Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/310309 
Year of Publication: 
2023
Citation: 
[Journal:] Logistics [ISSN:] 2305-6290 [Volume:] 7 [Issue:] 1 [Article No.:] 5 [Year:] 2023 [Pages:] 1-22
Publisher: 
MDPI, Basel
Abstract: 
Background: Due to the growing demand for energy and environmental issues related to using fossil fuels, it is becoming tremendously important to find alternative energy sources. Bioethanol produced from switchgrass is considered as one of the best alternatives to fossil fuels. Methods: This study develops a two-stage supply chain modeling approach that first determines feasible locations for constructing switchgrass-based biorefineries in the state of North Dakota by using Geographic Information Systems (GIS) analysis. In the second stage, the profit of the corresponding switchgrass-based bioethanol supply chain is maximized by developing a mixed-integer linear program that aims to commercialize the bioethanol production while impacts of energy use and carbon emission costs on the supply chain decisions and siting of biorefineries are included. Results: The numerical results show that carbon emissions and energy consumption penalties affect optimal biorefinery selections and supply chain decisions. Conclusions: We conclude that there is no need to penalize both emissions and energy use simultaneously to achieve desirable environmental benefits, otherwise, the supply chain becomes non-profitable. Moreover, imposing emissions or energy consumption penalties makes the optimization model closer to supply sources while having higher land rental costs. Such policies would promote sustainable second-generation biomass production, thus decreasing reliance on fossil fuels.
Subjects: 
biomass supply chain
emissions
energy use
GIS
optimization
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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