# Spatio-temporal analysis of particulate matter extremes in Seoul: use of multiscale approach

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## Abstract

This paper considers a problem of analyzing temporal and spatial structure of particulate matter (PM) data with emphasizing high-level \(\text {PM}_{10}\).
The proposed method is based on a combination of a generalized extreme value (GEV) distribution and a multiscale concept from scaling property theory used in hydrology. In this study, we use hourly \(\text {PM}_{10}\) data observed for 5 years on 25 stations located in Seoul metropolitan area, Korea. For our analysis, we calculate monthly maximum values for various duration times and area coverages at each station, and show that their distribution follows a GEV distribution. In addition, we identify that the GEV parameters of \(\text {PM}_{10}\) maxima hold a new scaling property, termed ‘piecewise linear scaling property’ for certain duration times. By using this property, we construct a 12-month return level map of hourly \(\text {PM}_{10}\) data at any arbitrary *d*-hour duration. Furthermore, we extend our study to understand spatio-temporal multiscale structure of \(\text {PM}_{10}\) extremes over different temporal and spatial scales.

### Keywords

Generalized extreme value distribution Kriging Particulate matter Return level Scaling property## Notes

### Acknowledgements

This paper is based on author’s report awarded at “The Seoul Institute Research Competition 2015” and the data provided by The Seoul Institute. This work was supported in part by the National Research Foundation of Korea (NRF) Grant funded by the Korea government (MSIP) (Nos. 20110030811 and 2015R1D1A1A01056854).

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