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Location Allocation of Biorefineries for a Switchgrass-Based Bioethanol Supply Chain Using Energy Consumption and Emissions

Author

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  • Seyed Ali Haji Esmaeili

    (Department of Management, Marketing and Operations, College of Business, Embry-Riddle Aeronautical University, Daytona Beach, FL 32114, USA)

  • Ahmad Sobhani

    (Department of Decision and Information Sciences, School of Business Administration, Oakland University, Rochester, MI 48309, USA)

  • Sajad Ebrahimi

    (Nicolais School Business, Wagner College, Staten Island, NY 10301, USA)

  • Joseph Szmerekovsky

    (Transportation, Logistics, and Finance Department, College of Business, North Dakota State University, Fargo, ND 58108, USA)

  • Alan Dybing

    (Upper Great Plains Transportation Institute, North Dakota State University, Fargo, ND 58108, USA)

  • Amin Keramati

    (School of Business, Widener University, Chester, PA 19013, USA)

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.

Suggested Citation

  • Seyed Ali Haji Esmaeili & Ahmad Sobhani & Sajad Ebrahimi & Joseph Szmerekovsky & Alan Dybing & Amin Keramati, 2023. "Location Allocation of Biorefineries for a Switchgrass-Based Bioethanol Supply Chain Using Energy Consumption and Emissions," Logistics, MDPI, vol. 7(1), pages 1-22, January.
  • Handle: RePEc:gam:jlogis:v:7:y:2023:i:1:p:5-:d:1038461
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    References listed on IDEAS

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    1. Mohamed Abdul Ghani, N. Muhammad Aslaam & Vogiatzis, Chrysafis & Szmerekovsky, Joseph, 2018. "Biomass feedstock supply chain network design with biomass conversion incentives," Energy Policy, Elsevier, vol. 116(C), pages 39-49.
    2. Haji Esmaeili, Seyed Ali & Sobhani, Ahmad & Szmerekovsky, Joseph & Dybing, Alan & Pourhashem, Ghasideh, 2020. "First-generation vs. second-generation: A market incentives analysis for bioethanol supply chains with carbon policies," Applied Energy, Elsevier, vol. 277(C).
    3. Hendricks, Aaron M. & Wagner, John E. & Volk, Timothy A. & Newman, David H. & Brown, Tristan R., 2016. "A cost-effective evaluation of biomass district heating in rural communities," Applied Energy, Elsevier, vol. 162(C), pages 561-569.
    4. Sultana, Arifa & Kumar, Amit, 2012. "Optimal siting and size of bioenergy facilities using geographic information system," Applied Energy, Elsevier, vol. 94(C), pages 192-201.
    5. Zhang, Fengli & Johnson, Dana M. & Johnson, Mark A., 2012. "Development of a simulation model of biomass supply chain for biofuel production," Renewable Energy, Elsevier, vol. 44(C), pages 380-391.
    6. Zhang, Jun & Osmani, Atif & Awudu, Iddrisu & Gonela, Vinay, 2013. "An integrated optimization model for switchgrass-based bioethanol supply chain," Applied Energy, Elsevier, vol. 102(C), pages 1205-1217.
    7. Fengli Zhang & Dana M. Johnson & Jinjiang Wang, 2015. "Life-Cycle Energy and GHG Emissions of Forest Biomass Harvest and Transport for Biofuel Production in Michigan," Energies, MDPI, vol. 8(4), pages 1-14, April.
    8. Kocoloski, Matt & Michael Griffin, W. & Scott Matthews, H., 2011. "Impacts of facility size and location decisions on ethanol production cost," Energy Policy, Elsevier, vol. 39(1), pages 47-56, January.
    9. Ren, Jingzheng & An, Da & Liang, Hanwei & Dong, Liang & Gao, Zhiqiu & Geng, Yong & Zhu, Qinghua & Song, Shaoxian & Zhao, Wenhui, 2016. "Life cycle energy and CO2 emission optimization for biofuel supply chain planning under uncertainties," Energy, Elsevier, vol. 103(C), pages 151-166.
    10. Kou, Nannan & Zhao, Fu, 2011. "Techno-economical analysis of a thermo-chemical biofuel plant with feedstock and product flexibility under external disturbances," Energy, Elsevier, vol. 36(12), pages 6745-6752.
    11. Ebrahimi, Sajad & Haji Esmaeili, Seyed Ali & Sobhani, Ahmad & Szmerekovsky, Joseph, 2022. "Renewable jet fuel supply chain network design: Application of direct monetary incentives," Applied Energy, Elsevier, vol. 310(C).
    12. Osmani, Atif & Zhang, Jun, 2013. "Stochastic optimization of a multi-feedstock lignocellulosic-based bioethanol supply chain under multiple uncertainties," Energy, Elsevier, vol. 59(C), pages 157-172.
    13. Gonela, Vinay & Zhang, Jun & Osmani, Atif & Onyeaghala, Raphael, 2015. "Stochastic optimization of sustainable hybrid generation bioethanol supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 1-28.
    14. James A. Larson & Tun‐Hsiang Yu & Burton C. English & Daniel F. Mooney & Chenguang Wang, 2010. "Cost evaluation of alternative switchgrass producing, harvesting, storing, and transporting systems and their logistics in the Southeastern USA," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 70(2), pages 184-200, August.
    15. Haji Esmaeili, Seyed Ali & Szmerekovsky, Joseph & Sobhani, Ahmad & Dybing, Alan & Peterson, Tim O., 2020. "Sustainable biomass supply chain network design with biomass switching incentives for first-generation bioethanol producers," Energy Policy, Elsevier, vol. 138(C).
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    1. Sojung Kim & Yeona Choi & Sumin Kim, 2023. "Simulation Modeling in Supply Chain Management Research of Ethanol: A Review," Energies, MDPI, vol. 16(21), pages 1-13, November.
    2. Sajad Ebrahimi & Joseph Szmerekovsky & Bahareh Golkar & Seyed Ali Haji Esmaeili, 2023. "Designing a Renewable Jet Fuel Supply Chain: Leveraging Incentive Policies to Drive Commercialization and Sustainability," Mathematics, MDPI, vol. 11(24), pages 1-20, December.

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