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The multi log-normal distribution function is widely in use to parameterize the aerosol particle size distributions. The main purpose of such a parameterization is to quantitatively describe size distributions and to allow straightforward comparisons between different aerosol particle data sets. In this study, we developed and evaluated an algorithm to parameterize aerosol particle number size distributions with the multi log-normal distribution function. The current algorithm is automatic and does not need a user decision for the initial input parameters; it requires only the maximum number of possible modes and then it reduces this number, if possible, without affecting the fitting quality. The reduction of the number of modes is based on an overlapping test between adjacent modes. The algorithm was evaluated against a previous algorithm that can be considered as a standard procedure. It was also evaluated against a long-term data set and different types of measured aerosol particle size distributions in the ambient atmosphere. The evaluation of the current algorithm showed the following advantages: (1) it is suitable for different types of aerosol particles observed in different environments and conditions, (2) it showed agreement with the previous standard algorithm in about 90% of long-term data set, (3) it is not time-consuming, particularly when long-term data sets are analyzed, and (4) it is a useful tool in the studies of atmospheric aerosol particle formation and transformation.
Hussein et al. (Thu,) studied this question.