SILICATE MIXTURES UNDER SIMULATED LUNAR ENVIRONMENT

Remote sensing is a primary source of information about planetary surfaces, thus it is imperative that we are able to quantitatively interpret remote spectral data. Because remote sensing relies in part on comparison to laboratory data, we must also understand how environmental conditions affect spectral features, and impact our interpretation of remote sensing data. Differences in environmental conditions become especially important when comparing laboratory data measured on Earth to remote sensing data from airless bodies, such as the Moon and asteroids. Without an atmosphere, these planetary surfaces experience extreme temperature gradients within the upper 100s of microns of regolith.

These temperature gradients result in the measurement of regolith at multiple temperatures with each observation, which complicates the analysis of mid-infrared spectral data. To have comparable laboratory data, we must measure minerals and regolith analogues under environmental conditions similar to those of the target bodies. Here, we describe measurements of minerals and mixtures of minerals under a simulated lunar environment achieved in the Planetary and Asteroid Regolith Spectroscopy Environmental Chamber (PARSEC) at Stony Brook University. PARSEC simulates environmental conditions like those on the surface of the Moon, so that we may examine their effects on regolith spectra. These effects largely consist of shifts in the Christiansen Feature (CF) and increases in the depths of Reststrahlen bands. Our work shows that the CF shifts both under the simulated lunar environment, and due to particle size fraction of the sample. We must have laboratory data which reflect these changes to properly interpret mid-infrared data from the Moon and other airless bodies.

This work contributes to our interpretation of spectra of mineral mixtures. The dominance of fine particulates on the lunar surface prevents the typical treatment of mid-infrared spectra as a linear combination of the mineral constituents. Applying this work to Diviner Lunar Radiometer data will help us begin to quantify mineral assemblages within the data.