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Ethanol distribution, dispensing, and use: analysis of a portion of the biomass-to-biofuels supply chain using system dynamics.

Vimmerstedt LJ, Bush B, Peterson S - PLoS ONE (2012)

Bottom Line: The National Renewable Energy Laboratory developed the Biomass Scenario Model, a system dynamics model which represents the primary system effects and dependencies in the biomass-to-biofuels supply chain.A large, economically sustainable ethanol fuel market (or other biofuel market) requires low end-user fuel price relative to gasoline and sufficient producer payment, which are difficult to achieve simultaneously.Other requirements (different for ethanol vs. other biofuel markets) include the need for infrastructure for distribution and dispensing and widespread use of high ethanol blends in flexible-fuel vehicles.

View Article: PubMed Central - PubMed

Affiliation: National Renewable Energy Laboratory, Strategic Energy Analysis Center, Golden, Colorado, United States of America. laura.vimmerstedt@nrel.gov

ABSTRACT
The Energy Independence and Security Act of 2007 targets use of 36 billion gallons of biofuels per year by 2022. Achieving this may require substantial changes to current transportation fuel systems for distribution, dispensing, and use in vehicles. The U.S. Department of Energy and the National Renewable Energy Laboratory designed a system dynamics approach to help focus government action by determining what supply chain changes would have the greatest potential to accelerate biofuels deployment. The National Renewable Energy Laboratory developed the Biomass Scenario Model, a system dynamics model which represents the primary system effects and dependencies in the biomass-to-biofuels supply chain. The model provides a framework for developing scenarios and conducting biofuels policy analysis. This paper focuses on the downstream portion of the supply chain-represented in the distribution logistics, dispensing station, and fuel utilization, and vehicle modules of the Biomass Scenario Model. This model initially focused on ethanol, but has since been expanded to include other biofuels. Some portions of this system are represented dynamically with major interactions and feedbacks, especially those related to a dispensing station owner's decision whether to offer ethanol fuel and a consumer's choice whether to purchase that fuel. Other portions of the system are modeled with little or no dynamics; the vehicle choices of consumers are represented as discrete scenarios. This paper explores conditions needed to sustain an ethanol fuel market and identifies implications of these findings for program and policy goals. A large, economically sustainable ethanol fuel market (or other biofuel market) requires low end-user fuel price relative to gasoline and sufficient producer payment, which are difficult to achieve simultaneously. Other requirements (different for ethanol vs. other biofuel markets) include the need for infrastructure for distribution and dispensing and widespread use of high ethanol blends in flexible-fuel vehicles.

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Ethanol consumption, incentive costs, and cost effectiveness of multiple incentive combinations with two incremental gasoline costs in 2030.The figure shows model results for 2030 under different policy and incremental gasoline cost conditions. Two levels for incremental gasoline costs are represented with two different sizes of marks. Policy conditions include three levels of Distribution and Storage Subsidy, one level of Fixed Capital Investment (FCI) Subsidy, two levels of high-blend (Hi-Blend) Point-of-use (PoU) Subsidy, two levels of Point-of-production (PoP) Subsidy, and one level of Repurposing Subsidy. The cumulative net subsidy color scale shows government payments or revenues generated, assuming that incremental gasoline costs are revenue in the form of gasoline taxes. The left-hand column of results shows ethanol consumption over time; the middle column shows cumulative subsidy (with incremental gasoline costs treated as a subsidy and added to other costs, rather than being subtracted as they were for the cumulative net subsidy scale); the right-hand column of results shows a metric of effectiveness of investment in annual production capacity–Capacity Expansion Cost Effectiveness.
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pone-0035082-g006: Ethanol consumption, incentive costs, and cost effectiveness of multiple incentive combinations with two incremental gasoline costs in 2030.The figure shows model results for 2030 under different policy and incremental gasoline cost conditions. Two levels for incremental gasoline costs are represented with two different sizes of marks. Policy conditions include three levels of Distribution and Storage Subsidy, one level of Fixed Capital Investment (FCI) Subsidy, two levels of high-blend (Hi-Blend) Point-of-use (PoU) Subsidy, two levels of Point-of-production (PoP) Subsidy, and one level of Repurposing Subsidy. The cumulative net subsidy color scale shows government payments or revenues generated, assuming that incremental gasoline costs are revenue in the form of gasoline taxes. The left-hand column of results shows ethanol consumption over time; the middle column shows cumulative subsidy (with incremental gasoline costs treated as a subsidy and added to other costs, rather than being subtracted as they were for the cumulative net subsidy scale); the right-hand column of results shows a metric of effectiveness of investment in annual production capacity–Capacity Expansion Cost Effectiveness.

Mentions: The choice of types and levels of incentives, resulting ethanol consumption, and associated costs and cost effectiveness are diverse. Figure 6 illustrates results for a larger set of combinations in a single year, 2030. The three columns of results, like the three rows of Figure 5, show ethanol consumption, incentive costs, and cost effectiveness. As in Figure 5, the cumulative net subsidy color scale shows government payments or revenues generated, assuming that incremental gasoline costs are revenue in the form of gasoline taxes. The green points have $0.50/gal gasoline tax; the red ones have $0.00/gal gasoline tax. The distance between these two points varies for the different rows. This shows how significantly the effect of an incremental $0.50/gal gasoline tax can vary, depending on other incentive levels, indicating once more that effects of a given incremental investment in any single type of incentive depend heavily upon the levels of other incentives and the state of development of the system. Again, the authors do not advocate a particular policy or level of incentive, but explore these scenarios for insights on performance of the system.


Ethanol distribution, dispensing, and use: analysis of a portion of the biomass-to-biofuels supply chain using system dynamics.

Vimmerstedt LJ, Bush B, Peterson S - PLoS ONE (2012)

Ethanol consumption, incentive costs, and cost effectiveness of multiple incentive combinations with two incremental gasoline costs in 2030.The figure shows model results for 2030 under different policy and incremental gasoline cost conditions. Two levels for incremental gasoline costs are represented with two different sizes of marks. Policy conditions include three levels of Distribution and Storage Subsidy, one level of Fixed Capital Investment (FCI) Subsidy, two levels of high-blend (Hi-Blend) Point-of-use (PoU) Subsidy, two levels of Point-of-production (PoP) Subsidy, and one level of Repurposing Subsidy. The cumulative net subsidy color scale shows government payments or revenues generated, assuming that incremental gasoline costs are revenue in the form of gasoline taxes. The left-hand column of results shows ethanol consumption over time; the middle column shows cumulative subsidy (with incremental gasoline costs treated as a subsidy and added to other costs, rather than being subtracted as they were for the cumulative net subsidy scale); the right-hand column of results shows a metric of effectiveness of investment in annual production capacity–Capacity Expansion Cost Effectiveness.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3351488&req=5

pone-0035082-g006: Ethanol consumption, incentive costs, and cost effectiveness of multiple incentive combinations with two incremental gasoline costs in 2030.The figure shows model results for 2030 under different policy and incremental gasoline cost conditions. Two levels for incremental gasoline costs are represented with two different sizes of marks. Policy conditions include three levels of Distribution and Storage Subsidy, one level of Fixed Capital Investment (FCI) Subsidy, two levels of high-blend (Hi-Blend) Point-of-use (PoU) Subsidy, two levels of Point-of-production (PoP) Subsidy, and one level of Repurposing Subsidy. The cumulative net subsidy color scale shows government payments or revenues generated, assuming that incremental gasoline costs are revenue in the form of gasoline taxes. The left-hand column of results shows ethanol consumption over time; the middle column shows cumulative subsidy (with incremental gasoline costs treated as a subsidy and added to other costs, rather than being subtracted as they were for the cumulative net subsidy scale); the right-hand column of results shows a metric of effectiveness of investment in annual production capacity–Capacity Expansion Cost Effectiveness.
Mentions: The choice of types and levels of incentives, resulting ethanol consumption, and associated costs and cost effectiveness are diverse. Figure 6 illustrates results for a larger set of combinations in a single year, 2030. The three columns of results, like the three rows of Figure 5, show ethanol consumption, incentive costs, and cost effectiveness. As in Figure 5, the cumulative net subsidy color scale shows government payments or revenues generated, assuming that incremental gasoline costs are revenue in the form of gasoline taxes. The green points have $0.50/gal gasoline tax; the red ones have $0.00/gal gasoline tax. The distance between these two points varies for the different rows. This shows how significantly the effect of an incremental $0.50/gal gasoline tax can vary, depending on other incentive levels, indicating once more that effects of a given incremental investment in any single type of incentive depend heavily upon the levels of other incentives and the state of development of the system. Again, the authors do not advocate a particular policy or level of incentive, but explore these scenarios for insights on performance of the system.

Bottom Line: The National Renewable Energy Laboratory developed the Biomass Scenario Model, a system dynamics model which represents the primary system effects and dependencies in the biomass-to-biofuels supply chain.A large, economically sustainable ethanol fuel market (or other biofuel market) requires low end-user fuel price relative to gasoline and sufficient producer payment, which are difficult to achieve simultaneously.Other requirements (different for ethanol vs. other biofuel markets) include the need for infrastructure for distribution and dispensing and widespread use of high ethanol blends in flexible-fuel vehicles.

View Article: PubMed Central - PubMed

Affiliation: National Renewable Energy Laboratory, Strategic Energy Analysis Center, Golden, Colorado, United States of America. laura.vimmerstedt@nrel.gov

ABSTRACT
The Energy Independence and Security Act of 2007 targets use of 36 billion gallons of biofuels per year by 2022. Achieving this may require substantial changes to current transportation fuel systems for distribution, dispensing, and use in vehicles. The U.S. Department of Energy and the National Renewable Energy Laboratory designed a system dynamics approach to help focus government action by determining what supply chain changes would have the greatest potential to accelerate biofuels deployment. The National Renewable Energy Laboratory developed the Biomass Scenario Model, a system dynamics model which represents the primary system effects and dependencies in the biomass-to-biofuels supply chain. The model provides a framework for developing scenarios and conducting biofuels policy analysis. This paper focuses on the downstream portion of the supply chain-represented in the distribution logistics, dispensing station, and fuel utilization, and vehicle modules of the Biomass Scenario Model. This model initially focused on ethanol, but has since been expanded to include other biofuels. Some portions of this system are represented dynamically with major interactions and feedbacks, especially those related to a dispensing station owner's decision whether to offer ethanol fuel and a consumer's choice whether to purchase that fuel. Other portions of the system are modeled with little or no dynamics; the vehicle choices of consumers are represented as discrete scenarios. This paper explores conditions needed to sustain an ethanol fuel market and identifies implications of these findings for program and policy goals. A large, economically sustainable ethanol fuel market (or other biofuel market) requires low end-user fuel price relative to gasoline and sufficient producer payment, which are difficult to achieve simultaneously. Other requirements (different for ethanol vs. other biofuel markets) include the need for infrastructure for distribution and dispensing and widespread use of high ethanol blends in flexible-fuel vehicles.

Show MeSH