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Spatial modeling framework for bioethanol plant siting and biofuel production potential in the U.S

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  • Sharma, B.
  • Birrell, S.
  • Miguez, F.E.

Abstract

Because of rising fuel prices and increasing energy demand, bioethanol has been recognized as an important future renewable energy source. The goals and mandates developed for renewable fuel production will require construction of several bioethanol plants throughout the U.S. Using high-resolution geospatial data from Geographic Information Systems-Multi Criteria Evaluation (GIS-MCE) a biorefinery suitability model has been developed for identifying feasible sites and appropriate biofuel production capacity in the U.S. The biomass feedstocks considered for analysis were switchgrass, miscanthus and corn stover. We conducted a spatial exclusion and preference GIS analysis subjected to environmental and infrastructure criteria combined with biomass yield estimates and identified 164 basic sites and 17 co-location scenarios. Biorefineries using miscanthus feedstock could produce biofuel satisfying a significant portion of the U.S. mandate. This national-scale assessment enhances strategic decision-making capabilities and understanding of spatial distribution of biorefineries.

Suggested Citation

  • Sharma, B. & Birrell, S. & Miguez, F.E., 2017. "Spatial modeling framework for bioethanol plant siting and biofuel production potential in the U.S," Applied Energy, Elsevier, vol. 191(C), pages 75-86.
    • Handle: RePEc:eee:appene:v:191:y:2017:i:c:p:75-86
    DOI: 10.1016/j.apenergy.2017.01.015
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    Cited by:

    1. Xu, Youjie & Wang, Donghai, 2017. "Integrating starchy substrate into cellulosic ethanol production to boost ethanol titers and yields," Applied Energy, Elsevier, vol. 195(C), pages 196-203.
    2. Lovrak, Ana & Pukšec, Tomislav & Duić, Neven, 2020. "A Geographical Information System (GIS) based approach for assessing the spatial distribution and seasonal variation of biogas production potential from agricultural residues and municipal biowaste," Applied Energy, Elsevier, vol. 267(C).
    3. Jayarathna, Lasinidu & Kent, Geoff & O’Hara, Ian & Hobson, Philip, 2022. "Geographical information system based fuzzy multi criteria analysis for sustainability assessment of biomass energy plant siting: A case study in Queensland, Australia," Land Use Policy, Elsevier, vol. 114(C).
    4. Elizabeth A. Moore & Callie W. Babbitt & Brian Tomaszewski & Anna Christina Tyler, 2020. "Spatial perspectives enhance modeling of nanomaterial risks," Journal of Industrial Ecology, Yale University, vol. 24(4), pages 855-870, August.
    5. Maryam Roudneshin & Amanda Sosa, 2024. "Optimising Agricultural Waste Supply Chains for Sustainable Bioenergy Production: A Comprehensive Literature Review," Energies, MDPI, vol. 17(11), pages 1-23, May.
    6. Chakraborty, Abhishek & Biswal, Anima & Pandey, Varun & Shadab, Syed & Kalyandeep, K. & Murthy, C.S. & Seshasai, M.V.R. & Rao, P.V.N. & Jain, Niveta & Sehgal, V.K. & Kaushik, Nirmala & Singh, Sanjay &, 2022. "Developing a spatial information system of biomass potential from crop residues over India: A decision support for planning and establishment of biofuel/biomass power plant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    7. Ida Nordin & Katarina Elofsson & Torbjörn Jansson, 2022. "Optimal localisation of agricultural biofuel production facilities and feedstock: a Swedish case study," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 49(4), pages 910-941.
    8. Ng, Rex T.L. & Kurniawan, Daniel & Wang, Hua & Mariska, Brian & Wu, Wenzhao & Maravelias, Christos T., 2018. "Integrated framework for designing spatially explicit biofuel supply chains," Applied Energy, Elsevier, vol. 216(C), pages 116-131.

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