to extract their implicit patterns and meaningful information. In the present study, we conducted some statistical analyses to identify daily, seasonal, and spatial patterns of particulate matters (PM₁₀) in Seoul, Korea. We used the daily PM₁₀ mass concentration data observed at 25 different monitoring sites in Seoul, Korea from 2005 to 2009. Analysis of variance and a k-means clustering algorithm were used to investigate seasonal and spatial patterns of PM₁₀ concentrations. Moreover, we used a bootstrap method to calculate the probabilities that PM₁₀ concentrations exceeded the environment limit or the comprehensive air quality index in different months.