This study aims to examine the relationship between urban densification and pedestrian thermal comfort at different times of the year, and to understand how this can impact patterns of activity in downtown areas. The focus of the research is on plazas in the urban core of downtown Tempe, given their importance to the pedestrian landscape. With that in mind, the research question for the study is: how does the microclimate of a densifying urban core affect thermal comfort in plazas at different times of the year? Based on the data, I argue that plazas in downtown Tempe are not maximally predisposed to pedestrian thermal comfort in the summer or the fall. Thus, the proposed intervention to improve thermal comfort in downtown Tempe’s plazas is the implementation of decision support tools focused on education, community engagement, and thoughtful building designs for heat safety.
The combined use of methamphetamine and opioids has been reported to be on the rise throughout the United States (U.S.). However, our knowledge of this phenomenon is largely based upon reported overdoses and overdose-related deaths, law enforcement seizures, and drug treatment records; data that are often slow, restricted, and only track a portion of the population participating in drug consumption activities. As an alternative, wastewater-based epidemiology (WBE) has the capability to track licit and illicit drug trends within an entire community, at a low cost and in near real-time, while providing anonymity to those contributing to the sewer shed. In this study, wastewater was collected from two Midwestern U.S. cities (2017-2019) and analyzed for the prevalence of methamphetamine and the opioids oxycodone, codeine, fentanyl, tramadol, hydrocodone, and hydromorphone. Monthly 24-hour time-weighted composite samples (n = 48) from each city were analyzed using isotope dilution liquid chromatography tandem mass spectrometry. Results showed that methamphetamine and total opioid consumption (milligram morphine equivalents) in City 1 were strongly correlated only in 2017 (Spearman rank order correlation coefficient, ρ = 0.78), the relationship driven by fentanyl, hydrocodone, and hydromorphone. For City 2, methamphetamine and total opioid consumption were strongly positively correlated during the entire study (ρ = 0.54), with the correlations driven by hydrocodone and hydromorphone. In both cities, hydrocodone and hydromorphone mass loads were highly correlated, suggesting a parent and metabolite relationship. WBE provides important insights into licit and illicit drug consumption patterns in near real-time as they evolve; important information for community stakeholders in municipalities across the U.S.
GitHub Repository: https://github.com/komal-agrawal/AD_GIS.git
Arizona is a unique state in that rain is not a normal occurrence throughout most of the year (NWS). Arizona averages from less than three months to half a month of measurable precipitation days per year (WRCC). With that, it is important to know the public’s understanding as well as their general trend of likeness towards the weather forecasts they receive. A questionnaire was distributed to 426 people in the state of Arizona to review what they understand from the forecasts and what they would like to see on social media and television.
Many people use public transportation in their daily lives, which is often praised at as a healthy and sustainable choice to make. However, in extreme temperatures this also puts people at a greater risk for negative consequences resulting from such exposure to heat. In Phoenix, public transportation riders are faced with extreme heat in the summer along with the increased internal heat production caused by the physical activity required to use public transportation. In this study, I estimated total exposure and average exposure per rider for six stops in Phoenix. To do this I used City of Phoenix ridership data, weather data, and survey responses from an ASU City of Phoenix Bus Stop Survey conducted in summer 2016. These data sets were combined by multiplying different metrics to produce various exposure values. During analysis two sets of calculations were made. One keeping weather constant and another keeping ridership constant. I found that there was a large range of exposure between the selected stops and that the thermal environment influences the amount of exposure depending on the time of day the exposure is occurring. During the morning a greener location leads to less exposure, while in the afternoon an urban location leads to less exposure. Know detailed information about exposure at these stops I was also able to evaluate survey participants' thermal comfort at each stop and how it may relate to exposure. These findings are useful in making educated transportation planning decisions and improving the quality of life for people living in places with extreme summer temperatures.