IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v160y2020ics0040162520310532.html
   My bibliography  Save this article

Modelling the impact of climate change risk on bioethanol supply chains

Author

Listed:
  • Ghadge, Abhijeet
  • van der Werf, Sjoerd
  • Er Kara, Merve
  • Goswami, Mohit
  • Kumar, Pankaj
  • Bourlakis, Michael

Abstract

The availability of bioethanol, a promising renewable alternative to fossil fuels depends on the supply of biomass produced from agricultural resources. The study attempts a system dynamics modelling approach to explore the implications of greenhouse gas concentration trajectories associated with climate change on bioethanol supply chains. Eight different climate change scenarios are simulated spanning over a 40-year horizon to predict biomass yield and bioethanol availability, by considering first generation (corn) and second generation (switchgrass) ethanol feedstocks. The developed model is used to assess the extent of potential disruptions resulting from global warming. Cascading effect of climate change risk is evident through decreased yield and production, and increased shortages at end customer in the bioethanol supply network. The results indicate that, if climate change risk is not adequately mitigated and current used source of ethanol (corn) continues to be leveraged, the bioethanol availability may decrease by one-fourth by the year 2060. The comparative study encourages exploring the increased use of switchgrass as a sustainable feedstock for renewable energy. Developed insights support identifying effective climate change mitigation policies and sustainable investment decisions for the reduction in carbon emissions.

Suggested Citation

  • Ghadge, Abhijeet & van der Werf, Sjoerd & Er Kara, Merve & Goswami, Mohit & Kumar, Pankaj & Bourlakis, Michael, 2020. "Modelling the impact of climate change risk on bioethanol supply chains," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
    • Handle: RePEc:eee:tefoso:v:160:y:2020:i:c:s0040162520310532
    DOI: 10.1016/j.techfore.2020.120227
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162520310532
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2020.120227?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Mafakheri, Fereshteh & Nasiri, Fuzhan, 2014. "Modeling of biomass-to-energy supply chain operations: Applications, challenges and research directions," Energy Policy, Elsevier, vol. 67(C), pages 116-126.
    2. 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.
    3. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.
    4. Awudu, Iddrisu & Zhang, Jun, 2012. "Uncertainties and sustainability concepts in biofuel supply chain management: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1359-1368.
    5. Abhijeet Ghadge & Hendrik Wurtmann & Stefan Seuring, 2020. "Managing climate change risks in global supply chains: a review and research agenda," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 44-64, January.
    6. Azadeh, Ali & Vafa Arani, Hamed, 2016. "Biodiesel supply chain optimization via a hybrid system dynamics-mathematical programming approach," Renewable Energy, Elsevier, vol. 93(C), pages 383-403.
    7. Ritesh Ojha & Abhijeet Ghadge & Manoj Kumar Tiwari & Umit S. Bititci, 2018. "Bayesian network modelling for supply chain risk propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 56(17), pages 5795-5819, September.
    8. Jacques, David & Fox, Glenn & White, Peter, 2018. "Farm level economic analysis of subsurface drip irrigation in Ontario corn production," Agricultural Water Management, Elsevier, vol. 203(C), pages 333-343.
    9. Tembo, Gelson & Epplin, Francis M. & Huhnke, Raymond L., 2003. "Integrative Investment Appraisal of a Lignocellulosic Biomass-to-Ethanol Industry," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 28(3), pages 1-23, December.
    10. Nunes, L.J.R. & Causer, T.P. & Ciolkosz, D., 2020. "Biomass for energy: A review on supply chain management models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    11. World Commission on Environment and Development,, 1987. "Our Common Future," OUP Catalogue, Oxford University Press, number 9780192820808, Decembrie.
    12. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    13. 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.
    14. Boris Sokolov & Dmitry Ivanov & Alexandre Dolgui & Alexander Pavlov, 2016. "Structural quantification of the ripple effect in the supply chain," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 152-169, January.
    15. Tadeusz W. Patzek, 2010. "A Probabilistic Analysis of the Switchgrass Ethanol Cycle," Sustainability, MDPI, vol. 2(10), pages 1-37, September.
    16. Sharma, B. & Ingalls, R.G. & Jones, C.L. & Khanchi, A., 2013. "Biomass supply chain design and analysis: Basis, overview, modeling, challenges, and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 608-627.
    17. Rentizelas, Athanasios A. & Tolis, Athanasios J. & Tatsiopoulos, Ilias P., 2009. "Logistics issues of biomass: The storage problem and the multi-biomass supply chain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(4), pages 887-894, May.
    18. Huang, Kefeng & Won, Wangyun & Barnett, Kevin J. & Brentzel, Zachary J. & Alonso, David M. & Huber, George W. & Dumesic, James A. & Maravelias, Christos T., 2018. "Improving economics of lignocellulosic biofuels: An integrated strategy for coproducing 1,5-pentanediol and ethanol," Applied Energy, Elsevier, vol. 213(C), pages 585-594.
    19. Balat, Mustafa & Balat, Havva, 2009. "Recent trends in global production and utilization of bio-ethanol fuel," Applied Energy, Elsevier, vol. 86(11), pages 2273-2282, November.
    20. Zabed, H. & Sahu, J.N. & Suely, A. & Boyce, A.N. & Faruq, G., 2017. "Bioethanol production from renewable sources: Current perspectives and technological progress," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 475-501.
    21. Bibi, Riaz & Ahmad, Zulfiqar & Imran, Muhammad & Hussain, Sabir & Ditta, Allah & Mahmood, Shahid & Khalid, Azeem, 2017. "Algal bioethanol production technology: A trend towards sustainable development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 976-985.
    22. Mohammad S. Roni & Sandra D. Eksioglu & Kara G. Cafferty & Jacob J. Jacobson, 2017. "A multi-objective, hub-and-spoke model to design and manage biofuel supply chains," Annals of Operations Research, Springer, vol. 249(1), pages 351-380, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gebhardt, Maximilian & Spieske, Alexander & Birkel, Hendrik, 2022. "The future of the circular economy and its effect on supply chain dependencies: Empirical evidence from a Delphi study," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    2. Irfan, Muhammad & Elavarasan, Rajvikram Madurai & Ahmad, Munir & Mohsin, Muhammad & Dagar, Vishal & Hao, Yu, 2022. "Prioritizing and overcoming biomass energy barriers: Application of AHP and G-TOPSIS approaches," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    3. Ye, Liping, 2022. "The effect of climate news risk on uncertainties," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    4. Muneeb, Syed Mohd & Asim, Zainab & Hajiaghaei-Keshteli, Mostafa & Abbas, Haidar, 2023. "A multi-objective integrated supplier selection-production-distribution model for re-furbished products: Towards a circular economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    5. Liu, Xiaoqin & Wojewodzki, Michal & Cai, Yifei & Sharma, Satish, 2023. "The dynamic relationships between carbon prices and policy uncertainties," Technological Forecasting and Social Change, Elsevier, vol. 188(C).
    6. Sujith S. Ratnayake & Lalit Kumar & Punchi B. Dharmasena & Harsha K. Kadupitiya & Champika S. Kariyawasam & Danny Hunter, 2021. "Sustainability of Village Tank Cascade Systems of Sri Lanka: Exploring Cascade Anatomy and Socio-Ecological Nexus for Ecological Restoration Planning," Challenges, MDPI, vol. 12(2), pages 1-23, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ba, Birome Holo & Prins, Christian & Prodhon, Caroline, 2016. "Models for optimization and performance evaluation of biomass supply chains: An Operations Research perspective," Renewable Energy, Elsevier, vol. 87(P2), pages 977-989.
    2. Mirkouei, Amin & Haapala, Karl R. & Sessions, John & Murthy, Ganti S., 2017. "A review and future directions in techno-economic modeling and optimization of upstream forest biomass to bio-oil supply chains," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 15-35.
    3. Malladi, Krishna Teja & Sowlati, Taraneh, 2018. "Biomass logistics: A review of important features, optimization modeling and the new trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 587-599.
    4. Martinez-Valencia, Lina & Garcia-Perez, Manuel & Wolcott, Michael P., 2021. "Supply chain configuration of sustainable aviation fuel: Review, challenges, and pathways for including environmental and social benefits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    5. Espinoza Pérez, Andrea Teresa & Camargo, Mauricio & Narváez Rincón, Paulo César & Alfaro Marchant, Miguel, 2017. "Key challenges and requirements for sustainable and industrialized biorefinery supply chain design and management: A bibliographic analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 350-359.
    6. Md Abu Helal & Nathaniel Anderson & Yu Wei & Matthew Thompson, 2023. "A Review of Biomass-to-Bioenergy Supply Chain Research Using Bibliometric Analysis and Visualization," Energies, MDPI, vol. 16(3), pages 1-32, January.
    7. Leonel J. R. Nunes & Sandra Silva, 2023. "Optimization of the Residual Biomass Supply Chain: Process Characterization and Cost Analysis," Logistics, MDPI, vol. 7(3), pages 1-21, August.
    8. De Meyer, Annelies & Cattrysse, Dirk & Van Orshoven, Jos, 2016. "Considering biomass growth and regeneration in the optimisation of biomass supply chains," Renewable Energy, Elsevier, vol. 87(P2), pages 990-1002.
    9. De Meyer, Annelies & Cattrysse, Dirk & Van Orshoven, Jos, 2015. "A generic mathematical model to optimise strategic and tactical decisions in biomass-based supply chains (OPTIMASS)," European Journal of Operational Research, Elsevier, vol. 245(1), pages 247-264.
    10. 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).
    11. Cambero, Claudia & Sowlati, Taraneh, 2014. "Assessment and optimization of forest biomass supply chains from economic, social and environmental perspectives – A review of literature," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 62-73.
    12. Razm, Sobhan & Brahimi, Nadjib & Hammami, Ramzi & Dolgui, Alexandre, 2023. "A production planning model for biorefineries with biomass perishability and biofuel transformation," International Journal of Production Economics, Elsevier, vol. 258(C).
    13. Rendon-Sagardi, Miguel A. & Sanchez-Ramirez, Cuauhtemoc & Cortes-Robles, Guillermo & Alor-Hernandez, Giner & Cedillo-Campos, Miguel G., 2014. "Dynamic analysis of feasibility in ethanol supply chain for biofuel production in Mexico," Applied Energy, Elsevier, vol. 123(C), pages 358-367.
    14. Mosayeb Dashtpeyma & Reza Ghodsi, 2021. "Forest Biomass and Bioenergy Supply Chain Resilience: A Systematic Literature Review on the Barriers and Enablers," Sustainability, MDPI, vol. 13(12), pages 1-21, June.
    15. Garvey, Myles D. & Carnovale, Steven, 2020. "The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation," International Journal of Production Economics, Elsevier, vol. 228(C).
    16. Zailan, Roziah & Lim, Jeng Shiun & Manan, Zainuddin Abdul & Alwi, Sharifah Rafidah Wan & Mohammadi-ivatloo, Behnam & Jamaluddin, Khairulnadzmi, 2021. "Malaysia scenario of biomass supply chain-cogeneration system and optimization modeling development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    17. Jensen, Ida Græsted & Münster, Marie & Pisinger, David, 2017. "Optimizing the supply chain of biomass and biogas for a single plant considering mass and energy losses," European Journal of Operational Research, Elsevier, vol. 262(2), pages 744-758.
    18. Seyedmohsen Hosseini & Dmitry Ivanov, 2022. "A new resilience measure for supply networks with the ripple effect considerations: a Bayesian network approach," Annals of Operations Research, Springer, vol. 319(1), pages 581-607, December.
    19. Moretti, Luca & Milani, Mario & Lozza, Giovanni Gustavo & Manzolini, Giampaolo, 2021. "A detailed MILP formulation for the optimal design of advanced biofuel supply chains," Renewable Energy, Elsevier, vol. 171(C), pages 159-175.
    20. Bairamzadeh, Samira & Saidi-Mehrabad, Mohammad & Pishvaee, Mir Saman, 2018. "Modelling different types of uncertainty in biofuel supply network design and planning: A robust optimization approach," Renewable Energy, Elsevier, vol. 116(PA), pages 500-517.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:tefoso:v:160:y:2020:i:c:s0040162520310532. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.