ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Creators: Fox, Peter
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
C.C. Cragin Reservoir’s location in the Coconino National Forest, Arizona makes it prone to wild fire. This study focused on the potential impacts of such a wild fire on the reservoir’s annual thermal stratification cycle impacts and water quality. The annual thermal stratification cycle impacted the reservoir’s water quality by increasing hypolimnion concentrations of magnesium, iron, turbidity, and specific ultraviolet absorbance (SUVA) values, as well as resulting in the hypolimnion having decreased dissolved oxygen concentrations during stratified months. The scarification process did not affect the dissolved organic carbon (DOC) concentrations in the reservoir or the total/dissolved nitrogen and phosphorous concentrations. Some general water quality trends that emerged were that phosphorous was the limiting nutrient, secchi disk depth and chlorophyll a concentration are inversely related, and no metals were found to be in concentrations that would violate an EPA drinking water maximum contaminant level (MCL). A carbon mass model was developed and parameterized using DOC measurements, and then using historic reservoir storage and weather data, the model simulated DOC concentrations in the reservoir following four hypothetical wild fire events. The model simulated varying initial reservoir storage volumes, initial flush volumes, and flush DOC concentrations, resulting in reservoir DOC concentrations varying from 17.41 mg/L to 8.82 mg/L.
ContributorsFlatebo, Theodore (Author) / Westerhoff, Paul K (Thesis advisor) / Fox, Peter (Committee member) / Perreault, Francois (Committee member) / Arizona State University (Publisher)
Created2018
Description
One of the two objectives of this dissertation is an investigation into the possible correlation between rainfall events and increased levels of E. coli and Mycobacterium using an existing data set. The literature states that levels of microbial concentrations do increase after rainfall events, but there are no studies to indicate this correlation applies in any Arizona water systems. The data analyzed for the bacterial concentrations project suggested the possibility of a correlation along one river but it is not conclusive to state that any correlation exists between rainfall events and the microbial concentration for many other sites included in the analysis. This is most likely due to the highly engineered water delivery systems that are not directly impacted.
The secondary objective was to determine if there are environmental variables collected from an ongoing project which would be a good candidate for making predictions about any of the project data parameters. Of the 79 possible opportunities for the model to accurately predict the dependent variable, it showed strong statistical favorability as well as experimentally favorable results towards Dissolved Organic Carbon as the best dependent variable from the data set, resulting in an accuracy of 41%. This is relevant since Dissolved Organic Carbon is one of the most important water quality parameters of concern for drinking water treatment plants where disinfection by-products are a limiting factor. The need for further analysis and additional data collection is an obvious result from both studies. The use of hydrograph data instead of rainfall would be a logical new direction for the heavily engineered water delivery systems.
The secondary objective was to determine if there are environmental variables collected from an ongoing project which would be a good candidate for making predictions about any of the project data parameters. Of the 79 possible opportunities for the model to accurately predict the dependent variable, it showed strong statistical favorability as well as experimentally favorable results towards Dissolved Organic Carbon as the best dependent variable from the data set, resulting in an accuracy of 41%. This is relevant since Dissolved Organic Carbon is one of the most important water quality parameters of concern for drinking water treatment plants where disinfection by-products are a limiting factor. The need for further analysis and additional data collection is an obvious result from both studies. The use of hydrograph data instead of rainfall would be a logical new direction for the heavily engineered water delivery systems.
ContributorsBuell, Andrew (Author) / Fox, Peter (Thesis advisor) / Abbaszadegan, Morteza (Thesis advisor) / Alum, Absar (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
Over the past decade, there has been a revival in applied algal research and attempts at commercialization. However, the main limitation in algal commercialization is the process of cultivation, which is one of the main cost and energy burdens in producing biomass that is economically feasible for different products. There are several parameters that must be considered when growing algae, including the type of growth system and operating mode, preferred organism(s), and many other criteria that affect the process of algal cultivation. The purpose of this dissertation was to assess key variables that affect algal productivity and to improve outdoor algal cultivation procedures. The effect of reducing or eliminating aeration of algal cultures at night, in flat panel photobioreactors (panels), was investigated to assess the reduction of energy consumption at night. The lack of aeration at night resulted in anoxic conditions, which significantly reduced lipid accumulation and productivity, but did not affect log phase biomass productivity. In addition, the reduction in aeration resulted in lower pH values, which prevented ammonia volatility and toxicity. Raceways are operated at deeper cultivation depths, which limit culture density and light exposure. Experimentation was accomplished to determine the effects of decreasing cultivation depth, which resulted in increased lipid accumulation and lipid productivity, but did not significantly affect biomass productivity. A comparison of semi-continuous cultivation of algae in raceways and panels in side-by-side experiments showed that panels provided better temperature control and higher levels of mixing, which resulted in higher biomass productivity. In addition, sub-optimal morning temperatures in raceways compared to panels were a significant factor in reducing algae biomass productivity. The results from this research indicate that increasing lipid productivity and biomass productivity cannot be completed simultaneously. Therefore, the desired product will determine if lipid or biomass productivity is more crucial, which also dictates whether the system should be operated in batch mode to either allow lipid accumulation or in semi-continuous mode to allow high biomass productivity. This work is a critical step in improving algal cultivation by understanding key variables that limit biomass and lipid productivity.
ContributorsEustance, Everett (Author) / Sommerfeld, Milton R (Thesis advisor) / Fox, Peter (Committee member) / Westerhoff, Paul (Committee member) / Arizona State University (Publisher)
Created2015
Description
Six high-production-volume neonicotinoids were traced through a municipal wastewater treatment plant (WWTP) and engineered wetland located downstream, in a study motivated by reports on these insecticides posing threats to non-target invertebrate species and potentially playing a role in the global honeybee colony collapse disorder. An array of automated samplers was deployed in a five-day monitoring campaign and resultant flow-weighted samples were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) using the isotope dilution method. Concentrations in WWTP influent and effluent were 54.7 ± 2.9 and 48.6 ± 2.7 ng/L for imidacloprid, respectively, and 3.7 ± 0.3 and 1.8 ± 0.1 ng/L for acetamiprid, respectively. A mass balance over the WWTP showed no (p=0.09, CI = 95%) removal of imidacloprid, and 56 ± 6% aqueous removal of acetamiprid. In the constructed wetland downstream, a lack of removal was noted for both imidacloprid (from 54.4 ± 3.4 ng/L to 49.9 ± 14.6 ng/L) and acetamiprid (from 2.00 ± 0.03 ng/L to 2.30 ± 0.21 ng/L). Clothianidin was detected only inconsistently in the WWTP and wetland (>2 to 288 ng/L; 60% detection frequency), whereas thiamethoxam (<10 ng/L), thiacloprid (<2 ng/L), and dinotefuran (<180 ng/L) were not detected at all. Thus, imidacloprid and acetamiprid were identified as recalcitrant sewage constituents (estimated U.S. WWTP discharge of 1920- 4780 kg/y) that persist during conventional wastewater treatment to enter U.S. surface waters at potentially harmful concentrations.
ContributorsSadaria, Akash Mahendra (Author) / Halden, Rolf (Thesis advisor) / Fox, Peter (Committee member) / Popat, Sudeep (Committee member) / Arizona State University (Publisher)
Created2015
Description
The need for rapid, specific and sensitive assays that provide a detection of bacterial indicators are important for monitoring water quality. Rapid detection using biosensor is a novel approach for microbiological testing applications. Besides, validation of rapid methods is an obstacle in adoption of such new bio-sensing technologies. In this study, the strategy developed is based on using the compound 4-methylumbelliferyl glucuronide (MUG), which is hydrolyzed rapidly by the action of E. coli β-D-glucuronidase (GUD) enzyme to yield a fluorogenic product that can be quantified and directly related to the number of E. coli cells present in water samples. The detection time required for the biosensor response ranged from 30 to 120 minutes, depending on the number of bacteria. The specificity of the MUG based biosensor platform assay for the detection of E. coli was examined by pure cultures of non-target bacterial genera and also non-target substrates. GUD activity was found to be specific for E. coli and no such enzymatic activity was detected in other species. Moreover, the sensitivity of rapid enzymatic assays was investigated and repeatedly determined to be less than 10 E. coli cells per reaction vial concentrated from 100 mL of water samples. The applicability of the method was tested by performing fluorescence assays under pure and mixed bacterial flora in environmental samples. In addition, the procedural QA/QC for routine monitoring of drinking water samples have been validated by comparing the performance of the biosensor platform for the detection of E. coli and culture-based standard techniques such as Membrane Filtration (MF). The results of this study indicated that the fluorescence signals generated in samples using specific substrate molecules can be utilized to develop a bio-sensing platform for the detection of E. coli in drinking water. The procedural QA/QC of the biosensor will provide both industry and regulatory authorities a useful tool for near real-time monitoring of E. coli in drinking water samples. Furthermore, this system can be applied independently or in conjunction with other methods as a part of an array of biochemical assays in order to reliably detect E. coli in water.
ContributorsHesari, Nikou (Author) / Abbaszadegan, Morteza (Thesis advisor) / Alum, Absar (Committee member) / Fox, Peter (Committee member) / Stout, Valerie (Committee member) / Arizona State University (Publisher)
Created2015
Description
Carbon dioxide (CO2) is one of the most dangerous greenhouse gas. Its concentration in the atmosphere has increased to very high levels since the industrial revolution. This continues to be a threat due to increasing energy demands. 60% of the worlds global emissions come from automobiles and other such moving sources. Hence, to stay within safe limits, it is extremely important to curb current emissions and remove those which have already been emitted. Out of many available technologies, one such technology is the moisture swing based air capture technology that makes use of resin material that absorbs CO2 when it is dry and releases it when it is wet. A mathematical model was developed to better understand the mechanism of this process. In order to validate this model, numerical simulation and experimentation was done. Once the mechanism was proved, it was seen that there are many factors and parameters that govern this process. Some of these do not have definite value. To find the best fit value for these parameters, an optimized fitting routine needs to be developed that can minimize the standard deviation of the error. This thesis looks into ways in which the optimization of parameters can be done and the possible future work by using substantial data.
ContributorsChopra, Vinuta (Author) / Lackner, Klaus S (Thesis advisor) / Fox, Peter (Committee member) / Wright, Allen (Committee member) / Arizona State University (Publisher)
Created2016
Description
Advanced oxidation processes (AOP’s) are water/wastewater treatment processes simultaneously providing disinfection and potential oxidation of contaminants that may cause long-term adverse health effects in humans. One AOP involves injecting peracetic acid (PAA) upstream of an ultraviolet (UV) irradiation reactor. Two studies were conducted, one in pilot-scale field conditions and another under laboratory conditions. A pilot-scale NeoTech UV reactor (rated for 375 GPM) was used in the pilot study, where a smaller version of this unit was used in the laboratory study (20 to 35 GPM). The pilot study analyzed coliform disinfection and also monitored water quality parameters including UV transmittance (UVT), pH and chlorine residual. Pilot study UV experiments indicate the unit is effectively treating flow streams (>6 logs total coliforms) twice the 95% UVT unit capacity (750 GPM or 17 mJ/cm2 UV Dose). The results were inconclusive on PAA/UV inactivation due to high data variability and field operation conditions creating low inlet concentrations.Escherichia coli (E. coli) bacteria and the enterobacteria phage P22—a surrogate for enteric viruses—were analyzed. UV inactivated >7.9 and 4 logs of E. coli and P22 respectively at a 16.8 mJ/cm2 UV dose in test water containing a significant organics concentration. When PAA doses of 0.25 and 0.5 mg/L were injected upstream of UV at approximately the same UV Dose, the average E.coli log inactivation increased to >8.9 and >9 logs respectively, but P22 inactivation decreased to 2.9 and 3.0 logs, respectively. A bench-scale study with PAA was also conducted for 5, 10 and 30 minutes of contact time, where 0.25 and 0.5 mg/L had <1 log inactivation of E. coli and P22 after 30 minutes of contact time. In addition, degradation of the chemical N-Nitrosodimethylamine (NDMA) in tap water was analyzed, where UV degraded NDMA by 48 to 97% for 4 and 0.5 GPM flowrates, respectively. Adding 0.5 mg/L PAA upstream of UV did not significantly improve NDMA degradation.
The results under laboratory conditions indicate that PAA/UV have synergy in the inactivation of bacteria, but decrease virus inactivation. In addition, the pilot study demonstrates the applicability of the technology for full scale operation.
The results under laboratory conditions indicate that PAA/UV have synergy in the inactivation of bacteria, but decrease virus inactivation. In addition, the pilot study demonstrates the applicability of the technology for full scale operation.
ContributorsCooper, Samantha (Author) / Abbaszadegan, Morteza (Thesis advisor) / Alum, Absar (Committee member) / Fox, Peter (Committee member) / Arizona State University (Publisher)
Created2017
Description
Bioretention basins are a common stormwater best management practice (BMP) used to mitigate the hydrologic consequences of urbanization. Dry wells, also known as vadose-zone wells, have been used extensively in bioretention basins in Maricopa County, Arizona to decrease total drain time and recharge groundwater. A mixed integer nonlinear programming (MINLP) model has been developed for the minimum cost design of bioretention basins with dry wells.
The model developed simultaneously determines the peak stormwater inflow from watershed parameters and optimizes the size of the basin and the number and depth of dry wells based on infiltration, evapotranspiration (ET), and dry well characteristics and cost inputs. The modified rational method is used for the design storm hydrograph, and the Green-Ampt method is used for infiltration. ET rates are calculated using the Penman Monteith method or the Hargreaves-Samani method. The dry well flow rate is determined using an equation developed for reverse auger-hole flow.
The first phase of development of the model is to expand a nonlinear programming (NLP) for the optimal design of infiltration basins for use with bioretention basins. Next a single dry well is added to the NLP bioretention basin optimization model. Finally the number of dry wells in the basin is modeled as an integer variable creating a MINLP problem. The NLP models and MINLP model are solved using the General Algebraic Modeling System (GAMS). Two example applications demonstrate the efficiency and practicality of the model.
The model developed simultaneously determines the peak stormwater inflow from watershed parameters and optimizes the size of the basin and the number and depth of dry wells based on infiltration, evapotranspiration (ET), and dry well characteristics and cost inputs. The modified rational method is used for the design storm hydrograph, and the Green-Ampt method is used for infiltration. ET rates are calculated using the Penman Monteith method or the Hargreaves-Samani method. The dry well flow rate is determined using an equation developed for reverse auger-hole flow.
The first phase of development of the model is to expand a nonlinear programming (NLP) for the optimal design of infiltration basins for use with bioretention basins. Next a single dry well is added to the NLP bioretention basin optimization model. Finally the number of dry wells in the basin is modeled as an integer variable creating a MINLP problem. The NLP models and MINLP model are solved using the General Algebraic Modeling System (GAMS). Two example applications demonstrate the efficiency and practicality of the model.
ContributorsLacy, Mason (Author) / Mays, Larry W. (Thesis advisor) / Fox, Peter (Committee member) / Wang, Zhihua (Committee member) / Arizona State University (Publisher)
Created2016