Chen, Peter H., authorQuinn, Jason C., advisorBradley, Thomas, committee memberMarchese, Anthony, committee memberReardon, Kenneth, committee member2022-05-302022-05-302022https://hdl.handle.net/10217/235257Researchers have recognized the potential of microalgae for renewable fuels for several decades, with a sharp increase in interest in the past decade. Though progress in algal cultivation and conversion has been substantial, commercialization of algal fuels has not yet been achieved. Economic metrics must be balanced with renewable fuel goals such that algal fuels can be competitive with conventional petroleum fuels. Through process modeling, techno-economic analysis (TEA), and life cycle assessment (LCA), the work in this dissertation seeks to illuminate improvements to algal fuel systems and outline the steps required to advance algal fuels toward commercialization. This work heavily focuses on hydrothermal liquefaction (HTL), a thermochemical process that converts whole wet biomass into biocrude, a petroleum crude oil analog. An aqueous phase, a gaseous phase, and a solid phase are created alongside the primary biocrude product. The aqueous phase of HTL notably contains a high content of nitrogen, which could potentially be recycled back to algae cultivation. At a scale where algal biofuels would meet a significant portion of transportation fuel needs, the demand for nutrients, specifically nitrogen and phosphorus, would exceed current global agricultural production. While recycling the aqueous phase could alleviate the demand for fresh nutrients in algae cultivation, it also contains toxic components, which include heterocyclic nitrogen compounds and phenolic compounds. The first phase of this research is an experimental component that focuses on methods for improving the recyclability of nutrients in the aqueous phase. A novel use of adsorbents (activated carbon and ion-exchange resins) was discovered for reducing the presence of components that are toxic to algae growth. The second research phase is a comprehensive modeling effort of the HTL process. A process model was developed in Aspen Plus from a robust assessment of current literature. These results are fed into TEA and LCA models to fully demonstrate the effects that process uncertainties have on the viability of HTL. For example, the high-temperature conditions that define HTL require the material to maintain a subcritical liquid state, which complicates the assessment of accurate thermochemical properties due to the required pressure. To clarify this issue, the work in this research phase compares the estimated performance of algal HTL between different thermodynamic models. HTL environmental metrics beyond global warming potential and net energy ratio are also discussed for the first time. Uncertainties in conversion performance are bounded through a scenario analysis that manipulates parameters such as product yield and nutrient recycle (as discussed in the first research phase) to establish a range of economic results and environmental impacts. The work is supplemented with a publicly available model to support future hydrothermal liquefaction assessments and accelerate the development of commercial-scale systems. The third and final research phase compares HTL with a fractionation train called Combined Algal Processing (CAP) and takes into consideration the possibility of integrating HTL downstream of CAP. CAP can be described as a pretreatment and fermentation step followed by a lipid extraction step to extract carbohydrates and lipids, respectively, for fuel products. However, CAP cannot convert proteins to fuels, making the process highly dependent on feed composition from the cultivation stage. HTL's advantage over CAP is its relative agnosticism to composition, but it requires greater capital costs and is more energetically intensive. A fuzzy logic approach is proposed to compare CAP and HTL process models through relevant performance metrics and to map algal feed conditions that lead to optimal algae-to-fuel pathways. Thresholds are set for fuzzy membership functions in relevant performance objectives: minimum fuel selling price (MFSP), global warming potential (GWP), and net energy ratio (NER). The membership functions yield "satisfaction scores" for each objective and factor into an overall satisfaction score. Individual and overall satisfaction scores for each pathway are mapped to the full range of feed compositions (proteins, carbohydrates, and lipids). A composition-based algal growth model was then implemented to perform an uncertainty analysis through Monte Carlo simulations. The impact on satisfaction scores from varying other key process model parameters, such as algae productivity, individual process yields, process operating parameters, and life cycle inventory uncertainty are highlighted in these select scenarios.born digitaldoctoral dissertationsengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.biofuelhydrothermal liquefactiontechno-economic analysisfuzzy set theoryalgaelife-cycle assessmentText