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Title: Biofuel impacts on water.

Abstract

Sandia National Laboratories and General Motors Global Energy Systems team conducted a joint biofuels systems analysis project from March to November 2008. The purpose of this study was to assess the feasibility, implications, limitations, and enablers of large-scale production of biofuels. 90 billion gallons of ethanol (the energy equivalent of approximately 60 billion gallons of gasoline) per year by 2030 was chosen as the book-end target to understand an aggressive deployment. Since previous studies have addressed the potential of biomass but not the supply chain rollout needed to achieve large production targets, the focus of this study was on a comprehensive systems understanding the evolution of the full supply chain and key interdependencies over time. The supply chain components examined in this study included agricultural land use changes, production of biomass feedstocks, storage and transportation of these feedstocks, construction of conversion plants, conversion of feedstocks to ethanol at these plants, transportation of ethanol and blending with gasoline, and distribution to retail outlets. To support this analysis, we developed a 'Seed to Station' system dynamics model (Biofuels Deployment Model - BDM) to explore the feasibility of meeting specified ethanol production targets. The focus of this report is water and its linkagemore » to broad scale biofuel deployment.« less

Authors:
; ;
Publication Date:
Research Org.:
Sandia National Laboratories
Sponsoring Org.:
USDOE
OSTI Identifier:
1030402
Report Number(s):
SAND2011-0375
TRN: US201201%%310
DOE Contract Number:
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
02 PETROLEUM; 09 BIOMASS FUELS; AVAILABILITY; BIOFUELS; BIOMASS; CHAINS; CONSTRUCTION; DISTRIBUTION; ENERGY SYSTEMS; ETHANOL; GASOLINE; LAND USE; MOTORS; PRODUCTION; SANDIA NATIONAL LABORATORIES; STORAGE; SYSTEMS ANALYSIS; TARGETS; WATER

Citation Formats

Tidwell, Vincent Carroll, Malczynski, Leonard A., and Sun, Amy Cha-Tien. Biofuel impacts on water.. United States: N. p., 2011. Web. doi:10.2172/1030402.
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Tidwell, Vincent Carroll, Malczynski, Leonard A., & Sun, Amy Cha-Tien. Biofuel impacts on water.. United States. doi:10.2172/1030402.
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Tidwell, Vincent Carroll, Malczynski, Leonard A., and Sun, Amy Cha-Tien. Sat . "Biofuel impacts on water.". United States. doi:10.2172/1030402. https://www.osti.gov/servlets/purl/1030402.
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@article{osti_1030402,
title = {Biofuel impacts on water.},
author = {Tidwell, Vincent Carroll and Malczynski, Leonard A. and Sun, Amy Cha-Tien},
abstractNote = {Sandia National Laboratories and General Motors Global Energy Systems team conducted a joint biofuels systems analysis project from March to November 2008. The purpose of this study was to assess the feasibility, implications, limitations, and enablers of large-scale production of biofuels. 90 billion gallons of ethanol (the energy equivalent of approximately 60 billion gallons of gasoline) per year by 2030 was chosen as the book-end target to understand an aggressive deployment. Since previous studies have addressed the potential of biomass but not the supply chain rollout needed to achieve large production targets, the focus of this study was on a comprehensive systems understanding the evolution of the full supply chain and key interdependencies over time. The supply chain components examined in this study included agricultural land use changes, production of biomass feedstocks, storage and transportation of these feedstocks, construction of conversion plants, conversion of feedstocks to ethanol at these plants, transportation of ethanol and blending with gasoline, and distribution to retail outlets. To support this analysis, we developed a 'Seed to Station' system dynamics model (Biofuels Deployment Model - BDM) to explore the feasibility of meeting specified ethanol production targets. The focus of this report is water and its linkage to broad scale biofuel deployment.},
doi = {10.2172/1030402},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sat Jan 01 00:00:00 EST 2011},
month = {Sat Jan 01 00:00:00 EST 2011}
}
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DOI:  10.2172/1030402
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