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Contract No. DE-AC36-08GO28308

Biomass Scenario Model 

Scenario Library: Definitions, 

Construction, and Description

Daniel Inman, Laura Vimmerstedt, 

and Brian Bush 

National Renewable Energy Laboratory

Steve Peterson 

Lexidyne, LLC

Technical Report

NREL/TP-6A20-60386

April 2014
NREL is a national laboratory of the U.S. Department of Energy

Office of Energy Efficiency & Renewable Energy

Operated by the Alliance for Sustainable Energy, LLC

This report is available at no cost from the National Renewable Energy

Laboratory (NREL) at www.nrel.gov/publications.

Contract No. DE-AC36-08GO28308

National Renewable Energy Laboratory

15013 Denver West Parkway

Golden, CO 80401

303-275-3000 • www.nrel.gov

Biomass Scenario Model 

Scenario Library: Definitions, 

Construction, and Description

Daniel Inman, Laura Vimmerstedt, 

and Brian Bush 

National Renewable Energy Laboratory

Steve Peterson 

Lexidyne, LLC

Prepared under Task No. BZ11.3003

Technical Report

NREL/TP-6A20-60386

April 2014
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iii

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Abstract

Understanding the development of the biofuels industry in the United States is important to 

policymakers and industry. The Biomass Scenario Model (BSM) is a system dynamics model of 

the biomass-to-biofuels system that can be used to explore many aspects of the industry. Because 

of the complexity of the model, as well as the wide range of possible future conditions that affect 

biofuels industry development, we have not developed a single reference case but instead have 

designed a set of six incentive-focused scenarios. The purpose of this report is to describe the 

scenarios that comprise the BSM scenario library. At present, we have the following six 

incentive-focused scenarios in our library: minimal incentives scenario; ethanol-focused

incentives scenario; equal access to incentives scenario; output-focused incentives scenario;

pathway-diversity-focused incentives scenario; and the point-of-production-focused incentives 

scenario. This report describes the model settings and rationale for each scenario.
iv

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Table of Contents

1 Introduction........................................................................................................................................... 1

1.1 Model Overview .............................................................................................................................. 2

Feedstock supply and logistics......................................................................................................... 2

Conversion....................................................................................................................................... 2

Petroleum industry........................................................................................................................... 3

Downstream ethanol and butanol..................................................................................................... 3

Vehicles ........................................................................................................................................... 3

Ethanol import ................................................................................................................................. 3

1.2 Purpose............................................................................................................................................. 3

2 Definitions ............................................................................................................................................. 6

3 Scenario Library ................................................................................................................................... 7

Minimal Incentives Scenario ........................................................................................................... 7

Ethanol-Focused Incentives Scenario.............................................................................................. 7

Equal Access to Incentives Scenario ............................................................................................... 8

Output-Focused Incentives Scenario ............................................................................................... 8

Pathway-Diversity-Focused Incentives Scenario............................................................................. 8

Point-of-Production-Focused Policies Scenario .............................................................................. 8

4 Summary ............................................................................................................................................. 10

5 References .......................................................................................................................................... 10

List of Figures

Figure 1. High-level schematic showing the elements of the biofuel supply chain modeled in the 

Biomass Scenario Model..................................................................................................................... 1

Figure 2. Generalized diagram of the biofuel supply chain modeled in the Biomass Scenario 

Model; incentives are indicated at the part of the supply chain upon which they are applied.... 5

Figure 3. Scenario library incentive type, level, and duration by scenario........................................... 9
1

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1 Introduction

Understanding the development of the biofuels industry in the United States is important to 

energy policymakers and many industrial sectors. Development of the biofuels industry responds 

to incentives, market disruptions, and technological changes, among other influences. Numerous 

research, development, and deployment strategies are currently being considered to advance the 

industry; decisions made at what is still an early stage of development will shape the future of 

biofuels in the United States. The biofuels industry can be considered a dynamically complex 

system of systems (Bush et al. 2008). Exploring the multifaceted and at times counterintuitive 

dynamics of large systems can elucidate unforeseen interactions and inform strategy. System 

dynamics models have a long history of being used to explore questions of public policy 

(Ghaffarzadegan et al. 2011). The U.S. Department of Energy has funded the development of the 

Biomass Scenario Model (BSM), which is a system dynamics model that is designed to explore 

the expansion of the biofuels industry in the United States (Figure 1). The BSM is used to

investigate a wide range of scenarios (e.g. policy, climate, demand, and deployment) across the 

entire biofuels industry as well as individual parts of the industry (e.g., feedstock supply and 

logistics). Below is a brief description of the BSM, please refer to Newes et al. (2011) and 

Peterson et al. (2013) for a more complete description of the BSM. 

Figure 1. High-level schematic showing the elements of the biofuel supply chain modeled in the 

Biomass Scenario Model

SUPPLY CHAIN

Feedstock 

Production

Feedstock 

Logistics

Biofuels 

Production

Biofuels 

Distribution

Biofuels End 

Use

DYNAMIC MODELS OF SUPPLY INFRASTRUCTURE,

PHYSICAL CONSTRAINTS, MARKETS, AND DECISION MAKING

POLICIES INCENTIVES EXTERNALITIES

Feedstock Supply Module

q 6 Feedstock types

q 10 geographic regions

q 10+ land uses

q Farmer decision logic

q Land allocation dynamics

q New agriculture practices

q Markets and prices

Feedstock Logistics Module

q Multiple logistics stages

q Cost breakdowns

q Transportation distance

q Land eligibility

Conversion Module

q 15 conversion platforms

q 4 development stages

q 6 learning attributes

q Cascading learning curves

q Project economics

q Industry growth and investment 

dynamics

Distribution Logistics Module

q Distribution terminal focus

q Differential cost structure, based on 

infrastructure (storage and intra/interregion transport costs)

Dispensing Station Module

q Fueling-station economics

q Tankage and equipment investment 

decision

q Distribution-coverage effects

Vehicle Scenario Module

q Cars and Light Trucks

q Multiple (9 +scenario) vehicle 

technologies

q Fleet vintaging

q Vehicle choice scenarios

q E10/E20/E85 potential

Fuel Use Module

q Non-, occasional, and 

frequent users

q Relative price/fuel choice 

dynamics
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1.1 Model Overview

The BSM is designed in a top-down, modular fashion that allows material (feedstocks) to flow 

down the supply chain and be converted into various types of biofuels, with feedback 

mechanisms among and between the various modules. The BSM’s structure is transparent, 

modular, and extensible, enabling standalone analysis of individual model components as well as 

testing of different module combinations. Below is a brief description of the primary sectors that 

are modeled in the BSM. Each sector described below is comprised of a “module” or set of 

“modules” which are self-contained models of specific parts of the supply chain. It is the use of 

“modules” that allows for singular aspects of the supply chain to be analyzed in isolation. The 

BSM is disaggregated into ten agricultural production regions (USDA-ERS, 2010).

Feedstock supply and logistics

The feedstock supply and logistics sector models the dynamics associated with producing and 

delivering biofuel feedstocks and includes harvesting and transport of starch, herbaceous (energy 

crops and residues), woody (crops and residues), and urban residues. Feedstock production 

competes with other uses of the agricultural land base such as commodity crop production (corn, 

wheat, soybean, small grains, and cotton), hay, pasture, and Conservation Reserve Program land. 

Conversion

The conversion sector is composed of six different modules, each corresponding to a different set 

of biofuel conversion pathways. Each conversion module represents pilot, demonstration, and 

pioneer-commercial and full-commercial scale biorefineries and includes learning curve 

dynamics, investment decision logic, and utilization logic. The starch to ethanol module 

represents dynamics associated with the existing starch (corn) ethanol industry. The industry is 

considered to be mature; hence, the module provides a simple representation of the financial 

logic that controls acquisition and utilization of commercial scale corn ethanol facilities. The 

cellulose to ethanol module captures the development of the cellulose-to-ethanol conversion 

industry. Biochemical and thermochemical conversion modeled based on published design 

reports (Humbird et al., 2011; Dutta et al., 2012). The cellulose to butanol module captures the 

development of the cellulose-to-butanol conversion industry. In the BSM, butanol serves as an 

industrial solvent and as a substitute for ethanol in the oxygenate market. The biomass to 

hydrocarbon module captures the industry development of biomass to hydrocarbon conversion 

processes. Currently the following conversion options are modeled: fast pyrolysis; FischerTropsch; methanol to gasoline; catalytic pyrolysis; fermentation of sugars to hydrocarbons; and 

aqueous phase reforming. Multiple products can be produced, including gasoline, diesel, and jet 

fuel. The oil crops module captures development of conversion capacity for soy-to-refinery and 

“other” oilseed-to-refinery processes. The algae module represents open pond, photo-bioreactor, 

and heterotrophic conversion options. Algae feedstock production is presumed to be vertically 

integrated in the algae to refinery-ready system. In addition to the six conversion modules, the 

conversion sector includes a module that models the attractiveness of investing in the various 

conversion options, allocating limited facility construction capacity among these options based 

on their perceived relative economic value.
3

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Petroleum industry

The petroleum industry sector is comprised of inputs around crude oil prices, providing logic that 

translates these prices into price inputs for the various refinery ready conversion modules as well 

as the pricing/inventory module of the downstream ethanol/butanol sector. Additionally, the 

petroleum industry model provides accounting logic that captures displacement of crude by 

biofuel-derived infrastructure compatible fuels.

Downstream ethanol and butanol

The downstream ethanol and butanol sector is composed of a set of four modules. These modules 

capture the dynamics of the activities that occur after fuel production. The pricing and inventory 

module captures pricing and inventory dynamics for both ethanol and bio-based butanol. Ethanol 

flows into two distinct but coupled markets: the oxygenate market and the high-blend ethanol 

fuel market. Bio-butanol can serve as a substitute for ethanol in the oxygenate market, and also 

can supplant butanol produced by other processes in the industrial market. The distribution 

logistics module provides a very simple representation of the regional expansion of the 

distribution network for fuel ethanol. The dispensing station module addresses the regional 

acquisition of tankage and equipment capable of dispensing ethanol. Expansion of E85-capable 

stations is driven by economic considerations, and is constrained by regional availability of 

ethanol from the distribution network. The fuel use module represents the mix of low-ethanolblend vs. high-ethanol-blend consumption is determined by the relative economics of the two 

products as constrained by the regional availability of ethanol for high-blend consumption 

through dispensing stations.

Vehicles

The vehicle module is used in BSM to keep track of the cumulative effect of volume, vehicle 

mix, vehicle efficiency, and vehicle miles traveled for the car and light duty truck sectors. Its 

structure captures acquisition, aging, and retirement of vehicles, as well as the translation of 

vehicles into potential demand for fuel. 

Ethanol import

The ethanol import module provides a simple representation of the evolution of non-domestic 

ethanol production capacity. It generates imports of ethanol into the United States based on a 

price differential as perceived from abroad. This structure enables the model to capture historical 

patterns of growth and decline in imports of fuel ethanol. It is structured to facilitate exploration 

of multiple scenarios around production cost.

1.2 Purpose

The scenarios described in this report are focused on biofuel incentives. The term “scenario: is 

used to represent a collection of model settings that are intended to represent a hypothetical 

future. Although this report describes incentive-focused scenarios, scenarios can also represent

other areas of the model such as the feedstock supply system and fuel use, for example. 

Development of a “baseline” or “reference” case is a common practice for users of a given model 

because such cases provide a stable reference point for comparative analyses and for 

modifications to the model. Because the future is uncertain with regard to biofuel policies and 

because the BSM has so many biofuel pathways modeled, developing a single reference case is 
4

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challenging. Instead, we designed a series of scenarios that are comprised of biofuel incentives. 

Each scenario represents a potential means to achieve a certain goal for the biofuels industry. 

These scenarios may be used as analyses by themselves or as the initial model conditions for 

other directed analysis. For example, analysts could use one or more scenarios as the base 

conditions to explore an analysis of oil price volatility. 

The purpose of this report is to describe the model settings used construct the scenarios in the 

BSM scenario library, as of October 2013. This report is intended as the first in a series of 

reports that describe the library scenarios used in BSM analyses. Subsequent reports will 

describe scenarios that are either added to the set described in this report, or describe changes to 

scenarios included in this report when such changes are significant. This report also serves as a 

singular reference document that will be used to provide a unified set of definitions and 

descriptions of our scenarios and the input parameters used to construct them.

This report first describes the types of economic incentives that are included in the BSM and 

how these incentives are combined to form scenarios. The scenarios described in this report 

represent incentives (both real and hypothetical) that are intended to achieve a specific outcome 

for the biofuels industry. In this report, the magnitude of each incentive and the ways in which 

they are activated and/or structured do not necessarily represent existing or proposed incentives. 

The types of incentives modeled in the BSM provide flexibility to model a wide range of 

incentive strategies (across different parts of the industry and characteristics of biomass-tobiofuels conversion pathways) as well as proxy existing and/or proposed incentive programs. 

The types of incentives modeled and where they affect the supply chain are shown in Figure 2. In 

the BSM, incentives that are applied to the portion of the industry that is “upstream” of the 

conversion facility include the Biomass Crop Assistance Program’s (BCAP) matching,

establishment, and annual payments (USDA, 2010). Incentives that are focused on expanding the 

industry through defraying the cost of installed capital include fixed capital investment (FCI) and 

government loan guarantees incentives. Incentives that are applied to the portion of the supply 

chain that is “downstream” of the conversion facility are aimed at lowering the risk of installing 

specialized equipment for the distribution and dispensing of ethanol-based fuels (e.g., 

distribution and storage incentives and FCI and dispensing equipment repurposing incentives and 

lowering the cost of purchasing qualified biofuels (point-of-use incentives). 
5

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Figure 2. Generalized diagram of the biofuel supply chain modeled in the Biomass Scenario Model; incentives are indicated at the part 

of the supply chain upon which they are applied.

Feedstock Supply 

& Logistics

Feedstock 

Production Biofuels Production Biofuels 

Distribution Biofuels End Use

Biomass Crop Assistance Program 

• Establishment payments

• Annual payment

• Matching payment

• Fixed capital investment

• Loan guarantee incentive

• Feedstock incentive

• Point-of-production incentive

• Distribution and storage incentive

• Dispensing station fixed capital investment incentive

• Dispensing station repurposing incentive

• High-blend point of use incentive

Upstream Downstream
6

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2 Definitions

Fixed Capital Investment (FCI) incentive (Unitless) is the fraction of the total capital costs, 

including a portion of capital cost growth, which is provided by the government. The portion of 

capital cost growth can range from 0 to 1 and is set to 1 in the BSM. This incentive can be 

applied to both pioneer- and commercial-scale biorefineries in the BSM. It lowers the 

construction cost associated with building new biorefineries. This incentive results in a direct 

payment to biofuel producers.

Government loan guarantee incentive (Unitless) is the equity portion of the FCI investment and 

reflects the amount that the government agrees to assume if the borrower defaults. The guarantee 

improves the ability of producers to obtain financing from private lenders and does not cost the 

government if the plant is successful. In the BSM, this incentive can be applied to both pioneerand commercial-scale biorefineries. 

Feedstock incentive (Units = USD ton-1) is provided to the biofuel producer for the purchase of 

qualifying feedstocks. This incentive lowers the costs associated with acquiring feedstocks and 

may be applied to both pioneer- and commercial-scale biorefineries in the BSM. 

Point-of-production incentive (Units = USD gallon-1

) is an incentive provided to fuel producers 

of qualifying biofuels based on the volume of biofuel produced. As used in the BSM, this 

incentive mimics some aspects of the Renewable Identification Number (RIN) program and 

provides a fixed, pre-tax amount to the biofuel producer for each gallon of biofuel produced. 

Ethanol distribution and storage incentive (Units = USD gallon-1

) is only applied to ethanol 

fuels and is provided to offset the costs associated with investing in additional capital equipment 

needed to store and distribute ethanol compared to other fuels. 

Ethanol dispensing station FCI Incentive (Unitless) is an incentive that is applied only to 

ethanol fuels. This incentive is provided to owners of retail dispensing stations to a fraction of 

the costs associated with purchasing the specialized tankage and dispensing equipment needed to 

handle ethanol fuels that are more expensive than equipment handling hydrocarbon fuels. 

Ethanol dispensing station repurposing incentive (Unitless) is applied only to ethanol fuels.

This incentive is provided to owners of retail dispensing stations to offset the costs associated 

with repurposing existing tankage and dispensing equipment to accommodate ethanol fuels. 

High-blend ethanol point-of-use incentive (Units = USD gallon-1

) affects high-blend ethanol 

fuels (i.e., E85 and higher) and accrues to retailers of ethanol fuels.

Biomass Crop Assitance Program (BCAP) Incentives is composed of three incentives: 

matching payments, establishment payments, and annual payments, each defined further below.

In the BSM, the BCAP is initiated in 2009 with only matching payments. In 2013, the program

transitions to establishment payments for one simulation year, followed by annual payments

which eventually cease in 2026. In the BSM we assume that all cellulosic feedstocks are eligible 

for BCAP payments. Please refer to the proposed rulemaking document for more information on 

the BCAP (United States Department of Agriculture 2010).

BCAP matching payment Incentive (a.k.a. collection, harvest, storage, and transport payments)

(Units = USD ton-1

) are provided for the collection, harvest, storage and transportation of

cellulosic biofuel feedstocks as a 50% match of costs to the grower up to $45 ton-1 for a contract 

term of 2 years.
7

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BCAP establishment payment Incentive (Units = USD acre-1year1) is given to offset 75% of 

the cost associated with preparing fields to produce herbaceous and woody energy crops.

BCAP annual payment Incentive (Units = USD year-1

) uses agricultural land cash rental rates

for land in the given project area as a basis for payment. This incentive is given to cellulosic 

biofuel feedstock producers in eligible project areas for a contract term of 5 or 15 years. 

Startup levels are applied to a subset of conversion-focused incentives (FCI, government loan 

guarantee, feedstock incentive, and point-of-production incentive). Startup levels for incentives 

are typically set to high amounts and for short periods of time. The idea behind applying a 

startup level for a given incentive is to essentially give a portion of the supply chain an early 

boost. Startup levels are constrained by a biofuel production level, once this level is met the level 

is either set to a lower level for a longer period of time (background level) or the incentive is 

turned off completely.

Background levels are applied to a subset of conversion-focused incentives (FCI, government 

loan guarantee, feedstock incentive, and point-of-production incentive). Background levels for 

incentives are typically set to low levels for long periods of time. The rationale behind applying a 

background level for a given incentive is to allow for protracted support at a low to modest level. 

Background levels are constrained by time, once a given year is reached the incentive is turned 

off.

3 Scenario Library

The scenarios discussed below are focused on incentivizing the biofuels industry. However, 

scenarios can be crafted that focus on any aspect of the supply chain (e.g., oil prices, feedstock 

production/disruption, technological assumptions, vehicle/end-use assumption) (see Figure 2). 

Incentive settings for each scenario are presented in Figure 3. In all of the scenarios described, 

there were no additional gasoline taxes applied (beyond state and federal taxes) and feedstocks 

were incentivized through BCAP.

Minimal Incentives Scenario

The minimal incentives scenario presents a case in which there are no substantive production 

incentives for biofuels. This scenario applies a point-of-production incentive of 0.45 USD gallon1 of ethanol produced, for one year (2011) which is consistent with the implementation of the 

Volumetric Ethanol Excise Tax Credit (VEETC), as it was applied to starch-based ethanol; the 

cellulosic portion of the VEETC is not represented in this scenario (Congressional Budget 

Office, 2010).

Ethanol-Focused Incentives Scenario

The ethanol-focused incentives scenario is structured to provide moderate support to the starch 

and cellulosic ethanol industries. Much of this scenario is focused on accelerating industrial

learning at an early stage through FCI and government loan guarantees for pioneer-scale 

cellulosic ethanol biorefineries. Support is also provided to cellulosic ethanol refineries through a 

point-of-production incentive. The starch industry receives a 0.45 USD gallon-1 point-ofproduction incentive that ends in 2012. The cellulosic ethanol industry receives a point-ofproduction incentive of 2.65 USD gallon-1 for the first one billion gallons of ethanol production, 

after which the level drops to 0.15 USD gallon-1. Additionally the point-of-use incentive and the
8

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distribution and storage incentive are applied equally to both the starch and cellulosic ethanol 

industries. 

Equal Access to Incentives Scenario

The equal-access-to-incentives scenario is constructed such that all cellulosic biofuel production 

technologies (i.e., cellulose-to-ethanol, -to-butanol, and -to-hydrocarbons) have access to the 

same incentives at the same levels. In other words, qualifying biofuel technologies have access to 

incentives regardless of their economic viability and attractiveness to investors. In this scenario, 

incentives are set to very high levels for the first decade. After which all but the point-ofproduction incentive is turned off.

Output-Focused Incentives Scenario

The overall goal of the output-focused incentives scenario is to maximize biofuel production 

(ethanol and biomass-derived hydrocarbons) without exceeding 10 billion USD in annual costs. 

The annual spending cap of 10 billion USD is loosely based on the spending observed for the 

VEETC program, which was reported to be over 6 billion USD in 2010 (Congressional Budget O 

2010). Much of this support is directed toward the construction of pioneer- and commercial-scale 

refineries by providing high levels of FCI and loan guarantee support. This scenario incentivizes

one biomass-to-hydrocarbon biofuel production technology in an effort to maximize its fuel 

production targeting the most technologically attractive biofuel pathway

Pathway-Diversity-Focused Incentives Scenario

The pathway-diversity-focused incentives scenario utilizes a series of incentives that lead to 

multiple biomass-to-hydrocarbon fuel pathways gaining market share in addition to the ethanol 

industry retaining some market share without exceeding 10 billion USD in annual spending . The 

incentives are triggered to promote as many pathways as reasonably possible. For example, 

pathways that are immature receive early and substantial support for the construction of 

biorefineries (FCI and loan guarantee). Once these pathways have enough industrial momentum 

(accumulated learning), the incentives are reduced or terminated. In contrast, more mature 

pathways are incentivized at either lower levels or for shorter periods of time, or both. In this 

scenario, four pathways can be incentivized to achieve at least modest success. Avoiding 

technological lockout is difficult and requires incentives to have staggered start times and 

variable duration. Some pathways have a combination of technoeconomic attributes (based on 

published data) such that they require only minimal incentives, while others need continued 

support to remain viable in the context of multiple competing pathways. 

Point-of-Production-Focused Policies Scenario

The point-of-production-focused incentives scenario is a case where a low level of production 

incentives is available. This scenario applies a point-of-production incentive of 0.45 USD gallon1 across all biofuels. In this scenario, starch-based ethanol is subsidized for one simulation year 

(2011), which is consistent with the implementation of VEETC. All other renewable fuels are 

subsidized for the duration of the simulation, which is within the range of historical RIN values 

and could be considered a very rough approximation of RIN market effects.
9

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Figure 3. Scenario library incentive type, level, and duration by scenario 

Notes: Only biofuel technologies that are active in the listed scenarios are shown. BCAP incentives are active in all scenarios and are not shown 

because BCAP is held constant across scenarios. 

Starch Ethanol .45 .45 .45 .45

Pathway

Cellulosic 

Ethanol 

All Ethanol

Minimal Incentives

Scenario

Ethanol-Focused 

Incentives Scenario

Output-Focused

Incentives Scenario

Pathway-DiversityFocused Incentives 

Scenario

.15

.6

0

1.0

1.0

3.75

1.0

0

1.0

1.0

2.0

.6

0

.9

.9

.7

.7

.7

.7

0

0

0

0

0

1.0

.6

0

.7

.7

0

0

0

0

0

0

1.25

0

.5

.45

2.0

.6

0

.9

.9

2.0

.6

0

.9

.9

2.0

0.6

0

.9

.9

.15

.5

2.65

.6

0

.7

0

.15

.6

0

.7

0

2.65

.7

.7

.7

.7

1.0

.6

.6

.6

.6

2.65

.7

.7

.7

.7

1.0

.6

.6

.6

.6

2.65

.7

.7

.7

.7

1.0

.6

.6

.6

.6

2.65

.7

.7

.7

.7

1.0

.6

.6

.6

.6

.6

0

.7

.7

.1

.6

0

.7

.7

0

.5

2.65

1.0

.3

1.0

1.0

.15

0

0

0

0

2.65

0

0

0

0

.15

0

0

0

0

2.65

0

0

0

0

.15

0

0

0

0

2.65

0

0

0

0

3.75

1.0

0

1.0

1.0

3.75

1.0

0

1.0

1.0

3.75

1.0

0

1.0

1.0

Equal Access to 

Incentives Scenario

Point of 

Production-Focused 

Incentives Scenario

Biomass-Based Hydrocarbons

Fast 

Pyrolysis

Fischer

Tropsch

Methanol to

Gasoline

Fermentation

of Sugars to

Hydrocarbons

2015 2020 2025 2030 2015 2020 2025 2030 2015 2020 2025 2030 2015 2020 2025 2030 2015 2020 2025 2030 2015 2020 2025 2030

.45

.45

.45

.45

.45

.7 .7 .45

Point of production incentive 

[USD gallon-1]

Fixed capital investment incentive 

for pioneer-scale refineries [fraction]

Downstream distribution and

storage incentive [USD gallon-1]

Downstream point of use

incentive [USD gallon-1]

Loan guarantee incentive 

for pioneer-scale refineries [fraction] 

Fixed capital investment incentive 

for commercial-scale refineries [fraction]

Loan guarantee incentive 

for commercial-scale refineries 

[fraction] 

1.25 Startup incentives are shown in red

1.25 Background incentives are shown in gray

Line thickness is proportional 

to the value (USD, fraction) of incentive. 

Line length is proportional 

to duration (years) of the incentive. 

Figure Legend

Gasoline tax [USD gallon-1]
10

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

4 Summary

We have developed six incentive-focused scenarios to provide background settings and context 

to analyses performed using the BSM. In this report, scenarios represent a set of hypothetical 

incentives. Scenarios will continue to be developed and added to the BSM scenario library as the 

model and analyses continue to mature. Future scenarios are not limited to incentive-focused 

scenarios and may include scenarios such as climate, oil prices, feedstock supply, and 

vehicle/end use assumptions, to name a few. 

Because the BSM is so complex and its results so impacted by initial model settings, having a 

singular reference case does not make sense. As with other models that provide a glimpse at a 

potential future, the BSM has a range of scenarios that provide alternative futures that may be 

compared and used to gain insights into the system and how certain analysis settings interact 

with a range of scenario settings. 

5 References

American Petroleum Institute (API). (2013). “State Motor Fuel Taxes.” Accessed October 24, 

2013: http://www.api.org/oil-and-natural-gas-overview/industry-economics/~/media/Files/

Statistics/state-motor-fuel-taxes-report-summary.pdf.

Bush, B.; Duffy, M.; Sandor, D.; Peterson, S. (2008). Using System Dynamics to Model the

Transition to Biofuels in the United States: Preprint. Golden, CO: National Renewable Energy 

Laboratory.

Congressional Budget Office (CBO). (July 2010). “Using Biofuel Tax Credits to Achieve Energy 

and Environmental Policy Goals.” Accessed October 24, 

2013: http://www.cbo.gov/sites/default/files/cbofiles/ftpdocs/114xx/doc11477/07-14-

biofuels.pdf.

Dutta, A.; Talmadge, M.; Hensley, J.; Worley, M.; Dudgeon, D.; Barton, D.; Groendijk, P.; 

Ferrari, D.; Stears, B.; Searcy, E. M.; Wright, C. T.; Hess, J. R. (2011). Process Design and 

Economics for Conversion of Lignocellulosic Biomass to Ethanol: Thermochemical Pathway by 

Indirect Gasification and Mixed Alcohol Synthesis 187 pp. NREL Report No. TP-5100-51400

Energy Independence and Security Act of 2007. Public Law 109-58.

Ghaffarzadegan, N.; Lyneis, J.; Richardson, G.P. (2011). “How Small System Dynamics Models 

Can Help the Public Policy Process.” Systems Dynamics Review (27:1); pp. 22–44. Doi: 

10.1002/sdr.442.

Humbird, D.; Davis, R.; Tao, L.; Kinchin, C.; Hsu, D.; Aden, A.; Schoen, P.; Lukas, J.; Olthof, 

B.; Worley, M.; Sexton, D.; Dudgeon, D. (2011). Process Design and Economics for 

Biochemical Conversion of Lignocellulosic Biomass to Ethanol Dilute-Acid Pretreatment and 

Enzymatic Hydrolysis of Corn Stover. NREL Report No. TP-5100-47764.
11

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications.

Newes, E.; Inman, D.; Bush, B. (2011). “Understanding the Developing Cellulosic Biofuels 

Industry Through Dynamic Modeling,” Chapter 18. Bernardes, M, ed. Economic Effects of 

Biofuel Production. Rijeka, Croatia: InTech; pp. 373-404. ISBN: 978-953-307-178-7.

Peterson, S.; Newes, E.; Inman, D.; Vimmerstedt, L.; Hsu, D.; Peck, C.; Stright, D.; Bush, B. 

(2013). “An Overview of the Biomass Scenario Model.” Proceedings of the 31st International 

Conference of the System Dynamics Society; July 21-25, 2013, Cambridge, Massachusetts.

Accessed November 5, 

2013: http://www.systemdynamics.org/conferences/2013/proceed/papers/P1352.pdf. 

United States Department of Agriculture. (8 February 2010). Biomass Crop Assistance Program. 

Federal Register (75:25). 

United States Department of Agriculture Economic Research Service (USDA-ERS). 2010. 

Agricultural Resource Management Survey (ARMS): Resource Regions. Accessed December 3, 

2013: 

http://webarchives.cdlib.org/wayback.public/UERS_ag_1/20111128195215/http://www.ers.usda.

gov/Briefing/ARMS/resourceregions/resourceregions.htm#older.