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Description
In an effort to stress the benefits of the application of renewable energy to the next generation of science, technology, engineering, arts, and mathematics (STEAM) professionals, instructional modules on energy and biogas were integrated into a summer camp curriculum that challenged students to apply STEAM concepts in the design and development of chain reaction machines. Each module comprised an interactive presentations and a hands-on component where students operated a manipulative relevant to the content. During summer 2013, this camp was implemented at two high schools in Arizona and one in Trinidad and Tobago. Assessments showed that the overall modules were effective in helping students learn and retain the information presented on energy and biogas production. To improve future implementations of these modules, specifically the module on biogas production, the anaerobic digester was redesigned. In addition, a designed experiment was conducted to determine how to optimize the influent and operational environment that is available in an average high school classroom to generate maximum biogas yield. Eight plug-flow anaerobic digesters made of PVC piping and fixtures were used in a 2x3 factorial design assessing: co-digestion (20mL or 50mL) used cooking oil, temperature (25°C or 40°C), and addition of inoculum (0mL or 200mL). Biogas production was captured at two intervals over a 30-day period, and the experiments were replicated three times. Results showed that temperature at 40°C significantly increased biogas production and should be used over 25°C when using anaerobic digesters. Other factors that may potentially increase biogas production are combination of temperature at 40°C and 50mL of used cooking oil. In the future, the improvements made in the design of the anaerobic digester, and the applications of the finding from the experimental design, are expected to lead to an improved manipulative for teaching students about biogas production.
ContributorsMcCall, Shakira Renee (Author) / Dalrymple, Odesma O (Thesis advisor) / Bradley, Rogers (Committee member) / Hristovski, Kiril (Committee member) / Arizona State University (Publisher)
Created2014
Description
Arsenic (As) is a naturally occurring element that poses a health risk when continually consumed at levels exceeding the Environmental Protection Agencies (EPA) maximum contaminant level (MCL) of 10 ppb. With the Arizona Department of Water Resources considering reliance on other sources of water other than just solely surface water, groundwater proves a reliable, supplemental source. The Salt River Project (SRP) wants to effectively treat their noncompliance groundwater sources to meet EPA compliance. Rapid small-scale column tests (RSSCTs) of two SRP controlled groundwater wells along the Eastern Canal and Consolidated Canal were designed to assist SRP in selection and future design of full-scale packed bed adsorbent media. Main concerns for column choice is effectiveness, design space at groundwater wells, and simplicity. Two adsorbent media types were tested for effective treatment of As to below the MCL: a synthetic iron oxide, Bayoxide E33, and a strong base anion exchange resin, SBG-1. Both media have high affinity toward As and prove effective at treating As from these groundwater sources. Bayoxide E33 RSSCT performance indicated that As treatment lasted to near 60,000 bed volumes (BV) in both water sources and still showed As adsorption extending past this operation ranging from several months to a year. SBG-1 RSSCT performance indicated As, treatment lasted to 500 BV, with the added benefit of being regenerated. At 5%, 13%, and 25% brine regeneration concentrations, regeneration showed that 5% brine is effective, yet would complicate overall design and footprint. Bayoxide E33 was selected as the best adsorbent media for SRP use in full-scale columns at groundwater wells due to its simplistic design and high efficiency.
ContributorsLesan, Dylan (Author) / Westerhoff, Paul (Thesis advisor) / Hristovski, Kiril (Committee member) / Fraser, Matthew (Committee member) / Arizona State University (Publisher)
Created2015
Description
Nitrate contamination to groundwater and surface water is a serious problem in areas with high agricultural production due to over application of fertilizers. There is a need for alternative technologies to reduce nutrient runoff without compromising yield. Carbon nanoparticles have adsorptive properties and have shown to improve germination and yield of a variety of crops. Graphite nanoparticles (CNP) were studied under a variety of different fertilizer conditions to grow lettuce for the three seasons of summer, fall, and winter. The aim of this thesis was to quantify the effect of CNPs on nitrate leaching and lettuce growth. This was accomplished by measuring the lettuce leaf yield, formulating a nutrient balance using the leachate, plant tissue, and soil data, and changing the hydraulic conductivity of the soil to assess the effect on nutrient mobility. summer and fall experiments used Arizona soil with different amounts of nitrogen, phosphorus, and potassium (NPK) fertilizer being applied to the soil with and without CNPs. The winter experiments used three different soil blends of Arizona soil, Arizona soil blended with 30% sand, and Arizona soil blended with 70% sand with a constant fertilizer treatment of 30% NPK with and without CNPs. The results showed that the 70% NPK with CNP treatment was best at reducing the amount of nitrate leached while having little to no compromise in yield. The winter experiments showed that the effectiveness of CNPs in reducing nitrate leaching and enhancing yield, improved with the higher the hydraulic conductivity of the soil.
ContributorsPandorf, Madelyn (Author) / Westerhoff, Paul K (Thesis advisor) / Boyer, Treavor (Committee member) / Perreault, Francois (Committee member) / Arizona State University (Publisher)
Created2018
Description
Existing water quality sensors in surface, environmental, and drinking water systems are not well suited for long-term, scalable use as they require calibration, replacement of reagents, and are subject to biofouling which degrades measurement accuracy. Microbial Potentiometric Sensors (MPSs) offer an alternative approach to water quality monitoring by monitoring a biofilm-mediated potentiometric response to diverse water quality parameters. MPS biofilms grow naturally on graphite electrodes in diverse aqueous systems, are regenerative, and their potentiometric response correlates with numerous water quality parameters. As such, the overarching hypothesis of this dissertation is that MPS signal can be used to assess water quality trends and that its signal is driven by biofilm vitality. To test this hypothesis, machine learning, statistical regression, and the use of more complex, impedimetric measurement techniques were explored to characterize water quality trends in diverse water systems. This was accomplished by completing three dissertation objectives: 1.) Assess whether Machine Learning/Artificial Intelligence (ML/AI) tools can be used to disaggregate various surface water quality parameter values from Open Circuit Potential (OCP) signals produced by MPSs; 2.) Determine whether residual free chlorine concentration in drinking water could be determined by monitoring MPSs; and 3.) Determine whether OCP and/or Electrochemical Impedance Spectroscopy (EIS)-derived impedance data from an MPS can be used to determine water quality trends while confirming its biological origins. The findings confirm the hypothesis by demonstrating that ML/AI can be used to disaggregate MPS signal and determine numerous water quality parameters, offering unique opportunities for real-time monitoring of aqueous environments. Additionally, MPSs are particularly useful in measuring free chlorine concentrations in drinking water distribution systems which offers opportunities for scalable, in-situ, continuous monitoring of chlorine throughout a distribution network. Finally, the findings demonstrate that coupling MPSs’ OCP signal with more advanced measurement techniques such as EIS can improve understanding of drinking water quality trends, however current open source, affordable technologies capable of conducting EIS are prone to high measurement noise and are not currently accurate enough to be used in drinking water systems.
ContributorsSaboe, Daniel (Author) / Hristovski, Kiril (Thesis advisor) / Olson, Larry (Committee member) / Perreault, Francois (Committee member) / Arizona State University (Publisher)
Created2022