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dc.contributor.advisorBradley, Thomas H.
dc.contributor.authorQuiroz-Arita, Carlos Enrique
dc.contributor.committeememberBark, David
dc.contributor.committeememberBlaylock, Myra
dc.contributor.committeememberMarchese, Anthony
dc.contributor.committeememberSharvelle, Sybil
dc.contributor.committeememberWillson, Bryan
dc.date.accessioned2018-09-10T20:05:13Z
dc.date.available2020-09-06T20:05:05Z
dc.date.issued2018
dc.description2018 Summer.
dc.descriptionIncludes bibliographical references.
dc.description.abstractPhotoautotroph-based biofuels are considered one of the most promising renewable resources to meet the global energy requirements for transportation systems. Long-term research and development has resulted in demonstrations of microalgae areal oil productivities that are higher than crop-based biofuels, about 10 times that of palm oil and about 130 times that of soybean. Cyanobacteria is reported to have ~4 times the areal productivity of microalgae on an equivalent energy basis. Downstream of this cultivation process, the cyanobacteria biomass and bioproducts can be supplied to biorefineries producing feed, biomaterials, biosynthetic chemicals, and biofuels. As such, cyanobacteria, and microalgae-based systems can be a significant contributor to more sustainable energy and production systems. This research presents novel means to be able to analyze, integrate, assess, and design sustainable photoautotrophic biofuel and bioproduct systems, as defined using lifecycle assessment methods (LCA). As part of a broad collaboration between industry, academia, and the national laboratories, I have developed models and experiments to quantify tradeoffs among the scalability, sustainability, and technical feasibility of cyanobacteria biorefineries and microalgae cultivation systems. A central hypothesis to this research is that the lifecycle energy costs and benefits, the cultivation productivity, and the scalability of any given organism or technology is governed by the fluid mechanics of the photobioreactor systems. The fluid characteristics of both open raceway ponds and flat photobioreactors, are characterized through industrial-scale experiment and modeling. Turbulent mixing is studied by applying Acoustic Doppler Velocimetry (ADV), Particle Image Velocimetry (PIV), and computational fluid dynamics (CFD) characterization tools. The implications of these fluid conditions on photoautotrophic organisms are studied through cultivation and modeling of the cyanobacteria, Synechocystis sp. PCC6803. Growth-stage models of this cyanobacteria include functions dependent on incident radiation, temperature, nutrient availability, dark and photo-respiration. By developing an integrated approach to laboratory experimentation and industrial-scale growth experiments, we have validated models to quantify the scalability and sustainability of these novel biosystems. These capabilities are utilized to perform long-term and industrially-relevant assessments of the costs and benefits of these promising technologies, and will serve to inform the biological engineering research and development of new organisms.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.identifierQuirozArita_colostate_0053A_15011.pdf
dc.identifier.urihttps://hdl.handle.net/10217/191419
dc.languageEnglish
dc.publisherColorado State University. Libraries
dc.relation.ispartof2000-2019 - CSU Theses and Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectbiofuels
dc.subjectlife cycle assessment
dc.subjectwastewater treatment
dc.subjectcyanobacteria
dc.subjectalgae
dc.subjectturbulent mixing/thermal
dc.titleSustainability tradeoffs within photoautotrophic cultivation systems: integrating physical and lifecycle modeling for design and optimization
dc.typeText
dcterms.embargo.expires2020-09-06
dcterms.rights.dplaThe copyright and related rights status of this Item has not been evaluated (https://rightsstatements.org/vocab/CNE/1.0/). Please refer to the organization that has made the Item available for more information.
thesis.degree.disciplineMechanical Engineering
thesis.degree.grantorColorado State University
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy (Ph.D.)


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