Dynamical mechanism in meteorological factors using detrended cross-correlation analysis

Abstract

We simulate and analyze the temporal dependence of fine dust particle with sizes less than 10 microns, denoted as PM10, on influencing factors such as temperature, humidity, and wind velocity in eight South Korean cities. We employ the detrended cross-correlation analysis method to extract the overall tendencies of the hourly variations of those dependences. The relationships between PM10 and the meteorological factors are established by using the cross-correlation coefficients. Particularly, we ascertain from a specific interval 3≤ n ≤168 of the hourly time series data that a city in Korea, Andong has the largest cross-correlation coefficient while another city in Korea, Busan, has the smallest value in the correlation between the dust density PM10 and the wind velocity. A city in Korea, Donghae has the largest negative value of the cross-correlation coefficient between PM10and the humidity. We find that the cross-correlation is statistically significant for the hourly time intervals n = 12, 24, and 48 for meteorological time series data.