Abstract
A microalgae-based biofuel supply chain was designed for different geographic regions, considering the local environmental conditions of sunlight, temperature, and available resources of water and CO2. The supply chain was designed in three distinct areas, Texas, U.S., Northern Territory of Australia, and La Guajira, Colombia, selected through a global analysis of suitable land based on GIS. A three-stage design framework developed in our previous research was improved to include a biomass productivity estimation model based on operating data provided by Algenol, a new photobioreactor (PBR) cultivation technology, direct air capture of CO2 as a feedstock option, and functional-unit based optimization. The framework focuses on the comparison of two major cultivation platforms, open raceway pond (ORP) and photobioreactor (PBR) using a net present value metric. A mixed-integer fractional programming (MIFP) model was formulated to make multi-period strategic and tactical decisions related to the supply chain design and operation under the objective of minimizing the total cost per gasoline gallon equivalent of products (GGE). Under the same assumptions, the supply chain was designed for seven years and the cost was estimated to be $15.5, $13.5, and $14.0/GGE for the U.S., Colombia, and Australia, respectively. While various processing pathways were considered in the model, only a single pathway involving PBR, an algae strain AB1166, and hydrothermal lique-faction was selected in all regions owing to its cost-efficiency. Direct air capture and hypothetical saline water species scenarios were examined to analyze the effect of alternative resource sources on the supply chain design and economics.
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Acknowledgements
This works was supported by the Carbon-to-X (C2X) R&D project (project no. 2020M3H7A1096361) sponsored by the National Research Foundation (NRF) of the Ministry of Science and ICT.
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Kang, S., Realff, M.J., Yuan, Y. et al. Global evaluation of economics of microalgae-based biofuel supply chain using GIS-based framework. Korean J. Chem. Eng. 39, 1524–1541 (2022). https://doi.org/10.1007/s11814-021-1053-4
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DOI: https://doi.org/10.1007/s11814-021-1053-4