Multifractal Analysis of Airborne Particle Count Data: The Influence of Data Preprocessing

We analyze particle count data samples (taken from the recordings of aerosol particle sensors in a c1eanroom environment measuring particles of size larger than 0,01 /Lm) by evaluating their multifractal f( a )-spectra. This is done by use of the canonical method, The data samples are preprocessed in various ways: The absolute values of the differences of successive original data values (the "derivative" of the original data) are taken as a measure for the multifractal analysis. Furthermore, the original data values are shifted by an additive constant, These shifts generate interesting effects in the resulting f(a.)-spectra if the size of the shifts is comparable to the mean value of the original data set, Additionally, we vary the range of the multifractal parameter q, -qmax < q < qmax Depending on the structure of a data set, qmax must be extended to higher values in order to allow a consistent and meaningful interpretation of the resulting f( a )-spectra and a useful comparison between the f(a)-spectra of different data samples,