Abstract
Biorefineries that plan to use switchgrass exclusively will encounter year-to-year variability in feedstock production. The economic success of the biorefinery will depend in part on the ability of the management team to strategically identify land for conversion from current use to the production of switchgrass enabling a flow of feedstock for the life of the biorefinery. The objective of this research is to determine the optimal quality, quantity, and location of land to lease while considering the spatial and temporal variability of switchgrass biomass yield. A calibrated biophysical simulation model was used to simulate switchgrass biomass yields for 50 years based on historical weather data from 1962 to 2011, for three land capability classes for each of 30 counties. Mathematical programming models were constructed and solved to determine the optimal leasing scheme for each of three strategies for a biorefinery that requires 2,000 Mg/day. As expected, a model based on the assumption that the average yield would be obtained in each year finds that production from land identified for leasing would be insufficient to fulfill the biorefinery’s needs in half of the years. In the absence of other sources of biomass, the feedstock shortage would require forced idling of the biorefinery for an average of 29.5 days during these years. Results of a strategy of leasing sufficient land to cover feedstock needs in the worst year from among 50 years for which data are available are compared to that of a strategy enabling year-to-year storage.
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Acknowledgments
Funding for this project was provided by the USDA-NIFA, USDA-DOE Biomass Research and Development Initiative, Grant No. 2009-10006-06070; by the USDA National Institute of Food and Agriculture, Hatch grant number H-2824; the Jean & Patsy Neustadt Chair; and by the Oklahoma Agricultural Experiment Station. Support does not constitute an endorsement of the findings expressed.
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Debnath, D., Epplin, F.M. & Stoecker, A.L. Managing Spatial and Temporal Switchgrass Biomass Yield Variability. Bioenerg. Res. 7, 946–957 (2014). https://doi.org/10.1007/s12155-014-9436-6
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DOI: https://doi.org/10.1007/s12155-014-9436-6