In the past the composition of the lunar atmosphere has been studied by many experiments, most notably by the Lunar Atmosphere Composition Experiment (LACE) deployed during the Apollo 17 mission, the Lyman-Alpha Mapping Project (LAMP) aboard the Lunar Reconnaissance Orbiter, and the Lunar Atmosphere and Dust Environment Explorer (LADEE). Nowadays, investigations of our Moon's atmosphere is mostly based on numerical models, with Monte-Carlo simulations being the preferred method due to the assumption of a thin, surface-bounded exosphere. These kinds of atmospheres assume no interactions between any two of its particles, allowing to track the constituents from their source until their eventual loss without any interferences and, thus, high numerical efficiency.
While several models of the lunar exosphere already exist for single species, a comprehensive model being able to simulate multiple different species and predict their global surface number density distribution has not yet been produced. A new numerical model based on the Monte-Carlo method and able to simulate noble gases, other single atom constituents, as well as molecules, is presented in this work. The current state of the model incorporates a "pseudo" two-dimensional approach, where the selenocentric longitude and the Moon's local time are equal. Due to the link between a spacial and a time dimension, no topological resolution of the lunar surface is possible, thus the Moon is assumed to be a perfect sphere. For numerical efficiency, the current state of the model does not feature a height dimension and the particle's path is only described analytically, with their landing position being calculated directly. These calculations are based on neutral elements which are only influenced by gravity and coriolis forces.
Surface number densities of the noble gases helium, neon, argon, krypton, and xenon, and of other gases including atomic and molecular hydrogen, methane, hydroxyl, and water have been studied. Besides the global distribution of the above mentioned species' surface number density, this work also compared the results with expected densities on the lunar surface, investigates the recycling process, and also looks at inter-species connections influencing the results. The work also includes references to present proposals listing expected surface number densities and evaluates their assumptions based on the presented new numerical model predictions. Lastly, a numerical analysis of the underlying grid of the lunar surface is also included. The model incorporates the physical mechanisms of a Sun-side source rate for solar wind related particles, a global source rate for endogenic species, photo-dissociation, thermal escape, ion recycling, and cold-trapping. The main conclusions drawn in this study are that the new model can reproduce all density predictions made by other numerical models found in the literature, that it can be fitted to measurement data and used to infer unknown parameters based on expected surface number densities, and, finally that inter-species connections can significantly influence the predictions.
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In the past the composition of the lunar atmosphere has been studied by many experiments, most notably by the Lunar Atmosphere Composition Experiment (LACE) deployed during the Apollo 17 mission, the Lyman-Alpha Mapping Project (LAMP) aboard the Lunar Reconnaissance Orbiter, and the Lunar Atmosphere and Dust Environment Explorer (LADEE). Nowadays, investigations of our Moon's atmosphere is mostly based on numerical models, with Monte-Carlo simulations being the preferred method due to the assump...
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