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Atmospheric flows exhibit self-similar fractal space-time fluctuations on allspace-time scales in association with inverse power law distribution for powerspectra of meteorological parameters such as wind, temperature, etc., and thusimplies long-range correlations, identified as self-organized criticalitygeneric to dynamical systems in nature. A general systems theory based onclassical statistical physical concepts developed by the author visualizes thefractal fluctuations to result from the coexistence of eddy fluctuations in aneddy continuum, the larger scale eddies being the integrated mean of enclosedsmaller scale eddies. The model satisfies the maximum entropy principle andpredicts that the probability distributions of component eddy amplitudes andthe corresponding variances (power spectra) are quantified by the sameuniversal inverse power law distribution which is a function of the goldenmean. Atmospheric particulates are held in suspension by the vertical velocitydistribution (spectrum). The atmospheric particulate size spectrum is derivedin terms of the model predicted universal inverse power law characterizingatmospheric eddy spectrum. Model predicted spectrum is in agreement with thefollowing four experimentally determined data sets: (i) CIRPAS missionTARFOX_WALLOPS_SMPS aerosol size distributions (ii) CIRPAS mission ARM-IOP(Ponca City, OK) aerosol size distributions (iii) SAFARI 2000 CV-580 (CARGAerosol and Cloud Data) cloud drop size distributions and (iv) TWP-ICE (Darwin,Australia) rain drop size distributions.

Universal Spectrum for Atmospheric Suspended Particulates: Comparison with Observations