Description of Atmospheric Aerosol Dynamics Using an Inverse Gaussian Distributed Method of Moments

Abstract

Abstract For nearly 60 years, the lognormal distribution has been the most widely used function in the field of atmospheric science for characterizing atmospheric aerosol size distribution. We verify whether the three-parameter inverse Gaussian distribution (IGD) is a more suitable function than the lognormal distribution for characterizing aerosol size distribution. An attractive feature of IGD is that with it a new method of moments (MOM) can be established for resolving atmospheric aerosol dynamics which is described by a kinetic aerosol dynamics equation, i.e., inverse Gaussian distributed MOM (IGDMOM). The advantage of IGDMOM is that all of its moments can be analytically calculated using a closure moment function inherited from IGD. The precision and efficiency of IGDMOM are verified by comparing it with other recognizable methods in test cases of four representative atmospheric aerosol dynamics. Several key statistical quantities determining aerosol size distributions, including kth moments (k = 0, 1/3, 2/3, and 2), geometric standard deviation, skewness, and kurtosis, are evaluated. IGDMOM has higher precision than the lognormal MOM with nearly identical efficiency. The article provides a novel alternative to atmospheric scientists for solving kinetic aerosol dynamics equations.