DIX Planetary Science Seminar

"Thermophysical modeling of (15) Eunomia with ALMA data"

We have obtained 1.3 mm thermal emission data from the Atacama Large Millimeter/submillimeter Array (ALMA) for (15) Eunomia, the largest S-type asteroid of diameter 270 km. Unlike thermal infrared observations with ground-based telescopes, ALMA can spatially resolve Eunomia at ~30 km at millimeter wavelengths. This allows us to study the spatial variations in lithology across the surface of Eunomia, which is thought to be partially differentiated based on its hemispherical compositional heterogeneity as determined by astronomical observations. We fit a thermophysical model to the ALMA thermal emission data to determine the thermal inertia and the dielectric constant; the latter is an indicator of surface composition, in particular surface metal content, on asteroids. The thermophysical model we have used is based on Delbo et al. (2015), and adapted to take into account the spatially resolved thermal emission data including emission from the subsurface, which is sensed at millimeter wavelengths.

"From spectra to mineralogy: a remote sensing approach to Earth's desert dust sources"

As Earth's climate changes, our need to understand the complex processes controlling climate and Earth's biogeochemical cycles increases. Major Earth systems models consider the role of atmospheric mineral dust, which is known to have a net radiative forcing effect in the atmosphere, influence cloud formation, and alter ocean biogeochemistry, among other roles. However, the nature and extent of mineral dust aerosols' impacts on climate cycles depends on its mineralogy and grain size and is currently unclear, including whether dust has a warming or cooling effect and how it influences cloud formation. The Earth Surface Mineral Dust Source Investigation (EMIT) is collecting visible/near infrared (VNIR) spectral data of dust source region land areas to inform how emitted dust mineralogy affects the climate system. Here, we examine the spectral variability of desert dust source regions as observed by EMIT. We develop improved methods to derive mineralogy quantitatively from VNIR spectra. We develop a dataset of representative desert dust source sediments with VNIR spectra, XRD-derived mineralogy, iron chemistry data, and particle size distribution. Qualitative analyses, spectral parameterization, and statistical techniques were applied to the dataset to understand mineral sources of variability in arid soils' VNIR spectra and relate these to lab-determined mineralogy.