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- Status: Published
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).
Much of Nepal lacks access to clean drinking water, and many water sources are contaminated with arsenic at concentrations above both World Health Organization and local Nepalese guidelines. While many water treatment technologies exist, it is necessary to identify those that are easily implementable in developing areas. One simple treatment that has gained popularity is biochar—a porous, carbon-based substance produced through pyrolysis of biomass in an oxygen-free environment. Arizona State University’s Engineering Projects in Community Service (EPICS) has partnered with communities in Nepal in an attempt to increase biochar production in the area, as it has several valuable applications including water treatment. Biochar’s arsenic adsorption capability will be investigated in this project with the goal of using the biochar that Nepalese communities produce to remove water contaminants. It has been found in scientific literature that biochar is effective in removing heavy metal contaminants from water with the addition of iron through surface activation. Thus, the specific goal of this research was to compare the arsenic adsorption disparity between raw biochar and iron-impregnated biochar. It was hypothesized that after numerous bed volumes pass through a water treatment column, iron from the source water will accumulate on the surface of raw biochar, mimicking the intentionally iron-impregnated biochar and further increasing contaminant uptake. It is thus an additional goal of this project to compare biochar loaded with iron through an iron-spiked water column and biochar impregnated with iron through surface oxidation. For this investigation, the biochar was crushed and sieved to a size between 90 and 100 micrometers. Two samples were prepared: raw biochar and oxidized biochar. The oxidized biochar was impregnated with iron through surface oxidation with potassium permanganate and iron loading. Then, X-ray fluorescence was used to compare the composition of the oxidized biochar with its raw counterpart, indicating approximately 0.5% iron in the raw and 1% iron in the oxidized biochar. The biochar samples were then added to batches of arsenic-spiked water at iron to arsenic concentration ratios of 20 mg/L:1 mg/L and 50 mg/L:1 mg/L to determine adsorption efficiency. Inductively coupled plasma mass spectrometry (ICP-MS) analysis indicated an 86% removal of arsenic using a 50:1 ratio of iron to arsenic (1.25 g biochar required in 40 mL solution), and 75% removal with a 20:1 ratio (0.5 g biochar required in 40 mL solution). Additional samples were then inserted into a column process apparatus for further adsorption analysis. Again, ICP-MS analysis was performed and the results showed that while both raw and treated biochars were capable of adsorbing arsenic, they were exhausted after less than 70 bed volumes (234 mL), with raw biochar lasting 60 bed volumes (201 mL) and oxidized about 70 bed volumes (234 mL). Further research should be conducted to investigate more affordable and less laboratory-intensive processes to prepare biochar for water treatment.
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.
Is there a mismatch between urban farmers’ perceptions of their farm’s environmental sustainability and its actual environmental impact? Focusing on the use of water and nutrients on each farm as described by the farmers through interviews, it is evident that there is some level of disconnect between ideals and practices. This project may aid in bridging the gap between the two in regard to the farmers’ sustainability goals. This project will move forward by continuing interviews with farmers as well as collecting soil and water from the farms in order to more accurately quantify the sustainability of the farms’ practices. This project demonstrates that there is some degree of misalignment between perception and reality. Two farms claimed they were sustainable when their practices did not reflect that, while 2 farms said they were not sure if they were sustainable when their practices indicated otherwise. Samples from two farms showed high concentrations of nutrients and salts, supporting the idea that there may be a mismatch between perceived and actual sustainability.
An analysis of university flight emissions, carbon neutrality goals, and the global impact of university sanctioned flight.