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.
Displaying 1 - 2 of 2
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
Several prominent research strategy organizations recommend applying life cycle assessment (LCA) early in the development of emerging technologies. For example, the US Environmental Protection Agency, the National Research Council, the Department of Energy, and the National Nanotechnology Initiative identify the potential for LCA to inform research and development (R&D) of photovoltaics and products containing engineered nanomaterials (ENMs). In this capacity, application of LCA to emerging technologies may contribute to the growing movement for responsible research and innovation (RRI). However, existing LCA practices are largely retrospective and ill-suited to support the objectives of RRI. For example, barriers related to data availability, rapid technology change, and isolation of environmental from technical research inhibit application of LCA to developing technologies. This dissertation focuses on development of anticipatory LCA tools that incorporate elements of technology forecasting, provide robust explorations of uncertainty, and engage diverse innovation actors in overcoming retrospective approaches to environmental assessment and improvement of emerging technologies. Chapter one contextualizes current LCA practices within the growing literature articulating RRI and identifies the optimal place in the stage gate innovation model to apply LCA. Chapter one concludes with a call to develop anticipatory LCA – building on the theory of anticipatory governance – as a series of methodological improvements that seek to align LCA practices with the objectives of RRI.
Chapter two provides a framework for anticipatory LCA, identifies where research from multiple disciplines informs LCA practice, and builds off the recommendations presented in the preceding chapter. Chapter two focuses on crystalline and thin film photovoltaics (PV) to illustrate the novel framework, in part because PV is an environmentally motivated technology undergoing extensive R&D efforts and rapid increases in scale of deployment. The chapter concludes with a series of research recommendations that seek to direct PV research agenda towards pathways with the greatest potential for environmental improvement.
Similar to PV, engineered nanomaterials (ENMs) are an emerging technology with numerous potential applications, are the subject of active R&D efforts, and are characterized by high uncertainty regarding potential environmental implications. Chapter three introduces a Monte Carlo impact assessment tool based on the toxicity impact assessment model USEtox and demonstrates stochastic characterization factor (CF) development to prioritize risk research with the greatest potential to improve certainty in CFs. The case study explores a hypothetical decision in which personal care product developers are interested in replacing the conventional antioxidant niacinamide with the novel ENM C60, but face high data uncertainty, are unsure regarding potential ecotoxicity impacts associated with this substitution, and do not know what future risk-relevant experiments to invest in that most efficiently improve certainty in the comparison. Results suggest experiments that elucidate C60 partitioning to suspended solids should be prioritized over parameters with little influence on results. This dissertation demonstrates a novel anticipatory approach to exploration of uncertainty in environmental models that can create new, actionable knowledge with potential to guide future research and development decisions.
Chapter two provides a framework for anticipatory LCA, identifies where research from multiple disciplines informs LCA practice, and builds off the recommendations presented in the preceding chapter. Chapter two focuses on crystalline and thin film photovoltaics (PV) to illustrate the novel framework, in part because PV is an environmentally motivated technology undergoing extensive R&D efforts and rapid increases in scale of deployment. The chapter concludes with a series of research recommendations that seek to direct PV research agenda towards pathways with the greatest potential for environmental improvement.
Similar to PV, engineered nanomaterials (ENMs) are an emerging technology with numerous potential applications, are the subject of active R&D efforts, and are characterized by high uncertainty regarding potential environmental implications. Chapter three introduces a Monte Carlo impact assessment tool based on the toxicity impact assessment model USEtox and demonstrates stochastic characterization factor (CF) development to prioritize risk research with the greatest potential to improve certainty in CFs. The case study explores a hypothetical decision in which personal care product developers are interested in replacing the conventional antioxidant niacinamide with the novel ENM C60, but face high data uncertainty, are unsure regarding potential ecotoxicity impacts associated with this substitution, and do not know what future risk-relevant experiments to invest in that most efficiently improve certainty in the comparison. Results suggest experiments that elucidate C60 partitioning to suspended solids should be prioritized over parameters with little influence on results. This dissertation demonstrates a novel anticipatory approach to exploration of uncertainty in environmental models that can create new, actionable knowledge with potential to guide future research and development decisions.
ContributorsWender, Ben A. (Author) / Seager, Thomas (Thesis advisor) / Guston, David (Committee member) / Westerhoff, Paul (Committee member) / Arizona State University (Publisher)
Created2016