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Predicting The Future: Determining Biomass Production Of New Crops For Bioenergy

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Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Projecting the extent at which a bioenergy industry will develop is a function of many variables. Quantifying the expected total source of energy is fundamental to assessing how much and in what form bioenergy might take shape in a particular region. Production is governed by land, yields, and the degree at which farmers are willing to begin growing bioenergy crops. Reasonable bounds can be calculated on the first two variables using existing data on agricultural production and energy densities of crops. The later component, which incorporates decision making by many different individuals, is more challenging. Probabilistic measures on willingness of producers can be accomplished through theory and empirically-based results on adoption of new technology. Contributions from the social sciences can inform the shape of adoption curves, and help estimate changes over time. However, projections of annual harvests are confounded by fluctuations in expected profitability. Supposing different scenarios of market forces, this research estimates potential aggregate production of biomass according to different levels of agricultural incentives. Outcomes from this initial analysis can be refined by applying other available data on agricultural management. For example, previously introduced crops to a region can indicate profitability versus readiness of farmers to take risks with new agricultural practices. This paper examines a case study of the potential for switchgrass to be grown for energy. With a model from which to build probabilistic outcomes, total biomass production from year to year can assist in identifying pathways to efficient and more complete realization of a bioenergy industry.

Ben Sharp
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Conference Proceeding
Full Citation
Ben Sharp and Shelie Miller. “Predicting The Future: Determining Biomass Production Of New Crops For Bioenergy.” 6th International Conference of the International Society for Industrial Ecology (ISIE) Proceedings. Berkeley, CA, June 7-10 2011, Abstract #172.