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Displaying 41 - 44 of 44

The location of ethanol plants is determined by infrastructure, product and input markets, fiscal attributes of local communities, and state and federal incentives. This empirical
analysis uses probit regression along with spatial clustering methods to analyze investment activity of ethanol plants at the county level for the lower U.S. 48 states from 2000 to 2007.
The availability of feedstock dominates the site selection decision. Other factors, such as access to navigable rivers or railroads, product markets, producer credit and excise tax

Author(s):
D.M. Lambert

A method is presented, which estimates the potential for power production from agriculture residues. A GIS decision support system (DSS) has been developed, which implements the method and provides the tools to identify the geographic distribution of the economically exploited biomass potential. The procedure introduces a four level analysis to determine the
theoretical, available, technological and economically exploitable potential. The DSS handles all possible restrictions and

Author(s):
D. Voivontas

Ethanol production using corn grain has exploded in the Upper Midwest. This new demand for corn, and the new opportunities
for value-added processing and cattle production in rural communities, has created the best economic development
opportunity in the Corn Belt states in a generation or more. Ethanol demand has increased rapidly recently because of favorable
economics of ethanol vs. gasoline, and the need for a performance enhancer to replace MTBE (methyl tertiary-butyl ether)

Author(s):
Dennis Keeney

The model is a vehicle fuel-cycle model for transportation systems. The model provides a set of outcomes that would involve feedstock production, biorefinery production, storage and consumer demand as the complete fuel-cycle. The data is internal to the model, but might be adaptive to different biofuels specifications. This model was developed by the Energy Systems Division at Argonne National Laboratory.

Author(s):
Michael Wang
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.