Features of the detrended cross-correlation analysis in the time series between absorbable particulate matter and meteorological factors

Abstract

We simulate and analyze the temporal variation characteristics of PM10, which are particles with an aerodynamic diameter of less than 10 microns, and meteorological factors (temperature, humidity, and wind speed) in eight cities on the Korean peninsula. We employ the detrended cross-correlation analysis (DCCA) method to extract the overall tendency of the hourly variation. The relationships between the PM10 density and meteorological factors are established by using cross-correlation coefficients. As a result of non-Asian dust events, we ascertain from weekly intervals that Andong has the largest value, while Mokpo has the smallest one, in the case of the DCCA cross-correlation coefficient between the PM10 and the temperature. Particularly, the cross-correlations can be compared in eight cities, after we examine whether the cross-correlation would be statistically significant from the random number and the shuffled time series surrogations.