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- Genre: Doctoral Dissertation
Description
Nanotechnology is a scientific field that has recently expanded due to its applications in pharmaceutical and personal care products, industry and agriculture. As result of this unprecedented growth, nanoparticles (NPs) have become a significant environmental contaminant, with potential to impact various forms of life in environment. Metal nanoparticles (mNPs) exhibit unique properties such as increased chemical reactivity due to high specific surface area to volume ratios. Bacteria play a major role in many natural and engineered biogeochemical reactions in wastewater treatment plants and other environmental compartments. I have evaluated the laboratory isolates of E. coli, Bacillus, Alcaligenes, Pseudomonas; wastewater isolates of E. coli and Bacillus; and pathogenic isolate of E. coli for their response to 50 & 100 nm sized Cu nanoparticles (CuNPs). Bactericidal tests, scanning electron microscopy (SEM) analyses, and probable toxicity pathways assays were performed. The results indicate that under continuous mixing conditions, CuNPs are effective in inactivation of the selected bacterial isolates. In general, exposure to CuNPs resulted in 4 to >6 log reduction in bacterial population within 2 hours. Based on the GR, LDH and MTT assays, bacterial cells showed different toxicity elicitation pathways after exposure to CuNPs. Therefore, it can be concluded that the laboratory isolates are good candidates for predicting the behavior of environmental isolates exposed to CuNPs. Also, high inactivation values recorded in this study suggest that the presence of CuNPs in different environmental compartments may have an impact on pollutants attenuation and wastewater biological treatment processes. These results point towards the need for an in depth investigation of the impact of NPs on the biological processes; and long-term effect of high load of NPs on the stability of aquatic and terrestrial ecologies.
ContributorsAlboloushi, Ali (Author) / Abbaszadegan, Morteza (Thesis advisor) / Alum, Absar (Committee member) / Fox, Peter (Committee member) / Olson, Larry (Committee member) / Arizona State University (Publisher)
Created2012
Description
Recognition of algae as a “Fit for Purpose” biomass and its potential as an energy and bio-product resource remains relatively obscure. This is due to the absence of tailored and unified production information necessary to overcome several barriers for commercial viability and environmental sustainability. The purpose of this research was to provide experimentally verifiable estimates for direct energy and water demand for the algal cultivation stage which yields algal biomass for biofuels and other bio-products. Algal biomass productivity was evaluated using different cultivation methods in conjunction with assessment for potential reduction in energy and water consumption for production of fuel and feed. Direct water and energy demands are the major focal sustainability metrics in hot and arid climates and are influenced by environmental and operational variables connected with selected algal cultivation technologies. Evaporation is a key component of direct water demand for algal cultivation and directly related to variations in temperature and relative humidity. Temperature control strategies relative to design and operational variables were necessary to mitigate overheating of the outdoor algae culture in panel photobioreactors and sub-optimal cultivation temperature in open pond raceways. Mixing in cultivation systems was a major component in direct energy demand that was provided by aeration in panel bioreactors and paddlewheels in open pond raceways. Management of aeration time to meet required biological interactions provides opportunities for reduced direct energy demand in panel photobioreactors. However, the potential for reduction in direct energy demand in raceway ponds is limited to hydraulics and head loss. Algal cultivation systems were reviewed for potential integration into dairy facilities in order to determine direct energy demand and nutrient requirements for algal biomass production for animal feed. The direct energy assessment was also evaluated for key components of related energy and design parameters for conventional raceway ponds and a gravity fed system. The results of this research provide a platform for selecting appropriate production scenarios with respect to resource use and to ensure a cost effective product with the least environmental burden.
ContributorsBadvipour, Shahrzad (Author) / Sommerfeld, Milton (Thesis advisor) / Downes, Meghan (Committee member) / Abbott, Joshua (Committee member) / Chester, Mikhail (Committee member) / Arizona State University (Publisher)
Created2015
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