1

ENVIRONMENTAL PROTECTION AGENCY 

40 CFR Part 80

[EPA-HQ-OAR-2005-0161; FRL-XXXX-X] 

RIN 2060-A081 

Regulation of Fuels and Fuel Additives: Changes to Renewable Fuel Standard 

Program 

AGENCY: Environmental Protection Agency (EPA). 

ACTION: Final rule. 

SUMMARY: Under the Clean Air Act Section 211(o), as amended by the Energy 

Independence and Security Act of 2007 (EISA), the Environmental Protection Agency is 

required to promulgate regulations implementing changes to the Renewable Fuel 

Standard program. The revised statutory requirements specify the volumes of cellulosic 

biofuel, biomass-based diesel, advanced biofuel, and total renewable fuel that must be 

used in transportation fuel. This action finalizes the regulations that implement the 

requirements of EISA, including the cellulosic, biomass-based diesel, advanced biofuel, 

and renewable fuel standards that will apply to all gasoline and diesel produced or 

imported in 2010. The final regulations make a number of changes to the current 

Renewable Fuel Standard program while retaining many elements of the compliance and 

trading system already in place. This final rule also implements the revised statutory 

definitions and criteria, most notably the new greenhouse gas emission thresholds for 
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renewable fuels and new limits on renewable biomass feedstocks. This rulemaking 

marks the first time that greenhouse gas emission performance is being applied in a 

regulatory context for a nationwide program. As mandated by the statute, our greenhouse 

gas emission assessments consider the full lifecycle emission impacts of fuel production 

from both direct and indirect emissions, including significant emissions from land use 

changes. In carrying out our lifecycle analysis we have taken steps to ensure that the 

lifecycle estimates are based on the latest and most up-to-date science. The lifecycle 

greenhouse gas assessments reflected in this rulemaking represent significant 

improvements in analysis based on information and data received since the proposal. 

However, we also recognize that lifecycle GHG assessment of biofuels is an evolving 

discipline and will continue to revisit our lifecycle analyses in the future as new 

information becomes available. EPA plans to ask the National Academy of Sciences for 

assistance as we move forward. Based on current analyses we have determined that 

ethanol from corn starch will be able to comply with the required greenhouse gas (GHG) 

threshold for renewable fuel. Similarly, biodiesel can be produced to comply with the 

50% threshold for biomass-based diesel, sugarcane with the 50% threshold for advanced 

biofuel and multiple cellulosic-based fuels with their 60% threshold. Additional fuel 

pathways have also been determined to comply with their thresholds. The assessment for 

this rulemaking also indicates the increased use of renewable fuels will have important 

environmental, energy and economic impacts for our Nation. 

DATES: This final rule is effective on July 1, 2010, and the percentage standards apply 

to all gasoline and diesel produced or imported in 2010. The incorporation by reference 
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of certain publications listed in the rule is approved by the Director of the Federal 

Register as of July 1, 2010. 

ADDRESSES: EPA has established a docket for this action under Docket ID No. EPAHQ-OAR-2005-0161. All documents in the docket are listed in the 

www.regulations.gov web site. Although listed in the index, some information is not 

publicly available, e.g., confidential business information (CBI) or other information 

whose disclosure is restricted by statute. Certain other material, such as copyrighted 

material, is not placed on the Internet and will be publicly available only in hard copy 

form. Publicly available docket materials are available either electronically through 

www.regulations.gov or in hard copy at the Air and Radiation Docket and Information 

Center, EPA/DC, EPA West, Room 3334, 1301 Constitution Ave., NW, Washington DC. 

The Public Reading Room is open from 8:30 a.m. to 4:30 p.m., Monday through Friday, 

excluding legal holidays. The telephone number for the Public Reading Room is (202) 

566-1744, and the telephone number for the Air Docket is (202) 566-1742. 

FOR FURTHER INFORMATION CONTACT: Julia MacAllister, Office of 

Transportation and Air Quality, Assessment and Standards Division, Environmental 

Protection Agency, 2000 Traverwood Drive, Ann Arbor MI 48105; Telephone number: 

734-214-4131; Fax number: 734-214-4816; E-mail address: macallister.julia@epa.gov, 

or Assessment and Standards Division Hotline; telephone number (734) 214-4636; Email address asdinfo@epa.gov. 
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SUPPLEMENTARY INFORMATION: 

General Information 

I. Does this Final Rule Apply to Me? 

Entities potentially affected by this final rule are those involved with the 

production, distribution, and sale of transportation fuels, including gasoline and diesel 

fuel or renewable fuels such as ethanol and biodiesel. Regulated categories include: 

Category NAICS1

Codes 

SIC2

Codes 

Examples of Potentially Regulated Entities 

Industry 

Industry 

Industry 

Industry 

Industry 

Industry 

 

Industry 

324110 

325193 

325199 

424690 

424710 

424720 

454319 

2911 

2869 

2869 

5169 

5171 

5172 

5989 

Petroleum Refineries 

Ethyl alcohol manufacturing 

Other basic organic chemical manufacturing 

Chemical and allied products merchant wholesalers 

Petroleum bulk stations and terminals 

Petroleum and petroleum products merchant 

wholesalers 

Other fuel dealers 

1

 North American Industry Classification System (NAICS) 

2

 Standard Industrial Classification (SIC) system code. 
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This table is not intended to be exhaustive, but rather provides a guide for readers 

regarding entities likely to be regulated by this final action. This table lists the types of 

entities that EPA is now aware could potentially be regulated by this final action. Other 

types of entities not listed in the table could also be regulated. To determine whether 

your activities would be regulated by this final action, you should carefully examine the 

applicability criteria in 40 CFR part 80. If you have any questions regarding the 

applicability of this final action to a particular entity, consult the person listed in the 

preceding section. 

Outline of This Preamble 

I. Executive Summary 

A. Summary of New Provisions of the RFS Program

1. Required Volumes of Renewable Fuel

2. Standards for 2010 and Effective Date for New Requirements

a. 2010 Standards

b. Effective Date

3. Analysis of Lifecycle Greenhouse Gas Emissions and Thresholds for Renewable Fuels

a. Background and Conclusions

b. Fuel Pathways Considered and Key Model Updates Since the Proposal

c. Consideration of Fuel Pathways Not Yet Modeled

4. Compliance with Renewable Biomass Provision

5. EPA-Moderated Transaction System

6. Other Changes to the RFS Program

B. Impacts of Increasing Volume Requirements in the RFS2 Program
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II. Description of the Regulatory Provisions 

A. Renewable Identification Numbers (RINs)

B. New Eligibility Requirements for Renewable Fuels

1. Changes in Renewable Fuel Definitions

a. Renewable Fuel

b. Advanced Biofuel

c. Cellulosic Biofuel

d. Biomass-Based Diesel

e. Additional Renewable Fuel

f. Cellulosic Diesel

2. Lifecycle GHG Thresholds

3. Renewable Fuel Exempt from 20 Percent GHG Threshold

a. General Background of the Exemption Requirement

b. Definition of Commenced Construction

c. Definition of Facility Boundary

d. Proposed Approaches and Consideration of Comments

i. Comments on the Proposed Basic Approach

ii. Comments on the Expiration of Grandfathered Status

e. Final grandfathering provisions

i. Increases in volume of renewable fuel produced at grandfathered facilities due to 

expansion

ii. Replacements of equipment

iii. Registration, Recordkeeping and Reporting

4. New Renewable Biomass Definition and Land Restrictions

a. Definitions of Terms

i. Planted Crops and Crop Residue

ii. Planted Trees and Tree Residue
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iii. Slash and Pre-Commercial Thinnings

iv. Biomass Obtained from Certain Areas at Risk from Wildfire

v. Algae

b. Implementation of Renewable Biomass Requirements

i. Ensuring That RINs Are Generated Only For Fuels Made From Renewable Biomass

ii. Whether RINs Must Be Generated For All Qualifying Renewable Fuel

c. Implementation Approaches for Domestic Renewable Fuel

i. Recordkeeping and Reporting for Feedstocks

ii. Approaches for Foreign Producers of Renewable Fuel

(1) RIN-generating importers

(2) RIN-generating foreign producers

iii. Aggregate Compliance Approach for Planted Crops and Crop Residue from Agricultural 

Land

(1) Analysis of Total Agricultural Land in 2007

(2) Aggregate Agricultural Land Trends over Time

(3) Aggregate Compliance Determination

d. Treatment of Municipal Solid Waste (MSW)

C. Expanded Registration Process for Producers and Importers

1. Domestic Renewable Fuel Producers

2. Foreign Renewable Fuel Producers

3. Renewable Fuel Importers

4. Process and Timing

D. Generation of RINs

1. Equivalence Values

2. Fuel Pathways and Assignment of D Codes

a. Producers

b. Importers
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c. Additional Provisions for Foreign Producers

3. Facilities With Multiple Applicable Pathways

4. Facilities that Co-Process Renewable Biomass and Fossil Fuels

5. Facilities that Process Municipal Solid Waste

6. RINless Biofuel

E. Applicable Standards

1. Calculation of Standards

a. How Are the Standards Calculated?

b. Standards for 2010

2. Treatment of Biomass-Based Diesel in 2009 and 2010

a. Shift in 2009 Biomass-Based Diesel Compliance Demonstration to 2010

b. Treatment of Deficit Carryovers, RIN Rollover, and RIN Valid Life For Adjusted 2010 

Biomass-Based Diesel Requirement

3. Future Standards

F. Fuels that are Subject to the Standards

1. Gasoline

2. Diesel

3. Other Transportation Fuels

G. Renewable Volume Obligations (RVOs)

1. Designation of Obligated Parties

2. Determination of RVOs Corresponding to the Four Standards

3. RINs Eligible to Meet Each RVO

4. Treatment of RFS1 RINs under RFS2

a. Use of RFS1 RINs to Meet Standards Under RFS2

b. Deficit Carryovers from the RFS1 Program to RFS2

H. Separation of RINs

1. Nonroad
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2. Heating Oil and Jet Fuel

3. Exporters

4. Requirement to Transfer RINs with Volume

5. Neat Renewable Fuel and Renewable Fuel Blends Designated as Transportation Fuel, Heating 

Oil, or Jet Fuel

I. Treatment of Cellulosic Biofuel

1. Cellulosic Biofuel Standard

2. EPA Cellulosic Biofuel Waiver Credits for Cellulosic Biofuel

3. Application of Cellulosic Biofuel Waiver Credits

J. Changes to Recordkeeping and Reporting Requirements

1. Recordkeeping

2. Reporting

3. Additional Requirements for Producers of Renewable Natural Gas, Electricity, and Propane

4. Attest Engagements

K. Production Outlook Reports

L. What Acts Are Prohibited and Who Is Liable for Violations?

III. Other Program Changes 

A. The EPA Moderated Transaction System (EMTS)

1. Need for the EPA Moderated Transaction System

2. Implementation of the EPA Moderated Transaction System

3. How EMTS Will Work

4. A Sample EMTS Transaction

B. Upward Delegation of RIN-Separating Responsibilities

C. Small Producer Exemption

D. 20% Rollover Cap
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E. Small Refinery and Small Refiner Flexibilities

1. Background- RFS1

a. Small Refinery Exemption

b. Small Refiner Exemption

2. Statutory Options for Extending Relief

3. The DOE Study/DOE Study Results

4. Ability to Grant Relief Beyond 211(o)(9)

5. Congress-Requested Revised DOE Study

6. What We’re Finalizing

a. Small Refinery and Small Refiner Temporary Exemptions

b. Case-by-Case Hardship for Small Refineries and Small Refiners

c. Program Review

7. Other Flexibilities Considered for Small Refiners

a. Extensions of the RFS1 Temporary Exemption for Small Refiners

b. Phase-in

c. RIN-Related Flexibilities

F. Retail Dispenser Labeling for Gasoline with Greater than 10 Percent Ethanol

G. Biodiesel Temperature Standardization

IV. Renewable Fuel Production and Use 

A. Overview of Renewable Fuel Volumes

1. Reference Cases

2. Primary Control Case

a. Cellulosic Biofuel

b. Biomass-Based Diesel

c. Other Advanced Biofuel

d. Other Renewable Fuel

3. Additional Control Cases Considered
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B. Renewable Fuel Production

1. Corn/Starch Ethanol

a. Historic/Current Production

b. Forecasted Production Under RFS2

2. Imported Ethanol

3. Cellulosic Biofuel

a. Current State of the Industry

b. Setting the 2010 Cellulosic Biofuel Standard

c. Current Production Outlook for 2011 and Beyond

d. Feedstock Availability

i. Urban Waste

ii. Agricultural and Forestry Residues

iii. Dedicated Energy Crops

iv. Summary of Cellulosic Feedstocks for 2022

4. Biodiesel & Renewable Diesel

a. Historic and Projected Production

i. Biodiesel

ii. Renewable Diesel

b. Feedstock Availability

C. Biofuel Distribution

1. Biofuel Shipment to Petroleum Terminals

2. Petroleum Terminal Accommodations

3. Potential Need for Special Blendstocks at Petroleum Terminals for E85

4. Need for Additional E85 Retail Facilities

D. Ethanol Consumption

1. Historic/Current Ethanol Consumption

2. Increased Ethanol Use under RFS2
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a. Projected Gasoline Energy Demand

b. Projected Growth in Flexible Fuel Vehicles

c. Projected Growth in E85 Access

d. Required Increase in E85 Refueling Rates

e. Market Pricing of E85 Versus Gasoline

3. Consideration of >10% Ethanol Blends

V. Lifecycle Analysis of Greenhouse Gas Emissions 

A. Introduction

1. Open and Science-Based Approach to EPA’s Analysis

2. Addressing Uncertainty

B. Methodology

1. Scope of Analysis

a. Inclusion of Indirect Land Use Change

b. Models Used

c. Scenarios Modeled

2. Biofuel Modeling Framework & Methodology for Lifecycle Analysis Components

a. Feedstock Production

i. Domestic Agricultural Sector Impacts

ii. International Agricultural Sector Impacts

b. Land Use Change

i. Amount of Land Area Converted and Where

ii. Type of Land Converted

iii. GHG Emissions Associated with Conversion

(1) Domestic Emissions

(2) International Emissions

iv. Timeframe of Emission Analysis

v. GTAP and Other Models
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c. Feedstock Transport

d. Biofuel Processing

e. Fuel Transportation

f. Vehicle Tailpipe Emissions

3. Petroleum Baseline

C. Threshold Determination and Assignment of Pathways

D. Total GHG Reductions

E. Effects of GHG Emission Reductions and Changes in Global Temperature and Sea 

Level

VI. How Would the Proposal Impact Criteria and Toxic Pollutant Emissions and 

Their Associated Effects? 

A. Overview of Impacts

B. Fuel Production & Distribution Impacts of the Proposed Program

C. Vehicle and Equipment Emission Impacts of Fuel Program

D. Air Quality Impacts

1. Particulate Matter

a. Current Levels

b. Projected Levels without RFS2 Volumes

c. Projected Levels with RFS2 Volumes

2. Ozone

a. Current Levels

b. Projected Levels without RFS2 Volumes

c. Projected Levels with RFS2 Volumes

3. Air Toxics

a. Current Levels
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b. Projected Levels

i. Acetaldehyde

ii. Formaldehyde

iii. Ethanol

iv. Benzene

v. 1,3-Butadiene

vi. Acrolein

vii. Population Metrics

4. Nitrogen and Sulfur Deposition

a. Current Levels

b. Projected Levels

E. Health Effects of Criteria and Air Toxics Pollutants

1. Particulate Matter

a. Background

b. Health Effects of PM

2. Ozone

a. Background

b. Health Effects of Ozone

3. NOX and SOX

a. Background

b. Health Effects of NOX

c. Health Effects of SOX

4. Carbon Monoxide

5. Air Toxics

a. Acetaldehyde

b. Acrolein

c. Benzene

d. 1,3-Butadiene
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e. Ethanol

f. Formaldehyde

g. Peroxyacetyl nitrate (PAN)

h. Naphthalene

i. Other Air Toxics

F. Environmental Effects of Criteria and Air Toxic Pollutants

1. Visibility

2. Atmospheric Deposition

3. Plant and Ecosystem Effects of Ozone

4. Environmental Effects of Air Toxics

VII. Impacts on Cost of Renewable Fuels, Gasoline, and Diesel 

A. Renewable Fuel Production Costs

1. Ethanol Production Costs

a. Corn Ethanol

b. Cellulosic Ethanol

i. Feedstock Costs

ii. Production Costs for Cellulosic Biofuels

c. Imported Sugarcane Ethanol

2. Biodiesel and Renewable Diesel Production Costs

a. Biodiesel

b. Renewable Diesel

B. Biofuel Distribution Costs

1. Ethanol Distribution Costs

2. Cellulosic Distillate and Renewable Diesel Distribution Costs

3. Biodiesel Distribution Costs

C. Reduced U.S. Refining Demand
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D. Total Estimated Cost Impacts

1. Refinery Modeling Methodology

2. Overall Impact on Fuel Cost

VIII. Economic Impacts and Benefits 

A. Agricultural and Forestry Impacts

1. Biofuel Volumes Modeled

2. Commodity Price Changes

3. Impacts on U.S. Farm Income

4. Commodity Use Changes

5. U.S. Land Use Changes

6. Impact on U.S. Food Prices

7. International Impacts

B. Energy Security Impacts

1. Implications of Reduced Petroleum Use on U.S. Imports

2. Energy Security Implications

a. Effect of Oil Use on Long-Run Oil Price, U.S. Import Costs, and Economic Output

b. Short-Run Disruption Premium from Expected Costs of Sudden Supply Disruptions

c. Costs of Existing U.S. Energy Security Policies

3. Combining Energy Security and Other Benefits

4. Total Energy Security Benefits

C. Benefits of Reducing GHG Emissions

1. Introduction

2. Derivation of Interim Social Cost of Carbon Values

3. Application of Interim SCC Estimates to GHG Emissions Reductions

D. Criteria Pollutant Health and Environmental Impacts

1. Overview
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2. Quantified Human Health Impacts

3. Monetized Impacts

4. What Are the Limitations of the Health Impacts Analysis?

E. Summary of Costs and Benefits

IX. Impacts on Water 

A. Background

1. Agriculture and Water Quality

2. Ecological Impacts

3. Impacts to the Gulf of Mexico

B. Upper Mississippi River Basin Analysis

1. SWAT Model

2. AEO 2007 Reference Case

3. Reference Cases and RFS2 Control Case

4. Case Study

5. Sensitivity Analysis

C. Additional Water Issues

1. Chesapeake Bay Watershed

2. Ethanol Production and Distribution

a. Production

b. Distillers Grain with Solubles

c. Ethanol Leaks and Spills from Fueling Stations

3. Biodiesel Plants

4. Water Quantity

5. Drinking Water

X. Public Participation 
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XI. Statutory and Executive Order Reviews 

A. Executive Order 12866: Regulatory Planning and Review

B. Paperwork Reduction Act

C. Regulatory Flexibility Act

1. Overview

2. Background

3. Summary of Potentially Affected Small Entities

4. Reporting, Recordkeeping, and Compliance

5. Related Federal Rules

6. Steps Taken to Minimize the Significant Economic Impact on Small Entities

a. Significant Panel Findings

b. Outreach With Small Entities (and the Panel Process)

c. Panel Recommendations, Proposed Provisions, and Provisions Being Finalized

i. Delay in Standards

ii. Phase-in

iii. RIN-Related Flexibilities

iv. Program Review

v. Extensions of the Temporary Exemption Based on a Study of Small Refinery Impacts

vi. Extensions of the Temporary Exemption Based on Disproportionate Economic Hardship

7. Conclusions

D. Unfunded Mandates Reform Act

E. Executive Order 13132: Federalism

F. Executive Order 13175: Consultation and Coordination with Indian Tribal Governments

G. Executive Order 13045: Protection of Children from Environmental Health Risks and 

Safety Risks
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H. Executive Order 13211: Actions Concerning Regulations That Significantly Affect 

Energy Supply, Distribution, or Use

I. National Technology Transfer Advancement Act

J. Executive Order 12898: Federal Actions to Address Environmental Justice in Minority 

Populations and Low-Income Populations

K. Congressional Review Act

XII. Statutory Provisions and Legal Authority 
 

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I. Executive Summary 

 Through this final rule, the U.S. Environmental Protection Agency is revising the 

National Renewable Fuel Standard program to implement the requirements of the Energy 

Independence and Security Act of 2007 (EISA). EISA made significant changes to both 

the structure and the magnitude of the renewable fuel program created by the Energy 

Policy Act of 2005 (EPAct). The EISA fuel program, hereafter referred to as RFS2, 

mandates the use of 36 billion gallons of renewable fuel by 2022--a nearly five-fold 

increase over the highest volume specified by EPAct. EISA also established four 

separate categories of renewable fuels, each with a separate volume mandate and each 

with a specific lifecycle greenhouse gas emission threshold. The categories are 

renewable fuel, advanced biofuel, biomass-based diesel, and cellulosic biofuel. There is 

a notable increase in the mandate for cellulosic biofuels in particular. EISA increased the 

cellulosic biofuel mandate to 16 billion gallons by 2022, representing the bulk of the 

increase in the renewable fuels mandate. 

EPA’s proposed rule sought comment on a multitude of issues, ranging from how 

to interpret the new definitions for renewable biomass to the Agency’s proposed 

methodology for conducting the greenhouse gas lifecycle assessments required by EISA. 

The decisions presented in this final rule are heavily informed by the many public 

comments we received on the proposed rule. In addition, and as with the proposal, we 

sought input from a wide variety of stakeholders. The Agency has had multiple meetings 

and discussions with renewable fuel producers, technology companies, petroleum refiners 
 

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and importers, agricultural associations, lifecycle experts, environmental groups, vehicle 

manufacturers, states, gasoline and petroleum marketers, pipeline owners and fuel 

terminal operators. We also have worked closely with other Federal agencies and in 

particular with the Departments of Energy and Agriculture. 

 

This section provides an executive summary of the final RFS2 program 

requirements that EPA is implementing as a result of EISA. The RFS2 program will 

replace the RFS1 program promulgated on May 1, 2007 (72 FR 23900)1

. Details of the 

final requirements can be found in Sections II and III, with certain lifecycle aspects 

detailed in Section V. 

 This section also provides a summary of EPA's assessment of the environmental 

and economic impacts of the use of higher renewable fuel volumes. Details of these 

analyses can be found in Sections IV through IX and in the Regulatory Impact Analysis 

(RIA). 

A. Summary of New Provisions of the RFS Program 

 Today's notice establishes new regulatory requirements for the RFS program that 

will be implemented through a new Subpart M to 40 CFR Part 80. EPA is maintaining 

several elements of the RFS1 program such as regulations governing the generation, 

 

1

 To meet the requirements of EPAct, EPA had previously adopted a limited program that applied only to 

calendar year 2006. The RFS1 program refers to the general program adopted in the May 2007 

rulemaking. 
 

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transfer, and use of Renewable Identification Numbers (RINs). At the same time, we are 

making a number of updates to reflect the changes brought about by EISA 

 1. Required Volumes of Renewable Fuel

 The RFS program is intended to require a minimum volume of renewable fuel to 

be used each year in the transportation sector. In response to EPAct 2005, under RFS1 

the required volume was 4.0 billion gallons in 2006, ramping up to 7.5 billion gallons by 

2012. Starting in 2013, the program also required that the total volume of renewable fuel 

contain at least 250 million gallons of fuel derived from cellulosic biomass. 

 In response to EISA, today's action makes four primary changes to the volume 

requirements of the RFS program. First, it substantially increases the required volumes 

and extends the timeframe over which the volumes ramp up through at least 2022. 

Second, it divides the total renewable fuel requirement into four separate categories, each 

with its own volume requirement. Third, it requires, with certain exceptions applicable to 

existing facilities, that each of these mandated volumes of renewable fuels achieve 

certain minimum thresholds of GHG emission performance. Fourth, it requires that all 

renewable fuel be made from feedstocks that meet the new definition of renewable 

biomass including certain land use restrictions. The volume requirements in EISA are 

shown in Table I.A.1-1. 
 

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Table I.A.1-1 

Renewable Fuel Volume Requirements for RFS2 (billion gallons) 

Cellulosic 

biofuel 

requirement 

Biomassbased diesel 

requirement 

Advanced biofuel 

requirement 

Total renewable 

fuel requirement 

2009 

2010 

2011 

2012 

2013 

2014 

2015 

2016 

2017 

2018 

2019 

2020 

2021 

2022 

2023+ 

n/a 

0.1 

0.25 

0.5 

1.0 

1.75 

3.0 

4.25 

5.5 

7.0 

8.5 

10.5 

13.5 

16.0 

b 

0.5 

0.65 

0.80 

1.0 

a 

a 

a 

a 

a 

a 

a 

a 

a 

a 

b 

0.6 

0.95 

1.35 

2.0 

2.75 

3.75 

5.5 

7.25 

9.0 

11.0 

13.0 

15.0 

18.0 

21.0 

b 

11.1 

12.95 

13.95 

15.2 

16.55 

18.15 

20.5 

22.25 

24.0 

26.0 

28.0 

30.0 

33.0 

36.0 

b 
 

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a To be determined by EPA through a future rulemaking, but no less than 1.0 billion 

gallons. 

b

 To be determined by EPA through a future rulemaking.

 As shown in the table, the volume requirements are not exclusive, and generally 

result in nested requirements. Any renewable fuel that meets the requirement for 

cellulosic biofuel or biomass-based diesel is also valid for meeting the advanced biofuel 

requirement. Likewise, any renewable fuel that meets the requirement for advanced 

biofuel is also valid for meeting the total renewable fuel requirement. See Section V.C 

for further discussion of which specific types of fuel may qualify for the four categories 

shown in Table I.A.1-1. 

 2. Standards for 2010 and Effective Date for New Requirements

 While EISA established the renewable fuel volumes shown in Table I.A.1-1, it 

also requires that the Administrator set the standards based on these volumes each 

November for the following year based in part on information provided from the Energy 

Information Agency (EIA). In the case of the cellulosic biofuel standard, section 

211(o)(7)(D) of EISA specifically requires that the standard be set based on the volume 

projected to be available during the following year. If the volume is lower than the level 

shown in Table I.A.1-1, then EISA allows the Administrator to also lower the advanced 

biofuel and total renewable fuel standards each year accordingly. Given the implications 

of these standards and the necessary judgment that can’t be reduced to a formula akin to 

the RFS1 regulations, we believe it is appropriate to set the standards through a notice-
 

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and-comment rulemaking process. Thus, for future standards, we intend to issue an 

NPRM by summer and a final rule by November 30 of each year in order to determine 

the appropriate standards applicable in the following year. However, in the case of the 

2010 standards, we are finalizing them as part of today’s action. 

 a. 2010 Standards 

While we proposed that the cellulosic biofuel standard would be set at the EISAspecified level of 100 million gallons for 2010, based on analysis of information available 

at this time, we no longer believe the full volume can be met. Since the proposal, we 

have had detailed discussions with over 30 companies that are in the business of 

developing cellulosic biofuels and cellulosic biofuel technology. Based on these 

discussions, we have found that many of the projects that served as the basis for the 

proposal have been put on hold, delayed, or scaled back. At the same time, there have 

been a number of additional projects that have developed and are moving forward. As 

discussed in Section IV.B.3, the timing for many of the projects indicates that while few 

will be able to provide commercial volumes for 2010, an increasing number will come on 

line in 2011, 2012, and 2013. The success of these projects is then expected to accelerate 

growth of the cellulosic biofuel industry out into the future. EIA provided us with a 

projection on October 29, 2009 of 5.04 million gallons (6.5 million ethanol-equivalent 

gallons) of cellulosic biofuel production for 2010. While our company-by-company 

assessment varies from EIA’s, as described in Section IV.B.3., and actual cellulosic 

production volume during 2010 will be a function of developments over the course of 
 

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2010, we nevertheless believe that 5 million gallons (6.5 million ethanol equivalent) 

represents a reasonable, yet achievable level for the cellulosic standard for 2010. While 

this is lower than the level specified in EISA, no change to the advanced biofuel and total 

renewable fuel standards is warranted. With the inclusion of an energy-based 

Equivalence Value for biodiesel and renewable diesel, 2010 compliance with the 

biomass-based diesel standard will be more than enough to ensure compliance with the 

advanced biofuel standard for 2010. 

 Today’s rule also includes special provisions to account for the 2009 biomassbased diesel volume requirements in EISA. As described in the NPRM, in November 

2008 we used the new total renewable fuel volume of 11.1 billion gallons from EISA as 

the basis for the 2009 total renewable fuel standard that we issued under the RFS1 

regulations.2

 While this approach ensured that the total mandated renewable fuel volume 

required by EISA for 2009 was used, the RFS1 regulatory structure did not provide a 

mechanism for implementing the 0.5 billion gallon requirement for biomass-based diesel 

nor the 0.6 billion gallon requirement for advanced biofuel. As we proposed, and as is 

described in more detail in Section II.E.2, we are addressing this issue in today’s rule by 

combining the 2010 biomass-based diesel requirement of 0.65 billion gallons with the 

2009 biomass based diesel requirement of 0.5 billion gallons to require that obligated 

parties meet a combined 2009/2010 requirement of 1.15 billion gallons by the end of the 

2010 compliance year. No similar provisions are required in order to fulfill the 2009 

advanced biofuel volume mandate. 

 

2

 73 FR 70643, November 21, 2008 
 

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The resulting 2010 standards are shown in Table I.A.2-1. These standards 

represent the fraction of a refiner's or importer's gasoline and diesel volume which must 

be renewable fuel. Additional discussion of the 2010 standards can be found in Section 

II.E.1.b. 

Table I.A.2-1 

Standards for 2010 

Cellulosic biofuel 0.004% 

Biomass-based diesel 1.10% 

Advanced biofuel 0.61% 

Renewable fuel 8.25% 

 b. Effective Date 

 Under CAA section 211(o) as modified by EISA, EPA is required to revise the 

RFS1 regulations within one year of enactment, or December 19, 2008. Promulgation by 

this date would have been consistent with the revised volume requirements shown in 

Table I.A.1-1 that begin in 2009 for certain categories of renewable fuel. As described in 

the NPRM, we were not able to promulgate final RFS2 program requirements by 

December 19, 2008. 
 

28

 Under today’s rule, the transition from using the RFS1 regulatory provisions 

regarding registration, RIN generation, reporting, and recordkeeping to using comparable 

provisions in this RFS2 rule will occur on July 1, 2010. This is the start of the 1st quarter 

following completion of the statutorily required 60-day Congressional Review period for 

such a rulemaking as this. This will provide adequate lead time for all parties to 

transition to the new regulatory requirements, including additional time to prepare for 

RFS2 implementation for those entities who may find it helpful, especially those covered 

by the RFS program for the first time. In addition, making the transition at the end of the 

quarter will help simplify the recordkeeping and reporting transition to RFS2. To 

facilitate the volume obligations being based on the full year’s gasoline and diesel 

production, and to enable the smooth transition from the RFS1 to RFS2 regulatory 

provisions, Renewable Identification Numbers (RINs - which are used in the program for 

both credit trading and for compliance demonstration) that were generated under the 

RFS1 regulations will continue to be valid for compliance with the RFS2 obligations. 

Further discussion of transition issues can be found in Sections II.A and II.G.4, 

respectively. 

 According to EISA, the renewable fuel obligations applicable under RFS2 apply 

on a calendar basis. That is, obligated parties must determine their renewable volume 

obligations (RVOs) at the end of a calendar year based on the volume of gasoline or 

diesel fuel they produce during the year, and they must demonstrate compliance with 

their RVOs in an annual report that is due two months after the end of the calendar year. 
 

29

For 2010, today’s rule will follow this same general approach. The four RFS2 

RVOs for each obligated party will be calculated on the basis of all gasoline and diesel 

produced or imported on and after January 1, 2010, through December 31, 2010. 

Obligated parties will be required to demonstrate by February 28 of 2011 that they 

obtained sufficient RINs to satisfy their 2010 RVOs. We believe this is an appropriate 

approach as it is more consistent with Congress’ provisions in EISA for 2010, and there 

is adequate lead time for the obligated parties to achieve compliance. 

The issue for EPA to resolve is how to apply the four volume mandates under 

EISA for calendar year 2010. These volume mandates are translated into applicable 

percentages that obligated parties then use to determine their renewable fuel volume 

obligations based on the gasoline and diesel they produce or import in 2010. There are 

three basic approaches that EPA has considered, based on comments on the proposal. 

The first is the approach adopted in this rule – the four RFS2 applicable percentages are 

determined based on the four volume mandates covered by this rule, and the renewable 

volume obligation for a refiner or importer will be determined by applying these 

percentages to the volume of gasoline and diesel fuel they produce during calendar year 

2010. Under this approach, there is no separate applicable percentage under RFS1 for 

2010, however RINs generated in 2009 and 2010 under RFS1 can be used to meet the 

four volume obligations for 2010 under the RFS2 regulations. Another option, which 

was considered and rejected by EPA, is much more complicated – (1) determine an RFS1 

applicable percentage based on just the total renewable fuel volume mandate, using the 

same total volume for renewable fuel as used in the first approach, and require obligated 
 

30

parties to apply that percentage to the gasoline produced from January 1, 2010 until the 

effective date of the RFS2 regulations, and (2) determine the four RFS2 applicable 

percentages as discussed above, but require obligated parties to apply them to only the 

gasoline and diesel in 2010 after the effective date of the RFS2 regulations. Of greater 

concern than its complexity, the second approach fails to ensure that the total volumes for 

three of the volume mandates are met for 2010. In effect EPA would be requiring that 

obligated parties use enough cellulosic biofuel, biomass-based diesel, and advanced 

biofuel to meet approximately 75% of the total volumes required for these fuels under 

EISA. While the total volume mandate under EISA for renewable fuel would likely be 

met, the other three volumes mandates would only be met in part. The final option would 

involve delaying the RFS2 requirements until January 1, 2011, which would avoid the 

complexity of the second approach but would be even less consistent with EISA’s 

requirements. 

The approach adopted in this rule is clearly the most consistent with EISA’s 

requirement of four different volume mandates for all of calendar year 2010. In addition, 

EPA is confident that obligated parties have adequate lead-time to comply with the four 

volume requirements under the approach adopted in this rule. The volume requirements 

are achieved by obtaining the appropriate number of RINs from producers of the 

renewable fuel. The obligated parties do not need lead time for construction or 

investment purposes, as they are not changing the way they produce gasoline or diesel, do 

not need to design to install new equipment, or take other actions that require longer lead 

time. Obtaining the appropriate amount of RINs involves contractual or other 
 

31

arrangements with renewable fuel producers or other holders of RINs. Obligated parties 

now have experience implementing RFS1, and the actions needed to comply under the 

RFS2 regulations are a continuation of these kinds of RFS1 activities. In addition, an 

adequate supply of RINs is expected to be available for compliance by obligated parties. 

RFS1 RINs have been produced throughout 2009 and continue to be produced since the 

beginning of 2010. There has been and will be no gap or lag in the production of RINS, 

as the RFS1 regulations continue in effect and require that renewable fuel producers 

generate RINs for the renewable fuel they produce. These 2009 and 2010 RFS1 RINs 

will be available and can be used towards the volume requirements of obligated parties 

for 2010. These RFS1 RINS combined with the RFS2 RINs that will be generated by 

renewable fuel producers are expected to provide an adequate supply of RINs to ensure 

compliance for all of the renewable volume mandates. For further discussion of the 

expected supply of renewable fuel, see section IV. 

In addition, obligated parties have received adequate notice of this obligation. 

The proposed rule called for obligated parties to meet the full volume mandates for all 

four volume mandates, and to base their volume obligation on the volume of gasoline and 

diesel produced starting January 1, 2010. While the RFS2 regulations are not effective 

until after January 1, 2010, the same full year approach is being taken for the 2010 

volumes of gasoline and diesel. Obligated parties have been on notice based on EPA’s 

proposal, discussions with many stakeholders during the rulemaking, the issuance of the 

final rule itself, and publication of this rule in the Federal Register. As discussed above, 
 

32

there is adequate time for obligated parties to meet their 2010 volume obligations by the 

spring of 2011. 

This approach does not impose any retroactive requirements. The obligation that 

is imposed under the RFS2 regulations is forward looking – by the spring of 2011, when 

compliance is determined, obligated parties must satisfy certain volume obligations. 

These future requirements are calculated in part based on volumes of gasoline and diesel 

produced prior to the effective date of the RFS2 regulations, but this does not make the 

RFS2 requirement retroactive in nature. The RFS2 regulations do not change in any way 

the legal obligations or requirements that apply prior to the effective date of the RFS2 

regulations. Instead, the RFS2 requirements impose new requirements that must be met 

in the future. There is adequate lead time to comply with these RFS2 requirements, and 

they achieve a result that is more consistent with Congress’ goals in establishing 4 

volume mandates for calendar year 2010, and for these reasons EPA is adopting this 

approach for calendar year 2010. 

 Parties that intend to generate RINs, own and/or transfer them, or use them for 

compliance purposes after July 1, 2010 will need to register or re-register under the RFS2 

provisions and modify their information technology (IT) systems to accommodate the 

changes we are finalizing today. As described more fully in Section II, these changes 

include redefining the D code within the RIN that identifies which standard a fuel 

qualifies for, adding a process for verifying that feedstocks meet the renewable biomass 

definition, and calculating compliance with four standards instead of one. EPA's 
 

33

registration system is available now for parties to complete the registration process. 

Further details on this process can be found elsewhere in today's preamble as well as at 

http://www.epa.gov/otaq/regs/fuels/fuelsregistration.htm. Parties that produce motor 

vehicle, nonroad, locomotive, and marine (MVNRLM) diesel fuel but not gasoline will 

be newly obligated parties and may be establishing IT systems for the RFS program for 

the first time. 

3. Analysis of Lifecycle Greenhouse Gas Emissions and Thresholds for 

Renewable Fuels

a. Background and Conclusions 

A significant aspect of the RFS2 program is the requirement that the lifecycle 

GHG emissions of a qualifying renewable fuel must be less than the lifecycle GHG 

emissions of the 2005 baseline average gasoline or diesel fuel that it replaces; four 

different levels of reductions are required for the four different renewable fuel standards. 

These lifecycle performance improvement thresholds are listed in Table I.A.3-1. 

Compliance with each threshold requires a comprehensive evaluation of renewable fuels, 

as well as the baseline for gasoline and diesel, on the basis of their lifecycle emissions. 

As mandated by EISA, the greenhouse gas emissions assessments must evaluate the 

aggregate quantity of greenhouse gas emissions (including direct emissions and 

significant indirect emissions such as significant emissions form land use changes) 
 

34

related to the full lifecycle, including all stages of fuel and feedstock production, 

distribution and use by the ultimate consumer. 

 

Table I.A.3-1 

Lifecycle GHG Thresholds Specified in EISA (percent reduction from baseline) 

Renewable fuela

Advanced biofuel 

Biomass-based diesel 

Cellulosic biofuel 

20% 

50% 

50% 

60% 

a The 20% criterion generally applies to renewable fuel from new facilities that 

commenced construction after December 19, 2007. 

 

It is important to recognize that fuel from the existing capacity of current facilities 

and the capacity of all new facilities that commenced construction prior to December 19, 

2007 (and in some cases prior to December 31, 2009) are exempt, or grandfathered, from 

the 20% lifecycle requirement for the Renewable Fuel category. Therefore, EPA has in 

the discussion below emphasized its analysis on those plants and fuels that are likely to 

be used for compliance with the rule and would be subject to the lifecycle thresholds. 

Based on the analyses and approach described in Section V of this preamble, EPA is 

determining that ethanol produced from corn starch at a new facility (or expanded 

capacity from an existing) using natural gas, biomass or biogas for process energy and 

using advanced efficient technologies that we expect will be most typical of new 

production facilities will meet the 20% GHG emission reduction threshold compared to 

the 2005 baseline gasoline. We are also determining that biobutanol from corn starch 
 

35

meets the 20% threshold. Similarly, EPA is making the determination that biodiesel and 

renewable diesel from soy oil or waste oils, fats and greases will exceed the 50% GHG 

threshold for biomass-based diesel compared to the 2005 petroleum diesel baseline. In 

addition, we have now modeled biodiesel and renewable diesel produced from algal oils 

as complying with the 50% threshold for biomass-based diesel. EPA is also determining 

that ethanol from sugarcane complies with the applicable 50% GHG reduction threshold 

for advanced biofuels. The modeled pathways (feedstock and production technology) for 

cellulosic ethanol and cellulosic diesel would also comply with the 60% GHG reduction 

threshold applicable to cellulosic biofuels. As discussed later in section V, there are also 

other fuels and fuel pathways that we are determining will comply with the GHG 

thresholds. 

Under EISA, EPA is allowed to adjust the GHG reduction thresholds downward 

by up to 10% if necessary based on lifecycle GHG assessment of biofuels likely to be 

available. Based on the results summarized above, we are not finalizing any adjustments 

to the lifecycle GHG thresholds for the four renewable fuel standard categories. 

EPA recognizes that as the state of scientific knowledge continues to evolve in 

this area, the lifecycle GHG assessments for a variety of fuel pathways are likely to be 

updated. Therefore, while EPA is using its current lifecycle assessments to inform the 

regulatory determinations for fuel pathways in this final rule, as required by the statute, 

the Agency is also committing to further reassess these determinations and lifecycle 

estimates. As part of this ongoing effort, we will ask for the expert advice of the National 
 

36

Academy of Sciences, as well as other experts, and incorporate their advice and any 

updated information we receive into a new assessment of the lifecycle GHG emissions 

performance of the biofuels being evaluated in this final rule. EPA will request that the 

National Academy of Sciences evaluate the approach taken in this rule, the underlying 

science of lifecycle assessment, and in particular indirect land use change, and make 

recommendations for subsequent lifecycle GHG assessments on this subject. At this time 

we are estimating this review by the National Academy of Sciences may take up to two 

years. As specified by EISA, if EPA revises the analytical methodology for determining 

lifecycle greenhouse gas emissions, any such revision will apply to renewable fuel from 

new facilities that commence construction after the effective date of the revision. 

 

b. Fuel Pathways Considered and Key Model Updates Since the Proposal 
 

37

EPA is making the GHG threshold determination based on a methodology that 

includes an analysis of the full lifecycle, including significant emissions related to 

international land-use change. As described in more detail below and in Section V of this 

preamble, EPA has used the best available models for this purpose, and has incorporated 

many modifications to its proposed approach based on comments from the public and 

peer reviewers and developing science. EPA has also quantified the uncertainty 

associated with significant components of its analyses, including important factors 

affecting GHG emissions associated with international land use change. As discussed 

below, EPA has updated and refined its modeling approach since proposal in several 

important ways, and EPA is confident that its modeling of GHG emissions associated 

with international land use is comprehensive and provides a reasonable and scientifically 

robust basis for making the threshold determinations described above. As discussed 

below, EPA plans to continue to improve upon its analyses, and will update it in the 

future as appropriate. 

Through technical outreach, the peer review process, and the public comment 

period, EPA received and reviewed a significant amount of data, studies, and information 

on our proposed lifecycle analysis approach. We incorporated a number of new, updated, 

and peer-reviewed data sources in our final rulemaking analysis including better satellite 

data for tracking land use changes and improved assessments of N2O impacts from 

agriculture. The new and updated data sources are discussed further in this section, and 

in more detail in Section V. 
 

38

We also performed dozens of new modeling runs, uncertainty analyses, and 

sensitivity analyses which are leading to greater confidence in our results. We have 

updated our analyses in conjunction with, and based on, advice from experts from 

government, academia, industry, and not for profit institutions. 

The new studies, data, and analysis performed for the final rulemaking impacted 

the lifecycle GHG results for biofuels in a number of different ways. In some cases, 

updates caused the modeled analysis of lifecycle GHG emissions from biofuels to 

increase, while other updates caused the modeled emissions to be reduced. Overall, the 

revisions since our proposed rule have led to a reduction in modeled lifecycle GHG 

emissions as compared to the values in the proposal. The following highlights the most 

significant revisions. Section V details all of the changes made and their relative impacts 

on the results. 

Corn Ethanol: The final rule analysis found less overall indirect land use change 

(less land needed), thereby improving the lifecycle GHG performance of corn 

ethanol. The main reasons for this decrease are: 

• Based on new studies that show the rate of improvement in crop yields as 

a function of price, crop yields are now modeled to increase in response to 

higher crop prices. When higher crop yields are used in the models, less 

land is needed domestically and globally for crops as biofuels expand. 
 

39

• New research available since the proposal indicates that the corn ethanol 

production co-product, distillers grains and solubles (DGS), is more 

efficient as an animal feed (meaning less corn is needed for animal feed) 

than we had assumed in the proposal. Therefore, in our analyses for the 

final rule, domestic corn exports are not impacted as much by increased 

biofuel production as they were in the proposal analysis. 

• Improved satellite data allowed us to more finely assess the types of land 

converted when international land use changes occur, and this more 

precise assessment led to a lowering of modeled GHG impacts. Based on 

previous satellite data, the proposal assumed cropland expansion onto 

grassland would require an amount of pasture to be replaced through 

deforestation. For the final rulemaking analysis we incorporated improved 

economic modeling of demand for pasture area and satellite data which 

indicates that pasture is also likely to expand onto existing grasslands. 

This reduced the GHG emissions associated with an amount of land use 

change. 

However, we note that not all modeling updates necessarily reduced predicted 

GHG emissions from land use change. As one example, since the proposal a new 

version of the GREET model (Version 1.8C) has been released. EPA reviewed 

the new version and concluded that this was an improvement over the previous 

GREET release that was used in the proposal analysis (Version 1.8B). Therefore, 
 

40

EPA updated the GHG emission factors for fertilizer production used in our 

analysis to the values from the new GREET version. This had the result of 

slightly increasing the GHG emissions associated with fertilizer production and 

thus slightly increasing the GHG emission impacts of domestic agriculture. 

For the final rule, EPA has analyzed a variety of corn ethanol pathways including 

ethanol made from corn starch using natural gas, coal, and biomass as process 

energy sources in production facilities utilizing both dry mill and wet mill 

processes. For corn starch ethanol, we also considered the technology 

enhancements likely to occur in the future such as the addition of corn oil 

fractionation or extraction technology, membrane separation technology, 

combined heat and power and raw starch hydrolysis. 

Biobutanol from corn starch: In addition to ethanol from corn starch, for this final 

rule, we have also analyzed bio-butanol from corn starch. Since the feedstock 

impacts are the same as for ethanol from corn starch, the assessment for 

biobutanol reflects the differing impacts due to the production process and energy 

content of biobutanol compared to that of ethanol. 

Soybean Biodiesel: The new information described above for corn ethanol also 

leads to lower modeled GHG impacts associated with soybean biodiesel. The 

revised assessment predicts less overall indirect land use change (less land 

needed) and less impact from the land use changed that does occur (due to 
 

41

updates in types of converted land assumed). In addition, the latest IPCC 

guidance indicates reduced domestic soybean N2O emissions, and updated USDA 

and industry data show reductions in biodiesel processing energy use and a higher 

co-product credit, all of which further reduced the modeled soybean biodiesel 

lifecycle GHG emissions. This has resulted in a significant improvement in our 

assessment of the lifecycle performance of soybean biodiesel as compared to the 

estimate in the proposal. 

Biodiesel and Renewable Diesel from Algal Oil and Waste Fats and Greases: In 

addition to biodiesel from soy oil, biodiesel and renewable diesel from algal oil 

(should it reach commercial production) and biodiesel from waste oils, fats and 

greases have been modeled. These feedstock sources have little or no land use 

impact so the GHG impacts associate with their use in biofuel production are 

largely the result of energy required to produce the feedstock (in the case of algal 

oil) and the energy required to turn that feedstock into a biofuel. 

Sugarcane Ethanol: Sugarcane ethanol was analyzed considering a range of 

technologies and assuming alternative pathways for dehydrating the ethanol prior 

to its use as a biofuel in the U.S. For the final rule, our analysis also shows less 

overall indirect land use change (less land needed) associated with sugarcane 

ethanol production. For the proposal, we assumed sugarcane expansion in Brazil 

would result in cropland expansion into grassland and lost pasture being replaced 

through deforestation. Based on newly available regional specific data from 
 

42

Brazil, historic trends, and higher resolution satellite data, in the final rule, 

sugarcane expansion onto grassland is coupled with greater pasture 

intensification, such that there is less projected impact on forests. Furthermore, 

new data provided by commenters showed reduced sugarcane ethanol process 

energy, which also reduced the estimated lifecycle GHG impact of sugarcane 

ethanol production. 

Cellulosic Ethanol: We analyzed cellulosic ethanol production using both 

biochemical (enzymatic) and thermo-chemical processes with corn stover, 

switchgrass, and forestry thinnings and waste as feedstocks. For cellulosic diesel, 

we analyzed production using the Fischer-Tropsch process. For the final rule, we 

updated the cellulosic ethanol conversion rates based on new data provided by the 

National Renewable Energy Laboratory (NREL.) As a result of this update, the 

gallons per ton yields for switchgrass and several other feedstock sources 

increased in our analysis for the final rule, while the predicted yields from corn 

residue and several other feedstock sources decreased slightly from the NPRM 

values. In addition, we also updated our feedstock production yields based on 

new work conducted by the Pacific Northwest National Laboratory (PNNL). This 

analysis increased the tons per acre yields for several dedicated energy crops. 

These updates increased the amount of cellulosic ethanol projected to come from 

energy crops. While the increase in crop yields and conversion efficiency 

reduced the GHG emissions associated with cellulosic ethanol, there remains an 

increased demand for land to grow dedicated energy crops; this land use impact 
 

43

resulted in increased GHG emissions with the net result varying by the type of 

cellulosic feedstock source. 

 We note that several of the renewable fuel pathways modeled are still in early 

stages of development or commercialization and are likely to continue to develop as the 

industry moves toward commercial production. Therefore, it will be necessary to 

reanalyze several pathways using updated data and information as the technologies 

develop. For example, biofuel derived from algae is undergoing wide ranging 

development. Therefore for now, our algae analyses presume particular processes and 

energy requirements which will need to be reviewed and updated as this fuel source 

moves toward commercial production. 

 For this final rule we have incorporated a statistical analysis of uncertainty about 

critical variables in our pathway analysis. This uncertainty analysis is explained in detail 

in Section V and is consistent with the specific recommendations received through our 

peer review and public comments on the proposal. The uncertainty analysis focused on 

two aspects of indirect land use change - the types of land converted and the GHG 

emission associated with different types of land converted. In particular, our uncertainty 

analysis focused on such specific sources of information as the satellite imaging used to 

inform our assessment of land use trends and the specific changes in carbon storage 

expected from a change in land use in each geographic area of the world modeled. We 

have also performed additional sensitivity analyses including analysis of two yield 

scenarios for corn and soy beans to assess the impact of changes in yield assumptions. 
 

44

This uncertainty analysis provides information on both the range of possible 

outcomes for the parameters analyzed, an estimate of the degree of confidence that the 

actual result will be within a particular range (in our case, we estimated a 95% confidence 

interval) and an estimate of the central tendency or midpoint of the GHG performance 

estimate. 

In the proposal, we considered several options for the timeframe over which to 

measure lifecycle GHG impacts and the possibility of discounting those impacts. Based 

on peer review recommendations and other comments received, EPA is finalizing its 

assessments based on an analysis assuming 30 years of continued emission impacts after 

the program is fully phased in by 2022 and without discounting those impacts. 

EPA also notes that it received significant comment on our proposed baseline 

lifecycle greenhouse gas assessment of gasoline and diesel (“petroleum baseline”). 

While EPA has made several updates to the petroleum analysis in response to comments 

(see Section V for further discussion), we are finalizing the approach based on our 

interpretation of the definition in the Act as requiring that the petroleum baseline 

represent an average of the gasoline and diesel fuel (whichever is being replaced by the 

renewable fuel) sold as transportation fuel in 2005. 

As discussed in more detail later, the modeling results developed for purposes of 

the final rule provide a rich and comprehensive base of information for making the 
 

45

threshold determinations. There are numerous modeling runs, reflecting updated inputs 

to the model, sensitivity analyses, and uncertainty analyses. The results for different 

scenarios include a range and a best estimate or mid-point. Given the potentially 

conservative nature of the base crop yield assumption, EPA believes the actual crop yield 

in 2022 may be above the base yield; however we are not in a position to characterize 

how much above it might be. To the extent actual yields are higher, the base yield 

modeling results would underestimate to some degree the actual GHG emissions 

reductions compared to the baseline. 

In making the threshold determinations for this rule, EPA weighed all of the 

evidence available to it, while placing the greatest weight on the best estimate value for 

the base yield scenario. In those cases where the best estimate for the base yield scenario 

exceeds the reduction threshold, EPA judges that there is a good basis to be confident that 

the threshold will be achieved and is determining that the bio-fuel pathway complies with 

the applicable threshold. To the extent the midpoint of the scenarios analyzed lies further 

above a threshold for a particular biofuel pathway, we have increasingly greater 

confidence that the biofuel exceeds the threshold. 

 EPA recognizes that certain commenters suggest that there is a very high degree 

of uncertainty associated in particular with determining international indirect land use 

changes and their emissions impacts, and because of this EPA should exclude any 

calculation of international indirect land use changes in its lifecycle analysis. 

Commenters say EPA should make the threshold determinations based solely on 
 

46

modeling of other sources of lifecycle emissions. In effect, commenters argue that the 

uncertainty of the modeling associated with international indirect land use change means 

we should use our modeling results but exclude that part of the results associated with 

international land use change. 

For the reasons discussed above and in more detail in Section V, EPA rejects the 

view that the modeling relied upon in the final rule, which includes emissions associated 

with international indirect land use change, is too uncertain to provide a credible and 

reasonable scientific basis for determining whether the aggregate lifecycle emissions 

exceed the thresholds. In addition, as discussed elsewhere, the definition of lifecycle 

emissions includes significant indirect emissions associated with land use change. In 

deciding whether a bio-fuel pathway meets the threshold, EPA has to consider what it 

knows about all aspects of the lifecycle emissions, and decide whether there is a valid 

basis to find that the aggregate lifecycle emissions of the fuel, taking into account 

significant indirect emissions from land use change meets the threshold. Based on the 

analyses conducted for this rule, EPA has determined international indirect land use 

impacts are significant and therefore must be included in threshold compliance 

assessment. 

If the international land use impacts were so uncertain that their impact on 

lifecycle GHG emissions could not be adequately determined, as claimed by commenters, 

this does not mean EPA could assume the international land use change emissions are 

zero, as commenters suggest. High uncertainty would not mean that emissions are small 
 

47

and can be ignored; rather it could mean that we could not tell whether they are large or 

small. If high uncertainty meant that EPA were not able to determine that indirect 

emissions from international land use change are small enough that the total lifecycle 

emissions meet the threshold, then that fuel could not be determined to meet the GHG 

thresholds of EISA and the fuel would necessarily have to be excluded from the program. 

In any case, that is not the situation here as EPA rejects commenters’ suggestion 

and does not agree that the uncertainty over the indirect emissions from land use change 

is too high to make a reasoned threshold determination. Therefore biofuels with a 

significant international land use impact are included within this program. 

 c. Consideration of Fuel Pathways Not Yet Modeled 

Not all biofuel pathways have been directly modeled for this rule. For example, 

while we have modeled cellulosic biofuel produced from corn stover, we have not 

modeled the specific GHG impact of cellulosic biofuel produced from other crop residues 

such as wheat straw or rice straw. Today, in addition to finalizing a threshold compliance 

determination for those pathways we specifically modeled, in some cases, our technical 

judgment indicates other pathways are likely to be similar enough to modeled pathways 

that we are also assured these similar pathways qualify. These pathways include fuels 

produced from the same feedstock and using the same production process but produced 

in countries other than those modeled. The agricultural sector modeling used for our 

lifecycle analysis does not predict any soybean biodiesel or corn ethanol will be imported 
 

48

into the U.S., or any imported sugarcane ethanol from production in countries other than 

Brazil. However, these rules do not prohibit the use in the U.S. of these fuels produced in 

countries not modeled if they are also expected to comply with the eligibility 

requirements including meeting the thresholds for GHG performance. Although the 

GHG emissions of producing these fuels from feedstock grown or biofuel produced in 

other countries has not been specifically modeled, we do not anticipate their use would 

impact our conclusions regarding these feedstock pathways. The emissions of producing 

these fuels in other countries could be slightly higher or lower than what was modeled 

depending on a number of factors. Our analyses indicate that crop yields for the crops in 

other countries where these fuels are also most likely to be produced are similar or lower 

than U.S. values indicating the same or slightly higher GHG impacts. Agricultural sector 

inputs for the crops in these other countries are roughly the same or lower than the U.S. 

pointing toward the same or slightly lower GHG impacts. If crop production were to 

expand due to biofuels in the countries where the models predict these biofuels might 

additionally be produced would tend to lower our assessment of international indirect 

impacts but could increase our assessment of the domestic (i.e., the country of origin) 

land use impacts. EPA believes, because of these offsetting factors along with the small 

amounts of fuel potentially coming from other countries, that incorporating fuels 

produced in other countries will not impact our threshold analysis. Therefore, fuels of the 

same fuel type, produced from the same feedstock using the same fuel production 

technology as modeled fuel pathways will be assessed the same GHG performance 

decisions regardless of country of origin. These pathways also include fuels that might be 

produced from similar feedstock sources to those already modeled and which are 
 

49

expected to have less or no indirect land use change. In such cases, we believe that in 

order to compete economically in the renewable fuel marketplace such pathways are 

likely to be at least as energy efficient as those modeled and thus have comparable 

lifecycle GHG performance. Based on these considerations, we are extending the 

lifecycle results for the fuel pathways already modeled to 5 broader categories of 

feedstocks. This extension of lifecycle modeling results is discussed further in Section 

V.C. 

We have established five categories of biofuel feedstock sources under which 

modeled feedstock sources and feedstock sources similar to those modeled are grouped 

and qualify on the basis of our existing modeling. These are: 

1. Crop residues such as corn stover, wheat straw, rice straw, citrus residue 

2. Forest material including eligible forest thinnings and solid residue remaining 

from forest product production 

3. Annual cover crops planted on existing crop land such as winter cover crops 

4. Separated food and yard waste including biogenic waste from food processing 

5. Perennial grasses including switchgrass and miscanthus 

The full set of pathways for which we have been able to make a compliance 

decision are described in Section V. 
 

50

Threshold determinations for certain other pathways were not possible at this time 

because sufficient modeling or data is not yet available. In some of these cases, we 

recognize that a renewable fuel is already being produced from an alternative feedstock. 

Although we have the data needed for analysis, we did not have sufficient time to 

complete the necessary lifecycle GHG impact assessment for this final rule. We will 

model and evaluate additional pathways after this final rule on the basis of current or 

likely commercial production in the near-term and the status of current analysis at EPA. 

EPA anticipates modeling grain sorghum ethanol, woody pulp ethanol, and palm oil 

biodiesel after this final rule and including the determinations in a rulemaking within 6 

months. Our analyses project that they will be used in meeting the RFS2 volume 

standard in the near-term. During the course of the NPRM comment period, EPA 

received detailed information on these pathways and is currently in the process of 

analyzing these pathways. We have received comments on several additional 

feedstock/fuel pathways, including rapeseed/canola, camelina, sweet sorghum, wheat, 

and mustard seed, and we welcome parties to utilize the petition process described in 

Section V.C to request EPA to examine additional pathways. 

We anticipate there could be additional cases where we currently do not have 

information on which to base a lifecycle GHG assessment perhaps because we are not yet 

aware of potential unique plant configurations or operations that could result in greater 

efficiencies than assumed in our analysis. In many cases, such alternative pathways 

could have been explicitly modeled as a reasonably straightforward extension of 

pathways we have modeled if the necessary information had been available. For 
 

51

example, while we have modeled specific enhancements to corn starch ethanol 

production such as membrane separation or corn oil extraction, there are likely other 

additional energy saving or co-product pathways available or under development by the 

industry. It is reasonable to also consider these alternative energy saving or co-product 

pathways based upon their technical merits. Other current or emerging pathways may 

require new analysis and modeling for EPA to fully evaluate compliance. For example, 

fuel pathways with feedstocks or fuel types not yet modeled by EPA may require 

additional modeling and, it follows, public comment before a determination of 

compliance can be made. 

Therefore, for those fuel pathways that are different than those pathways EPA has 

listed in today’s regulations, EPA is establishing a petition process whereby a party can 

petition the Agency to consider new pathways for GHG reduction threshold compliance. 

As described in Section V.C, the petition process is meant for parties with serious 

intention to move forward with production via the petitioned fuel pathway and who have 

moved sufficiently forward in the business process to show feasibility of the fuel 

pathway’s implementation. In addition, if the petition addresses a fuel pathway that 

already has been determined to qualify as one or more types of renewable fuel under RFS 

(e.g., renewable fuel, or advanced biofuel), the pathway must have the potential to result 

in qualifying for a renewable fuel type for which it was not previously qualified. Thus, 

for example, the Agency will not undertake any additional review for a party wishing to 

get a modified LCA value for a previously approved fuel pathway if the desired new 

value would not change the overall pathway classification. 
 

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 The petition must contain all the necessary information on the fuel pathway to 

allow EPA to effectively assess the lifecycle performance of the new fuel pathway. See 

Section V.C for a full description. EPA will use the data supplied via the petition and 

other pertinent data available to the Agency to evaluate whether the information for that 

fuel pathway, combined with information developed in this rulemaking for other fuel 

pathways that have been determined to exceed the threshold, is sufficient to allow EPA to 

evaluate the pathway for a determination of compliance. We expect such a determination 

would be pathway specific. For some fuel pathways with unique modifications or 

enhancements to production technologies in pathways otherwise modeled for the 

regulations listed today, EPA may be able to evaluate the pathway as a reasonably 

straight-forward extension of our current assessments. In such cases, we would expect to 

make a decision for that specific pathway without conducting a full rulemaking process. 

We would expect to evaluate whether the pathway is consistent with the definitions of 

renewable fuel types in the regulations, generally without going through rulemaking, and 

issue an approval or disapproval that applies to the petitioner. We anticipate that we will 

subsequently propose to add the pathway to the regulations. Other current or emerging 

fuel pathways may require significant new analysis and/or modeling for EPA to conduct 

an adequate evaluation for a compliance determination (e.g., feedstocks or fuel types not 

yet included in EPA’s assessments for this regulation). For these pathways, EPA would 

give notice and seek public comment on a compliance determination under the annual 

rulemaking process established in today’s regulations. If we make a technical 

determination of compliance, then we anticipate the fuel producer will be able to generate 
 

53

RINs for fuel produced under the additional pathway following the next available 

quarterly update of the EPA Moderated Transaction System (EMTS). EPA will process 

those petitions as expeditiously as possible for those pathways which are closer to the 

commercial production stage than others. In all events, parties are expected to begin this 

process with ample lead time as compared to their commercial start dates. Further 

discussion of this petition process can be found in Section V.C. 

We note again that the continued work of EPA and others is expected to result in 

improved models and data sources, and that re-analysis based on such updated 

information could revise these determinations. Any such reassessment that would impact 

compliance would necessarily go through rulemaking and would only be applicable to 

production from future facilities after the revised rule was finalized, as required by EISA.

 4. Compliance with Renewable Biomass Provision

EISA changed the definition of “renewable fuel” to require that it be made from 

feedstocks that qualify as “renewable biomass.” EISA’s definition of the term 

“renewable biomass” limits the types of biomass as well as the types of land from which 

the biomass may be harvested. The definition includes: 

• Planted crops and crop residue from agricultural land cleared prior to 

December 19, 2007 and actively managed or fallow on that date 
 

54

• Planted trees and tree residue from tree plantations cleared prior to 

December 19, 2007 and actively managed on that date 

• Animal waste material and byproducts 

• Slash and pre-commercial thinnings from non-federal forestlands that are 

neither old-growth nor listed as critically imperiled or rare by a State 

Natural Heritage program 

• Biomass cleared from the vicinity of buildings and other areas at risk of 

wildfire 

• Algae 

• Separated yard waste and food waste. 

In today’s rule, EPA is finalizing definitions for the many terms included within 

the definition of renewable biomass. Where possible, EPA has adhered to existing 

statutory, regulatory or industry definitions for these terms, although in some cases we 

have altered definitions to conform to EISA’s statutory language, to further the goals of 

EISA, or for ease of program implementation. For example, EPA is defining 

“agricultural land” from which crops and crop residue can be harvested for RINgenerating renewable fuel production as including cropland, pastureland, and land 
 

55

enrolled in the Conservation Reserve Program. An in-depth discussion of the renewable 

biomass definitions can be found in Section II.B.4. 

In keeping with EISA, under today’s final rule, renewable fuel producers may 

only generate RINs for fuels made from feedstocks meeting the definition of renewable 

biomass. In order to implement this requirement, we are finalizing three potential 

mechanisms for domestic and foreign renewable fuel producers to verify that their 

feedstocks comply with this requirement. The first involves renewable biomass 

recordkeeping and reporting requirements by renewable fuel producers for their 

individual facilities. As an alternative to these individual recordkeeping and reporting 

requirements, the second allows renewable fuel producers to form a consortium to fund 

an independent third-party to conduct an annual renewable biomass quality-assurance 

survey, based on a plan approved by EPA. The third is an aggregate compliance 

approach applicable only to crops and crop residue from the U.S. It utilizes USDA’s 

publicly available agricultural land data as the basis for an EPA determination of 

compliance with the renewable biomass requirements for these particular feedstocks. 

This determination will be reviewed annually, and if EPA finds it is no longer warranted, 

then renewable fuel producers using domestically grown crops and crop residue will be 

required to conduct individual or consortium-based verification processes to ensure that 

their feedstocks qualify as renewable biomass. These final provisions are described 

below, with a more in-depth discussion in Section II.B.4. 
 

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For renewable fuel producers using feedstocks other than planted crops or crop 

residue from agricultural land that do not choose to participate in the third-party survey 

funded by an industry consortium, the final renewable biomass recordkeeping and 

reporting provisions require that individual producers obtain documentation about their 

feedstocks from their feedstock supplier(s) and take the measures necessary to ensure that 

they know the source of their feedstocks and can demonstrate to EPA that they have 

complied with the EISA definition of renewable biomass. Specifically, EPA’s renewable 

biomass reporting requirements for producers who generate RINs include a certification 

on renewable fuel production reports that the feedstock used for each renewable fuel 

batch meets the definition of renewable biomass. Additionally, producers will be 

required to include with their quarterly reports a summary of the types and volumes of 

feedstocks used throughout the quarter, as well as maps of the land from which the 

feedstocks used in the quarter were harvested. EPA’s final renewable biomass 

recordkeeping provisions require renewable fuel producers to maintain sufficient records 

to support their claims that their feedstocks meet the definition of renewable biomass, 

including maps or electronic data identifying the boundaries of the land where the 

feedstocks were produced, documents tracing the feedstocks from the land to the 

renewable fuel production facility, other written records from their feedstock suppliers 

that serve as evidence that the feedstock qualifies as renewable biomass, and for 

producers using planted trees or tree residue from tree plantations, written records that 

serve as evidence that the land from which the feedstocks were obtained was cleared 

prior to December 19, 2007 and actively managed on that date. 
 

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Based on USDA’s publicly available agricultural land data, EPA is able to 

establish a baseline of the aggregate amount of U.S. agricultural land (meaning cropland, 

pastureland and CRP land in the United States) that is available for the production of 

crops and crop residues for use in renewable fuel production consistent with the 

definition of renewable biomass. EPA has determined that, in the aggregate this amount 

of agricultural land (land cleared or cultivated prior to EISA’s enactment (December 19, 

2007) and actively managed or fallow, and nonforested on that date) is expected to, at 

least in the near term, be sufficient to support EISA renewable fuel obligations and other 

foreseeable demands for crop products, without clearing and cultivating additional land. 

EPA also believes that economic factors will lead farmers to use the “agricultural land” 

available for crop production under EISA rather than bring new land into crop 

production. As a result, EPA is deeming renewable fuel producers using domesticallygrown crops and crop residue as feedstock to be in compliance with the renewable 

biomass requirements, and those producers need not comply with the recordkeeping and 

quarterly reporting requirements as established for the non–crop based biomass sector. 

However, EPA will annually review USDA data on lands in agricultural production to 

determine if these conclusions remain valid. If EPA determines that the 2007 baseline 

amount of eligible agricultural land has been exceeded, EPA will publish a notice of that 

finding in the Federal Register. At that point, renewable fuel producers using planted 

crops or crop residue from agricultural lands would be subject to the same recordkeeping 

and reporting requirements as other renewable fuel producers. 

 5. EPA-Moderated Transaction System
 

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We introduced the EPA Moderated Transaction System (EMTS) in the NPRM as 

a new method for managing the generation of RINs and transactions involving RINs. 

EMTS is designed to resolve the RIN management issues of RFS1 that lead to 

widespread RIN errors, many times resulting in invalid RINs and often tedious remedial 

procedures to resolve those errors. It is also designed to address the added RIN 

categories, more complex RIN generation requirements, and additional volume of RINs 

associated with RFS2. Commenters broadly support EMTS and most stated that its use 

should coincide with the start of RFS2; however, many commenters expressed concerns 

over having sufficient time to implement the new system. In today’s action, we are 

requiring the use of EMTS for all RFS2 RIN generations and transactions beginning July 

1, 2010. EPA has utilized an open process for the development of EMTS since it was 

first introduced in the NPRM, conducting workshops and webinars, and soliciting 

stakeholder participation in its evaluation and testing. EPA pledges to work with the 

regulated community, as a group and individually, to ensure EMTS is successfully 

implemented. EPA anticipates that with this level of assistance, regulated parties will not 

experience significant difficulties in transitioning to the new system, and EPA believes 

that the many benefits of the new system warrant its immediate use. 

 6. Other Changes to the RFS Program

 Today's final rule also makes a number of other changes to the RFS program that 

are described in more detail in Sections II and III below, including: 
 

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• Grandfathering provisions: Renewable fuel from existing facilities is exempt from 

the lifecycle GHG emission reduction threshold of 20% up to a baseline volume 

for that facility that will be established at the time of registration. As discussed in 

Section II.B.3, the exemption from the 20% GHG threshold applies only to 

renewable fuel that is produced from facilities which commenced construction on 

or before December 19, 2007, or in the case of ethanol plants that use natural gas 

or biodiesel for process heat, on or before December 31, 2009. 

• Renewable fuels produced from municipal solid waste (MSW): The new 

renewable biomass definition in EISA modified the ability for MSW-derived fuels 

to qualify under the RFS program by restricting it to “separated yard waste or 

food waste.” We are finalizing provisions that would allow certain portions of 

MSW to be included as renewable biomass, provided that reasonable separation 

has first occurred. 

• Equivalence Values: We are generally maintaining the provisions from RFS1 that 

the Equivalence Value for each renewable fuel will be based on its energy content 

in comparison to ethanol, adjusted for renewable content. The cellulosic biofuel, 

advanced biofuel, and renewable fuel standards can be met with ethanolequivalent volumes of renewable fuel. However, since the biomass-based diesel 

standard is a “diesel” standard, its volume must be met on a biodiesel-equivalent 

energy basis. 
 

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• Cellulosic biofuel waiver credits: If EPA reduces the required volume of 

cellulosic biofuel according to the waiver provisions in EISA, EPA will offer a 

number of credits to obligated parties no greater than the reduced cellulosic 

biofuel standard. These waiver credits are not allowed to be traded or banked for 

future use, and are only allowed to be used to meet the cellulosic biofuel standard 

for the year that they are offered. In response to concerns expressed in comments 

on the proposal, we are implementing certain restrictions on the use of these 

waiver credits. For example, unlike Cellulosic Biofuel RINs, waiver credits may 

not be used to meet either the advanced biofuel standard or the total renewable 

fuel standard. For the 2010 compliance period, since the cellulosic standard is 

lower than the level otherwise required by EISA, we are making cellulosic waiver 

credits available to obligated parties for end-of-year compliance should they need 

them at a price of $1.56 per gallon-RIN. 

• Obligated fuels: EISA expanded the program to cover “transportation fuel”, not 

just gasoline. Therefore, under RFS2, obligated fuel volumes will include all 

gasoline and all MVNRLM diesel fuel. Other fuels such as jet fuel and fuel 

intended for use in ocean-going vessels are not obligated fuels under RFS2. 

However, renewable fuels used in jet fuel or heating oil are valid for meeting the 

renewable fuel volume mandates. Similarly, while we are not including natural 

gas, propane or electricity used in transportation as obligated fuels at this time, we 
 

61

will allow renewable forms of these fuels to qualify under the program for 

generating RINs. 

B. Impacts of Increasing Volume Requirements in the RFS2 Program 

 The displacement of gasoline and diesel with renewable fuels has a wide range of 

environmental and economic impacts. As we describe in Sections IV-IX, we have 

assessed many of these impacts for the final rule. It is difficult to ascertain how much of 

these impacts might be due to the natural growth in renewable fuel use due to market 

forces as crude oil prices rise versus what might be forced by the RFS2 standards. 

Regardless, these assessments provide important information on the wider public policy 

considerations related to renewable fuel production and use, climate change, and national 

energy security. Where possible, we have tried to provide two perspectives on the 

impacts of the renewable fuel volumes mandated in EISA – both relative to the RFS1 

mandated volumes, and relative to a projection from EIA (AEO 2007) of renewable fuel 

volumes that would have been expected without EISA. 

Based on the results of our analyses, when fully phased in by 2022, the increased 

volume of renewable fuel required by this final rule in comparison to the AEO 2007 

forecast would result in 138 million metric tons fewer CO2-equivalent GHG emissions 

(annual average over 30 years), the equivalent of removing 27 million vehicles from the 

road today. 
 

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At the same time, increases in emissions of hydrocarbons, nitrogen oxides, 

particulate matter, and other pollutants are projected to lead to increases in populationweighted annual average ambient PM and ozone concentrations, which in turn are 

anticipated to lead to up to 245 cases of adult premature mortality. The air quality 

impacts, however, are highly variable from region to region. Ambient PM2.5 is likely to 

increase in areas associated with biofuel production and transport and decrease in other 

areas; for ozone, many areas of the country will experience increases and a few areas will 

see decreases. Ethanol concentrations will increase substantially; for the other modeled 

air toxics there are some localized impacts, but relatively little impact on national average 

concentrations. We note that the air quality modeling results presented in this final rule 

do not constitute the “anti-backsliding” analysis required by Clean Air Act section 

211(v). EPA will be analyzing air quality impacts of increased renewable fuel use 

through that study and will promulgate appropriate mitigation measures under section 

211(v), separate from this final action. 

In addition to air quality, there are also expected to be adverse impacts on both 

water quality and quantity as the production of biofuels and their feedstocks increase. 

In addition to environmental impacts, the increased volumes of renewable fuels 

required by this final rule are also projected to have a number of other energy and 

economic impacts. The increased renewable fuel use is estimated to reduce dependence 

on foreign sources of crude oil, increase domestic sources of energy, and diversify our 

energy portfolio to help in moving beyond a petroleum-based economy. The increased 

use of renewable fuels is also expected to have the added benefit of providing an 
 

63

expanded market for agricultural products such as corn and soybeans and open new 

markets for the development of cellulosic feedstock industries and conversion 

technologies. Overall, however, we estimate that the renewable fuel standards will result 

in significant net benefits, ranging between $16 and $29 billion in 2022. 

Table I.B-1 summarizes the results of our impacts analyses of the volumes of 

renewable fuels required by the RFS2 standards in 2022 relative to the AEO2007 

reference case and identifies the section where you can find further explanation of it. As 

we work to implement the requirements of EISA, we will continue to assess these 

impacts. These are the annual impacts projected in 2022 when the program is fully 

phased in. Impacts in earlier years would differ but in most cases were not able to be 

modeled or assessed for this final rule. 
 

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Table I.B-1 

Impact Summary of the RFS2 Standards in 2022 Relative to the AEO2007 

Reference Case (2007 Dollars) 

Category Impact in 2022 Section 

Discussed 

Emissions and Air Quality 

GHG Emissions -138 million metric tons V.D. 

Non-GHG Emissions 

(criteria and toxic 

pollutants) 

-1% to +10% depending on the pollutant VI.A. 

Nationwide Ozone +0.12 ppb population-weighted seasonal max 

8hr average 

VIII.D. 

Nationwide PM2.5 +0.002 μg/m3 population-weighted annual 

average PM2.5 

VIII.D. 

Nationwide Ethanol +0.409 μg/m3 population-weighted annual 

average 

VI.D. 

Other Nationwide 

Air Toxics 

-0.0001 to -0.023 μg/m3 population-weighted 

annual average depending on the pollutant 

VI.D. 

PM2.5-related Premature 

Mortality 

33 to 85 additional cases of adult mortality 

(estimates vary by study) 

VIII.D. 

Ozone-related Premature 

Mortality 

36 to 160 additional cases of adult mortality 

(estimates vary by study) 

VIII.D. 
 

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Other Environmental Impacts 

Loadings to the 

Mississippi River from the 

Upper Mississippi River 

Basin 

Nitrogen: +1,430 million lbs. (1.2%) 

Phosphorus: +132 million lbs. (0.7%) 

IX 

 

Fuel Costs 

Gasoline Costs -2.4¢/gal VII.D. 

Diesel Costs -12.1 ¢/gal VII.D. 

Overall Fuel Cost -$11.8 Billion VII.D. 

Gasoline and Diesel 

Consumption 

- 13.6 Bgal VII.C. 

 

Food Costs 

Corn +8.2% VIII.A. 

Soybeans +10.3% VIII.A. 

Food +$10 per capita VIII.A. 

 

Economic Impacts 

Energy Security +$2.6 Billion VIII.B. 

Monetized Health Impacts -$0.63 to -$2.2 Billion VIII.D. 

GHG Impacts (SCC)a +$0.6 to $12.2 Billion (estimates vary by SCC VIII.C. 
 

66

assumption) 

Oil Imports -$41.5 Billion VIII.B 

Farm Gate Food +$3.6 Billion VIII.A. 

Farm Income +$13 Billion (+36%) VIII.A. 

Corn Exports -$57 Million (-8%) VIII.A. 

Soybean Exports -$453 Million (-14%) VIII.A 

 

Total Net Benefitsb +$13 to $26 Billion (estimates vary by SCC 

assumption) 

VIII.F 

 

a

 The models used to estimate SCC values have not been exercised in a systematic manner that would allow 

researchers to assess the probability of different values. Therefore, the interim SCC values should not be 

considered to form a range or distribution of possible or likely values. See Section VIII.D for a complete 

summary of the interim SCC values. 

b

 Sum of Overall Fuel Costs, Energy Security, Monetized Health Impacts, and GHG Impacts (SCC). 
 

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II. Description of the Regulatory Provisions 

 While EISA made a number of changes to CAA section 211(o) that must be reflected in 

the RFS program regulations, it left many of the basic program elements intact, including the 

mechanism for translating national renewable fuel volume requirements into applicable standards 

for individual obligated parties, requirements for a credit trading program, geographic 

applicability, treatment of small refineries, and general waiver provisions. As a result, many of 

the regulatory requirements of the RFS1 program will remain largely or, in some cases, entirely 

unchanged. These provisions include the distribution of RINs, separation of RINs, use of RINs 

to demonstrate compliance, provisions for exporters, recordkeeping and reporting, deficit 

carryovers, and the valid life of RINs. 

 The primary elements of the RFS program that we are changing to implement the 

requirements in EISA fall primarily into the following seven areas: 

1) Expansion of the applicable volumes of renewable fuel 

2) Separation of the volume requirements into four separate categories of renewable 

fuel, with corresponding changes to the RIN and to the applicable standards 

3) New definitions of renewable fuel, advanced biofuel, biomass-based diesel, and 

cellulosic biofuel. 
 

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4) New requirement that renewable fuels meet certain lifecycle emission reduction 

thresholds. 

5) New definition of renewable biomass from which renewable fuels can be made, 

including certain land use restrictions. 

6) Expansion of the types of fuels that are subject to the standards to include diesel. 

7) Inclusion of specific types of waivers for different categories of renewable fuels 

and, in certain circumstances, EPA-generated credits for cellulosic biofuel. 

 EISA does not change the basic requirement under CAA 211(o) that the RFS program 

include a credit trading program. In the May 1, 2007 final rulemaking implementing the RFS1 

program, we described how we reviewed a variety of approaches to program design in 

collaboration with various stakeholders. We finally settled on a RIN-based system for 

compliance and credit purposes as the one which met our goals of being straightforward, 

maximizing flexibility, ensuring that volumes are verifiable, and maintaining the existing system 

of fuel distribution and blending. RINs represent the basic framework for ensuring that the 

statutorily required volumes of renewable fuel are used as transportation fuel in the U.S. Since 

the RIN-based system generally has been successful in meeting the statutory goals, we are 

maintaining much of its structure under RFS2. 
 

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 This section describes the regulatory changes we are finalizing to implement the new 

EISA provisions. Section III describes other changes to the RFS program that we considered or 

are finalizing, including an EPA-moderated RIN trading system that provides a context within 

which all RIN transfers will occur. 

A. Renewable Identification Numbers (RINs) 

 Under RFS2, each RIN will continue to represent one gallon of renewable fuel in the 

context of demonstrating compliance with Renewable Volume Obligations (RVO), consistent 

with our approach under RFS1, and the RIN will continue to have unique information similar to 

the 38 digits in RFS1. However in the EPA Moderated Transaction System (EMTS), RIN detail 

information will be available but generally hidden during transactions. In general the codes 

within the RIN will have the same meaning under RFS2 as they do under RFS1, with the 

exception of the D code which will be expanded to cover the four categories of renewable fuel 

defined in EISA. 

 As described in Section I.A.2, the RFS2 regulatory program will go into effect on July 1, 

2010, but the 2010 percentage standards issued as part of today's rule will apply to all gasoline 

and diesel produced or imported on or after January 1, 2010. As a result, some 2010 RINs will 

be generated under the RFS1 requirements and others will be generated under the RFS2 

requirements, but all RINs generated in 2010 will be valid for meeting the 2010 annual 

standards. Since RFS1 RINs and RFS2 RINs will differ in the meaning of the D codes, we are 

implementing a mechanism for distinguishing between these two categories of RINs in order to 
 

70

appropriately apply them to the standards. In short, we are requiring the use of D codes under 

RFS2 that do not overlap the values for the D codes under RFS1. Table II.A-1 describes the D 

code definitions we are finalizing in today's action. 

Table II.A-1 

Final D Code Definitions 

D value Meaning under RFS1 Meaning under RFS2 

1 Cellulosic biomass ethanol Not applicable 

2 Any renewable fuel that is not 

cellulosic biomass ethanol 

Not applicable 

3 Not applicable Cellulosic biofuel 

4 Not applicable Biomass-based diesel 

5 Not applicable Advanced biofuel 

6 Not applicable Renewable fuel 

7 Not applicable Cellulosic diesel 

 Under this approach, D code values of 1 and 2 are only relevant for RINs generated under 

RFS1, and D code values of 3, 4, 5, 6, and 7 are only relevant for RINs generated under RFS2. 

As described in Section I.A.2, the RFS1 regulations will apply in January through June of 2010, 

while the RFS2 regulations will become effective on July 1, 2010. RINs generated under RFS1 

regulations in the first three months of 2010 can be used for meeting the four 2010 standards 

applicable under RFS2. To accomplish this, these RFS1 RINs will be subject to the RFS1/RFS2 

transition provisions wherein they will be deemed equivalent to one of the four RFS2 RIN 
 

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categories using their RR and/or D codes. See Section II.G.4 for further description of how 

RFS1 RINs will be used to meet standards under RFS2. The determination of which D code will 

be assigned to a given batch of renewable fuel is described in more detail in Section II.D.2 

below. 

 Table II.A-1 includes one D code corresponding to each of the four renewable fuel 

categories defined in EISA, and an additional D code of 7 corresponding to the unique, 

additional type of renewable fuel called cellulosic diesel. As described in the NPRM, a diesel 

fuel product produced from cellulosic feedstocks that meets the 60% GHG threshold could 

qualify as either cellulosic biofuel or biomass-based diesel. The NPRM described two possible 

approaches to this unique category of renewable fuel: 

1. Have the producer of the cellulosic diesel designate their fuel up front as either 

cellulosic biofuel with a D code of 3, or biomass-based diesel with a D code of 4, 

limiting the subsequent potential in the marketplace for the RIN to be used for just 

one standard or the other. 

2. Have the producer of the cellulosic diesel designate their fuel with a new 

cellulosic D code of 7, allowing the subsequent use of the RIN in the marketplace 

interchangeably for either the cellulosic biofuel standard or the biomass-based 

diesel standard. 
 

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 We are finalizing the second option. By creating an additional D code of 7 to represent 

cellulosic diesel RINs, we believe its value in the marketplace will be maximized as it will be 

priced according to the relative demand for cellulosic biofuel and biomass-based diesel RINs. 

For instance, if demand for cellulosic biofuel RINs is higher than demand for biomass-based 

diesel RINs, then cellulosic diesel RINs will be priced as if they are cellulosic biofuel RINs. Not 

only does this approach benefit producers, but it allows obligated parties the flexibility to apply a 

RIN with a D code of 7 to either their cellulosic biofuel RVO or their biomass-based diesel 

RVO, depending on the number of RINs they have acquired to meet these two obligations. It 

also helps the functionality of the RIN program by helping protect against the potential for 

artificial RIN shortages in the marketplace for one standard or the other even though sufficient 

qualifying fuel was produced. 

 Under RFS2, each batch-RIN generated will continue to uniquely identify not only a specific 

batch of renewable fuel, but also every gallon-RIN assigned to that batch. Thus the RIN will 

continue to be defined as follows: 

RIN: KYYYYCCCCFFFFFBBBBBRRDSSSSSSSSEEEEEEEE 

Where 

K = Code distinguishing assigned RINs from separated RINs 

YYYY = Calendar year of production or import 

CCCC = Company ID 
 

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FFFFF = Facility ID 

BBBBB = Batch number 

RR = Code identifying the Equivalence Value 

D = Code identifying the renewable fuel category 

SSSSSSSS = Start of RIN block 

EEEEEEEE = End of RIN block 

 B. New Eligibility Requirements for Renewable Fuels 

 Aside from the higher volume requirements, most of the substantive changes that EISA 

makes to the RFS program affect the eligibility of renewable fuels in meeting one of the four 

volume requirements. Eligibility is determined based on the types of feedstocks that are used, 

the land that is used to grow feedstocks for renewable fuel production, the processes that are 

used to convert those feedstocks into fuel, and the lifecycle greenhouse gas (GHG) emissions 

that are emitted in comparison to the gasoline or diesel that the renewable fuel displaces. This 

section describes these eligibility criteria and how we are implementing them for the RFS2 

program. 

 1. Changes in Renewable Fuel Definitions 

 Under the previous Renewable Fuel Standards (RFS1), renewable fuel was defined 

generally as “any motor vehicle fuel that is used to replace or reduce the quantity of fossil fuel 

present in a fuel mixture used to fuel a motor vehicle”. The RFS1 definition included motor 
 

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vehicle fuels produced from biomass material such as grain, starch, fats, greases, oils, and 

biogas. The definition specifically included cellulosic biomass ethanol, waste derived ethanol, 

and biodiesel, all of which were defined separately. (See 72 FR 23915). 

 The definitions of renewable fuels under today’s rule (RFS2) are based on the new 

statutory definition in EISA. Like the previous rules, the definitions in RFS2 include a general 

definition of renewable fuel, but unlike RFS1, we are including a separate definition of 

“Renewable Biomass” which identifies the feedstocks from which renewable fuels may be made. 

 Another difference in the definitions of renewable fuel is that RFS2 contains three 

subcategories of renewable fuels: 1) Advanced Biofuel, 2) Cellulosic Biofuel and 3) BiomassBased Diesel. Each must meet threshold levels of reduction of greenhouse gas emissions as 

discussed in Section II.B.2. The specific definitions and how they differ from RFS1 follow 

below. 

a. Renewable Fuel 

 “Renewable Fuel” is defined as fuel produced from renewable biomass and that is used to 

replace or reduce the quantity of fossil fuel present in a transportation fuel. The definition of 

“Renewable Fuel” now refers to “transportation fuel” rather than referring to motor vehicle fuel. 

“Transportation fuel” is also defined, and means fuel used in motor vehicles, motor vehicle 

engines, nonroad vehicles or nonroad engines (except for ocean going vessels). Also renewable 

fuel now includes heating fuel and jet fuel. 
 

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 Given that the primary use of electricity, natural gas, and propane is not for fueling 

vehicles and engines, and the producer generally does not know how it will be used, we cannot 

require that producers or importers of these fuels generate RINs for all the volumes they produce 

as we do with other renewable fuels. However, we are allowing fuel producers, importers and 

end users to include electricity, natural gas, and propane made from renewable biomass as a 

RIN-generating renewable fuel in RFS only if they can identify the specific quantities of their 

product which are actually used as a transportation fuel,. This may be possible for some portion 

of renewable electricity and biogas since many of the affected vehicles and equipment are in 

centrally-fueled fleets supplied under contract by a particular producer or importer of natural gas 

or propane. A producer or importer of renewable electricity or biogas who documents the use of 

his product in a vehicle or engine through a contractual pathway would be allowed to generate 

RINs to represent that product, if it met the definition of renewable fuel. (This is also discussed 

in Section II.D.2.a) 

 

 b. Advanced Biofuel 

 “Advanced Biofuel” is a renewable fuel other than ethanol derived from corn starch and 

for which lifecycle GHG emissions are at least 50% less than the gasoline or diesel fuel it 

displaces. Advanced biofuel would be assigned a D code of 5 as shown in Table II.A-1. 
 

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 While “Advanced Biofuel” specifically excludes ethanol derived from corn starch, it 

includes other types of ethanol derived from renewable biomass, including ethanol made from 

cellulose, hemicellulose, lignin, sugar or any starch other than corn starch, as long as it meets the 

50% GHG emission reduction threshold. Thus, even if corn starch-derived ethanol were made so 

that it met the 50% GHG reduction threshold, it will still be excluded from being defined as an 

advanced biofuel. Such ethanol while not an advanced biofuel will still qualify as a renewable 

fuel for purposes of meeting the standards. 

 c. Cellulosic Biofuel 

 Cellulosic biofuel is renewable fuel derived from any cellulose, hemicellulose, or lignin 

each of which must originate from renewable biomass. It must also achieve a lifecycle GHG 

emission reduction of at least 60%, compared to the gasoline or diesel fuel it displaces. 

Cellulosic biofuel is assigned a D code of 3 as shown in Table II.A-1. Cellulosic biofuel in 

general also qualifies as both “advanced biofuel” and “renewable fuel”. 

 The definition of cellulosic biofuel for RFS2 is broader in some respects than the RFS1 

definition of “cellulosic biomass ethanol”. That definition included only ethanol, whereas the 

RFS2 definition of cellulosic biofuels includes any biomass-to-liquid fuel such as cellulosic 

gasoline or diesel in addition to ethanol. The definition of “cellulosic biofuel” in RFS2 differs 

from RFS1 in another significant way. The RFS1 definition provided that ethanol made at any 

facility—regardless of whether cellulosic feedstock is used or not—may be defined as cellulosic 

if at such facility “animal wastes or other waste materials are digested or otherwise used to 
 

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displace 90% or more of the fossil fuel normally used in the production of ethanol.” This 

provision was not included in EISA, and therefore does not appear in the definitions pertaining to 

cellulosic biofuel in the final rule. 

 d. Biomass-Based Diesel 

 

 “Biomass-based diesel” includes both biodiesel (mono-alkyl esters) and non-ester 

renewable diesel (including cellulosic diesel). The definition of biodiesel is the same very broad 

definition of “biodiesel” that was in EPAct and in RFS1, and thus, it includes any diesel fuel 

made from biomass feedstocks. However, EISA added three restrictions. First, EISA requires 

that such fuel be made from renewable biomass. Second, its lifecycle GHG emissions must be at 

least 50% less than the diesel fuel it displaces. Third, the statutory definition of “Biomass-based 

diesel” excludes renewable fuel derived from co-processing biomass with a petroleum feedstock. 

In our proposed rule, we sought comment on two options for how co-processing could be treated. 

The first option considered co-processing to occur only if both petroleum and biomass feedstock 

are processed in the same unit simultaneously. The second option considered co-processing to 

occur if renewable biomass and petroleum feedstock are processed in the same unit at any time; 

i.e., either simultaneously or sequentially. Under the second option, if petroleum feedstock was 

processed in the unit, then no fuel produced from such unit, even from a biomass feedstock, 

would be deemed to be biomass-based diesel. 

We selected the first option to be used in the final rule. Under this approach, a batch of 

fuel qualifying for the D code of 4 that is produced in a processing unit in which only renewable 
 

78

biomass is the feedstock for such batch, will meet the definition of “Biomass-Based Diesel. 

Thus, serial batch processing in which 100% vegetable oil is processed one day/week/month and 

100% petroleum the next day/week/month could occur without the activity being considered “coprocessing.” The resulting products could be blended together, but only the volume produced 

from vegetable oil will count as biomass-based diesel. We believe this is the most 

straightforward approach and an appropriate one, given that it would allow RINs to be generated 

for volumes of fuel meeting the 50% GHG reduction threshold that is derived from renewable 

biomass, while not providing any credit for fuel derived from petroleum sources. In addition, 

this approach avoids the need for potentially complex provisions addressing how fuel should be 

treated when existing or even mothballed petroleum hydrotreating equipment is retrofitted and 

placed into new service for renewable fuel production or vice versa. 

 

 Under today’s rule, any fuel that does not satisfy the definition of biomass-based diesel 

only because it is co-processed with petroleum will still meet the definition of “Advanced 

Biofuel” provided it meets the 50% GHG threshold and other criteria for the D code of 5. 

Similarly it will meet the definition of renewable fuel if it meets a GHG emission reduction 

threshold of 20%. In neither case, however, will it meet the definition of biomass-based diesel. 

 This restriction is only really an issue for renewable diesel and biodiesel produced via the 

fatty acid methyl ester (FAME) process. For other forms of biodiesel, it is never made through 

any sort of co-processing with petroleum3

. Producers of renewable diesel must therefore specify 

 

3

 The production of biodiesel (mono alkyl esters) does require the addition of methanol which is usually derived 

from natural gas, but which contributes a very small amount to the resulting product. We do not believe that this 

was intended by the statute's reference to "co-processing" which we believe was intended to address only renewable 

fats or oils co-processed with petroleum in a hydrotreater to produce renewable diesel. 
 

79

whether or not they use "co-processing" to produce the fuel in order to determine the correct D 

code for the RIN. 

 e. Additional Renewable Fuel 

 The statutory definition of "additional renewable fuel" specifies fuel produced from 

renewable biomass that is used to replace or reduce fossil fuels used in heating oil or jet fuel. 

EISA indicates that EPA may allow for the generation of credits for such additional renewable 

fuel that will be valid for compliance purposes. Under the RFS program, RINs operate in the 

role of credits, and RINs are generated when renewable fuel is produced rather than when it is 

blended. In most cases, however, renewable fuel producers do not know at the time of fuel 

production (and RIN generation) how their fuel will ultimately be used. 

 Under RFS1, only RINs assigned to renewable fuel that was blended into motor vehicle 

fuel (i.e., highway fuel) are valid for compliance purposes. We therefore created special 

provisions requiring that RINs be retired if they were assigned to renewable fuel that was 

ultimately blended into nonroad fuel. The new EISA provisions regarding additional renewable 

fuel make the RFS1 requirement for retiring RINs unnecessary if renewable fuel is blended into 

heating oil or jet fuel. As a result, we have modified the regulatory requirements to allow RINs 

assigned to renewable fuel blended into heating oil or jet fuel in addition to highway and nonroad 

transportation fuels to continue to be valid for compliance purposes. From a regulatory 

standpoint, there is no difference between renewable fuels used for transportation purposes, 

versus heating oil and jet fuels. 
 

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EISA uses the term “home heating oil” in the definition of “additional renewable fuel.” 

The statute does not clarify whether the term should be interpreted to refer only to heating oil 

actually used in homes, or to all fuel of a type that can be used in homes. We note that the term 

“home heating oil” is typically used in industry in the latter manner, to refer to a type of fuel, 

rather than a particular use of it, and the term is typically used interchangeably in industry with 

heating oil, heating fuel, home heating fuel, and other terms depending on the region and market. 

We believe this broad interpretation based on typical industry usage best serves the goals and 

purposes of the statute. If EPA interpreted the term to apply only to heating oil actually used in 

homes, we would necessarily require tracking of individual gallons from production through 

ultimate use in use in homes in order to determine eligibility of the fuel for RINs. Given the 

fungible nature of the oil delivery market, this would likely be sufficiently difficult and 

potentially expensive so as to discourage the generation of RINs for renewable fuels used as 

home heating oil. This problem would be similar to that which arose under RFS1 for certain 

renewable fuels (in particular biodiesel) that were produced for the highway diesel market but 

were also suitable for other markets such as heating oil and non-road applications where it was 

unclear at the time of fuel production (when RINs are typically generated under the RFS 

program) whether the fuel would ultimately be eligible to generate RINs. Congress eliminated 

the complexity with regards to non-road applications in RFS2 by making all fuels used in both 

motor vehicle and nonroad applications subject to the renewable fuel standard program. We 

believe it best to interpret the Act so as to also avoid this type of complexity in the heating oil 

context. Thus, under today’s regulations, RINs may be generated for renewable fuel used as 

“heating oil,” as defined in existing EPA regulations at 80.2(ccc). In addition to simplifying 
 

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implementation and administration of the Act, this interpretation will best realize the intent of 

EISA to reduce or replace the use of fossil fuels, 

f. Cellulosic Diesel 

In the proposed rule, we sought comment on how diesel made from cellulosic feedstocks 

should be considered. Specifically, a diesel fuel product produced from cellulosic feedstocks 

that meets the 60% GHG threshold could qualify as either cellulosic biofuel or biomass-based 

diesel. Based on comments received, and as discussed previously in Section II.A, today’s rule 

requires the cellulosic diesel producer to categorize their product as cellulosic diesel with a D 

code of 7. It can then be traded in the marketplace and used for compliance with either the 

biomass-based diesel standard or the cellulosic biofuel standard. 

 2. Lifecycle GHG Thresholds 

 As part of the new definitions that EISA creates for cellulosic biofuel, biomass-based 

diesel, advanced biofuel, and renewable fuel, EISA also sets minimum performance measures or 

"thresholds" for lifecycle GHG emissions. These thresholds represent the percent reduction in 

lifecycle GHGs that is estimated to occur when a renewable fuel displaces gasoline or diesel fuel. 

Table II.B.2-1 lists the thresholds established by EISA. 
 

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Table II.B.2-1 

Lifecycle GHG Thresholds in EISA 

(percent reduction from a 2005 gasoline or diesel baseline) 

Renewable fuel 

Advanced biofuel 

Biomass-based diesel 

Cellulosic biofuel 

20% 

50% 

50% 

60% 

 

There are also special provisions for each of these thresholds: 

Renewable fuel: The 20% threshold only applies to renewable fuel from new 

facilities that commenced construction after December 19, 2007, with an 

additional exemption from the 20% threshold for ethanol plants that commenced 

construction in 2008 or 2009 and are fired with natural gas, biomass, or any 

combination thereof. Facilities not subject to the 20% threshold are 

"grandfathered." See Section II.B.3 below for a complete discussion of 

grandfathering. Also, EPA can adjust the 20% threshold to as low as 10%, but the 

adjustment must be the minimum possible, and the resulting threshold must be 

established at the maximum achievable level based on natural gas fired cornbased ethanol plants. 

Advanced biofuel and biomass-based diesel: The 50% threshold can be adjusted 

to as low as 40%, but the adjustment must be the minimum possible and result in 
 

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the maximum achievable threshold taking cost into consideration. Also, such 

adjustments can be made only if it is determined that the 50% threshold is not 

commercially feasible for fuels made using a variety of feedstocks, technologies, 

and processes. 

Cellulosic biofuel: Similarly to advanced biofuel and biomass-based diesel, the 

60% threshold applicable to cellulosic biofuel can be adjusted to as low as 50%, 

but the adjustment must be the minimum possible and result in the maximum 

achievable threshold taking cost into consideration. Also, such adjustments can 

be made only if it is determined that the 60% threshold is not commercially 

feasible for fuels made using a variety of feedstocks, technologies, and processes. 

 Our analyses of lifecycle GHG emissions, discussed in detail in Section V, identified a 

range of fuel pathways that are capable of complying with the GHG performance thresholds for 

each of these separate fuel standards. Thus, we have determined that the GHG thresholds in 

Table II.B.2-1 should not be adjusted. Further discussion of this determination can be found in 

Section V.C. 

3. Renewable Fuel Exempt from 20 Percent GHG Threshold

After considering comments received, the Agency has decided to implement the proposed 

option for interpreting the grandfathering provisions that provide an indefinite exemption from 

the 20 percent GHG threshold for renewable fuel facilities which have commenced construction 
 

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prior to December 19, 2007. For these facilities, only the baseline volume of renewable fuel is 

exempted. For ethanol facilities which commenced construction after that date and which use 

natural gas, biofuels or a combination thereof, we proposed that such facilities would be 

“deemed compliant” with the 20 percent GHG threshold. The exemption for such facilities is 

conditioned on construction being commenced on or before December 31, 2009, and is specific 

only to facilities which produce ethanol only, per language in EISA. The exemption would 

continue indefinitely, provided the facility continues to use natural gas and/or biofuel. This 

section provides the background and summary of the original proposal, and the reasons for the 

selection of this option. 

 a. General Background of the Exemption Requirement 

EISA amends section 211(o) of the Clean Air Act to provide that renewable fuel 

produced from new facilities which commenced construction after December 19, 2007 must 

achieve at least a 20% reduction in lifecycle greenhouse gas emissions compared to baseline 

lifecycle greenhouse gas emissions.7 

Facilities that commenced construction before December 

19, 2007 are “grandfathered” and thereby exempt from the 20% GHG reduction requirement. 

 For facilities that produce ethanol and for which construction commenced after 

December 19, 2007, section 210 of EISA states that 'for calendar years 2008 and 2009, any 

ethanol plant that is fired with natural gas, biomass, or any combination thereof is deemed to 

be in compliance with the 20% threshold.” Since all renewable fuel production facilities 

that commenced construction prior to the date of EISA enactment are covered by the more 

general grandfathering provision, this exemption can only apply to those facilities that 
 

85

commenced construction after enactment of EISA, and before the end of 2009. We 

proposed that the statute be interpreted to mean that fuel from such qualifying facilities, 

regardless of date of startup of operations, would be exempt from the 20% GHG threshold 

requirement for the same time period as facilities that commence construction prior to 

December 19, 2007, provided that such plants commence construction on or before 

December 31, 2009, complete such construction in a reasonable amount of time, and 

continue to burn only natural gas, biomass, or a combination thereof. Most commenters 

generally agreed with our proposal, while other commenters argued that the exemption was 

only meant to last for a two-year period. As we noted in the NPRM, we believe that it 

would be a harsh result for investors in these new facilities, and would be generally 

inconsistent with the energy independence goals of EISA, to interpret the Act such that these 

facilities would only be guaranteed two years of participation in the RFS2 program. In light 

of these considerations, we continue to believe that it is an appropriate interpretation of the 

Act to allow the deemed compliant exemption to continue indefinitely with the limitations 

we proposed. Therefore we are making final this interpretation in today’s rule. 

 b. Definition of Commenced Construction 

 In defining “commence” and “construction”, we proposed to use the definitions of 

“commence” and “begin actual construction” from the Prevention of Significant Deterioration 

(PSD) regulations, which draws upon definitions in the Clean Air Act. (40 CFR 52.21(b)(9) and 

(11)). Specifically, under the PSD regulations, “commence” means that the owner or operator 

has all necessary preconstruction approvals or permits and either has begun a continuous 
 

86

program of actual on-site construction to be completed in a reasonable time, or entered into 

binding agreements which cannot be cancelled or modified without substantial loss.” Such 

activities include, but are not limited to, “installation of building supports and foundations, 

laying underground pipe work and construction of permanent storage structures.” We proposed 

adding language to the definition that is currently not in the PSD definition with respect to multiphased projects. We proposed that for multi-phased projects, commencement of construction of 

one phase does not constitute commencement of construction of any later phase, unless each 

phase is “mutually dependent” on the other on a physical and chemical basis, rather than 

economic. 

 The PSD regulations provide additional conditions beyond addressing what constitutes 

commencement. Specifically, the regulations require that the owner or operator “did not 

discontinue construction for a period of 18 months or more and completed construction within a 

reasonable time.” (40 CFR 52.21(i)(4)(ii)(c). While “reasonable time” may vary depending on 

the type of project, we proposed that for RFS2 a reasonable time to complete construction of 

renewable fuel facilities be no greater than 3 years from initial commencement of construction. 

We sought comment on this time frame. 

Commenters generally agreed with our proposed definition of commenced construction. 

Some commenters felt that the 3 year time frame was not a ‘reasonable time” to complete 

construction in light of the economic difficulties that businesses have been and will likely 

continue to be facing. We recognize that there have been extreme economic problems in the past 

year. Based on historical data which show construction of ethanol plants typically take about 
 

87

one year, we believe that the 3 year time frame allows such conditions to be taken into account 

and that it is an appropriate and fair amount of time to allow for completion Therefore, we are 

not extending the amount of time that constitutes “reasonable” to five years as was suggested. 

 

 c. Definition of Facility Boundary 

We proposed that the grandfathering and deemed compliant exemptions apply to 

“facilities.” Our proposed definition of this term is similar in some respects to the definition of 

“building, structure, facility, or installation” contained in the PSD regulations in 40 CFR 52.21. 

We proposed to modify the definition, however, to focus on the typical renewable fuel plant. We 

proposed to describe the exempt “facilities” as including all of the activities and equipment 

associated with the manufacture of renewable fuel which are located on one property and under 

the control of the same person or persons. Commenters agreed with our proposed definition of 

“facility” and we are making that definition final today. 

 

 d. Proposed Approaches and Consideration of Comments 

We proposed one basic approach to the exemption provisions and sought comment on 

five additional options. The basic approach would provide an indefinite extension of 

grandfathering and deemed compliant status but with a limitation of the exemption from the 20% 

GHG threshold to a baseline volume of renewable fuel. The five additional options for which we 

sought comment were: 1) Expiration of exemption for grandfathered and “deemed compliant” 

status when facilities undergo sufficient changes to be considered “reconstructed”; 2) Expiration 
 

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of exemption 15 years after EISA enactment, industry-wide; 3) Expiration of exemption 15 years 

after EISA enactment with limitation of exemption to baseline volume; 4) “Significant” 

production components are treated as facilities and grandfathered or deemed compliant status 

ends when they are replaced; and 5) Indefinite exemption and no limitations placed on baseline 

volumes. 

i. Comments on the Proposed Basic Approach 

Generally, commenters supported the basic approach in which the volume of renewable fuel 

from grandfathered facilities exempt from the 20% GHG reduction threshold would be limited to 

baseline volume. One commenter objected to the basic approach and argued that the statute's use 

of the word "new" and the phrase "after December 19, 2007" provided evidence that facilities 

which commenced construction prior to that date would not ever be subject to the threshold 

regardless of the volume produced from such facilities. In response, we note first that the statute 

does not provide a definition of the term "new facilities" for which the 20% GHG threshold 

applies. . We believe that it would be reasonable to include within our interpretation of this 

term a volume limitation, such that a production plant is considered a new facility to the extent 

that it produces renewable fuel above baseline capacity. This approach also provides certainty in 

the marketplace in terms of the volumes of exempt fuel, and a relatively straightforward 

implementation and enforcement mechanism as compared to some of the other alternatives 

considered. Furthermore, EPA believes that the Act should not be interpreted as allowing 

unlimited expansion of exempt facilities for an indefinite time period, with all volumes exempt, 

as suggested by the commenter. Such an approach would likely lead to a substantial increase in 
 

89

production of fuel that is not subject to any GHG limitations, which EPA does not believe would 

be consistent with the objectives of the Act 

We solicited comment on whether changes at a facility that resulted in an increase in 

GHG emissions, such as a change in fuel or feedstock, should terminate the facility’s 

exemption from the 20 percent GHG threshold. Generally, commenters did not support such a 

provision, pointing out that there are many variations within a plant that cannot be adequately 

captured in a table of fuel and feedstock pathways as we proposed (see 74 FR 24927). 

Implementing such a provision would create questions of accounting and tracking that would 

need to be evaluated on a time-consuming case-by-case basis. For example, if a switch to a 

different feedstock or production process resulted in less efficiency, facilities may argue that 

they are increasing energy efficiency elsewhere (e.g. purchasing waste heat instead of burning 

fuel onsite to generate steam). We would then need to assess such changes to track the net 

energy change a plant undergoes. Given the added complexity and difficulty in carrying out 

such an option, we have decided generally not to implement it. There is an exception, however, 

for “deemed compliant” facilities. These facilities achieve their status in part by being fired 

only by natural gas or biomass, or a combination thereof. Today’s rule provides, as proposed, 

that these facilities will lose their exemption if they switch to a fuel other than natural gas, 

biomass, or a combination thereof, since these were conditions that Congress deemed critical to 

granting them the exemption from the 20% GHG reduction requirement. 

We also solicited comment on whether we should allow a 10% tolerance on the baseline 

volume for which RINs can be generated without complying with the 20% GHG reduction 
 

90

threshold to allow for increases in volume due to debottlenecking. Some favored this concept, 

while others argued that the tolerance should be set at 20 percent. After considering the 

comments received, we have decided that a 10% (and 20%) level is not appropriate for this 

regulation for the following reasons: 1) we have decided to interpret the exemption of the 

baseline volume of renewable fuel from the 20 percent requirement as extending indefinitely. 

Any tolerance provided could, therefore, be present in the marketplace for a considerable time 

period; 2) increases in volume of 10% or greater could be the result of modifications other than 

debottlenecking. Consistent with the basic approach we are taking today towards interpreting the 

grandfathering and deemed compliant provisions, we believe that the fuel produced as a result of 

such modifications comes from “new facilities” within the meaning of the statute, and should be 

subject to the 20% GHG reduction requirement; 3) we are allowing baseline volume to be based 

on the maximum capacity that is allowed under state and federal air permits. With respect to the 

last reason, facilities that have been operating below the capacity allowed in their state permits 

would be able to claim a baseline volume based on the maximum capacity. As such, these 

facilities may indeed be able to increase their volume by 10 to 20 percent by virtue of how their 

baseline volume is defined. We believe this is appropriate, however, since their permits should 

reflect their design, and the fuel resulting from their original pre-EISA (or pre-2010, for deemed 

compliant facilities) design should be exempt from the 20% GHG reduction requirement. 

Nevertheless, we recognize and agree with commenters that some allowances should be made for 

minor changes brought about by normal maintenance which are consistent with the proper 

operation of a facility. EPA is not aware of a particular study or analysis that could be used as a 

basis for picking a tolerance level reflecting this concept, We believe, however, that the value 

should be relatively small, so as not to encourage plant expansions that are unrelated to 
 

91

debottlenecking. We believe that a 5% tolerance level is consistent with these considerations, 

and have incorporated that value in today’s rule. 

ii. Comments on the Expiration of Grandfathered Status 

Commenters who supported an expiration of the exemption did so because of concerns 

that the proposed approach of providing an indefinite exemption would not provide any 

incentives to bring these plants into compliance with current standards. They also objected to 

plants being allowed an indefinite period beyond the time period when it could be expected that 

they would have paid off their investors. The commenters argued that the cost of operation for 

such plants would be less than competing plants that do have to comply with current standards; 

as such, commenters opposed to the basic approach felt an indefinite exemption would be a 

subsidy to plants that will never comply with the 20 percent threshold level. The renewable 

fuels industry, on the other hand, viewed the options that would set an expiration date (either 

via cumulative reconstruction, or a 15 year period from date of enactment) as harsh, 

particularly if the lifecycle analysis results make it costly for existing facilities to meet the 20% 

threshold. Some also argued that no such temporal limitation appears in the statute. 

We considered such comments, but in light of recent lifecycle analyses we conducted in 

support of this rule we have concluded that many of the current technology corn ethanol plants 

may find it difficult if not impossible to retrofit existing plants to comply with the 20 percent 

GHG reduction threshold. In addition, the renewable fuels industry viewed the alternative 

proposals that would set an expiration date (either via cumulative reconstruction, or a 15 year 

period from date of enactment) as harsh, particularly if the lifecycle analysis results make it 

costly for existing facilities to meet the 20% threshold. Given the difficulty of meeting such 
 

92

threshold, owners of such facilities could decide to shut down the plant. Given such 

implications of meeting the 20 percent threshold level for existing facilities we have chosen not 

to finalize any expiration date. 

e. Final grandfathering provisions 

For the reasons discussed above, the Agency has decided to proceed with the proposed 

baseline volume approach, rather than the expiration options. We hold open the possibility, 

therefore, of revisiting and reproposing the exemption provision in a future rulemaking to take 

such advances into account. Ending the grandfathering exemption after its usefulness is over 

would help to streamline the ongoing implementation of the program. 

 The final approach adopted today is summarized as follows: 

i. Increases in volume of renewable fuel produced at grandfathered facilities due to 

expansion 

 

 For facilities that commenced construction prior to December 19, 2007, we are defining 

the baseline volume of renewable fuel exempt from the 20% GHG threshold requirement to be 

the maximum volumetric capacity of the facility that is allowed in any applicable state air permit 

or Federal Title V operating permit.4

 We had proposed in the NPRM that nameplate capacity be 

defined as permitted capacity, but that if the capacity was not stipulated in any federal, state or 

 

4

 Volumes also include expansions to existing facilities, provided that the construction for such expansion 

commences prior to December 19, 2007. In such instances, the total volume from the original facility plus the 

additional volume due to expansion is grandfathered. 
 

93

local air permit, then the actual peak output should be used. We have decided that since 

permitted capacity is the limiting condition, by virtue of it being an enforceable limit contained 

in air permits, that the term “nameplate capacity” is not needed. In addition, we are allowing a 

5% tolerance as discussed earlier. Therefore, today’s rule defines permitted capacity as 105% of 

the maximum permissible volume output of renewable fuel allowed under operating conditions 

specified in all applicable preconstruction, construction and operating permits issued by 

regulatory authorities (including local, regional, state or a foreign equivalent of a state, and 

federal permits) If the capacity of a facility is not stipulated in such air permits, then the 

grandfathered volume is 105% of the maximum annual volume produced for any of the last five 

calendar years prior to 2008. Volumes greater than this amount which may typically be due to 

expansions of the facility which occur after December 19, 2007, will be subject to the 20% GHG 

reduction requirement if the facility wishes to generate RINs for the incremental expanded 

volume. The increased volume will be considered as if produced from a “new facility” which 

commenced construction after December 19, 2007. Changes that might occur to the mix of 

renewable fuels produced within the facility are irrelevant—they remain grandfathered as long as 

the overall volume falls within the baseline volume. Thus, for example, if an ethanol facility 

changed its operation to produce butanol, but the baseline volume remained the same, the fuel so 

produced would be exempt from the 20% GHG reduction requirement. 

 The baseline volume will be defined as above for deemed compliant facilities (those 

ethanol facilities fired by natural gas or biomass or a combination thereof that commenced 

construction after December 19, 2007 but before January 1, 2010) with the exception that if the 

maximum capacity is not stipulated in air permits, then the exempt volume is the maximum 
 

94

annual peak production during the plant’s first three years of operation. In addition, any 

production volume increase that is attributable to construction which commenced prior to 

December 31, 2009 would be exempt from the 20% GHG threshold, provided that the facility 

continued to use natural gas, biomass or a combination thereof for process energy. Because 

deemed compliant facilities owe their status to the fact that they use natural gas, biomass or a 

combination thereof for process heat, their status will be lost, and they will be subject to the 20% 

GHG threshold requirement, at any time that they change to a process energy source other than 

natural gas and/or biomass. Finally, because EISA limits deemed compliant facilities to ethanol 

facilities, if there are any changes in the mix of renewable fuels produced by the facility, only the 

ethanol volume remains grandfathered. We had solicited comment on whether fuels other than 

ethanol could also be deemed compliant. Based on comments received and additional 

consideration to this matter, we decided that because the Act does not authorize EPA to allow 

fuels other than ethanol, the deemed compliant provisions will apply only to facilities producing 

that fuel. 

Volume limitations contained in air permits may be defined in terms of peak hourly 

production rates or a maximum annual capacity. If they are defined only as maximum hourly 

production rates, they will need to be converted to an annual rate. Because assumption of a 24-

hour per day production over 365 days per year (8,760 production hours) may overstate the 

maximum annual capacity we are requiring a conversion rate of 95% of the total hours in a year 

(8,322 production hours) based on typical operating “uptime” of ethanol facilities. 
 

95

 The facility registration process (see Section II.C) will be used to define the baseline 

volume for individual facilities. Owners and operators must submit information substantiating 

the permitted capacity of the plant, or the maximum annual peak capacity if the maximum 

capacity is not stipulated in a federal, state or local air permit, or EPA Title V operating permit. 

Copies of applicable air permits which stipulate the maximum annual capacity of the plant, must 

be provided as part of the registration process. Subsequent expansions at a grandfathered facility 

that results in an increase in volume above the baseline volume will subject the increase in 

volume to the 20% GHG emission reduction threshold (but not the original baseline volume). 

Thus, any new expansions will need to be designed to achieve the 20% GHG reduction threshold 

if the facility wants to generate RINs for that volume. Such determinations will be made on the 

basis of EPA-defined fuel pathway categories that are deemed to represent such 20% reduction. 

EPA enforcement personnel commented that claims for an exemption from the 20% 

GHG reduction requirement should be made promptly, so that they can be verified with recent 

supporting information. They were concerned, in particular, that claims for exempt status could 

be made many years into the future for facilities that may or may not have concluded 

construction within the required time period, but delayed actual production of renewable fuel due 

to market conditions or other reasons. EPA believes that this comment has merit, and has 

included a requirement in Section 80.1450(f) of the final rule for registration of facilities 

claiming an exemption from the 20% GHG reduction requirement by May 1, 2013. This 

provision does not require actual fuel production, but simply the filing of registration materials 

that assert a claim for exempt status. It will benefit both fuel producers, who will likely be able 

to more readily collect the required information if it is done promptly, and EPA enforcement 
 

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personnel seeking to verify the information. However, given the potentially significant 

implications of this requirement for facilities that may qualify for the exemption but miss the 

registration deadline, the rule also provides that EPA may waive the requirement if it determines 

that the submission is verifiable to the same extent as a timely-submitted registration. 

 ii. Replacements of equipment 

 If production equipment such as boilers, conveyors, hoppers, storage tanks and other 

equipment are replaced, it would not be considered construction of a “new facility” under this 

option of today’s final rule – the baseline volume of fuel would continue to be exempt from the 

20% GHG threshold. We sought comment on an approach that would require that if coal-fired 

units are replaced, that the replacement units must be fired with natural gas or biofuel for the 

product to be eligible for RINs that do not satisfy the 20% GHG threshold. Some commenters 

supported such an approach. We agreed, however, with other commenters who point out that the 

language in EISA provides for an indefinite exemption for grandfathered facilities. While we 

interpret the statute to limit the exemption to the baseline volume of a grandfathered facility, we 

do not interpret the language to allow EPA to require that replacements of coal fired units be 

natural gas or biofuel. Thus replacements of coal fired equipment will not affect the facility’s 

grandfathered status. 

 iii. Registration, Recordkeeping and Reporting 
 

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 Facility owner/operators will be required to provide evidence and certification of 

commencement of construction. Such certification will require copies of all applicable air 

permits that apply to the construction and operation of the facility. Owner/operators must 

provide annual records of process fuels used on a BTU basis, feedstocks used and product 

volumes. For facilities that are located outside the United States (including outside the 

Commonwealth of Puerto Rico, the U.S. Virgin Islands, Guam, American Samoa, and the 

Commonwealth of the Northern Mariana Islands) owners will be required to provide certification 

as well. Since the definition of commencement of construction includes having all necessary air 

permits, we will require that facilities outside the United States certify that such facilities have 

obtained all necessary permits for construction and operation required by the appropriate national 

and local environmental agencies. 

4. New Renewable Biomass Definition and Land Restrictions

As explained in Section I, EISA lists seven types of feedstock that qualify as “renewable 

biomass.” EISA limits not only the types of feedstocks that can be used to make renewable fuel, 

but also the land that these renewable fuel feedstocks may come from. Specifically, EISA’s 

definition of renewable biomass incorporates land restrictions for planted crops and crop residue, 

planted trees and tree residue, slash and pre-commercial thinnings, and biomass from wildfire 

areas. EISA prohibits the generation of RINs for renewable fuel made from feedstock that does 

not meet the definition of renewable biomass, which includes not meeting the associated land 

restrictions. The following sections describe EPA’s interpretation of several key terms related to 
 

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the definition of renewable biomass, and the approach in today’s rule to implementing the 

renewable biomass requirements. 

a. Definitions of Terms 

 EISA’s renewable biomass definition includes a number of terms that require definition. 

The following sections discuss EPA’s definitions for these terms, which were developed with 

ease of implementation and enforcement in mind. We have made every attempt to define these 

terms as consistently with other federal statutory and regulatory definitions as well as industry 

standards as possible, while keeping them workable for purposes of program implementation. 

i. Planted Crops and Crop Residue 

 The first type of renewable biomass described in EISA is planted crops and crop residue 

harvested from agricultural land cleared or cultivated at any time prior to December 19, 2007, 

that is either actively managed or fallow, and nonforested. We proposed to interpret the term 

“planted crops” to include all annual or perennial agricultural crops that may be used as 

feedstock for renewable fuel, such as grains, oilseeds, and sugarcane, as well as energy crops, 

such as switchgrass, prairie grass, and other species, providing that they were intentionally 

applied to the ground by humans either by direct application as seed or nursery stock, or through 

intentional natural seeding by mature plants left undisturbed for that purpose. We received 

numerous comments on our proposed definition of “planted crops,” largely in support of our 

proposed definition. However, some commenters noted that “microcrops,” such as duckweed, a 
 

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flowering plant typically grown in ponds or tanks, are also being investigated for used as 

renewable fuel feedstocks. These microcrops are typically grown in a similar manner to algae, 

but cannot be categorized as algae since they are relatively more complex organisms. EPA’s 

proposed definition would have unintentionally excluded microcrops such as duckweed through 

the requirement that planted crops be “applied to the ground.” After considering comments 

received, EPA does not believe that there is any basis under EISA for excluding from the 

definition of renewable biomass crops such as duckweed that are applied to a tank or pond for 

growth rather than to the soil. As with other planted crops, these ponds or tanks must be located 

on existing “agricultural land,” as described below, to qualify as renewable biomass under EISA. 

Therefore, including such microcrops within the definition of renewable biomass will not result 

in the direct loss of forestland or other ecologically sensitive land that Congress sought to protect 

through the land restrictions in the definition of renewable biomass. Doing so will further the 

objectives of the statute of promoting the development of emerging technologies to produce 

clean alternatives to petroleum-based fuels, and to further U.S. energy independence. 

For these reasons, we are finalizing our proposed definition of “planted crops,” with the 

inclusion of provisions allowing for the growth of “microcrops” in ponds or tanks that are 

located on agricultural land. Our final definition also includes a reference to “vegetative 

propagation,” in which a new plant is produced from an existing vegetative structure, as one 

means by which planted crops may reproduce, since this is an important method of reproduction 

for microcrops such as duckweed. The final definition of “planted crops” includes all annual or 

perennial agricultural crops from existing agricultural land that may be used as feedstock for 

renewable fuel, such as grains, oilseeds, and sugarcane, as well as energy crops, such as 
 

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switchgrass, prairie grass, duckweed and other species (but not including algae species or planted 

trees), providing that they were intentionally applied by humans to the ground, a growth 

medium, or a pond or tank, either by direct application as seed or plant, or through intentional 

natural seeding or vegetative propagation by mature plants introduced or left undisturbed for 

that purpose. We note that because EISA contains specific provisions for planted trees and tree 

residue from tree plantations, our final definition of planted crops in EISA excludes planted 

trees, even if they may be considered planted crops under some circumstances. 

 We proposed that “crop residue” be limited to the residue, such as corn stover and 

sugarcane bagasse, left over from the harvesting of planted crops. We sought comment on 

including biomass from agricultural land removed for purposes of invasive species control or fire 

management. We received many comments supporting the inclusion of biomass removed from 

agricultural land for purposes of invasive species control and/or fire management. We believe 

that such biomass is typically removed from agricultural land for the purpose of preserving or 

enhancing its value in agricultural crop production. It may be removed at the time crops are 

harvested, post harvest, periodically (e.g., for pastureland) or during extended fallow periods. 

We agree with the commenters that this material is a form of biomass residue related to crop 

production, whether or not derived from a crop itself, and, therefore, are modifying the proposed 

definition of “crop residue” to include it. We also received comments encouraging us to expand 

the definition of crop residue to include materials left over after the processing of the crop into a 

useable resource, such as husks, seeds, bagasse and roots. EPA agrees with these comments and 

has altered the final definition to cover such materials. Based on comments received, our final 

definition of “crop residue” is the biomass left over from the harvesting or processing of planted 
 

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crops from existing agricultural land and any biomass removed from existing agricultural land 

that facilitates crop management (including biomass removed from such lands in relation to 

invasive species control or fire management), whether or not the biomass includes any portion of 

a crop or crop plant. 

 Our proposed regulations restricted planted crops and crop residue to that harvested from 

existing agricultural land, which, under our proposed definition, includes three land categories – 

cropland, pastureland, and Conservation Reserve Program (CRP) land. We proposed to define 

cropland as land used for the production of crops for harvest, including cultivated cropland for 

row crops or close-grown crops and non-cultivated cropland for horticultural crops. We 

proposed to define pastureland as land managed primarily for the production of indigenous or 

introduced forage plants for livestock grazing or hay production, and to prevent succession to 

other plant types. We also proposed that CRP land, which is administered by USDA’s Farm 

Service Agency, qualify as “agricultural land” under RFS2. 

EPA received numerous comments on our proposed definition of existing agricultural 

land. Generally, commenters were in support of our definition of “cropland” and its inclusion in 

the definition of existing agricultural land. Additionally, commenters generally did not object to 

CRP lands or pastureland being included in the definition of agricultural land. Based on our 

consideration of comments received on the proposed rule, EPA is including cropland, 

pastureland and CRP land in the definition of existing agricultural land, as proposed. 

 
 

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We sought comment in the proposal on whether rangeland should be included as 

agricultural land under RFS2. Rangeland is land on which the indigenous or introduced 

vegetation is predominantly grasses, grass-like plants, forbs or shrubs and which – unlike 

cropland or pastureland – is predominantly managed as a natural ecosystem. EPA received a 

number of comments concerning whether rangeland should be included in the definition of 

existing agricultural land under RFS2. Some commenters urged EPA to expand the definition of 

existing agricultural land to include rangeland, arguing that rangelands could serve as important 

sources of renewable fuel feedstocks. Many of these commenters argued that, although it is 

generally less intensively managed than cropland, rangeland is nonetheless actively managed 

through control of brush or weed species, among other practices. In contrast, other commenters 

argued against the inclusion of rangeland, contending that the potential conversion of rangeland 

into cropland for growing renewable biomass would lead to losses of carbon, soil, water quality, 

and biodiversity. 

Under EISA, renewable biomass includes crops and crop residue from agricultural land 

cleared or cultivated at any time prior to the enactment of EISA that is either “actively managed 

of fallow” and nonforested. In determining whether rangeland should be considered existing 

agricultural land under this provision, EPA must decide if rangeland qualifies as “actively 

managed or fallow.” EPA believes that the term “actively managed” is best interpreted by 

reference to the type of material and practices that this provision addresses – namely crops and 

residue associated with growing crops. We think it is appropriate to inquire whether the type of 

management involved in a land type is consistent with that which would occur on land where 

crops are harvested. Thus, while we acknowledge that some types of rangeland are managed to a 
 

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certain degree, the level of “active management” that is typically associated with land dedicated 

to growing agricultural crops is far more intensive than the types of management associated with 

rangeland. For example, rangeland is rarely tilled, fertilized or irrigated as croplands and, to a 

lesser degree, pasturelands, are. Furthermore, since rangeland encompasses a wide variety of 

ecosystems, including native grasslands or shrublands, savannas, wetlands, deserts and tundra, 

including it in the definition of agricultural land would increase the risk that these sensitive 

ecosystems would become available under EISA for conversion into intensively managed monoculture cropland. Finally, the conversion of relatively undisturbed rangeland to the production of 

annual crops could in some cases lead to large releases of GHGs stored in the soil, as well as a 

loss of biodiversity, both of which would be contrary to EISA’s stated goals. For these reasons, 

EPA is not including rangeland in the definition of “existing agricultural land” in today’s final 

rule. 

 We proposed to include in our definition of existing agricultural land the requirement that 

the land was cleared or cultivated prior to December 19, 2007, and that, since December 19, 

2007, it has been continuously actively managed (as agricultural land) or fallow, and 

nonforested. We proposed to interpret the phrase “that is actively managed or fallow, and 

nonforested” as meaning that land must have been actively managed or fallow, and nonforested, 

on December 19, 2007, and continuously thereafter in order to qualify for renewable biomass 

production. We received extensive comments on this interpretation. Many commenters 

suggested an interpretation of the requirement that agricultural land be “actively managed” to 

mean that the land had to be “actively managed” at the time EISA was passed on December 17, 

2007, such that the amount of land available for biofuel feedstock production was established at 
 

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that point and would not diminish over time. Other commenters supported our proposed 

interpretation, which would mean that the amount of land available for biofuel feedstock 

production could diminish over time if parcels of land cease to be actively managed at any point, 

thus taking them out of contention for biofuel feedstock cultivation. Some commenters argued 

that this interpretation is contrary to Congress’ intent and the basic premise of the RFS program 

since, over time, it could lead to a reduction in the amount of renewable biomass available for 

use as renewable fuel feedstocks, while the statutorily required volumes of renewable fuel 

increase over time. These commenters further argue that the active management provision 

should be interpreted as a “snapshot” of agricultural land existing and actively managed on 

December 19, 2007. Under this interpretation, the land that was cleared or cultivated prior to 

December 19, 2007 and was actively managed on that date, would be eligible for renewable 

biomass production indefinitely. 

We agree that that the goal of the EISA and RFS program, to increase the presence of 

renewable fuels in transportation fuel, will be better served by interpreting the “actively managed 

or fallow” requirement in the renewable biomass definition as applying to land actively managed 

or fallow on December 19, 2007, rather than interpreting this requirement as applying beginning 

on December 19, 2007 and continuously thereafter. In addition, by simplifying the requirement 

in this fashion, there will be significantly less burden on regulated parties in ensuring that their 

feedstocks come from qualifying lands. For these reasons, we are modifying the definition of 

existing agricultural land so that the “active management” requirement is satisfied for those that 

were cleared or cultivated and actively managed or fallow, and non-forested on December 19, 

2007. 
 

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Further, we proposed and are finalizing that “actively managed” means managed for a 

predetermined outcome as evidenced by any of the following: sales records for planted crops, 

crop residue, or livestock; purchasing records for land treatments such as fertilizer, weed control, 

or reseeding; a written management plan for agricultural purposes; documentation of 

participation in an agricultural program sponsored by a Federal, state or local government 

agency; or documentation of land management in accordance with an agricultural certification 

program. While we received comments indicating that including a definitive checklist of 

required evidential records would be helpful to have explicitly identified in the regulations, we 

are not doing so in order to maintain flexibility, as feedstock producers may vary in the types of 

evidence they can readily obtain to show that their agricultural land was actively managed. We 

are adding, however, a clarification that the records must be traceable to the land in question. 

For example, it will not be sufficient to have a receipt for seed purchase if there is not additional 

evidence indicating that the seed was applied to the land which is claimed as existing agricultural 

land. 

 The term “fallow” is generally used to describe cultivated land taken out of production 

for a finite period of time. We proposed and sought comment on defining fallow to mean 

agricultural land that is intentionally left idle to regenerate for future agricultural purposes, with 

no seeding or planting, harvesting, mowing, or treatment during the fallow period. We also 

proposed and sought comment on requiring documentation of such intent. We received many 

comments that supported our proposed definition of fallow. We also received comments 

indicating that EPA should set a time limit for land to qualify as fallow (as opposed to 
 

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abandoned for agricultural purposes). We have decided not to include a time limit for land to 

qualify as “fallow” because we understand that agricultural land may be left fallow for many 

different purposes and for varying amounts of time. Any particular timeframe that EPA might 

choose for this purpose would be somewhat arbitrary. Further, EISA does not indicate a time 

limit on the period of time that qualifying land could be fallow, so EPA does not believe that it 

would be appropriate to do so in its regulations. Therefore, EPA is finalizing its proposed 

definition of “fallow.” 

 Finally, in order to define the term “nonforested” as used in the definition of “existing 

agricultural land,” we proposed first to define the term “forestland” as generally undeveloped 

land covering a minimum area of one acre upon which the predominant vegetative cover is trees, 

including land that formerly had such tree cover and that will be regenerated. We also proposed 

that forestland would not include tree plantations. “Nonforested” land under our proposal would 

be land that is not forestland. 

We received many comments on our proposed definition of forestland. Some 

commenters urged EPA to broaden the definition of “forestland” to include tree plantations, 

arguing that plantations are well-accepted as a subset of forestland. Others advocated that EPA 

should make every effort to distinguish between tree plantations and forestland so as not to run 

the risk of allowing native forests to be converted into less diverse tree plantations from which 

trees could be harvested for renewable fuel production. For today’s final rule, EPA is including 

tree plantations as a subset of forestland since it is commonly understood as such throughout the 

forestry industry. Under EISA, renewable biomass may include “slash and pre-commercial 
 

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thinnings” from non-federal forestlands, and “planted trees and tree residue” from actively 

managed tree plantations on non-federal land. One effect under EISA of the modification from 

the proposed rule to include tree plantations as a subset of forestland is to allow pre-commercial 

thinnings and slash, in addition to planted trees and tree residue, harvested from tree plantations 

to serve as qualifying feedstocks for renewable fuel production. EPA believes it is appropriate to 

include pre-commercial thinnings and slash from actively managed tree plantations as renewable 

biomass, consistent with the EISA provision allowing harvested trees and tree residue from tree 

plantations to qualify as renewable biomass. Another effect of including the tree plantations as 

a kind of forestland is that, since crops and crop residue must come from land that was “nonforested” as of the date of EISA enactment, a tract of land managed as a tree plantation on the 

date of EISA enactment could not be converted to cropland for the production of feedstock for 

RIN-generating renewable fuel. EPA believes that this result in keeping with Congressional 

desire to avoid the conversion of new lands to crop production for renewable fuel production. 

Additionally, EPA received comments indicating that, in order to be consistent with 

existing statutory and/or regulatory definitions of “forestland,” EPA should exclude tree covered 

areas in intensive agricultural crop production settings, such as fruit orchards, or tree-covered 

areas in urban settings such as city parks from the definition of forestland. EPA agrees that these 

types of land cannot be characterized as “forestland,” and is thus excluding them from the 

definition. EPA’s final definition of forestland is “generally undeveloped land covering a 

minimum of 1 acre upon which the primary vegetative species is trees, including land that 

formerly had such tree cover and that will be regenerated and tree plantations. Tree covered 
 

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areas in intensive agricultural crop production settings, such as fruit orchards, or tree-covered 

areas in urban settings such as city parks, are not considered forestland.” 

ii. Planted Trees and Tree Residue 

 The definition of renewable biomass in EISA includes planted trees and tree residue from 

actively managed tree plantations on non-federal land cleared at any time prior to December 19, 

2007, including land belonging to an Indian tribe or an Indian individual, that is held in trust by 

the United States or subject to a restriction against alienation imposed by the United States. 

We proposed to define the term “planted trees” to include not only trees that were 

established by human intervention such as planting saplings and artificial seeding, but also trees 

established from natural seeding by mature trees left undisturbed for such a purpose. Some 

commenters disagreed with our inclusion of naturally seeded trees in our definition of “planted 

trees.” They argue that an area which is managed for natural regeneration of trees is more akin 

to a natural forest than a tree plantation, and that the difference between the two types of land 

should be clear in order to distinguish between the two and to avoid the effective conversion of 

natural forests to tree plantations under EISA. EPA agrees that the inclusion of natural reseeding 

in the definition of “planted trees” would make distinguishing between tree plantations and 

forests difficult or impossible, thus negating the separate restrictions that Congress placed on the 

two types of land. On the other hand, EPA believes that trees that are naturally seeded and 

grown together with hand- or machine-planted trees in a tree plantation should not categorically 

be excluded from qualifying as renewable biomass. Such natural reseeding may occur after 
 

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planting the majority of trees in a tree plantation, and may be consistent with the management 

plan for a tree plantation. EPA has decided, therefore, to modify its proposed definition of 

“planted tree” to be trees harvested from a tree plantation. The term “tree plantation” is defined 

as a stand of no less than 1 acre composed primarily of trees established by hand- or machineplanting of a seed or sapling, or by coppice growth from the stump or root of a tree that was 

hand- or machine-planted.” The net effect is that as long as a tree plantation consists “primarily” 

of trees that were hand- or machine planted (or derived therefrom, as described below), then all 

trees from the tree plantation, including those established from natural seeding by mature trees 

left undisturbed for such a purpose, will qualify as renewable biomass. 

We also received a number of comments suggesting that EPA broaden the definition of 

planted trees to include other methods of tree regeneration, such as coppice (the production of 

new stems from stumps or roots), that are frequently used in the forestry industry to regenerate 

tree plantations. EPA believes that “planted” implies direct human intervention, and that 

allowing stump-growth from the stump or roots of a tree that was hand- or machine-planted is 

consistent with this concept. Therefore, today’s final rule broadens the concept of “planted 

trees” from a tree plantation to include “a tree established by hand- or machine-planting of a seed 

or sapling, or by coppice growth from the stump or root of a tree that was hand- or machineplanted.” This new language will appear in the definition of “tree plantation.” 

 

 In the NPRM, we proposed to define a “tree plantation” as a stand of no fewer than 100 

planted trees of similar age and comprising one or two tree species, or an area managed for 

growth of such trees covering a minimum of one acre. We received numerous comments on our 
 

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definition of tree plantation. Several commenters urged EPA to define tree plantation more 

broadly by using the definition from the Dictionary of Forestry- “a stand composed primarily of 

trees established by planting or artificial seeding,” However, this definition does not provide 

sufficiently clear guidelines for determining whether a given parcel of land would be considered 

a tree plantation rather than a natural forest. Since trees are considered renewable biomass under 

RFS2 only if they are harvested from tree plantations, we believe that our proposed definition 

was clearer and more easily applied in the field. Accordingly, EPA has not adopted the 

definition of this term from the Dictionary of Forestry. Other commenters argued that there is no 

technical justification for limiting the number of species or number of trees in a plantation, and 

that many tree plantations include a variety of species. EPA believes that there is merit in these 

comments. Accordingly, EPA is finalizing a broadened definition of “tree plantation,” by 

removing the limitations on the number and species of trees. EPA is defining tree plantation as 

“a stand of no less than 1 acre composed primarily of trees established by hand- or machineplanting of a seed or sapling, or by coppice growth from the stump or root of a tree that was 

hand- or machine-planted.” 

We proposed to apply similar management restrictions to tree plantations as would apply 

to existing agricultural land and also to interpret the EISA language as requiring that to qualify as 

renewable biomass for renewable fuel production under RFS2, a tree plantation must have been 

cleared at any time prior to December 19, 2007, and continuously actively managed since 

December 19, 2007. Consistent with our final position regarding actively managed existing 

agricultural land, we are defining the term “actively managed” in the context of tree plantations 

as managed for a predetermined outcome as evidenced by any of the following that must be 
 

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traceable to the land in question: sales records for planted trees or slash; purchasing records for 

seeds, seedlings, or other nursery stock together with other written documentation connecting the 

land in question to these purchases; a written management plan for silvicultural purposes; 

documentation of participation in a silvicultural program sponsored by a Federal, state or local 

government agency; documentation of land management in accordance with an agricultural or 

silvicultural product certification program; an agreement for land management consultation with 

a professional forester that identifies the land in question; or evidence of the existence and 

ongoing maintenance of a road system or other physical infrastructure designed and maintained 

for logging use, together with one of the above-mentioned documents. Silvicultural programs 

such as those of the Forest Stewardship Council, the Sustainable Forestry Initiative, the 

American Tree Farm System, or USDA are examples of the types of programs that could 

indicate actively managed tree plantations. As with the definition of “actively managed” as it 

applies to crops from existing agricultural lands, we received extensive comments on this 

interpretation. As with our final position for crops from existing agricultural lands, we are 

interpreting the “active management” requirement for tree plantations to apply on the date of 

EISA’s enactment, December 19, 2007. Those tree plantations that were cleared or cultivated 

and actively managed on December 19, 2007 are eligible for the production of planted trees, tree 

residue, slash and pre-commercial thinnings for renewable fuel production. 

In lieu of the term “tree residue,” we proposed to use the term “slash” in our regulations 

as a more descriptive, but otherwise synonymous, term. According to the Dictionary of Forestry 

(1998, pp. 168), a source of commonly understood industry definitions, slash is “the residue, e.g., 

treetops and branches, left on the ground after logging or accumulating as a result of a storm, 
 

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fire, girdling, or delimbing.” We also proposed to clarify that slash can include tree bark and can 

be the result of any natural disaster, including flooding. We received comments in support of 

this additional inclusion and are expanding the definition of “slash” to include tree bark and 

residue resulting from natural disaster, including flooding. We received general support for our 

proposal to substitute our definition of “slash” for “tree residue,” however; several commenters 

argued that our definition of slash is too narrow to be substituted for “tree residue,” which should 

include woody residues from saw mills and paper mills that process planted trees from tree 

plantations. EPA agrees that the term “residue” should include this material. Therefore, EPA is 

expanding the definition of “tree residue” to include residues from processing planted trees at 

lumber and paper mills, but is limiting it to the biogenically derived portion of the residues that 

can be traced back to feedstocks meeting the definition of renewable biomass (i.e. planted trees 

and tree residue from actively managed tree plantations on non-federal land cleared at any time 

prior to December 19, 2007). RINs may only be generated for the fraction of fuel produced that 

represents the biogenic portion of the tree residue, using the procedures described in ASTM test 

method D-6866. Thus, if the tree residues are mixed with chemicals or other materials during 

processing at the lumber or paper mills, producers may only generate RINs for the portion of the 

mixture that is actually derived from planted trees. EPA’s final definition of “tree residue” is 

“slash and any woody residue generated during the processing of planted trees from actively 

managed tree plantations for use in lumber, paper, furniture or other applications, providing that 

such woody residue is not mixed with similar residue from trees that do not originate in actively 

managed tree plantations. 

iii. Slash and Pre-Commercial Thinnings 
 

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 The EISA definition of renewable biomass includes slash and pre-commercial thinnings 

from non-federal forestlands, including forestlands belonging to an Indian tribe or an Indian 

individual, that are held in trust by the United States or subject to a restriction against alienation 

imposed by the United States. However, EISA excludes slash and pre-commercial thinnings 

from forests or forestlands that are ecological communities with a global or State ranking of 

critically imperiled, imperiled, or rare pursuant to a State Natural Heritage Program, old growth 

forest, or late successional forest. 

 As described in Sec. II.B.4.a.i of this preamble, our definition of “forestland” is generally 

undeveloped land covering a minimum of 1 acre upon which the primary vegetative species is 

trees, including land that formerly had such tree cover and that will be regenerated and tree 

plantations. Tree covered areas in intensive agricultural crop production settings, such as fruit 

orchards or tree-covered areas in urban setting such as city parks, are not considered forestland. 

Also as noted in Sec. III.B.4.a.ii of this preamble, we are adopting the definition of slash listed in 

the Dictionary of Forestry, with the addition of tree bark and residue resulting from natural 

disaster, including flooding. 

As for “pre-commercial thinnings,” the Dictionary of Forestry defines the act of such 

thinning as “the removal of trees not for immediate financial return but to reduce stocking to 

concentrate growth on the more desirable trees.” Because what may now be considered precommercial may eventually be saleable as renewable fuel feedstock, we proposed not to include 

any reference to “financial return” in our definition, but rather to define pre-commercial 
 

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thinnings as those trees removed from a stand of trees in order to reduce stocking to concentrate 

growth on more desirable trees. Additionally, we proposed to include diseased trees in the 

definition of pre-commercial thinnings due to the fact that they can threaten the integrity of an 

otherwise healthy stand of trees, and their removal can be viewed as reducing stocking to 

promote the growth of more desirable trees. We sought comment on whether our definition of 

pre-commercial thinnings should include a maximum diameter and, if so, what the appropriate 

maximum diameter should be. We received comments on our proposed definition of precommercial thinnings that were generally supportive of our proposed definition. Many 

commenters argued that EPA should not use a maximum tree diameter as a basis for defining 

pre-commercial thinning as tree diameter varies greatly by forest type and location, making any 

diameter limitation EPA might set arbitrary. EPA agrees with this assessment. Commenters also 

argued that pre-commercial thinnings may include other non-tree vegetative material that is 

removed to promote and improve tree growth. EPA is attempting to utilize standard industry 

definitions to the extent practicable, and believes that the proposed definition of pre-commercial 

thinnings, based largely on the Dictionary of Forestry definition with the addition of other 

vegetative material removed to promote tree growth, is appropriate. Therefore, we are finalizing 

the proposed definition of “pre-commercial thinnings,” with the addition of the phrase “or other 

vegetative material that is removed to promote tree growth.” 

 We proposed that the State Natural Heritage Programs referred to in EISA are those 

comprising a network associated with NatureServe, a non-profit conservation and research 

organization. Individual Natural Heritage Programs collect, analyze, and distribute scientific 

information about the biological diversity found within their jurisdictions. As part of their 
 

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activities, these programs survey and apply NatureServe’s rankings, such as critically imperiled 

(S1), imperiled (S2), and rare (S3) to species and ecological communities within their respective 

borders. NatureServe meanwhile uses data gathered by these Natural Heritage Programs to 

apply its global rankings, such as critically imperiled (G1), imperiled (G2), or vulnerable (the 

equivalent of the term “rare,” or G3), to species and ecological communities found in multiple 

States or territories. We proposed and sought comment on prohibiting slash and pre-commercial 

thinnings from all forest ecological communities with global or State rankings of critically 

imperiled, imperiled, or vulnerable (“rare” in the case of State rankings) from being used for 

renewable fuel for which RINs may be generated under RFS2. 

 We proposed to use data compiled by NatureServe and published in special reports to 

identify “ecologically sensitive forestland.” The reports listed all forest ecological communities 

in the U.S. with a global ranking of G1, G2, or G3, or with a State ranking of S1, S2, or S3, and 

included descriptions of the key geographic and biologic attributes of the referenced ecological 

community. We proposed that the document be incorporated by reference into the definition of 

renewable biomass in the final RFS2 regulations (and updated as appropriate through notice and 

comment rulemaking). The document would identify specific ecological communities from 

which slash and pre-commercial thinnings could not be used as feedstock for the production of 

renewable fuel that would qualify for RINs under RFS2. Draft versions of the document 

containing the global and State rankings were placed in the docket for the proposed rule. 

EPA received several comments on our proposed interpretation of EISA’s State Natural 

Heritage Program requirement and the reports listing G1-G3 and S1-S3 ecological communities. 
 

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Several commenters argued that while EISA authorizes EPA to exclude slash and precommercial thinnings from S1-3 and G1 and G2 communities, it does not authorize the exclusion 

of biomass from G3 communities, which are designated as “vulnerable,” not “critically 

imperiled, imperiled or rare,” as EISA requires. The commenters further argue that there is little 

or no environmental benefit to adding G3 communities to the list of lands unavailable for 

renewable fuel feedstock production, and that their inclusion limits the availability of forestderived biomass. EPA agrees with these comments, and has drafted today’s final rule so as not 

to specifically exclude from the definition of renewable biomass slash and pre-commercial 

thinnings from G3-ranked “vulnerable” ecological communities to qualify as renewable biomass 

for purposes of RFS2. We are interpreting EISA’s language to exclude from the definition of 

renewable biomass any biomass taken from ecological communities in the U.S. with Natural 

Heritage Programs global ranking of G1 or G2, or with a State ranking of S1, S2, or S3. We are 

including in today’s rulemaking docket (EPA-HQ-OAR-2005-0161) the list of ecological 

communities fitting this description. 

 To complete the definition of “ecologically sensitive forestland,” we proposed to include 

old growth and late successional forestland which is characterized by trees at least 200 years old. 

We received comments on this proposed definition recommending that EPA not use a single tree 

age in the define old growth and late-successional forests, as this criterion does not apply to all 

types of forests. While EPA understands that there are a number of criteria for determining 

whether a forest is old growth and that the criteria differ depending on the type of forest, for 

purposes of the RFS2 rule, EPA seeks to use definitive criteria that can be applied by nonprofessionals. EPA is finalizing the definition of “old growth” as proposed. 
 

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iv. Biomass Obtained from Certain Areas at Risk from Wildfire 

 The EISA definition of renewable biomass includes biomass obtained from the 

immediate vicinity of buildings and other areas regularly occupied by people, or of public 

infrastructure, at risk from wildfire. We proposed to clarify in the regulations that “biomass” is 

organic matter that is available on a renewable or recurring basis, and that it must be obtained 

from within 200 feet of buildings, campgrounds, and other areas regularly occupied by people, or 

of public infrastructure, such as utility corridors, bridges, and roadways, in areas at risk of 

wildfire. 

Furthermore, we proposed to define “areas at risk of wildfire” as areas located within – or 

within one mile of – forestland, tree plantations, or any other generally undeveloped tract of land 

that is at least one acre in size with substantial vegetative cover. We sought comment on two 

possible implementation alternatives for identifying areas at risk of wildfire. The first proposed 

alternative would incorporate into our definition of “areas at risk of wildfire” any communities 

identified as “communities at risk” and covered by a community wildfire protection plan 

(CWPP). Communities at risk are defined through a process within the document, "Field 

Guidance - Identifying and Prioritizing Communities at Risk” (National Association of State 

Foresters, June 2003). CWPPs are developed in accordance with "Preparing a Community 

Wildfire Protection Plan – A Handbook for Wildland-Urban Interface Communities” (Society of 

American Foresters, March 2004) and certified by a State Forester or equivalent. We sought 

comment on incorporating by reference into the final RFS2 regulations a list of “communities at 
 

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risk” with an approved CWPP. We also sought comment on a second implementation approach, 

which would incorporate into our definition of “areas at risk of wildfire” any areas identified as 

wildland urban interface (WUI) land, or land in which houses meet wildland vegetation or are 

mixed with vegetation. We noted that SILVIS Lab, in the Department of Forest Ecology and 

Management and the University of Wisconsin, Madison, has, with funding provided by the U.S. 

Forest Service, mapped WUI lands based on the 2000 Census and the U.S. Geological Survey 

National Land Cover Data (NLCD), and we sought comment on how best to use this map. 

We received comments on the proposal and on the two proposed alternative options for 

identifying areas at risk of wildfire. A number of commenters argued that EPA should define 

“areas at risk of wildfire” using an existing definition of WUI from the Healthy Forests 

Restoration Act (Pub. L. 108-148). Many commenters recommended that EPA include both 

lands covered by a CWPP as well as lands meeting the Healthy Forests Restoration Act 

definition of WUI in order to maximize the amount of land available for biomass feedstock and 

to encourage the removal of hazardous fuel for wildfires. EPA understands that very few 

communities that might be eligible for a CWPP actually have one in place, due to the numerous 

administrative steps that must be taken in order to have a CWPP approved, so the option of 

defining areas at risk of wildfire exclusively by reference to a list of communities with an 

approved CWPP would be underinclusive of all lands that a professional forester would consider 

to be at risk of wildfire. Furthermore, EPA believes that the statutory definition of WUI from the 

Healthy Forests Restoration Act (Pub. L. 108-148) is too vague using directly in implementing 

the RFS2 program. If EPA used this WUI definition, individual plots of land would have to be 

assessed by a professional forester on a case-by-case basis in order to determine if they meet the 
 

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WUI definition, creating an expensive burden for landowners seeking to sell biomass from their 

lands as renewable fuel feedstocks. 

In light of the comments received and the need for a simple way for landowners and 

renewable fuel producers to track the status of particular plots of land, for the final rule we are 

identifying “areas at risk of wildfire” as those areas identified as wildland urban interface. Those 

areas are depicted and mapped at http://silvis.forest.wisc.edu/Library/WUILibrary.asp. The 

electronic WUI map is a readily accessible reference tool that was prepared by experts in the 

field of identifying areas at risk of wildfire, and is thus an ideal reference for purposes of 

implementing RFS2. EPA has included in the rulemaking docket instructions on using the WUI 

map to find the status of a plot of land. 

v. Algae 

EISA specifies that “algae” qualify as renewable biomass. EPA did not propose a 

definition for this term. A number of commenters have requested clarification, specifically 

asking whether cyanobacteria (also known as blue-green algae), diatoms, and angiosperms are 

within the definition. Technically, the term “algae” has recently been defined as “thallophytes 

(plants lacking roots, stems and leaves) that have chlorophyll a as their primary photosynthetic 

pigment and lack a sterile covering of cells around the reproductive cells.”5

 Algae are relatively 

simple organisms that are virtually ubiquitous, occurring in freshwater, brackish water, saltwater, 

and terrestrial habitats. When present in water, they may be suspended, or grow attached to 

various substrates. They range in size from unicellular to among the longest living organisms 

 

5

 Phycology, Robert Edward Lee, Cambridge University Press, 2008, page 3. 
 

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(e.g. sea kelp). There is some disagreement among scientists as to whether cyanobacteria should 

be considered bacteria or algae. Some consider them to be bacteria because of their cellular 

organization and biochemistry. However, others find it more significant that they contain 

chlorophyll a, which differs from the chlorophyll of bacteria which are photosynthetic, and also 

because free oxygen is liberated in blue-green algal photosynthesis but not in that of the 

bacteria.6

 EPA believes that it furthers the purposes of EISA to interpret the term “algae” in 

EISA broadly to include cyanobacteria, since doing so will make available another possible 

feedstock for renewable fuel production that will further the energy independence and 

greenhouse gas reduction objectives of the Act. Further, EPA expects that cyanobacteria used in 

biofuel production would be cultivated, as opposed to harvested, and therefore that there would 

be no significant impact from use of cyanobacteria for biofuel production on naturally occurring 

algal populations. Diatoms are generally considered by the scientific community to be algae,7

and, consistent with this general scientific consensus, EPA interprets the EISA definition of 

algae to include them. Microcrop angiosperms, however, do not meet the definition of algae, 

even if they live in an aquatic habitat, since they are relatively more complex organisms than the 

algae. A discussion of microcrop angiosperms is included above in the discussion of “planted 

crops and crop residue.” 

b. Implementation of Renewable Biomass Requirements 

 Our proposed approach to the treatment of renewable biomass under RFS2 was intended 

to define the conditions under which RINs can be generated as well as the conditions under 

 

6

 See, generally, Introduction to the Algae. Structure and Reproduction, by Harold C. Bold and Michael J. Wynne, 

Prentice-Hall Inc. 1978, page 31. 

7

 See id. 
 

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which renewable fuel can be produced or imported without RINs. Our proposed and final 

approaches to both of these areas are described in more detail below. 

i. Ensuring That RINs Are Generated Only For Fuels Made From Renewable 

Biomass 

 The effect of adding EISA's definition of renewable biomass to the RFS program is to 

ensure that renewable fuels are only eligible for the program if made from certain feedstocks, 

and if some of those feedstocks come from certain types of land. In the context of our regulatory 

program, this means that RINs could only be generated if it can be established that the feedstock 

from which the fuel was made meets EISA’s definitions of renewable biomass include land 

restrictions. Otherwise, no RINs could be generated to represent the renewable fuel produced or 

imported. The EISA language does not distinguish between domestic renewable fuel feedstocks 

and renewable fuel feedstocks that come from abroad, so our final rule requires similar feedstock 

affirmation and recordkeeping requirements for both RIN-generating domestic renewable fuel 

producers and RIN-generating foreign producers or importers. 

 We acknowledge that incidental contaminants can be introduced into feedstocks during 

cultivation, transport or processing. It is not EPA's intent that the presence of such contaminants 

should disqualify the feedstock as renewable biomass. The final regulations therefore stipulate 

that the term "renewable biomass" includes incidental contaminants related to customary 

feedstock production and transport that are present in feedstock that otherwise meets the 

definition if such incidental contaminants are impractical to remove and occur in de minimus 
 

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levels. By "related to customary feedstock production and transport," we refer to contaminants 

related to crop production, such as soil or residues related to fertilizer, pesticide and herbicide 

applications to crops, as well as contaminants related to feedstock transport, such as nylon rope 

used to bind feedstock materials. It would also include agricultural contaminants introduced to 

the feedstock during sorting or shipping, such as miscellaneous sorghum grains present in a load 

of corn kernels. However, contamination is not related to customary feedstock production and 

transport, so such feedstocks would not qualify, and in particular, any hazardous waste or toxic 

chemical contaminant in feedstock would disqualify the feedstock as renewable biomass. 

ii. Whether RINs Must Be Generated For All Qualifying Renewable Fuel 

 Under RFS1, virtually all renewable fuel is required to be assigned a RIN by the producer 

or importer. This requirement was developed and finalized in the RFS1 rulemaking in order to 

address stakeholder concerns, particularly from obligated parties, that the number of available 

RINs should reflect the total volume of renewable fuel used in the transportation sector in the 

U.S. and facilitate program compliance. EISA has dramatically increased the mandated volumes 

of renewable fuel that obligated parties must ensure are produced and used in the U.S. At the 

same time, EISA makes it more difficult for renewable fuel producers to demonstrate that they 

have fuel that qualifies for RIN generation by restricting qualifying renewable fuel to that made 

from “renewable biomass.” The inclusion of such restrictions under RFS2 may mean that, in 

some situations, a renewable fuel producer would prefer to forgo the benefits of RIN generation 

to avoid the cost of ensuring that its feedstocks qualify for RIN generation. If a sufficient 

number of renewable fuel producers acted in this way, it could lead to a situation in which not all 
 

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qualifying fuel is assigned RINs, thus resulting in a shortage of RINs in the market that could 

force obligated parties into non-compliance even though biofuels are being produced and used. 

Another possible outcome would be that the demand for and price of RINs would increase 

significantly, making compliance by obligated parties more costly and difficult than necessary 

and raising prices for consumers. 

With these concerns in mind, EPA proposed to preserve in RFS2 the RFS1 requirement 

that RINs be generated for all qualifying renewable fuel. We also proposed that renewable fuel 

producers maintain records showing that they utilized feedstocks made from renewable biomass 

if they are generating RINs, or, if they are not generating RINs, that they did not use feedstocks 

that qualify as renewable biomass. However, we considered this matter further, and we realize 

that the implication of these proposed requirements is that renewable fuel producers would be 

caught in the untenable position of being forced to participate in the RFS2 program (register, 

keep records, etc.) even if they are unable to generate RINS because their feedstocks do not meet 

the definition of renewable biomass. We received many comments on the proposed requirement 

to generate RINs for all qualifying renewable fuel. Most commenters argued that the 

requirement to keep records for non-qualifying renewable fuels was excessively onerous and 

served little purpose for the program. 

 

After considering the comments received, EPA has determined that this requirement 

would be overly burdensome and unreasonable for producers. The burden stems from the 

requirement that producers prove that their feedstocks do not qualify if they are not generating 

RINs. If the data did not exist or could not be obtained, producers could not produce the fuel, 
 

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even if no RINs would be generated. Thus, for the final rule, EPA is requiring only that 

producers that do generate RINs have the requisite records (as discussed in section II.B.4.c.i. of 

this preamble) documenting that their fuel is produced from feedstocks meeting the definition of 

renewable biomass. Non-RIN generating producers need not maintain any paperwork related to 

their feedstocks and their origins. 

Although EPA is not requiring that RINs be generated for all qualifying renewable fuel, 

EPA is seeking to avoid situations where biofuels are produced, but RINs are not made available 

to the market for compliance. EPA received comments requesting that we consider a provision 

in which any volume of renewable fuel for which RINs were not generated would be an 

obligated volume for that producer, to serve as a disincentive for those producers who might not 

generate RINs in order to avoid the RFS program requirements. While EPA is not finalizing this 

provision in today’s rule, we may consider a future rulemaking to promulgate a provision such as 

this if we find that EISA volumes are not being met due to producers declining to generate RINs 

for their qualifying renewable fuel. We also note that it is ultimately the availability of 

qualifying renewable fuel, as determined in part by the number of RINs in the marketplace, that 

will determine the extent to which EPA should issue a waiver of RFS requirements on the basis 

of inadequate domestic supply. It is in the interest of renewable fuel producers to avoid a 

situation where a waiver of the EISA volume requirements appears necessary. EPA encourages 

renewable fuel producers to generate RINs for all fuel that is made from feedstocks meeting the 

definition of renewable biomass and that meets the GHG emissions reduction thresholds set out 

in EISA. Please see section II.D.6 for additional discussion of this issue. 
 

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c. Implementation Approaches for Domestic Renewable Fuel 

 Consistent with RFS1, renewable fuel producers will be responsible for generating 

Renewable Identification Numbers (RINs) under RFS2. In order to determine whether or not 

their fuel is eligible for generating RINs, renewable fuel producers will generally need to have at 

least basic information about the origin of their feedstocks, to ensure they meet the definition of 

renewable biomass. In the proposal, EPA described and sought comment on several approaches 

for implementing the land restrictions on renewable biomass contained in EISA. 

 The proposed approach for ensuring that producers generate RINs properly was that EPA 

would require that renewable fuel producers obtain documentation about their feedstocks from 

their feedstock supplier(s) and take the measures necessary to ensure that they know the source 

of their feedstocks and can demonstrate to EPA that they fall within the EISA definition of 

renewable biomass. EPA would require renewable fuel producers who generate RINs to affirm 

on their renewable fuel production reports that the feedstock used for each renewable fuel batch 

meets the definition of renewable biomass. EPA would also require renewable fuel producers to 

maintain sufficient records to support these claims. Specifically, we proposed that renewable 

fuel producers who use planted crops or crop residue from existing agricultural land, or who use 

planted trees or slash from actively managed tree plantations, would be required to have copies 

of their feedstock producers’ written records that serve as evidence of land being actively 

managed (or fallow, in the case of agricultural land) since December 2007, such as sales records 

for planted crops or trees, livestock, crop residue, or slash; a written management plan for 

agricultural or silvicultural purposes; or, documentation of participation in an agricultural or 
 

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silvicultural program sponsored by a Federal, state or local government agency. In the case of all 

other biomass, we proposed to require renewable fuel producers to have, at a minimum, written 

records from their feedstock supplier that serve as evidence that the feedstock qualifies as 

renewable biomass. 

We sought comment on this approach generally as well as other methods of verifying 

renewable fuel producers’ claims that feedstocks qualify as renewable biomass. EPA received 

extensive comments on the proposed approach. Many affected parties argued that the proposed 

approach would pose an unnecessary recordkeeping burden on both feedstock and renewable 

fuel producers when, in practice, new lands will not be cleared, at least in the near future, for 

purposes of growing renewable fuel feedstocks. Commenters argued that individual 

recordkeeping was onerous, when compliance with the renewable biomass requirements could be 

determined through the use of existing data and third-party programs. Commenters contend that 

the recordkeeping and feedstock tracking requirements are particularly arduous for corn, 

soybeans and other agricultural crops that are used as renewable fuel feedstocks due to both the 

maturity and the highly fungible nature of those feedstock systems. In contrast, other 

commenters argued that recordkeeping and reporting requirements are necessary to ensure that 

feedstocks are properly verified as renewable biomass to prevent undesirable impacts on natural 

ecosystems and wildlife habitat globally. 

We also sought comment on the possible use under EISA of non-governmental, thirdparty verification programs used for certifying and tracking agricultural and forest products from 

point of origin to point of use both within the U.S. and outside the U.S. We examined third party 
 

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organizations that certify specific types of biomass from croplands and organizations that certify 

forest lands, including the Roundtable on Sustainable Palm Oil, the Basel Criteria for 

Responsible Soy Production, the Roundtable on Sustainable Biofuels (RSB) and the Better 

Sugarcane Initiative (BSI). Additionally, we examined the work of the international Soy 

Working Group, the Brazilian Association of Vegetable Oil Industries (ABIOVE) and Brazil’s 

National Association of Grain Exporters (ANEC), Greenpeace, Verified Sustainable Ethanol 

initiative, the Sustainable Agriculture Network (SAN), the Forest Stewardship Council (FSC), 

American Tree Farm program and Sustainable Forestry Initiative (SFI). We proposed not to 

solely rely on any existing third-party verification program to implement the land restrictions on 

renewable biomass under RFS2 for several reasons. These programs are limited in the scope of 

products they certify, the acreage of land certified through third parties in the U.S. covers only a 

small portion of the total available land estimated to qualify for renewable biomass production 

under the EISA definition, and none of the existing third-party systems had definitions or criteria 

that perfectly match the land use definitions and restrictions contained in the EISA definition of 

renewable biomass. 

We received several comments indicating that producers would like to use evidence of 

their participation in these types of programs to prove that their feedstocks meet the definition of 

renewable biomass. Others argued that while, at this time, the requirements of third party 

programs may not encompass all of the restrictions and requirements of EISA’s renewable 

biomass definition, the programs may alter their criteria in the future to parallel EISA’s 

requirements. EPA agrees that this is a possibility and, in the future, will consider the use of 

these programs in order to simplify compliance with the renewable biomass requirements. We 
 

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encourage fuel producers to work to identify changes to such programs that could allow them to 

be used as a viable compliance option. 

In the proposal, EPA also acknowledged that land restrictions contained within the 

definition of renewable biomass may not, in practice, result in a significant change in agricultural 

practices, since biomass from nonqualifying lands may still be used for non-fuel (e.g. food) 

purposes. Therefore, we sought comment on a stakeholder suggestion to establish a baseline 

level of production of biomass feedstocks such that reporting and recordkeeping requirements 

would be triggered only when the baseline production levels of feedstocks used for biofuels were 

exceeded. Additionally, EPA offered as an alternative the use of existing satellite and aerial 

imagery and mapping software and tools to implement the renewable biomass provisions of 

EISA. We received numerous comments in support of these options. Commenters argued that 

USDA collects and maintains ample data on land use that EPA could use to demonstrate that, 

due to increasing crop yields and other considerations, agricultural land acreage will not expand, 

at least in the near term, to accommodate the increased renewable fuel obligations of RFS2. 

EPA also sought comment on an additional alternative in which EPA would require 

renewable fuel producers to set up and administer a company-wide quality assurance program 

that would create an additional level of rigor in the implementation scheme for the EISA land 

restrictions on renewable biomass. EPA is not finalizing this company-wide quality assurance 

program approach, but rather, is encouraging the option for an industry-wide quality assurance 

program, as described in the following section, to be administered. 
 

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i. Recordkeeping and Reporting for Feedstocks 

 

 After considering the comments we received on the proposed approach, EPA is finalizing 

reporting and recordkeeping requirements comparable to those in the approach we discussed in 

the proposed rule for all categories of renewable biomass, with the exception of planted crops 

and crop residue from agricultural land in the United States, which will be covered by the 

aggregate compliance approach discussed below in Section II.B.4.c.iii. EPA believes that these 

requirements on the fuel producer utilizing feedstocks other than crops and crop residue are 

necessary to ensure that the definition of renewable biomass is being met, and to allow 

feedstocks to be traced from their original producer to the renewable fuel production facility. 

Furthermore, we believe that, in most cases, feedstock producers will already have or will be 

able to easily generate the specified documentation for renewable fuel producers necessary to 

provide them with adequate assurance that the feedstock in question meets the definition of 

renewable biomass. 

 Under today’s rule, all renewable fuel producers must maintain written records from their 

feedstock suppliers for each feedstock purchase that identify the type and amount of feedstocks 

and where the feedstock was produced and that are sufficient to verify that the feedstock 

qualifies as renewable biomass. Specifically, renewable fuel producers must maintain maps 

and/or electronic data identifying the boundaries of the land where the feedstock was produced, 

product transfer documents (PTDs) or bills of lading tracing the feedstock from that land to the 

renewable fuel production facility, and other written records that serve as evidence that the 
 

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feedstock qualifies as renewable biomass. We believe the maps or electronic data can be easily 

generated using existing web-based information. 

Producers using planted trees and tree residue from tree plantations must maintain 

additional documentation that serves as evidence that the tree plantation was cleared prior to 

December 19, 2007, and actively managed as a tree plantation on December 19, 2007. This 

documentation must consist of the following types of records which must be traceable to the land 

in question: sales records for planted trees or slash; purchasing records for fertilizer, weed 

control, or reseeding, including seeds, seedlings, or other nursery stock together with other 

written documentation connecting the land in question to these purchases; a written management 

plan for silvicultural purposes; documentation of participation in a silvicultural program 

sponsored by a Federal, state or local government agency; or documentation of land management 

in accordance with a silvicultural product certification program; an agreement for land 

management consultation with a professional forester that identifies the land in question; or 

evidence of the existence and ongoing maintenance of a road system or other physical 

infrastructure designed and maintained for logging use. There are many existing programs, such 

as those administered by USDA and independent third-party certifiers, that could be used as 

documentation that verifies that feedstock from certain land qualifies as renewable biomass. For 

example, many tree plantation owners already participate in a third-party certification program 

such as FSC or SFI. Written proof of participation by a tract of land in a program of this type on 

December 19, 2007 would be sufficient to show that a tree plantation was cleared prior to that 

date and that it was actively managed on that date. The tree plantation owner would need to send 
 

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copies of this documentation to the renewable fuel producer when supplying them with biomass 

that will be used as a renewable fuel feedstock. 

We anticipate that the recordkeeping requirements will result in renewable fuel producers 

amending their contracts and modifying their supply chain interactions to satisfy the requirement 

that producers have documented assurance and proof about their feedstock’s origins. 

Enforcement will rely in part on EPA’s review of renewable fuel production reports and attest 

engagements of renewable fuel producers’ records. EPA will also consult other data sources, 

including any data made available by USDA, and may conduct site visits or inspections of 

feedstock producers’ and suppliers’ facilities. 

The reporting requirements for renewable biomass in today’s final rule include, as 

proposed, include an affirmation by the renewable fuel producer for each batch of renewable fuel 

for which they generate RINs that the feedstocks used to produce the batch meet the definition of 

renewable biomass. Additionally, the final reporting requirements include a quarterly report to 

be sent to EPA by each renewable fuel producer that includes a summary of the types and 

volumes of feedstocks used throughout the quarter, as well as electronic data or maps identifying 

the land from which those feedstocks were harvested. Producers need not provide duplicate maps 

if purchasing feedstocks multiple times from one plot of land; producers may cross-reference the 

previously submitted map. Producers will also be required to keep records tracing the feedstocks 

from the land to the renewable fuel production facility, other written records from their feedstock 

suppliers that serve as evidence that the feedstock qualifies as renewable biomass, and for 

producers using planted trees or tree residue from tree plantations, written records that serve as 
 

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evidence that the land from which the feedstocks were obtained was cleared prior to December 

19, 2007 and actively managed on that date. These requirements will apply to renewable fuel 

producers using feedstocks from foreign sources (unless special approvals are granted in the 

future, as described below), or from domestic sources, except for planted crops or crop residue 

(discussed below). 

This approach will be integrated into the existing registration, recordkeeping, reporting, 

and attest engagement procedures for renewable fuel producers. It places the burden of 

implementation and enforcement on renewable fuel producers rather than bringing feedstock 

producers and suppliers directly under EPA regulation, minimizing the number of regulated 

parties under RFS2. 

 EPA also sought comment on, and is finalizing as an option, an alternative approach in 

which EPA allows renewable fuel producers and renewable fuel feedstock producers and 

suppliers to develop a quality assurance program for the renewable fuel production supply chain, 

similar to the model of the successful Reformulated Gasoline Survey Association. While 

individual renewable fuel producers may still choose to comply with the individual renewable 

biomass recordkeeping and reporting requirements rather than participate in a quality assurance 

program, we believe that this preferred alternative could be less costly than an individual 

compliance demonstration, and it would add a quality assurance element to RFS2. Those 

participating renewable fuel producers would be presumed to be in compliance with the 

renewable biomass requirements unless and until the quality assurance program finds evidence to 

the contrary. Under today’s rule, renewable fuel producers must choose either to comply with 
 

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the individual renewable biomass recordkeeping and reporting described above, or they must 

participate in the quality assurance program. 

The quality assurance program must be carried out by an independent auditor funded by 

renewable fuel producers and feedstock suppliers. The program must consist of a verification 

program for participating renewable fuel producers and renewable feedstock producers and 

handlers designed to provide independent oversight of the feedstock handling processes that are 

required to determine if a feedstock meets the definition of renewable biomass. Under this 

option, a participating renewable fuel producer and its renewable feedstock suppliers and 

handlers would have to participate in the funding of an organization which arranges to have an 

independent auditor conduct a program of compliance surveys. The compliance audit must be 

carried out by an independent auditor pursuant to a detailed survey plan submitted to EPA for 

approval by November 1 of the year preceding the year in which the alternative compliance 

program would be implemented. The compliance survey program plan must include a 

statistically supportable methodology for the survey, the locations of the surveys, the frequency 

of audits to be included in the survey, and any other elements that EPA determines are necessary 

to achieve the same level of quality assurance as the individual recordkeeping and reporting 

requirements included in the RFS2 regulations. 

Under this alternative compliance program, the independent auditor would be required to 

visit participating renewable feedstock producers and suppliers to determine if the biomass they 

supply to renewable fuel producers meets the definition of renewable biomass. This program 

would be designed to ensure representative coverage of participating renewable feedstock 
 

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producers and suppliers. The auditor would generate and report the results of the surveys to EPA 

each calendar quarter. In addition, where the survey finds improper designations or handling, the 

renewable fuel producers would be responsible for identifying and addressing the root cause of 

the problem. The renewable fuel producers would have to take corrective action to retire the 

appropriate number of invalid RINs depending on the violation. EPA received comments from a 

number of parties who were supportive of this option as an alternative and less-burdensome way 

of ensuring that renewable fuel feedstocks meet the definition of renewable biomass. EPA 

believes this option to be an efficient and effective means of implementing and enforcing the 

renewable biomass requirements of EISA, and has therefore included it as a compliance option 

in today’s final rule. 

 

ii. Approaches for Foreign Producers of Renewable Fuel 

The EISA renewable biomass language does not distinguish between domestic renewable 

fuel and fuel feedstocks and renewable fuel and fuel and feedstocks that come from abroad. 

EPA proposed that foreign producers of renewable fuel that is exported to the U.S. be required to 

meet the same compliance obligations as domestic renewable fuel producers, as well as some 

additional measure, discussed in Section II.C., designed to facilitate EPA enforcement in other 

countries. These proposed obligations include facility registration and submittal of independent 

engineering reviews (described in Section II.C below), and reporting, recordkeeping, and attest 

engagement requirements. The proposal also would have included for foreign producers the 

same obligations that domestic producers have for verifying that their feedstock meets the 

definition of renewable biomass, such as certifying on each renewable fuel production report that 
 

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their renewable fuel feedstock meets the definition of renewable biomass and working with their 

feedstock suppliers to ensure that they receive and maintain accurate and sufficient 

documentation in their records to support their claims. 

(1) RIN-generating importers 

 

 EPA proposed to allow importers to generate RINs for renewable fuel they are importing 

into the U.S. only if the foreign producer of that renewable fuel had not already done so. Under 

the proposal, in order to generate RINs, importers would need to obtain information from the 

registered foreign producers concerning the point of origin of their fuel’s feedstock and whether 

it meets the definition of renewable biomass. Therefore, we proposed that in the event that a 

batch of foreign-produced renewable fuel does not have RINs accompanying it when it arrives at 

a U.S. port, an importer must obtain documentation that proves that the fuel’s feedstock meets 

the definition of renewable biomass (as described in Section II.B.4.a. of this preamble) from the 

fuel’s producer, who must have registered with the RFS program and conducted a third-party 

engineering review. With such documentation, the importer could generate RINs prior to 

introducing the fuel into commerce in the U.S. 

 We sought comment on this proposed approach and whether and to what extent the 

approaches for ensuring compliance with the EISA’s land restrictions by foreign renewable fuel 

producers should differ from the proposed approach for domestic renewable fuel producers. We 

received comments on the proposed implementation option for importers of foreign renewable 

fuel. Some argue that the proposed recordkeeping requirements for imported fuel were overly 
 

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burdensome. On the other hand, others argued that importers, similarly to domestic producers, 

should be required to obtain information that can serve as evidence that the feedstocks meet the 

definition of renewable biomass, in order to avoid fraud. Some commenters also argued that 

importers should be able to generate RINs for fuel imported from foreign producers that are not 

registered with EPA under the RFS2 program. 

For the final rule, EPA is requiring that importers may only generate RINs for renewable 

fuel if the foreign producer has not already done so. The foreign producers must be registered 

with EPA under the RFS2 program, and must have conducted an independent engineering 

review. Furthermore, we are requiring that importers obtain from the foreign producer and 

maintain in their records written documentation that serves as evidence that the renewable fuel 

for which they are generating RINs was made from feedstocks meeting the definition of 

renewable biomass. The foreign producer that originally generated the fuel must ensure that 

these feedstock records are transferred with each batch of fuel and ultimately reach the RINgenerating importer. A requirement that importers maintain these renewable biomass records is 

consistent with the renewable biomass recordkeeping requirements imposed on domestic 

producers of renewable fuel. 

(2) RIN-generating foreign producers 

Foreign producers that intend to generate RINs would be required to designate renewable 

fuel intended for export to the U.S. as such, segregate the volume until it reaches the U.S., and 

post a bond to ensure that penalties can be assessed in the event of a violation, as discussed in 
 

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Section II.D.2.b. Similarly to domestic producers of renewable fuel, foreign producers must 

obtain and maintain written documentation from their feedstock providers that can serve as 

evidence that their feedstocks meet the definition of renewable biomass. Foreign producers may 

also develop a quality assurance program for their renewable fuel production supply chain, as 

described above. However, while domestic renewable fuel producers using crops or crop 

residues may rely on the aggregate compliance approach described below to ensure that their 

feedstocks are renewable biomass, this approach is not available at this time to foreign renewable 

fuel producers, as described below. 

EPA believes that the renewable biomass recordkeeping provisions are necessary in order 

for EPA to ensure that RINs are being generated for fuel that meets EISA’s definition of 

renewable fuel. Just as for domestic producers, foreign producers must maintain evidence that 

the fuel meets the GHG reduction requirements and is made from renewable biomass. 

iii. Aggregate Compliance Approach for Planted Crops and Crop Residue from 

Agricultural Land 

In light of the comments received on the proposed renewable biomass recordkeeping 

requirements and implementation options, EPA sought assistance from USDA in determining 

whether existing data and data sources might suggest an alternative method for verifying 

compliance with renewable biomass requirements associated with the use of crops and crop 

residue for renewable fuel production. Taking into consideration publicly available data on 

agricultural land available from USDA and USGS as well as expected economic incentives for 
 

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feedstock producers, EPA has determined that an aggregate compliance approach is appropriate 

for certain types of renewable biomass, namely planted crops and crop residue from the United 

States. 

Under the aggregate compliance approach, EPA is determining for this rule the total 

amount of “existing agricultural land” in the U.S. (as defined above in Section II.B.4.a.) at the 

enactment date of EISA, which is 402 million acres. EPA will monitor total agricultural land 

annually to determine if national agricultural land acreage increases above this 2007 national 

aggregate baseline. Feedstocks derived from planted crops and crop residues will be considered 

to be consistent with the definition of renewable biomass and renewable fuel producers using 

these feedstocks will not be required to maintain specific renewable biomass records as 

described below unless and until EPA determines that the 2007 national aggregate baseline is 

exceeded. If EPA finds that the national aggregate baseline is exceeded, individual 

recordkeeping and reporting requirements as described below will be triggered for renewable 

fuel producers using crops and crop residue. We believe that the aggregate approach will fully 

ensure that the EISA renewable biomass provisions related to crops and crop residue are 

satisfied, while also easing the burden for certain renewable fuel producers and their feedstock 

suppliers vis-à-vis verification that their feedstock qualifies as renewable biomass. 

As discussed in more detail below, there are five main factors supporting the aggregate 

compliance approach we are taking for planted crops and crop residue. First, EPA is using data 

sets that allow us to obtain an appropriately representative estimate of the agricultural lands 

available under EISA for the production of crops and crop residue as feedstock for renewable 
 

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fuel production. Second, USDA data indicate an overall trend of agricultural land contraction. 

These data, together with EPA economic modeling, suggest that 2007 aggregate baseline acreage 

should be sufficient to support EISA renewable fuel obligations and other foreseeable demands 

for crop products, at least in the near term, without clearing and cultivating additional land. 

Third, EPA believes that existing economic factors for feedstock producers favor more efficient 

utilization practices of existing agricultural land rather than converting non-agricultural lands to 

crop production. Fourth, if, at any point, EPA finds that the total amount of land in use for the 

production of crops including crops for grazing and forage is equal or greater than 397 million 

acres (i.e. within 5 million acres of EPA’s established 402 million acre baseline), EPA will 

conduct further investigations to evaluate whether the presumption built into the aggregate 

compliance approach remains valid. Lastly, EPA has set up a trigger mechanism that in the 

event there are more than the baseline amount of acres of cropland, pastureland and CRP land in 

production, renewable fuel producers will be required to meet the same individual or consortiumbased recordkeeping and reporting requirements applicable to RIN-generating renewable fuel 

producers using other feedstocks. Taken together, these factors give EPA high confidence that 

the aggregate compliance approach for domestically grown crops and crop residues meets the 

statutory obligation to ensure feedstock volumes used to meet the renewable fuel requirements 

also comply with the definition of renewable biomass. 

(1) Analysis of Total Agricultural Land in 2007 

As described in Section II.B.4.a. above, EPA is defining “existing agricultural land” for 

purposes of the EISA land use restrictions on crops and crop residue to include cropland, 
 

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pastureland and CRP land that was cleared and actively managed or fallow and nonforested on 

the date of EISA enactment. To determine the aggregate total acreage of existing agricultural 

land for the aggregate compliance approach on the date of EISA enactment, EPA obtained from 

USDA data representing total cropland (including fallow cropland), pastureland, and CRP land 

in 2007 from three independently gathered national land use data sources (discussed in further 

detail below): the Farm Service Agency (FSA) Crop History Data, the USDA Census of 

Agriculture (2007), and the satellite-based USDA Crop Data Layer (CDL). In addition, CRP 

acreage is provided by FSA’s annually published “Conservation Reserve Program: Summary 

and Enrollment Statistics.” By definition, the cropland, pastureland, and CRP land included in 

these data sources for 2007 were cleared or cultivated on the date of EISA enactment (December 

19, 2007) and, consistent with the principles set forth in Section II.4.a.i, would be considered 

"actively managed" or fallow and nonforested on that date. These categories of lands include 

those from which traditional crops, such as corn, soy, wheat and sorghum, would likely be 

grown. Therefore quantification of cropland, pastureland, and CRP land from these data sources 

represents a reasonable assessment of the acreage in the United States that is available under the 

Act for the production of crops and crop residues that could satisfy the definition of renewable 

biomass in EISA. 

Conservation Reserve Program Data. FSA reports CRP enrollment acreage each year in 

the publication “Conservation Reserve Program: Summary and Enrollment Statistics.” The CRP 

program includes the general CRP, the Conservation Reserve Enhancement Program (CREP), 

and the Farmable Wetlands Program (FWP). The Wetlands Reserve Program (WRP) and 

Grasslands Reserve Program (GRP) are not under CRP and are not included in the total 
 

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agricultural land figure in this rulemaking. The 2007 CRP acreage was 36.7 million acres. This 

is an exact count of acreage within the CRP program in 2007. 

Farm Service Agency Crop History Data. The FSA maintains annual records of fieldlevel land use data for all farms enrolled in FSA programs. Almost all national cropland and 

pastureland is reported through FSA and recorded in this data set. We used the “Cropland” 

category to determine total agricultural land. Pastureland is reported by farms under the category 

“Cropland” as cropland used for grazing and forage under the crop type “mixed forage.” Timber 

land and any grazed native grass was removed from the “Cropland” category, because these land 

types represent either forestland or rangeland, which are not within the definition of existing 

agricultural land. CRP lands and other conservation program lands are also reported as cropland. 

Because GRP and WRP lands are not within the definition of “existing agricultural land” as 

defined in today’s regulations, they were also subtracted from the “Cropland” category total. 

FSA Crop History Data show that there was 402 million acres of agricultural land, as defined 

here, in the U.S. in 2007 (See Table II.B.4-1). 

Table II.B.4-1 

Total U.S. Agricultural Land in 2007 from USDA Data Sources 

Land Category FSA Crop History Data Agricultural Census Data 

Cropland and Pastureland 365 367 

CRP Land 37 37 

Total Land 402 404 
 

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USDA Census of Agriculture. USDA conducts a full census of the U.S. agricultural 

sector once every five years. The data are available for the U.S., each of the 50 States, and for 

each county. The most recent census available is the 2007 Census of Agriculture. For the 

purpose of this rulemaking, USDA provided EPA total acreage and 95% confidence intervals for 

the Census category “Total Cropland,” which includes the sub-categories “Harvested cropland,” 

“Cropland used only for pasture and grazing,” and “Other cropland.” WRP and GRP acreage are 

included in “Other cropland,” so, for purposes of this rulemaking, they were subtracted from the 

sub-category number (see above). The analysis excluded the “Permanent rangeland and pasture” 

category, as the pasture data cannot be separated from rangeland in this category. Total CRP 

acreage in 2007 was added to “Total cropland.” With these adjustments, the Census of 

Agriculture showed 404 million acres (95% confidence range 401-406 million acres) of existing 

agricultural land as defined in today’s rule, in the U.S. in 2007 (See Table II.B.4-1). 

Crop Data Layer. The USDA National Agricultural Statistics Service (NASS) Crop Data 

Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer suitable for use in 

geographic information systems (GIS) analysis. Based on satellite data, the CDL has a ground 

resolution of 56 meters and was verified using FSA surveys. The CDL covers 21 major 

agricultural states for 2007 and therefore cannot be used to determine a 2007 national aggregate 

agricultural land baseline. There will be full coverage of the 48 contiguous states for 2009, and 

the CDL can be used for analysis validation purposes during monitoring. From 2010 onward, it 

coverage of the 48 contiguous states will be dependent on available funding. GIS analyses of the 

CDL will include all cropland and pastureland data for each state. To ensure that non-pasture 
 

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grasslands are not included in the final sum, all areas of the “Grassland herbaceous” category 

from the U.S. Geological National Land Cover Data layer (NLCD) that overlap the CDL layers 

are removed from the total agricultural land number. Producer and user accuracies8

 are available 

for the CDL crop categories. 

Primary Data Source Selection for Aggregate Compliance Approach. EPA has 

determined that the FSA Crop History Data will be used as the data set on which the total 

existing agricultural land baseline will be based for the aggregate compliance approach. The 

FSA Crop History Data is the only complete data set for 2007 that is collected annually, enabling 

EPA to monitor agricultural land expansion or contraction from year to year using a consistent 

data set. The total existing agricultural land value derived from FSA Crop History Data rests 

within the 95% confidence interval of the 2007 Census of Agriculture and is only 2 million acres 

less than the Census of Agriculture point estimate. The Census of Agriculture provides slightly 

fuller coverage than the FSA Crop History Data due to the nature of the data collection; 

however, given that both data collection systems have consistent and long-standing 

methodologies, the disparity between the two should remain approximately constant. Therefore, 

the FSA Crop History Data will provide a consistent data set for analyzing any expansion or 

contraction of total national agricultural land in the U.S. 

During its annual monitoring, EPA will use the FSA Crop History Data and the CDL 

analyses as a secondary source to validate our annual assessment. In years when the Census of 

Agriculture is updated, this data will also be used to validate our annual assessment. Other data 

 

8

 "Producer Accuracy" indicates the probability that a groundtruth pixel will be correctly mapped and measures 

errors of omission; "User Accuracy" indicates the probability that a pixel from the classification actually matches 

the groundtruth data and measures errors of omission. 
 

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sources, such as the annual NASS Farms, Land in Farms and Livestock Operations may also be 

useful as secondary data checks. Lastly, EPA intends to consider, as appropriate, other data 

sources for the annual monitoring analysis of total agricultural land as new technologies and data 

sources come online that would improve the accuracy and robustness of annual monitoring. 

(2) Aggregate Agricultural Land Trends over Time 

The Census of Agriculture (conducted every five years) shows that U.S. agricultural land 

has decreased by 44 million acres from 1997 to 2007, indicating an overall decade trend of 

contraction of agricultural land utilization despite some year-to-year variations that can be seen 

by reference to the annual FSA Crop History records (See Table II.B.4-2 and Table II.B.4-3). 

EPA’s FASOM modeling results, which model full EISA volumes in 2022, support this 

contraction trend, indicating that total cropland, pastureland, and CRP land in the U.S. in 2022, 

under a scenario of full renewable fuel volume as required by EISA, would be less than the 2007 

national acreage reported in the FSA Crop History Data (See preamble Section VII and RIA 

Chapter 5). 

Table II.B.4-2 

Total agricultural land (as defined in Section II.B.4.a) counted in the Census of Agriculture from 

1997-2007 

Census 

Year 

Total Agricultural 

Land 

(millions of acres) 
 

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2007 404 

2002* 431 

1997* 445 

*2002 data do not include farms with land in FWP or CREP. 

Table II.B.4-3 

Total agricultural land (as defined in Section II.B.4.a) recorded in FSA Crop History Data from 

2005-2007 

Year 

Total Agricultural 

Land 

(millions of acres) 

2007 402 

2006 393 

2005 392 

(3) Aggregate Compliance Determination 

 The foundation of the aggregate compliance approach is establishment of a baseline 

amount of eligible agricultural land that was cleared or cultivated and actively managed or fallow 

and non-forested on December 19, 2007. Based on USDA-FSA Crop History Data, EPA is 

establishing a baseline of 402 million acres of U.S. agricultural land, as defined in Section 

II.B.4.a and based upon the methods described in Section II.B.4.c.iii.(1), that is eligible for 
 

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production of planted crops and crop residue meeting the EISA definition of renewable biomass. 

EPA will monitor total U.S. agricultural land annually, using FSA Crop History Data as a 

primary determinant, but using other data sources for support (See Section II.4.c.iii.(1)). If, at 

any point, EPA finds that the total land in use for the production of crops, including crops for 

grazing and forage, is greater than 397 million acres (i.e. within 5 million acres of EPA’s 

established 402 million acre baseline), EPA will conduct further investigations to evaluate 

whether the presumption built into the aggregate compliance approach remains valid. 

Additionally, if EPA determines that the data indicates that this 2007 baseline level of eligible 

agricultural land has been exceeded, EPA will publish in the Federal Register a finding to that 

effect, and additional requirements will be triggered for renewable fuel producers to verify that 

they are using planted crops and crop residue from “existing agricultural land” as defined in 

today’s rule as their renewable fuel feedstock. EPA’s findings will be published by November 

30, at the latest. If in November the 402 million acres baseline is found to be exceeded, then on 

July 1 of the following year, renewable fuel producers using feedstocks qualifying for this 

aggregate compliance approach, namely planted crops and crop residue from the United States, 

will be required to comply with the recordkeeping and reporting requirements applicable to 

producers using other types of renewable biomass, as described in the previous sections. This 

includes the option that fuel producers could utilize a third-party consortium to demonstrate 

compliance. 

EPA acknowledges that it is possible that under this approach some of the land available 

under EISA for crop production on the date of EISA enactment could be retired and other land 

brought into production, without altering the assessment of the aggregate amount of cropland, 
 

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pastureland and CRP land. Under EISA, crops or crop residues from the new lands would not 

qualify as renewable biomass. However, EPA expects such shifts in acreage to be de minimus, 

as long as the total aggregate amount of agricultural land does not exceed the 2007 national 

aggregate baseline. EPA expects that new lands are unlikely to be cleared for agricultural 

purposes for two reasons. First, it can be assumed that most undeveloped land that was not used 

as agricultural land in 2007 is generally not suitable for agricultural purposes and would serve 

only marginally well for production of renewable fuel feedstocks. Due to the high costs and 

significant inputs that would be required to make the non-agricultural land suitable for 

agricultural purposes, it is highly unlikely that farmers will undertake the effort to “shift” land 

that is currently non-agricultural into agricultural use. Second, crop yields are projected to 

increase, reducing the need for farmers to clear new land for agricultural purposes. We believe 

that this effect is reflected in the overall trend, discussed earlier, of an overall contraction in 

agricultural land acreage over time. 

If EPA determines that the baseline is exceeded, and that individual compliance with the 

renewable biomass reporting and recordkeeping requirements is triggered, renewable fuel 

producers using crops and crop residue as a feedstock for renewable fuel would become 

responsible, beginning July 1 of the following year, for meeting individual recordkeeping and 

reporting requirements related to renewable biomass verification. These requirements are 

identical to those that apply to producers using other types of renewable biomass feedstocks, 

such as planted trees from tree plantations, as described in the previous sections. Renewable fuel 

producers generating RINs under the RFS2 program would continue to be required to affirm 

(through EMTS – EPA Moderated Transaction System) for each batch of renewable fuel that 
 

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their feedstocks meet the definition of renewable biomass. Additionally, producers would send a 

quarterly report to EPA that includes a summary of the types and volumes of feedstocks used 

throughout the quarter, as well as electronic data or maps identifying the land from which those 

feedstocks were harvested. 

Furthermore, those RIN-generating renewable fuel producers will be required to obtain 

and maintain in their files written records from their feedstock suppliers for each feedstock 

purchase that identify where the feedstocks were produced and that are sufficient to verify that 

the feedstocks qualify as renewable biomass. This includes maps and/or electronic data 

identifying the boundaries of the land where the feedstock was produced, PTDs or bills of lading 

tracing the feedstock from that land to the renewable fuel production facility, and other written 

records that serve as evidence that the feedstock qualifies as renewable biomass. Finally, 

producers using planted crops and crop residue must maintain additional documentation that 

serves as evidence that the agricultural land used to produce the crop or crop residue was cleared 

or cultivated and actively managed or fallow, and nonforested on December 19, 2007. This 

documentation must consist of the following types of records which must be traced to the land in 

question: sales records for planted crops, crop residue, or livestock, purchasing records for land 

treatments such as fertilizer, weed control, or reseeding or a written agricultural management 

plan or documentation of participation in an agricultural program sponsored by a Federal, State 

or local government agency. 

Alternatively, if the baseline is exceeded and the requirements are triggered for individual 

producer verification that their feedstocks are renewable biomass renewable fuel producers may 
 

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choose to work with other renewable fuel producers as well as feedstock producers and suppliers 

to develop a quality assurance program for the renewable fuel production supply chain. This 

quality assurance program would take the place of individual accounting and would consist of an 

independent third party quality-assurance survey of all participating renewable fuel producers 

and their feedstock suppliers, completed in accordance with an industry-developed, EPAapproved plan, to ensure that they are utilizing feedstocks that meet the definition of renewable 

biomass. An in-depth discussion of this industry survey option is included in the previous 

section. 

While the aggregate compliance approach is appropriate for planted crops and crop 

residues from agricultural land in the United States, due in part to certain additional or different 

constraints imposed by EISA, the aggregate approach cannot be applied, at this time, to the other 

types of renewable biomass. Renewable fuel producers utilizing these types of renewable 

biomass, including planted trees and tree residues from tree plantations, slash and precommercial thinnings from non-federal forestland, animal waste, separated yard and food waste, 

etc., will be subject to the individual reporting and recordkeeping requirements discussed in the 

previous section. 

Additionally, EPA is not finalizing the aggregate compliance approach for foreign 

producers of renewable fuel. EPA does not, at this time, have sufficient data to make a finding 

that non-domestically grown crops and crop residues used in renewable fuel production satisfy 

the definition of renewable biomass. Nevertheless, if, in the future, adequate land use data 

becomes available to make a finding that, in the aggregate, crops and crop residues used in 
 

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renewable fuel production in a particular country satisfy the definition of renewable biomass, 

EPA is willing to consider an aggregate compliance approach for renewable biomass on a 

country by country basis, in lieu of the individual recordkeeping and reporting requirements. 

 d. Treatment of Municipal Solid Waste (MSW) 

The statutory definition of “renewable biomass” does not include a reference to 

municipal solid waste (MSW) as did the definition of “cellulosic biomass ethanol” in the Energy 

Policy Act of 2005 (EPAct), but instead includes “separated yard waste and food waste.” 

We solicited comment on whether EPA can and should interpret EISA as including MSW 

that contains yard and/or food waste within the definition of renewable biomass. On the one 

hand, the reference in the statutory definition to “separated yard waste and food waste,” and the 

lack of reference to other components of MSW (such as waste paper and wood waste) suggests 

that only yard and food wastes physically separated from other waste materials satisfy the 

definition of renewable biomass. On the other hand, we noted that EISA does not define the 

term “separated,” and so does not specify the degree of separation required. We also noted that 

there was some evidence in the Act that Congress did not intend to exclude MSW entirely from 

the definition of renewable biomass. The definition of “advanced biofuel” includes a list of 

fuels that are “eligible for consideration” as advanced biofuel, including “ethanol derived from 

waste material” and biogas “including landfill gas.” 
 

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As an initial matter, we note that some materials clearly fall within the definition of 

“separated yard or food waste.” The statute itself identifies “recycled cooking and trap grease” 

as one example of separated food waste. An example of separated yard waste is the leaf waste 

that many municipalities pick up at curbside and keep separate from other components of MSW 

for mulching or other uses. However, a large quantity of food and yard waste is disposed of 

together with other household waste as part of MSW. EPA estimates that about 120 million tons 

of MSW are disposed of annually much of it inextricably mixed with yard and especially food 

waste. This material offers a potentially reliable, abundant and inexpensive source of feedstock 

for renewable fuel production which, if used, could reduce the volume of discarded materials 

sent to landfills and could help achieve both the GHG emissions reductions and energy 

independence goals of EISA. Thus, EPA believes we should consider under what conditions 

yard and food waste that is present in MSW can be deemed sufficiently separated from other 

materials to qualify as renewable biomass. 

One commenter stated that it is clear that MSW does not qualify as renewable biomass 

under EISA, since the 2005 Energy Policy Act explicitly allowed for qualifying renewable fuel 

to be made from MSW, and EISA has no mention of it. Commenters from the renewable fuel 

industry generally favored maximum flexibility for the use of MSW in producing qualifying 

fuels under EISA, offering a variety of arguments based on the statutory text and reasons why it 

would benefit the environment and the nation’s energy policy to do so. They favored either 1) a 

determination that unsorted MSW can be used as a feedstock for advanced biofuel even if it does 

not meet the definition of renewable biomass, 2) that the Act be interpreted to include MSW as 

renewable biomass, or 3) that MSW from which varying amounts of recyclable materials have 
 

152

been removed could qualify as renewable biomass. A consortium of ten environmental groups 

said that for EISA volume mandates to be met, it is important to take advantage of biomass 

resources from urban wastes that would otherwise be landfilled. They urged that post-recycling 

residues (i.e., those wastes that are left over at material recovery facilities after separation and 

recycling) would fit within the letter and spirit of the definition of renewable biomass. 

EPA does not believe that the statute can be reasonably interpreted to allow advanced 

biofuel to be made from material that does not meet the definition of renewable biomass as 

suggested in the first approach. The definition of advanced biofuel specifies that it is a form of 

“renewable fuel,” and renewable fuel is defined in the statute as fuel that is made from renewable 

biomass. While the definition of advanced biofuel includes a list of materials that “may” be 

“eligible for consideration” as advanced biofuel, and that list includes “ethanol derived from 

waste materials” and biogas “including landfill gas,” the fact that the specified items are “eligible 

for consideration” indicates that they do not necessarily qualify but must meet the definitional 

requirements – being “renewable fuel” made from renewable biomass and having life cycle 

greenhouse gas emissions that are at least 50% less than baseline fuel. There is nothing in the 

statute to suggest that Congress used the term “renewable fuel” in the definition of “advanced 

biofuel” to have a different meaning than the definition provided in the statute. The result of the 

commenter’s first approach would be that general renewable fuel and cellulosic biofuel would be 

required to be made from renewable biomass because the definitions of those terms specifically 

refer to renewable biomass, whereas advanced biofuel and biomass-based diesel would not, 

because their definitions refer to “renewable fuel” rather than “renewable biomass.” EPA can 

discern no basis for such a distinction. EPA believes that the Act as a whole is best interpreted 

as requiring all types of qualifying renewable fuels under EISA to be made from renewable 
 

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biomass. In this manner the land and feedstock restrictions that Congress deemed important in 

the context of biofuel production apply to all types of renewable fuels. 

EPA also does not agree with the commenter who suggested that the listing in the 

definition of renewable biomass of “biomass obtained from the immediate vicinity of buildings 

and other areas regularly occupied by people, or of public infrastructure, at risk from wildfire” 

should be interpreted to include MSW. It is clear that the term “at risk of wildfire” modifies the 

entire sentence, and the purpose of the listing is to make the biomass that is removed in wildfire 

minimization efforts, such as brush and dead woody material, available for renewable fuel 

production. Such material does not typically include MSW. Had Congress intended to include 

MSW in the definition of renewable biomass, EPA believes it would have clearly done so, in a 

manner similar to the approach taken in EPAct 

 EPA also does not believe that it would be reasonable to interpret the reference to 

“separated yard or food waste” to include unsorted MSW. Although MSW contains yard and 

food waste, such an approach would not give meaning to the word “separated.” 

 We do believe, however, that yard and food wastes that are part of MSW, and are 

separated from it, should qualify as renewable biomass. MSW is the logical source from which 

yard waste and food waste can be separated. As to the degree of separation required, some 

commenters suggested a simple “post recycling” test be appropriate. They would leave to 

municipalities and waste handlers a determination of how much waste should be recycled before 

the residue was used as a feedstock for renewable fuel production. EPA believes that such an 

approach would not guarantee sufficient “separation” from MSW of materials that are not yard 

waste or food waste to give meaning to the statutory text. Instead, EPA believes it would be 
 

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reasonable in the MSW context to interpret the word “separated” in the term “separated yard or 

food waste” to refer to the degree of separation to the extent that is reasonably practicable. A 

large amount of material can be, and is, removed from MSW and sold to companies that will 

recycle the material. EPA believes that the residues remaining after reasonably practicable 

efforts to remove recyclable materials other than food and yard waste (including paper, 

cardboard, plastic, textiles, metal and glass) from MSW should qualify as separated yard and 

food waste. This MSW-derived residue would likely include some amount of residual nonrecyclable plastic and rubber of fossil fuel origin, much of it being wrapping and packaging 

material for food. Since this material cannot be practicably separated from the remaining food 

and yard waste, EPA believes it is incidental material that is impractical to remove and therefore 

appropriate to include in the category of separated food and yard waste. In sum, EPA believes 

that the biogenic portion of the residue remaining after paper, cardboard, plastic, textiles metal 

and glass have been removed for recycling should qualify as renewable biomass. This 

interpretation is consistent with the text of the statute, and will promote the productive use of 

materials that would otherwise be landfilled. It will also further the goals of EISA in promoting 

energy independence and the reduction of GHG emissions from transportation fuels. 

EPA notes there are a variety of recycling methods that can be used, including curbside 

recycling programs, as well as separation and sorting at a material recovery facility (MRF). For 

the latter, the sorting could be done by hand or by automated equipment, or by a combination of 

the two. Sorting by hand is very labor intensive and much slower than using an automated 

system. In most cases the ‘by-hand’ system produces a slightly cleaner stream, but the high cost 

of labor usually makes the automated system more cost-effective. Separation via MRFs is 
 

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generally very efficient and can provide comparable if not better removal of recyclables to that 

achieved by curbside recycling. 

Based on this analysis, today’s rule provides that those MSW-derived residues that 

remain after reasonably practicable separation of recyclable materials other than food and yard 

waste is renewable biomass. What remains to be addressed is what regulatory mechanisms 

should be used to ensure the appropriate generation of RINs when separated yard and food waste 

is used as a feedstock. We are finalizing two methods. 

The first method would apply primarily to a small subset of producers who are able to 

obtain yard and/or food wastes that have been kept separate since waste generation from the 

MSW waste stream. Examples of such wastes are lawn and leaf waste that have never entered 

the general MSW waste stream. Typically, such wastes contain incidental amounts of materials 

such as the plastic twine used to bind twigs together, food wrappers, and other extraneous 

materials. As with our general approach to the presence of incidental, de minimus contaminants 

in feedstocks that are unintentionally present and impractical to remove, the presence of such 

material in separated yard or food waste will not disqualify such wastes as renewable biomass, 

and the contaminants may be disregarded by producers and importers generating RINs . (See 

definition of renewable biomass and 80.1426(f)(1).) Waste streams kept separate since 

generation from MSW that consist of yard waste are expected to be composed almost entirely of 

woody material or leaves, and therefore will be deemed to be composed of cellulosic materials. 

Waste streams consisting of food wastes, however, may contain both cellulosic and noncellulosic materials. For example, a food processing plant may generate both wastes that are 

primarily starches and sugars (such as carrot and potato peelings, as well as fruits and vegetables 
 

156

that are discarded) as well as corn cobs and other materials that are cellulosic. We will deem 

waste streams consisting of food waste to be composed entirely of non-cellulosic materials, and 

qualifying as advanced biofuels, unless the producer demonstrates that some portion of the food 

waste is cellulosic. The cellulosic portion would then qualify as cellulosic biofuel. The method 

for quantifying the cellulosic and non-cellulosic portions of the food waste stream is to be 

described in a written plan which must be submitted to EPA under the registration procedures in 

80.1450(b)(vii) for approval and which indicates the location of the facility from which wastes 

are obtained, how identification and quantification of waste material is to be accomplished, and 

evidence that the wastes qualify as fully separated yard or food wastes. The producer must also 

maintain records regarding the source of the feedstock and the amounts obtained. 

The second method would involve use as feedstock by a renewable fuel producer of the 

portion of MSW remaining after reasonably practical separation activities to remove recyclable 

materials, resulting in a separated MSW-derived residue that qualifies as separated yard and food 

waste. Today’s rule requires that parties that intend to use MSW-derived residue as a feedstock 

for RIN-generating renewable fuel production ensure that reasonably practical efforts are made 

to separate recyclable paper, cardboard, textiles, plastics, metal and glass from the MSW, 

according to a plan that is submitted by the renewable fuel producer and approved by EPA under 

the registration procedures in 80.1450(b)(viii). In determining whether the plan submittals 

provide for reasonably practicable separation of recyclables EPA will consider: 1) the extent and 

nature of recycling that may have occurred prior to receipt of the MSW material by the 

renewable fuel producer, 2) available recycling technology and practices, and 3) the technology 

or practices selected by the fuel producer, including an explanation for such selection and 
 

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reasons why other technologies or practices were not selected. EPA asks that any CBI 

accompanying a plan or a party's justification for a plan be segregated from the non-CBI portions 

of the submissions, so as to facilitate disclosure of the non-CBI portion of plan submittals, and 

approved plans, to interested members of the public. 

 Producers using this second option, will need to determine what RINs to assign to a fuel 

that is derived from a variety of materials, including yard waste (largely cellulosic) and food 

waste (largely starches and sugar), as well as incidental materials remaining after reasonably 

practical separation efforts such as plastic and rubber of fossil origin. EPA has not yet evaluated 

the lifecycle greenhouse gas performance of fuel made from such mixed sources of waste, so is 

unable at this time to assign a D code for such fuel. However, if a producer uses ASTM test 

method D-6866 on the fuel made from MSW-derived feedstock, it can determine what portion of 

the rule is of fossil and non-fossil origin. The non-fossil portion of the fuel will likely be largely 

derived from cellulosic materials (yard waste, textiles, paper, and construction materials), and to 

a much smaller extent starch-based materials (food wastes). Unfortunately, EPA is not aware of 

a test method that is able to distinguish between cellulosic- and starch-derived renewable fuel. 

Under these circumstances, EPA believes that it is appropriate for producers to base RIN 

assignment on the predominant component and, therefore, to assume that the biogenic portion of 

their fuel is entirely of cellulosic origin. The non-biogenic portion of the fuel, however, would 

not qualify for RINs at this time. Thus, in sum, we are providing via the ASTM testing method 

an opportunity for producers using a MSW-derived feedstock to generate RINs only for the 

biogenic portion of their renewable fuel. There is no D code for the remaining fossil-derived 

fraction of the fuel in today’s rule nor for the entire volume of renewable fuel produced when 
 

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using MSW-derived residue as a feedstock. The petition process for assigning such codes in 

today’s rule can be used for such purpose. 

 Procedures for the use of ASTM Method D-6866 are detailed in 40 CFR 80.1426(f)(9) of 

today’s rule. We solicited comment on this method, and while the context of the discussion of 

method D-6866 was with respect to using it for gasoline (see 74 FR 24951), the comments we 

received provided us information on the method itself. Also, commenters were supportive of its 

use. Fuel producers must either run the ASTM D-6866 method for each batch of fuel produced, 

or run it on composite samples of the food and yard waste-derived fuel derived from postrecycling MSW residues. Producers will be required at a minimum to take samples of every 

batch of fuel produced over the course of one month and combine them into a single composite 

sample. The D-6866 test would then be applied to the composite sample, and the resulting nonfossil derived fraction will be deemed cellulosic biofuel, and applied to all batches of fuel 

produced in the next month to determine the appropriate number of RINs that must be generated. 

The producer would be required to recalculate this fraction at least monthly. For the first month, 

the producer can estimate the non-fossil fraction, and then make a correction as needed in the 

second month. (The procedure using the ASTM D-6866 method applies not only to the wastederived fuel discussed here but also to all partially renewable transportation fuels, and is 

discussed in further detail in Section II.D.4 See also the regulations at §80.1426(f)(4)). 

The procedures for assigning D codes to the fuel produced from such wastes are 

discussed in further detail in Section II.D.5. 
 

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One commenter suggested that biogas from landfills should be treated in the same 

manner as renewable fuel produced from MSW. EPA agrees with the commenter to a certain 

extent. The definition of “advanced biofuels” in EISA identifies “Biogas (including landfill 

gas and sewage waste treatment gas) produced through the conversion of organic matter from 

renewable biomass” as “eligible for consideration” as an advanced biofuel. However, as with 

MSW, the statute requires that advanced biofuel be a “renewable fuel” and that such fuel be 

made from “renewable biomass.” The closest reference within the definition of renewable 

biomass to landfill material is “separated yard or food waste.” However, in applying the 

interpretation of “separated” yard and food waste described above for MSW to landfill material, 

we come to a different result. Landfill material has by design been put out of practical human 

reach. It has been disposed of in locations, and in a manner, that is designed to be permanent. 

For example, modern landfills are placed over impermeable liners and sealed with a permanent 

cap. In addition, the food and yard waste present in a landfill has over time become intermingled 

with other materials to an extraordinary extent. This occurs in the process of waste collection, 

shipment, and disposal, and subsequently through waste decay, leaching and movement within 

the landfill. Additionally, we note that the process of biogas formation in a landfill provides 

some element of separation, in that it is formed only from the biogenic components of landfill 

material, including but not strictly limited to food and yard waste. Thus, plastics, metal and 

glass are effectively “separated” out through the process of biogas formation. As a result of the 

intermixing of wastes, the fact that biogas is formed only from the biogenic portion of landfill 

material, and the fact that landfill material is as a practical matter inaccessible for further 

separation, EPA believes that no further practical separation is possible for landfill material and 
 

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biogas should be considered as produced from separated yard and food waste for purposes of 

EISA. Therefore, all biogas from landfills is eligible for RIN generation 

We have considered whether to require biogas producers to use ASTM Method D-6866 

to identify the biogenic versus non-biogenic fractions of the fuel. However, as noted above, 

biogas is not formed from non-biogenic compounds in landfills. (Kaplan, et. al., 2009)9

 Thus, 

no purpose would be solved in using the ASTM method in the biogas context. 

C. Expanded Registration Process for Producers and Importers 

 In order to implement and enforce the new restrictions on qualifying renewable fuel 

under RFS2, we are revising the registration process for renewable fuel producers and importers. 

Under the RFS1 program, all producers and importers of renewable fuel who produce or import 

more than 10,000 gallons of fuel annually must register with EPA’s fuels program prior to 

generating RINs. Renewable fuel producer and importer registration under the RFS1 program 

consists of filling out two forms: 3520-20A (Fuels Programs Company/Entity Registration), 

which requires basic contact information for the company and basic business activity information 

and 3520-20B (Gasoline Programs Facility Registration) or 3520-20B1 (Diesel Programs 

Facility Registration), which require basic contact information for each facility owned by the 

producer or importer. More detailed information on the renewable fuel production facility, such 

as production capacity and process, feedstocks, and products was not required for most 

 

9

 Kaplan, et. al. (2009). “Is it Better to Burn or Bury Waste for Clean Electricity Generation?” Environmental 

Science & Technology 2009 43 (6), 1711-1717 (Found in Table S1 of supplemental material to the article, at 

http://pubs.acs.org/doi/suppl/10.1021/es802395e/suppl_file/es802395e_si_001.pdf ) 
 

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producers or importers to generate RINs under RFS1 (producers of cellulosic biomass ethanol 

and waste-derived ethanol are the exception to this). 

Additionally, EPA recommends companies register their renewable fuels or fuel additives 

under title 40 CFR part 79 as a motor vehicle fuel. In fact, renewable fuels intended for use in 

motor vehicles will be required to be registered under title 40 CFR part 79 prior to any 

introduction into commerce. Manufactures and subsequent parties of fuels and fuel additives not 

registered under part 79 will be liable for separate penalties under 40 CFR parts 79 and 80 in the 

event their unregistered product is introduced into commerce for use in a motor vehicle. Further 

if a registered fuel or fuel additive is used in manner that is not consistent with their product’s 

registration under part 79 the manufacturer and subsequent parties will be liable for penalties 

under parts 79 and 80. If EPA determines based on the company’s registration that they are not 

producing renewable fuel, the company will not be able to generate RINs and the RINs generated 

for fuel produced from nonrenewable sources will be invalidated. 

 Due to the revised definitions of renewable fuel under EISA, we proposed to expand the 

registration process for renewable fuel producers and importers in order to implement the new 

program effectively. We received a number of comments that opposed the expanded registration 

as commenters deemed it overly burdensome, costly and unnecessary. However, EPA is 

finalizing the proposed expanded registration requirements for the following reasons. The 

information to be collected through the expanded registration process is essential to generating 

and assigning a certain category of RIN to a volume of fuel. Additionally, the information 

collected is essential to determining whether the feedstock used to produce the fuel meets the 
 

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definition of renewable biomass, whether the lifecycle greenhouse gas emissions of the fuel 

meets a certain GHG reduction threshold and, in some cases, whether the renewable fuel 

production facility is considered to be grandfathered into the program. Therefore, we are 

requiring producers, including foreign producers, and importers that generate RINs to provide us 

with information on their feedstocks, facilities, and products, in order to implement and enforce 

the program and have confidence that producers and importers are properly categorizing their 

fuel and generating RINs. The registration procedures will be integrated with the new EPA 

Moderated Transaction System, discussed in detail in Section III.A of this preamble. 

 1. Domestic Renewable Fuel Producers

 Information on products, feedstocks, and facilities contained in a producer's 

registration will be used to verify the validity of RINs generated and their proper categorization 

as either cellulosic biofuel, biomass-based diesel, advanced biofuel, or other renewable fuel. In 

addition, producers of renewable fuel from facilities that qualify for the exemption from the 20% 

GHG reduction threshold (as discussed in Section II.B.3) must provide information that 

demonstrates when the facility commenced construction, and that establishes the baseline 

volume of the fuel. For those facilities that would qualify as grandfathered but are not in 

operation we are allowing until May 1, 2013 to submit and receive approval for a complete 

facility registration. This provision does not require actual fuel production, but simply the filing 

of registration materials that assert a claim for exempt status. It will benefit both fuel producers, 

who will likely be able to more readily collect the required information if it is done promptly, 

and EPA enforcement personnel seeking to verify the information. However, given the 
 

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potentially significant implications of this requirement for facilities that may qualify for the 

exemption but miss the registration deadline, the rule also provides that EPA may waive the 

requirement if it determines that the submission is verifiable to the same extent as a timelysubmitted registration. 

 With respect to products, we are requiring that producers provide information on the 

types of renewable fuel and co-products that a facility is capable of producing. With respect to 

feedstocks, we are requiring producers to provide to EPA a list of all the different feedstocks that 

a renewable fuel producer’s facility is likely to use to convert into renewable fuel. With respect 

to the producer’s facilities, two types of information must be reported to the Agency. First, 

producers must describe each facility’s fuel production processes (e.g., wet mill, dry mill, 

thermochemical, etc.), and thermal/process energy source(s). Second, in order to determine what 

production volumes would be grandfathered and thus deemed to be in compliance with the 20% 

GHG threshold, we are requiring evidence and certification of the facility’s qualification under 

the definition of “commence construction” as well as information necessary to establish its 

renewable fuel baseline volume per the requirement outlined in Section II.B.3 of this preamble. 

 EPA proposed to require that renewable fuel producers have a third-party engineering 

review of their facilities prior to generating RINs under RFS2, and every 3 years thereafter. EPA 

received comments that the on-site engineering review was overly burdensome, unnecessary and 

costly. A number of commenters noted that the time allotted for conducting the reviews, 

between the rule’s publication and prior to RIN generation, is not adequate for producers to hire 
 

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an engineer and conduct the review for all of their facilities. Several commenters requested that 

on-site licensed engineers be allowed to conduct any necessary facility reviews. 

EPA is finalizing the proposed requirement for an on-site engineering review of facilities 

producing renewable fuel due to the variability of production facilities, the increase in the 

number of categories of renewable fuels, and the importance of ensuring that that RINs are 

generated in the correct category. Without these engineering reviews, we do not believe it would 

be possible to implement the RFS2 program in a manner that ensured the requirements of EISA 

were being fulfilled. Additionally, the engineering review provides a check against fraudulent 

RIN generation. In order to establish the proper basis for RIN generation, we are requiring that 

every renewable fuel producer have the on-site engineering review of their facility performed in 

conjunction with his or her initial registration for the new RFS program. The engineering 

reviews must be conducted by independent third parties who can maintain impartiality and 

objectivity in evaluating the facilities and their processes. Additionally, the on-site engineering 

review must be conducted every three years thereafter to verify that the fuel pathways 

established in the initial registration are still applicable. These requirements apply unless the 

renewable fuel producer updates its facility registration information to qualify for a new RIN 

category (i.e., D code), in which case the review needs to be performed within 60 days of the 

registration update. Finally, producers are required to submit a copy of their independent 

engineering review to EPA, for verification and enforcement purposes. 

 2. Foreign Renewable Fuel Producers
 

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 Under RFS1, foreign renewable fuel producers of cellulosic biomass ethanol and wastederived ethanol may apply to EPA to generate RINs for their own fuel. For RFS2, we proposed 

that foreign producers of renewable fuel meet the same requirements as domestic producers, 

including registering information about their feedstocks, facilities, and products, as well as 

submitting an on-site independent engineering review of their facilities at the time of registration 

for the program and every three years thereafter. These requirements apply to all foreign 

renewable fuel producers who plan to export their products to the U.S. as part of the RFS2 

program, whether the foreign producer generates RINs for their fuel or an importer does. 

 Foreign producers, like domestic producers, must also undergo an independent 

engineering review of their facilities, conducted by an independent third party who is a licensed 

professional engineer (P.E.), or foreign equivalent who works in the chemical engineering field. 

The independent third party must provide to EPA documentation of his or her qualifications as 

part of the engineering review, including proof of appropriate P.E. license or foreign equivalent. 

The third-party engineering review must be conducted by both foreign producers who plan to 

generate RINs and those that don’t generate RINs but anticipate their fuel will be exported to the 

United States by an importer who will generate the RINs. 

 3. Renewable Fuel Importers

 We are requiring importers who generate RINs for imported fuel that they receive 

without RINs may only do so under certain circumstances. If an importer receives fuel without 

RINs, the importer may only generate RINs for that fuel if they can verify the fuel pathway and 
 

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that feedstocks use meet the definition of renewable biomass. An importer must rely on his 

supplier, a foreign renewable fuel producer, to provide documentation to support any claims for 

their decision to generate RINs. An importer may have an agreement with a foreign renewable 

fuel producer for the importer to generate RINs if the foreign producer has not done so already. 

However, the foreign renewable fuel producer must be registered with EPA and must have had a 

third-party engineering review conducted, as noted above, in order for EPA to be able to verify 

that the renewable biomass and GHG reduction requirements of EISA are being fulfilled. 

Section II.D.2.b describes the RIN generating restrictions and requirements for importers under 

RFS2. 

 4. Process and Timing

 We are making forms for expanded registration for renewable fuel producers and 

importers, as well as forms for registration of other regulated parties, available electronically 

with the publication of this final rule. Paper registration forms will only be accepted in 

exceptional cases. Registration forms must be submitted and accepted by the EPA by July 1, 

2010, or 60 days prior to a producer producing or importer importing any renewable fuel, 

whichever dates comes later. If a producer changes its fuel pathway (feedstock, production 

process, or fuel type) to not listed in his registration information on file with EPA but the change 

will not incur a change of RIN category for the fuel (i.e., a change in the appropriate D code), the 

producer must update his registration information within seven (7) days of the change. However, 

if the fuel producer changes its fuel pathway in a manner that would result in a change in its RIN 

category (and thus a new D code), such an update would need to be submitted at least 60 days 
 

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prior to the change, followed by submittal of a complete on-site independent engineering review 

of the producer's facility also within 60 days of the change. If EPA finds that these deadlines and 

requirements have not been met, or that a facility’s registered profile, dictated by the various 

parameters for product, process and feedstock, does not reflect actual products produced, 

processes employed, or feedstocks used, then EPA reserves the right to void, ab initio, any 

affected RINs generated and may impose significant penalties. For example a newly registered 

(i.e. not grandfathered) ethanol production facility claims in their registration that they qualify to 

generate RINs based upon the use of two advanced engineering practices 1) corn oil fractionation 

and 2) production of wet DGS co-product that is, at a minimum, 35% of its total DGS produced 

annually. However, during an audit of the producer’s records, it is found that of all their DGS 

produced, less than 15% was wet. In this example, the producer has committed a violation that 

results in the disqualification of their eligibility to generate RINs; that is, they no longer have an 

eligible pathway that demonstrates qualification with the 20% GHG threshold requirement for 

corn ethanol producers. As such any and all RINs produced may be deemed invalid and the 

producer may be subject to Clean Air Act penalties. 

 The required independent engineering review as discussed above for domestic and 

foreign renewable fuel producers is an integral part of the registration process. The agency 

recognizes, through comments received, that there are significant concerns involving timing 

necessary and ability to produce a completed engineering review to satisfy registration 

requirements. Since the publication of the RFS2 NPRM, we have delivered consistently a 

message stating that advanced planning and preparation was necessary from all parties, EPA and 

the regulated community inclusive, for successful implementation of this program. In an effort 
 

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to reduce demand on engineering resources, we are allowing grandfathered facilities an 

additional six months to submit their engineering review. This will direct the focus of 

engineering review resources on producers of advanced, cellulosic and biomass based diesel. 

EPA fully expects these producers of advanced renewable fuels to meet the engineering review 

requirement; however, if they are having difficulties producing engineer’s reports prior to April 

1, we ask that they contact us. 

D. Generation of RINs 

 Under RFS2, each RIN will continue to be generated by the producer or importer of the 

renewable fuel, as in the RFS1 program. In order to determine the number of RINs that must be 

generated and assigned to a batch of renewable fuel, the actual volume of the batch of renewable fuel 

must be multiplied by the appropriate Equivalence Value. The producer or importer must also 

determine the appropriate D code to assign to the RIN to identify which of the four standards the 

RIN can be used to meet. This section describes these two aspects of the generation of RINs. Other 

aspects of the generation of RINs, such as the definition of a batch, as well as the assignment of 

RINs to batches, will remain unchanged from the RFS1 requirements. We received several 

comments regarding the method for calculating temperature standardization of biodiesel and address 

this issue in Section III.G. 

 1. Equivalence Values
 

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 For RFS1, we interpreted CAA section 211(o) as allowing us to develop Equivalence 

Values representing the number of gallons that can be claimed for compliance purposes for every 

physical gallon of renewable fuel. We described how the use of Equivalence Values adjusted for 

renewable content and based on energy content in comparison to the energy content of ethanol 

was consistent with the sections of EPAct that provided extra credit for cellulosic and wastederived renewable fuels, and the direction that EPA establish “appropriate” credit for biodiesel 

and renewable fuel volumes in excess of the mandated volumes. We also noted that the use of 

Equivalence Values based on energy content was an appropriate measure of the extent to which a 

renewable fuel would replace or reduce the quantity of petroleum or other fossil fuel present in a 

fuel mixture. EPA stated that these provisions indicated that Congress did not intend to restrict 

EPA discretion in implementing the program to utilizing a straight volume measurement of 

gallons. See 72 FR 23918-23920, and 71 FR 55570-55571. The result was an Equivalence 

Value for ethanol of 1.0, for butanol of 1.3, for biodiesel (mono alkyl ester) of 1.5, and for nonester renewable diesel of 1.7. 

 In the NPRM we noted that EISA made a number of changes to CAA section 211(o) that 

impacted our consideration of Equivalence Values in the context of the RFS2 program. For 

instance, EISA eliminated the 2.5-to-1 credit for cellulosic biomass ethanol and waste-derived 

ethanol and replaced this provision with large mandated volumes of cellulosic biofuel and 

advanced biofuels. EISA also expanded the program to include four separate categories of 

renewable fuel (cellulosic biofuel, biomass-based diesel, advanced biofuel, and total renewable 

fuel) and included GHG thresholds in the definitions of each category. Each of these categories 

of renewable fuel has its own volume requirement, and thus there will exist a guaranteed market 
 

170

for each. As a result of these new requirements, we indicated that there may no longer be a need 

for additional incentives for certain fuels in the form of Equivalence Values greater than 1.0. 

 In the NPRM we co-proposed and took comment on two options for Equivalence Values: 

1. Equivalence Values would be based on the energy content and renewable content of 

each renewable fuel in comparison to denatured ethanol, consistent with the approach 

under RFS1, with the addition that biomass-based diesel standard would be based on 

energy content in comparison to biodiesel. 

2. All liquid renewable fuels would be counted strictly on the basis of their measured 

volumes, and the Equivalence Values for all renewable fuels would be 1.0 

(essentially, Equivalence Values would no longer apply). 

 In response to the NPRM, some stakeholders pointed to the aforementioned changes 

brought about by EISA as support for a straight volume approach to Equivalence Values, and 

argued that it had always been the intent of Congress that the statutory volume mandates be 

treated as straight volumes. Stakeholders taking this position were generally producers of corn 

ethanol. However, a broad group of other stakeholders including refiners, biodiesel producers, a 

broad group of advanced biofuel producers, fuel distributor and States indicated that the first 

option for an energy-based approach to Equivalence Values was both supported by the statute 

and necessary to provide for equitable treatment of advanced biofuels. They noted that EISA did 

not change certain of the statutory provisions EPA looked to for support under RFS1 in 
 

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establishing Equivalence Values based on relative volumetric energy content in comparison to 

ethanol. For instance, CAA 211(o) continues to direct EPA to determine an “appropriate” credit 

for biodiesel, and also directs EPA to determine the “appropriate” amount of credit for renewable 

fuel use in excess of the required volumes. Had Congress intended to change these provisions 

they could have easily done so. Moreover, some stakeholders argued that the existence of four 

standards is not a sufficient reason to eliminate the use of energy-based Equivalence Values for 

RFS2. The four categories are defined in such a way that a variety of different types of 

renewable fuel could qualify for each category, such that no single specific type of renewable 

fuel will have a guaranteed market. For example, the cellulosic biofuel requirement could be 

met with both cellulosic ethanol or cellulosic diesel. As a result, the existence of four standards 

under RFS2 does not obviate the value of standardizing for energy content, which provides a 

level playing field under RFS1 for various types of renewable fuels based on energy content. 

 Some stakeholders who supported an energy-based approach to Equivalence Values also 

argued that a straight volume approach would be likely to create a disincentive for the 

development of new renewable fuels that have a higher energy content than ethanol. For a given 

mass of feedstock, the volume of renewable fuel that can be produced is roughly inversely 

proportional to its energy content. For instance, one ton of biomass could be gasified and 

converted to syngas, which could then be catalytically reformed into either 80 gallons of ethanol 

(and another 14 gal of other alcohols) or 50 gallons of diesel fuel (and naphtha)10. If RINs were 

assigned on a straight volume basis, the producer could maximize the number of RINs he is able 

to generate and sell by producing ethanol instead of diesel. Thus, even if the market would 

 

10 Another example would be a fermentation process in which one ton of cellulose could be used to produce either 

70 gallons of ethanol or 55 gallons of butanol. 
 

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otherwise lean towards demanding greater volumes of diesel, the greater RIN value for 

producing ethanol may favor their production instead. However, if the energy-based 

Equivalence Values were maintained, the producer could assign 1.7 RINs to each gallon of diesel 

made from biomass in comparison to 1.0 RIN to each gallon of ethanol from biomass, and the 

total number of RINs generated would be essentially the same for the diesel as it would be for 

the ethanol. The use of energy-based Equivalence Values could thus provide a level playing 

field in terms of the RFS program's incentives to produce different types of renewable fuel from 

the available feedstocks. The market would then be free to choose the most appropriate 

renewable fuels without any bias imposed by the RFS regulations, and the costs imposed on 

different types of renewable fuel through the assignment of RINs would be more evenly aligned 

with the ability of those fuels to power vehicles and engines, and displace fossil fuel-based 

gasoline or diesel. Since the technologies for producing more energy-dense fuels such as 

cellulosic diesel are still in the early stages of development, they may benefit from not having to 

overcome the disincentive in the form of the same Equivalence Value based on straight volume. 

 Based on our interpretation of EISA as allowing the use of energy-based Equivalence 

Values, and because we believe it provides a level playing field for the development of different 

fuels that can displace the use of fossil fuels, and that this approach therefore furthers the energy 

independence goals of EISA, we are finalizing the energy-based approach to Equivalence Values 

in today's action. We also note that a large number of companies have already made investments 

based on the decisions made for RFS1, and using energy-based Equivalence Values will 

maintain consistency with RFS1 and ease the transition into RFS2. Insofar as renewable fuels 

with volumetric energy contents higher than ethanol are used, the actual volumes of renewable 
 

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fuel that are necessary to meet the EISA volume mandates will be smaller than those shown in 

Table I.A.1-1. The impact on the physical volume will depend on actual volumes of various 

advanced biofuels produced in the future. The main scenario modeled for this final rule includes 

a forecast for considerable volumes of relatively high energy diesel fuel made from renewable 

biomass, and still results in a physical volume mandate of 30.5 billion gallons. The energy-based 

approach results in the advanced biofuel standard being automatically met during the first few 

years of the program. For instance, the biomass-based diesel mandated volume for 2010 is 0.65 

billion gallons, which will be treated as 0.975 billion gallons (1.5 x 0.65) in the context of 

meeting the advanced biofuel standard. Since the mandated volume for advanced biofuel in 

2010 is 0.95 billion gallons, this requirement is automatically met by compliance with the 

biomass-based diesel standard. 

 Although we are finalizing an energy-based approach to Equivalence Values, we believe 

that Congress intended the biomass-based diesel volume mandate to be treated as diesel volumes 

rather than as ethanol-equivalent volumes. Since all RINs are generated based on energy 

equivalency to ethanol, to accomplish this, we have modified the formula for calculating the 

standard for biomass-based diesel to compensate such that one physical gallon of biomass-based 

diesel will count as one gallon for purposes of meeting the biomass-based diesel standard, but 

will be counted based on their Equivalence Value for purposes of meeting the advanced biofuel 

and total renewable fuel standards. Since it is likely that the statutory volume mandates were 

based on projections for biodiesel, we have chosen to use the Equivalence Value for biodiesel, 

1.5, in this calculation. See Section II.E.1.a for further discussion. Other diesel fuel made from 

renewable biomass can also qualify as biomass-based diesel (e.g., renewable diesel, cellulosic 
 

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diesel). But since the variation in energy content between them is relatively small, variation in 

the total physical volume of biomass-based diesel will likewise be small. 

 In the NPRM we also proposed that the energy content of denatured ethanol be changed 

from the 77,550 Btu/gal value used in the RFS1 program to 77,930 Btu/gal (lower heating 

value). The revised value was intended to provide a more accurate estimate of the energy 

content of pure ethanol, 76,400 Btu/gal, rather than the rounded value of 76,000 Btu/gal that was 

used under RFS1. Except for the Renewable Fuels Association who supported this change, most 

stakeholders did not comment on this proposal. However, based on new provisions in the Food, 

Conservation, and Energy Act of 2008, we have since determined that the denaturant content of 

ethanol should be assumed to be 2% rather than the 5% used in the RFS1 program. This 

additional change results in a denatured ethanol energy content of 77,000 Btu/gal and a 

renewable content of denatured ethanol of 97.2%11. The value of 77,000 Btu/gal will be used to 

convert biogas and renewable electricity into volumes of renewable fuel under RFS2. This 

change also affects the formula for calculating Equivalence Values assigned to renewable fuels. 

The new formula is shown below: 

EV = (R / 0.972) * (EC / 77,000) 

Where: 

EV = Equivalence Value for the renewable fuel, rounded to the nearest tenth. 

R = Renewable content of the renewable fuel. This is a measure of the portion of a renewable 

 

11 Value is lower than 98% because it is based on energy content of denaturant versus ethanol, not relative volume. 
 

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fuel that came from a renewable source, expressed as a percent, on an energy basis. 

EC = Energy content of the renewable fuel, in Btu per gallon (lower heating value). 

Under this new formula, Equivalence Values assigned to specific types of renewable fuel under 

RFS1 will continue unchanged under RFS2. However, non-ester renewable diesel will be 

required to have a lower energy content of at least 123,500 Btu/gal in order to qualify for an 

Equivalence Value of 1.7. A non-ester renewable diesel with a lower energy content would be 

required to apply for a different Equivalent Value according to the provisions in §80.1415. 

 2. Fuel Pathways and Assignment of D Codes

 As described in Section II.A, RINs under RFS2 would in general continue to have the 

same number of digits and code definitions as under RFS1. The one change will be that, while 

the D code will continue to identify the standard to which the RIN can be applied, it will be 

modified to have four values corresponding to the four different renewable fuel categories 

defined in EISA. These four D code values and the corresponding categories are shown in Table 

II.A-1. 

 In order to generate RINs for renewable fuel that meets the various eligibility 

requirements (see Section II.B), a producer or importer must know which D code to assign to 

those RINs. Following the approach we described in the NPRM, a producer or importer will 

determine the appropriate D code using a lookup table in the regulations. The lookup table lists 

various combinations of fuel type, production process, and feedstock, and the producer or 
 

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importer chooses the appropriate combination representing the fuel he is producing and for 

which he is generating RINs. Parties generating RINs are required to use the D code specified in 

the lookup table and are not permitted to use a D code representing a broader renewable fuel 

category. For example, a party whose fuel qualified as biomass-based diesel could not choose to 

categorize that fuel as advanced biofuel or general renewable fuel for purposes of RIN 

generation12. 

 

 This section describes our approach to the assignment of D codes to RINs for domestic 

producers, foreign producers, and importers of renewable fuel. Subsequent sections address the 

generation of RINs in special circumstances, such as when a production facility has multiple 

applicable combinations of feedstock, fuel type, and production process within a calendar year, 

production facilities that co-process renewable biomass and fossil fuels, and production facilities 

for which the lookup table does not provide an applicable D code. 

 a. Producers 

 For both domestic and foreign producers of renewable fuel, the lookup table identifies 

individual fuel "pathways" comprised of unique combinations of the type of renewable fuel 

being produced, the feedstock used to produce the renewable fuel, and a description of the 

production process. Each pathway is assigned to one of the D codes on the basis of the revised 

renewable fuel definitions provided in EISA and our assessment of the GHG lifecycle 

 

12 However, a biomass-based diesel RIN can be used to satisfy Renewable Volume Obligations (RVO) for biomassbased diesel, advanced biofuel, and total renewable fuel. See Section II.G.3 for further discussion of the use of 

RINs for compliance purposes. 
 

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performance for that pathway. A description of the lifecycle assessment of each fuel pathway 

and the process we used for determining the associated D code can be found in Section V. 

 Note that the generation of RINs also requires as a prerequisite that the feedstocks used to 

make the renewable fuel meet the definition of "renewable biomass" as described in Section 

II.B.4, including applicable land use restrictions. If a producer is not able to demonstrate that his 

feedstocks meet the definition of renewable biomass, RINs cannot be generated. However, as 

noted in Section II.B.4.b.1, feedstocks typically include incidental contaminants. These 

contaminants may have been intentionally added to promote cultivation (e.g., pesticides, 

herbicides, fertilizer) or transport (e.g., nylon baling rope). In addition, there may be some 

incidental contamination of a particular load of feedstocks with co-product during feedstock 

production, or with other agricultural materials during shipping. For example, there may be 

incidental corn kernels remaining on some corn cobs used to produce cellulosic biofuel, or some 

sorghum kernels left in a shipping container that are introduced into a load of corn kernels being 

shipped to a biofuel production facility. The final regulations clarify that in assigning D codes 

for renewable fuel, producers and importers should disregard the presence of incidental 

contaminants in their feedstocks if the incidental contaminants are related to customary feedstock 

production and transport, and are impractical to remove and occur in de minimus levels. 

 Through our assessment of the lifecycle GHG impacts of different pathways and the 

application of the EISA definitions for each of the four categories of renewable fuel, including 

the GHG thresholds, we have determined that all four categories will have pathways that could 

be used to meet the Act's volume requirements. For example, ethanol made from corn stover or 
 

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switchgrass in an enzymatic hydrolysis process will count as cellulosic biofuel. Biodiesel made 

from waste grease or soybean oil can count as biomass-based diesel. Ethanol made from 

sugarcane sugar will count as advanced biofuel. Finally, a variety of pathways will count as 

renewable fuel under the RFS2 program. The complete list of pathways that are valid under our 

final RFS2 program is discussed in Section V.C and are provided in the regulations at 

§80.1426(f). 

 Producers must choose the appropriate D code from the lookup table in the regulations 

based on the fuel pathway that describes their facility. The fuel pathway must be specified by 

the producer in the registration process as described in Section II.C. If there are changes to a 

producer's facility or feedstock such that their fuel would require a D code that was different 

from any D code(s) which their existing registration information already allowed, the producer is 

required to revise its registration information with EPA 30 days prior to changing the applicable 

D code it uses to generate RINs. Situations in which multiple fuel pathways could apply to a 

single facility are addressed in Section II.D.3 below. 

 For producers for whom none of the defined fuel pathways in the lookup table apply, a 

producer can still generate RINs if he meets the criteria for grandfathered or deemed compliant 

status as described in Section II.B.3 and his fuel meets the definition of renewable fuel as 

described in Section II.B.1. In this case he would use a D code of 6 for those RINs generated 

under the grandfathering or deemed compliant provisions. 
 

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A diesel fuel product produced from cellulosic feedstocks that meets the 60% GHG 

threshold can qualify as either cellulosic biofuel or biomass-based diesel. In the NPRM, we 

proposed that the producer of such "cellulosic diesel" be required to choose whether to 

categorize his product as either cellulosic biofuel or biomass-based diesel. However, we 

requested comment on an alternative approach in which an additional D code would be defined 

to represent cellulosic diesel allowing the cellulosic diesel RIN to be sold into either market. As 

described more fully in Section II.A above, we are finalizing this alternative approach in today's 

final rule. Producers or importers of a fuel that qualifies as both biomass-based diesel and 

cellulosic biofuel must use a D code of 7 in the RINs they generate, and will thus have the 

flexibility of marketing such RINs to parties seeking either cellulosic biofuel or biomass-based 

diesel RINs, depending on market demand. Obligated parties can apply RINs with a D code of 7 

to either their cellulosic biofuel or biomass-based diesel RVOs, but not both. 

In addition to the above comments, we received comments requesting that the use of 

biogas as process heat in the production of ethanol, should not be limited to use at the site of 

renewable fuel production. Specifically, commenters point out that the introduction of gas 

produced from landfills or animal wastes to fungible pipelines is the only practical manner for 

most renewable fuel facilities to acquire and use landfill gas, since very few are located adjacent 

to landfills, or have dedicated pipelines from landfill gas operations to their facilities.13 The 

commenters suggested that ethanol plants causing landfill gas to be introduced into a fungible 

gas pipeline be allowed to claim those volumes. The alternative would be to allow landfill gas 

that is only used onsite to be counted in establishing the pathway. 

 

13 This suggestion was also made by several companies with respect to the RFS1 definition of cellulosic biomass 

ethanol, which allowed corn-based ethanol to be deemed cellulosic if 90% of the fossil fuel used at the ethanol 

facility to make ethanol was displaced by fuel derived from animal or other waste materials, including landfill gas. 
 

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 We believe that the suggested approach has merit. We agree that it does not make any 

difference in terms of the beneficial environmental attributes associated with the use of landfill 

gas whether the displacement of fossil fuel occurs in a fungible natural gas pipeline, or in a 

specific facility that draws gas volume from that pipeline. In fact, a similar approach is widely 

used with respect to electricity generated by renewable biomass that is placed into a commercial 

electricity grid. A party buying the renewable power is credited with doing so in state 

renewable portfolio programs even though the power from these sources is placed in the fungible 

grid and the electrons produced by a renewable source may never actually be used by the party 

purchasing it. In essence these programs assume that the renewable power purchased and 

introduced into the grid is in fact used by the purchaser, even though all parties acknowledge that 

use of the actual renewable-derived electrons can never be verified once placed in the fungible 

grid. We believe that this approach will ultimately further the GHG reduction and energy 

security goals of RFS2. 

Producers may therefore take into account such displacement provided that they 

demonstrate that a verifiable contractual pathway exists and that such pathway ensures that 1) a 

specific volume of landfill gas was placed into a commercial pipeline that ultimately serves the 

transportation fueling facility and 2) that the drawn into this facility from that pipeline matches 

the volume of landfill gas placed into the pipeline system. Thus facilities using such a fuel 

pathway may then use an appropriate D code for generation of RINs.

This approach also applies to biogas and electricity made from renewable fuels and 

which are used for transportation. Producers of such fuel will be able to generate RINs, provided 
 

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that a contractual pathway exists that provides evidence that specific quantities of the renewable 

fuel (either biogas or electricity) was purchased and contracted to be delivered to a specific 

transportation fueling facility.14 We specify that the pipeline (or transmission line) system must 

ultimately serve the subject facility. For electricity that is produced by the co-firing of fossil 

fuels with renewable biomass derived fuels, we are requiring that the resulting electricity is prorated to represent only that amount of electricity generated by the qualifying biogas, for the 

purpose of computing RINs. 

We are also providing for those situations in which biogas or renewable electricity is 

provided directly to the transportation facility, rather than using a commercial distribution 

system such as pipelines or transmission lines. For both cases—dedicated use and commercial 

distribution—producers must provide contractual evidence of the production and sale of such 

fuel, and there are also reporting and recordkeeping requirements to be followed as well. 

Presently, there is no D code for electricity that is produced from renewable biomass. 

The petition process for assigning such codes in today’s rule can be used for such purpose. 

 b. Importers 

 For imported renewable fuel under RFS2, we are anticipating the importer to be the 

primary party responsible for generating RINs. However, the foreign producer of renewable fuel 

can instead elect to generate RINs themselves under certain conditions as described more fully in 

Section II.D.2.c below. This approach is consistent with the approach under RFS1. 

 

14 Note that biogas used for transportation fuel includes propane made from renewable biomass. 
 

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 Under RFS1, importers who import more than 10,000 gallons in a calendar year were 

required to generate RINs for all imported renewable fuel based on its type, except for cases in 

which the foreign producer generated RINs for cellulosic biomass ethanol or waste-derived 

ethanol. Due to the new definitions of renewable fuel and renewable biomass in EISA, importers 

can no longer generate RINs under RFS2 on the basis of fuel type alone. Instead, they must be 

able to demonstrate that the renewable biomass definition has been met for the renewable fuel 

they intend to import and for which they will generate RINs. They must also have sufficient 

information about the feedstock and process used to make the renewable fuel to allow them to 

identify the appropriate D code from the lookup table for the RINs they generate. Therefore, in 

order to generate RINs, the importer will be required to obtain this information from a foreign 

producer. RINs can only be generated if a demonstration is made that the feedstocks used to 

produce the renewable fuel meet the definition of renewable biomass. 

 In summary, under today's final rule, importers can import any renewable fuel, but can 

only generate RINs to represent the imported renewable fuel under the two conditions described 

below. If these conditions do not apply, the importer can import biofuel but cannot generate 

RINs to represent that biofuel. 

1. The imported renewable fuel is not accompanied by RINs generated by the 

registered foreign producer 

2. The importer obtains from the foreign producer: 
 

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- Documentation demonstrating that the renewable biomass definition has 

been met for the volume of renewable fuel being imported. 

- Documentation about the feedstock and production process used to 

produce the renewable fuel to allow the importer to determine the 

appropriate D-code designation in the RINs generated 

We are also finalizing additional requirements for foreign producers who either generate RINs or 

provide documentation to an importer sufficient to allow the importer to generate RINs. As 

described more fully in the next section, these additional requirements include restrictions on 

mixing of biofuels in the distribution system as it travels from the foreign producer to the 

importer. 

Finally, EPA is assessing whether additional requirements on foreign-generated fuel may 

be necessary for situations in which importers are generating RINs for the fuel. Additional 

requirements may be necessary to ensure that the importers have sufficient information to 

properly generate the RINs and that EPA has sufficient information to determine whether those 

RINs have been legitimately generated. EPA will pursue an amendment to the final RFS2 

regulations if we find that additional requirements are appropriate and necessary. 

 c. Additional Provisions for Foreign Producers 
 

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 In general, we are requiring foreign producers of renewable fuel to meet the same 

requirements as domestic producers with respect to registration, recordkeeping and reporting, 

attest engagements, and the transfer of RINs they generate with the batches of renewable fuel 

that those RINs represent. However, we are also placing additional requirements on foreign 

producers to ensure that RINs entering the U.S. are valid and that the regulations can be enforced 

at foreign facilities. These additional requirements are designed to accommodate the more 

limited access that EPA enforcement personnel have to foreign entities that are regulated parties 

under RFS2, and also the fact that foreign-produced biofuel intended for export to the U.S. is 

often mixed with biofuel that will not be exported to the U.S. 

 Under RFS1, foreign producers had the option of generating RINs for the renewable fuel 

that they export to the U.S. if they wanted to designate their fuel as cellulosic biomass ethanol or 

waste-derived ethanol, and thereby take advantage of the additional 1.5 credit value afforded by 

the 2.5 Equivalence Value for such products. In order to ensure that EPA had the ability to 

enforce the regulations relating to the generation of RINs from such foreign ethanol producers, 

the RFS1 regulations specified additional requirements for them, including posting a bond, 

admitting EPA enforcement personnel, and submitting to third-party engineering reviews of their 

production process. For RFS2, we are maintaining these additional requirements for foreign 

producers because EPA enforcement personnel have the same limitations under RFS2 with 

regard to access to foreign entities that are regulated parties as they did under RFS1. 

 EISA also creates other unique challenges in the implementation and enforcement of the 

renewable fuel standards for foreign-produced renewable fuel imported into the U.S. Unlike our 
 

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other fuels programs, EPA cannot determine whether a particular shipment of renewable fuel is 

eligible to generate RINs under the new program by testing the fuel itself. Instead, information 

regarding the feedstock that was used to produce renewable fuel and the process by which it was 

produced is vital to determining the proper renewable fuel category and RIN type for the 

imported fuel under the RFS2 program. Thus, whether foreign producers or importers generate 

RINs, this information must be collected and maintained by the RIN generator. 

 If a foreign producer generates RINs for renewable fuel that it produces and exports to 

the U.S., we are requiring that ethanol must be dewatered and denatured by the foreign producer 

prior to leaving the production facility and prior to the generation of RINs. This is consistent 

with our definition of renewable fuel in which ethanol that is valid under RFS2 must be 

denatured. Moreover, the foreign producer is required to strictly segregate a batch of renewable 

fuel and its associated RINs from all other volumes of renewable fuel as it travels from the 

foreign producer to the importer. The strict segregation ensures that RINs entering the U.S. 

appropriately represent the renewable fuel imported into the U.S. both in terms of renewable fuel 

type and volume. 

 Several commenters requested that in general the importer be the RIN generator for 

imported renewable fuel. Since most imported ethanol is currently made in Brazil and is not 

denatured by the foreign producer, any RINs generated must be generated by the importer. 

However, to accomplish this, the importer must obtain the appropriate information from a 

foreign producer regarding compliance with the renewable biomass definition and a description 

of the associated pathway for the renewable fuel. Under these circumstances, the foreign 
 

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producer must ensure that the information is transferred along with the renewable fuel through 

the distribution system until it reaches the importer. The foreign producer's volume of renewable 

fuel need not be strictly segregated from other volumes in this case, so long as a volume of 

chemically indistinguishable renewable fuel is tracked through the distribution system from the 

foreign producer to the importer, and the information needed by the importer to generate RINs 

follows this same path through the distribution system. Strict segregation of the volume is not 

necessary in this case, and the importer will determine appropriate number of RINs for the 

specific volume and type of renewable fuel that he imports. 

 Finally, if a foreign producer chooses not to participate in the RFS2 program and thus 

neither generates RINs nor provides information to the importer so that the importer can generate 

RINs, the foreign producer can still export biofuel to the U.S. However, under these 

circumstances the biofuel would not be renewable fuel under RFS2, no RINs could be generated 

by any party, and thus the foreign producer would not be subject to any of the registration, 

recordkeeping, reporting, or attest engagement requirements. 

 3. Facilities With Multiple Applicable Pathways

 If a given facility's operations can be fully represented by a single pathway, then a single 

D code taken from the lookup table will be applicable to all RINs generated for fuel produced at 

that facility. However, we recognize that this will not always be the case. Some facilities use 

multiple feedstocks at the same time, or switch between different feedstocks over the course of a 

year. A facility may be modified to produce the same fuel but with a different process, or may 
 

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be modified to produce a different type of fuel. Any of these situations could result in multiple 

pathways being applicable to a facility, and thus there may be more than one applicable D code 

for various RINs generated at the facility. 

 If more than one pathway applies to a facility within a compliance period, no special 

steps will need to be taken if the D code is the same for all the applicable pathways. In this case, 

all RINs generated at the facility will have the same D code regardless. Such a producer with 

multiple applicable pathways must still describe its feedstock(s), fuel type(s), and production 

process(es) in its initial registration and annual report to the Agency so that we can verify that 

the D code used was appropriate. 

 However, if more than one pathway applies to a facility within a compliance period and 

these pathways have been assigned different D codes, then the producer must determine which D 

codes to use when generating RINs. There are a number of different ways that this could occur. 

For instance, a producer could change feedstocks, production processes, or the type of fuel he 

produces in the middle of a compliance period. Or, he could use more than one feedstock or 

produce more than one fuel type simultaneously. The approach we are finalizing for designating 

D codes for RINs in these cases follows the approach described in the NPRM and is summarized 

in Table II.D.3-1. 
 

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Table II.D.3-1 

Approach to Assigning Multiple D Codes for Multiple Applicable Pathways 

Case Description Proposed approach 

1 The pathway applicable to a facility 

changes on a specific date, such that 

one single pathway applies before the 

date and another single pathway 

applies on and after the date. 

The applicable D code used in 

generating RINs must change on the 

date that the fuel produced changes 

pathways. 

2 One facility produces two or more 

different types of renewable fuel at the 

same time. 

The volumes of the different types of 

renewable fuel should be measured 

separately, with different D codes 

applied to the separate volumes. 

3 One facility uses two or more different 

feedstocks at the same time to produce 

a single type of renewable fuel. 

For any given batch of renewable fuel, 

the producer should assign the 

applicable D codes using a ratio 

(explained below) defined by the 

amount of each type of feedstock used. 

Commenters were generally supportive of this approach to multiple applicable pathways, 

and as a result we are finalizing it with few modifications from the proposal. Further discussion 

of the comments we received can be found in Section 3.5.4 of the S&A document. 
 

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 Following our proposal, cases listed in Table II.D.3-1 will be treated as hierarchical, with 

Case 2 only being used to address a facility's circumstances if Case 1 is not applicable, and Case 

3 only being used to address a facility's circumstances if Case 2 is not applicable. This approach 

covers all likely cases in which multiple applicable pathways may apply to a renewable fuel 

producer. Some examples of how Case 2 or 3 would apply are provided in the NPRM. 

 A facility where two or more different types of feedstock are used to produce a single 

fuel (such as Case 3 in Table II.D.3-1) will be required to generate two or more separate batchRINs15 for a single volume of renewable fuel, and these separate batch-RINs will have different 

D codes. The D codes will be chosen on the basis of the different pathways as defined in the 

lookup table in §80.1426(f). The number of gallon-RINs that will be included in each of the 

batch-RINs will depend on the relative amount of the different types of feedstocks used by the 

facility. In the NPRM, we proposed to use the relative energy content of the feedstocks to 

determine how many gallon-RINs should be assigned to each D code. Commenters generally 

did not address this aspect of our proposal, and we are finalizing it in today's action. Thus, the 

useable energy content of each feedstock must be used to divide the total number of gallon-RINs 

generated for a batch of renewable fuel into two or more groups, each corresponding to a 

different D code. Several separate batch-RINs can then be generated and assigned to the single 

volume of renewable fuel. The applicable calculations are given in the regulations at 

§80.1426(f)(3). 

 We proposed several elements of the calculation of the useable energy content of the 

feedstocks, including the following: 

 

15 Batch-RINs and gallon-RINs are defined in the regulations at 40 CFR 80.1401. 
 

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1. Only that fraction of a feedstock which is expected to be converted into renewable 

fuel by the facility can be counted in the calculation, taking into account facility 

conversion efficiency. 

2. The producer of the renewable fuel is required to designate this fraction once each 

year for the feedstocks processed by his facility during that year, and to include 

this information as part of his reporting requirements. 

3. Each producer is required to designate the energy content (in Btu/lb) once each 

year of the portion of each of his feedstocks which is converted into fuel. The 

producer may determine these values for his own feedstocks, or may use default 

values provided in the regulations at §80.1426(f)(7). 

4. Each producer is required to determine the total mass of each type of feedstock 

used by the facility on at least a daily basis. 

 Based on the paucity of comments we received on this issue, we are finalizing the 

provisions regarding the calculation of useable energy content of the feedstocks as it was 

proposed in the NPRM. As described in Section II.J, producers of renewable fuel will be 

required to submit information in their reports on the feedstocks they used, their production 

processes, and the type of fuel(s) they produced during the compliance period. This will apply to 
 

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both domestic producers and foreign producers who export any renewable fuel to the U.S. We 

will use this information to verify that the D codes used in generating RINs were appropriate. 

 4. Facilities that Co-Process Renewable Biomass and Fossil Fuels

 We expect situations to arise in which a producer uses a renewable feedstock 

simultaneously with a fossil fuel feedstock, producing a single fuel that is only partially 

renewable. For instance, biomass might be co-fired with coal in a coal-to-liquids (CTL) process 

that uses Fischer-Tropsch chemistry to make diesel fuel, biomass and waste plastics might be fed 

simultaneously into a catalytic or gasification process to make diesel fuel, or vegetable oils could 

be fed to a hydrotreater along with petroleum to produce a diesel fuel. In these cases, the diesel 

fuel will be only partially renewable. RINs can be generated in such cases, but must be done in 

such a way that the number of gallon-RINs corresponds only to the renewable portion of the fuel. 

 Under RFS1, we created a provision to address the co-processing of "renewable crudes" 

along with petroleum feedstocks to produce a gasoline or diesel fuel that is partially renewable. 

See 40 CFR 80.1126(d)(6). However, this provision would not apply in cases where either the 

renewable feedstock or the fossil fuel feedstock is a gas (e.g., biogas, natural gas) or a solid (e.g., 

biomass, coal). Therefore, we are eliminating the RFS1 provision applicable only to liquid 

feedstocks and replacing it with a more comprehensive approach that will apply to liquid, solid, 

or gaseous feedstocks and any type of conversion process. In this final approach, producers are 

required to use the relative energy content of their renewable and non-renewable feedstocks to 

determine the renewable fraction of the fuel that they produce. This fraction in turn is used to 
 

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determine the number of gallon-RINs that should be generated for each batch. Commenters said 

little about our proposed methodology to use the relative energy content of the feedstocks, and 

we are therefore finalizing it largely as proposed. 

 We also requested comment on allowing renewable fuel producers to use an accepted test 

method to directly measure the fraction of the fuel that is derived from biomass rather than a 

fossil fuel feedstock. For instance, ASTM D-6866 is a radiocarbon dating test method that can 

be used to determine the renewable content of transportation fuel. The use of such a test method 

can be used in lieu of the calculation of the renewable portion of the fuel based on the relative 

energy content of the renewable biomass and fossil feedstocks. Commenters generally supported 

the option of using a radiocarbon dating approach. As a result, we believe it would be 

appropriate and are finalizing a provision to allow parties that co-process renewable biomass and 

fossil fuels to choose between using the relative energy in the feedstocks or ASTM D-6866 to 

determine the number of gallon-RINs that should be generated. Regardless of the approach 

chosen, the producer will still need to separately verify that the renewable feedstocks meet the 

definition of renewable biomass. 

 If a producer chose to use the energy content of the feedstocks, the calculation would be 

similar to the treatment of renewable fuels with multiple D codes as described in Section II.D.3 

above. As shown in the regulations at §80.1426(f)(3), the producer would determine the 

renewable fuel volume that would be assigned RINs based on the amount of energy in the 

renewable feedstock relative to the amount of energy in the fossil feedstock. Only one batchRIN would be generated for a single volume of fuel produced from both a renewable feedstock 
 

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and a fossil feedstock, and this one batch-RIN must be based on the contribution that the 

renewable feedstock makes to the total volume of fuel. The calculation of the relative energy 

contents includes factors that take into account the conversion efficiency of the plant, and as a 

result potentially different reaction rates and byproduct formation for the various feedstocks will 

be accounted for. The relative energy content of the feedstocks is used to adjust the basic 

calculation of the number of gallon-RINs downward from that calculated on the basis of batch 

fuel volume and the applicable Equivalence Value. The D code that must be assigned to the 

RINs is drawn from the lookup table in the regulations as if the feedstock was entirely renewable 

biomass. Thus, for instance, a coal-to-liquids plant that co-processes some cellulosic biomass to 

make diesel fuel would be treated as a plant that produces only cellulosic diesel for purposes of 

identifying the appropriate D code for the fraction of biofuel that qualifies as renewable fuel 

under EISA. 

 If a producer chose to use D-6866, he would be required to either apply this test to every 

batch, or alternatively to take samples of every batch of fuel he produced over the course of one 

month and combine them into a single composite sample. The D-6866 test would then be 

applied to the composite sample, and the resulting renewable fraction would be applied to all 

batches of fuel produced in the next month to determine the appropriate number of RINs that 

must be generated. For the first month, the producer can estimate the non-fossil fraction, and 

then make a correction as needed in the second month. The producer would be required to 

recalculate the renewable fraction every subsequent month. See the regulations at 

§80.1426(f)(9). 
 

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 5. Facilities that Process Municipal Solid Waste

 As described in Section II.B.4.d, only the separated yard and food waste of municipal 

solid waste (MSW) are considered to be renewable biomass and may be used to produce 

renewable fuels under the RFS2 program. While renewable fuel producers may produce fuel 

from all organic components of MSW, they may generate RINs for only that portion of MSW 

that qualifies as renewable biomass. We are providing two methods for determining the 

appropriate number of RINs to generate for each batch of fuel, depending on whether the 

feedstock is pure food and yard waste, or separated municipal solid waste, as described in 

Section II.B.4.d. While not all biogenic material in the separated MSW is cellulosic, the vast 

majority of it is likely to be in most situations. Specifically, separated municipal solid waste may 

contain some non-biogenic materials such as plastics that were unable to be recycled due to 

market conditions. We are requiring producers of renewable fuel made from separated 

municipal solid waste to use the radiocarbon dating method D-6866 to calculate the biogenic 

fraction, presumed to be composed of cellulosic materials. Therefore, unless a renewable fuel 

producer is using MSW streams that are clearly not cellulosic, we anticipate that a D code of 

either 3 or 7 will be appropriate for such RINs. See the regulations at §80.1426(f). 

 6. RINless Biofuel

 Under the RFS1 program, all renewable fuel made from renewable feedstocks and used 

as motor vehicle fuel in the U.S. was assigned RINs. Therefore, aside from the very small 

amounts of biofuel used in nonroad applications or as heating oil, all renewable fuel produced or 
 

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imported counted towards the mandated volume goals of the RFS program. Although 

conventional diesel fuel was not subject to the standards under RFS1, all other motor vehicle fuel 

fell into two groups: fuel subject to the standards, and fuel for which RINs were generated and 

was used to meet those standards. 

 Under RFS2, our approach to compliance with the renewable biomass provision will 

allow the possibility for some biofuel to be produced without RINs. As described in Section 

II.B.4 above, we are modifying our approach to compliance with the renewable biomass 

provision so that renewable fuel producers using feedstocks from domestic planted crops and 

crop residue will be presumed to meet the renewable biomass provision. Under this "aggregate 

compliance" approach, these producers will be generating RINs for all their renewable fuel. 

However, producers who use foreign-grown crops or crop residue or other feedstocks such as 

planted trees or forestry residues will not be able to take advantage of this aggregate compliance 

approach. Instead, they will be required to demonstrate that their feedstocks meet the renewable 

biomass definition, including the associated land use restrictions, before they will be permitted to 

generate RINs. Absent such a demonstration, these producers can still produce biofuel but will 

not generate RINs. In addition, fuel producers whose fuel does not qualify as renewable fuel 

under this program because it does not meet the 20% GHG threshold (and is not grandfathered) 

can still produce biofuel but will not be allowed to generate RINs. Transportation fuel consumed 

in the U.S. will therefore be comprised of three groups: fuel subject to the standards (gasoline 

and diesel), fuel for which RINs are generated and will be used to meet those standards, and 

RINless biofuel. RINless biofuel will not be covered under any aspect of the RFS2 program, 
 

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despite the fact that in many cases it will meet the EISA definition of transportation fuel upon 

blending with gasoline or diesel. 

 In their comments in response to the NPRM, several refiners suggested that RINless 

biofuel should be treated as an obligated volume similar to gasoline and diesel, and thus be 

subject to the standards. Doing so would ensure that all transportation fuels are covered under 

the RFS2 program, consistent with RFS1. Such an approach would also provide renewable fuel 

producers with an incentive to demonstrate that their feedstocks meet the renewable biomass 

definition and thus generate RINs for all the biofuel that they produce. There could be less 

potential for market manipulation on the part of biofuel producers who might be considering 

producing RINless biofuel as a means for increasing demand for renewable fuel and RINs. 

 Nevertheless, we do not believe that it would be appropriate at this time to finalize a 

requirement that RINless biofuel be considered an obligated fuel subject to the standards. We 

did not propose such an approach in the NPRM, and as a result many renewable fuel producers 

who could be affected did not have an opportunity to consider and comment on it. Moreover, the 

volume of RINless biofuel is likely to be small compared to the volume of renewable fuel with 

RINs since RINs have value and producers currently have an incentive to generate them. 

However, if in the future RIN values should fall - for instance, if crude oil prices rise high 

enough and the market drives up demand for biofuels - the incentive to demonstrate compliance 

with the renewable biomass definition may decrease and there may be an increase in the volume 

of RINless biofuel. Under such circumstances it may be appropriate to reconsider whether 

RINless biofuel should be designated as an obligated volume subject to the standards. 
 

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 E. Applicable Standards 

The renewable fuel standards are expressed as a volume percentage, and are used by each 

refiner, blender or importer to determine their renewable fuel volume obligations. The 

applicable percentages are set so that if each regulated party meets the percentages, then the 

amount of renewable fuel, cellulosic biofuel, biomass-based diesel, and advanced biofuel used 

will meet the volumes specified in Table I.A.1-1.16 

 The formulas finalized today for use in deriving annual renewable fuel standards are 

based in part on an estimate of combined gasoline and diesel volumes, for both highway and 

nonroad uses, for the year in which the standards will apply. The standards will apply to 

refiners, blenders, and importers of these fuels. As described more fully in Section II.F.3, other 

producers of transportation fuel, such as producers of natural gas, propane, and electricity from 

fossil fuels, are not subject to the standards. Since the standards apply to refiners, blenders and 

importers of gasoline and diesel, these are also the transportation fuels that are used to determine 

the annual volume obligations of an individual refiner, blender, or importer. 

The projected volumes of gasoline and diesel used to calculate the standards will 

continue to be provided by EIA's Short-Term Energy Outlook (STEO). The standards applicable 

to a given calendar year will be published by November 30 of the previous year. Gasoline and 

 

16 Actual volumes can vary from the amounts required in the statute. For instance, lower volumes may result if the 

statutorily required volumes are adjusted downward according to the waiver provisions in CAA 211(o)(7)(D). Also, 

higher or lower volumes may result depending on the actual consumption of gasoline and diesel in comparison to 

the projected volumes used to set the standards. 
 

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diesel volumes will continue to be adjusted to account for the required renewable fuel volumes. 

In addition, gasoline and diesel volumes produced by small refineries and small refiners will be 

exempt through 2010, and that year’s standard is adjusted accordingly, as discussed below. 

 As discussed in the proposal, four separate standards are required under the RFS2 

program, corresponding to the four separate volume requirements shown in Table I.A.1-1. The 

specific formulas we use to calculate the renewable fuel standards are described below in Section 

II.E.1. 

 In order for an obligated party to demonstrate compliance, the percentage standards are 

converted into the volume of renewable fuel each obligated party is required to satisfy. This volume 

of renewable fuel is the volume for which the obligated party is responsible under the RFS program, 

and continues to be referred to as its Renewable Volume Obligation (RVO). Since there are four 

separate standards under the RFS2 program, there are likewise four separate RVOs applicable to 

each obligated party. Each standard applies to the sum of all gasoline and diesel produced or 

imported. Determination of RVOs is discussed in Section II.G.2. 

 1. Calculation of Standards

 a. How Are the Standards Calculated? 

 The four separate renewable fuel standards are based primarily on (1) the 49-state17

gasoline and diesel consumption volumes projected by EIA, and (2) the total volume of 

 

17 Hawaii opted-in to the original RFS program; that opt-in is carried forward to this program. 
 

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renewable fuels required by EISA for the coming year. Table I.A.2-1 shows the required overall 

volumes of four types of renewable fuel specified in EISA. Each renewable fuel standard is 

expressed as a volume percentage of combined gasoline and diesel sold or introduced into 

commerce in the U.S., and is used by each obligated party to determine its renewable volume 

obligation. 

 

 Today we are finalizing an approach to setting standards that is based in part on the sum 

of all gasoline and diesel produced or imported in the 48 contiguous states and Hawaii. An 

approach we are not adopting but which we discussed in the proposal would have split the 

standards between those that would be specific to gasoline and those that would be specific to 

diesel. Though this approach to setting standards would more readily align the RFS obligations 

with the relative amounts of gasoline and diesel produced or imported by each obligated party, 

we are not adopting this approach because it relies on projections of the relative amounts of 

gasoline-displacing and diesel-displacing renewable fuels. These projections would need to be 

updated every year, and as stated in the proposal, we believe that such an approach would 

unnecessarily complicate the program. 

 

 While the required amount of total renewable fuel for a given year is provided by EISA, 

the Act requires EPA to base the standards on an EIA estimate of the amount of gasoline and 

diesel that will be sold or introduced into commerce for that year. As discussed in the proposal, 

EIA’s STEO will continue to be the source for projected gasoline, and now diesel, consumption 

estimates. In order to achieve the volumes of renewable fuels specified in EISA, the gasoline 

and diesel volumes used to determine the standard must be the non-renewable portion of the 
 

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gasoline and diesel pools. Because the STEO volumes include renewable fuel use, we must 

subtract the total renewable fuel volume from the total gasoline and diesel volume to get total 

non-renewable gasoline and diesel volumes. The Act also requires EPA to use EIA estimates of 

renewable fuel volumes; the best estimation of the coming year’s renewable fuel consumption is 

found in Table 8 (U.S. Renewable Energy Supply and Consumption) of the STEO. Additional 

information on projected renewable fuel use will be included as it becomes available. 

As discussed in Section II.D.1, we are finalizing the energy content approach to 

Equivalence Values for the cellulosic biofuel, advanced biofuel, and total renewable fuel 

standards. However, the biomass-based diesel standard is based on the volume of biodiesel. In 

order to align both of these approaches simultaneously, biodiesel will continue to generate 1.5 

RINs per gallon as in RFS1, and the biomass-based diesel volume mandate from EISA is then 

adjusted upward by the same 1.5 factor. The net result is a biomass-based diesel gallon being 

worth 1.0 gallons toward the biomass-based diesel standard, but 1.5 gallons toward the other 

standards. 

CAA section 211(o) exempts small refineries18 from the RFS requirements until the 2011 

compliance period. In RFS1, we extended this exemption to the few remaining small refiners 

not already exempted.19 Small refineries and small refiners will continue to be exempt from the 

program until 2011 under the new RFS2 regulations. Thus we have excluded their gasoline and 

diesel volumes from the overall non-renewable gasoline and diesel volumes used to determine 

the applicable percentages until 2011. As discussed in the proposal, total small refinery and 

 

18 Under section 211(o) of the Clean Air Act, small refineries are those with 75,000 bbl/day or less average 

aggregate daily crude oil throughput. 

19 See Section III.E. 
 

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small refiner gasoline production volume is expected to be fairly constant compared to total U.S. 

transportation fuel production. Thus we estimated small refinery and small refiner gasoline and 

diesel volumes using a constant percentage of national consumption, as we did in RFS1. Using 

information from gasoline batch reports submitted to EPA for 2006, EIA data, and input from the 

California Air Resources Board regarding California small refiners, we estimate that small 

refinery volumes constitute 11.9% of the gasoline pool, and 15.2% of the diesel pool. 

 CAA section 211(o) requires that the small refinery adjustment also account for 

renewable fuels used during the prior year by small refineries that are exempt and do not 

participate in the RFS2 program. Accounting for this volume of renewable fuel would reduce 

the total volume of renewable fuel use required of others, and thus directionally would reduce the 

percentage standards. However, as we discussed in RFS1, the amount of renewable fuel that 

would qualify, i.e., that was used by exempt small refineries and small refiners but not used as 

part of the RFS program, is expected to be very small. In fact, these volumes would not 

significantly change the resulting percentage standards. Whatever renewable fuels small 

refineries and small refiners blend will be reflected as RINs available in the market; thus there is 

no need for a separate accounting of their renewable fuel use in the equations used to determine 

the standards. We proposed and are finalizing this value as zero. 

 The levels of the percentage standards would be reduced if Alaska or a U.S. territory 

chooses to participate in the RFS2 program, as gasoline and diesel produced in or imported into 

that state or territory would then be subject to the standard. Section 211(o) of the Clean Air Act 

requires that the renewable fuel be consumed in the contiguous 48 states, and any other state or 
 

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territory that opts-in to the program (Hawaii has subsequently opted in). However, because 

renewable fuel produced in Alaska or a U.S. territory is unlikely to be transported to the 

contiguous 48 states or to Hawaii, including their renewable fuel volumes in the calculation of 

the standard would not serve the purpose intended by section 211(o) of the Clean Air Act of 

ensuring that the statutorily required renewable fuel volumes are consumed in the 48 contiguous 

states and any state or territory that opts-in. Therefore, renewable fuels used in Alaska or U.S. 

territories are not included in the renewable fuel volumes that are subtracted from the total 

gasoline and diesel volume estimates. 

 In summary, the total projected non-renewable gasoline and diesel volumes from which 

the annual standards are calculated are based on EIA projections of gasoline and diesel 

consumption in the contiguous 48 states and Hawaii, adjusted by constant percentages of 11.9% 

and 15.2% in 2010 to account for small refinery/refiner gasoline and diesel volumes, 

respectively, and with built-in correction factors to be used when and if Alaska or a territory optin to the program. 

The following formulas are used to calculate the percentage standards: 

Gi − RGi + GSi − RGSi − GEi + Di − RDi + DSi − RDSi − DEi

= ×

( ) ( ) ( ) ( )

RFV Std 100% CB, i

CB, i

Gi − RGi + GSi − RGSi − GEi + Di − RDi + DSi − RDSi − DEi

× = ×

( ) ( ) ( ) ( )

RFV 1.5 Std 100% BBD, i 

BBD, i
 

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Gi − RGi + GSi − RGSi − GEi + Di − RDi + DSi − RDSi − DEi

= ×

( ) ( ) ( ) ( )

RFV Std 100% AB, i

AB, i

Gi − RGi + GSi − RGSi − GEi + Di − RDi + DSi − RDSi − DEi

= ×

( ) ( ) ( ) ( )

RFV Std 100% RF, i

RF, i

Where 

StdCB,i = The cellulosic biofuel standard for year i, in percent 

StdBBD,i = The biomass-based diesel standard (ethanol-equivalent basis) for year i, in percent 

StdAB,i = The advanced biofuel standard for year i, in percent 

StdRF,i = The renewable fuel standard for year i, in percent 

RFVCB,i = Annual volume of cellulosic biofuel required by section 211(o)(2)(B) of the Clean 

Air Act for year i, in gallons

RFVBBD,i = Annual volume of biomass-based diesel required by section 211(o)(2)(B) of the 

Clean Air Act for year i, in gallons 

RFVAB,i = Annual volume of advanced biofuel required by section 211(o)(2)(B) of the Clean 

Air Act for year i, in gallons 
 

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RFVRF,i = Annual volume of renewable fuel required by section 211(o)(2)(B) of the Clean 

Air Act for year i, in gallons 

Gi = Amount of gasoline projected to be used in the 48 contiguous states and Hawaii, in 

year i, in gallons* 

Di = Amount of diesel projected to be used in the 48 contiguous states and Hawaii, in 

year i, in gallons 

RGi = Amount of renewable fuel blended into gasoline that is projected to be consumed 

in the 48 contiguous states and Hawaii, in year i, in gallons 

RDi = Amount of renewable fuel blended into diesel that is projected to be consumed in 

the 48 contiguous states and Hawaii, in year i, in gallons 

GSi = Amount of gasoline projected to be used in Alaska or a U.S. territory in year i if 

the state or territory opts-in, in gallons* 

RGSi = Amount of renewable fuel blended into gasoline that is projected to be consumed 

in Alaska or a U.S. territory in year i if the state or territory opts-in, in gallons 
 

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DSi = Amount of diesel projected to be used in Alaska or a U.S. territory in year i if the 

state or territory opts-in, in gallons* 

RDSi = Amount of renewable fuel blended into diesel that is projected to be consumed in 

Alaska or a U.S. territory in year i if the state or territory opts-in, in gallons 

GEi = The amount of gasoline projected to be produced by exempt small refineries and 

small refiners in year i, in gallons, in any year they are exempt per §§80.1441 and 

80.1442, respectively. Equivalent to 0.119*(Gi-RGi). 

DEi = The amount of diesel projected to be produced by exempt small refineries and 

small refiners in year i, in gallons, in any year they are exempt per §§80.1441 and 

80.1442, respectively. Equivalent to 0.152*(Di-RDi). 

* Note that these terms for projected volumes of gasoline and diesel use include gasoline 

and diesel that has been blended with renewable fuel. 

 b. Standards for 2010 

 We are finalizing the standards for 2010 in today’s action. As explained in Section I.A.2, 

while the rulemaking is not effective until July 1, 2010, the 2010 standards we are setting are 

annual standards with compliance demonstrations are due by February 28, 2011. 

 
 

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 Under CAA section 211(o)(7)(D)(i), EPA is required to make a determination each year 

regarding whether the required volumes of cellulosic biofuel for the following year can be 

produced. For any calendar year for which the projected volume of cellulosic biofuel production 

is less than the minimum required volume, the projected volume becomes the basis for the 

cellulosic biofuel standard. In such a case, the statute also indicates that EPA may also lower the 

required volumes for advanced biofuel and total renewable fuel. 

As discussed in Section IV.B., we are utilizing the EIA projection of 5.04 million gallons 

(6.5 million ethanol equivalent gallons) of cellulosic biofuel as the basis for setting the 

percentage standard for cellulosic biofuel for 2010. This is lower than the 100 million gallon 

standard set by EISA that we proposed upholding, but reflects the current state of the industry, as 

discussed in section V.B. We expect continued growth in the industry in 2011 and beyond. 

Since the advanced biofuel standard is met by just the biomass-based diesel volume required in 

2010, and additional volumes of other advanced biofuels (e.g., sugarcane ethanol) are available 

as well, no change to the advanced biofuel standard is necessary for 2010. Moreover, given the 

nested nature of the volume mandates, since no change in the advanced biofuel standard is 

necessary, the total renewable fuel standard need not be changed either. 

Table II.E.1.b-1 

Standards for 2010 

Cellulosic biofuel 0.004% 

Biomass-based diesel 1.10% 

Advanced biofuel 0.61% 
 

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Renewable fuel 8.25% 

 2. Treatment of Biomass-Based Diesel in 2009 and 2010

 As described in Section I.A.2, the four separate 2010 standards issued in today's rule will 

apply to all gasoline and diesel produced in 2010. However, EISA included volume mandates 

for biomass-based diesel, advanced biofuel, and total renewable fuel that applied in 2009. Since 

the RFS2 program was not effective in 2009 and thus the volume mandates for biomass-based 

diesel and advanced biofuel were not implemented in 2009, our NPRM proposed a mechanism to 

ensure that the 2009 biomass-based diesel volume mandate would eventually be met. In today's 

final rule we are finalizing the proposed approach. 

 a. Shift in 2009 Biomass-Based Diesel Compliance Demonstration to 2010 

 Under the RFS1 regulations that applied in 2009, we set the applicable standard for total 

renewable fuel in November 200820 using the required volume of 11.1 billion gallons specified 

in the Clean Air Act (as amended by EISA), gasoline volume projections from EIA, and the 

formula provided in the regulations at §80.1105(d). The existing RFS1 regulations did not 

provide a mechanism for requiring the use of 0.5 billion gallons of biomass-based diesel or the 

0.6 billion gallons of advanced biofuel mandated by EISA for 2009. 

 

20 See 73 FR 70643 (November 21, 2008) 
 

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 In the NPRM we proposed that the compliance demonstration for the 2009 biomassbased diesel requirement of 0.5 bill gal be extended to 2010. This approach would combine the 

0.5 bill gal requirement for 2009 and the 0.65 bill gal requirement for 2010 into a single 

requirement of 1.15 bill gal for which compliance demonstrations would be made by February 

28, 2011. As described in the NPRM, we believe that the deficit carryover provision provides a 

conceptual mechanism for this approach, since it would have allowed obligated parties to defer 

compliance with any or all of the 2009 standards until 2010. We are finalizing this approach in 

today's action. We believe it will ensure that these two year's worth of biomass-based diesel will 

be used, while providing reasonable lead time for obligated parties. It avoids a transition that 

fails to have any requirements related to the 2009 biomass-based diesel volume, and instead 

requires the use of the 2009 volume but achieves this by extending the compliance period by one 

year. We believe this is a reasonable exercise of our authority under section 211(o)(2) to issue 

regulations that ensure that the volumes for 2009 are ultimately used, even though we were 

unable to issue final regulations prior to the 2009 compliance year. We announced our intentions 

to implement the 2009 and 2010 biomass-based diesel requirements in this manner in the 

November 2008 Federal Register notice cited previously. We reiterated these intentions in our 

NPRM. Thus, obligated parties will have had sufficient lead time to acquire a sufficient number 

of biomass-based diesel RINs by the end of 2010 to comply with the standard based on 1.15 bill 

gal. 

 Data available at the time of this writing suggests that approximately 450 million gallons 

of biodiesel was produced in 2009, thus requiring 700 million gallons to be produced in 2010 to 

satisfy the combined 2009 and 2010 volume mandates. Information from commenters and other 
 

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contacts in the biodiesel industry indicate that feedstocks and production facilities will be 

available in 2010 to produce this volume. 

 Refiners generally commented that the proposed approach to 2009 and 2010 biomassbased diesel volumes was not appropriate and should not be implemented. They also 

recommended that the RFS2 program should be made effective on January 1, 2011 with no 

carryover of any previous-year obligations for biomass-based diesel or any other volume 

mandate. In contrast, the National Biodiesel Board and several individual biodiesel producers 

supported the proposed approach, but believed it was insufficient to compel obligated parties to 

purchase biodiesel in 2009, something they considered critical to the survival of the biodiesel 

industry. Many of these commenters requested that we conduct an interim rulemaking that 

would apply to 2009 to implement the EISA mandated volume of 0.5 billion gallons of biomassbased diesel. If the RFS2 program could not be implemented until 2011, they likewise requested 

that interim measures be taken for 2010 to ensure that the full 1.15 bill gal requirement would be 

implemented. However, putting in place this new volume requirement without also putting in 

place EISA's new definition for biomass-based diesel, renewable fuel, and renewable biomass 

would have raised significant legal and policy issues that would necessarily have required a new 

proposal with its own public notice and comment process. Because of the significant time 

required for notice and comment rulemaking, the need to provide industry with adequate lead 

time for new requirements, and the fact that we were already well into calendar year 2009 at the 

time the request for an interim rule was received, it was unlikely that any interim rule could have 

impacted biodiesel demand in 2009. Moreover, Agency resources applied to the interim 

rulemaking would have been unavailable for development of the final RFS2 rulemaking. 
 

210

Developing an interim rule could have undermined EPA's ability to complete the full RFS2 

program regulations in time for 2010 implementation. As a result, we did not pursue an interim 

rulemaking. 

 With regard to advanced biofuel, it is not necessary to implement a separate requirement 

for the 0.6 billion gallon mandate for 2009. Due to the nested nature of the volume requirements 

and the fact that Equivalence Values will be based on the energy content relative to ethanol, the 

0.5 billion gallon requirement for biomass-based diesel will count as 0.75 billion gallons of 

advanced biofuel, exceeding the requirement of 0.6 billion gallons. Thus compliance with the 

biomass-based diesel requirement in 2009 automatically results in compliance with the advanced 

biofuel standard. 

 All 2009 biodiesel and renewable diesel RINs, identifiable through an RR code of 15 or 

17 respectively under the RFS1 regulations, will be valid for showing compliance with the 

adjusted 2010 biomass-based diesel standard of 1.15 billion gallons. This use of previous year 

RINs for current year compliance is consistent with our approach to any other standard for any 

other year and consistent with the flexibility available to any obligated party that carries a deficit 

from one year to the next. Moreover, it allows an obligated party to acquire sufficient biodiesel 

and renewable diesel RINs during 2009 to comply with the 0.5 billion gallons requirement, even 

though their compliance demonstration would not occur until the 2010 compliance period. 

 We did not reduce the 2009 volume requirement for total renewable fuel by 0.5 billion 

gallons to account for the fact that we intended to move the compliance demonstration for this 
 

211

volume has been moved to the 2010 compliance period. Instead, we are allowing 2009 biodiesel 

and renewable diesel RINs to be used for compliance purposes for both the 2009 total renewable 

fuel standard as well as the 2010 adjusted biomass-based diesel standard (but not for the 2010 

advanced biofuel or total renewable fuel standards). To accomplish this, we proposed in the 

NPRM that an obligated party would add up the 2009 biodiesel and renewable diesel RINs that 

he used for 2009 compliance with the RFS1 standard for total renewable fuel, and reduce his 

2010 biomass-based diesel obligation by this amount. Thus, 2009 biodiesel and renewable diesel 

RINs are essentially used twice. Any remaining 2010 biomass-based diesel obligation would 

need to be covered either with 2009 biodiesel and renewable diesel RINs that were not used for 

compliance in 2009 or with 2010 biomass-based diesel RINs. We are finalizing this approach in 

today's notice. 

b. Treatment of Deficit Carryovers, RIN Rollover, and RIN Valid Life For Adjusted 

2010 Biomass-Based Diesel Requirement 

 Our transition approach for biomass-based diesel is conceptually similar, but not 

identical, to the statutory deficit carryover provision. In a typical deficit carryover situation, an 

obligated party can carry forward any amount of a current-year deficit to the following year. In 

the absence of any modifications to the deficit carryover provisions for our biomass-based diesel 

transition provisions, then, an obligated party that did not fully comply with the 2010 biomassbased diesel requirement of 1.15 billion gallons could carry a deficit of any amount into 2011. 

As described in the NPRM, we believe that the deficit carryover provisions should be modified 

in the context of the transition biomass-based diesel approach to more closely represent what 
 

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would have occurred if we had been able to implement the 0.5 bill gal requirement in 2009. 

Specifically, we are prohibiting obligated parties from carrying over a biomass-based diesel 

deficit into 2011 larger than that based on the 0.65 bill gal volume requirement for 2010. This is 

the amount that would have been permitted had we been able to implement the biomass-based 

diesel requirements in 2009. In practice, this means that deficit carryovers from 2010 into 2011 

for biomass-based diesel cannot not exceed 57% (0.65/1.15) of an obligated party's 2010 RVO. 

This approach also helps to ensure a minimum volume mandate for companies producing 

biomass-based diesel each year. 

 Similarly, in the absence of any modifications to the provisions regarding valid life of 

RINs, 2008 biodiesel and renewable diesel RINs could not be used for compliance in 2010 with 

the adjusted biomass-based diesel standard, despite the fact that the 2010 standard includes the 

2009 requirement for which 2008 RINs should be valid. The National Biodiesel Board opposed 

this approach on the basis that the use of 2008 RINs for 2010 compliance demonstrations 

violated the 2-year valid life limit for RINs. However, since the 2010 compliance demonstration 

will include the obligation that would have applied in 2009, and 2008 RINs would be valid for 

2009 compliance, we are allowing excess 2008 biodiesel and renewable diesel RINs that were 

not used for compliance purposes in 2008 to be used for compliance purposes in 2009 or 2010. 

 As described in Section III.D, we are requiring the 20% RIN rollover cap to apply in all 

years, and separately for all four standards. However, consistent with our approach to deficit 

carryovers, we believe that an additional constraint is warranted in the application of the rollover 

cap to the biomass-based diesel obligation in the 2010 compliance year to more closely represent 
 

213

what would have occurred if we had been able to implement the 0.5 bill gal requirement in 2009. 

Specifically, we are limiting the use of excess 2008 RINs to 20% of the statutory 2009 

requirement of 0.5 bill gal. This is equivalent to 0.1 bill gal (20% of 0.5 bill gal), or 8.7% of the 

combined 2009/2010 obligation of 1.15 bill gal (0.1/1.15). Thus, obligated parties will be 

allowed to use excess 2008 and 2009 biodiesel and renewable diesel RINs for compliance with 

the 2010 combined standard of 1.15 bill gal, so long as the sum of all previous-year RINs (2008 

plus 2009 RINs) does not exceed 20% of their 2010 obligation, and the 2008 RINs do not exceed 

8.7% of their 2010 obligation. 

 Under RFS1, RINs are generated when renewable fuel is produced, but if the fuel is 

ultimately used for purposes other than as motor vehicle fuel the RINs must generally be retired. 

Under EISA, however, RINs generated for renewable fuel that is ultimately used for nonroad 

purposes, heating oil, or jet fuel are valid for compliance purposes. To more closely align our 

transition approach for biomass-based diesel to what could have occurred if we had issued the 

RFS2 standards prior to 2009, we are allowing 2009 RINs that are retired because they are 

ultimately used for nonroad, heating oil or jet fuel purposes to be valid for compliance with the 

2010 standards. Such RINs can be reinstated by the retiring party in 2010. 

 3. Future Standards

 The statutorily-prescribed phase-in period ends in 2012 for biomass-based diesel and in 

2022 for cellulosic biofuel, advanced biofuel, and total renewable fuel. Beyond these years, 

EISA requires EPA to determine the applicable volumes based on a review of the 
 

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implementation of the program up to that time, and an analysis of a wide variety of factors such 

as the impact of the production of renewable fuels on the environment, energy security, 

infrastructure, costs, and other factors. For these future standards, EPA must promulgate rules 

establishing the applicable volumes no later than 14 months before the first year for which such 

applicable volumes would apply. For biomass-based diesel, this would mean that final rules 

would need to be issued by October 31, 2011 for application starting on January 1, 2013. In 

today's rulemaking, we are not suggesting any specific volume requirements for biomass-based 

diesel for 2013 and beyond that would be appropriate under the statutory criteria that we must 

consider. Likewise, we are not suggesting any specific volume requirements for the other three 

renewable fuel categories for 2023 and beyond. However, the statute requires that the biomassbased diesel volume in 2013 and beyond must be no less than 1.0 billion gallons, and that 

advanced biofuels in 2023 and beyond must represent at a minimum the same percentage of total 

renewable fuel as it does in 2022. These provisions will be implemented as part of an annual 

standard-setting process. 

F. Fuels that are Subject to the Standards 

 Under RFS1, producers and importers of gasoline are obligated parties subject to the 

standards - any party that produces or imports only diesel fuel is not subject to the standards. 

EISA changes this provision by expanding the RFS program in general to include all 

transportation fuel. As discussed above, however, section 211(o)(3) continues to require EPA to 

determine which refiners, blenders, and importers are treated as subject to the standard. As 

described further in Section II.G below, under this rule, the sum of all highway and nonroad 
 

215

gasoline and diesel fuel produced or imported within a calendar year will be the basis on which 

the RVOs are calculated. This section provides our final definition of gasoline and diesel for the 

purposes of the RFS2 program. 

 1. Gasoline

 As with the RFS1 rule, the volume of gasoline used in calculating the RVO under RFS2 

will continue to include all finished gasoline (reformulated gasoline (RFG) and conventional 

gasoline (CG)) produced or imported for use in the contiguous United States or Hawaii, as well 

as all unfinished gasoline that becomes finished gasoline upon the addition of oxygenate blended 

downstream from the refinery or importer. This includes both unfinished reformulated gasoline, 

called “reformulated gasoline blendstock for oxygenate blending,” or “RBOB,” and unfinished 

conventional gasoline designed for downstream oxygenate blending (e.g., sub-octane 

conventional gasoline), called “CBOB.” The volume of any other unfinished gasoline or 

blendstock, (such as butane or naphtha produced in a refinery) or exported gasoline, will not be 

included in the obligated volume, except where the blendstock is combined with other 

blendstock or gasoline to produce finished gasoline, RBOB, or CBOB. Where a blendstock is 

blended with other blendstock to produce finished gasoline, RBOB, or CBOB, the total volume 

of the gasoline blend will be included in the volume used to determine the blender’s renewable 

fuels obligation. Where a blendstock is added to finished gasoline, only the volume of the 

blendstock will be included, since the finished gasoline would have been included in the 

compliance determinations of the refiner or importer of the gasoline. For purposes of this 
 

216

preamble, the various gasoline products described above that we are including in a party's 

obligated volume are collectively called “gasoline.” 

 Also consistent with the RFS1 program, we are continuing the exclusion of any volume 

of renewable fuel contained in gasoline from the volume of gasoline used to determine the 

renewable fuels obligations. This exclusion applies to any renewable fuels that are blended into 

gasoline at a refinery, contained in imported gasoline, or added at a downstream location. Thus, 

for example, any ethanol added to RBOB or CBOB at a refinery's rack or terminal downstream 

from the refinery or importer will be excluded from the volume of gasoline used by the refiner or 

importer to determine the obligation. This is consistent with how the standard itself is calculated 

– EPA determines the applicable percentage by comparing the overall projected volume of 

gasoline used to the overall renewable fuel volume that is specified in the statute, and EPA 

excludes ethanol and other renewable fuels that are blended into the gasoline in determining the 

overall projected volume of gasoline. When an obligated party determines their RVO by 

applying the applicable percentage to the amount of gasoline they produce or import, it is 

consistent to also exclude ethanol and other renewable fuel blends from the calculation of the 

volume of gasoline produced. 

As with the RFS1 rule, Gasoline Treated as Blendstock (GTAB) will continue to be 

treated as a blendstock under the RFS2 program, and thus will not count towards a party's 

renewable fuel obligation. Where the GTAB is blended with other blendstock (other than 

renewable fuel) to produce gasoline, the total volume of the gasoline blend, including the GTAB, 

will be included in the volume of gasoline used to determine the renewable fuel obligation. 
 

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Where GTAB is blended with renewable fuel to produce gasoline, only the GTAB volume will 

be included in the volume of gasoline used to determine the renewable fuel obligation. Where 

the GTAB is blended with finished gasoline, only the GTAB volume will be included in the 

volume of gasoline used to determine the renewable fuel obligation. 

 2. Diesel

EISA expanded the RFS program to include transportation fuels other than gasoline, thus 

both highway and nonroad diesel must be used in calculating a party’s RVO. Any party that 

produces or imports petroleum-based diesel fuel that is designated as motor vehicle, nonroad, 

locomotive, and marine diesel fuel (MVNRLM) (or any subcategory of MVNRLM) will be 

required to include the volume of that diesel fuel in the determination of its RVO under the RFS2 

rule. Diesel fuel includes any distillate fuel that meets the definition of MVNRLM diesel fuel as 

it has already been defined in the regulations at §80.2(qqq), including any subcategories such as 

MV (motor vehicle diesel fuel produced for use in highway diesel engines and vehicles), NRLM 

(diesel fuel produced for use in nonroad, locomotive, and marine diesel engines and 

equipment/vessels), NR (diesel fuel produced for use in nonroad engines and equipment), and 

LM (diesel fuel produced for use in locomotives and marine diesel engines and vessels)21. 

Transportation fuels meeting the definition of MVNRLM will be used to calculate the RVOs, 

and refiners, blenders, or importers of MVNRLM will be treated as obligated parties. As such, 

diesel fuel that is designated as heating oil, jet fuel, or any designation other than MVNRLM or a 

 

21 EPA’s diesel fuel regulations use the term “nonroad” to designate one large category of land based off-highway 

engines and vehicles, recognizing that locomotive and marine engines and vessels are also nonroad engines and 

vehicles under EPAct’s definition of nonroad. Except where noted, the discussion of nonroad in reference to 

transportation fuel includes the entire category covered by EPAct’s definition of nonroad. 
 

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subcategory of MVNRLM, will not be subject to the applicable percentage standard and will not 

be used to calculate the RVOs.22 We requested comment on the idea that any diesel fuel not 

meeting these requirements, such as distillate or residual fuel intended solely for use in oceangoing vessels, would not be used to calculate the RVOs. 

One commenter expressed support for including heating oil and jet fuel into the RIN 

program, but not to subject these fuels to the RVO mandate. The commenter stated that 

fluctuating weather conditions make it hard to predict with any reliability the volumes of heating 

oil that will be used in a given year. Another commenter stated that it supports the extension of 

the RFS program to transportation fuels, including diesel and nonroad fuels. 

With respect to fuels for use in ocean-going vessels, EISA specifies that “transportation 

fuels” do not include such fuels. We are interpreting that "fuels for use in ocean-going vessels" 

means residual or distillate fuels other than MVNRLM intended to be used to power large oceangoing vessels (e.g., those vessels that are powered by Category 3 (C3), and some Category 2 

(C2), marine engines and that operate internationally). Thus, fuel for use in ocean-going vessels, 

or that an obligated party can verify as having been used in an ocean-going vessel, will be 

excluded from the renewable fuel standards. Also, in the context of the recently finalized fuel 

standards for C3 marine vessels, this would mean that fuel meeting the 1,000 ppm fuel sulfur 

standard would not be considered obligated volume, while all MVNRLM diesel fuel would. 

 3. Other Transportation Fuels

 

22 See 40 CFR 80.598(a) for the kinds of fuel types used by refiners or importers in designating their diesel fuel. 
 

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 Transportation fuels other than gasoline or MVNRLM diesel fuel (natural gas, propane, 

and electricity) will not be used to calculate the RVOs of any obligated party. We believe this is 

a reasonable way to implement the obligations of 211(o)(3) because the volumes are small and 

the producers cannot readily differentiate the small portion used in the transportation sector from 

the large portion used in other sectors (in fact, the producer may have no knowledge of its 

ultimate use). We will reconsider this approach if and when these volumes grow. At the same 

time, it is clear that these fuels can be used as transportation fuel, and under certain 

circumstances, producers of such "other transportation fuels" may generate RINs as a producer 

or importer of a renewable fuel. See Section II.D.2.a for further discussion of other RINgenerating fuels. 

G. Renewable Volume Obligations (RVOs) 

 Under RFS1, each obligated party was required to determine its RVO based on the applicable 

percentage standard and its annual gasoline volume. The RVO represented the volume of renewable 

fuel that the obligated party was required to ensure was used in the U.S. in a given calendar year. 

Obligated parties were required to meet their RVO through the accumulation of RINs which 

represent the amount of renewable fuel used as motor vehicle fuel that was sold or introduced into 

commerce within the U.S. Each gallon-RIN counted as one gallon of renewable fuel for compliance 

purposes. 

 We are maintaining this approach to compliance under the RFS2 program. However, one 

primary difference between RFS1 and the new RFS2 program in terms of demonstrating compliance 
 

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is that each obligated party now has four RVOs instead of one (through 2012) or two (starting in 

2013) under the RFS1 program. Also, as discussed above, RVOs are now calculated based on 

production or importation of both gasoline and diesel fuels, rather than gasoline alone. 

 By acquiring RINs and applying them to their RVOs, obligated parties are deemed to have 

satisfied their obligation to cause the renewable fuel represented by the RINs to be consumed as 

transportation fuel in highway or nonroad vehicles or engines. Obligated parties are not required to 

physically blend the renewable fuel into gasoline or diesel fuel themselves. The accumulation of 

RINs will continue to be the means through which each obligated party shows compliance with its 

RVOs and thus with the renewable fuel standards. 

 If an obligated party acquires more RINs than it needs to meet its RVOs, then in general it 

can retain the excess RINs for use in complying with its RVOs in the following year (subject to the 

20% rollover cap discussed in Section III.D) or transfer the excess RINs to another party. If, 

alternatively, an obligated party has not acquired sufficient RINs to meet its RVOs, then under 

certain conditions it can carry a deficit into the next year. 

 This section describes our approach to the calculation of RVOs under RFS2 and the RINs 

that are valid for demonstrating compliance with those RVOs. This includes a description of the 

special treatment that must be applied to RFS1 RINs used for compliance purposes under RFS2, 

since RINs generated under RFS1 regulations are not exactly the same as those generated in 

under RFS2. 
 

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 1. Designation of Obligated Parties

 In the NPRM, we proposed to continue to designate obligated parties under the RFS2 

program as they were designated under RFS1, with the addition of diesel fuel producers and 

importers. Regarding gasoline producers and importers, we proposed that obligated parties who 

are subject to the standard would be those that produce or import finished gasoline (RFG and 

conventional) or unfinished gasoline that becomes finished gasoline upon the addition of an 

oxygenate blended downstream from the refinery or importer. Unfinished gasoline would 

include reformulated gasoline blendstock for oxygenate blending (RBOB), and conventional 

gasoline blendstock designed for downstream oxygenate blending (CBOB) which is generally 

sub-octane conventional gasoline. The volume of any other unfinished gasoline or blendstock, 

such as butane, would not be included in the volume used to determine the RVO, except where 

the blendstock was combined with other blendstock or finished gasoline to produce finished 

gasoline, RBOB, or CBOB. Thus, parties downstream of a refinery or importer would only be 

obligated parties to the degree that they use non-renewable blendstocks to make finished 

gasoline, RBOB, CBOB, or diesel fuel. 

 We also took comment on two alternative approaches to the designation of obligated 

parties: 

- Elimination of RBOB and CBOB from the list of fuels that are subject to the 

standard, such that a party's RVO would be based only on the non-renewable 

volume of finished gasoline or diesel that he produces or imports, thereby moving 
 

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a portion of the obligation to downstream blenders of renewable fuels into RBOB 

and CBOB. 

- Moving the obligations for all gasoline and diesel downstream of refineries and 

importers to parties who supply finished transportation fuels to retail outlets or to 

wholesale purchaser-consumer facilities. 

These alternative approaches have the potential to more evenly align a party's access to RINs 

with that party's obligations under the RFS2 program. As described more fully in the NPRM, we 

considered these alternatives because of market conditions that had changed since the RFS1 

program began. For instance, obligated parties who have excess RINs have been observed to 

retain rather than sell them to ensure they have a sufficient number for the next year's 

compliance. This was most likely to occur with major integrated refiners who operate gasoline 

marketing operations and thus have direct access to RINs for ethanol blended into their gasoline. 

Refiners whose operations are focused primarily on producing refined products with less 

marketing do not have such direct access to RINs and could potentially find it difficult to acquire 

a sufficient number for compliance despite the fact that the total nationwide volumes of 

renewable fuel meets or exceeds the standard. The result might be a higher price for RINs (and 

fuel) in the marketplace than would be expected under a more liquid RIN market. For similar 

reasons, we also took comment on possible changes to the requirement that RINs be transferred 

with volume through the distribution system as discussed more fully in Section II.H.4. 
 

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 In response to the NPRM, stakeholders differed significantly on whether EPA should 

implement one of these alternative approaches. For instance, while some refiners expressed 

support for moving the obligations to downstream parties such as blenders, terminals, and/or 

wholesale purchaser-consumers, other refiners preferred to maintain the current approach. 

Blenders and other downstream parties generally expressed opposition to a change in the 

designation of obligated parties, citing the additional burden of demonstrating compliance with 

the standard especially for small businesses. They also pointed to the need to implement new 

systems for determining and reporting compliance, the short leadtime for doing so, and the fewer 

resources that smaller downstream companies have to manage such work in comparison to the 

much larger refiners. Finally, they pointed to the additional complexity that would be added to 

the RFS program beyond that which is necessary to carry out the renewable fuels mandate under 

CAA section 211(o). 

 When the RFS1 regulations were drafted, the obligations were placed on the relatively 

small number of refiners and importers rather than on the relatively large number of downstream 

blenders and terminals in order to minimize the number of regulated parties and keep the 

program simple. However, with the expanded RFS2 mandates, essentially all downstream 

blenders and terminals are now regulated parties under RFS2 since essentially all gasoline will 

be blended with ethanol. Thus the rationale in RFS1 for placing the obligation on just the 

upstream refiners and importers is no longer valid. Nevertheless, based on the comments we 

received, we do not believe that the concerns expressed warrant a change in the designation of 

obligated parties for the RFS2 program at this time. We continue to believe that the market will 

provide opportunities for parties who are in need of RINs to acquire them from parties who have 
 

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excess. Refiners who market considerably less gasoline or diesel than they produce can establish 

contracts with splash blenders to purchase RINs. Such refiners can also purchase ethanol from 

producers directly, separate the RINs, and then sell the ethanol without RINs to blenders. Since 

the RFS program is based upon ownership of RINs rather than custody of volume, refiners need 

never take custody of the ethanol in order to separate RINs from volumes that they own. 

Moreover, a change in the designation of obligated parties would result in a significant change in 

the number of obligated parties and the movement of RINs, changes that could disrupt the 

operation of the RFS program during the transition from RFS1 to RFS2. 

 We will continue to evaluate the functionality of the RIN market. Should we determine 

that the RIN market is not operating as intended, driving up prices for obligated parties and fuel 

prices for consumers, we will consider revisiting this provision in future regulatory efforts. 

 In the NPRM we also took comment on several other possible ways to help ensure that 

obligated parties can demonstrate compliance. For instance, one alternative approach would 

have left our proposed definitions for obligated parties in place, but would have added a 

regulatory requirement that any party who blends ethanol into RBOB or CBOB must transfer the 

RINs associated with the ethanol to the original producer of the RBOB or CBOB. Stakeholders 

generally opposed this change, agreeing with our assessment that it would be extremely difficult 

to implement given that RBOB and CBOB are often transferred between multiple parties prior to 

ethanol blending. As a result, a regulatory requirement for RIN transfers back to the original 

producer would have necessitated an additional tracking requirement for RBOB and CBOB so 

that the blender would know the identity of the original producer. It would also be difficult to 
 

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ensure that RINs representing the specific category of renewable fuel blended were transferred to 

the producer of the RBOB or CBOB, given the fungible nature of RINs assigned to batches of 

renewable fuel. For these reasons, we have not finalized this alternative approach. 

 Another alternative approach on which we took comment would have allowed use of 

RINs that expire without being used for compliance by an obligated party to be used to reduce 

the nationwide volume of renewable fuel required in the following year. This alternative 

approach could have helped to prevent the hoarding of RINs from driving up demand for 

renewable fuel. However, it would also effectively alter the valid life limit for RINs. Comments 

from stakeholders did not change our position that such an approach is not warranted at this time, 

and thus we have not finalized it. 

 2. Determination of RVOs Corresponding to the Four Standards

 In order for an obligated party to demonstrate compliance, the percentage standards 

described in Section II.E.1 which are applicable to all obligated parties must be converted into the 

volumes of renewable fuel each obligated party is required to satisfy. These volumes of renewable 

fuel are the volumes for which the obligated party is responsible under the RFS program, and are 

referred to here as its RVO. Under RFS2, each obligated party will need to acquire sufficient RINs 

each year to meet each of the four RVOs corresponding to the four renewable fuel standards. 

 The calculation of the RVOs under RFS2 follows the same format as the formulas in the 

RFS1 regulations at §80.1107(a), with one modification. The standards for a particular 
 

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compliance year must be multiplied by the sum of the gasoline and diesel volume produced or 

imported by an obligated party in that year rather than only the gasoline volume as under the 

RFS1 program23. To the degree that an obligated party did not demonstrate full compliance with 

its RVOs for the previous year, the shortfall will be included as a deficit carryover in the 

calculation. CAA section 211(o)(5) only permits a deficit carryover from one year to the next if 

the obligated party achieves full compliance with each of its RVOs including the deficit 

carryover in the second year. Thus deficit carryovers cannot occur two years in succession for 

any of the four individual standards. They can, however, occur as frequently as every other year 

for a given obligated party for each standard. 

 Note that a party that produces only diesel fuel will have an obligation for all four standards 

even though he will not have the opportunity to blend ethanol into his own gasoline. Likewise, a 

party that produces only gasoline will have an obligation for all four standards even though he will 

not have an opportunity to blend biomass-based diesel into his own diesel fuel. 

 3. RINs Eligible to Meet Each RVO

 Under RFS1, all RINs had the same compliance value and thus it did not matter what the 

RR or D code was for a given RIN when using that RIN to meet the total renewable fuel 

standard. In contrast, under RFS2 only RINs with specified D codes can be used to meet each of 

the four standards. 

 

23 As discussed above, the diesel fuel that is used to calculate the RVO is any diesel designated as MVNRLM or a 

subcategory of MVNRLM. 
 

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 As described in Section I.A.1, the volume requirements in EISA are generally nested 

within one another, so that any fuel that satisfies the advanced biofuel requirement also satisfies 

the total renewable fuel requirement, and fuel that meets either the cellulosic biofuel or the 

biomass-based diesel requirements also satisfies the advanced biofuel requirement. As a result, 

the RINs that can be used to meet the four standards are likewise nested. Using the D codes 

defined in Table II.A-1, the RFS2 RINs that can be used to meet each of the four standards are 

shown in Table II.G.3-1. RFS1 RINs generated in 2010 and identified by a D code of 1 or 2 can 

also be applied to these standards using the protocol described in Section II.G.4 below. 

Table II.G.3-1 

RINs That Can Be Used To Meet Each Standard 

Standard Obligation Allowable D codes 

Cellulosic biofuel RVOCB 3 and 7 

Biomass-based diesel RVOBBD 4 and 7 

Advanced biofuel RVOAB 3, 4, 5, and 7 

Renewable fuel RVORF 3, 4, 5, 6, and 7 

 The nested nature of the four standards also means that in some cases we must allow the 

same RIN to be used to meet more than one standard in the same year. Thus, for instance, a RIN 

with a D code of 3 can be used to meet three of the four standards, while a RIN with a D code of 

5 can be used to meet both the advanced biofuel and total renewable fuel standards. However, a 

D code of 6 can only be used to meet the renewable fuel standard. Consistent with our proposal, 
 

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we are continuing to prohibit the use of a single RIN for compliance purposes in more than one 

year or by more than one party24. 

 4. Treatment of RFS1 RINs under RFS2

 As described in the introduction to this section, we are implementing a number of 

changes to the RFS program as a result of the requirements in EISA. These changes will go into 

effect on July 1, 2010 and, among other things, will affect the conditions under which RINs are 

generated and their applicability to each of the four standards. As a result, RINs generated in 

2010 under these RFS2 regulations will not be exactly the same as RINs generated under RFS1 

regulations. Given the valid RIN life that allows a RIN to be used in the year generated or the 

year after, we must address circumstances in which excess 2009 RINs are used for compliance 

purposes in 2010. Also, since RINs generated in January through June of 2010 will be generated 

under RFS1 regulations, we must provide a means for them to be used to meet the annual 2010 

RFS2 standards. Finally, we must address deficit carryovers from 2009 to 2010, since the total 

renewable fuel standards in these two years will be defined differently. 

 a. Use of RFS1 RINs to Meet Standards Under RFS2 

 In 2009 and the first three months of 2010, the RFS1 regulations will continue to apply 

and thus producers will not be required to demonstrate that their renewable fuel is made from 

renewable biomass as defined by EISA, nor that their combination of fuel type, feedstock, and 

 

24 Note that we are finalizing an exception to this general prohibition for the specific and limited case of 2008 and 

2009 biodiesel and renewable diesel RINs used to demonstrate compliance with both the 2009 total renewable fuel 

standard and the 2010 biomass-based diesel standard. See Section II.E.2.a. 
 

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process meets the GHG thresholds specified in EISA. Moreover, there is no practical way to 

determine after the fact if RINs generated under RFS1 regulations meet any of these criteria. 

However, we believe that the vast majority of RFS1 RINs generated in 2009 and the first two 

months of 2010 will in fact meet the RFS2 requirements. First, while ethanol made from corn 

must meet a 20% GHG threshold under RFS2 if produced by a facility that commenced 

construction after December 19, 2007, facilities that were already built or had commenced 

construction as of December 19, 2007 are exempt from this requirement. Essentially all ethanol 

produced in 2009 and the first three months of 2010 will meet the prerequisites for this 

exemption. Second, it is unlikely that renewable fuels produced in 2009 or the first three months 

of 2010 will have been made from feedstocks that do not meet the new renewable biomass 

definition. It is very unlikely that new land would have been cleared or cultivated since 

December 19, 2007 for use in growing crops for renewable fuel production, and thus the land use 

restrictions associated with the renewable biomass definition will very likely be met. Finally, the 

text of section 211(o)(5) states that a “credit generated under this paragraph shall be valid to 

show compliance for the 12 months as of the date of generation,” and EISA did not change this 

provision and did not specify any particular transition protocol to follow. A straightforward 

interpretation of this provision is to allow RFS1 RINs generated in 2009 and early 2010 to be 

valid to show compliance for the annual 2010 obligations. 

 The separate definitions for cellulosic biofuel and biomass-based diesel require GHG 

thresholds of 60% and 50%, respectively. While we do not have a mechanism in place to 

determine if these thresholds have been met for RFS1 RINs generated in 2009 or early 2010, any 

shortfall in GHG performance for this one transition period is unlikely to have a significant 
 

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impact on long-term GHG benefits of the program. Few stakeholders commented on our 

proposed treatment of RFS1 RINs under RFS2. Of those that did, most supported our proposed 

approach to the use of RFS1 RINs to meet RFS2 obligations. Based on our belief that it is 

critical to the smooth operation of the program that excess 2009 RINs be allowed to be used for 

compliance purposes in 2010, we are allowing RFS1 RINs that were generated in 2009 or 2010 

representing cellulosic biomass ethanol to be valid for use in satisfying the 2010 cellulosic 

biofuel standard. Likewise, we are allowing RFS1 RINs that were generated in 2009 or 2010 

representing biodiesel and renewable diesel to be valid for use in satisfying the 2010 biomassbased diesel standard. 

 Consistent with our proposal, we have used information contained in the RR and D codes 

of RFS1 RINs to determine how those RINs should be treated under RFS2. The RR code is used 

to identify the Equivalence Value of each renewable fuel, and under RFS1 these Equivalence 

Values are unique to specific types of renewable fuel. For instance, biodiesel (mono alkyl ester) 

has an Equivalence Value of 1.5, and non-ester renewable diesel has an Equivalence Value of 

1.7, and both of these fuels may be valid for meeting the biomass-based diesel standard under 

RFS2. Likewise, RINs generated for cellulosic biomass ethanol under RFS1 regulations must be 

identified with a D code of 1, and these fuels will be valid for meeting the cellulosic biofuel 

standard under RFS2. Our final treatment of RFS1 RINs for compliance under RFS2 is shown in 

Table II.G.4.a-1. 
 

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Table II.G.4.a-1 

Treatment of RFS1 RINs for RFS2 Compliance Purposes 

RINs Generated under RFS1a

 Treatment under RFS2b

Any RIN with D code of 2 and RR 

code of 15 or 17 

Equivalent to RFS2 RINs with D code of 4 

All other RINs with D code of 2 Equivalent to RFS2 RINs with D code of 6 

Any RIN with D code of 1 Equivalent to RFS2 RINs with D code of 3 

 a See RFS1 RIN code definitions at §80.1125

 b See RFS2 RIN code definitions at §80.1425

 b. Deficit Carryovers from the RFS1 Program to RFS2 

 The calculation of RVOs in 2010 under the RFS2 regulations will be somewhat different 

than the calculation of RVOs in 2009 under RFS1. In particular, 2009 RVOs were based on 

gasoline production only, while 2010 RVOs will be based on volumes of gasoline and diesel. As 

a result, 2010 compliance demonstrations that include a deficit carried over from 2009 will 

combine obligations calculated on two different bases. 

 We do not believe that deficits carried over from 2009 to 2010 will undermine the goals 

of the program in requiring specific volumes of renewable fuel to be used each year. Although 

RVOs in 2009 and 2010 will be calculated differently, obligated parties must acquire sufficient 

RINs in 2010 to cover any deficit carried over from 2009 in addition to that portion of their 2010 

obligation which is based on their 2010 gasoline and diesel production. As a result, the 2009 
 

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nationwide volume requirement of 11.1 billion gallons of renewable fuel will be consumed over 

the two year period concluding at the end of 2010. Thus, we are not implementing any special 

treatment for deficits carried over from 2009 to 2010. 

 A deficit carried over from 2009 to 2010 will only affect a party's total renewable fuel 

obligation in 2010, as the 2009 obligation is for total renewable fuel use, not a subcategory. The 

RVOs for biomass-based diesel or advanced biofuel will not be affected, as they do not have 

parallel obligations in 2009 under RFS125. 

H. Separation of RINs 

 As we proposed in the NPRM, we are requiring the RFS1 provisions regarding the 

separation of RINs from volumes of renewable fuel to be retained for RFS2. However, the 

modifications in EISA required changes to the treatment of RINs associated with nonroad 

renewable fuel and renewable fuels used in heating oil and jet fuel. Our approach to the 

separation of RINs by exporters must also be modified to account for the fact that there would be 

four categories of renewable fuel under RFS2. 

1. Nonroad

 Under RFS1, RINs associated with renewable fuels used in nonroad vehicles and engines 

downstream of the renewable fuel producer were required to be retired by the party who owned 

the renewable fuel at the time of blending. This provision derived from the EPAct definition of 

 

25 There is no cellulosic biofuel standard for 2010. 
 

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renewable fuel which was limited to fuel used to replace fossil fuel used in a motor vehicle. 

However, EISA expands the definition of renewable fuel, and ties it to the definition of 

transportation fuel which is defined as any “fuel for use in motor vehicles, motor vehicle 

engines, nonroad vehicles, or nonroad engines (except for ocean-going vessels)." To implement 

these changes, the RFS2 program eliminates the RFS1 RIN retirement requirement for renewable 

fuels used in nonroad applications, with the exception of RINs associated with renewable fuels 

used in ocean-going vessels. 

 Since RINs have a valid life of two years, the NPRM proposed that a 2009 RFS1 RIN 

that is retired because the renewable fuel associated with it was used in nonroad vehicles or 

engines could be reinstated in 2010 for use in compliance with the 2010 standards. Stakeholders 

supported this approach, and we are finalizing it in today's action. 

 2. Heating Oil and Jet Fuel

 EISA defines ‘additional renewable fuel’ as “fuel that is produced from renewable 

biomass and that is used to replace or reduce the quantity of fossil fuel present in home heating 

oil or jet fuel.”26 While we are not requiring fossil-based heating oil and jet fuel to be included 

in the fuel used by a refiner or importer to calculate their RVOs, we are allowing renewable fuels 

used as or in heating oil and jet fuel to generate RINs. Similarly, RINs associated with a 

renewable fuel, such as biodiesel, that is blended into heating oil will continue to be valid for 

compliance purposes. See also discussion in Section II.B.1.e. 

 

26 EISA, Title II, Subtitle A-Renewable Fuel Standard, Section 201. 
 

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 3. Exporters

 Under RFS1, exporters were assigned an RVO representing the volume of renewable fuel 

that was exported, and they were required to separate all RINs that were assigned to fuel that was 

exported. Since there was only one standard, there was only one possible RVO applicable to 

exporters. 

 Under RFS2, there are four possible RVOs corresponding to the four categories of 

renewable fuel (cellulosic biofuel, biomass-based diesel, advanced biofuel, and total renewable 

fuel). However, given the fungible nature of the RIN system and the fact that an assigned RIN 

transferred with a volume of renewable fuel may not be the same RIN that was originally 

generated to represent that volume, RINs from different fuel types can accompany volumes. 

Thus, there may be no way for an exporter to determine from an assigned RIN which of the four 

categories applies to an exported volume. In order to determine its RVOs, the only information 

available to the exporter may be the type of renewable fuel that he is exporting. 

 However, if an exporter knows, or has reason to know, that the renewable fuel that it is 

exporting is either cellulosic biofuel or advanced biofuel, we are requiring the exporter to 

determine an RVO for the exported fuel based upon these fuel types. For instance, if an exporter 

purchases cellulosic biofuel or advanced biofuel directly from a producer or if the fuel has been 

segregated from other fuels, we would expect the exporter to know or have reason to know the 

type of fuel that it is exporting. Another example of when we would expect an exporter to know 
 

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or have reason to know that the fuel that it is exporting is cellulosic or advanced biofuel would 

be if the commercial documents that accompany the purchase or sale of the renewable fuel 

identify the product as cellulosic or advanced biofuel. 

 EPA recognizes that in many situations, exporters will not know or have reason to know 

which of the four categories of renewable fuel apply to the exported fuel. If this is the case, we 

are requiring exporters to follow the approach proposed in the NPRM. Exported volumes of 

biodiesel (mono alkyl esters) and renewable diesel must be used to determine the exporter's RVO 

for biomass-based diesel. For all other types of renewable fuel, the most likely category is 

general renewable fuel. Thus, we are requiring that all renewable fuels be used to determine the 

exporter's RVO for total renewable fuel. Our final approach is provided at §80.1430. 

 In the NPRM we took comment on an alternative approach in which the total nationwide 

volumes required in each year (see Table I.A.1-1) would be used to apportion specific types of 

renewable fuel into each of the four categories. For example, exported ethanol may have 

originally been produced from cellulose to meet the cellulosic biofuel requirement, from corn to 

meet the total renewable fuel requirement, or may have been imported as advanced biofuel. If 

ethanol were exported, we could divide the exported volume into three RVOs for cellulosic 

biofuel, advanced biofuel, and total renewable fuel using the same proportions represented by the 

national volume requirements for that year. However, as described in the NPRM, we believe 

that this alternative approach would have added considerable complexity to the compliance 

determinations for exporters without necessarily adding more precision. Given the expected 
 

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small volumes of exported renewable fuel, we continue to believe that this added complexity is 

not warranted at this time. 

 As described above, exporters must separate any RINs assigned to renewable fuel that 

they export. However, since RINs are fungible and the owner of a batch of renewable fuel has 

the flexibility to assign between zero and 2.5 gallon-RINs to each gallon, we have made this 

flexibility explicit for exporters. Thus, an exporter can separate up to 2.5 gallon-RINs for each 

gallon of renewable fuel that he exports. While the exporter is not required to retain these 

separated RINs for use in complying with his RVOs calculated on the basis of the exported 

volumes, this would be the most straightforward approach and would ensure that the exporter has 

sufficient RINs to comply. However, we are aware of some exporters who sell RINs that they 

separate as a source of revenue, with the intention to purchase replacement RINs on the open 

RIN market later in the year to comply with their RVOs. At this time we are not aware of such 

activities resulting in noncompliance, and thus the RFS2 regulations promulgated today will 

continue to allow this. However, we may revisit this issue in the future if there is evidence that 

exporters are failing to comply because they are selling RINs that they separate from exported 

volumes. 

 4. Requirement to Transfer RINs with Volume

 In the NPRM, we proposed that the approach to RIN transfers established under RFS1 - 

that RINs generated by renewable fuel producers and importers must be assigned to batches of 

renewable fuel and transferred along with those batches - be continued under RFS2. However, 
 

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given the higher volumes required under RFS2 and the resulting expansion in the number of 

regulated parties, we also took comment on two alternative approaches to RIN transfers. Along 

with the alternative approaches for designation of obligated parties as described in Section II.G.1 

above, a change to the requirement to transfer RINs with batches had the potential to more 

evenly align a party's access to RINs with that party's obligations under the RFS2 program. 

Nevertheless, for the reasons described below, we have determined that it would not be 

appropriate to implement these alternative approaches at this time. 

 In the first alternative approach, we would have removed the restriction established under 

the RFS1 rule requiring that RINs be assigned to batches of renewable fuel and transferred with 

those batches. Instead, renewable fuel producers could have sold RINs (with a K code of 2 

rather than 1) separately from volumes of renewable fuel to any party. 

 In the second alternative approach, producers and importers of renewable fuels would be 

required to separate and transfer the RIN, but only to an obligated party. This "direct transfer" 

approach would require renewable fuel producers to transfer RINs with renewable fuel for all 

transactions with obligated parties, and sell all other RINs directly to obligated parties on a 

quarterly basis for any renewable fuel volumes that were not sold directly to obligated parties. 

Any RINs not sold in this way would be required to be offered for sale to any obligated party 

through a public auction. Only renewable fuel producers, importers, and obligated parties would 

be allowed to own RINs. 
 

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 Many renewable fuel producers supported the concept of allowing them to separate the 

RINs from renewable fuel that they produce. They generally argued in favor of a free market 

approach to RINs in which there would be no restrictions on whom they could sell RINs to, or in 

what timeframe. The direct transfer approach was unnecessary, they argued, since the market 

would compel them to sell all RINs they generated, and all RINs would eventually end up in the 

hands of the obligated parties that need them. However, other renewable fuel producers opposed 

any change to the requirement that RINs be assigned to volumes of renewable and transferred 

with those volumes through the distribution system. They argued that the system established 

under RFS1 has proven to work and it would create an unwarranted burden to require producers 

to modify their IT systems for RFS2. 

 Marketers and distributors were generally opposed to our proposed alternative 

approaches to RIN transfers. Moreover, SIGMA and NACS, as in the RFS1 rulemaking process, 

recommended that RINs not be generated by producers at all, but rather by the party that blends 

renewable fuel into gasoline or diesel, or uses renewable fuel in its neat form as a transportation 

fuel. 

 Obligated parties generally opposed any change to the RFS1 requirement that RINs be 

assigned to volumes of renewable fuel by the producer or importer, and transferred with volumes 

through the distribution system. They reiterated their concern, first raised in the RFS1 

rulemaking, that a free market approach would place them at greater risk of market manipulation 

by renewable fuel producers. Moreover, while generally expressing support for the concept of a 

direct transfer approach, they also expressed doubt that the auctions could be regulated in such a 
 

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way as to ensure that RIN generators could not withhold RINs from the market by such means as 

failing to adequately advertise the time and location of an auction, by setting the selling price too 

high, by specifying a minimum number of bids before selling, by conducting auctions 

infrequently, by having unduly short bidding windows, etc. These concerns were exacerbated by 

the nested standards required by EISA, under which many obligated parties have expressed 

concern about being able to acquire sufficient RINs for compliance. 

 Given the significant challenges associated with a change to the requirement that RINs be 

transferred with volume and the opposing views among stakeholders, we are not making any 

change in today's final rule. 

5. Neat Renewable Fuel and Renewable Fuel Blends Designated as Transportation 

Fuel, Heating Oil, or Jet Fuel

 Under RFS1, RINs must, with limited exceptions, be separated by an obligated party 

taking ownership of the renewable fuel, or by a party that blends renewable fuel with gasoline or 

diesel. In addition, a party that designates neat renewable fuel as motor vehicle fuel may 

separate RINs associated with that fuel if the fuel is in fact used in that manner without further 

blending. One exception to these provisions is that biodiesel blends in which diesel constitutes 

less than 20 volume percent are ineligible for RIN separation by a blender. While EPA 

understands that in the vast majority of cases, biodiesel is blended with diesel in concentrations 

of 80 volume percent or less, there may be instances in which biodiesel is blended with diesel in 
 

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concentrations of more than 80 percent biodiesel, but the blender is prohibited from separating 

RINs under the RFS1 regulations. 

 Thus, in order to account for situations in which biodiesel blends of 81 percent or greater 

may be used as transportation fuel, heating oil, or jet fuel without ever having been owned by an 

obligated party, EPA proposed, and is finalizing a change to the applicability of the RIN 

separation provisions for RFS2. Section 80.1429(b)(4) will allow for separation of RINs for neat 

renewable fuel or blends of renewable fuel and diesel fuel that the party designates as 

transportation fuel, heating oil, or jet fuel, provided the neat renewable fuel or blend is used in 

the designated form, without further blending, as transportation fuel, heating oil, or jet fuel. 

Those parties that blend renewable fuel with gasoline or diesel fuel (in a blend containing 80 

percent or less biodiesel) must separate RINs pursuant to §80.1429(b)(2). 

 Thus, for example, if a party intends to separate RINs from a volume of B85, the party 

must designate the blend for use as transportation fuel, heating oil, or jet fuel and the blend must 

be used in its designated form without further blending. The party is also required to maintain 

records of this designation pursuant to §80.1454(b)(5). Finally, the party is required to comply 

with the proposed PTD requirements in §80.1453(a)(11)(iv), which serve to notify downstream 

parties that the volume of fuel has been designated for use as transportation fuel, heating oil, or 

jet fuel, and must be used in that designated form without further blending. Parties may separate 

RINs at the time they comply with the designation and PTD requirements, and do not need to 

physically track ultimate fuel use. 
 

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I. Treatment of Cellulosic Biofuel 

 1. Cellulosic Biofuel Standard

 EISA requires that the Administrator set the cellulosic biofuel standard each November 

for the next year based on the lesser of the volume specified in the Act or the projected volume 

of cellulosic biofuel production based on EIA estimates for that year. In the event that the 

projected volume is less than the amount required in the Act, EPA may also reduce the 

applicable volume of the total renewable fuel and advanced biofuels requirement by the same or 

a lesser volume. We will examine EIA’s projected volumes and other available data including 

the required production outlook reports discussed in Section II.K to decide the appropriate 

standard for the following year. The outlook reports from all renewable fuel producers will 

assist EPA in determining what the cellulosic biofuel standard should be and if the total 

renewable fuel and/or advanced biofuel standards should be adjusted. For years where EPA 

determines that the projected volume of cellulosic biofuels is not sufficient to meet the levels in 

EISA we will consider the availability of other advanced biofuels in deciding whether to lower 

the advanced biofuel standard as well. 

 In determining whether the advanced biofuel and/or total renewable fuel volume 

requirements should also be adjusted downward in the event that projected volumes of cellulosic 

biofuel fall short of the statutorily required volumes, we believe it may be appropriate to allow 

excess advanced biofuels to make up some or all of the shortfall in cellulosic biofuel. For 

instance, if we determined that sufficient biomass-based diesel was available, we could decide 
 

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that the required volume of advanced biofuel need not be lowered, or that it should be lowered to 

a smaller degree than the required cellulosic biofuel volume. Thus, the Act requires EPA to 

examine the total and advanced renewable fuel standards and volumes in the event of a cellulosic 

volume waiver. EPA will look at projections for each year on an individual yearly basis to 

determine if the standards should be adjusted. EPA believes that since the standards are nested 

and the total and advanced renewable fuel volume mandates are met in part by the cellulosic 

volume mandate, Congress gave EPA the flexibility to lower the required total and advanced 

volumes, but Congress also wanted to encourage the development of advanced renewable fuels 

as well and allow in appropriate circumstances for the use of those fuels in the event they can 

meet that year’s required volumes that would have been met by the cellulosic mandate. 

 2. EPA Cellulosic Biofuel Waiver Credits for Cellulosic Biofuel

 Whenever EPA sets the cellulosic biofuel standard at a level lower than that required in 

EISA, but greater than zero, EPA is required to provide a number of cellulosic credits for sale 

that is no more than the volume used to set the standard. Congress also specified the price for 

such credits: adjusted for inflation, they must be offered at the price of the higher of 25 cents per 

gallon or the amount by which $3.00 per gallon exceeds the average wholesale price of a gallon 

of gasoline in the United States. The inflation adjustment will be for years after 2008. The 

inflation adjustment will be based on the standard US inflation measure Consumer Price Index 

for All Urban Consumers (CPI-U) for All Items expenditure category as provided by the Bureau 

of Labor Statistics.27 

 

27 See U.S. Department of Labor, Bureau of Labor Statistics (BLS), Consumer Price Index website at: 

http://www.bls.gov/cpi/. 
 

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 Congress afforded the Agency considerable flexibility in implementing the system of 

cellulosic biofuel credits. EISA states EPA; “shall include such provisions, including limiting 

the credits’ uses and useful life, as the Administrator deems appropriate to assist market liquidity 

and transparency, to provide appropriate certainty for regulated entities and renewable fuel 

producers, and to limit any potential misuse of cellulosic biofuel credits to reduce the use of 

other renewable fuels, and for such other purposes as the Administrator determines will help 

achieve the goals of this subsection.” 

 We have fashioned a number of limitations on the use of cellulosic that reflect these 

considerations. Specifically, the credits will be called “Cellulosic Biofuel Waiver Credits” (or 

“waiver credits”) so that there is no confusion with RINs or allowances used in the acid rain 

program. Such waiver credits will only be available for the current compliance year for which 

we have waived some portion of the cellulosic biofuel standard, they will only be available to 

obligated parties, and they will be nontransferable and nonrefundable. Further, obligated parties 

may only purchase waiver credits up to the level of their cellulosic biofuel RVO less the number 

of cellulosic biofuel RINs that they own. A company owning cellulosic biofuel RINs and 

cellulosic waiver credits may use both types of credits if desired to meet their RVOs, but unlike 

RINs obligated parties will not be able to carry waiver credits over to the next calendar year. 

Obligated parties may not use waiver credits to meet a prior year deficit obligation. These 

restrictions help ensure that waiver credits are not overutilized at the expense of actual renewable 

volume. 
 

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 In the NPRM, EPA proposed that the credits could be usable for the advanced and total 

renewable standards similarly to cellulosic biofuel RINs. Several commenters stated this 

provision could displace advanced and total renewable fuel that was actually produced which 

would be against the intent of the Act, and that unlike RINs a company should only be permitted 

to use waiver credits to meet its cellulosic biofuel obligation. We agree, and are limiting the use 

of waiver credits for compliance with only a company's cellulosic biofuel RVO. 

In the event the total volume of conventional gasoline and diesel fuel produced or 

imported in the country exceeds the projections used to set the standard, companies will still be 

able to purchase waiver credits up to their cellulosic volume obligation. When setting a reduced 

cellulosic biofuel standard EPA makes a determination that the cellulosic volume specified in 

EISA will not be met and that determination is not based on how much nonrenewable motor fuel 

will be produced. EPA sets the standard based on the volumes in the Act and a projection of 

gasoline production to ensure the obligation is broken up most equitably. EPA believes that 

Congress wanted all obligated parties to have equal access to the waiver credits in the event of 

the waiver and did not want obligated parties to incur a deficit due to the timing of when they 

purchased waiver credits. 

 Cellulosic Biofuel Waiver Credits, in the event of a waiver, will be offered in a generic 

format rather than a serialized format, like RINs. Waiver credits can be purchased using 

procedures defined by the EPA, and at the time that an obligated party submits its annual 

compliance demonstration to the EPA and establishes that it owns insufficient cellulosic biofuel 

RINs to meet its cellulosic biofuel RVO. EPA will define these procedures with the US 
 

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Treasury before the end of the first annual compliance period. EPA will publish these 

procedures with the obligated party annual compliance report template. EPA will provide the 

forms necessary to purchase the credits. EPA intends to provide options for obligated parties to 

use Pay.Gov or if desired to mail payment to the US Treasury. 

 The wholesale price of gasoline used by EPA in setting the price of the waiver credits 

will be based on the average monthly bulk (refinery gate) price of gasoline using data from the 

most recent twelve months of data from EIA available to EPA at the time it develops the 

cellulosic biofuel standard. 28 EPA will use refinery gate price, U.S. Total Gasoline Bulk Sales 

(Price) by Refiners from EIA in calculating the average, since it is the price most reflective of 

what most obligated parties are selling their fuel. EPA will use the most recent twelve months of 

data provided by EIA to develop an average price on actual volumes produced in the year prior 

to the compliance year. In order to provide regulatory certainty, we will set the waiver credits 

price for the following year each November when and if we set a cellulosic biofuel standard for 

the following year that is based on achieving a lower volume of cellulosic biofuel use than is 

specified in EISA. 

 For the 2010 compliance period, since the cellulosic standard is lower than the level 

otherwise required by EISA, we are also making cellulosic waiver credits available to obligated 

parties for end-of-year compliance should they need them at a price of $1.56 per gallon-RIN." 

The price for the 2011 compliance period, if necessary will be set when we announce the 2011 

cellulosic biofuel standard. 

 

28 More information on wholesale gasoline prices can be found on the Department of Energy’s (DOE), Energy 

Information Administration’s (EIA) website at: 

http://tonto.eia.doe.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=A103B00002&f=M
 

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 3. Application of Cellulosic Biofuel Waiver Credits

 While the credit provisions of section 202(e) of EISA ensure that there is a predictable 

upper limit to the price that cellulosic biofuel producers can charge for a gallon of cellulosic 

biofuel and its assigned RIN, there may be circumstances in which this provision has other 

unintended consequences. This could occur in situations where the cost of total renewable fuel 

RINs exceeds the cost of the cellulosic waiver credits. To prevent this, we sought comment on 

and are finalizing an additional restriction: an obligated party may only purchase waiver credits 

from the EPA to the degree that it establishes it owns insufficient cellulosic biofuel RINs to meet 

its cellulosic biofuel RVO. This approach forces obligated parties to apply all their cellulosic 

biofuel RINs to their cellulosic biofuel RVO before applying any waiver credits to their 

cellulosic biofuel RVO. 

 Even with this restriction the approach in the NPRM might not have operated as 

intended. For instance, if the combination of cellulosic biofuel volume price and RIN price were 

to become low compared to that for general renewable fuel, a small number of obligated parties 

could have purchased more cellulosic biofuel than they need to meet their cellulosic biofuel 

RVOs and could have used the additional cellulosic biofuel RINs to meet their advanced biofuel 

and total renewable fuel RVOs. Other obligated parties would then have had no access to 

cellulosic biofuel volume nor cellulosic biofuel RINs, and would have been forced to purchase 

waiver credits from the EPA. This situation would have had the net effect of waiver credits 

replacing advanced biofuels and/or general renewable fuel rather than cellulosic biofuel. Based 
 

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on comments received on the NPRM, EPA is placing the additional restriction of only allowing 

the waiver credits to count towards the cellulosic biofuel standard and not the advanced or 

renewable fuel standards. 

 Moreover, under certain conditions it may be possible for the market price of general 

renewable fuel RINs to be significantly higher than the market price of cellulosic biofuel RINs, 

as the latter is limited in the market by the price of EPA-generated waiver credits according to 

the statutory formula described in Section II.I.2 above. Under some conditions, this could result 

in a competitive disadvantage for cellulosic biofuel in comparison to corn ethanol, for example. 

For instance, if gasoline prices at the pump are significantly higher than ethanol production costs, 

while at the same time corn-ethanol production costs are lower than cellulosic ethanol production 

costs, profit margins for corn-ethanol producers will be larger than for cellulosic ethanol 

producers. Under these conditions, while obligated parties may still purchase cellulosic ethanol 

volume and its associated RINs rather than waiver credits, cellulosic ethanol producers will 

realize lower profits than corn-ethanol producers due to the upper limit placed on the price of 

cellulosic biofuel RINs through the pricing formula for waiver credits. For a newly forming and 

growing cellulosic biofuel industry, this competitive disadvantage could make it more difficult 

for investors to secure funding for new projects, threatening the ability of the industry to reach 

the statutorily mandated volumes. 

 Finally, in the NPRM we sought comment on a "dual RIN" approach to cellulosic 

biofuel. In this approach, both cellulosic biofuel RINs (with a D code of 3) and waiver credits 

would have only been applied to an obligated party's cellulosic biofuel RVO, but producers of 
 

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cellulosic biofuel would also generate an additional RIN representing advanced biofuel (with a D 

code of 5). The producer would have only been required to transfer the advanced biofuel RIN 

with a batch of cellulosic biofuel, and could retain the cellulosic biofuel RIN for separate sale to 

any party29. The cellulosic biofuel and its attached advanced biofuel RIN would then have 

competed directly with other advanced biofuel and its attached advanced biofuel RIN, while the 

separate cellulosic biofuel RIN would have an independent market value that would have been 

effectively limited by the pricing formula for waiver credits as described in Section II.I.2. 

However, this approach would have been a more significant deviation from the RIN generation 

and transfer program structure that was developed cooperatively with stakeholders during RFS1. 

It would have provided cellulosic biofuel producers with significantly more control over the sale 

and price of cellulosic biofuel RINs, which was one of the primary concerns of obligated parties 

during the development of RFS1. Therefore, EPA is treating the transfer of cellulosic RINs in 

the same manner as the other required volumes. 

J. Changes to Recordkeeping and Reporting Requirements 

 1. Recordkeeping

 Recordkeeping, including product transfer documents (PTDs), will support the 

enforcement of the use of RINs for compliance purposes. Parties are afforded significant 

freedom with regard to the form that PTDs take. Product codes may be used as long as they are 

understood by all parties, but they may not be used for transfers to truck carriers or to retailers or 

 

29 The cellulosic biofuel RIN would be a separated RIN with a K code of 2 immediately upon generation. 
 

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wholesale purchaser-consumers. Parties must keep copies of all PTDs they generate and receive, 

as well as copies of all reports submitted to EPA and all records related to the sale, purchase, 

brokering or transfer or RINs, for five (5) years. Parties must keep copies of records that relate 

to program flexibilities, such as small business-oriented provisions. Upon request, parties are 

responsible for providing their records to the Administrator or the Administrator's authorized 

representative. We reserve the right to request to receive documents in a format that we can read 

and use. 

 In Section III.A. of this preamble, we describe an EPA-Moderated Transaction System 

(EMTS) for RINs. The new system allows for “real-time” recording of transactions involving 

RINs. 

 

2. Reporting

Producers and importers who generate or take ownership of RINs shall submit RIN 

Transaction Reports30 and/or RIN Generation Reports quarterly. Renewable fuel exporters and 

obligated parties shall submit their RIN Transaction Reports quarterly, and RIN owners shall 

submit their RIN Transaction Reports quarterly. EMTS will be used by all parties to record “real 

time” generation of RINs and transactions involving RINs starting July 1, 2010. "Real time” 

means recordation within five (5) business days of generation or any transaction involving a 

RIN. 

 

30 For ease of reference, the current RFS (i.e. RFS1) form may be viewed at the EPA Fuels Reporting website at the 

following URL: http://www.epa.gov/otaq/regs/fuels/rfsforms.htm (accessed November 16, 2009). These forms will 

be updated for RFS2. 
 

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 Quarterly reports are to be submitted on the following schedule. Quarterly reports 

include RIN Activity Reports and, with EMTS, simplified reporting and certification of the RIN 

Generation and RIN Transaction Reports. 

Table II.J-1 

Quarterly Reporting Schedule 

Quarter Covered by Report Due Date for Report 

January - March May 31 

April - June August 31 

July - September November 30 

October - December February 28 

 Annual reports (covering January through December) would continue to be due on 

February 28. The only annual report is the Obligated Party Annual Compliance Report.31 

 

 Simplified, secure reporting is currently available through our Central Data Exchange 

(CDX). CDX permits us to accept reports that are electronically signed and certified by the 

submitter in a secure and robustly encrypted fashion. Using CDX eliminates the need for wet 

ink signatures and reduces the reporting burden on regulated parties. EMTS will also make use 

of the CDX environment. 

 

31 For RFS1, this form is numbered RFS0300. 
 

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 Due to the criteria that renewable fuel producers and importers must meet in order to 

generate RINs under RFS2, and due to the fact that renewable fuel producers and importers must 

have documentation about whether their feedstock(s) meets the definition of “renewable 

biomass,” we proposed several changes to the RIN Generation Report.32 We proposed to make 

the report a more general report on renewable fuel production in order to capture information on 

all batches of renewable fuel, whether or not RINs are generated for them. This final rule adopts 

the proposed approach. All renewable fuel producers and importers above 10,000 gallons per 

year must report to EPA on each batch of their fuel and indicate whether or not RINs are 

generated for the batch. If RINs are generated, the producer or importer is required to certify 

that his feedstock meets the definition of “renewable biomass.” If RINs are not generated, the 

producer or importer must state the reason for not generating RINs, such as they have 

documentation that states that their feedstock did not meet the definition of “renewable 

biomass,” or the fuel pathway used to produce the fuel was such that the fuel did not qualify to 

generate RINs as a renewable fuel. For each batch of renewable fuel produced, we require 

information about the types and volumes of feedstock used and the types and volumes of coproducts produced, as well as information about the process or processes used. This information 

is necessary to confirm that the producer or importer assigned the appropriate D code to their 

fuel and that the D code was consistent with their registration information. In this final rule, we 

adopt the approach set forth in the notice of proposed rulemaking. 

 In addition, we proposed two changes for the RIN Transaction Report33. First, for reports 

of RINs assigned to a volume of renewable fuel, the volume of renewable fuel must be reported. 

 

32 For RFS1, this form is numbered RFS0400. 

33 For RFS1, this form is numbered RFS0200. 
 

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Second, RIN price information must be submitted for transactions involving both separated RINs 

and RINs assigned to a renewable volume. This information was not collected under RFS1, but 

because we believe this information has great programmatic value to EPA, we proposed to 

collect it for RFS2. As we explained in the proposed rule, price information may help us to 

anticipate and appropriately react to market disruptions and other compliance challenges, will be 

beneficial when setting future renewable standards, and will provide additional insight into the 

market when assessing potential waivers. Our incomplete knowledge regarding RIN pricing for 

RFS1 adversely affected our ability to assess the general health and direction of the market and 

overall liquidity of RINs. Because we believe the inclusion of price information in reports will 

be beneficial to both EPA and to regulated parties, this final rule includes that information 

element in reports, as well as incorporating it as part of the “real time” transactional information 

collected via EMTS. 

 

3. Additional Requirements for Producers of Renewable Natural Gas, Electricity, 

and Propane

 In addition to the general reporting requirement listed above, we are requiring an 

additional item of reporting for producers of renewable natural gas, electricity, and propane who 

choose to generate and assign RINs. While producers of renewable natural gas, electricity, and 

propane who generate and assign RINs are responsible for filing the same reports as other 

producers of RIN-generating renewable fuels, we are requiring that additional reporting for these 

producers support the actual use of their products in the transportation sector. We believe that 

one simple way to achieve this may be to add a requirement that producers of renewable natural 
 

253

gas, electricity, and propane add the name of the purchaser (e.g., the name of the wholesale 

purchaser-consumer (WPC) or fleet) to their RIN generation reports and then maintain 

appropriate records that further identify the purchaser and the details of the transaction. We are 

not requiring that a purchaser who is either a WPC or an end user would have to register under 

this scenario, unless that party engages in other activities requiring registration under this 

program. 

 4. Attest Engagements

 The purpose of an attest engagement is to receive third party verification of information 

reported to EPA. An attest engagement, which is similar to a financial audit, is conducted by a 

Certified Public Accountant (CPA) or Certified Independent Auditor (CIA) following agreedupon procedures. We have found the information in attest engagements submitted under RFS1 

to be extremely valuable as a compliance monitoring tool. The approach adopted in this final rule 

is identical to the approach adopted under the RFS1 program,34 although the universe of 

obligated parties and renewable fuels producers is broader under this final rule for RFS2. 

 As with the RFS1 program, an attest engagement must be conducted by an individual 

who is a Certified Public Accountant (CPA) or Certified Internal Auditor (CIA), who is 

independent of the party whose records are being reviewed, and who will follow agreed-upon 

procedures to determine whether underlying records, reported items, and transactions agree. The 

CPA or CIA will generate a report as to their findings. 

 

34 See “Regulation of Fuel and Fuel Additives: Renewable Fuel Standard Program,” 72 FR 23900, 23949-23950 

(May 1, 2007) for a detailed discussion of attest engagement requirements under RFS1. 
 

254

 We have received numerous question and comments related to how attest engagements 

apply to foreign companies and whether or not a foreign accountant may perform the required 

agreed-upon procedures. EPA will accept an attest engagement performed by a foreign 

accountant who holds an equivalent credential to an American CPA or CIA. A written 

explanation as to the foreign accountant’s qualifications and the equivalency of the credential 

must accompany the attest engagement. 

 Producers of renewable fuels, obligated parties, exporters, and any party who owns RINs 

must arrange for an annual attest engagement. The attest engagement report for any given year 

must be submitted to EPA by no later than May 31 of the following year. Section 80.1464 of the 

regulations specifies the attest engagement procedures to be followed. 

K. Production Outlook Reports 

 Under this program we are requiring the submission, starting in 2010, of annual 

production outlook reports from all domestic renewable fuel producers, foreign renewable fuel 

producers who register to generate RINs, and importers of renewable fuels. These production 

outlook reports will be similar in nature to the pre-compliance reports required under the 

Highway and Nonroad Diesel programs. These reports will contain information about existing 

and planned production capacity, long-range plans, and feedstocks and production processes to 

be used at each production facility. For expanded production capacity that is planned or 

underway at each existing facility, or new production facilities that are planned or underway, the 
 

255

progress reports will require information on: 1) Strategic planning; 2) Planning and front-end 

engineering; 3) Detailed engineering and permitting; 4) Procurement and construction; 5) 

Commissioning and startup; 6) Projected volumes; 7) Contracts currently in place (feedstocks, 

sales, delivery, etc.); and 8) Whether or not feedstocks have been purchased. The first five 

project phases are described in EPA's June 2002 Highway Diesel Progress Review report (EPA 

document number EPA420-R-02-016, located at: 

www.epa.gov/otaq/regs/hd2007/420r02016.pdf). In the proposed rule, we asked for comment on 

the first five project phases, and whether or not they were appropriate for renewable fuels 

production. We also proposed additional phases in order to provide better specificity for 

ascertaining industry status. EPA plans to use this information in order to provide annual 

summary reports regarding such planned capacity. 

 The full list of requirements for the production outlook reports is provided in the 

regulations at §80.1449. The information submitted in the reports will be used to evaluate the 

progress that the industry is making towards the renewable fuels volume goals mandated by 

EISA. They will help EPA set the annual cellulosic biofuel standard and consider whether 

waivers would be appropriate with respect to the advanced biofuel, biomass-based diesel, and 

total renewable fuel standards (see Section II.I of this preamble for more discussion on this). 

Production outlook reports will be due annually by March 31 (except that for the year 2010, the 

report will be due September 1) and each annual report must provide projected information, 

including any updated information from the previous year’s report. 
 

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 As mentioned in the preamble to the proposed rule, EPA currently receives data on 

projected flexible-fuel vehicle (FFV) sales and conversions from vehicle manufacturers. These 

are helpful in providing EPA with information regarding the potential market for renewable 

fuels. We requested comment on whether we should require the annual submission of data to 

facilitate our evaluation of the ability of the distribution system to deliver the projected volumes 

of biofuels to petroleum terminals that are needed to meet the RFS2 standards, the extent to 

which such information is already publicly available or can be purchased from a proprietary 

source, and the extent to which such publicly available or purchasable data would be sufficient 

for EPA to make its determination. We further requested comment on the parties that should be 

required to report to EPA, and data requirements. We believe that publicly available information 

on E15, E85, and other refueling facilities is sufficient for us to make a determination about the 

adequacy of such facilities to support the projected volumes that would be used to satisfy the 

RFS2 standards. Therefore, we are not finalizing such a requirement. 

 While we understand that the types of projections we request in the Outlook Reports 

could be somewhat speculative in nature, we believe that the projections will provide us with the 

most reliable information possible to inform the annual RFS standards and waiver 

considerations. Further, we believe this information will be more useful to us than other public 

information that is released in other contexts (e.g., announcements for marketing purposes). As 

mentioned above in Section II.I, we believe that we can use this information to supplement other 

available information (such as volume projections from EIA) to help set the standard for the 

following year. Specifically, it will provide more accurate information for setting the cellulosic 
 

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biofuel and biomass-based diesel standards, and any adjustments to the advanced biofuel and 

total renewable fuel standards. 

We received comments that both support and oppose the Production Outlook Reports, or 

some element of them. One commenter stated that EPA provided no reasonable explanation to 

require the information being requested for the reports; the commenter further stated that such 

information is not needed to assist parties to come into compliance. Another commenter stated 

that the renewable fuels industry cannot confidently project what will happen in 2010, or even 

2020, because there are too many unknowns, no previous history of renewable fuels mandates, 

and no sense of continued tax rebate. The commenter suggested that until the industry operates 

for a few years under the RFS2 carve-outs and the issues on the tax rebates for renewables are 

resolved, the industry cannot develop a meaningful outlook forecast. The commenter further 

suggested that EPA instead hire a consultant who can look at the big picture and provide a more 

meaningful evaluation than could the individual members of the biofuels industry. However, as 

discussed above, while these reports will have their limitations, we believe they will provide the 

best and most up to date information available for us to use in setting the standards and 

considering any waiver requests. We will of course also look to other publicly available 

information, and may consider using contractors to help out in this regard, but it cannot replace 

the need for the production outlook report data. 

 A commenter noted that this provision is similar to reports required under the diesel 

program. The commenter further stated that if the required information can be captured by 

EMTS, the commenter fully supports this requirement. However, the commenter stated that it is 
 

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opposed to some of the required elements of the reports for planned expanded or new production 

(strategic planning, planning and front-end engineering, detailed engineering and permitting, 

procurement and construction, and commissioning and start-up); these are an aspect of financial 

planning that the commenter believes EPA has no jurisdiction over and cannot derive basis from 

EISA in any form regardless of interpretation. As explained above, this information will be used 

by EPA to inform us for setting the standards on an annual basis and in responding to any waiver 

petitions. It will not be used to assess compliance with the program. The other provisions for 

registration, recordkeeping and reporting serve that purpose. 

 Another commenter stated that the reports should be required, but that EPA should not 

rely too heavily upon the data (particularly for new biofuel technologies). Some commenters 

noted that they believe that requiring Production Outlook Reports is duplicative in nature and/or 

a burden to the industry. These commenters also believe that EPA already receives such 

information through the reporting that currently exists, and that EPA could also obtain this 

information from DOE’s Energy Information Administration (EIA) and the National Biodiesel 

Board (NBB). Other commenters expressed concern over reporting such confidential and 

strategic information (even as confidential business information (CBI)), and that information out 

to 2022 seems excessive and useless; and that the reports should be limited to just domestic and 

foreign producers of renewable fuels but not importers (as they tend to import renewable fuels 

based on variable economic conditions and will not likely have the ability to reliably predict their 

future import volumes). The information that currently exists from other sources is current and 

historical information. For the purposes of setting future standards, we need to have information 

on future plans and projections. We understand that reality will always be different from the 
 

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projections, but they will still give us the best possible source of information. Furthermore, by 

having projections five years out into the future, and then obtaining new reports every year, we 

will be able to assess the trends in the data and reports to better utilize them over time. 

 Some commenters have expressed concern that the information required for Production 

Outlook Reports is not needed, won’t provide useful information because it is speculative, or 

asks for information that could be sensitive/confidential. However, we continue to believe that 

such information is essential to our annual cellulosic biofuel standard setting, and consideration 

of whether waivers should be provided for other standards. All information submitted to EPA 

will be treated as confidential business information (CBI), and if used by EPA in a regulatory 

context will only be reported out in very general terms. As with our Diesel Pre-compliance 

Reports, we fully expect that the information will be somewhat speculative in the early reports, 

and we will weight it accordingly. As the program progresses, however, information submitted 

for the reports will continue to improve. We believe that any information, whether speculative 

or concrete, will be helpful for the purposes described above. Thus we are finalizing Production 

Outlook Reports, and the required elements at §80.1449. 

L. What Acts Are Prohibited and Who Is Liable for Violations? 

 The prohibition and liability provisions under this rule are similar to those of the RFS1 

program and other fuels programs in 40 CFR Part 80. The rule identifies certain prohibited acts, 

such as a failure to acquire sufficient RINs to meet a party's RVOs, producing or importing a 

renewable fuel that is not assigned a proper RIN category (or D Code), improperly assigning 
 

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RINs to renewable fuel that was not produced with renewable biomass, failing to assign RINs to 

qualifying fuel, or creating or transferring invalid RINs. Any person subject to a prohibition is 

liable for violating that prohibition. Thus, for example, an obligated party is liable if the party 

failed to acquire sufficient RINs to meet its RVO. A party who produces or imports renewable 

fuels is liable for a failure to assign proper RINs to qualifying batches of renewable fuel 

produced or imported. Any party, including an obligated party, is liable for transferring a RIN 

that was not properly identified. 

 In addition, any person who is subject to an affirmative requirement under this program 

is liable for a failure to comply with the requirement. For example, an obligated party is liable 

for a failure to comply with the annual compliance reporting requirements. A renewable fuel 

producer or importer is liable for a failure to comply with the applicable batch reporting 

requirements. Any party subject to recordkeeping or product transfer document (PTD) 

requirements is liable for a failure to comply with these requirements. Like other EPA fuels 

programs, this rule provides that a party who causes another party to violate a prohibition or fail 

to comply with a requirement may also be found liable for the violation. 

 EPAct amended the penalty and injunction provisions in section 211(d) of the Clean 

Air Act to apply to violations of the renewable fuels requirements in section 211(o). 

Accordingly, any person who violates any prohibition or requirement of this rule is subject to 

civil penalties of up to $37,500 per day and per each individual violation, plus the amount of any 

economic benefit or savings resulting from each violation. Under this rule, a failure to acquire 
 

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sufficient RINs to meet a party's renewable fuels obligation constitutes a separate day of 

violation for each day the violation occurred during the annual averaging period. 

 As discussed above, the regulations prohibit any party from creating or transferring 

invalid RINs. These invalid RIN provisions apply regardless of the good faith belief of a party 

that the RINs are valid. These enforcement provisions are necessary to ensure the RFS2 program 

goals are not compromised by illegal conduct in the creation and transfer of RINs. 

 As in other motor vehicle fuel credit programs, the regulations address the 

consequences if an obligated party is found to have used invalid RINs to demonstrate compliance 

with its RVO. In this situation, the obligated party that used the invalid RINs will be required to 

deduct any invalid RINs from its compliance calculations. An obligated party is liable for 

violating the standard if the remaining number of valid RINs was insufficient to meet its RVO, 

and the obligated party might be subject to monetary penalties if it used invalid RINs in its 

compliance demonstration. In determining what penalty is appropriate, if any, we would 

consider a number of factors, including whether the obligated party did in fact procure sufficient 

valid RINs to cover the deficit created by the invalid RINs, and whether the purchaser was 

indeed a good faith purchaser based on an investigation of the RIN transfer. A penalty might 

include both the economic benefit of using invalid RINs and/or a gravity component. 

 Although an obligated party is liable under our proposed program for a violation if it 

used invalid RINs for compliance purposes, we would normally look first to the generator or 

seller of the invalid RINs both for payment of penalty and to procure sufficient valid RINs to 
 

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offset the invalid RINs. However, if, for example, that party was out of business, then attention 

would turn to the obligated party who would have to obtain sufficient valid RINs to offset the 

invalid RINs. 
 

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III. Other Program Changes 

 In addition to the regulatory changes we are finalizing today in response to comments 

received on the proposed rule and EISA (which are designed to implement the provisions of 

RFS2), there are a number of other changes to the RFS program that we are making. We believe 

that these changes will increase flexibility, simplify compliance, or address RIN transfer issues 

that have arisen since the start of the RFS1 program. Throughout the rulemaking process, we 

also investigated impacts on small businesses and we are finalizing provisions to address the 

impacts of the program on them. 

A. The EPA Moderated Transaction System (EMTS) 

The EPA Moderated Transaction System (EMTS) emerged as a result of our experiences 

with and lessons learned from implementing RFS1. Recognizing that the addition of significant 

volumes of renewable fuels and expansion of renewable fuel categories were adding complexity 

to an already stressed system, EMTS was introduced as a new approach for managing RINs in 

our NPRM. We received broad acceptance of the EMTS concept in the public comments as well 

as support for its expeditious implementation. This section describes the need for EMTS, 

implementation of EMTS, and an explanation of how EMTS will work. By implementing 

EMTS, we believe that we will be able to greatly reduce RIN-related errors while efficiently and 

accurately managing the universe of RINs. EMTS will save considerable time and resources for 

both industry and EPA. This is most evident considering that the system virtually eliminates 

multiple sources of administrative errors, resulting in a reduction of costs and effort expended to 
 

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correct and regenerate product transfer documents, documentation and recordkeeping, and 

resubmitting reports to EPA. Use of EMTS will result in fewer report resubmissions and easier 

reporting for industry, while leaving fewer reports to be processed by EPA. Industry will spend 

less time and effort validating the RINs they procure with greater assurance and confidence in 

the RIN market. EPA will spend less time tracking down invalid RINs and working with 

regulated parties on complex remedial actions. This is possible because EMTS removes 

management of the 38-digit RIN from the hands of the reporting community. At the same time, 

EPA and the reporting community will be working with a standardized system, reducing stresses 

and development costs on IT systems. 

We received comments suggesting that EPA remove the attest engagement requirements 

and certain recordkeeping requirements due to the use of EMTS. While we believe that EMTS 

will simplify and reduce burdens on the regulated community, it is important to point out that 

EMTS is strictly a RIN tracking and managing tool designed to facilitate reporting under the 

Renewable Fuel Standard program. Product transfer documents are the commercial documents 

used to memorialize transactions of RINs between a buyer and a seller in the market. The EMTS 

will rely on references to these documents, which can take many forms, but it is not capable of 

replacing those documents. Attest engagements are used to verify that the records required to be 

kept by regulated parties, including information retained by a regulated party as well as 

information reported to EPA such as laboratory test results, contracts between renewable 

fuel/RIN buyers and sellers, feedstock documentation, etc. is correctly maintained or reported. 

The information reported via EMTS is but a subset of the information required to be maintained 
 

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in a regulated party’s records, and both PTDs and attest engagements are necessary to ensure that 

the information collected and tracked in EMTS concurs with actual events. 

 1. Need for the EPA Moderated Transaction System

In implementing RFS1, we found that the 38-digit standardized RINs proved to be 

confusing to many parties in the distribution chain. Parties made various errors in generating and 

using RINs. For example, parties transposed digits within the RIN and incorrectly referenced 

volume numbering. Also, parties created alphanumeric RINs, despite the fact that RINs were 

supposed to consist of all numbers. 

Once an error is made within a RIN, the error propagates throughout the distribution 

system. Correcting an error can require significant time and resources and usually involves 

many steps. Not only must reports to EPA be corrected, underlying records and reports 

reflecting RIN transactions must also be located and corrected to reflect discovery of an error. 

Because reporting related to RIN transactions under RFS1 was only on a quarterly basis, a RIN 

error could exist for several months before being discovered. 

 Incorrect RINs are invalid RINs. If parties in the distribution system cannot track down 

and correct errors in a timely manner, then all downstream parties that traded the invalid RIN are 

in violation. Because RINs are the basic unit of compliance for the RFS program, it is important 

that parties have confidence when generating and using them. 
 

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 All parties in the RFS1 and the RFS2 regulated community are required to use RINs. 

Under RFS2, we foresee that regulated party community will substantially expand. Newer 

regulated parties of an already complex system necessitate EMTS. These parties include 

renewable fuel producers and importers, obligated parties, exporters, and other RIN owners; 

(typically marketers of renewable fuels and blenders). Under RFS1, all RINs were used to 

comply with a single standard. With RFS2, there are four standards. RINs must be generated to 

identify one of the fuel categories: cellulosic biofuel, cellulosic diesel, biomass-based diesel, 

advanced biofuel, and renewable fuels (e.g., corn ethanol). (For a more detailed discussion of 

RINs, see Section II.A of this preamble.) The different types of RINs will be managed in the 

EMTS. 

 

 2. Implementation of the EPA Moderated Transaction System 

We proposed that EMTS would be an opt-in for the calendar year 2010 and mandatory 

for calendar year 2011. We received many comments strongly supporting EMTS 

implementation with the start of the RFS2 program to ensure confidence and simplicity in an 

increasingly complex program. We also received comments that EMTS implementation with 

RFS2 is necessary so industry would not have to create a new system to handle RFS2 RINs for 

2010 and then move to EMTS for 2011 while still handling RFS1 RINs. Potentially, three RIN 

transaction systems would exist during transition from RFS1 to RFS2 if EMTS could not be 

implemented with the start of the RFS2 program. EPA agrees that this three system issue would 

be an undue burden to industry as it would require industry to create two systems within a 12 

month period. EMTS development started with the introduction of the NPRM, and has been in 
 

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beta testing since early November with a select group of different industry stakeholders. 

Industry feedback has been overwhelmingly strong for the implementation of EMTS with the 

start of RFS2. With this final rule, EPA decided that EMTS will start on the same date when 

RFS2 RINs are required to be generated. In addition, to ensure that parties will have enough 

time to incorporate RFS2 and EMTS requirements into private RIN tracking systems, the 

generation of RFS2 RINs will begin on July 1, 2010. Therefore, all RFS regulated parties are 

required to use EMTS starting July 1, 2010. 

RIN transactions are required to be verified and certified on a quarterly basis. EMTS will 

provide summaries for parties to verify, report, and certify transactions to EPA through the fuels 

reporting system, DCFuels. Additional information may be required to be added to the EMTS 

provided summary. This additional certification step allows parties to verification that the 

information sent to EMTS is accurate. However, parties may choose to review their data by 

checking their EMTS account at anytime. 

With EMTS, RIN transactions are required to be verified and certified on a quarterly 

basis. EMTS will provide summaries for parties to verify, report, and certify transactions to EPA 

through the fuels reporting system, DCFuels. Additional information may be required to be 

added to the EMTS provided report. This additional certification step allows parties to verify 

that the information sent to EMTS is accurate. However, parties may choose to review their data 

by checking their EMTS account at any time. 

 3. How EMTS Will Work
 

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EMTS will be a closed, EPA-moderated system that provides a mechanism for screening 

RINs and a structured environment for conducting RIN transactions. “Screening” of RINs 

means that parties can have greater confidence that the RINs they handle are genuine. Although 

screening cannot remove all human error, we believe it can remove most of it. 

We received comments opposing the 3 day time window for reporting transactions to the 

EMTS. One commenter requested 7 days from the event for sellers to report a transaction and 7 

days after that for the buyer to accept the transaction. In order for this to be a “real time” system, 

we must require that the information comes in a timely manner. One commenter requested 10 

days from the event to send information to EMTS. EPA has concluded that five days, or a 

business week, is an appropriate amount of time for both parties to receive or provide necessary 

documentation in order to interact with EMTS accurately and timely. “Real time” will be 

defined as within five (5) business days of a reportable event (e.g., generation and assignment of 

RINs, transfer of RINs). 

 Parties who use EMTS must first register with EPA in accordance with the RFS2 

registration program described in Section II.C of this preamble. Parties will also have to create 

an account (i.e., register) via EPA’s Central Data Exchange (CDX), as users will access EMTS 

via CDX. CDX is a secure and central electronic portal through which parties may submit 

compliance reports. Parties must establish an account with EMTS by July 1, 2010 or 60 days 

prior to engaging in any transaction involving RINs, whichever is later. Once registration 
 

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occurs, individual accounts will be established within EMTS and the system will enable a party 

to submit transactions based on their registration information. 

In EMTS, the screening and assignment of RINs will be made at the logical point, i.e., 

the point when RINs are generated through production or importation of renewable fuel. A 

renewable producer will electronically submit, in “real time,” a volume of renewable fuel 

produced or imported, as well as a number of the RINs generated and assigned. EMTS will 

automatically screen each batch and either reject the information or allow RINs created in the 

RIN generator's account as one of the five types of RINs. 

We received comments supporting the RFS1 approach that allows producers and 

importers to generate RINs at the renewable fuel point of sale. EPA realizes that this is an 

industry practice and this flexibility will still be allowed for RIN generators, but only if applied 

consistently. 

After RINs have entered the system, parties may then trade them based on agreements 

outside of EMTS. One major advantage of EMTS, over the RFS1 system, is that the system will 

simplify trading by allowing RINs to be traded generically. Only some specifying information 

will be needed to trade RINs, such as RIN quantity, fuel type, RIN assignment, RIN year, RIN 

price or price per gallon. The unique identification of the RIN will exist within EMTS, but 

parties engaging in RIN transactions will no longer have to worry about incorrectly recording or 

using 38-digit RIN numbers. The actual items of transactional information covered under RFS2 
 

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are very similar to those reported under RFS1. The RIN price is one of the new pieces of 

transactional information required to be submitted under RFS2. 

We received several adverse comments strongly opposing the collection of price 

information due to Confidential Business Information (CBI) concerns, other services being able 

to provide this information, marketplace delays and undue stress on the EMTS from 

disagreements in RIN price. We received one comment strongly supporting EPA collecting this 

information. EPA decided that the price information has great programmatic value because it 

will help us anticipate and appropriately react to market disruptions and other compliance 

challenges, assess and develop responses to potential waivers, and assist in setting future 

renewable fuel standards. In addition, EPA decided that highly summarized price information 

(e.g., the average price of RINs traded nationwide) may be valuable to regulated parties, as well, 

and may help them to anticipate and avoid market disruptions. Also, EPA will not require the 

matching of the exact RIN price to alleviate the burden of resubmission due to price mistakes. 

However, the price information must be accurate and rounded to the nearest cent (US Dollar) at 

the time of sending the transactional information to EMTS. 

 

We received one comment requesting publication of security precautions taken by EPA 

to protect EMTS from attacks. EPA cannot provide security information to the public because 

providing such information may create security vulnerabilities. However, EMTS will be 

compliant with the appropriate security requirements for all federal agency information 

technology systems. 
 

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Also as with RFS1, there is no “good faith” provision to RIN ownership. An underlying 

principle of RIN ownership is still one of "buyer beware" and RINs may be prohibited from use 

at any time if they are found to be invalid. Because of the “buyer beware” aspect, we will offer 

the option for a buyer to accept or reject RINs from specific RIN generators or from classes of 

RIN generators. 

 4. A Sample EMTS Transaction 

This sample illustrates how two parties may trade RINs in EMTS: 

1) Seller logs into EMTS and posts a sale of 10,000 RINs to Buyer at X price. For 

this example, assume the RINs were generated in 2010 and were assigned to 

10,000 gallons of “Renewable fuel (D=6)”. Seller’s RIN account for “Renewable 

fuel (D=6)” is put into a “pending” status of 10,000 with the posting of the sale to 

Buyer. Buyer receives automatic notification of the pending transaction. 

2) Buyer logs into EMTS. Buyer sees the sale transaction pending. Assuming it is 

correct, Buyer accepts it. Upon acceptance, Buyer’s RIN account for “Renewable 

fuel (D=6)” RINs is automatically increased by 10,000 2010 assigned RINs sold 

at X price. 

3) After Seller has posted the sale and Buyer has accepted it, EMTS automatically 

notifies both Buyer and Seller that the transaction has been fully completed. 
 

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Under EMTS, the seller will always have to initiate any transaction. The specific amount 

of RINs are put into a pending status when the seller posts the sale. The buyer must confirm the 

sale in order to have the RINs transferred to the buyer’s account. Transactions will always be 

limited to available RINs. Notification will automatically be sent to both the buyer and the 

seller upon completion of the transaction. EPA considers any sale or transfer as complete upon 

acknowledgement by the buyer. We will also allow buyers to submit their acknowledgement 

prior to a seller initiating the transaction. However, these buy transactions will not initiate any 

RINs being put into a pending status from a seller’s account. Instead, the buy transactions will 

be queued and checked periodically to see if a “sell” transaction was posted by the seller. If a 

buy is posted without a matching sell transaction, then the seller will be notified that a buy 

transaction is pending. Both buy and sell transactions must be matched within a set number of 

days from the submission date or they will expire. Transactions will expire 7 days after the 

submission of the file. Since both parties are required to submit information within 5 days, we 

allow the full 5 days to expire plus 2 days in the case of late submissions. 

In summary, the advantage to implementing EMTS is that parties may engage in RIN 

transactions with a high degree of confidence, errors will be virtually eliminated, and everyone 

engaging in RIN transactions will have a simplified environment in which to work, which should 

minimize the level of resources needed for implementation. 

B. Upward Delegation of RIN-Separating Responsibilities 
 

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 Since the start of the RFS program on September 1, 2007, there have been a number of 

instances in which a party who receives RINs with a volume of renewable fuel is required to 

either separate or retire those RINs, but views the recordkeeping and reporting requirements 

under the RFS program as an unnecessary burden. Such circumstances typically might involve a 

renewable fuel blender, a party that uses renewable fuel in its neat form, or a party that uses 

renewable fuel in a non-highway application and is therefore required to retire the RINs (under 

RFS1) associated with the volume. In some of these cases, the affected party may purchase 

and/or use only small volumes of renewable fuel and, absent the RFS program, would be subject 

to few (if any other) EPA regulations governing fuels. 

 This situation will become more prevalent with the RFS2 rule, as EISA added diesel fuel 

to the RFS program. With the RFS1 rule, small blenders (generally farmers and other parties 

that use nonroad diesel fuel) blending small amounts of biodiesel were not covered under the 

rule as EPAct mandated renewable fuel blending for highway gasoline only. EISA mandates 

certain amounts of renewable fuels to be blended into all transportation fuels—which includes 

highway and nonroad diesel fuel. Thus, parties that were not regulated under the RFS1 rule who 

only blend a small amount of renewable fuel (and, as mentioned above, are generally not subject 

to EPA fuels regulations) will now be regulated by the RFS program. 

 Consequently, we believe it is appropriate, and thus we are finalizing as proposed, to 

permit blenders who only blend a small amount of renewable fuel to allow the party directly 

upstream to separate RINs on their behalf. Such a provision is consistent with the fact that the 

RFS program already allows marketers of renewable fuels to assign more RINs to some of their 
 

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sold product and no RINs to the rest of their sold product. We believe that this provision will 

eliminate undue burden on small parties who would otherwise not be regulated by this program. 

This provision is solely for the case of blenders who blend and trade less than 125,000 total 

gallons of renewable fuel per year (i.e., a company that blends 100,000 gallons and trades 

another 100,000 gallons would not be able to use this provision) and is available to any blender 

who must separate RINs from a volume of renewable fuel under §80.1429(b)(2). 

We requested comment in the NPRM on this concept, the 125,000 gallon threshold, and 

appropriate documentation to authorize this upward delegation. In general, those that 

commented on this provision support the idea of upward delegation for small blenders, though 

one commenter stated that EPA should not allow small entities to delegate their RIN-related 

responsibilities upward. Those commenters that support the upward delegation provision stated 

that it should be limited to small blenders only and should only be for delegating to the party 

directly upstream. A few commenters stated that they believe the 125,000 gallon threshold is 

appropriate; while others commented that it should be higher. We believe that the 125,000 

gallon limit strikes the correct balance between providing relief to small blenders, while still 

ensuring that non-obligated parties cannot unduly influence the RIN market. 

We did not receive any comments on appropriate documentation, however a couple 

commenters suggested that we retain the proposed annual authorization between the blender and 

the party directly upstream, as well as allowing a small blender to enter into arrangements with 

multiple suppliers on a transaction-by-transaction basis. Please see Chapter 5 of the Summary 
 

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and Analysis of Comments Document for more discussion on the comments received and our 

responses to those comments. 

We are also finalizing, as stated in the preamble to the proposed rule, that for upstream 

delegation, both parties must sign a quarterly written statement (which must be included with the 

reporting party’s reports) authorizing the upward delegation. Copies of these statements must be 

retained as records by both parties. The supplier would then be allowed to retain ownership of 

RINs assigned to a volume of renewable fuel when that volume is transferred, under the 

condition that the RINs be separated or retired concurrently with the transfer of the volume. This 

statement would apply to all volumes of renewable fuel transferred between the two parties. 

Thus, the two parties would enter into a contract stating that the supplier has RIN-separation 

responsibilities for all transferred volumes between the two parties, and no additional 

permissions from the small blender would be needed for any volumes transferred. A blender 

may enter into such an agreement with as many parties as they wish. 

C. Small Producer Exemption 

 Under the RFS1 rule, parties who produce or import less than 10,000 gallons of 

renewable fuel in a year are not required to generate RINs for that volume, and are not required 

to register with the EPA if they do not take ownership of RINs generated by other parties. These 

producers and importers are also exempt from registration, reporting, recordkeeping, and attest 

engagement requirements. In the preamble to the proposed rule, we requested comment on 

whether or not this 10,000 gallon threshold was appropriate. One commenter suggested that we 
 

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retain the 10,000 gallon threshold as-is. Another commenter supported the concept of less 

burdensome requirements for small producers, but suggested that these entities should, at a 

minimum, be required to generate RINs for all qualifying renewables. We are maintaining this 

exemption under the RFS2 rule for parties who produce or import less than 10,000 gallons of 

renewable fuel per year. 

 In addition to the permanent exemption for those producers and importers who produce 

or import less than 10,000 gallons of renewable fuel per year, we are also finalizing a temporary 

exemption for renewable fuel producers who produce less than 125,000 gallons of renewable 

fuel each year from new production facilities. These producers are not required to generate and 

assign RINs to batches of renewable fuel for a period of up to three years, beginning with the 

calendar year in which the production facility produces its first gallon of renewable fuel. Such 

producers are also exempt from registration, reporting, recordkeeping, and attest engagement 

requirements as long as they do not own RINs or voluntarily generate and assign RINs. This 

provision is intended to allow pilot and demonstration plants of new renewable fuel technologies 

to focus on developing the technology and obtaining financing during these early stages of their 

development without having to comply with the RFS2 regulations. 

D. 20% Rollover Cap 

 EISA does not change the language in CAA section 211(o)(5) stating that renewable fuel 

credits must be valid for showing compliance for 12 months as of the date of generation. As 

discussed in the RFS1 final rulemaking, we interpreted the statute such that credits would represent 
 

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renewable fuel volumes in excess of what an obligated party needs to meet their annual compliance 

obligation. Given that the renewable fuel standard is an annual standard, obligated parties determine 

compliance shortly after the end of the year, and credits would be identified at that time. In the 

context of our RIN-based program, we have accomplished the statute's objective by allowing RINs 

to be used to show compliance for the year in which the renewable fuel was produced and its 

associated RIN first generated, or for the following year. RINs not used for compliance purposes in 

the year in which they were generated will by definition be in excess of the RINs needed by 

obligated parties in that year, making excess RINs equivalent to the credits referred to in section 

211(o)(5). Excess RINs are valid for compliance purposes in the year following the one in which 

they initially came into existence. RINs not used within their valid life will thereafter cease to be 

valid for compliance purposes. 

 In the RFS1 final rulemaking, we also discussed the potential "rollover" of excess RINs over 

multiple years. This can occur in situations wherein the total number of RINs generated each year 

for a number of years in a row exceeds the number of RINs required under the RFS program for 

those years. The excess RINs generated in one year could be used to show compliance in the next 

year, leading to the generation of new excess RINs in the next year, causing the total number of 

excess RINs in the market to accumulate over multiple years despite the limit on RIN life. When 

renewable fuel volumes are being produced that exceed the RFS2 standards, the rollover issue could 

undermine the ability of a limit on credit life to guarantee an ongoing market for renewable fuels. 

 To implement EISA's restriction on the life of credits and address the rollover issue, the 

RFS1 final rulemaking implemented a 20% cap on the amount of an obligated party's RVO that can 
 

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be met using previous-year RINs. Thus each obligated party is required to use current-year RINs to 

meet at least 80% of its RVO, with a maximum of 20% being derived from previous-year RINs. 

Any previous-year RINs that an obligated party may have that are in excess of the 20% cap can be 

traded to other obligated parties that need them. If the previous-year RINs in excess of the 20% cap 

are not used by any obligated party for compliance, they will thereafter cease to be valid for 

compliance purposes. 

 As described in the NPRM, EISA does not modify the statutory provisions regarding credit 

life, and the volume changes by EISA also do not change at least the possibility of large rollovers of 

RINs for individual obligated parties. As a result we proposed to maintain the regulatory 

requirement for a 20% rollover cap under the new RFS2 program, and to apply this cap separately to 

all four RVOs under RFS2. However, we took comment on changing the level of the cap to some 

alternative value lower or higher than 20%. 

 A lower cap could provide a greater incentive for parties with excess RINs to sell them rather 

than hold onto them, increasing the availability of RINs for parties that need them for compliance 

purposes. But a lower cap would also reduce flexibility for obligated parties attempting to minimize 

the costs of compliance with increasing annual volume requirements, particularly if there are 

concerns that the RIN market may be tighter in the future than it is currently. 

 Conversely, the increasing annual volume requirements in EISA make it less likely that 

renewable fuel producers will overcomply, and as a result it is less likely that there will be an excess 

of RINs in the market. Under these circumstances, there is little opportunity for RINs to build up in 
 

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the market, and the rollover cap would have less of an impact on the market as a whole. Thus a 

higher cap might be warranted. However, while a higher cap would create greater flexibility for 

some obligated parties, it could also create disruptions in the RIN market as parties with excess RINs 

would have a greater opportunity to hold onto them rather than sell them. Parties without direct 

access to RINs through the purchase and blending of renewable fuels would be placed at a 

competitive disadvantage in comparison to parties with excess RINs. In the extreme, removal of the 

cap entirely would allow obligated parties to roll over up to one year's worth of their obligations 

indefinitely. 

 In general, commenters on the NPRM reiterated the positions that they raised during 

development of the RFS1 program. While one renewable fuel producer requested that the rollover 

cap be left at 20%, most producers requested that the rollover cap be reduced to 0%, such that 

compliance with the standards applicable in a given year could only be demonstrated using RINs 

generated in that year. In contrast, refiners requested that the rollover cap be either eliminated, such 

that any number of previous year RINs could be used for current year compliance, or at least raised 

to 40 or 50 percent. Small refiners requested that the cap be raised for small refiners only to 

accommodate the competitive disadvantage with respect to the RIN market that they believe they 

experience in comparison to larger refiners. 

 Based on the comments received, we believe that the 20% level continues to provide the 

appropriate balance between, on the one hand, allowing legitimate RIN carryovers and protecting 

against potential supply shortfalls that could limit the availability of RINs, and on the other hand 
 

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ensuring an annual demand for renewable fuels as envisioned by EISA. Therefore, we are 

continuing the 20% rollover cap for obligated parties for the RFS program. 

E. Small Refinery and Small Refiner Flexibilities 

 This section discusses flexibilities for small refineries and small refiners for the RFS2 

rule. As explained in the discussion of our compliance with the Regulatory Flexibility Act below 

in Section XI.C and in the Final Regulatory Flexibility Analysis in Chapter 7 of the RIA, we 

considered the impacts of the RFS2 regulations on small businesses (small refiners). Most of our 

analysis of small business impacts was performed as a part of the work of the Small Business 

Advocacy Review Panel (SBAR Panel, or “the Panel”) convened by EPA for this rule, pursuant 

to the Regulatory Flexibility Act as amended by the Small Business Regulatory Enforcement 

Fairness Act of 1996 (SBREFA). The Final Report of the Panel is available in the rulemaking 

docket. For the SBREFA process, we conducted outreach, fact-finding, and analysis of the 

potential impacts of our regulations on small business refiners. 

1. Background- RFS1

a. Small Refinery Exemption 

CAA section 211(o)(9), enacted as part of EPAct, provides a temporary exemption to 

small refineries (those refineries with a crude throughput of no more than 75,000 barrels of crude 
 

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per day, as defined in section 211(o)(1)(K)) through December 31, 201035. Accordingly, the 

RFS1 program regulations exempt gasoline produced by small refineries from the renewable 

fuels standard (unless the exemption was waived), see 40 CFR 80.1141. EISA did not alter the 

small refinery exemption in any way. 

b. Small Refiner Exemption 

As mentioned above, EPAct granted a temporary exemption from the RFS program to 

small refineries through December 31, 2010. In the RFS1 final rule, we exercised our discretion 

under section 211(o)(3)(B) and extended this temporary exemption to the few remaining small 

refiners that met the Small Business Administration’s (SBA) definition of a small business 

(1,500 employees or less company-wide) but did not meet the EPAct small refinery definition as 

noted above. 

2. Statutory Options for Extending Relief

There are two provisions in section 211(o)(9) that allow for an extension of the temporary 

exemption for small refineries beyond December 31, 2010. 

One provision involves a study by the Department of Energy (DOE) concerning whether 

compliance with the renewable fuel requirements would impose disproportionate economic 

hardship on small refineries, and would grant an automatic extension of at least two years for 

small refineries that DOE determines would be subject to such disproportionate hardship (per 

 

35 Small refineries are also allowed to waive this exemption. 
 

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section 211(o)(9)(A)(ii)). If the DOE study determines that such hardship exists, then section 

211(o)(9)(A)(ii) (which was retained in EISA) provides that EPA shall extend the exemption for 

a period of at least two years. 

The second provision, at section 211(o)(9)(B), authorizes EPA to grant an extension for a 

small refinery based upon disproportionate economic hardship, on a case-by-case basis. A small 

refinery may, at any time, petition EPA for an extension of the small refinery exemption on the 

basis of disproportionate economic hardship. EPA is to consult with DOE and consider the 

findings of the DOE small refinery study in evaluating such petitions. These petitions may be 

filed at any time, and EPA has discretion to determine the length of any exemption that may be 

granted in response. 

3. The DOE Study/DOE Study Results

As discussed above, EPAct required that DOE perform a study by December 31, 2008 on 

the impact of the renewable fuel requirements on small refineries (section 211(o)(9)(A)(ii)(I)), 

and whether or not the requirements would impose a disproportionate economic hardship on 

these refineries. In the small refinery study, “EPACT 2005 Section 1501 Small Refineries 

Exemption Study”, DOE’s finding was that there is no reason to believe that any small refinery 

would be disproportionately harmed by inclusion in the proposed RFS2 program. This finding 

was based on the fact that there appeared to be no shortage of RINs available under RFS1, and 

EISA has provided flexibility through waiver authority (per section 211(o)(7)). Further, in the 

case of the cellulosic biofuel standard, cellulosic biofuel allowances can be provided from EPA 
 

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at prices established in EISA (see regulation section 80.1456). DOE thus determined that small 

refineries would not be subject to disproportionate economic hardship under the proposed RFS2 

program, and that the exemption should not, on the basis of the study, be extended for small 

refineries (including those small refiners who own refineries meeting the small refinery 

definition) beyond December 31, 2010. DOE noted in the study that, if circumstances were to 

change and/or the RIN market were to become non-competitive or illiquid, individual small 

refineries have the ability to petition EPA for an extension of their small refinery exemption 

(pursuant to Section 211(o)(9)(B)). 

4. Ability to Grant Relief Beyond 211(o)(9)

The SBREFA panel made a number of recommendations for regulatory relief and 

additional flexibility for small refineries and small refiners. These are described in the Final 

Panel Report (located in the rulemaking docket), and summarized below. During the 

development of this final rule, we again evaluated the various options recommended by the Panel 

and also comments on the proposed rule. We also consulted the small refinery study prepared by 

DOE. 

As described in the Final Panel Report, EPA early-on identified limitations on its 

authority to issue additional flexibility and exemptions to small refineries. In section 211(o)(9) 

Congress specifically addressed the issue of an extension of time for compliance for small 

refineries, temporarily exempting them from renewable fuel obligations through December 31, 

2010. As discussed above, the statute also includes two specific provisions describing the basis 
 

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and manner in which further extensions of this exemption can be provided. In the RFS1 

rulemaking, EPA considered whether it should provide additional relief to the limited number of 

small refiners who were not covered by the small refinery provision, by providing them a 

temporary exemption consistent with that provided by Congress for small refineries. EPA 

exercised its discretion under section 211(o)(3) and provided such relief. Thus, in RFS1, EPA 

did not modify the relief provided by Congress for small refineries, but did exercise its discretion 

to provide the same relief specified by statute to a few additional parties. 

In RFS2 we are faced with a different issue—the extent to which EPA should provide 

additional relief to small refineries beyond the relief specified by statute, and whether it should 

provide such further relief to small refiners as well. There is considerable overlap between 

entities that are small refineries and those that are small refiners. Providing additional relief just 

to small refiners would, therefore, also extend additional relief to at least a number of small 

refineries. Congress spoke directly to the relief that EPA may provide for small refineries, 

including those small refineries operated by small refiners, and limited that relief to a blanket 

exemption through December 31, 2010, with additional extensions if the criteria specified by 

Congress are met. EPA believes that an additional or different extension, relying on a more 

general provision in section 211(o)(3) would be inconsistent with Congressional intent. Further, 

we do not believe that the statute allows us the discretion to give relief to small refiners only—as 

this would result in a subset of small refineries (those that also qualify as small refiners) 

receiving relief that is greater than the relief already given to all small refineries under EISA. 
 

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EPA also notes that the criteria specified by statute for providing a further compliance 

extension to small refineries is a demonstration of “disproportionate economic hardship.” The 

statute provides that such hardship can be identified through the DOE study, or in individual 

petitions submitted to the Agency. However, the DOE study has concluded that no 

disproportionate economic hardship exists, at least under current conditions and for the 

foreseeable future under RFS2. Therefore, absent further information that may be provided 

through the petition process, there does not currently appear to be a basis under the statute for 

granting further compliance extensions to small refineries. If DOE revises its study and comes to 

a different conclusion, EPA can revisit this issue. 

5. Congress-Requested Revised DOE Study

In their written comments, as well as in discussions we had with them on the proposed 

rule, small refiners indicated that they did not believe that EPA should rely on the results of the 

DOE small refinery study to inform any decisions on small refiner provisions. Small refiners 

generally commented that they believe that the study was flawed and that the conclusions of the 

study were reached without adequate analysis of, or outreach with, small refineries (as the 

majority of the small refiners own refineries that meet the Congressional small refinery 

definition). One commenter stated that such a limited investigation into the impact on small 

refineries could not have resulted in any in-depth analysis on the economic impacts of the 

program on these entities. Another commenter stated that it believes that DOE should be 

directed to reopen and reassess the small refinery study be June 30, 2010, as suggested by the 

Senate Appropriations Committee. 
 

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We are aware that there have been expressions of concern from Congress regarding the 

DOE Study. Specifically, in Senate Report 111-45, the Senate Appropriations Committee 

“directed [DOE] to reopen and reassess the Small Refineries Exemption Study by June 30, 

2010,” noting a number of factors that the Committee intended that DOE consider in the revised 

study. The Final Conference Report 111-278 to the Energy & Water Development 

Appropriations Act (H.R. 3183), referenced the language in the Senate Report, noting that the 

conferees “support the study requested by the Senate on RFS and expect the Department to 

undertake the requested economic review.” At the present time, however, the DOE study has not 

been revised. If DOE prepares a revised study and the revised study finds that there is a 

disproportionate economic impact, we will revisit the exemption extension at that point in 

accordance with section 211(o)(9)(A)(ii). 

6. What We’re Finalizing

a. Small Refinery and Small Refiner Temporary Exemptions 

As mentioned above, the RFS1 program regulations exempt gasoline produced by small 

refineries from the renewable fuels standard through December 31, 2010 (at 40 CFR 80.1141), 

per EPAct. As EISA did not alter the small refinery exemption in any way, we are retaining this 

small refinery temporary exemption in the RFS2 program without change (except for the fact 

that all transportation fuel produced by small refineries will be exempt, as EISA also covers 

diesel and nonroad fuels). 
 

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Likewise, as we extended under RFS1 the small refinery temporary exemption to the few 

remaining small refiners that met the Small Business Administration’s (SBA) definition of a 

small business (1,500 employees or less company-wide), we are also finalizing a continuation of 

the small refiner temporary exemption through December 31, 2010. 

 b. Case-by-Case Hardship for Small Refineries and Small Refiners 

As discussed in Section III.E.2, EPAct also authorizes EPA to grant an extension for a 

small refinery based upon disproportionate economic hardship, on a case-by-case basis. We 

believe that these avenues of relief can and should be fully explored by small refiners who are 

covered by the small refinery provision. In addition, we believe that it is appropriate to allow 

petitions to EPA for an extension of the temporary exemption based on disproportionate 

economic hardship for those small refiners who are not covered by the small refinery provision 

(again, per our discretion under section 211(o)(3)(B)); this would ensure that all small refiners 

have the same relief available to them as small refineries do. Thus, we are finalizing a hardship 

provision for small refineries in the RFS2 program, that any small refinery may apply for a caseby-case hardship at any time on the basis of disproportionate economic hardship per CAA 

section 211(o)(9)(B). We are also finalizing a case-by-case hardship provision for those small 

refiners that do not operate small refineries using our discretion under CAA section 

211(o)(3)(B). This provision will allow those small refiners that do not operate small refineries 

to apply for the same kind of hardship extension as a small refinery. In evaluating applications 

for this hardship provision EPA will take into consideration information gathered from annual 
 

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reports and RIN system progress updates, as recommended by the SBAR Panel, as well as 

information provided by the petitioner and through consultation with DOE. 

 c. Program Review 

 During the SBREFA process, the small refiner Small Entity Representatives (SERs) also 

requested that EPA perform an annual program review, to begin one year before small refiners 

are required to comply with the program, to provide information on RIN system progress. As 

mentioned in the preamble to the proposed rule, we were concerned that such a review could 

lead to some redundancy with the notice of the applicable RFS standards that EPA will publish 

in the Federal Register annually, and this annual process will inevitably include an evaluation of 

the projected availability of renewable fuels. Nevertheless, some Panel members commented 

that they believe a program review could be beneficial to small entities in providing them some 

insight to the RFS program’s progress and alleviate some uncertainty regarding the RIN system. 

As we will be publishing a Federal Register notice annually, the Panel recommended, and we 

proposed, that an update of RIN system progress (e.g., RIN trading, publicly-available 

information on RIN availability, etc.) be included in this annual notice. 

 Based on comments received on the proposed rule, we believe that such information 

could be helpful to industry, especially to small businesses to help aid the proper functioning of 

the RIN market, especially in the first years of the program. However, during the development 

of the final rule, it became evident that there could be instances where we would want to report 

out RIN system information on a more frequent basis than just once a year. Thus we are 
 

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finalizing that we will periodically report out elements of RIN system progress; but such 

information will be reported via other means (e.g., the RFS website 

(www.epa.gov/otaq/renewablefuels/index.htm), EMTS homepage, etc.). 

7. Other Flexibilities Considered for Small Refiners

During the SBREFA process, and in their comments on the proposed rule, small refiners 

informed us that they would need to rely heavily on RINs and/or make capital improvements to 

comply with the RFS2 requirements. These refiners raised concerns about the RIN program 

itself, uncertainty (with the required renewable fuel volumes, RIN availability, and costs), the 

desire for an annual RIN system review, and the difficulty in raising capital and competing for 

engineering resources to make capital improvements. 

The Panel recommended that EPA consider the issues raised by the small refiner SERs 

and discussions had by the Panel itself, and that EPA should consider comments on flexibility 

alternatives that would help to mitigate negative impacts on small businesses to the extent 

allowable by the Clean Air Act. A summary of further recommendations of the Panel are 

discussed in Section XI.C of this preamble, and a full discussion of the regulatory alternatives 

discussed and recommended by the Panel can be found in the SBREFA Final Panel Report. 

Also, a complete discussion of comments received on the proposed rule regarding small refinery 

and small refiner flexibilities can be found in Chapter 5 of the Summary and Analysis of 

Comments document. 
 

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a. Extensions of the RFS1 Temporary Exemption for Small Refiners 

As previously stated, the RFS1 program regulations provide small refiners who operate 

small refineries, as well as those small refiners who do not operate small refineries, with a 

temporary exemption from the standards through December 31, 2010. This provided an 

exemption for small refineries (and small refiners) for the first five years of the RFS program. 

Small refiner SERs suggested that an additional temporary exemption for the RFS2 program 

would be beneficial to them in meeting the RFS standards as increased by Congress in EISA. 

The Panel recommended that EPA propose a delay in the effective date of the standards until 

2014 (for a total of eight years) for small entities, to the extent allowed by the statute. 

During the development of both the Final Panel Report and the proposed rule, we 

evaluated various options for small refiners, including an additional temporary exemption for 

small refiners from the required RFS2 standards. As discussed above, we concluded that we do 

not have the statutory authority to provide such extensions through means other than those 

specified in the statute. Thus, further extensions will be as a result of any revised DOE study, or 

in response to a petition, pursuant to the authorities specified in section 211(o)(9). 

We proposed to continue the temporary exemption finalized in RFS1—through 

December 31, 2010. Commenters that oppose an extension of the temporary exemption 

generally stated that an extension is not warranted, and some commenters expressed concerns 

about allowing provisions for small refiners. One commenter also stated that it believes that the 

small refinery exemption should not be extended and that the small refiner exemption should be 
 

291

eliminated completely. Two commenters supported the continuation of the exemption through 

December 31, 2010 only, and one stated that it does not support an extension as it believes that 

all parties have been well aware of the passage of EISA and small refineries and small refiners 

should have been striving to achieve compliance by the end of 2010. Two commenters also 

expressed views that the exemption should not have been offered to small refiners in RFS1 as 

this was not provided by EPAct, and that an extension of the exemption should not be finalized 

for small refineries at all. The commenters further commented that an economic hardship 

provision was included in EPAct, and any exemption extension should be limited to such cases, 

and only to the specific small refinery (not small refiner) that has petitioned for such an 

extension. 

 Commenters supporting an extension of the exemption commented that they believe that 

the statutes (EPAct and EISA) do not prohibit EPA from providing relief to regulated small 

entities on which the rule will have a significant economic impact, and that such a delay could 

lessen the burden on these entities. One commenter stated that it believes EPA denied or ignored 

much of the relief recommended by the Panel in the proposal. Another commenter stated that it 

believes EPA’s concerns regarding the legal authority are unsustainable considering EPA’s past 

exercises of discretion under the RFS1 program, and with the discretion afforded to EPA under 

section 211(o) of the CAA. Some commenters requested a delay until 2014 for small refiners. 

One additional commenter expressed support for an extension of the small refinery exemption 

only, and that these small refineries should be granted a permanent exemption. 
 

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During the development of this final rule, we again evaluated the various options 

recommended by the Panel, the legality of offering an extension of the exemption to small 

refiners only, and also comments on the proposed rule. Specifically in the case of an extension 

of the exemption for small refiners, we also consulted the small refinery study prepared by DOE, 

as the statute directs us to use this as a basis for providing an additional two year exemption. As 

discussed above in Sections III.E.4 and 5, we do not believe that we can provide an extension of 

the exemption considering the outcome of the DOE small refinery study, which did not find that 

there was a disproportionate economic hardship. Further, we do not believe that the statute 

allows us the discretion to give relief to a subset of small refineries (those that also qualify as 

small refiners) that is greater than the relief already given to all small refineries under EPAct. 

However, it is important to recognize that the 211(o)(9) small refinery provision does allow for 

extensions beyond December 31, 2010, as discussed above in Section III.E.2. Thus, refiners may 

apply for individual hardship relief. 

b. Phase-in 

The small refiner SERs suggested that a phase-in of the obligations applicable to small 

refiners would be beneficial for compliance, such that small refiners would comply by gradually 

meeting the standards on an incremental basis over a period of time, after which point they 

would comply fully with the RFS2 standards. However we stated in the NPRM that we had 

serious concerns about our legal authority to provide such a phase-in. CAA section 211(o)(3)(B) 

states that the renewable fuel obligation shall “consist of a single applicable percentage that 

applies to all categories of persons specified” as obligated parties. A phase-in approach would 
 

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essentially result in different applicable percentages being applied to different obligated parties. 

Further, such a phase-in approach would provide more relief to small refineries operated by 

small refiners than that provided under the statutory small refinery provisions. 

Some commenters stated that they believe that EPA has the ability to consider a phase-in 

of the standards for small refiners. One commenter suggested that a temporary phase-in could 

help lessen the burden of regulation on small entities and promote compliance. Another 

commenter stated that it believes EPA’s legal concerns regarding a phase-in are unsustainable 

considering EPA’s past exercises of discretion under the RFS1 program and with the discretion 

afforded to EPA under section 211(o) of the CAA. 

After considering the comments on this issue, EPA continues to believe that allowing a 

phase-in of regulatory requirements for small refineries and/or small refiners would be 

inconsistent with the statute, for the reasons mentioned above. Any individual entities that are 

experiencing hardship that could justify a phase-in of the standards have the ability to petition 

EPA for individualized relief. Therefore we are not including a phase-in of standards for small 

refiners in today’s rule. 

c. RIN-Related Flexibilities 

The small refiner SERs requested that the RFS2 rule contain provisions for small refiners 

related to the RIN system, such as flexibilities in the RIN rollover cap percentage and allowing 

small refiners only to use RINs interchangeably. In the RFS1 rule, up to 20% of a previous 
 

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year’s RINs may be “rolled over” and used for compliance in the following year. In the 

preamble to the proposed rule, we discussed the concept of allowing for flexibilities in the 

rollover cap, such as a higher RIN rollover cap for small refiners for some period of time or for 

at least some of the four standards. As the rollover cap is the means through which we are 

implementing the limited credit lifetime provisions in section 211(o) of the CAA, and therefore 

cannot simply be eliminated, we requested comment on the concept of increasing the RIN 

rollover cap percentage for small refiners and an appropriate level of that percentage. In 

response to the Panel’s recommendation, we also sought comment on allowing small refiners to 

use the four types of RINs interchangeably. 

In their comments on the proposed rule, one small refiner commented that, in regards to 

small refiners’ concerns about RIN pricing and availability, there is no mechanism in the rule to 

address the possibility that the RIN market will not be viable. The commenter further suggested 

that more “durable” RINs are needed for small refiners that can be carried over from year to 

year, to alleviate some of the potentially market volatility for renewable fuels. Another 

commenter suggested that RINs should be interchangeable for small refiners, or alternatively, 

some mechanism should be implemented to ensure that RIN prices are affordable for small 

refiners. Further, with regard to interchangeable RINs, one commenter stated that small refiners 

do not have the staff or systems to manage and account for four different categories of RINs and 

rural small refiners will suffer economic hardship and disadvantage because of the unavailability 

of biofuels. The commenter also requested an increase in the rollover cap to 50% for small 

refiners. 
 

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We are not finalizing additional RIN-related flexibilities for small refiners in today’s 

action. As highlighted in the NPRM, we continue to believe that the concept of interchangeable 

RINs for small refiners only fails to require the four different standards mandated by Congress 

(e.g., conventional biofuel could not be used instead of cellulosic biofuel or biomass-based 

diesel), and is not consistent with section 211(o) of the Clean Air Act. Essentially, it would 

circumvent the explicit direction of Congress in EISA to require that the four RFS2 standards be 

met separately. Further, given the findings from the DOE study that small refineries (and thus, 

most small refiners) do not currently face disproportionate economic hardship, and are not 

expected to do so as RFS2 is implemented, we do not believe that a basis exists to justify 

providing small refiners with a larger rollover cap than other regulated entities. Thus, small 

refiners will be held to the same RIN rollover cap as other obligated parties. 

 

F. Retail Dispenser Labeling for Gasoline with Greater than 10 Percent Ethanol 

We proposed labeling requirements for fuel dispensers that handle greater than 10 

volume percent ethanol blends which included the following text: For use only in flexible-fuel 

vehicles, May damage non-flexible-fuel vehicles, Federal law prohibits use in non-flexible-fuel 

vehicles. This proposal was primarily meant to help address concerns about the potential 

misfueling of non-flex-fuel vehicles with E85, in light of the anticipated increase in E85 sales 

volumes in response to the RFS2 program. All ethanol blends above 10 volume percent were 

included due to the increasing industry focus on ethanol blender pumps that are designed to 

dispense a variety of ethanol blends (e.g., E30, and E40) for use in flex-fuel vehicles. 
 

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Commenters stated that EPA should undertake additional analysis of the potential 

impacts from misfueling and what preventative measures might be appropriate before finalizing 

labeling requirements for >E10 blends. They also stated that EPA should coordinate any such 

labeling provisions with those already in place by the Federal Trade Commission. EPA is also 

currently evaluating a petition to allow the use of up to 15 volume percent ethanol in non-flex 

fuel vehicles. One potential result of this evaluation might be for EPA to grant a partial waiver 

that is applicable only for a subset of the current vehicle population. Under such an approach, a 

label for E15 fuel dispensers would be needed that identifies what vehicles are approved to use 

E15. 

Based on the public comments and the fact that EPA has not completed its evaluation of 

the E15 waiver petition, we believe that it is appropriate to defer finalizing labeling requirements 

for >E10 blends at this time. This will afford us the opportunity to complete our analysis of what 

measures might be appropriate to prevent misfueling with >E10 blends before this may become a 

concern in the context of the RFS2 program. 

G. Biodiesel Temperature Standardization 

The volume of a batch of renewable fuel can change under extreme changes in temperature. 

The volume of a batch of renewable fuel can experience expansion as the temperature increases, 

or can experience contraction as temperature decreases. The Agency requires temperature 

standardization of renewable fuels at 60 ° Fahrenheit (°F) so renewable fuel volumes are 

accounted for on a uniform and consistent basis over the entire fuels industry. In the May 1, 
 

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2007 Renewable Fuels Standard (RFS) final rule the Agency required biodiesel temperature 

standardization to be completed as follows: 

Vs,b = Va,b × (-0.0008008 × T + 1.0480) 

Where 

Vs,b = Standard Volume of biodiesel at 60 degrees F, in gallons; 

Va,b = Actual volume of biodiesel, in gallons; 

T = Actual temperature of batch, in degrees F. 

 This equation was based on data from a published research paper by Tate et al.

 36 

Members of the petroleum industry have indicated that the current biodiesel temperature 

standardization equation in the regulations provides different results than that commonly used by 

both the petroleum and biodiesel industry for commercial trading of biodiesel. These 

commercial values are either based on American Petroleum Institute (API) tables for petroleum 

products or on empirical values from industry measurements at common temperatures and 

pressures observed in bulk fuel facilities. The difference between RIN calculated volumes and 

commercial sales volumes has created confusion within the record keeping system of both the 

petroleum and biodiesel industry. 

 

36 Equation was derived from R.E. Tate et al. “The Densities of Three Biodiesel Fuels at Temperatures up to 

300°C.”, Department of Biological Engineering, Dalhousie University, April 2005. “Fuel 85 (2006) 1004-1009, 

Table 1 for soy methyl ester.” 
 

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 In the RFS2 proposed rule, the Agency proposed the temperature standardization of 

biodiesel remain unchanged from the RFS1 requirements.37 The Agency received comments 

from Archer Daniels Midland Company (ADM), World Energy Alternatives, Marathon 

Petroleum Company (Marathon) and the National Biodiesel Board (NBB) to revise the biodiesel 

temperature standardization equation. 

 Both ADM and NBB agreed on the necessity for biodiesel temperature standardization at 

60 °F. ADM and NBB commented on several empirical calculations which have been developed 

specific to biodiesel temperature standardization since the 2007 RFS1 final rule. These include a 

2004 data set developed by the Minnesota Department of Commerce and the Renewable Energy 

Group and updated in 2008; information embedded in the European Biodiesel Specification EN 

14214; and information from the Alberta Research Council. The table below provides values 

from NBB for 1000 gallons of biodiesel standardized to a temperature at 60 °F for these 

empirical calculations, along with the current EPA equation, and the American Petroleum 

Institute (API) Refined Products Table 6. 

Table III.G-1 

NBB Comparison of Biodiesel Temperature Standardization Calculations to 60°F for 1000 

gallons of Biodiesel at 90°F 

2007 EPA Biodiesel Formula 975.28 gallons 

2008 Minnesota (Hedman) data 986.270 gallons 

API Refined Products Table 6 (biodiesel 986.625 gallons 

 

37 74 FR 24943, May 26, 2009. 
 

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density @ 7.359) 

Alberta Research Council 986.238 gallons 

EN 14214 data 986.401 gallons 

2004 Minnesota Renewable Energy Group data 986.830 gallons 

 As illustrated by the results from the above table, the values for the various biodiesel 

temperature standardization empirical calculations are within 1 gallon of agreement of each other 

for a 1000 gallon biodiesel batch, except for the current biodiesel temperature standardization 

equation in the regulations. 

To ensure consistency in RIN generation, ADM commented EPA should adopt only one 

biodiesel temperature standardization calculation. ADM commented that all biodiesel 

temperature standardization calculations developed, including the API Refined Products Table 6, 

are in very close agreement with each other and the differences between them all are 

insignificant. They further commented the API Refined Products Table 6 has provided a 

uniform measurement of volume for years for the entire liquid fuels industry. Thus, ADM 

believes the API Refined Products Table 6 should be adopted for biodiesel to be consistent with 

the calculation of sales volumes. Finally ADM comments adoption of the API Refined Products 

Table 6 would allow for easier verification within the marketplace, eliminate the need for 

calculating one volume for sales and trades and another for RINs, and prevents the entire 

distribution network from facing the financial burden of reprogramming existing meters that 

already are based on the API Refined Products Table 6. 
 

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NBB commented that earlier surveys from its members indicate a fifty-fifty split between 

members using the API Refined Products Table 6 or some variation of the current EPA biodiesel 

formula for biodiesel temperature standardization. Some NBB members indicated that the API 

Refined Products Table 6 was more commonly used by the petroleum industry and embedded 

into the meters, pumps and accounting systems of the petroleum industry. Companies already 

using the API Refined Products Table 6 would have a reduction in required paperwork with RIN 

generation and tracking because already existing commercial documents could serve that 

purpose and they thus could eliminate or reduce their current dual tracking system. Other NBB 

members have already embedded the current EPA biodiesel equation within their accounting and 

sales systems and would like to continue using that type of biodiesel temperature standardization 

approach rather than the API Refined Products Table 6. The NBB recommended EPA revise its 

current equation in the regulations to the 2008 Hedman biodiesel temperature standardization 

equation. Thus, NBB commented EPA should provide flexibility to their members by allowing 

the use of either the API Refined Products Table 6 or the use of a biodiesel temperature 

standardization equation. 

Marathon commented the regulations allow for the standardization of volume for other 

renewable fuels to be determined by an appropriate formula commonly accepted by the industry 

which may be reviewed by the EPA for appropriateness. They recommended that EPA extend 

this courtesy to biodiesel. 

The Agency acknowledges that the current biodiesel temperature standardization 

equation is likely not correct for biodiesel temperature standardization at ambient temperatures 
 

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observed in the fuel distribution system. Based on the comments received, the Agency is 

amending the regulations to allow for two ways for biodiesel temperature standardization: 1) the 

American Petroleum Institute Refined Products Table 6B, as referenced in ASTM D1250-08, 

entitled, “Standard Guide for Use of the Petroleum Measurement Tables”, and 2) a biodiesel 

temperature standardization equation that utilizes the 2008 data generated by the Minnesota 

Department of Commerce and the Renewable Energy Group. These two methods for biodiesel 

temperature standardization are within one gallon of agreement of each other for a 1000 gallon 

biodiesel batch and thus in very close agreement. Both ADM and NBB acknowledged that the 

differences between these two methods are insignificant and the resulting corrected volumes 

from these two methods of calculation are within accuracy tolerances of any metered 

measurement. Thus, the Agency believes the allowance of both of these methods for biodiesel 

temperature standardization will increase flexibility while still providing for a consistent 

generation and accounting of biodiesel RINs over the entire fuel delivery system. 
 

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IV. Renewable Fuel Production and Use 

 An assessment of the impacts of increased volumes of renewable fuel must begin with an 

analysis of the kind of renewable fuels that could be used, the types and locations of their 

feedstocks, the fuel volumes that could be produced by a given feedstock, and any challenges 

associated with their use. This section provides an assessment of the potential feedstocks and 

renewable fuels that could be used to meet the Energy Independence and Security Act (EISA) 

and the rationale behind our projections of various fuel types to represent the control cases for 

analysis purposes. As new technologies, feedstocks, and fuels continue to develop on a daily 

basis, markets may appear differently from our projections. Although actual volumes and 

feedstocks may differ, we believe the projections made for our control cases are within the range 

of possible predictions for which the standards are met and allow for an assessment of the 

potential impacts of the increases in renewable fuel volumes that meet the requirements of EISA. 

A. Overview of Renewable Fuel Volumes 

 EISA mandates the use of increasing volumes of renewable fuel. To assess the impacts 

of this increase in renewable fuel volume from business-as-usual (what is likely to have occurred 

without EISA), we have established reference and control cases from which subsequent analyses 

are based. The reference cases are projections of renewable fuel volumes without the enactment 

of EISA and are described in Section IV.A.1. The control cases are projections of the volumes 

and types of renewable fuel that might be used in the future to comply with the EISA volume 

mandates. For the NPRM we had focused on one primary control case (see Section IV.A.2) 
 

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whereas for the final rule we have expanded the analysis to include two additional sensitivity 

cases (see Section IV.A.3). Based on the public comments received as well as new information, 

we have updated the primary control case volumes from the NPRM to reflect what we believe 

could be a more likely set of volumes to analyze. We assume in each of the cases the same 

ethanol-equivalence basis as was used in the RFS1 rulemaking to meet the standard. Volumes 

are listed in tables for this section in both straight-gallons and ethanol-equivalent gallons (i.e., 

times 1.5 for biodiesel or 1.7 for cellulosic diesel and renewable diesel). The volumes included 

in this section are for 2022. For intermediate years, refer to Section 1.2 of the RIA. 

 1. Reference Cases 

 Our primary reference case renewable fuel volumes are based on the Energy Information 

Administration’s (EIA) Annual Energy Outlook (AEO) 2007 reference case projections.38 While 

AEO 2007 is not as up-to-date as AEO 2008 or AEO 2009, we chose to use AEO 2007 because 

later versions of AEO already include the impact of increased renewable fuel volumes under 

EISA as well as fuel economy improvements under CAFE as required in EISA, whereas AEO 

2007 did not. 

For the final rule we have also assessed a number of the impacts relative to a reference 

case assuming the mandated renewable fuel volumes under RFS1 from the Energy Policy Act of 

2005 (EPAct). This allows for a more complete assessment of the impacts of the EISA volume 

mandates, especially when combined with the impacts assessment conducted for the RFS1 

 

38 AEO 2007 was only used to derive renewable fuel volume projections for the primary reference case. AEO 2009 

was used for future crude oil cost estimates and for estimating total transportation fuel energy use. 
 

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rulemaking (though many factors have changed since then). Table IV.A.1-1 summarizes the 

2022 renewable fuel volumes for the AEO 2007 and the RFS1 reference cases (listed in both 

straight volumes and ethanol-equivalent volumes). 

Table IV.A.1-1 

Reference Case Renewable Fuel Volumes in 2022 (billion gallons) 

Advanced Biofuel 

Cellulosic 

Biofuel 

BiomassBased Diesela

Other 

Advanced 

Biofuel 

NonAdvanced 

Biofuel 

Source/Volume 

Type 

Cellulosic 

Ethanolc 

FAME 

Biodieselb

Imported 

Ethanol 

Corn Ethanol 

Total 

Renewable 

Fuel 

AEO 2007 

Straight Volume 0.25 0.38 0.64 12.29 13.56 

AEO 2007 

Ethanol-Equivalent 0.25 0.58 0.64 12.29 13.76 

RFS 1 

Straight Volume 0.00 0.30 0.00 7.05 7.35 

RFS 1 

Ethanol-Equivalent 0.00 0.45 0.00 7.05 7.50 

a Biomass-Based Diesel could include FAME biodiesel, cellulosic diesel, and non-co-processed renewable 

diesel. 

b Only fatty acid methyl ester (FAME) biodiesel volumes were considered 

c

 Under the RFS1 reference case, we assumed the 250-million gallon cellulosic standard set by EPAct 

would be met primarily by corn ethanol plants utilizing 90% biomass for energy, thus actual production of 
 

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cellulosic biofuel is zero. AEO 2007 reference case assumes actual production of cellulosic biofuel and 

therefore assumed to be 0.25 billion gallons. 

 2. Primary Control Case 

 Our assessment of the renewable fuel volumes required to meet EISA necessitates 

establishing a primary set of fuel types and volumes on which to base our assessment of the 

impacts of the new standards. EISA contains four broad categories: cellulosic biofuel, biomassbased diesel, total advanced biofuel, and total renewable fuel. As these categories could be met 

with a wide variety of fuel choices, in order to assess the impacts of increased volumes of 

renewable fuel, we projected a set of reasonable renewable fuel volumes based on our projection 

of fuels that could come to market. 

 Although actual volumes and feedstocks will be different, we believe the projections 

made for our control cases are within the range of possible predictions for which the standards 

are met and allow for an assessment of the potential impacts of increased volumes of renewable 

fuel. Table IV.A.2-1 summarizes the fuel types used for the primary control case and their 

corresponding volumes for the year 2022. 
 

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Table IV.A.2-1 

Primary Control Case Projected Renewable Fuel Volumes in 2022 (billion gallons) 

Advanced Biofuel

Cellulosic Biofuel Biomass-Based 

Diesela

Other Advanced 

Biofuel

NonAdvanced 

Biofuel

Volume 

Type 

Cellulosic 

Ethanol 

Cellulosic 

Dieselb

FAMEc

Biodiesel NCRDd

Other 

Biodiesele

Imported 

Ethanol 

Corn 

Ethanol 

Total 

Renewable 

Fuel

Straight 

Volume 4.92 6.52 0.85 0.15 0.82 2.24 15.00 30.50 

EthanolEquivalent 4.92 11.08 1.28 0.26 1.23 2.24 15.00 36.00 

 

a Biomass-Based Diesel could include FAME biodiesel, cellulosic diesel, and non-co-processed renewable diesel. 

b Cellulosic Diesel includes at least 1.96 billion gallons (3.33 billion ethanol-equivalent gallons) from FischerTropsch Biomass-to-Liquids (BTL) processes based on EIA’s forecast and an additional 4.56 billion gallons (7.75 

billion ethanol-equivalent gallons) from this or other types of cellulosic diesel processes 

c

 Fatty acid methyl ester (FAME) biodiesel 

d

 Non-Co-processed Renewable Diesel (NCRD) 

e

 Other Biodiesel is biodiesel that could be produced in addition to the amount needed to meet the biomass-based 

diesel standard. 

The following subsections detail our rationale for projecting the amount and type of fuels 

needed to meet EISA as shown in Table IV.A.2-1. For cellulosic biofuel we have assumed that 

by 2022 on a straight-volume basis about half would come from cellulosic ethanol and the other 

half from cellulosic diesel. On an ethanol-equivalent volume basis, cellulosic diesel would make 

up almost 70% of the 16 billion gallons cellulosic biofuel standard. Biomass-based diesel is 
 

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assumed to be comprised of a majority of fatty-acid methyl ester (FAME) biodiesel and a smaller 

portion of non-co-processed renewable diesel. The portion of the advanced biofuel category not 

met by cellulosic biofuel and biomass-based diesel is assumed to come mainly from imported 

sugarcane ethanol with a smaller amount from additional biodiesel sources. The total renewable 

fuel volume not required to be comprised of advanced biofuels is assumed to be met with corn 

ethanol with small amounts of other grain starches and waste sugars. 

 The main difference between the volumes used for the NPRM and the volumes used for 

the FRM is the inclusion of cellulosic diesel for the FRM. The NPRM made the simplifying 

assumption that the cellulosic biofuel standard would be met entirely with cellulosic ethanol. 

However, due to growing interest and recent developments in hydrocarbon-based or so-called 

“drop-in” renewable fuels as well as butanol, and marketplace challenges for consuming high 

volumes of ethanol, we have included projections of more non-ethanol renewables in our 

primary control case for the final rule.39 In the future, this could include various forms of “green 

hydrocarbons” (i.e., cellulosic gasoline, diesel and jet) and higher alcohols, but for analysis 

purposes, we have modeled it as cellulosic diesel fuel. We describe these fuels in greater detail 

in Section IV.B-D. We have also included some algae-derived biofuels in our FRM analyses 

given the large interest and potential for such fuels. We have continued to assume zero volume 

for renewable fuels or blendstocks such as biogas, jatropha, palm, imported cellulosic biofuel, 

and other alcohols or ethers in our control cases. Although we have not included these 

 

39 Comments received from Advanced Biofuels Association, Testimony on June 9, 2009 suggesting a number of 

advanced biofuel technologies will be able to produce renewable diesel, jet fuels, gasoline, and gasoline component 

fuels (e.g. butanol, iso-octane). Similar comments were received from the New York State Department of 

Environmental Conservation (Docket EPA-HQ-OAR-2005-0161-2143), OPEI and AllSAFE (Docket EPA-HQOAR-2005-0161-2241), and the Low Carbon Synthetic Fuels Association (Docket EPA-HQ-OAR-2005-0161-

2310). 
 

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renewable fuels and blendstocks in our impact analyses, it is important to note that they can still 

be counted under our program if they meet the lifecycle thresholds and definitions for renewable 

biomass, and recent information suggests that some of them may be likely. 

 a. Cellulosic Biofuel 

 As discussed in our NPRM, whether cellulosic biofuel is ethanol will depend on a 

number of factors, including production costs, the form of tax subsidies, credit programs, and 

factors influencing the blending of biofuel into the fuel pool. It will also depend on the relative 

demand for gasoline and diesel fuel. As a result of our analyses on ethanol consumption (see 

Section IV.D) and continual tracking of the industry’s interest in hydrocarbon-based renewables 

(see Section IV.B), we have decided to analyze a cellulosic biofuel standard made up of both 

cellulosic ethanol and cellulosic diesel fuels. 

 

For assessing the impacts of the RFS2 standards, we used AEO 2009 (April release) 

cellulosic ethanol volumes (4.92 billion gallons), as well as the cellulosic biomass-to-liquids 

(BTL) diesel volumes (1.96 billion gallons) using Fischer-Tropsch (FT) processes. We consider 

BTL diesel from FT processes as a subset of cellulosic diesel. In order to reach a total of 16 

billion ethanol-equivalent gallons, we assumed that an additional 4.56 billion gallons of 

cellulosic diesel could be produced from other cellulosic diesel processes. Refer to Section 1.2 

of the RIA for more discussion. 

 b. Biomass-Based Diesel 
 

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 Biomass-based diesel can include fatty acid methyl ester (FAME) biodiesel, renewable 

diesel (RD) that has not been co-processed with a petroleum feedstock, as well as cellulosic 

diesel. Although cellulosic diesel could potentially contribute to the biomass-based diesel 

category, we have assumed for our analyses that the fuel produced through Fischer-Tropsch (FT) or other processes and its corresponding feedstocks (cellulosic biomass) are already accounted 

for in the cellulosic biofuel category discussed previously in Section IV.A.2.a. 

 FAME and RD processes can both utilize vegetable oils, rendered fats, and greases, and 

thus will generally compete for the same feedstock pool. We have based RD volumes on our 

forecast of industry plans, and expect these plants to use rendered fats as feedstock. Most 

biodiesel plants now have the capability to use vegetable or animal fats as feedstock, and thus 

our analysis assumes biodiesel will be made from a mix of inputs, depending on local 

availability, economics, and season. Refer to Section 1.1 of the RIA for more detail on FAME 

and RD feedstocks 

 Renewable diesel production can be further classified as co-processed or non-coprocessed, depending on whether the renewable material is mixed with petroleum during the 

hydrotreating operations. EISA specifically forbids co-processed RD from being counted as 

biomass-based diesel, but it can still count toward the total advanced biofuel requirement. At 

this time, based on current industry plans, we expect most, if not all, RD will be non-coprocessed (that is, non-refinery operations). 
 

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Perhaps the feedstock with the greatest potential for providing large volumes of oil for 

the production of biomass-based diesel is algae. However, several technical hurdles do still exist. 

Specifically, more efficient harvesting, dewatering, and lipid extraction methods are needed to 

lower costs to a level competitive with other feedstocks. For all three control cases, we have 

chosen to include 100 million gallons of algae-based biodiesel by 2022. We believe this is 

reasonable given several announcements from the algae industry about their production plans.40 

Although algae to biofuel companies can focus on producing algae oil for traditional biodiesel 

production, several companies are alternatively using algae for producing ethanol or crude oil for 

gasoline or diesel which could also help contribute to the advanced biofuel mandate. For more 

detail on algae as a feedstock, refer to Section 1.1 of the RIA. 

 During the comment period, we received information from stakeholders on alternative 

biodiesel feedstocks such as camelina and pennycress, to name a few. These feedstocks are 

currently being researched due to their potential for lower agricultural inputs and higher oil 

yields than traditional vegetable oil feedstocks as well as their use in additional crop rotations 

(i.e., winter cover crops) on a given area of land. We acknowledge that as we learn more about 

the challenges and benefits to the use of newer feedstocks, these could be used in the future 

towards meeting the biomass-based diesel standard under the RFS2 program provided they meet 

the lifecycle thresholds and definitions for renewable biomass. For the purpose of our impacts 

analysis, however, we have chosen not to include these feedstocks in our analyses at this time. 

 

40 Sapphire Energy plans for 135 MMgal by 2018 and 1 Bgal by 2025; Petrosun plans for 30 MMgal/yr facility; 

Solazyme plans for 100 MMgal by 2012/13; U.S. Biofuels plans for 4 MMgal by 2010 and 50 MMgal by full scale. 

Only several companies have thus far revealed production plans, and more are announced each day. It is important 

to realize that future projections are highly uncertain, and we have taken into account the best information we could 

acquire at the time. 
 

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 c. Other Advanced Biofuel 

 As defined in EISA, advanced biofuel includes the cellulosic biofuel and biomass-based 

diesel categories that were mentioned in Sections IV.A.2.a and IV.A.2.b above. However, EISA 

requires greater volumes of advanced biofuel than just the volumes required of these fuels. It is 

entirely possible that greater volumes of cellulosic biofuel and biomass-based diesel than 

required by EISA could be produced in the future. Our control case assumes that the cellulosic 

biofuel volumes will not exceed those required under EISA. We do assume, however, that 

additional biodiesel than that needed to meet the biomass-based diesel volume will be used to 

meet the total advanced biofuel volume. Despite additional volumes assumed from biodiesel, to 

fully meet the total advanced biofuel volume required under EISA, other types of advanced 

biofuel are necessary through 2022. 

 We have assumed for our control case that the most likely sources of advanced fuel other 

than cellulosic biofuel and biomass-based diesel would be from imported sugarcane ethanol and 

perhaps limited amounts of co-processed renewable diesel. Our assessment of international fuel 

ethanol production and demand indicate that anywhere from 3.8-4.2 Bgal of sugarcane ethanol 

from Brazil could be available for export by 2020/2022. If this volume were to be made 

available to the U.S., then there would be sufficient volume to meet the advanced biofuel 

standard. To calculate the amount of imported ethanol needed to meet the EISA advanced 

biofuel standards, we assumed it would make up the difference not met by cellulosic biofuel, 

biomass-based diesel and additional biodiesel categories (see Table IV.A.2-1). The amount of 

imported ethanol required by 2022 is approximately 2.2 Bgal. 
 

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As discussed in the NPRM, other potential advanced biofuels could include for example, 

U.S. domestically produced sugarcane ethanol, biobutanol, and biogas. While we have not 

chosen to reflect these fuels in our control case, they can still be counted under our program 

assuming they meet the lifecycle thresholds and other definitions under the program. 

 d. Other Renewable Fuel 

 The remaining portion of total renewable fuel not met with advanced biofuel was 

assumed to come from corn-based ethanol (including small amounts from other grains and waste 

sugars). EISA effectively sets a limit for participation in the RFS program of 15 Bgal of corn 

ethanol, and we are assuming for our analysis that sufficient corn ethanol will be produced to 

meet the 15-Bgal limit that either meets the 20% GHG threshold or is grandfathered. It should 

be noted, however, that there is no specific “corn-ethanol” mandated volume, and that any 

advanced biofuel produced above and beyond what is required for the advanced biofuel 

requirements could reduce the amount of corn ethanol needed to meet the total renewable fuel 

standard. This occurs in our projections during the earlier years (2010-2015) in which we project 

that some fuels could compete favorably with corn ethanol (e.g., biodiesel and imported ethanol). 

Refer to Section 1.2 of the RIA for more details on interim years. Beginning around 2016, fuels 

qualifying as advanced biofuels likely will be devoted to meeting the increasingly stringent 

volume mandates for advanced biofuel. It is also important to note that more than 15 Bgal of 

corn ethanol could be produced and RINs generated for that volume under the RFS2 regulations. 
 

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However, obligated parties would not be required to purchase more than 15 Bgal worth of nonadvanced biofuel RINs, e.g. corn ethanol RINs. 

3. Additional Control Cases Considered

Since there is significant uncertainty surrounding what fuels will be produced to meet the 

16 billion gallon cellulosic biofuel standard, we have decided to investigate two other sensitivity 

cases for our cost and emission impact analyses conducted for the rule. The first case, we refer 

to as the “low-ethanol” control case and assume only 250 million gallons of cellulosic ethanol 

(from AEO 2007 reference case). The rest of the 16 billion gallon cellulosic biofuel standard is 

made up of cellulosic diesel as shown in Table IV.A.3-1. The second case, we refer to as the 

“high-ethanol” control case and assume the entire 16 billion gallon cellulosic biofuel standard is 

met with cellulosic ethanol, also shown in Table IV.A.3-1. 
 

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Table IV.A.3-1 

Control Case Projected Renewable Fuel Volumes in 2022 (billion gallons) 

Advanced Biofuel

Cellulosic Biofuel Biomass-Based 

Diesela

Other Advanced 

Biofuel

NonAdvanced 

Biofuel

Case/ 

Volume 

Type 

Cellulosic 

Ethanol 

Cellulosic 

Dieselb

FAMEc

Biodiesel NCRDd

Other 

Biodiesele

Imported 

Ethanol 

Corn 

Ethanol 

Total 

Renewable 

Fuel

LowEthanol 

Straight 

Volume 0.25 9.26 0.85 0.15 0.82 2.24 15.00 28.57 

LowEthanol 

EthanolEquivalent 0.25 15.75 1.28 0.26 1.23 2.24 15.00 36.00 

HighEthanol 

Straight 

Volume 16.00 0.00 0.85 0.15 0.82 2.24 15.00 35.06 

HighEthanol 

EthanolEquivalent 16.00 0.00 1.28 0.26 1.23 2.24 15.00 36.00 

a Biomass-Based Diesel could include FAME biodiesel, cellulosic diesel, and non-co-processed renewable diesel. 
 

315

b Cellulosic Diesel includes 1.96 billion gallons (3.33 ethanol-equivalent billion gallons) from Fischer-Tropsch 

Biomass-to-Liquids (BTL) processes and 7.30 billion gallons (12.42 ethanol-equivalent billion gallons) from other 

types of cellulosic diesel processes for the Low-Ethanol case and zero cellulosic diesel in the High-Ethanol Case 

c

 Fatty acid methyl ester (FAME) biodiesel 

d

 Non-Co-processed Renewable Diesel (NCRD) 

e

 Other Biodiesel is biodiesel that could be produced in addition to the amount needed to meet the biomass-based 

diesel standard. 

 In comparison, our primary control case described in Section IV.A.2, could be considered 

a “mid-ethanol” control case, as the cellulosic ethanol and diesel volumes analyzed are in 

between the low-ethanol and high-ethanol cases described in this section. We believe the 

addition of these sensitivity cases is useful in understanding the potential impacts of the 

renewable fuels standards. Refer to Section 1.2 of the RIA for more detail on three control cases 

analyzed as part of this rule. 

B. Renewable Fuel Production 

 1. Corn/Starch Ethanol 

 The majority of domestic biofuel production currently comes from plants processing corn 

and other similarly-processed grains in the Midwest. However, there are a handful of plants 

located outside the Corn Belt and a few plants processing simple sugars from food or beverage 

waste. In this section, we summarize the present state of the corn/starch ethanol industry and 

discuss how we expect things to change in the future under the RFS2 program. 
 

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 a. Historic/Current Production 

 The United States is currently the largest ethanol producer in the world. In 2008, the U.S. 

produced nine billion gallons of fuel ethanol for domestic consumption, the majority of which 

came from locally-grown corn.41 The nation is currently on track for producing over 10 billion 

gallons by the end of 2009.42 Although the U.S. ethanol industry has been in existence since the 

1970s, it has rapidly expanded in recent years due to the phase-out of methyl tertiary butyl ether 

(MTBE), elevated crude oil prices, state mandates and tax incentives, the introduction of the 

Federal Volume Ethanol Excise Tax Credit (VEETC)43, the implementation of the existing RFS1 

program

44, and the new volume requirements established under EISA. As shown in Figure 

IV.B.1-1, U.S. ethanol production has grown exponentially over the past decade. 

 

41 Based on total transportation ethanol reported in EIA’s September 2009 Monthly Energy Review (Table 10.2) less 

imports (http://tonto.eia.doe.gov/dnav/pet/hist/mfeimus1a.htm). 

42 Based on ethanol projected in EIA’s October 2009 Short Term Energy Outlook less projected imports. Actual 

year-end data for 2009 was unavailable at the time of this FRM assessment. 

43 On October 22, 2004, President Bush signed into law H.R. 4520, the American Jobs Creation Act of 2004 (JOBS 

Bill), which created the Volumetric Ethanol Excise Tax Credit (VEETC). The $0.51/gal ethanol blender credit 

replaced the former fuel excise tax exemption, blender’s credit, and pure ethanol fuel credit. However, the 2008 

Farm Bill modified the alcohol credit so that corn ethanol gets a reduced credit of $0.45/gal and cellulosic biofuel 

gets a credit of $1.01/gal. 

44 On May 1, 2007, EPA published a final rule (72 FR 23900) implementing the Renewable Fuel Standard required 

by EPAct (also known as RFS1). RFS1 requires that 4.0 billion gallons of renewable fuel be blended into 

gasoline/diesel by 2006, growing to 7.5 billion gallons by 2012. 
 

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Figure IV.B.1-1 

Historical Growth in U.S. Corn/Starch Ethanol Production45

1.4 1.6 1.7

2.0

2.7

3.3

3.8

4.6

6.3

9.0

0

1

2

3

4

5

6

7

8

9

10

1999

20002001

2002

200320042005

2006

2007

2008

Year

Corn/Starch Ethanol Production (Bgal)

 

45 Based on total transportation ethanol reported in EIA’s September 2009 Monthly Energy Review (Table 10.2) 

less imports (http://tonto.eia.doe.gov/dnav/pet/hist/mfeimus1a.htm). 
 

318

 As of November 2009 there were 180 corn/starch ethanol plants operating in the U.S. 

with a combined production capacity of approximately 12 billion gallons per year.46 This does 

not include idled ethanol plants, discussed later in this subsection. The majority of today’s 

ethanol production (91.5% by volume) comes from 155 plants relying exclusively on corn. 

Another 8.3% comes from 18 plants processing a blend of corn and/or similarly-processed grains 

(milo, wheat, or barley). The remainder comes from seven small plants processing waste 

beverages or other waste sugars and starches. 

 Of the 173 plants processing corn and/or other similarly processed grains, 162 utilize drymilling technologies and the remaining 11 plants rely on wet-milling processes. Dry mill ethanol 

plants grind the entire kernel and generally produce only one primary co-product: distillers’ 

grains with solubles (DGS). The co-product is sold wet (WDGS) or dried (DDGS) to the 

agricultural market as animal feed. However, there are a growing number of plants using frontend fractionation to produce food-grade corn oil or back-end extraction to produce fuel-grade 

corn oil for the biodiesel industry. A company called GreenShift has corn oil extraction facilities 

located at five ethanol plants in Michigan, Indiana, New York and Wisconsin.47 Collectively, 

these facilities are designed to extract in excess of 7.3 million gallons of corn oil per year. 

Primafuel Solutions is another company offering corn oil extraction technologies to make 

 

46 Our November 2009 corn/starch ethanol industry characterization was based on a variety of sources including 

plant lists published online by the Renewable Fuels Association and Ethanol Producer Magazine (updated October 

22, 2009), information from ethanol producer websites including press releases, and follow-up correspondence with 

producers. The baseline does not include ethanol plants whose primary business is industrial or food-grade ethanol 

production nor does it include plants that might be located in the Virgin Islands or U.S. territories. Where 

applicable, current/historic production levels have been used in lieu of nameplate capacities to estimate production 

capacity. 

47 Two plants in Michigan and one in each of the other three states. All company information based on GreenShift’s 

Q2 2009 SEC filing available at http://www.greenshift.com/pdf/GERS_Form10Q_Q209_FINAL.pdf. 
 

319

existing ethanol plants more sustainable. For more information on corn oil extraction and other 

advanced technologies being pursued by today’s corn ethanol industry, refer to Section 1.4.1 of 

the RIA. 

 In contrast to dry mill plants, wet mill facilities separate the kernel prior to processing 

into its component parts (germ, fiber, protein, and starch) and in turn produce other co-products 

(usually gluten feed, gluten meal, and food-grade corn oil) in addition to DGS. Wet mill plants 

are generally more costly to build but are larger in size on average.48 As such, 11.4% of the 

current grain ethanol production comes from the 11 previously-mentioned wet mill facilities. 

 The remaining seven ethanol plants process waste beverages or waste sugars/starches and 

operate differently than their grain-based counterparts. These small production facilities do not 

require milling and operate simpler enzymatic fermentation processes. 

 

48 According to our November 2009 corn ethanol plant assessment, the average wet mill plant capacity is 125 

million gallons per year – almost twice that of the average dry mill plant capacity (65 million gallons per year). For 

more on average plant sizes, refer to Section 1.5 of the RIA. 
 

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 Ethanol production is a relatively resource-intensive process that requires the use of 

water, electricity, and steam. Steam needed to heat the process is generally produced on-site or 

by other dedicated boilers.49 The ethanol industry relies primarily on natural gas. Of today’s 

180 ethanol production facilities, an estimated 151 burn natural gas50 (exclusively), three burn a 

combination of natural gas and biomass, one burns natural gas and coal (although natural gas is 

the primary fuel), one burns a combination of natural gas, landfill biogas and wood, and two 

burn natural gas and syrup from the process. We are aware of 17 plants that burn coal as their 

primary fuel and one that burns a combination of coal and biomass.51 Our research suggests that 

three corn ethanol plants rely on a combination of waste heat and natural gas and one plant does 

not have a boiler and relies solely on waste heat from a nearby power plant. Overall, our 

research suggests that 27 plants currently utilize cogeneration or combined heat and power 

(CHP) technology, although others may exist.52 CHP is a mechanism for improving overall plant 

efficiency. Whether owned by the ethanol facility, their local utility, or a third party, CHP 

facilities produce their own electricity and use the waste heat from power production for process 

steam, reducing the energy intensity of ethanol production.53 

 

49 Some plants pull steam directly from a nearby utility. 

50 Facilities were assumed to burn natural gas if the plant boiler fuel was unspecified or unavailable on the public 

domain. 

51 Includes corrections from NPRM based on new information obtained on Cargill plants and Blue Flint ethanol 

plant. 

52 CHP assessment based on information provided by EPA’s Combined Heat and Power Partnership, literature 

searches and correspondence with ethanol producers. 

53 For more on CHP technology, refer to Section 1.4.1.3 of the RIA. 
 

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 During the ethanol fermentation process, large amounts of carbon dioxide (CO2) gas are 

released. In some plants the CO2 is vented into the atmosphere, but where local markets exist, it 

is captured, purified, and sold to the food processing industry for use in carbonated beverages 

and flash-freezing applications. We are currently aware of 40 fuel ethanol plants that recover 

CO2 or have facilities in place to do so. According to Airgas, a leading gas distributor, the U.S. 

ethanol industry currently recovers 2 to 2.5 million tons of CO2 per year which translates to 

about 5-7% of all the CO2 produced by the industry.54

 Since the majority of ethanol is made from corn, it is no surprise that most of the plants 

are located in the Midwest near the Corn Belt. Of today’s 180 ethanol production facilities, 163 

are located in the 15 states comprising PADD 2. For a map of the government’s Petroleum 

Administration for Defense Districts or PADDs, refer to Figure IV.B.1-2. 

 

54 Based on information provided by Bruce Woerner at Airgas on August 14, 2009. 
 

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Figure IV.B.1-2 

Petroleum Administration for Defense Districts 
 

323

 As a region, PADD 2 accounts for over 94% (or 11.3 billion gallons) of today’s estimated 

ethanol production capacity, followed by PADD 3 (2.4%), PADDs 4 and 1 (each with 1.3%) and 

PADD 5 (0.8%). For more information on today’s ethanol plant locations, refer to Section 1.5.1 

of the RIA. 

 The U.S. ethanol industry is currently comprised of a mixture of company-owned plants 

and locally-owned farmer cooperatives (co-ops). The majority of today’s ethanol production 

facilities are company-owned, and on average these plants are larger in size than farmer-owned 

co-ops. Accordingly, these facilities account for about 80% of today’s online ethanol production 

capacity.55 Furthermore, nearly 30% of the total domestic product comes from 40 plants owned 

by just three different companies – POET Biorefining, Archer Daniels Midland (ADM), and 

Valero Renewables. Valero entered the ethanol industry in March of 2009 when it acquired 

seven ethanol plants from former ethanol giant, Verasun. The oil company currently has 

agreements in place to purchase three more ethanol plants that would bring the company’s 

ethanol production capacity to 1.1 billion gallons per year.56 However, ethanol plants are much 

smaller than petroleum refineries. Valero’s smallest petroleum refinery in Ardmore, OK has 

about twice the throughput of all its ethanol plants combined.57 Still, as obligated parties under 

RFS1 and RFS2, the refining industry continues to show increased interest in biofuels. Suncor 

and Murphy Oil recently joined Valero as the second and third oil companies to purchase idled 

 

55 Company-owned plants were assumed to be all those companies not denoted as locally-owned based on 

Renewable Fuels Association (RFA), Ethanol Biorefinery Locations (updated October 22, 2009). For more on 

average plant sizes, refer to Section 1.5.1 of the RIA. 

56 Valero recently announced that it has purchase agreements in place to acquire the last two Verasun plants in 

Linden, IN and Bloomington, OH and the former Renew Energy plant in Jefferson Junction, WI. 

57 Based on refinery information provided at http://www.valero.com/OurBusiness/OurLocations/ 
 

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U.S. ethanol plants. Many refiners are also supporting the development of cellulosic biofuels 

and algae-based biodiesel. 

 b. Forecasted Production Under RFS2 

 As highlighted earlier, domestic ethanol production is projected to grow to over 10 billion 

gallons in 2009. And with over 12 billion gallons of capacity online as of November 2009, 

ethanol production should continue to grow in 2010, provided plants continue to produce at or 

above today’s production levels. In addition, despite current market conditions (i.e., poor 

ethanol margins), the ethanol industry is expected to grow in the future under the RFS2 program. 

Although there is not a set corn ethanol requirement, EISA allows for 15 billion gallons of the 

36-billion gallon renewable fuel standard to be met by conventional biofuels. We expect that 

corn ethanol will fulfill this requirement, provided it is more cost competitive than imported 

ethanol or cellulosic biofuel in the marketplace. 

 In addition to the 180 aforementioned corn/starch ethanol plants currently online, 27 

plants are presently idled.58 Some of these are smaller ethanol plants that have been idled for 

quite some time, whereas others are in a more temporary “hot idle” mode, ready to be restarted. 

In response to the economic downturn, a number of ethanol producers have idled production, 

halted construction projects, sold off plants and even filed for Chapter 11 bankruptcy protection. 

Some corn ethanol companies have exited the industry all together (e.g., Verasun) whereas 

 

58 Based on our November 2009 corn/starch ethanol industry characterization. We are aware of at least one plant 

that has come back online since then. 
 

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others are using bankruptcy as a means to protect themselves from creditors as they restructure 

their finances with the goal of becoming sustainable. 

 Crude oil prices are expected to increase in the future making corn ethanol more 

economically viable. According to EIA’s AEO 2009, crude oil prices are projected to increase 

from about $80/barrel (today’s price) to $116/barrel by 2022.59 As oil and gas prices rebound, 

we expect that the biofuels industry will as well. Since our April 2009 industry assessment used 

for the NPRM, at least nine corn ethanol plants have come back online. 

 For analysis purposes, we assumed that all 27 idled corn/starch ethanol plants would 

resume operations by 2022 under the RFS2 program. We also assumed that a total of 11 new 

ethanol plants and two expansion projects currently under construction or in advanced stages of 

planning would come online.60 This includes two large dry mill expansion projects currently 

underway at existing ADM wet mill plants and two planned combination corn/cellulosic ethanol 

plants that received funding from DOE. While several of these projects are delayed or on hold at 

the moment, we expect that these facilities (or comparable replacement projects) would 

eventually come online to get the nation to approximately 15 billion gallons of corn ethanol 

production capacity. 

 Almost 100% of conventional ethanol plant growth is expected to come from facilities 

processing corn or other similarly processed grains. And not surprisingly, the majority of growth 

 

59 EIA, Annual Energy Outlook 2009 – ARRA Update (Table 12). 

60 Sources include Renewable Fuels Association, Ethanol Biorefinery Locations (updated October 22, 2009) and 

Ethanol Producer Magazine, Producing, Not Producing, Under Construction, and Expansions lists (last modified on 

October 22, 2009) in addition to information gathered from producer websites and follow-up correspondence. 
 

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(approximately 70% by volume) is expected to originate from PADD 2. However, growth is 

expected to occur in all PADDs. With the exception of one facility61, all new corn/grain ethanol 

plants are expected to utilize dry milling technologies and the majority of new production is 

expected to come from plants burning natural gas. However, we anticipate that two manure 

biogas plants62, one biomass-fired plant, and two coal-fired ethanol plants will be added to the 

mix.63 Of these new and returning idled plants, we’re aware of five facilities currently planning 

to use CHP technology, bringing the U.S. total to 32. 

 

 The above predictions are based on the industry’s current near-term production plans. 

However, we anticipate additional growth in advanced ethanol production technologies under the 

RFS2 program. Forecasted fuel prices are projected to drive corn ethanol producers to transition 

from conventional boiler fuels to biomass feedstocks. In addition, fossil fuel/electricity prices 

will likely drive a number of ethanol producers to pursue CHP technology. For more on our 

projected 2022 utilization of these technologies under the RFS2 program, refer to Section 1.5.1.3 

of the RIA. 

 

 2. Imported Ethanol 

 As discussed in the proposal, ethanol imports have traditionally played a relatively small 

role in the U.S. transportation fuel market due to historically low crude prices and the tariff on 

imported ethanol. Between years 2000 and 2008, the volume of ethanol imported into the U.S. 

 

61 Tate and Lyle is currently in the process of building a 115 MGY wet mill corn ethanol plant in Fort Dodge, IA. 

62 One manure biogas plant that is currently idled and another that was under construction but is now on hold. 

63 The two coal fired plants are the aforementioned dry mill expansion projects currently underway at existing ADM 

sites. These projects commenced construction on or before December 19, 2007 and would therefore should likely be 

grandfathered under the RFS2 rule. For more on our grandfathering assessment, refer to Section 1.5.1.4 of the RIA. 
 

327

has ranged from 46-720 million gallons per year. So far this year, from January through 

November 2009, imported ethanol has only reached 197 million gallons.64 As the data show, the 

volume of imported ethanol can fluctuate greatly. 

In the past, the majority of volume has originated from countries that are part of the 

Caribbean Basin Initiative. Direct Brazilian imports have also made up a sizeable portion of 

total ethanol imported into the U.S. However, recently there have been relatively small amounts 

of direct imports of ethanol from Brazil.65 This indicates that current market conditions have 

made importing Brazilian ethanol directly to the U.S. uneconomical. Part of the reason for this 

decline in imports is the cessation of the duty drawback that became effective on October 1, 

2008, but also changes in world sugar prices.66 

It is difficult to project the potential volume of future ethanol imports to the U.S based 

purely on historical data. Rather, it is necessary to assess future import potential by analyzing 

the major players for foreign ethanol production and consumption. In 2008, the top three fuel 

ethanol producers were the U.S., Brazil, and the European Union (EU), producing 9.0, 6.5, and 

0.7 billion gallons, respectively.67 Consumption of fuel ethanol is also dominated by the United 

States and Brazil with approximately 9.6 and 4.9 billion gallons consumed in each country, 

respectively.68,69 The EU consumed approximately 0.9 billion gallons of fuel ethanol in 2008.70 

 

64 Official Statistics of the U.S. Department of Commerce, U.S. ITC 

65 Approximately 19,000 gallons directly from Brazil in the month of June 2009 and 4 million gallons from Brazil in 

the month of November 2009, zero gallons reported from November 2008-May 2009 and July 2009-October 2009. 

66 Lundell, Drake, “Brazilian Ethanol Export Surge to End; U.S. Customs Loophole Closed Oct. 1,” Ethanol and 

Biodiesel News, Issue 45, November 4, 2008. 

67 Renewable Fuels Association (RFA), “2008 World Fuel Ethanol Production, ” 

http://www.ethanolrfa.org/industry/statistics/#E, March 31, 2009. 

68 Ibid. 

69 UNICA, “Sugarcane Industry in Brazil: Ethanol Sugar, Bioelectricity” Brochure, 2008. 
 

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 In our assessment of foreign ethanol production and consumption, we analyzed the 

following countries or group of countries: Brazil, the EU, Japan, India, and China. Our analyses 

indicate that Brazil would likely be the only nation able to supply any meaningful amount of 

ethanol to the U.S. in the future. Depending on whether the mandates and goals of the EU, 

Japan, India, and China are enacted or met in the future, it is likely that this group of countries 

would consume any growth in their own production and be net importers of ethanol, thus 

competing with the U.S. for Brazilian ethanol exports. 

 Due to uncertainties in the future demand for ethanol domestically and internationally, 

uncertainties in the actual investments made in the Brazilian ethanol industry, as well as 

uncertainties in future sugar prices, there appears to be a wide range of Brazilian production and 

domestic consumption estimates. The most current and complete estimates indicate that total 

Brazilian ethanol exports will likely reach 3.8-4.2 billion gallons by 2022.71,72,73 As this volume 

of ethanol export is available to countries around the world, only a portion of this will be 

available exclusively to the United States. If the balance of the EISA advanced biofuel 

requirement not met with cellulosic biofuel and biomass-based diesel were to be met with 

imported sugarcane ethanol alone, it would require about 2.2 billion gallons (see Table IV.A.2-

1), or approximately 55% of total Brazilian ethanol export estimates. This is aggressive, yet 

 70 EurObserv’ER, “Biofuels Barometer” July 2009, http://www.eurobserv-er.org/pdf/baro192.pdf. 

71 EPE, “Plano Nacional de Energia 2030,” Presentation from Mauricio Tolmasquim, 2007. 

72UNICA, “Sugarcane Industry in Brazil: Ethanol, Sugar, Bioelectricity,” 2008. 

73 USEPA International Visitors Program Meeting October 30, 2007, correspondence with Mr. Rodrigues Technical 

Director from UNICA Sao Paulo Sugarcane Agro-industry Union, stated approximately 3.7 billion gallons probable 

by 2017/2020; Consistent with brochure “Sugarcane Industry in Brazil: Ethanol Sugar, Bioelectricity” from UNICA 

(3.25 Bgal export in 2015 and 4.15 Bgal export in 2020) 
 

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within the bounds of reason, therefore, we have made this simplifying assumption for the 

purposes of further analysis. 

 

 Generally speaking, Brazilian ethanol exporters will seek routes to countries with the 

lowest costs for transportation, taxes, and tariffs. With respect to the U.S., the most likely route 

is through the Caribbean Basin Initiative (CBI).74 Brazilian ethanol entering the U.S. through 

CBI countries is not currently subject to the 54 cent/gal imported ethanol tariff and yet receives 

the 45 cent/gal ethanol blender credit. In addition to the U.S., other countries also have similar 

tariffs on imported ethanol. Refer to Section 1.5.2 of the RIA for more details. Due to the 

economic incentive of transporting ethanol through the CBI, we expect the majority of the tariff 

rate quota (TRQ) to be met or exceeded, perhaps 90% or more. The TRQ is set each year as 7% 

of the total domestic ethanol consumed in the prior year. If we assume that 90% of the TRQ is 

met and that total domestic ethanol (corn and cellulosic ethanol) consumed in 2021 was 19.2 

Bgal (under the primary control case), then approximately 1.21 Bgal of ethanol could enter the 

U.S. through CBI countries in 2022. The rest of the Brazilian ethanol exports not entering the 

CBI will compete on the open market with the rest of the world demanding some portion of 

direct Brazilian ethanol. To meet our advanced biofuel standard, we assumed 1.03 Bgal of 

sugarcane ethanol would be imported directly to the U.S. in 2022. 

 

3. Cellulosic Biofuel 

 

74 Other preferential trade agreements include the North American Free Trade Agreement (NAFTA) which permits 

tariff-free ethanol imports from Canada and Mexico and the Andean Trade Promotion and Drug Eradication Act 

(ATPDEA) which allows the countries of Columbia, Ecuador, Bolivia, and Peru to import ethanol duty-free. 

Currently, these countries export or produce relatively small amounts of ethanol, and thus we have not assumed that 

the U.S. will receive any substantial amounts from these countries in the future for our analyses. 
 

330

 The majority of the biofuel currently produced in the United States comes from plants 

processing first-generation feedstocks like corn, plant oils, sugarcane, etc. Non-edible cellulosic 

feedstocks have the potential to greatly expand biofuel production, both volumetrically and 

geographically. Research and development on cellulosic biofuel technologies has exploded over 

the last few years, and plants to commercialize a number of these technologies are already 

beginning to materialize. The $1.01/gallon tax credit for cellulosic biofuel that was introduced in 

the 2008 Farm Bill and recently became effective, is also offering much incentive to this 

developing industry. In addition to today’s RFS2 program which sets aggressive goals for 

cellulosic biofuel production, the Department of Energy (DOE), Department of Agriculture 

(USDA), Department of Defense (DOD) and state agencies are helping to spur industry growth. 

 a. Current State of the Industry 

 
 

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 There are a growing number of biofuel producers, biotechnology companies, universities 

and research institutes, start-up companies as well as refiners investigating cellulosic biofuel 

production. The industry is currently pursuing a wide range of feedstocks, conversion 

technologies and fuels. There is much optimism surrounding the long-term viability of cellulosic 

ethanol and other alcohols for gasoline blending. There is also great promise and growing 

interest in synthetic hydrocarbons like gasoline, diesel and jet fuel as “drop in” petroleum 

replacements. Some companies intend to start by processing corn or sugarcane and then 

transition to cellulosic feedstocks while others are focusing entirely on cellulosic materials. 

Regardless, cellulosic biofuel production is beginning to materialize. 

 We are currently aware of over 35 small pilot- and demonstration-level plants operating 

in North America. However, the main focus at these facilities is research and development, not 

commercial production. Most of the plants are rated at less than 250,000 gallons per year and 

that’s if they were operated at capacity. Most only operate intermittently for the purpose of 

demonstrating that the technologies can be used to produce transportation fuels. The industry as 

a whole is still working to increase efficiency, improve yields, reduce costs and prove to the 

public, as well as investors, that cellulosic biofuel is both technologically and economically 

feasible. 

 As mentioned above, a variety of feedstocks are being investigated for cellulosic biofuel 

production. There is a great deal of interest in urban waste (MSW and C&D debris) because it is 

virtually free and abundant in many parts of the country, including large metropolitan areas 

where the bulk of fuel is consumed. There is also a lot of interest in agricultural residues (corn 
 

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stover, rice and other cereal straws) and wood (forest thinnings, wood chips, pulp and paper mill 

waste and yard waste). However, researchers are still working to find viable harvesting and 

storage solutions. Others are investigating the possibility of growing dedicated energy crops for 

cellulosic biofuel production, e.g., switchgrass, energy cane, sorghum, poplar, miscanthus and 

other fast-growing trees. While these crops have tremendous potential, many are starting with 

the feedstocks that are available today with the mentality that once the industry has proven itself, 

it will be easier to secure growing contracts and start producing energy crops. For more 

information on cellulosic feedstock availability, refer to preamble Section IV.B.3.d and Section 

1.1.2 of the RIA. 

 The industry is also pursuing a number of different cellulosic conversion technologies 

and biofuels. Most of the technologies fall into one of two categories: biochemical or 

thermochemical. Biochemical conversion involves the use of acids and/or enzymes to hydrolyze 

cellulosic materials into fermentable sugars and lignin. Thermochemical conversion involves the 

use of heat to convert biomass into synthesis gas or pyrolysis oil for upgrading. A third 

technology pathway is emerging that involves the use of catalysts to depolymerize or reform the 

feedstocks into fuel. The technologies currently being considered are capable of producing 

cellulosic alcohols or hydrocarbons for the transportation fuel market. Many companies are also 

researching the potential of co-firing biomass to produce plant energy in addition to biofuels. 

For a more in-depth discussion on cellulosic technologies, refer to Section 1.4.3 of the RIA. 

 

 b. Setting the 2010 Cellulosic Biofuel Standard 
 

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 The Energy Independence and Security Act (EISA) set aggressive cellulosic biofuel 

targets beginning with 100 million gallons in 2010. However, EISA also supplied EPA with 

cellulosic biofuel waiver authority. For any calendar year in which the projected cellulosic 

biofuel production is less than the minimum applicable volume, EPA can reduce the standard 

based on the volume expected to be available that year. EPA is required to set the annual 

cellulosic standard by November 30th each year and should consider the annual estimate made by 

EIA by October 31st of each year. We are setting the 2010 standard as part of this final rule. 

 Setting the cellulosic biofuel standard for 2010 represents a unique challenge. As 

discussed above, the industry is currently characterized by a wide range of companies mostly 

focused on research, development, demonstration, and financing their developing technologies. 

In addition, while we are finalizing a requirement that producers and importers of renewable fuel 

provide us with production outlook reports detailing future supply estimates (refer to §80.1449), 

we do not have the benefit of this valuable cellulosic supply information for setting the 2010 

standard. Finally, since today’s cellulosic biofuel production potential is relatively small, and the 

number of potential producers few (as described in more detail below), the overall volume for 

2010 can be heavily influenced by new developments, either positive or negative associated with 

even a single company, which can be very difficult to predict. This is evidenced by the 

magnitude of changes in cellulosic biofuel projections and the potential suppliers of these fuels 

since the proposal. 

 In the proposal, we did a preliminary assessment of the cellulosic biofuel industry to 

arrive at the conclusion that it was possible to uphold the 100 million gallon standard in 2010 
 

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based on anticipated production. At the time of our April 2009 NPRM assessment, we were 

aware of a handful of small pilot and demonstration plants that could help meet the 2010 

standard, but the largest volume contributions were expected to come from Cello Energy and 

Range Fuels. 

 Cello Energy had just started up a 20 million gallon per year (MGY) cellulosic diesel 

plant in Bay Minette, AL. EPA staff visited the facility twice in 2009 to confirm that the first-ofits-kind commercial plant was mechanically complete and poised to produce cellulosic biofuel. 

It was assumed that start-up operations would go as planned and that the facility would be 

operating at full capacity by the end of 2009 and that three more 50 MGY cellulosic diesel plants 

planned for the Southeast could be brought online by the end of 2010. 

At the time of our assessment, we were also anticipating cellulosic biofuel production 

from Range Fuels’ first commercial-scale plant in Soperton, GA. The company received a $76 

million grant from DOE to help build a 40 MGY wood-based ethanol plant and they broke 

ground in November 2007. In January 2009, Range was awarded an $80 million loan guarantee 

from USDA.75 With the addition of this latest capital, the company seemed well on its way to 

completing construction of its first 10 MGY phase by the end of 2009 and beginning production 

in 2010. 

 Since our April 2009 industry assessment there have been a number of changes and 

delays in production plans due to technological, contractual, financial and other reasons. Cello 

Energy and Range Fuels have delayed or reduced their production plans for 2010. Some of the 

 

75 For more information on federal support for biofuels, refer to Section 1.5.3.3 of the RIA. 
 

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small plants expected to come online in 2010 have pushed back production to the 2011-2012 

timeframe, e.g., Clearfuels Technology, Fulcrum River Biofuels, and ZeaChem. Alltech/Ecofin 

and RSE Pulp & Chemical, two companies that were awarded DOE funding back in 2008 to 

build small-scale biorefineries appear to be permanently on hold or off the table. In addition, 

Bell Bio-Energy, a company that received DOD funding has since abandoned plans to produce 

cellulosic diesel from MSW at U.S. military bases.76 

 At the same time, there has also been an explosion of new companies, new business 

relationships, and new advances in the cellulosic biofuel industry. Keeping track of all of them 

is a challenge in and of it self as the situation can change on a daily basis. EIA recently provided 

EPA with their first cellulosic biofuel supply estimate required under CAA section 

211(o)(7)(D)(i). In a letter to the Administrator dated October 29, 2009, they arrived at a 5.04 

million gallon estimate for 2010 based on publicly available information and assumptions made 

with respect production capacity utilization.77 A summary of the plants they considered is shown 

below in Table IV.B.3-1. 

 

76 Bell Bio-Energy is currently investigating other locations for turning MSW into diesel fuel according to an 

October 14, 2009 conversation with JC Bell. 

77 Letter from Richard Newell, EIA Administrator to Lisa Jackson, EPA Administrator dated October 29, 2009 

(Table 2). 
 

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Table IV.B.3-1 

EIA’s Projected Cellulosic Biofuel Plant Production Capacities for 2010 

Online Company Location Product 

Capacity 

(million 

gallons) 

Expected 

Utilization 

(%) 

Production 

(million 

gallons)3

2007 KL Process Design Upton, WY Ethanol 1.5 10 0.15 

2008 Verenium Jennings, LA Ethanol 1.4 10 0.14 

2008 Terrabon Bryan, TX Bio-Crude 0.93 10 0.09 

2010 Zeachem Boardman, OR Ethanol 1.5 10 0.15 

2010 Cello Energy Bay Minette, AL Diesel 20.0 101 2.00 

2010 Range Fuels Soperton, GA Ethanol 5.02 50 2.5 

 Total 30.35 5.04 

Notes: 1. Cello Energy is assigned a 10-percent utilization factor as they have not been able to run on a continuous 

basis long enough to apply for a Synthetic Minor Operating Permit or produce significant amounts of fuel during 

2009. 2. It is estimated that only half the 2010 projected capacity (10 million gallons per year) will be a qualified 

fuel. 3. The production from these facilities in 2009 is not surveyed by EIA or EPA. 

 In addition to receiving EIA’s information and coordinating with them and other offices 

in DOE, we have initiated meetings and conversations with over 30 up-and-coming advanced 

biofuel companies to verify publicly available information, obtain confidential business 

information, and better assess the near-term cellulosic biofuel production potential for use in 

setting the 2010 standard. What we have found is that the cellulosic biofuel landscape has 

continued to evolve. Based on information obtained, not only do we project significantly 
 

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different production volumes on a company-by-company basis, but the list of potential producers 

of cellulosic biofuel in 2010 is also significantly different than that identified by EIA. 

 Overall, our industry assessment suggests that it is difficult to rely on commercial 

production from small pilot or demonstration-level plants. The primary purpose of these 

facilities is to prove that a technology works and demonstrate to investors that the process is 

capable of being scaled up to support a larger commercial plant. Small plants are cheaper to 

build to demonstrate technology than larger plants, but the operating costs ($/gal) are higher due 

to their small scale. As a result, it’s not economical for most of these facilities to operate 

continuously. Most of these plants are regularly shut down and restarted as needed as part of the 

research and development process. Due to their intermittent nature, most of these plants operate 

at a fraction of their rated capacity, some less than the 10% utilization rate assumed by EIA. In 

addition, few companies plan on making their biofuel available for commercial sale. 

 However, there are at least two cellulosic biofuel companies currently operating 

demonstration plants in the U.S. and Canada that could produce fuel commercially in 2010. The 

first is KL Energy Corporation, a company we considered for the NPRM with a 1.5 MGY 

cellulosic ethanol plant in Upton, WY. This plant was considered by EIA and is included in 

Table IV.B.3-1. The second is Iogen’s cellulosic ethanol plant in Ottawa, Canada with a 0.5 

MGY capacity. Iogen’s commercial demonstration plant was referenced by EIA as a potential 

foreign source for cellulosic biofuel but was not included in their final table. In addition to these 

online demonstration plants, there are three additional companies not on EIA’s list that are 

currently building demonstration-level cellulosic biofuel plants in North America that are 
 

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scheduled to come online in 2010. This includes DuPont Danisco Cellulosic Ethanol and 

Fiberight, companies building demonstration plants in the U.S. and Enerkem, a company 

building a demonstration plant in Canada. Cello Energy’s plant in Bay Minette, AL continues to 

offer additional potential for cellulosic biofuel in 2010. And finally, Dynamotive, a company 

that currently has two biomass-based pyrolysis oil production plants in Canada is another 

potential source of cellulosic biofuel in 2010. All seven aforementioned companies are 

discussed in greater detail below along with Range Fuels. 

KL Energy Corporation (KL Energy), through its majority-owned Western Biomass 

Energy, LLC (WBE) located in Upton, WY, is designed to convert wood products and wood 

waste products into ethanol. Since the end of construction in September 2007, equipment 

commissioning and process revisions continued until the October 2009 startup. The plant was 

built as a 1.5 MGY demonstration plant and was designed to both facilitate research and operate 

commercially. It is KL Energy’s intent that WBE’s future use will involve the production and 

sale of small but commercial-quality volumes of ethanol and lignin co-product. The company’s 

current 2010 goal is for WBE to generate RINs under the RFS2 program.78 

 Iogen is responsible for opening the first commercial demonstration cellulosic ethanol 

plant in North America. Iogen’s plant located in Ottawa, Canada has been producing cellulosic 

ethanol from wheat straw since 2004. Like KL Energy, Iogen has slowly been ramping up 

production at its 0.5 MGY plant. According to the company’s website, they produced 

approximately 24,000 gallons in 2004 and 34,000 gallons in 2005. Production dropped 

 

78 Based on information provided by Lori Litzen, Environmental Permit Engineer at KL Energy on December 10, 

2009. 
 

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dramatically in 2006 and 2007 but came back strong with 55,000 gallons in 2008. Iogen recently 

produced over 150,000 gallons of ethanol from the demonstration plant in 2009. Iogen also 

recently became the first cellulosic ethanol producer to sell its advanced biofuel at a retail service 

station in Canada. Their cellulosic ethanol was blended to make E10 available for sale to 

consumers at an Ottawa Shell station. Iogen also recently announced plans to build its first 

commercial scale plant in Prince Albert, Saskatchewan in the 2011/2012 timeframe. Based on 

the company’s location and operating status, Iogen certainly has the potential to participate in the 

RFS2 program. However, at this time, we are not expecting them to import any cellulosic 

ethanol into the U.S. in 2010.79 

 DuPont Danisco Cellulosic Ethanol, LLC (DDCE), a joint venture between DuPont and 

Danisco, is another potential source for cellulosic biofuel in 2010. DDCE received funding from 

the State of Tennessee and the University of Tennessee to build a small 0.25 MGY 

demonstration plant in Vonore, TN to pursue switchgrass-to-ethanol production. According to 

DDCE, construction commenced in October 2008 and the plant is now mechanically complete 

and undergoing start-up operations. The facility is scheduled to come online by the end of 

January and the company hopes to operate at or around 50% of production capacity in 2010. 

According to the DDCE, the objective in Vonore is to validate processes and data for 

commercial scale-up, not to make profits. However, the company does plan to sell the cellulosic 

ethanol it produces.80

 

79 Based on website information, comments submitted in response to our proposal, and a follow-up phone call with 

Iogen Executive VP, Jeff Passmore on December 17, 2009. 

80 Based on a December 16, 2009 telephone conversation with DDCE Director of Corporate Communications, 

Jennifer Hutchins and follow-up e-mail correspondence. 
 

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 Enerkem is another company pursuing cellulosic ethanol production. The Canadianbased company was recently announced as a recipient of a joint $50 million grant from DOE and 

USDA to build a 10 MGY woody biomass-to-ethanol plant in Pontotoc, MS.81 The U.S. plant is 

not scheduled to come online until 2012, but Enerkem is currently building a 1.3 MGY 

demonstration plant in Westbury, Quebec. According to the company, plant construction in 

Westbury started in October 2007 and the facility is currently scheduled to come online around 

the middle of 2010. While it’s unclear at this time whether the cellulosic ethanol produced will 

be exported to the United States, Enerkem has expressed interest in selling its fuel 

commercially.82 

 Additional cellulosic biofuel could come from Fiberight, LLC (Fiberight) in 2010. We 

recently became aware of this start-up company and contacted them to learn more about their 

process and cellulosic biofuel production plans. According to Fiberight, they have been 

operating a pilot-scale facility in Lawrenceville, VA for three years. They have developed a 

proprietary process that not only fractionates MSW but biologically converts the non-recyclable 

portion into cellulosic ethanol and biochemicals. Fiberight recently purchased a shut down corn 

ethanol plant in Blairstown, IA and plans to convert it to become MSW-to-ethanol capable. 

According to the company, construction is currently underway and the goal is to bring the 2 

MGY demonstration plant online by February or March, 2010. If the plant starts up according to 

plan, the company intends on making cellulosic ethanol commercially available in 2010 and 

generating RINS under the RFS2 program. Fiberight’s long-term goal is to expand the 

 

81 Refer to December 4, 2009 DOE press release entitled, “Recovery Act Announcement: Secretaries Chu and 

Vilsack Announce More Than $600 Million Investment in Advanced Biorefinery Projects. 

82 Based on an October 14, 2009 meeting with Enerkem and follow-up telephone conversation with VP of 

Government Affairs, Marie-Helene Labrie on December 14, 2009. 
 

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Blairstown plant to a 5-8 MGY capacity and build other small commercial plants around the 

country that could convert MSW into fuel.83 

 

Cello Energy, a company considered in the proposal, continues to be another viable 

source for cellulosic biofuel in 2010. Despite recent legal issues which have constrained the 

company’s capital, Cello Energy is still pursuing cellulosic diesel production. According to the 

company, they are currently working to resolve materials handling and processing issues that 

surfaced when they attempted to scale up production to 20 MGY from a previously operated 

demonstration plant. As of November 2009, they were waiting for new equipment to be ordered 

and installed which they hoped would allow for operations to be restarted as early as February or 

March, 2010. Cello’s other planned commercial facilities are currently on hold until the Bay 

Minette plant is operational.84 

 

 Another potential supplier of cellulosic biofuel is Dynamotive Energy Systems 

(Dynamotive) headquartered in Vancouver, Canada. Dynamotive currently has two plants in 

West Lorne and Guelph, Ontario that produce biomass-based pyrolysis oil (also known as 

“BioOil”) for industrial applications. The BioOil production capacity between the two plants is 

estimated at around 9 MGY, but both plants are currently operating at a fraction of their rated 

capacity.85 However, according to a recent press release, Dynamotive has contracts in place to 

 

83 Based on a December 15, 2009 telephone conversation with Fiberight CEO, Craig Stuart-Paul and follow-up email correspondence. 

84 Based on a November 9, 2009 telephone conversation with Cello Energy CEO, Jack Boykin. 

85 According to Dynamotive’s website, the Guelph plant has a capacity to convert 200 tonnes of biomass into BioOil 

per day. If all modules are fully operational, the plant has the ability to process 66,000 dry tons of biomass per year 

with an energy output equivalent to 130,000 barrels of oil. The West Lorne plant has a capacity to convert 130 

tonnes of biomass into BioOil per day which, if proportional to the Guelph plant, translates to an energy-equivalent 

of 84,500 barrels of oil. According to a November 3, 2009 press release, Dynamotive has contracts in place to 

supply a U.S.-based client with at least nine shipments of BioOil in 2010. 
 

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supply a U.S.-based client with at least nine shipments of BioOil in 2010. If Dynamotive’s 

BioOil is used as heating oil or upgraded to transportation fuel, it could potentially count towards 

meeting the cellulosic biofuel standard in 2010. 

 As for the Range Fuels plant, construction of phase one in Soperton, GA is about 85% 

complete, with start-up planned for mid-2010. However, there have been some changes to the 

scope of the project that will limit the amount of cellulosic biofuel that can be produced in 2010. 

The initial capacity has been reduced from 10 to 4 million gallons per year. In addition, since 

they plan to start up the plant using a methanol catalyst they are not expected to produce 

qualifying renewable fuel in 2010. During phase two of their project, currently slated for mid2012, Range plans to expand production at the Soperton plant and transition from a methanol to 

a mixed alcohol catalyst. This will allow for a greater alcohol production potential as well as a 

greater cellulosic biofuel production potential.86 

 

Overall, our most recent industry assessment suggests that there could potentially be over 

30 MGY of cellulosic biofuel production capacity online by the end of 2010.87 However, since 

most of the plants are still under construction today, the amount of cellulosic biofuel produced in 

2010 will be contingent upon when and if these plants come online and whether the projects get 

delayed due to funding or other reasons. In addition, based on our discussions with the 

developing industry, it is clear that we cannot count on demonstration plants to produce at or 

near capacity in 2010, or in their first few years of operation for that matter. The amount of 

cellulosic biofuel actually realized will depend on whether the process works, the efficiency of 

 

86 Based on a November 5, 2009 telephone conversation with Range Fuels VP of Government Affairs, Bill Schafer. 

87 For more information, refer to Section 1.5.3.2 of the RIA. 
 

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the process, and how regularly the plant is run. As mentioned earlier, most small plants, 

including commercial demonstration plants, are not operated continuously. As such, we cannot 

base the standard on these plants running at capacity - at least until the industry develops further 

and proves that such rates are achievable. We currently estimate that production from first-ofit’s kind plants could be somewhere in the 25-50% range in 2010. Together, the implementation 

timelines and anticipated production levels of the plants described above brings the cellulosic 

biofuel supply estimate to somewhere in the 6-13 million gallon range for 2010. 

In addition, it is unclear how much was can rely on Canadian plants for cellulosic biofuel 

in 2010. Although we currently receive some conventional biofuel imports from Canada and 

many of the aforementioned Canadian companies have U.S. markets in mind, the country also 

has its own renewable fuel initiatives that could keep much of the cellulosic biofuel produced 

from coming to the United States, e.g., Iogen. Finally, it’s unclear whether all fuel produced by 

these facilities will qualify as cellulosic biofuel under the RFS2 program. Several of the 

companies are producing fuels or using feedstocks which may not in fact qualify as cellulosic 

biofuel once we receive their detailed registration information. Factoring in these considerations, 

the cellulosic biofuel potential from the six more likely companies described above could result 

in several different production scenarios in the neighborhood of the recent EIA estimate. We 

believe this estimate of 5 million gallons or 6.5 ethanol-equivalent million gallons represents a 

reasonable yet achievable level for the cellulosic biofuel standard in 2010 considering the degree 

of uncertainty involved with setting the standard for the first year. As mentioned earlier, we 

believe standard setting will be easier in future years once the industry matures, we start 
 

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receiving production outlook reports and there is less uncertainty regarding feasibility of 

cellulosic biofuel production. 

 c. Current Production Outlook for 2011 and Beyond 

 Since the proposal, we have also learned about a number of other cellulosic biofuel 

projects in addition to those described above. This includes commercial U.S. production plans 

by Coskata, Enerkem and Vercipia. However, production isn’t slated to begin until 2011 or later 

and the same is true for most of the other larger plants we’re aware of that are currently under 

development. Nonetheless, while cellulosic biofuel production in 2010 may be limited, it is 

remarkable how much progress the industry has made in such a short time, and there is a 

tremendous growth opportunity for cellulosic biofuels over the next several years. 

 Most of the cellulosic biofuel companies we’ve talked to are in different stages of 

proving their technologies. Regardless of where they are at, many have fallen behind their 

original commercialization schedules. As with any new technology, there have been delays 

associated with scaling up capacity, i.e., bugs to work out going from pilot to demonstration to 

commercialization. However, most are saying it’s not the technologies that are delaying 

commercialization, it is lack of available funding. Obtaining capital has been very challenging 

given the current recession and the banking sector's financial difficulties. This is especially true 

for start-up companies that do not have access to capital through existing investors, plant profits, 

etc. From what we understand, banks are looking for cellulosic companies to be able to show 

that their plants are easily “scalable” or expandable to commercial size. Many are only 
 

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considering companies that have built plants to one-tenth of commercial scale and have logged 

many hours of continuous operation. 

 The government is currently trying to help in this area. To date, the Department of 

Energy (DOE) and the Department of Agriculture (USDA) have allocated over $720 million in 

federal funding to help build pilot and demonstration-scale biorefineries employing advanced 

technologies in the United States. The largest installment from Recovery Act funding was 

recently announced on December 4, 2009 and includes funding for a series of larger commercial 

demonstration plants including cellulosic ethanol projects by Enerkem and INEOS New Planet 

BioEnergy, LLC. DOE has also issued grants to help fund some of the first commercial 

cellulosic biofuel plants. Current recipients include Abengoa Bioenergy, BlueFire Ethanol88 and 

POET Biorefining in addition to Range Fuels. DOE and USDA are also issuing loan guarantees 

to help support the up-and-coming cellulosic biofuels industry and funding research and 

development. Many states are also providing assistance. For more information on government 

support for biofuels, refer to Section 1.5.3.3 of the RIA. 

 The refining industry is also helping to fund cellulosic biofuel R&D efforts and some of 

the first commercial plants. Many of the major oil companies have invested in advanced secondgeneration biofuels over the past 12-18 months. A few refiners (e.g., BP and Shell) have even 

entered into joint ventures to become cellulosic biofuel producers. General Motors and other 

 

88 Although BlueFire is still working on obtaining financing to build its first demonstration plant, it has received two 

installments of federal funding towards its first planned commercial-scale plant. The 19 MGY plant planned for 

Fulton, MS (originally planned for Southern California) was awarded $40 million from DOE on February 28, 2008 

and another $81.1 million from DOE and USDA on December 4, 2009. 
 

346

vehicle/engine manufacturers are also providing financial support to help with research and 

development. 

 A summary of some of the cellulosic biofuel companies with near-term 

commercialization plans in North America is provided in Table IV.B.3-2. The capacities 

presented represent maximum annual average throughput based on each company’s current 

production plans. However, as noted, capacity does not necessarily translate to production. 

Actual production of cellulosic biofuel will likely be well below capacity, especially in the early 

years of production. We will continue to track these companies and the cellulosic biofuel 

industry as a whole throughout the duration of the RFS2 program. In addition, we will continue 

to collaborate with EIA in annual standard setting. A more detailed discussion of the plants 

corresponding to these company estimates is provided in Section 1.5.3 of the RIA. 
347

Table IV.B.3-2 

 Potential Growth in Cellulosic Biofuel Capacity by Company and Year* 
348

Today Dec-10 Dec-11 Dec-12 Dec-13 2014+

Abengoa Ethanol 0.02 0.02 0.02 16.02 16.02 16.02

AE Biofuels Ethanol 0.15 0.15 15.15 20.15 20.15 20.15

BlueFire Ethanol Ethanol - - - - - 22.90

Cello Energy Diesel - 20.00 20.00 20.00 20.00 120.00

CMEC / SunOpta Ethanol - - - - - 10.00

Coskata Ethanol 0.04 0.04 0.04 50.04 50.04 100.04

Dynamotivea BioOil 9.00 9.00 9.00 9.00 9.00 9.00

Enerkem Ethanol - 1.30 11.30 21.30 21.30 41.30

Fiberight Ethanol - 2.00 6.50 6.50 6.50 6.50

Flambeau River Biofuels Diesel - - - 8.00 8.00 8.00

Fulcrum Bioenergy Ethanol - - - 10.50 10.50 10.50

Inbicon / Great River Energy Ethanol - - - - 20.00 20.00

INEOS Bio / New Planet Energy Ethanol - - 8.00 8.00 8.00 8.00

Iogen Ethanol 0.50 0.50 0.50 23.50 23.50 23.50

KL Energy Ethanol 1.50 1.50 1.50 1.50 1.50 6.50

Mascoma Corporation Ethanol 0.20 0.20 0.20 2.20 20.20 80.20

New Page Diesel - - - 2.50 2.50 2.50

Ohio River Clean Fuels / Baardb Diesel, Naphtha - - - - - 17.00

Pacific Ethanol Ethanol - - - - - 2.70

POET Biorefining Ethanol 0.02 0.02 25.02 25.02 25.02 25.02

Range Fuels Methanol, Ethanol - 4.00 4.00 30.00 30.00 100.00

Rentechc Diesel - - 0.15 7.15 7.15 7.15

Vercipia (Verenium/BP JV) Ethanol 1.40 1.40 1.40 37.40 37.40 37.40

Maximum Plant Capacity (MGY) 12.83 40.13 102.78 298.78 336.78 694.38

Capacity Expansion Plans (MGY)

Biofuel(s)

Plant will co-process biomass and coal. It is unclear at this time how much fuel would come from biomass and potentially quali bCapacity has been estimated. a

Cellulosic Company

fy as 

c

cellulosic biofuel.

Includes Clearfuels demo plant and Silvagas commercial plant.

*Capacity, not actual production
 

349

 d. Feedstock Availability 

 A wide variety of feedstocks can be used for cellulosic biofuel production, including: 

agricultural residues, forestry biomass, certain renewable portions of municipal solid waste and 

construction and demolition waste (i.e., separated food, yard and incidental, and post-recycled 

paper and wood waste as discussed in Section II.B.4) and energy crops. These feedstocks are 

currently much more difficult to convert into biofuel than traditional corn/starch crops or at least 

require new and different processes because of the more complex structure of cellulosic material. 

 To determine the likely cellulosic feedstocks for production of 16 billion gallons 

cellulosic biofuel by 2022, we analyzed the data and results from various sources. Sources 

include agricultural modeling from the Forestry Agriculture Sector Optimization Model 

(FASOM) to determine the most economical volume of agriculture residues, energy crops, and 

forestry resources (see Section VIII for more details on the FASOM) used to meet the standard. 

We supplemented these estimates with feedstock assessment estimates for the biomass portions 

of municipal solid waste and construction and demolition waste.89 

 The following subsections describe the availability of various cellulosic feedstocks and 

the estimated amounts from each feedstock needed to meet the EISA requirement of 16 Bgal of 

 

89 It is important to note that our original plant siting analysis for cellulosic ethanol facilities used the most current 

version of outputs from FASOM at the time, which was from April 2008. The siting analysis was used to inform the 

air quality modeling, which requires long leadtimes. Since then, FASOM has been updated to reflect better 

assumptions. Therefore, the version used for the FRM in Section VIII on economic impacts is different from the 

one used for the plant siting analysis in the NPRM. We do not believe that the differences between the two versions 

are enough to have a major impact on the plant siting analysis. 
 

350

cellulosic biofuel by 2022. Refer to Section IV.B.2.c.iv for the summarized results of the types 

and volumes of cellulosic feedstocks chosen based on our analyses. 

 i. Urban Waste 

 Cellulosic feedstocks available at the lowest cost to the ethanol producer will likely be 

chosen first. This suggests that urban waste which is already being gathered today and incurs a 

fee for its disposal may be among the first to be used. Urban wastes are used in a variety of 

ways. Most commonly, wastes are ground into mulch, dumped into land-fills, or incinerated. We 

describe two components of urban waste, municipal solid waste (MSW) and construction and 

demolition (C&D) debris, below. 

 MSW consists of paper, glass, metals, plastics, wood, yard trimmings, food scraps, 

rubber, leather, textiles, etc. The portion of MSW that can qualify as renewable biomass under 

the program is discussed in Section II.B.4.d. The bulk of the biogenic portion of MSW that can 

be converted into biofuel is cellulosic material such as wood, yard trimmings, paper, and much 

of food wastes. Paper made up approximately 31% of the total MSW generated in 2008.90 

Although recycling/recovery rates are increasing over time, there appears to still be a large 

fraction of biogenic material that ends up unused and in land-fills. C&D debris is typically not 

available in wood waste assessments, although some have estimated this feedstock based on 

population. Utilization of such feedstocks could help generate energy or biofuels for 

transportation. However, despite various assessments on urban waste resources, there is still a 

 

90 EPA. Municipal Solid Waste Generation, Recycling, and Disposal in the United States: Facts and figures for 

2008. 
 

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general lack of reliable data on delivered prices, issues of quality (potential for contamination), 

and lack of understanding of potential competition with other alternative uses (e.g., recycling, 

burning for electricity). 

 We estimated that a total of 44.5 million dry tons of MSW (wood, yard trimmings, paper, 

and food waste) and C&D wood waste could be available for producing biofuels after factoring 

in several assumptions, e.g., percent contamination, percent recovered or combusted for other 

uses, and percent moisture.91,92 Between the proposal and this final rule, we have updated the 

assumptions noted above based on newer reports. It should be noted, however, that our estimates 

of urban waste availability have not changed significantly between the proposal and the final 

rule. We assumed that approximately 26 million dry tons (of the total 44.5 million dry tons) 

could be used to produce biofuels. However, many areas of the U.S. (e.g., much of the Rocky 

Mountains) have such sparse resources that an MSW and C&D cellulosic facility would not 

likely be justifiable. We did assume that in areas with other cellulosic feedstocks (forest and 

agricultural residue), that the MSW would be used even if the MSW could not justify the 

installation of a plant on its own. Therefore, we have estimated that urban waste could help 

contribute to the production of approximately 2.3 ethanol-equivalent billion gallons of fuel.93 

Note that some processes are likely to also process other portions of MSW (e.g., plastics, 

rubbers) into fuel, but we have only accounted for the portion expected to qualify as renewable 

fuel and produce RINs. 

 

91 Wiltsee, G. , “Urban Wood Waste Resource Assessment,” NREL/SR-570-25918, National Renewable Energy 

Laboratory, November 1998 

92 Biocycle, “The State of Garbage in America,” Vol. 49, No. 12, December 2008, p. 22. 

93 Assuming 90 gal/dry ton ethanol conversion yield for urban waste in 2022 
 

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 In addition to MSW and C&D waste generated from normal day-to-day activities, there is 

also potential for renewable biomass to be generated from natural disasters. This includes 

diseased trees, other woody debris, and C&D debris. For instance, Hurricane Katrina was 

estimated to have damaged approximately 320 million large trees.94 Katrina also generated over 

100 million tons of residential debris, not including the commercial sector. Much of this waste 

would likely be disposed of and therefore go unused. Collection of this material for the 

generation of biofuel could be a better alternative use for this waste. While we acknowledge this 

material could provide a large source in the short-term, natural disasters are highly variable, 

making it hard to predict amounts of material available in the future. Thus, for our analyses we 

have not included natural disaster renewable biomass in our estimates. 

 ii. Agricultural and Forestry Residues

 The next category of feedstocks chosen will likely be those that are readily produced but 

have not yet been commercially collected. This includes both agricultural and forestry residues. 

 Agricultural residues are expected to play an important role early on in the development 

of the cellulosic ethanol industry due to the fact that they are already being grown. Agricultural 

crop residues are biomass that remains in the field after the harvest of agricultural crops. The 

most common residues are corn stover (the stalks, leaves, and/or cobs) and straw from wheat, 

rice, barley, and oats. These U.S. crops and others produce more than 500 million tons of 

residues each year, although only a fraction can be used for fuel and/or energy production due to 

 

94 Chambers, J., “Hurricane Katrina’s Carbon Footprint on U.S. Gulf Coast Forests” Science Vol. 318, 2007. 
 

353

sustainability and conservation constraints.95 Crop residues can be found all over the United 

States, but are primarily concentrated in the Midwest since corn stover accounts for half of all 

available agricultural residues. 

 Agricultural residues play an important role in maintaining and improving soil quality, 

protecting the soil surface from water and wind erosion, helping to maintain nutrient levels, and 

protecting water quality. Thus, collection and removal of agricultural residues raise concerns 

about the potential for increased erosion, reduced crop productivity, depletion of soil carbon and 

nutrients, and water pollution. Sustainable removal rates for agricultural residues have been 

estimated in various studies, many showing tremendous variability due to local differences in 

soil and erosion conditions, soil type, landscape (slope), tillage practices, crop rotation 

managements, and the use of cover crops. One of the most recent studies by top experts in the 

field shows that under current rotation and tillage practices, about 30% of corn stover (about 59 

million metric tons) produced in the U.S. could be collected, taking into consideration erosion, 

soil moisture concerns, and nutrient replacement costs.96 The same study shows that if farmers 

convert to no-till corn management and total stover production does not change, then 

approximately 50% of stover (100 million metric tons) could be collected without causing 

erosion to exceed the tolerable soil loss. This study, however, did not consider possible soil 

carbon loss which other studies indicate may be a greater constraint to environmentally 

sustainable feedstock harvest than that needed to control water and wind erosion.97 Experts 

 

95 Elbehri, Aziz. USDA, ERS. “An Evaluation of the Economics of Biomass Feedstocks: A Synthesis of the 

Literature. Prepared for the Biomass Research and Development Board,” 2007; Since 2007, a final report has been 

released. Biomass Research and Development Board., “The Economics of Biomass Feedstocks in the United States: 

A Review of the Literature,” October 2008. 

96 Graham, R.L., “Current and Potential U.S. Corn Stover Supplies,” American Society of Agronomy 99:1-11, 2007. 97 Wilhelm, W.W. et. al., “Corn Stover to Sustain Soil Organic Carbon Further Constrains Biomass Supply,” Agron. 

J. 99:1665-1667, 2007. 
 

354

agree that additional studies are needed to further evaluate how soil carbon and other factors 

affect sustainable removal rates. Despite unclear guidelines for sustainable removal rates due to 

the uncertainties explained above, our agricultural modeling analysis assumes that no stover is 

removable on conventional tilled lands, 35% of stover is removable on conservation tilled lands, 

and 50% is removable on no-till lands. In general, these removal guidelines are appropriate only 

for the Midwest, where the majority of corn is currently grown. 

 As already noted, removal rates will vary by region due to local differences. Given the 

current understanding of sustainable removal rates, we believe that such assumptions are 

reasonably justified. Based on our research, we also note that calculating residue maintenance 

requirements for the amount of biomass that must remain on the land to ensure soil quality is 

another approach for modeling sustainable residue collection quantities. This approach would 

likely be more accurate for all landscapes as site-specific conditions such as soil type, 

topography, etc. could be taken into account. This would prevent site-specific soil erosion and 

soil quality concerns that would inevitably exist when using average values for residue removal 

rates across all soils and landscapes. At the time of our analyses, however, we had limited data 

on which to accurately apply this approach and therefore assumed the removal guidelines based 

on tillage practices. 

 

 Our agricultural modeling (FASOM) suggests that corn stover will make up the majority 

of agricultural residues used by 2022 to meet the EISA cellulosic biofuel standard (4.9 ethanolequivalent Bgal).98 Smaller contributions are expected to come from other crop residues 

 

98 Assuming 92.3 gal/dry ton ethanol conversion yield for corn stover in 2022 
 

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including sugarcane bagasse (0.6 ethanol-equivalent Bgal), wheat residues (0.1 ethanolequivalent Bgal), and sweet sorghum pulp (0.1 ethanol-equivalent Bgal).99 

 The U.S. also has vast amounts of forest resources that could potentially provide 

feedstock for the production of cellulosic biofuel. One of the major sources of woody biomass 

could come from logging residues. The U.S. timber industry harvests over 235 million dry tons 

annually and produces large volumes of non-merchantable wood and residues during the 

process.100 Logging residues are produced in conventional harvest operations, forest management 

activities, and clearing operations. In 2004, these operations generated approximately 67 million 

dry tons of forest residues that were left uncollected at harvest sites.101 Other feedstocks include 

those from other removal residues, thinnings from timberland, and primary mill residues. 

 For the NPRM, FASOM was not able to model forestry biomass as a potential feedstock. 

As a result, we relied on USDA-Forest Service (FS) for information on the forestry sector at the 

time. For the final rule, we were able to incorporate the forestry sector model in FASOM. EISA 

does not allow forestry material from national forests and virgin forests that could be used to 

produce biofuels to count towards the renewable fuels requirement under EISA. Therefore, our 

modeling of forestry biomass excluded such material. The FASOM model estimated that 

approximately 0.1 ethanol-equivalent billion gallons would be produced from forestry biomass to 

meet EISA. 

 

99 Bagasse is a byproduct of sugarcane crushing and not technically an agricultural residue. Sweet sorghum pulp is 

also a byproduct of sweet sorghum processing. We have included it under this heading for simplification due to 

sugarcane and sorghum being an agricultural feedstock. 

100 Smith, W. Brad et. al., ”Forest Resources of the United States, 2002 General Technical Report NC-241,” St. Paul, 

MN: U.S. Dept. of Agriculture, Forest Service, North Central Research Station, 2004. 

101 USDA-Forest Service. “Timber Products Output Mapmaker Version 1.0.” 2004. 
 

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 iii. Dedicated Energy Crops 

 While urban waste, agricultural residues and forest residues will likely be the first 

feedstocks used in the production of cellulosic biofuel, there may be limitations to their use due 

to land availability and sustainable removal rates. Energy crops which are not yet grown 

commercially but have the potential for high yields and a series of environmental benefits could 

help provide additional feedstocks in the future. Dedicated energy crops are plant species grown 

specifically for energy purposes. Various perennial plants have been researched as potential 

dedicated feedstocks, including switchgrass, mixed prairie grasses, hybrid poplar, miscanthus, 

energy cane, energy sorghum, and willow trees. Refer to Section 1.1.2.2 of the RIA for more 

information on the benefits and challenges with using dedicated energy crops. 

 In addition to estimating the extent that agricultural residues might contribute to 

cellulosic ethanol production, FASOM also estimated the contribution that energy crops might 

provide (7.9 ethanol-equivalent Bgal).102 FASOM covers all cropland and pastureland in 

production in the 48 contiguous United States. For the NPRM, FASOM did not contain all 

categories of grassland and rangeland captured in USDA’s Major Land Use data sets. For the 

final rule, FASOM accounts for all major land categories, including forestland and rangeland. 

All crop production, including dedicated energy crops, takes place on cropland. Land categories 

that can be converted to cropland production include cropland pasture, forest pasture, and 

forestland. More detail can be found in Chapter VIII of this preamble. Furthermore, we 

 

102 Assuming 16 Bgal cellulosic biofuel total, 2.3 Bgal from Urban Waste; 13.7 Bgal of cellulosic biofuel for ag 

residues, forestry biomass, and/or energy crops would be needed. 
 

357

constrained FASOM to be consistent with the 2008 Farm Bill and assumed 32 million acres 

would stay in Conservation Reserve Program (CRP).103 Other models, such as USDA’s 

Regional Environment and Agriculture Programming (REAP) model and University of 

Tennessee’s POLYSYS model, have shown that the use of energy crops to meet EISA could be 

significant, similar to our FASOM modeling results for the final rule.104 

 iv. Summary of Cellulosic Feedstocks for 2022

 Table IV.B.3-3 summarizes our internal estimate of the types of cellulosic feedstocks 

projected to be used and their corresponding volume contribution to 16 billion gallons cellulosic 

biofuel by 2022 for the purposes of our impacts assessment. The majority of feedstock is 

projected to come from dedicated energy crops. Other feedstocks include agricultural residues, 

forestry biomass, and urban waste. 

 

103 Beside the economic incentive of a farmer payment to keep land in CRP, local environmental interests may also 

fight to maintain CRP land for wildlife preservation. Also, we did not know what portion of the CRP is wetlands 

which likely could not support harvesting equipment. 

104 Biomass Research and Development Initiative (BR&DI), “Increasing Feedstock Production for Biofuels: 

Economic Drivers, Environmental Implications, and the Role of Research,” http://www.brdisolutions.com, 

December 2008. 
 

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Table IV.B.3-3 

Cellulosic Feedstocks Assumed To Meet EISA In 2022105 

Feedstock 

Volume 

(Ethanol-equivalent Bgal) 

Agricultural Residues 5.7 

Corn Stover 4.9 

Sugarcane Bagasse 0.6 

Wheat Residue 0.1 

Sweet Sorghum Pulp 0.1 

Forestry Biomass 0.1 

Urban Waste 2.3 

Dedicated Energy Crops 

(Switchgrass) 

7.9 

Total 16.0 

 

 4. Biodiesel & Renewable Diesel

 Biodiesel and renewable diesel are replacements for petroleum diesel that are made from 

plant or animal fats. Biodiesel consists of fatty acid methyl esters (FAME) and can be used in 

low-concentration blends in most types of diesel engines and other combustion equipment with 

no modifications. The term renewable diesel covers fuels made by hydrotreating plant or animal 

 

105 Volumes are represented here as ethanol-equivalent volumes, a mix of diesel and ethanol volumes as described in 

Section IV.A, above. 
 

359

fats in processes similar to those used in refining petroleum. Renewable diesel is chemically 

analogous to blendstocks already used in petroleum diesel, thus its use can be transparent and its 

blend level essentially unlimited. The goal of both biodiesel and renewable diesel conversion 

processes is to change the properties of a variety of feedstocks to more closely match those of 

petroleum diesel (such as its density, viscosity, and storage stability) for which the engines have 

been designed. The definition of biodiesel given in applicable regulations is sufficiently broad to 

be inclusive of both fuels.106 However, the EISA stipulates that renewable diesel that is coprocessed with petroleum diesel cannot be counted as biomass-based diesel for purposes of 

complying with the RFS2 volume requirements.107

 In general, plant and animal oils are valuable commodities with many uses other than 

transportation fuel. Therefore we expect the primary limiting factor in the supply of both 

biodiesel and renewable diesel to be feedstock availability and price. Expansion of their market 

volumes is dependent on being able to compete on price with the petroleum diesel they are 

displacing, which will depend largely on continuation of current subsidies and other incentives. 

 Other biomass-based diesel fuel processes are at various stages of development, but due 

to uncertainty on production timelines, we didn’t include these fuels in the biomass-based diesel 

impact assessments. 

 a. Historic and Projected Production

 

106 See Section 1515 of the Energy Policy Act of 2005. More discussion of the definitions of biodiesel and 

renewable diesel are given in the preamble of the Renewable Fuel Standard rulemaking, Section II.B.2, as published 

in the Federal Register Vol.72, No. 83, p.23917. 

107 For more detailed discussion of the definition of coprocessing and its implications for compliance with EISA, see 

Section II.B.1 of this preamble. 
 

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 i. Biodiesel

As of November 2009, the aggregate production capacity of biodiesel plants in the U.S. 

was estimated at 2.8 billion gallons per year across approximately 191 facilities.108 (However, at 

the time of this writing it is anticipated that capacity utilization will be approximately 17% for 

calendar year 2009.) Biodiesel plants exist in nearly all states, with the largest density of plants 

in the Midwest and Southeast where agricultural feedstocks are most plentiful. 

 Table IV.B.4-1 gives data on U.S. biodiesel production and use for recent years, 

including net domestic use after accounting for imports and exports. The figures suggest that the 

industry has grown out of proportion with actual biodiesel demand. Reasons for this include 

various state incentives to build plants, along with state and federal incentives to blend biodiesel, 

which have given rise to an optimistic industry outlook over the past several years. Since the 

cost of capital is relatively low for the biodiesel production process (typically four to six percent 

of the total per-gallon cost), this industry developed along a path of more small, privately-owned 

plants in comparison to the ethanol industry, with median size less than 10 million gallons/yr. 109 

These small plants, with relatively low costs other than feedstock, have generally been able to 

survive producing well below their nameplate capacities. 

 

108 Capacity data taken from National Biodiesel Board as of November 2009. 109 Assessment of plant capital cost based on USDA production cost models. A publication describing USDA 

modeling of biodiesel production costs can be found in Bioresource Technology 97(2006) 671-8. 
 

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Table IV.B.4-1 

Summary of U.S. Biodiesel Production and Use (million gallons) 110

Year Domestic 

production 

capacity 

Domestic 

total 

production 

Apparent 

capacity 

utilization 

Net domestic 

biodiesel use 

Net domestic use 

as percent of 

production 

2004 245 28 11% 27 96% 

2005 395 91 23% 91 100% 

2006 792 250 32% 261 104% 

2007 1,809 490 27% 358 73% 

2008 2,610 776 30% 413 53% 

2009 2,806 475 (est.) 17% 296 (est.) 62% 

 Some of this industry capacity may not be dedicated specifically to fuel production, 

instead being used to make oleochemical feedstocks for further conversion into products such as 

surfactants, lubricants, and soaps. These products do not show up in renewable fuel sales 

figures. 

 During 2004-2006, demand for biodiesel grew rapidly, but the trend of increasing sales 

was quickly surpassed by construction and start-up of new plants Since then, periods of high 

commodity prices followed by reduced demand for transportation fuel during the economic 

downturn have caused additional strain on the industry beyond the overcapacity situation. 

 

110 Capacity data taken from National Biodiesel Board as of November 2009. Production, import, and export figures 

taken from EIA Monthly Energy Review, Table 10.4 as of December 2009. 
 

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Biodiesel producers were able to find additional markets overseas, and a significant portion of 

the 2007 and 2008 production was exported to Europe where fuel prices and additional tax 

subsidies helped offset high feedstock costs. However, the EU enacted a tariff to protect 

domestic producers early in 2009, after which exports dropped to a small fraction of 

production.111 We understand there may be some additional export markets developing within 

North America, but given the uncertainty at this time, we do not account for any biodiesel 

exports in our projections. 

 To perform our impacts analyses for this rule, it was necessary to forecast the state of the 

biodiesel industry in the timeframe of the fully-phased-in RFS. In general, this consisted of 

reducing the industry capacity to be much closer to 1.67 billion gallons per year by 2022 (based 

on the volume requirements to meet the standard; see Section IV.A.2). This was accomplished 

by considering as screening factors the current production and sales incentives in each state as 

well as each plant’s primary feedstock type and whether it was BQ-9000 certified.112 Going 

forward producers will compete for feedstocks and markets may consolidate. During this period 

the number of operating plants is expected to shrink, with surviving plants utilizing feedstock 

segregation and pre-treatment capabilities, giving them flexibility to process any mix of 

feedstocks available in their area. By the end of this period we project a mix of large regional 

plants and some smaller plants taking advantage of local market niches, with an overall average 

capacity utilization around 85%. Table IV.B.4-2 summarizes this forecast. See Section 1.5.4 of 

the RIA for more details. 

 

111 Ibid. 112 Information on state incentives was taken from U.S. Department of Energy website, accessed July 30, 2008, at 

http://www.eere.energy.gov/afdc/fuels/biodiesel_laws.html. Information on feedstock and BQ-9000 status was 

taken from Biodiesel Board fact sheet, accessed July 30, 2008. 
 

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Table IV.B.4-2 

Summary of Projected Biodiesel Industry Characterization Used in Our Analyses 113

 2008 2022 

Total production capacity on-line (million gal/yr) 2,610 1,968 

Number of operating plants 176 121 

Median plant size (million gal/yr) 5 5 

Total biodiesel production (million gal) 776 1,670 

Average plant utilization 0.30 0.85 

 ii. Renewable Diesel

 Renewable diesel is a fuel (or blendstock) produced from animal fats, vegetable oils, and 

waste greases using chemical processes similar to those employed in petroleum hydrotreating. 

These processes remove oxygen and saturate olefins, converting the triglycerides and fatty acids 

into paraffins. Renewable diesel typically has higher cetane, lower nitrogen, and lower 

aromatics than petroleum diesel fuel, while also meeting stringent sulfur standards. 

 As a result of the oxygen and olefins in the feedstock being removed, renewable diesel 

has storage, stability, and shipping properties equivalent to petroleum diesel. This allows 

renewable diesel fuel to be shipped in existing petroleum pipelines used for transporting fuels, 

 

113 2008 capacity data taken from National Biodiesel Board; production figures taken from EIA Monthly Energy 

Review, Table 10.4 as of October 2009. 
 

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thus avoiding a significant issue with distribution of biodiesel. For more on fuel distribution, 

refer to Section IV.C. 

 Considering that this industry is still in development and that there are no long-term 

projections of production volume, we base our volume estimate of 150 MMgal/yr primarily on 

recent industry project announcements involving proven technology. Due to the current status of 

tax incentives, we project all of this fuel will be produced at stand-alone facilities. 

 b. Feedstock Availability 

 Publically available industry information along with agricultural commodity modeling 

we have done for this rule (see Section VIII.A) suggests that the three largest sources of 

feedstock for biodiesel will be rendered animal fats, soy oil, and corn oil extracted from dry mill 

ethanol facilities. Renewable diesel plants are expected to use solely animal fats due to the fact 

that these feedstocks are cheaper than vegetable oils and the process can handle them without 

issue. Comments we have received from a large rendering company suggest there will be 

adequate fats and greases feedstocks to supply biofuels as well as other historical uses. Table 

IV.B.4-3 summarizes the feedstock types, process types, and volumes projected to be used in 

2022 for biodiesel and renewable diesel. More details on feedstock sources and volumes are 

presented in Section 1.1.3 of the RIA. 

Table IV.B.4-3 

Summary of Projected Biodiesel and Renewable Diesel Feedstock Use in 2022 (MMgal) 
 

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Feedstock type Base catalyzed 

biodiesel 

Acid-pretreatment 

biodiesel 

Renewable 

diesel 

Virgin vegetable oil 660 - - 

Corn oil from ethanol production - 680 - 

Rendered animal fats and greases - 230 150 

Algae oil or other advanced source 100 - - 

C. Biofuel Distribution 

The current motor fuel distribution infrastructure has been optimized to facilitate the 

movement of petroleum-based fuels. Consequently, there are very efficient pipeline-terminal 

networks that move large volumes of petroleum-based fuels from production/import centers on 

the Gulf Coast and the Northeast into the heartland of the country. In contrast, most biofuel is 

produced in the heartland of the country and needs to be shipped to the coasts, flowing roughly 

in the opposite direction of petroleum-based fuels. In addition, while some renewable fuels such 

as hydrocarbons may be transparent to the distribution system, the physical/chemical nature of 

other renewable fuels may limit the extent to which they can be shipped/stored fungibly with 

petroleum-based fuels. The vast majority of biofuels are currently shipped by rail, barge and 

tank truck to petroleum terminals. All biofuels are currently blended with petroleum-based fuels 

prior to use.114 Most biofuel blends can be used in conventional vehicles. However, E85 can 

only be used in flex-fuel vehicles, requires specially-constructed retail dispensing/storage 

 

114 The prescribed blending ratio for a given biofuel is based on vehicle compatibility and emissions considerations. 

Some biofuels may be found to be suitable for use without the need for blending with petroleum-based fuel. 
 

366

equipment, and may require special blendstocks at terminals. These factors limit the ability of 

biofuels to utilize the existing petroleum fuel distribution infrastructure. Hence, the distribution 

of renewable fuels raises unique concerns and in many instances requires the addition of new 

transportation, storage, blending, and retail equipment. 

 1. Biofuel Shipment to Petroleum Terminals

 Ethanol currently is not commonly shipped by pipeline because it can cause stress 

corrosion cracking in pipeline walls and its affinity for water and solvency can result in product 

contamination concerns. A short gasoline pipeline in Florida is currently shipping batches of 

ethanol and other more extensive pipeline systems have feasibility studies underway.115 Thus, 

existing petroleum pipelines in some areas of the country may play an increasing role in the 

shipment of ethanol. Evaluations are also currently underway regarding the feasibility of 

constructing a new dedicated ethanol pipeline from the Midwest to the East coast. We expect 

that cellulosic distillate fuels will not have materials compatibility issues with the existing 

petroleum fuel distribution infrastructure. Thus, there may be more opportunity for cellulosic 

distillate fuel to be shipped by pipeline. However, the location of both ethanol and cellulosic 

distillate production facilities relative to the origination points for existing petroleum pipelines 

will be a limiting factor regarding the extent to which pipelines can be used. 

Our analysis of the shipment of ethanol and cellulosic distillate fuels to petroleum 

terminals is based on the projections of the location of biofuel production facilities and end use 

areas contained in the NPRM. We assume that the majority of ethanol and cellulosic distillate 

 

115 Shipment of ethanol in pipelines that carry distillate fuels as well as gasoline presents additional challenges. 
 

367

fuel would be produced in the Midwest, and that both fuels would be shipped to petroleum 

terminals in a similar fashion (by rail, barge, and tank truck). To the extent which new biofuel 

production facilities are more dispersed than projected in the NPRM, there may be more 

opportunity for both fuels to be used closer to their point of manufacture. This potential benefit 

would primarily apply to cellulosic ethanol and distillate production facilities given that such 

facilities have yet to be constructed, whereas most corn-ethanol production facilities have 

already been constructed in the Midwest. 

Biodiesel is currently not typically shipped by pipeline due to concerns that it may 

contaminate jet fuel that is shipped on the same pipeline and potential incompatibility with 

pipeline gaskets and seals. Kinder Morgan’s Plantation pipeline is currently shipping B5 blends 

on segments of its system that do not handle jet fuel. The shipment of biodiesel by pipeline may 

become more widespread and might be expanded to systems that handle jet fuel. However, the 

relatively small production volumes from individual biodiesel plants and the widespread location 

of such production facilities will tend to limit the extent to which biodiesel may be shipped by 

pipeline. 

Due to the uncertainties regarding the extent to which pipelines might participate in the 

transportation of biofuels in the future, we assumed that biofuels will continue to be transported 

by rail, barge, and truck to petroleum terminals as the vast majority of biofuel volumes are today. 

To the extent that pipelines do play an increasing role in the distribution of ethanol, this may 

improve reliability in supply and reduce distribution costs. Apart from increased shipment by 

pipeline, biofuel distribution, and in particular ethanol distribution can be further optimized 
 

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primarily through the expanded use of unit trains.116 We anticipate that the vast majority of 

ethanol and cellulosic distillate facilities will be sized to facilitate unit train service.117 We do 

not expect that biodiesel facilities will be of sufficient size to justify shipment by unit train. In 

the NPRM, we projected that unit train receipt facilities would be located at petroleum terminals 

and existing rail terminals. Based on industry input regarding the logistical hurdles in locating 

unit train receipt facilities at petroleum/existing rail terminals, we expect that such facilities will 

be constructed on dedicated property with rail access that is as close to petroleum terminals as 

practicable.118 

Shipment of biofuels by manifest rail to existing rail terminals will continue to be an 

important means of supplying biofuels to distant markets where the volume of the production 

facility and/or the local demand is not sufficient to justify shipment by unit train.119 Shipments 

by barge will also play an important role in those instances where production and demand 

centers have water access and in some cases as the final link from a unit train receipt facility to a 

petroleum terminal. Direct shipment by tank truck from production facilities to petroleum 

terminals will also continue for shipment over distances shorter than 200 miles. 

We project that most biofuel volumes shipped by rail will be delivered to petroleum 

terminals by tank truck.120 We expect that this will always be the case for manifest rail 

 

116 Unit trains are composed of 70 to 100 rail cars that are dedicated to shuttle back and forth from production 

facilities downstream receipt facilities near petroleum terminals. 

117 A facility exists in Iowa to consolidate rail cars of ethanol from some ethanol plants that are not large enough to 

support unit train service by themselves. 

118 Existing unit train receipt facilities have primarily followed this model. 119 Manifest rail shipment refers to the shipment of rail cars of biofuels in trains that also carry other products. 120 At least one current ethanol unit train receipt facility has a pipeline link to a nearby terminal. To the extent that 

additional unit train receipt facilities could accomplish the final link to petroleum terminals by pipeline, this would 

significantly reduce the need for shipment by tank truck. 
 

369

shipments. In the NPRM, we projected that trans-loading of biofuels from rail cars to tank trucks 

would be an interim measure until biofuel storage tanks were constructed.121 Based on industry 

input, we now expect trans-loading will be a long-term means of transferring manifest rail car 

shipments of biofuels received at existing rail terminals to tank trucks for delivery to petroleum 

terminals. We also anticipate that trans-loading will be used at some unit train receipt facilities, 

although we expect that most of these facilities will install biofuel storage tanks from which tank 

trucks will be filled for delivery to petroleum terminals. Imported biofuels will typically be 

received and be further distributed by tank truck from petroleum terminals that already have 

receipt facilities for waterborne fuel shipments. 

We anticipate that the deployment of the necessary distribution infrastructure to 

accommodate the shipment of biofuels to petroleum terminals is achievable.122 We believe that 

construction of the requisite rail cars, barges, tank trucks, tank truck and rail/barge/truck receipt 

facilities is within the reach of corresponding construction firms.123 Although shipment of 

biofuels by rail represents a major fraction of all biofuel ton-miles, it is projected to account for 

approximately 0.4% of all rail freight by 2022. Many improvements to the freight rail system 

will be required in the next 15 years to keep pace with the large increase in the overall freight 

demand. Given the broad importance to the U.S. economy of meeting the anticipated increase in 

freight rail demand, and the substantial resources that seem likely to be focused on this cause, we 

believe that overall freight rail capacity would not be a limiting factor to the successful 

implementation of the biofuel requirements under EISA. 

 

121 Trans-loading refers to the direct transfer of the contents of a rail car to a tank truck without the intervening 

delivery into a storage tank. 

122 See Section 1.6 of the RIA for additional discussion of the challenges in distributing biofuels from the 

production/import facility to the end user. 

123 Vessels that transport biodiesel will need to be heated/insulated in cold climates to prevent gelling. 
 

370

 2. Petroleum Terminal Accommodations

 Terminals will need to install additional storage capacity to accommodate the volume of 

biofuels that we anticipate will be used in response to the RFS2 standards. Petroleum terminals 

will also need to install truck receipt facilities for biofuels and equipment to blend biofuels into 

petroleum-based fuels. Upgrades to barge receipt facilities to handle deliveries of biofuels may 

also be needed at petroleum terminals with water access. Biodiesel storage and blending 

facilities will need to be insulated/heated in cold climates to prevent biodiesel from gelling.124 

Questions have been raised about the ability of some terminals to install the needed storage 

capacity due to space constraints and difficulties in securing permits.125 Overall demand for fuel 

used in motor vehicles is expected to remain relatively constant through 2022. Thus, much of 

the increased demand for biofuel storage could be accommodated by modifying storage tanks 

previously used for the gasoline and petroleum-based diesel fuels that would displaced by 

biofuels. The areas served by existing terminals also often overlap. In such cases, one terminal 

might be space constrained while another serving the same area may be able to install the 

additional capacity to meet the increase in demand. In cases where it is impossible for existing 

terminals to expand their storage capacity due to a lack of adjacent available land or difficulties 

in securing the necessary permits, new satellite storage or new separate terminal facilities may be 

needed for additional storage of biofuels. However, we believe that there would be few such 

situations. 

 

124 Some terminals are avoiding the need for heated/insulated biodiesel facilities by storing high biodiesel blends 

(e.g. B50) for blending with petroleum-based diesel fuel. 

125 The Independent Fuel Terminal Operators Association represents terminals in the Northeast. 
 

371

In the NPRM, we stated the current EPA policy that the RFG and anti-dumping 

regulations currently require certified gasoline to be blended with denatured ethanol to produce 

E85. We also stated that if terminal operators add blendstocks to finished gasoline for use in 

manufacturing E85, the terminal operator would need to register as a refiner with EPA and meet 

all applicable standards for refiners. Commenters questioned these statements. As we are not 

taking any action in this final rule with respect to policies surrounding E85, we will consider 

these comments outside the context of this rule. 

 3. Potential Need for Special Blendstocks at Petroleum Terminals for E85

 ASTM International is considering a proposal to lower the minimum ethanol 

concentration in E85 to facilitate meeting ASTM minimum volatility specifications in cold 

climates and when only low vapor pressure gasoline is available at terminals.126 Commenters 

have stated that the current proposal to lower the minimum ethanol concentration to 68 volume 

percent may not be sufficient for this purpose. ASTM International may consider an additional 

proposal to further decrease the minimum ethanol concentration. Absent such an adjustment, a 

high-vapor pressure petroleum-based blendstock such as butane would need to be supplied to 

most petroleum terminals to produce E85 that meets minimum volatility specifications. In such 

a case, butane would need to be transported by tank truck from petroleum refineries to terminals 

and storage and blending equipment would be needed at petroleum terminals.127

 

126 Minimum volatility specifications were established by ASTM to address safety and vehicle driveability 

considerations. 

127 See Section 1.6 of the RIA for a discussion of the potential distribution of butane to petroleum terminals for 

blending with E85 and Section 4.2 for the potential costs. 
 

372

 Instead of lowering the minimum ethanol concentration of E85, some stakeholders are 

discussing establishing a new high-ethanol blend for use in flex-fuel vehicles. Such a fuel would 

have a minimum ethanol concentration that would be sufficient to allow minimum volatility 

specifications to be satisfied while using finished gasoline that is already available at petroleum 

terminals.128 E85 would continue to be marketed in addition to this new fuel for use in flex-fuel 

vehicles when E85 minimum volatility considerations could be satisfied. 

 We believe that industry will resolve the concerns over the ability to meet the minimum 

volatility needed for high-ethanol blends used in flex-fuel vehicles in a manner that will not 

necessitate the use of high-vapor pressure blendstocks in their manufacture. Nevertheless, 

petroleum terminals may find it advantageous to blend butane into E85 because of the low cost 

of butane relative to gasoline provided that the cost benefit outweighs the associated butane 

distribution costs.129

 4. Need for Additional E85 Retail Facilities

 The number of additional E85 retail facilities needed to consume the volume of ethanol 

used under EISA varies substantially depending on the control case. Under our primary midethanol scenario, we estimate that by 2022 an additional 19,765 E85 retail facilities would be 

needed relative to the AEO reference case to enable the consumption of the ethanol that we 

 

128 Such a new fuel might have a lower ethanol concentration of 60% and a maximum ethanol concentration of 85%. 129 EPA may consider reevaluating its policies regarding the blendstocks used in the manufacture of E85 to facilitate 

this practice. 
 

373

project would be used in E85.130 Under the high-ethanol scenario, we estimate that an additional 

23,809 E85 facilities would be needed and that 4,500 E85 facilities that would otherwise be in 

place would need to be upgraded to include more E85 dispensers by 2022. Whereas under the 

low-ethanol volume scenario, we project that 11,677 additional E85 facilities would be needed 

by 2022. 

On average, approximately 1,520 additional E85 facilities will be needed each year from 

2010 through 2022 under our primary scenario. Under the high and low ethanol scenarios, an 

additional 1,820 and 900 E85 retail facilities per year respectively would be needed. Under the 

high ethanol case and to a lesser extent under the primary case, this represents an aggressive 

timeline for the addition of new E85 facilities given that there are approximately 2,000 E85 retail 

facilities in service today. Nevertheless, we believe the addition of these new E85 facilities may 

be possible for the industries that manufacture and install E85 retail equipment. Underwriters 

Laboratories requires that E85 refueling dispenser systems must be certified as complete units.131 

To date, no complete E85 dispenser systems have been certified by UL. We understand that all 

the fuel dispenser components with the exception of the hoses that connect to the refueling 

nozzle have successfully passed the necessary testing. There does not appear to be a technical 

difficulty in finding hoses that can pass the required testing. Therefore, we anticipate this 

situation will be resolved once the demand for new E85 facilities is demonstrated. Hence, we 

 

130 See Section 1.6 of the RIA for a discussion of the projected number of E85 refueling facilities that would be 

needed. There would need to be a total of 24,265 E85 retail facilities under the primary scenario, 4,500 of which are 

projected to have been placed in service absent the RFS2 standards under the AEO reference case. Our analysis 

assumes the installation of new dispensers and underground storage tank (UST) systems for E85. EPA’s Office of 

Underground Storage Tanks requires that UST systems must be compatible with the fuel stored. Authorities who 

Have Jurisdiction (such as local fire marshals) typically require that fuel dispensers be listed by an organization such 

as Underwriters Laboratories. 

131 See http://ulstandardsinfonet.ul.com/outscope/0087A.html 
 

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believe that the current lack of a UL certification for complete E85 dispenser systems will not 

impede the installation of the additional E85 facilities that we projected will be needed. 

 Petroleum retailers expressed concerns about their ability to bear the cost installing the 

needed E85 refueling equipment given that most retailers are small businesses and have limited 

capital resources. They also expressed concern regarding their ability to discount the price of 

E85 relative to E10 sufficiently to persuade flexible fuel vehicle owners to choose E85 given the 

lower energy density of ethanol. Today’s rule does not contain a requirement for retailers to 

carry E85. We understand that retailers will only install E85 facilities if they can be assured of 

sufficient E85 throughput to recover their capital costs. The current projections regarding the 

future cost of gasoline relative to ethanol indicate that it may be possible to price E85 in a 

competitive fashion to E10. Thus, demand for E85 may be sufficient to encourage retailers to 

install the needed E85 refueling facilities. 

D. Ethanol Consumption 

 1. Historic/Current Ethanol Consumption 

 Ethanol and ethanol-gasoline blends have a long history as automotive fuels. In fact, the 

well-known Model-T was capable of running on both ethanol and gasoline.132 However, 

inexpensive crude oil prices kept ethanol from making a significant presence in the 

transportation sector until the end of the 20th century. Over the past decade, ethanol use has 

grown rapidly due to oxygenated fuel requirements, MTBE bans, tax incentives, state mandates, 

 

132 The Model T was also capable of running on kerosene. 
 

375

the first federal renewable fuels standard (“RFS1”), and rising crude oil prices. Although the 

cost of crude has come down since reaching record levels in 2008, uncertainty surrounding 

pricing and the environmental implications of fossil fuels continue to drive ethanol use. 

 A record 9.5 billion gallons of ethanol were blended into U.S. gasoline in 2008 and EIA 

is forecasting additional growth in the years to come.133 According to their recently released 

Short-Term Energy Outlook (STEO), EIA is forecasting 0.7 million barrels of daily ethanol use 

in 2009, which equates to 10.7 billion gallons. The October 2009 STEO projects that total 

ethanol usage (domestic production plus imports) will reach 12.1 billion gallons by 2010.134 

 The National Petrochemical and Refiners Association (NPRA) estimates that ethanol is 

currently blended into about 75 percent of all gasoline sold in the United States.135 The vast 

majority is blended as E10 or 10 volume percent ethanol, although a small amount is blended as 

E85 for use in flexible fuel vehicles (FFVs). 

 Complete saturation of the gasoline market with E10 is referred to as the ethanol “blend 

wall.” The height of the blend wall in any given year is directly related to gasoline demand. In 

AEO 2009, EIA projects that gasoline demand will peak around 2013 and then start to taper off 

due to vehicle fuel economy improvements. Based on the primary ethanol growth scenario 

we’re forecasting under today’s RFS2 program, the nation is expected to hit the 14-15 billion 

gallon blend wall by around 2014 (refer ahead to Figure IV.D.2-1), although it could be sooner if 

 

133 EIA, Monthly Energy Review, September 2009 (Table 10.2b). 134 Letter from Richard Newell, EIA Administrator to Lisa Jackson, EPA Administrator dated October 29, 2009 

(Table 1). 

135 Based on comments provided by NPRA (EPA-HQ-OAR-2005-0161-2124.1). 
 

376

gasoline demand is lower than expected. It could also be lower if projected volumes of nonethanol renewables do not materialize and ethanol usage is higher than expected. 

 

 Over the years there have been several policy attempts to increase FFV sales including 

Corporate Average Fuel Economy (CAFE) credits and government fleet alternative-fuel vehicle 

requirements. As a result, there are an estimated 8 million FFVs on the road today, up from just 

over 7 million in 2008. While this is not insignificant in terms of growth, FFVs continue to 

make up less than 4 percent of the total gasoline vehicle fleet. In addition, E85 is only currently 

offered at about 1 percent of gas stations nationwide. Ethanol consumption is currently limited 

by the number of FFVs on the road and the number of E85 outlets or, more specifically, the 

number of FFVs with access to E85. Still many FFV owners with access to E85 are not 

choosing it because it is currently priced almost 40 cents per gallon higher than conventional 

gasoline on an energy equivalent basis.136 According to EIA, only 12 million gallons of E85 

were consumed in 2008.137 

 To meet today’s RFS2 requirements we are going to need to see growth in FFV and E85 

infrastructure as well as changes in retail pricing and consumer behavior. However, the amount 

of change needed is proportional to the amount of ethanol observed under the RFS2 program. 

As explained in Section IV.A, EPA expects total ethanol demand could be anywhere from 17.5 

to 33.2 billion gallons in 2022, depending on the amount of non-ethanol cellulosic biofuels that 

are realized. The low-ethanol case would require only moderate changes in FFV/E85 

infrastructure and refueling whereas the high-ethanol case would require very dramatic changes 

 

136 Based on average E85 and regular unleaded gasoline prices reported at http://www.fuelgaugereport.com/ on 

November 23, 2009 

137 EIA, Annual Energy Outlook 2009 – ARRA Update (Table 2). 
 

377

and likely a mandate. For the final rule, we have chosen to focus our impact analyses on the 

primary mid-ethanol case of 22.2 billion gallons. A discussion of how this volume of ethanol 

could be consumed in 2022 with expanded FFV/E85 infrastructure is presented below. As 

expected, the infrastructure changes required under this FRM scenario are less extreme than 

those highlighted in the proposal based on a predominant ethanol world (34.2 billion gallons of 

ethanol). However, there are additional technological, logistical and financial barriers that will 

need to be overcome with respect to commercialization of BTL and non-ethanol cellulosic 

biofuels. For more on cellulosic diesel technologies, distribution impacts, and production costs, 

refer to Sections 1.4, 1.6 and 4.1 of the RIA. 

 2. Increased Ethanol Use under RFS2

 Under the primary ethanol growth scenario considered as part of today’s rule, ethanol 

consumption will need to be about three times higher than RFS1 levels, more than twice as much 

as today’s levels, and 9 billion gallons higher than the ethanol predicted to occur in 2022 absent 

RFS2 (according to AEO 2007). To get to 22.2 billion gallons of ethanol use according to the 

potential ramp-up described in Section 1.2 of the RIA, the nation is predicted to hit the blend 

wall in 2014 as shown below in Figure IV.D.2-1. 
 

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Figure IV.D.2-1 

RFS2 Primary Control Case Compared to E10 Blend Wall 

 

0

5

10

15

20

25

30

35

40

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

Year

Billion Gallons of Fuel (ETOH-Eq)

Non-Ethanol Biofuels

Cellulosic Ethanol

Imported Ethanol

Corn Ethanol

E10 Blendwall
 

379

 As shown above, we are anticipating almost 14 billion gallons of non-ethanol advanced 

biofuels under today’s RFS2 program. But overall, ethanol is expected to continue to be the 

nation’s primary biofuel with over 22 billion gallons in 2022. To get beyond the blend wall and 

consume more than 14-15 billion gallons of ethanol, we are going to need to see increases in the 

number FFVs on the road, the number of E85 retailers, and the FFV E85 refueling frequency. 

 It is possible that conventional gasoline (E0) could continue to co-exist with E10 and E85 

for quite some time. However, for analysis purposes, we have assumed that E10 would replace 

E0 as expeditiously as possible and that all subsequent ethanol growth would come from E85. 

Furthermore, we assumed that no ethanol consumption would come from the mid-level ethanol 

blends (e.g., E15) under our primary control case since they are not currently approved for use in 

non-FFVs. However, as a sensitivity analysis, we have examined the impacts that E15 would 

have on ethanol consumption (refer to Section IV.D.3). 

 a. Projected Gasoline Energy Demand 

 The maximum amount of ethanol our country is capable of consuming in any given year 

is a function of the total gasoline energy demanded by the transportation sector. Our nation’s 

gasoline energy demand is dependent on the number of gasoline-powered vehicles on the road, 

their average fuel economy, vehicle miles traveled (VMT), and driving patterns. For analysis 

purposes, we relied on the gasoline energy projections provided by EIA in the AEO 2009 final 
 

380

release.138 AEO 2009 takes the fuel economy improvements set by EISA into consideration and 

also assumes a slight dieselization of the light-duty vehicle fleet.139 It also takes the recession’s 

impacts on driving patterns into consideration. The result is a 25% reduction in the projected 

2022 gasoline energy demand from AEO 2007 (a pre-EISA world) to AEO 2009.140 EIA 

essentially has total gasoline energy demand (petroleum-based gasoline plus ethanol) flattening 

out, and even slightly decreasing, as we move into the future. 

 b. Projected Growth in Flexible Fuel Vehicles 

 Over one million FFVs were sold in both 2008 and 2009 according to EPA certification 

data. Despite the recession and current state of the auto industry, automakers are incorporating 

more and more FFVs into their light-duty production plans. While the FFV system (i.e., fuel 

tank, sensor, delivery system, etc.) used to be an option on some vehicles, most automakers are 

moving in the direction of converting entire product lines over to E85-capable systems. Still, the 

number of FFVs that will be manufactured and purchased in future years is uncertain. 

 To measure the impacts of increased volumes of renewable fuel, we considered three 

different FFV production scenarios that might correspond to the three biofuel control cases 

analyzed for the final rule. For all three cases, we assumed that total light-duty vehicle sales 

would follow AEO 2009 trends. The latest EIA report suggests lower than average sales in 

 

138 EIA, Annual Energy Outlook 2009 - ARRA Update (Table 2). 139 The gasoline energy demand forecast provided in AEO 2009 – ARRA Update is reasonably consistent with the 

recently Proposed Rulemaking To Establish Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate 

Average Fuel Economy Standards (referred to hereafter as the “Light-Duty Vehicle GHG Rule.” For more 

information on the Light-Duty Vehicle GHG Rule, refer to 74 FR 49454 (September 28, 2009). 

140 EIA, Annual Energy Outlooks 2007 & 2009 – ARRA Update (Table 2). 
 

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2008-2013 (less than 16 million vehicles per year) before rebounding and growing to over 17 

million vehicles by 2019.141 These vehicle projections are consistent with EPA’s recently 

proposed Light-Duty Vehicle GHG Rule.142 

 Although we assumed total vehicle and car/truck sales would be the same in all three 

cases, we assumed varying levels of FFV production. For our low-ethanol control case, we 

assumed steady business-as-usual FFV growth according to AEO 2009 predictions.143 For our 

primary mid-ethanol control case, we assumed increased FFV sales under the presumption that 

GM, Ford and Chrysler (referred to hereafter as the “Detroit 3”) would follow through with their 

commitment to produce 50% FFVs by 2012. Despite the current state of the economy and the 

hardships facing the auto industry (GM and Chrysler filed for bankruptcy earlier this year), the 

Detroit 3 appear to still moving forward with their voluntary FFV commitment.144 Under our 

primary control case, we assumed that non-domestic FFVs sales would track around 2%, 

consistent with today’s production/plans.145 Finally, for our high-ethanol control case, we 

assumed a theoretical 80% FFV mandate based on the Open Fuel Standard Act of 2009 that was 

reintroduced in Congress on March 12, 2009.146 Given today’s reduced vehicle sales and 

gasoline demand, we believe a mandate would be the only viable means for consuming 32.2 

billion gallons of ethanol in 2022. 

 

141 EIA, Annual Energy Outlook 2009 - ARRA Update (Table 47). 142 Rulemaking to Establish Light-Duty Vehicle GHG Emission Standards and Corporate Average Fuel Economy 

Standards, 74 FR 49454 (September 28, 2009). 

143 EIA, Annual Energy Outlook 2009 - ARRA Update (Table 47). 144 Ethanol Producer Magazine, “Automakers Maintain FFV Targets in Bailout Plans.” February 2009. This is 

consistent with information provided in GM and Chrysler’s restructuring plans submitted to the U.S. Department of 

Treasury on February 17, 2009. 

145 Based on 2008 FFV certification data and 2009 projections based on the National Ethanol Vehicle Coalition, 

2009 FFV Purchasing Guide. 

146 A copy of H.R. 1476 can be found at: http://www.opencongress.org/bill/111-h1476/text 
 

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 Under our primary mid-ethanol control case, total FFV sales are estimated at just over 4 

million vehicles per year in 2017 and beyond. This is less aggressive than the assumptions made 

in the NPRM. At that time, we were expecting more cellulosic ethanol which could justify 

higher FFV production assumptions. We assumed that not only would the Detroit 3 fulfill their 

50% by 2012 FFV production commitment, non-domestic automakers might follow suit and 

produce 25% FFV in 2017 and beyond. We also assumed that annual light-duty vehicle sales 

would continue around the historical 16 million vehicle mark resulting in 6 million FFVs in 2017 

and beyond. 

 Based on our revised vehicle/FFV production assumptions coupled with vehicle survival 

rates, VMT, and fuel economy estimates applied in the recently proposed Light-Duty Vehicle 

GHG Rule, the maximum percentage of fuel (gasoline/ethanol mix) that could feasibly be 

consumed by FFVs in 2022 would be about 20% (down from 30% in the NPRM). For more 

information on our FFV production assumptions and fuel fraction calculations, refer to Section 

1.7.2 of the RIA. 

 c. Projected Growth in E85 Access 

 According to the National Ethanol Vehicle Coalition (NEVC), there are currently 2,100 

gas stations offering E85 in 44 states plus the District of Columbia.147 While this represents 

significant industry growth, it still only translates to 1.3% of U.S. retail stations nationwide 

carrying the fuel.148 As a result, most FFV owners clearly do not have reasonable access to E85. 

 

147 NEVC website, accessed on November 23, 2009 148 Based on National Petroleum News gasoline station estimate of 161,768 in 2008. 
 

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For our FFV/E85 analysis, we have defined “reasonable access” as one-in-four pumps offering 

E85 in a given area.149 Accordingly, just over 5% of the nation currently has reasonable access 

to E85, up from 4% in 2008 (based on a mid-year NEVC pump estimate).150 

 There are a number of states promoting E85 usage by offering FFV/E85 awareness 

programs and/or retail pump incentives. A growing number of states are also offering 

infrastructure grants to help expand E85 availability. Currently, 10 Midwest states have adopted 

a progressive Energy Security and Climate Stewardship Platform.151 The platform includes a 

Regional Biofuels Promotion Plan with a goal of making E85 available at one third of all stations 

by 2025. In addition, the American Recovery and Reinvestment Act of 2009 (ARRA or 

Recovery Act) recently increased the existing federal income tax credit from $30,000 or 30% of 

the total cost of improvements to $100,000 or 50% of the total cost of needed alternative fuel 

equipment and dispensing improvements.152 

 Given the growing number of subsidies, it is clear that E85 infrastructure will continue to 

expand in the future. However, like FFVs, we expect that E85 station growth will be somewhat 

proportional to the amount of ethanol realized under the RFS2 program. As such, we analyzed 

three different E85 growth scenarios for the final rule that could correspond to the three different 

RFS2 control cases. As an upper bound for our high-ethanol control case, we maintained the 

 

149 For a more detailed discussion on how we derived our one-in-four reasonable access assumption, refer to Section 

1.6 of the RIA. For the distribution cost implications as well as the cost impacts of assuming reasonable access is 

greater than one-in-four pumps, refer to Section 4.2 of the RIA. 

150 Computed as percent of stations with E85 (2,101/161,768 as of November 2009 or 1,733/161,768 as of August 

2008) divided by 25% (one-in-four stations). 

151 The following states have adopted the plan: Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, 

Ohio, South Dakota and Wisconsin. For more information, visit: 

http://www.midwesterngovernors.org/resolutions/Platform.pdf 

152 http://frwebgate.access.gpo.gov/cgi-bin/getdoc.cgi?dbname=111_cong_bills&docid=f:h1enr.pdf 
 

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70% access assumption we applied for the NPRM. This is roughly equivalent to all urban areas 

in the United States offering reasonable (one-in-four-station) access to E85.153 For our other 

control cases we assumed access to E85 would be lower with the logic that retail stations (the 

majority of which are independently owned and operated and net around $30,000 per year) 

would not invest in more E85 infrastructure than what was necessary to meet the RFS2 

requirements. For our primary mid-ethanol control case we assumed reasonable access would 

grow from 4% in 2008 to 60% in 2022 and for our low-ethanol control case we assumed that 

access would only grow to 40% by 2022. As discussed in Section IV.C, we believe these E85 

growth scenarios are possible based on our assessment of distribution infrastructure capabilities. 

 d. Required Increase in E85 Refueling Rates 

 As mentioned earlier, there were just over 7 million FFVs on the road in 2008. If all 

FFVs refueled on E85 100% of the time, this would translate to about 8.3 billion gallons of E85 

use.154 However, E85 usage was only around 12 million gallons in 2008.155 This means that, on 

average, FFV owners were only tapping into about 0.15% of their vehicles’ E85/ethanol usage 

potential last year. Assuming that only 4% of the nation had reasonable one-in-four access to 

E85 in 2008 (as discussed above), this equates to an estimated 4% E85 refueling frequency for 

those FFVs that had reasonable access to the fuel. 

 

153 For this analysis, we’ve defined “urban” as the top 150 metropolitan statistical areas according to the U.S. census 

and/or counties with the highest VMT projections according the EPA MOVES model, all RFG areas, winter oxyfuel areas, low-RVP areas, and other relatively populated cities in the Midwest. 

154 Based on average vehicle miles traveled (VMT) and in-use fuel economy (MPG) for FFVs in the fleet in 2008. 

For more information on FFV E85 fuel consumption calculations, refer to Section 1.7.4 of the RIA. 

155 EIA, Annual Energy Outlook 2009 - ARRA Update (Table 17). 
 

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 There are several reasons behind today’s low E85 refueling frequency. For starters, 

many FFV owners may not know they are driving a vehicle that is capable of handling E85. As 

mentioned earlier, more and more automakers are starting to produce FFVs by engine/product 

line, e.g., all 2008 Chevy Impalas are FFVs.156 Consequently, consumers (especially brand loyal 

consumers) may inadvertently buy a flexible fuel vehicle without making a conscious decision to 

do so. And without effective consumer awareness programs in place, these FFV owners may 

never think to refuel on E85. In addition, FFV owners with reasonable access to E85 and 

knowledge of their vehicle’s E85 capabilities may still not choose to refuel on E85. They may 

feel inconvenienced by the increased refueling requirements. Based on its lower energy density, 

FFV owners will need to stop to refuel 21% more often when filling up on E85 over E10 (and 

likewise, 24% more often when refueling on E85 over conventional gasoline).157 In addition, 

some FFV owners may be deterred from refueling on E85 out of fear of reduced vehicle 

performance or just plain unfamiliarity with the new motor vehicle fuel. However, as we move 

into the future, we believe the biggest determinant will be price – whether E85 is priced 

competitively with gasoline based on its reduced energy density (discussed in more detail in the 

subsection that follows). 

 To comply with the RFS2 program and consume 22.2 billion gallons of ethanol by 2022 

(under our primary ethanol control case), not only would we need more FFVs and more E85 

retailers, we would need to see a significant increase in the current FFV E85 refueling frequency. 

 

156 NEVC, “2008 Purchasing Guide for Flexible Fuel Vehicles.” Refers to all mass produced 3.5 and 3.9L Impalas. 

However, it is our understanding that consumers may still place special orders for non-FFVs. 

157 Based on our assumption that denatured ethanol has an average lower heating value of 77,012 BTU/gal and 

conventional gasoline (E0) has average lower heating value of 115,000 BTU/gal. For analysis purposes, E10 was 

assumed to contain 10 vol% ethanol and 90 vol% gasoline. Based on EIA’s AEO 2009 assumption, E85 was 

assumed to contain 74 vol% ethanol and 26 vol% gasoline on average. 
 

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Based on the FFV and retail assumptions described above in subsections (b) and (c), our analysis 

suggests that FFV owners with reasonable access to E85 would need to fill up on it as often as 

58% of the time, a significant increase from today’s estimated 4% refueling frequency. In order 

for this to be possible, there will need to be an improvement in the current E85/gasoline price 

relationship. 

 e. Market Pricing of E85 Versus Gasoline 

 According to an online fuel price survey, E85 is currently priced almost 40 cents per 

gallon or about 15% lower than regular grade conventional gasoline.158 But this is still about 30 

cents per gallon higher than conventional gasoline on an energy-equivalent basis. To increase 

our nation’s E85 refueling frequency to the levels described above, E85 needs to be priced 

competitively with (if not lower than) conventional gasoline based on its reduced energy content, 

increased time spent at the pump, and limited availability. Overall, we estimate that E85 would 

need to be priced about 25% lower than E10 at retail in 2022 in order for it to make sense to 

consumers. 

 However, ultimately it comes down to what refiners are willing to pay for ethanol 

blended as E85. The more ethanol you try to blend as E85, the more devalued ethanol becomes 

as a gasoline blendstock. Changes to state and Federal excise tax structures could help promote 

ethanol blending as E85. Similarly, high crude prices make E85 look more attractive. 

According to EIA’s AEO 2009, crude oil prices are expected to increase from about $80 per 

 

158 Based on average E85 and regular unleaded gasoline prices reported at http://www.fuelgaugereport.com/ on 

November 23, 2009. 
 

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barrel (today’s price) to $116/barrel by 2022.159 Based on our retail cost calculations, ethanol 

would have to be priced around $2/gallon or less in order to be attractive to refiners for E85 

blending in 2022. According to the DTN Ethanol Center, the current rack price for ethanol is 

around $2.20/gallon.160 However, as explained in Section 4.4 of the RIA, we project that the 

average ethanol delivered price will come down in the future under the RFS2 program. 

Therefore, while gasoline refiners and markets will always have a greater profit margin selling 

ethanol in low-level blends to consumers based on volume, they should be able to maintain a 

profit selling it as E85 based on energy content in the future. 

 Once the nation gets past the blend wall, more ethanol will need to be blended as E85 and 

less as E10. FFV owners who were formerly refueling on gasoline will need to start filling up on 

E85. Under our primary control case, we expect that 12.9 billion gallons of ethanol would be 

blended as E10 and 9.3 billion gallons would be blended as E85 to reach the 22.2 billion gallons 

in 2022. For more on our ethanol consumption feasibility and retail cost calculations, including 

discussion of the other two control cases, refer to Section 1.7 of the RIA. 

 3. Consideration of >10% Ethanol Blends

 

 On March 6, 2009, Growth Energy and 54 ethanol manufacturers submitted an 

application for a waiver of the prohibition of the introduction into commerce of certain fuels and 

fuel additives set forth in section 211(f) of the Act. This application seeks a waiver for ethanol-

 

159 EIA, Annual Energy Outlook 2009 – ARRA Update (Table 12). 160 http://www.dtnethanolcenter.com/index.cfm?show=10&mid=32 
 

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gasoline blends of up to 15 percent ethanol by volume.161 On April 21, 2009, EPA issued a 

Federal Register notice announcing receipt of the Growth Energy waiver application and 

soliciting comment on all aspects of it.162 On May 20, 2009, EPA issued an additional Federal 

Register notice extending the public comment period by an additional 60 days.163 The comment 

period ended on July 20, 2009, and EPA is now evaluating the waiver application and 

considering the comments which were submitted. 

 In a letter dated November 30, 2009, EPA notified the applicant that, because crucial 

vehicle durability information being developed by the Department of Energy would not be 

available until mid-2010, EPA would be delaying its decision on the application until a sufficient 

amount of this information could be included in its analysis so that the most scientifically 

supportable decision could be made.164 As the current Growth Energy waiver application is still 

under review, EPA believes it is appropriate to address aspects of the mid-level blend waiver in 

its decision announcement on the waiver application as opposed to dealing with the comments 

and evaluation of the potential waiver in the preamble of today’s final rule. 

 Although EPA has yet to make a waiver decision, since its approval could have a 

significant impact on our analyses that are based on the use of E85, as a sensitivity analysis, we 

have evaluated the impacts that E15 could have on ethanol consumption feasibility. More 

specifically, we have assessed the impacts of a partial waiver for newer technology vehicles 

consistent with the direction of EPA’s November 30, 2009 letter. We assumed that E10 would 

 

161 http://www.growthenergy.org/2009/e15/Waiver%20Cover%20Letter.pdf. Additional supporting documents are 

available on the Growth Energy website. 

162 Refer to 74 FR 18228 (April 21, 2009). 163 Refer to 74 FR 23704 (May 20, 2009). 164 http://www.epa.gov/OMS/regs/fuels/additive/lettertogrowthenergy11-30-09.pdf. 
 

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need to continue to co-exist for legacy and non-road equipment based on consumer demand 

regardless of any waiver decision. For analysis purposes, we assumed E10 would be marketed 

as premium-grade gasoline (the universal fuel), E15 would be marketed as regular-grade 

gasoline (to maximize ethanol throughput) and, like today, midgrade would be blended from the 

two fuels to make a 12.5 vol% blend (E12.5). In addition, we assumed that some E15-capable 

vehicles would continue to choose E10 or E12.5 based on our knowledge of today’s premium 

and midgrade sales.165 

 

 In the event of a partial waiver, it is unclear how long it would take for E15 to be fully 

deployed or whether it would ever be available nationwide. For analysis purposes, we assumed 

that E15 would be fully phased in and available at all retail stations nationwide by the time the 

nation hit the blend wall, or around 2014 for our primary control case shown in Figure IV.D.3-1. 

 

 

165 According to EIA’s 2008 Petroleum Annual Outlook (Table 45), midgrade and premium comprise 13.5% of total 

gasoline sales. 
 

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Figure IV.D.3-1 

Max E15 Ethanol Consumption Compared to Primary Control Case 

 

0

5

10

15

20

25

30

35

40

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

Year

Billion Gallons of Fuel (ETOH-Eq)

Non-Ethanol Biofuels

Cellulosic Ethanol

Imported Ethanol

Corn Ethanol

E15 Blendwall (Partial Waiver)

E10 Blendwall
 

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 As modeled, a partial waiver for E15 could increase the ethanol consumption potential 

from conventional vehicles to about 19 billion gallons. Under our primary control case (shown 

in Figure IV.D.3-1), E15 could postpone the blend wall by up to five years, or to 2019. 

Although E15 would fall short of meeting the RFS2 requirements under this scenario, it could 

provide interim relief while the county ramps up non-ethanol cellulosic biofuel production and 

expands E85/FFV infrastructure. Under our high-ethanol control case, a partial waiver for E15 

could eliminate the need for FFV or E85 infrastructure mandates. Under our low-ethanol control 

case, E15 could eliminate the need for additional FFV/E85 infrastructure all together. For more 

information, refer to Section 1.7.6 of the RIA. 
 

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V. Lifecycle Analysis of Greenhouse Gas Emissions 

A. Introduction 

As recognized earlier in this preamble, a significant aspect of the RFS2 program is the 

requirement that a fuel meet a specific lifecycle greenhouse gas (GHG) emissions threshold for 

compliance for each of four types of renewable fuels. This section describes the methodology 

used by EPA to determine the lifecycle GHG emissions of biofuels, and the petroleum-based 

transportation fuels that they replace. EPA recognizes that this aspect of the RFS2 regulatory 

program has received particular attention and comment throughout the public comment period. 

Therefore, this section also will describe the enhancements made to our approach in conducting 

the lifecycle analysis for the final rule. This section will highlight areas where we have 

incorporated new scientific data that has become available since the proposal as well as the 

approach the Agency has taken to recognize and quantify, where appropriate, the uncertainty 

inherent in this analysis. 

1. Open and Science-Based Approach to EPA’s Analysis

Throughout the development of EPA’s lifecycle analysis, the Agency has employed a 

collaborative, transparent, and science-based approach. EPA’s lifecycle methodology, as 

developed for the RFS2 proposal, required breaking new scientific ground and using analytical 

tools in new ways. The work was generally recognized as state of the art and an advance on 

lifecycle thinking, specifically regarding the indirect impacts of biofuels. 
 

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However, the complexity and uncertainty inherent in this work made it extremely 

important that we seek the advice and input of a broad group of stakeholders. In order to 

maximize stakeholder outreach opportunities, the comment period for the proposed rule was 

extended to 120 days. In addition to this formal comment period, EPA made multiple efforts to 

solicit public and expert feedback on our approach. Beginning early in the NPRM process and 

continuing throughout the development of this final rule, EPA held hundreds of meetings with 

stakeholders, including government, academia, industry, and non-profit organizations, to gather 

expert technical input. Our work was also informed heavily by consultation with other federal 

agencies. For example, we have relied on the expert advice of USDA and DOE, as well as 

incorporating the most recent inputs and models provided by these Agencies. Dialogue with the 

State of California and the European Union on their parallel, on-going efforts in GHG lifecycle 

analysis also helped inform EPA’s methodology. As described below, formal technical 

exchanges and an independent, formal peer review of the methodology were also significant 

components of the Agency’s outreach. A key result of our outreach effort has been awareness of 

new studies and data that have been incorporated into our final rule analysis. 

Technology Exchanges: Immediately following publication of the proposed rule, EPA 

held a two-day public workshop focused specifically on lifecycle analysis to assure full 

understanding of the analyses conducted, the issues addressed, and the options discussed. The 

workshop featured EPA presentations on each component of the methodology as well as 

presentations and discussions by stakeholders from the renewable fuel community, federal 

agencies, universities, and environmental groups. The Agency also took advantage of 
 

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opportunities to meet in the field with key, affected stakeholders. For example, the Agency was 

able to twice participate in meetings and tours in Iowa hosted by the local renewable fuel and 

agricultural community. As described in this section, one of the many outcomes of these 

meetings was an improved understanding of agricultural and biofuel production practices. 

As indicated in the proposal, our lifecycle results were particularly impacted by 

assumptions about land use patterns and emissions in Brazil. During the public comment 

process we were able to update and refine these assumptions, including the incorporation of new, 

improved sources of data based on Brazil-specific data and programs. In addition, the Agency 

received more recent trends on Brazilian crop productivity, areas of crop expansion, and regional 

differences in costs of crop production and land availability. Lastly, we received new 

information on efforts to curb deforestation allowing the Agency to better predict this impact 

through 2022. 

Peer Review: To ensure the Agency made its decisions for this final rule on the best 

science available, EPA conducted a formal, independent peer review of key components of the 

analysis. The reviews were conducted following the Office of Management and Budget’s peer 

review guidance that ensures consistent, independent government-wide implementation of peer 

review, and according to EPA's longstanding and rigorous peer review policies. In accordance 

with these guidelines, EPA used independent, third-party contractors to select highly qualified 

peer reviewers. The reviewers selected are leading experts in their respective fields, including 

lifecycle assessment, economic modeling, remote sensing imagery, biofuel technologies, soil 

science, agricultural economics, and climate science. They were asked to evaluate four key 
 

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components of EPA’s methodology: (1) land use modeling, specifically the use of satellite data 

and EPA’s proposed land conversion GHG emission factors; (2) methods to account for the 

variable timing of GHG emissions; (3) GHG emissions from foreign crop production (both the 

modeling and data used); and (4) how the models EPA relied upon are used together to provide 

overall lifecycle estimates. 

 The advice and information received through this peer review are reflected throughout 

this section. EPA’s use of higher resolution satellite data is one example of a direct outcome of 

the peer review, as is the Agency’s decision to retain its reliance upon this data. The reviewers 

also provided recommendations that have helped to inform the larger methodological decisions 

presented in this final rule. For example, the reviewers in general supported the importance of 

assessing indirect land use change and determined that EPA used the best available tools and 

approaches for this work. However, the review also recognized that no existing model 

comprehensively simulates the direct and indirect effects of biofuel production both domestically 

and internationally, and therefore model development is still evolving. The uncertainty 

associated with estimating indirect impacts and the difficulty in developing precise results also 

were reflected in the comments. In the long term, this peer review will help focus EPA’s 

ongoing lifecycle analysis work as well as our future interactions with the National Academy of 

Science and other experts. 

Altogether, the many and extensive public comments we received to the rule docket, the 

numerous meetings, workshops and technical exchanges, and the scientific peer review have all 
 

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been instrumental to EPA’s ability to advance our analysis between proposal and final and to 

develop the methodological and regulatory approach described in this section. 

2. Addressing Uncertainty

The peer review, the public comments we have received, and the analysis conducted for 

the proposal and updated here for the final rule, indicate that it is important to take into account 

indirect emissions when looking at lifecycle emissions from biofuels. It is clear that, especially 

when considering commodity feedstocks, including the market interactions of biofuel demand on 

feedstock and agricultural markets is a more accurate representation of the impacts of an increase 

in biofuels production on GHG emissions than if these market interactions are not considered. 

However, it is also clear that there are significant uncertainties associated with these 

estimates, particularly with regard to indirect land use change and the use of economic models to 

project future market interactions. Reviewers highlighted the uncertainty associated with our 

lifecycle GHG analysis and pointed to the inherent uncertainty of the economic modeling. 

In the proposal, we asked for comment on whether and how to conduct an uncertainty 

analysis to help quantify the magnitude of this uncertainty and its relative impact on the resulting 

lifecycle emissions estimates. The results of the peer review, and the feedback we have received 

from the comment process, supported the value of conducting such an analysis. Therefore, 

working closely with other government agencies as well as incorporating feedback from experts 
 

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who commented on the rule, we have quantified the uncertainty associated specifically with the 

international indirect land use change emissions associated with increased biofuel production. 

Although there is uncertainty in all portions of the lifecycle modeling, we focused our 

uncertainty analysis on the factors that are the most uncertain and have the biggest impact on the 

results. For example, the energy and GHG emissions used by a natural gas-fired ethanol plant to 

produce one gallon of ethanol can be calculated through direct observations, though this will 

vary somewhat between individual facilities. The indirect domestic emissions are also fairly 

well understood, however these results are sensitive to a number of key assumptions (e.g., 

current and future corn yields). The indirect, international emissions are the component of our 

analysis with the highest level of uncertainty. For example, identifying what type of land is 

converted internationally and the emissions associated with this land conversion are critical 

issues that have a large impact on the GHG emissions estimates. 

Therefore, we focused our efforts on the international indirect land use change emissions 

and worked to manage the uncertainty around those impacts in three ways: (1) getting the best 

information possible and updating our analysis to narrow the uncertainty, (2) performing 

sensitivity analysis around key factors to test the impact on the results, and (3) establishing 

reasonable ranges of uncertainty and using probability distributions within these ranges in 

threshold assessment. The following sections outline how we have incorporated these three 

approaches into our analysis. 
 

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EPA recognizes that as the state of scientific knowledge continues to evolve in this area, 

the lifecycle GHG assessments for a variety of fuel pathways will continue to change. 

Therefore, while EPA is using its current lifecycle assessments to inform the regulatory 

determinations for fuel pathways in this final rule, as required by the statute, the Agency is also 

committing to further reassess these determinations and lifecycle estimates. As part of this 

ongoing effort, we will ask for the expert advice of the National Academy of Sciences, as well as 

other experts, and incorporate their advice and any updated information we receive into a new 

assessment of the lifecycle GHG emissions performance of the biofuels being evaluated in this 

final rule. EPA will request that the National Academy of Sciences over the next two years 

evaluate the approach taken in this rule, the underlying science of lifecycle assessment, and in 

particular indirect land use change, and make recommendations for subsequent rulemakings on 

this subject. This new assessment could result in new determinations of threshold compliance 

compared to those included in this rule that would apply to future production (from plants that 

are constructed after each subsequent rule). 

 B. Methodology 

The regulatory purpose of this analysis is to determine which biofuels (both domestic and 

imported) qualify for the four different GHG reduction thresholds and renewable fuel categories 

established in EISA (see Section I.A). This threshold assessment compares the lifecycle 

emissions of a particular biofuel against the lifecycle emissions of the petroleum-based fuel it is 

replacing (e.g., ethanol replacing gasoline or biodiesel replacing diesel). This section discusses 
 

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the Agency’s approach both for assessing the lifecycle GHG emissions from biofuels as well as 

for the petroleum-based fuels replaced by the biofuels. 

As described in detail below, EPA has received a number of comments on the different 

pieces of this analysis and has thoroughly considered those comments as well as feedback from 

our peer review process. In each section below we will discuss comments received and how they 

impacted our analysis. 

1. Scope of Analysis

As stated in the proposal, the definition of lifecycle GHG emissions established by 

Congress in EISA is critical to establishing the scope of our analysis. Congress specified that: 

The term ‘lifecycle greenhouse gas emissions’ means the aggregate quantity of 

greenhouse gas emissions (including direct emissions and significant indirect emissions 

such as significant emissions from land use changes), as determined by the 

Administrator, related to the full fuel lifecycle, including all stages of fuel and feedstock 

production and distribution, from feedstock generation or extraction through the 

distribution and delivery and use of the finished fuel to the ultimate consumer, where the 

mass values for all greenhouse gases are adjusted to account for their relative global 

warming potential.166

 

166 Clean Air Act Section 211(o)(1). 
 

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This definition forms the basis of defining the goal and scope of our lifecycle GHG 

analysis and in determining to what extent changes should be made to the analytical approach 

outlined in our proposed rulemaking. 

a. Inclusion of Indirect Land Use Change 

EPA notes that it received significant comment on including international indirect 

emissions in its lifecycle calculations. Most of the comments suggested that the science of 

international indirect land use change was too new, or that the uncertainty involved was too 

great, to be included in a regulatory analysis. EPA continues to believe that compliance with the 

EISA mandate — determining “the aggregate GHG emissions related to the full fuel lifecycle, 

including both direct emissions and significant indirect emissions such as land use changes” — 

makes it necessary to assess those direct and significant indirect impacts that occur not just 

within the United States, but also those that occur in other countries. 

Some commenters strongly supported EPA’s proposal to include significant GHG 

emissions that occur overseas and are related to the lifecycle of renewable fuels or baseline fuels 

used in the United States. These commenters agreed that the text of the statute supports EPA’s 

proposed approach, and that the alternative of ignoring such emissions would result in grossly 

inaccurate assessments, and would be inconsistent with the international nature of GHG 

pollution and the fact that overseas emissions have domestic impacts. 
 

401

Other commenters argued that the presumption against extraterritorial application of 

domestic laws carries with it the presumption that Congress is concerned with domestic effects 

and domestic impacts only. They assert further that Congress intended to benefit domestic 

agriculture through EISA enactment, and that the statute’s ambiguous terms should not be 

interpreted in a manner that could harm domestic agriculture in general or, for one commenter, 

the biodiesel industry in particular. Although considering international emissions in its analyses 

could result in different implications under the statute for various fuels and fuel pathways as 

compared to ignoring these emissions, EPA believes that this is precisely the outcome that 

Congress intended. Implementation of EISA will undoubtedly benefit the domestic agricultural 

sector as a whole, with some components benefiting more than others depending in part on the 

lifecycle GHG emissions associated with the products to be made from individual feedstocks. If 

Congress had sought to promote all biofuel production without regard to GHG emissions related 

to the full lifecycle of those fuels, it would not have specified GHG reduction thresholds for each 

category of renewable fuel for which volume targets are specified in the Act. 

It is also important to note that including international indirect emissions in EPA’s 

lifecycle analysis does not exercise regulatory authority over activities that occur solely outside 

the U.S., nor does it raise questions of extra-territorial jurisdiction. EPA’s regulatory action 

involves an assessment of products either produced in the U.S. or imported into the U.S. EPA is 

simply assessing whether the use of these products in the U.S. satisfies requirements under EISA 

for the use of designated volumes of renewable fuel, cellulosic biofuel, biomass-based diesel, 

and advanced biofuel. Considering international emissions in determining the lifecycle GHG 
 

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emissions of the domestically-produced or imported fuel does not change the fact that the actual 

regulation of the product involves its use solely inside the U.S. 

A number of commenters pointed to the text and structure of the definition of “lifecycle 

greenhouse gas emissions” to argue that EPA either is not authorized to consider GHG emissions 

related to international land use change, or that it is not required to do so. One commenter 

suggested that the reference in the definition of “lifecycle greenhouse gas emissions” to “all 

stages” of the lifecycle “from” feedstock generation “through” use of the fuel by the ultimate 

consumer does not include indirect emissions that result from decisions to place more land in 

acreage overseas for such non-fuel purposes as cattle feed. Another commenter stated that 

EPA’s approach does not give any meaning to the terms “significant” and “fuel lifecycle” in the 

definition, but instead focuses on the words such as “full” to arrive at an expansive meaning. 

This commenter also noted the lack of any specific reference to international considerations in 

Section 211(o), as opposed to other provisions in the CAA, such as Section 115. 

EPA believes that a complete analysis of the aggregate GHG emissions related to the full 

lifecycle of renewable fuels includes the significant indirect emissions from international land 

use change that are predicted to result from increased domestic use of agricultural feedstocks to 

produce renewable fuel. The statute specifically directs EPA to include in its analyses 

significant indirect emissions such as significant emissions from land use changes. EPA has not 

ignored either the terms “significant” or “life cycle.” It is clear from EPA’s assessments that the 

modeled indirect emissions from land use changes are “significant” in terms of their relationship 

to total GHG emissions for given fuel pathways. Therefore, they are appropriately considered in 
 

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the total GHG emissions profile for the fuels in question. EPA has not ignored the term “life 

cycle.” The entire approach used by EPA is directed to fully analyzing emissions related to the 

complete lifecycle of renewable and baseline fuels. 

Although the definition of lifecycle greenhouse gas emissions in Section 211(o) does not 

specifically mention international emissions, it would be inconsistent with the intent of this 

section of the amended Act to exclude them. A large variety of activities outside the U.S. play a 

major part in the full fuel lifecycle of both baseline (gasoline and diesel fuel used as 

transportation fuel in 2005) and renewable fuels. For example, several stages of the lifecycle 

process for gasoline and diesel can occur overseas, including extraction and delivery of imported 

crude oil, and for imported gasoline and diesel products, emissions associated with refining and 

distribution of the finished product to the U.S. For imported renewable fuel, all of the emissions 

associated with feedstock production and distribution, fuel processing, and delivery of the 

finished renewable fuel to the U.S. occur overseas. The definition of lifecycle GHG emissions 

makes it clear that EPA is to determine the aggregate emissions related to the “full” fuel 

lifecycle, including “all stages of fuel and feedstock production and distribution.” Thus, EPA 

could not, as a legal matter, ignore those parts of a fuel lifecycle that occur overseas. 

Drawing a distinction between GHG emissions that occur inside the U.S. as compared to 

emissions that occur outside the U.S. would result in a lifecycle analysis that bears no apparent 

relationship to the purpose of this provision. The purpose of the thresholds in EISA is to require 

the use of renewable fuels that achieve reductions in GHG emissions compared to the baseline. 

Ignoring international emissions, a large part of the GHG emission associated with the different 
 

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fuels, would result in a GHG analysis that bears no relationship to the real world emissions 

impact of transportation fuels. The baseline would be significantly understated, given the large 

amount of imported crude and imported finished gasoline and diesel used in 2005. Likewise, the 

emissions estimates for imported renewable fuel would be grossly reduced in comparison to the 

aggregate emissions estimates for fuels made domestically with domestically-grown feedstocks, 

simply because the impacts of domestically produced fuels occurred within the U.S. EPA does 

not believe that Congress intended such a result. 

Excluding international impacts means large percentages of GHG emissions would be 

ignored. This would take place in a context where the global warming impact of emissions is 

irrespective of where the emissions occur. If the purpose of thresholds is to achieve some 

reduction in GHG emissions in order to help address climate change, then ignoring emissions 

outside our borders interferes with the ability to achieve this objective. Such an approach would 

essentially undermine the purpose of the provision, and would be an arbitrary interpretation of 

the broadly phrased text used by Congress. 

One commenter stated that matters that could appropriately be considered part of a food 

lifecycle (new land clearing for overseas grain production as a result of decreased US grain 

exports) should not be considered part of a renewable fuel lifecycle. However, the suggested 

approach would mean that EPA would fail to account for the significant indirect emissions that 

relate to renewable fuel production. EPA believes this would be counter to Congressional intent. 

Although a life cycle analysis of foreign food production may also take into account a given land 
 

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use change, that does not mean that the same land use change should not be considered in 

evaluating its ultimate cause, which may be renewable fuel production in the United States. 

Some comments asserted that significant GHG gas emissions from international land use 

change should not be considered if the only available models for doing so are not generally 

accepted or valid considering economics or science, or where the approach is new and untested, 

or where the data are faulty and EPA models unrealistic scenarios. As described in this 

rulemaking, EPA has used the best available models and substantially modified key inputs to 

those models to reflect comments by peer reviewers, the public, and emerging science. EPA has 

also modeled additional scenarios from those described in the NPRM. EPA recognizes that 

uncertainty exists with respect to the results, and has attempted to quantify the range of 

uncertainty. While EPA agrees that application of the models it has used in the context of 

assessing GHG emissions represents changes from previous biofuel lifecycle modeling, EPA 

disagrees that it has used faulty data, modeled unrealistic scenarios, or that its approach is 

otherwise scientifically indefensible. Although the results of modeling GHG emissions 

associated with international land use change are uncertain, EPA has attempted to quantify that 

uncertainty and is now in a better position to consider the uncertainty inherent in its approach. 

One commenter asserted that by considering international land use changes, EPA is 

seeking to penalize domestic renewable fuel producers for impacts over which they have no 

control. In response, EPA disagrees that it is seeking to penalize anyone at all. EPA is simply 

attempting to account for all GHG emissions related to the full fuel lifecycle. Domestic 

renewable fuel producers may have no direct control over land use changes that occur overseas 
 

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as a result of renewable fuel production and use here, but their choice of feedstock can and does 

influence oversees activities, and EPA believes it is appropriate to consider the GHG emissions 

from those activities in its analyses. 

Some commenters noted that a finding of causation is built into the definitions of 

“indirect effects” in the Endangered Species Act and the National Environmental Policy Act, and 

that EPA should interpret the reference to “indirect emissions’ in EISA as requiring similar 

findings of causation. Specifically, they argue that for EPA to count GHG emissions from 

international land use change in its assessments, EPA must find that renewable fuel production 

“caused” the land use change. In response, without addressing the commenter’s claims 

regarding the requirements of NEPA or the ESA, EPA notes that Congress has specified in 

Section 211(o) the required causal link between a fuel and indirect emissions. The indirect 

emissions must be “related to” the full fuel lifecycle. EPA believes that it has demonstrated this 

link through its modeling efforts. Specifically, the models predict that increased demand for 

feedstocks to produce renewable fuel that satisfies EISA mandates will likely result in 

international land use change. Such change is, then, “related to” the full fuel lifecycle of these 

fuels. EPA does not believe that the statute requires EPA to wait until these effects occur to 

establish the required linkage, but instead believes that it is authorized to use predictive models 

to demonstrate likely results. 

The term “related to” is generally interpreted broadly as meaning to have a connection to 

or refer to a matter. To determine whether an indirect emission has the appropriate connection to 

the full fuel lifecycle, we must look at both the objectives of this provision as well as the nature 
 

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of the relationship. EPA has used a suite of global models to project a variety of agricultural 

impacts of the RFS program, including changes in the types of crops and number of acres 

planted world-wide. These shifts in the agricultural market are a direct consequence of the 

increased demand for biofuels in the U.S. This increased demand diverts biofuel feedstocks from 

other competing uses, and also increases the price of the feedstock, thus spurring additional 

international production. Our analysis uses country-specific information to determine the 

amount, location, and type of land use change that would occur to meet these changes in 

production patterns. The linkages of these changes to increased U.S. biofuel demand in our 

analysis are generally close, and are not extended or overly complex. 

Overall, EPA is confident that it is appropriate to consider indirect emissions, including 

those from both domestic and international land use changes, as “related to” the full fuel 

lifecycle, based on the results of our modeling. These results form a reasonable technical basis 

for the linkage between the full fuel lifecycle of transportation fuels and indirect emissions, as 

well as for the determination that these emissions are significant. EPA believes that while 

uncertainty in the resulting aggregate GHG estimates should be taken into consideration, it 

would be inappropriate to exclude indirect emissions estimates from this analysis. The use of 

reasonable estimates of these kinds of indirect emissions allows EPA to conduct a reasoned 

evaluation of total GHG impacts, which is needed to promote the objectives of this provision, as 

compared to ignoring or not accounting for these indirect emissions. 

EPA understands that including international indirect land use change is a key decision 

and that there is significant uncertainty associated with it. That is why we have taken an 
 

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approach that quantifies that uncertainty and presents the weight of currently available evidence 

in making our threshold determinations. 

b. Models Used 

As described in the proposal, to estimate lifecycle indirect impacts of biofuel production 

requires the use of economic modeling to determine the market impacts of using agricultural 

commodity feedstocks for biofuels. The use of economic models and the uncertainty of those 

models to accurately predict future agricultural sector scenarios was one of the main comments 

we received on our analysis. While the comments and specifically the peer review supported our 

need to use economic models to incorporate and measure indirect impacts of biofuel production, 

they also highlighted the uncertainty with that modeling approach, especially in projecting out to 

the future. 

However, it is important to note that while there are many factors that impact the 

uncertainty in predicting total land used for crop production, making accurate predictions of 

many of these factors are not relevant to our analysis. For example different assumptions about 

economic growth rates, weather, and exchange rates will all impact future agricultural 

projections including amount of land use for crops. However, we are interested only in the 

difference between two biofuel scenarios holding all other changes constant. So the absolute 

values and projections for crops and other variables in the model projections are not as important 

as the difference the model is projecting due to an increase in biofuels production. This limits 

the uncertainty of using the economic models for our analysis. 
 

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Furthermore, one of the key uncertainties associated with our agricultural sector 

economic modeling that has the biggest impact on land use change results is the assumptions 

around crop yields. As discussed in Section V.A.2, we are conducting sensitivity analysis 

around different yield assumptions in our analysis. 

Therefore, because of the fact that we are only using the economic models to determine 

the difference between two projected scenarios and the fact that we are conducting sensitivity 

analysis around the yield assumptions we feel it is appropriate and acceptable to use economic 

models in our analysis of determining GHG thresholds in our final rule analysis. 

As was the case in the proposed analysis, to estimate the changes in the domestic 

agricultural sector (e.g., changes in crop acres resulting from increased demand for biofuel 

feedstock or changes in the number of livestock due to higher corn prices) and their associated 

emissions, EPA uses the Forestry and Agricultural Sector Optimization Model (FASOM), 

developed by Texas A&M University and others. To estimate the impacts of biofuels feedstock 

production on international agricultural and livestock production, we used the integrated Food 

and Agricultural Policy and Research Institute international models, as maintained by the Center 

for Agricultural and Rural Development (FAPRI-CARD) at Iowa State University. 

One of the main comments we received on our choice of models was the issue of 

transparency. Several comments were concerned that the results of EPA’s modeling efforts can 

not be duplicated outside the experts who developed the models and conducted the analysis used 
 

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by EPA in the proposal. Upon the release of the proposal, EPA requested comment on the use of 

these various models. EPA conducted a number of measures to gather comments, including the 

public comment period upon release of the NPRM analysis, holding a public workshop on the 

lifecycle methodology, and conducting a peer review of the lifecycle methodology. Specifically, 

one of the major tasks of the peer review of EPA’s lifecycle GHG methodology was to review 

and comment on the use of the various models and their linkages. The response we received 

through the peer review is supportive of our use of the FASOM and FAPRI-CARD models, 

affirming that they are the strong and appropriate tools for the task of estimating land use 

changes stemming from agricultural economic impacts due to changes in biofuel policy. 

In addition, in an effort to garner as useful comments as possible and to be as transparent 

as possible about the modeling process, EPA supplied in the docket technical documents for the 

FASOM and FAPRI-CARD models, the output received by EPA from each model, and the 

models themselves such that the public and commenters could learn and examine how each 

model operates. 

Building upon the support for the use of the FASOM and FAPRI-CARD models, a 

number of important enhancements were made to both models in response to comments received 

through the public comment system and through the peer review, and in consultation with 

various experts on domestic and international agronomics. These enhancements include updated 

substitution rates of corn and soybean meal for distillers grains (DG) based on recent scientific 

research by Argonne National Laboratory, the addition of a corn oil from the dry mill ethanol 

extraction process as a source of biodiesel, the full incorporation of FASOM’s forestry model 
 

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that dynamically interacts with the agriculture sector model in the U.S., as well as the addition of 

a Brazil regional model to the FAPRI-CARD modeling system. All of these enhancements are 

discussed in more detail below and in the RIA (Chapter 2 and 5). In addition to the model 

enhancements we also conducted a sensitivity analysis on yields as part of our final rule analysis. 

These updates to our modeling and the sensitivity analysis was done in response to public 

comments specifically asking for this to add transparency to the modeling and modeling results. 

We also received comments on the combined use of FASOM and FAPRI-CARD. 

Several comments and peer reviewers questioned the benefit of using two agricultural sector 

models. Specifically reviewers pointed to some of the inconsistencies in the FASOM and 

FAPRI-CARD domestic results. For the final rule analysis we worked to reconcile the two 

model results. We apply the same set of scenarios and key input assumptions in both models. 

For example, both models were updated to apply consistent treatment of DGs in domestic 

livestock feed replacement and consistent assumptions regarding DG export. 

Some reviewers questioned the benefits of using FASOM and suggested we rely entirely 

on the FAPRI-CARD model for the analysis. However, we continue to believe there are benefits 

to the use of FASOM. Specifically, the fact that FASOM has domestic land use change 

interactions between crop, pasture, and forest integrated into the modeling is an advantage over 

using the domestic FAPRI-CARD model that only tracks cropland. 

c. Scenarios Modeled 
 

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As was done for the proposal, to quantify the lifecycle GHG emissions associated with 

the increase in renewable fuel mandated by EISA, we compared the differences in total GHG 

emissions between two future volume scenarios in our economic models. For each individual 

biofuel, we analyzed the incremental GHG emission impacts of increasing the volume of that 

fuel to the total mix of biofuels needed to meet the EISA requirements. Rather than focus on the 

impacts associated with a specific gallon of fuel and tracking inputs and outputs across different 

lifecycle stages, we determined the overall aggregate impacts across sectors of the economy in 

response to a given volume change in the amount of biofuel produced. 

 Volume Scenarios: The two future scenarios considered included a “business as usual” 

volume of a particular renewable fuel based on what would likely be in the fuel pool in 2022 

without EISA, as predicted by the Energy Information Agency’s Annual Energy Outlook (AEO) 

for 2007 (which took into account the economic and policy factors in existence in 2007 before 

EISA). The second scenario assumed a higher volume of renewable fuels as mandated by EISA 

for 2022. 

We project our analysis and economic modeling through the life of the program. We 

then consider the impacts of an increase of biofuels on the agricultural sector in 2022 as the basis 

for our threshold analysis. This was an area that we received numerous comments on 

highlighting that this approach adds uncertainty to our results because we are projecting 

uncertain technology and other changes out into the future. One of the recommendations was to 

base the lifecycle GHG assessments on a near term time frame and update the analysis every few 

years to capture actual technology changes. 
 

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We continue to focus our final rule analyses on 2022 results for two main reasons. First, 

it would require an extremely complex assessment and administratively difficult implementation 

program to track how biofuel production might continuously change from month to month or 

year to year. Instead, it seems appropriate that each biofuel be assessed a level of GHG 

performance that is constant over the implementation of this rule, allowing fuel providers to 

anticipate how these GHG performance assessments should affect their production plans. 

Second, it is appropriate to focus on 2022, the final year of ramp up in the required volumes of 

renewable fuel as this year. Assessment in this year allows the complete fuel volumes specified 

in EISA to be incorporated. This also allows for the complete implementation of technology 

changes and updates that were made to improve or modeling efforts. For example, the inclusion 

of price induced yield increases and the efficiency gains of DGs replacement are phased in over 

time. Furthermore, these changes are in part driven by the changes in earlier years of increased 

biofuel use. 

Crop Yield Scenarios: EPA received numerous comments to the effect that we should 

consider a case in our economic models with higher yields that what were projected for the 

proposed rule analysis. There are many factors that go into the economic modeling but the yield 

assumptions for different crops has one of the biggest impacts on land use and land use change. 

Therefore, for this analysis we ran a base yield case and a high yield case. This will provide two 

distinct model results for key parameters like total amount of land converted by crop by country. 
 

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EPA’s base yield projections are derived from extrapolating through 2022 long-term 

historical U.S. corn yields from 1985 to 2009. This estimate, 183 bushels/acre for corn and 48 

bushels/acre for soybeans, is consistent with USDA’s method of projecting future crop yields. 

During the public comment process we learned that numerous technical advancements-- 

including better farm practices, seed hybridization and genetic modification--have led to more 

rapid gains in yields since 1995. In addition, commenters, including many leading seed 

companies, provided data supporting more rapid improvements in future yields. For example, 

commenters pointed to recent advancements in seed development (including genetic 

modification) and the general accumulation of knowledge of how to develop and bring to market 

seed varieties—factors that would allow for a greater rate of development of seed varieties 

requiring fewer inputs such as fertilizer and pest management applications. This new 

information would suggest that the base yield may be a conservative estimate of future yields in 

the U.S. Therefore, in coordination with USDA experts, EPA has developed for this final rule a 

high yield case scenario of 230 bushels/acre for corn and 60 bushels/acre for soybeans. These 

figures represent the 99% upper bound confidence limit of variability in historical U.S. yields. 

This high yield case represents a feasible high yield scenario for the purpose of a sensitivity test 

of the impact on the results of higher yields. 

Feedback we received indicated that corn and soybean yields respond in tandem and that 

a high yield corn case would also imply a higher yield for soybeans as well. The high yield case 

is therefore based on higher yield corn and soybeans in the U.S. as well as in the major corn and 

soybean producing countries around the world. For international yields, it is reasonable to 

assume the same percent increases from the baseline yield assumptions could occur as we are 
 

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estimating for the U.S. Thus in the case of corn, 230 bushels per acre is approximately 25% 

higher than the U.S. baseline yield of 183 bushels per acre in 2022. This same 25% increase in 

yield can be expected for the top corn producers in the rest of the world by 2022, as justified 

improvements in seed varieties and, perhaps even more so than in the case of the U.S., 

improvements in farming practices which can take more full advantage of the seed varieties' 

potential. For example, seeds can be more readily developed to perform well in the particular 

regions of these countries and can be coupled with much improved farming practices as farmers 

move away from historical practices such as saving seeds from their crop for use the next year 

and better understand the economic advantages of modern farming practices. So the high yield 

scenarios would not have the same absolute yield values in other countries as the U.S. but would 

have the same percent increase. 

While we modeled a high yield scenario for this analysis we continue to rely primarily on 

the base yield estimates in our assessments of different biofuel lifecycle GHG emissions 

recognizing that the base yields could be conservative. The reasons outlined above could lead to 

higher rates of yield growth in the future, however, there are mitigating factors that could limit 

this yield growth or potentially cause reductions in yield growth rates. For example, the water 

requirements for both increased corn farming and ethanol production could lead to future water 

constraints that may in some regions limit yield growth potential. Furthermore, one of the long 

term impacts of potential global climate change could be a reduction in agricultural output of 

different impacted regions around the world, including the U.S. This could also serve to reduce 

yield growth. As with many aspects of this lifecycle modeling, as the science and data evolves 

on crop yields, the Agency will update its factors accordingly. 
 

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2. Biofuel Modeling Framework & Methodology for Lifecycle Analysis 

Components

As discussed above, to account for the direct and indirect emissions of biofuel production 

required the use of agricultural sector economic models. The results of these models were 

combined with other data sources to generate lifecycle GHG emissions for the different fuels. 

The basic modeling framework involved the following steps and modeling tools. 

To estimate the changes in the domestic agricultural sector we used FASOM, developed 

by Texas A&M University and others. FASOM is a partial equilibrium economic model of the 

U.S. forest and agricultural sectors that tracks over 2,000 production possibilities for field crops, 

livestock, and biofuels for private lands in the contiguous United States. Because FASOM 

captures the impacts of all crop production, not just biofuel feedstock, we are able to use it to 

determine secondary agricultural sector impacts, such as crop shifting and reduced demand due 

to higher prices. 

The output of the FASOM analysis includes changes in total domestic agricultural sector 

fertilizer and energy use. These are calculated based on the inputs required for all the different 

crops modeled and changes in the amounts of the different crops produced due to increased 

biofuel production. FASOM output also includes changes in the number and type of livestock 

produced. These changes are due to the changes in animal feed prices and make-up due to the 

increase in biofuel production. The FASOM output changes in fertilizer, energy use, and 
 

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livestock are combined with GHG emission factors from those sources to generate biofuel 

lifecycle impacts. The GHG emission factors for fuel and fertilizer production come from the 

Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) spreadsheet 

analysis tool developed by Argonne National Laboratories, and livestock GHG emission factors 

are from IPCC guidance. 

To estimate the domestic impacts of N2O emissions from fertilizer application, we used 

the DAYCENT model developed by Colorado State University. The DAYCENT model 

simulates plant-soil systems and is capable of simulating detailed daily soil water and 

temperature dynamics and trace gas fluxes (CH4, N2O, and NOx). DAYCENT model results for 

N2O emissions from different crop and land use changes were combined with FASOM output to 

generate overall domestic N2O emissions. 

FASOM output also provides changes in total land use required for agriculture and land 

use shifting between crops, and interactions with pasture, and forestry. This output is combined 

with emission factors from land use change to generate domestic land use change GHG 

emissions from increased biofuel production. 

To estimate the impacts of biofuels feedstock production on international agricultural and 

livestock production, we used the integrated FAPRI-CARD international models, developed by 

Iowa State University. These worldwide agricultural sector economic models capture the 

biological, technical, and economic relationships among key variables within a particular 

commodity and across commodities. 
 

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The output of the FAPRI-CARD model included changes in crop acres and livestock 

production by type by country globally. Unlike FASOM, the FAPRI-CARD output did not 

include changes in fertilizer or energy use or have land type interactions built in. These were 

developed outside the FAPRI-CARD model and combined with the FAPRI-CARD output to 

generate GHG emission impacts. 

Crop input data by crop and country was developed and combined with the FAPRICARD output crop acreage change data to generate overall changes in fertilizer and energy use. 

These fertilizer and energy changes along with the FAPRI-CARD output livestock changes were 

then converted to GHG emissions based on the same basic approach used for domestic sources, 

which involves combining with emission factors from GREET and IPCC. 

International land use change emissions were determined based on combining FAPRICARD output of crop acreage change with satellite data to determine types of land impacted by 

the projected crop changes and then applying emission factors of different land use conversions 

to generate GHG impacts. 

Additional modeling and data sources used to determine the GHG emissions of other 

stages in the biofuel lifecycle include studies and data on the distance and modes of transport 

needed to ship feedstock from the field to the biofuel processing facility and the finished biofuel 

from the facility to end use. These distances and modes are used to develop amount and type of 

energy used for transport which is combined with GREET factors to generate GHG emissions. 
 

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We also calculate energy use needed in the biofuel processing facility from industry sources, 

reports, and process modeling. This energy use is combined with emissions factors from 

GREET to develop GHG impacts of the biofuel production process 

The following sections outline how the modeling tools and methodology discussed above 

were used in conducting the analysis for the different lifecycle stages of biofuel production, 

including changes made since the proposal. Lifecycle stages discussed include feedstock 

production, land use change, feedstock and fuel transport, biofuel production, and vehicle end 

use. The modeling of the petroleum fuels baseline is discussed in Section V.B.3. 

a. Feedstock Production 

Our analysis addresses the lifecycle GHG emissions from feedstock production by 

capturing both the direct and indirect impacts of growing corn, soybeans, and other renewable 

fuel feedstocks. For both domestic and international agricultural feedstock production, we 

analyzed four main sources of GHG emissions: agricultural inputs (e.g., fertilizer and energy 

use), fertilizer N2O, livestock, and rice methane. (Emissions related to land use change are 

discussed in the next section). 

i. Domestic Agricultural Sector Impacts 

Agricultural Sector Inputs: The proposal analysis calculated GHG emissions from 

domestic agriculture fertilizer and energy use and production change by applying rates of energy 
 

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and fertilizer use by crop by region to the FASOM acreage data and then multiplying by default 

factors for GHG emissions from GREET. Fuel use emissions from GREET include both the 

upstream emissions associated with production of the fuel and downstream combustion 

emissions. 

In general commenters supported this approach as it captures all indirect impacts of 

agricultural sector emissions and not just those associated with the specific biofuel crop in 

question. However, we did receive comments as part of our Model Linkages Peer Review that 

the input data for some crops may be overestimating GHG emissions. Specifically, the 

commenter highlighted that N2O emissions from domestic hay production seemed to be over 

estimated. As part of the final rule analysis EPA confirmed that input data was being used 

correctly, however, the hay N2O emissions in the proposal may have been overestimated based 

on the approach used in the proposal to generate N2O emissions from nitrogen fixing crops. This 

has been updated for the final rule analysis as discussed in the next section which resulted in 

lower emissions from nitrogen fixing crops. 

Other comments indicated that we should be using the most up to date data for our 

calculations of GHG emissions. Since the proposal there has been a new release of the GREET 

model (Version 1.8C). EPA reviewed the new version and concluded that this was an 

improvement over the previous GREET release that was used in the proposal analysis (Version 

1.8B). Therefore, EPA updated the GHG emission factors for fertilizer production used in our 

analysis to the values from the new GREET version. This had the result of slightly increasing 
 

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the GHG emissions associated with fertilizer production and thus slightly increasing the GHG 

emission impacts of domestic agriculture. 

 As was the case in the proposal, we held the rates of domestic fertilizer application 

constant over time. This is true for both of our yield scenarios considered as well as for price 

induced yield increases. This constant rate of application is justified based on USDA data 

indicating that crops are becoming more efficient in their uptake of fertilizer such that higher 

yields can be achieved based on the same per acre fertilizer application rates. 

N2O Emissions: The proposal analysis calculated N2O emissions from domestic fertilizer 

application and nitrogen fixing crops based on the amount of fertilizer used and different 

regional factors to represent the percent of nitrogen (N) fertilizer applied that result in N2O 

emissions. The proposal analysis N2O factors were based on existing DAYCENT modeling that 

was developed using the 1996 IPCC guidance for calculating N2O emissions from fertilizer 

applications and nitrogen fixing crops. We identified in the proposal that this was an area we 

would be updating for the final rule based on new analysis from Colorado State University using 

the DAYCENT model. This update was not available at time of proposal. 

We received a number of comments on our proposal results indicating that the N2O 

emissions were overestimated from soybean and other legume production (e.g., nitrogen fixing 

hay) in our analysis. The main issue is that because the N2O emission factors used in the 

proposal were based on the 1996 IPCC guidance for N2O accounting they were overestimating 

N2O emissions from nitrogen fixing crops. As an update in 2006, IPCC guidance was changed 
 

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such that biological nitrogen fixation was removed as a direct source of N2O because of the lack 

of evidence of significant emissions arising from the fixation process itself. IPCC concluded that 

the N2O emissions induced by the growth of legume crops/forages may be estimated solely as a 

function of the above-ground and below-ground nitrogen inputs from crop/forage residue. This 

change effectively reduces the N2O emissions from nitrogen fixing crops like soybeans and 

nitrogen fixing hay from the 1996 to 2006 IPCC guidance. 

Therefore, as part of the update to new N2O emission factors from DAYCENT used for 

our final rule analysis we have updated to the 2006 IPCC guidance which reduces the N2O 

emissions from soybean production. This has the effect of reducing lifecycle GHG emissions for 

soybean biodiesel production. When we model corn expansion as would result from increased 

production of corn-based ethanol, one of the impacts is that the increase in corn acres displaces 

some acres otherwise planted to soy beans. Since the GHG emissions impact of this change in 

land use considers the N2O emissions benefit from the displaced soy, the result of this lower soy 

bean N2O assessment means that the benefits for soy displacement are less, directionally 

increasing the net GHG emissions for corn expansion. 

We also received comments on our approach that we should use IPCC factors directly as 

opposed to relying on DAYCENT modeling. The difference is that IPCC provides default 

factors by crop by country, while DAYCENT models N2O emissions by crop but also by region 

within the US, accounting for different soil types and weather factors. For the final rule we still 

rely on the DAYCENT modeling results as we believe them to be more accurate. For example, 

the National Greenhouse Gas Inventory as reported annually by the US to the Framework 
 

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Convention on Climate Change uses the DAYCENT model to determine N2O emissions from 

domestic fertilizer use as opposed to using default IPCC factors as the DAYCENT modeling is 

recognized to be a more accurate approach. 

Livestock Emissions: GHG emissions from livestock have two main sources: enteric 

fermentation and manure management. For the proposal, enteric fermentation methane 

emissions were determined by applying IPCC default factors for different livestock types to herd 

values as calculated by FASOM to get GHG emissions. Comments we received on this approach 

were that the default IPCC factors do not account for the beneficial use of distiller grains (DGs) 

as animal feed. Use of DGs has been shown to decrease methane produced from enteric 

fermentation if replacing corn as animal feed. This is due to the fact that the DGs are a more 

efficient feed source. Consistent with our assumptions regarding the efficiency of DGs as an 

animal feed in our agricultural sector modeling, we have also included the enteric fermentation 

methane reductions of DGs use in our final rule analysis. The reduction amount was based on 

default factors in GREET that calculated this reduction based on the same Argonne report used 

to determine DGs feed replacement efficiency discussed in Section V.B.2.b.i. This resulted in a 

reduction in the lifecycle GHG emissions for corn ethanol compared to the proposal 

assumptions. More detail on the enteric fermentation methane reductions of DGs use can be 

found in Chapter 2 of the RIA. 

The proposal analysis also included the methane and N2O emissions of livestock manure 

management based on IPCC default factors for emissions from the different types of livestock 

and management methods combined with FASOM results for livestock changes. We received 
 

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comments that this was a good approach as it quantifies the indirect impacts of emissions 

associated with biofuel production. The same approach was used for the final rule analysis. 

Methane from Rice: For the proposal, methane emissions from rice production were 

calculated by taking the FASOM output predicted changes in rice acres, resulting from the 

increase in biofuel production, and multiplying by default methane emission factors from IPCC 

to generate GHG impacts. We received comments that this was a good approach as it quantifies 

the indirect impacts of emissions associated with biofuel production. The same approach was 

used for the final rule analysis. 

ii. International Agricultural Sector Impacts 

Agricultural Sector Inputs: For the proposal we determined international fertilizer and 

energy use emissions based on applying input data collected by the Food and Agriculture 

Organization (FAO) of the United Nations and the International Energy Agency (IEA) to the 

FAPRI-CARD crop output data and then applied GREET defaults for converting those inputs to 

GHG emissions. 

As part of our public comment and peer review process we had this component of our 

analysis specifically peer reviewed. The main comment we received was to update our input 

data with newer data sources. Therefore, for the final rule analysis we updated fertilizer and 

pesticide consumption projections from the incorporation of updates made by the FAO to its 

Fertistat and FAOStat datasets, as well as the incorporation of more up-to-date fertilizer 
 

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consumption statistics provided by a recent International Fertilizer Institute (IFA) report. This 

update had varying impacts on the amount of fertilizer used on different crops in different 

countries but in general increased the amount of fertilizer assumed and thus international 

agriculture lifecycle GHG emissions from fertilizer use for all biofuels. 

Another comment from the peer review was that we should include lime use for some of 

the key crops modeled in our analysis. Lime use was not included in the proposal because of 

lack of international data on lime use by crop. Excluding lime used is an underestimate of 

international agriculture GHG emissions. For our final rule analysis we included lime use for 

sugarcane production in Brazil based on information received from Brazilian agricultural experts 

provided as part of the comment process. This led to an increase in GHG emissions from 

sugarcane farming. We did not include lime use for other crops in the final rule analysis because 

of lack of other data sources for other crops. 

Others comments we received on our approach were that we were potentially 

underestimating GHG emissions from international agriculture energy use. Our proposal based 

international agriculture energy use on factors from the International Energy Agency (IEA) that 

included all energy use for agriculture that we divided by all agricultural sector land by country 

to get a GHG emission per acre for each country considered. The comment raised the issue that 

by using all agricultural land this includes pasture land that would not have the same energy 

input as crop production. Effectively, higher energy use from crop production was getting 

averaged with lower energy use for pasture and then this lower number was applied only to crop 

production. We specifically asked as part of our peer review for guidance and comment on our 
 

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international agriculture energy use calculation. We did not receive significant comments or data 

to suggest that we change our approach and reviewers generally agreed we were using the best 

data available. Furthermore, the energy use values represent all agriculture including forestry 

and fishing which could in some countries be overestimating energy use for crop production. So 

for our final rule analysis we used the same approach as for the proposal to calculate 

international agriculture energy use GHG emissions. 

We also received comments on the applicability of applying GREET defaults for fuel and 

fertilizer production to international fuel and fertilizer use to generate GHG emissions. The 

comments noted that GREET factors are developed for domestic US conditions and would not 

necessarily apply internationally. Specifically on the issue of nitrogen fertilizer production, the 

comments indicated that nitrogen fertilizer production internationally could rely on coal as a fuel 

source as opposed to natural gas used in the US, which would cause international GHG 

emissions associated with fertilizer production and hence biofuel production to be 

underestimated in our analysis. This was also an area we asked peer reviewers for comment and 

guidance. The peer review response generally supported our approach and did not offer 

suggestions for other data sources. So for our final rule analysis we used the same approach as 

for the proposal and applied GREET defaults to calculate international fertilizer production GHG 

emissions. 

As was the case in the proposal and for domestic agriculture, we held the rates of 

international fertilizer application constant over time. This is true for both of our yield scenarios 

considered as well as for price induced yield increases. This was an area that was specifically 
 

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addressed in our peer review of International Agricultural Greenhouse Gas Emissions and 

Factors. The reviewers supported the approach we have taken, for example indicating that 

generally crop production as a unit of fertilizer application has increased over time, therefore, 

crop yields have increased with the same or lower fertilizer applications. 

N2O Emissions: For the proposal we included N2O emissions from fertilizer application 

by applying IPCC default factors for different crops in different countries. We use IPCC default 

factors because we do not have the same level of regional factors like we do in the US from the 

DAYCENT model. The IPCC guidance has emission factors for four sources of N2O emissions 

from crops, Direct N2O Emissions from Synthetic Fertilizer Application, Indirect N2O Emissions 

from Synthetic Fertilizer Application, Direct Emissions from Crop Residues, and Indirect 

Emissions from Crop Residues. The proposal did not include N2O emissions from the Direct and 

Indirect Emissions from Crop Residues for cotton, palm oil, rapeseed, sugar beet, sugarcane, or 

sunflower. These were not included for these crops because default crop-specific IPCC factors 

used in the calculation were not available. 

Comments from our peer review process suggested that we include proxy emissions from 

these crops based on similar crop types that do have default factors. Therefore, for our final rule 

analysis we have included crop residue N2O emissions from sugarcane production based on 

perennial grass as a proxy. Perennial grass is chosen as a proxy based on input from N2O 

modeling experts. This change results in an increase in N2O emissions from sugarcane and 

therefore sugarcane ethanol production compared to the proposal. 
 

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Livestock Emissions: Similar to domestic livestock impacts, enteric fermentation and 

manure management GHG emissions were included in our proposal analysis. The proposal 

calculated international livestock GHG impacts based on activity data provided by the FAPRICARD model (e.g., number and type of livestock by country) multiplied by IPCC default factors 

for GHG emissions. 

Based on the peer review of the methodology used for the proposal it was determined that 

the calculations for manure management did not include emissions from soil application. These 

emissions were included for our final rule analysis but do not cause a significant change in the 

livestock GHG emission results. 

Rice Emissions: To estimate rice emission impacts internationally, the proposal used the 

FAPRI-CARD model to predict changes in international rice production as a result of the 

increase in biofuels demand in the U.S. We then applied IPCC default factors by country to 

these predicted changes in rice acres to generate GHG emissions. We received comments that 

this was a good approach as it quantifies the indirect impacts of emissions associated with 

biofuel production. The same approach was used for the final rule analysis. 

b. Land Use Change 

The following sections discuss our final rulemaking assessment of GHG emissions 

associated with land use changes that occur domestically and internationally as a result of the 
 

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increase in renewable fuels demand in the U.S. There are four main methodology questions 

addressed both domestically and internationally: 

• Amount of Land Converted and Where 

• Type of Land Converted 

• GHG Emissions Associated with Conversion 

• Timeframe of Emission Analysis 

Each of those methodology components are discussed as are the comments we received 

as part of the comment and peer review process. We also outline in addition to our main 

FASOM and FAPRI-CARD approach a general equilibrium modeling approaches and its results. 

 

i. Amount of Land Area Converted and Where

Based on a number of modeling changes made to the FASOM and FAPRI-CARD models 

since the NPRM, the amount of land use change resulting from an increase in biofuel demand in 

the U.S. is significantly lower in this FRM analysis for most renewable fuels. Many of the 

changes made were a direct result of comments received through the notice-and-comment 

period, comments received from the peer-reviewers, or as a result of incorporating new science 

that has become available since the analysis was conducted in the proposal. Some of the key 

changes that had the largest impact on the land use change estimates are included in this section. 

For additional information, see Chapter 2 of the RIA. 
 

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As discussed in the NPRM, one of the key factors in determining the amount of new land 

needed to meet an increase in biofuel demand is the treatment of co-products of ethanol and 

biodiesel production. We received many comments on this topic, particularly on the amount of 

corn and soybean meal a pound of DGS, the byproduct of dry mill grain ethanol production, can 

replace in animal feed. For the final rule, we predict that distiller grains will be absorbed by 

livestock more efficiently over time. We updated the displacement rate assumptions in the 

FASOM and FAPRI-CARD models based on comments we received and on the recent research 

conducted by Argonne National Laboratory and others.167 According to this research, one pound 

of DGS replaces more than a pound of corn and/or soybean meal in beef and dairy rations, in 

part because cattle fed DGS show faster weight gain and increased milk production compared to 

those fed a traditional diet. While this study represents a significant increase over current DGS 

replacement rates, we believe it is reasonable to assume that improvements will be made in the 

use and efficiency of DGS over time as the DGS market matures, the quality and consistency of 

DGS improves, and as livestock producers learn to optimize DGS feed rations. As a result of 

this modification, less land is needed to replace the amount of corn diverted to ethanol 

production. Additional details on the DGS assumptions are included in Chapters 2 and 5 of the 

RIA. 

A second factor that can have a significant impact on the amount of land that may be 

converted as a result of increasing biofuel demand are changes in crop yields over time. As 

discussed in the NPRM, our proposal based domestic yields on USDA projections for both the 

reference case and the control case. As discussed in Section V.B.1.c, for this FRM we have also 

 

167 Salil, A., M. Wu, and M. Wang. 2008. “Update of Distillers Grains Replacement Ratios for Corn Ethanol LifeCycle Analysis.” Available at http://www.transportation.anl.gov/pdfs/AF/527.pdf. 
 

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included scenarios that use higher yield projections in both the reference case and the control 

case. However, in the NPRM we also requested comment on whether the higher prices caused 

by an increased in demand for biofuels would increase future yield projections in the policy case 

beyond the yield trends in the reference case (sometimes referred to as “price induced yields”), 

or whether these price induced yields would be offset by the reduction in yields associated with 

expanding production onto new marginal acres (sometimes referred to as extensification). Based 

on the comments we received, along with additional historical trend analysis conducted by 

FAPRI-CARD, the international agricultural modeling framework now incorporates a price 

induced yield component.168 The new yield adjustments are partially offset by the 

extensification factor, however, the combined impact is that fewer new acres are needed for 

agricultural production to meet world agricultural demands. 

One additional change we made to the yield assumptions was to update the FASOM 

model with new analysis by Pacific Northwest National Laboratories (PNNL) on switchgrass 

yields. 169 We included this new data for two reasons. First, we received several comments that 

our assumptions on switchgrass yields were too low, based on more recent field work. In 

addition, for out NPRM analysis, we did not have data for switchgrass yields in certain regions 

of the US. Therefore, the PNNL data helped to fill a pre-existing data gap. As a result of these 

updates, less land is needed per gallon of switchgrass ethanol produced. Additional details on 

switchgrass yields and other agricultural sector modeling assumptions are included in RIA 

Chapter 5. 

 

168 Technical Report: An Analysis of EPA Renewable Fuel Scenarios with the FAPRI-CARD International Models, 

CARD Staff, January, 2010 

169 Thomson, A.M., R.C. Izarrualde, T.O. West, D.J. Parrish, D.D. Tyler, and J.R. Williams. 2009. Simulating 

Potential Switchgrass Production in the United States. PNNL-19072. College Park, MD: Pacific Northwest National 

Laboratory. 
 

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One of the major changes made to the FAPRI-CARD model between the NPRM and 

FRM includes the more detailed representation of Brazil through a new integrated module. The 

Brazil module was developed by Iowa State with input from Brazilian agricultural sector experts 

and we believe it is an improvement over the approach used in the proposal. In the NPRM, we 

requested additional data for countries outside the U.S. We received comments encouraging us 

to use regional and country specific data where it was available. We also received comments 

encouraging us to take into account the available supply of abandoned pastureland in Brazil as a 

potential source of new crop land. The new Brazil module addresses these comments. Since the 

Brazil module contains data specific to six regions, this additional level of details allows FAPRICARD to more accurately capture real-world responses to higher agricultural prices. For 

example, double cropping (the practice of planting a winter crop of corn or wheat on existing 

crop acres) is a common practice in Brazil. Increased double cropping is feasible in response to 

higher agricultural prices, which increases total production without increasing land use 

conversion. The new Brazil module also explicitly accounts for changes in pasture acres, 

therefore accounting for the competition between crop and pasture acres. Furthermore, the 

Brazil module explicitly models livestock intensification, the practice of increasing the number 

of heads of cattle per acre of land in response to higher commodity prices or increased demand 

for land. 

In addition to modifying how pasture acres are treated in Brazil, we also improved the 

methodology for calculating pasture acreage changes in other countries. We received several 

comments through the public comment period and peer reviewers supporting a better analysis of 
 

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the interaction between crops, pasture, and livestock. In the NPRM, although we accounted for 

GHG emissions from livestock production (e.g., manure management), we did not explicitly 

account for GHG emissions from changes in pasture demand. In response to comments received, 

our new methodology accounts for changes in pasture area resulting from livestock fluctuations 

and therefore captures the link between livestock and land used for grazing. Based on regional 

pasture stocking rates (livestock per acre), we now calculate the amount of land used for 

livestock grazing. The regional stocking rates were determined with data on livestock 

populations from the UN Food and Agricultural Organization (FAO) and data on pasture area 

measured with agricultural inventory and satellite-derived land cover data. As a result of this 

change, in countries where livestock numbers decrease, less land is needed for pasture. 

Therefore, unneeded pasture acres are available for crop land or allowed to revert to their natural 

state. In countries where livestock numbers increase, more land is needed for pasture, which can 

be added on abandoned cropland or unused grassland, or it can result in deforestation. We 

believe this new methodology provides a more realistic assessment of land use changes, 

especially in regions where livestock populations are changing significantly. For additional 

information on the pasture replacement methodology, see RIA Chapter 2. 

Although the total amount of land use conversion is lower in the FRM analysis compared 

to the NPRM analysis, the regional distribution of this land use change has shifted. Due to the 

many changes made in response to comments associated with agriculture and livestock markets, 

Brazil is now much more responsive to changes in world biofuel and agricultural product 

demand. As a result, a larger portion of the projected land use change occurs in Brazil compared 
 

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to the NPRM analysis. Additional details on the geographical location of land use change are 

included in Chapter 2 of the RIA. 

ii. Type of Land Converted 

Based on a number of improvements in our analysis, the types of land affected by 

biofuel-induced tend to be less carbon intensive compared to the NPRM. Therefore, the net 

effect of our revisions to this part of our analysis significantly reduced land use change GHG 

emissions. The updated FAPRI-CARD Brazil model, discussed in the previous section, showed 

more pasture expansion in the Amazon which increased land use change emissions. However, 

the most important revisions to this part of our international analysis, in terms of their net effect 

on GHG emissions, were improvements that we made in our modeling of the interactions 

between livestock, pasture, crops and unused, or underutilized, grasslands globally. In the 

NPRM we made the broad assumption that international crop expansion would necessarily 

displace pasture, which would require an equivalent amount of pasture to expand into forests and 

shrublands. In the FRM analysis as discussed in the previous section, we have linked 

international changes in livestock production with changes in pasture area to allow for pasture 

abandonment in regions where livestock production decreases as a result of biofuel production. 

We also incorporated the ability of pasture to expand onto unused, or underutilized, grasslands 

and savannas which on a global basis reduced the amount of forest conversion compared to the 

proposal. These revisions, as well as a quantitative uncertainty assessment, are discussed in this 

section. 
 

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In the same way that the amount and location of land use change is important, the type of 

land converted is also a critical determinant of the magnitude of the GHG emissions impacts 

associated with biofuel production. For example, the conversion of rainforest to agriculture 

results in a much larger GHG release than conversion of grassland. In the proposed rule analysis 

we used two approaches, based on the best available information to us at the time, to evaluate the 

types of land that would be affected domestically and internationally. Domestically, we used 

the FASOM model, which simulates rental rates for different types of land (e.g., forest, pasture, 

crop) and chooses the land uses that would produce the highest net returns. Internationally, we 

used the FAPRI-CARD/Winrock analysis whereby historical land conversion trends, as 

evaluated with satellite imagery, are used to determine what types of land are affected by 

agricultural land use changes in each country or sub-region. 

In the proposed rule we also explained several other options to determine what types of 

land will be affected by biofuel-induced land use changes, such as the use of general equilibrium 

models. EPA specifically sought expert peer review input and public comment on our approach 

and all of the analytical options for this part of the lifecycle assessment. The expert peer 

reviewers agreed that EPA’s approach was scientifically justifiable, but they highlighted 

problematic areas and suggested important revisions to improve our analysis. The public 

comments received on this issue expressed a wide range of views regarding EPA’s approach. In 

general, the commenters that objected to our analytical approach raised similar concerns as the 

peer reviewers, such as the need for more data validation and uncertainty assessment. As 

discussed below, we made significant improvements to our analysis based on the 

recommendations and comments we received. Based on the peer reviewers agreement that our 
 

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general approach is scientifically justifiable, and in light of the significant improvements made, 

we think that our approach represents the best available analysis of the types of land affected by 

biofuel-induced land use changes. We did consider a range of other analytical options, but based 

on all of the information considered and the requirements for this analysis, we did not find any 

alternative approaches that are superior at this time. As part of periodic updates to the lifecycle 

analysis, we will continue to consider ways to improve this part of our analysis, as well as the 

merits of alternate approaches. 

 

Domestic: In response to comments received, we made two major improvements to the 

FASOM model for the final rulemaking. As discussed in the NPRM and supported by 

comments, we were able to include the forestry sector into the FASOM analysis. Only the 

agricultural sector of FASOM was analyzed for the NPRM, due to the fact that the forestry 

sector component was undergoing model modifications. For this FRM analysis, we were able to 

use the fully integrated forestry and agricultural sector model, thereby capturing the interaction 

between agricultural land and forests in the U.S. In addition, the inclusion of the forestry model 

allows us to explicitly model the land use change impacts of the competing demand for cellulosic 

ethanol from agricultural sources with cellulosic ethanol from logging and mill residues. As a 

result of this modification, the FRM analysis includes some land use conversion from forests into 

agriculture in the U.S. as a result of the increased demand for renewable fuels. 

The second major modification we made in response to comments was the disaggregation 

of different types of land included in FASOM. In the proposed rulemaking, the FASOM model 

included three major categories of land: cropland, pasture, and acres enrolled in the Conservation 
 

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Reserve Program (CRP). Although this categorization allowed for a detailed regional analysis of 

land used to grow crops, acres used for livestock production were not fully captured. We 

received comments requesting a more detailed breakdown of land types in order to capture the 

interaction between livestock, pasture, and cropland. Therefore, the FASOM model now 

includes rangeland, pasture and forest land that can be used for grazing. Since we also received 

comments that we should take into account the potential for idle land to be used for other 

purposes such as the production of cellulosic ethanol, FASOM now accounts for the amount of 

land within each category that is either idle or used for production. 

These two major modifications to the FASOM model now allow us to explicitly track 

land transfers between various land categories in the U.S. As a result, we can more accurately 

capture the GHG impacts of different types of land use changes domestically. More detail and 

results of the FASOM model can be found in Section V.B.1.b of the preamble. 

 International: The proposed rule included a detailed description of the FAPRICARD/Winrock approach used to determine the type of land affected internationally. This 

approach uses satellite data depicting recent land conversion trends in conjunction with 

economic projections from the FAPRI-CARD model (an economic model of global agricultural 

markets) to determine the type of land converted internationally. In the proposed rule we 

described areas of uncertainty in this approach, illustrated the uncertainty with sensitivity 

analyses, and discussed other potential approaches for this analysis. To encourage expert and 

stakeholder feedback, EPA specifically invited comment on this issue, held public hearings and 

workshops, and sponsored an independent peer-review, all of which specifically highlighted this 
 

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part of our analysis for feedback. While there were a wide range of views expressed in these 

forums, the feedback received by the Agency generally supported the FAPRI-CARD/Winrock 

approach as appropriate for this analysis. For example, all five experts that peer reviewed EPA’s 

use of satellite imagery agreed that it is scientifically justifiable to use historic remote sensing 

data in conjunction with agricultural sector models to evaluate and project land use change 

emissions associated with biofuel production. Additionally, the peer reviewers and public 

commenters highlighted problematic areas and suggested revisions to improve our analysis. 

Below, we describe the key revisions that were implemented which have significantly improved 

our analysis based on the feedback received. 

FAPRI-CARD/Satellite Data Approach: As described above in Section V.B.1.b, the 

FAPRI-CARD model was used to determine the amount of land use change in each 

country/region in response to increased biofuel production. Because the FAPRI-CARD model 

does not provide information about what type of land is converted to crop production or pasture, 

we worked with Winrock International to evaluate the types of land that would be affected 

internationally. Winrock is a global nonprofit organization with years of experience in the 

development and application of the IPCC agricultural forestry and other land use (AFOLU) 

guidance. For the proposed rule, we used satellite data from 2001-2004 to provide a breakdown 

of the types of land converted to crop production. A key strength of this approach is that satellite 

information is based on empirical observations which can be verified and statistically tested for 

accuracy. Furthermore, it is reasonable to assume that recent land use change decisions have 

been driven largely by economics, and, as such, recent patterns will continue in the future, absent 
 

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major economic or land use regime shifts caused, for example, by changes in government 

policies. 

 As discussed above, all five of the expert peer reviewers that reviewed our use of satellite 

imagery for this analysis agreed that our general approach was scientifically justifiable. 

However, all of the peer reviewers qualified that statement by describing relevant uncertainties 

and highlighting revisions that would improve our analysis. Some of the public commenters 

supported EPA’s use of satellite imagery, while other expressed concern. In general, both sets of 

public commenters—those in favor and opposed—outlined the same criticisms and suggestions 

as the expert peer reviewers. Among the many valuable suggestions for satellite data analysis 

provided in the expert peer reviews and public comments, several major recommendations 

emerged: EPA should use the most recent satellite data set that covers a period of at least 5 years; 

EPA should use higher resolution satellite imagery; EPA's analysis should consider a wider 

range of land categories; EPA should improve it’s analysis of the interaction between cropland, 

pasture and unused or underutilized land; and EPA's analysis should include thorough data 

validation and a full assessment of uncertainty. Below, we describe these and other 

recommendations and how we addressed each of them to improve our analysis. Based on the 

peer reviewers agreement that our general approach is scientifically justifiable, and in light of the 

significant improvements made, we think that our approach represents the best available analysis 

of the types of land affected internationally. 

 One of the fundamental improvements in this analysis since the proposed rule is that it 

now provides global coverage. The analysis for the proposed rule included satellite imagery for 
 

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6 land categories in 314 regions across 35 of the most important countries, with a weighted 

average applied to the rest of the world. We have since completed a global satellite data analysis 

including 9 land categories in over 750 distinct regions across 160 countries. This was an 

analytical improvement that we committed to do in the proposed rule. As described below, the 

other major analytical enhancements were conducted in response to the many technical 

recommendations that we received as part of the peer review and public comment process. 

All of the expert peer reviewers agreed that the version 4 MODIS data set used in the 

proposed rule, which covers 2001-2004 with one square-kilometer (1km) spatial resolution, was 

appropriate for our analysis given the goals of the study at the time. However, almost all of the 

reviewers strongly recommended using a data set covering a longer time period. The reviewers 

argued that the 3-year time period from 2001-2004 was too short to capture the often gradual, or 

sequential, cropland expansion that has been observed in the tropics. The short time period may 

also show unusual or temporary trends in land use caused by short-term policy changes or 

market influences. The reviewers suggested that remote sensing observations covering 5-10 

years would be adequate to address these problems. The reviewers also recommended that 

remote sensing observations should be as recent as possible in order to capture current land use 

change drivers and patterns (e.g., political systems, infrastructure, and protected areas). To use 

the best available data and respond to the peer reviewers’ recommendations, the analysis was 

updated to include the most recent MODIS data set, version 5, which covers the time period 

2001-2007. MODIS land cover products are not available for years prior to 2001, so it is not 

currently possible to analyze a time period longer than six years (i.e., 2001-2007) with a single, 

or consistent, data set. Thus, consistent with the peer review recommendations, we are now 
 

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using the most recent global data set which covers at least 5 years. There are other advantages to 

using the version 5 MODIS data, such as improved spatial resolution, and robust data validation, 

which are discussed below. 

There was strong agreement among the peer reviewers that higher resolution satellite 

imagery would be an important improvement over the 1-km resolution data used in the proposed 

rule analysis. Higher spatial resolution is especially useful in categorizing highly fragmented 

landscapes. One of the reviewers hypothesized that land use change driven by biofuel 

production would likely involve large parcels of land, and thus 1-km resolution may be 

sufficient. However, all of the reviewers agreed that higher resolution data would be preferable. 

A number of the peer reviewers specifically said that the version 5 MODIS data set, with 500 

meter resolution, would be adequate. With four-times higher spatial resolution than version 4, 

the peer reviewers anticipated that the 500m imagery would classify less area of “mixed class” 

land, thus providing a more detailed representation of the land in that category. Consistent with 

the peer reviewer’s recommendations and with our goal to use the best available information, our 

analysis was updated with the higher resolution version 5 MODIS data. 

Related to the issue of spatial resolution, the peer review experts were asked whether they 

would recommend augmenting our global analysis with even higher resolution data for specific 

regions where there is a high degree of agricultural land use change. All of the peer reviews 

agreed that this type of analysis would be worthwhile. In response to this recommendation, we 

analyzed select geographic regions (e.g., Brazil, India) with the higher resolution 30m Landsat 

data set covering 2000-2005. The Landsat data set does not currently provide global coverage, 
 

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thus it was not an option for use in the full analysis; instead, it was used as a way to 

check/validate the appropriateness of the version 5 MODIS imagery. In general, the higher 

resolution data showed similar land use change patterns as the MODIS data. The results of this 

analysis are discussed further in Chapter 2 of the RIA. 

 Another issue that we invited comments on was the re-classification of the MODIS data 

from 17 land cover categories into 6 aggregated categories (e.g., open and closed shrubland were 

both re-classified as shrubland). The category aggregation was intended to remove unnecessary 

complexity from the analysis. All five expert reviewers agreed that the methodology used to reclassify land cover categories using International Geosphere-Biosphere Programme (IGBP) land 

definitions was sound; however, the reviewers recommended inclusion of more than 6 

aggregated land categories. The reviewers specifically recommended the addition 

cropland/natural vegetation mosaic, permanent wetlands, and barren or sparsely vegetated land, 

all of which are now included in our analysis. Consistent with these recommendations, there are 

9 aggregate land categories in our revised analysis: barren, cropland, excluded (e.g., urban, ice, 

water bodies), forest, grassland, mixed (i.e., cropland/natural vegetation mosaic), savanna, 

shrubland and wetland. These land cover categories capture all significant types of land affected 

by agricultural land use changes. As described below in Section V.B.2.b.iii, we also estimated 

carbon sequestrations for all of these land categories. The impact of adding these land categories 

to our analysis is discussed further in RIA Chapter 2. 

 Another important addition to our analysis was consideration of the types of land affected 

by changes in pasture area, and the interaction of pasture land with cropland. In the proposed 
 

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rule, we made a broad assumption that the total land area used for pasture would stay the same in 

each country or region. Thus, in the proposed rule, we assumed that any crop expansion onto 

pasture would necessarily require an equal amount of pasture to be replaced on forest or 

shrubland. We received a large number of comments questioning these assumptions, and the 

expert peer reviewers encouraged us to develop a better representation of the interactions 

between cropland and pasture land. As described above in Section V.B.2.6.i, the results from the 

FAPRI-CARD model are now used to determine pasture area changes in each country or region. 

In regions where we project that pasture and crop area both increase, the land types affected by 

pasture expansion are determined using the same analysis used for crop expansion. This new 

approach accounts for the ability of pasture to expand on to previously unused, or underutilized, 

grasslands and savanna. In regions where we project that crop and pasture area will change in 

opposite directions (e.g., crop area increases and pasture decreases) we assume that crops will 

expand onto abandoned pasture, and vice versa. Our analysis also now accounts for carbon 

sequestration resulting from crop or pasture abandonment. We used our satellite analysis, which 

shows the dominant ecosystems and land cover types in each region, to determine which types of 

ecosystems would grow back on abandoned agricultural lands in each region. More information 

about our analysis of pasture and abandoned agricultural land are provided in RIA Chapter 2. 

 A sub-set of the expert peer reviewers recommended combining the historic satellite 

imagery with other information on land use change drivers (e.g., transportation infrastructure, 

poverty rates, opportunity costs) as an additional means to estimate the types of land affected. 

Consideration of these types of information could potentially address two conceptual issues with 

the use of satellite imagery in this analysis: first, biofuel-induced land use change could affect 
 

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different types of land than the generic agricultural expansion captured by the historic data; and 

second, future land use change patterns may differ from historic patterns. Our concerns with the 

first issue are allayed to some degree by one of the peer reviewers who observed, “While it is 

theoretically possible that the changes in land use resulting from biofuel production occur in 

ecosystems or regions that would not be the ones affected by other drivers, this doesn’t appear 

very likely.”170 Furthermore, the economic drivers of land use change are to a large degree 

captured by the economic models that are used in our analysis. For example, the FAPRI-CARD 

model considers economic drivers in its projections of where and how much crop production will 

change as a result of specifically biofuel-induced changes. The second issue is also addressed to 

some degree by the FAPRI-CARD model which includes baseline forecasts of future 

international agricultural, economic and demographic conditions. Furthermore, as discussed 

above, we used the most recently available satellite data sets in order to capture the most current 

land use change drivers. Thus, while we think that these issues are currently addressed to a 

scientifically justifiable degree for the purposes of this analysis, we recognize that these are areas 

for future investigation, and we have tried to capture the uncertainty from these factors in 

uncertainty and sensitivity analyses as described below. 

 While EPA has made significant improvements to the methodology in response to peer 

review comments, the use of satellite data for forecasting land use changes is a key area of 

uncertainty in the analysis. To facilitate substantive comments on the impact of uncertainty in 

international land use changes, and how to address the uncertainty, the proposed rule highlighted 

areas of uncertainty and included multiple sensitivity analyses. For example, we presented a 

 

170 Peer Review Report, Emissions from Land Use Change due to Increased Biofuel Production: Satellite Imagery 

and Emissions Factor Analysis, July 31, 2009, p. 2 
 

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range of lifecycle results assuming at the high-end that all land conversion caused deforestation 

and at the low-end that biofuels would cause no deforestation. Further, EPA sought input on this 

issue in public hearings and workshops, and expert feedback through the independent peer 

review. The feedback we received, both from experts and the public, overwhelmingly supported 

a more systematic analysis of the uncertainty in using satellite data to project biofuel-induced 

land use change patterns. Additionally, commenters recommended more data validation, 

especially regarding the satellite imagery. To respond to these comments, we incorporated 

satellite imagery validation and conducted a Monte Carlo analysis of the MODIS satellite data 

using assessments provided by NASA to quantitatively evaluate the uncertainty in our 

application of satellite imagery. 

One benefit of using the MODIS data set is that it is routinely and extensively validated 

by NASA’s MODIS land validation team. NASA uses several validation techniques for quality 

assurance and to develop uncertainty information for its products. NASA’s primary validation 

technique includes comparing the satellite classifications to data collected through field and 

aircraft surveys, and other satellite data sensors. The accuracy of the version 5 MODIS land 

cover product was assessed over a significant set of international locations, including roughly 

1,900 sample site clusters covering close to 150 million square kilometers. The results of these 

validation efforts are summarized in a “confusion matrix” which compares the satellite’s land 

classifications with the actual land types observed on the ground. We used this information to 

assess the accuracy and systematic biases in the published MODIS data. In general, the 

validation process found that MODIS version 5 was quite accurate at distinguishing forest from 
 

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cropland or grassland. However, the satellite was more likely; for example, to confuse savanna 

and shrubland because these land types can look quite similar from space. 

Using the data validation information from NASA about which types of land MODIS 

tends to confuse which each other, our Monte Carlo analysis was able to account for systematic 

misclassifications in the MODIS data set. Therefore, part of the Monte Carlo analysis can be 

viewed as a way to correct and reduce the inaccuracies in the MODIS data. After this correction 

is performed, the uncertainty in the satellite data is no longer solely a function of the accuracy of 

the satellite. Instead, the sizes of the standard errors for each classification are also a function of 

the sample sizes in the data validation exercise. For example, if NASA validated every pixel on 

Earth, the corrected data set would be 100% accurate, even if the original satellite data were only 

50% accurate. Similarly, although NASA reports that the overall accuracy of the MODIS version 

5 land cover data set is approximately 75%, the standard errors after the Monte Carlo procedure 

are less than 5% for each aggregate land category. These standard errors were used to quantify 

the uncertainty added by the satellite data used in our analysis. This procedure and the results 

are described in more detail in Chapter 2 of the RIA. 

It should be noted that our assessment of satellite data uncertainty did not try to fully 

quantify the uncertainty of using historical data to make future projections about the types of 

land that would be affected internationally. As noted above, we think it is reasonable to assume 

that in general, recent land use change patterns will continue in the future absent major economic 

or land use regime shifts caused, for example, by changes in government policies. Thus, our 

uncertainty assessment provides a reasonable estimate of the variability in land use change 
 

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patterns absent any fundamental shifts in the factors that affect land use patterns. However, our 

uncertainty assessment does not attempt to fully quantify the probability of major shifts in land 

use regimes, such as the implementation of effective international policies to curb deforestation. 

 Some of the peer reviewers recommended a satellite imagery analysis approach known as 

change detection, instead of the “differencing” approach used in the Winrock analysis. 

However, there was disagreement among the peer reviewers on this point, with one peer 

reviewer saying that thematic differencing between land cover maps generated for two specific 

dates, as conducted in this study, provides the best approach for detecting and analyzing land use 

pattern changes globally. In general terms, the differencing method employed by Winrock 

compared global land cover maps from 2001 and 2007 to evaluate the pattern of land use change 

during this period. Thus, the differencing method shows all of the land that changed categories, 

as well as all of the land that stayed the same over this period. For change detection, instead of 

using comprehensive land cover maps, the data set only shows land categories that changed. 

One advantage of change detection is that it is better suited to capture the sequential nature of 

land use changes, e.g., a forest could be converted to savanna, then grassland and then cropland. 

The differencing method that we employed lends itself more readily to comprehensive global 

analysis, data validation, and uncertainty assessment. Given the timeframe and priorities for our 

analysis, we think that the differencing method provides the best approach available at this time. 

However, we will continue to consider alternative analytical techniques, such as change 

detection, for use as part of periodic updates to this analysis. 
 

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Some of the peer reviewers recommended additional alternative technical approaches for 

satellite data and land use change analysis. For example, some of the reviewers recommended 

the use of satellite imagery to identify specific crop-types and rotations, and one reviewer 

suggested that EPA develop a new interactive spatial model. The Summary and Analysis of 

Comments document includes discussion of these and other technical comments and 

recommendations that are not covered here. 

iii. GHG Emissions Associated with Conversion 

(1) Domestic Emissions 

GHG emissions impacts due to domestic land use change are based on GHG emissions 

the FASOM model generates in association with land type conversions projected in the model. 

In the proposed rule analysis, estimates of land use change emissions were limited to conversion 

between different types of agricultural land (e.g., cropland, fallow cropland, pasture). The 

analysis did not allow for the addition of new domestic agricultural land. 

In response to feedback EPA received during the public comment period and based on 

commitments EPA made in the NPRM, several changes and additions have augmented the 

analysis of domestic land use change GHG emissions since the proposed rule analysis. The 

addition of the forest land types and the interaction between cropland, pastureland, forestland, 

and developed land to the FASOM model provides a more complete emissions profile due to 

domestic land use change (see Section V.B.4.b.ii). We have updated soil carbon accounting 
 

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based on new available data. Lastly, the methodology now captures GHG emission streams over 

time associated with discrete land use changes. 

For agricultural soils, FASOM models GHG emissions associated with changes in crop 

production acreage and with changes in crop type produced. FASOM generates soil carbon 

factors for cropland and pasture according to IPCC Agriculture, Forestry, and Other Land Use 

(AFOLU) Guidelines. In the proposed rule, we committed to updating FASOM soil carbon 

accounting for agriculture. Per our commitment, we have updated FASOM soil carbon 

accounting for cropland and pasture using the latest DAYCENT modeling from Colorado State 

University. 

In the proposed rule, EPA committed to incorporate the forestry sector and the GHG 

emission impacts due to the land use interactions between the domestic agricultural and forestry 

sectors into the FASOM analysis. We received comment supporting the incorporation of the 

forestry sector. By including the forestry sector in the FASOM domestic model (see Section 

V.B.4.b.ii), we have incorporated GHG emission impacts associated with change in forest aboveground and below-ground biomass, forest soil carbon stocks, forest management practices (e.g. 

timber harvest cycles), and forest products and product emission streams over time. Forest 

carbon accounting in FASOM is based on the FORCARB developed by the U.S. Forest Service 

and on data derived largely from the U.S. Forest Service RPA modeling system. 

With the changes to FASOM discussed above, we also updated the final calculation 

method of domestic land use change GHG emissions to account for FASOM’s cumulative 
 

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assessment of GHG emissions and the continuous (rather than discrete) nature of soil carbon and 

forest product emissions. For each category of agricultural and forestry land use emissions, we 

calculated the mean cumulative emissions from the initial year of FASOM modeling (2000) to 

2022. Changes in agricultural and forest soil carbon and forest products have a stream of GHG 

emissions associated with them in addition to the initial pulse associate with a discrete instance 

or year of land use change. For each of these categories FASOM calculates the emissions over 

time associated with the mean land use change over a year. We included in total domestic land 

use change emissions the annualized emission streams associated with all agricultural soil, forest 

soil, and forest product changes included in the mean cumulative emissions (2000-2022) for 30 

years after 2022. 

(2) International Emissions 

Based on input from the expert peer review and public comments, we incorporated new 

data sources and made other methodological improvements in our estimates of GHG emissions 

from international land conversions. Some of these modifications increased land use change 

GHG emissions compared to the NPRM, such as the consideration of carbon releases from 

drained peat soils. Other modifications, such as more conservative foregone sequestration 

estimates, tended to decrease land use change GHG emissions. For example, our estimates of 

emissions per acre of deforestation in Brazil tended to increase because of improved data on 

forest biomass carbon stocks in that region. However, for example, our deforestation estimates 

in China decreased, in part because of new data on foregone forest sequestration. The net effect 

of the revisions varied depending on the location and types of land use changes in each biofuel 
 

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scenario. The major changes to this part of our analysis, including a quantitative uncertainty 

assessment, are discussed in this section. 

To determine the GHG emissions impacts of international land use changes, we followed 

the 2006 IPCC Agriculture, Forestry, and Other Land Use (AFOLU) Guidelines.171 We worked 

with Winrock, which has years of experience developing and implementing the IPCC guidelines, 

to estimate land conversion emissions factors, including changes in biomass carbon stocks, soil 

carbon stocks, non- CO2 emissions from clearing with fire and foregone forest sequestration (i.e., 

lost future growth in vegetation and soil carbon). In addition to seeking comment on our 

analysis in the proposed rule, EPA organized public hearings and workshops, and an expert peer 

review specifically eliciting feedback on this part of the lifecycle analysis. All of the expert peer 

reviewers generally felt that our analysis followed IPCC guidelines and was scientifically 

justifiable; however, they did make several suggestions of new data sources and recommended 

areas that could benefit from additional clarification. Based on the detailed comments we 

received, we worked with Winrock to make a number of important revisions, which have 

significantly improved this part of our analysis. 

 

The proposed rule analysis included land conversion emissions factors for 5 land 

categories in 314 regions across 35 of the most important countries, with a weighted average 

applied to the rest of the world. We augmented this analysis to provide global coverage, 

including emissions factors for 10 land categories in over 750 regions across 160 countries. 

Other significant improvements included incorporation of new data sources, emissions factors 

 

171 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, Agriculture, Forestry and Other 

Land Use (AFOLU). See http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html 
 

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for peat soil drainage, sequestration factors for abandoned agricultural land, and a full 

uncertainty assessment considering every data input. 

 Another significant improvement in our analysis was incorporation of higher resolution 

soil carbon data. One of the expert peer reviewers commented that the weakest part of EPA’s 

international emissions factor analysis for the proposed rule was the global soil carbon map that 

was used because of its coarse resolution. To address this comment, we incorporated the new 

Harmonized World Soil Database, released in March 2009. This dataset provides one square 

kilometer spatial resolution, which is a major improvement compared to the proposed rule 

analysis. This dataset also includes an updated soil map of China that the peer reviewers 

recommended. Using this updated soil carbon data, the change in soil carbon following 

conversion of natural land to annual crop production was estimated following the 2006 IPCC 

guidelines. When land is plowed in preparation for crop production the soil loses carbon over 

time until a new equilibrium is established. To calculate soil carbon emissions the IPCC 

approach considers both tillage practices and agricultural inputs. Some of the peer reviewers 

expressed concern with our annual soil carbon change estimates, which assumed a constant rate 

of change over 20 years. However, for analytical timeframes greater than 20 years, such as used 

in our lifecycle analysis, the peer reviewers agreed that the our approach was scientifically 

justifiable. More information about soil carbon stock estimates is available in Chapter 2 of the 

RIA. 

 The expert peer reviewers generally agreed that EPA’s estimate of forest carbon stocks 

followed IPCC guidelines and used the best available data. They did, however, recommend that 
 

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the analysis could be updated with improved forest biomass maps as they become available. 

Consistent with these suggestions, we incorporated improved forest biomass maps for regions 

where they were available. More information about the specific data sources used is available in 

RIA Chapter 2. 

 In addition to estimating forest carbon stocks for each region, EPA’s analysis also 

includes estimates of annual forest carbon uptake. When a forest is cleared the future carbon 

uptake from the forest is lost; this is known as foregone forest sequestration. In the proposed 

rule, to estimate annual forgone forest sequestration, we used IPCC default data for the growth 

rates of forests greater than 20 years old. The expert peer reviewers noted that these estimates 

could be refined with more detailed information from the scientific literature. Many of the 

public commenters were also concerned that EPA’s approach overestimated foregone 

sequestration because it did not adequately account for natural disturbances, such as fires and 

disease. To address these comments, our analysis has been updated with peer reviewed studies 

of long-term growth rates for both tropical and temperate forests. These estimates are based on 

long-term records (i.e., monitoring stations in old-growth forests for the tropics and multidecadal inventory comparisons for the temperate regions) and reflect all losses/gains over time. 

These studies show that the old-growth forests in the tropics that many once assumed to be in 

"steady state" (i.e., carbon gains equal losses) are in fact still gaining carbon. In summary, our 

analysis now includes more conservative foregone forest sequestration estimates that account for 

natural gains and losses over time. More information about these estimates is provided in RIA 

Chapter 2. 
 

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 Another consideration when estimating GHG emissions resulting from deforestation is 

that some of the wood from the cleared forest can be harvested and used in wooden products, 

such as a table, that retain biogenic carbon for a long period of time. Some commenters argued 

that consideration of the use of harvested wood in products would decrease land use change 

emissions and reduce the impacts of biofuel production. As part of analysis for the proposed 

rule, we investigated the share of cleared forest biomass that is typically used in harvested wood 

products (HWP). However, we did not account for this factor in the proposed rule after it was 

determined that HWP would have a very small impact on the magnitude of land use change 

emissions. A number of commenters expressed concern that we did not account for HWP, and 

they argued that HWP would be more significant than we had determined. However, in response 

to specific questions on this topic, all of the expert peer reviewers agreed that EPA had properly 

accounted for HWP and other factors (e.g., land filling) that could prevent or delay emissions 

from land clearing. One of the peer reviewers noted that forests converted to croplands are 

generally driven by interests unrelated to timber, and thus the trees are simply burned and 

exceptions are probably of minor importance. To study this issue further, we looked at FAO 

timber volume estimates for 111 developing countries, and published literature on the share of 

harvested timber used in wood products and the oxidation period for wood products, such as 

wood-based panels and other industrial roundwood. Consistent with the peer reviewers’ 

statements, our analysis concluded that even in countries with high rates of harvested timber 

utilization, such as Indonesia, a very small share of harvested forest biomass would be 

sequestered in HWP for longer than 30 years. The details of our HWP analysis are discussed 

further in RIA Chapter 2. This is an area for further work, but based on our analysis, and the 

feedback from expert commenters, we do not expect that consideration of HWP would have a 
 

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significant impact on the magnitude of GHG emissions from international deforestation in our 

analysis. Furthermore, the range of outcomes from consideration of HWP is indirectly captured 

in our assessment of forest carbon stock uncertainty, which is described below. 

 The land conversion emissions estimates used in our analysis consider the carbon stored 

in crop biomass. In the proposed rule, we used the IPCC default biomass sequestration factor of 

5 metric tons of carbon per hectare for annual crops, and applied this value to all crops globally. 

The final rule analysis now distinguishes between annual and perennial crops, with separate 

sequestration estimates for sugarcane and oil palm determined from the scientific literature. The 

peer reviewers suggested approaches to refine our biomass carbon estimates for different types 

of annual crops, e.g., for corn versus soybeans. However, we determined that adding cropspecific biomass sequestration estimates would have a very small impact on our results, because 

in general annual cropland carbon stocks range only from 3 to 7 tons per hectare and the average 

would likely be very close to the IPCC default factor currently applied. This is an area for future 

work, but we are confident that it would have very small impact. Furthermore, the range of 

potential outcomes is captured in the uncertainty analysis described below. 

 Other issues that were covered in the expert peer review and public comments included 

EPA’s carbon stock estimates for grasslands, savanna, shrublands and wetlands, and our 

assumptions about which regions use fire to clear land prior to agricultural expansion. There is 

less data available for these parameters relative to some of the other issues discussed above, e.g., 

forest carbon stocks. Therefore, we worked to use expert judgment to derive global estimates for 

these parameters. In general, the peer reviewers thought that EPA’s approach to these issues was 
 

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reasonable and scientifically justifiable. Some of the peer reviewers recommended more 

resource-intensive techniques to refine some of our estimates. For example, regarding the issue 

of clearing with fire, one of the peer reviewers suggested that we could review fire events in the 

historical satellite data to estimate where fire is most commonly used. We carefully considered 

these suggestions, but did not make significant revisions to our analysis of these issues. Our 

review concluded that given the timeframe and goals of our analysis, the approach used in the 

proposed rule was most appropriate. We recognize that these are areas for future work, and we 

will consider new data as part of periodic updates. Furthermore, our uncertainty analysis, 

described below, considered the fact that these are areas where less data is available. 

 Other improvements in our analysis included the addition of emissions from peat soil 

drainage in Indonesia and Malaysia, and sequestration factors for abandoned agricultural land. 

Consistent with the expert peer reviewers’ recommendations, we considered a number of recent 

studies to estimate average carbon emissions when peat soils are drained in Indonesia and 

Malaysia (the countries where peat soil is sometimes drained in preparation for new agricultural 

production). To estimate annual sequestration on abandoned agricultural land we used our 

foregone sequestration estimates and other data from IPCC. More information about these 

estimates is available in RIA Chapter 2. 

As discussed in Section V.A.2, the uncertainty of land use change emissions is an important 

consideration in EPA’s threshold determinations as part of this rulemaking. We conducted a full 

assessment of the uncertainty in international land use change emissions factors consistent with 
 

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2006 IPCC guidance.172 This analysis considers the uncertainty in the every parameter used in 

our emissions factor estimates. Standard deviations for each parameter were estimated based on 

the quality and quantity the underlying data. For example, in our analysis the standard errors (as 

a percent of the mean) tend to be smallest for forest carbon stocks in Brazil, because a large 

amount of high quality/resolution data was considered to estimate that parameter. Standard 

errors are largest for parameters that were estimated by scaling other data, or applying IPCC 

defaults, e.g., savanna carbon stocks in Yemen. More detail about our estimate of parameter 

uncertainty is available in RIA Chapter 2. 

Following IPCC guidance, the uncertainties in the individual parameters of an emission 

factor can be combined using either error propagation methods (IPCC Tier 1) or Monte Carlo 

simulation (IPCC Tier 2). We used the Tier 2 Monte Carlo simulation method for this analysis. 

Monte Carlo is a method for analyzing uncertainty propagation by randomly sampling from the 

probability distributions of model parameters, calculating the results of the model from each 

sample, and characterizing the probability of the outcomes. An important consideration for 

Monte Carlo analysis is the treatment of correlation, or dependencies, among parameter errors. 

Strong positive correlation among parameter errors will result in greater overall uncertainty. As 

a simplified example, if the errors in our forest carbon stock estimates are positively correlated, 

then if we are overestimating forest carbon in one region we likely overestimating forest carbon 

in every region. We worked with Winrock to estimate the degree of correlation among variables 

– both the correlation of one variable across space as well as the correlation of one variable to 

any others used in the analysis. This was done by considering dependencies in the underlying 

 

172 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 1: General Guidance and Reporting, 

Chapter 3: Uncertainties, available at http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol1.html 
 

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data used to estimate each parameter. For example, our forest carbon stock estimates are 

correlated across Russia because they were derived from one biomass map covering Russia. 

However, forest carbon stocks in Russia are not correlated with China, because they were 

derived from separate biomass maps. This partial correlation approach tended to reduce the 

overall uncertainty associated with GHG emissions factor data. 

The information about the uncertainty in each parameter and the degree of correlation across 

parameters was utilized in Monte Carlo analysis to determine the overall uncertainty in our 

emissions factor estimates. We used the Monte Carlo simulation to combine the emissions factor 

and satellite data uncertainty for every biofuel scenario analyzed. Uncertainty ranges varied 

across scenarios depending on the types and locations of land use changes. For example, based 

on the sources of uncertainty analyzed, the 95% confidence range for land use change emissions 

(as a percent of the mean) was -27% to +32% for base yield corn ethanol in 2022, and -56% to 

+76% for base yield soy biodiesel in 2022. 173 More details about this uncertainty analysis are 

provided in RIA Chapter 2. 

iv. Timeframe of Emission Analysis 

Based on input from the expert peer review and public comments, EPA has chosen to 

analyze lifecycle GHG emissions using a 30 year time period, over which emissions are not 

discounted, i.e., a zero discount rate is applied to future emissions. The input we received and 

the reasons for our use of this approach are described in this section. 

 

173 The 95% confidence range indicates there is no more than a 5% chance the actual value is likely to be outside this 

range. 
 

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As required by EISA, EPA must determine whether biofuels reduce GHG emissions by 

the required percentage relative to the 2005 petroleum baseline. In the proposal the Agency 

discussed a number of accounting methods for capturing the full stream of GHG emissions and 

benefits over time. When accounting for the time profile of lifecycle GHG emissions, two 

important assumptions to consider are: (1) the time period considered and (2) the discount rate 

(which could be zero) applied to future emissions streams. At the time of proposal, EPA 

requested public comment on the choice of time frames and discounting approaches for purposes 

of estimating lifecycle GHG emissions. Also, as part of the peer review process, EPA requested 

comment from expert peer reviewers on the choice of the appropriate time frames and discount 

rates for the RFS2 analysis. Below is a summary of the comments we received on these issues 

and how we address them in our analytical approach. 

Time Period for Analysis: In the proposed rule, EPA highlighted two time periods, 30 

years and 100 years, for consideration in our lifecycle analysis. The Agency discussed the 

relative advantages of these, and other, time periods. In addition, the Agency sought comment 

on whether it is appropriate to split the time period for GHG emissions assessment based upon 

how long the biofuel would be produced (i.e., the “project” period) and the time period for which 

there would likely be GHG emissions changes (i.e., the “impact” period). To encourage expert 

and public comments on these issues, EPA held public hearings and workshops and sponsored an 

expert peer review specifically focused on this topic. The expert input and comments that we 

received included many valuable points which guided our decisions about which time frame 

should be the focus of our analysis. Below we summarize some of the key arguments made by 
 

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the peer reviewers and commenters, and how these arguments factored into our choice of 

analytical approach. 

The expert peer reviewers discussed a number of justifiable time periods ranging from 13 

to 100 years for assessing lifecycle GHG emissions. A subset of the reviewers said that EPA’s 

analysis should be restricted to 2010-2022 based on the years specified in EISA, because these 

reviewers argued that EPA should not assume that biofuel production will continue beyond 2022 

at the RFS2 levels. The reviewers said that longer time frames, such as 100 years, were only 

appropriate if the Agency used positive discount rates to value future emissions. Almost all of 

the peer reviewers said that a time frame of 20 to 30 years would be a reasonable timeframe for 

assessing lifecycle GHG emissions. They gave several reasons for why a short time period is 

appropriate: this time frame is the average life of a typical biofuel production facility; future 

emissions are less certain and more difficult to value, so the analysis should be confined insofar 

as possible to the foreseeable future; and a near-term time horizon is consistent with the latest 

climate science that indicates that relatively deep reductions of heat-trapping gasses are needed 

to avoid catastrophic changes due to a warming climate. The peer reviewers suggested that 

while there is no unassailable basis for choosing a precise timeframe the expected average 

lifetime of a biofuel production facility is the “most sensible anchor” for the choice of a 

timeframe. 

There was support in the public comments for both the 30 year and 100 year time frames. 

A number of public commenters supported the use of a 30 year time period, or less, and made 

arguments similar to those of the expert peer reviewers. They argued that shorter time periods 
 

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give more weight to the known, more immediate, effects of biofuel production and that use of 

longer time periods gives more weight to activities that are much more uncertain, and that the 

100 year timeframe is inappropriate because it is much longer than the life of individual biofuel 

plants. 

On the issue of whether to split the time period for GHG emissions analysis into the 

“project and “impact” periods, there was little support for the use of a split time frame for 

evaluating lifecycle GHG emissions by the peer reviewers or in the public comments. The peer 

reviewers thought that it would be difficult to find a scientific basis for determining the length of 

the two different time horizons. Also, splitting the time horizon would necessitate consideration 

of the land use changes following the end of the project time horizon such as land reversion. 

However, the majority of expert peer reviewers did not think it was appropriate to attribute 

potential land reversions, following the project time frame, to a biofuel’s lifecycle. 

Based upon the comments discussed above, EPA has decided to use a 30 year frame for 

assessing the lifecycle GHG emissions. There are several reasons why the 30 year time frame 

was chosen. The full life of a typical biofuel plant seems reasonable as a basis for the timeframe 

for assessing the GHG emissions impacts of a biofuel, because it provides a guideline for how 

long we can expect biofuels to be produced from a particular entity using a specific processing 

technology. Also, the 30 year time frame focuses on GHG emissions impacts that are more near 

term and, hence, more certain. We also determined that longer time periods were less 

appropriate because the peer reviewers recommended that they should only be used in 

conjunction with positive discount rates; but, for the reasons discussed below, we are using a 
 

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zero discount rate in our analysis. In addition, the 30 year time frame is consistent with 

responses of the peer reviewers that EPA should not split the time periods for analysis, or include 

potential land reversions following the project time period in the biofuel lifecycle. 

Discounting: In the RFS2 Proposal, EPA highlighted two principal options for 

discounting the lifecycle GHG emission streams from biofuels over time. The first involved the 

use of a 2% discount rate using the 100 year time horizon for assessing lifecycle GHG emissions 

streams. The second option involved using a 30 year time horizon for examining lifecycle GHG 

emissions impacts. In the 30 year case, each GHG emission is treated equally through time, 

which implicitly assumes a zero discount rate to GHG lifecycle emissions streams. The issue of 

whether to discount lifecycle GHG emissions was raised as a topic that EPA sought comment on 

in both the peer review process and in public comments. 

EPA received numerous of comments on the issue of whether the Agency should be 

discounting lifecycle GHG emissions through time. While many of peer reviewers thought that 

current GHG emissions reductions should be more strongly weighted than future reductions, the 

peer reviewers were in general agreement that a discount rate should only be applied to a 

monetary unit, rather than a physical unit, such as GHG emissions. Public commenters 

suggested that discounting is an essential part of long term cost benefit analysis but it is not 

necessary in the context of the physical aggregation of lifecycle GHG emissions called for in the 

EISA. Further, public commenters expressed concerns that any discount rate chosen by the 

Agency would be based upon relatively arbitrary criteria. 
 

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After considering the comments on discounting from the peer review and the public, EPA 

has decided not to discount (i.e., use a 0% discount rate) GHG emissions due to the many issues 

associated with applying an economic concept to a physical parameter. First, it is unclear 

whether EISA intended lifecycle GHG emissions to be converted into a metric whose 

underpinnings rest on principals of economic valuation. A more literal interpretation of EISA is 

that EPA should consider only physical GHG emissions. Second, even if the principle of tying 

GHG emissions to economic valuation approaches were to be accepted, there would still be the 

problem that there is a lack of consensus in the scientific community about the best way to 

translate GHG emissions into a proxy for economic damages. Also, there is a lack of consensus 

as to the appropriate discount rate to apply to GHG lifecycle emissions streams through time. 

Finally, since EPA has decided to base threshold assessments of lifecycle GHG emissions on a 

30 year time frame, the issue of whether to discount GHG emissions is not as significant as if the 

EPA had chosen the 100 year time frame to assess GHG emissions impacts. More discussion of 

discount rates and their impact on the lifecycle results can be found in Chapter 2 of the RIA. 

v. GTAP and Other Models

Although we have used the partial equilibrium (PE) models FASOM and FAPRI-CARD 

as the primary tools for evaluating whether individual biofuels meet the GHG thresholds, as part 

of the peer review process, we explicitly requested input on whether general equilibrium (GE) 

models should be used. None of the comments recommended using a GE model as the sole tool 

for estimating GHG emissions, given the limited details on the agricultural sector contained in 

most GE models. The peer reviewers generally supported the use of the FASOM and FAPRI-
 

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CARD models for our GHG analysis given the need for additional detail offered in the PE 

models, however several comments suggested incorporating GE models into the analysis. 

Given these recommendations, we opted to use the GTAP model to inform the range of 

potential GHG emissions associated with land use change resulting from an increase in 

renewable fuels. As discussed in the NPRM, there are several advantages to using GTAP. As a 

general equilibrium model, GTAP captures the interaction between different markets (e.g., 

agriculture and energy) in different regions. It is distinctive in estimating the complex 

international land use change through trade linkages. In addition, GTAP explicitly models landuse conversion decisions, as well as land management intensification. Most importantly, in 

contrast to other models, GTAP is designed with the framework of predicting the amount and 

types of land needed in a region to meet demands for both food and fuel production. The GTAP 

framework also allows predictions to be made about the types of land available in the region to 

meet the needed demands, since it explicitly represents different types of land cover within each 

Agro-Ecological Zone. 

Like the peer reviewers, we felt that some of the drawbacks of the GTAP model prevent 

us from using GTAP as the sole model for estimating GHG emissions from biofuels. As 

discussed in the NPRM, GTAP does not utilize unmanaged cropland, nor is it able to capture the 

long-run baseline issues (e.g., the state of the economy in 2022). For our analysis, the GTAP 

model was most valuable for providing another estimate of the quantity and type of land 

conversion resulting from an increase in corn ethanol and biodiesel given the competition for 

land and other inputs from other sectors of the economy. These results were therefore 
 

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considered as part of the weight of evidence when determining whether corn ethanol or biodiesel 

met the GHG thresholds. 

The quantity of total acres converted to crop land projected by FAPRI-CARD were 

within the range of values projected by GTAP when normalized on a per BTU basis, although 

there were differences in the regional distribution of these changes. The land use changes 

projected by GTAP were smaller than land use changes predicted by FAPRI-CARD, which is 

primarily due to several important differences in the modeling frameworks. First, the GTAP 

model incorporates a more optimistic view of intensification options by which higher prices 

induced by renewable fuels results in higher yields, not just for corn, but also for other displaced 

crops. Second, the demands for other uses of land are explicitly captured in GTAP. Therefore, 

when land is withdrawn from these uses, the prices of these products rise and provide a certain 

amount of “push-back” on the conversion of land to crops from pasture or forest. Third, none of 

the peer-reviewed versions of GTAP currently contain unmanaged cropland, thereby omitting 

additional sources of land. Finally, the GTAP model also predicted larger increases in forest 

conversion than the FAPRI-CARD/Winrock analysis, in part because the GTAP model includes 

only three types of land (i.e., crops, pasture, forest). As discussed in the FAPRI-CARD/Winrock 

section, there are many other categories of land which may be converted to pasture and crop 

land. 

As with all economic models, GTAP results are sensitive to certain key parameter values. 

One advantage of this framework is that it offers a readily usable approach to Systematic 

Sensitivity Analysis (SSA) using efficient sampling techniques. We have exploited this tool in 
 

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order to develop a set of 95% confidence intervals around the projected land use changes. 

Several key parameters were identified that have a significant impact on the land use change 

projections, including the yield elasticity (i.e., the change in yield that results from a change in 

that commodity’s price), the elasticity of transformation of land supply (i.e., the measure of how 

easily land can be converted between forest, pasture, and crop land), and the elasticity of 

transformation of crop land (i.e., the measure of how easily land can be converted between 

crops). Although the confidence intervals are relatively large, in most cases the ranges do not 

bracket zero. Therefore, we conclude that the impacts of the corn ethanol and soybean biodiesel 

mandates on land use change are statistically significant. These confidence intervals also bracket 

the FAPRI-CARD results. Additional information on the GTAP results is discussed in RIA 

Chapter 2. 

c. Feedstock Transport 

To estimate the GHG impacts of transporting corn from the field to an ethanol production 

facility and transporting the co-product DDGS from the ethanol facility to the point of use, we 

used the method described in the proposed rule. We also did not change our estimates for the 

transport of cellulosic biofuel feedstock and biomass-based diesel feedstock. 

 For sugarcane transport, we received the comment that the GREET defaults used to 

estimate the energy consumption and associated GHG emissions do not all reflect current 

industry practices. To address this concern, we reviewed the current literature on sugarcane 

transport and updated our assumptions on the distance sugarcane travels by truck from the field 
 

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to ethanol production facilities as well as the payload and fuel economy of those trucks. We 

incorporated these revised inputs into an updated version of the GREET model (Version 1.8c) in 

order to estimate the GHG impacts of sugarcane transport. More details on these updates can be 

found in Chapter 2 of the RIA. 

 

In the proposal, we discussed updating our analysis to incorporate the results of a recent 

study detailing biofuel production locations and modes of transport. This study, conducted by 

Oak Ridge National Laboratory, modeled the transportation of ethanol from production or import 

facilities to petroleum blending terminals. Since the study did not explicitly address the transport 

of biofuel feedstocks, we did not implement the results for this part of the analysis. However, we 

did incorporate the results into our assessment of the GHG impacts of fuel transportation. We 

will continue to examine whether our feedstock transport estimates could be significantly 

improved by implementing more detailed information on the location of biofuel production 

facilities. 

We also discussed updating the transportation modes and distances assumed for corn and 

DDGS to account for the secondary or indirect transportation impacts. For example, decreases in 

exports will reduce overall domestic agricultural commodity transport and emissions but will 

increase transportation of commodities internationally. We did not implement these secondary 

transportation impacts in this final rule. While we do not anticipate that such impacts would 

significantly change the lifecycle analysis, we plan to continue to look at this issue and consider 

incorporating them in the future. 
 

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d. Biofuel Processing 

For the proposal the GHG emissions from renewable fuel production were calculated by 

multiplying the Btus of the different types of energy inputs at biofuel process plants by emissions 

factors for combustion of those fuel sources. The Btu of energy input was determined based on 

analysis of the industry and specific work done as part of the NPRM. The emission factors for 

the different fuel types are from GREET and were based on assumed carbon contents of the 

different process fuels. The emissions from producing electricity in the U.S. were also taken 

from GREET and represent average U.S. grid electricity production emissions. 

We received comments on our approach and updated the analysis of GHG emissions 

from biofuel process for the final rule specifically regarding process energy use and the treatment 

of co-products. 

 Process Energy Use: For the final rule we updated each of our biofuel pathways to 

include the latest data available on process energy use. For the proposal, one of the key sources 

of information on energy use for corn ethanol production was a study from the University of 

Illinois at Chicago Energy Resource Center. Between proposal and final rule, the study was 

updated, therefore, we incorporated the results of the updated study in our corn ethanol pathways 

process energy use for the final rule. We also updated corn ethanol production energy use for 

different technologies in the final rule based on feedback from industry technology providers as 

part of the public comment period. The main difference between proposal and final corn ethanol 
 

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energy use values was a slight increase in energy use for the corn ethanol fractionation process, 

based on feedback from industry technology providers. 

For the proposal we based biodiesel processing energy on a process model developed by 

USDA-ARS to simulate biodiesel production from the Fatty Acid Methyl Ester (FAME) 

transesterification process. We received a number of comments from stakeholders that the 

energy balance for biodiesel production was overestimating energy use and should be updated. 

During the comment period USDA updated their energy balance for biodiesel production to 

incorporate a different biodiesel dehydration process based on a system which has resulted in a 

decrease in energy requirements. This change was reflected in the energy use values for 

biodiesel assumed in our final rule analysis which resulted in reduced GHG impacts from the 

biodiesel production process. 

In addition, for the final rule we have included an analysis of algae oil production for 

biodiesel based on ASPEN process modeling from NREL.174 The analysis is for two major 

cultivation pathways (open pond and photobioreactors) for a facility that can be feasibly 

commercialized in the future, represented by a “2022” target production. We coupled the algae 

oil production process (which includes cultivation, harvesting, and extraction) with the biodiesel 

production energy use from virgin oils energy use model under the assumption that algae oil is 

similar enough to that of virgin oil. 

 

174 Davis, Ryan. November 2009. Techno-economic analysis of microalgae-derived biofuel production. National 

Renewable Energy Laboratory (NREL) 
 

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For the cellulosic biofuel pathways, we updated our final rule energy consumption 

assumptions on process modeling also completed by NREL. For the NPRM, NREL estimated 

energy use for the biochemical enzymatic process to ethanol route in the near future (2010) and 

future (2015 and 2022).175,176,177 As there are multiple processing pathways for cellulosic 

biofuel, we have expanded the analysis for the FRM to also include thermochemical processes 

(Mixed-Alcohols route and Fischer-Tropsch to diesel route) for plants which assume woody 

biomass as its feedstock. 

Under the imported sugarcane ethanol cases we updated process energy use assumptions 

to reflect anticipated increases in electricity production for 2022 based on recent literature and 

comments to the proposal. One major change was assuming the potential use of trash (tops and 

leaves of sugarcane) collection in future facilities to generate additional electricity. The NPRM 

had only assumed the use of bagasse for electricity generation. Based on comments received, we 

are also assuming marginal electricity production (i.e., natural gas) instead of average electricity 

mix in Brazil which is mainly hydroelectricity. This approach assumes surplus electricity will 

likely displace electricity which is normally dispatched last, in this case typically natural gas 

based electricity. The result of this change is a greater credit for displacing marginal grid 

electricity and thus a lower GHG emissions profile for imported sugarcane ethanol than that 

assumed in the NPRM. We also received public comment that there are differences in the types 

of process fuel e.g. used in the dehydration process for ethanol. While using heavier fuels such 

 

175 Tao, Ling and Aden, Andy. November 2008. Techno-economic Modeling to Support the EPA Notice of 

Proposed Rulemaking (NOPR). National Renewable Energy Laboratory (NREL) 

176 Aden, Andy. September 2009. Mixed Alcohols from Woody Biomass – 2010, 2015, 2022. National Renewable 

Energy Laboratory (NREL) 

177 Davis, Ryan. August 2009. Techno-economic analysis of current technology for Fischer-Tropsch fuels. National 

Renewable Energy Laboratory (NREL) 
 

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as diesel or bunker fuel tends to increase the imported sugarcane ethanol emissions profile, the 

overall impact was small enough that lifecycle results did not change dramatically. 

Co-Products: In response to comments received, we included corn oil fractionation and 

extraction as a potential source of renewable fuels for this final rulemaking. Based on research 

of various corn ethanol plant technologies, corn oil as a co-product from dry mill corn ethanol 

plants can be used as an additional biodiesel feedstock source (see Section VII.A.2 for additional 

information). Dry mill corn ethanol plants have two different technological methods to withdraw 

corn oil during the ethanol production process. The fractionation process withdraws corn oil 

before the production of the DGS co-product. The resulting product is food-grade corn oil. The 

extraction process withdraws corn oil after the production of the DGS co-product, resulting in 

corn oil that is only suitable for use as a biodiesel feedstock. 

 Based on cost projections outlined in Section VII.A, it is estimated that by 2022, 70% of 

dry mill ethanol plants will conduct extraction, 20% will conduct fractionation, and that 10% will 

choose to do neither. These parameters have been incorporated into the FASOM and FAPRICARD models for the final rulemaking analysis, allowing for corn oil from extraction as a major 

biodiesel feedstock. 

Glycerin is a co-product of biodiesel production. Our proposal analysis did not assume 

any credit for this glycerin product. The assumption for the proposal was that by 2022 the 

market for glycerin would be saturated due to the large increase in biodiesel production in both 

the US and abroad and the glycerin would therefore be a waste product. We received a number 
 

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of comments that we should be factoring in a co-product credit for glycerin as there would be 

some valuable use for this product in the market. Based on these comments we have included 

for the final rule analysis that glycerin would displace residual oil as a fuel source on an energy 

equivalent basis. This is based on the assumption that the glycerin market would still be 

saturated in 2022 and that glycerin produced from biodiesel would not displace any additional 

petroleum glycerin production. However, the biodiesel glycerin would not be a waste and a low 

value use would be to use the glycerin as a fuel source. The fuel source assumed to be replaced 

by the glycerin is residual oil. This inclusion of a co-product credit for glycerin reduces the 

overall GHG impact of biodiesel compared to the proposal analysis. 

e. Fuel Transportation 

For the proposed rule, we estimated the GHG impacts associated with the transportation 

and distribution of domestic and imported ethanol and biomass-based diesel using GREET 

defaults. We have upgraded to the most recent version of GREET (Version 1.8c) for our 

transportation analysis in the final rule178. We made several other updates to the method we 

utilized in the proposed rule. These updates are described here and in more detail in Chapter 2 of 

the RIA. 

In the proposal, we noted our intention to incorporate the results of a recent study by Oak 

Ridge National Laboratory (ORNL) into our transportation analysis for the final rule. The 

ORNL study models the transportation of ethanol from refineries or import facilities to the 

 

178 The method used to estimate the GHG impacts associated with biodiesel transportation has not been changed 

since the proposal. This method utilized an earlier version of the GREET model. 
 

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petroleum blending terminals by domestic truck, marine, and rail distribution systems. We used 

ORNL’s transportation projections for 2022 under the EISA policy scenario to update our 

estimates of the GHG impacts associated with the transportation of corn, cellulosic, and 

sugarcane ethanol. Since the study did not address the distribution of ethanol from petroleum 

blending terminals to refueling stations, we continued to use GREET defaults to estimate these 

impacts. 

 The ORNL study also did not address the transportation of imported ethanol within its 

country of origin or en route to the import facility in the United States. As in the proposal, we 

used GREET defaults to estimate the impacts associated with the transportation of sugarcane 

ethanol within Brazil. We updated the GREET default for the average distance sugarcane 

ethanol travels by ocean tanker using recent shipping data from EIA in order to account for both 

direct Brazilian exports and the shipment of ethanol from countries in the Caribbean Basin 

Initiative. We received several comments on the back-haul emissions associated with ocean 

transport. For the final rule, we assumed that these emissions were negligible. 

f. Vehicle Tailpipe Emissions 

We updated the CO2 emissions factors for ethanol and biodiesel to be consistent with 

those used in the October 30, 2009 final rulemaking for the Mandatory GHG Reporting Rule. 

These changes caused the tailpipe GHG emission factors to increase by 0.8% for ethanol and to 

decrease by 1.5% for biodiesel. Specific tailpipe combustion values used in this final rule can be 
 

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found in Chapter 2of the RIA. Estimates for CH4 and N2O were made using outputs from EPA’s 

MOVES model. 

3. Petroleum Baseline

For the proposed rule, we conducted an analysis to determine the lifecycle greenhouse 

gas emissions for the petroleum baseline against which renewable fuels were to be compared. 

We utilized the GREET model (Version 1.8b), which uses an energy efficiency metric to 

calculate GHG emissions associated with the production of petroleum-based fuels. We received 

numerous comments regarding this approach. 

Petroleum baseline calculation from proposed rule: The GREET model relies on using 

average values as inputs to estimate aggregate emissions, rather than using site-specific values. 

Commenters noted a number of GREET input values that they believed to be incorrect. These 

included: energy efficiency values for crude oil extraction; methane emission factors for oil 

production and flaring; transportation distances for crude oil and petroleum products; and the oil 

tanker cargo payload value. Commenters also noted that GREET does not account for the 

energy consumption associated with crude oil transport in the country of extraction. 

In addition, commenters stated that the crude oil import slate assumed in the proposed 

rule was inconsistent with EIA crude oil production and import data for 2005. Commenters also 

noted that the gasoline and diesel mix that we used for the proposal did not match with EIA 

prime supplier sales volume data. One specific comment focused on the definition of low-sulfur 

diesel in GREET, where it is defined as being 11 ppm sulfur content, which is inconsistent with 
 

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EPA’s definition. As a result, in the proposed rule, all transportation diesel produced in 2005 

was assumed to be ultra-low sulfur diesel. 

We largely agree with the above comments. An updated version of the GREET model 

(Version 1.8c) is available, and it may address some of the issues raised by commenters. We 

considered using this new version of GREET with updated input values from publically available 

sources to determine the petroleum baseline for the final rule. However, we have decided that 

using the 2005 petroleum baseline model developed by the National Energy Technology 

Laboratory (NETL)179 would address the commenters’ concerns, and result in a more accurate 

and comprehensive assessment of the petroleum baseline than we could obtain using the GREET 

model. 

Use of NETL study for final rule petroleum baseline calculation: In the proposed rule, 

we requested comment on using the NETL study for our 2005 petroleum baseline for the final 

rulemaking. We only received one comment, which agreed that the NETL values were generally 

more accurate and better documented than the values in GREET. However, the commenter also 

stated that NETL’s use of 2002 crude oil extraction data would underestimate extraction 

emissions for 2005, and that it would be inconsistent to use the GREET model for determining 

GHG emissions from biofuels, but not for petroleum. 

We do not agree with the commenters’ criticism of the NETL model. We have not seen 

data that indicates that the GHG emissions associated with crude oil extraction would be 

 

179 Department of Energy: National Energy Technology Laboratory. 2009. NETL: Petroleum-Based Fuels Life 

Cycle Greenhouse Gas Analysis - 2005 Baseline Model. 
 

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appreciably different in 2005 than 2002. EPA also believes that it is important to use the best 

available tools to estimate a petroleum baseline that can be compared to renewable fuels. The 

fact that some GREET emission factors are used in the calculation of biofuel lifecycle GHG 

impacts is not a reason to use the GREET model for the petroleum baseline analysis over what 

we feel to be a better tool for the baseline calculation needed. 

NETL states that the goal of their study is to “determine the life cycle greenhouse gas 

emissions for liquid fuels (conventional gasoline, conventional diesel, and kerosene-based jet 

fuel) production from petroleum as consumed in the U.S. in 2005 to allow comparisons with 

alternative transportation fuel options on the same basis (i.e., life cycle modeling assumptions, 

boundaries, and allocation procedures).” Unlike GREET, the NETL study utilized site-specific 

data, such as country-specific crude oil extraction profiles and port-to-port travel distances for 

imported crude oil and petroleum products. The NETL model also accounts for NGLs and 

unfinished oils as refinery inputs, which is not available in GREET. 

Thus, we believe that use of the NETL model addresses the commenters’ concerns with 

the GREET inputs used in the proposed rule. We have also verified that the NETL model uses a 

crude oil input mix and gasoline and diesel product slate consistent with EIA data for 2005. 

For the final rule, we have also updated the CO2 emissions factors to be consistent with 

other EPA rulemakings. EPA recently revised the CO2 emission factors for gasoline and diesel 

and used them in the September 28, 2009 proposed rule to establish GHG standards for light-
 

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duty vehicles. These new factors are slightly lower than those used in the RFS2 proposal and 

result in a decrease in tailpipe GHG emissions of 0.4% for gasoline of 0.6% and for diesel. 

Overall, with the switch to NETL and the updated tailpipe values, the final petroleum 

baseline value calculated for the final rule analysis does not differ significantly from what we 

calculated in the proposed rule. 

Inclusion of estimate for land use change: Numerous commenters raised the issue of land 

use change with regard to oil production, both on a direct and indirect basis. The proposed rule 

analysis for baseline petroleum emissions did not consider any land use change emissions 

associated with crude oil extraction. For the final rule, we do not consider land use emissions 

associated with road or other infrastructure construction for petroleum extraction, transport, 

refining, or upgrading, as the land use change associated with roads constructed for crop and 

livestock production was also not included. Furthermore, land use associated with natural gas 

extracted for use in oil sands extraction or upgrading was also not considered, as the land use 

change from natural gas extracted for biofuels production was not considered. 

However, for the final rule we did consider the inclusion of land use emissions associated 

with oil extraction. Using estimates for land-use change from conventional oil production and 

oil sands in conjunction with our data for the carbon intensity of land being developed, we were 

able to determine GHG emissions associated with land use change for oil production. Our 

analysis showed that the value was negligible compared to the full petroleum lifecycle. More 

detail on this analysis can be found in Chapter 2 of the RIA. 
 

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Consideration of marginal impacts: We received several comments stating that we did 

not use consistent system boundaries in our comparisons of biofuels and petroleum-based fuels, 

in particular by using a marginal assessment of GHG emissions related to biofuel, but not doing 

so for baseline petroleum fuels. According to commenters, by not assessing the marginal 

impacts of petroleum production, we overestimated the GHG impacts of an increase in biofuel 

use in the proposed rule. Commenters argued that a consistent modeling approach would 

involve a marginal analysis for both biofuels and the petroleum baseline. 

The reason the system boundaries used for threshold assessment in the proposed rule and 

the final rule did not include a marginal analysis of petroleum production was due to the 

definition of “baseline lifecycle greenhouse gas emissions” in Section 211(o)(1)(C) of the CAA. 

The definitions of the different renewable fuel categories specify that the lifecycle threshold 

analysis be compared to baseline lifecycle greenhouse gas emissions, which are defined as: 

The term ‘baseline lifecycle greenhouse gas emissions’ means the average lifecycle 

greenhouse gas emissions, as determined by the Administrator, after notice and 

opportunity for comment, for gasoline or diesel (whichever is being replaced by the 

renewable fuel) sold or distributed as transportation fuel in 2005. 

Therefore, the petroleum production component of the system boundaries is specifically 

mandated by EISA to be based on the 2005 average for crude oil used to make gasoline or diesel 

sold or distributed as transportation fuel, and not the marginal crude oil that will be displaced by 
 

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renewable fuel. Furthermore, as the EISA language specifies that the baseline emissions are to 

be only “average” lifecycle emissions for this single specified year and volume, it does not allow 

for a comparison of alternative scenarios. Indirect effects can only be determined using such an 

analysis; therefore there are no indirect emissions to include in the baseline lifecycle greenhouse 

gas emissions. 

On the other hand, assessing the lifecycle GHG emissions of renewable fuel is not tied by 

statute to the 2005 baseline and could therefore be based on a marginal analysis of anticipated 

changes in transportation fuel as would result from meeting the EISA mandates. 

Thus, Congress did not, as many commenters suggested, intend to accomplish simply a 

reduction in GHG emissions as compared to the situation that would exist in the future without 

enactment of EISA, as would be the case if Congress had specified that EPA use a marginal 

analysis in assessing the GHG emissions related to conventional baseline fuels that the EISAmandated biofuels would replace Rather, the statute specifies a logical approach for reducing 

the GHG emissions of transportation fuel as compared to those emissions that occurred in 2005. 

Therefore, EPA has retained in today’s final rule the basic analytical approach (marginal analysis 

for biofuels and 2005 average for baseline fuels) used in the proposed rule. 

 C. Threshold Determination and Assignment of Pathways 

As required by EISA, EPA is making a determination of lifecycle GHG emission 

threshold compliance for the range of pathways likely to produce significant volumes of biofuel 
 

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for use in the U.S. by 2022. These threshold assessments only pertain to biofuels which are not 

produced in production facilities that are grandfathered (grandfathering of production facilities is 

discussed at the end of Section V.C).

As described in Section I.A.3, because of the inherent uncertainty and the state of the 

evolving science on this issue, EPA is basing its GHG threshold compliance determinations for 

this rule on an approach that considers the weight of evidence currently available. For fuel 

pathways with a significant land use impact, the evidence considered includes the best estimate 

as well as the range of possible lifecycle greenhouse gas emission results based on formal 

uncertainty and sensitivity analyses conducted by the Agency. In making the threshold 

determinations for this rule, EPA weighed all of the evidence available to it, while placing the 

greatest weight on the best estimate value for the base yield scenario. In those cases where the 

best estimate for the potentially conservative base yield scenario exceeds the reduction threshold, 

EPA judges that there is a good basis to be confident that the threshold will be achieved and is 

determining that the bio-fuel pathway complies with the applicable threshold. To the extent the 

midpoint of the scenarios analyzed lies further above a threshold for a particular biofuel 

pathway, we have increasingly greater confidence that the biofuel exceeds the threshold. 

EPA recognizes that the state of scientific knowledge in this area is continuing to evolve, 

and that as the science evolves, the lifecycle greenhouse gas assessments for a variety of fuel 

pathways will continue to change. Therefore, while EPA is making regulatory determinations 

for fuel pathways as required by the statute in this final rule based on its current assessment, EPA 

is at the same time committing to further reassess these determinations and the lifecycle 
 

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estimates. As part of the ongoing effort, we will ask for the expert advice of the National 

Academy of Sciences as well as other experts and then reflect this advice and any updated 

information in a new assessment of the lifecycle GHG emission performance of the biofuels 

being evaluated today. EPA will request that the National Academy of Sciences evaluate the 

approach taken in this rule, and the underlying science of lifecycle assessment and in particular 

indirect land use change, and make recommendations for subsequent rulemakings on this subject. 

This new assessment could in some cases result in new determinations of threshold compliance 

compared to those included in this rule which would apply to future production from plants that 

are constructed after each subsequent rule. 

Nonetheless, EPA is required by EISA to make threshold determinations at this time as to 

what fuels qualify for each of the four different fuel categories and lifecycle GHG thresholds. In 

the previous sections, we have described the analytical basis EPA is using for its lifecycle GHG 

assessment. These analyses represent the most up to date information currently available on the 

GHG emissions associated with each element of the full lifecycle assessment. Notably these 

analyses include an assessment of uncertainty for key parameters of the pathways evaluated. 

The best estimates and ranges of results for the different pathways can be used to help assess 

whether a particular pathway should be considered as attaining the 20%, 50% or 60% thresholds, 

as applicable. The graphs included in the discussion below provide representative depictions of 

the results of our analysis (including the uncertainty in the modeling) for typical pathways for 

corn ethanol, biodiesel produced from soy oil and from waste oils, fats and greases, sugarcane 

ethanol and cellulosic biofuel from switchgrass. We have also conducted lifecycle modeling 

assessments for cellulosic biofuel pathways using other feedstock sources, for biobutanol and for 
 

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two specific pathways for emerging biofuels that would use oil from algae as their feedstock. 

Additional GHG performance assessment results for other feedstock/fuel/technology 

combinations are also described below as well as in the RIA Chapter 2. 

Below we consider the analytical results of scenarios and fuel pathways modeled by EPA 

as well as additional appropriate information to determine the threshold compliance for an array 

of biofuels likely to be produced in 2022. 

Ethanol from corn starch: While EPA analyzed the lifecycle GHG performance of a 

variety of ethanol from corn starch pathways (complete results can be found in the RIA), for 

purposes of this threshold determination we have focused the discussion on the impacts of those 

plant designs that are most likely to be built in the future. We have focused this discussion on 

new plant designs because production from existing plants is grandfathered for purposes of 

compliance with the 20% lifecycle GHG threshold. Only new plants and expanded capacity at 

existing plants need to comply with a 20% lifecycle GHG emissions threshold to comply with 

the total renewable fuel mandate under the RFS2. 

While we focus our lifecycle GHG threshold analysis on the new plant designs most 

likely to be built through 2022, we also note that some existing plant designs, although subject to 

the grandfathering provisions, would not qualify if having to meet the 20% performance 

threshold. For example, existing designs of ethanol plants using coal as their process heat source 

would not qualify. 
 

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As discussed in Section IV, EPA anticipates that by 2022 any new dry mill plants 

producing ethanol from corn starch will be equipped with more energy efficient technology 

and/or enhanced co-product production than today’s average plant. These predictions are largely 

based on economic considerations. To compete economically, future ethanol plants will need to 

employ energy saving technologies and other value added technologies that have the effect of 

also reducing their GHG footprint. For example, while only in limited use today, we predict 

approximately 90% of all plants will be producing corn oil as a by-product either through a 

fractionation or extraction process; it is likely most if not all new plants will elect to include such 

technology. We also predict that all will use natural gas, biomass or biogas as the process energy 

source.180 181 We also expect that, to lower their operating costs, most facilities will sell a 

portion of their co-product DGS prior to drying thus reducing energy consumption and 

improving the efficiency and lifecycle GHG performance of the plant. The current national 

average plant sells approximately 37% of the DGS co-product prior to drying. 

In analyzing the corn ethanol plant designs we expect could be built through 2022 using 

natural gas or biomass for process energy and employing advanced technology, in all cases, the 

midpoint and therefore the majority of the scenarios analyzed are above the 20% threshold. 

This indicates that, based on the current modeling approaches and sets of assumptions, we are 

 

180 Dry mill corn ethanol plants using coal as a process energy source would not qualify as exceeding the 20% 

reduction threshold as modeled. We do not expect plants relying on coal for process energy to be built through 

2022. However, if they were built, they would need to use technology improvements such as carbon capture and 

storage (CCS) technology. We did not model what the performance would be if these plants also installed CCS 

technology. 

181 We believe do not believe new wet mill corn ethanol plants will be built through 2022 since this design is much 

more complicated and expensive than a dry mill plant. Especially since dry mill plants equipped with corn oil 

fractionation will produce additional supplies of food grade corn oil (one of the products and therefore reasons to 

construct a wet mill plant), we see no near term incentive for additional wet mill ethanol production capacity. 

However, we have modeled the lifecycle GHG impact of ethanol produced at a wet mill plant when relying on 

biomass as the process energy source and have determined it would meet the 20% GHG threshold. Therefore, this 

type of facility is also included in Table V.C-6. 
 

484

over 50% confident the actual GHG performance of the ethanol from new corn ethanol plants 

will exceed the threshold of 20% improvement in lifecycle GHG emissions performance 

compared to the gasoline it is replacing. 

We are determining at this time that the corn ethanol produced at such new plants (and 

existing plants with expanded capacity employing the same technology) will exceed the 20% 

GHG performance threshold. A complete listing of complying facilities using advanced 

technologies and operating procedures is included in Table V.C-6. 

Figure V.C-1 shows the percent change in the lifecycle GHG emissions compared to the 

petroleum gasoline baseline in 2022 for a corn ethanol dry mill plant using natural gas for its 

process energy source, drying the national average of 63% of the DGS it produces and 

employing corn oil fractionation technology. Lifecycle GHG emissions equivalent to the 

gasoline baseline are represented on the graph by the zero on the X-axis. The 20% reduction 

threshold is represented by the dashed line at -20 on the graph. The results for this corn ethanol 

scenario are that the midpoint of the range of results is a 21% reduction in GHG emissions 

compared to the gasoline 2005 baseline. The 95% confidence interval around that midpoint 

ranges from a 7% reduction to a 32% reduction compared to the gasoline baseline. 
 

485

Figure V.C-1 

Distribution of Results for a New Natural Gas Fired Corn Ethanol Plant 

Average 2022 plant: natural gas, 63% dry, 37% wet DGS (w/ fractionation) 

-50 -40 -30 -20 -10 0 10

Percentage Change in Biofuel GHG Lifecycle Emissions Compared to Petroleum Fuel
 

486

Table V.C-1 below includes lifecycle GHG emissions broken down by several stages of 

the lifecycle impacts for a natural gas dry mill corn ethanol facility as compared to the 2005 

baseline average for gasoline. This table (and similar tables which follow in the discussion for 

other biofuels) is included to transparently demonstrate the contribution of each stage and their 

relative significance. Lifecycle emissions are normalized per energy unit of fuel produced and 

presented in kilograms of carbon-dioxide equivalent GHG emissions per million British Thermal 

Units of renewable fuel produced (kg CO2e/mmBTU). The domestic and international 

agriculture rows include emissions from changes in agricultural production (e.g., fertilizer and 

energy use, rice methane) and livestock production. The fuel production row includes emissions 

from the fuel production or refining facility, primarily from energy consumption. For renewable 

fuels, tailpipe emissions only include non- CO2 gases, because the carbon emitted as a result of 

fuel combustion is offset by the uptake of biogenic carbon during feedstock production. Note, 

that while the table separates the emissions into different categories, the results are based on 

integrated modeling; therefore, one component can not be removed without impacting the other 

results. For example, domestic land use and agricultural sector emissions depend on the 

international assumptions. If a case without international impacts were modeled, the domestic 

results would likely be significantly different. 

The table includes our mean estimate of international land use change emissions as well 

as the 95% confidence range from our uncertainty assessment, which accounts for uncertainty in 

the types of land use changes and the magnitude of resulting GHG emissions. The last row 

includes mean, low and high total lifecycle GHG emissions based on the 95% confidence range 
 

487

for land use change emissions. For the petroleum baseline, the fuel production stage includes 

emissions from extraction, transport, refining and distribution of petroleum transportation fuel. 

Petroleum tailpipe emissions include CO2 and non- CO2 gases emitted from fuel combustion. 

Table V.C-1 

Lifecycle GHG Emissions for Corn Ethanol, 2022 

(kg CO2e/mmBTU) 

Fuel Type Ethanol 

2005 Gasoline 

Baseline 

Fuel Production Technology 

Natural Gas 

Fired Dry Mill 

Net Domestic Agriculture (w/o land 

use change) 4 

Net International Agriculture (w/o 

land use change) 12 

Domestic Land Use Change -2 

International Land Use Change, 

Mean (Low/High) 32 (21/46) 

Fuel Production 28 19 

Fuel and Feedstock Transport 4 

Tailpipe Emissions 1 79 

Total Emissions, 

Mean (Low/High) 79 (54/97) 98
 

488

While we are projecting technology enhancements which would allow corn ethanol 

plants to exceed the threshold, plant designs which do not included such advance technology 

would not comply. For example, a basic plant which is not equipped with combinations of 

advanced technologies such as corn oil fractionation or dries more than 50% of its DGS is 

predicted to not comply. While we do not expect such a basic, low technology plant to be built 

nor existing plants to expand their production without also installing such advanced technology, 

if this were to occur, ethanol produced at such facilities would not comply with the 20% 

threshold. 

Biodiesel from soybean oil: We analyzed the lifecycle GHG emission impacts of 

producing biodiesel using soy oil as a feedstock for compliance with a lifecycle GHG 

performance threshold of 50%. The modeling framework for this analysis was much the same as 

used for the proposal. However, as noted above, based on comments, updated information and 

enhanced models, the results are significantly updated. 

As in the case of ethanol produced from corn starch, EPA has relied on a weight of 

evidence in developing its threshold assessment for biodiesel produced from soybean oil. In 

analyzing the base yield case, the midpoint and therefore the majority of the scenarios analyzed 

exceed the threshold. This indicates that based on currently available information and our 

current analysis over the range of scenarios considered, the actual performance of soy oil-based 

biodiesel likely exceeds the applicable 50% threshold. 
 

489

The scenarios analyzed also indicate, based on current data, we are at least 95% confident 

biodiesel produced from soy oil will have GHG impacts which are better than the 2005 baseline 

diesel fuel. From a GHG impact perspective, we therefore conclude that even in the less likely 

event the actual performance of biodiesel from soy oil does not exceed the 50% threshold, GHG 

emission performance of transportation fuel would still improve if this biodiesel replaced diesel 

fuel. 

We are further confident that biodiesel exceeds the 50% threshold since our assessment 

of biodiesel GHG performance does not include any prediction of significant improvements in 

plant technology or unanticipated energy saving improvements that would further improve GHG 

performance. Additionally, our assumption that the co-product of glycerin would only have 

GHG value as replacement for residual heating oil could be conservative. While we have not 

analyzed the range of potential uses of glycerin, potential uses of glycerin including as a 

feedstock to the chemical industry could be higher in GHG benefit than its assumed use as a 

heating fuel. 

Considering all of the above current information and analyses, EPA concludes that 

biodiesel made from soy oil will exceed its lifecycle GHG threshold. Further, we see no benefit 

in lowering the threshold to as low as 40% as allowed under EISA as this will neither benefit 

available supply nor GHG performance of the fuel. Therefore, the threshold for this rule will be 

maintained at 50%. 
 

490

Figure V.C-2 shows the percent change in the typical 2022 soybean biodiesel lifecycle 

GHG emissions compared to the petroleum diesel fuel 2005 baseline. Lifecycle GHG emissions 

equivalent to the diesel fuel baseline are represented on the graph by the zero on the X-axis. The 

50% reduction threshold is represented by the dashed line at -50 on the graph. The results for 

soybean biodiesel are that the midpoint of the range of results is a 57% reduction in GHG 

emissions compared to the diesel fuel baseline. The 95% confidence interval around that 

midpoint results in range of a 22% reduction to an 85% reduction compared to the diesel fuel 

2005 baseline. 
 

491

Figure V.C-2 

Distribution of Results Soybean Biodiesel 

Average 2022 plant; natural gas 

-140 -120 -100 -80 -60 -40 -20 0 20

Percentage Change in Biofuel GHG Lifecycle Emissions Compared to Petroleum Fuel

 
 

492

Biodiesel from waste oils, fats and greases: The lifecycle assessment of GHG 

performance for biodiesel produced from waste oils, fats and greases is much simpler than 

comparable assessments for biofuels made from crops. In the case of biodiesel made from waste 

material, there is no land use impact so the agricultural assessments required for crop-based 

biofuels are unnecessary. Without the uncertainty concerns due to land use impacts, there was 

no need to conduct an uncertainty analysis for biodiesel from waste oils, fats and greases. The 

assessment methodology for biofuel from waste oils fats and greases is much the same as that 

analyzed for the proposal. As was the case for the proposal, the assessment of each element in 

the lifecycle process is straight forward and includes collecting and transporting the feedstock, 

transforming it into a biofuel and distributing and using the fuel. Based on the lifecycle 

assessment for this final rule, we are estimating biofuel from waste oils, fats and greases result in 

an 86% reduction in GHG emissions compared to the 2005 baseline for petroleum diesel. As 

was the case for the assessment included in the proposal, biofuel from these feedstock sources 

easily exceeds the applicable threshold of 50%. 

Table V.C-2 below breaks down by stage the lifecycle GHG emissions for soy-based 

biodiesel, biodiesel from waste grease feedstocks and the 2005 diesel baseline. The average 

2022 biodiesel production process reflected in this table assumes that natural gas is used for 

process energy and accounts for co-product glycerin displacing residual oil. This table 

demonstrates the contribution of each stage and their relative significance. 
 

493

Table V.C-2 

Lifecycle GHG Emissions for Biodiesel, 2022 

(kg CO2e/mmBTU) 

Fuel Type 

Soy-Based 

Biodiesel 

Waste Grease 

Biodiesel 

2005 Diesel 

Baseline 

Net Domestic Agriculture (w/o 

land use change) -10 0 

Net International Agriculture 

(w/o land use change) 1 0 

Domestic Land Use Change -9 0 

International Land Use Change, 

Mean (Low/High) 43 (15/76) 0 

Fuel Production 13 10 18 

Fuel and Feedstock Transport 3 3 

Tailpipe Emissions 1 1 79 

Total Emissions, Mean 

(Low/High) 42 (14/76) 14 97 

Biodiesel from algae oil: We analyzed the lifecycle GHG emission impacts of producing 

biodiesel from algae oil as a feedstock for compliance with a lifecycle performance threshold of 

50%. Our analyses were based on technoeconomic modeling completed by NREL, as previously 

discussed. The NREL modeling included algae cultivation, harvesting, extraction, and recover 

of algae oil. Algae oil is further assumed to use the same oil to biodiesel production technology 
 

494

as soy oil, which was updated based on enhanced models. As algae are expected to be grown on 

relatively small amounts of non-arable lands, it is expected that the land use impact will be 

negligible. Based on our current lifecycle assessment of algae oil for the final rule, we are 

determining that biodiesel from algae oil will comply with the lifecycle performance advanced 

biofuel threshold of 50%. 

Ethanol from sugarcane: As is the case for other crop-based biofuels, EPA considered 

the weight of evidence currently available information in assessing the lifecycle GHG 

performance of this fuel. As noted in Section I.A.3, this lifecycle GHG assessment includes 

significant updates from the analysis performed for the proposal. We have added pathways for 

sugarcane ethanol such that we now distinguish sugarcane ethanol produced assuming most crop 

residue (leaves and stalks) are collected and therefore available for burning as process energy, or 

sugarcane produced without the extra crop residue being collected nor burned as process energy. 

We also analyzed pathways assuming the ethanol is distilled in Brazil or alternatively being 

distilled in the Caribbean. We did not analyze a “high yield” case for sugarcane as we did for 

corn and soy since we had no information available suggesting there could be an appreciable 

range in expected sugarcane yields. 

Based on the currently available information, the midpoint and thus the majority of the 

scenarios analyzed exceed the 50% threshold applicable to advanced biofuels. This indicates 

that based on currently available information and our current analysis, it is more than 50% likely 

that the actual performance of ethanol produced from sugarcane exceeds the applicable 50% 

threshold. 
 

495

The analyses also indicate, based on current data, ethanol produced from sugarcane will 

clearly have GHG impacts which are better than the 2005 baseline gasoline. From a GHG 

impact perspective, we therefore conclude that even in the less likely event the actual 

performance of sugarcane does not exceed the 50% threshold, GHG emission performance of 

ethanol from sugarcane would be better than gasoline. 

We also considered what would happen if we determine that ethanol from sugarcane does 

not comply with a 50% threshold due to the relatively low risk that this biofuel will actually be 

below that threshold. Based on our current analysis of available pathways for producing 

advanced biofuel, we believe that it will be necessary to include over 2 billion gallons of 

sugarcane ethanol in order to meet the advanced biofuel volumes anticipated by EISA. If 

sugarcane ethanol was not an eligible source of advanced biofuel and other unanticipated sources 

did not become available, the standard for advanced biofuel would have to be lower to the extent 

necessary to compensate for the lack of eligible sugarcane ethanol. The lower amount of 

advanced biofuel would then most likely be replaced with petroleum-based gasoline. The 

replacement fuel would have a worse GHG performance than the sugarcane ethanol. Therefore, 

GHG performance of the transportation fuel pool would suffer. 

Considering the above, EPA has concluded that, based on currently available information 

and our analysis, ethanol from sugarcane qualifies as an advanced biofuel. 
 

496

Figure V.C-3 shows the percent change in the average 2022 sugarcane ethanol lifecycle 

GHG emissions compared to the petroleum gasoline 2005 baseline. These results assume the 

ethanol is produced and dehydrated in Brazil prior to being imported into the U.S. Lifecycle 

GHG emissions equivalent to the gasoline baseline are represented on the graph by the zero on 

the X-axis. The 50% reduction threshold is represented by the dashed line at -50 on the graph. 

The results for this sugarcane ethanol scenario are that the midpoint of the range of results is a 

61% reduction in GHG emissions compared to the gasoline baseline. The 95% confidence 

interval around that midpoint results in a range of a 52% to 71% reduction compared to the 

gasoline 2005 baseline. 
 

497

Figure V.C-3 

Distribution of Results for Sugarcane Ethanol 

Average 2022 plant: no residue collection, 

-90 -80 -70 -60 -50 -40 -30 -20 -10 0

Percentage Change in Biofuel GHG Lifecycle Emissions Compared to Petroleum Fuel
 

498

Table V.C-3 below presents results for sugarcane ethanol production and use by lifecycle 

stage. This table demonstrates the contribution of each stage and their relative significance. The 

fuel production emissions include displacement of marginal Brazilian electricity because 

electricity is generated with the sugarcane bagasse co-product. As in similar previous tables, 

domestic emissions include all emissions sources in the United States, with all other emissions—

including emissions from Brazil—presented in the international categories. 

Table V.C-3 

Lifecycle GHG Emissions for Sugarcane Ethanol, 2022 

(kg CO2e/mmBTU) 

Fuel Type 

Sugarcane 

Ethanol 

2005 

Gasoline 

Baseline 

Net Domestic Agriculture (w/o land use change) 0 0 

Net International Agriculture (w/o land use change) 38 0 

Domestic Land Use Change 1 0 

International Land Use Change, Mean (Low/High) 4 (-5/12) 0 

Fuel Production -11 19 

Fuel and Feedstock Transport 5 0 

Tailpipe Emissions 1 79 

Total Emissions, Mean (Low/High) 38 (29/46) 98 
 

499

Cellulosic Biofuels: In the proposal, we analyzed biochemical cellulosic ethanol 

pathways from both switchgrass and corn stover, and on that basis proposed that such cellulosic 

biofuels met the required 60% lifecycle threshold by a considerable margin. As described in 

Section V.B, we have considerably updated our lifecycle analysis, and have analyzed additional 

cellulosic biofuel pathways (i.e., thermochemical cellulosic ethanol and a BTL diesel pathway). 

We analyzed the GHG impacts of each element of the lifecycle for producing and using biofuels 

from cellulosic biomass, and as for other fuel pathways, considered the range of possible 

outcomes. 

Figure V.C-4 shows the percent change in the average lifecycle GHG emissions in 2022 

for ethanol produced from switchgrass using the biochemical process compared to the petroleum 

gasoline 2005 baseline. Lifecycle GHG emissions equivalent to the gasoline baseline are 

represented on the graph by the zero on the X-axis. The 60% reduction threshold is represented 

by the dashed line at -60 on the graph. The results for this switchgrass ethanol scenario are that 

the midpoint of the range of results is a 110% reduction in GHG emissions compared to the 

gasoline baseline. The 95% confidence interval around that midpoint ranges from 102% 

reduction to a 117% reduction compared to the gasoline baseline. 
 

500

Figure V.C-4 

Distribution of Results for Switchgrass Biochemical Ethanol

Average 2022 plant: biochemical process producing ethanol, excess electricity production 

-140 -120 -100 -80 -60 -40 -20 0

Percentage Change in Biofuel GHG Lifecycle Emissions Compared to Petroleum Fuel
 

501

Table V.C-4 below shows lifecycle GHG emissions for cellulosic ethanol produced from 

switchgrass (as depicted in Figure V.C-4, above) and also corn residue by lifecycle stage, 

comparing these to the 2005 baseline gasoline. This table is included to demonstrate the 

contribution of each stage and their relative significance. Results are presented for the 

biochemical production technology depicted in Figure V.C-4 above and also for thermochemical 

production technologies. The fuel production emissions for the biochemical pathway include 

credit for excess electricity generation at the fuel production facility. 

Table V.C-4 

Lifecycle GHG Emissions for Cellulosic Ethanol, 2022 

(kg CO2e/mmBTU) 

Fuel Type 

Switchgrass Ethanol Corn Residue 

2005 

Gasoline 

Baseline 

Fuel Production 

Technology 

BioChemical ThermoChemical BioChemical ThermoChemical 

Net Domestic 

Agriculture (w/o 

land use change) 6 6 11 11 0 

Net International 

Agriculture (w/o 

land use change) 0 0 0 0 0 
 

502

Domestic Land Use 

Change -2 -3 -11 -11 0 

International Land 

Use Change, 

Mean (Low/High) 15 (9/23) 16 (9/24) 0 0 0 

Fuel Production -33 4 -33 4 19 

Fuel and Feedstock 

Transport 3 3 2 2 0 

Tailpipe Emissions 1 1 1 1 79 

Total Emissions, 

Mean (Low/High) 

-10 

(-17/-2) 

27 

(20/35) -29 7 98 

 Table V.C-5 below presents lifecycle GHG emissions for cellulosic diesel produced with 

a Fischer-Tropsch process by lifecycle stage. 

Table V.C-5 

Lifecycle GHG Emissions for Cellulosic Diesel, 2022 

(kg CO2e/mmBTU) 

Fuel Type 

Switchgrass 

Diesel 

Corn Residue 

Diesel 

2005 Diesel 

Baseline 

Fuel Production Technology F-T Diesel F-T Diesel 

Net Domestic Agriculture 

(w/o land use change) 6 11 0 
 

503

Net International Agriculture 

(w/o land use change) 0 0 0 

Domestic Land Use Change -3 -11 0 

International Land Use 

Change, Mean (Low/High) 16 (9/24) 0 0 

Fuel Production 5 5 18 

Fuel and Feedstock 

Transport 3 2 0 

Tailpipe Emissions 1 1 79 

Total Emissions, 

Mean (Low/High) 29 (22/37) 9 97 

Based on the currently available information, we conclude that all modeled cellulosic 

biofuel pathways are expected to exceed the 60% threshold applicable to cellulosic biofuels. 

Assessments of similar feedstock sources: In the proposal, we indicated that although we 

did not specifically analyze all potential feedstock sources, some feedstock sources are similar 

enough to those modeled that we believe the modeled results could be extended to these similar 

feedstock types. Comments received supported this approach and the specific recommendations 

for similar feedstock designations as proposed. 
 

504

For this final rule, consistent with what was proposed, we are relying on modeling results 

and only expanding to additional pathways where we have good information these additional 

pathways will have lifecycle GHG results which either will not impact our overall assessment of 

the performance of that fuel pathway or would have at least as good as the modeled pathways. 

The agricultural sector modeling used for our lifecycle analysis does not predict any soybean 

biodiesel or corn ethanol will be imported into the U.S., or any imported sugarcane ethanol from 

production in countries other than Brazil. However, these rules do not prohibit the use in the U.S. 

of these fuels produced in countries not modeled if they are also expected to comply with the 

eligibility requirements including meeting the thresholds for GHG performance. Although the 

GHG emissions of producing these fuels from feedstock grown or biofuel produced in other 

countries has not been specifically modeled, we do not anticipate their use would impact our 

conclusions regarding these feedstock pathways. The emissions of producing these fuels in other 

countries could be slightly higher or lower than what was modeled depending on a number of 

factors. Our analyses indicate that crop yields for the crops in other countries where these fuels 

are also most likely to be produced are similar or lower than U.S. values indicating the same or 

slightly higher GHG impacts. Agricultural sector inputs for the crops in these other countries are 

roughly the same or lower than the U.S. pointing toward the same or slightly lower GHG 

impacts. If crop production were to expand due to biofuels in the countries where the models 

predict these biofuels might additionally be produced, this would tend to lower our assessment of 

international indirect impacts but could increase our assessment of the domestic (i.e., the country 

of origin) land use impacts. EPA believes, because of these offsetting factors along with the 

small amounts of fuel potentially coming from other countries, that incorporating fuels produced 

in other countries will not impact our threshold analysis. Therefore, fuels of the same fuel type, 
 

505

produced from the same feedstock using the same fuel production technology as modeled fuel 

pathways will be assessed the same GHG performance decisions regardless of country of origin. 

We are also able to conclude that some feedstock types not specifically modeled should 

be covered as we have good reason to believe their performance would be better than the 

feedstock pathways modeled. Thus for example, we can conclude that, as in the case of corn 

stover which we have modeled as a feedstock source, cellulosic biofuel produced from other 

agricultural waste will also have no land use impact and would be expected to have lifecycle 

GHG emission impacts similar enough to the modeled corn stover feedstock pathway such that 

they would also comply. Similarly, we have information on miscanthus indicating that this 

perennial will yield more feedstock per acre than the modeled switchgrass feedstock without 

additional GHG inputs such as fertilizer. Therefore we are concluding that since cellulosic 

biofuel from switchgrass complies with the cellulosic threshold of 60% reduction, fuel produced 

using miscanthus and other perennial grasses will also surely comply. 

We are also determined that biofuel from separated yard and food wastes (which may 

contain incidental and post-recycled paper and wood wastes) satisfy biofuel thresholds. 

Separated food waste is largely starch-based and thus qualifies for the advanced biofuel standard 

of 50% reduction. If the biofuel producer can demonstrate that it is able to quantify the 

cellulosic portion of food wastes, fuel made from the cellulosic portion can qualify as cellulosic 

biofuel. Since we have determined that yard wastes are largely cellulosic, biofuel from yard 

waste will qualify as cellulosic biofuel. The use of separated yard and food wastes for biofuel 

production including the requirements for demonstrating what portion of food waste is cellulosic 
 

506

feedstock is discussed further in Section II.B.4.d. EPA believes that renewable fuel produced 

from feedstocks consisting of wastes that would normally be discarded or put to a secondary use, 

and which have not been intentionally rendered unfit for productive use, should be assumed to 

have little or no land use emissions of GHGs. The use of wastes that would normally be 

discarded does not increase the demand for land. For example, the use in biofuel production of 

food waste from a food processing facility that would normally be placed in a landfill will not 

increase the demand for land to grow the crops that were purchased by the food processing 

facility. Similarly, wastes that would not normally be discarded because there are alternative 

secondary uses for them (for example contaminated vegetable oil might be burned in a boiler) 

are not produced for the purpose of such secondary use and the use of these feedstocks also does 

not increase demand for land. Since these waste-derived feedstocks have little or no land use 

impact, the lifecycle GHG emissions associated with their use for biofuel production are largely 

the result of the energy required to collect and process the feedstock prior to conversion, and the 

energy required to convert that feedstock into a biofuel. This has led us to conclude it is 

reasonable to include a restricted set of additional feedstocks in pathways complying with the 

applicable threshold. 

The look-up table identifies a number of individual fuel "pathways" that allow for the use 

of waste feedstocks. These feedstocks include 1) waste ethanol from beverage production, 2) 

waste starches from food production and agricultural residues, 3) waste oils/fats/greases, 4) 

waste sugar from food and beverage production, and 5) food and beverage production wastes. 

For the purpose of this rule only, EPA will consider these feedstocks to be “wastes” if they are 

used as feedstock to produce fuel, but would otherwise normally be discarded or used for another 
 

507

secondary purpose because they are no longer suitable for their original intended use. They may 

be unsuitable for their original intended use either because they are themselves waste from that 

original use (e.g., table scraps) or because of contamination, spoilage or other unintentional acts. 

EPA will not consider any material that has been intentionally rendered unsuitable for its original 

use to be a “waste.” 

 As discussed in more detail in Section II.B.4.d, EPA has also determined that the 

biogenic portion of post recycled MSW is eligible to produce renewable fuel and will largely be 

made up of cellulosic material. Therefore biofuel made from this waste-derived material will 

qualify as cellulosic biofuel. 

 

 EPA has also considered biofuels produced from annual cover crops such as cover crops 

grown in the winter. These annual cover crops are normally planted as a rotation between 

primary planted crops or between trees and vines in orchards and vineyards, typically to protect 

soil from erosion, improve the soil between periods of regular crops, or for other conservation 

purposes. For annual cover crops grown on the same land as the primary crops, we have 

determined that there is little or no land use impact such that the GHG emissions associated with 

them would largely result due to inputs required to grow the crop, harvesting and transporting to 

the biofuel production facility, turning that feedstock into a biofuel and transporting it to its end 

use. As such, the biofuel from cellulosic biomass from annual cover crops are, for example, 

determined to meet requirements of cellulosic biofuel, oil from annual cover crops are 

determined to meet the requirements of renewable diesel and starches from annual cover crops 

are determined to meet the requirements of advanced biofuel. 
 

508

While we have not been able to model all possible feedstocks that can and are being used 

for renewable fuel production, there are a variety of feedstocks that should have similar enough 

characteristics to those already modeled to allow them to be grouped in with already modeled 

fuel pathways. In particular, as discussed below, there are five categories of biofuel feedstock 

sources for which we are confident, by virtue of their lack of any land-use change impact, in 

qualifying them for particular renewable fuel standards (D-codes) on the basis of our existing 

modeling. 

1. All crop residues which provide starch or cellulosic feedstock. By virtue of the fact 

that they do not cause any land-use change impacts, they should all have similar 

lifecycle GHG impacts. Thus, modeling conducted for corn stover is being extended 

to other crop residues such as wheat straw, rice straw, and citrus residue. These 

residues are what remains after a primary crop is harvested, and can be similarly 

collected, transported and used in biofuel production. 

2. Slash, forest thinnings, and forest residue providing cellulosic feedstock. As excess 

material, these represent another form of residue which should also result in no landuse change GHG impacts. Their GHG emission impacts would only be associated 

with collection, transport, and processing into biofuel. Consequently, modeling 

conducted for corn stover is also being extended to these residues. 

3. Annual cover crops planted on existing crop land such as winter cover crops and 

providing cellulosic material, starch or oil for biofuel production. While different 

from crop residues, these secondary crops also have no land use impact since they are 
 

509

planted on land otherwise used for primary crop production. GHG emissions would 

only be associated with growing, harvesting and transporting the secondary crop and 

then processing into biofuel. In the case of secondary crops that might be used for 

cellulosic biofuel production, they would also have no land-use change impact, and 

consequently modeling conducted for corn stover is also being extended to these 

crops. In the case of secondary crops used for oil production, they would then have 

no land-use change similar to waste fats, oils and greases. Consequently, modeling 

conducted for biodiesel and renewable diesel from these waste oils is also being 

extended to these annual cover crops. 

4. Separated food and yard wastes, including food and beverage wastes from food 

production and processing are another category of waste product that would not have 

any land-use change impact. These waste products can be used as feedstock for 

advanced biofuel production or cellulosic biofuel production. Waste oils have 

already been modeled as complying with the biomass-based diesel standard. 

Applying our sugarcane results without the land-use change component to waste 

sugars clearly demonstrates compliance with the advanced biofuel threshold. 

Applying our corn results without the land-use component to waste starches clearly 

demonstrates compliance with the renewable fuel standard 

5. Perennial grasses including switchgrass and miscanthus. We modeled switchgrass 

and miscanthus has higher yield per acre without any significant (or perhaps less) 

inputs such as fertilizer per acre. We believe other perennial grasses likely to 

compete as feedstock sources will have similar land use and agricultural inputs are 

therefore confident the results from switchgrass can be extended to miscanthus and 
 

510

other perennial grasses. However, we note that the energy crop industry is just 

starting to develop and therefore as favored perennial grasses start to emerge, 

additional analyses may be warranted. 

Applicable D-Codes for Fuel Pathways: Based on the above, corn ethanol facilities using 

natural gas or biomass as the process energy source will meet the applicable 20% GHG 

performance threshold if it either also uses at least two of the technologies Table V.C-6 or one of 

the technologies in Table V.C-6 but marketing at least 35% of its DGS as wet. Alternatively, a 

facility using none of the advanced technologies listed in Table V.C-6 will qualify as producing 

ethanol meeting the 20% performance threshold if it sells at least 50% of its DGS prior to drying. 

Table V.C-6 

Modeled Advanced Technologies 

Corn oil fractionation 

Corn oil extraction 

Membrane separation 

Raw starch hydrolysis 

Combined heat and power 
 

511

Following the criteria for D-Codes defined in Section II.A-1, the following renewable fuel 

pathways have been found to comply with the applicable lifecycle GHG thresholds and are 

therefore eligible for the D-Codes specified in Table V.C-7. 
 

512

Table V.C-7 

D-Code Designations 

Fuel Type Feedstock Production Process 

requirements 

D-Code 

Ethanol Corn starch All of the following: 

Drymill process, using 

natural gas, biomass or 

biogas for process 

energy and at least two 

advanced technologies 

from Table V.C-6) 

6 (renewable 

fuel) 

Ethanol Corn starch All of the following: 

Dry mill process, using 

natural gas, biomass or 

biogas for process 

energy and one of the 

advanced technologies 

from Table V.C-6 plus 

drying no more than 65% 

of the DGS it markets 

annually. 

6 (renewable 

fuel) 
 

513

Ethanol Corn starch All of the following: 

Dry mill process, using 

natural gas, biomass or 

biogas for process 

energy and drying no 

more than 50% of the 

DGS it markets annually.

6 (renewable 

fuel) 

Ethanol Corn starch Wet mill process using 

biomass or biogas for 

process energy. 

6 (renewable 

fuel) 

Ethanol Starches from 

agricultural residues; 

starches from annual 

cover crops 

Fermentation using 

natural gas, biomass or 

biogas for process 

energy 

6 (renewable 

fuel) 

Biodiesel, and 

renewable diesel 

Soy bean oil; 

Oil from annual cover 

crops 

Algal oil 

Biogenic waste 

One of the following: 

Trans-Esterification 

Hydrotreating 

Excluding processes that 

coprocess renewable 

4 (biomass-based 

diesel) 
 

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oils/fats/greases; 

Non-food grade corn oil 

biomass and petroleum 
 

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Biodiesel, and 

renewable diesel 

Soy bean oil; 

Oil from annual cover 

crops 

Algal oil 

Biogenic waste 

oils/fats/greases; 

Non-food grade corn oil 

One of the following: 

Trans-Esterification 

Hydrotreating 

Includes only processes 

that coprocess renewable 

biomass and petroleum 

5 (Advanced) 

Ethanol Sugarcane Fermentation (Any) 5 (Advanced) 

Ethanol Cellulosic Biomass from 

agricultural residues, 

slash, forest thinnings, 

forest product residues, 

annual cover crops, 

switchgrass and 

miscanthus; cellulosic 

components of separated 

yard wastes; cellulosic 

components of separated 

food wastes; and 

Any 3 (Cellulosic 

Biofuel) 
 

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cellulosic components of 

separated MSW 

Cellulosic Diesel, 

Jet Fuel and 

Heating Oil 

Cellulosic Biomass from 

agricultural residues, 

slash, forest thinnings, 

forest product residues, 

annual cover crops, 

switchgrass and 

miscanthus; cellulosic 

components of separated 

yard wastes, cellulosic 

components of separated 

food wastes, and 

cellulosic components of 

separated MSW 

Any 7 (Cellulosic 

Biofuel or 

Biomass-Based 

Diesel) 

 Butanol Corn starch Fermentation; dry mill 

using natural gas, 

biomass or biogas for 

process energy 

 6 (renewable 

fuel) 

Cellulosic Naphtha Cellulosic Biomass from 

agricultural residues, 

slash, forest thinnings, 

forest product residues, 

Fischer-Tropsch process 3 (Cellulosic 

Biofuel) 
 

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annual cover crops, 

switchgrass and 

miscanthus; cellulosic 

components of separated 

yard wastes, cellulosic 

components of separated 

food wastes, and 

cellulosic components of 

separated MSW 

Ethanol, renewable 

diesel, jet fuel, 

heating oil, and 

naphtha 

The non-cellulosic 

portions of separated 

food wastes 

Any 5 (Advanced) 

Biogas Landfills, sewage and 

waste treatment plants, 

manure digesters 

Any 5 (Advanced) 

Pathways for which we have not made a threshold compliance decision: The pathways 

identified in the Table V.C-6 represent those pathways we have analyzed and determined meet 

the applicable thresholds as establish by EISA. We did not analyze all pathways that might be 
 

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feasible through 2022. In some cases, we did not have sufficient time to complete the necessary 

lifecycle GHG impact assessment for this final rule. In addition to the pathways identified in 

Table V.C-6, EPA anticipates modeling grain sorghum ethanol, woody pulp ethanol, and palm 

oil biodiesel after this final rule and including the determinations in a rulemaking within 6 

months. Based on current and projected commercial trends and the status of current analysis at 

EPA, biofuels from these three pathways are either currently being produced or are planned 

production in the near-term. Our analyses project that they will be used in meeting the RFS2 

volume standard in the near-term. During the course of the NPRM comment period, EPA 

received detailed information on these pathways and is currently in the process of analyzing 

these pathways. We have received comments on several additional feedstock/fuel pathways, 

including rapeseed/canola, camelina, sweet sorghum, wheat, and mustard seed, and we welcome 

parties to utilize the petition process described below to request EPA to examine additional 

pathways. 

In other cases, we have not modeled the lifecycle GHG performance of pathways because 

we did not have sufficient information. For those fuel pathways that are different than those 

pathways EPA has listed in today’s regulations, EPA is establishing a petition process whereby a 

party can petition the Agency to consider new pathways for GHG reduction threshold 

compliance. The petition process is meant for parties with serious intention to moved forward 

with production via the petitioned fuel pathway and who have moved sufficiently forward in the 

business process to show feasibility of the fuel pathway’s implementation. The Agency will not 

consider frivolous petitions with insufficient information and clarity for Agency analysis. In 

addition, if the petition addresses a fuel pathway that already complies for one or more types of 
 

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renewable fuels under RFS (e.g., renewable fuel or advanced biofuel), the pathway must have the 

potential to result in the pathway qualifying for a new renewable fuel category for which it was 

not previously qualified. Thus, for example, the Agency will not undertake any additional 

review for a party wishing to get a modified LCA value for a previously approved fuel pathway 

if the desired new value would not change the overall pathway classification. EPA will process 

these petitions as expeditiously as possible, taking into consideration that some fuel pathways are 

closer to the commercial production stage than others. In all events, parties are expected to begin 

this process with ample lead time as compared to their commercial start dates. 

In addition to the technical information described below and listed in today’s regulations 

(see § 80.1416), a petition must include all information required in the registration process 

except the engineering review. The petition should demonstrate technical and commercial 

feasibility. For example, a petition could include copies of applications for air or construction 

permits, copies of blue prints of the facility, or photographs of the facility or pilot plant. The 

petition must include information necessary to allow EPA to effectively determine the lifecycle 

green house gas emissions of the fuel. The petitioner must describe the alternative production 

facility technology applied and supply data establishing the energy savings that will result from 

the use of the alternative technology. The information required would include, at a minimum, a 

mass and energy balance for the proposed fuel production process. This would include for 

example, mass inputs of raw material feedstocks and consumables, mass outputs of fuel product 

produced as well as co-products and waste materials production. Energy inputs information 

should include fuels used by type, including purchased electricity. If steam or hot water is 

purchased, the source and fuel required for its generation would also be reported. Energy output 
 

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information should include energy content of the fuel product produced (with heating value 

specified) as well as energy content of any co-products. The petitioner should also report the 

extent to which excess electricity is generated and distributed outside the production facility. 

Information on co-products should include the expected use of the co-products and their market 

value. All information should be provided in a format such that it can be normalized on a fuel 

output basis (for example, tons feedstock per gallon of fuel produced). Other process 

descriptions necessary to understand the fuel production process should be included (e.g., 

process modeling flowcharts). Any other relevant information, including that pertaining to 

energy saving technologies or other process improvements that document significant differences 

between the fuel production processes outlined in this rule and that used by the renewable fuel 

producer, should also be submitted with the petition. 

For fuel pathways that utilize feedstocks that have not yet been modeled for this 

rulemaking, the petition must also submit information on the feedstock. Information would 

include, at a minimum, the feedstock type and feedstock production source and data on the 

market value of the feedstock and current uses of the feedstock, if any. The petition should also 

include chemical input requirements (e.g., fertilizer, pesticides, etc.) and energy use in feedstock 

production listed by type of energy. Yield information would also be required for both the 

current yields of the feedstock as well as anticipated changes in feedstock yields over time. 

EPA will use the data supplied in the petition and other data and information available to 

the Agency to technically evaluate whether the information is sufficient for EPA to make a 

determination of the RFS standards for which the fuel pathway may qualify. If EPA determines 
 

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that the petition is insufficient for determination, the petitioner will be so notified. If EPA 

determines it has been provided sufficient data from the petitioner to evaluate the fuel pathway, 

we will then proceed with any analyses required to make a technical determination of 

compliance. 

 EPA anticipates that for some petitioned fuel pathways with unique modifications or 

enhancements to production technologies of pathways otherwise modeled for the regulations 

listed today, EPA may be able to evaluate the pathway as a reasonably straight-forward 

extension of our current assessments. We expect such a determination would be pathway 

specific, and would be based on a technical analysis that compared the applicant fuel pathway to 

the fuel a pathway(s) that had already been analyzed. In these cases, EPA would be able make a 

determination without proceeding through a full rulemaking process. For example, petitions may 

submit unique biofuel production facility configurations, operations, or co-product pathways that 

could result in greater efficiencies than the pathways modeled for this rulemaking, but otherwise 

do not differ greatly from the modeled fuel pathways. In such cases, we would expect to make a 

decision for that specific pathway without conducting a full rulemaking process. We would 

expect to evaluate whether the pathway is consistent with the definitions of renewable fuel types 

in the regulations, generally without going through rulemaking, and issue an approval or 

disapproval that applies to the petitioner. We anticipate that we will subsequently propose to add 

the pathway to the regulations. 

If EPA determines that a petitioned fuel pathway requires significant new analysis and/or 

modeling, EPA will need to give notice and seek public comment. For example, we anticipate 
 

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that pathways with feedstocks or fuel types not yet modeled by EPA will require additional 

modeling and public comment before a determination of compliance can be made. In these cases, 

the determination would be incorporated into the annual rulemaking process established in 

today’s regulations. 

When EPA makes a technical determination is made that a petitioned fuel pathway 

qualifies for a RFS volume standard, a D-code will be assigned to the fuel pathway. We 

anticipate that renewable fuel producers and importers will be able to generate RINs for the 

additional pathway after the next available update of the EPA Moderated Transaction System 

(EMTS) that follows a determination. EPA expects to update the EMTS quarterly, as long as 

necessary. Renewable fuel producers will be able to register the fuel pathway through the EPA 

Fuels Programs Registration System two weeks after the date of determination, but as described 

above, will not be able to generate RINs until the quarterly EMTS update. 

In the proposal, we suggested a system of temporary D-codes for biofuel pathways we 

had not analyzed. This was proposed as a means of assuring no undue hardship for biofuel 

producers using feedstock sources or processing technologies not analyzed by EPA. As 

proposed, these producers could market their fuel on the basis of temporarily assigned D-codes. 

While the objective was sound, EPA now believes it is best to properly assure compliance with 

thresholds on the basis of completed lifecycle GHG assessments. As noted above, the Agency 

commits to expedited assessment and rulemaking for those pathways most likely to generate 

biofuel in the immediate future, including ethanol produced from grain sorghum, ethanol, woody 

pulp ethanol, and palm oil biodiesel. We also plan to continue to model additional pathways we 
 

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expect will be commercially available in the U.S. as soon as sufficient information is available to 

complete a quality lifecycle assessment. For these reasons, EPA is not finalizing a provision for 

assigning temporary D-codes. 

D. Total GHG Reductions

Similar to the analysis done in our proposal, our analysis of the overall GHG emission 

impacts of increased volumes of renewable fuel was performed in parallel with the lifecycle 

analysis performed to develop the individual fuel thresholds described in previous sections. The 

same sources of emissions apply such that this analysis includes the effects of three main areas: 

a) emissions related to the production of biofuels, including the growing of feedstock (corn, 

soybeans, etc.) with associated domestic and international land use change impacts, transport of 

feedstock to fuel production plants, fuel production, and distribution of finished fuel; b) 

emissions related to the extraction, production and distribution of petroleum gasoline and diesel 

fuel that is replaced by use of biofuels; and c) difference in tailpipe combustion of the renewable 

and petroleum based fuels. 

The main difference between the results of the proposal analysis and the final rule 

analysis are higher domestic land use change emissions in the final rule analysis. As was the 

case in the proposal, simply adding up the individual lifecycle results determined in Section V.C. 

multiplied by their respective volumes would yield a different assessment of the overall impacts. 

The two analyses are separate in that the overall impacts capture interactions between the 
 

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different fuels that can not be broken out into per fuels impacts, while the threshold values 

represent impacts of specific fuels but do not account for all the interactions. 

 While individual fuel analysis generally had small domestic land use change emission 

impacts, the overall impacts had larger domestic land use change emissions. The primary reason 

for the difference in domestic land use change between the individual fuel scenarios and the 

combined fuel scenarios is that when looking at individual fuels there is some interaction 

between different crops (e.g., corn replacing soybeans), but with combined volume scenario 

when all mandates need to be met there is less opportunity for crop replacement (e.g., both corn 

and soybean acres needed) and therefore more land is required. 

As discussed in previous sections on lifecycle GHG thresholds there is an initial one time 

release from land conversion and smaller ongoing releases, but there are also ongoing benefits of 

using renewable fuels over time replacing petroleum fuel use. Based on the volume scenario 

considered, the one time land use change impacts result in 313 million metric tons of CO2-eq. 

emissions increase. There are, however, based on the biofuel use replacing petroleum fuels, 

GHG reductions in each year. Totaling the emissions impacts over 30 years but assuming a 0% 

discount rate over this 30 year period would result in an estimated total NPV reduction in GHG 

emissions of 4.15 billion tons over 30 years. 

This total NPV reduction can be converted into annual average GHG reductions, which 

can be used for the calculations of the monetized GHG benefits as shown in Section VIII.C.3. 

This annualized value is based on converting the lump sum present values described above into 
 

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their annualized equivalents. A comparable value assuming 30 years of GHG emissions 

changes, but not applying a discount rate to those emissions results in an estimated annualized 

average emission reduction of approximately 138 million metrics tons of CO2-eq. emissions. 

We also considered the uncertainty in the international land use change emission 

estimates for the overall impacts. Based on the range of results for the international land use 

change emissions the overall annualized average emission reductions of increased volumes of 

renewable fuel could range from -136 to -140 million metrics tons of CO2-eq. emissions. 

E. Effects of GHG Emission Reductions and Changes in Global Temperature and 

Sea Level 

The reductions in CO2 and other GHGs associated with increased volumes of renewable 

fuel will affect climate change projections. GHGs mix well in the atmosphere and have long 

atmospheric lifetimes, so changes in GHG emissions will affect future climate for decades to 

centuries. Two common indicators of climate change are global mean surface temperature and 

global mean sea level rise. This section estimates the response in global mean surface 

temperature and global mean sea level rise projections to the estimated net global GHG 

emissions reductions associated with increased volumes of renewable fuel. 

EPA estimated changes in projected global mean surface temperatures to 2050 using the 

MiniCAM (Mini Climate Assessment Model) integrated assessment model182 coupled with the 

 

182MiniCAM is a long-term, global integrated assessment model of energy, economy, agriculture and land use, that 

considers the sources of emissions of a suite of greenhouse gases (GHGs), emitted in 14 globally disaggregated 
 

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MAGICC (Model for the Assessment of Greenhouse-Gas Induced Climate Change) simple 

climate model.183 MiniCAM was used to create the globally and temporally consistent set of 

climate relevant variables required for running MAGICC. MAGICC was then used to estimate 

the change in the global mean surface temperature over time. Given the magnitude of the 

estimated emissions reductions associated with the increased volumes of renewable fuel, a 

simple climate model such as MAGICC is reasonable for estimating the climate response. 

EPA applied the estimated annual GHG emissions changes for the final rule to a 

MiniCAM baseline emissions scenario.184 Specifically, the CO2, N2O, and CH4 annual emission 

 

global regions (i.e., U.S., Western Europe, China), the fate of emissions to the atmosphere, and the consequences of 

changing concentrations of greenhouse related gases for climate change. MiniCAM begins with a representation of 

demographic and economic developments in each region and combines these with assumptions about technology 

development to describe an internally consistent representation of energy, agriculture, land-use, and economic 

developments that in turn shape global emissions. Brenkert A, S. Smith, S. Kim, and H. Pitcher, 2003: Model 

Documentation for the MiniCAM. PNNL-14337, Pacific Northwest National Laboratory, Richland, Washington. 

For a recent report and detailed description and discussion of MiniCAM, see Clarke, L., J. Edmonds, H. Jacoby, H. 

Pitcher, J. Reilly, R. Richels, 2007. Scenarios of Greenhouse Gas Emissions and Atmospheric Concentrations. Subreport 2.1A of Synthesis and Assessment Product 2.1 by the U.S. Climate Change Science Program and the 

Subcommittee on Global Change Research. Department of Energy, Office of Biological & Environmental Research, 

Washington, DC., USA, 154 pp. 

183 MAGICC consists of a suite of coupled gas-cycle, climate and ice-melt models integrated into a single 

framework. The framework allows the user to determine changes in GHG concentrations, global-mean surface air 

temperature and sea-level resulting from anthropogenic emissions of carbon dioxide (CO2), methane (CH4), nitrous 

oxide (N2O), reactive gases (e.g., CO, NOx, VOCs), the halocarbons (e.g. HCFCs, HFCs, PFCs) and sulfur dioxide 

(SO2). MAGICC emulates the global-mean temperature responses of more sophisticated coupled 

Atmosphere/Ocean General Circulation Models (AOGCMs) with high accuracy. Wigley, T.M.L. and Raper, S.C.B. 

1992. Implications for Climate and Sea-Level of Revised IPCC Emissions Scenarios Nature 357, 293-300. Raper, 

S.C.B., Wigley T.M.L. and Warrick R.A. 1996. in Sea-Level Rise and Coastal Subsidence: Causes, Consequences 

and Strategies J.D. Milliman, B.U. Haq, Eds., Kluwer Academic Publishers, Dordrecht, The Netherlands, pp. 11-45. 

Wigley, T.M.L. and Raper, 

S.C.B. 2002. Reasons for larger warming projections in the IPCC Third Assessment Report J. Climate 15, 2945-

2952. 

184 The reference scenario is the MiniCAM reference (no climate policy) scenario used as the basis for the 

Representative Concentration Pathway RCP4.5 using historical emissions until 2005. This scenario is used because 

it contains a comprehensive suite of greenhouse and pollutant gas emissions including carbonaceous aerosols. The 

four RCP scenarios will be used as common inputs into a variety of Earth System Models for inter-model 

comparisons leading to the IPCC AR5 (Moss et al. 2008). The MiniCAM RCP4.5 is based on the scenarios 

presented in Clarke et al. (2007) with non-CO2 and pollutant gas emissions implemented as described in Smith and 

Wigley (2006). Base-year information has been updated to the latest available data for the RCP process. 
 

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changes from 2022-2052 from Section V.D were applied as net reductions to this baseline 

scenario for each GHG. 

Table V.E-1 provides our estimated reductions in projected global mean surface 

temperatures and mean sea level rise associated with the reductions in GHG emissions due to the 

increase in renewable fuels in 2022. To capture some of the uncertainty in the climate system, we 

estimated the changes in projected temperatures and sea level across the most current 

Intergovernmental Panel on Climate Change (IPCC) range of climate sensitivities, 1.5°C to 

6.0°C.185 To illustrate the time profile of the estimated reductions in projected global mean 

surface temperatures and mean sea level rise, we have also provided Figures V.E-1 and V.E-2. 

Table V.E-1 

Estimated Reductions in Projected Global Mean Surface Temperature and Global Mean Sea 

Level Rise from Baseline in 2020-2050 

Climate Sensitivity 

1.5 2 2.5 3 4.5 6 

Year Change in global mean surface temperatures (degrees Celsius) 

2020 0.000 0.000 0.000 0.000 0.000 0.000 

2025 0.000 0.000 0.000 0.000 0.000 0.000 

2030 0.000 0.000 0.000 0.000 0.000 0.000 

 

185 In IPCC reports, equilibrium climate sensitivity refers to the equilibrium change in the annual mean global 

surface temperature following a doubling of the atmospheric equivalent carbon dioxide concentration. The IPCC 

states that climate sensitivity is “likely” to be in the range of 2°C to 4.5°C and described 3°C as a "best estimate." 

The IPCC goes on to note that climate sensitivity is “very unlikely” to be less than 1.5°C and “values substantially 

higher than 4.5°C cannot be excluded.” IPCC WGI, 2007, Climate Change 2007 - The Physical Science Basis, 

Contribution of Working Group I to the Fourth Assessment Report of the IPCC, http://www.ipcc.ch/. 
 

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2035 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 

2040 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 

2045 -0.001 -0.001 -0.001 -0.001 -0.002 -0.002 

2050 -0.001 -0.001 -0.002 -0.002 -0.002 -0.002 

Year Change in global mean sea level rise (centimeters) 

2020 0.000 0.000 0.000 0.000 0.000 0.000 

2025 0.000 0.000 0.000 0.000 0.000 0.000 

2030 -0.001 -0.001 -0.001 -0.001 -0.001 -0.001 

2035 -0.002 -0.002 -0.002 -0.003 -0.003 -0.003 

2040 -0.003 -0.004 -0.004 -0.005 -0.005 -0.006 

2045 -0.005 -0.006 -0.006 -0.007 -0.008 -0.009 

2050 -0.006 -0.008 -0.009 -0.009 -0.011 -0.012 

The results in Table V.E-1 and Figures V.E-1 and V.E-2 show small reductions in the 

global mean surface temperature and sea level rise projections across all climate sensitivities. 

Overall, the reductions are small relative to the IPCC’s “best estimate” temperature increases by 

2100 of 1.8oC to 4.0oC.186 Although IPCC does not issue “best estimate” sea level rise 

projections, the model-based range across SRES scenarios is 18 to 59 cm by 2099.187 While the 

distribution of potential temperatures in any particular year is shifting down, the shift is not 

uniform. The magnitude of the decrease is larger for higher climate sensitivities. The same pattern 

 

186 IPCC WGI, 2007. 187 “Because understanding of some important effects driving sea level rise is too limited, this report does not assess 

the likelihood, nor provide a best estimate or an upper bound for sea level rise.” IPCC Synthesis Report, p. 45 
 

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appears in the reductions in the sea level rise projections. Thus, we can conclude that the impact of 

increased volumes of renewable fuel is to lower the risk of climate change, as the probabilities of 

temperature increase and sea level rise are reduced.
 

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VI. How Would the Proposal Impact Criteria and Toxic Pollutant Emissions and 

Their Associated Effects? 

This section presents our assessment of the changes in emissions and air quality resulting 

from the increased renewable fuel volumes needed to meet the RFS2 standards. Increases in 

emissions of hydrocarbons, nitrogen oxides, particulate matter, and other pollutants are projected 

to lead to increases in population-weighted annual average ambient PM and ozone 

concentrations. The air quality impacts, however, are highly variable from region to region. 

Ambient PM2.5 is likely to increase in areas associated with biofuel production and transport and 

decrease in other areas; for ozone, many areas of the country will experience increases and a few 

areas will see decreases. Ethanol concentrations will increase substantially; for the other 

modeled air toxics there are some localized impacts, but relatively little impact on national 

average concentrations. 

 A. Overview of Emissions Impacts 

Today’s action will affect the emissions of “criteria” pollutants (those pollutants for 

which EPA has established a National Ambient Air Quality Standard has been established), 

criteria pollutant precursors,188 and air toxics, which may affect overall air quality and health. 

Emissions are affected by the processes required to produce and distribute large volumes of 

biofuels required by today’s action and the direct effects of these fuels on vehicle and equipment 

emissions. As detailed in Chapter 3 of the Regulatory Impact Analysis (RIA), we have estimated 

emissions impacts of production and distribution-related emissions using the life cycle analysis 

methodology described in Section V with emission factors for criteria and toxic emissions for 

each stage of the life cycle, including agriculture, feedstock transportation, and the production 

 

188 NOx and VOC are precursors to the criteria pollutant ozone; we group them with criteria pollutants in this 

chapter for ease of discussion 
 

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and distribution of biofuel; included in this analysis are the impacts of reduced gasoline and 

diesel refining as these fuels are displaced by biofuels. Emission impacts of tailpipe and 

evaporative emissions for on and off road sources have been estimated by incorporating “per 

vehicle” fuel effects from recent research into mobile source emission inventory estimation 

methods. 

In the proposal we analyzed a single renewable fuel volume scenario, largely dependent 

on ethanol, relative to three different reference cases, including the RFS1 base case. For today’s 

rule we are presenting emission impacts for three fuel volume scenarios relative to two reference 

cases (RFS1 mandate and AEO) to show a range of the possible effects of biofuels depending on 

the relative quantities of various biofuels that may be used to meet the overall renewable fuel 

requirements. We have also updated our modeling for the RFS1 mandate reference case to better 

reflect the emissions for this case. Table VI.A-1 shows the fuel volumes for the two reference 

cases and all three control scenarios. Further discussion of these fuel volumes and the 

subcategories within each are available in Section IV.A. The emission impacts of the primary 

control scenario (22.2 Bgal of ethanol) are presented here relative to both reference cases. The 

corresponding results for all three control cases are available in Chapter 3 of the Regulatory 

Impact Analysis for this rule. 
 

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Table VI.A-1 

Renewable Fuel Volumes for Each Reference Case and Control Scenario 

(Bgal/year in 2022) 

Ethanol 

Scenario 

Corn Cellulosic Imported Total 

Biodiesel

Renewable 

Diesel 

Cellulosic 

Diesel 

RFS1 Ref 7.046 0.0 0.0 7.046 0.303 0.0 0.0 

AEO Ref 12.29 0.25 0.64 13.18 0.38 0.0 0.0 

Low Ethanol 15.0 0.25 2.24 17.49 1.67 0.15 9.26 

Mid Ethanol 

(Primary) 

15.0 4.92 2.24 22.16 1.67 0.15 6.52 

High Ethanol 15.0 16.0 2.24 33.24 1.67 0.15 0.0 

There have been a number of other enhancements and corrections to the non-GHG 

emission inventory estimates since the NPRM, some of which were included in the air quality 

modeling inventories, while others occurred later than that. The major changes are mentioned 

here, and all the significant changes are explained in detail in Chapter 3 of the RIA. 

One significant change relates to the “downstream” vehicle and equipment emission 

impacts of using the increased proportions of renewable fuels. In the proposal we provided two 

different analyses based on two different assumptions regarding the effects of E10 and E85 

versus E0 on exhaust emissions from cars and trucks. Those were referred to as "less sensitive" 

and "more sensitive" cases. Based on analysis of recent emissions test data conducted since 
 

533

publication of the NPRM, we are modeling a single case. As detailed in Section VI.C, the case 

modeled for the final rule is a hybrid approach, applying “more sensitive” impacts for E10 and 

pre-Tier 2 light duty vehicles, and applying the “less sensitive” E10 effects for Tier 2 light duty 

cars and trucks, which means no impact for NOx or non-methane hydrocarbons (NMHC). We 

have also updated our estimates of evaporative permeation impacts of E10 based on recent 

studies. Finally, for the final rule inventories we are only claiming emission effects with use of 

E85 in flex-fueled vehicles relative to E0 for two pollutants: ethanol and acetaldehyde, for which 

data suggests the effects are more certain. For the “more sensitive case” presented in the 

NPRM, and used in the air quality modeling, we had estimated changes to additional pollutants 

(including significant PM reductions) based on some very limited data. Until such time as 

additional data is collected to enhance this analysis it is premature to use such assumptions. 

For “upstream” emissions associated with fuel production and distribution, the largest 

change that was included in the air quality modeling was the improved estimate of VOC and 

ethanol vapor emissions during ethanol transport, made possible by a detailed analysis of costs 

and transport modes conducted by Oak Ridge National Laboratory (ORNL).189 This change 

alone more than doubled the predicted overall increase in ethanol emissions from the increased 

use of renewable fuels, increasing the VOC enough to change the overall VOC impact from a 

decrease to a substantial increase. 

Significant updates have also been made to emissions from cellulosic biofuel plants, in 

part to reflect the assumed shift in volumes from cellulosic ethanol to diesel between the 

 

189 “Analysis of Fuel Ethanol Transportation Activity and Potential Distribution Constraints,” Oak Ridge National 

Laboratory, U.S. Department of Energy, March 2009. 
 

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proposed and final rules. For cellulosic ethanol plants, after the air quality modeling was done 

we discovered that the calculation of emissions from these plants had been overestimated due to 

failing to account for the portion of biomass that is not used for process energy. This change 

decreases the estimated NOx and CO impacts, and shifts the PM impact of these plants from an 

increase to a small decrease. However, these changes are counterbalanced by varying degrees 

by shifting some of the cellulosic volume from ethanol to diesel, which requires nearly twice the 

biomass as needed by ethanol to produce one gallon. While the net effect of the changes in 

cellulosic plant emissions is a decrease in NOx and CO emission impacts relative to the proposal, 

the shift to cellulosic diesel under the primary scenario results in a larger increase in “upstream” 

PM emissions than reported in the NPRM or used in the air quality analysis. 

Updates to agricultural modeling assumptions made between proposal and final had a 

significant impact on ammonia (NH3) emissions. Final modeling reflects an increase in fertilizer 

use with the primary control case, which results in a 1.2 percent increase in NH3 emissions, a 

change from the 0.5 percent decrease projected for the proposal and negligible impact used in the 

air quality analyses. 

Analysis of criteria and toxic emission impacts was performed for calendar year 2022, 

since this year reflects the full implementation of today’s rule. Our 2022 projections account for 

projected growth in vehicle travel and the effects of applicable emission and fuel economy 

standards, including Tier 2 and Mobile Source Air Toxics (MSAT) rules for cars and light trucks 

and recently finalized controls on spark-ignited off-road engines. 
 

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The analysis presented here provides estimates of the change in national emission totals 

that would result from the increased use of renewable fuels to meet the statutory requirements of 

EISA. These totals may not be a good indication of local or regional air quality and health 

impacts. These results are aggregated across highly localized sources, such as emissions from 

ethanol plants and evaporative emissions from cars, and reflect offsets such as decreased 

emissions from gasoline refineries. The location and composition of emissions from these 

disparate sources may strongly influence the air quality and health impacts of the increased use 

of renewable fuels, so full-scale photochemical air quality modeling was also performed to 

accurately assess this. These localized impacts are discussed in Section VI.D. 

Our projected emission impacts for the primary renewable fuel scenario relative to the 

two reference cases are shown in Table VI.A-2 for 2022. This shows the expected emission 

changes for the U.S. in that year, and the percent contribution of this impact relative to the total 

U.S. inventory. Overall we project that increases in the use of renewable fuels will result in 

significant increases in ethanol and acetaldehyde emissions – increasing the total U.S inventories 

of these pollutants by 16-18 percent in 2022 relative to the RFS1 mandate case. We project more 

modest increases in NOx, HC, PM, formaldehyde, 1,3-butadiene, acrolein, and ammonia (NH3) 

relative to the RFS1 mandate case. We project a 5 percent decrease in CO (due to impacts of 

ethanol on exhaust emissions from vehicles and nonroad equipment), and a 2.4 percent decrease 

in benzene (due to displacement of gasoline with ethanol in the fuel pool). Impacts on SO2 and 

naphthalene are much smaller. Relative to the AEO reference case the results are similar 

directionally, but smaller in magnitude due to the less drastic differences in fuel volumes. 
 

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Table VI.A-2 

Total Combined Upstream and Downstream Emission Impacts in 2022 

for Primary Scenario Relative to Each Reference Case 

RFS1 Mandate AEO 

Pollutant Annual 

Short Tons 

% of Total 

US 

Inventory 

Annual 

Short Tons 

% of Total 

US 

Inventory 

NOx 247,604 1.95% 184,820 1.45% 

HC 100,762 0.87% 24,523 0.21% 

PM10 69,013 1.92% 63,323 1.76% 

PM2.5 15,549 0.46% 14,393 0.42% 

CO -2,869,842 -5.30% -376,419 -0.69% 

Benzene -4,264 -2.41% -1,004 -0.57% 

Ethanol 100,123 18.20% 54,137 9.84% 

1,3-Butadiene 224 1.70% 59 0.45% 

Acetaldehyde 5,848 15.80% 3,108 8.40% 

Formaldehyde 355 0.48% 130 0.17% 

Naphthalene -1 -0.01% -4 -0.03% 

Acrolein 22 0.38% 21 0.35% 

SO2 3,286 0.04% 5,065 0.06% 

NH3 48,711 1.15% 48,711 1.15% 

The breakdown of these results by the fuel production /distribution (“well-to-pump” 

emissions) and vehicle and equipment (“pump-to-wheel”) emissions is discussed in the 

following sections. 
 

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B. Fuel Production & Distribution Impacts of the Proposed Program 

Fuel production and distribution emission impacts of the increased use of renewable fuels 

were estimated in conjunction with the development of life cycle GHG emission impacts and the 

GHG emission inventories discussed in Section V. These emissions are calculated according to 

the breakdowns of agriculture, feedstock transport, fuel production, and fuel distribution; the 

basic calculation is a function of fuel volumes in the analysis year and the emission factors 

associated with each process or subprocess. Additionally, the emission impact of displaced 

petroleum is estimated, using the same domestic/import shares discussed in Section V above. 

In general the basis for this life cycle evaluation was the analysis conducted as part of the 

Renewable Fuel Standard (RFS1) rulemaking, but enhanced significantly. While our approach 

for the RFS1 was to rely heavily on the “Greenhouse Gases, Regulated Emissions, and Energy 

Use in Transportation” (GREET) model, developed by the Department of Energy’s Argonne 

National Laboratory (ANL), we are now able to take advantage of additional information and 

models to significantly strengthen and expand our analysis for this rule. In particular, the 

modeling of the agriculture sector was greatly expanded beyond the RFS1 analysis, employing 

economic and agriculture models to consider factors such as land-use impact, agricultural 

burning, fertilizer, pesticide use, livestock, crop allocation, and crop exports. 

Other updates and enhancements to the GREET model assumptions include updated 

feedstock energy requirements and estimates of excess electricity available for sale from new 
 

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cellulosic ethanol plants, based on modeling by the National Renewable Energy Laboratory 

(NREL). Per-gallon emission factors for new corn ethanol plants were updated based on EPA 

analysis of energy efficiency technologies currently available (such as combined heat and power) 

and their expected market penetrations. There are no new standards planned at this time that 

would offer any additional control of emissions from corn or cellulosic ethanol plants. EPA also 

updated the fuel and feedstock transport emission factors to account for recent EPA emission 

standards and modeling, such as the locomotive and commercial marine standards finalized in 

2008, and revised heavy-duty truck emission rates contained in EPA’s draft MOVES2009 model. 

EPA also modified the ethanol transport distances based on a detailed analysis of costs versus 

transport mode conducted by Oak Ridge National Laboratory. In addition, GREET does not 

include air toxics or ethanol. Thus emission factors for ethanol and the following air toxics were 

added: benzene, 1,3-butadiene, formaldehyde, acetaldehyde, acrolein and naphthalene. 

Results of these calculations relative to each reference case in 2022 are shown in Table 

VI.B-1 for the criteria pollutants, ammonia, ethanol and individual air toxic pollutants. Due to 

the complex interactions involved in projections in the agricultural modeling, we did not attempt 

to adjust the agricultural inputs of the AEO reference case for the RFS1 mandate reference case. 

So the fertilizer and pesticide quantities, livestock counts, and total agricultural acres were the 

same for both reference cases. The agricultural modeling that had been done for the RFS1 rule 

itself was much simpler and inconsistent with the new modeling, so it would be inappropriate to 

use those estimates. 
 

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The fuel production and distribution impacts of the increased use of renewable fuels on 

VOC are mainly due to increases in emissions connected with biofuel production, countered by 

decreases in emissions associated with gasoline production and distribution as ethanol displaces 

some of the gasoline. Increases in PM2.5, SOx and especially NOx are driven by stationary 

combustion emissions from the substantial increase in corn and cellulosic ethanol production. 

Biofuel plants (corn and cellulosic) tend to have greater combustion emissions relative to 

petroleum refineries on a per-BTU of fuel produced basis. Increases in SOx emissions are also 

due to increases in agricultural chemical production and transport, while substantial PM 

increases are also associated with fugitive dust from agricultural operations. Ammonia 

emissions are expected to increase substantially due to increased ammonia from fertilizer use. 

Ethanol vapor and most air toxic emissions associated with fuel production and 

distribution are projected to increase. Relative to the US total reference case emissions with 

RFS1 mandate ethanol volumes, increases of 4-13 percent for acetaldehyde and ethanol vapor 

are especially significant because they are driven directly by the increased ethanol production 

and distribution. Formaldehyde and acrolein increases are smaller, on the order of 0.4-1 percent. 

There are also very small decreases in benzene, 1,3-butadiene and naphthalene relative to the US 

total emissions. 
 

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Table VI.B-1 

“Upstream” Fuel Production and Distribution Impacts of the Primary Scenario 

 in 2022 Relative to Each Reference Case 

RFS1 Mandate AEO 

Pollutant Annual 

Short Tons 

% of Total 

US 

Inventory 

Annual 

Short Tons 

% of Total 

US 

Inventory 

NOx 169,665 1.34% 164,170 1.29% 

HC 77,014 0.67% 19,737 0.17% 

PM10 69,583 1.94% 63,892 1.78% 

PM2.5 15,864 0.47% 14,707 0.43% 

CO 135,658 0.25% 130,172 0.24% 

Benzene -231 -0.13% -236 -0.13% 

Ethanol 69,445 12.63% 35,865 6.52% 

1,3-Butadiene -1 -0.01% 0 0.00% 

Acetaldehyde 1,617 4.37% 933 2.52% 

Formaldehyde 293 0.39% 187 0.25% 

Naphthalene -8 -0.06% -6 -0.04% 

Acrolein 67 1.13% 37 0.63% 

SO2 3,266 0.04% 5,044 0.06% 

NH3 48,711 1.15% 48,711 1.15% 

C. Vehicle and Equipment Emission Impacts of Fuel Program 
 

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The effects of the increased use of renewable fuels on vehicle and equipment emissions 

are a direct function of the effects of these fuels on exhaust and evaporative emissions from 

vehicles and off-road equipment, and evaporation of fuel from portable containers. To assess 

these impacts we conducted separate analyses to quantify the emission impacts of additional E10 

due to the increased use of renewable fuels on gasoline vehicles, nonroad spark-ignited engines 

and portable fuel containers; E85 on cars and light trucks; biodiesel on diesel vehicles; and 

increased refueling events due to lower energy density of biofuels.190

In the proposal we provided two different analyses based on two different assumptions 

regarding the effects of E10 and E85 on exhaust emissions from cars and trucks. Those were 

referred to as "less sensitive" and "more sensitive" cases. Based on analysis of recent studies, 

today's analysis is based on a hybrid of these two scenarios. As detailed in the RIA, EPA and 

other parties have been gathering additional data on the emission impacts of ethanol fuels on 

later model vehicles. Data available in time for this analysis supports the hypothesis of the “less 

sensitive” case that newer technology Tier 2 vehicles are generally able to control for changes to 

emissions associated with low level ethanol blends; for this analysis we therefore are not 

attributing any NOx or VOC impact to the use of E10 on these vehicles. The data does show 

sensitivity for older technology (pre-Tier 2) vehicles, so this analysis does attribute an increase in 

NOx and decrease in NMHC to the use of E10 in these vehicles. This analysis does not include 

any emission impacts with use of E85 in flex-fueled vehicles, except for increases in ethanol and 

acetaldehyde, as the limited data currently available is insufficient to quantify the impact with 

any degree of certainty. Overall the sensitivity of exhaust emissions to ethanol assumed for the 

 

190 The impact of renewable diesel was not estimated for this analysis; we expect little overall impact on criteria and 

toxic emissions due to the relatively small volume change, and because emission effects relative to conventional 

diesel are presumed to be negligible. 
 

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final rule analysis is closer to the “less sensitive” case presented in the proposal; and is generally 

less sensitive than the case used for the air quality modeling, as discussed in Section VI.D. 

We have also updated our estimates of E10 effects on permeation emissions from lightduty vehicles based on testing recently completed by the Coordinating Research Council (CRC), 

showing that the relative increase in VOC emissions is higher for newer technology vehicles. 

Nonroad spark ignition (SI) emission impacts of E10 were based on EPA’s NONROAD model 

and show trends similar to light duty vehicles. Biodiesel effects for this analysis were unchanged 

from the proposal, and are based on an analysis of recent biodiesel testing, detailed in the RIA, 

showing a 2 percent increase in NOx with a 20 percent biodiesel blend, a 16 percent decrease in 

PM, and a 14 percent decrease in HC. These results essentially confirm the results of an earlier 

EPA analysis. This analysis does not attribute any downstream emission impact from the use of 

renewable diesel or cellulosic-based diesel relative to conventional diesel due to their chemical 

similarity to diesel fuel and limited test data. 

Summarized vehicle and equipment emission impacts in 2022, updated as noted above, 

are shown in Table VI.C-1 relative to each reference case. The totals shown below reflect the 

net impacts from all mobile sources, including car and truck evaporative emissions, off road 

emissions, and portable fuel containers. Additional breakdowns by mobile source category can 

be found in Chapter 3 of the RIA. 
 

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 Carbon monoxide, PM, benzene, and acrolein are projected to decrease in 2022 as a 

result of the increased use of renewable fuels, while NOx, HC and the other air toxics, especially 

ethanol and acetaldehyde, are projected to increase due to the impacts of E10. 

Table VI.C-1 

“Downstream” Vehicle and Equipment Emission Impacts of the Primary Scenario 

 in 2022 Relative to Each Reference Case 

RFS1 Mandate AEO 

Pollutant Annual 

Short Tons 

% of Total 

US 

Inventory 

Annual 

Short Tons 

% of Total 

US 

Inventory 

NOx 77,939 0.61% 20,650 0.16% 

HC 23,748 0.21% 4,786 0.04% 

PM10 -569 -0.02% -569 -0.02% 

PM2.5 -315 -0.01% -315 -0.01% 

CO -3,005,500 -5.55% -506,591 -0.94% 

Benzene -4,033 -2.28% -768 -0.43% 

Ethanol 30,678 5.58% 18,272 3.32% 

1,3-Butadiene 225 1.71% 59 0.45% 

Acetaldehyde 4,231 11.43% 2,175 5.88% 

Formaldehyde 62 0.08% -57 -0.08% 

Naphthalene 7 0.05% 2 0.01% 

Acrolein -44 -0.75% -16 -0.28% 

SO2 21 0.00% 21 0.00% 

NH3 0 0.00% 0 0.00% 
 

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D. Air Quality Impacts 

Air quality modeling was performed to assess the projected impact of the renewable fuel 

volumes required by RFS2 on emissions of criteria and air toxic pollutants. Our air quality 

modeling reflects the impact of increased renewable fuel use required by RFS2 compared with 

two different reference cases that include the use of renewable fuels: a 2022 reference case 

projection based on the RFS1-mandated volume of 7.1 billion gallons of renewable fuels, and a 

2022 reference case projection based on the AEO 2007 volume of roughly 13.6 billion gallons of 

renewable fuels. Thus, the results represent the impact of an incremental increase in ethanol and 

other renewable fuels. We note that the air quality modeling results presented in this final rule 

do not constitute the “anti-backsliding” analysis required by Clean Air Act section 211(v). EPA 

will be analyzing air quality impacts of increased renewable fuel use through that study and will 

promulgate appropriate mitigation measures under section 211(v), separate from this final action. 

It is critical to note that a key limitation of the analysis is that it employed interim 

emission inventories, which were somewhat enhanced compared to what was described in the 

proposal, but due to the timing of the analysis did not include some of the later enhancements 

and corrections of the final emission inventories presented in this FRM (see Section VI.A 

through VI.C of this preamble). Most significantly, our modeling of the air quality impacts of 

the renewable fuel volumes required by RFS2 relied upon interim inventories that assumed that 

ethanol will make up 34 of the 36 billion gallon renewable fuel mandate, that approximately 20 

billion gallons of this ethanol will be in the form of E85, and that the use of E85 results in fewer 

emissions of direct PM2.5 from vehicles. The emission impacts and air quality results would be 
 

545

different if, instead of E85, more non-ethanol biofuels are used or mid-level ethanol blends are 

approved. 

In fact, as explained in Section IV, our more recent analyses indicate that ethanol and 

E85 volumes are likely to be significantly lower than what we assumed in the interim 

inventories. Furthermore, the final emission inventories do not include vehicle-related PM 

reductions associated with E85 use, as discussed in Section VI.A and VI.C of this preamble. 

There are additional, important limitations and uncertainties associated with the interim 

inventories that must be kept in mind when considering the results: 

• Error in PM2.5 emissions from locomotive engines 

After the air quality modeling was completed, we discovered an error in the way that 

PM2.5 emissions from locomotive engines were allocated to counties in the inventory. 

Although there was very little impact on national-level PM2.5 emissions, PM2.5

emission changes were too high in some counties and too low in others, by varying 

degrees. As a result, we do not present the modeling results for specific localized 

PM2.5 impacts. However, we have concluded that PM2.5 modeling results are still 

informative for national-level benefits assessment, as discussed at more length in 

Section VIII.D of this preamble and the RIA. 

• Sensitivity of light-duty vehicle exhaust emissions to ethanol blends

As discussed above in Sections VI.A and VI.C of this preamble, the interim emission 

inventories used for the air quality modeling analysis are the “more sensitive” case 

described in the proposal. As a result, the interim inventories used for air quality 
 

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modeling assume that vehicles operating on E10 have higher NOx emissions and 

lower VOC, CO and PM exhaust emissions compared to the FRM inventories. 

• Cellulosic plant emissions

The interim emission inventories used in air quality modeling generally assumed 

higher emissions from cellulosic plants than the FRM inventories, which used revised 

estimates based on updates to the fraction of biomass burned at these plants. 

However, as noted in Section VI.A, the shift of some cellulosic volume from ethanol 

to diesel results in higher PM emissions from cellulosic plants in the final rule 

inventories than used in the air quality modeling inventories. 

• Ethanol volume

As mentioned above, the interim emission inventories used in our air quality 

modeling reflect the use of ethanol in about 34 of the mandated 36 billion gallons and 

do not include any cellulosic diesel. As shown in Table VI.A-1, the FRM inventories 

assume 22 billion gallons of ethanol in the primary case and 6.5 billion gallons of 

cellulosic diesel. The inventories used for air quality modeling assume ethanol 

volumes are more consistent with the FRM's high-ethanol case inventory, which 

reflects the use of 33 billion gallons of ethanol and no cellulosic diesel. 

• Renewable fuel transport emissions 

As discussed in Section 3.3, the estimates of renewable fuel transport volumes and 

distances differ between the air quality modeling and final rule inventories. 
 

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In this section, we present information on current modeled levels of pollution as well as 

projections for 2022, with respect to ambient PM2.5, ozone, selected air toxics, and nitrogen and 

sulfur deposition. The air quality modeling results indicate that ambient PM2.5 is likely to 

increase in areas associated with biofuel production and transport and decrease in other areas. 

The results of the air quality modeling also indicate that many areas of the country will 

experience increases in ambient ozone and a few areas will see decreases in ambient ozone as a 

result of the renewable fuel volumes required by RFS2. The modeling also shows that ethanol 

concentrations increase substantially with increases in renewable fuel volumes. For the other 

modeled air toxics, there are some localized impacts, but relatively little impact on national 

average concentrations. Our air quality modeling does not show substantial overall nationwide 

impacts on the annual total sulfur and nitrogen deposition occurring across the U.S. However, 

the air quality modeling results indicate that the entire Eastern half of the U.S. along with the 

Pacific Northwest would see increases in nitrogen deposition as a result of increased renewable 

fuel use. The results of the modeling also show that sulfur deposition will increase in the 

Midwest and in some rural areas of the west associated with biofuel production. The results are 

discussed in more detail below and in Section 3.4 of the RIA. 

We used the Community Multi-scale Air Quality (CMAQ) photochemical model, version 

4.7, for our analysis. This version of CMAQ includes a number of improvements to previous 

versions of the model that are important in assessing impacts of the increased use of renewable 

fuels, including additional pathways for formation of soluble organic aerosols (SOA). These 

improvements are discussed in Section 3.4 of the RIA. 

In addition to the limitations of the analysis that result from the use of interim emission 

inventories rather than the FRM inventories, there are uncertainties in the air quality analysis that 
 

548

should be noted. First, there are uncertainties inherent in the modeling process. Pollutants such 

as ozone, PM, acetaldehyde, formaldehyde, acrolein, and 1,3-butadiene can be formed 

secondarily through atmospheric chemical processes. These processes can be very complex, and 

there are uncertainties in emissions of precursor compounds and reaction pathways. In addition, 

simplifications of chemistry must be made in order to handle reactions of thousands of chemicals 

in the atmosphere. Another source of uncertainty involves the hydrocarbon speciation profiles, 

which are applied to the VOC inventories to break VOC down into individual constituent 

compounds which react in the atmosphere. Given the complexity of the atmospheric chemistry, 

the hydrocarbon speciation has an important influence on the air quality modeling results. 

Speciation profiles for a number of key sources are based on data with significant limitations. 

Finally, there are uncertainties in the surrogates used to allocate emissions spatially and 

temporally; this is particularly significant in projecting the location of new ethanol plants, 

especially future cellulosic biofuel plants. These plants can have large impacts on local 

emissions. A more detailed discussion of these and additional uncertainties and limitations 

associated with our air quality modeling is presented in Section 3.4 of the RIA. 

1. Particulate Matter

a. Current Levels 

PM2.5 concentrations exceeding the level of the PM2.5 NAAQS occur in many parts of the 

country. In 2005, EPA designated 39 nonattainment areas for the 1997 PM2.5 NAAQS (70 FR 

943, January 5, 2005). These areas are composed of 208 full or partial counties with a total 

population exceeding 88 million. The 1997 PM2.5 NAAQS was recently revised and the 2006 

24-hour PM2.5 NAAQS became effective on December 18, 2006. On October 8, 2009, the EPA 
 

549

issued final nonattainment area designations for the 2006 24-hour PM2.5 NAAQS (74 FR 58688, 

November 13, 2009). These designations include 31 areas composed of 120 full or partial 

counties with a population of over 70 million. In total, there are 54 PM2.5 nonattainment areas 

composed of 245 counties with a population of 101 million people. 

b. Projected Levels without RFS2 Volumes 

States with PM2.5 nonattainment areas are required to take action to bring those areas into 

compliance in the future. Areas designated as not attaining the 1997 PM2.5 NAAQS will need to 

attain the 1997 standards in the 2010 to 2015 time frame, and then maintain them thereafter. The 

2006 24-hour PM2.5 nonattainment areas will be required to attain the 2006 24-hour PM2.5

NAAQS in the 2014 to 2019 time frame and then be required to maintain the 2006 24-hour PM2.5

NAAQS thereafter. 

EPA has already adopted many emission control programs that are expected to reduce 

ambient PM2.5 levels and which will assist in reducing the number of areas that fail to achieve 

the PM2.5 NAAQS. Even so, recent air quality modeling for the “Control of Emissions from 

New Marine Compression-Ignition Engines at or Above 30 Liters per Cylinder” rule projects 

that in 2020, at least 10 counties with a population of almost 25 million may not attain the 1997 

annual PM2.5 standard of 15 μg/m3

 and 47 counties with a population of over 53 million may not 

attain the 2006 24-hour PM2.5 standard of 35 μg/m3

.

191 These numbers do not account for those 

areas that are close to (e.g., within 10 percent of) the PM2.5 standards. These areas, although not 

 

191 US EPA (2009). Final Rule “Control of Emissions from New Marine Compression-Ignition Engines at or Above 

30 Liters per Cylinder”. (This rule was signed on December 18, 2009 but has not yet been published in the Federal 

Register. The signed version of the rule is available at http://epa.gov/otaq/oceanvessels.htm). 
 

550

violating the standards, will also benefit from any reductions in PM2.5 ensuring long-term 

maintenance of the PM2.5 NAAQS. 

c. Projected Levels with RFS2 Volumes 

 

We are not able to present air quality modeling results which detail changes in PM2.5 

design values for specific local areas due to the error in the locomotive inventory mentioned in 

the introduction to this section. However, we do know that ambient PM2.5 increases in some 

areas of the country and decreases in other areas of the country. Ambient PM2.5 is likely to 

increase as a result of emissions at biofuel production plants and from biofuel transport, both of 

which are more prevalent in the Midwest. PM concentrations are likely to decrease in some 

areas due to reductions in SOA formation and reduced emissions from gasoline refineries. In 

addition, decreases in ambient PM are predicted because our modeling inventory assumed that 

E85 usage reduces PM tailpipe emissions. The decreases in ambient PM from reductions in SOA 

and tailpipe emissions are likely to occur where there is a higher density of vehicles, such as the 

Northeast. See Section VIII.D for a discussion of the changes in national average populationweighted PM2.5 concentrations.

2. Ozone

a. Current Levels 

8-hour ozone concentrations exceeding the level of the ozone NAAQS occur in many 

parts of the country. In 2008, the U.S. EPA amended the ozone NAAQS (73 FR 16436, March 

27, 2008). The final 2008 ozone NAAQS rule set forth revisions to the previous 1997 NAAQS 
 

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for ozone to provide increased protection of public health and welfare. As of January 6, 2010 

there are 51 areas designated as nonattainment for the 1997 8-hour ozone NAAQS, comprising 

266 full or partial counties with a total population of over 122 million people. These numbers do 

not include the people living in areas where there is a future risk of failing to maintain or attain 

the 1997 8-hour ozone NAAQS. The numbers above likely underestimate the number of 

counties that are not meeting the ozone NAAQS because the nonattainment areas associated with 

the more stringent 2008 8-hour ozone NAAQS have not yet been designated.192 Table VI.D-1 

provides an estimate, based on 2005-07 air quality data, of the counties with design values 

greater than the 2008 8-hour ozone NAAQS of 0.075 ppm. 

 

192 EPA recently proposed to reconsider the 2008 NAAQS. Because of the uncertainty the reconsideration proposal 

creates regarding the continued applicability of the 2008 ozone NAAQS, EPA has used its authority to extend by 1 

year the deadline for promulgating designations for those NAAQS. The new deadline is March 2011. EPA intends 

to complete the reconsideration by August 31, 2010. 
 

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Table VI.D-1 

Counties with Design Values Greater Than the 2008 Ozone NAAQS Based on 2005-2007 Air 

Quality Data 

 NUMBER OF 

COUNTIES 

POPULATIONa

1997 Ozone Standard: counties within the 51 

areas currently designated as nonattainment 

(as of 1/6/10) 

266 122,343, 799 

2008 Ozone Standard: additional counties 

that would not meet the 2008 NAAQSb

227 41,285,262 

Total 493 163,629,061 

Notes: 

a

 Population numbers are from 2000 census data. 

b

 Area designations for the 2008 ozone NAAQS have not yet been made. Nonattainment for the 2008 Ozone 

NAAQS would be based on three years of air quality data from later years. Also, the county numbers in this row 

include only the counties with monitors violating the 2008 Ozone NAAQS. The numbers in this table may be an 

underestimate of the number of counties and populations that will eventually be included in areas with multiple 

counties designated nonattainment. 

b. Projected Levels without RFS2 Volumes 

States with 8-hour ozone nonattainment areas are required to take action to bring those 

areas into compliance in the future. Based on the final rule designating and classifying 8-hour 

ozone nonattainment areas for the 1997 standard (69 FR 23951, April 30, 2004), most 8-hour 

ozone nonattainment areas will be required to attain the ozone NAAQS in the 2007 to 2013 time 
 

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frame and then maintain the NAAQS thereafter. EPA has recently proposed to reconsider the 

2008 ozone NAAQS. If EPA promulgates different ozone NAAQS in 2010 as a result of the 

reconsideration, they would fully replace the 2008 ozone NAAQS and there would no longer be 

a requirement to designate areas for the 2008 NAAQS. EPA would designate nonattainment 

areas for a potential new 2010 primary ozone NAAQS based on the reconsideration of the 2008 

ozone NAAQS in 2011. The attainment dates for areas designated nonattainment for a potential 

new 2010 primary ozone NAAQS are likely to be in the 2014 to 2031 timeframe, depending on 

the severity of the problem. 

EPA has already adopted many emission control programs that are expected to reduce 

ambient ozone levels and assist in reducing the number of areas that fail to achieve the ozone 

NAAQS. Even so, our air quality modeling projects that in 2022, with all current controls but 

excluding the impacts of the renewable fuel volumes required by RFS2, up to 7 counties with a 

population of over 22 million may not attain the 2008 ozone standard of 0.075 ppm (75 ppb). 

These numbers do not account for those areas that are close to (e.g., within 10 percent of) the 

2008 ozone standard. These areas, although not violating the standards, will also benefit from 

any reductions in ozone ensuring long-term maintenance of the ozone NAAQS. 

c. Projected Levels with RFS2 Volumes 

Our modeling indicates that the required renewable fuel volumes will cause increases in 

ozone design value concentrations in many areas of the country and decreases in ozone design 

value concentrations in a few areas. Air quality modeling of the expected impacts of the 

renewable fuel volumes required by RFS2 shows that in 2022, most counties with modeled data, 

especially those in the southeast U.S., will see increases in their ozone design values. These 
 

554

adverse impacts are likely due to increased upstream emissions of NOx in many areas that are 

NOx-limited (acting as a precursor to ozone formation). The majority of these design value 

increases are less than 0.5 ppb. The maximum projected increase in an 8-hour ozone design 

value is in Morgan County, Alabama, 1.56 ppb and 1.27 ppb when compared with the RFS1 

mandate and AEO 2007reference cases respectively. As mentioned above there are some areas 

which see decreases in their ozone design values. This is likely due to VOC emission reductions 

at the tailpipe in urban areas that are VOC-limited (reducing VOC’s role as a precursor to ozone 

formation). The maximum decrease projected in an 8-hour ozone design value is in Riverside, 

CA, 0.66 ppb and 0.6 ppb when compared with the RFS1 mandate and AEO 2007 reference 

cases respectively. On a population-weighted basis, the average modeled future-year 8-hour 

ozone design values are projected to increase by 0.28 ppb in 2022 when compared with the RFS1 

mandate reference case and increase by 0.16 ppb when compared with the AEO 2007 reference 

case. On a population-weighted basis the design values for those counties that are projected to 

be above the 2008 ozone standard in 2022 will see decreases of 0.14 ppb when compared with 

the RFS1 mandate reference case and 0.15 ppb when compared with the AEO 2007 reference 

case. 

3. Air Toxics

a. Current Levels 

The majority of Americans continue to be exposed to ambient concentrations of air toxics 

at levels which have the potential to cause adverse health effects.193 The levels of air toxics to 

which people are exposed vary depending on where people live and work and the kinds of 

 

193 U. S. EPA. (2009) 2002 National-Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata2002/ 
 

555

activities in which they engage, as discussed in detail in U.S. EPA’s recent Mobile Source Air 

Toxics Rule.194 According to the National Air Toxic Assessment (NATA) for 2002,195 mobile 

sources were responsible for 47 percent of outdoor toxic emissions, over 50 percent of the cancer 

risk, and over 80 percent of the noncancer hazard. Benzene is the largest contributor to cancer 

risk of all 124 pollutants quantitatively assessed in the 2002 NATA and mobile sources were 

responsible for 59 percent of benzene emissions in 2002. Over the years, EPA has implemented 

a number of mobile source and fuel controls resulting in VOC reductions, which also reduce 

benzene and other air toxic emissions. 

b. Projected Levels 

Our modeling indicates that, while there are some localized impacts, the renewable fuel 

volumes required by RFS2 have relatively little impact on national average ambient 

concentrations of the modeled air toxics. An exception is increased ambient concentrations of 

ethanol. For more information on the air toxics modeling results, see Section 3.4 of the RIA for 

annual average results and Appendix 3A of the RIA for seasonal average results. Our discussion 

of the air quality modeling results focuses primarily on impacts of the renewable fuel volumes 

required by RFS2 in reference to the RFS1 mandate for 2022. Except where specifically 

discussed below, air quality modeling results of increased renewable fuel use with RFS2 as 

compared to the AEO 2007 reference case are presented in Appendix 3A of this RIA. 

i. Acetaldehyde 

 

194 U. S. Environmental Protection Agency (2007). Control of Hazardous Air Pollutants from Mobile Sources; Final 

Rule. 72 FR 8434, February 26, 2007. 

195 U. S. EPA. (2009) 2002 National-Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata2002/ 
 

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Our air quality modeling does not show substantial overall nationwide impacts on 

ambient concentrations of acetaldehyde as a result of the renewable fuel volumes required by this 

rule, although there is considerable uncertainty associated with the results. Annual percent 

changes in ambient concentrations of acetaldehyde are less than 1% for most of the country, and 

annual absolute changes in ambient concentrations of acetaldehyde are generally less than 0.1 

μg/m3. Some urban areas show decreases in ambient acetaldehyde concentrations ranging from 

1 to 10%, and some rural areas associated with new ethanol plants show increases in ambient 

acetaldehyde concentrations ranging from 1 to 10% with RFS2 volumes. This increase is due to 

an increase in emissions of primary acetaldehyde and precursor emissions from ethanol plants. A 

key reason for the decrease in urban areas is reductions in certain acetaldehyde precursors, 

primarily alkenes (olefins). Most ambient acetaldehyde is formed from secondary 

photochemical reactions of numerous precursor compounds, and many photochemical 

mechanisms are responsible for this process. 

The uncertainty associated with these results is described in more detail in Section 3.4 of 

the RIA. For example, some of the modeled decreases would likely become increases using data 

recently collected by EPA’s Office of Research and Development on the composition of 

hydrocarbon emissions from gasoline storage, gasoline distribution, and gas cans. Furthermore, 

as noted in the introduction to Section VI.D, the inventories used for air quality modeling may 

overestimate NOx, because they assumed that use of E10 would lead to increases in NOx 

emissions for later model year vehicles. The emission inventories for the final rule no longer 

make this assumption, based on recent EPA testing results.196 Because increases in NOx may 

 

196 “Summary of recent findings for fuel effects of a 10% ethanol blend on light duty exhaust emissions”, Memo 

from Aron Butler to Docket EPA-HQ-OAR-2005-0161 
 

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result in more acetyl peroxy radical forming PAN rather than acetaldehyde, our air quality 

modeling results may underestimate the ambient concentrations of acetaldehyde. 

Some previous U.S. monitoring studies have suggested an insignificant or small impact 

of increased use of ethanol in fuel on ambient acetaldehyde, as discussed in more detail in 

Section 3.4 of the RIA. These studies suggest that increases in direct emissions of acetaldehyde 

are offset by decreases in the secondary formation of acetaldehyde. Other past studies have 

shown increases in ambient acetaldehyde with increased use of ethanol in fuel, although factors 

such as differences in vehicle fleet, lack of RVP control, and exclusion of upstream impacts may 

limit the ability of these studies to inform expected impacts on ambient air quality Given the 

conflicting results among past studies and the limitations of our analysis, considerable additional 

work is needed to address the impacts of the renewable fuel volumes required by this rule on 

ambient concentrations of acetaldehyde. 

ii. Formaldehyde 

Our air quality modeling results do not show substantial impacts on ambient 

concentrations of formaldehyde from the renewable fuel volumes required by this rule. Most of 

the U.S. experiences a 1% or less change in ambient formaldehyde concentrations. Decreases in 

ambient formaldehyde concentrations range between 1 and 5% in a few urban areas. Increases 

range between 1 and 2.5% in some rural areas associated with new ethanol plants; this result is 

due to increases in emissions of primary formaldehyde and formaldehyde precursors from the 
 

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new ethanol plants. Absolute changes in ambient concentrations of formaldehyde are generally 

less than 0.1 μg/m3. 

iii. Ethanol 

Our modeling projects that the renewable fuel volumes required by this rule will lead to 

significant nationwide increases in ambient ethanol concentrations. Increases ranging between 

10 to 50% are seen across most of the country. The largest increases (more than 100%) occur in 

urban areas with high amounts of on-road emissions and in rural areas associated with new 

ethanol plants. Absolute increases in ambient ethanol concentrations are above 1.0 ppb in some 

urban areas. Analysis of a modeling error that impacted ethanol emissions suggests that this 

error resulted in overestimates of ethanol impacts by more than 10% across much of the country. 

For a detailed discussion of this error, please refer to the emissions modeling TSD, found in the 

docket for this rule (EPA-HQ-OAR-2005-0161). 

iv. Benzene 

Our modeling projects that the renewable fuel volumes required by this rule will lead to 

small nationwide decreases in ambient benzene concentrations. Decreases in ambient benzene 

concentrations range between 1 and 10% across most of the country and can be higher in a few 

urban areas. Absolute changes in ambient concentrations of benzene show reductions up to 0.2 

μg/m3. 
 

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v. 1,3-Butadiene 

The results of our air quality modeling show small increases and decreases in ambient 

concentrations of 1,3-butadiene in parts of the U.S. as a result of increases in renewable fuel 

volumes required by RFS2. Generally, decreases occur in some southern areas of the country 

and increases occur in some northern areas and areas with high altitudes. Percent changes in 1,3-

butadiene concentrations are over 50% in several areas; but the changes in absolute 

concentrations of ambient 1,3-butadiene are generally less than 0.005 μg/m3. Annual increases 

in ambient concentrations of 1,3-butadiene are driven by wintertime changes. These increases 

appear in rural areas with cold winters and low ambient levels but high contributions of 

emissions from snowmobiles, and a major reason for this modeled increase may be deficiencies 

in available emissions test data used to estimate snowmobile 1,3-butadiene emission inventories. 

vi. Acrolein 

Our air quality modeling shows small regional increases and decreases in ambient 

concentrations of acrolein as a result of increases in renewable fuel volumes required by this 

rule. Decreases in acrolein concentrations occur in some eastern and southern parts of the U.S. 

and increases occur in some northern areas and areas associated with new ethanol plants. 

Changes in absolute ambient concentrations of acrolein are between ± 0.001 μg/m3 with the 

exception of the increases associated with new ethanol plants. These increases can be up to and 

above 0.005 μg/m3 with percent changes above 50% and are due to increases in emissions of 

acrolein from the new plants. Ambient acrolein increases in northern regions are driven by 
 

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wintertime changes, and occur in the same areas of the country that have wintertime increases in 

ambient 1,3-butadiene. 1,3-butadiene is a precursor to acrolein, and these increases are likely 

associated with the same emission inventory issues in areas of high snowmobile usage seen for 

1,3-butadiene, as described above.

vii. Population Metrics 

To assess the impact of projected changes in ambient air toxics as a result of increases in 

renewable fuel volumes required by this rule, we developed population metrics that show the 

population experiencing increases and decreases in annual ambient concentrations of the 

modeled air toxics. Table VI.D-2 below illustrates the percentage of the population impacted by 

changes of various magnitudes in annual ambient concentrations with the renewable fuel 

volumes required by RFS2, as compared to the RFS1 mandate reference case. 

Table VI.D-2 

Percent of Total Population Impacted by Changes in Annual Ambient Concentrations of Toxic 

Pollutants: RFS2 Compare to RFS1 Mandate 

Percent Change in 

Annual Ambient 

Concentration Acetaldehyde Acrolein Benzene 1,3-Butadiene Ethanol Formaldehyde 

≤-100 

>-100 to ≤-50 

>-50 to ≤-10 0.76% 1.18% 1.38% 

>-10 to ≤-5 8.17% 0.18% 12.92% 28.11% 

>-5 to ≤-2.5 13.29% 13.66% 48.76% 31.98% 4.11% 

>-2.5 to ≤-1 25.26% 40.13% 23.60% 12.87% 19.30% 
 

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> -1 to <1 52.24% 36.03% 13.55% 19.37% 76.08% 

≥1 to <2.5 0.24% 3.44% 1.53% 0.48% 

≥2.5 to <5 0.04% 2.93% 1.13% 0.22% 0.01% 

≥5 to <10 0.02% 2.00% 1.13% 1.23% 

≥10 to <50 1.51% 2.15% 63.29% 

≥50 to <100 0.08% 0.28% 34.49% 

≥100 0.05% 0.06% 0.77% 

 Table VI.D-3 shows changes in the population-weighted average ambient concentrations 

of air toxics that are projected to occur in 2022 with increased renewable fuel use as required by 

this rule. 

Table VI.D-3 

Population-Weighted Average Ambient Concentrations of Air Toxics in 2022 with RFS2 

Renewable Fuel Requirements 

Population-weighted Concentration 

(Annual Average in μg/m3) 

RFS2 v. RFS1 Mandate Reference Case 

Population-weighted Concentration 

(Annual Average in μg/m3) 

RFS2 v. AEO 2007 Reference Case 

RFS2 

RFS1 

Mandate Diff. RFS2-RFS1 RFS2 AEO 2007 Diff. RFS2-AEO 

Acetaldehyde 1.590 1.618 -0.028 1.590 1.613 -0.023 

Acrolein 0.017 0.018 -0.001 0.017 0.017 -0.0001 

Benzene 0.520 0.535 -0.015 0.520 0.527 -0.007 

1,3-Butadiene 0.022 0.023 -0.001 0.022 0.230 -0.208 
 

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Ethanol 1.521 1.039 0.482 1.521 1.112 0.409 

Formaldehyde 1.549 1.558 -0.009 1.549 0.004 -0.006 

4. Nitrogen and Sulfur Deposition

a. Current Levels 

Over the past two decades, the EPA has undertaken numerous efforts to reduce nitrogen 

and sulfur deposition across the U.S. Analyses of long-term monitoring data for the U.S. show 

that deposition of both nitrogen and sulfur compounds has decreased over the last 17 years 

although many areas continue to be negatively impacted by deposition. Deposition of inorganic 

nitrogen and sulfur species routinely measured in the U.S. between 2004 and 2006 were as high 

as 9.6 kilograms of nitrogen per hectare per year (kg N/ha/yr) and 21.3 kilograms of sulfur per 

hectare per year (kg S/ha/yr). The data show that reductions were more substantial for sulfur 

compounds than for nitrogen compounds. These numbers are generated by the U.S. national 

monitoring network and they likely underestimate nitrogen deposition because neither ammonia 

nor organic nitrogen is measured. In the eastern U.S., where data are most abundant, total sulfur 

deposition decreased by about 36% between 1990 and 2005, while total nitrogen deposition 

decreased by 19% over the same time frame.197 

b. Projected Levels 

Our air quality modeling does not show substantial overall nationwide impacts on the 

annual total sulfur and nitrogen deposition occurring across the U.S. as a result of increased 

renewable fuel volumes required by this rule. For sulfur deposition, when compared to the RFS1 

 

197 U.S. EPA. U.S. EPA's 2008 Report on the Environment (Final Report). U.S. Environmental Protection Agency, 

Washington, D.C., EPA/600/R-07/045F (NTIS PB2008-112484).
 

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mandate reference case, the RFS2 renewable fuel volumes will result in annual percent increases 

in the Midwest ranging from 1% to more than 4%. Some rural areas in the west, likely 

associated with new ethanol plants, will also have increases in sulfur deposition ranging from 1% 

to more than 4% as a result of the RFS2 renewable fuel volumes. When compared to the AEO 

2007 reference case, the changes are more limited. The Midwest will still have sulfur deposition 

increases ranging from 1% to more than 4%, but the size of the area with these changes will be 

smaller. The Pacific Northwest has minimal areas with increases in sulfur deposition when 

compared to the AEO 2007 reference case. When compared to both the RFS1 mandate and AEO 

2007 reference cases, areas along the Gulf Coast in Louisiana and Texas will experience 

decreases in sulfur deposition of 2% to more than 4%. The remainder of the country will see 

only minimal changes in sulfur deposition, ranging from decreases of less than 1% to increases 

of less than 1%. For a map of 2022 sulfur deposition impacts and additional information on 

these impacts, see Section 3.4.2.2 of the RIA. 

Overall, nitrogen deposition impacts in 2022 resulting from the renewable fuel volumes 

required by RFS2 are more widespread than the sulfur deposition impacts. When compared to 

the RFS1 mandate 2007 reference case, nearly the entire eastern half of the United States will see 

nitrogen deposition increases ranging from 0.5% to more than 2%. The largest increases will 

occur in the states of Illinois, Michigan, Indiana, Wisconsin, and Missouri, with large portions of 

each of these states seeing nitrogen deposition increases of more than 2%. The Pacific 

Northwest will also experience increases in nitrogen of 0.5% to more than 2%. When compared 

to the AEO 2007 reference case, the changes in nitrogen deposition are more limited. The 

eastern half of the United States will still see nitrogen deposition increases ranging from 0.5% to 
 

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more than 2%; however, the size of the area with these changes will be smaller. Increases of 

more than 2% will primarily occur only in Illinois, Indiana, Michigan, and Missouri. Fewer 

areas in the Pacific Northwest will have increases in nitrogen deposition when compared to the 

AEO 2007 reference case. In both the RFS1 mandate and AEO 2007 reference cases, the 

Mountain West and Southwest will see only minimal changes in nitrogen deposition, ranging 

from decreases of less than 0.5% to increases of less than 0.5%. A few areas in Minnesota and 

western Kansas would experience reductions of nitrogen up to 2%. See Section 3.4.2.2 of the 

RIA for a map and additional information on nitrogen deposition impacts. 

 E. Health Effects of Criteria and Air Toxics Pollutants 

 1. Particulate Matter 

a. Background 

Particulate matter is a generic term for a broad class of chemically and physically diverse 

substances. It can be principally characterized as discrete particles that exist in the condensed 

(liquid or solid) phase spanning several orders of magnitude in size. Since 1987, EPA has 

delineated that subset of inhalable particles small enough to penetrate to the thoracic region 

(including the tracheobronchial and alveolar regions) of the respiratory tract (referred to as 

thoracic particles). Current NAAQS use PM2.5 as the indicator for fine particles (with PM2.5

referring to particles with a nominal mean aerodynamic diameter less than or equal to 2.5 μm), 

and use PM10 as the indicator for purposes of regulating the coarse fraction of PM10 (referred to 
 

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as thoracic coarse particles or coarse-fraction particles; generally including particles with a 

nominal mean aerodynamic diameter greater than 2.5 μm and less than or equal to 10 μm, or 

PM10-2.5). Ultrafine particles are a subset of fine particles, generally less than 100 nanometers 

(0.1 μm) in aerodynamic diameter. 

Fine particles are produced primarily by combustion processes and by transformations of 

gaseous emissions (e.g., SOX, NOX and VOC) in the atmosphere. The chemical and physical 

properties of PM2.5 may vary greatly with time, region, meteorology, and source category. Thus, 

PM2.5 may include a complex mixture of different pollutants including sulfates, nitrates, organic 

compounds, elemental carbon and metal compounds. These particles can remain in the 

atmosphere for days to weeks and travel hundreds to thousands of kilometers. 

b. Health Effects of PM 

Scientific studies show ambient PM is associated with a series of adverse health effects. 

These health effects are discussed in detail in EPA’s 2004 Particulate Matter Air Quality Criteria 

Document (PM AQCD) and the 2005 PM Staff Paper.198,199,200 Further discussion of health 

effects associated with PM can also be found in the RIA for this rule. 

 

198 U.S. EPA (2004). Air Quality Criteria for Particulate Matter. Volume I EPA600/P-99/002aF and Volume II 

EPA600/P-99/002bF. Retrieved on March 19, 2009 from Docket EPA-HQ-OAR-2003-0190 at 

http://www.regulations.gov/. 

199 U.S. EPA. (2005). Review of the National Ambient Air Quality Standard for Particulate Matter: Policy 

Assessment of Scientific and Technical Information, OAQPS Staff Paper. EPA-452/R-05-005a. Retrieved March 

19, 2009 from http://www.epa.gov/ttn/naaqs/standards/pm/data/pmstaffpaper_20051221.pdf. 

200 The PM NAAQS is currently under review and the EPA is considering all available science on PM health effects, 

including information which has been published since 2004, in the development of the upcoming PM Integrated 

Science Assessment Document (ISA). A second draft of the PM ISA was completed in July 2009 and was 

submitted for review by the Clean Air Scientific Advisory Committee (CASAC) of EPA’s Science Advisory Board. 
 

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Health effects associated with short-term exposures (hours to days) to ambient PM 

include premature mortality, aggravation of cardiovascular and lung disease (as indicated by 

increased hospital admissions and emergency department visits), increased respiratory symptoms 

including cough and difficulty breathing, decrements in lung function, altered heart rate rhythm, 

and other more subtle changes in blood markers related to cardiovascular health.201 Long-term 

exposure to PM2.5 and sulfates has also been associated with mortality from cardiopulmonary 

disease and lung cancer, and effects on the respiratory system such as reduced lung function 

growth or development of respiratory disease. A new analysis shows an association between 

long-term PM2.5 exposure and a subclinical measure of atherosclerosis.202,203 

Studies examining populations exposed over the long term (one or more years) to 

different levels of air pollution, including the Harvard Six Cities Study and the American Cancer 

Society Study, show associations between long-term exposure to ambient PM2.5 and both all 

 

Comments from the general public have also been requested. For more information, see 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=210586. 

201 U.S. EPA. (2006). National Ambient Air Quality Standards for Particulate Matte. 71 FR 61144, October 17, 

2006. 

202 Künzli, N., Jerrett, M., Mack, W.J., et al. (2004). Ambient air pollution and atherosclerosis in Los Angeles. 

Environ Health Perspect.,113, 201-206 203 This study is included in the 2006 Provisional Assessment of Recent Studies on Health Effects of Particulate 

Matter Exposure. The provisional assessment did not and could not (given a very short timeframe) undergo the 

extensive critical review by CASAC and the public, as did the PM AQCD. The provisional assessment found that 

the “new” studies expand the scientific information and provide important insights on the relationship between PM 

exposure and health effects of PM. The provisional assessment also found that “new” studies generally strengthen 

the evidence that acute and chronic exposure to fine particles and acute exposure to thoracic coarse particles are 

associated with health effects. Further, the provisional science assessment found that the results reported in the 

studies did not dramatically diverge from previous findings, and taken in context with the findings of the AQCD, the 

new information and findings did not materially change any of the broad scientific conclusions regarding the health 

effects of PM exposure made in the AQCD. However, it is important to note that this assessment was limited to 

screening, surveying, and preparing a provisional assessment of these studies. For reasons outlined in Section I.C of 

the preamble for the final PM NAAQS rulemaking in 2006 (see 71 FR 61148-49, October 17, 2006), EPA based its 

NAAQS decision on the science presented in the 2004 AQCD. 
 

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cause and cardiopulmonary premature mortality.204,205,206 In addition, an extension of the 

American Cancer Society Study shows an association between PM2.5 and sulfate concentrations 

and lung cancer mortality.207

 2. Ozone 

a. Background 

Ground-level ozone pollution is typically formed by the reaction of VOC and NOX in the 

lower atmosphere in the presence of heat and sunlight. These pollutants, often referred to as 

ozone precursors, are emitted by many types of pollution sources, such as highway and nonroad 

motor vehicles and engines, power plants, chemical plants, refineries, makers of consumer and 

commercial products, industrial facilities, and smaller area sources. 

The science of ozone formation, transport, and accumulation is complex.208 Ground-level 

ozone is produced and destroyed in a cyclical set of chemical reactions, many of which are 

 

204 Dockery, D.W., Pope, C.A. III, Xu, X, et al. (1993). An association between air pollution and mortality in six 

U.S. cities. N Engl J Med, 329, 1753-1759. Retrieved on March 19, 2009 from 

http://content.nejm.org/cgi/content/full/329/24/1753. 

205 Pope, C.A., III, Thun, M.J., Namboodiri, M.M., Dockery, D.W., Evans, J.S., Speizer, F.E., and Heath, C.W., Jr. 

(1995). Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults. Am. J. Respir. Crit. 

Care Med, 151, 669-674. 206 Krewski, D., Burnett, R.T., Goldberg, M.S., et al. (2000). Reanalysis of the Harvard Six Cities study and the 

American Cancer Society study of particulate air pollution and mortality. A special report of the Institute's Particle 

Epidemiology Reanalysis Project. Cambridge, MA: Health Effects Institute. Retrieved on March 19, 2009 from 

http://es.epa.gov/ncer/science/pm/hei/Rean-ExecSumm.pdf. 

207 Pope, C. A., III, Burnett, R.T., Thun, M. J., Calle, E.E., Krewski, D., Ito, K., Thurston, G.D., (2002). Lung 

cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution. J. Am. Med. Assoc., 287, 

1132-1141.

208 U.S. EPA. (2006). Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). EPA/600/R05/004aF-cF. Washington, DC: U.S. EPA. Retrieved on March 19, 2009 from Docket EPA-HQ-OAR-2003-0190 at 

http://www.regulations.gov/. 
 

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sensitive to temperature and sunlight. When ambient temperatures and sunlight levels remain 

high for several days and the air is relatively stagnant, ozone and its precursors can build up and 

result in more ozone than typically occurs on a single high-temperature day. Ozone can be 

transported hundreds of miles downwind from precursor emissions, resulting in elevated ozone 

levels even in areas with low local VOC or NOX emissions. 

b. Health Effects of Ozone 

The health and welfare effects of ozone are well documented and are assessed in EPA’s 

2006 Air Quality Criteria Document (ozone AQCD) and 2007 Staff Paper.209, 210 Ozone can 

irritate the respiratory system, causing coughing, throat irritation, and/or uncomfortable sensation 

in the chest. Ozone can reduce lung function and make it more difficult to breathe deeply; 

breathing may also become more rapid and shallow than normal, thereby limiting a person’s 

activity. Ozone can also aggravate asthma, leading to more asthma attacks that require medical 

attention and/or the use of additional medication. In addition, there is suggestive evidence of a 

contribution of ozone to cardiovascular-related morbidity and highly suggestive evidence that 

short-term ozone exposure directly or indirectly contributes to non-accidental and 

cardiopulmonary-related mortality, but additional research is needed to clarify the underlying 

mechanisms causing these effects. In a recent report on the estimation of ozone-related 

premature mortality published by the National Research Council (NRC), a panel of experts and 

 

209 U.S. EPA. (2006). Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). EPA/600/R05/004aF-cF. Washington, DC: U.S. EPA. Retrieved on March 19, 2009 from Docket EPA-HQ-OAR-2003-0190 at 

http://www.regulations.gov/. 

210 U.S. EPA. (2007). Review of the National Ambient Air Quality Standards for Ozone: Policy Assessment of 

Scientific and Technical Information, OAQPS Staff Paper. EPA-452/R-07-003. Washington, DC, U.S. EPA. 

Retrieved on March 19, 2009 from Docket EPA-HQ-OAR-2003-0190 at http://www.regulations.gov/. 
 

569

reviewers concluded that short-term exposure to ambient ozone is likely to contribute to 

premature deaths and that ozone-related mortality should be included in estimates of the health 

benefits of reducing ozone exposure.211 Animal toxicological evidence indicates that with 

repeated exposure, ozone can inflame and damage the lining of the lungs, which may lead to 

permanent changes in lung tissue and irreversible reductions in lung function. People who are 

more susceptible to effects associated with exposure to ozone can include children, the elderly, 

and individuals with respiratory disease such as asthma. Those with greater exposures to ozone, 

for instance due to time spent outdoors (e.g., children and outdoor workers), are of particular 

concern. 

The 2006 ozone AQCD also examined relevant new scientific information that has 

emerged in the past decade, including the impact of ozone exposure on such health effects as 

changes in lung structure and biochemistry, inflammation of the lungs, exacerbation and 

causation of asthma, respiratory illness-related school absence, hospital admissions and 

premature mortality. Animal toxicological studies have suggested potential interactions between 

ozone and PM with increased responses observed to mixtures of the two pollutants compared to 

either ozone or PM alone. The respiratory morbidity observed in animal studies along with the 

evidence from epidemiologic studies supports a causal relationship between acute ambient ozone 

exposures and increased respiratory-related emergency room visits and hospitalizations in the 

warm season. In addition, there is suggestive evidence of a contribution of ozone to 

cardiovascular-related morbidity and non-accidental and cardiopulmonary mortality. 

 

211 National Research Council (NRC), 2008. Estimating Mortality Risk Reduction and Economic Benefits from 

Controlling Ozone Air Pollution. The National Academies Press: Washington, D.C. 
 

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3. NOX and SOX 

a. Background 

Nitrogen dioxide (NO2) is a member of the NOX family of gases. Most NO2 is formed in 

the air through the oxidation of nitric oxide (NO) emitted when fuel is burned at a high 

temperature. SO2, a member of the sulfur oxide (SOX) family of gases, is formed from burning 

fuels containing sulfur (e.g., coal or oil derived), extracting gasoline from oil, or extracting 

metals from ore. 

SO2 andNO2 can dissolve in water vapor and further oxidize to form sulfuric and nitric 

acid which react with ammonia to form sulfates and nitrates, both of which are important 

components of ambient PM. The health effects of ambient PM are discussed in Section VI.D.1 

of this preamble. NOX along with non-methane hydrocarbon (NMHC) are the two major 

precursors of ozone. The health effects of ozone are covered in Section VI.D.2. 

 b. Health Effects of NOX

Information on the health effects of NO2 can be found in the U.S. Environmental 

Protection Agency Integrated Science Assessment (ISA) for Nitrogen Oxides.212 The U.S. EPA 

has concluded that the findings of epidemiologic, controlled human exposure, and animal 

toxicological studies provide evidence that is sufficient to infer a likely causal relationship 

 

212 U.S. EPA (2008). Integrated Science Assessment for Oxides of Nitrogen – Health Criteria (Final Report).

EPA/600/R-08/071. Washington, DC,: U.S.EPA. Retrieved on March 19, 2009 from 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=194645. 
 

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between respiratory effects and short-term NO2 exposure. The ISA concludes that the strongest 

evidence for such a relationship comes from epidemiologic studies of respiratory effects 

including symptoms, emergency department visits, and hospital admissions. The ISA also draws 

two broad conclusions regarding airway responsiveness following NO2 exposure. First, the ISA 

concludes that NO2 exposure may enhance the sensitivity to allergen-induced decrements in lung 

function and increase the allergen-induced airway inflammatory response following 30-minute 

exposures of asthmatics to NO2 concentrations as low as 0.26 ppm. In addition, small but 

significant increases in non-specific airway hyperresponsiveness were reported following 1-hour 

exposures of asthmatics to 0.1 ppm NO2. Second, exposure to NO2 has been found to enhance 

the inherent responsiveness of the airway to subsequent nonspecific challenges in controlled 

human exposure studies of asthmatic subjects. Enhanced airway responsiveness could have 

important clinical implications for asthmatics since transient increases in airway responsiveness 

following NO2 exposure have the potential to increase symptoms and worsen asthma control. 

Together, the epidemiologic and experimental data sets form a plausible, consistent, and 

coherent description of a relationship between NO2 exposures and an array of adverse health 

effects that range from the onset of respiratory symptoms to hospital admission. 

Although the weight of evidence supporting a causal relationship is somewhat less certain 

than that associated with respiratory morbidity, NO2 has also been linked to other health 

endpoints. These include all-cause (nonaccidental) mortality, hospital admissions or emergency 

department visits for cardiovascular disease, and decrements in lung function growth associated 

with chronic exposure. 
 

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c. Health Effects of SOX

Information on the health effects of SO2 can be found in the U.S. Environmental 

Protection Agency Integrated Science Assessment for Sulfur Oxides.213 SO2 has long been 

known to cause adverse respiratory health effects, particularly among individuals with asthma. 

Other potentially sensitive groups include children and the elderly. During periods of elevated 

ventilation, asthmatics may experience symptomatic bronchoconstriction within minutes of 

exposure. Following an extensive evaluation of health evidence from epidemiologic and 

laboratory studies, the EPA has concluded that there is a causal relationship between respiratory 

health effects and short-term exposure to SO2. Separately, based on an evaluation of the 

epidemiologic evidence of associations between short-term exposure to SO2 and mortality, the 

EPA has concluded that the overall evidence is suggestive of a causal relationship between shortterm exposure to SO2 and mortality. 

 4. Carbon Monoxide 

Carbon monoxide (CO) forms as a result of incomplete fuel combustion. CO enters the 

bloodstream through the lungs, forming carboxyhemoglobin and reducing the delivery of oxygen 

to the body’s organs and tissues. The health threat from exposures to lower levels of CO is most 

serious for those who suffer from cardiovascular disease, particularly those with angina or 

peripheral vascular disease. Epidemiological studies have suggested that exposure to ambient 

levels of CO is associated with increased risk of hospital admissions for cardiovascular causes, 

 

213 U.S. EPA. (2008). Integrated Science Assessment (ISA) for Sulfur Oxides – Health Criteria (Final Report). 

EPA/600/R-08/047F. Washington, DC: U.S. Environmental Protection Agency. Retrieved on March 18, 2009 from 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=198843 
 

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fetal effects, and possibly premature cardiovascular mortality. Healthy individuals also are 

affected, but only when they are exposed to higher CO levels. Exposure of healthy individuals to 

elevated CO levels is associated with impairment of visual perception, work capacity, manual 

dexterity, learning ability and performance of complex tasks. Carbon monoxide also contributes 

to ozone nonattainment since carbon monoxide reacts photochemically in the atmosphere to form 

ozone.214 Additional information on CO related health effects can be found in the Carbon 

Monoxide Air Quality Criteria Document (CO AQCD).215,216 

 

5. Air Toxics 

The population experiences an elevated risk of cancer and noncancer health effects from 

exposure to the class of pollutants known collectively as “air toxics.”217 Fuel combustion 

contributes to ambient levels of air toxics that can include, but are not limited to, acetaldehyde, 

acrolein, benzene, 1,3-butadiene, formaldehyde, ethanol, naphthalene and peroxyacetyl nitrate 

(PAN). Acrolein, benzene, 1,3-butadiene, formaldehyde and naphthalene have significant 

contributions from mobile sources and were identified as national or regional risk drivers in the 

2002 National-scale Air Toxics Assessment (NATA).218 PAN, which is formed from precursor 

compounds by atmospheric processes, is not assessed in NATA. Emissions and ambient 

 

214 U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide, EPA/600/P-99/001F. This document is available in 

Docket EPA-HQ-OAR-2004-0008. 

215 U.S. EPA (2000). Air Quality Criteria for Carbon Monoxide, EPA/600/P-99/001F. This document is available in 

Docket EPA-HQ-OAR-2004-0008. 

216 The CO NAAQS is currently under review and the EPA is considering all available science on CO health effects, 

including information which has been published since 2000, in the development of the upcoming CO Integrated 

Science Assessment Document (ISA). A second draft of the CO ISA was completed in September 2009 and was 

submitted for review by the Clean Air Scientific Advisory Committee (CASAC) of EPA’s Science Advisory Board. 

For more information, see http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=213229. 

217 U. S. EPA. 2002 National-Scale Air Toxics Assessment. http://www.epa.gov/ttn/atw/nata2002/risksum.html 218 U.S. EPA .2009. National-Scale Air Toxics Assessment for 2002. http://www.epa.gov/ttn/atw/nata2002. 
 

574

concentrations of compounds are discussed in Chapter 3 of the RIA and Section VI.D.3 of this 

preamble. 

a. Acetaldehyde 

Acetaldehyde is classified in EPA’s IRIS database as a probable human carcinogen, 

based on nasal tumors in rats, and is considered toxic by the inhalation, oral, and intravenous 

routes.219 Acetaldehyde is reasonably anticipated to be a human carcinogen by the U.S. DHHS 

in the 11th Report on Carcinogens and is classified as possibly carcinogenic to humans (Group 

2B) by the IARC.220,221 EPA is currently conducting a reassessment of cancer risk from 

inhalation exposure to acetaldehyde. 

The primary noncancer effects of exposure to acetaldehyde vapors include irritation of 

the eyes, skin, and respiratory tract.222 In short-term (4 week) rat studies, degeneration of 

olfactory epithelium was observed at various concentration levels of acetaldehyde exposure.223, 

224 Data from these studies were used by EPA to develop an inhalation reference concentration. 

Some asthmatics have been shown to be a sensitive subpopulation to decrements in functional 

 

219 U.S. EPA. 1991. Integrated Risk Information System File of Acetaldehyde. Research and Development, National 

Center for Environmental Assessment, Washington, DC. This material is available electronically at 

http://www.epa.gov/iris/subst/0290.htm.

220 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens 

available at: ntp.niehs.nih.gov/index.cfm?objectid=32BA9724-F1F6-975E-7FCE50709CB4C932. 

221 International Agency for Research on Cancer (IARC). 1999. Re-evaluation of some organic chemicals, 

hydrazine, and hydrogen peroxide. IARC Monographs on the Evaluation of Carcinogenic Risk of Chemical to 

Humans, Vol 71. Lyon, France. 

222 U.S. EPA. 1991. Integrated Risk Information System File of Acetaldehyde. This material is available 

electronically at http://www.epa.gov/iris/subst/0290.htm. 223 Appleman, L. M., R. A. Woutersen, V. J. Feron, R. N. Hooftman, and W. R. F. Notten. 1986. Effects of the 

variable versus fixed exposure levels on the toxicity of acetaldehyde in rats. J. Appl. Toxicol. 6: 331-336. 224 Appleman, L.M., R.A. Woutersen, and V.J. Feron. 1982. Inhalation toxicity of acetaldehyde in rats. I. Acute and 

subacute studies. Toxicology. 23: 293-297. 
 

575

expiratory volume (FEV1 test) and bronchoconstriction upon acetaldehyde inhalation.225 The 

agency is currently conducting a reassessment of the health hazards from inhalation exposure to 

acetaldehyde. 

 

b. Acrolein 

 Acrolein is extremely acrid and irritating to humans when inhaled, with acute exposure 

resulting in upper respiratory tract irritation, mucus hypersecretion and congestion. The intense 

irritancy of this carbonyl has been demonstrated during controlled tests in human subjects, who 

suffer intolerable eye and nasal mucosal sensory reactions within minutes of exposure.226 These 

data and additional studies regarding acute effects of human exposure to acrolein are 

summarized in EPA’s 2003 IRIS Human Health Assessment for acrolein.227 Evidence available 

from studies in humans indicate that levels as low as 0.09 ppm (0.21 mg/m3) for five minutes 

may elicit subjective complaints of eye irritation with increasing concentrations leading to more 

extensive eye, nose and respiratory symptoms.228 Lesions to the lungs and upper respiratory 

tract of rats, rabbits, and hamsters have been observed after subchronic exposure to acrolein.229 

 

225 Myou, S.; Fujimura, M.; Nishi K.; Ohka, T.; and Matsuda, T. 1993. Aerosolized acetaldehyde induces 

histamine-mediated bronchoconstriction in asthmatics. Am. Rev. Respir.Dis.148(4 Pt 1): 940-3. 

226 Sim VM, Pattle RE. Effect of possible smog irritants on human subjects JAMA165: 1980-

2010, 1957. 

227 U.S. EPA (U.S. Environmental Protection Agency). (2003) Toxicological review of acrolein 

in support of summary information on Integrated Risk Information System (IRIS) National 

Center for Environmental Assessment, Washington, DC. EPA/635/R-03/003. Available online 

at: http://www.epa.gov/ncea/iris. 228 Weber-Tschopp, A; Fischer, T; Gierer, R; et al. (1977) Experimentelle reizwirkungen von 

Acrolein auf den Menschen. Int Arch Occup Environ Hlth 40(2):117-130. In German 

229 Integrated Risk Information System File of Acrolein. Office of Research and Development, 

National Center for Environmental Assessment, Washington, DC. This material is available at 

http://www.epa.gov/iris/subst/0364.htm 
 

576

Acute exposure effects in animal studies report bronchial hyper-responsiveness.230 In a recent 

study, the acute respiratory irritant effects of exposure to 1.1 ppm acrolein were more 

pronounced in mice with allergic airway disease by comparison to non-diseased mice which also 

showed decreases in respiratory rate.231 Based on animal data, individuals with compromised 

respiratory function (e.g., emphysema, asthma) are expected to be at increased risk of developing 

adverse responses to strong respiratory irritants such as acrolein. 

EPA determined in 2003 that the human carcinogenic potential of acrolein could not be 

determined because the available data were inadequate. No information was available on the 

carcinogenic effects of acrolein in humans and the animal data provided inadequate evidence of 

carcinogenicity.232 The IARC determined in 1995 that acrolein was not classifiable as to its 

carcinogenicity in humans.233

c. Benzene 

The EPA’s IRIS database lists benzene as a known human carcinogen (causing leukemia) 

by all routes of exposure, and concludes that exposure is associated with additional health 

 

230 U.S. EPA (U.S. Environmental Protection Agency). (2003) Toxicological review of acrolein in 

support of summary information on Integrated Risk Information System (IRIS) National Center for 

Environmental Assessment, Washington, DC. EPA/635/R-03/003. Available online at: 

http://www.epa.gov/ncea/iris. 231 Morris JB, Symanowicz PT, Olsen JE, et al. 2003. Immediate sensory nerve-mediated 

respiratory responses to irritants in healthy and allergic airway-diseased mice. J Appl Physiol 

94(4):1563-1571. 

232 U.S. EPA. 2003. Integrated Risk Information System File of Acrolein. Research and Development, National Center 

for Environmental Assessment, Washington, DC. This material is available at 

http://www.epa.gov/iris/subst/0364.htm 

233 International Agency for Research on Cancer (IARC). 1995. Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 63, Dry cleaning, some chlorinated solvents and other industrial chemicals , World 

Health Organization, Lyon, France. 
 

577

effects, including genetic changes in both humans and animals and increased proliferation of 

bone marrow cells in mice.234,235,236 EPA states in its IRIS database that data indicate a causal 

relationship between benzene exposure and acute lymphocytic leukemia and suggest a 

relationship between benzene exposure and chronic non-lymphocytic leukemia and chronic 

lymphocytic leukemia. The International Agency for Research on Carcinogens (IARC) has 

determined that benzene is a human carcinogen and the U.S. Department of Health and Human 

Services (DHHS) has characterized benzene as a known human carcinogen.237,238 

A number of adverse noncancer health effects including blood disorders, such as 

preleukemia and aplastic anemia, have also been associated with long-term exposure to 

benzene.239,240 The most sensitive noncancer effect observed in humans, based on current data, 

is the depression of the absolute lymphocyte count in blood.241, 242 In addition, recent work, 

including studies sponsored by the Health Effects Institute (HEI), provides evidence that 

 

234 U.S. EPA. 2000. Integrated Risk Information System File for Benzene. This material is available electronically 

at http://www.epa.gov/iris/subst/0276.htm.

235 International Agency for Research on Cancer (IARC). 1982. Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 29, Some industrial chemicals and dyestuffs, World Health Organization, Lyon, 

France, p. 345-389. 

236 Irons, R.D.; Stillman, W.S.; Colagiovanni, D.B.; Henry, V.A. 1992. Synergistic action of the benzene metabolite 

hydroquinone on myelopoietic stimulating activity of granulocyte/macrophage colony-stimulating factor in vitro, 

Proc. Natl. Acad. Sci. 89:3691-3695. 

237 International Agency for Research on Cancer (IARC). 1987. Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 29, Supplement 7, Some industrial chemicals and dyestuffs, World Health 

Organization, Lyon, France. 

238 U.S. Department of Health and Human Services National Toxicology Program 11th Report on Carcinogens 

available at: http://ntp.niehs.nih.gov/go/16183. 

239 Aksoy, M. (1989). Hematotoxicity and carcinogenicity of benzene. Environ. Health Perspect. 82: 193-197. 240 Goldstein, B.D. (1988). Benzene toxicity. Occupational medicine. State of the Art Reviews. 3: 541-554. 241 Rothman, N., G.L. Li, M. Dosemeci, W.E. Bechtold, G.E. Marti, Y.Z. Wang, M. Linet, L.Q. Xi, W. Lu, M.T. 

Smith, N. Titenko-Holland, L.P. Zhang, W. Blot, S.N. Yin, and R.B. Hayes (1996) Hematotoxicity among Chinese 

workers heavily exposed to benzene. Am. J. Ind. Med. 29: 236-246. 

242 U.S. EPA (2002) Toxicological Review of Benzene (Noncancer Effects). Environmental Protection Agency, 

Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental 

Assessment, Washington DC. This material is available electronically at http://www.epa.gov/iris/subst/0276.htm. 
 

578

biochemical responses are occurring at lower levels of benzene exposure than previously 

known.243,244,245,246 EPA’s IRIS program has not yet evaluated these new data.

 

 d. 1,3-Butadiene 

EPA has characterized 1,3-butadiene as carcinogenic to humans by inhalation.247,248 The 

IARC has determined that 1,3-butadiene is a human carcinogen and the U.S. DHHS has 

characterized 1,3-butadiene as a known human carcinogen.249,250 There are numerous studies 

consistently demonstrating that 1,3-butadiene is metabolized into genotoxic metabolites by 

experimental animals and humans. The specific mechanisms of 1,3-butadiene-induced 

carcinogenesis are unknown; however, the scientific evidence strongly suggests that the 

carcinogenic effects are mediated by genotoxic metabolites. Animal data suggest that females 

may be more sensitive than males for cancer effects associated with 1,3-butadiene exposure; 

there are insufficient data in humans from which to draw conclusions about sensitive 

 

243 Qu, O.; Shore, R.; Li, G.; Jin, X.; Chen, C.L.; Cohen, B.; Melikian, A.; Eastmond, D.; Rappaport, S.; Li, H.; 

Rupa, D.; Suramaya, R.; Songnian, W.; Huifant, Y.; Meng, M.; Winnik, M.; Kwok, E.; Li, Y.; Mu, R.; Xu, B.; 

Zhang, X.; Li, K. (2003) HEI Report 115, Validation & Evaluation of Biomarkers in Workers Exposed to Benzene 

in China. 

244 Qu, Q., R. Shore, G. Li, X. Jin, L.C. Chen, B. Cohen, et al. (2002) Hematological changes among Chinese 

workers with a broad range of benzene exposures. Am. J. Industr. Med. 42: 275-285. 

245 Lan, Qing, Zhang, L., Li, G., Vermeulen, R., et al. (2004) Hematotoxically in Workers Exposed to Low Levels of 

Benzene. Science 306: 1774-1776. 

246 Turtletaub, K.W. and Mani, C. (2003) Benzene metabolism in rodents at doses relevant to human exposure from 

Urban Air. Research Reports Health Effect Inst. Report No.113. 

247 U.S. EPA (2002) Health Assessment of 1,3-Butadiene. Office of Research and Development, National Center for 

Environmental Assessment, Washington Office, Washington, DC. Report No. EPA600-P-98-001F. This document 

is available electronically at http://www.epa.gov/iris/supdocs/buta-sup.pdf. 

248 U.S. EPA (2002) Full IRIS Summary for 1,3-butadiene (CASRN 106-99-0). Environmental Protection Agency, 

Integrated Risk Information System (IRIS), Research and Development, National Center for Environmental 

Assessment, Washington, DC http://www.epa.gov/iris/subst/0139.htm. 249 International Agency for Research on Cancer (IARC) (1999) Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 71, Re-evaluation of some organic chemicals, hydrazine and hydrogen peroxide 

and Volume 97 (in preparation), World Health Organization, Lyon, France. 

250 U.S. Department of Health and Human Services (2005) National Toxicology Program 11th Report on 

Carcinogens available at: ntp.niehs.nih.gov/index.cfm?objectid=32BA9724-F1F6-975E-7FCE50709CB4C932. 
 

579

subpopulations. 1,3-butadiene also causes a variety of reproductive and developmental effects in 

mice; no human data on these effects are available. The most sensitive effect was ovarian 

atrophy observed in a lifetime bioassay of female mice.251

e. Ethanol 

EPA is conducting an assessment of the cancer and noncancer effects of exposure to 

ethanol, a compound which is not currently listed in EPA’s IRIS. A description of these effects 

to the extent that information is available will be presented, as required by Section 1505 of 

EPAct, in a Report to Congress on public health, air quality and water resource impacts of fuel 

additives. We expect to release that report in 2010. 

 Extensive data are available regarding adverse health effects associated with the 

ingestion of ethanol while data on inhalation exposure effects are sparse. As part of the IRIS 

assessment, pharmacokinetic models are being evaluated as a means of extrapolating across 

species (animal to human) and across exposure routes (oral to inhalation) to better characterize 

the health hazards and dose-response relationships for low levels of ethanol exposure in the 

environment. 

The IARC has classified “alcoholic beverages” as carcinogenic to humans based on 

sufficient evidence that malignant tumors of the mouth, pharynx, larynx, esophagus, and liver are 

 

251 Bevan, C.; Stadler, J.C.; Elliot, G.S.; et al. (1996) Subchronic toxicity of 4-vinylcyclohexene in rats and mice by 

inhalation. Fundam. Appl. Toxicol. 32:1-10. 
 

580

causally related to the consumption of alcoholic beverages.252 The U.S. DHHS in the 11th Report 

on Carcinogens also identified “alcoholic beverages” as a known human carcinogen (they have 

not evaluated the cancer risks specifically from exposure to ethanol), with evidence for cancer of 

the mouth, pharynx, larynx, esophagus, liver and breast.253 There are no studies reporting 

carcinogenic effects from inhalation of ethanol. EPA is currently evaluating the available human 

and animal cancer data to identify which cancer type(s) are the most relevant to an assessment of 

risk to humans from a low-level oral and inhalation exposure to ethanol. 

Noncancer health effects data are available from animal studies as well as epidemiologic 

studies. The epidemiologic data are obtained from studies of alcoholic beverage consumption. 

Effects include neurological impairment, developmental effects, cardiovascular effects, immune 

system depression, and effects on the liver, pancreas and reproductive system.254 There is 

evidence that children prenatally exposed via mothers’ ingestion of alcoholic beverages during 

pregnancy are at increased risk of hyperactivity and attention deficits, impaired motor 

coordination, a lack of regulation of social behavior or poor psychosocial functioning, and 

deficits in cognition, mathematical ability, verbal fluency, and spatial 

memory.255,256,257,258,259,260,261,262 In some people, genetic factors influencing the metabolism of 

 

252 International Agency for Research on Cancer (IARC). 1988. Monographs on the evaluation of carcinogenic risk 

of chemicals to humans, Volume 44, Alcohol Drinking, World Health Organization, Lyon, France.

253 U.S. Department of Health and Human Services. 2005. National Toxicology Program 11th Report on 

Carcinogens available at: ntp.niehs.nih.gov/index.cfm?objectid=32BA9724-F1F6-975E-7FCE50709CB4C932. 

254 U.S. Department of Health and Human Services. 2000. 10th Special Report to the U.S. Congress on Alcohol and 

Health. June. 2000. 

255 Goodlett CR, KH Horn, F Zhou. 2005. Alcohol teratogeniesis: mechanisms of damage and strategies for 

intervention. Exp. Biol. Med. 230:394-406. 

256 Riley EP, CL McGee. 2005. Fetal alcohol spectrum disorders: an overview with emphasis on changes in brain 

and behavior. Exp. Biol. Med. 230:357-365. 

257 Zhang X, JH Sliwowska, J Weinberg. 2005. Prenatal alcohol exposure and fetal programming: effects on 

neuroendocrine and immune function. Exp. Biol. Med. 230:376-388. 

258 Riley EP, CL McGee, ER Sowell. 2004. Teratogenic effects of alcohol: a decade of brain imaging. Am. J. Med. 

Genet. Part C: Semin. Med. Genet. 127:35-41. 
 

581

ethanol can lead to differences in internal levels of ethanol and may render some subpopulations 

more susceptible to risks from the effects of ethanol. 

 

f. Formaldehyde 

Since 1987, EPA has classified formaldehyde as a probable human carcinogen based on 

evidence in humans and in rats, mice, hamsters, and monkeys.263 EPA is currently reviewing 

recently published epidemiological data. For instance, research conducted by the National 

Cancer Institute (NCI) found an increased risk of nasopharyngeal cancer and 

lymphohematopoietic malignancies such as leukemia among workers exposed to 

formaldehyde.264, 265 In an analysis of the lymphohematopoietic cancer mortality from an 

extended follow-up of these workers, NCI confirmed an association between 

lymphohematopoietic cancer risk and peak exposures.266 A recent National Institute of 

Occupational Safety and Health (NIOSH) study of garment workers also found increased risk of 

 259 Gunzerath L, V Faden, S Zakhari, K Warren. 2004. National Institute on Alcohol Abuse and Alcoholism report 

on moderate drinking. Alcohol. Clin. Exp. Res. 28:829-847. 

260 World Health Organization (WHO). 2004. Global status report on alcohol 2004. Geneva, Switzerland: 

Department of Mental Health and Substance Abuse. Available: 

http://www.who.int/substance_abuse/publications/global_status_report_2004_overview.pdf 

261 Chen W-JA, SE Maier, SE Parnell, FR West. 2003. Alcohol and the developing brain: neuroanatomical studies. 

Alcohol Res. Health 27:174-180. 

262 Driscoll CD, AP Streissguth, EP Riley. 1990. Prenatal alcohol exposure comparability of effects in humans and 

animal models. Neurotoxicol. Teratol. 12:231-238. 

263 U.S. EPA (1987) Assessment of Health Risks to Garment Workers and Certain Home Residents from Exposure 

to Formaldehyde, Office of Pesticides and Toxic Substances, April 1987. 

264 Hauptmann, M.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2003. Mortality from lymphohematopoetic 

malignancies among workers in formaldehyde industries. Journal of the National Cancer Institute 95: 1615-1623.

265 Hauptmann, M.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Blair, A. 2004. Mortality from solid cancers among 

workers in formaldehyde industries. American Journal of Epidemiology 159: 1117-1130.

266 Beane Freeman, L. E.; Blair, A.; Lubin, J. H.; Stewart, P. A.; Hayes, R. B.; Hoover, R. N.; Hauptmann, M. 2009. 

Mortality from lymphohematopoietic malignancies among workers in formaldehyde industries: The National Cancer 

Institute cohort. J. National Cancer Inst. 101: 751-761. 
 

582

death due to leukemia among workers exposed to formaldehyde.267 Extended follow-up of a 

cohort of British chemical workers did not find evidence of an increase in nasopharyngeal or 

lymphohematopoietic cancers, but a continuing statistically significant excess in lung cancers 

was reported.268 Recently, the IARC re-classified formaldehyde as a human carcinogen (Group 

1).269 

Formaldehyde exposure also causes a range of noncancer health effects, including 

irritation of the eyes (burning and watering of the eyes), nose and throat. Effects from repeated 

exposure in humans include respiratory tract irritation, chronic bronchitis and nasal epithelial 

lesions such as metaplasia and loss of cilia. Animal studies suggest that formaldehyde may also 

cause airway inflammation – including eosinophil infiltration into the airways. There are several 

studies that suggest that formaldehyde may increase the risk of asthma – particularly in the 

young.270,271

g. Peroxyacetyl nitrate (PAN) 

Peroxyacetyl nitrate (PAN) has not been evaluated by EPA’s IRIS program. Information 

regarding the potential carcinogenicity of PAN is limited. As noted in the EPA air quality 

 

267 Pinkerton, L. E. 2004. Mortality among a cohort of garment workers exposed to formaldehyde: an update. 

Occup. Environ. Med. 61: 193-200.

268 Coggon, D, EC Harris, J Poole, KT Palmer. 2003. Extended follow-up of a cohort of British chemical workers 

exposed to formaldehyde. J National Cancer Inst. 95:1608-1615. 

269 International Agency for Research on Cancer (IARC). 2006. Formaldehyde, 2-Butoxyethanol and 1-tertButoxypropan-2-ol. Volume 88. (in preparation), World Health Organization, Lyon, France. 

270 Agency for Toxic Substances and Disease Registry (ATSDR). 1999. Toxicological profile for Formaldehyde. 

Atlanta, GA: U.S. Department of Health and Human Services, Public Health Service. 

http://www.atsdr.cdc.gov/toxprofiles/tp111.html 

271 WHO (2002) Concise International Chemical Assessment Document 40: Formaldehyde. Published under the 

joint sponsorship of the United Nations Environment Programme, the International Labour Organization, and the 

World Health Organization, and produced within the framework of the Inter-Organization Programme for the Sound 

Management of Chemicals. Geneva. 
 

583

criteria document for ozone and related photochemical oxidants, cytogenetic studies indicate that 

PAN is not a potent mutagen, clastogen (a compound that can cause breaks in chromosomes), or 

DNA-damaging agent in mammalian cells either in vivo or in vitro. Some studies suggest that 

PAN may be a weak bacterial mutagen at high concentrations much higher than exist in present 

urban atmospheres.272

Effects of ground-level smog causing intense eye irritation have been attributed to 

photochemical oxidants, including PAN.273 Animal toxicological information on the inhalation 

effects of the non-ozone oxidants has been limited to a few studies on PAN. Acute exposure to 

levels of PAN can cause changes in lung morphology, behavioral modifications, weight loss, and 

susceptibility to pulmonary infections. Human exposure studies indicate minor pulmonary 

function effects at high PAN concentrations, but large inter-individual variability precludes 

definitive conclusions.274

 

h. Naphthalene 

Naphthalene is found in small quantities in gasoline and diesel fuels. Naphthalene 

emissions have been measured in larger quantities in both gasoline and diesel exhaust compared 

 

272 U.S. EPA. 2006. Air quality criteria for ozone and related photochemical oxidants (Ozone CD). Research 

Triangle Park, NC: National Cetner for Environmental Assesssment; report no. EPA/600/R-05/004aF-cF.3v. page 5-

78 Available at http://cfpub.epa.gov/ncea/. 

273 U.S. EPA Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S. Environmental 

Protection Agency, Washington, D.C., EPA 600/R-05/004aF-cF, 2006. page 5-63. This document is available in 

Docket EPA-HQ-OAR-2005-0161. This document may be accessed electronically at: 

http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_cd.html 

274 U.S. EPA Air Quality Criteria for Ozone and Related Photochemical Oxidants (Final). U.S. Environmental 

Protection Agency, Washington, D.C., EPA 600/R-05/004aF-cF, 2006. page 5-78. This document is available in 

Docket EPA-HQ-OAR-2005-0161. This document may be accessed electronically at: 

http://www.epa.gov/ttn/naaqs/standards/ozone/s_o3_cr_cd.html 
 

584

with evaporative emissions from mobile sources, indicating it is primarily a product of 

combustion. EPA released an external review draft of a reassessment of the inhalation 

carcinogenicity of naphthalene based on a number of recent animal carcinogenicity studies.275 

The draft reassessment completed external peer review.276 Based on external peer review 

comments received, additional analyses are being undertaken. This external review draft does 

not represent official agency opinion and was released solely for the purposes of external peer 

review and public comment. The National Toxicology Program listed naphthalene as 

"reasonably anticipated to be a human carcinogen" in 2004 on the basis of bioassays reporting 

clear evidence of carcinogenicity in rats and some evidence of carcinogenicity in mice.277 

California EPA has released a new risk assessment for naphthalene, and the IARC has 

reevaluated naphthalene and re-classified it as Group 2B: possibly carcinogenic to humans.278 

Naphthalene also causes a number of chronic non-cancer effects in animals, including abnormal 

cell changes and growth in respiratory and nasal tissues.279

 

i. Other Air Toxics 

 

275 U. S. EPA. 2004. Toxicological Review of Naphthalene (Reassessment of the Inhalation Cancer Risk), 

Environmental Protection Agency, Integrated Risk Information System, Research and Development, National 

Center for Environmental Assessment, Washington, DC. This material is available electronically at 

http://www.epa.gov/iris/subst/0436.htm. 

276 Oak Ridge Institute for Science and Education. (2004). External Peer Review for the IRIS Reassessment of the 

Inhalation Carcinogenicity of Naphthalene. August 2004. 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=84403

277 National Toxicology Program (NTP). (2004). 11th Report on Carcinogens. Public Health Service, U.S. 

Department of Health and Human Services, Research Triangle Park, NC. Available from: http://ntpserver.niehs.nih.gov. 

278 International Agency for Research on Cancer (IARC). (2002). Monographs on the Evaluation of the 

Carcinogenic Risk of Chemicals for Humans. Vol. 82. Lyon, France.

279 U. S. EPA. 1998. Toxicological Review of Naphthalene, Environmental Protection Agency, Integrated Risk 

Information System, Research and Development, National Center for Environmental Assessment, Washington, DC. 

This material is available electronically at http://www.epa.gov/iris/subst/0436.htm 
 

585

In addition to the compounds described above, other compounds in gaseous hydrocarbon 

and PM emissions from vehicles will be affected by today’s final action. Mobile source air toxic 

compounds that will potentially be impacted include ethylbenzene, polycyclic organic matter, 

propionaldehyde, toluene, and xylene. Information regarding the health effects of these 

compounds can be found in EPA’s IRIS database.280

F. Environmental Effects of Criteria and Air Toxic Pollutants 

In this section we discuss some of the environmental effects of PM and its precursors 

such as visibility impairment, atmospheric deposition, and materials damage and soiling, as well 

as environmental effects associated with the presence of ozone in the ambient air, such as 

impacts on plants, including trees, agronomic crops and urban ornamentals, and environmental 

effects associated with air toxics. 

1. Visibility

Visibility can be defined as the degree to which the atmosphere is transparent to visible 

light.281 Airborne particles degrade visibility by scattering and absorbing light. Visibility is 

important because it has direct significance to people’s enjoyment of daily activities in all parts 

of the country. Individuals value good visibility for the well-being it provides them directly, 

where they live and work, and in places where they enjoy recreational opportunities. Visibility is 

 

280 U.S. EPA Integrated Risk Information System (IRIS) database is available at: www.epa.gov/iris 281 National Research Council, 1993. Protecting Visibility in National Parks and Wilderness Areas. National 

Academy of Sciences Committee on Haze in National Parks and Wilderness Areas. National Academy Press, 

Washington, DC. This document is available in Docket EPA-HQ-OAR-2005-0161. This book can be viewed on 

the National Academy Press Website at http://www.nap.edu/books/0309048443/html/ 
 

586

also highly valued in significant natural areas such as national parks and wilderness areas and 

special emphasis is given to protecting visibility in these areas. For more information on 

visibility, see the final 2004 PM AQCD as well as the 2005 PM Staff Paper.282,283 

EPA is pursuing a two-part strategy to address visibility. First, to address the welfare 

effects of PM on visibility, EPA has set secondary PM2.5 standards which act in conjunction with 

the establishment of a regional haze program. In setting this secondary standard, EPA has 

concluded that PM2.5 causes adverse effects on visibility in various locations, depending on PM 

concentrations and factors such as chemical composition and average relative humidity. Second, 

section 169 of the Clean Air Act provides additional authority to address existing visibility 

impairment and prevent future visibility impairment in the 156 national parks, forests and 

wilderness areas categorized as mandatory class I federal areas (62 FR 38680-81, July 18, 

1997).284 In July 1999, the regional haze rule (64 FR 35714) was put in place to protect the 

visibility in mandatory class I federal areas. Visibility can be said to be impaired in both PM2.5

nonattainment areas and mandatory class I federal areas. 

2. Atmospheric Deposition

Wet and dry deposition of ambient particulate matter delivers a complex mixture of 

metals (e.g., mercury, zinc, lead, nickel, aluminum, cadmium), organic compounds (e.g., POM, 

 

282 U.S. EPA (2004) Air Quality Criteria for Particulate Matter (Oct 2004), Volume I Document No. EPA600/P99/002aF and Volume II Document No. EPA600/P-99/002bF. This document is available in Docket EPA-HQOAR-2005-0161. 

283 U.S. EPA (2005) Review of the National Ambient Air Quality Standard for Particulate Matter: Policy 

Assessment of Scientific and Technical Information, OAQPS Staff Paper. EPA-452/R-05-005. This document is 

available in Docket EPA-HQ-OAR-2005-0161. 

284 These areas are defined in CAA section 162 as those national parks exceeding 6,000 acres, wilderness areas and 

memorial parks exceeding 5,000 acres, and all international parks which were in existence on August 7, 1977. 
 

587

dioxins, furans) and inorganic compounds (e.g., nitrate, sulfate) to terrestrial and aquatic 

ecosystems. The chemical form of the compounds deposited depends on a variety of factors 

including ambient conditions (e.g., temperature, humidity, oxidant levels) and the sources of the 

material. Chemical and physical transformations of the compounds occur in the atmosphere as 

well as the media onto which they deposit. These transformations in turn influence the fate, 

bioavailability and potential toxicity of these compounds. Atmospheric deposition has been 

identified as a key component of the environmental and human health hazard posed by several 

pollutants including mercury, dioxin and PCBs.285

Adverse impacts on water quality can occur when atmospheric contaminants deposit to 

the water surface or when material deposited on the land enters a waterbody through runoff. 

Potential impacts of atmospheric deposition to waterbodies include those related to both nutrient 

and toxic inputs. Adverse effects to human health and welfare can occur from the addition of 

excess nitrogen via atmospheric deposition. The nitrogen-nutrient enrichment contributes to 

toxic algae blooms and zones of depleted oxygen, which can lead to fish kills, frequently in 

coastal waters. Deposition of heavy metals or other toxins may lead to the human ingestion of 

contaminated fish, human ingestion of contaminated water, damage to the marine ecology, and 

limits to recreational uses. Several studies have been conducted in U.S. coastal waters and in the 

Great Lakes Region in which the role of ambient PM deposition and runoff is 

investigated.286,287,288,289,290 

 

285 U.S. EPA (2000) Deposition of Air Pollutants to the Great Waters: Third Report to Congress. Office of Air 

Quality Planning and Standards. EPA-453/R-00-0005. This document is available in Docket EPA-HQ-OAR-2005-

0161. 

286 U.S. EPA (2004) National Coastal Condition Report II. Office of Research and Development/ Office of Water. 

EPA-620/R-03/002. This document is available in Docket EPA-HQ-OAR-2005-0161. 

287 Gao, Y., E.D. Nelson, M.P. Field, et al. 2002. Characterization of atmospheric trace elements on PM2.5 

particulate matter over the New York-New Jersey harbor estuary. Atmos. Environ. 36: 1077-1086. 
 

588

Atmospheric deposition of nitrogen and sulfur contributes to acidification, altering 

biogeochemistry and affecting animal and plant life in terrestrial and aquatic ecosystems across 

the U.S. The sensitivity of terrestrial and aquatic ecosystems to acidification from nitrogen and 

sulfur deposition is predominantly governed by geology. Prolonged exposure to excess nitrogen 

and sulfur deposition in sensitive areas acidifies lakes, rivers and soils. Increased acidity in 

surface waters creates inhospitable conditions for biota and affects the abundance and nutritional 

value of preferred prey species, threatening biodiversity and ecosystem function. Over time, 

acidifying deposition also removes essential nutrients from forest soils, depleting the capacity of 

soils to neutralize future acid loadings and negatively affecting forest sustainability. Major 

effects include a decline in sensitive forest tree species, such as red spruce (Picea rubens) and 

sugar maple (Acer saccharum), and a loss of biodiversity of fishes, zooplankton, and macro 

invertebrates.

In addition to the role nitrogen deposition plays in acidification, nitrogen deposition also 

causes ecosystem nutrient enrichment leading to eutrophication that alters biogeochemical 

cycles. Excess nitrogen also leads to the loss of nitrogen sensitive lichen species as they are 

outcompeted by invasive grasses as well as altering the biodiversity of terrestrial ecosystems, 

such as grasslands and meadows. For a broader explanation of the topics treated here, refer to 

the description in Section 3.6.2 of the RIA. 

 288 Kim, G., N. Hussain, J.R. Scudlark, and T.M. Church. 2000. Factors influencing the atmospheric depositional 

fluxes of stable Pb, 210Pb, and 7Be into Chesapeake Bay. J. Atmos. Chem. 36: 65-79. 289 Lu, R., R.P. Turco, K. Stolzenbach, et al. 2003. Dry deposition of airborne trace metals on the Los Angeles 

Basin and adjacent coastal waters. J. Geophys. Res. 108(D2, 4074): AAC 11-1 to 11-24. 290 Marvin, C.H., M.N. Charlton, E.J. Reiner, et al. 2002. Surficial sediment contamination in Lakes Erie and 

Ontario: A comparative analysis. J. Great Lakes Res. 28(3): 437-450. 
 

589

Adverse impacts on soil chemistry and plant life have been observed for areas heavily 

influenced by atmospheric deposition of nutrients, metals and acid species, resulting in species 

shifts, loss of biodiversity, forest decline and damage to forest productivity. Potential impacts 

also include adverse effects to human health through ingestion of contaminated vegetation or 

livestock (as in the case for dioxin deposition), reduction in crop yield, and limited use of land 

due to contamination. 

Atmospheric deposition of pollutants can reduce the aesthetic appeal of buildings and 

culturally important articles through soiling, and can contribute directly (or in conjunction with 

other pollutants) to structural damage by means of corrosion or erosion. Atmospheric deposition 

may affect materials principally by promoting and accelerating the corrosion of metals, by 

degrading paints, and by deteriorating building materials such as concrete and limestone. 

Particles contribute to these effects because of their electrolytic, hygroscopic, and acidic 

properties, and their ability to adsorb corrosive gases (principally sulfur dioxide). The rate of 

metal corrosion depends on a number of factors, including: the deposition rate and nature of the 

pollutant; the influence of the metal protective corrosion film; the amount of moisture present; 

variability in the electrochemical reactions; the presence and concentration of other surface 

electrolytes; and the orientation of the metal surface. 

3. Plant and Ecosystem Effects of Ozone

Elevated ozone levels contribute to environmental effects, with impacts to plants and 

ecosystems being of most concern. Ozone can produce both acute and chronic injury in sensitive 

species depending on the concentration level and the duration of the exposure. Ozone effects 
 

590

also tend to accumulate over the growing season of the plant, so that even low concentrations 

experienced for a longer duration have the potential to create chronic stress on vegetation. 

Ozone damage to plants includes visible injury to leaves and impaired photosynthesis, both of 

which can lead to reduced plant growth and reproduction, resulting in reduced crop yields, 

forestry production, and use of sensitive ornamentals in landscaping. In addition, the impairment 

of photosynthesis, the process by which the plant makes carbohydrates (its source of energy and 

food), can lead to a subsequent reduction in root growth and carbohydrate storage below ground, 

resulting in other, more subtle plant and ecosystems impacts. 

These latter impacts include increased susceptibility of plants to insect attack, disease, 

harsh weather, interspecies competition and overall decreased plant vigor. The adverse effects of 

ozone on forest and other natural vegetation can potentially lead to species shifts and loss from 

the affected ecosystems, resulting in a loss or reduction in associated ecosystem goods and 

services. Lastly, visible ozone injury to leaves can result in a loss of aesthetic value in areas of 

special scenic significance like national parks and wilderness areas. The final 2006 Ozone Air 

Quality Criteria Document presents more detailed information on ozone effects on vegetation 

and ecosystems. 

4. Environmental Effects of Air Toxics

Fuel combustion emissions contribute to ambient levels of pollutants that contribute to 

adverse effects on vegetation. PAN is a well-established phytotoxicant causing visible injury to 

leaves that can appear as metallic glazing on the lower surface of leaves with some leafy 
 

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vegetables exhibiting particular sensitivity (e.g., spinach, lettuce, chard).291, 292, 293 PAN has been 

demonstrated to inhibit photosynthetic and non-photosynthetic processes in plants and retard the 

growth of young navel orange trees.294, 295 In addition to its oxidizing capability, PAN 

contributes nitrogen to forests and other vegetation via uptake as well as dry and wet deposition 

to surfaces. As noted in Section IX, nitrogen deposition can lead to saturation of terrestrial 

ecosystems and research is needed to understand the impacts of excess nitrogen deposition 

experienced in some areas of the country on water quality and ecosystems.296

Volatile organic compounds (VOCs), some of which are considered air toxics, have long 

been suspected to play a role in vegetation damage.297 In laboratory experiments, a wide range 

of tolerance to VOCs has been observed.298 Decreases in harvested seed pod weight have been 

reported for the more sensitive plants, and some studies have reported effects on seed 

germination, flowering and fruit ripening. Effects of individual VOCs or their role in 

conjunction with other stressors (e.g., acidification, drought, temperature extremes) have not 

been well studied. In a recent study of a mixture of VOCs including ethanol and toluene on 

herbaceous plants, significant effects on seed production, leaf water content and photosynthetic 

 

291 Nouchi I, S Toyama. 1998. Effects of ozone and peroxyacetyl nitrate on polar lipids and fatty acids in leaves of 

morning glory and kidney bean. Plant Physiol. 87:638-646. 

292 Oka E, Y Tagami, T Oohashi, N Kondo. 2004. A physiological and morphological study on the injury caused by 

exposure to the air pollutant, peroxyacetyl nitrate (PAN), based on the quantitative assessment of the injury. J Plant 

Res. 117:27-36. 

293 Sun E-J, M-H Huang. 1995. Detection of peroxyacetyl nitrate at phytotoxic level and its effects on vegetation in 

Taiwan. Atmos. Env. 29:2899-2904. 

294 Koukol J, WM Dugger, Jr., RL Palmer. 1967. Inhibitory effect of peroxyacetyl nitrate on cyclic 

photophosphorylation by chloroplasts from black valentine bean leaves. Plant Physiol. 42:1419-1422. 

295 Thompson CR, G Kats. 1975. Effects of ambient concentrations of peroxyacetyl nitrate on navel orange trees. 

Env. Sci. Technol. 9:35-38. 

296 Bytnerowicz A, ME Fenn. 1995. Nitrogen deposition in California forests: A Review. Environ. Pollut. 92:127-

146. 

297 US EPA. 1991. Effects of organic chemicals in the atmosphere on terrestrial plants. EPA/600/3-91/001. 298 Cape JN, ID Leith, J Binnie, J Content, M Donkin, M Skewes, DN Price AR Brown, AD Sharpe. 2003. Effects of 

VOCs on herbaceous plants in an open-top chamber experiment. Environ. Pollut. 124:341-343. 
 

592

efficiency were reported for some plant species.299 

Research suggests an adverse impact of vehicle exhaust on plants, which has in some 

cases been attributed to aromatic compounds and in other cases to nitrogen oxides.300, 301, 302 The 

impacts of VOCs on plant reproduction may have long-term implications for biodiversity and 

survival of native species near major roadways. Most of the studies of the impacts of VOCs on 

vegetation have focused on short-term exposure and few studies have focused on long-term 

effects of VOCs on vegetation and the potential for metabolites of these compounds to affect 

herbivores or insects. 

 

 

299 Cape JN, ID Leith, J Binnie, J Content, M Donkin, M Skewes, DN Price AR Brown, AD Sharpe. 2003. Effects of 

VOCs on herbaceous plants in an open-top chamber experiment. Environ. Pollut. 124:341-343. 

300 Viskari E-L. 2000. Epicuticular wax of Norway spruce needles as indicator of traffic pollutant deposition. Water, 

Air, and Soil Pollut. 121:327-337. 

301 Ugrekhelidze D, F Korte, G Kvesitadze. 1997. Uptake and transformation of benzene and toluene by plant leaves. 

Ecotox. Environ. Safety 37:24-29. 

302 Kammerbauer H, H Selinger, R Rommelt, A Ziegler-Jons, D Knoppik, B Hock. 1987. Toxic components of 

motor vehicle emissions for the spruce Pciea abies. Environ. Pollut. 48:235-243. 
 

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594

VII. Impacts on Cost of Renewable Fuels, Gasoline, and Diesel 

 We have assessed the impacts of the renewable fuel volumes required by EISA on their 

costs and on the costs of the gasoline and diesel fuels into which the renewable fuels will be 

blended. More details of feedstock costs are addressed in Section VIII.A. 

A. Renewable Fuel Production Costs 

 1. Ethanol Production Costs

 a. Corn Ethanol 

 A significant amount of work has been done in the last decade surveying and modeling the 

costs involved in producing ethanol from corn in order to serve business and investment purposes as 

well as to try to educate energy policy decisions. Corn ethanol costs for our work were estimated 

using models developed and maintained by USDA. Their work has been described in a peerreviewed journal paper on cost modeling of the dry-grind corn ethanol process, and compares well 

with cost information found in surveys of existing plants. 303,304 The USDA models were adjusted to 

reflect the energy usage we anticipate for the average ethanol plant in 2022 and intermediate years, 

as well as the prices of energy and agricultural commodities as projected by AEO and the FASOM 

model respectively. 

 

303 Kwaitkowski, J.R., Macon, A., Taylor, F., Johnston, D.B.; Industrial Crops and Products 23 (2006) 288-296 304 Shapouri, H., Gallagher, P.; USDA’s 2002 Ethanol Cost-of-Production Survey (published July 2005) 
 

595

 For our policy case scenario, we used corn prices of $3.60/bu in 2022 with corresponding 

DDGS prices of $124.74/ton (all 2007$). These estimates are taken from agricultural economics 

modeling work done for this rule using the Forestry and Agricultural Sector Optimization Model 

(see Section VIII.A). 

 For natural gas-fired ethanol production producing dried co-product (currently describes the 

largest fraction of the industry), in the policy case corn feedstock minus DDGS sale credit represents 

about 54% of the final per-gallon cost, while utilities, facility, chemical and enzymes, and labor 

comprise about 22%, 13%, 7%, and 4%, respectively. Thus, the cost of ethanol production is most 

sensitive to the prices of corn and the primary co-product, DDGS, and relatively insensitive to 

economy of scale over the range of plant sizes typically seen (40-100 MMgal/yr). 

 We expect that several process fuels will be used to produce corn ethanol (see RIA Section 

1.4), which are presented by their projected 2022 volume production share in Table VII.A.1-1 and 

cost impacts for each in Table VII.A.1-2.305

 

305 Projected fuel mix was taken from Mueller, S., Energy Research Center at the University of Chicago; An 

Analysis of the Projected Energy Use of Future Dry Mill Corn Ethanol Plants (2010-2030); cost estimates were 

derived from modifications to the USDA process models. 
 

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Table VII.A.1-1 

Projected 2022 Breakdown of Fuel Types Used to Estimate Production Cost of Corn Ethanol, 

Percent Share of Total Production Volume 

 Fuel Type Total by Plant 

Type 

Plant Type Biomass Coal Natural Gas Biogas All Fuels 

Coal/Biomass Boiler 11% 0% - - 11% 

Coal/Biomass Boiler + 

CHP 

10% 4% - - 14% 

Natural Gas Boiler - - 49% 14% 63% 

Natural Gas Boiler + 

CHP 

- - 12% - 12% 

Total by Fuel Type 21% 4% 61% 14% 100% 
 

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Table VII.A.1-2 

Projected 2022 Breakdown of Cost Impacts By Fuel Type Used in Estimating Production Cost of 

Corn Ethanol, Dollars Per Gallon Relative to Natural Gas Baseline 

 Fuel Type Total by Plant 

Type 

Plant Type Biomass a Coal Natural Gas Biogas b All Fuels 

Coal/Biomass Boiler +$0.009 +$0.009 - - - 

Coal/Biomass Boiler + 

CHP 

-$0.021 -$0.021 - - - 

Natural Gas Boiler - - baseline +$0.00 - 

Natural Gas Boiler + 

CHP 

- - -$0.032 - - 

Total by Fuel Type - - - - -$0.006 

a Assumes biomass has same plant-delivered cost as coal. 

b Assumes biogas has same plant-delivered cost as natural gas. 

 In addition to the primary fuel type used by ethanol production facilities, we also anticipate 

new technologies and efficiency improvements will impact the cost of ethanol production. More 

efficient motors and turbines are currently under development and are likely to be adopted by 

ethanol producers as ways to lower green house gas emissions and reduce energy costs. Several new 

process technologies, including corn oil extraction, corn fractionation, cold starch fermentation, and 

ethanol dehydration membranes will allow ethanol producers to further reduce energy consumption 

and produce higher value co-products. These technologies are discussed in sections 1.4.1.3 and 
 

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1.5.1.3 of the RIA. In order to reflect the cost advantages of ethanol producers using these 

technologies the USDA models were adapted to take into account the capital costs, lower energy 

usage, and higher value co-products that result from the adoption of these new technologies. The 

projected adoption rates of these technologies, and their impacts on the production cost of corn 

ethanol, are summarized in Table VII.A.1-3 below. More detail on how the USDA models were 

adjusted and the impact this had on the average price of ethanol production can be found in section 

4.1.1.1 of the RIA. 

Table VII.A.1-3 

Projected Cost Impacts or New Corn Ethanol Technologies 

Technology Percent of Plants 

Adopting Technology

Cost Impact (Change 

from Baseline) 

Weighted 

Cost Impact 

More Efficient 

Boilers/Motors/Turbines 

100% Baseline $0.00/gal 

Raw Starch Hydrolysis 22% -$0.066/gal -$0.015/gal 

Corn Fractionation 20% -$0.093/gal -$0.019/gal 

Corn Oil Extraction 70% -$0.079/gal -$0.055/gal 

Membrane Separation 5% -$0.064/gal -$0.003/gal 

Total Cost Impact N/A N/A -$0.092/gal 

 Whether or not the distillers grains and solubles (DGS) are dried also has an impact on the 

cost of ethanol production. Drying the DGS is an energy intensive process and results in a 

significant increase energy usages as well as cost. The advantages of dry DGS are reduced 
 

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transportation costs and a product that is less susceptible to spoilage, and can therefore be sold to a 

much wider market. If the DGS can be sold wet, the cost of ethanol production can be reduced by 

$0.083 per gallon. A 2007 survey of ethanol producers indicated that 37% of DGS were being sold 

wet. We anticipate that this percentage of wet DGS will remain constant in 2022. The net cost 

impact of selling 37% of the DGS wet is an average cost reduction of $0.031 per gallon. 

Table VII.A.1-4 

Average Ethanol Cost of Production 

Baseline Cost of Production (Natural Gas, 

 no new technologies, 100% dry DGS) 

$1.627/gal 

Fuel Type Cost Impact -$0.006/gal 

New Technology Cost Impact -$0.092/gal 

DGS Drying Cost Impact -$0.031/gal 

Average Cost of Ethanol Production (2022) $1.499/gal 

Based on energy prices from EIA's Annual Energy Outlook (AEO) April 2009 updated 

reference case ($116/bbl crude oil), we arrive at a production cost of $1.50/gal. More details on the 

ethanol production cost estimates can be found in Chapter 4 of the RIA. This estimate represents the 

full cost to the plant operator, including purchase of feedstocks, energy required for operations, 

capital depreciation, labor, overhead, and denaturant, minus revenue from sale of co-products. The 

capital cost for a 65 MMgal/yr natural gas fired dry mill plant is estimated at $97MM (the projected 

average size of such plants in 2022). 
 

600

Similarly, coal and biomass fired plants were assumed to be 110 MGY in capacity, with an 

estimated capital cost of $184MM. 306 Despite the lower operating costs of coal and biomass fired 

plants the higher capital costs result, on average, ethanol produced in a facility using coal or biomass 

as a primary energy source results in a per-gallon cost $0.01/gal higher compared to production 

using natural gas. See Chapter 4.1 of the RIA for more details. 

 In this cost estimation work, we did not assume any pelletizing of DDGS. Pelletizing is 

expected to improve ease of shipment to more distant markets, which may become more important at 

the larger volumes projected for the future. However, while many in industry are aware of this 

technology, those we spoke with are not employing it in their plants, and do not expect widespread 

use in the foreseeable future. According to USDA’s model, pelletizing adds $0.035/gal to the 

ethanol production cost. 

 Note that the ethanol production cost given here does not account for any subsidies on 

production or sale of ethanol, and is independent of the market price of ethanol. 

 b. Cellulosic Ethanol 

 i. Feedstock Costs

Cellulosic Feedstock Costs 

 

306 Capital costs for a natural gas fired plant were taken from USDA cost model; incremental costs to use coal as the 

primary energy source were derived from conversations with ethanol plant construction contractors. 
 

601

To estimate the cost of producing cellulosic biofuels, it was first necessary to estimate the 

cost of harvesting, storing, processing and transporting the feedstocks to the biofuel production 

facilities. Ethanol or other cellulosic biofuels can be produced from crop residues such as corn 

stover, wheat, rice, oat, and barley straw, sugar cane bagasse, and sorghum, from other cellulosic 

plant matter such as forest thinnings and forest-fuel removal, pulping residues, and from the 

cellulosic portions of municipal solid waste (MSW). 

Our feedstock supply analysis projected that energy crops would be the most abundant of 

the cellulosic feedstocks, comprising about 49% of the total biomass feedstock inventory. 

Agricultural residues, predominantly corn stover, make up approximately 36% of the total, 

followed by MSW at approximately 15% and forestry residue at about 1%. At present, there are 

no commercial sized cellulosic ethanol plants in the U.S. Likewise, there are no commercially 

proven, fully-integrated feedstock supply systems dedicated to providing any of the feedstocks 

we mentioned to ethanol facilities of any size, although certain biomass is harvested for other 

purposes. For this reason, our feedstock cost estimates are projections and not based on any 

existing market data. 

Our feedstock costs include an additional preprocessing cost that many other feedstock 

cost estimates do not include – thus our costs may seem higher. We used biofuel plant cost 

estimates provided by NREL which no longer includes the cost for finely grinding the feedstock 

prior to feeding it to the biofuel plant. Thus, our feedstock costs include an $11 per dry ton cost 

to account for the costs of this grinding operation, regardless of whether this operation occurs in 

the field or at the plant gate. 
 

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 Crop Residue and Energy Crops 

Crop residue harvest is currently a secondary harvest; that is they are harvested or 

gathered only after the prime crop has been harvested. In most northern areas, the harvest 

periods will be short due to the onset of winter weather. In some cases, it may be necessary to 

gather a full year’s worth of residue within just a few weeks. Consequently, to accomplish this 

hundreds of pieces of farm equipment will be required for a few weeks each year to complete a 

harvest. Winter conditions in the South make it somewhat easier to extend the harvest periods; 

in some cases, it may be possible to harvest a residue on an as needed basis. 

During the corn grain harvest, generally only the cob and the leaves above the cob are 

taken into the harvester. Thus, the stover harvest would likely require some portion of the 

standing-stalks be mowed or shredded, following which the entire residue, including that 

discharged from the combine residue-spreader, would need to be raked. Balers, likely a mix of 

large round and large square balers, would follow the rakes. The bales would then be removed 

from the field, usually to the field-side in the first operation of the actual harvest, following 

which they would then be hauled to a satellite facility for intermediate storage. For our analysis 

we assumed that bales would then be hauled by truck and trailer to the processing plant on an as 

needed basis. 

The small grain straws (wheat, rice, oats, barley, sorghum) are cut near the ground at the 

time of grain harvest and thus likely won’t require further mowing or shredding. They will 

likely need to be raked into a windrow prior to baling. Because small grain straws have been 

baled and stored for many years, we don’t expect unusual requirements for handling these 

residues. Their harvest and storage costs will likely be less than those for corn stover, but their 
 

603

overall quantity is much less than corn stover (corn stover makes up about 68% of all the crop 

residues), so we don’t expect their lower costs to have, individually or collectively, a huge effect 

on the overall feedstock costs. Thus, we project that for several years, the feedstock costs will be 

largely a function of the cost to harvest, store, and haul corn stover. 

For the crop residues, we relied on the FASOM agricultural cost model for farm 

harvesting and collection costs. FASOM estimates corn stover would cost $34.49 per dry ton at 

the farm gate. This reflects the cost to mow, rake, bale, and field haul the bales and replace 

nutrients. This farm gate cost could be lower if new equipment is developed that would allow 

the farmer to harvest the corn stover at the same time as the corn. Energy crops such as 

switchgrass and miscanthus would be harvested, baled, stored and transported in a manner very 

similar to crop residues. The FASOM model estimates switch grass, which we are using to be 

representative of all energy crops, would be available at farm side at a cost of $40.85. 

Forestry Residue 

Harvest and transport costs for woody biomass in its different forms vary due to tract 

size, tree species, volumes removed, distance to the wood-using/storage facility, terrain, road 

condition, and other many other considerations. There is a significant variation in these factors 

within the United States, so timber harvest and delivery systems must be designed to meet 

constraints at the local level. Harvesting costs also depend on the type of equipment used, 

season in which the operation occurs, along with a host of other factors. Much of the forest 

residue is already being harvested by logging operations, or is available from milling operations. 

However, the smaller branches and smaller trees proposed to be used for biofuel production are 

not collected for their lumber so they are normally left behind. Thus, this forest residue would 
 

604

have to be collected and transported out of the forest, and then most likely chipped before 

transport to the biofuel plant. 

In general, most operators in the near future would be expected to chip at roadside in the 

forest, blowing the chips directly into a chip van. When the van is full it will be hauled to an end 

user's facility and a new van will be moved into position at the chipper. The process might 

change in the future as baling systems become economically feasible or as roll-off containers are 

proven as a way to handle logging slash. At present, most of the chipping for biomass 

production is done in connection with forest thinning treatments as part of a forest fire 

prevention strategy. The major problem associated with collecting logging residues and biomass 

from small trees is handling the material in the forest before it gets to the chipper. Speciallybuilt balers and roll-off containers offer some promise to reduce this cost. Whether the material 

is collected from a forest thinning operation or a commercial logging operation, chips from 

residues will be dirty and will require screening or some type of filtration at the end-user's 

facility.307 

 As with agricultural residues and energy crops we relied on the FASOM model for road 

side costs for forestry residue. The FASOM model estimates costs for both hardwood and 

softwood logging residues. We anticipate that forestry residue for the production of cellulosic 

biofuels would be a mixture of both hard and soft woods. In order to obtain a cost for forest 

residues to be used as a feedstock for cellulosic biofuels we averaged the costs of the hardwood 

and softwood logging residue prices reported by FASOM. This resulted in a forestry residue 

price of $20.79 at the roadside. Note that this does not include the cost of the grinding operation 

that would be required before the forestry residues can be processed by the biofuel producer. 

 

307 Personal Communication, Eini C. Lowell, Research Scientist, USDA Forest Service 
 

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Municipal Solid Waste 

Millions of tons of municipal solid waste (MSW) continue to be disposed of in landfills 

across the country, despite recent large gains in waste reduction and diversion. The biomass 

fraction of this total stream represents a potentially significant resource for renewable energy 

(including electricity and biofuels). Because this waste material is already being generated, 

collected and transported (it would only need to be transported to a different location), its use is 

likely to be less expensive than other cellulosic feedstocks. One important difficulty facing those 

who plan to use MSW fractions for fuel production is that in many places, even today, MSW is a 

mixture of all types of wastes, including biomaterials such as animal fats and grease, tin, iron, 

aluminum, and other metals, painted woods, plastics, and glass. Many of these materials can’t be 

used in biochemical and thermochemical ethanol production, and, in fact, would inflate the 

transportation costs, impede the operations at the cellulosic ethanol plant and cause an expensive 

waste stream for biofuel producers. 

In today’s regulation the definition of “renewable biomass” includes the separated yard 

and food waste portion of MSW. As discussed in Section III.B.4.d, we are including as part of 

separated yard and food waste, incidental and post-recycled paper and wood wastes. Thus, firms 

planning on using MSW for producing cellulosic biofuels will be required to account for those 

components of the waste. We offer three methods for performing such accounting. One method 

is “feedstock accounting” in which the components of the waste stream are inventoried to obtain 

the fraction representing the portion of the waste stream that qualifies as renewable biomass. 

The second method is that upon verification that the food and yard waste is reasonably separated, 
 

606

that 100 percent of such waste may be counted as renewable biomass for purpose of generating 

RINs. Reasonable separation is considered to occur where curbside recycling is implemented, or 

where technologies are employed that ensure a maximum degree of separation, including but not 

limited to material recovery facilities. Under the second method, the renewable portion of the 

fuel so produced must be verified via a carbon dating method (ASTM D-6866 method) which is 

specified and incorporated by reference in today’s regulation. The third method is the 

application of a default fraction of 50% to be applied to the waste stream purchased and used by 

the fuel producer. 

One method for sorting that would qualify to ensure reasonable separation has occurred is 

single stream recycling, in which the waste is sorted either at a sorting facility or at the landfill 

prior to dumping. There are two prominent options here. The first is that there is no sorting at 

the waste creation site, the home or business, and thus a single waste stream must be sorted at the 

facility. The second is that the sorting occurs at the waste collection facility. The sorting would 

likely be done by hand or by automated equipment at the facility known as material recovery 

facilities (MRFs). To do so by hand is very labor intensive and somewhat slower than using an 

automated system. In most cases the ‘by-hand’ system produces a slightly cleaner stream, but 

the high cost of labor usually makes the automated system more cost-effective. Perhaps the best 

approach for low cost and a clean stream is the combination of hand sorting with automated 

sorting. 

Another method is a combination of the two which requires that there is at least some 

sorting at the home or business which helps to prevent contamination of the waste material, but 

then the final sorting occurs downstream at a sorting site, or at the landfill. 
 

607

We have little data and few estimates for the cost to sort MSW. One estimate generated 

by our Office of Solid Waste for a combination of mechanically and manually sorting a single 

waste stream downstream of where the waste is generated puts the cost in the $20 to $30 per ton 

range. There is a risk, though, that the waste stream could still be contaminated and this would 

increase the cost of both transporting the material and using this material at the biofuel plant due 

to the toxic ash produced which would require disposal at a toxic waste facility. If a less 

contaminated stream is desired it would probably require sorting at the generation site – the 

home or business - which would likely be more costly since many more people in society would 

then have to be involved and special trucks would need to be used. Also, widespread 

participation is difficult when a change in human behavior is required as some may not be so 

willing to participate. Offering incentives could help to speed the transition to curbside recycling 

(i.e., charging a fee for nonsorted waste, or paying a small amount for sorted tree trimmings and 

construction and demolition waste). Assuming that curbside sorting is involved, at least in a 

minor way, total sorting costs might be in the $30 to $40 per ton range. 

These sorting costs would be offset by the cost savings for not disposing of the waste 

material. Most landfills charge tipping fees, the cost to dump a load of waste into a landfill. In 

the United States, the national average nominal tipping fee increased fourfold from 1985 to 2000. 

The real tipping fee almost doubled, up from a national average (in 1997 dollars) of about $12 

per ton in 1985 to just over $30 in 2000. Equally important, it is apparent that the tipping fees 

are much higher in densely populated regions and for areas along the U.S. coast. For example, in 

2004, the tipping fees were $9 per ton in Denver and $97 per ton in Spokane. Statewide 

averages also varied widely, from $8 a ton in New Mexico to $75 in New Jersey. Tipping fees 

ranged from $21 to 98 per ton in 2006 for MSW and $18/ton to $120/ton for construction and 
 

608

demolition waste. It is likely that the tipping fees are highest for contaminated waste that require 

the disposal of the waste in more expensive waste sites that can accept the contaminated waste as 

opposed to a composting site. However, this same contaminated material would probably not be 

desirable to biofuel producers. Presuming that only the uncontaminated cellulosic waste (yard 

trimmings, building construction and demolition waste and some paper) is collected as 

feedstocks for biofuel plants, the handling and tipping fees are likely much lower, in the $30 per 

ton range.308 

The wide variance in the cost of many of these areas affecting the final cost of MSW as a 

cellulosic feedstock, including costs for collecting and sorting MSW as well as the tipping fees 

for disposing of waste materials, makes approximating the cost of MSW a difficult task. Rather 

than attempt to build a model ourselves that would estimate the cost of sorted MSW, we decided 

to contact several companies that are currently planning on using MSW as a feedstock for 

cellulosic biofuel production. In confidential conversations with these companies they indicated 

that they believed that sorted MSW would be available at a near zero cost. In one case they had 

already begun securing MSW sources of feedstock for future biofuel production facilities. They 

indicated to us that while there would be a significant cost associated with sorting the MSW, this 

would be offset, or nearly so, by income generated from the sale of recovered materials (paper, 

metals, plastics, etc.) and the avoidance of tipping fees. There would still, however, be some 

costs associated with the transportation and disposal of materials unfit for the biofuels production 

process. Based on this information, we conservatively estimate that MSW would be available 

for use in a cellulosic biofuel production process at a cost of $15 per ton. See section 4.1 of the 

RIA for further discussion on the cost of MSW as a feedstock for cellulosic biofuels production. 

 

308 We plan on conducting a more thorough analysis of tipping fees by waste type for the final rulemaking. 
 

609

Secondary Storage and Transportation 

In addition to the roadside costs cited in the preceding sections, there will also be a cost 

to transport the cellulosic materials from the farm or forest to the production facility. We relied 

on our own cost analysis to determine the transportation costs. For MSW we do not anticipate 

any additional costs to transport the cellulosic material to the biofuel production facility if it is 

sourced from within the same county as the production facility. This is because this material is 

already being collected and transported to a sorting center landfill, and would simply be rerouted to the production facility. 

For agricultural residues, energy crops, and forestry residue, however, there will be 

additional costs associated with transporting them from the farm or forest side to the production 

facility. These costs are heavily dependent on the distance that the feedstock must be transported 

from the places where it is produced to the biofuel production facility. In order to estimate these 

costs we created a cost estimating tool that calculated transportation costs based on the distance 

the cellulosic material would have to be transported from the farm or forest side to the 

production facility. This tool relies on data provided by the National Agricultural Statistics 

Service for information on the availability and location of agricultural residue. Information on 

abandoned crop land, which was assumed to be the source of energy crops, was provided by 

Elliot Campbell at UC Davis. Data on the availability and location of forest residues was 

provided by the national forestry service. For more information on this secondary storage and 

transportation cost estimating tool that we used to estimate transportation costs see Chapter 4.1 

of the RIA. 
 

610

We also believe that some cellulosic feedstocks will require secondary storage. 

Agricultural residues and energy crops will generally be harvested annually, sometimes in time 

periods as short as a few weeks in order to complete the harvest before the onset of winter 

weather. The large quantity of feedstock required for a commercial scale biofuel production 

plant makes it highly unlikely that a year’s worth of feedstock would be stored at the production 

facility. It is also unlikely that farmers would tolerate the baled agricultural residues or energy 

crops to be stored on their farms and transported to the production facility on an as needed basis 

unless they were compensated for the space bales occupy and damage done to their fields by the 

heavy traffic that would be involved in the collection of this material from their farms. Bales left 

exposed to the weather would also decompose much more rapidly resulting in a higher cost per 

ton of usable cellulosic material to biofuel producers. This loss would be minimized if the bales 

are stored in covered sheds. Our cost estimating tool takes these secondary storage costs into 

account for agricultural residues and energy crops. MSW and forestry residues have no 

secondary storage costs as they can be collected and transported on an as needed basis. 

Cellulosic Feedstock Cost Curve 

 When the various costs described above are combined, together with the cost of grinding 

the cellulosic material ($11/ton), the result is not a single cost, but rather a cost curve. This is 

due to the fact that each feedstock source has a unique price based on the FASOM estimate of 

the cost of production of the feedstock and the cost of transportation and secondary storage (if 

appropriate), where feedstocks have the lowest total cost in the parts of the country where the 

cellulosic plants are likely to be located. The cost per ton of feedstock is lower when the total 

production of cellulosic biofuel is low as the cheapest feedstocks are utilized first. As cellulosic 
 

611

biofuel production increases, so does the cost of cellulosic feedstocks, as more expensive sources 

of feedstock are used. The cost curve for cellulosic feedstocks for the production of up to 16 

billion ethanol equivalent gallons of cellulosic biofuels is shown in Graph VIII.A.1-1 below. 

The average cost of cellulosic feedstock at a production level of 16 billion ethanol equivalent 

gallons is $67.42, and is summarized in Table VII.A.1-5. 

Figure VII.A.1-1 

Cellulosic Feedstock Cost Curve 

 

0

10

20

30

40

50

60

70

80

0 2 4 6 8 10 12 14 16

Billion Gallons Cellulosic Biofuel

$/Ton Cellulosic Feedstock
 

612

Table VII.A.1-5 

 Summary of Cellulosic Feedstock Costs 

Ag Residue Switchgrass Forest Residue MSW 

36% of Total 

Feedstock 

49% of total 

Feedstock 

1% of Total 

Feedstock 

15% of Total 

Feedstock 

Mowing, 

Raking, Baling, 

Hauling, 

Nutrients and 

Farmer 

Payment 

$34.49/ton 

Mowing, 

Raking, Baling, 

Hauling, 

Nutrients and 

Farmer 

Payment 

$40.85/ton 

Harvesting, 

Hauling to 

Forest Edge, 

$20.79/ton 

Sorting, 

Contaminant 

Removal, 

Tipping Fees 

Avoided 

$15/ton 

Hauling to Secondary Storage, Secondary Storage, Hauling to Plant 

$21.53/ton (average) 

Grinding 

$11/ton 

Total 

$67.42/ton 
 

613

 ii. Production Costs for Cellulosic Biofuels 

In this section, we discuss the cost to biochemically and thermochemically convert 

cellulosic feedstocks into fuel ethanol. 

Biochemical Ethanol 

The National Renewable Energy Laboratory has been evaluating the state of biochemical 

cellulosic plant technology over the past decade or so, and it has identified principal areas for 

improvement. In 1999, it released its first report on the likely design concept for an nth 

generation biochemical cellulosic ethanol plant which projected the state of technology in some 

future year after the improvements were adopted. In 2002, NREL released a follow-up report 

which delved deeper into biochemical plant design in areas that it had identified in the 1999 

report as deserving for additional research. Again, the 2002 report estimated the ethanol 

production cost for an nth generation biochemical cellulosic ethanol plant. These reports not 

only helped to inform policy makers on the likely capability and cost for biochemically 

converting cellulose to ethanol, but it helped to inform biochemical technology researchers on 

the most likely technology improvements that could be incorporated into these plant designs. 

To comply with the RFS 2 requirements, NREL assessed the likely state of biochemical 

cellulosic plant technology for EPA over the years that the RFS standard is being phased in. The 

specific years assessed by NREL were 2010, 2015 and 2022. The year 2010 technology 

essentially represents the status of today’s biochemical cellulosic plants. The year 2015 
 

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technology captures the expected near-term improvements including the rapid improvements 

being made in enzyme technology. The year 2022 technology captures the cost of mature 

biochemical cellulosic plant technology. Table VII.A.1-6 summarizes NREL’s estimated and 

projected production costs for biochemical cellulosic ethanol plant technology for their projected 

year 2022 technology in 2007 dollars reflecting a 7 percent before tax rate of return on 

investment. The biochemical cellulosic ethanol costs are based on a cellulosic feedstock cost of 

67 per dry ton. 
 

615

Table VII.A.1-6 

Year 2022 Biochemical Cellulosic Ethanol Production Costs 

Provided by NREL (2007 dollars and 7% before tax rate of return) 

Year 

Technology 

2022 

Plant Size 

MMgal/yr 

71 

Capital Cost 

$MM 

199 

 $MM/yr c/gal 

Capital Cost 

7% ROI before 

taxes 

22 31 

Fixed Costs 8 12 

Feedstock Cost 52 73 

Other raw 

matl. costs 

12 16 

Enzyme Cost 5 8 

Enzyme 

nutrients 

2 2 

Electricity -12 -16 

Waste disposal 1 1 

Total Costs 90 127 
 

616

Thermochemical Ethanol 

Thermochemical conversion is another reaction pathway which exists for converting 

cellulose to ethanol. Thermochemical technology is based on the heat and pressure-based 

gasification or pyrolysis of nearly any biomass feedstock, including those we’ve highlighted as 

likely biochemical feedstocks. The syngas could then be converted into mixed alcohols, 

hydrocarbon fuels, chemicals, and power. In the case that the syngas is converted to ethanol, a 

possible means for doing so would be to pass the syngas over a catalyst which converts the 

syngas to mixed alcohols – mainly methanol. The methanol can be reacted further to ethanol. 

NREL has authored a thermochemical report: Phillips, S Thermochemical Ethanol via 

Indirect Gasification and Mixed Alcohol Synthesis of Lignocellulosic Biomass; April, 2007, 

which already provided a cost estimate. However, this report only hypothesized how a 

thermochemical ethanol plant could achieve production costs at a very low cost of $1 per gallon. 

Rather than rely on a very aggressively analyzed cost assessment that may not be achievable 

within the timeframe of our program, EPA contracted NREL to assess the costs for a 

thermochemical technology which produces mixed alcohols for years 2010, 2015 and 2022. 

Table VII.A.1-7 summarizes NREL’s estimated and projected production costs for biochemical 

cellulosic ethanol plant technology for their projected year 2022 technology in 2007 dollars 

reflecting a 7 percent before tax rate of return on investment. The costs are based on a cellulosic 

feedstock cost of 67 per dry ton. 
 

617

Table VII.A.1-7 

Year 2022 Thermochemical Cellulosic Production Costs of Mixed Alcohols 

Provided by NREL (2007 dollars and 7% before tax rate of return) 

Year 

Technology 

2022 

Plant Size 

MMgal/yr 

72.7 Total Alcohol 

61.9 Ethanol 

Capital Cost 

$MM 

207 

 $MM/yr c/gal 

Capital Cost 

7% ROI before 

taxes 

23 37 

Fixed Costs 13 21 

Feedstock Cost 52 85 

Coproduct 

Credit 

-13 -21 

Other Raw 

Material, 

Waste 

Disposal and 

Catalyst Costs 

1 4 

Total Costs 76 126 
 

618

Cost estimates for both biochemical and thermochemical ethanol pathways ended up 

being ultimately identical. For our cost analysis, we based the cellulosic ethanol costs on the 

average of the biochemical and thermochemical cellulosic ethanol costs. 

BTL Diesel Fuel 

If cellulose is converted to syngas, rather than converting the syngas to mixed alcohols, a 

Fischer Tropsch reactor can be added to convert the syngas to diesel fuel and naphtha. This 

technology is commonly termed biomass-to-liquids (BTL) because of its similarity to gas-toliquids and coal-to-liquids technology. Diesel fuel’s higher energy density per gallon than 

ethanol and even biodiesel provides it an inherent advantage over these other fuels. In addition, 

BTL diesel fuel can be more easily distributed from production to retail outlets and used by 

motor vehicles. The diesel fuel produced by the Fischer Tropsch process tends to be comprised 

of paraffins which provide a much higher cetane number than petroleum diesel fuel, with a 

downside of poorer cloud point which reduces its widespread use in cold temperatures. 

The naphtha produced by the BTL process is also largely comprised of paraffins, 

however, as a gasoline blendstock it is poor because of its very low octane (potentially as low as 

50 octane). This material could be processed by refinery isomerization units raising its octane to 

perhaps 70 octane, but it cannot be processed by refinery reformers since it does not contain the 

naphthenic compounds that are necessary for octane improvement by those units. Because of the 

large amount of octane rich ethanol which is expected to be made available from both corn and 
 

619

cellulose, it could be that BTL naphtha could be blended along with the ethanol into the gasoline 

pool. Rather than prejudge how this naphtha may be utilized in the future, for our cost analysis 

we simply assigned it a coproduct credit. So we set the BTL naphtha cost to be 83% as much of 

the cost of BTL diesel fuel based on its relative energy density. 

Although there were several studies available which provided costs estimates for BTL 

diesel fuel, they did not provide sufficient detail to understand all the cost elements of BTL 

diesel fuel and naphtha. EPA therefore asked NREL to estimate the production costs for BTL 

diesel fuel and naphtha. Like the other technologies, we asked for cost estimates for the same 

years assessed above for cellulosic ethanol which was for 2010, 2015 and 2022, however, NREL 

did not believe that the costs would change that much over this time span. So NREL only 

provided the costs for 2022, advising us that the costs would only be slightly less for earlier 

years, and most of that difference would because of the poorer economies of scale for the initial 

smaller sized plants. 

Table VII.A.1-8 summarizes NREL’s estimated and projected production costs for a 

thermochemical Fischer Tropsch biochemical cellulosic ethanol plant technology for their 

projected year 2022 technology in 2007 dollars reflecting a 7 percent before tax rate of return on 

investment. The costs are based on a cellulosic feedstock cost of 67 per dry ton. 
 

620

Table VII.A.1-8 

Year 2022 Production Costs of Thermochemical (BTL) Cellulosic Fischer Tropsch 

Diesel Fuel Provided by NREL (2007 dollars and 7% before tax rate of return) 

Plant Size MMgal/yr 33.2 Diesel Fuel 

49.4 All Liquid 

Capital Cost $MM 346 

Capital Cost 7% ROI before taxes ($MM/yr) 38 

Fixed Costs ($MM/yr) 18 

Feedstock Cost ($MM/yr) 52 

Coproduct Credit ($MM/yr)a -32 

Other raw matl. Costs ($MM/yr) 1.5 

Waste Disposal and Catalyst Costs ($MM/yr) 1.5 

Total Costs ($MM/yr) 79 

Total Costs (cents/gallon of diesel fuel) 237 

a Based on a naphtha coproduct value of 198 cents per gallon. 

Other Cellulosic Diesel Fuel Costs 

 

For our volumes analysis, we assumed early on for our final rule analysis that there 

would likely be several different cellulosic biofuel technologies, other than BTL, producing 

cellulosic diesel fuel. However, we were either not able to obtain cost information from them, or 

we were uncertain enough about their future that we felt that we should not base the cost of the 

program on them. For example, Cello Energy has already built a cellulosic diesel fuel facility in 
 

621

Alabama here in the US with projected costs of about one dollar per gallon of diesel fuel. 

However, the facility has had difficulty operating as designed. As a result, perhaps very 

conservatively, we assumed that the other cellulosic diesel fuel costs would be the same as the 

BTL diesel fuel costs, and used the 237 cents per gallon cost for BTL diesel fuel for the entire 

cost for cellulosic diesel fuel. 

c. Imported Sugarcane Ethanol 

We based our imported ethanol fuel costs on cost estimates of sugarcane ethanol in 

Brazil. Generally, ethanol from sugarcane produced in developing countries with warm climates 

is much cheaper to produce than ethanol from grain or sugar beets. This is due to favorable 

growing conditions, relatively low cost feedstock and energy inputs, and other cost reductions 

gained from years of experience. 

 

 As discussed in Chapter 4 of the RIA, our literature search of production costs for sugar 

cane ethanol in Brazil indicates that production costs tend to range from as low as $0.57 per 

gallon of ethanol to as high as $1.48 per gallon of ethanol. This large range for estimating 

production costs is partly due to the significant variations over time in exchange rates, costs of 

sugarcane and oil products, etc. For example, earlier estimates may underestimate current crude 

and natural gas costs which influence the cost of feedstock as well as energy costs at the plant. 

Another possible difference in production cost estimates is whether or not the estimates are 

referring to hydrous or anhydrous ethanol. Costs for anhydrous ethanol (for blending with 

gasoline) are typically several cents per gallon higher than hydrous ethanol (for use in dedicated 
 

622

ethanol vehicles in Brazil).309 It is not entirely clear from the majority of studies whether 

reported costs are for hydrous or anhydrous ethanol. Yet another difference could be the slate of 

products the plant is producing, for example, future plants may be dedicated ethanol facilities 

while others involve the production of both sugar and ethanol in the same facility. Due to 

economies of scale, production costs are also typically smaller per gallon for larger facilities. 

 

 The study by OECD (2008) entitled “Biofuels: Linking Support to Performance”, appears 

to provide the most recent and detailed set of assumptions and production costs. As such, our 

estimate of sugarcane production costs primarily relies on the assumptions made for the study, 

which are shown in Table VII.A.1-9. The estimate assumes an ethanol-dedicated mill and is 

based off an internal rate of return of 12%, a debt/equity ratio of 50% with an 8% interest rate 

and a selling of surplus power at $57 per MWh. 

 

309 International Energy Agency (IEA), “Biofuels for Transport: An International Perspective,” 2004. 
 

623

Table VII.A.1-9 

Cost of Production in a Standard Ethanol Project in Brazil 

Sugarcane Productivity 71.5 t/ha 

Sugarcane Consumption 2 million tons/year 

Harvesting days 167 

Ethanol productivity 85 liters/ton (22.5 gal/ton) 

Ethanol Production 170 million liters/year (45 MGY) 

Surplus power produced 40 kWh/ton sugarcane 

Investment cost in mill USD 97 million 

Investment cost for sugarcane production USD 36 million 

O & M (Operating & Maintenance) costs $0.26/gal 

Variable sugarcane production costs $0.64/gal 

Capital costs $0.49/gal 

Total production costs $1.40/gal 

 The estimate above is based on the costs of producing ethanol in Brazil on average, 

today. However, we are interested in how the costs of producing ethanol will change by the year 

2022. Although various cost estimates exist, analysis of the cost trends over time shows that the 

cost of producing ethanol in Brazil has been steadily declining due to efficiency improvements in 

cane production and ethanol conversion processes. Between 1980 and 1998 (total span of 19 

years) ethanol cost declined by approximately 30.8%.310 This change in the cost of production 

over time in Brazil is known as the ethanol cost “Learning Curve”. 

 

310 Goldemberg, J. as sited in Rothkopf, Garten, “A Blueprint for Green Energy in the Americas,” 2006. 
 

624

 The change in ethanol costs will depend on the likely productivity gains and 

technological innovations that can be made in the future. As the majority of learning may have 

already occurred, it is likely that the decline in sugarcane ethanol costs will be less drastic in the 

future as the production process and cane practices have matured. Industrial efficiency gains are 

already at about 85% and are expected to increase to 90% in 2015.311 Most of the productivity 

growth is expected to come from sugarcane production, where yields are expected to grow from 

the current 70 tons/ha, to 96 tons/ha in 2025.312 Sugarcane quality is also expected to improve, 

with sucrose content growing from 14.5% to 17.3% in 2025.313 All productivity gains together 

could allow the increase in the production of ethanol from 6,000 liters/ha (at 85 liters/ton 

sugarcane in 2005) to 10,400 liters/ha (at 109 liters/ton sugarcane) by 2025.314 Although not 

reflected here, there could also be cost and efficiency improvements related to feedstock 

collection, storage, and distribution. 

Assuming that ethanol productivity increases to 100 liters/ton by 2015 and 109 liters/ton 

by 2025, variable sugarcane ethanol production costs are be expected to decrease to 

approximately $0.51/gal from $0.64/gal since less feedstock is needed to produce the same 

volume of ethanol using the estimates from Table VII.A.1-7, above. We assumed a linear 

decrease between data points for 2005, 2015, and 2025. Adding operating ($0.26/gal) and 

 

311 Unicamp “A Expansāo do Proalcool como Programa de Desenvolvimento Nacional”. Powerpoint presentation at 

Ethanol Seminar in BNDES, 2006. As sited in OECD, “Biofuels: Linking Support to Performance,” ITF Round 

Tables No. 138, March 2008. 

312 Ibid. 313 Ibid. 314 Ibid. 
 

625

capital costs ($0.49/gal) from Table VII.A.1-7, to a sugarcane cost of $0.51/gal, total production 

costs are $1.26/gal in 2022. 

 Brazil sugarcane producers are also expected to move from burned cane manual 

harvesting to mechanical harvesting. As a result, large amounts of straw are expected to be 

available. Costs of mechanical harvesting are lower compared to manually harvesting, therefore, 

we would expect costs for sugarcane to decline as greater sugarcane producers move to 

mechanical harvesting. However, diesel use increases with mechanical harvesting and with 

diesel fuel prices expected to increase in the future, costs may be higher than expected. 

Therefore, we have not assumed any changes to harvesting costs due to the switchover from 

manual harvesting to mechanical harvesting. 

 As more straw is expected to be collected at future sugarcane ethanol facilities, there is 

greater potential for production of excess electricity. The production costs estimates in the 

OECD study assumes an excess of 40 kWh per ton sugarcane, however, future sugarcane plants 

are expected to produce 135 kWh per ton sugarcane assuming the use of higher efficiency 

condensing-extraction steam turbine (CEST) systems and use of 40% of available straw.315

Assuming excess electricity is sold for $57 per MWh, the production of 95 kWh per ton would 

be equivalent to a credit of $0.22 per gallon ethanol produced. We have included this potential 

additional credit from greater use of bagasse and straw in our estimates at this time, calculated as 

a decrease in operating costs from $0.26 per gallon to $0.04 per gallon. 

 

315 Macedo. I.C., “Green house gases emissions in the production and use of ethanol from sugarcane in Brazil: The 

2005/2006 Averages and a Prediction for 2020,” Biomass and Bioenergy, 2008. 
 

626

 It is also important to note that ethanol production costs can increase if the costs of 

compliance with various sustainability criteria are taken into account. For instance, using 

organic or green cane production, adopting higher wages, etc. could increase production costs for 

sugarcane ethanol.316 Such sustainability criteria could also be applicable to other feedstocks, for 

example, those used in corn- or soy-based biofuel production. If these measures are adopted in 

the future, production costs will be higher than we have projected. 

In addition to production costs, there are also logistical and port costs. We used the 

report from AgraFNP to estimate such costs since it was the only resource that included both 

logistical and port costs. The total average logistical and port cost for sugarcane ethanol is 

$0.20/gal and $0.09/gal, respectively, as shown in Table VII.A.1-10. 

Table VII.A.1-10 

Imported Ethanol Cost at Port in Brazil (2006 $) 

 Logistical Costs Port Cost 

Region US ($/gal) 

US 

($/gal) 

NE Sao Paulo 0.150 0.097 

W Sao Paulo 0.210 0.097 

SE Sao Paulo 0.103 0.097 

S Sao Paulo 0.175 0.097 

 

316 Smeets E, Junginger M, Faaij A, Walter A, Dolzan P, Turkenburg W, “The sustainability of Brazilian ethanol-An 

Assessment of the possibilities of certified production,” Biomass and Bioenergy, 2008. 
 

627

N Parana 0.238 0.097 

S Goias 0.337 0.097 

E Mato Grosso do sul 0.331 0.097 

Triangulo mineiro 0.207 0.097 

NE Cost 0.027 0.060 

Sao Francisco Valley 0.193 0.060 

Average 0.197 0.089 

 Total fuel costs must also include the cost to ship ethanol from Brazil to the U.S. The 

average cost from 2006-2008 was estimated to be approximately $0.17 per gallon of ethanol.317

Costs were estimated as the difference between the unit value cost of insurance and freight (CIF) 

and the unit value customs price. The average cost to ship ethanol from Caribbean countries 

(e.g. El Salvador, Jamaica, etc.) to the U.S. from 2006-2008 was approximately $0.13 per gallon 

of ethanol. Although this may seem to be an advantage for Caribbean countries, it should be 

noted that there would be some additional cost for shipping ethanol from Brazil to the Caribbean 

country. Therefore, we assume all costs for shipping ethanol to be $0.17 per gallon regardless of 

the country importing ethanol to the U.S. 

 Total imported ethanol fuel costs (at U.S. ports) prior to tariff and tax for 2022 is shown 

in Table VII.A.1-11, at $1.50/gallon. Direct Brazilian imports are also subject to an additional 

$0.54 per gallon tariff, whereas those imports arriving in the U.S. from Caribbean Basin 

 

317 Official Statistics of the U.S. Department of Commerce, USITC 
 

628

Initiative (CBI) countries are exempt from the tariff. In addition, all imports are given an ad 

valorem tax of 2.5% for undenatured ethanol and a 1.9% tax for denatured ethanol. We assumed 

an ad valorem tax of 2.5% for all ethanol. Thus, including tariffs and ad valorem taxes, the 

average cost of imported ethanol is shown in Table VII.A.1-12 in the “Brazil Direct w/ Tax & 

Tariff” and “CBI w/ Tax” columns for 2022. 

Table VII.A.1-11 

Average Imported Ethanol Costs Prior to Tariff and Taxes in 2022 

Sugarcane 

Production 

Cost ($/gal) 

Operating 

Cost 

($/gal) 

Capital 

Cost 

($/gal) 

Logistical 

Cost 

($/gal) 

Port 

Cost 

($/gal) 

Transport 

Cost from 

Port to US 

($/gal) 

Total 

Cost 

($/gal) 

0.51 0.04 0.49 0.20 0.09 0.17 1.50 

Table VII.A.1-12 

Average Imported Ethanol Costs in 2022 

Brazil Direct 

($/gal) 

Brazil Direct w/ Tax 

& Tariff ($/gal) 

CBI 

($/gal) 

CBI w/ Tax 

($/gal) 

1.50 2.08 1.50 1.54 

 

 2. Biodiesel and Renewable Diesel Production Costs 
 

629

 Biodiesel and renewable diesel production costs are primarily a function of the feedstock 

cost, and to a much lesser extent, the capital and other operating costs of the facility. 

 a. Biodiesel 

 Biodiesel production costs for this rule were estimated using two versions of a biodiesel 

production facility model obtained from USDA, one using degummed soy oil as a feedstock and 

the other using yellow grease. The biodiesel from yellow grease model includes acid pretreatment steps required to utilize feedstocks with high free fatty acid content. 

 The production model simulates a 10 million-gallon-per-year plant operating a 

continuous flow transesterification process. USDA used the SuperPro Designer chemical 

process simulation software to estimate heat and material flowrates and equipment sizing. 

Outputs from this software were then combined in a spreadsheet with equipment, energy, labor, 

and chemical costs to generate a final estimate of production cost. The model is described in a 

2006 publication in Bioresource Technology, peer-reviewed scientific journal. 318 For the 

purpose of estimating biodiesel production cost for this rulemaking, a model with updated 

facility, labor, and chemical costs was used. Installed capital cost was $11.9 million, and energy 

prices were taken from AEO 2009: natural gas at $7.75/MMBtu and electricity at $0.066/kWh. 

Capital charge plus maintenance was assumed to be 14% of total capital per year. Table 

VII.A.2-1 shows the production cost allocation for the soy oil-to-biodiesel facility as modeled in 

the 2022 policy case. 

 

318 Haas, M.J, A process model to estimate biodiesel production costs, Bioresource Technology 97 (2006) 671-678. 
 

630

Table VII.A.2-1 

Production Cost Allocation for Soy Biodiesel for Policy Case in 2022 

Cost Category Contribution to Cost 

Soy Oil 85% 

Other Materials a 6% 

Capital & Facility 6% 

Labor 2% 

Utilities 2% 

a Includes acids, bases, methanol, catalyst 

 Soy oil costs were generated by the FASOM agricultural model (described in more detail 

in Section VIII.A). Historically, the majority of biodiesel production in the U.S. has used soy 

oil, a relatively high-value feedstock, but a growing fraction of biodiesel is being made from 

yellow grease (rendered or reclaimed oil that is not suitable for use in food products). This 

material has historically sold for about 70% of the value of virgin soy oil. However, conversion 

of yellow grease into biodiesel requires an additional acid pre-treatment step, and therefore the 

processing costs are higher than for virgin soy oil (40-50 cents/gal if feedstock costs are equal), 

reducing the attractiveness of the cheaper feedstock to some extent. Another feedstock we 

expect to be used in significant quantities in the future is distressed corn oil extracted from 

process streams that make up distillers’ grains. This material will also require processing in acid 

pre-treatment facilities, and is projected by the FASOM model to have about one half the value 

of soy oil. 
 

631

Finally, we project a small amount of algae-derived oil (or similarly advanced feedstock) 

will be used by 2022. As algal biofuel technology is still in a relatively early stage of 

development, there are many possible configurations for the production of this material and thus 

there is considerable uncertainty regarding process performance and cost. Based on work done 

by NREL at the time of this rulemaking, we assumed a production cost of $0.68/lb for this 

feedstock. 319 More details on how this estimate was made can be found in Chapter 4.1 of the 

RIA. 

 A co-product of transesterification is crude glycerin. With the upswing in worldwide 

biodiesel production in recent years, its price has been depressed in most markets. Closure of 

remaining petrochemical glycerin plants, along with development of processes to make new use 

of it as a feedstock for other commodity chemicals has provided some support for a price 

recovery. Some companies are experimenting with using glycerin as a fuel for process or facility 

heat. We expect new uses for this coproduct to continue growing to reach an equilibrium with 

supply at or near its heating value, which we estimate to be $0.15/lb. As a result, the sale of this 

material as a co-product reduces biodiesel production cost by about $0.13/gal in our control case. 

 b. Renewable Diesel 

 Renewable diesel production can occur in a few different configurations: within the 

boundaries of an existing refinery where it may or may not be coprocessed with petroleum, or at 

a stand-alone plant that may or may not be co-located with other facilities that provide utilities or 

 

319 See Technical Memo in the docket entitled “Techno-economic analysis of microalgae-derived biofuel 

production” by Ryan Davis of the National Renewable Energy Laboratory. 
 

632

hydrogen. Given changes in the tax incentives as well as current project announcements, we 

have chosen to project that all renewable diesel will be produced in stand-alone facilities, not 

coprocessing with petroleum. The 75 MMgal/yr Syntroleum facility scheduled to come online in 

Geismar, Louisiana, in 2010 is an example of such a plant. 

 Our production cost estimates used hydrogen requirements made available publicly by 

UOP, Inc. and overall project cost of $150MM taken from Syntroleum, Corp. materials. 320, 321 

The feedstock was assumed to be yellow grease or similar rendered material. Hydrogen and coproduct prices were taken from refinery modeling done for this rule, while an aggregate figure of 

$0.069/gal, derived from the UOP publication, was used to cover other variable operating costs 

besides hydrogen (includes labor, catalyst, and utilities). Cost contributions of various process 

aspects are shown in Table VII.A.2-2. More details are available in Chapter 4.1 of the RIA. 

Table VII.A.2-2 

Production Cost Allocation for Renewable Diesel for Policy Case in 2022 

Cost Category Contribution to Cost 

Feedstock 78% 

Capital & Facility 11% 

Hydrogen 7% 

Other variable costs 3% 

 

320 A New Development in Renewable Fuels: Green Diesel, AM-07-10 Annual Meeting NPRA, March 18-20, 2007. 321 Taken from Syntroleum Investor Presentation, November 5, 2009. See 

http://www.syntroleum.com/Presentations/SyntroleumInvestorPresentation.November%205.2009.FINAL.pdf 
 

633

 Table VII.A.2-3 summarizes the production costs for biodiesel and renewable diesel as 

estimated for this rule, as well as their projected volume contribution in 2022. Biodiesel made 

from yellow grease is projected to be about 10% cheaper to produce despite its higher production 

cost due to the large influence of the feedstock cost, which is about 30% lower. Biodiesel from 

extracted corn oil is expected to be significantly cheaper to produce than this, again due to the 

projected feedstock cost being about half that of soy oil. Finally, renewable diesel from standalone production is estimated in this analysis to have total production cost similar to biodiesel 

from yellow grease. However, given the business partnership between the fuel production and 

animal processing companies who have announced or are constructing the U.S. plants to date, we 

expect the feedstock being used there may be made available at a lower cost than we are 

projecting here for yellow grease. 
 

634

Table VII.A.2-3 

Summary of Cost for Biodiesel and Renewable Diesel for Policy Case in 2022 

(2007$) 

Fuel / Feedstock Feedstock Price 

($/lb) 

Fuel Production Cost 

($/gal) 

Biodiesel / soy oil 0.33 a 2.73 

Biodiesel / corn oil extraction at ethanol 

plants 

0.17 a 1.90 

Biodiesel / yellow grease or other rendered 

fats 

0.23 b 2.43 

Biodiesel / algae or other advanced virgin oil 

feedstock 

0.58 c 4.52 d

Renewable diesel / yellow grease or other 

rendered fats 

0.23 b 2.42 

a Taken from outputs of FASOM model. 

b

 Derived from outputs of FASOM model, assuming 70% value of soy oil. 

c

 Derived from figures in a Technical Memo by Ryan Davis of NREL entitled “Techno-economic analysis of 

microalgae-derived biofuel production” (available in docket). 

d

 This production cost assumes this advanced feedstock has very low free fatty acid content. 

B. Biofuel Distribution Costs

Our analysis of the costs associated with distributing the volume of biofuels that we 

project will be used under RFS2 focuses on: 1) the capital cost of making the necessary 
 

635

upgrades to the fuel distribution infrastructure system directly related to handling these fuels, and 

2) the ongoing additional freight costs associated with shipping renewable fuels to the point 

where they are blended with petroleum-based fuels.322 The following sections outline our 

estimates of the distribution costs for the additional volumes of ethanol, cellulosic distillate fuel, 

renewable diesel fuel, and biodiesel that we project would be used in response to the RFS2 

standards under the three control scenarios that we analyzed relative to the two reference 

cases.323 

A discussion of the capability of the transportation system to accommodate the volumes 

of renewable fuels projected to be used under RFS2 is contained in Section IV.C. of today’s 

preamble and 1.6 of the RIA. There will be ancillary costs associated with upgrading the basic 

rail, marine, and road transportation nets to handle the increase in freight volume due to the 

RFS2. We have not sought to quantify these ancillary costs because 1) the growth in freight 

traffic that is attributable to RFS2 represents a small fraction of the total anticipated increase in 

freight tonnage (approximately 3% of rail traffic by 2022, see Section IV.C.1), and 2) we do not 

believe there is an adequate way to estimate such non-direct costs.

1. Ethanol Distribution Costs

The capital costs to upgrade the distribution system to handle the increased volumes of 

ethanol vary substantially under the three control scenarios that we analyzed. Table VII.B.1-1 

contains our estimates of the fuel distribution infrastructure capital costs to support the use of the 

 

322 The anticipated ways that the renewable fuels projected to be used in response to the EISA will be distributed is 

discussed in Section IV.C. of today’s preamble. 

323 Please refer to Section 4.2 of the RIA for additional discussion of how these estimates were derived. 
 

636

additional ethanol that we project will be used under the three use scenarios by 2022 relative to 

the RFS1 reference case forecast of 7.05 BGY.324 The total estimated capital costs under our 

primary case are estimated at $7.90 billion which when amortized equates to approximately 6 

cents per gallon of the additional ethanol volume that would be used in 2022 in response to the 

RFS2 standards relative to the RFS1 reference case.325 Capital costs under the low-ethanol and 

high-ethanol scenarios are estimated at $5.47 billion and $11.92 billion respectively. This 

equates to 6 and 5 cents per gallon respectively relative to the RFS1 reference case. 

 

324 See Section IV.C. of today’s preamble for discussion of the upgrades we project will be needed to the distribution 

system to handle the increase in ethanol volumes under EISA. The derivation of these estimates is discussed in 

Section 4.2 of the RIA. 

325 These capital costs will be incurred incrementally through 2022 as ethanol volumes increase. Capital costs for 

tank trucks were amortized over 10 years with a 7% cost of capital. Other capital costs were amortized over 15 

years with a 7% return on capital. 
 

637

Table VII.B.1-1 

Estimated Ethanol Distribution Infrastructure Capital Costs 

Under the RFS1 Reference Case 

Million $ 

Low-Ethanol 

Scenario 

Primary 

Scenario 

High-Ethanol 

Scenario 

Fixed Facilities

Marine Import Facilities 

Marine Facilities for Shipment Inside US 

Unit Train Receipt Facilities 

Manifest Rail Receipt Facilities 

Petroleum Terminals 

 Terminal Storage Tanks 

 Blending & Misc. Equipment 

E85 Retail 

 49 

 98 

 444 

 15 

 859 

1,006 

1,957 

 53 

 130 

 586 

 20 

1,243 

1,064 

3,293 

 63 

 186 

 838 

 28 

2,073 

1,144 

4,973 

Mobile Facilities

Rail Cars 

Barges 

Tank Trucks 

 884 

 53 

 107 

1,279 

 77 

 154 

2,218 

 133 

 268 

Total Capital Costs (Million $) 5,471 7,898 11,922 

Total Capital Costs 

(cents per gallon ethanol) 

6 6 5 
 

638

Table VII.B.1-2 contains our estimates of the fuel distribution infrastructure costs to 

support the use of the additional ethanol that we project will be used under the three use 

scenarios by 2022 relative to the AEO reference case forecast of 13.18 BGY. The total estimated 

capital costs under our primary case are estimated at $5.50 billion which when amortized equates 

to approximately 7 cents per gallon of the additional ethanol volume that would be used in 2022 

in response to the RFS2 standards relative to the AEO reference case. Capital costs under the 

low-ethanol and high-ethanol scenarios are estimated at $3.02 billion and $9.93 billion 

respectively. This equates to 8 and 6 cents per gallon respectively relative to the AEO reference 

case. 
 

639

Table VII.B.1-2 

Estimated Ethanol Distribution Infrastructure Capital Costs 

Under the AEO Reference Case 

Million $ 

Low-Ethanol 

Scenario 

Primary 

Scenario 

High-Ethanol 

Scenario 

Fixed Facilities

Marine Import Facilities 

Marine Facilities for Shipment Inside US 

Unit Train Receipt Facilities 

Manifest Rail Receipt Facilities 

Petroleum Terminals 

 Terminal Storage Tanks 

 Blending & Misc. Equipment 

E85 Retail 

 49 

 76 

 238 

 7 

 355 

 345 

1,526 

 53 

 100 

 434 

 12 

 739 

 411 

2,863 

 63 

 144 

 748 

 21 

 

1,568 

 503 

4,893 

Mobile Facilities

Rail Cars 

Barges 

Tank Trucks 

 309 

 16 

 68 

 522 

 28 

 103 

1,133 

 63 

 194 

Total Capital Costs (Million $) 3,025 5,505 9,935 

Total Capital Costs 

(cents per gallon ethanol) 

8 7 6 
 

640

We estimate that ethanol freight costs under the primary and high-ethanol scenarios 

would be 13 cents per gallon on a national average basis. Ethanol freight costs under the highethanol scenario are estimated at 12 cents per gallon. These estimates are based on an analysis 

conducted for EPA by Oak Ridge National Laboratory (ORNL) which were modified to reflect 

projected higher transportation fuel costs in the future, the likely installation of fewer unit train 

receipt facilities than that projected by ORNL based on industry comments, and to conform to 

the ethanol volumes under the three control scenarios analyzed in today’s rule.326 The ORNL 

analysis contains detailed projections of which transportation modes and combination of modes 

(e.g. unit train to barge) are best suited for delivery of ethanol to specific markets considering 

ethanol source and end use locations, the current configuration and projected evolution of the 

distribution system, and cost considerations for the different transportation modes. 

Summing the freight and capital costs estimates results in an estimate of 19 cents per 

gallon for ethanol distribution costs for our primary and low-ethanol scenarios under the RFS1 

reference case. Total ethanol distribution costs under the RFS1 reference case for the highethanol scenario are estimated at 17 cents per gallon. Under the AEO reference case, total 

ethanol distribution costs are estimated at 21, 20, and 18 cents per gallon respectively for the 

low-ethanol, primary, and high-ethanol scenarios. 

 As discussed in Section IV.C. of today’s preamble, ASTM International is considering a 

change to specification on the minimum ethanol content in E85 to facilitate the manufacture of 

 

326 “Analysis of Fuel Ethanol Transportation Activity and Potential Distribution Constraints”, prepared for EPA by 

Oak Ridge National Laboratory, March 2009. The ORNL analysis indicates that ethanol freight costs decrease 

somewhat with increasing ethanol volume. See Section 4.2 of the RIA for additional discussion of the estimation of 

ethanol freight costs. 
 

641

E85 at terminals which meets minimum volatility specifications using commonly-available 

finished gasoline. If the current difficulties in blending E85 to meet minimum volatility 

specifications can not be resolved by lowering the minimum ethanol concentration of E85, high 

vapor pressure blendstocks will need to be supplied to approximately two thirds of petroleum 

terminals for blending with E85.327 This would necessitate the installation of new 

blending/storage equipment at petroleum terminals and additional butane tank cars and tank 

trucks. The capital costs for such facilities would be $2.2 billion, $1.4 billion, and $0.6 billion 

under the high-ethanol, primary, and low-ethanol scenarios respectively under both reference 

cases. By amortizing these capital costs and adding in butane freight costs, we estimate that the 

need to supply special blendstocks at terminals for E85 blending would add approximately 1 cent 

per gallon to ethanol distribution costs for all three analysis scenarios relative to the RFS1 

reference case. Relative to the AEO reference case, the additional cost would be approximately 

2 cents per gallon under the primary and low-ethanol scenarios, and approximately 1 cent per 

gallon under the high-ethanol scenario. 

 In the NPRM, we estimated that half of the new ethanol rail receipt capability needed to 

support the use of the projected ethanol volumes under the EISA would be installed at petroleum 

terminals, and half would be installed at rail terminals. Based on input from industry and a study 

conducted for us by ORNL, we now believe that all unit train receipt facilities will be installed at 

new dedicated locations.328 This change results in the need for additional tank truck receipt 

equipment at terminals and additional tank trucks to carry ethanol from rail to petroleum 

 

327 If this is the case, EPA would need to reconsider its policies regarding what blendstocks can be used at petroleum 

terminals in the manufacture of E85. 

328 “Analysis of Fuel Ethanol Transportation Activity and Potential Distribution Constraints”, prepared for EPA by 

Oak Ridge National Laboratory (ORNL), March 2009. 
 

642

terminals compared to the NPRM. However, we also received additional input from industry on 

the cost of unit train facilities which indicates that such facilities are not as costly as we projected 

in the NPRM. We also increased the average E85 facility cost relative to the NPRM to reflect 

the likely need for additional E85 dispensers and a larger underground storage tank to maintain 

sufficient throughput per facility.329 

 2. Cellulosic Distillate and Renewable Diesel Distribution Costs

We chose to evaluate the distribution costs for cellulosic distillate and renewable diesel 

together because the same considerations apply to their handling in the fuel distribution system 

and because the projected volume of renewable diesel fuel is relatively small. 

Table VII.B.2-1 contains our estimates of the fuel distribution infrastructure capital costs 

to support the use of the cellulosic distillate and renewable diesel fuel that we project will be 

used under the three use scenarios by 2022 under the RFS1 reference case.330 The total 

estimated capital costs by 2022 under our primary and low-ethanol scenarios are estimated at 

$1.38 billion and $2.00 billion respectively under the RFS1 reference case. 

 

329 This is a sensitivity case that was evaluated in the NPRM. 330 See Section IV.C. of today’s preamble for discussion of the upgrades we project will be needed to the distribution 

system to handle the increase in ethanol volumes under EISA. The derivation of these estimates is discussed in 

Section 1.6 of the RIA. 
 

643

Table VII.B.2-1 

Estimated Cellulosic Distillate Fuel Distribution Infrastructure Capital Costs 

Under the RFS1 Reference Case 

Million $ 

Low-Ethanol 

Scenario 

Primary 

Scenario 

High-Ethanol 

Case 

Fixed Facilities

Marine Facilities for Shipment Inside US 

Unit Train Receipt Facilities 

Manifest Rail Receipt Facilities 

Petroleum Terminals 

 Terminal Storage Tanks 

 Blending & Misc. Equipment 

 87 

 394 

 13 

 218 

 361 

 56 

 253 

 8 

 154 

 252 

- 

- 

- 

- 

- 

Mobile Facilities

Rail Cars 

Barges 

Tank Trucks 

 784 

 47 

 95 

 552 

 33 

- 

- 

- 

- 

Total Capital Costs (Million $) 1,999 1,375 NA 

Total Capital Costs 

(cents per gallon of cellulosic distillate fuel) 

2 2 NA 

 
 

644

Table VII.B.2-2 contains our estimates of the infrastructure changes and associated 

capital costs to support the use of the cellulosic distillate and renewable diesel fuel that we 

project will be used under the three use scenarios by 2022 under the AEO reference case. Total 

capital costs are estimated at $1.02 and $1.46 billion for the primary and low-ethanol scenarios 

respectively under the AEO reference case. The difference in estimated capital costs for the two 

control scenarios under the two reference scenarios is obscured by rounding when translating 

these costs to a cents-per-gallon basis. When amortized, these capital costs equate to 

approximately 2 cents per gallon for both control scenarios under both reference cases.331

 

331 These capital costs will be incurred incrementally through 2022 as ethanol volumes increase. Capital costs for 

tank trucks were amortized over 10 years with a 7% cost of capital. Other capital costs were amortized over 15 

years with a 7% return on capital. 
 

645

Table VII.B.2-2 

Estimated Cellulosic Distillate Fuel Distribution Infrastructure Capital Costs 

Under the AEO Reference Case 

Million $ 

Low-Ethanol 

Scenario 

Primary 

Scenario 

High-Ethanol 

Case 

Fixed Facilities

Marine Facilities for Shipment Inside US 

Unit Train Receipt Facilities 

Manifest Rail Receipt Facilities 

Petroleum Terminals 

 Terminal Storage Tanks 

 Blending & Misc. Equipment 

 67 

 511 

 15 

 218 

 304 

 43 

 315 

 9 

 154 

 223 

- 

- 

- 

- 

- 

Mobile Facilities

Rail Cars 

Barges 

Tank Trucks 

 784 

 47 

 90 

 552 

 33 

 63 

- 

- 

- 

Total Capital Costs (Million $) 2,036 1,392 NA 

Total Capital Costs 

(cents per gallon of cellulosic distillate fuel) 

2 2 NA 
 

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We estimate that cellulosic distillate freight costs would be 13 cents per gallon on a 

national average basis under both the primary and low-ethanol scenarios. This estimate is based 

on the application to cellulosic distillate freight costs of an analysis conducted for EPA by Oak 

Ridge National Laboratory (ORNL) of ethanol freight costs.332 The underlying premise is that 

both ethanol and cellulosic distillate fuel would be handled by the same types of distribution 

facilities on the journey to petroleum terminals.333 Summing the freight and capital costs results 

in an estimated 15 cents per gallon in total distribution costs for both the primary and lowethanol scenarios under both reference cases. 

The ethanol and cellulosic distillate distribution cost estimates are based on the 

projections of the location of biofuel production facilities and end use areas contained in the 

NPRM. The extent to which new biofuel production facilities are more dispersed than projected 

in the NPRM, distribution costs for ethanol from new production facilities and for all cellulosic 

distillate facilities may tend be lower than those projected by this analysis as the fuel has more 

opportunity to be used locally. This would potentially be a greater benefit in lowering cellulosic 

distillate distribution costs than overall ethanol distribution costs given the large number of 

ethanol production facilities currently located in the Midwest. Cellulosic distillate costs should 

also tend to be lower than those for ethanol because cellulosic distillate fuel blends are 

compatible with existing petroleum distribution equipment, whereas there are special 

considerations associated with the distribution of ethanol. The most notable of these 

considerations is the need for special fuel retail equipment for E85 (as evidenced in Table 

 

332 “Analysis of Fuel Ethanol Transportation Activity and Potential Distribution Constraints”, prepared for EPA by 

Oak Ridge National Laboratory, March 2009. See Section 4.2 of the RIA for additional discussion of the estimation 

of cellulosic distillate freight costs. 

333 The same unit train and manifest rail receipt facilities would be used to handle shipments of both fuels. 
 

647

VII.B.1-1). Thus, the cellulosic distillate distribution costs estimated here are likely to be 

conservative. 

 3. Biodiesel Distribution Costs

Table VII.B.3-1 contains our estimates of the infrastructure changes and associated 

capital costs to support the use of the additional biodiesel that we project will be used under 

RFS2 by 2022 relative to the RFS reference case of 300 MGY by 2022.334 The total capital 

costs are estimated at $1.2 billion which equates to approximately 10 cents per gallon of 

additional biodiesel volume.335 

 

 

334 We project that by 2022 300 MGY of biodiesel would be used under the RFS1 reference case, 380 MGY of 

biodiesel would be used under the RFS reference case and that a total of 1.67 BGY of biodiesel would be used under 

the EISA. Biodiesel use is projected to be the same under all three of analysis scenarios. 

335 These capital costs will be incurred incrementally through 2022 as biodiesel volumes increase. Capital costs for 

tank trucks were amortized over 10 years with a 7% cost of capital. Other capital costs were amortized over 15 

years with a 7% return on capital. 
 

648

Table VII.B.3-1 

Estimated Biodiesel Distribution Infrastructure Capital Costs 

Under the RFS1 Reference Case 

 Million $ 

Fixed Facilities

Petroleum Terminals 

 Storage Tanks 

 Blending & Misc. Equipment 

 411 

 612 

Mobile Facilities

Rail Cars 

Barges 

Tank Trucks 

 111 

 53 

 25 

Total Capital Costs (Million $) 1,212 

Total Capital Costs 

(cents per gallon of biodiesel) 

10 

Table VII.B.3-2 contains our estimates of the infrastructure changes and associated 

capital costs to support the use of the additional biodiesel that we project will be used under 

RFS2 by 2022 relative to the AEO reference case of 380 MGY. The total capital costs are 

estimated at $1.1 billion which equates to approximately 10 cents per gallon of additional 

biodiesel volume. 

 
 

649

Table VII.B.3-2 

Estimated Biodiesel Distribution Infrastructure Capital Costs 

Under the AEO Reference Case 

 Million $ 

Fixed Facilities

Petroleum Terminals 

 Storage Tanks 

 Blending & Misc. Equipment 

 387 

 576 

Mobile Facilities

Rail Cars 

Barges 

Tank Trucks 

 105 

 50 

 24 

Total Capital Costs (Million $) 1,141 

Total Capital Costs 

(cents per gallon of biodiesel) 

10 

We estimate that biodiesel freight costs would be 10 cents per gallon on a national 

average basis. State biodiesel use requirements and biodiesel production locations were taken 

into account in formulating this estimate.336 The biodiesel blend ratio was estimated to vary 

between 2 and 5%. Adding the estimated freight costs to the amortized capital costs results in an 

 

336 See Section 4.2 of the RIA for a discussion of our derivation of biodiesel distribution costs. 
 

650

estimate of total biodiesel distribution costs of 20 cents per gallon under both the RFS1 and AEO 

reference cases. 

C. Reduced U.S. Refining Demand 

 As renewable and alternative fuel use increases, the volume of petroleum-based products, 

such has gasoline and diesel fuel, would decrease. This reduction in finished refinery petroleum 

products results in reduced refinery industry costs. The reduced costs would essentially be the 

volume of fuel displaced multiplied by the cost for producing the fuel. There is also a reduction 

in capital costs as investment in new refinery capacity is displaced by investments in renewable 

and alternative fuels capacity. 

 Although we conducted refinery modeling for estimating the cost of blending ethanol 

(see Section VII.B), we did not rely on the refinery model results for estimating the volume of 

displaced petroleum as other economic factors also come into play. Instead we conducted an 

energy balance around the increased use of renewable fuels, estimating the energy-equivalent 

volume of gasoline or diesel fuel displaced. This allowed us to more easily apply our best 

estimates for how much of the petroleum would displace imports of finished products versus 

crude oil for our energy security analysis which is discussed in Section VIII.B of this preamble. 

 As part of this petroleum displacement analysis, we accounted for the change in 

petroleum demanded by upstream processes related to additional production of the renewable 

fuels as well as reduced production of petroleum fuels. For example, growing corn used for 
 

651

ethanol production requires the use of diesel fuel in tractors, which reduces the volume of 

petroleum displaced by the ethanol. Similarly, the refining of crude oil uses by-product 

hydrocarbons for heating within the refinery, therefore the overall effect of reduced gasoline and 

diesel fuel consumption is actually greater because of the additional upstream effect. We used 

the lifecycle petroleum demand estimates provided for in the GREET model to account for the 

upstream consumption of petroleum for each of the renewable and alternative fuels, as well as 

for gasoline and diesel fuel. Although there may be some renewable fuel used for upstream 

energy, we assumed that this entire volume is petroleum because the volume of renewable and 

alternative fuels is fixed by the RFS2 standard. 

 We assumed that a portion of the gasoline displaced by ethanol would have been 

produced from domestic refineries causing reduced demand from US refineries, while the rest of 

the additional ethanol displaces imported gasoline or gasoline blendstocks which does not affect 

domestic refining sector costs. To estimate the portion of new ethanol which displaces US 

refinery production we relied on some Markal refinery modeling conducted for us by DOE. The 

Markal refinery model models all the refinery sectors of the world and thus can do a fair job 

estimating how renewable fuels would impact imports of finished gasoline and gasoline 

blendstocks. The Markal refinery model estimated that 2/3rds of a reduction in petroleum 

gasoline demand would be met by a reduction in imported gasoline or gasoline blendstocks, 

while the other 1/3rd would be met by reduced refining production by the US refining sector. In 

the case of biodiesel and renewable diesel, all of it is presumed to offset domestic diesel fuel 

production. For ethanol, biodiesel and renewable diesel, the amount of petroleum fuel displaced 

is estimated based on the relative energy contents of the renewable fuels to the fuels which they 
 

652

are displacing. The savings due to lower imported gasoline and diesel fuel is accounted for in 

the energy security analysis contained in Section VIII.B. 

 For estimating the U.S. refinery industry cost reductions, we multiplied the estimated 

volume of domestic gasoline and diesel fuel displaced by the projected wholesale price for each 

of these fuels in 2022, which are $3.42 per gallon for gasoline, and $3.83 per gallon for diesel 

fuel. For the volume of petroleum displaced upstream, we valued it using the wholesale diesel 

fuel price. Table VII.C-1 shows the net volumetric impact on the petroleum portion of gasoline 

and diesel fuel demand, as well as the reduced refining industry costs for 2022. 

Table VII.C-1 

Changes in U.S. Refinery Industry Volumes and Costs for Increased Renewable Fuel Volumes 

in 2022 Relative to the AEO 2007 Reference Case 

(2007 dollars) 

Low Ethanol 

Case

Primary Case 

(mid-ethanol case)

High Ethanol Case

 Bil 

Gals 

Bil $ Bil 

Gals 

Bil $ Bil 

Gals 

Bil $ 

Upstream Petroleum 0.34 1.3 0.34 1.3 0.33 1.3 

End Use Gasoline -0.9 -3.1 -2.0 -6.8 -4.4 -15.0 

Diesel 

Fuel 

-10.1 -38.7 -7.5 -28.7 -1.3 -5.0 

 Total -10.7 -40.5 -9.2 -34.2 -5.4 -18.7 
 

653

 For the primary control case relative to the AEO 2007 reference case, this analysis 

estimates that the increased volumes of renewable fuel would reduce the gasoline and diesel fuel 

production volume of US refineries by 9.2 billion gallons in 2022, which would reduce their raw 

material purchases and production costs by $34 billion dollars. Accounting for all the petroleum 

displaced (domestic and foreign), the increased volumes of renewable fuel caused by the RFS 2 

fuels program are estimated to reduce gasoline and diesel fuel demand by 13.2 billion gallons. 

D. Total Estimated Cost Impacts 

 The previous sections of this chapter presented estimates of the cost of producing and 

distributing corn-based and cellulosic-based ethanol, cellulosic diesel fuel, imported ethanol, 

biodiesel, and renewable diesel. In this section, we briefly summarize the methodology used and 

the results of our analysis to estimate the cost and other implications for increased use of 

renewable fuels to displace gasoline and diesel fuel. An important aspect of this analysis is 

refinery modeling which primarily was used to estimate the costs of blending ethanol into 

gasoline, as well as the overall refinery industry impacts of the fuel program. A detailed 

discussion of how the renewable fuel volumes affect refinery gasoline production volumes and 

cost is contained in Chapter 4 of the RIA. 

 1. Refinery Modeling Methodology

 The refinery modeling was conducted in three distinct steps. The first step involved the 

establishment of a 2004 base case which calibrated the refinery model against 2004 volumes, 
 

654

gasoline quality, and refinery capital in place. The EPA and ASTM fuel quality constraints in 

effect by 2004 are imposed on the products. 

 For the second step, we established two year 2022 future year reference cases which 

based their energy demand off of the 2009Annual Energy Outlook (AEO). One of the reference 

cases assumes business-as-usual demand growth from the AEO 2007 reference case discussed in 

Section IV.A.1. The other utilized the RFS1 reference case. The refinery modeling results are 

based on $116 per barrel crude oil prices which are the 2022 projected prices by EIA in its 2009 

AEO. We also modeled the implementation of several new environmental programs that will 

have required changes in fuel quality by 2022, including the 30 part per million (ppm) average 

gasoline sulfur standard, the 15 ppm cap standards on highway and nonroad diesel fuel, the 

Mobile Source Air Toxics (MSAT) 0.62 volume percent benzene standard. We also modeled the 

implementation of EPAct of 2005, which by rescinding the reformulated gasoline oxygenate 

standard, resulted in the discontinued use of MTBE, and a large increase in the amount of 

ethanol blended into reformulated gasoline. We also modeled the EISA Energy Bill corporate 

average fuel economy (café) standards in the reference case because it will be phasing-in, and 

affect the phase-in of the RFS2. 

 The third step, or the control cases, involved the modeling of three different possible 

renewable fuels volumes. The three different volumes were designed to capture the additional 

use of corn ethanol and biodiesel and a range of cellulosic ethanol and cellulosic diesel fuel 

volumes. The volumes that we assessed in our analysis are summarized in Section IV.A above 
 

655

 The price of ethanol and E85 used in the refinery modeling is a critical determinant of the 

overall economics of using ethanol. Ethanol was priced initially based on the historical average 

price spread between regular grade conventional gasoline and ethanol, but then adjusted postmodeling to reflect the projected production cost for both corn and cellulosic-based ethanol. The 

refinery modeling assumed that all ethanol added to gasoline for E10 is match-blended for octane 

by refiners in the reference and control cases. For the control case, E85 was assumed to be 

priced lower than gasoline to reflect its lower energy content, longer refueling time and lower 

availability (see Chapter 4 of the RIA for a detailed discussion for how we projected E85 prices). 

For the refinery modeling, E85 was assumed to be blended with gasoline blendstock designed for 

blending with E10, and with butane to bring the RVP of E85 up to that allowed by ASTM 

International standards for E85. Thus, unlike current practices today where E85 is blended at 

85% in the summer and E70 in the winter, we assumed that E85 is blended at 85% year-round. 

As E85 specifications are still under consideration by ASTM, this assumption may differ from 

future procedures. E85 use in any one market is limited to levels which we estimated would 

reflect the ability of FFV vehicles in the area to consume the E85 volume. Our costs also include 

the incremental costs of producing flexible fuel vehicles (FFVs) over that of conventionally 

fueled vehicles. 

 The refinery model was provided some flexibility and also was constrained with respect 

to the applicable gasoline volatility standards for blending up E10. The refinery model allowed 

conventional gasoline and most low RVP control programs to increase by 1.0 pounds per square 

inch (psi) in Reid Vapor Pressure (RVP) waiver during the summer. However, wintertime 

conventional gasoline was assumed to comply with the wintertime ASTM RVP and 
 

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Volume/Liquid (V/L) standards. 

 

 The costs for producing, distributing and using biodiesel and renewable diesel are 

accounted for outside the refinery modeling. Their production and distribution costs are 

estimated first, compared to the costs of producing diesel fuel, and then are added to the costs 

estimated by the refinery cost model for blending the ethanol. 

 2. Overall Impact on Fuel Cost

 Utilizing the refinery modeling output conducted for today’s final rule, we calculated the 

costs for each control case, which represented the three different renewable fuels scenarios in 

2022, relative to the AEO 2007 and RFS1 reference cases. The costs are reported separately for 

blending ethanol into gasoline, as E10 and E85, and for blending cellulosic diesel fuel, biodiesel 

and renewable diesel into petroleum-based diesel fuel. These costs do not include the biofuel 

consumption tax subsidies. The costs are based on 2007 dollars and the capital costs are 

amortized at seven percent return on investment (ROI) before taxes. 

 

 Tables VII.D.2-1 and VII.D.2-2 summarize the costs for each of the three control cases, 

including the aggregated total for all the fuel changes and the per-gallon costs, relative to the 

AEO 2007 and RFS1 reference cases, respectively. This estimate of costs reflects the changes in 

gasoline that are occurring with the expanded use of renewable and alternative fuels. These costs 

include the labor, utility and other operating costs, fixed costs and the capital costs for all the fuel 

changes expected. These cost estimates do not account for the various tax subsidies. The per-
 

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gallon costs are derived by dividing the total costs over all U.S. gasoline and diesel fuel projected 

to be consumed in 2022. These costs are only for the incremental renewable fuel volumes 

beyond the volumes modeled in the two reference cases. 

Table VII.D.2-1 

Estimated Fuel Costs of Increased Volumes of Renewable Fuel in 2022 

Incremental to the AEO2007 Reference Case 

(2007 dollars, 7% ROI before taxes) 

 Low Ethanol Case Primary Case 

(mid-ethanol case) 

High Ethanol Case 

Gasoline $billion/yr -0.67 -3.31 -5.90 

Impacts c/gal -0.48 -2.35 -4.08 

Diesel Fuel $billion/yr -11.7 -8.5 -1.27 

Impacts c/gal -16.4 -12.1 -1.79 

Total Impact $billion/yr -12.4 -11.8 -7.17 

Incremental to the AEO 2007 reference case, our analysis shows that for the low ethanol 

case which models mostly cellulosic diesel instead of cellulosic ethanol, the gasoline and diesel 

fuel costs are projected to decrease by $0.7 billion and $11.70 billion, respectively, for a total 

savings of $12.4 billion. Expressed as per-gallon costs, these fuel changes would decrease the 

cost of producing gasoline and diesel fuel by 0.5 and 16.4 cents per gallon, respectively. 

 For our primary case which models a mix of cellulosic diesel fuel and cellulosic ethanol, 

the gasoline and diesel fuel costs are projected to decrease by $3.3 billion and $8.5 billion, 
 

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respectively, for a total savings of $11.8 billion. Expressed as per-gallon costs, these fuel 

changes would decrease the cost of producing gasoline and diesel fuel by 2.4 and 12.1 cents per 

gallon, respectively. 

 For the high ethanol case where the cellulosic biofuel is cellulosic ethanol (as in the 

proposal), the gasoline and diesel fuel costs are projected to decrease by $5.9 billion and $1.3 

billion, respectively, for a total savings of $7.2 billion. Expressed as per-gallon costs, these fuel 

changes would decrease the cost of producing gasoline and diesel fuel by 4.1 and 1.8 cents per 

gallon, respectively. 

 Crude oil prices have been very volatile over the last several years which raises 

uncertainty about future crude oil prices. Because our cost model was created to be able to 

assess the cost of the program at a higher crude oil price, we can also assess the cost at other 

crude oil prices. As a sensitivity, we varied crude oil prices in our model to find the break-even 

(no cost) point of the RFS2 program. Using our cost model we estimate that, for the primary 

control case relative to the AEO 2007 reference case, the RFS2 program (total of gasoline and 

diesel fuel costs) would break-even at a 2022 crude oil price of $88 per barrel. Thus, in 2022 if 

crude oil is priced lower than $88 per barrel, the RFS2 program would cost money; if crude oil is 

priced higher than $88 per barrel, the RFS2 program would result in a cost savings. 
 

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Table VII.D.2-2 

Estimated Fuel Costs of Increased Volumes of Renewable Fuel in 2022 

 Incremental to the RFS1 Reference Case 

(2007 dollars, 7% ROI before taxes) 

 Low Ethanol Case Primary Case 

(mid-ethanol case) 

High Ethanol Case 

Gasoline $billion/yr -3.12 -5.63 -7.79 

Impacts c/gal -2.24 -4.00 -5.38 

Diesel Fuel $billion/yr -11.7 -8.6 -1.35 

Impacts c/gal -16.5 -12.1 -1.90 

Total Impact $billion/yr -14.8 -14.2 -9.14 

 Incremental to the RFS1 reference case, our analysis shows that for the low ethanol case 

which models mostly cellulosic diesel instead of cellulosic ethanol, the gasoline and diesel fuel 

costs are projected to decrease by $3.1 billion and $11.70 billion, respectively, for a total savings 

of $14.8 billion. Expressed as per-gallon costs, these fuel changes would decrease the cost of 

producing gasoline and diesel fuel by 2.4 and 16.5 cents per gallon, respectively. 

 For our primary case which models a mix of cellulosic diesel fuel and cellulosic ethanol, 

the gasoline and diesel fuel costs are projected to decrease by $5.6 billion and $8.6 billion, 

respectively, for a total savings of $14.2.billion. Expressed as per-gallon costs, these fuel 

changes would decrease the cost of producing gasoline and diesel fuel by 4.0 and 12.1 cents per 

gallon, respectively. 
 

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 For the high ethanol case where the cellulosic biofuel is cellulosic ethanol (as in the 

proposal), the gasoline and diesel fuel costs are projected to decrease by $7.8 billion and $1.4 

billion, respectively, for a total savings of $9.1 billion. Expressed as per-gallon costs, these fuel 

changes would decrease the cost of producing gasoline and diesel fuel by 5.4 and 1.9 cents per 

gallon, respectively. 

 Both the gasoline and diesel fuel costs are negative because of the relatively high crude 

oil prices estimated by EIA for the year 2022. Given the higher projected crude oil prices and 

these savings, it is difficult to quantify how much of the increase in renewable fuels and the 

associated savings is due to the RFS 2 program versus what would have happened regardless in 

the marketplace. However, even with the high crude oil prices as projected by EIA, some or 

perhaps even most of the investments in these emerging renewable fuels technologies may not 

occur without the RFS 2 program in place. The reason for this is that investors are hesitant to 

invest in emerging technologies when the threat remains for a drop in the price of crude oil 

leaving their investment dollars stranded. The RFS2 program provides certainty for investors to 

invest in renewable fuel technologies. 

There are two important reasons why the diesel fuel costs are more negative than the 

gasoline costs when comparing the low ethanol case (high cellulosic diesel case) to the high 

ethanol case: 1) cellulosic ethanol costs include the costs for fuel flexible vehicles, while 

vehicles using cellulosic diesel fuel are not expected to require any vehicle modifications, hence 

there is no additional estimated cost, 2) the crude oil price adjustment based on crude oil and 
 

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finished gasoline and diesel fuel price data from 2002 to 2008 increases the estimated production 

cost for petroleum diesel fuel more so than for gasoline – therefore cellulosic diesel shows a 

greater cost savings. If the diesel fuel prices do not increase more than gasoline prices with 

higher crude oil prices, then the significantly higher savings for renewable diesel fuel over that 

for renewable ethanol would be less than that modeled here. 

 The increased use of renewable and alternative fuels would require capital investments in 

corn and cellulosic ethanol plants, and renewable diesel fuel plants. In addition to producing the 

fuels, storage and distribution facilities along the whole distribution chain, including at retail, 

will have to be constructed for these new fuels. Conversely, as these renewable and alternative 

fuels are being produced, they supplant gasoline and diesel fuel demand which results in less 

new investments in refineries compared to business-as-usual. In Table VII.D.2-3, we list the 

total incremental capital investments that we project would be made for this RFS2 rulemaking 

incremental to the RFS1 reference case (refer to Chapter 4 of the RIA for more detail). 
 

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Table VII.D.2-3 

Total Projected U.S. Capital Investments to Meet the Increased Volumes of Renewable Fuel 

(incremental to the AEO 2007 reference case, billion dollars) 

Cost Type Plant Type Low Ethanol 

Case

Primary Case 

(mid-ethanol 

case)

High Ethanol 

Case

Corn Ethanol 3.9 3.9 3.9 

Cellulosic Ethanol 0 14.3 48.3 

Cellulosic Diesel a 96.5 68.0 0 

Production 

Costs 

Renewable Diesel and 

Algae 

1.1 1.1 1.1 

All Ethanol 5.6 8.2 11.9 

Cellulosic and 

Renewable Diesel Fuel 

2.0 1.4 - 

Distribution 

Costs 

Biodiesel 1.2 1.2 1.2 

 FFV Costs 0.8 1.8 6.1 

 Refining -10.7 -9.4 -4.1 

Total Capital Investments 110.4 90.5 68.4 

a Cellulosic diesel fuel is assumed to be produced by BTL plants which is a very capital intensive technology. If 

some or even most of this volume comes from other cellulosic diesel fuel technologies which are less capital 

intensive, the capital costs attributed to cellulosic diesel would be much lower. 

 Table VII.D.2-3 shows that the total U.S. capital investments attributed to this program 
 

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ranges from $71 to $111 billion in 2022 for the high ethanol to low ethanol cases. The capital 

investments made for renewable fuels technologies are much more than the decrease in refining 

industry capital investments because 1) a large part of the decrease in petroleum gasoline supply 

was from reduced imports, 2) renewable fuels technologies are more capital intensive per gallon 

of fuel produced than incremental increases in gasoline and diesel fuel production at refineries, 

and 3) ethanol and biodiesel require considerable distribution and retail infrastructure 

investments.
 

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VIII. Economic Impacts and Benefits 

A. Agricultural and Forestry Impacts 

EPA used two principal tools to model the potential domestic and international 

impacts of the RFS2 on the U.S. and global agricultural sectors. The Forest and 

Agricultural Sector Optimization Model (FASOM), developed by Professor Bruce 

McCarl of Texas A&M University and others, provides detailed information on the 

domestic agricultural and forestry sectors, as well as greenhouse gas impacts of 

renewable fuels. The Food and Agricultural Policy Research Institute (FAPRI) at Iowa 

State University and the University of Missouri-Columbia maintains a number of 

econometric models that are capable of providing detailed information on impacts on 

international agricultural markets from the wider use of renewable fuels in the U.S. EPA 

worked directly with the Center for Agriculture and Rural Development (CARD) at Iowa 

State University to implement the FAPRI model to analyze the impacts of the RFS2 on 

the global agriculture sector. Thus, this model will henceforth be referred to as the 

FAPRI-CARD model. 

 FASOM is a long-term economic model of the U.S. agriculture and forestry 

sectors that attempts to maximize total revenues for producers while meeting the 

demands of consumers. FASOM can be utilized to estimate which crops, livestock, 

forest stands, and processed agricultural and forestry products would be produced in the 

U.S. given RFS2 biofuel requirements. In each model simulation, crops compete for 
 

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price sensitive inputs such as land and labor at the regional level and the cost of these and 

other inputs are used to determine the price and level of production of primary 

commodities (e.g., field crops, livestock, and biofuel products). FASOM also estimates 

prices using costs associated with the processing of primary commodities into secondary 

products (e.g., converting livestock to meat and dairy, crushing soybeans to soybean meal 

and oil, etc.). FASOM does not capture short-term fluctuations (i.e., month-to-month, 

annual) in prices and production, however, as it is designed to identify long-term trends 

(i.e., five to ten years). 

There are a few notable changes that have been made to both the FASOM and 

FAPRI-CARD models, as well as to some of the underlying assumptions used in the 

agro-economic analysis since the release of the proposed rulemaking analysis. These 

changes were made as a result of further research and consultation with experts, as well 

as in response to comments received during the public comment period following the 

release of the proposed rulemaking. In regards to the FASOM model, the first major 

change made to the model is the inclusion of the full interaction between the forestry and 

agriculture sectors, as discussed in the NPRM and supported by comments received. For 

the proposed rulemaking, the FASOM model was only capable of modeling the changes 

in the agriculture sector alone. In terms of land use, the only land use that could be 

examined was cropland and pasture use. With the incorporation of a forestry sector that 

dynamically interacts with the agriculture, we are able to examine how crop and forest 

acres compete for land in response to changes in policy. Also, similar to the agriculture 
 

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sector, the forestry sector has its own set of forestry products, including logging and 

milling residues that are available for the production of cellulosic ethanol. 

The second major change to the FASOM model is the addition of a full 

accounting of major land types in the U.S., including cropland, cropland pasture, 

forestland, forest pasture, rangeland, acres enrolled in the Conservation Reserve Program 

(CRP), and developed land. These changes address comments raised by peer reviewers 

and the general public that we should more explicitly link the interaction between 

livestock, pasture land, cropland, and forest land, as well as have a detailed accounting of 

acres in the U.S. across different land uses. Cropland is actively managed cropland, used 

for both traditional crops (e.g., corn and soybeans) and dedicated energy crops (e.g., 

switchgrass). Cropland pasture is managed pasture land used for livestock production, 

but which can also be converted to cropland production. Forestland contains a number of 

sub-categories, tracking the number of acres both newly and continually harvested 

(reforested), the number of acres harvested and converted to other land uses (afforested), 

as well as the amount of forest acres on public land. Forest pasture is unmanaged pasture 

land with varying amounts of tree cover that can be used for livestock production. A 

portion of this land may be used for timber harvest. Rangeland is unmanaged land that 

can be used for livestock grazing production. While the amount of rangeland idled or 

used for production may vary, rangeland may not be used for any other purpose than for 

cattle grazing. 
 

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A third major change in the FASOM model is the adoption of updated cellulosic 

ethanol conversion rates. We updated the cellulosic ethanol conversion rates based on 

new data provided by the National Renewable Energy Laboratory (NREL). The new 

analysis by NREL simplified and updated the conversion yields of the different types of 

feedstocks. As a result of these changes, the gallons per ton yields for switchgrass and 

several other feedstocks increased from the values used in the proposal, while the yields 

for corn residue and several other feedstocks decreased slightly from the NPRM values. 

In addition, we also updated our feedstock production yields based on new work 

conducted by the Pacific Northwest National Laboratory (PNNL).337 This analysis 

increased the tons per acre yields for several dedicated energy crops. These changes 

increased the amount of cellulosic ethanol projected to come from energy crops. 

Additional details on the FASOM model changes can be found in Chapter 5 of the RIA. 

 The FAPRI-CARD models are econometric models covering many agricultural 

commodities. These models capture the biological, technical, and economic relationships 

among key variables within a particular commodity and across commodities. They are 

based on historical data analysis, current academic research, and a reliance on accepted 

economic, agronomic, and biological relationships in agricultural production and 

markets. The international modeling system includes international grains, oilseeds, 

ethanol, sugar, and livestock models. In general, for each commodity sector, the 

economic relationship that supply equals demand is maintained by determining a marketclearing price for the commodity. In countries where domestic prices are not solved 

 

337 Thomson, A.M., R.C. Izarrualde, T.O. West, D.J. Parrish, D.D. Tyler, and J.R. Williams. 2009. 

Simulating Potential Switchgrass Production in the United States. PNNL-19072. College Park, MD: 

Pacific Northwest National Laboratory. 
 

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endogenously, these prices are modeled as a function of the world price using a price 

transmission equation. Since econometric models for each sector can be linked, changes 

in one commodity sector will impact other sectors. Elasticity values for supply and 

demand responses are based on econometric analysis and on consensus estimates. 

 As one of the largest and fastest developing countries in the world, a major 

producer and exporter of sugar ethanol, and in possession of one of the world’s largest 

carbon sinks, the Amazon, Brazil is acknowledged to be an important part of our analysis 

in terms of indirect land use change. For the proposal’s analysis, the FAPRI-CARD 

model analyzed Brazil at a national level as any other non-US nation in the model, 

covering only crop area and commodity prices. Comments and feedback received 

indicated the importance of analyzing Brazil at a regional level, given its diverse natural 

lands across the country, and to also closely examine livestock production in terms of 

land use. 

 In response to these comments, the FAPRI-CARD model now includes an 

integrated Brazil module that provides additional detail on agricultural land use in Brazil 

for six geographic regions. The new Brazil module explicitly models the competition 

between cropland and pastureland used for livestock production in each region. In 

addition, the Brazil module allows for region-specific agriculture practices such as double 

cropping and livestock intensification in response to higher commodity prices. The 

addition of the Brazil module allows for a more refined analysis of land use change and 

economic impacts in Brazil than what was able to be done for the proposal’s analysis. 
 

669

Another topic that we received comments on was in regards to price-induced 

yields. Namely that with an increase in price for a particular crop, seed producers and/or 

farmers have a greater incentive to increase yields for that particular crop in order to 

maximize revenue. In the analysis for proposal, the FAPRI-CARD model did not include 

impacts of commodity price changes on yields. For the final rulemaking, the FAPRICARD model now includes feedback from changes in commodity prices on yields. The 

elasticities for these responses are based on an econometric analysis of historical data on 

yield and price changes for various commodities. Additional details on the FAPRICARD modeling updates can be found in Chapter 5 of the RIA. 

In the NPRM, we specifically requested comments on our assumptions regarding 

distiller grain with solubles (DGS) replacement rates. For the proposal, we assumed that 

one pound of DGS replaced one pound of total of corn and soybean meal for all fed 

animals. We received numerous comments on this assumption. Many commenters 

suggested that we adopt the replacement rates included in the recent research by Argonne 

National Laboratory (ANL) and others.338 The ANL study found that one pound of DGS 

can be used to replace 1.196 pounds total of corn and soybean meal for various fed 

animals due to the higher nutritional content of DGS per pound compared to corn and 

soybean meal. For the final rulemaking analysis, these replacement rates are 

incorporated in both the FASOM and FAPRI-CARD models, and are treated as a 

maximum replacement rate possibility that is fully phased in by 2015. In addition, the 

 

338 Salil Arora, May Wu, and Michael Wang, “Update of Distillers Grains Displacement Ratios for Corn 

Ethanol Life-Cycle Analysis,” September 2008. See http://www.transportation.anl.gov/pdfs/AF/527.pdf 
 

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maximum inclusion rates for DGS in an animal’s diet have also been incorporated into 

the models. Given these parameters, each agriculture sector model determines the total 

quantity of DGS used in feed based on relative prices for competing feed sources. 

In addition, both FASOM and FAPRI-CARD now explicitly model corn oil from 

the dry mill ethanol extraction process as a new source of biodiesel. Based on 

engineering research (refer to Section VII.A) regarding expected technological adoption, 

it is estimated that 70% of dry mill ethanol plants will withdraw corn oil via extraction 

(from DGS), resulting in corn oil that is non-food grade and can only be used as a 

biodiesel source; 20% will withdraw corn oil via fractionation (prior to the creation of 

DGS), resulting in corn oil that is food-grade; and 10% will do neither extraction or 

fractionation. Based on this research, both the FASOM and FAPRI-CARD models are 

estimating that approximately 681 million gallons of biodiesel can be produced from nonfood grade corn oil from extraction by 2022 in the Control Case. Additional information 

regarding these changes to the FASOM and FAPRI-CARD models can be found in RIA 

Chapter 5. 

 1. Biofuel Volumes Modeled

 For the agricultural sector analysis using the FASOM and FAPRI-CARD models 

of the RFS2 biofuel volumes, we assumed 15 billion gallons (Bgal) of corn ethanol 

would be produced for use as transportation fuel by 2022, an increase of 2.7 Bgal from 

the Reference Case. Also, we modeled 1.7 Bgal of biodiesel use as fuel in 2022, an 
 

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increase of 1.3 Bgal from the Reference Case. In addition, we modeled an increase of 16 

Bgal of cellulosic ethanol in 2022. In FASOM, this volume consists of 4.9 billion gallons 

of cellulosic ethanol coming from corn residue in 2022, 7.9 billion gallons from 

switchgrass, 0.6 billion gallons from sugarcane bagasse, and 0.1 billion gallons from 

forestry residues. 

 Given the nature of the models, there are some limitations on what each model 

may explicitly model as a biofuel feedstock source. For example, since FASOM is a 

domestic agricultural sector model it cannot be utilized to examine the impacts of the 

wider use of biofuel imports into the U.S. Similarly, the FAPRI-CARD model does not 

explicitly model the forestry sector in the U.S. and therefore does not include biofuels 

produced from the U.S. forestry sector. Also, neither of the two models used for this 

analysis—FASOM or FAPRI-CARD—include biofuels derived from domestic municipal 

solid waste. Thus, for the RFS2 agricultural sector analysis, these biofuel sources are 

analyzed outside of the agricultural sector models. 

 All of the results presented in this section are relative to the AEO 2007 Reference 

Case renewable fuel volumes, which include 12.3 Bgal of grain-based ethanol, 0.4 Bgal 

of biodiesel, and 0.3 Bgal of cellulosic ethanol in 2022. The domestic figures are 

provided by FASOM, and all of the international numbers are provided by FAPRICARD. The detailed FASOM results, detailed FAPRI-CARD results, and additional 

sensitivity analyses are described in more detail in the RIA. 
 

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Table VIII.A.1-1 

Ethanol Source Volumes Modeled in 2022 

(Billions of Gallons) 

Ethanol Source AEO 2007 

Reference Case 

Control Case Change 

Corn Ethanol 12.3 15.0 2.7 

Corn Residue Cellulosic Ethanol * 0 4.9 4.9 

Sugarcane Bagasse Cellulosic Ethanol * 0.2 0.6 0.4 

Switchgrass Cellulosic Ethanol * 0 7.9 7.9 

Forestry Residue Cellulosic Ethanol * 0 0.1 0.1 

Net Imports of Sugarcane Ethanol ** 0.6 2.2 1.6 

Other Ethanol *** 0.1 2.6 2.5 

* Cellulosic Ethanol feedstocks are not explicitly modeled in FAPRI-CARD 

** Net Imports of Sugarcane Ethanol is not explicitly modeled in FASOM 

*** Includes MSW, which is not explicitly modeled by either FASOM or FAPRI-CARD. 

Table VIII.A.1-2 

Biodiesel Source Volumes Modeled in 2022 

(Millions of Gallons) 

Biodiesel Source AEO 2007 

Reference Case 

Control Case Change 

Soybean Oil 119.9 659.4 539.5 

Corn Oil (Dry Mill Extraction) 0.4 681.3 680.8 
 

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Animal Fats 93.9 126.9 33.0 

Yellow Grease 170.9 253.1 82.3 

 2. Commodity Price Changes

 

 For the scenario modeled, FASOM predicts that in 2022 U.S. corn prices would 

increase by $0.27 per bushel (8.2%) above the Reference Case price of $3.32 per bushel. 

By 2022, U.S. soybean prices would increase by $1.02 per bushel (10.3%) above the 

Reference Case price of $9.85 per bushel. In 2022, U.S. soybean oil prices would 

increase $183.32 per ton (37.9%) above the Reference Case price of $483.10 per ton. 

Hardwood lumber prices are unaffected by the increase in biofuel demand, however 

softwood lumber prices increase by $0.46 per board foot (0.1%) in 2022 to $386 per 

board foot. Additional price impacts are included in Section 5 of the RIA. 

Table VIII.A.2-1 

Change in U.S. Commodity Prices 

from the AEO 2007 Reference Case (2007$) 

Commodity Change % Change 

Corn $0.27/bushel 8.2% 

Soybeans $1.02/bushel 10.3% 

Soybean Oil $183.32/ton 37.9% 

Hardwood Lumber $0.00/board foot 0% 

Softwood Lumber $0.46/board foot 0.1% 
 

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By 2022, the price of switchgrass would increase by $20.12 per wet ton to the 

Control Case price of $40.85 per wet ton. Additionally, the farm gate feedstock price of 

corn residue would increase by $29.48 per wet ton to the Control Case price of $34.49 

per wet ton. The price of sugarcane bagasse would increase $23.27 to the Control Case 

price of $29.70 per wet ton by 2022. Softwood logging residue prices would increase 

$8.99 per wet ton to $18.37 per wet ton in the Control Case in 2022. Similarly, the price 

of hardwood logging residues would increase by $17.85 per wet ton to the Control Case 

price of $23.22 per wet ton in 2022. These prices do not include the storage, handling, or 

delivery costs, which would result in a delivered price to the ethanol facility of at least 

twice the farm gate cost, depending on the region. 

Table VIII.A.2-2 

Change in U.S. Cellulosic Feedstock Prices 

from the AEO 2007 Reference Case (2007$) 

Commodity Control Case Price Change 

Switchgrass $40.85/wet ton $20.12/wet ton 

Corn Residue $34.49/wet ton $29.48/wet ton 

Sugarcane Bagasse $29.70/wet ton $23.27/wet ton 

Softwood Logging Residue $18.37/wet ton $8.99/wet ton 

Hardwood Logging Residue $23.22 $17.85/wet ton 
 

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 3. Impacts on U.S. Farm Income

 The increase in renewable fuel production provides a significant increase in net 

farm income to the U.S. agricultural sector. FASOM predicts that net U.S. farm income 

would increase by $13 billion dollars in 2022 (36%), relative to the AEO 2007 Reference 

Case. 

 4. Commodity Use Changes

 Changes in the consumption patterns of U.S. corn can be seen by the increasing 

percentage of corn used for ethanol. FASOM estimates the amount of domestically 

produced corn used for ethanol in 2022 would increase to 40.5%, relative to the 33.2% 

usage rate under the Reference Case. 

 The rising price of corn and soybeans in the U.S. would also have a direct impact 

on how corn is used. Higher domestic corn prices would lead to lower U.S. exports as 

the world markets shift to other sources of these products or expand the use of substitute 

grains. FASOM estimates that U.S. corn exports would drop 188 million bushels (-8.2%) 

to 2.1 billion bushels by 2022. In value terms, U.S. exports of corn would fall by $57 

million (-0.8%) to $7.5 billion in 2022. U.S. exports of soybeans would also decrease 

due to the increased use of renewable fuels. FASOM estimates that U.S. exports of 

soybeans would decrease 135 million bushels (-13.6%) to 858 million bushels by 2022. 
 

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In value terms, U.S. exports of soybeans would decrease by $453 million (-4.6%) to $9.3 

billion in 2022. 

Table VIII.A.4-1 

Change in U.S. Exports 

from the AEO 2007 Reference Case in 2022 

Exports Change % Change 

Corn in Bushels -188 million -8.2 % 

Soybeans in Bushels -135 million -13.6% 

 

Total Value of Exports Change % Change 

Corn (2007$) - $57 million -0.8% 

Soybeans (2007$) - $453 million -4.6% 

 Lumber production in the U.S. is affected as well, as forestry acres decrease as a 

result of expanding crop acres (see below). In 2022, hardwood lumber production 

increases by 0.2%, and softwood production decreases by -0.2%. 

Table VIII.A.4-2 

Percent Change in U.S. Lumber Production 

from the AEO 2007 Reference Case in 2022 

Commodity % Change 
 

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Hardwood Lumber 0.2% 

Softwood Lumber -0.2% 

 Higher U.S. demand for corn for ethanol production would cause a decrease in the 

use of corn for U.S. livestock feed. Substitutes are available for corn as a feedstock, and 

this market is price sensitive. Several ethanol processing byproducts could also be used 

to replace a portion of the corn used as feed, depending on the type of animal. One of the 

major byproducts of the ethanol production process that can be used as a feed source, and 

as a substitute for corn and soybean meal, is distiller grains with solubles (DGS). DGS 

are a by-product of the dry mill ethanol production process. As discussed above, the 

replacement rates of DGs for corn and soybean meal in the diets of fed animals is higher 

than what was used in the proposal based on the latest scientific research regarding 

nutritional content of feed sources. In addition, as discussed above and in Chapter VI, 

there are new processes for withdrawing corn oil from the dry mill ethanol production 

process. Therefore, we are now modeling two types of DGS: those that are created 

during the extraction/fractionation process (fractionated DGS), and those created in 

plants that do not conduct fractionation or extraction (traditional DGS). In addition, other 

byproducts that can be used as feed substitutes include gluten meal and gluten feed, 

which are byproducts of wet milling ethanol production. In 2022, traditional DGS used 

in feed decreases by 27.5 million tons from the Reference Case to 6.5 million tons in the 

Control Case. However, the use of fractionated DGS increases by 32.7 million tons from 

20 thousand tons used in the Reference Case in 2022. Gluten meal used in feed decreases 

by 0.1 million tons (-4.5%) to 2.1 million tons in the Control Case. Gluten feed use 
 

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increases by 0.3 million tons (6.4%) in 2022 to 4.8 million tons in the Control Case. By 

2022, FASOM predicts total ethanol byproducts used in feed would increase by 5.4 

million tons (13.2%) to 46.1 million tons, compared to 40.8 million tons under the 

Reference Case. 

Table VIII.A.4-3 

Change in Ethanol Byproducts Use 

in Feed Relative to the AEO 2007 Reference Case 

(Millions of Tons) 

Category Control Case Change 

DGS (Traditional) 6.5 -27.5 

DGS (Fractionated) 32.7 32.7 

Gluten Meal 2.1 -0.1 

Gluten Feed 4.8 0.3 

Total Ethanol Byproducts 46.1 5.4 

 The EISA cellulosic ethanol requirements result in the production of residual 

agriculture and forestry products, as well as dedicated energy crops. By 2022, FASOM 

predicts production of 97.4 million tons of switchgrass and 59.9 million tons of corn 

residue. Sugarcane bagasse for cellulosic ethanol production increases by 6 million tons 

to 9.6 million tons in 2022 relative to the Reference Case. In addition, FASOM predicts 

production of 1.7 million tons of forestry residues for cellulosic ethanol production. 
 

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 5. U.S. Land Use Changes

 Higher U.S. corn prices would have a direct impact on the value of U.S. 

agricultural land. As demand for corn and other farm products increases, the amount of 

land devoted to cropland production would increase. FASOM estimates an increase of 

3.6 million acres (4.6%) in harvested corn acres, relative to 77.9 million acres harvested 

under the Reference Case by 2022.339 Most of the new corn acres come from a reduction 

in existing crop acres, such as rice, wheat, and hay. 

 Though demand for biodiesel increases, FASOM predicts a fall in U.S. soybean 

acres harvested. According to the model, harvested soybean acres would decrease by 

approximately 1.4 million acres (-2.1%), relative to the Reference Case acreage of 68.1 

million acres in 2022. Despite the decrease in soybean acres in 2022, soybean oil 

production would increase by 0.5 million tons (4.7%) by 2022 over the Reference Case. 

This occurs due to the decrease in soybean exports mentioned above. Additionally, 

FASOM predicts that soybean oil exports would decrease 1.2 million tons by 2022 (-

51%) relative to the Reference Case. 

 As the demand for cellulosic ethanol increases, most of the production is derived 

from switchgrass. By 2022, switchgrass acres from nearly zero acres in the Reference 

Case, to 12.5 million acres in the Control Case as demand for cellulosic ethanol increases 

 

339 Total U.S. planted corn acres increases to 87.1 million acres from the Reference Case level of 83.5 

million acres in 2022. 
 

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between cases. Similarly, as demand for cellulosic ethanol from bagasse increases, 

sugarcane acres increase by 0.1 millions acres (20%) to 0.9 million acres by 2022. 

Although we received comments suggesting that acres enrolled in the Conservation 

Reserve Program (CRP) may decrease below the 32 million acres assumed in the NPRM, 

we did not revise this assumption for several reasons. First, the commodity price changes 

predicted by FASOM are relatively modest and would therefore have a limited impact on 

the decision to re-enroll in the program. Second, the CRP program is designed to allow 

for increased payment if land rental rates increase. Therefore, for the reasons outlined in 

the NPRM, we believe the assumption that CRP acres will not drop below 32 million 

acres is a plausible future projection. 

Table VIII.A.5-1 

Change in U.S. Crop Acres Relative to 

the AEO 2007 Reference Case in 2022 

(millions of acres) 

Crop Change % Change 

Corn 3.6 4.6% 

Soybeans -1.4 -2.1% 

Sugarcane 0.1 20% 

Switchgrass 12.5 20,000% 
 

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 With the increase in biofuel demand that results from the implementation of the 

RFS2 policy, there is an increase of 3.1 million acres are dedicated towards crop 

production. This increase in crop acres results in a decrease of -1.9 million pasture acres, 

an increase of 1.1 million acres of forest pasture, and a decrease of 1.2 million forestry 

acres. 

Table VIII.A.5-2 

Change in U.S. Crop Acres Relative to 

the AEO 2007 Reference Case in 2022 

(millions of acres) 

Land Type Change % Change 

Cropland 3.1 1.0% 

Cropland Pasture -1.9 -5.8% 

Forest Pasture 1.1 0.7% 

Forestry -1.2 -0.3% 

 The additional demand for corn and other crops for biofuel production also results 

in increased use of fertilizer in the U.S. In 2022, FASOM estimates that U.S. nitrogen 

fertilizer use would increase 1.5 billion pounds (5.7%) over the Reference Case nitrogen 

fertilizer use of 26.2 billion pounds. In 2022, U.S. phosphorous fertilizer use would 

increase by 714 million pounds (12.7%) relative to the Reference Case level of 5.6 billion 

pounds. 
 

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Table VIII.A.5-3 

Change in U.S. Fertilizer Use Relative 

 to the AEO 2007 Reference Case (millions of pounds) 

Fertilizer Change % Change 

Nitrogen 1,501 5.7% 

Phosphorous 714 12.7% 

 6. Impact on U.S. Food Prices

 Due to higher commodity prices, FASOM estimates that U.S. food costs340 would 

increase by roughly $10 per person per year by 2022, relative to the Reference Case.341 

Total effective farm gate food costs would increase by $3.6 billion (0.2%) in 2022.342 To 

put these changes in perspective, average U.S. per capita food expenditures in 2007 were 

$3,778 or approximately 10% of personal disposable income. The total amount spent on 

food in the U.S. in 2007 was $1.14 trillion dollars.343 

 

 

340 FASOM does not calculate changes in price to the consumer directly. The proxy for aggregate food 

price change is an indexed value of all food prices at the farm gate. It should be noted, however, that 

according to USDA, approximately 80% of consumer food expenditures are a result of handling after it 

leaves the farm (e.g., processing, packaging, storage, marketing, and distribution). These costs consist of a 

complex set of variables, and do not necessarily change in proportion to an increase in farm gate costs. In 

fact, these intermediate steps can absorb price increases to some extent, suggesting that only a portion of 

farm gate price changes are typically reflected at the retail level. See 

http://www.ers.usda.gov/publications/foodreview/septdec00/FRsept00e.pdf. 

341 These estimates are based on U.S. Census population projections of 331 million people in 2017 and 348 

million people in 2022. See http://www.census.gov/population/www/projections/summarytables.html 

342 Farm Gate food prices refer to the prices that farmers are paid for their commodities. 343 See www.ers.usda.gov/Briefing/CPIFoodAndExpenditures/Data/table15.htm. 
 

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7. International Impacts 

 

 Changes in the U.S. agriculture economy are likely to have affects in other 

countries around the world in terms of trade, land use, and the global price and 

consumption of fuel and food. We utilized the FAPRI-CARD model to assess the 

impacts of the increased use of renewable fuels in the U.S. on world agricultural markets. 

 The FAPRI-CARD modeling shows that world corn prices would increase by 

$0.12 per bushel (3.1%) to $3.88 per bushel in 2022, relative to the Reference Case. The 

impact on world soybean prices is somewhat smaller, increasing $0.08 per bushel (0.8%) 

to $9.63 per bushel in 2022. 

This increase in international commodity prices has a direct impact on world food 

consumption.344 The FAPRI-CARD model indicates that world consumption of corn for 

food would decrease by 0.6 million metric tons in 2022 relative to the Reference Case. 

Similarly, the FAPRI-CARD model estimates that world consumption of oil for food 

(e.g., vegetable oils) decreases by 1.7 million metric tons by 2022. Wheat consumption 

is not estimated to change substantially in 2022. The model also estimates a small 

change in world meat consumption, decreasing by -0.1 million metric tons in 2022. 

When considering all the food uses included in the model, world food consumption 

decreases by 2.4 million metric tons by 2022 (-0.11%). While FAPRI-CARD provides 

 

344 The food commodities included in the FAPRI model include corn, wheat, sorghum, barley, soybeans, 

sugar, peanuts, oils, beef, pork, poultry, and dairy products. 
 

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estimates of changes in world food consumption, estimating effects on global nutrition is 

beyond the scope of this analysis. 

Table VIII.A.7-1 

Change in World Food Consumption 

Relative to the AEO 2007 Reference Case 

(millions of metric tons) 

Category 2022

Corn -0.6

Wheat 0.0

Vegetable Oils -1.7

Meat -0.1

Total Food -2.4

 Additional information on the U.S. agricultural and forestry sectors, as well as 

international trade impacts are described in more detail in the RIA (Chapter 5). 

B. Energy Security Impacts 

 Increasing usage of renewable fuels helps to reduce U.S. petroleum imports. A 

reduction of U.S. petroleum imports reduces both financial and strategic risks associated 

with a potential disruption in supply or a spike in cost of a particular energy source. This 
 

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reduction in risks is a measure of improved U.S. energy security. In this section, we 

detail an updated methodology for estimating the energy security benefits of reduced U.S. 

oil imports which explicitly includes biofuels and, based upon this updated approach, we 

estimate the monetary value of the energy security benefits of the RFS2 required 

renewable fuel volumes. 

 

 1. Implications of Reduced Petroleum Use on U.S. Imports 

In 2008, U.S. petroleum import expenditures represented 21% of total U.S. 

imports of all goods and services.345 In 2008, the U.S. imported 66% of the petroleum it 

consumed, and the transportation sector accounted for 70% of total U.S. petroleum 

consumption. This compares to approximately 37% of petroleum from imports and 55% 

consumption of petroleum in the transportation sector in 1975.346 It is clear that 

petroleum imports have a significant impact on the U.S. economy. Requiring the wider 

use of renewable fuels in the U.S. is expected to lower U.S. petroleum imports. 

 For this final rule, EPA estimated the reductions in U.S. petroleum imports using 

a modified version of the National Energy Modeling System (EPA-NEMS). EPA-NEMS 

is an energy-economy modeling system of U.S. energy markets through the 2030 time 

period. EPA-NEMS projects U.S. production, imports, conversion, consumption, and 

prices of energy; subject to assumptions on world energy markets, resource availability 

 

345 Source: U.S. Bureau of Economic Analysis, U.S. International Transactions Accounts Data, as shown on 

June 24, 2009. 

346 Source: U.S. Department of Energy, Annual Energy Review 2008, Report No. DOE/EIA-0384(2008), 

Tables 5.1 and 5.13c, June 26, 2009. 
 

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and costs, behavioral and technological choice criteria, cost and performance 

characteristics of energy technologies, and demographics. For this analysis, the 2009 

NEMS model was modified to use the 2007 (pre-EISA) Annual Energy Outlook (AEO) 

levels of biofuels in the Reference Case. These results were compared to our Control 

Case, which assumes the renewable fuel volumes required by EISA will be met by 2022. 

The reductions in U.S. oil imports projected by EPA-NEMS as a result of the RFS2 is 

approximately 0.9 million barrels per day, which amounts to about $41.5 billion in lower 

crude oil and refined product import payments in 2022. 

2. Energy Security Implications

In order to understand the energy security implications of the increased use of 

renewable fuels, EPA used the Oil Security Metrics Model 347,348 (OSMM), developed 

and maintained by Oak Ridge National Laboratory. This model examines the future 

economic costs of oil imports and oil supply disruptions to the U.S., grouping costs into 

(1) the higher costs for oil imports resulting from the effect of U.S. import demand on the 

world oil price and OPEC market power (i.e., the "import demand" or "monopsony" 

costs); and (2) the expected cost of reductions in U.S. economic output and disruption of 

 

347 The OSMM methods are consistent with the recommended methodologies of the National Resource 

Council’s (NRC’s) (2005) Committee on Prospective Benefits of DOE’s Energy Efficiency and Fossil 

Energy R&D Programs. The OSMM defines and implements a method that makes use of the NRC’s 

typology of prospective benefits and methodological framework, satisfies the NRC’s criteria for 

prospective benefits evaluation, and permits measurement of prospective energy security benefits for 

policies and technologies related to oil. It has been used to estimate the prospective oil security benefits of 

Department of Energy’s Energy Efficiency and Renewable Energy R&D programs, and is also applicable 

to other strategies and policies aimed at changing the level and composition of U.S. petroleum demand. To 

evaluate the RFS2, the OSMM was modified to include supplies and demand of biofuels (principally 

ethanol) as well as petroleum. 

348 Leiby, P.N., Energy Security Impacts of Renewable Fuel Use Under the RFS2 Rule – Methodology, Oak 

Ridge National Laboratory, January 19, 2010 
 

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the U.S. economy caused by sudden disruptions in the supply of imported oil to the U.S. 

(i.e., macroeconomic disruption/adjustment costs). Beginning with Reference projections 

for the oil and liquid fuel markets from the EIA’s 2009 AEO, the OSMM compares costs 

under those futures with selected cases under differing energy policies and technology 

mixes. It provides measures of expected costs and risk by probabilistic simulation 

through 2022. Uncertainty is inherent in energy security analysis, and it is explicitly 

represented for long-run future oil market conditions, disruption events, and key 

parameters. 

An important aspect of the OSMM is that it explicitly addresses the energy 

security implications of the wider use of biofuels as transportation fuels in the U.S. 

Increased use of biofuels not only results in changes in the levels of U.S. oil imports and 

consumption, but also can alter key supply and demand oil elasticities. The elasticities 

are significant for energy security since they measure the potential for substitution away 

from oil, in the long and short-run, depending on how oil prices evolve and whether oil 

supply disruptions occur. Also, the OSMM accounts for the potential of supply 

disruptions from biofuels. For example, there could be a drought in the U.S. that could 

cause a reduction in the supply of key agricultural feedstocks (i.e., corn) that are used to 

make ethanol. To the extent that supply disruptions in feedstocks used to make biofuels 

are correlated with oil supply disruptions, the energy security benefits of biofuels may be 

lessened, by substituting one fuel with supply disruptions for another. For this analysis, 

the energy security implications of the wider use of biofuels in the U.S. are broken down 
 

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between biofuels produced domestically (e.g., ethanol made from corn/switchgrass, soybased biodiesel) and imported biofuels (e.g., ethanol made from sugarcane). 

 

 For the proposed RFS2 rule, EPA worked with Oak Ridge National Laboratory 

(ORNL), which has developed approaches for evaluating the social costs and energy 

security implications of oil use. In the study entitled "The Energy Security Benefits of 

Reduced Oil Use, 2006-2015," completed in March, 2008, ORNL updated and applied 

the analytical approach used in the 1997 Report "Oil Imports: An Assessment of Benefits 

and Costs." 349,350 This study is included as part of the record in this rulemaking.351 This 

study underwent a Peer Review, sponsored by the Agency. 

 The prior approach that ORNL has developed estimates the incremental benefits 

to society, in dollars per barrel, of reducing U.S. oil imports, called the “oil import 

premium”. With OSMM, ORNL uses a consistent approach, estimating the incremental 

cost to the U.S. of the increased use of renewable fuels required by EISA, and reporting 

that cost in dollars per barrel of biofuel. In this case, these increased volumes alter both 

the U.S. oil import and consumption levels, while introducing a substitute fuel and 

altering demand responsiveness. As before, OSMM considers the economic cost of 

importing petroleum into the U.S. The economic cost of importing petroleum into the 

U.S. was defined as (1) the higher costs for oil imports resulting from the effect of U.S. 

 

349 Leiby, Paul N., Donald W. Jones, T. Randall Curlee, and Russell Lee, Oil Imports: An Assessment of 

Benefits and Costs, ORNL-6851, Oak Ridge National Laboratory, November, 1997. 350 The 1997 ORNL paper was cited and its results used in DOT/NHTSA’s rules establishing CAFE 

standards for 2008 through 2011 model year light trucks. See DOT/NHTSA, Final Regulatory Impacts 

Analysis: Corporate Average Fuel Economy and CAFE Reform MY 2008-2011, March 2006. 

351 Leiby, Paul N. "Estimating the Energy Security Benefits of Reduced U.S. Oil Imports," Oak Ridge 

National Laboratory, ORNL/TM-2007/028, Final Report, 2008. 
 

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import demand on the world oil price and OPEC market power (i.e., "monopsony" costs); 

and (2) the risk of reductions in U.S. economic output and disruption of the U.S. 

economy caused by sudden disruptions in the supply of imported oil to the U.S. (i.e., 

macroeconomic disruption/adjustment costs). Maintaining a U.S. military presence to 

help secure stable oil supply from potentially vulnerable regions of the world is also a 

measure of energy security, but has been excluded from this analysis because its 

attribution to particular military missions or activities is difficult. 

a. Effect of Oil Use on Long-Run Oil Price, U.S. Import Costs, and 

Economic Output 

 The first component of the economic costs of importing petroleum into the U.S. 

follows from the effect of U.S. import demand on the world oil price over the long-run. 

Because the U.S. is a sufficiently large purchaser of foreign oil supplies, its purchases can 

affect the world oil price. This monopsony power means that increases in U.S. petroleum 

demand can cause the world price of crude oil to rise, and conversely, that reduced U.S. 

petroleum demand can reduce the world price of crude oil. Thus, one benefit of 

decreasing U.S. oil purchases is the potential decrease in the crude oil price paid for all 

crude oil purchased. 

 In the case of the RFS2, increasing U.S. demand for biofuels partially offsets the 

U.S. oil market import cost reduction. The offset is because the RFS2 results in a modest 

increases in biofuels imported to the U.S. (1.6 billion gallons in 2022), and a modest 
 

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increase in the world ethanol price (from $1.48/gallon to $1.61/gallon, a $0.13/gallon 

increase in 2022). Thus, the biofuels that the U.S. had imported would be higher priced, 

partially offsetting the reduction in U.S. oil import costs. The ORNL estimates this 

monopsony component of the energy security benefit (oil market and biofuel market 

impacts combined) is $7.86/barrel of biofuel (2007$) for the year 2022, as shown in 

Table VIII.B.2-1. Based upon the 90 percent confidence interval, the monopsony portion 

of the energy security benefit ranges from $5.37 to $10.71/barrel of biofuel in the year 

2022. 

b. Short-Run Disruption Premium from Expected Costs of Sudden Supply 

Disruptions 

 The second component of the external economic costs resulting from U.S. oil 

imports arises from the vulnerability of the U.S. economy to oil shocks. The cost of 

shocks depends on their likelihood, size, and length; the capabilities of the market and 

U.S. Strategic Petroleum Reserve (SPR) to respond; and the sensitivity of the U.S. 

economy to sudden price increases. The total vulnerability of the U.S. economy to oil 

price shocks depends on the levels of both U.S. petroleum consumption and imports. 

Variation in oil consumption levels can change the sensitivity of the economy to oil price 

shocks, and variation in import levels or demand flexibility can affect the magnitude of 

potential increases in oil price due to supply disruptions 
 

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 A major strength of the OSMM is that it addresses risk-shifting that might occur 

as the U.S. reduces its dependency on petroleum and increases its use of biofuels, which 

the other “oil premium model” could not. The prior “oil premium” analysis focused only 

on the potential for biofuels to reduce U.S. oil imports, and the resulting implications of 

lower U.S. oil imports for energy security. As the U.S. relies more heavily on biofuels, 

such as corn-based ethanol, there could be adverse consequences from a supplydisruption perspective associated with, for example, a long-term drought. Alternatively, a 

supply disruption of petroleum will more likely be caused by geopolitical factors rather 

than extreme weather conditions. Hence, the causal factors of a supply-disruption from 

imported petroleum and, alternatively, biofuels, are likely to be unrelated. Thus, 

diversifying the sources of U.S. transportation fuel is expected to provide energy security 

benefits. Biofuel supply disruptions are represented based on the historical volatility of 

yields for biofuel feedstocks or similar crops. The ORNL estimates this 

macroeconomic/disruption component of the energy security benefit (oil market and 

biofuel market impacts combined) is $6.56/barrel (2007$) for the year 2022, as shown in 

Table VIII.B.2-1. Based upon the 90 percent confidence interval, the 

macroeconomic/disruption component of the energy security benefit ranges from $0.94 to 

$12.23/barrel of biofuel in the year 2022. 

 

Table VIII.B.2-1 

Energy Security Benefits of The Volumes Required by RFS2 in 2022 

(2007$ per barrel of biofuel) 
 

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Component Estimate 

Monopsony $7.86 

($5.37-$10.71) 

Macroeconomic Disruption $6.56 

($0.94-$12.23) 

Total $14.42 

($6.31-$22.95) 

 c. Costs of Existing U.S. Energy Security Policies

 Another often-identified component of the full economic costs of U.S. oil imports 

is the costs to the U.S. taxpayers of existing U.S. energy security policies. The two 

primary examples are maintaining a military presence to help secure stable oil supply 

from potentially vulnerable regions of the world and maintaining the SPR to provide 

buffer supplies and help protect the U.S. economy from the consequences of global oil 

supply disruptions. 

 U.S. military costs are excluded from the analysis performed by ORNL because 

their attribution to particular missions or activities is difficult. Most military forces serve 

a broad range of security and foreign policy objectives. Attempts to attribute some share 

of U.S. military costs to oil imports are further challenged by the need to estimate how 

those costs might vary with incremental variations in U.S. oil imports. In the peer review 
 

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of the energy security analysis that the Agency commissioned, a majority of peer 

reviewers believed that U.S. military costs should be excluded absence a widely agreed 

methodology for estimating this component of U.S. energy security. Similarly, while the 

costs for building and maintaining the SPR are more clearly related to U.S. oil use and 

imports, historically these costs have not varied in response to changes in U.S. oil import 

levels. Thus, while SPR is factored into the ORNL analysis, the cost of maintaining the 

SPR is excluded. 

 Some commenters felt that the Agency should attempt to monetize U.S. military 

costs and include these costs in the energy security analysis, while other commenters 

agreed with the Agency that these costs should be excluded. The Agency did not receive 

any new analysis or methodological approach from commenters which could be used to 

monetize U.S. military costs in a meaningful or credible manner. Since U.S. military 

impacts are not factored into the energy security analysis, they are also excluded from the 

lifecycle GHG analysis. 

3. Combining Energy Security and Other Benefits 

 The literature on the energy security for the last two decades has routinely 

combined the monopsony and the macroeconomic disruption components when 

calculating the total value of the energy security premium. However, in the context of 

using a global value for the Social Cost of Carbon (SCC) the question arises: how should 

the energy security premium be used when some benefits from the increased use of 
 

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renewable fuels, such as the benefits of reducing greenhouse gas emissions, are 

calculated at a global level? Monopsony benefits represent avoided payments by the U.S. 

to oil producers in foreign countries that result from a decrease in the world oil price as 

the U.S. decreases its consumption of imported oil (net of increased imported biofuel 

payments by the U.S.) Although there is clearly a benefit to the U.S. when considered 

from the domestic perspective, the decrease in price due to decreased demand in the U.S. 

also represents a loss to other countries. Given the redistributive nature of this effect, do 

the negative effects on other countries “net out” the positive impacts to the U.S.? If this 

is the case, then, the monopsony portion of the energy security premium should be 

excluded from the net benefits calculation. Based on this reasoning, EPA's estimates of 

net benefits for the increased use of renewable fuels required by EISA exclude the 

portion of energy security benefits stemming from the U.S. exercising its monopsony 

power in oil markets. Thus, EPA only includes the macroeconomic 

disruption/adjustment cost portion of the energy security premium. 

 However, even when the global value for greenhouse gas reduction benefits is 

used, a strong argument can be made that the monopsony benefits should be included in 

net benefits calculation. Maintaining the earth’s climate is a global public good and as 

such requires that a global perspective be taken on the benefits of GHG mitigation by all 

nations, including the U.S. The global SCC is used in these calculations, not because the 

global net benefits of the increased use of renewable fuels are being computed (they are 

not), but rather because in the context of a global public good, the global marginal benefit 

is the correct benefit against which domestic costs are to be compared. In other words, 
 

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using the global SCC does not transform the calculation from a domestic (i.e., U.S.) to a 

global one. Rather, the domestic perspective is maintained while recognizing that the 

impacts from domestic GHG emissions are truly global in nature. 

 Energy security, on the other hand, is broadly defined as protecting the U.S. 

economy against circumstances that threaten significant short- and long-term increases in 

energy costs. Energy security is inherently a domestic benefit. However, the use of the 

domestic monopsony benefit is not necessarily in conflict with the use of the global SCC, 

because the global SCC represents the benefits against which the costs associated with 

our (i.e., the U.S.’s) domestic mitigation efforts should be judged. In addition, the U.S. 

values both maintaining the earth’s climate and providing for its own energy security. If 

this reasoning holds, the two benefits—the global benefits of reducing greenhouse gas 

emissions and the full energy security premium, including the monopsony benefits—

should be counted in the net benefits estimates. In the final analysis, the Agency 

determined that the first argument is more compelling and therefore has determined that 

using only the macroeconomic disruption component of the energy security benefit is the 

appropriate metric for this rule. 

 4. Total Energy Security Benefits

 In 2022, total annual energy security benefits are estimated for the difference 

between the renewable fuel volumes in the Primary Control Case (30.50 billion gallons) 

and the AEO2007 Reference Case (13.56 billion gallons). Total annual energy security 
 

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benefits are calculated by multiplying the change in renewable fuel volumes (16.94 

billion gallons or 403 million barrels) and the macroeconomic disruption/adjustment 

portion of the energy security premium ($6.56/barrel of renewable fuels). The estimated 

total energy security benefit is $2.6 billion (2007$) for the year 2022. The estimated total 

energy security benefit using the macroeconomic disruption/adjustment portion of the 

energy security benefit in 2022 ranges from $379 million to $4.9 billion based upon the 

90 percent confidence intervals. 

C. Benefits of Reducing GHG Emissions 

 

1. Introduction

This section presents estimates of the economic benefits that could be monetized 

for the reductions in GHG emissions projected to occur through the increased use of 

renewable fuels required by EISA. The total benefit estimates were calculated by 

multiplying a marginal dollar value (i.e., cost per ton) of carbon emissions, also referred 

to as “social cost of carbon” (SCC), by the anticipated level of emissions reductions in 

tons. 

The SCC values underlying the benefits estimates for this rule represent U.S. 

government-wide interim values for SCC. As discussed below, federal agencies will use 

these interim values to assess some of the economic benefits of GHG reductions while an 

interagency workgroup develops SCC values for use in the long-term. The interim values 
 

697

should not be viewed as an expectation about the results of the longer-term process. 

Although these values were not used in the NPRM, some commenters raised issues with 

these values and the methodology used to develop them in response to their publication 

elsewhere. Many of these issues are being examined by the interagency workgroup. 

The rest of this Preamble section will provide the basis for the interim SCC 

values, and the estimates of the total climate-related benefits of the increased use of 

renewable fuels that follow from these interim values. As discussed below, the interim 

dollar estimates of the SCC represent a partial accounting of climate change impacts. 

In addition to the quantitative account presented in this section, a qualitative 

appraisal of climate-related impacts is published in Section V of today’s rule and in other 

recent climate change analyses. For example, EPA’s Endangerment and Cause or 

Contribute Findings for Greenhouse Gases under Section 202(a) of the Clean Air Act and 

the accompanying Technical Support Document (TSD) presents a summary of impacts 

and risks of climate change projected in the absence of actions to mitigate GHG 

emissions.352 The TSD synthesizes major findings from the best available scientific 

assessments of the scientific literature that have gone through rigorous and transparent 

peer review, including the major assessment reports of both the Intergovernmental Panel 

on Climate Change (IPCC) and the U.S. Climate Change Science Program (CCSP). 

 

352 See Federal Register /Vol.74, No.2398/Wednesday, December 16, 2009/Rules and Regulations at 

http://frwebgate4.access.gpo.gov/cgibin/PDFgate.cgi?WAISdocID=969788398047+0+2+0&WAISaction=retrieve or 

http://epa.gov/climatechange/endangerment.html 
 

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2. Derivation of Interim Social Cost of Carbon Values 

The “social cost of carbon” (SCC) is intended to be a monetary measure of the 

incremental damage resulting from carbon dioxide (CO2) emissions, including (but not 

limited to) net agricultural productivity loss, human health effects, property damages 

from sea level rise, and changes in ecosystem services. Any effort to quantify and to 

monetize the consequences associated with climate change will raise serious questions of 

science, economics, and ethics. But with full regard for the limits of both quantification 

and monetization of impacts, the SCC can be used to provide an estimate of the social 

benefits of reductions in GHG emissions. 

 

For at least three reasons, any particular figure will be contestable. First, scientific 

and economic knowledge about the impacts of climate change continues to grow. With 

new and better information about relevant questions, including the cost, burdens, and 

possibility of adaptation, current estimates will inevitably change over time. Second, 

some of the likely and potential damages from climate change—for example, the loss of 

endangered species—are generally not included in current SCC estimates. These 

omissions may turn out to be significant in the sense that they may mean that the best 

current estimates are too low. As noted by the IPCC Fourth Assessment Report, “It is 

very likely that globally aggregated figures underestimate the damage costs because they 

cannot include many non-quantifiable impacts.” Third, when economic efficiency 

criteria, under specific assumptions, are juxtaposed with ethical considerations, the 

outcome may be controversial. These ethical considerations, including those involving 
 

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the treatment of future generations, should and will also play a role in judgments about 

the SCC (see in particular the discussion of the discount rate, below). 

To date, SCC estimates presented in recent regulatory documents have varied 

within and among agencies, including DOT, DOE, and EPA. For example, a regulation 

proposed by DOT in 2008 assumed a value of $7 per metric tonne CO2

353 (2006$) for 

2011 emission reductions (with a range of $0-14 for sensitivity analysis). One of the 

regulations proposed by DOE in 2009 used a range of $0-$20 (2007$). Both of these 

ranges were designed to reflect the value of damages to the United States resulting from 

carbon emissions, or the “domestic” SCC. In the final MY2011 CAFE EIS, DOT used 

both a domestic SCC value of $2/t-CO2 and a global SCC value of $33/t-CO2 (with 

sensitivity analysis at $80/t-CO2) (in 2006 dollars for 2007 emissions), increasing at 2.4% 

per year thereafter. The final MY2011 CAFE rule also presented a range from $2 to 

$80/t-CO2. 

In the May 2009 proposal leading to today’s final rule, EPA identified 

preliminary SCC estimates that spanned three orders of magnitude. EPA’s May 2009 

proposal also presented preliminary global SCC estimates developed from a survey 

analysis of the peer reviewed literature (i.e., meta analysis). The global mean values from 

 

353 For the purposes of this discussion, we present all values of the SCC as the cost per metric tonne of CO2

emissions. Some discussions of the SCC in the literature use an alternative presentation of a dollar per 

metric ton of carbon. The standard adjustment factor is 3.67, which means, for example, that a SCC of $10 

per ton of CO2 would be equivalent to a cost of $36.70 for a ton of carbon emitted. Unless otherwise 

indicated, a “ton” refers to a metric ton. 
 

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the meta analysis were $68 and $40/t-CO2 for discount rates of 2% and 3% respectively 

(in 2006 real dollars for 2007 emissions).354 

Since publication of the May 2009 proposal, a federal interagency working group 

has established a methodology for selecting a range of interim SCC estimates for use in 

regulatory analyses. Today’s final rule uses the five values for the SCC that are the 

outcome of this process. A complete description of the methodology used to generate this 

interim set of SCC estimates can be found in the RIA for this rule and in multiple other 

published rules, including a proposal to limit vehicle greenhouse gas emissions that 

requests public comment on the estimates and underlying methodology.355

It should be emphasized that the analysis here is preliminary. These interim 

estimates are being used for the short-term while an interagency group develops a more 

comprehensive characterization of the distribution of SCC values for future economic 

and regulatory analyses. The interim values should not be viewed as an expectation about 

the results of the longer-term process.

This process will allow the workgroup to explore questions raised in the May 

2009 proposal as they are relevant to the development of SCC values for use in the longterm. The workgroup may evaluate factors not currently captured in today’s estimates 

due to time constraints, such as the quantification of additional impact categories where 

 

354 74 FR 25094 (May 26, 2009). 355 Federal Register 40 CFR Parts 86 and 600, September 28, 2009 “Proposed Rulemaking To Establish 

Light-Duty Vehicle Greenhouse Gas Emission Standards and Corporate Average Fuel Economy Standards; 

Proposed Rule” 
 

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possible and an uncertainty analysis. The Administration will seek comment on all of the 

scientific, economic, and ethical issues before establishing improved estimates for use in 

future rulemakings. 

The outcomes of the Administration’s process to develop interim values are 

judgments in favor of a) global rather than domestic values, b) an annual growth rate of 

3%, and c) interim global SCC estimates for 2007 (in 2007 dollars) of $56, $34, $20, $10, 

and $5 per metric ton of CO2. As noted, this is an emphatically interim SCC value. The 

judgments herein will be subject to further scrutiny and exploration. 

3. Application of Interim SCC Estimates to GHG Emissions Reductions

While no single rule or action can independently achieve the deep worldwide 

emissions reductions necessary to halt and reverse the growth of GHGs, the combined 

effects of multiple strategies to reduce GHG emissions domestically and abroad could 

make a major difference in the climate change impacts experienced by future 

generations.356 The projected net GHG emissions reductions associated with the 

increased use of renewable fuels reflect an incremental change to projected total global 

emissions. Given that the climate response is projected to be a marginal change relative 

to the baseline climate, we estimate the marginal value of changes in climate change 

impacts over time and use this value to measure the monetized marginal benefits of the 

 

356 The Supreme Court recognized in Massachusetts v. EPA that a single action will not on its own achieve 

all needed GHG reductions, noting that “[a]gencies, like legislatures, do not generally resolve massive 

problems in one fell regulatory swoop.’’ See Massachusetts v. EPA, 549 U.S. at 524 (2007). 
 

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GHG emissions reductions projected for the increased renewable fuel volumes required 

by EISA. 

Accordingly, EPA has used the set of interim, global SCC values described above 

to estimate the benefits of the increased use of renewable fuels. The interim SCC values 

for emissions in 2007, which reflect the Administration’s interim interpretation of the 

current literature, are $5, $10, $20, $34, and $56, in 2007 dollars, and are based on a CO2

emissions change of 1 metric ton in 2007. Table VIII.C.3-1 presents the interim SCC 

values for both the years 2007 and 2022 in 2007 dollars. 

Table VIII.C.3-1 

Interim SCC Schedule (2007$ per metric tonne of CO2)

Year 5% 5% (NewellPizer)* Average SCC 

from 3% and 5% 

3% 3% (NewellPizer)* 

2007 $5 $10 $20 $34 $56 

2022 $8 $16 $30 $53 $88 

Note: The SCC values are dollar-year and emissions-year specific. These values are presented in 

2007$, for individual year of emissions. To determine values for other years not presented in the 

table, use a 3% per year growth rate. SCC values represent only a partial accounting for climate 

impacts. 

*SCC values are adjusted based on Newell and Pizer (2003) to account to future uncertainty in 

discount rates. 
 

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Table VIII.C.3-2 provides, for the low, base, and high cases, the average annual 

GHG emissions reductions in 2022. The annualized emissions reductions are multiplied 

by the SCC estimates for 2022 from Table VIII.C.3-1 to produce the average annual 

monetized benefit from the emissions reductions for CO2-equivalent GHGs. This is 

equivalent to taking the time stream of emissions from the increase in renewable fuel 

volumes, multiplying them by the SCC (which is increasing at a rate of 3 percent per 

year), and then discounting the stream of benefits by 3 percent. 

 

Table VIII.C.3-2 

Average Annual Emissions Reduction (Million Metric Tonnes CO2-e) and Monetized 

Benefits (Million 2007$) in 2022

 Low Case Base Case High Case 

Emissions 

Reductions 

136.104 138.411 140.291 

5% $1,089 $1,107 $1,122 

5% (Newell-Pizer) $2,178 $2,215 $2,245 

Average SCC from 

3% and 5% $4,138 $4,208 $4,265 

3% $7,186 $7,308 $7,407 

3% (Newell-Pizer) $11,976 $12,179 $12,344 
 

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Table VIII.C.3-3 provides, for the high, base, and low cases, the monetized 

benefits from the emissions reductions from the increase in renewable fuel volumes for 

CO2-equivalent GHGs in 2022. The SCC estimates for 2022 increase at a rate of 3 

percent per year, and are then multiplied by the stream of emissions for each respective 

year for 30 years. The monetized benefits in table VIII.C.3-3 represent the net present 

value of these emissions for 30 years using a discount rate of 7 percent. 

Table VIII.C.3-3. 

Monetized Benefits (Million 2007$) of RFS-2 Volumes in 2022 

Using a 7% Discount Rate 

 High Base Low 

5% $606 $620 $631 

5% (Newell-Pizer) $1,212 $1,239 $1,262 

Average SCC from 

3% and 5% $2,302 $2,355 $2,397 

3% $3,999 $4,089 $4,163 

3% (Newell-Pizer) $6,665 $6,816 $6,939 

D. Criteria Pollutant Health and Environmental Impacts 

 1. Overview
 

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This section describes EPA’s analysis of the co-pollutant health and 

environmental impacts that can be expected to occur as a result of the increase in 

renewable fuel use throughout the period from initial implementation of the RFS2 rule 

through 2022. Although the purpose of this final rule is to implement the renewable fuel 

requirements established by the Energy Independence and Security Act (EISA) of 2007, 

the increased use of renewable fuels will also impact emissions of criteria and air toxic 

pollutants and their resultant ambient concentrations. The fuels changes detailed in 

Section 3.1 of the RIA will influence emissions of VOCs, PM, NOX, and SOX and air 

toxics and affect exhaust and evaporative emissions of these pollutants from vehicles and 

equipment. They will also affect emissions from upstream sources such as fuel 

production, storage, distribution and agricultural emissions. Any decrease or increase in 

ambient ozone, PM2.5, and air toxics associated with the increased use of renewable fuels 

will impact human health in the form of a decrease or increase in the risk of incurring 

premature death and other serious human health effects, as well as other important public 

health and welfare effects. 

This analysis reflects the impact of the 2022 mandated renewable fuel volumes 

(the “RFS2 control case”) compared with two different reference scenarios that include 

the use of renewable fuels: a 2022 baseline projection based on the RFS1-mandated 

volume of 7.1 billion gallons of renewable fuels, and a 2022 baseline projection based on 

the AEO 2007 volume of roughly 13.6 billion gallons of renewable fuels. 357 Thus, the 

 

357 The 2022 modeled scenarios assume the following: RFS1 reference case assumes 6.7 Bgal/yr ethanol 

and 0.38 Bgal/yr biodiesel; AEO2007 reference case assumes 13.18 Bgal/yr ethanol and 0.38 Bgal/yr 
 

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results represent the impact of an incremental increase in ethanol and other renewable 

fuels. We note that the air quality modeling results presented in this final rule do not 

constitute the “anti-backsliding” analysis required by Clean Air Act section 211(v). EPA 

will be analyzing air quality and health impacts of increased renewable fuel use through 

that study and will promulgate appropriate mitigation measures under section 211(v), 

separate from this final action. 

As can be seen in Section VI.D of this preamble, as well as in Section 3.4 of the 

RIA that accompanies this preamble, there are both increased and decreased 

concentrations of ambient criteria pollutants and air toxics. Overall, we estimate that the 

required renewable fuel volumes will lead to a net increase in criteria pollutant-related 

health impacts. By 2022, the final RFS2 volumes relative to both reference case 

scenarios (RFS1 and AEO2007), are projected to adversely impact PM2.5 air quality over 

parts of the U.S., while some areas will experience decreases in ambient PM2.5. As 

described in Section VI, ambient PM2.5 is likely to increase as a result of emissions at 

biofuel production plants and from biofuel transport, both of which are more prevalent in 

the Midwest. PM concentrations are also likely to decrease in some areas. While the 

PM-related air quality impacts are relatively small, the increase in population-weighted 

national average PM2.5 exposure results in a net increase in adverse PM-related human 

health impacts. (the increase in national population weighted annual average PM2.5 is 

0.006 μg/m3 and 0.002 μg/m3 relative to the RFS1 and AEO2007 reference cases, 

respectively). 

 

biodiesel; RFS2 control case assumes 34.14 Bgal/yr ethanol, 0.81 Bgal/yr biodiesel, and 0.38 Bgal/yr 

renewable diesel. Please refer to Chapter 3.3 and Table 3.3-1 for more information about the renewable 

fuel volumes assumed in the modeled analyses and the corresponding emissions inventories. 
 

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The required renewable fuel volumes, relative to both reference scenarios, are 

also projected to adversely impact ozone air quality over much of the U.S., especially in 

the Midwest, Northeast and Southeast. These adverse impacts are likely due to increased 

upstream emissions of NOx in many areas that are NOx-limited (acting as a precursor to 

ozone formation). There are, however, ozone air quality improvements in some highlypopulated areas that currently have poor air quality. This is likely due to VOC emission 

reductions at the tailpipe in urban areas that are VOC-limited (reducing VOC’s role as a 

precursor to ozone formation). Relative to the RFS1 mandate reference case, the RFS2 

volumes result in an increase in national ozone-related health impacts (population 

weighted maximum 8-hour average ozone increases by 0.177 ppb). Relative to the 

AEO2007 reference case, the RFS2 volumes result in an increase in national ozonerelated health impacts (population weighted maximum 8-hour average ozone increases by 

0.116 ppb). 

The analysis of national-level PM2.5- and ozone-related health and environmental 

impacts associated with the required renewable fuel volumes is based on peer-reviewed 

studies of air quality and human health effects (see US EPA, 2006 and US EPA, 

2008).358,359 We are also consistent with the benefits analysis methods that supported the 

recently proposed Portland Cement National Emissions Standards for Hazardous Air 

 

358 U.S. Environmental Protection Agency. (2006). Final Regulatory Impact Analysis (RIA) for the 

Proposed National Ambient Air Quality Standards for Particulate Matter. Prepared by: Office of Air and 

Radiation. Retrieved March, 26, 2009 at http://www.epa.gov/ttn/ecas/ria.html 

359 U.S. Environmental Protection Agency. (2008). Final Ozone NAAQS Regulatory Impact Analysis. 

Prepared by: Office of Air and Radiation, Office of Air Quality Planning and Standards. Retrieved March, 

26, 2009 at http://www.epa.gov/ttn/ecas/ria.html 
 

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Pollutants (NESHAP) RIA (U.S. EPA, 2009a),360 the proposed NO2 primary NAAQS 

RIA (U.S. EPA, 2009b), 361 and the proposed Category 3 Marine Diesel Engines RIA 

(U.S. EPA, 2009c).362 These methods are described in more detail in the RIA that 

accompanies this preamble. To model the ozone and PM air quality impacts of the 

required renewable fuel volumes, we used the Community Multiscale Air Quality 

(CMAQ) model (see Section VI.D). The modeled ambient air quality data serves as an 

input to the Environmental Benefits Mapping and Analysis Program (BenMAP).363 

BenMAP is a computer program developed by the U.S. EPA that integrates a number of 

the modeling elements used in previous analyses (e.g., interpolation functions, population 

projections, health impact functions, valuation functions, analysis and pooling methods) 

to translate modeled air concentration estimates into health effects incidence estimates 

and monetized benefits estimates. 

The range of total national-level ozone- and PM-related monetized impacts 

associated with the required renewable fuel volumes is presented in Table VIII.D.1-1.364 

 

360 U.S. Environmental Protection Agency (U.S. EPA). 2009a. Regulatory Impact Analysis: National 

Emission Standards for Hazardous Air Pollutants from the Portland Cement Manufacturing Industry. 

Office of Air Quality Planning and Standards, Research Triangle Park, NC. April. Available on the 

Internet at <http://www.epa.gov/ttn/ecas/regdata/RIAs/portlandcementria_4-20-09.pdf>. 

361 U.S. Environmental Protection Agency (U.S. EPA). 2009b. Proposed NO2 NAAQS Regulatory Impact 

Analysis (RIA). Office of Air Quality Planning and Standards, Research Triangle Park, NC. April. 

Available on the Internet at http://www.epa.gov/ttn/ecas/regdata/RIAs/proposedno2ria.pdf. Note: The 

revised NO2 NAAQS may be final by the publication of this action. 

362 U.S. Environmnetal Protection Agency (U.S. EPA). 2009c. Draft Regulatory Impact Analysis: Control 

of Emissions of Air Pollution from Category 3 Marine Diesel Engines. Office of Transportation and Air 

Quality, June. Available on the Internet at http://www.epa.gov/otaq/regs/nonroad/420d09002.htm. Note: 

The C3 rule may be final by the publication of this action. 

363 Information on BenMAP, including downloads of the software, can be found at 

http://www.epa.gov/ttn/ecas/ benmodels.html. 

364 Note that these impacts reflect the national total of PM-related benefits and disbenefits and ozonerelated benefits and disbenefits. The sum of total of benefits and disbenefits yields a net negative benefit, 

or disbenefit. See Tables VIII.D.2-1 and VIII.D.2-2 for pollutant- and endpoint-specific incidence 

estimates and Table VIII.D.3-1 for pollutant- and endpoint specific monetized values. 
 

709

We present total monetized impacts based on the PM- and ozone-related premature 

mortality function used. Total monetized impacts therefore reflect the addition of each 

estimate of ozone-related premature mortality (each with its own row in Table VIII.D.1-

1) to estimates of PM-related premature mortality. These estimates represent EPA’s 

preferred approach to characterizing the best estimate of monetized impacts associated 

with the required renewable fuel volumes. 

Emissions and air quality modeling decisions were made early in the analytical 

process and as a result, there are a number of important limitations and uncertainties 

associated with the air quality modeling analysis that must be kept in mind when 

considering the results. A key limitation of the analysis is that it employed interim 

emission inventories, which were enhanced compared to what was described in the 

proposal, but did not include some of the later enhancements and corrections of the final 

emission inventories presented in this FRM (see Section VI.A through VI.C of this 

preamble). Most significantly, our modeling of the air quality impacts of RFS2 relied 

upon interim inventories that assumed that ethanol will make up 34 of the 36 billion 

gallon renewable fuel mandate, that approximately 20 billion gallons of this ethanol will 

be in the form of E85, and that the use of E85 results in fewer emissions of direct PM2.5

from vehicles. The emission impacts, air quality results and benefits analysis would be 

different if, instead of E85, more non-ethanol biofuels are used or mid-level ethanol 

blends are approved and utilized. 

In fact, as explained earlier in this preamble, our more recent analyses indicate 

that ethanol and E85 volumes are likely to be significantly lower than what we assumed 
 

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in the interim inventories. Furthermore, the final emission inventories do not include 

vehicle-related PM reductions associated with E85 use, as discussed in Section VI.A 

through VI.C. There are additional, important limitations and uncertainties associated 

with the interim inventories that must be kept in mind when considering the results, 

which are described in more detail in Section VI. While it is difficult to describe the 

overall impact of these limitations and uncertainties on the quantified and monetized 

health impacts of the increased renewable fuel volumes without updating the air quality 

modeling analysis, we believe the results are still useful for describing potential nationallevel health impacts. 

Additionally, after the air quality modeling was completed, we discovered an 

error in the way that PM2.5 emissions from locomotive engines were allocated to counties 

in the inventory. The mismatched allocations between the reference and control scenarios 

resulted in PM2.5 emission changes that were too high in some counties and too low in 

others, by varying degrees. As a result, we did not present the modeling results for 

specific localized PM2.5 impacts in Section VI.D. However, because the error was 

random and offsetting, there was very little impact on national-level PM2.5 emissions. An 

analysis of the error's impact on the national emission inventories found that direct PM2.5

emissions were inflated by 8% relative to the AEO reference case and by 0.6% relative to 

the RFS1 reference case, leading to a small overestimation of national PM-related 

adverse health impacts. Note that this error did not impact other PM precursor 

inventories such as NOx and SO2. As a result, we have concluded that PM2.5 modeling 

results are still informative for national-level benefits assessment, particularly given that 
 

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other uncertainties in the PM2.5 inventory (such as E85 usage, discussed below) have a 

more important (and offsetting) effect. 
 

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Table VIII.D.1-1 

Estimated 2022 Monetized PM-and Ozone-Related Health Impacts from the Mandated 

Renewable Fuel Volumesa

2022 Total Ozone and PM Benefits, RFS2 Control Case Compared to RFS1 Reference Casea

Premature Ozone 

Mortality Function 

Reference Total Benefits 

(Billions, 2007$, 3% 

Discount Rate)b,c 

Total Benefits 

(Billions, 2007$, 7% 

Discount Rate) b,c

Bell et al., 2004 Total: -$1.4 to -$2.8 

PM: -$0.92 to -$2.3 

Ozone: -$0.52 

Total: -$1.4 to -$2.6 

PM: -$0.84 to -$2.0 

Ozone: -$0.52 

Huang et al., 2005 Total: -$1.8 to -$3.1 

PM: -$0.92 to -$2.3 

Ozone: -$0.83 

Total: -$1.7 to -$2.9 

PM: -$0.84 to -$2.0 

Ozone: -$0.83 

Multi-city analyses 

Schwartz, 2005 Total: -$1.7 to -$3.0 

PM: -$0.92 to -$2.3 

Ozone: -$0.77 

Total: -$1.6 to -$2.8 

PM: -$0.84 to -$2.0 

Ozone: -$0.77 

Bell et al., 2005 Total: -$2.5 to -$3.8 

PM: -$0.92 to -$2.3 

Ozone: -$1.6 

Total: -$2.4 to -$3.6 

PM: -$0.84 to -$2.0 

Ozone: -$1.6 

Ito et al., 2005 Total: -$3.1 to -$4.5 

PM: -$0.92 to -$2.3 

Ozone: -$2.2 

Total: -$3.0 to -$4.2 

PM: -$0.84 to -$2.0 

Ozone: -$2.2 

Meta-analyses 

Levy et al., 2005 Total: -$3.1 to -$4.5 

PM: -$0.92 to -$2.3 

Ozone: -$2.2 

Total: -$3.1 to -$4.3 

PM: -$0.84 to -$2.0 

Ozone: -$2.2 

2022 Total Ozone and PM Benefits, RFS2 Control Case Compared to AEO Reference Casea
 

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Premature Ozone 

Mortality Function 

Reference Total Benefits 

(Millions, 2007$, 3% 

Discount Rate)b,c 

Total Benefits 

(Millions, 2007$, 7% 

Discount Rate) b,c

Bell et al., 2004 Total: -$0.63 to -$1.0 

PM: -$0.29 to -$0.70 

Ozone: -$0.34 

Total: -$0.60 to -$0.98 

PM: -$0.26 to -$0.63 

Ozone: -$0.34 

Huang et al., 2005 Total: -$0.84 to -$1.3 

PM: -$0.29 to -$0.70 

Ozone: -$0.55 

Total: -$0.81 to -$1.2 

PM: -$0.26 to -$0.63 

Ozone: -$0.55 

Multi-city analyses 

Schwartz, 2005 Total: -$0.80 to -$1.2 

PM: -$0.29 to -$0.70 

Ozone: -$0.51 

Total: -$0.77 to -$1.1 

PM: -$0.26 to -$0.63 

Ozone: -$0.51 

Bell et al., 2005 Total: -$1.3 to -$1.8 

PM: -$0.29 to -$0.70 

Ozone: -$1.0 

Total: -$1.3 to -$1.7 

PM: -$0.26 to -$0.63 

Ozone: -$1.0 

Ito et al., 2005 Total: -$1.7 to -$2.2 

PM: -$0.29 to -$0.70 

Ozone: -$1.5 

Total: -$1.7 to -$2.1 

PM: -$0.26 to -$0.63 

Ozone: -$1.5 

Meta-analyses 

Levy et al., 2005 Total: -$1.8 to -$2.2 

PM: -$0.29 to -$0.70 

Ozone: -$1.5 

Total: -$1.7 to -$2.1 

PM: -$0.26 to -$0.63 

Ozone: -$1.5 

Notes:

a Total includes premature mortality-related and morbidity-related ozone and PM2.5 benefits. Range was 

developed by adding the estimate from the ozone premature mortality function to the estimate of PM2.5-

related premature mortality derived from either the ACS study (Pope et al., 2002) or the Six-Cities study 

(Laden et al., 2006).

b

 Note that total benefits presented here do not include a number of unquantified benefits categories. A 

detailed listing of unquantified health and welfare effects is provided in Table VIII.D.1-2. 
 

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c

 Results reflect the use of both a 3 and 7 percent discount rate, as recommended by EPA’s Guidelines for 

Preparing Economic Analyses and OMB Circular A-4. Results are rounded to two significant digits for 

ease of presentation and computation. 

The monetized estimates in Table VIII.D.1-1 include all of the human health 

impacts we are able to quantify and monetize at this time. However, the full complement 

of human health and welfare effects associated with PM and ozone remain unquantified 

because of current limitations in methods or available data. We have not quantified a 

number of known or suspected health effects linked with ozone and PM for which 

appropriate health impact functions are not available or which do not provide easily 

interpretable outcomes (i.e., changes in heart rate variability). Additionally, we are 

unable to quantify a number of known welfare effects, including acid and particulate 

deposition damage to cultural monuments and other materials, and environmental 

impacts of eutrophication in coastal areas. These are listed in Table VIII.D.1-2. 
 

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Table VIII.D.1-2 

Unquantified and Non-Monetized Potential Effects from the Mandated Renewable Fuel 

Volumes 

Pollutant/Effects Effects Not Included in Analysis - Changes in: 

Ozone Healtha Chronic respiratory damageb 

Premature aging of the lungsb 

Non-asthma respiratory emergency room visits 

Exposure to UVb (+/-)e

Ozone Welfare Yields for 

-commercial forests 

-some fruits and vegetables 

-non-commercial crops 

Damage to urban ornamental plants 

Impacts on recreational demand from damaged forest aesthetics 

Ecosystem functions 

Exposure to UVb (+/-)e 

PM Healthc Premature mortality - short term exposuresd

Low birth weight 

Pulmonary function 

Chronic respiratory diseases other than chronic bronchitis 

Non-asthma respiratory emergency room visits 

Exposure to UVb (+/-)e 

PM Welfare Residential and recreational visibility in non-Class I areas 

Soiling and materials damage 

Damage to ecosystem functions 

Exposure to UVb (+/-)e 
 

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Nitrogen and Sulfate 

Deposition Welfare 

Commercial forests due to acidic sulfate and nitrate deposition 

Commercial freshwater fishing due to acidic deposition 

Recreation in terrestrial ecosystems due to acidic deposition 

Existence values for currently healthy ecosystems 

Commercial fishing, agriculture, and forests due to nitrogen deposition 

Recreation in estuarine ecosystems due to nitrogen deposition 

Ecosystem functions 

Passive fertilization 

CO Health Behavioral effects 

HC/Toxics Healthf Cancer (benzene, 1,3-butadiene, formaldehyde, acetaldehyde) 

Anemia (benzene) 

Disruption of production of blood components (benzene) 

Reduction in the number of blood platelets (benzene) 

Excessive bone marrow formation (benzene) 

Depression of lymphocyte counts (benzene) 

Reproductive and developmental effects (1,3-butadiene) 

Irritation of eyes and mucus membranes (formaldehyde) 

Respiratory irritation (formaldehyde) 

Asthma attacks in asthmatics (formaldehyde) 

Asthma-like symptoms in non-asthmatics (formaldehyde) 

Irritation of the eyes, skin, and respiratory tract (acetaldehyde) 

Upper respiratory tract irritation and congestion (acrolein) 

HC/Toxics Welfare Direct toxic effects to animals 

Bioaccumulation in the food chain 

Damage to ecosystem function 

Odor 

Notes: 
 

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a

 The public health impact of biological responses such as increased airway responsiveness to stimuli, 

inflammation in the lung, acute inflammation and respiratory cell damage, and increased susceptibility to 

respiratory infection are likely partially represented by our quantified endpoints. 

b

 The public health impact of effects such as chronic respiratory damage and premature aging of the lungs 

may be partially represented by quantified endpoints such as hospital admissions or premature mortality, 

but a number of other related health impacts, such as doctor visits and decreased athletic performance, 

remain unquantified. 

c

 In addition to primary economic endpoints, there are a number of biological responses that have been 

associated with PM health effects including morphological changes and altered host defense mechanisms. 

The public health impact of these biological responses may be partly represented by our quantified 

endpoints. 

d

 While some of the effects of short-term exposures are likely to be captured in the estimates, there may be 

premature mortality due to short-term exposure to PM not captured in the cohort studies used in this 

analysis. However, the PM mortality results derived from the expert elicitation do take into account 

premature mortality effects of short term exposures. 

e

 May result in benefits or adverse health impacts. 

f

 Many of the key hydrocarbons related to this rule are also hazardous air pollutants listed in the Clean Air 

Act. 

While there will be impacts associated with air toxic pollutant emission changes 

that result from the increased use of renewable fuels, we do not attempt to monetize those 

impacts. This is primarily because currently available tools and methods to assess air 

toxics risk from mobile sources at the national scale are not adequate for extrapolation to 

incidence estimations or benefits assessment. The best suite of tools and methods 

currently available for assessment at the national scale are those used in the NationalScale Air Toxics Assessment (NATA). The EPA Science Advisory Board specifically 
 

718

commented in their review of the 1996 NATA that these tools were not yet ready for use 

in a national-scale benefits analysis, because they did not consider the full distribution of 

exposure and risk, or address sub-chronic health effects.365 While EPA has since 

improved the tools, there remain critical limitations for estimating incidence and 

assessing benefits of reducing mobile source air toxics. EPA continues to work to 

address these limitations; however, we did not have the methods and tools available for 

national-scale application in time for the analysis of the final rule.366 

 2. Quantified Human Health Impacts 

Tables VIII.D.2-1 and VIII.D.2-2 present the annual PM2.5 and ozone health 

impacts in the 48 contiguous U.S. states associated with the required renewable fuel 

volumes relative to both the RFS1 and AEO reference cases for 2022. For each endpoint 

presented in Tables VIII.D.2-1 and VIII.D.2-2, we provide both the mean estimate and 

the 90% confidence interval. 

Using EPA’s preferred estimates, based on the ACS and Six-Cities studies and no 

threshold assumption in the model of mortality, we estimate that the required renewable 

fuel volumes will result in between 110 and 270 cases of PM2.5-related premature deaths 

 

365 Science Advisory Board. 2001. NATA – Evaluating the National-Scale Air Toxics Assessment for 

1996 – an SAB Advisory. http://www.epa.gov/ttn/atw/sab/sabrev.html. 

366 In April, 2009, EPA hosted a workshop on estimating the benefits or reducing hazardous air pollutants. 

This workshop built upon the work accomplished in the June 2000 Science Advisory Board/EPA 

Workshop on the Benefits of Reductions in Exposure to Hazardous Air Pollutants, which generated 

thoughtful discussion on approaches to estimating human health benefits from reductions in air toxics 

exposure, but no consensus was reached on methods that could be implemented in the near term for a broad 

selection of air toxics. Please visit http://epa.gov/air/toxicair/2009workshop.html for more information 

about the workshop and its associated materials. 
 

719

annually in 2022 when compared to the RFS1 reference case. When compared to the 

AEO reference scenario, we estimate that the required renewable fuel volumes will result 

in between 33 and 85 cases of PM2.5-related premature deaths annually in 2022 For 

ozone-related premature mortality, we estimate that national changes in ambient ozone 

will contribute to between 54 to 250 additional premature mortalities in 2022 as a result 

of the required renewable fuel volumes relative to the RFS1 scenario. When compared to 

the AEO reference scenario, we estimate that the required renewable fuel volumes will 

contribute to between 36 to 160 additional ozone-related premature mortalities in 2022. 
 

720

Table VIII.D.2-1 

Estimated PM2.5-Related Health Impacts Associated with the Mandated Renewable Fuel 

Volumesa

Health Effect 

2022 RFS2 Control Case 

Compared to RFS1 

Reference Case 

(5th% - 95th%ile) 

2022 RFS2 Control Case 

Compared to AEO Reference

Case 

(5th% - 95th%ile) 

Premature Mortality – Derived from Epidemiology 

Literatureb

 Adult, age 30+, ACS Cohort Study (Pope et al., 2002)

 Adult, age 25+, Six-Cities Study (Laden et al., 2006) 

 Infant, age <1 year (Woodruff et al., 1997) 

-110 

(-42 - -170) 

-270 

(-150 - -400) 

0 

(0 - -1) 

-33 

(-13 - -53) 

-85 

(-46 - -120) 

0 

(0 - -1) 

Chronic bronchitis (adult, age 26 and over) -65 

(-26 - -110) 

-19 

(-4 - -18) 

Non-fatal myocardial infarction (adult, age 18 and over) -180 

(-65 - -290) 

-51 

(-19 - -84) 

Hospital admissions - respiratory (all ages)c

 -26 

(-25 - -26) 

-7 

(-5 - -8) 

Hospital admissions - cardiovascular (adults, age >18)d -55 

(-44 - -70) 

-12 

(-9 - -16) 

Emergency room visits for asthma (age 18 years and 

younger) 

-180 

(-110 - -260) 

-99 

(-58 - -140) 
 

721

Acute bronchitis, (children, age 8-12) -160 

(0 - -330) 

-50 

(0 - -100) 

Lower respiratory symptoms (children, age 7-14) -1,900 

(-910 - -2,900) 

-600 

(-290 - -910) 

Upper respiratory symptoms (asthmatic children, age 9-

18) 

-1,400 

(-450 - -2,400) 

-450 

(-140 - -750) 

Asthma exacerbation (asthmatic children, age 6-18) -1,700 

(-190 - -4,800) 

-540 

(-60 - -1,500) 

Work loss days -11,000 

(-10,000 - -13,000) 

-3,200 

(-2,800 - -3,700) 

Minor restricted activity days (adults age 18-65) -68,000 

(-57,000 - -78,000) 

-19,000 

(-16,000 - -22,000) 

Notes:

a Note that negative incidence expressed in this table reflects disbenefits; in other words, an increase in total 

aggregated national-level PM-related health impacts. Incidence is rounded to two significant digits. 

Estimates represent incidence within the 48 contiguous United States. 

b PM-related adult mortality based upon the American Cancer Society (ACS) Cohort Study (Pope et al., 

2002) and the Six-Cities Study (Laden et al., 2006). Note that these are two alternative estimates of adult 

mortality and should not be summed. PM-related infant mortality based upon a study by Woodruff, Grillo, 

and Schoendorf, (1997).367

c Respiratory hospital admissions for PM include admissions for chronic obstructive pulmonary disease 

(COPD), pneumonia and asthma. 

d Cardiovascular hospital admissions for PM include total cardiovascular and subcategories for ischemic 

heart disease, dysrhythmias, and heart failure.

 

367 Woodruff, T.J., J. Grillo, and K.C. Schoendorf. 1997. “The Relationship Between Selected Causes of 

Postneonatal Infant Mortality and Particulate Air Pollution in the United States.” Environmental Health 

Perspectives 105(6):608-612. 
 

722

Table VIII.D.2-2 

Estimated Ozone-Related Health Impacts Associated with the Mandated Renewable Fuel 

Volumesa

Health Effect 

2022 RFS2 Control Case 

Compared to RFS1 Reference 

Case 

(5th% - 95th%ile) 

2022 RFS2 Control Case 

Compared to AEO Reference 

Case 

(5th% - 95th%ile) 

Premature Mortality, All agesb 

Multi-City Analyses 

 Bell et al. (2004) – Non-accidental 

 Huang et al. (2005) – Cardiopulmonary 

 Schwartz (2005) – Non-accidental 

Meta-analyses:

 Bell et al. (2005) – All cause 

 Ito et al. (2005) – Non-accidental 

 Levy et al. (2005) – All cause 

-54 

(-17 - -92) 

-90 

(-31 - -149) 

-83 

(-24 - -140) 

-180 

(-80 - -270) 

-240 

(-140 - -350) 

-250 

(-170 - -330) 

-36 

(-10 - -62) 

-59 

(-18 - -100) 

-55 

(-13 - -97) 

-120 

(-49 - -180) 

-160 

(-90 - -230) 

-160 

(-110 - -220) 

Hospital admissions- respiratory causes (adult, 65

and older)c

-470 

(-20 - -860) 

-310 

(-5 - -580) 

Hospital admissions -respiratory causes (children

under 2) 

-83 

(-24 - -140) 

-190 

(-52 - -330) 
 

723

Emergency room visit for asthma (all ages) -260 

(0 - -740) 

-180 

(0 - -510) 

Minor restricted activity days (adults, age 18-65) -300,000 

(-110,000 - -500,000) 

-200,000 

(-59,000 - -340,000) 

School absence days -110,000 

(-35,000 - -180,000) 

-75,000 

(-19,000 - -120,000) 

Notes: 

a

 Note that negative incidence expressed in this table reflects disbenefits; in other words, an increase in total 

aggregated national-level ozone-related health impacts. Incidence is rounded to two significant digits. 

Estimates represent incidence within the 48 contiguous United States. Note that negative incidence 

estimates represent additional cases of an endpoint related to pollution increases associated with the 

increased use of renewable fuels. 

b

 Estimates of ozone-related premature mortality are based upon incidence estimates derived from several 

alternative studies: Bell et al. (2004); Huang et al. (2005); Schwartz (2005) ; Bell et al. (2005); Ito et al. 

(2005); Levy et al. (2005). The estimates of ozone-related premature mortality should therefore not be 

summed. 

c Respiratory hospital admissions for ozone include admissions for all respiratory causes and subcategories 

for COPD and pneumonia. 

 3. Monetized Impacts

 

Table VIII.D.3-1 presents the estimated monetary value of the increase in ozone 

and PM2.5-related health effects incidence associated with the required renewable fuel 

volumes relative to both the RFS1 and AEO reference cases for 2022. All monetized 

estimates are stated in 2007$. These estimates account for growth in real gross domestic 
 

724

product (GDP) per capita between the present and the year 2022. As the table indicates, 

total adverse health impacts are driven primarily by the increase in PM2.5- and ozonerelated premature fatalities. 

Our estimate of monetized adverse health impacts in 2022 for the required 

renewable fuel volumes relative to the RFS1 reference case, using the ACS and SixCities PM mortality studies and the range of ozone mortality assumptions, are between 

$1.4 billion and $4.5 billion, assuming a 3 percent discount rate, or between $1.4 billion 

and $4.3 billion, assuming a 7 percent discount rate. The total monetized adverse health 

impacts in 2022 for the required renewable fuel volumes relative to the AEO reference 

case are between $0.63 billion and $2.2 billion assuming a 3 percent discount rate, and 

between $0.60 billion and $2.1 billion assuming a 7 percent discount rate. We are unable 

to quantify a number of health and environmental impact categories (see Table VIII.D.1-

2). These unquantified impacts may be substantial, although their magnitude is highly 

uncertain. 
 

725

Table VIII.D.3-1 

Estimated Monetary Value of Health and Welfare Effect Incidence (in millions of 2007$)

a,b

 2022 RFS2 Control 

Case Compared to 

RFS1 Reference 

Case 

2022 RFS2 Control 

Case Compared to AEO

Reference Case 

PM2.5-Related Health Effect Estimated Mean Value of Reductions 

(5th and 95th %ile) 

Adult, age 30+ - ACS study 

(Pope et al., 2002) 

 3% discount rate 

 7% discount rate 

-$860 

(-$100 - -$2,300) 

-$770 

(-$91 - -$2,000) 

-$270 

(-$32 - -$700) 

-$240 

(-$28 - -$630) 

Adult, age 25+ - Six-cities 

study (Laden et al., 2006) 

 3% discount rate 

 7% discount rate 

-$2,200 

(-$29 - -$5,500) 

-$2,000 

(-$26 - -$5,000) 

-$680 

(-$90 - -$1,700) 

-$620 

(-$81 - -$1,600) 

Premature Mortality – 

Derived from 

Epidemiology 

Studiesc,d,

Infant Mortality, <1 year – 

(Woodruff et al. 1997) 

-$4.0 

(-$3.0 - -$15) 

-$1.7 

(-$1.3 - -$6.7) 
 

726

Chronic bronchitis (adults, 26 and over) -$32 

(-$2.5 - -$110) 

-$9.4 

(-$0.72 - -$33) 

Non-fatal acute myocardial infarctions 

 3% discount rate 

 7% discount rate 

-$23 

(-$4.1 - -$58) 

-$23 

(-$3.8 - -$58) 

-$6.6 

(-$1.0 - -$17) 

-$6.4 

(-$0.95 - -$16) 

Hospital admissions for respiratory causes -$0.39 

(-$0.19 - -$0.57 

-$0.11 

(-$0.06 - -$0.17) 

Hospital admissions for cardiovascular causes -$1.5 

(-$0.96 - -$2.1) 

-$0.33 

(-$0.20 - -$0.45) 

Emergency room visits for asthma -$0.07 

(-$0.04 - -$0.10) 

-$0.04 

(-$0.02 - -$0.06) 

Acute bronchitis (children, age 8–12) -$0.01 

($0 - -$0.03) 

-$0.004 

($0 - -$0.01) 

Lower respiratory symptoms (children, 7–14) -$0.04 

(-$0.01 - -$0.07) 

-$0.01 

(-$0.004 - -$0.02) 

Upper respiratory symptoms (asthma, 9–11) -$0.04 

(-$0.01 - -$0.10) 

-$0.01 

(-$0.004 - -$0.03) 

Asthma exacerbations -$0.09 

(-$0.009 - -$0.28) 

-$0.03 

(-$0.003 - -$0.09) 

Work loss days -$1.7 

(-$1.5 - -$1.9) 

-$0.49 

(-$0.42 - -$0.55) 

Minor restricted-activity days (MRADs) -$4.3 

(-$2.5 - -$6.2) 

-$1.2 

(-$0.69 - -$1.7) 

Ozone-related Health Effect 
 

727

Bell et al., 2004 -$480 

(-$51 - -$1,300) 

-$320 

(-$32 - -$880) 

Huang et al., 2005 -$800 

(-$90 - -$2,200) 

-$530 

(-$56 - -$1,400) 

Premature Mortality, All ages – 

Derived from Multi-city 

analyses

Schwartz, 2005 -$740 

(-$76 - -$2,000) 

-$490 

(-$48 - -$1,300) 

Bell et al., 2005 -$1,600 

(-$200 - -$4,000) 

-$1,000 

(-$130 - -$,700) 

Ito et al., 2005 -$2,200 

(-$290 - -$5,400) 

-$1,400 

(-$190 - -$3,600) 

Premature Mortality, All ages – 

Derived from Meta-analyses 

Levy et al., 2005 -$2,200 

(-$300 - -$5,300) 

-$1,400 

(-$200 - -$3,500) 

Hospital admissions- respiratory causes (adult, 65 and 

older) 

-$11 

(-$0.49 - -$20) 

-$7.4 

(-$0.13 - -$14) 

Hospital admissions- respiratory causes (children, under 2) -$3.0 

(-$1.0 - -$4,9) 

-$1.9 

(-$0.52 - -$3.3) 

Emergency room visit for asthma (all ages) -$0.10 

(-$0.009 - -$0.26) 

-$0.07 

(-$0.008 - -$0.18) 

Minor restricted activity days (adults, age 18-65) -$19 

(-$6.4 - -$35) 

-$13 

(-$3.6 - -$24) 

School absence days -$10 

(-$3.1 - -$16) 

-$6.7 

(-$1.7 - -$11) 

Notes: 

a

 Negatives indicate a disbenefit, or an increase in health effect incidence. Monetary impacts are rounded 

to two significant digits for ease of presentation and computation. PM and ozone impacts are nationwide. 

b

 Monetary impacts adjusted to account for growth in real GDP per capita between 1990 and the analysis 

year (2022) 
 

728

c

 Valuation assumes discounting over the SAB recommended 20 year segmented lag structure. Results 

reflect the use of 3 percent and 7 percent discount rates consistent with EPA and OMB guidelines for 

preparing economic analyses. 

 4. What Are the Limitations of the Health Impacts Analysis?

Every benefit-cost analysis examining the potential effects of a change in 

environmental protection requirements is limited to some extent by data gaps, limitations 

in model capabilities (such as geographic coverage), and uncertainties in the underlying 

scientific and economic studies used to configure the benefit and cost models. 

Limitations of the scientific literature often result in the inability to estimate quantitative 

changes in health and environmental effects, such as premature mortality associated with 

exposure to carbon monoxide. Deficiencies in the economics literature often result in the 

inability to assign economic values even to those health and environmental outcomes 

which can be quantified. These general uncertainties in the underlying scientific and 

economics literature, which can lead to valuations that are higher or lower, are discussed 

in detail in the RIA and its supporting references. Key uncertainties that have a bearing 

on the results of the benefit-cost analysis of the coordinated strategy include the 

following: 

• The exclusion of potentially significant and unquantified benefit categories (such as 

health, odor, and ecological benefits of reduction in air toxics, ozone, and PM); 

• Errors in measurement and projection for variables such as population growth; 

• Uncertainties in the estimation of future year emissions inventories and air quality; 
 

729

• Uncertainty in the estimated relationships of health and welfare effects to changes in 

pollutant concentrations including the shape of the C-R function, the size of the effect 

estimates, and the relative toxicity of the many components of the PM mixture; 

• Uncertainties in exposure estimation; and 

• Uncertainties associated with the effect of potential future actions to limit emissions. 

As Table VIII.D.3-1 indicates, total impacts are driven primarily by the additional 

premature mortalities estimated to occur each year. Some key assumptions underlying 

the premature mortality estimates include the following, which may also contribute to 

uncertainty: 

• Inhalation of fine particles is causally associated with premature death at 

concentrations near those experienced by most Americans on a daily basis. Although 

biological mechanisms for this effect have not yet been completely established, the 

weight of the available epidemiological, toxicological, and experimental evidence 

supports an assumption of causality. The impacts of including a probabilistic 

representation of causality were explored in the expert elicitation-based results of the 

PM NAAQS RIA. 

• All fine particles, regardless of their chemical composition, are equally potent in 

causing premature mortality. This is an important assumption, because PM related to 

fuel use in mobile sources may differ significantly from PM precursors released from 

electric generating units and other industrial sources. However, no clear scientific 

grounds exist for supporting differential effects estimates by particle type. 
 

730

• The C-R function for fine particles is approximately linear within the range of 

ambient concentrations under consideration. Thus, the estimates include health 

benefits from reducing fine particles in areas with varied concentrations of PM, 

including both regions that may be in attainment with PM2.5 standards and those that 

are at risk of not meeting the standards. 

• There is uncertainty in the magnitude of the association between ozone and premature 

mortality. The range of ozone impacts associated with the increased use of renewable 

fuels is estimated based on the risk of several sources of ozone-related mortality 

effect estimates. In a recent report on the estimation of ozone-related premature 

mortality published by the National Research Council, a panel of experts and 

reviewers concluded that short-term exposure to ambient ozone is likely to contribute 

to premature deaths and that ozone-related mortality should be included in estimates 

of the health impacts of reducing ozone exposure.368 EPA has requested advice from 

the National Academy of Sciences on how best to quantify uncertainty in the 

relationship between ozone exposure and premature mortality in the context of 

quantifying health impacts. 

Acknowledging the omission of a range of health and environmental impacts, and 

the uncertainties mentioned above, we present a best estimate of the total monetized 

impacts based on our interpretation of the best available scientific literature and methods 

supported by EPA’s technical peer review panel, the Science Advisory Board’s Health 

Effects Subcommittee (SAB-HES). The National Academies of Science (NRC, 2002) 

 

368 National Research Council (NRC), 2008. Estimating Mortality Risk Reduction and Economic Benefits 

from Controlling Ozone Air Pollution. The National Academies Press: Washington, D.C. 
 

731

has also reviewed EPA’s methodology for analyzing air pollution-related health and 

environmental impacts. EPA addressed many of these comments in the analysis of the 

final PM NAAQS.369,370 This analysis incorporates this most recent work to the extent 

possible. 

 E. Summary of Costs and Benefits 

 

Presented in this section are a summary of costs, benefits, and net benefits of the 

renewable fuel volumes required by final RFS2 program. Table VIII.E–1 shows the 

estimated annual societal costs and benefits of the increased use of renewable fuels in 

2022. The table also presents estimated annual net benefits for 2022. In this table, fuel 

savings are presented as negative costs associated with the increased use of renewable 

fuels (rather than positive savings). Note that all costs and benefits are presented in 

annual terms; we were unable to estimate a stream of costs and benefits for many of the 

cost-benefit categories and were therefore unable to estimate net present value. 

Table VIII.E-1 presents the benefits of reduced GHG emissions—and 

consequently the annual quantified benefits (i.e., total benefits) and quantified net 

benefits—for each of five interim SCC values considered by EPA. As discussed in 

Section VIII.C, there is a very high probability (very likely according to the IPCC) that 

the benefit estimates from GHG reductions are underestimates because, in part, models 

 

369 National Research Council (NRC). 2002. Estimating the Public Health Benefits of Proposed Air 

Pollution Regulations. The National Academies Press: Washington, D.C. 

370 U.S. Environmental Protection Agency. October 2006. Final Regulatory Impact Analysis (RIA) for the 

Proposed National Ambient Air Quality Standards for Particulate Matter. Prepared by: Office of Air and 

Radiation. Available at HTTP://www.epa.gov/ttn/ecas/ria.html. 
 

732

used to calculate SCC values do not include information about impacts that have not been 

quantified. 

Table VIII.E-1 

Quantified Costs and Benefits of the Volumes Required by RFS2 Relative to the AEO 

Reference Case in 2022 (Billions of 2007 dollars)371

 2022 

Quantified Annual Costs 

Overall Fuel Costa -$11.8 

Quantified Annual Benefits 

Reduced GHG Emissions (by SCC) 

 

371 In this table, we have included only the estimates from the sector models as they provided a more 

detailed breakdown of costs and benefits. We have excluded estimates of the agricultural sector impacts of 

the RFS2 in Table VIII F-1 since these impacts are considered economic rents. 
 

733

SCC 5% $0.6 to $1.1 

SCC 5% Newell-Pizer $1.2 to $2.2 

SCC from 3% and 5% $2.4 to $4.2 

SCC 3% $4.1 to $7.3 

SCC 3% Newell-Pizer $6.8 to $12.2 

PM2.5- and Ozone-Related 

Benefitsb,c

-$0.63 to -$2.2 

Energy Security Impacts $2.6 

Total Benefits (by SCC) 

SCC 5% $1 to $3.1 

SCC 5% Newell-Pizer $1.6 to $4.2 

SCC from 3% and 5% $2.8 to $6.2 

SCC 3% $4.5 to $9.3 

SCC 3% Newell-Pizer $7.2 to $14.2 

Quantified Net Benefits 
 

734

Net Benefits (by SCC) 

SCC 5% $13 to $15 

SCC 5% Newell-Pizer $13 to $16 

SCC from 3% and 5% $15 to $18 

SCC 3% $16 to $21 

SCC 3% Newell-Pizer $19 to $26 

a

 Negative costs represent fuel savings from decreased gasoline and diesel consumption. 

b

 Negative benefits indicate a disbenefit, or an increase in monetized health impacts. Total includes 

premature mortality-related and morbidity-related ozone and PM2.5 impacts. Range was developed by 

adding the estimate from the ozone premature mortality function to the estimate of PM2.5-related premature 

mortality derived from either the ACS study (Pope et al., 2002) or the Six-Cities study (Laden et al., 2006).

c

 The PM2.5-related impacts presented in this table assume a 3% discount rate in the valuation of premature 

mortality to account for a twenty-year segmented cessation lag. If a 7% discount rate had been used, the 

values would be approximately 9% lower. 
 

735

IX. Impacts on Water 

A. Background 

 As the production of biofuels increases as required by this rule, there may be adverse 

impacts on both water quality and water quantity affecting drinking water sources and ecological 

habitats. The impacts could come from several different pathways: growing crops for the biofuel 

feedstock as well as production, storage, and distribution of the biofuels. Increased production 

of biofuel crops may lead to changes in the management of cropland and the use of fertilizer and 

pesticides that could lead to greater loadings of nutrients, pesticides, and sediment to our water 

resources. While there are methods to minimize and mitigate the effects on water resources, 

there is still a potential to impact both human health and the environment. Since both the 

irrigation of corn and ethanol production use large quantities of water, the supply of water could 

also be significantly affected in some locations. 

 1. Agriculture and Water Quality

 There are three major pathways for contaminants to reach water from agricultural lands: 

run off from the land’s surface, man-made ditches or subsurface tile drains, and leaching to 

ground water. Many factors influence the potential for contaminants such as fertilizers, 

sediment, and pesticides to reach water from agricultural lands, including: soil type, slope, 

climate, crop type, and management. Management of agricultural lands can take many forms, 

but key factors include nutrient and pesticide application rates and application methods, tillage, 
 

736

use of conservation practices and crop rotations by farmers, and acreage and intensity of 

artificially drained lands. 

 To examine the potential water-related impacts of growing crops for biofuels, EPA 

focused its analysis on corn production for several reasons. First, corn acres have increased 

dramatically, 20% from 2006 to 2007. Although corn acres have since declined somewhat, total 

corn acres in 2009 remained the second highest since 1946.372 Second, corn kernels are 

currently the predominant and most economically viable feedstock for significant ethanol 

production. In addition, corn stover (stalks, leaves) will likely be the predominant feedstock for 

cellulosic ethanol production in the Upper Mississippi River Basin where we modeled water 

quality impacts. And third, corn production can contribute significantly to water pollution. Corn 

has the highest fertilizer and pesticide use per acre and accounts for the largest share of nitrogen 

fertilizer use among all crops373. Corn generally utilizes only 40 to 60 percent of the applied 

nitrogen fertilizer or the residual organic nitrogen from sources such as manure or soybeans. The 

remaining nitrogen is available to leave the field and run off to surface waters, leach into ground 

water, or volatilize to the air where it can return to water through depositional processes. 

 Over the past 20 years, corn has been increasingly grown in rotation with other crops, 

especially soybeans. As corn prices increase relative to prices for other crops, more farmers 

choose to grow corn every year (continuous corn). Continuous corn production results in 

 

372U.S. Department of Agriculture, National Agricultural Statistics Service, ‘‘Crop Production’’, August 12, 2009, 

available online at: http://usda.mannlib.cornell.edu/usda/current/CropProd/CropProd-08-12-2009.pdf 

373 Committee on Water Implications of Biofuels Production in the United States, National Research Council, 2008, 

Water implications of biofuels production in the United States, The National Academies Press, Washington, DC, 88 

pp. 
 

737

significantly greater nitrogen losses annually than a corn-soybean rotation and lower yields per 

acre. In response, farmers may add higher rates of nitrogen fertilizer to try to match yields of 

corn grown in rotation. Growing continuous corn also increases the viability of pests such as 

corn rootworm. Farmers may increase the use of pesticides to control these pests. As corn acres 

increase, use of the common herbicides like atrazine and glyphosate (e.g. Roundup) may also 

increase. 

 High corn prices may encourage farmers to grow corn on lands that are marginal for row 

crop production such as hay land or pasture. Typically, agricultural producers apply far less 

fertilizers and pesticides on pasture land than land in row crops. Corn yield on these marginal 

lands will be lower and may require higher fertilizer rates. Disturbances of these soils can 

release nitrogen that has been stored in the soil. Since nitrogen fertilizer prices are tied to oil 

prices, fertilizer costs have fluctuated. How agricultural producers have responded to these 

changes in both corn and fertilizer prices is unclear. 

 Artificial drainage is another important factor in determining the losses of nutrients from 

cropland. Artificial drainage consists either of subsurface tiles/pipes or man-made ditches that 

move water from wet soils to surface waters so crops can be planted. In a few areas, drains 

move water to wells and then groundwater instead of to surface water. Artificial drainage has 

transformed large expanses of historic wetland soils into productive agriculture lands. However, 

the artificial drains or ditches also move nutrients and pesticides more quickly to surface waters 

without any of the attenuation that would occur if these contaminants moved through soils or 

wetlands. The highest proportion of tile drainage occurs in the Upper Mississippi and the Ohio-
 

738

Tennessee River basins in areas of intensive corn production.374 Manmade ditches 

predominate in areas like the Eastern Shore of the Chesapeake Bay. 

 The increase in corn production and prices may also have significant impacts on 

voluntary conservation programs funded by the U.S. Department of Agriculture (USDA). 

Conservation programs provide important funding to help agricultural producers implement 

practices to protect water quality and other resources. As land values increase due to higher 

crop prices, USDA payments may not keep up with the need for farmers and tenant farmers, to 

make an adequate return. For example, the cost of farmland in Iowa increased an average of 18% 

in 2007 from 2006 prices. 

 Both land retirement programs, like the Conservation Reserve Program (CRP), and 

working land programs, like the Environmental Quality Incentives Program (EQIP), can be 

affected. Under CRP, USDA contracts with farmers to take land out of crop production to plant 

grasses or trees. Generally farmers put land into CRP because it is less productive and has other 

characteristics that make the cropland more environmentally sensitive, such as high erosion rates. 

CRP provides valuable environmental benefits both for water quality and for wildlife habitat. 

Midwestern states, where much of U.S. corn is grown, tend to have lower CRP reenrollment 

rates than the national average. Under EQIP, USDA makes cost-share payments to farmers to 

implement conservation practices. Some of the most cost-effective practices implemented 

through these conservation programs include: riparian buffers; crop rotation; appropriate rate, 

 

374 U.S. Environmental Protection Agency, EPA Science Advisory Board, Hypoxia in the northern Gulf of Mexico, 

EPA–SAB–08–003, 275 p, available online at: 

http://yosemite.epa.gov/sab/sabproduct.nsf/C3D2F27094E03F90852573B800601D93/$File/EPA–SAB–08–

003complete.unsigned.pdf
 

739

timing, and method of fertilizer application; cover crops; and, on tile-drained lands, treatment 

wetlands and controlled drainage. If producers believe that participation in conservation 

programs may reduce their profits, they may be less willing to participate and/or require higher 

payments to offset perceived losses. 

 The water quality impacts of agricultural cellulosic feedstocks such as corn stover and 

switchgrass are unknown, since cellulosic ethanol is not currently produced commercially. Corn 

stover appears to be one of the most viable feedstock for cellulosic ethanol, especially in the 

Corn Belt states. When left in the field, corn stover maintains the soil organic carbon which has 

many benefits as a source of nutrients, preventing erosion by wind and water, and increasing soil 

aeration and water infiltration. If corn stover is overharvested, there may be impacts to both soil 

quality and water quality. Unlike corn, switchgrass is a native, perennial crop that does not 

require high inputs of fertilizers or pesticides. As a perennial crop, there is limited sediment 

runoff compared to annual crops. There is very minimal acreage of switchgrass grown at the 

present time, so it is difficult to predict what inputs farmers will use to cultivate it as a 

commercial crop. Some concern has been expressed about farmers increasing fertilizer 

application rates and irrigation on switchgrass to increase yields. 

 2. Ecological Impacts

 Nitrogen and phosphorus enrichment due to human activities is one of the leading 

problems facing our nation’s lakes, reservoirs, and estuaries. Nutrient enrichment also has 

negative impacts on aquatic life in streams; adverse health effects on humans and domestic 
 

740

animals; and impairs aesthetic and recreational use. Excess nutrients can lead to excessive 

growth of algae in rivers and streams, and aquatic plants in all waters. For example, declines in 

invertebrate community structure have been correlated directly with increases in phosphorus 

concentration. High concentrations of nitrogen in the form of ammonia are toxic to aquatic 

animals. Excessive levels of algae have also been shown to be damaging to invertebrates. 

Finally, fish and invertebrates will experience growth problems and can die if either oxygen is 

depleted or pH increases are severe. Both of these conditions are symptoms of eutrophication. As 

a biologic system becomes more enriched by nutrients, different species of algae may spread and 

species composition can shift. 

 Nutrient pollution is widespread. Although the most widely known examples of 

significant nutrient impacts are in the Gulf of Mexico and the Chesapeake Bay, there are known 

impacts in over 80 estuaries/bays, and thousands of rivers, streams, and lakes. Waterbodies in 

virtually every state and territory in the U.S. are impacted by nutrient-related degradation. 

Reducing nutrient pollution is a priority for EPA. 

 3. Impacts to the Gulf of Mexico

 According to the National Research Council, nutrients and sediment are the two 

primary water quality problems in the Mississippi River Basin and the Gulf of Mexico.375 

Production of corn for ethanol may exacerbate these existing serious water quality problems. 

 

375 Committee on the Mississippi River and the Clean Water Act, National Research Council, 2008, Mississippi 

River Water Quality and the Clean Water Act: Progress, Challenges, and Opportunities, The National Academies 

Press, Washington, DC, 252 pp. 
 

741

Nitrogen fertilizer applications to corn are already the major source of total nitrogen loadings to 

the Mississippi River. A large area of low oxygen, or hypoxia, forms in the Gulf of Mexico every 

year, often called the ‘‘dead zone.’’ The primary cause of the hypoxia is excess nutrients 

(nitrogen and phosphorus) from the Upper Midwest flowing into the Mississippi River to the 

Gulf. These nutrients trigger excessive algal growth (or eutrophication) resulting in reduced 

sunlight, loss of aquatic habitat, and a decrease in oxygen dissolved in the water. Hypoxia 

threatens commercial and recreational fisheries in the Gulf because fish, shrimp, and other 

aquatic species cannot live in the low oxygen waters. 

 The 2008 hypoxic zone was measured at 8,000 square miles, the second largest since 

measurements began in 1985.376 In 2009 models predicted an even larger hypoxic zone, but it 

was measured at only 3,000 square miles. A combination of below average high flows on the 

Mississippi River and winds that mixed Gulf waters are the likely causes of the reduced size of 

the 2009 zone. The Mississippi River/Gulf of Mexico Watershed Nutrient Task Force’s ‘‘Gulf 

Hypoxia Action Plan 2008’’ calls for a 45% reduction in both nitrogen and phosphorus reaching 

the Gulf to reduce the size of the zone.377 The Action Plan states that an additional reduction in 

nitrogen and phosphorus beyond the 45% would be necessary to account for increased corn 

production for ethanol and climate change impacts. 

 

376 Louisiana Universities Marine Consortium, 2009, ‘Gulf of Mexico Dead Zone Surprising Small, but Severe, 

available online at: http://www.gulfhypoxia.net/Research/Shelfwide%20Cruises/2009/Files/Press_Release.pdf

377 Mississippi River/Gulf of Mexico Watershed Nutrient Task Force, 2008, Gulf hypoxia action plan 2008 for 

reducing, mitigating, and controlling hypoxia in the northern Gulf of Mexico and improving water quality in the 

Mississippi River basin, 61 p., Washington, DC, available online at: http://www.epa.gov/msbasin/actionplan.htm
 

742

 Alexander, et al.378 modeled the sources of nutrient loadings to the Gulf of Mexico using 

the USGS SPARROW model. They estimated that agricultural sources contribute more than 

70% of the delivered nitrogen and phosphorus. Corn and soybean production accounted for 52% 

of nitrogen delivery and 25% of the phosphorus delivery. 

 Several recent scientific reports have estimated the impact of increasing ethanol 

feedstock acres in the Gulf of Mexico watershed. Donner and Kucharik’s 379 study showed 

increases in nitrogen export to the Gulf as a result of increasing corn ethanol production from 

2007 levels to 15 billion gallons in 2022. They concluded that the expansion of corn-based 

ethanol production could make it almost impossible to meet the Gulf of Mexico nitrogen 

reduction goals without a ‘‘radical shift’’ in feed production, livestock diet, and management of 

agricultural lands. The study estimated a mean dissolved inorganic nitrogen load increase of 10% 

to 18% from 2007 to 2022 to meet the 15 billion gallon corn ethanol goal. EPA’s Science 

Advisory Board report to the Mississippi River/Gulf of Mexico Watershed Task Force estimated 

that corn grown for ethanol will result in an additional national annual loading of almost 300 

million pounds of nitrogen. An estimated 80% of that nitrogen loading or 238 million pounds 

will occur in the Mississippi-Atchafalaya River Basin and contribute nitrogen to the hypoxia in 

the Gulf of Mexico. The results of a study by Costello, et al. indicate that moving from corn to 

switchgrass and corn stover to produce ethanol will result in a 20% decrease in the nitrate 

 

378 Alexander, R.B., Smith, R.A., Schwarz, G.E., Boyer, E.W., Nolan, J.V., and Brakebill, J.W., 2008, Differences in 

phosphorus and nitrogen delivery to the Gulf of Mexico from the Mississippi River basin, Environmental Science 

and Technology, v. 42, no. 3, p. 822–830, available online at: http://pubs.acs.org/cgibin/abstract.cgi/esthag/2008/42/i03/abs/es0716103.html

379 Donner, S. D. and Kucharik, C. J., 2008, Corn-based ethanol production compromises goal of reducing nitrogen 

export by the Mississippi River, PNAS, v. 105, no. 11, p. 4513–4518, available online at: 

http://www.pnas.org/content/105/11/4513.full 
 

743

outputs from the Mississippi-Atchafalaya River Basin. This decrease is not enough to meet the 

EPA target for reduction of the hypoxic zone reduction.380 

B. Upper Mississippi River Basin Analysis 

 To provide a quantitative estimate of the impact of the increased use of renewable fuels 

and production of corn ethanol generally on water quality, EPA conducted an analysis that 

modeled the changes in loadings of nitrogen, phosphorus, and sediment from agricultural 

production in the Upper Mississippi River Basin (UMRB). The UMRB drains approximately 

189,000 square miles, including large parts of the states of Illinois, Iowa, Minnesota, Missouri, 

and Wisconsin. Small portions of Indiana, Michigan, and South Dakota also lie within the basin. 

EPA selected the UMRB because it is representative of the many potential issues associated with 

ethanol production, including its connection to major water quality concerns such as Gulf of 

Mexico hypoxia, large corn production, and numerous ethanol production plants. 

 On average the UMRB contributes about 39% of the total nitrogen loads and 26% of the 

total phosphorus loads to the Gulf of Mexico.377 The high percentage of nitrogen from the 

UMRB is primarily due to the large inputs of fertilizer for agriculture and the 60% of cropland 

that is artificially drained by tiles. Since the mid 1990s, the annual nitrate-nitrogen flux has 

steadily decreased. The Science Advisory Board report attributes this decline to higher amount 

of nitrogen removed during harvest, due to higher crop yields. For the same time period, 

phosphorus inputs increased 12%. 

 

380 Costello, C.; Griffin, W.M.; Landis, A.E.; Matthew, H. S., 2009, Impact of biofuel crop production on the 

formation of hypoxia in the Gulf of Mexico, Environmental Science and Technology, 43 (20), pp 7985–7991 
 

744

 1. SWAT Model

 EPA selected the SWAT (Soil and Water Assessment Tool) model to assess nutrient and 

sediment loads from changes in agricultural production in the UMRB. SWAT is a physical 

process model developed to quantify the impact of land management practices in large, complex 

watersheds.381 

 2. AEO 2007 Reference Case

In order to assess alternative potential future conditions within the UMRB, EPA developed a 

SWAT model of a reference case scenario of current conditions against which to analyze the 

future impact of increased corn production. For the NPRM, we used a 2005 baseline. For the 

final rule, we revised the baseline to correspond with the agricultural analysis described in 

Section VIII.A. Therefore we used the corn ethanol production baseline from the Annual Energy 

Outlook (AEO) 2007 report382 as our reference case. We assumed that 33% of the corn 

produced in the UMRB was converted to corn ethanol, based on estimates from USDA.383 

This baseline does not include corn ethanol produced at the volumes required by this rulemaking. 

The analysis assumes that no cellulosic ethanol, including ethanol produced from corn stover, 

 

381 Gassman, P.W., Reyes, M.R., Green, C.H., Arnold, J.G., 2007, The soil and water assessment tool: Historical 

development, applications, and future research directions. Transactions of the American Society of Agricultural and 

Biological Engineers, v. 50, no. 4, p. 1211–1240. http://www.card.iastate.edu/environment/items/asabe_swat.pdf

382 U. S. Department of Energy, Energy Information Administration, Annual Energy Outlook 2007 With Projections 

to 2030, February 2007, available on-line at: http://tonto.eia.doe.gov/ftproot/forecasting/0383(2007).pdf

383 U.S. Department of Agriculture, USDA Agricultural Projections to 2018, February 2009, available on-line at: 

http://www.ers.usda.gov/Publications/OCE091/
 

745

would be produced in the reference case since the AEO report did not include cellulosic ethanol 

production in its estimates. 

 The SWAT model was applied (i.e., calibrated) to the UMRB using 1960 to 2001 

weather data and flow and water quality data from 13 USGS gages on the main stem of the 

Mississippi River. The 42-year SWAT model runs were performed and the results analyzed to 

establish runoff, sediment, nitrogen, and phosphorous loadings from each of the 131 8-digit HUC 

subwatersheds and the larger 4-digit subbasins, along with the total outflow from the UMRB and 

at the various USGS gage sites along the Mississippi River. These results provided the Reference 

Scenario model values to which the future alternatives are compared. 

 Physical structures that disconnect fertile floodplains with seasonal fluctuation of stream 

and river levels also affect water quantity and quality by altering the ability of these soils to serve 

as a sink for nutrient rich waters. In lieu of data on where these structures are or may be 

constructed, these effects were not modeled. 

 3. Reference Cases and RFS2 Control Case

 To assess the impacts of the increased use of corn ethanol, we modeled an RFS2 

Control Case and compared it to both the AEO 2007 Reference Case and the RFS1 Mandate 

Reference Case for the years 2010, 2015, 2020, and 2022. The RFS2 national corn ethanol 

volumes of 11.24 billion gallons a year (BGY) for 2010, and 15 BGY for 2016 to 2022 were 

adjusted for the UMRB. Annual increases in corn yield of 1.23% were built into the future 
 

746

scenarios. National average corn yields have been increasing primarily due to favorable weather 

conditions and improvement in practices to reduce stress on the corn plants from excess water, 

drought, and pests. Fewer corn acres were needed to meet ethanol production goals in the 

Control Case scenario after 2015 due to those yield increases. Corn acres increased 9% in 2022 

between the AEO 2007 Reference Case and the RFS2 (No Stover) Control Case. We were not 

able to model the impacts of corn stover removal at this time, so the analysis only reflects the 

impacts of increased use of corn grain for renewable fuel use. 

 Tables IX.B.3-1 through IX.B.3-3 compare the model outputs for nitrogen, phosphorus, 

and sediment between the AEO 2007 Reference Case and the RFS2 (No Stover) Control Case 

scenarios for the years 2010, 2015, 2020, and 2022. Land load is the total amount of nitrogen or 

phosphorus that reaches a stream within the UMRB. The total outflow is the nitrogen, 

phosphorus, or sediment measured at the outlet of the UMRB at Grafton, Illinois after accounting 

for in-stream loses due to uptake or assimilation. These results only estimate loadings from the 

Upper Mississippi River basin, not the entire Mississippi River watershed. As noted earlier, the 

UMRB contributes about 39% of the total nitrogen loads and 26% of total phosphorus loads to 

the Gulf of Mexico. The decreasing nutrient load over time is likely attributable to the increased 

average corn yield per acre, resulting in greater plant uptake of nitrogen and fewer corn acres 

planted to reach the ethanol production requirements of this rule. 

Table IX.B.3–1 
 

747

Average annual nitrogen loads: comparison of AEO 2007 Reference Case to the 2022 RFS2 (No 

Stover) Control Case (% difference in parentheses) 

 AEO 2007 Reference Case 2022 RFS2 (No Stover) Control Case 

Model 

Run 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

2010 1948 1470 1944 (-0.21) 1467 (-0.20) 

2015 1911 1441 1946 (1.83) 1469 (1.94) 

2020 1887 1421 1912 (1.32) 1442 (1.48) 

2022 1877 1413 1897 (1.07) 1430 (1.20) 

 About 24 to 26 % of the nitrogen and phosphorus leaving agricultural fields was 

assimilated (taken by aquatic plants or volatilized) before reaching the outlet of the UMRB. The 

assimilated nitrogen is not necessarily eliminated as an environmental concern. Five percent or 

more of the nitrogen can be converted to nitrous gas, a powerful greenhouse gas that has 300 

times the climate warming potential of carbon dioxide, the major greenhouse. Thus, a water 

pollutant becomes an air pollutant until it is either captured through biological sequestration or 

converted fully to elemental nitrogen. 

Table IX.B.3–2 

Average annual phosphorus loads: comparison of AEO 2007 Reference Case to the 2022 RFS2 

(No Stover) Control Case (% difference in parentheses) 
 

748

 AEO 2007 Reference Case 2022 RFS2 (No Stover) Control Case 

Model 

Run 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

Total Land Load, 

million lbs 

Total Outflow, 

million lbs 

2010 180.0 133.8 179.9 (-0.06) 133.7 (-0.07) 

2015 178.2 132.3 179.6 (0.79) 133.6 (0.98) 

2020 177.0 131.3 178.2 (0.68) 132.4 (0.84) 

2022 176.5 130.9 177.6 (0.62) 131.8 (0.69) 

 Total sediment outflow showed very little change over all scenarios. This result is 

primarily due to corn stover remaining on the field following harvest and therefore reducing 

sediment transport to water. 

Table IX.B.3-3 

Average annual sediment loads: comparison of AEO 2007 Reference Case to the 2022 RFS2 

Control Case (% difference in parentheses) 

 2007 AEO 2022 Control 

Volume Case 

Model 

Run 

Total Outflow, 

million tons 

Total Outflow, 

million tons 

2010 6.231 6.232 (0.02) 

2015 6.221 6.233 (0.19) 

2020 6.214 6.224 (0.16) 
 

749

2022 6.211 6.220 (0.14) 

 

 The relationship between the number of acres of corn needed to produce ethanol and the 

crop yield is a complex relationship. Increased demand for corn based ethanol will not always 

result in increases in corn acres. Our modeling demonstrated that in less than a decade, 

increasing corn yields may counter the need for increased corn production resulting in the 

number of acres of corn stabilizing and additional nutrient and sediment loadings decreasing 

from the earlier peaks. 

 At this time, we are not able to assess the impact of these additional loadings on the size 

of the Gulf of Mexico hypoxia zone or water quality within the UMRB. For more details on the 

analysis, including comparisons with the RFS1, see Chapter 6 in the RIA. 

 4. Case Study

 To evaluate local water quality impacts that are impossible to ascertain at the scale of the 

UMRB, we also modeled the Raccoon River watershed in central Iowa. The criteria for 

choosing this watershed included: percentage of corn area representative of the UMRB, stream 

segments included in EPA’s 303(d) list of impaired waters due to high nutrient levels, 

biorefinery plants, drinking water intakes, and observed streamflow and water quality data. 

Nearly 88% of the watershed is in agriculture. 75% of the watershed produces corn and 

soybeans, mostly in rotation. Hay and other row crops are produced on the remaining agriculture 
 

750

land. The city of Des Moines makes up about 8% of the watershed. The state of Iowa has listed 

numerous stream segments of the Raccoon River as impaired. 

 The case study used the same assumptions and scenarios as those used for the UMRB 

analysis. SWAT-simulated streamflow and water quality (total nitrogen and phosphorus, and 

sediment loadings) were calibrated against observed data at both monthly and yearly time steps. 

 As in the UMRB study, nitrogen loads to water increased for the future scenarios, though 

at a greater rate. Future phosphorus loads decreased in the Raccoon River model, where they 

had shown minor increases in the UMRB model. For the Raccoon River, there was a greater 

decrease in sediment load, which is the likely cause for the decrease in phosphorus loadings. 

 5. Sensitivity Analysis

 Using the existing UMRB SWAT model, a sensitivity analysis was conducted on a 

number of important meteorological and management related factors. The goal was to further 

understand the model characteristics and sensitivities to parameters and input forcing functions 

that control the model response for the key environmental indicators of concern. Scenarios 

were constructed using four factors: fertilization application threshold, corn residue removal, 

daily air temperature, and daily precipitation. The results of the analysis showed that rainfall and 

temperature are the most influential factors for all model outputs: water yield, total nitrogen and 

phosphorus loadings, and sediment loadings. These results underscored the importance of 

representing these two driving factors accurately in hydrologic modeling. Corn residue removal 
 

751

noticeably reduced nutrient loading into streams while increasing sediment loads. However, 

since corn residue is the main source of organic nitrogen and phosphorus, the removal of the 

residue leads to the need for higher nutrient inputs in the growing season. The fertilization 

application threshold scenario did not tangibly impact water yield and sediment loading. The 

findings from this study indicated that future climate change could greatly influence water 

availability and pollution from corn cropland. 

C. Additional Water Issues 

 The full water quality and water quantity impacts resulting from corn ethanol production 

go beyond the ability of our model. For example, the model does not account for fresh water 

constraints in irrigated agriculture in corn producing areas or predict future increases in drainage 

of agricultural lands. The following issues are summarized to provide additional context about 

the broader range of potential impacts. See Chapter 6 in the RIA for more discussion of these 

issues. 

 1. Chesapeake Bay Watershed

 In May 2009, President Obama issued Executive Order 13508 on Chesapeake Bay 

Restoration and Protection. The order established a Federal Leadership Committee, chaired by 

EPA, and with senior representatives from the departments of Agriculture, Commerce, Defense, 

Homeland Security, Interior, and Transportation. In November 2009, these federal agencies 

released a draft strategy which contains a range of approaches for accelerating cleanup of the 
 

752

nation’s largest estuary and its vast watershed.384 

 The draft strategy calls for increased accountability and performance from pollution 

control, habitat protection and land conservation programs at all levels of government, including 

an expanded use of regulatory authorities to address pollution control and additional voluntary 

and market-based solutions – particularly when it comes to habitat protection and land 

conservation programs. The proposed actions are in response to overwhelming scientific 

evidence that the health of the Chesapeake Bay remains exceptionally poor, despite the concerted 

restoration efforts of the past 25 years. 

 Agricultural lands contribute more nutrients to the Chesapeake Bay than any other land 

use. To estimate the increase in nutrient loads to the Bay from changes to agricultural crop 

production from 2005 to 2008, the Chesapeake Bay Program Watershed Model Phase 4.3 and 

Vortex models were utilized. Total nitrogen loads increased by almost 2.4 million pounds from 

an increase of almost 66,000 corn acres. As agriculture land use shifts from hay and pasture to 

more intensively fertilized row crops, this analysis estimates that nitrogen loads increase by 8.8 

million pounds. 

 2. Ethanol Production and Distribution

 a. Production 

 

384 Federal Leadership Committee for the Chesapeake Bay, November 9, 2009, Executive Order 13508: Draft 

Strategy for Protecting and Restoring the Chesapeake Bay, available on-line at: 

http://executiveorder.chesapeakebay.net/
 

753

 There are three principal sources of discharges to water from ethanol plants: reject water 

from water purification, cooling water blowdown, and off-batch ethanol. Most ethanol facilities 

use onsite wells to produce the process water for the ethanol process. Groundwater sources are 

generally not suitable for process water because of their mineral content. Therefore, the water 

must be treated, commonly by reverse osmosis. For every two gallons of pure water produced, 

about a gallon of brine is discharged as reject water from this process. Most estimates of water 

consumption in ethanol production are based on the use of clean process water and neglect the 

water discharged as reject water. 

 The largest source of wastewater discharge is reverse osmosis reject water from process 

water purification. The reverse osmosis process concentrates groundwater minerals to levels 

where they can have water quality impacts. There is really no means of ‘‘treating’’ these ions to 

reduce toxicity, other than further concentration and disposal, or use of in-stream dilution. Some 

facilities have had to construct long pipelines to get access to dilution so they can meet water 

quality standards. Ethanol plants also discharge cooling water blowdown, where some water is 

discharged to avoid the buildup of minerals in the cooling system. These brines are similar to the 

reject water described above. In addition, if off-batch ethanol product or process water is 

discharged, the waste stream can have high Biochemical Oxygen Demand (BOD) levels. BOD 

directly affects the amount of dissolved oxygen in rivers and streams. The greater the BOD, the 

more rapidly oxygen is depleted in the stream. The consequences of high BOD are the same as 

those for low dissolved oxygen: aquatic organisms become stressed, suffocate, and die. 
 

754

 Older generation production facilities used four to six gallons of process water to produce 

a gallon of ethanol, but newer facilities use less than three gallons of water in the production 

process. Most of this water savings is gained through improved recycling of water and heat in the 

process. Water supply is a local issue, and there have been concerns with water consumption as 

new plants go online. Some facilities are tapping into deeper aquifers as a source of water. These 

deeper water resources tend to contain higher levels of minerals and this can further increase the 

concentration of minerals in reverse osmosis reject water. Geographic impacts of water use vary. 

A typical plant producing 50 million gallons of ethanol per year uses a minimum of 175 million 

gallons of water annually. In Iowa, water consumption from ethanol refining accounts for about 

seven percent of all industrial water use, and is projected to be 14% by 2012—or about 50 

million gallons per day. 

 b. Distillers Grain with Solubles 

 Distillers grain with solubles (DGS) is an important co-product of ethanol production. 

About one-third of the corn processed into ethanol is converted into DGS. DGS has become an 

increasingly important feed component for confined livestock. DGS are higher in crude protein 

(nitrogen) and three to four times higher in phosphorus relative to traditional feeds. When 

nitrogen and phosphorus are fed in excess of the animal’s needs, these nutrients are excreted in 

the manure. When manure is applied to crops at rates above their nutrient needs or at times the 

crop can not use the nutrients, the nutrients can run off to surface waters or leach into ground 

waters. 
 

755

 Livestock producers can limit the potential pollution from manure applications to crops 

by implementing comprehensive nutrient management. Due to the substantially higher 

phosphorus content of manure from livestock fed DGS, producers will potentially need 

significantly more acres to apply the manure so that phosphorus will not be applied at rates 

above the needs of the crops. This is a particularly important concern in areas where 

concentrated livestock production already produces more phosphorus in the manure than can be 

taken up by crops or pasture land in the vicinity. 

 Several recent studies have indicated that DGS may have an impact on food safety. Cattle 

fed DGS have a higher prevalence of a major food-borne pathogen, E. coli O157, than cattle 

without DGS in their diets.385 More research is needed to confirm these studies and devise 

methods to eliminate the potential risks. 

 c. Ethanol Leaks and Spills from Fueling Stations 

 The potential for exposure to fuel components and/or additives can occur when 

underground fuel storage tanks leak fuel into ground water that is used for drinking water 

supplies or when spills occur from aboveground tanks or distribution systems that contaminate 

surface drinking water supplies. or surface waters. Additionally, in surface waters, rapid 

biodegradation of ethanol can result in depletion of dissolved oxygen with potential mortality to 

aquatic life. 

 

385 Jacob, M. D., Fox, J. T., Drouillard, J. S., Renter, D. G., Nagaraja, T. G., 2008, Effects of dried distillers’ grain 

on fecal prevalence and growth of Escherichia coli O157 in batch culture fermentations from cattle, Applied and 

Environmental Microbiology, v. 74, no. 1, p. 38–43, available online at: 

http://aem.asm.org/cgi/content/abstract/74/1/38
 

756

 Regarding leaks or spills and drinking water impacts, ethanol biodegrades quickly and is 

not necessarily the pollutant of greatest concern in these situations. Instead, ethanol’s high 

biodegradability shifts the subsurface geochemistry, which can cause the reduced biodegradation 

of benzene, toluene, and xylene (up to 50% for toluene and 95% for benzene).386 The plume of 

BTEX compounds from a fuel spill (benzene, toluene, ethylbenzene and xylenes) can extend as 

much as 70% farther in ground water and can persist longer, thereby increasing potential 

exposures to these compounds.387

 Ethanol leak and spills from the approximately 600,000 gas stations in the U.S, could 

have a significant impact on water quality and drinking water supplies. Urban areas, that rely on 

ground water for drinking water would be affected most, especially where are existing water 

shortages. 

 With the increasing use of ethanol in the fuel supply nationwide, it is important to 

understand the impact of ethanol on the existing tank infrastructure. Federal regulations require 

that underground storage tank (UST) systems be compatible with the fuel stored. Because much 

of the current underground storage tank equipment was designed and tested for use with 

petroleum fuels, there may be many UST systems currently in use that contain materials that are 

 

386 Mackay, D.M., de Sieyes, N. R., Einarson, M.D., Feris, K.P., Pappas, A.A., Wood, I.A., Jacobson, L., Justice, 

L.G., Noske, M.N., Scow, K.M., and Wilson, J.T., 2006, Impact of ethanol on the natural attenuation of benzene, 

toluene, and o-Xylene in a normally sulfate-reducing aquifer, Environmental Science & Technology, v. 40, p. 6123-

6130. 

387 Ruiz-Aguilar, G. M. L.; O’Reilly, K.; Alvarez, P. J. J., 2003, Forum: A comparison of benzene and toluene 

plume lengths for sites contaminated with regular vs. ethanol-amended gasoline, Ground Water Monitoring and 

Remediation, v. 23, p. 48–53. 
 

757

incompatible with ethanol blends greater than 10%. Combined with the fact that ethanol is more 

corrosive than petroleum, there is concern regarding the increased potential for leaks from 

existing distribution systems, terminals and gas stations and subsequent impacts on water 

supplies. Given the practical challenges of determining the age and materials of underground 

storage equipment at approximately 233,000 federally regulated facilities, it may be difficult or 

impossible to confirm the compatibility of current underground storage tanks and other tankrelated hardware with ethanol blends. Further discussion of challenges in retail distribution are 

discussed in Section 1.6 of the RIA. 

In 2008, there were 7,400 reported releases from underground storage tanks. Therefore, EPA is 

undertaking analyses designed to assess the potential impacts of ethanol blends on tank 

infrastructure and leak detection systems and determine the resulting water quality impacts. 

 

 3. Biodiesel Plants

 Biodiesel plants use much less water than ethanol plants. Water is used for washing 

impurities from the finished product. Water use is variable, but is usually less than one gallon of 

water for each gallon of biodiesel produced. Larger well-designed plants use water more 

sparingly, while smaller producers use more water. Some facilities recycle washwater, which 

reduces water consumption. The levels of BOD (biological oxygen demand) in process 

wastewater from biodiesel plants is highly variable. Most production processes produce 

washwater that has very high BOD levels. The high BOD levels of these wastes can overload 

and disrupt municipal treatment plants. 
 

758

 Crude glycerin is an important side product from the biodiesel process and is about 10% 

of the final product. Although there is a commercial market for glycerin, the rapid development 

of the biodiesel industry has caused a glut of glycerin production and many facilities dispose of 

their glycerin. Poor handling of crude glycerin has resulted in disruptions at sewage treatment 

plants and fish kills. 

 4. Water Quantity

 Water demand for crop production for ethanol could potentially be much larger than 

biorefinery demand. According to the National Research Council, the demand for water to 

irrigate crops for biofuels will not have an impact on national water use, but it is likely to have 

significant local and regional impacts.373 The impact is crop and region specific, but could be 

especially great in areas where new acres are irrigated. 

 5. Drinking Water 

Increased corn production will result in the increased use of fertilizers and herbicides which can 

drain to surface water or ground water sources used by public water systems and individual 

home owners on private wells. This may increase the occurrence of nitrate, nitrite, and the 

herbicide Atrazine in sources of drinking water. The U.S. Geological Survey evaluated the fate 

and transport of herbicides in surface water, ground water, and in precipitation in the Midwest 
 

759

during the 1990s. The results of these studies showed the occurrence and temporal distribution of 

herbicides and their associated degradation products in reservoir outflows.388

 

 Under the Safe Drinking Water Act, EPA has established enforceable standards for these 

contaminants that apply to public water systems. Source water contamination by these chemicals 

may raise local water system costs for treatment or for increased energy to pump water where 

ethanol production is accelerating the long running depletion of aquifers e.g., pumping extra 

water to grow the additional corn in addition to pumping extra water to process the corn into 

ethanol. There is also an (often concurrent) risk of exhausting local drinking water supplies 

where aquifers have been severely depleted. 

 

388 Scribner, E.A., Thurman, E.M., Goolsby, D.A., Meyer, M.T., Battaglin, W.A., and Kolpin, D.W., 2005, 

Summary of significant results from studies of triazine herbicides and their degradation products in surface water, 

ground water, and precipitation in the Midwestern United States during the 1990s: U.S. Geological Survey Scientific 

Investigations Report 2005–5094, 27 p. 
 

760
 

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X. Public Participation 

 Many interested parties participated in the rulemaking process that culminates 

with this final rule. This process provided opportunity for submitting written public 

comments following the proposal that we published on May 26, 2009 (74 FR 24904), and 

we considered these comments in developing the final rule. In addition, we held a public 

hearing on the proposed rulemaking on June 9, 2009, and we have considered comments 

presented at the hearing. 

Throughout the rulemaking process, EPA met with stakeholders including 

representatives from the fuel and renewable fuels industries, the agricultural sector, and 

others. The program we are finalizing today was developed as a collaborative effort with 

these stakeholders. 

We have prepared a detailed Summary and Analysis of Comments document, 

which describes the comments we received on the proposal and our response to each of 

these comments. The Summary and Analysis of Comments is available in the docket for 

this rule at the Internet address listed under ADDRESSES, as well as on the Office of 

Transportation and Air Quality Web site (www.epa.gov/otaq/renewablefuels/index.htm). 

In addition, comments and responses for key issues are included throughout this 

preamble. 
 

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XI. Statutory and Executive Order Reviews 

A. Executive Order 12866: Regulatory Planning and Review 

 

 Under section 3(f)(1) of Executive Order (EO) 12866 (58 FR 51735, October 4, 1993), 

this action is an "economically significant regulatory action” because it is likely to have an 

annual effect on the economy of $100 million or more. Accordingly, EPA submitted this action 

to the Office of Management and Budget (OMB) for review under EO 12866 and any changes 

made in response to OMB recommendations have been documented in the docket for this action. 

In addition, EPA prepared an analysis of the potential costs and benefits associated with 

this action. This analysis is contained in the Regulatory Impact Analysis, which is available in 

the docket for this rulemaking and at the docket internet address listed under ADDRESSES in 

the first part of this final rule. 

B. Paperwork Reduction Act 

The information collection requirements in this have been submitted for approval to the 

Office of Management and Budget (OMB) under the Paperwork Reduction Act, 44 U.S.C. 3501 

et seq. The information collection requirements are not enforceable until OMB approves them. 

 Information to be collected under this rulemaking includes compliance reports and 

reports regarding the generation and assignment of, and transactions involving, RINs. This final 
 

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rule involves registration requirements, recordkeeping and reporting. Affected parties include 

producers of renewable fuels, importers, domestic and foreign refiners, exporters, domestic and 

foreign parties who own RINs, and biofuel feedstock producers. Individual items of 

recordkeeping and reporting are discussed in great detail in this preamble and in the “Supporting 

Statement for the Renewable Fuels Standard (RFS2) Final Rule,” which has been placed in the 

public docket. 

 We estimate the annual recordkeeping and reporting burden for this rule at 3.2 hours per 

response. We estimate a total of 1,060,026 respondents; 4,781,126 responses; 1,485,008 burden 

hours, and a total cost associated with responding of $112,872,105. Burden is defined at 5 CFR 

1320.3(b). 

 An agency may not conduct or sponsor, and a person is not required to respond to, a 

collection of information unless it displays a currently valid OMB control number. The OMB 

control numbers for EPA's regulations in 40 CFR are listed in 40 CFR Part 9. In addition, EPA is 

amending the table in 40 CFR part 9 of currently approved OMB control numbers for various 

regulations to list the regulatory citations for the information requirements contained in this final 

rule. 

C. Regulatory Flexibility Act 
 

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 1. Overview

 The Regulatory Flexibility Act (RFA) generally requires an agency to prepare a 

regulatory flexibility analysis of any rule subject to notice and comment rulemaking 

requirements under the Administrative Procedure Act or any other statute unless the agency 

certifies that the rule will not have a significant economic impact on a substantial number of 

small entities. Small entities include small businesses, small organizations, and small 

governmental jurisdictions. 

 For purposes of assessing the impacts of the renewable fuel volume requirements of 

RFS2 on small entities, small entity is defined as: (1) a small business as defined by the Small 

Business Administration’s (SBA) regulations at 13 CFR 121.201 (see table below); (2) a small 

governmental jurisdiction that is a government of a city, county, town, school district or special 

district with a population of less than 50,000; and (3) a small organization that is any not-forprofit enterprise which is independently owned and operated and is not dominant in its field. 

The following table provides an overview of the primary SBA small business categories 

potentially affected by this regulation: 

Industrya

 Defined as small entity by SBA if: NAICSa codes 

Gasoline and diesel fuel refiners ≤1,500 employees 324110

a- North American Industrial Classification System 

 
 

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 2. Background

Section 1501 of the Energy Policy Act of 2005 (EPAct) amended section 211 of the 

Clean Air Act (CAA) by adding section 211(o) which required the Environmental Protection 

Agency (EPA) to promulgate regulations implementing a renewable fuel program. EPAct 

specified that the regulations must ensure a specific volume of renewable fuel to be used in 

gasoline sold in the U.S. each year, with the total volume increasing over time. The goal of the 

program was to reduce dependence on foreign sources of petroleum, increase domestic sources 

of energy, and help transition to alternatives to petroleum in the transportation sector. 

The final Renewable Fuels Standard (RFS1) program rule was published on May 1, 2007, 

and the program began on September 1, 2007. Per EPAct, the RFS1 program created a specific 

annual level for minimum renewable fuel use that increases over time—resulting in a 

requirement that 7.5 billion gallons of renewable fuel be blended into gasoline (for highway use 

only) by 2012. Under the RFS1 program, compliance is based on meeting the required annual 

renewable fuel volume percent standard (published annually in the Federal Register by EPA) 

through the use of Renewable Identification Numbers, or RINs, 38-digit serial numbers assigned 

to each batch of renewable fuel produced. For obligated parties (those who must meet the annual 

volume percent standard), RINs must be acquired to show compliance. 

The Energy Independence and Security Act of 2007 (EISA) amended section 211(o), and 

the RFS program, by requiring higher volumes of renewable fuels, to result in 36 billion gallons 

of renewable fuel by 2022. EISA also expanded the purview of the RFS1 program by requiring 
 

766

that these renewable fuels be blended into gasoline and diesel fuel (both highway and nonroad). 

This expanded the pool of regulated entities, so the obligated parties under the RFS program will 

now include certain refiners, importers, and blenders of these fuels that were not previously 

covered by the RFS1 program. In addition to the total renewable fuel standard required by 

EPAct, EISA added standards for three additional types of renewable fuels to the program 

(advanced biofuel, cellulosic biofuel, and biomass-based diesel) and requires compliance with all 

four standards. 

As required by section 609(b) of the RFA, as amended by SBREFA, EPA also conducted 

outreach to small entities and convened a Small Business Advocacy Review Panel to obtain 

advice and recommendations of representatives of the small entities that potentially would be 

subject to the rule's requirements. 

 3. Summary of Potentially Affected Small Entities

The small entities that will potentially be subject to the RFS program include: domestic 

refiners that produce gasoline and/or diesel and importers of gasoline and/or diesel into the 

United States. Based on 2007 data, EPA believes that there are about 95 refiners of gasoline and 

diesel fuel. Of these, EPA believes that there are currently 17 refiners, owning 20 refineries, 

producing gasoline and/or diesel fuel that meet the SBA small entity definition of having 1,500 

employees or less. Further, we believe that three of these refiners own refineries that do not 

meet the Congressional “small refinery” definition.389 It should be noted that because of the 

 

389 EPAct defined a “small refinery” as a refinery with a crude throughput of no more than 75,000 barrels of crude 

per day (at CAA section 211(o)(1)(K)). This definition is based on facility size and is different than SBA’s small 
 

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dynamics in the refining industry (i.e., mergers and acquisitions), the actual number of refiners 

that ultimately qualify for small refiner status under the RFS2 rule could be different than this 

estimate. 

 4. Reporting, Recordkeeping, and Compliance

Registration, reporting, and recordkeeping are necessary to track compliance with the 

RFS standards and transactions involving RINs. As discussed above in Sections II.J and III.A, 

the compliance requirements under the RFS2 rule are in many ways similar to those required 

under the RFS1 rule, with some modifications (e.g., those to account for the new requirements of 

EISA). New provisions being finalized in today’s action include the new EPA Moderated 

Transaction System (EMTS) which allows for “real-time” reporting of RIN generation 

transactions, and the ability for small blenders to “delegate” their RIN-separation responsibilities 

to the party directly upstream. Please see Sections II and III of this preamble for more detailed 

information on these and other registration, recordkeeping, reporting, and compliance 

requirements of this final rule. 

 5. Related Federal Rules

 We are aware of a few other current or proposed Federal rules that are related to this rule. 

The primary related Federal rules are: the first Renewable Fuel Standard (RFS1) rule (72 FR 

23900, May 1, 2007), the RFS1 Technical Amendment Direct Final Rulemaking (73 FR 57248, 

 

refiner definition (which is based on company size). A small refinery could be owned by a larger refiner that 

exceeds SBA’s small entity standards. SBA’s size standards were established to set apart those businesses which 

are most likely to be at an inherent economic disadvantage relative to larger businesses. 
 

768

October 2, 2008)

390, and Control of Emissions from New Marine Compression-Ignition Engines 

at or Above 30 Liters per Cylinder (proposed rule: 74 FR 44442, August 28, 2009; final rule: 

signed December 22, 2009). 

6. Steps Taken to Minimize the Significant Economic Impact on Small Entities

 

a. Significant Panel Findings 

 We convened a Small Business Advocacy Review Panel (SBAR Panel, or the Panel), 

which considered many regulatory options and flexibilities that would help mitigate potential 

adverse effects on small businesses as a result of the increased volumes of renewable fuel 

required by RFS2. During the SBREFA Panel process, the Panel sought out and received 

comments on the regulatory options and flexibilities that were presented to Small Entity 

Representatives (SERs) and Panel members. The major flexibilities and hardship relief 

provisions that were recommended by the Panel were proposed and some are being finalized 

today (for more information regarding the Panel process, see the SBREFA Final Panel Report, 

which is available in the public docket for this rule). 

b. Outreach With Small Entities (and the Panel Process) 

 

As required by section 609(b) of the RFA as amended by SBREFA, EPA conducted 

outreach to small entities and convened a SBAR Panel prior to proposing the RFS2 rule to obtain 

 

390 This Direct Final Rule corrects minor typographical errors and provides clarification on existing provisions in the 

RFS1 regulations. 
 

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advice and recommendations of representatives of the small entities that potentially would be 

subject to the rule’s requirements. 

 As part of the SBAR Panel process, we conducted outreach with representatives from the 

various small entities that would be affected by the rule. We met with these SERs to discuss the 

potential rulemaking approaches and potential options to decrease the impact of the rulemaking 

on their industries. The Panel received written comments from the SERs, specifically on 

regulatory alternatives that could help to minimize the rule’s impact on small businesses. In 

general, SERs stated that they believed that small refiners would face challenges in meeting the 

new standards. More specifically, they voiced concerns with respect to the RIN program itself, 

uncertainty (with the required renewable fuel volumes, RIN availability, and cost), and the desire 

for a RIN system review. 

 The Panel agreed that EPA should consider the issues raised by the SERs (and 

discussions had by the Panel itself) and that EPA should consider comments on flexibility 

alternatives that would help to mitigate any negative impacts on small businesses. Alternatives 

discussed throughout the Panel process included those offered in previous or current EPA 

rulemakings, as well as alternatives suggested by SERs and Panel members, and the Panel 

recommended that all be considered in the development of the rule. 

 A summary of the Panel’s recommendations, what the Agency proposed, and what is 

being finalized today is discussed below. A detailed discussion of the regulatory alternatives and 

hardship provisions discussed and recommended by the Panel can be found in the SBREFA Final 
 

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Panel Report, and a discussion of the provisions being finalized today is located in Section III.E 

of this preamble. 

c. Panel Recommendations, Proposed Provisions, and Provisions Being Finalized 

The purpose of the Panel process is to solicit information as well as suggested flexibility 

options from the SERs, and the Panel recommended that EPA continue to do so during the 

development of the RFS2 rule. Recognizing the concerns about EPA’s authority to provide 

extensions to a subset of small refineries (i.e., those that are owned by small refiners) different 

from that provided to small refineries in section 211(o)(9), the Panel recommended that EPA 

continue to evaluate this issue, and that EPA request comment on its authority and the 

appropriateness of providing extensions beyond those authorized by section 211(o)(9) for small 

refineries operated by a small refiner. The Panel also recommended that EPA propose to provide 

the same extension provision of 211(o)(9) to small refiners who do not own small refineries as is 

provided for small refiners who do own small refineries. 

 i. Delay in Standards

 The RFS1 program regulations provide small refiners who operate small refineries as 

well as small refiners who do not operate small refineries with a temporary exemption from the 

standard through December 31, 2010. Small refiner SERs suggested that an additional 

temporary exemption for the RFS2 program would be beneficial to them in meeting the RFS2 

standards. EPA evaluated a temporary exemption for at least some of the four required RFS2 
 

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standards for small refiners. The Panel recommended that EPA propose a delay in the effective 

date of the standards until 2014 for small entities, to the maximum extent allowed by the statute. 

However, the Panel recognized that EPA has serious concerns about its authority to provide an 

extension of the temporary exemption for small refineries that is different from that provided in 

CAA section 211(o)(9), since Congress specifically addressed an extension for small refineries 

in that provision. 

The Panel did recommend that EPA propose other avenues through which small 

refineries and small refiners could receive extensions of the temporary exemption. These 

avenues were a possible extension of the temporary exemption for an additional two years 

following a study of small refineries by the Department of Energy (DOE) and provisions for 

case-by-case economic hardship relief. 

 We proposed and took comment on the recommendations of the Panel and SERs above. 

As discussed in section III.E of this preamble, based on our analysis and further review of the 

provisions and the DOE Small Refinery Study, we have decided to finalize continuing the small 

refinery and small refiner exemption finalized in RFS1 through December 31, 2010 for all small 

refiners. 

 ii. Phase-in

Small refiner SERs’ suggested that a phase-in of the obligations applicable to small 

refiners would be beneficial for compliance, such that small refiners would comply by gradually 
 

772

meeting the standards on an incremental basis over a period of time, after which point they 

would comply fully with the RFS2 standards, EPA has serious concerns about its authority to 

allow for such a phase-in of the standards. CAA section 211(o)(3)(B) states that the renewable 

fuel obligation shall “consist of a single applicable percentage that applies to all categories of 

persons specified” as obligated parties. This kind of phase-in approach would result in different 

applicable percentages being applied to different obligated parties. Further, as discussed above, 

such a phase-in approach would provide more relief to small refineries operated by small refiners 

than that provided under the small refinery provision. Thus the Panel recommended that EPA 

should invite comment on a phase-in, but not propose such a provision. 

We took comment on this provision, however we are not finalizing this provision, as we 

continue to believe that a phase-in of the applicable standards would in fact result in different 

standards for small refiners. 

 iii. RIN-Related Flexibilities

The small refiner SERs requested that the proposed rule contain provisions for small 

refiners related to the RIN system, such as flexibilities in the RIN rollover cap percentage and 

allowing all small refiners to use RINs interchangeably. In the RFS1 program, EPA allows for 

20% of a previous year’s RINs to be “rolled over” and used for compliance in the following year. 

We noted during the Panel process that a provision to allow for flexibilities in the rollover cap 

could include a higher RIN rollover cap for small refiners for some period of time or for at least 

some of the four standards. Further, we noted our belief that since the concept of a rollover cap 
 

773

was not mandated by section 211(o), EPA believes that there may be an opportunity to provide 

appropriate flexibility in this area to small refiners under the RFS2 program but only if it is 

determined in the DOE small refinery study that there is a disproportionate effect warranting 

relief. The Panel recommended that EPA request comment on increasing the RIN rollover cap 

percentage for small refiners, and further that EPA should request comment on an appropriate 

level of that percentage. The Panel also recommended that EPA invite comment on allowing 

RINs to be used interchangeably for small refiners, but not propose this concept because under 

this approach small refiners would arguably be subject to a different applicable percentage than 

other obligated parties. 

We proposed a change to the RIN rollover cap, and took comment on the concept of 

allowing RINs to be used interchangeably for small refiners only. As noted above in section III 

of this preamble, we are not finalizing RIN-related provisions in today’s action. As highlighted 

in the NPRM, we continue to believe that the concept of interchangeable RINs for small refiners 

only fails to require the four different standards mandated by Congress (e.g., conventional 

biofuel could not be used instead of cellulosic biofuel or biomass-based diesel). Further, given 

the findings from the DOE study, if small refineries and small refiners do not face 

disproportionate economic hardship, then we do not believe that we have the basis for granting 

such additional relief beyond what Congress already provided. Thus, small refiners will be held 

to the same RIN rollover cap as other obligated parties. 

 iv. Program Review
 

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With regard to the suggested program review, EPA raised the concern that this could lead 

to some redundancy since EPA is required to publish a notice of the applicable RFS standards in 

the Federal Register annually, and that this annual process will inevitably include an evaluation 

of the projected availability of renewable fuels. Nevertheless, the SBA and OMB Panel 

members stated that they believe that a program review could be helpful to small entities in 

providing them some insight to the RFS program’s progress and alleviate some uncertainty 

regarding the RIN system. As EPA will be publishing a Federal Register notice annually, the 

Panel recommended that EPA include an update of RIN system progress (e.g., RIN trading, RIN 

availability, etc.) in this notice and that the results of this evaluation be considered in any request 

for case-by-case hardship relief. 

We did propose that in the annual notice of the RFS standards that EPA must publish in 

the Federal Register, we would also include information to help inform industry about the RIN 

system. We also proposed that information from the annual Production Outlook Reports that 

producers and importers must submit to EPA, as well as information required in EMTS reports, 

could be used in the annual Federal Register notice to update RIN system progress. However, 

during the development of the final rule, it became evident that there could be instances where 

we would want to report out RIN system information on a more frequent basis than just once a 

year. Thus we are finalizing that we will report out elements of RIN system progress; but such 

information will be reported via other means (e.g., the RFS website 

(www.epa.gov/otaq/renewablefuels/index.htm), EMTS homepage, etc.). Additionally, we will 

also publish annual summaries of the Production Outlook Reports. 
 

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v. Extensions of the Temporary Exemption Based on a Study of Small Refinery 

Impacts

The Panel recommended that EPA propose in the RFS2 program the provision at 40 CFR 

80.1141(e) extending the RFS1 temporary exemption for at least two years for any small refinery 

that DOE determines would be subject to disproportionate economic hardship if required to 

comply with the RFS2 requirements. 

Section 211(o)(9)(A)(ii) required that by December 31, 2008, DOE was to perform a 

study of the economic impacts of the RFS requirements on small refineries to assess and 

determine whether the RFS requirements would impose a disproportionate economic hardship on 

small refineries, and submit this study to EPA. Section 211(o)(9) also provided that small 

refineries found to be in a disproportionate economic hardship situation would receive an 

extension of the temporary exemption for at least two years. 

The Panel also recommended that EPA work with DOE in the development of the small 

refinery study, specifically to communicate the comments that SERs raised during the Panel 

process. 

 We did not propose and are not finalizing this hardship provision given the outcome of 

the DOE small refinery study. In the small refinery study, “EPACT 2005 Section 1501 Small 

Refineries Exemption Study”, DOE’s finding was that there is no reason to believe that any 

small refinery would be disproportionately harmed by inclusion in the proposed RFS2 program. 
 

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This finding was based on the fact that there appeared to be no shortage of RINs available under 

RFS1, and EISA has provided flexibility through waiver authority (per section 211(o)(7)). 

Further, in the case of the cellulosic biofuel standard, cellulosic biofuel allowances can be 

provided from EPA at prices established in EISA (see regulation section 80.1455). DOE thus 

determined that no small refinery would be subject to disproportionate economic hardship under 

the proposed RFS2 program, and that the small refinery exemption should not be extended 

beyond December 31, 2010. DOE noted in the study that, if circumstances were to change 

and/or the RIN market were to become non-competitive or illiquid, individual small refineries 

have the ability to petition EPA for an extension of their small refinery exemption (as stated in 

regulation section 80.1441). 

As discussed in section III.E of this preamble, since the only small refinery study 

available for us to use as a basis for whether or not to grant small refineries an automatic twoyear extension of the exemption is the study that was performed in 2008, we had to use this study 

to develop this final rule. EPAct directs EPA to consider the DOE small refinery study in 

assessing the impacts to small refineries, and we interpret this to mean that any extension past 

December 31, 2010 has to be tied to the DOE Study. Further, since that study found that there 

was no disproportionate economic impact on small refineries, we cannot grant an automatic 

additional extension for small refineries or small refiners (except on a case-by-case hardship 

basis). However, this does not preclude small refiners from applying for case-by-case extensions 

of the small refiner temporary exemption. 

Note that if the revised DOE study (see Section III.E.3 of this preamble) finds that there 
 

777

is a disproportionate economic impact, we will revisit the extension of the temporary exemption 

at that point. 

vi. Extensions of the Temporary Exemption Based on Disproportionate Economic 

Hardship

While SERs did not specifically comment on the concept of hardship provisions for the 

upcoming proposal, the Panel noted that under CAA section 211(o)(9)(B) small refineries may 

petition EPA for case-by-case extensions of the small refinery temporary exemption on the basis 

of disproportionate economic hardship. Refiners may petition EPA for this case-by-case 

hardship relief at any time. 

The Panel recommended that EPA propose in the RFS2 program a case-by-case hardship 

provision for small refineries similar to that provided at 40 CFR 80.1141(e)(1). The Panel also 

recommended that EPA propose a case-by-case hardship provision for small refiners that do not 

operate small refineries that is comparable to that provided for small refineries under section 

211(o)(9)(B), using its discretion under CAA section 211(o)(3)(B). This would apply if EPA 

does not adopt an automatic extension for small refiners, and would allow those small refiners 

that do not operate small refineries to apply for the same kind of extension as a small refinery. 

The Panel recommended that EPA take into consideration the results of the annual update of RIN 

system progress and the DOE small refinery study in assessing such hardship applications. 
 

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We believe that these avenues of relief can and should be fully explored by small refiners 

who are covered by the small refinery provision. In addition, we believe that it is appropriate to 

allow petitions to EPA for an extension of the temporary exemption based on disproportionate 

economic hardship for those small refiners who are not covered by the small refinery provision 

(again, per our discretion under section 211(o)(3)(B)); this would ensure that all small refiners 

have the same relief available to them as small refineries do. Thus, we are finalizing a hardship 

provision for small refineries in the RFS2 program, that any small refinery may apply for a caseby-case hardship at any time on the basis of disproportionate economic hardship per CAA 

section 211(o)(9)(B). We are also finalizing a case-by-case hardship provision for those small 

refiners that do not operate small refineries (section 80.1442(h)) using our discretion under CAA 

section 211(o)(3)(B). This provision will allow those small refiners that do not operate small 

refineries to apply for the same kind of extension as a small refinery. In evaluating applications 

for this hardship provision EPA will take into consideration information gathered from annual 

reports and RIN system progress updates, as recommended by the SBAR Panel. 

 7. Conclusions

 Pursuant to section 603 of the RFA, EPA prepared an initial regulatory flexibility 

analysis (IRFA) for the proposed rule and convened a Small Business Advocacy Review Panel to 

obtain advice and recommendations of representatives of the regulated small entities (see 74 FR 

24904, May 26, 2009). A detailed discussion of the Panel’s advice and recommendations is 

found in the Panel Report, located in the rulemaking docket. A summary of the Panel’s 

recommendations is presented at 74 FR 25106 (May 26, 2009). 
 

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 As required by section 604 of the RFA, we also prepared a final regulatory flexibility 

analysis (FRFA) for today’s final rule. The FRFA addresses the issues raised by public 

comments on the IRFA, which was part of the proposal of this rule. The FRFA is available for 

review in the docket and is summarized above. 

Many aspects of the RFS2 rule, such as the required amounts of annual renewable fuel 

volumes, are specified in EPAct and EISA. As discussed above, small refiners and small 

refineries receive an exemption from the RFS standards until January 1, 2011 and are not 

required to make expensive capital improvements like those required under other EPA fuels 

programs. Further the DOE small refinery study did not find that there was a disproportionate 

economic impact on small refineries as a whole as a result of this rule (and the majority of the 

refiners that meet the definition of a small refiner, also own refineries that meet the 

Congressional small refinery definition). 

A cost-to-sales ratio test, a ratio of the estimated annualized compliance costs to the value 

of sales per company, was performed for gasoline and/or diesel small refiners. From this cost-tosales test, it was estimated that all small entities have compliance costs that are less than one 

percent of their sales (a complete discussion of the costs to refiners as a result of the increased 

volumes of renewable fuel required by EISA is located in Section VII of this preamble). 

As required by section 212 of SBREFA, EPA also is preparing a Small Entity 

Compliance Guide to help small entities comply with this rule. This guide will be available on 
 

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the RFS website (www.epa.gov/otaq/renewablefuels/index.htm), and will be available 60 days 

after the rule is finalized. 

D. Unfunded Mandates Reform Act 

 Title II of the Unfunded Mandates Reform Act of 1995 (UMRA), 2 U.S.C. 1531-1538, 

requires Federal agencies, unless otherwise prohibited by law, to assess the effects of their 

regulatory actions on State, local, and tribal governments and the private sector. Under section 

202 of the UMRA, EPA generally must prepare a written statement, including a cost-benefit 

analysis, for proposed and final rules with "Federal mandates" that may result in expenditures to 

State, local, and tribal governments, in the aggregate, or to the private sector, of $100 million or 

more in any one year. 

This rule is not subject to the requirements of section 203 of UMRA because it contains 

no regulatory requirements that might significantly or uniquely affect small governments. EPA 

has determined that this rule contains a Federal mandate that may result in expenditures of $100 

million or more for the private sector in any one year, but the rule imposes no enforceable duty 

on any State, local or tribal governments. Nonetheless, EPA believes that today’s action 

represents the least costly, most cost-effective approach to achieve the statutory requirements of 

the rule. The costs and benefits associated with the increased use of renewable fuels are 

discussed above and in the Regulatory Impact Analysis, as required by the UMRA. 

E. Executive Order 13132: Federalism 
 

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 Executive Order 13132, entitled “Federalism” (64 FR 43255, August 10, 1999), requires 

EPA to develop an accountable process to ensure “meaningful and timely input by State and 

local officials in the development of regulatory policies that have federalism implications.” 

“Policies that have federalism implications” is defined in the Executive Order to include 

regulations that have “substantial direct effects on the States, on the relationship between the 

national government and the States, or on the distribution of power and responsibilities among 

the various levels of government.” 

 This final rule does not have federalism implications. It will not have substantial direct 

effects on the States, on the relationship between the national government and the States, or on 

the distribution of power and responsibilities among the various levels of government, as 

specified in Executive Order 13132. Thus, Executive Order 13132 does not apply to this rule. 

 In the spirit of Executive Order 13132, and consistent with EPA policy to promote 

communications between EPA and State and local governments, EPA specifically solicited 

comment on the proposed rule from State and local officials. 

F. Executive Order 13175: Consultation and Coordination with Indian Tribal 

Governments 

 This action does not have tribal implications, as specified in Executive Order 13175 (65 

FR 67249, November 9, 2000). This rule will be implemented at the Federal level and impose 
 

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compliance costs only on transportation fuel refiners, blenders, marketers, distributors, 

importers, and exporters. Tribal governments would be affected only to the extent they purchase 

and use regulated fuels. Thus, Executive Order 13175 does not apply to this action. EPA 

specifically solicited comment on the proposed rule from tribal officials. 

G. Executive Order 13045: Protection of Children from Environmental Health 

Risks and Safety Risks 

 EPA interprets EO 13045 (62 F.R. 19885, April 23, 1997) as applying only to those 

regulatory actions that concern health or safety risks, such that the analysis required under 

section 5-501 of the EO has the potential to influence the regulation. This action is not subject to 

EO 13045 because it does not establish an environmental standard intended to mitigate health or 

safety risks and because it implements specific standards established by Congress in statutes. 

H. Executive Order 13211: Actions Concerning Regulations That Significantly 

Affect Energy Supply, Distribution, or Use 

 This rule is not subject to Executive Order 13211 (66 FR 28355 (May 22, 2001)), 

because it is not likely to have a significant adverse effect on the supply, distribution, or use of 

energy. In fact, this rule has a positive effect on energy supply and use. By promoting the 

diversification of transportation fuels, the increased use of renewable fuels enhances energy 

supply. Therefore, we have concluded that this rule is not likely to have any adverse energy 

effects. Our energy effects analysis is discussed in Section VIII.B. 
 

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I. National Technology Transfer Advancement Act 

 Section 12(d) of the National Technology Transfer and Advancement Act of 1995 

(“NTTAA”), Public Law No. 104-113, 12(d) (15 U.S.C. 272 note) directs EPA to use voluntary 

consensus standards in its regulatory activities unless to do so would be inconsistent with 

applicable law or otherwise impractical. Voluntary consensus standards are technical standards 

(e.g., materials specifications, test methods, sampling procedures, and business practices) that are 

developed or adopted by voluntary consensus standards bodies. NTTAA directs EPA to provide 

Congress, through OMB, explanations when the Agency decides not to use available and 

applicable voluntary consensus standards. 

 This rulemaking changes the Renewable Fuel Standard (RFS) program at Title 40 of the 

Code of Federal Regulations, Subpart K which already contains voluntary consensus standard 

ASTM D6751-06a “Standard Specification for Biodiesel Fuel Blend Stock (B100) for Middle 

Distillate Fuels”. This rulemaking incorporates the most recent version of that standard (ASTM 

D-6751-08) and adds several more voluntary consensus standards: ASTM D-1250-08, “Standard 

Guide for Use of the Petroleum Measurement Tables”; ASTM D-4442, “Standard Test Methods 

for Direct Moisture Content Measurement of Wood and Wood-Base Materials”; ASTM D-4444, 

“Standard Test Method for Laboratory Standardization and Calibration of Hand-Held Moisture 

Meters”; ASTM D-6866-08 “Standard Test Methods for Determining the Biobased Content of 

Solid, Liquid, and Gaseous Samples Using Radiocarbon Analysis”; ASTM E-711, “Standard 

Test Method for Gross Calorific Value of Refuse-Derived Fuel by the Bomb Calorimeter”; and 
 

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ASTM E-870, “Standard Test Methods for Analysis of Wood Fuels”. Information about these 

standards may be obtained through the ASTM website (www.astm.org) or by calling ASTM at 

(610) 832-9585. 

 This rulemaking does not change these voluntary consensus standards, and does not 

involve any other technical standards. Therefore, EPA is not considering the use of any voluntary 

consensus standards other than those described above. 

J. Executive Order 12898: Federal Actions to Address Environmental Justice 

in Minority Populations and Low-Income Populations 

 Executive Order (EO) 12898 (59 FR 7629 (Feb. 16, 1994)) establishes federal executive 

policy on environmental justice. Its main provision directs federal agencies, to the greatest 

extent practicable and permitted by law, to make environmental justice part of their mission by 

identifying and addressing, as appropriate, disproportionately high and adverse human health or 

environmental effects of their programs, policies, and activities on minority populations and lowincome populations in the United States. 

EPA lacks the discretionary authority to address environmental justice in this rulemaking 

since the Agency is implementing specific standards established by Congress in statutes. 

Although EPA lacks authority to modify today’s regulatory action on the basis of environmental 

justice considerations, EPA nevertheless determined that this rule does not have a 
 

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disproportionately high and adverse human health or environmental impact on minority or lowincome populations. 

K. Congressional Review Act 

The Congressional Review Act, 5 U.S.C. 801 et seq., as added by the Small Business 

Regulatory Enforcement Fairness Act of 1996, generally provides that before a rule may take 

effect, the agency promulgating the rule must submit a rule report, which includes a copy of the 

rule, to each House of the Congress and to the Comptroller General of the United States. EPA 

will submit a report containing this rule and other required information to the U.S. Senate, the 

U.S. House of Representatives, and the Comptroller General of the United States prior to 

publication of the rule in the Federal Register. A Major rule cannot take effect until 60 days 

after it is published in the Federal Register. This action is a “major rule” as defined by 5 U.S.C. 

804(2). This rule will be effective July 1, 2010. 
 

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XII. Statutory Provisions and Legal Authority 

Statutory authority for the rule finalized today can be found in section 211 of the Clean 

Air Act, 42 U.S.C. 7545. Additional support for the procedural and compliance related aspects 

of today's rule, including the recordkeeping requirements, come from Sections 114, 208, and 

301(a) of the Clean Air Act, 42 U.S.C. 7414, 7542, and 7601(a). 

 

List of Subjects in 40 CFR Part 80 

Environmental protection, Administrative practice and procedure, Agriculture, Air pollution 

control, Confidential business information, Diesel Fuel, Energy, Forest and Forest Products, Fuel 

additives, Gasoline, Imports, Incorporation by reference, Labeling, Motor vehicle pollution, 

Penalties, Petroleum, Reporting and recordkeeping requirements. 

Dated: ____________________________ 

__________________________________ 

Lisa P. Jackson, 

Administrator.