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Exoplanetary research is a key component in the search for life outside of Earth and the Solar System. It provides people with a sense of wonder about their role in the evolution of the Universe and helps scientists understand life's potential throughout a seemingly infinite number of unique exoplanetary environments.

Exoplanetary research is a key component in the search for life outside of Earth and the Solar System. It provides people with a sense of wonder about their role in the evolution of the Universe and helps scientists understand life's potential throughout a seemingly infinite number of unique exoplanetary environments. The purpose of this research project is to identify the most plausible biosignature gases that would indicate life's existence in the context of hyperarid exoplanetary atmospheres. This analysis first defines hyperarid environments based on known analogues for Earth and Mars and discusses the methods that researchers use to determine whether or not an exoplanet is hyperarid. It then identifies the most relevant biosignatures to focus on based on the scientific literature on analogous hyperarid environments and ranks them in order from greatest to least biological plausibility within extreme hyperarid conditions. The research found that methane (CH4) and nitrous oxide (N2O) are the most helpful biosignature gases for these particular exoplanetary scenarios based on reviews of the literature. The research also found that oxygen (O2), hydrogen sulfide (H2S) and ammonia (NH3) are the biosignatures with the least likely biological origin and the highest likelihood of false positive detection. This analysis also found that carbon dioxide (CO2) is a useful companion biosignature within these environments when paired with either CH4 or the pairing of hydrogen (H2) and carbon monoxide (CO). This information will provide a useful road map for dealing with the detection of biosignatures within hyperarid exoplanetary atmospheres during future astrobiology research missions.
ContributorsBrown, Kyle William (Author) / Cadillo-Quiroz, Hinsby (Thesis director) / Finn, Damien (Committee member) / Hartnett, Hilairy (Committee member) / School of International Letters and Cultures (Contributor) / School of Earth and Space Exploration (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
With the ability to observe the atmospheres of terrestrial exoplanets via transit spectroscopy on the near-term horizon, the possibility of atmospheric biosignatures has received considerable attention in astrobiology. While traditionally exoplanet scientists looking for life focused on biologically relevant trace gases such as O2 and CH4, this approach has raised

With the ability to observe the atmospheres of terrestrial exoplanets via transit spectroscopy on the near-term horizon, the possibility of atmospheric biosignatures has received considerable attention in astrobiology. While traditionally exoplanet scientists looking for life focused on biologically relevant trace gases such as O2 and CH4, this approach has raised the spectre of false positives. Therefore, to address these shortcomings, a new set of methods is required to provide higher confidence in life detection. One possible approach is measuring the topology of atmospheric chemical reaction networks (CRNs). To investigate and assess this approach, the ability of network-theoretic metrics to distinguish the distance from thermochemical equilibrium in the atmosphere of hot jupiters was tested. After modeling the atmospheres of hot jupiters over a range of initial conditions using the VULCAN modeling package, atmospheric CRNs were constructed from the converged models and their topology measured using the Python package NetworkX. I found that network metrics were able to predict the distance from thermochemical equilibrium better than atmospheric species abundances alone. Building on this success, I modeled 30,000 terrestrial worlds. These models divided into two categories: Anoxic Archean Earth-like planets that varied in terms of CH4 surface flux (modeled as either biotic or abiotic in origin), and modern Earth-like planets with and without a surface flux of CCl2F2 (to represent the presence of industrial civilizations). I constructed atmospheric CRNs from the converged models, and analyzed their topology. I found that network metrics could distinguish between atmospheres with and without the presence of life or technology. In particular, mean degree and average shortest path length consistently performed better at distinguishing between abiotic and biotic Archean-like atmospheres than CH4 abundance.
ContributorsFisher, Theresa Mason (Author) / Walker, Sara I (Thesis advisor) / Hartnett, Hilairy (Committee member) / Line, Michael (Committee member) / Shkolnik, Evgenya (Committee member) / Okie, Jordan (Committee member) / Arizona State University (Publisher)
Created2023