Surveys have shown that several hundred billion weather forecasts are obtained by the United States public each year, and that weather news is one of the most consumed topics in the media. This indicates that the forecast provides information that is significant to the public, and that the public utilizes details associated with it to inform aspects of their life. Phoenix, Arizona is a dry, desert region that experiences a monsoon season and extreme heat. How then, does the weather forecast influence the way Phoenix residents make decisions? This paper aims to draw connections between the weather forecast, decision making, and people who live in a desert environment. To do this, a ten-minute survey was deployed through Amazon Mechanical Turk (MTurk) in which 379 respondents were targeted. The survey asks 45 multiple choice and ranking questions categorized into four sections: obtainment of the forecast, forecast variables of interest, informed decision making based on unique weather variables, and demographics. This research illuminates how residents in the Phoenix metropolitan area use the local weather forecast for decision-making on daily activities, and the main meteorological factors that drive those decisions.

As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).

In this thesis paper, the mental health consequences of the COVID-19 pandemic are discussed. Chapter 1 discusses what inspired me to write this thesis and follows with a discussion of social isolation during the COVID-19 pandemic. Chapter 2 takes a step back and discusses biological effects of social isolation in general. Chapter 3 discusses the psychological effects of social isolation. Finally, this thesis concludes with a discussion of what can be done to help those experiencing social isolation during the pandemic.

In my undergraduate honors thesis, I strive to convey my idea that dance is more than just movement, it’s one of the many artistic tools used to express emotions; which therefore has the power to storytell without words. It is my hope to create a captivating form of art that you not only view, but can interact and interpret.

For my creative project, I explored using natural sound to create a sound score or song. I used contrasting natural sounds to create the sound scores. Most of the sound recordings are from the New York City subways as well as other recordings around different cities in the United States. I created new sounds using sound manipulation techniques. I explored the use of electronic music production to translate the natural noise into the patterns, repetition and other elemental musical techniques to create a song. I used Ableton as the music production platform to develop the three songs.

This qualitative project was done as a way to learn more about the personal experiences of Asian American participants surrounding education and how it has impacted their identities, and questions how and if the model minority stereotype has impacted the Asian American student particiapnts. 14 participants were interviewed one-on-one to see if there were any patterns in values that their parents had pushed, and revealed that cultural expectations influence the participants’s educational choices, leading to self-regulation in regards to education. Because the shared trait of these participants are being current Asian American students in university at the time of their interviews, experiences range with how acculturated their parents are, the ethnic background of their families, and prior expectations with education.

Animal shelters are stressful environments for dogs and a plethora of research has been conducted on interventions aimed at improving the welfare of these animals. One type of intervention is social interaction, either between dogs and people or dogs and conspecifics. To investigate the types of social interaction dogs engage in and the impact of that contact on their welfare, 12 dogs were enrolled to participate in group sessions with other dogs, supervised by staff, in a shelter setting. There were three, 15-minute sessions per day across three days in which groups of two to four dogs were observed and recorded on video. These videos were then analyzed per dog for three types of interactions: dog-dog, dog-human, and dog-environment. It was found that the dogs spent significantly more time engaging with the staff members in the room than with conspecifics or the environment. Physiological measurements, including cortisol and S-IgA levels, were taken using urinary and fecal samples obtained both in the morning prior to these interaction sessions and after the final interaction of the day. No significant correlations were found between the amount of time that the dogs spent in each type of interaction and dogs’ cortisol or S-IgA levels. However, smaller statistical effects suggest that human interaction may correspond with decreased stress the day after interaction while conspecific interaction may be related to increases in stress the following day. Overall, these findings suggest that social interaction, particularly with people, may be beneficial, and should be further explored as a method to enhance the well-being of shelter dogs.

This study investigates the impact of urban form and landscaping type on the mid-afternoon microclimate in semi-arid Phoenix, Arizona. The goal is to find effective urban form and design strategies to ameliorate temperatures during the summer months. We simulated near-ground air temperatures for typical residential neighborhoods in Phoenix using the three-dimensional microclimate model ENVI-met. The model was validated using weather observations from the North Desert Village (NDV) landscape experiment, located on the Arizona State University's Polytechnic campus. The NDV is an ideal site to determine the model's input parameters, since it is a controlled environment recreating three prevailing residential landscape types in the Phoenix metropolitan area (mesic, oasis, and xeric).

After validation, we designed five neighborhoods with different urban forms that represent a realistic cross-section of typical residential neighborhoods in Phoenix. The scenarios follow the Local Climate Zone (LCZ) classification scheme after Stewart and Oke. We then combined the neighborhoods with three landscape designs and, using ENVI-met, simulated microclimate conditions for these neighborhoods for a typical summer day. Results were analyzed in terms of mid-afternoon air temperature distribution and variation, ventilation, surface temperatures, and shading. Findings show that advection is important for the distribution of within-design temperatures and that spatial differences in cooling are strongly related to solar radiation and local shading patterns. In mid-afternoon, dense urban forms can create local cool islands. Our approach suggests that the LCZ concept is useful for planning and design purposes.

The City of Phoenix (Arizona, USA) developed a Tree and Shade Master Plan and a Cool Roofs initiative to ameliorate extreme heat during the summer months in their arid city. This study investigates the impact of the City's heat mitigation strategies on daytime microclimate for a pre-monsoon summer day under current climate conditions and two climate change scenarios. We assessed the cooling effect of trees and cool roofs in a Phoenix residential neighborhood using the microclimate model ENVI-met. First, using xeric landscaping as a base, we created eight tree planting scenarios (from 0% canopy cover to 30% canopy cover) for the neighborhood to characterize the relationship between canopy cover and daytime cooling benefit of trees. In a second set of simulations, we ran ENVI-met for nine combined tree planting and landscaping scenarios (mesic, oasis, and xeric) with regular roofs and cool roofs under current climate conditions and two climate change projections. For each of the 54 scenarios, we compared average neighborhood mid-afternoon air temperatures and assessed the benefits of each heat mitigation measure under current and projected climate conditions. Findings suggest that the relationship between percent canopy cover and air temperature reduction is linear, with 0.14 °C cooling per percent increase in tree cover for the neighborhood under investigation. An increase in tree canopy cover from the current 10% to a targeted 25% resulted in an average daytime cooling benefit of up to 2.0 °C in residential neighborhoods at the local scale. Cool roofs reduced neighborhood air temperatures by 0.3 °C when implemented on residential homes. The results from this city-specific mitigation project will inform messaging campaigns aimed at engaging the city decision makers, industry, and the public in the green building and urban forestry initiatives.