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Modeling net energy balance of ethanol production from native warm season grasses

Author

Listed:
  • Illukpitiya, Prabodh
  • Reddy, K.C.
  • Bansal, Ankit

Abstract

There has been an increasing interest in the use of perennial grasses as potential feedstock for ethanol production. The characteristics which make perennial grasses attractive for bioenergy feedstock development initiative are their high yield potential and the high contents of lignin and cellulose. The objective of the study is to model energy input and output and simulate Net Energy Value (NEV) of producing ethanol from native warm season grasses. According to simulated results, the mean NEV of ethanol production from native warm season grasses considered in the analysis was positive. Mean NEV for switchgrass and eastern gammagrass was higher compared to Indiangrass and big bluestem. Although the probability of having positive NEV is high, there is a risk of having negative energy balance under low output scenarios.

Suggested Citation

  • Illukpitiya, Prabodh & Reddy, K.C. & Bansal, Ankit, 2017. "Modeling net energy balance of ethanol production from native warm season grasses," Energy Economics, Elsevier, vol. 64(C), pages 346-352.
    • Handle: RePEc:eee:eneeco:v:64:y:2017:i:c:p:346-352
    DOI: 10.1016/j.eneco.2017.04.008
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    References listed on IDEAS

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    3. Bansal, Ankit & Illukpitiya, Prabodh & Tegegne, Fisseha & Singh, Surendra P., 2016. "Energy efficiency of ethanol production from cellulosic feedstock," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 141-146.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Biofuel; Native grass; Net energy; Probability distribution; Simulation;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • Q16 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - R&D; Agricultural Technology; Biofuels; Agricultural Extension Services
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q57 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Ecological Economics

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