Abstract
This study presents comprehensive predictive models and an economic and environmental assessment of HTL for converting macroalgae into biofuels and valuable co-products. Predictive models were developed based on experimental kinetic data to simulate batch HTL of brown seaweed, capturing the yields of biocrude, gas, biochar, and water-soluble compounds as functions of key process variables, including temperature, time, pressure, and water-to-biomass ratio. Analysis of Variance (ANOVA) confirmed that temperature and residence time significantly affect biocrude yield, with an optimal yield of 23% achieved at 283°C, 200 bar, 54 minutes, and a 10:1 water-to-biomass ratio. The model’s predictive accuracy was validated with 91% agreement within a 95% prediction interval, highlighting its robustness for process optimization. Sensitivity analysis of reaction rate constants further identified key pathways for maximizing biocrude output. The TEA modeled a commercial-scale HTL process at 25 metric tons per hour, evaluating both a conventional and an intensified case. The intensified case, incorporating advanced separation technologies, achieved a significant reduction in operating costs compared to the conventional case, with a capital investment of $445 million and a 22% cost reduction. The MFSP varied widely with macroalgae feedstock prices, estimated between $11.42 to $25.31/GGE for the conventional case and $4.83 to $11.26/GGE for the intensified case. Co-producing alginate from macroalgae was proposed to enhance economic viability, meeting the Bioenergy Technology Office (BETO) 5 target of $3/GGE, with MPSP ranging from $2.85 to $7.24/kg in the conventional case and $0.44 to $4.25/kg in the intensified case. Integrating alginate production reduced operating costs by 79% and 22% for the conventional and intensified cases, respectively, providing a promising pathway toward commercially feasible biofuel production. The LCA of both HTL scenarios demonstrated that the intensified case generally achieved better environmental performance than the conventional setup, showing a 45% reduction in global warming potential (GWP) and lower respiratory health impacts. Compared to fossil-based fuels, both HTL cases exhibited a lower GWP than diesel and soybean biodiesel, though slightly higher than microalgae HTL fuel. Natural gas dependency significantly contributed to the Net Energy Ratio (NER), particularly in the conventional case, where it constituted nearly 90% of the energy input. Resource recovery through recycled nutrients provided environmental credits, contributing to an 18-22% reduction in ozone depletion potential and reducing GWP. These findings highlight the intensified HTL process as a viable pathway for sustainable biofuel production from macroalgae, with further opportunities to enhance sustainability by reducing fossil fuel inputs and increasing resource recovery. This study’s insights into process optimization, economic feasibility, and environmental impact provide a foundation for advancing HTL as a competitive renewable fuel technology.
Date of publication
Fall 12-12-2024
Document Type
Thesis
Language
english
Persistent identifier
http://hdl.handle.net/10950/4795
Committee members
Fernando Resende, Ph.D. ,Aaditya Khanal, Ph.D. , Mohammad Biswas, Ph.D.
Degree
Masters in Mechanical Engineering
Recommended Citation
Asama, Micheal O., "Predictive Modeling and Sustainability Assessment of Hydrothermal Liquefaction of Seaweeds: A Techno-Economic and Life Cycle Analysis Approach" (2024). Mechanical Engineering Theses. Paper 40.
http://hdl.handle.net/10950/4795