This paper seeks to enhance understanding of the data distribution of ground-level ozone time series by analysing their multifractal spectra. Emphasis is placed on the suitability of the box-counting and moments methods for characterizing scaling properties of ozone concentration, enabling us to describe similarities and differences inferred from the multifractal spectra by analysing various types of monitoring stations (urban, suburban and rural monitoring sites) under identical atmospheric

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... ditions. It is herein demonstrated that that multifractal features are to a considerable extent similar for each type of monitoring station under warm atmospheric conditions and high solar radiation, owing to the fact that these weather characteristics homogenize the scaling behaviour of ozone. On the contrary, location and chemical precursors play a more prominent role under low temperatures and solar radiation, highlighting differences among multifractal features of ozone concentrations in the monitoring sites. At rural stations, the absence of anthropogenic emissions promotes less variability in ozone data and homogenization of multifractal behaviour throughout the year. Furthermore, a data shuffling procedure was performed in order to analyse changes occurring in multifractal spectra as time series are subjected to varying degrees of data position disturbance. Results indicate that multifractal analysis is a useful tool for describing the temporal scaling behaviour of ozone time series at different monitoring sites which refines results that have been traditionally provided by statistical analyses on ozone pollution.