Spatiotemporal Analysis of Variability in Domestic PM10 Data Using Grid Based Spatial Interpolation Method

Abstract

This study analyzed spatiotemporal variability in domestic PM10 data from 2001 to 2019. From annual numbers of stations between 175 and 484, the point data at each station were spatially interpolated using the inverse distance weighted method. A periodic variability in daily mean data was examined through wavelet analysis, which showed that there was a clear annual pattern with the periodic change following a regular cycle. The Mann-Kendall Test for monthly and annual mean data showed a decreasing trend in about 1 µg/m³ per year. The spatial change in the grid data for annual mean data represented that it was relatively higher in the northern regions than that in the southern regions and its mean and deviation decreased significantly over time. For the entire period of observation data, it was found that annual mean and standard deviation of PM10 concentrations were relatively high in the region near the metropolitan area.