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- All Subjects: Water resources management
- Creators: Mascaro, Giuseppe
- Resource Type: Text
Description
This dissertation focuses on the application of urban metabolism metrology (UMM) to process streams of the natural and built water environment to gauge public health concerning exposure to carcinogenic N-nitrosamines and abuse of narcotics. A survey of sources of exposure to N-nitrosamines in the U.S. population identified contaminated food products (1,900 ± 380 ng/day) as important drivers of attributable cancer risk (Chapter 2). Freshwater sediments in the proximity of U.S. municipal wastewater treatment plants were shown for the first time to harbor carcinogenic N-nitrosamine congeners, including N-nitrosodibutylamine (0.2-3.3 ng/g dw), N-nitrosodiphenylamine (0.2-4.7 ng/g dw), and N-nitrosopyrrolidine (3.4-19.6 ng/g dw) were, with treated wastewater discharge representing one potential factor contributing to the observed contamination (p=0.42) (Chapter 3). Opioid abuse rates in two small midwestern communities were estimated through the application of wastewater-based epidemiology (WBE). Average concentrations of opioids (City 1; City 2) were highest for morphine (713 ± 38, 306 ± 29 ng/L) and varied by for the remainder of the screened analytes. Furthermore, concentrations of the powerful opioid fentanyl (1.7 ± 0.2, 1.0 ± 0.5 ng/L) in wastewater were reported for the first time in the literature for the U.S. (Chapter 4). To gauge narcotic consumption within college-aged adults the WBE process used in Chapter 4 was applied to wastewater collected from a large university in the Southwestern U.S. Estimated narcotics consumption, in units of mg/day/1,000 persons showed the following rank order: cocaine (470 ± 42), heroin (474 ± 32), amphetamine (302 ± 14) and methylphenidate (236 ± 28). Most parental drugs and their respective metabolites showed detection frequencies in campus wastewater of 80% or more, with the notable exception of fentanyl, norfentanyl, buprenorphine, and norbuprenorphine. Estimated consumption of all narcotics, aside from attention-deficit/hyperactivity disorder medication, were higher than values reported in previous U.S. WBE studies for U.S. campuses (Chapter 5). The analyses presented here have identified variation in narcotic consumption habits across different U.S. communities, which can be gauged through UMM. Application of these techniques should be implemented throughout U.S. communities to provide insight into ongoing substance abuse and health issues within a community.
ContributorsGushgari, Adam Jon (Author) / Halden, Rolf U. (Thesis advisor) / Kavazanjian, Edward (Committee member) / Fraser, Matthew (Committee member) / Venkatesan, Arjun (Committee member) / Mascaro, Giuseppe (Committee member) / Arizona State University (Publisher)
Created2018
Description
In the recent past, Iraq was considered relatively rich considering its water resources compared to its surroundings. Currently, the magnitude of water resource shortages in Iraq represents an important factor in the stability of the country and in protecting sustained economic development. The need for a practical, applicable, and sustainable river basin management for the Tigris and Euphrates Rivers in Iraq is essential. Applicable water resources allocation scenarios are important to minimize the potential future water crises in connection with water quality and quantity. The allocation of the available fresh water resources in addition to reclaimed water to different users in a sustainable manner is of the urgent necessities to maintain good water quantity and quality.
In this dissertation, predictive water allocation optimization models were developed which can be used to easily identify good alternatives for water management that can then be discussed, debated, adjusted, and simulated in greater detail. This study provides guidance for decision makers in Iraq for potential future conditions, where water supplies are reduced, and demonstrates how it is feasible to adopt an efficient water allocation strategy with flexibility in providing equitable water resource allocation considering alternative resource. Using reclaimed water will help in reducing the potential negative environmental impacts of treated or/and partially treated wastewater discharges while increasing the potential uses of reclaimed water for agriculture and other applications. Using reclaimed water for irrigation is logical and efficient to enhance the economy of farmers and the environment while providing a diversity of crops, especially since most of Iraq’s built or under construction wastewater treatment plants are located in or adjacent to agricultural lands. Adopting an optimization modelling approach can assist decision makers, ensuring their decisions will benefit the economy by incorporating global experiences to control water allocations in Iraq especially considering diminished water supplies.
In this dissertation, predictive water allocation optimization models were developed which can be used to easily identify good alternatives for water management that can then be discussed, debated, adjusted, and simulated in greater detail. This study provides guidance for decision makers in Iraq for potential future conditions, where water supplies are reduced, and demonstrates how it is feasible to adopt an efficient water allocation strategy with flexibility in providing equitable water resource allocation considering alternative resource. Using reclaimed water will help in reducing the potential negative environmental impacts of treated or/and partially treated wastewater discharges while increasing the potential uses of reclaimed water for agriculture and other applications. Using reclaimed water for irrigation is logical and efficient to enhance the economy of farmers and the environment while providing a diversity of crops, especially since most of Iraq’s built or under construction wastewater treatment plants are located in or adjacent to agricultural lands. Adopting an optimization modelling approach can assist decision makers, ensuring their decisions will benefit the economy by incorporating global experiences to control water allocations in Iraq especially considering diminished water supplies.
ContributorsAhmed, Ahmed Abdulrazzaq (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Muenich, Rebecca (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation critically evaluated methodologies and devices for assessing and protecting the health of human populations, with particular emphasis on groundwater remediation and the use of wastewater-based epidemiology (WBE) to inform population health. A meta-analysis and assessment of laboratory-scale treatability studies for removing chlorinated solvents from groundwater found that sediment microcosms operated as continuous-flow columns are preferable to batch bottles when seeking to emulate with high fidelity the complex conditions prevailing in the subsurface in contaminated aquifers (Chapter 2). Compared to monitoring at the field-scale, use of column microcosms also showed (i) improved chemical speciation, and (ii) qualitative predictability of field parameters (Chapter 3). Monitoring of glucocorticoid hormones in wastewater of a university campus showed (i) elevated stress levels particularly at the start of the semester, (ii) on weekdays relative to weekend days (p = 0.05) (161 ± 42 μg d-1 per person, 122 ± 54 μg d-1 per person; p ≤ 0.05), and (iii) a positive association between levels of stress hormones and nicotine (rs: 0.49) and caffeine (0.63) consumption in this student population (Chapter 4). Also, (i) alcohol consumption determined by WBE was in line with literature estimates for this young sub-population (11.3 ± 7.5 g d-1 per person vs. 10.1 ± 0.8 g d-1 per person), whereas caffeine and nicotine uses were below (114 ± 49 g d-1 per person, 178 ± 19 g d-1 per person; 627 ± 219 g d-1 per person, 927 ± 243 g d-1 per person). The introduction of a novel continuous in situ sampler to WBE brought noted benefits relative to traditional time-integrated sampling, including (i) a higher sample coverage (93% vs. 3%), (ii) an ability to captured short-term analyte pulses (e.g., heroin, fentanyl, norbuprenorphine, and methadone), and (iii) an overall higher mass capture for drugs of abuse like morphine, fentanyl, methamphetamine, amphetamine, and the opioid antagonist metabolite norbuprenorphine (p ≤ 0.01). Methods and devices developed in this work are poised to find applications in the remediation sector and in human health assessments.
ContributorsDriver, Erin Michelle (Author) / Halden, Rolf (Thesis advisor) / Conroy-Ben, Otakuye (Committee member) / Kavazanjian, Edward (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2018
Description
The phrase water-energy nexus is commonly used to describe the inherent and critical interdependencies between the electric power system and the water supply systems (WSS). The key interdependencies between the two systems are the power plant’s requirement of water for the cooling cycle and the water system’s need of electricity for pumping for water supply. While previous work has considered the dependency of WSS on the electrical power, this work incorporates into an optimization-simulation framework, consideration of the impact of short and long-term limited availability of water and/or electrical energy.
This research focuses on the water supply system (WSS) facet of the multi-faceted optimization and control mechanism developed for an integrated water – energy nexus system under U.S. National Science Foundation (NSF) project 029013-0010 CRISP Type 2 – Resilient cyber-enabled electric energy and water infrastructures modeling and control under extreme mega drought scenarios. A water supply system (WSS) conveys water from sources (such as lakes, rivers, dams etc.) to the treatment plants and then to users via the water distribution systems (WDS) and/or water supply canal systems (WSCS). Optimization-simulation methodologies are developed for the real-time operation of water supply systems (WSS) under critical conditions of limited electrical energy and/or water availability due to emergencies such as extreme drought conditions, electric grid failure, and other severe conditions including natural and manmade disasters. The coupling between WSS and the power system was done through alternatively exchanging data between the power system and WSS simulations via a program control overlay developed in python.
A new methodology for WDS infrastructural-operational resilience (IOR) computation was developed as a part of this research to assess the real-time performance of the WDS under emergency conditions. The methodology combines operational resilience and component level infrastructural robustness to provide a comprehensive performance assessment tool.
The optimization-simulation and resilience computation methodologies developed were tested for both hypothetical and real example WDS and WSCS, with results depicting improved resilience for operations of the WSS under normal and emergency conditions.
This research focuses on the water supply system (WSS) facet of the multi-faceted optimization and control mechanism developed for an integrated water – energy nexus system under U.S. National Science Foundation (NSF) project 029013-0010 CRISP Type 2 – Resilient cyber-enabled electric energy and water infrastructures modeling and control under extreme mega drought scenarios. A water supply system (WSS) conveys water from sources (such as lakes, rivers, dams etc.) to the treatment plants and then to users via the water distribution systems (WDS) and/or water supply canal systems (WSCS). Optimization-simulation methodologies are developed for the real-time operation of water supply systems (WSS) under critical conditions of limited electrical energy and/or water availability due to emergencies such as extreme drought conditions, electric grid failure, and other severe conditions including natural and manmade disasters. The coupling between WSS and the power system was done through alternatively exchanging data between the power system and WSS simulations via a program control overlay developed in python.
A new methodology for WDS infrastructural-operational resilience (IOR) computation was developed as a part of this research to assess the real-time performance of the WDS under emergency conditions. The methodology combines operational resilience and component level infrastructural robustness to provide a comprehensive performance assessment tool.
The optimization-simulation and resilience computation methodologies developed were tested for both hypothetical and real example WDS and WSCS, with results depicting improved resilience for operations of the WSS under normal and emergency conditions.
ContributorsKhatavkar, Puneet (Author) / Mays, Larry W. (Thesis advisor) / Vittal, Vijay (Committee member) / Mascaro, Giuseppe (Committee member) / Fox, Peter (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation details an attempt to experimentally evaluate the Giroud et al. (1995) concentration factors for geomembranes loaded in tension perpendicular to a seam by laboratory measurement. Field observations of the performance of geomembrane liner systems indicates that tears occur at average strains well below the yield criteria. These observations have been attributed, in part, to localized strain concentrations in the geomembrane loaded in tension in a direction perpendicular to the seam. Giroud et al. (1995) has presented theoretical strain concentration factors for geomembrane seams loaded in tension when the seam is perpendicular to the applied tensile strain. However, these factors have never been verified. This dissertation was prepared in fulfillment of the requirements for graduation from Barrett, the Honors College at Arizona State University. The work described herein was sponsored by the National Science Foundation as a part of a larger research project entitled "NEESR: Performance Based Design of Geomembrane Liner Systems Subject to Extreme Loading." The work is motivated by geomembrane tears observed at the Chiquita Canyon landfill following the 1994 Northridge earthquake. Numerical analysis of the strains in the Chiquita Canyon landfill liner induced by the earthquake indicated that the tensile strains, were well below the yield strain of the geomembrane material. In order to explain why the membrane did fail, strain concentration factors due to bending at seams perpendicular to the load in the model proposed by Giroud et al. (1995) had to be applied to the geomembrane (Arab, 2011). Due to the localized nature of seam strain concentrations, digital image correlation (DIC) was used. The high resolution attained with DIC had a sufficient resolution to capture the localized strain concentrations. High density polyethylene (HDPE) geomembrane samples prepared by a leading geomembrane manufacturer were used in the testing described herein. The samples included both extrusion fillet and dual hot wedge fusion seams. The samples were loaded in tension in a standard triaxial test apparatus. to the seams in the samples including both extrusion fillet and dual hot wedge seams. DIC was used to capture the deformation field and strain fields were subsequently created by computer analysis.
ContributorsAndresen, Jake Austin (Author) / Kavazanjian, Edward (Thesis director) / Gutierrez, Angel (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Accelerated climate and land use land cover (LULC) changes are anticipated to significantly impact water resources in the Colorado River Basin (CRB), a major freshwater source in the southwestern U.S. The need for actionable information from hydrologic research is growing rapidly, given considerable uncertainties. For instance, it is unclear if the predicted high degree of interannual precipitation variability across the basin could overwhelm the impacts of future warming and how this might vary in space. Climate change will also intensify forest disturbances (wildfire, mortality, thinning), which can significantly impact water resources. These impacts are not constrained, given findings of mixed post-disturbance hydrologic responses. Process-based models like the Variable Infiltration Capacity (VIC) platform can quantitatively predict hydrologic behaviors of these complex systems. However, barriers limit their effectiveness to inform decision making: (1) simulations generate enormous data volumes, (2) outputs are inaccessible to managers, and (3) modeling is not transparent. I designed a stakeholder engagement and VIC modeling process to overcome these challenges, and developed a web-based tool, VIC-Explorer, to “open the black box” of my efforts. Meteorological data was from downscaled historical (1950-2005) and future projections (2006-2099) of eight climate models that best represent climatology under low- and high- emissions. I used two modeling methods: (1) a “top-down” approach to assess an “envelope of hydrologic possibility” under the 16 climate futures; and (2) a “bottom-up” evaluation of hydrology in two climates from the ensemble representing “Hot/Dry” and “Warm/Wet” futures. For the latter assessment, I modified land cover using projections of a LULC model and applied more drastic forest disturbances. I consulted water managers to expand the legitimacy of the research. Results showed Far-Future (2066-2095) basin-wide mean annual streamflow decline (relative to 1976-2005; ensemble median trends of -5% to -25%), attributed to warming that diminished spring snowfall and melt and year-round increased soil evaporation from the Upper Basin, and overall precipitation declines in the Lower Basin. Forest disturbances partially offset warming effects (basin-wide mean annual streamflow up to 12% larger than without disturbance). Results are available via VIC-Explorer, which includes documentation and guided analyses to ensure findings are interpreted appropriately for decision-making.
ContributorsWhitney, Kristen Marie (Author) / Vivoni, Enrique R (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Whipple, Kelin X (Committee member) / White, Dave D (Committee member) / Xu, Tianfang (Committee member) / Arizona State University (Publisher)
Created2022
Description
The Water-Energy Nexus (WEN) is a concept that recognizes the interdependence of water and energy systems. The Phoenix metropolitan region (PMA) in Arizona has significant and potentially vulnerable WEN interactions. Future projections indicate that the population will increase and, with it, energy needs, while changes in future water demand are more uncertain. Climate change will also likely cause a reduction in surface water supply sources. Under these constraints, the expansion of renewable energy technology has the potential to benefit both water and energy systems and increase environmental sustainability by meeting future energy demands while lowering water use and CO2 emissions. However, the WEN synergies generated by renewables have not yet been thoroughly quantified, nor have the related costs been studied and compared to alternative options.Quantifying WEN intercations using numerical models is key to assessing renewable energy synergy. Despite recent advances, WEN models are still in their infancy, and research is needed to improve their accuracy and identify their limitations. Here, I highlight three research needs. First, most modeling efforts have been conducted for large-scale domains (e.g., states), while smaller scales, like metropolitan regions, have received less attention. Second, impacts of adopting different temporal (e.g., monthly, annual) and spatial (network granularity) resolutions on simulation accuracy have not been quantified. Third, the importance of simulating feedbacks between water and energy components has not been analyzed.
This dissertation fills these major research gaps by focusing on long-term water allocations and energy dispatch in the metropolitan region of Phoenix. An energy model is developed using the Low Emissions Analysis Platform (LEAP) platform and is subsequently coupled with a water management model based on the Water Evaluation and Planning (WEAP) platform. Analyses are conducted to quantify (1) the value of adopting coupled models instead of single models that are externally coupled, and (2) the accuracy of simulations based on different temporal resolutions of supply and demand and spatial granularity of the water and energy networks. The WEAP-LEAP integrated model is then employed under future climate scenarios to quantify the potential of renewable energy technologies to develop synergies between the PMA's water and energy systems.
ContributorsMounir, Adil (Author) / Mascaro, Giuseppe (Thesis advisor) / White, Dave (Committee member) / Garcia, Margaret (Committee member) / Xu, Tianfang (Committee member) / Chester, Mikhail (Committee member) / Arizona State University (Publisher)
Created2022
Description
Cities are facing complex problems in urban water management due to unprecedented changes in climate, natural and built environment. The shift in urban hydrology from pre-development to post-development continues to accelerate the challenges of managing excess stormwater runoff, mitigating urban flood hazards and flood damages. Physically based hydrologic-hydraulic stormwater models are a useful tool for broad subset of urban flood management including risk and hazard assessment, flood forecasting, and infrastructure adaptation decision making and planning. The existing limitations in data availability, gaps in data, and uncertainty in data preclude reliable model construction, testing, deployment, knowledge generation, effective communication of flood risks, and adaptation decision making. These challenges that affect both the science and practice motivate three chapters of this dissertation. The first study conducts diagnostic analysis of the effects of stormwater infrastructure data completeness on model’s ability to simulate flood duration, flooding flow rate; and assesses the combined effects of data gaps and model resolution to simulate flood depth, extent and volume (chapter 2). The analysis showed the significance of complete stormwater infrastructure data and high model resolution to reduce error, bias and uncertainty; this study also presented an approach for filling infrastructure data gaps using available data and design standards. The second study addresses the lack of long-term hydrological observation in urban catchment by investigating the process and benefits of leveraging novel data sources in urban flood model construction and testing (chapter 3). A proof-of-concept demonstrated the application and benefits of leveraging novel data sources for urban flood monitoring and modeling. Furthermore, it highlights the need for developing and streamlining novel data collection infrastructure. The third study applies the hydrologic-hydraulic model as an adaptation planning tool and assess the effects of uncertainty in design precipitation estimates and land use change on the optimal configuration of green infrastructure (chapter 4). Several uncertainties affect infrastructure decision making as showed by variation in optimal green infrastructure configuration under precipitation estimates and land use change. Thus, the study further highlights the need of flexible planning process in infrastructure decision making.
ContributorsShrestha, Ashish (Author) / Garcia, Margaret (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Chester, Mikhail (Committee member) / Fletcher, Sarah (Committee member) / Arizona State University (Publisher)
Created2022
Description
Uncertainty is inherent in predictive decision-making, both with respect to forecasting plausible future conditions based on a historic record, and with respect to backcasting likely upstream states from downstream observations. In the first chapter, I evaluated the status of current water resources management policy in the United States (U.S.) with respect to its integration of projective uncertainty into state-level flooding, drought, supply and demand, and climate guidance. I found uncertainty largely absent and discussed only qualitatively rather than quantitatively. In the second chapter, I turned to uncertainty in the interpretation of downstream observations as indicators of upstream behaviors in the field of Wastewater-Based Epidemiology (WBE), which has made possible the near real-time, yet anonymous, monitoring of public health via measurements of biomarkers excreted to wastewater. I found globally, seasonality of air and soil temperature causes biomarker degradation to vary up to 13-fold over the course of a year, constituting part of the background processes WBE must address, or detrend, prior to decision-making. To determine whether the seasonal change in degradation rates was introducing previously unaccounted for uncertainty with respect to differences in observed summertime and winter-time populations, I evaluated demographic indicators recorded by the Census Bureau for correlation with their distance from all major wastewater treatment plants across the U.S. The analysis identified statistically significant correlation for household income, education attainment, unemployment, military service, and the absence of health insurance. Finally, the model was applied to a city-wide case study to test whether temperature could explain some of the trends observed in monthly observations of two opiate compounds. Modeling suggests some of the monthly changes were attributed to natural temperature fluctuation rather than to trends in the substances’ consumption, and that uncertainty regarding discharge location can dominate even relative observed differences in opiate detections. In summary, my work has found temperature an important modulator of WBE results, influencing both the type of populations observed and the likelihood of upstream behaviors disproportionally magnified or obscured, particularly for the more labile biomarkers. There exists significant potential for improving the understanding of empirical observations via numerical modeling and the application of spatial analysis tools.
ContributorsHart, Olga (Author) / Halden, Rolf (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Renaut, Rosemary (Committee member) / Nelson, Keith (Committee member) / Arizona State University (Publisher)
Created2019
Description
Imagine you live in a place without any storm water or wastewater systems!
Wastewater and storm water systems are two of the most crucial systems for urban infrastructure. Water resources have become more limited and expensive in arid and semi-arid regions. According to the fourth World Water Development Report, over 80% of global wastewater is released into the environment without adequate treatment. Wastewater collection and treatment systems in the Kingdom of Saudi Arabia (KSA) covers about 49% of urban areas; about 25% of treated wastewater is used for landscape and crop irrigation (Ministry of Environment Water and Agriculture [MEWA], 2017). According to Guizani (2016), during each event of flooding, there are fatalities. In 2009, the most deadly flood occurred in Jeddah, KSA within more than 160 lives lost. As a consequence, KSA has set a goal to provide 100% sewage collection and treatment services to every city with a population above 5000 by 2025, where all treated wastewater will be used.
This research explores several optimization models of planning and designing collection systems, such as regional wastewater and stormwater systems, in order to understand and overcome major performance-related disadvantages and high capital costs. The first model (M-1) was developed for planning regional wastewater system, considering minimum costs of location, type, and size sewer network and wastewater treatment plants (WWTPs). The second model (M-2) was developed for designing a regional wastewater system, considering minimum hydraulic design costs, such as pump stations, commercial diameters, excavation costs, and WWTPs. Both models were applied to the Jizan region, KSA.
The third model (M-3) was developed to solve layout and pipe design for storm water systems simultaneously. This model was applied to four different case scenarios, using two approaches for commercial diameters. The fourth model (M-4) was developed to solve the optimum pipe design of a storm sewer system for given layouts. However, M-4 was applied to a storm sewer network published in the literature.
M-1, M-2, and M-3 were developed in the general algebraic modeling system (GAMS) program, which was formulated as a mixed integer nonlinear programming (MINLP) solver, while M-4 was formulated as a nonlinear programming (NLP) procedure.
Wastewater and storm water systems are two of the most crucial systems for urban infrastructure. Water resources have become more limited and expensive in arid and semi-arid regions. According to the fourth World Water Development Report, over 80% of global wastewater is released into the environment without adequate treatment. Wastewater collection and treatment systems in the Kingdom of Saudi Arabia (KSA) covers about 49% of urban areas; about 25% of treated wastewater is used for landscape and crop irrigation (Ministry of Environment Water and Agriculture [MEWA], 2017). According to Guizani (2016), during each event of flooding, there are fatalities. In 2009, the most deadly flood occurred in Jeddah, KSA within more than 160 lives lost. As a consequence, KSA has set a goal to provide 100% sewage collection and treatment services to every city with a population above 5000 by 2025, where all treated wastewater will be used.
This research explores several optimization models of planning and designing collection systems, such as regional wastewater and stormwater systems, in order to understand and overcome major performance-related disadvantages and high capital costs. The first model (M-1) was developed for planning regional wastewater system, considering minimum costs of location, type, and size sewer network and wastewater treatment plants (WWTPs). The second model (M-2) was developed for designing a regional wastewater system, considering minimum hydraulic design costs, such as pump stations, commercial diameters, excavation costs, and WWTPs. Both models were applied to the Jizan region, KSA.
The third model (M-3) was developed to solve layout and pipe design for storm water systems simultaneously. This model was applied to four different case scenarios, using two approaches for commercial diameters. The fourth model (M-4) was developed to solve the optimum pipe design of a storm sewer system for given layouts. However, M-4 was applied to a storm sewer network published in the literature.
M-1, M-2, and M-3 were developed in the general algebraic modeling system (GAMS) program, which was formulated as a mixed integer nonlinear programming (MINLP) solver, while M-4 was formulated as a nonlinear programming (NLP) procedure.
ContributorsAlfaisal, Faisal M (Author) / Mays, Larry W. (Thesis advisor) / Mascaro, Giuseppe (Committee member) / Fox, Peter (Committee member) / Arizona State University (Publisher)
Created2019