In an effort to address the lack of literature in on-campus active travel, this study aims to investigate the following primary questions:<br/>• What are the modes that students use to travel on campus?<br/>• What are the motivations that underlie the mode choice of students on campus?<br/>My first stage of research involved a series of qualitative investigations. I held one-on-one virtual interviews with students in which I asked them questions about the mode they use and why they feel that their chosen mode works best for them. These interviews served two functions. First, they provided me with insight into the various motivations underlying student mode choice. Second, they provided me with an indication of what explanatory variables should be included in a model of mode choice on campus.<br/>The first half of the research project informed a quantitative survey that was released via the Honors Digest to attract student respondents. Data was gathered on travel behavior as well as relevant explanatory variables.<br/>My analysis involved developing a logit model to predict student mode choice on campus and presenting the model estimation in conjunction with a discussion of student travel motivations based on the qualitative interviews. I use this information to make a recommendation on how campus infrastructure could be modified to better support the needs of the student population.

Papago Park in Tempe, Arizona (USA) is host to several buttes composed of landslide breccias. The focus of this thesis is a butte called “Contact Hill,” which is composed of metarhyolitic debris flows, granitic debris flows, and Barnes Butte Breccia. The Barnes Butte Breccia can be broken down into several different compositional categories that can be dated based on their relative ages. The depositional timeline of these rocks is explored through their mineral and physical properties. The rhyolitic debris flow is massively bedded and dips at 26° to the southeast. The granitic debris flow is not bedded and exhibits a mixture of granite clasts of different grain sizes. In thin section analysis, five mineral types were identified: opaque inclusions, white quartz, anhedral and subhedral biotite, yellow stained K-feldspar, and gray plagioclase. It is hypothesized that regional stretching and compression of the crust, accompanied with magmatism, helped bring the metarhyolite and granite to the surface. Domino-like fault blocks caused large brecciation, and collapse of a nearby quartzite and granite mountain helped create the Barnes Butte Breccia: a combination of quartzite, metarhyolite, and granite clasts. Evidence of Papago Park’s ancient terrestrial history is seen in metarhyolite clasts containing sand grains. These geologic events, in addition to erosion, are responsible for Papago Park’s unique appearance today.

Stardust grains can provide useful information about the Solar System environment before the Sun was born. Stardust grains show distinct isotopic compositions that indicate their origins, like the atmospheres of red giant stars, asymptotic giant branch stars, and supernovae (e.g., Bose et al. 2010). It has been argued that some stardust grains likely condensed in classical nova outbursts (e.g., Amari et al. 2001). These nova candidate grains contain 13C, 15N and 17O-rich nuclides which are produced by proton burning. However, these nuclides alone cannot constrain the stellar source of nova candidate grains. Nova ejecta is rich in 7Be that decays to 7Li (which has a half-life of ~53 days). I want to measure 6,7Li isotopes in nova candidate grains using the NanoSIMS 50L (nanoscale secondary ion mass spectrometry) to establish their nova origins without ambiguity. Several stardust grains that are nova candidate grains were identified in meteorite Acfer 094 on the basis of their oxygen isotopes. The identified silicate and oxide stardust grains are <500 nm in size and exist in the meteorite surrounded by meteoritic silicates. Therefore, 6,7Li isotopic measurements on these grains are hindered because of the large 300-500 nm oxygen ion beam in the NanoSIMS. I devised a methodology to isolate stardust grains by performing Focused Ion Beam milling with the FIB – Nova 200 NanoLab (FEI) instrument. We proved that the current FIB instrument cannot be used to prepare stardust grains smaller than 1 𝜇m due to lacking capabilities of the FIB. For future analyses, we could either use the same milling technique with the new and improved FIB – Helios 5 UX or use the recently constructed duoplasmatron on the NanoSIMS that can achieve a size of ~75 nm oxygen ion beam.

In this study, the influence of fluid mixing on temperature and geochemistry of hot spring fluids is investigated. Yellowstone National Park (YNP) is home to a diverse range of hot springs with varying temperature and chemistry. The mixing zone of interest in this paper, located in Geyser Creek, YNP, has been a point of interest since at least the 1960’s (Raymahashay, 1968). Two springs, one basic (~pH 7) and one acidic (~pH 3) mix together down an outflow channel. There are visual bands of different photosynthetic pigments which suggests the creation of temperature and chemical gradients due to the fluids mixing. In this study, to determine if fluid mixing is driving these changes of temperature and chemistry in the system, a model that factors in evaporation and cooling was developed and compared to measured temperature and chemical data collected downstream. Comparison of the modeled temperature and chemistry to the measured values at the downstream mixture shows that many of the ions, such as Cl⁻, F⁻, and Li⁺, behave conservatively with respect to mixing. This indicates that the influence of mixing accounts for a large proportion of variation in the chemical composition of the system. However, there are some chemical constituents like CH₄, H₂, and NO₃⁻, that were not conserved, and the concentrations were either depleted or increased in the downstream mixture. Some of these constituents are known to be used by microorganisms. The development of this mixing model can be used as a tool for predicting biological activity as well as building the framework for future geochemical and computational models that can be used to understand the energy availability and the microbial communities that are present.