@inproceedings{813c37c01fec42a79f4dd6077907fdab,
title = "Daily, seasonal, and spatial patterns of PM10 in Seoul, Korea",
abstract = "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.",
keywords = "air pollution, bootstrapping, k-menas clustering, particulate matter",
author = "Lee, \{Kyu Jong\} and Kim, \{Seoung Bum\} and Park, \{Sun Kyoung\}",
year = "2011",
doi = "10.1109/ISI.2011.5984097",
language = "English",
isbn = "9781457700828",
series = "Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011",
pages = "278--283",
booktitle = "Proceedings of 2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011",
note = "2011 IEEE International Conference on Intelligence and Security Informatics, ISI 2011 ; Conference date: 10-07-2011 Through 12-07-2011",
}