A general solution for data processing of large numbers of micrometer- or submicrometer-particle mass spectra in aerosol analysis is described. The method is based on immediate evaluation of bipolar laser desorption ionization mass spectra acquired in an on-line (impact free) time-of-flight instrument. The goal of the procedure is a characterization of the particle population under investigation in terms of chemical composition of particle classes, particle distributions, size distributions, and time courses, rather than an investigation of each individual particle. After automatic peak analysis of each newly acquired bipolar mass spectrum, the mass spectral information is statistically evaluated by a fuzzy clustering algorithm, providing for an immediate attribution of the particle to predefined particle classes. The particle distributions over these classes can be monitored as a function of time and particle size range. Definition of the particle classes as used for on-line evaluation is performed in an earlier step, either by manual approach, or by selection from a particle class database, or, as in most cases, by fuzzy clustering of a set of particle mass spectra from the population (the aerosol) under investigation. Definition of the particle classes is depending only on the distinguishability of the spectra patterns of different particles. It is not necessary for the clustering approach to fully "understand" the mass spectra. The range of possible applications of the method is therefore very broad. Particles dominated by inorganic components, as typically observed in aerosol chemistry for example, can be investigated the same way as organic particles (e.g., from smoke or automobile exhaust) or even biological particles such as bacteria, yeast, or pollen. The data processing method has been successfully applied in several fields of stationary applications and will be employed in mobile instruments for large scale field studies in atmospheric chemistry, engine combustion research, and the characterization of house dust. (C) 1999 American Society for Mass Spectrometry.