Calculating the Scattering Properties of Fine Particulates on Planetary Surfaces

Abstract:

Infrared radiation is used to remotely determine the mineralogical composition of planetary surfaces. However, determining the compositions of fine particulates has been a problematic task. This is due to an increased difficulty in determining the scattering properties for multiple scattering of light that occurs when regolith particles have diameters on the order of the wavelength of incident light. Radiative transfer models have been used to calculate the emissivity of closely-packed, fine particles with some success, but these models are not accurate enough. In particular, Mie theory has been used to obtain the necessary parameters for radiative transfer models in hope of capturing the diffraction effects. Although these methods have been adjusted to account for closely-packed particles, the physics of radiative transfer and Mie theory only holds for truly well-separated particles. Considering this, our study takes a different approach, Multiple Sphere T-Matrix (MSTM) method, to capture the multiple scattering process. For a cluster composed of many particles, MSTM solves Maxwell’s equations at every light and particle interface. Then, the cluster-averaged scattering properties of a single volume are input into equations of emissivity in Hapke [1996]. We generated a cluster of closely-packed spheres of forsterite composition with different diameters. Emissivities were calculated using MSTM/Hapke approach, then its quality was compared to that of Mie method. Furthermore, emissivity measurements were taken in a laboratory. Emission spectra derived from MSTM method resembled those from laboratory measurements closer than Mie method. This is an indication that MSTM method is capturing the multiple scattering process that increasingly becomes complex for particles with diameters on the order of the wavelength of incident radiation. MSTM method was shown to be more effective than Mie method, but not perfect; our next steps are to explore the effects of particle packing density, cluster size, particle size distribution, compositional heterogeneity, and particle shape to improve its accuracy. Our improved modeling capability will aid in analyzing remote sensed data in the infrared and determining the correct compositions of planetary surfaces covered with fine regolith particulates.