IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v294y2021ics0306261921004232.html
   My bibliography  Save this article

The nth-plant scenario for blended feedstock conversion and preprocessing nationwide: Biorefineries and depots

Author

Listed:
  • Hossain, Tasmin
  • Jones, Daniela
  • Hartley, Damon
  • Griffel, L. Michael
  • Lin, Yingqian
  • Burli, Pralhad
  • Thompson, David N.
  • Langholtz, Matthew
  • Davis, Maggie
  • Brandt, Craig

Abstract

The sustainability of the biofuel industry depends on the development of a mature conversion technology on a national level that can take advantage of the economies of scale: the nth-plant. Defining the future location and supply logistics of conversion plants is imperative to ultimately transform the nation’s renewable biomass resources into cost-competitive, high-performance feedstock for production of biofuels and bioproducts. Since the US has put restrictions on production levels of conventional biofuels from edible resources, the nation needs to plan for the widespread accessibility and development of the cellulosic biofuel scenario. Conventional feedstock supply systems will be unable to handle cellulosic biomass nationwide, making it essential to expand the industry with an advanced feedstock supply system incorporating a distributed network of preprocessing depots and conversion plants, or biorefineries. Current studies are mostly limited to designing supply systems for specific regions of the country. We developed a national database with potential locations for depots and biorefineries to meet the nation’s target demand of cellulosic biofuel. Blended feedstock with switchgrass and corn stover (harvested by either a two- or three-pass method) are considered in a Mixed Integer Linear Programming model to deliver on-spec biomass that considers both, a desired quantity and quality at the biorefinery. The model solves for a network of varying size depots that supply to biorefineries of 725,000 dry tons/year. A total delivered feedstock cost that is less than $79.07/dry tons (2016$) is evaluated for years 2022, 2030, and 2040. In 2022, 124 depots and 59 biorefineries could be supplied with 42.8 million dt of corn stover and switchgrass. In 2030 and 2040, the total accessible biomass could increase to 215% and 393% respectively when compared to 2022. However, an $8/dry tons reduction in targeted delivery cost could reduce total accessible biomass by 67%. Kansas, Nebraska, South Dakota and Texas were identified as potential states with a strong biofuel economy given that they had six or more biorefineries located in all scenarios. In some scenarios, Colorado, Alabama, Georgia, Minnesota, Mississippi and South Carolina would greatly benefit from a depot network as these could only deliver to a biorefinery in a nearby state. To elaborate the impact of a nationwide consideration, the findings were compared with existing literature for different US regions. We also present results for biorefinery capacities that are double, triple and quadruple in size.

Suggested Citation

  • Hossain, Tasmin & Jones, Daniela & Hartley, Damon & Griffel, L. Michael & Lin, Yingqian & Burli, Pralhad & Thompson, David N. & Langholtz, Matthew & Davis, Maggie & Brandt, Craig, 2021. "The nth-plant scenario for blended feedstock conversion and preprocessing nationwide: Biorefineries and depots," Applied Energy, Elsevier, vol. 294(C).
  • Handle: RePEc:eee:appene:v:294:y:2021:i:c:s0306261921004232
    DOI: 10.1016/j.apenergy.2021.116946
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921004232
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2021.116946?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. Bai, Yun & Hwang, Taesung & Kang, Seungmo & Ouyang, Yanfeng, 2011. "Biofuel refinery location and supply chain planning under traffic congestion," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 162-175, January.
    2. Roni, Mohammad S. & Thompson, David N. & Hartley, Damon S., 2019. "Distributed biomass supply chain cost optimization to evaluate multiple feedstocks for a biorefinery," Applied Energy, Elsevier, vol. 254(C).
    3. Ng, Rex T.L. & Maravelias, Christos T., 2017. "Design of biofuel supply chains with variable regional depot and biorefinery locations," Renewable Energy, Elsevier, vol. 100(C), pages 90-102.
    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. Piradee Jusakulvijit & Alberto Bezama & Daniela Thrän, 2022. "An Integrated Assessment of GIS-MCA with Logistics Analysis for an Assessment of a Potential Decentralized Bioethanol Production System Using Distributed Agricultural Residues in Thailand," Sustainability, MDPI, vol. 14(16), pages 1-24, August.
    2. Hossain, Tasmin & Jones, Daniela S. & Hartley, Damon S. & Thompson, David N. & Langholtz, Matthew & Davis, Maggie, 2022. "Nth-plant scenario for forest resources and short rotation woody crops: Biorefineries and depots in the contiguous US," Applied Energy, Elsevier, vol. 325(C).
    3. Conteratto, Caroline & Artuzo, Felipe Dalzotto & Benedetti Santos, Omar Inácio & Talamini, Edson, 2021. "Biorefinery: A comprehensive concept for the sociotechnical transition toward bioeconomy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).

    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. Ibrahim M. Hezam & Fausto Cavallaro & Jyoti Lakshmi & Pratibha Rani & Subhanshu Goyal, 2023. "Biofuel Production Plant Location Selection Using Integrated Picture Fuzzy Weighted Aggregated Sum Product Assessment Framework," Sustainability, MDPI, vol. 15(5), pages 1-19, February.
    2. 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.
    3. Ge, Yuntian & Li, Lin & Yun, Lingxiang, 2021. "Modeling and economic optimization of cellulosic biofuel supply chain considering multiple conversion pathways," Applied Energy, Elsevier, vol. 281(C).
    4. Hossain, Tasmin & Jones, Daniela S. & Hartley, Damon S. & Thompson, David N. & Langholtz, Matthew & Davis, Maggie, 2022. "Nth-plant scenario for forest resources and short rotation woody crops: Biorefineries and depots in the contiguous US," Applied Energy, Elsevier, vol. 325(C).
    5. Kheybari, Siamak & Kazemi, Mostafa & Rezaei, Jafar, 2019. "Bioethanol facility location selection using best-worst method," Applied Energy, Elsevier, vol. 242(C), pages 612-623.
    6. 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.
    7. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    8. Roni, Md.S. & Eksioglu, Sandra D. & Searcy, Erin & Jha, Krishna, 2014. "A supply chain network design model for biomass co-firing in coal-fired power plants," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 61(C), pages 115-134.
    9. Andrzej Bochniak & Monika Stoma, 2021. "Estimating the Optimal Location for the Storage of Pellet Surplus," Energies, MDPI, vol. 14(20), pages 1-16, October.
    10. Gilani, H. & Sahebi, H. & Oliveira, Fabricio, 2020. "Sustainable sugarcane-to-bioethanol supply chain network design: A robust possibilistic programming model," Applied Energy, Elsevier, vol. 278(C).
    11. Li, Yu & Kesharwani, Rajkamal & Sun, Zeyi & Qin, Ruwen & Dagli, Cihan & Zhang, Meng & Wang, Donghai, 2020. "Economic viability and environmental impact investigation for the biofuel supply chain using co-fermentation technology," Applied Energy, Elsevier, vol. 259(C).
    12. Dekker, Rommert & Bloemhof, Jacqueline & Mallidis, Ioannis, 2012. "Operations Research for green logistics – An overview of aspects, issues, contributions and challenges," European Journal of Operational Research, Elsevier, vol. 219(3), pages 671-679.
    13. Huang, Endai & Zhang, Xiaolei & Rodriguez, Luis & Khanna, Madhu & de Jong, Sierk & Ting, K.C. & Ying, Yibin & Lin, Tao, 2019. "Multi-objective optimization for sustainable renewable jet fuel production: A case study of corn stover based supply chain system in Midwestern U.S," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    14. Maung, Thein A. & Gustafson, Cole R. & Saxowsky, David M. & Nowatzki, John & Miljkovic, Tatjana & Ripplinger, David, 2013. "The logistics of supplying single vs. multi-crop cellulosic feedstocks to a biorefinery in southeast North Dakota," Applied Energy, Elsevier, vol. 109(C), pages 229-238.
    15. Calvert, K. & Pearce, J.M. & Mabee, W.E., 2013. "Toward renewable energy geo-information infrastructures: Applications of GIScience and remote sensing that build institutional capacity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 416-429.
    16. Xiaoguang Chen & Hayri Önal, 2014. "An Economic Analysis of the Future U.S. Biofuel Industry, Facility Location, and Supply Chain Network," Transportation Science, INFORMS, vol. 48(4), pages 575-591, November.
    17. Ouyang, Yanfeng & Wang, Zhaodong & Yang, Hai, 2015. "Facility location design under continuous traffic equilibrium," Transportation Research Part B: Methodological, Elsevier, vol. 81(P1), pages 18-33.
    18. Guo, Jian-Xin & Tan, Xianchun & Gu, Baihe & Zhu, Kaiwei, 2022. "Integration of supply chain management of hybrid biomass power plant with carbon capture and storage operation," Renewable Energy, Elsevier, vol. 190(C), pages 1055-1065.
    19. Bengtsson, Selma & Fridell, Erik & Andersson, Karin, 2012. "Environmental assessment of two pathways towards the use of biofuels in shipping," Energy Policy, Elsevier, vol. 44(C), pages 451-463.
    20. Taesung Hwang & Yanfeng Ouyang, 2015. "Urban Freight Truck Routing under Stochastic Congestion and Emission Considerations," Sustainability, MDPI, vol. 7(6), pages 1-16, May.

    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:appene:v:294:y:2021:i:c:s0306261921004232. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.