The Lunar Atmosphere and Dust Environment Explorer (LADEE) hosted a Neutral Mass Spectrometer (NMS) that analyzed variations of molecular species in the lunar exosphere due to the time of day. The NMS data expressed the amount of a species as count/sec readings. Here, we report on our efforts to carry out the first analyses of NMS data of molecular hydrogen. H₂ is produced in the lunar environment by solar wind implantation (Tucker et al., 2021) and impact vaporization from meteorite bombardment (Hurley et al., 2016). These findings will help analyze the variation of H₂ in the exosphere as a function of the lunar phase to gain a higher understanding of the lunar hydrogen cycle. The Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter reported averaged measurements of H₂ of 1,000 ± 500 and 1,400 ± 500 cm−3 in the morning and evening, respectively (Cook et al., 2013). The Chandrayaan-I Altitudinal Composition Explorer reported an H₂ density of 500 – 800 cm−3 on the lunar dayside during the full Moon phase (Thampi et al., 2015). These measurements suggest that solar wind protons are a primary source of H₂ in the exosphere (Crandall et al., 2019; Tucker et al. 2019). LADEE operated for about 7 months obtaining information about the exosphere, e.g., day vs. night differences, altitude variations, and variations while in the magnetotail. The NMS instrument measured upper atmospheric gas samples like H₂ using a closed ion source. This project reviews all closed source raw data for channels that sampled the mass 2 Da peak from the LADEE mission via the NASA Planetary Data System (PDS). A custom program has been developed in Python to convert LADEE counts/sec of mass channels 1.8 – 2.2 Da into units of number density. In this presentation, we will discuss the conversion of LADEE H₂ counts/sec to number density. We will compare the variations in the measurements with solar flux and the lunar phase. Future work will include comparisons to Monte Carlo models of the solar wind (Tucker et al., 2021) and impact vaporization (Hurley et al., 2016). Such model-data studies would allow the partitioning of both the source and respective inventories of water products to obtain greater insight into the lunar water cycle.
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