High-Resolution Spectroscopic Observations of Potassium Emissions in the Lunar Exosphere

We investigate lunar exospheric potassium D1 emissions (7698.9646 Å) using high-resolution (R = 180,000 or 1.7 km/s) spectroscopy with our dual-etalon Fabry-Perot instrument to measure line widths and radial velocities. The Field of View (FOV) is 2 arcmins (~224 km at the mean lunar distance of 384,400 km) positioned tangent to the sunlit limb. The FOV placements are at cardinal directions from a variety of reference craters. All observations are collected at the National Solar Observatory McMath-Pierce Telescope in Kitt Peak, Arizona. The data are from several observations from 2014 through 2017 at various times of the year. Results are produced via a newly created automated data reduction using Python. Python was chosen as an open-source alternative to the previously used IDL and MATLAB scripts to decrease the cost of software licenses and maintenance. The potassium spectral line profiles provide a direct method to track exospheric effective temperatures and velocities. By monitoring the state of the potassium emissions over different lunar phases, solar activity, and the influx of meteor streams, we can constrain physical processes of sources and sinks at the lunar surface. Mechanisms that create the exosphere include photon-stimulated desorption, thermal evaporation, meteoroid impact vaporization, and ion sputtering via solar wind. In contrast, the exosphere is diminished due to the low lunar escape velocity, solar radiation pressure, and neutral gas being ionized and swept away by the interplanetary and terrestrial magnetic field. Preliminary analysis of 2017 data (January through June, excluding February) indicates an average potassium temperature of 1140 K but varying over the range of 550 K to 2000 K. Preliminary results from 2014 data depict a similar range of temperatures to that of 2017. Further analysis is expected for additional data from 2014 to later observations in 2017 that were not included in the initial set of models.