The Temporal Variations of PM10 Concentration in Taipei: A Fractal Approach

Abstract

A one-year series of hourly average PM 10 observations, which was obtained from the urban and national park air monitoring station at Taipei (Taiwan), was analyzed by descriptive statistics and fractal methods to examine the temporal structures of PM 10 concentrations. It was found that all PM 10 measurements exhibited the characteristic right-skewed unimodal frequency distribution and long-term memory. A monodimensional fractal analysis was performed by transferring the PM 10 concentration time series into a useful compact form: the box-dimension (D B)-threshold (T h) and critical scale (C S)-threshold (T h) plots. Scale invariance was found in these time series and the box dimension was shown to be a decreasing function of the threshold PM 10 level, implying multifractal characteristics, (i.e., the weak and intense regions scale differently). To test this hypothesis, the PM 10 concentration time series were transferred into multifractal spectra, i.e., the τ(q)-q plots. The analysis confirmed the existence of multifractal characteristics. A simple two-scale Cantor set with unequal scales and weights was then used to fit the calculated τ(q)-q plots. This model fits well with the entire spectrum of scaling exponents for the examined PM 10 time series. The relationship between the fractal parameters and classical statistical characteristics, as well as some problems concerning the applicability of fractal methods on air pollution, are discussed.