Federal Register / Vol. 87, No. 74 / Monday, April 18, 2022 / Proposed Rules 22823 

proposed revision to Env-A 2805 retains 

these requirements without 

modification. EPA considers New 

Hampshire’s fugitive dust control 

requirements to be reasonable and 

concurs with retaining the standard. 

The current SIP-approved version of 

Env-A 2806 establishes Permit-ByNotification (PBN) procedures for nonmetallic mineral processing plants. The 

proposed revision to Env-A 2806 

updates these procedures to allow 

owners or operators to notify NH DES 

within 10 days after initial startup of an 

affected facility by electronic means as 

well as traditional hardcopy delivery 

methods. 

EPA concurs with New Hampshire 

that the proposed revisions to Env-A 

1000 and Env-A 2800 serve to 

strengthen and clarify these regulations 

and is, therefore, proposing to approve 

these revised regulations into the New 

Hampshire SIP. Furthermore, EPA 

agrees that the addition of Appendix A 

provides relevant references for 

implementing Env-A 2800. Therefore, 

EPA is proposing to approve the 

submitted revision of Env-A 2800 into 

the New Hampshire SIP. 

III. Proposed Action 

EPA is proposing to approve, and 

incorporate into the New Hampshire 

SIP, Env-A 1000 and Env-A 2800, which 

were submitted by the State of New 

Hampshire on August 19, 2021, and on 

January 8, 2020, respectively. 

EPA is soliciting public comments on 

the issues discussed in this proposal or 

on other relevant matters. These 

comments will be considered before 

EPA takes final action. Interested parties 

may participate in the Federal 

rulemaking procedure by submitting 

comments to this proposed rule by 

following the instructions listed in the 

ADDRESSES section of this Federal 

Register. 

IV. Incorporation by Reference 

In accordance with requirements of 1 

CFR 51.5, EPA is proposing to 

incorporate by reference into the New 

Hampshire SIP two New Hampshire 

Code of Administrative Rules: Env-A 

1000 (Prevention, Abatement, and 

Control of Open Source Air Pollution), 

effective August 1, 2019, and Env-A 

2800 (Sand and Gravel Sources; NonMetallic Mineral Processing Plants; 

Cement and Concrete Sources), effective 

December 20, 2018. 

The EPA has made, and will continue 

to make, these documents generally 

available electronically through https:// 

www.regulations.gov and/or in hard 

copy at the appropriate EPA office. 

V. Statutory and Executive Order 

Reviews 

Under the Clean Air Act, the 

Administrator is required to approve a 

SIP submission that complies with the 

provisions of the Act and applicable 

Federal regulations. 42 U.S.C. 7410(k); 

40 CFR 52.02(a). Thus, in reviewing SIP 

submissions, EPA’s role is to approve 

state choices, provided that they meet 

the criteria of the Clean Air Act. 

Accordingly, this proposed action 

merely approves state law as meeting 

Federal requirements and does not 

impose additional requirements beyond 

those imposed by state law. For that 

reason, this proposed action: 

• Is not a significant regulatory action 

subject to review by the Office of 

Management and Budget under 

Executive Orders 12866 (58 FR 51735, 

October 4, 1993) and 13563 (76 FR 3821, 

January 21, 2011); 

• Does not impose an information 

collection burden under the provisions 

of the Paperwork Reduction Act (44 

U.S.C. 3501 et seq.); 

• Is certified as not having a 

significant economic impact on a 

substantial number of small entities 

under the Regulatory Flexibility Act (5 

U.S.C. 601 et seq.); 

• Does not contain any unfunded 

mandate or significantly or uniquely 

affect small governments, as described 

in the Unfunded Mandates Reform Act 

of 1995 (Pub. L. 104–4); 

• Does not have federalism 

implications as specified in Executive 

Order 13132 (64 FR 43255, August 10, 

1999); 

• Is not an economically significant 

regulatory action based on health or 

safety risks subject to Executive Order 

13045 (62 FR 19885, April 23, 1997); 

• Is not a significant regulatory action 

subject to Executive Order 13211 (66 FR 

28355, May 22, 2001); 

• Is not subject to requirements of 

Section 12(d) of the National 

Technology Transfer and Advancement 

Act of 1995 (15 U.S.C. 272 note) because 

application of those requirements would 

be inconsistent with the Clean Air Act; 

and 

• Does not provide EPA with the 

discretionary authority to address, as 

appropriate, disproportionate human 

health or environmental effects, using 

practicable and legally permissible 

methods, under Executive Order 12898 

(59 FR 7629, February 16, 1994). 

In addition, the SIP is not approved 

to apply on any Indian reservation land 

or in any other area where EPA or an 

Indian tribe has demonstrated that a 

tribe has jurisdiction. In those areas of 

Indian country, the rule does not have 

tribal implications and will not impose 

substantial direct costs on tribal 

governments or preempt tribal law as 

specified by Executive Order 13175 (65 

FR 67249, November 9, 2000). 

List of Subjects in 40 CFR Part 52 

Environmental protection, Air 

pollution control, Carbon monoxide, 

Incorporation by reference, 

Intergovernmental relations, Lead, 

Nitrogen dioxide, Ozone, Particulate 

matter, Reporting and recordkeeping 

requirements, Sulfur oxides, Volatile 

organic compounds. 

Dated: April 12, 2022. 

David Cash, 

Regional Administrator, EPA Region 1. 

[FR Doc. 2022–08155 Filed 4–15–22; 8:45 am] 

BILLING CODE 6560–50–P 

ENVIRONMENTAL PROTECTION 

AGENCY 

40 CFR Part 80 

[EPA–HQ–OAR–2021–0845; FRL–9075–03– 

OAR] 

RIN 2060–AV55 

Renewable Fuel Standard Program: 

Canola Oil Pathways to Renewable 

Diesel, Jet Fuel, Naphtha, Liquefied 

Petroleum Gas and Heating Oil 

AGENCY: Environmental Protection 

Agency (EPA). 

ACTION: Proposed rule. 

SUMMARY: In this proposed rule, the 

Environmental Protection Agency (EPA) 

is providing an opportunity for 

comment on a proposed analysis of the 

lifecycle greenhouse gas (GHG) 

emissions associated with certain 

biofuels that are produced from canola/ 

rapeseed oil. This assessment considers 

diesel, jet fuel, heating oil, naphtha, and 

liquefied petroleum gas (LPG) produced 

from canola/rapeseed oil via a 

hydrotreating process, and proposes to 

find that these pathways would meet 

the lifecycle GHG emissions reduction 

threshold of 50 percent required for 

advanced biofuels and biomass-based 

diesel under the Renewable Fuel 

Standard (RFS) program. Based on these 

analyses, EPA is proposing to approve 

these fuel pathways, making them 

eligible to generate Renewable 

Identification Numbers (RINs), provided 

they satisfy the other definitional and 

RIN generation criteria for renewable 

fuel specified in the RFS regulations. 

DATES:

Comments. Comments must be 

received on or before May 18, 2022. 


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22824 Federal Register / Vol. 87, No. 74 / Monday, April 18, 2022 / Proposed Rules 

Public hearing. EPA will not hold a 

public hearing on this matter unless a 

request is received by the person 

identified in the FOR FURTHER

INFORMATION CONTACT section of this 

preamble by May 3, 2022. If EPA 

receives such a request, we will publish 

information related to the timing and 

location of the hearing and a new 

deadline for submission of public 

comments. 

ADDRESSES: You may send comments, 

identified by Docket ID No. EPA–HQ– 

OAR–2021–0845, by any of the 

following methods: 

• Federal eRulemaking Portal: 

https://www.regulations.gov (our 

preferred method). Follow the online 

instructions for submitting comments. 

• Email: a-and-r-Docket@epa.gov. 

Include Docket ID No. EPA–HQ–OAR– 

2021–0845 in the subject line of the 

message. 

• Mail: U.S. Environmental 

Protection Agency, EPA Docket Center, 

OAR, Docket EPA–HQ–OAR–2021– 

0845, Mail Code 28221T, 1200 

Pennsylvania Avenue NW, Washington, 

DC 20460. 

• Hand Delivery or Courier (by 

scheduled appointment only): EPA 

Docket Center, WJC West Building, 

Room 3334, 1301 Constitution Avenue 

NW, Washington, DC 20004. The Docket 

Center’s hours of operations are 8:30 

a.m.–4:30 p.m., Monday–Friday (except 

Federal Holidays). 

Instructions: All submissions received 

must include the Docket ID No. for this 

rulemaking. Comments received may be 

posted without change to https://

www.regulations.gov, including any 

personal information provided. For the 

full EPA public comment policy, 

information about CBI or multimedia 

submissions, and general guidance on 

making effective comments, please visit 

http://www.epa.gov/dockets/ 

commenting-epa-dockets. 

Out of an abundance of caution for 

members of the public and our staff, the 

EPA Docket Center and Reading Room 

are closed to the public, with limited 

exceptions, to reduce the risk of 

transmitting COVID–19. Our Docket 

Center staff will continue to provide 

remote customer service via email, 

phone, and webform. We encourage the 

public to submit comments via https:// 

www.regulations.gov or email, as there 

may be a delay in processing mail and 

faxes. Hand deliveries and couriers may 

be received by scheduled appointment 

only. For further information on EPA 

Docket Center services and the current 

status, please visit us online at https:// 

www.epa.gov/dockets. 

EPA continues to monitor information 

carefully and continuously from the 

Centers for Disease Control and 

Prevention (CDC), local area health 

departments, and our Federal partners 

so that we can respond rapidly as 

conditions change regarding COVID–19. 

FOR FURTHER INFORMATION CONTACT: 

Christopher Ramig, Office of Air and 

Radiation, Office of Transportation and 

Air Quality, Mail Code: 6401A, U.S. 

Environmental Protection Agency, 1200 

Pennsylvania Avenue NW, Washington, 

DC 20460; telephone number: 202–564– 

1372; email address: ramig.christopher@

epa.gov. 

SUPPLEMENTARY INFORMATION: 

Does this action apply to me? 

Entities potentially affected by this 

proposed rule are those involved with 

the production, distribution, and sale of 

transportation fuels, including gasoline 

and diesel fuel or renewable fuels such 

as ethanol, biodiesel, heating oil, 

renewable diesel, naphtha and liquified 

petroleum gas. Potentially regulated 

categories include: 

Category NAICS1 code Examples of potentially affected entities 

Industry ....................................................................................... 111120 Oilseed (except Soybean) Farming. 

Industry ....................................................................................... 324110 Petroleum refineries (including importers). 

Industry ....................................................................................... 325193 Ethyl alcohol manufacturing. 

Industry ....................................................................................... 325199 Other basic organic chemical manufacturing. 

Industry ....................................................................................... 424690 Chemical and allied products merchant wholesalers. 

Industry ....................................................................................... 424710 Petroleum Bulk Stations and Terminals. 

Industry ....................................................................................... 424720 Petroleum and Petroleum Products Merchant Wholesalers. 

Industry ....................................................................................... 454310 Other fuel dealers. 

1 North American Industry Classification System (NAICS). 

This table is not intended to be 

exhaustive, but rather provides a guide 

for readers regarding entities likely to be 

regulated or otherwise affected by this 

action. This table lists the types of 

entities that EPA is now aware could 

potentially be affected by this action. 

Other types of entities not listed in the 

table could also be affected. To 

determine whether your entity is 

regulated by this action, you should 

carefully examine the applicability 

criteria in the referenced regulations. If 

you have any questions regarding the 

applicability of this action to a 

particular entity, consult the person 

listed in the FOR FURTHER INFORMATION

CONTACT section. 

Table of Contents 

I. Introduction 

II. Analysis of GHG Emissions Associated 

With Production of Biofuels From 

Canola Oil 

A. Overview of Canola Oil 

B. Petition Overview 

C. Analysis of Lifecycle GHG Emissions 

III. Consideration of Lifecycle Analysis 

Results 

IV. Summary 

V. Statutory & Executive Order Reviews 

A. Executive Order 12866: Regulatory 

Planning and Review and Executive 

Order 13563: Improving Regulation and 

Regulatory Review 

B. Paperwork Reduction Act (PRA) 

C. Regulatory Flexibility Act (RFA) 

D. Unfunded Mandates Reform Act 

(UMRA) 

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 

and Safety Risks 

H. Executive Order 13211: Actions 

Concerning Regulations That 

Significantly Affect Energy Supply, 

Distribution, or Use 

I. National Technology Transfer and 

Advancement Act (NTTAA) 

J. Executive Order 12898: Federal Actions 

To Address Environmental Justice in 

Minority Populations and Low-Income 

Populations 

VI. Statutory Authority 

I. Introduction 

Section 211(o) of the Clean Air Act 

(CAA) establishes the Renewable Fuel 

Standard (RFS) program, under which 

EPA sets annual percentage standards 

specifying the total amount of 

renewable fuel, as well as three 

subcategories of renewable fuel, that 

must be used to reduce or replace fossil 

fuel present in transportation fuel, 

heating oil, or jet fuel. Non-exempt 

renewable fuels must achieve at least a 


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Federal Register / Vol. 87, No. 74 / Monday, April 18, 2022 / Proposed Rules 22825 

1See generally 42 U.S.C. 7545(o)(1). 

2For additional information see: https://

www.epa.gov/renewable-fuel-standard-program/ 

fuel-pathways-under-renewable-fuel-standard. 

3See, e.g., 83 FR 37735 (August 2, 2018) 

approving grain sorghum oil pathways and 78 FR 

41703 (July 11, 2013) approving giant reed and 

Napier grass pathways. 

4 42 U.S.C. 7545(o)(1)(H). 

5Hydrotreating, the process used to produce the 

vast majority of renewable diesel, consists of 

catalytic reactions in the presence of hydrogen. This 

process produces a ‘‘drop-in’’ fuel with properties 

virtually identical to petroleum diesel and distinct 

from biodiesel. 

6U.S. Canola Association. (2020). Petition for 

Pathways for Renewable Diesel from Canola Oil as 

‘‘Advanced Biofuel’’ Under the Renewable Fuel 

Standard Program. 

7The full set of modeling results, post-processing 

spreadsheets and other technical documents 

describing this analysis are available in the docket 

for this action. 

20-percent reduction in lifecycle 

greenhouse gas (GHG) emissions as 

compared to a 2005 petroleum baseline. 

Advanced biofuel and biomass-based 

diesel must achieve at least a 50 percent 

reduction, and cellulosic biofuel must 

achieve at least a 60 percent reduction.1

In addition to meeting the applicable 

lifecycle GHG reduction requirements, 

RINs may only be generated if the fuel 

meets the definitional and other criteria 

for renewable fuel (e.g., produced from 

renewable biomass as defined in the 

regulations and used to reduce or 

replace the quantity of fossil fuel 

present in transportation fuel, heating 

oil, or jet fuel) in CAA 211(o) and the 

RFS regulations at 40 CFR part 80, 

subpart M. 

Only fuels produced using pathways 

that EPA has approved as meeting all 

applicable requirements are eligible to 

generate RINs. There are three critical 

components of fuel pathways under the 

RFS program: (1) Fuel type; (2) 

feedstock; and (3) production process. 

Each approved pathway is associated 

with a specific ‘‘D code’’ corresponding 

to whether the fuel meets the 

requirements for renewable fuel, 

advanced fuel, cellulosic fuel, or 

biomass-based diesel.2 Since the 

formation of the RFS program, EPA has 

periodically promulgated rules to add 

new pathways to the regulations.3 In 

addition, EPA has approved facilityspecific pathways through the petition 

process in 40 CFR 80.1416. 

EPA’s lifecycle analyses are used to 

assess the overall GHG impacts of a fuel 

throughout each stage of its production 

and use. The results of these analyses, 

considering uncertainty and the weight 

of available evidence, are used to 

determine whether a fuel meets the 

necessary GHG reductions required 

under the CAA. Lifecycle analysis 

includes an assessment of emissions 

related to the full fuel lifecycle, 

including feedstock production, 

feedstock transportation, fuel 

production, fuel transportation and 

distribution, and tailpipe emissions. Per 

the CAA definition of lifecycle GHG 

emissions,4 EPA’s lifecycle analyses 

also include an assessment of significant 

indirect emissions, such as those from 

land use changes and agricultural sector 

impacts. 

EPA conducted lifecycle GHG 

analyses for several combinations of 

biofuel feedstocks, production 

processes, and fuels and promulgated 

several fuel pathways as part of its 

March 26, 2010 RFS final rule (75 FR 

14670) (the ‘‘March 2010 RFS2 rule’’). In 

the preamble to that final rule, EPA 

indicated that it intended to add fuel 

pathways to the regulations via further 

notice-and-comment rulemakings. EPA 

subsequently completed a proposed 

assessment for canola oil biodiesel; this 

proposed assessment was published in 

the Federal Register for notice and 

comment on July 26, 2010 (75 FR 

43522). This proposed assessment 

evaluated the GHG emissions associated 

with biodiesel produced from canola oil 

through a transesterification process. On 

September 28, 2010, EPA published a 

rule finalizing our determination that 

canola oil biodiesel meets the lifecycle 

GHG emissions reduction threshold of 

50 percent required by the CAA, and 

added row G to table 1 to 40 CFR 

80.1426, making canola oil biodiesel 

produced through a transesterification 

process eligible for biomass-based diesel 

(D-code 4) RINs (75 FR 59622) 

(September 2010 Canola Oil rule). This 

final rule did not include 

determinations for renewable diesel, jet 

fuel, naphtha, LPG, or heating oil 

produced from canola oil via a 

hydrotreating process.5 In the 2013 

Pathways I final rule (78 FR 14190, 

March 5, 2013) (‘‘2013 Pathways I 

rule’’), EPA added ‘‘rapeseed’’ to the 

existing pathway in row G for renewable 

fuel made from canola oil because ‘‘we 

had not intended the supplemental 

determination to cover just those 

varieties or sources of rapeseed that are 

identified as canola’’ (78 FR 14214). In 

that same rule, for clarity EPA also 

added ‘‘heating oil’’ to the rows in Table 

1 that already included renewable diesel 

or biodiesel (78 FR 14201). As in the 

2013 Pathways I rule, in this action we 

are similarly proposing to add new 

pathways to table 1 for biofuels 

produced from ‘‘Canola/Rapeseed oil’’ 

but for simplicity we refer to both 

canola and rapeseed as ‘‘canola.’’ 

In 2020, the United States Canola 

Association (USCA) submitted a 

petition to EPA requesting an evaluation 

of the GHG emissions associated with 

renewable diesel, jet fuel, naphtha, LPG 

and heating oil produced from canola 

oil via a hydrotreating process, and a 

determination of the renewable fuel 

categories, if any, for which such 

biofuels may be eligible.6 This preamble 

describes EPA’s analysis of the lifecycle 

GHG emissions associated with these 

fuel pathways and provides a brief 

overview of its results.7

As described in Section II.C.12 of this 

preamble, we estimate that the lifecycle 

GHG emissions associated with the 

production of renewable diesel via a 

hydrotreating process are approximately 

63 to 69 percent less than the applicable 

diesel baseline. We estimate that the 

naphtha and LPG co-produced with the 

renewable diesel has similar reductions 

of 64 to 69 percent and 63 to 69 percent 

compared to baseline GHG emissions, 

respectively. We estimate that jet fuel 

produced from canola oil through a 

hydrotreating process configured to 

maximize jet fuel output has lifecycle 

GHG emissions approximately 59 to 67 

percent lower than baseline emissions. 

These ranges of GHG emissions 

estimates are based on differences in 

hydrotreating process configurations. 

Section II.C.9 of this preamble discusses 

these estimates and our consideration of 

uncertainty in the analysis. 

Based on these estimates, we propose 

to find that these biofuels meet the 50 

percent GHG reduction threshold 

required for advanced biofuel and 

biomass-based diesel. In this action, 

based on our analysis of available data 

and other input, EPA is proposing to 

add to table 1 of 40 CFR 80.1426 

pathways for the production of 

renewable diesel, jet fuel, naphtha, LPG 

and heating oil produced from canola 

oil via a hydrotreating process. 

Specifically, we propose to add ‘‘Canola 

oil’’ to the Feedstock column in rows G, 

H, and I of table 1 to 40 CFR 80.1426. 

If finalized, these fuel pathways would 

be eligible for either biomass-based 

diesel (D-code 4) or advanced biofuel 

(D-code 5) RINs, depending on the fuel 

type and whether they are produced 

through a hydrotreating process that coprocesses renewable biomass with 

petroleum. EPA requests public 

comment on these proposed pathway 

approvals. 

EPA is also seeking comment on its 

proposal to add these fuel pathways to 

rows G, H, and I of table 1 to 40 CFR 

80.1426. We note that in addition to 

approving generally-applicable 

pathways by adding them to table 1, 

EPA has also approved fuel pathways 


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22826 Federal Register / Vol. 87, No. 74 / Monday, April 18, 2022 / Proposed Rules 

8See 21 CFR 184.1555 Rapeseed oil. 

9 75 FR 59622 (September 28, 2010). 

10For documentation of this methodology, see 

Docket Item No. EPA-HQ-OAR-2005–0161–3173. 

11For further discussion of the scientific 

reasoning behind the use of these two specific 

models of this methodology, see Chapter 2 of the 

Final Regulatory Impact Analysis associated with 

the March 2010 RFS2 rule (EPA–420–R–10–006). 

12 78 FR 41703 (July 11, 2013). 

13 64 FR 6183 (February 3, 1999). 

14United States Department of Agriculture, 

Foreign Agricultural Service. PSD Only Query tool. 

https://apps.fas.usda.gov/psdonline/app/ 

index.html#/app/advQuery. Data queried November 

5, 2021. 

on a facility-specific basis in cases 

where the evaluation involved a 

straightforward application of prior 

modeling and analysis established 

through a notice and comment process. 

Consistent with this practice, EPA may 

also consider the analysis in this 

proposed rule and any comments it 

receives in evaluating facility-specific 

pathway petitions submitted pursuant 

to 40 CFR 80.1416 that propose using 

canola oil as a biofuel feedstock or 

hydrotreating as a production process. 

II. Analysis of GHG Emissions 

Associated With Production of Biofuels 

From Canola Oil 

A. Overview of Canola Oil 

Canola oil is a vegetable oil that 

contains low concentrations of erucic 

acid (less than 2 percent), originally 

bred from cultivars of the Brassica and 

Sinapis genera.8 In addition to use as a 

renewable fuel feedstock, canola oil is a 

common vegetable oil for food use. In 

many instances, canola oil is used 

synonymously with rapeseed oil, or is 

considered a varietal of it. We propose 

definitions of canola/rapeseed oil to be 

included in 40 CFR 80.1401. We request 

comment on this definition. 

In September 2010, EPA evaluated a 

pathway for biodiesel produced from 

canola oil using a transesterification 

process to generate biomass-based diesel 

(D-code 4) RINs.9 For that analysis, EPA 

performed lifecycle analysis using the 

methodology first described in the 

March 2010 RFS2 rule.10 This 

methodology included the Forest and 

Agricultural Sector Optimization Model 

with Greenhouse Gases model (hereafter 

referred to as ‘‘FASOM’’) and the 

FAPRI–CARD model (Food and 

Agricultural Policy Research Institute 

international model; hereafter referred 

to as ‘‘FAPRI’’) developed at the Center 

for Agriculture and Rural Development 

at Iowa State University. These 

frameworks were used to estimate 

upstream GHG emissions associated 

with the production and transport of the 

canola oil feedstock.11 These upstream 

emissions were evaluated in concert 

with a transesterification biodiesel 

production process using natural gas 

and electricity for process energy and 

glycerin as a co-product. Based on that 

analysis, EPA determined that canola oil 

biodiesel produced via 

transesterification meets the 50 percent 

GHG reduction threshold and added 

this fuel pathway to row G in table 1 to 

40 CFR 80.1426, making this fuel 

eligible for biomass-based diesel (Dcode 4) RINs. The September 2010 

Canola Oil rule did not address 

pathways for renewable diesel, naphtha, 

LPG, jet fuel or heating oil produced 

from canola oil through a hydrotreating 

process. 

In addition to the lifecycle GHG 

analysis, another factor EPA has 

analyzed in pathway determinations is 

the invasiveness properties of the 

feedstock and the appropriateness of 

requiring associated risk management 

measures. EPA began evaluating 

invasiveness concerns in the context of 

fuel pathway evaluation under the RFS 

program in the July 11, 2013 rule 

approving renewable fuel pathways for 

giant reed (Arundo Donax) and Napier 

grass (Pennisetum Purpureum) after 

receiving comments that these 

feedstocks present a risk of 

invasiveness.12 Commenters stated that 

EPA should conduct an invasiveness 

species analysis, citing requirements of 

Executive Order (E.O.) 13112.13 E.O. 

13112, signed in February 1999, defines 

‘‘invasive species’’ as ‘‘an alien species 

whose introduction does or is likely to 

cause economic or environmental harm 

or harm to human health.’’ In the July 

2013 rule (78 FR 41703), we established 

requirements that producers of 

renewable fuel using giant reed or 

napier grass include a Risk Mitigation 

Plan (RMP) demonstrating measures 

taken to prevent the spread of these 

species, or demonstrate that an RMP is 

not needed because the species do not 

pose a significant likelihood of spread 

beyond the planted area. We are not 

proposing any risk management 

measures related to potential 

invasiveness of canola in this rule. 

Canola is an established feedstock with 

89 million acres planted in over 30 

countries in 2020.14 We do not believe 

canola is an invasive species as defined 

in E.O. 13112, and we do not believe the 

approval of additional canola oil-based 

fuels would have implications for 

invasiveness. We request comment on 

this decision and the appropriateness of 

risk mitigation practices. 

B. Petition Overview 

The USCA submitted a petition in 

March 2020, pursuant to the petition 

process described at 40 CFR 80.1416, 

requesting EPA’s evaluation of the 

lifecycle GHG emissions associated with 

producing renewable diesel, jet fuel, 

naphtha, LPG and heating oil from 

canola oil feedstock through a 

hydrotreating process. The petition 

requested that EPA evaluate these 

pathways using the same lifecycle 

analysis modeling approach used to 

evaluate canola-oil based biodiesel in 

the September 2010 Canola Oil Rule (75 

FR 59622). However, USCA stated in 

their petition that, in our 2010 analysis 

of canola oil-based biodiesel, we 

overestimated the lifecycle GHG 

emissions associated with canola oil 

production in four categories: Domestic 

land use change, domestic crop inputs, 

international land use change and 

international crop inputs. USCA 

supported their statements by 

comparing data sources underlying 

parts of our 2010 assessment of canola 

oil with more recent data. Specifically, 

the petition referenced more recent data 

on canola production, yields, trade, and 

oil extraction. Based on these 

comparisons, the USCA petition 

requested that we adjust our 2010 

canola oil estimates without conducting 

new agricultural sector modeling. 

The USCA petition requests that we 

simply adjust the results of our 

previously completed agricultural sector 

modeling based on new information. We 

believe such adjustments would be 

inappropriate because they would create 

inconsistencies between the agricultural 

sector modeling and the results. For 

example, it would be inappropriate to 

reduce planted area of canola based on 

new yield data and simply assume that 

the rest of the agricultural model results 

would remain unchanged. Thus, while 

we are not adjusting or otherwise 

reopening our 2010 canola oil-based 

biodiesel analysis or estimates, we do 

believe that the USCA petition 

highlights appropriate and significant 

areas where the data and information 

considered in the 2010 canola modeling 

should be updated for purposes of 

evaluating new fuel pathways that use 

canola oil feedstock. The petition 

includes detailed information showing 

that more recent data on canola oil 

production and trade patterns differed 

significantly from the data considered in 

the 2010 analysis. Based on these 

significant differences, and since we 

have not previously published lifecycle 

GHG emissions estimates for canola oilbased fuels produced through a 

hydrotreating process, we believe it is 

important to consider the more recent 

data highlighted in the USCA petition in 

a new lifecycle GHG analysis for these 


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15For documentation of the LCA frameworks and 

methodology, see Docket Item No. 

EPA-HQ-OAR-2005–0161–3173. 

16For information about our 2010 methodology 

and analysis see Section 2 of the regulatory impact 

analysis (RIA) for the March 2010 RFS2 rule and the 

associated lifecycle results (Docket Item No. 

EPA-HQ-OAR-2005–0161–3173). 

17See documentation and description available 

from Argonne National Lab at https://

greet.es.anl.gov. 

18Argonne National Laboratory. (2021). 

Greenhouse gases, Regulated Emissions, and Energy 

use in Transportation (GREET) Model. https://

greet.es.anl.gov/. 

19As noted previously, we are not reopening the 

2010 lifecycle GHG analysis for canola oil biodiesel. 

20Both the natural gas and electricity emissions 

factor comparisons are weighted with the same 100- 

year GWP values from the IPCC Fifth Assessment 

Report. 

fuel pathways. This analysis uses the 

same modeling frameworks and 

methodology as we have used 

previously to evaluate agricultural 

feedstocks but includes updated data 

inputs as discussed later in this 

proposal.15

C. Analysis of Lifecycle GHG Emissions 

1. Overview of Lifecycle Analysis 

Methodology 

For this proposed rule, we evaluated 

the lifecycle GHG emissions of 

producing renewable diesel and other 

biofuels from canola oil. In this section, 

we describe our methodology for 

conducting this evaluation, the 

assumptions and scenarios evaluated 

using this methodology, and the results 

of our analysis. We used the same 

biofuel lifecycle analysis methodology 

and modeling framework developed for 

the March 2010 RFS2 rule and that was 

subsequently used for the September 

2010 Canola Oil Rule.16 The 

components of this methodology are 

described further later in this proposal, 

but generally involve the use of 

agricultural modeling to estimate 

emissions from land use change, crop 

production, livestock, and rice methane, 

as well as application of coefficients and 

assumptions from the Greenhouse 

Gases, Regulated Emissions, and Energy 

use in Technologies (GREET) model 17

and other sources to evaluate emissions 

associated with feedstock and fuel 

transport, processing, and use. This 

methodology was developed to estimate 

‘‘lifecycle greenhouse gas emissions’’ as 

defined at section 211(o)(1)(H) of the 

Clean Air Act. It was used for the March 

2010 RFS2 rule after an extensive peer 

review and public comment process. 

In general, this methodology involves 

using two agricultural sector models, 

FASOM and the FAPRI–CARD model, 

to estimate U.S. and non-U.S. GHG 

emissions impacts respectively. In this 

methodology, we model and evaluate a 

hypothetical canola oil demand shock 

scenario to estimate changes in 

agricultural production and land use 

and associated GHG emissions 

associated with the biofuel pathway 

under consideration. In this demand 

shock scenario, U.S. domestic 

consumption of a specific biofuel 

pathway is assumed to increase by some 

amount relative to the volume of U.S. 

domestic consumption in a reference 

scenario. 

Following the lifecycle GHG analysis 

methodology developed for the March 

2010 RFS2 rule, the modeling scenarios 

used in this analysis are designed to 

isolate the GHG impacts associated with 

the biofuel pathway being considered. 

They are not meant to project or forecast 

future market conditions, or to 

otherwise predict what will happen in 

the future if a given biofuel pathway is 

approved. Some of our assumptions, 

which are necessary to construct a 

scenario which appropriately isolates 

the impacts of a single fuel pathway, 

intentionally simplify what we would 

expect to occur in the real world. For 

example, in these scenarios, we hold 

U.S. consumption of all biofuels 

constant throughout the entire modeled 

period, except for the biofuel being 

evaluated. In reality, an increase in 

domestic consumption of one biofuel 

product would be expected to have 

some impact on consumption of other 

biofuel products. However, allowing for 

such market-balancing behavior would 

confound our ability to estimate the 

GHG impacts of one biofuel in isolation. 

Therefore, such simplifying 

assumptions are necessary for the 

purposes of our analysis. For these same 

reasons, it would be inappropriate to 

characterize the scenario results 

presented later in this proposal as a 

projection or forecast; these results 

should be interpreted as hypothetical 

scenarios. 

This methodology also includes 

estimating GHG emissions associated 

with fuel production, distribution and 

use based on data from GREET and 

other sources. All of these GHG 

emissions estimates are added together 

and divided by the change in the 

amount of biofuel produced in the 

scenarios evaluated to estimate the 

lifecycle GHG emissions associated with 

fuel produced through the evaluated 

pathway, in terms of carbon dioxideequivalent emissions per megajoule (MJ) 

of fuel produced. We are not reopening 

this overall lifecycle analysis 

methodology and modeling framework 

in this proposed rule; thus, any 

comments on the overall methodology 

and modeling framework are outside the 

scope of this rulemaking action. 

Although we are using the same 

overall methodology and modeling 

framework as developed for the March 

2010 RFS2 rule, we have updated the 

data inputs into this analysis in the 

following areas: (1) Canola/rapeseed oil 

production, crushing, yields and trade 

based on historical data from USDA and 

other sources, (2) GHG emissions factors 

and transportation and distribution 

assumptions based on the latest version 

of the GREET model,18 (3) the most 

recent global warming potentials from 

the Intergovernmental Panel on Climate 

Change (IPCC), (4) international crop 

production energy inputs based on 

historical FAO data, and (5) 

hydrotreating process assumptions 

based on literature review and 

information submitted through new 

pathway petitions. We request comment 

on these data input updates. As 

discussed in Section II.C.9 of this 

preamble, we also request comment on 

our use of the energy allocation method 

to account for co-products from the 

hydrotreating process, given that prior 

RFS rules used a displacement approach 

for some of these co-products. The rest 

of this section describes the updated 

data inputs used in our analysis and the 

scenarios modeled. 

The lifecycle analysis for the March 

2010 RFS2 rule relied to a relatively 

large extent on data and GHG emissions 

factors from the GREET model 

developed and maintained by Argonne 

National Laboratory. Version 1.8b of 

GREET was the most recent version 

available at the time of the March 2010 

RFS2 rule.19 For the analysis for this 

proposed rule, we have updated GHG 

emissions factors based on more recent 

data in GREET–2020. Some of the 

emissions factors have not changed 

substantially, while others have. For 

example, the carbon dioxide-equivalent 

emissions factor for natural gas 

consumed in the U.S. in medium-size 

industrial boiler increased by only 1% 

from GREET 1.8b to GREET–2020. 

Whereas, the emissions factor for U.S. 

average electricity has decreased by 

41% reflecting significant changes to the 

U.S. grid.20

The latest version of GREET was 

released in October 2021. While the 

analysis for this proposed rule was 

almost entirely complete using data and 

emissions factors from GREET–2020 

prior to the release of GREET–2021, we 

do consider the updated hydrotreating 

input-output data from GREET–2021 in 

this proposed rule. A brief review shows 

that the other relevant changes to 

emissions factors from GREET–2020 to 

GREET–2021 are relatively small—for 


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21 IPCC, 2014: Climate Change 2014: Synthesis 

Report. Contribution of Working Groups I, II and III 

to the Fifth Assessment Report of the 

Intergovernmental Panel on Climate Change [Core 

Writing Team, R.K. Pachauri and L.A. Meyer (eds.)]. 

IPCC, Geneva, Switzerland, 151 pp. 

22 In most of the world, canola is referred to as 

‘‘rapeseed’’. For consistency, we use ‘‘canola’’ 

throughout to refer to both canola and rapeseed. 

23United States Department of Agriculture, 

Foreign Agricultural Service. PSD Only Query tool. 

https://apps.fas.usda.gov/psdonline/app/ 

index.html#/app/advQuery. Last accessed March 

16, 2022. 

24These are taken from the USDA PSD data cited 

above and from the USDA National Agricultural 

Statistical Service QuickStats database (USDA 

NASS QuickStats). https://quickstats.nass.usda.gov. 

Last accessed March 16, 2022. 

25Complete sets of results for these FASOM and 

FAPRI modeling scenarios are available on the 

docket. 

26A memorandum describing these updates and 

referencing their sources is available on the docket. 

27 Depending on the source of hydrotreating 

process data used, the size of the shock ranges from 

187 million gallons of hydrotreated renewable fuel 

(based on GREET–2021) to 220 million gallons 

(based on data in petitions submitted pursuant to 

40 CFR 80.1416 claimed as confidential business 

information). 

28See for reference the USDA Oil Crop Yearbook 

at https://www.ers.usda.gov/data-products/oilcrops-yearbook. Last accessed March 16, 2022. 

29United States Department of Agriculture, 

Foreign Agricultural Service. PSD Only Query tool. 

https://apps.fas.usda.gov/psdonline/app/ 

index.html#/app/advQuery. Data queried March 16, 

2022 

example, in the latest version of GREET 

the GHG emissions factors per energy 

unit for average natural gas did not 

change, the emissions factor for gaseous 

hydrogen increased by one percent, and 

U.S. average grid electricity decreased 

by two percent. We intend to update 

these data to GREET–2021 for the final 

rule, but we do not expect these updates 

to change our estimates enough to affect 

our overall finding that the pathways 

evaluated satisfy the statutory 50 

percent GHG reduction threshold for 

qualification as biomass-based diesel or 

advanced biofuel. 

Another update is that the analysis for 

the March 2010 RFS2 rule used 100-year 

global warming potential (GWP) values 

from the IPCC Second Assessment 

Report. The analysis for this proposed 

rule uses 100-year GWP values from the 

most recent IPCC Fifth Assessment 

Report.21 Based on these updates, the 

GWP for methane increased from 21 to 

30, and the GWP for nitrous oxide 

decreased from 310 to 265. 

Our analysis for this proposed rule 

considers updated data based on 

information submitted as part of the 

USCA petition. Global canola acreage 

has increased over the last decade, from 

83 million acres globally in 2010 to 89 

million acres in 2020.22 U.S. canola 

acreage increased over this time from 

1.43 million acres in 2010 to 1.80 

million acres in 2020, representing 1.7 

percent and 2 percent of global totals 

respectively. Yields have increased over 

the same period in several producing 

regions. Average U.S. yields grew from 

1,713 pounds per acre in 2010 to 1,927 

pounds per acre in 2020 (12.5 percent 

increase) while yields improved more 

substantially in Canada and China over 

the same period (25 percent and 18 

percent increases respectively). Global 

production of canola oil increased 24 

percent between 2010 and 2020 to meet 

growing demand. This increase in 

demand was led by China. China’s 

consumption of canola oil grew from 13 

billion pounds in 2010 to 18 billion 

pounds in 2020. The U.S. canola oil 

consumption grew by 1.9 billion pounds 

over this timeframe, from 3.7 billion 

pounds to 5.6 billion pounds, 

representing a 54 percent increase.23

Specifically, for the purpose of this 

rulemaking we have updated our 

FASOM and FAPRI input assumptions 

to include more recent USDA historical 

data on global canola oil production, 

yields and trade.24 Updates were made 

consistently between the two 

frameworks, using common data sources 

and assumption values where 

applicable (i.e., where both models 

require the same input assumption). 

These assumption updates are described 

in more detail in Sections II.C.2 and 3 

later in this proposal. We have also 

updated the data source for estimating 

GHG emissions associated with farming 

energy use for canola oil and other crop 

production outside of the U.S. For more 

details, see Section II.C.5 of this 

preamble. We also consider new data on 

canola crushing from the USCA 

petition, feedstock and fuel transport 

from GREET–2020 and hydrotreating 

from GREET–2021, as well as data from 

review of the literature and information 

provided through RFS new pathway 

petitions. All these updates taken 

together decrease our estimates of the 

lifecycle GHG emission associated with 

using canola oil as a biofuel feedstock 

compared to compared to our analysis 

for the September 2010 Canola Oil Rule. 

EPA previously determined that 

biodiesel produced from canola oil via 

transesterification meets the 50 percent 

threshold to generate D4 RINs. EPA is 

not revisiting, revising, or requesting 

comment on canola oil-based biodiesel 

or any other existing pathways. Given 

that most of the updates for this 

proposed rule pertain specifically to 

canola oil, we note that it would be 

inappropriate to draw any conclusions 

about the lifecycle GHG emissions 

associated with biofuel pathways that 

use feedstocks other than canola oil 

from our estimates for this proposed 

rule. EPA is therefore not requesting 

comment on pathways using any other 

feedstock besides canola oil. 

EPA conducted two modeling 

scenarios in both FASOM and FAPRI for 

this analysis.25 The difference in GHG 

emissions between these two scenarios 

represents our estimate of the emissions 

from land use change, agricultural 

input, livestock, and rice methane 

associated with using canola oil as a 

biofuel feedstock (our emissions 

estimates are described in Table II.C.8– 

1). First, we ran an updated Control 

Case that reflected the updated 

assumptions for global canola oil 

production, yields, and trade.26 In this 

Control Case, we assumed no canola oilbased biofuels were consumed in the 

U.S. over the period of analysis (2012– 

2052 in FASOM, 2012–2022 in FAPRI), 

consistent with our Control Case 

assumptions for previous analyses. 

Second, we conducted a shock scenario 

that assumed a 1.53 billion pound 

increase in canola oil production for use 

as feedstock to produce approximately 

200 million gallons of canola oil-based 

renewable diesel, jet fuel, naphtha, LPG 

and heating oil for U.S. consumption of 

in 2022 (hereafter the ‘‘Canola Case’’), 

which was assumed to ramp up linearly 

from 2012 to 2022 (see Table II.C.1–1).27

According to USDA historical data, 

annual U.S. consumption of canola oil 

ranged from about 5.3 to 6.4 billion 

pounds over the period between 2015 

and 2020.28 In addition, global canola/ 

rapeseed seed annual exports ranged 

from approximately 32 to 38 billion 

pounds between 2015 and 2020 and 

canola/rapeseed oil exports ranged from 

about 9 to 13 billion pounds over the 

same period; this suggests substantial 

quantities of additional feedstock may 

be available for import to the U.S. 

market.29 Based on data from the EPA 

Moderated Transaction System (EMTS), 

the U.S. produced approximately 160 

million gallons of canola oil biodiesel in 

2020, and another 123 million gallons of 

biodiesel produced from a mix of 

feedstocks were imported from Canada, 

which likely included a portion from 

canola oil. Thus, the volume of 

hydrotreated canola oil-based fuels in 

the modeled shock is a similar order of 

magnitude as the volume of biodiesel 

currently produced from canola oil. 

Finally, according to EPA’s 

administrative data from the RFS 

program, about 1.5 billion RINs were 

generated for renewable diesel in 2019, 

equivalent to about 900 million 


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30See public data from the RFS program at 

https://www.epa.gov/fuels-registration-reportingand-compliance-help/rins-generated-transactions. 31Note that, consistent with our existing 

methodology, the volume shock is implemented 

slightly differently in FASOM and FAPRI. For 

FASOM, which operates in 5-year time steps, the 

values in this table fully represent the assumptions 

used to implement the shock. For FAPRI, which 

operates in annual time steps, interim year 

assumption values are interpolated linearly to 

create a smooth ‘‘ramp-up’’ path for the volume 

shock. Further description of this methodology can 

be found in Chapter 2 of the Final Regulatory 

Impact Analysis associated with the March 2010 

RFS2 rule (EPA–420–R–10–006). 

32See Docket Item No. EPA–HQ–OAR–2005– 

0161–3173 for details on the version of FASOM 

used to analyze emissions associated with soybean 

oil-based biodiesel. See Docket No. EPA–HQ–OAR– 

2010–0133 for details on the version of FASOM 

used to analyze emissions associated with canola 

oil-based biodiesel. See Docket No. EPA–HQ–OAR– 

2016–0771 for details on the version of FASOM 

used to analyze emissions associated with sugar 

beet-based ethanol. 

33See Docket No. EPA–HQ–OAR–2016–0771 for 

details on the version of FASOM used to analyze 

emissions associated with sugar beets. 

34Further information about our assumptions and 

the modeling results are available in the docket for 

this action. 

35See USDA NASS QuickStats. https://

quickstats.nass.usda.gov. Last accessed March 16, 

2022. 

36Further information regarding these updated 

assumptions is detailed in the memorandum, 

‘‘Memo on FASOM Assumptions,’’ available in the 

docket for this action. 

37For detailed data on US imports of canola seed, 

meal, and oil by trade partner, see the UN Comtrade 

database at https://comtrade.un.org/data. 

38For U.S. price data see USDA ERS—Oil Crops 

Yearbook. Canola Seed and Canola Seed Products. 

https://www.ers.usda.gov/data-products/oil-cropsyearbook. Last accessed March 16, 2022. For 

Canadian price data, see Canola Council of Canada. 

Canadian canola export statistics. https://

www.canolacouncil.org/markets-stats/exports/ 

#export-values. Last accessed March 16, 2022. 

39Further information regarding the assumptions 

made to conduct the FASOM modeling in support 

of this analysis is available in the memorandum, 

‘‘Memo on FASOM Assumptions,’’ available in the 

docket for this action. 

40EPA (2010). Renewable fuel standard program 

(RFS2) regulatory impact analysis. Washington, DC, 

US Environmental Protection Agency Office of 

Transportation Air Quality. EPA–420–R–10–006. 

gallons.30 Based on these data, we 

believe the magnitude of the assumed 

shock in the Canola Case is reasonable 

and appropriate. 

All other assumptions were held 

constant between the Control Case and 

the Canola Case. The structure of this 

shock was designed to be consistent 

with the shock methodology approach 

used for EPA’s previous lifecycle GHG 

analyses of agricultural feedstocks 

under the RFS program. 

TABLE II.C.1–1—CANOLA OIL SHOCK

SCENARIO 31

Year 

Assumed increase 

in USA canola oil 

consumption 

for biodiesel 

production 

(billion pounds of 

canola oil) 

2012 .......................................... 0.25 

2017 .......................................... 0.9 

2022 through 2057 .................... 1.53 

2. FASOM Analysis 

EPA used FASOM to estimate the 

GHG emissions from domestic land use 

change, farm inputs, livestock, and rice 

methane associated with using canola 

oil as a biofuel feedstock. This is the 

same methodology EPA previously used 

to estimate these GHG emissions 

sources for soybean oil-based biodiesel 

and other agricultural feedstocks.32 EPA 

updated several aspects of its analysis of 

the domestic U.S. emissions associated 

with production of fuels from canola oil 

for this analysis, building on the version 

of FASOM used for the analysis of the 

GHG emissions attributable to the 

production and transport of sugar beets 

for use as a biofuel feedstock.33 In this 

section, we first review the updates 

made to model inputs and other 

assumptions for this analysis. Following 

this, we present a summary of the 

FASOM modeling results.34

i. Modifications to Model Inputs and 

Assumptions 

For this analysis, EPA updated 

FASOM assumptions related to market 

conditions for canola seed, canola meal, 

and canola oil. This included 

assumptions about historical U.S. 

prices; quantities of seed, meal, and oil 

consumed; planted area; seed yields; 

and trade quantities and elasticities. 

Updated assumptions for prices, planted 

area, and seed yields were primarily 

taken from USDA National Agricultural 

Statistical Service (NASS) historical 

data sets.35 In some cases, these NASS 

data were supplemented with additional 

data taken from the USDA Oil Crop 

Yearbook and the USCA. These updates 

replaced previous assumptions in 

FASOM for the years 2011 through 

2020. In the case of canola seed yields, 

FASOM’s baseline trend of future yields 

was also reprojected using the updated 

NASS data.36

EPA also updated FASOM to reflect 

differences in historical pricing between 

U.S. domestically-produced canola 

seed, oil, and meal and imported canola 

seed, oil, and meal. Imported canola 

seed and oil from Canada are important 

components of the U.S. market, 

generally representing well over 90 

percent of the canola products 

consumed in the U.S. in any given 

year.37 Reflective of this market 

dynamic, historical data show that 

Canadian producers exporting to the 

U.S. were systematically paid less for 

their canola oil than domestic U.S. 

producers.38 In previous modeling 

analyses, FASOM assumed a single 

price for both domestic and imported 

canola oil. This led to a consumption 

mix that included a greater percentage 

share of domestically-produced canola 

products, especially oil, than actually 

occurred historically. In the updated 

modeling conducted for this assessment, 

EPA differentiated the prices at which 

domestic and imported canola seed and 

oil could be supplied to the U.S. market 

and then recalibrated canola trade 

elasticities to better reproduce historical 

market shares of domestically-produced 

canola products and Canadian imported 

canola products more accurately in 

FASOM.39 EPA requests comment on 

these updates to our modeling 

assumptions. We are not seeking 

comment on the overall lifecycle 

analysis methodology and modeling 

framework used to conduct this 

analysis, which were subject to notice 

and comment in the March 2010 RFS2 

rule.40

ii. Summary of Results 

This section describes the differences 

in FASOM results between modeled 

outcomes from the Control Case and the 

Canola Case (described in Table II.C.1– 

1). Unless otherwise stated, the data 

presented in this section are the 

calculated differences between the 

Control Case and the Canola Case (i.e., 

the model output value for a variable 

reported in the Canola Case minus the 

output value for that same variable 

reported in the Control Case). In this 

summary, we first describe the ways in 

which FASOM estimates the canola oil 

feedstock used to supply the biofuel 

shock would be sourced. We then 

describe the market adjustments in 

canola oil prices, supply, demand, and 

trade which FASOM estimates would be 

necessary to facilitate this sourcing of 

canola oil for fuel use. Following this, 

we describe the shifts in production of 

other crops, cropland use, and land use 

which FASOM estimates would occur 

as a result of the sourcing of canola oil 

for fuel use. 

The total quantity of canola oil 

required to produce the assumed 

marginal volume shock in the Canola 

Case was assumed to be approximately 

1.53 billion pounds. To supply this 

quantity of canola oil to the biofuel 

production sector, FASOM made several 

market adjustments. Of the total 1.53 

billion pounds required, FASOM 

estimated approximately 1.28 billion 

pounds would be supplied by 

increasing the total U.S. supply of 


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41FASOM is a U.S.-only model and does not 

disaggregate imports and exports to and from the 

U.S. by country of origin. 

42Further information is available in the 

documents, ‘‘Canola_FASOM results’’ and ‘‘FASOM 

HTML (full results)’’ available in the docket for this 

action. 

canola oil via a combination of 

increased imports and increased 

domestic production. These 1.28 billion 

pounds would represent an 

approximately 28 percent increase in 

total domestic supplies of canola oil. 

FASOM estimates canola oil imports 

would increase by about 1.18 billion 

pounds. Domestic crushing of canola 

seed into meal and oil would produce 

about 0.1 billion pounds of additional 

canola oil. Domestic demand for nonfuel uses of canola oil, inclusive of all 

food uses (e.g., cooking, baking, salad 

dressings) and non-fuel industrial uses 

(e.g., industrial lubricants, cleaning 

products, cosmetics), would decrease by 

approximately 0.25 billion pounds to 

provide the remaining canola oil 

required to meet the 1.53-billion-pound 

shock. These shares of biofuel feedstock 

are summarized in Table II.C.2.ii–1. 

TABLE II.C.2.ii–1—SOURCES OF CANOLA OIL FOR BIOFUEL FEEDSTOCK IN THE CANOLA CASE

Feedstock source 

Quantity 

(billion 

pounds) 

Percent 

of total 

volume shock 

Increased Imports .................................................................................................................................................... 1.18 77 

Reduced Domestic Demand for Non-Fuel Uses ..................................................................................................... 0.25 16 

Increased Domestic Production ............................................................................................................................... 0.1 7 

Total Volume Shock ......................................................................................................................................... 1.53 100 

As stated earlier in this proposal, 

most of the additional supply of biofuel 

feedstock is expected to come from 

imported canola oil.41 FASOM 

estimates these imports would increase 

by approximately 40 percent in 2022 in 

response to the shock. Because modeled 

non-fuel uses of canola oil are not 

drawn on as significantly to provide 

feedstock for this shock, FASOM does 

not estimate there would be a significant 

need to backfill the domestic U.S. 

vegetable oil market. Domestic 

consumption of other vegetable oils 

therefore does not change significantly 

in these results. Following this, FASOM 

estimates virtually no changes in 

imports of other vegetable oils in these 

results. Increased demand for canola oil 

in response to the volume shock is 

estimated to cause the average price of 

canola oil for all uses to increase by 

approximately 24 percent in the Canola 

Case. This price increase would put 

downward pressure on other uses of 

canola oil, and non-biofuel domestic 

demand for canola oil is estimated to 

decrease by approximately 5.6 percent. 

FASOM estimates these higher prices 

would also induce domestic U.S. 

production of canola oil to increase by 

about 7 percent. Table II.C.2.ii–2 reports 

changes in supply, demand, and prices 

for canola oil in the Canola Case relative 

to the Control case. Changes for other 

modeled vegetable oils, specifically 

soybean oil and corn oil, are estimated 

to be in the range of 0.03 percent or less 

and are not presented here, though these 

results are available in the docket.42

TABLE II.C.2.ii–2—CANOLA OIL

MARKET RESPONSES IN 2022 

[In percentage changes] 

Percent 

change from 

control case 

Total Domestic Demand ..................... ¥5.6 

U.S. Imports ........................................ 38.9 

U.S. Production ................................... 7.0 

U.S. Price ............................................ 24.1 

FASOM estimates the increase in 

canola oil production would result in an 

increase in canola seed crushing of 

approximately 253.5 million pounds, an 

increase in domestic canola oil 

production of about 7 percent compared 

to the Control Case. Most of this 

increase in canola crushing would be 

supplied through increased imports of 

whole canola seed. Of the total increase 

in canola seed supply to the crushing 

market, 87 percent is estimated to come 

from increased imports and 13 percent 

is estimated to come from increased 

domestic U.S. production. As observed 

above, the U.S. canola product markets 

are historically import-dependent. 

Based on this, we believe the response 

in FASOM is consistent with historical 

market patterns. However, FASOM 

estimates the increase in domestic 

crushing would also induce a response 

from domestic canola seed demands. 

FASOM estimates direct domestic uses 

of canola seed other than crushing 

would decrease by approximately 16 

percent. Domestic canola seed 

production also responds, and FASOM 

estimates domestic production would 

increase by approximately 1 percent. 

These impacts are summarized in Table 

II.C.2.ii–3. This increase in U.S. canola 

seed production would be facilitated in 

part by a modeled expansion in canola 

harvested crop area of about 17,600 

acres, or about 1.2 percent, in the U.S. 

in 2022 (see Table II.C.2.ii–4). 

TABLE II.C.2.ii–3—CANOLA SEED

MARKET RESPONSES IN 2022 

[In million pounds] 

Change from 

control case 

Total Domestic Demand ........... ¥5.8 (¥16%) 

U.S. Imports .............................. 216.5 (20%) 

U.S. Production ......................... 31.3 (1%) 

U.S. Canola Seed Crushing ...... 253.5 (7%) 

These shifts in canola supply, 

demand, and trade would also have 

implications for production and 

consumption of other crops. The 

modeled increase in canola crushing 

also produces an additional 156 million 

pounds of canola meal, all of which 

FASOM estimates would be supplied to 

the domestic livestock market. This 

influx of meal would primarily displace 

corn in livestock diets. Corn 

consumption in the domestic feed 

market is estimated to decrease by about 

306 million pounds (about 0.08 

percent). This same dynamic can be 

observed in the FASOM results for 

commodity trade. As international trade 

partners increase exports of canola oil to 

the U.S., these exporters crush 

additional canola seed. This creates 

additional supplies of meal for these 

canola-producing nations, reducing 

their demands for corn as well. As a 

result, corn exports from U.S. are 

estimated to decrease by about 271 

million pounds (about 0.28 percent). On 

net, FASOM estimates that U.S. corn 

production would decline by about 589 

million pounds and that corn harvested 

area would decline by about 49,100 

acres, or about 0.06 percent (see Table 

II.C.2.ii–4). 

Canola and wheat can be produced on 

the same type of land in high latitude 


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43National Oilseed Processors Association, 

‘‘NOPA Plant Locations’’, https://www.nopa.org/ 

oilseed-processing/nopa-plant-locations/. Last 

accessed March 16, 2022. 

44Note that FASOM does not track conversion of 

other land types to cropland by crop. This modeled 

expansion in North Dakota cropland is best 

understood as an increase in total cropland at the 

expense of other land uses rather than an expansion 

cropland for canola, wheat, or any other specific 

crop into previously uncropped area. 

agricultural systems like Canada and 

North Dakota, and many farmers rotate 

the two crops. In response to an increase 

in production of canola, farmers are 

likely to respond in one of two ways. 

One option is that total acres in wheat/ 

canola rotation could increase. The 

other option is for canola to displace 

wheat area to some extent as farmers tilt 

rotations more heavily towards the 

former (e.g., canola-canola rotations 

rather than canola-wheat rotations). We 

observe these complex dynamics in the 

FASOM results for the Canola Case. To 

increase canola exports to the U.S. 

market, FASOM estimates the 

international market would decrease 

production of wheat, creating an 

opportunity for U.S. wheat producers to 

increase their exports. This impact is 

relatively marginal in comparison to the 

shock. However, FASOM estimates U.S. 

wheat exports would increase by about 

174 million pounds, or about 0.18 

percent. Domestic wheat production 

would increase by about 169 million 

pounds and the harvested area in wheat 

production (excluding wheat used for 

grazing) would expand by about 63,000 

acres, or about 0.02 percent (see Table 

II.C.2.ii–4). 

The modeling results also show some 

minor net shifts in other cropland as 

markets re-equilibrate in response to the 

shock, totaling about 28,100 harvested 

acres, or about 0.01 percent. Harvested 

crop area impacts are summarized in 

Table II.C.2.ii–4. The shock results in 

modeled net increase in total domestic 

harvested crop area of approximately 

60,600 acres. This increase would 

require some shifting of land use from 

other uses to cropland; as discussed 

later in this section this land is shifted 

into cropland from pasture and 

cropland pasture on net. 

TABLE II.C.2.ii–4—HARVESTED CROP

AREA RESPONSES IN 2022 

[In thousand acres] 

Change from 

control 

Canola ....................................... 17.6 (1.2%) 

Wheat ........................................ 63 (0.02%) 

Corn ........................................... ¥49.1 (¥0.06%) 

All Else ...................................... 28.1 (0.01%) 

Total ................................... 60.6 (0.02%) 

Our FASOM results estimate these 

small shifts in agricultural production 

volumes would have some modest 

impact on agricultural prices. In our 

scenario, canola meal and wheat prices 

are estimated to decline as production 

increases, by 0.02 percent and 0.51 

percent respectively, while corn prices 

would rise by 0.44 percent as 

production decreases. FASOM estimates 

the livestock market would respond to 

the increase in corn prices by 

consuming slightly less corn (0.08 

percent compared to baseline 

consumption). This would be made up 

in part by a modeled increase in canola 

meal consumption. However, the 

modeled increase in corn prices is 

estimated to create some upward 

pressure on overall feed prices as well, 

raising the estimated cost of livestock 

production. On net in these results, beef 

slaughter is estimated to decrease by 

0.04 percent in response to higher costs 

and chicken (broiler) slaughter would 

decrease by 0.05 percent. 

Geographically, the modeled domestic 

response to the shock is concentrated in 

North Dakota. Canola production is 

estimated to increase in North Dakota by 

about 28.9 million pounds (about 1.4 

percent) and canola crop area is 

estimated to expand by 16,300 acres (as 

discussed later in this section, this 

acreage comes from a mix of existing 

and new agricultural land). This 

accounts for about 92 percent of the 

total estimated increase in U.S. 

domestic canola production in the 

Canola Case. As North Dakota is the 

dominant producer of canola in the 

U.S., this modeled impact appears to be 

consistent with historical agricultural 

patterns. North Dakota is also a 

significant producer of wheat. As canola 

production is estimated to expand in 

North Dakota, FASOM estimated wheat 

production would shift to North Dakota 

region by about 218 million pounds, 

decreasing on net in all other regions by 

about 50 million pounds. 

Canola is generally crushed near areas 

of cultivation and a majority of U.S. 

facilities that process canola seed are 

located in North Dakota.43 Following 

this, as North Dakota canola production 

is estimated to expand to supply the 

canola shock, FASOM estimates the 

additional seed would be crushed into 

oil and meal in this region as well. This 

would expand regional supply of 

livestock feed and would decrease 

regional feed prices, relative to other 

regions of the U.S. FASOM estimates 

that this, in turn, would create 

incentives to shift livestock production 

to North Dakota and nearby states. Since 

livestock feed mixes require several 

different components, FASOM estimates 

this shift in livestock production 

towards North Dakota would also shift 

production of other feed crops (e.g., 

corn, soybeans, hay) into North Dakota. 

Production of these feed crops are 

estimated to increase by a total of 

115,000 acres in 2022. The modeled 

changes in North Dakota crop area are 

summarized in Table II.C.2.ii–5. 

FASOM estimates net cropland in North 

Dakota would increase by 218,300 

acres.44

TABLE II.C.2.ii–5—CHANGES IN NORTH

DAKOTA CROP AREA IN 2022 

[In thousand acres] 

Change from 

control case 

Canola ....................................... 16.3 (1.39%) 

Wheat ........................................ 86.8 (1.42%) 

All Else ...................................... 115.2 (1.38%) 

Total ................................... 218.3 (1.39%) 

Within North Dakota, FASOM 

estimates that most this additional 

cropland (212,000 acres) would be taken 

from Conservation Reserve Program 

(CRP) land and a smaller amount (7,000 

acres) would be taken from cropland 

pasture. However, as discussed later in 

this section, the nationwide net effect 

on land use from the shock would affect 

other land types as well. 

As crop area expands in North Dakota 

in response to the shock and livestock 

production shifts to this region, FASOM 

estimates total crop area would decrease 

in the rest of the U.S. FASOM estimates 

this dynamic would primarily shift 

production from Iowa and Kansas to 

North Dakota, suggesting a relatively 

modest northwesterly shift overall. On 

net, national crop area is estimated to 

expand by 60,600 acres in 2022. The 

modeled state-level changes in total 

harvested crop area are summarized in 

Table II.C.2.ii–6. 

TABLE II.C.2.ii–6—CHANGES IN REGIONAL HARVESTED CROP AREA IN

2022 

[In thousand acres] 

Change from 

control case 

North Dakota ............................. 218.3 (1.4%) 

Iowa ........................................... ¥82.7 (¥0.3%) 

Kansas ...................................... ¥60.5 (¥0.5%) 

All Other Regions ...................... ¥14.5 (¥0.01%) 

Total ....................................... 60.6 (0.02%) 

As FASOM estimates cropland would 

expand in North Dakota, the majority, 

about 212,000 acres, is estimated to shift 

into cropland status from land that is 

placed in CRP in the Control Case. The 


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45Note that cropland reported in national land 

area includes land that is planted but intentionally 

not harvested, e.g., crops grown for grazing. Land 

area totals will therefore differ slightly from the 

harvested crop area data discussed above. 

46See 82 FR 34656, July 26, 2017 for details on 

the version of FAPRI used to analyze emissions 

associated with sugar beets. 

47Further information about our assumptions and 

the modeling results are available in the document, 

‘‘FAPRI Outputs,’’ available in the docket for this 

action. 

48USDA, Foreign Agricultural Service. PSD Only 

Query tool. https://apps.fas.usda.gov/psdonline/ 

app/index.html#/app/advQuery. Last accessed 

March 16, 2022. 

49USDA, Foreign Agricultural Service. PSD Only 

Query tool. https://apps.fas.usda.gov/psdonline/ 

app/index.html#/app/advQuery. Last accessed 

March 16, 2022. 

50USDA, Foreign Agricultural Service. Oilseeds 

and Products Annual. March 31, 2021. Available at 

https://apps.fas.usda.gov/newgainapi/api/Report/ 

DownloadReportByFileName?fileName=

Oilseeds%20and%20Products%20Annual_

New%20Delhi_India_04-01-2021. Last accessed 

March 16, 2022. 

51USDA, Foreign Agricultural Service. PSD Only 

Query tool. https://apps.fas.usda.gov/psdonline/ 

app/index.html#/app/advQuery. Last accessed 

March 16, 2022. 

52Further information regarding these updated 

assumptions is detailed in the memorandum, 

‘‘TITLE,’’ available in the docket for this action. 

remaining area shifting into cropland 

status is estimated to shift from 

cropland pasture. As modeled crop 

production shifts on the margin out of 

Iowa and Kansas, FASOM estimates 

CRP area would increase in these 

regions to compensate for the decrease 

in North Dakota CRP area; nationwide 

CRP area does not change on net in our 

results. FASOM estimates pasture area 

would decrease nationwide as greater 

availability of livestock feed would 

slightly reduce demand for grazing. In 

some regions, FASOM estimates this 

previously grazed pastureland would be 

forested instead, leading to a modeled 

increase in forestland. The changes in 

total regional crop area are summarized 

in Table II.C.2.ii–7. 

TABLE II.C.2.ii–7—CHANGES IN

NATIONAL LAND AREA IN 2022 

[In thousand acres] 

Change from control case 

Cropland 45 ................................ 61 (0.02%) 

Cropland Pasture ...................... ¥57 (¥0.07%) 

Pasture ...................................... ¥36 (¥0.04%) 

Forest ........................................ 32 (0.01%) 

3. FAPRI Analysis 

Like the assessment of domestic 

impacts using the FASOM model 

described in Section II.C.2, EPA used 

FAPRI to estimate the GHG emissions 

associated with producing canola oil 

biofuel from international land use 

change and livestock. This is the same 

methodology EPA previously used to 

estimate these emissions sources for 

soybean oil-based biodiesel and other 

agricultural feedstocks (e.g., in the 

March 2010 RFS2 rule, but also in 

several subsequent pathway 

determinations). EPA updated several 

aspects of its analysis of the 

international GHG emissions associated 

with canola oil biofuel feedstock 

production this analysis, building on 

the FAPRI model used for EPA’s 

analysis of the GHG emissions 

attributable to the production and 

transport of sugar beets for use as a 

biofuel feedstock.46 In this section, we 

first review the updates made for this 

analysis. Following this, we present a 

summary of the FAPRI modeling 

results.47

i. Modifications to Model Inputs and 

Assumptions 

For this analysis, EPA updated FAPRI 

assumptions related to market 

conditions for canola seed, canola meal, 

and canola oil. This included 

assumptions about historical U.S. 

consumption, planted area, seed yields, 

and trade quantities. Updated 

assumptions for prices, planted area, 

and seed yields were primarily taken 

from NASS historical data sets. In some 

cases, these NASS data were 

supplemented with additional data 

taken from the USDA Oil Crop Yearbook 

and the USCA. In addition to updated 

canola yields in the U.S., USDA Foreign 

Agricultural Service (FAS) Production, 

Supply and Distribution (PSD) data 48

was used to update the FAPRI baseline 

trend of future yields in the EU, China, 

and Canada, regions where real-world 

yields had diverged most from previous 

FAPRI baseline assumptions. 

Additionally, three elasticities were 

adjusted to better align the projected 

international canola market conditions 

from FAPRI with recent historical data. 

Notably, the previous FAPRI baseline 

did not reflect the emergence of Canada 

as an important producer and exporter 

of canola and canola oil. Changes were 

made to align production and trade 

patterns in Canada, China, and the 

European (EU) using historical data for 

the 2009/2010–2021/2022 model 

periods obtained from the USDA PSD 

database. The first adjustment made was 

to increase the crush demand elasticity 

of canola in Canada from 0.22 to 0.4 to 

reflect Canada’s greater canola oil 

production and export relative to the 

previous FAPRI baseline. Increasing this 

elasticity estimate results in more 

canola crushed in Canada if the price 

increases. If Canada produces more 

canola oil, all else equal, Canadian 

exports would increase because of this 

assumption of increased elasticity. 

Second, we reduced the Chinese canola 

crush elasticity from 0.26 to 0.18 to 

reduce the higher-than-observed 

Chinese canola oil production and 

export in the FAPRI baseline relative to 

historical data.49 As a results of this 

change, Chinese canola crushing is less 

responsive to a change in the price of 

canola. If China crushes less canola, all 

else equal, Chinese canola exports 

would decrease. Last, the own-price 

demand elasticity for rapeseed oil in 

China was reduced from –0.25 to –0.15. 

This adjustment was made to further 

reduce the strong Chinese canola oil 

export position estimated by the 

previous FAPRI baseline. Making the 

Chinese own-price elasticity of demand 

for canola oil more inelastic has the 

effect of making Chinese domestic 

consumption of canola oil less 

responsive (‘‘stickier’’) to changes in 

price. 

EPA also updated the representation 

of canola and canola oil production in 

the India region to further align FAPRI 

with historical data. Indian trade of 

canola and canola oil are fixed in the 

FAPRI model at historical levels given 

very low levels of trade activity of these 

commodities historically.50 Similarly, 

the FAPRI modeling for this proposed 

rule does not allow for any changes in 

Indian canola or canola oil production 

in response to increased demand for 

canola oil-based biofuels. In 2020, 

global exports of canola oil were 14 

billion pounds. Of this total, India 

exported 11 million pounds, or 0.08 

percent. India does not export any 

canola seed.51 Therefore, we believe 

these adjustments are reasonable based 

on consideration of recent data and 

generally consistent with observed 

agricultural trade patterns.52

ii. Summary of Results 

To meet the 200 million gallons per 

year shock of canola oil biofuel, FAPRI 

estimates that the U.S. will import 100 

percent of the feedstock required to 

meet the canola oil biodiesel shock in 

2022. The FAPRI modeling results 

estimate that 48 percent of this canola 

oil feedstock would come from new 

production, with the remainder coming 

from shifts in other end uses. FAPRI 

estimates that global agricultural 

markets would provide the U.S. this 

feedstock in several ways. EU and 

Canadian net exports are estimated to 

increase by 750 and 278 million 

pounds, equivalent to 49 percent and 18 

percent of the increase in U.S. net 

imports respectively. China’s net 

imports of canola oil would be reduced 


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53The purpose of lifecycle assessment for RFS 

pathway assessments is not to precisely estimate 

lifecycle GHG emissions associated with particular 

biofuels, but instead to determine whether or not 

the fuels satisfy specified lifecycle GHG emissions 

thresholds to qualify as one or more of the four 

types of renewable fuel specified in the statute 

(March 26, 2010, 75 FR 14785). Where there are a 

range of possible outcomes and the fuel satisfies the 

GHG reduction requirements when ‘‘conservative’’ 

assumptions are used, then a more precise 

quantification of the matter is not required for 

purposes of a pathway determination. 

54As explained earlier in this section, we are not 

reopening the overall modeling framework or 

approach established in 2010 in this rulemaking. 

by 362 million pounds relative to the 

baseline, equivalent to 23 percent of the 

increase in U.S. net imports. The 

remaining increase in U.S. net imports 

are modeled to be supplied through 

increased net exports from other 

countries. 

FAPRI estimates that all of the canola 

oil to satisfy the shock would be 

supplied through increased net imports 

to the U.S. Since we use the FASOM 

results to estimate U.S. GHG emissions 

and the FAPRI results for non-U.S. GHG 

emissions, the effect of this discrepancy 

likely increases our GHG emissions 

estimates relative to a case where both 

models are perfectly aligned on the 

share of canola oil supplied through 

increased U.S. canola production. This 

is because we include the GHG 

emissions in the U.S. associated with 

producing 7 percent of the needed 

canola oil as estimated with FASOM 

and also the GHG emissions associated 

with producing 100 percent of the 

needed canola oil outside of the U.S. as 

estimated with FAPRI. For this reason, 

our estimates may be viewed as 

conservative (i.e., resulting in greater 

GHG emissions).53 In the March 2010 

RFS2 rule, we considered comments 

that questioned the benefit of using both 

FASOM and FAPRI given the 

inconsistencies in the results and 

decided that the benefits of FASOM’s 

more detailed representation of the U.S. 

agricultural and forestry sectors and 

associated GHG emissions outweighed 

the inevitable inconsistencies associated 

with using both models (75 FR 14768). 

We took steps in the March 2010 RFS2 

rule and in the analysis for this 

proposed rule to reconcile the two 

model results to the extent possible by 

applying the same set of scenarios and 

key input assumptions in both 

models.54 Overall, we believe the 7 

percent difference in sourcing of U.S. 

canola oil supplies provides a 

reasonably aligned and conservative 

estimate of the lifecycle GHG emissions 

associated with scenario modeled. 

FAPRI results show that canola seed 

production would increase by 1,743 

million pounds and canola oil 

production by 733 million pounds 

globally in 2022 in response to the 

shock. Table II.C.3.ii-1 illustrates the 

source and amounts of additional canola 

and canola oil production in 2022. 

TABLE II.C.3.ii–1—FAPRI 2022 CANOLA AND CANOLA OIL PRODUCTION RESPONSE BY REGION IN 2022 RELATIVE TO

CONTROL CASE

Canola Canola oil 

Acreage 

(thousand acres) 

Production 

(million pounds) 

Production 

(million pounds) 

Australia ..................................................................................................................... 60 70 4 

Canada ...................................................................................................................... 207 453 263 

China .......................................................................................................................... 285 536 173 

EU .............................................................................................................................. 223 629 234 

All Other ..................................................................................................................... 43 56 60 

Total .................................................................................................................... 819 1,743 733 

While FAPRI estimates that the EU 

will produce the most additional canola 

(629 million pounds), Canada is 

estimated to produce the most 

additional canola oil (263 million 

pounds). This is because, in addition to 

increasing of domestic production of 

canola seed, Canada is also estimated to 

reduce net exports of canola seed by 146 

million pounds, and to crush that 

additional amount of seed. 

The amount and composition of land 

use change associated with these canola 

expansions varies by region. While 

FAPRI estimates that China would 

experience the largest expansion of 

canola acres in 2022 (285,000 acres), 

there would be a relatively small 

amount of net cropland expansion 

(12,000 acres) as there would also be 

reductions in wheat and corn acres. 

Similarly, is the results show a net 

reduction of 12,000 acres of cropland in 

Canada as wheat, corn, and barley 

production would be reduced due to a 

change in relative prices stemming from 

the canola oil shock. In the EU, there 

would be a net expansion of cropland of 

103,000 acres, and in Brazil there would 

be an increase of 58,000 acres of 

cropland, led by corn and soybean 

expansion. FAPRI also estimates a 

reduction of 232,000 acres of pasture in 

Brazil, as the infusion of canola meal as 

a byproduct of additional canola 

crushing alleviates demand for grazing. 

In total, FAPRI estimates that cropland 

would expand by 372,000 acres outside 

of the U.S. in response to the shock. 

TABLE II.C.3.ii–2—NON-U.S. CHANGES IN AGRICULTURAL LAND BY REGION IN 2022 RELATIVE TO CONTROL CASE

[In thousand acres] 

Change in area 

harvested 

Change in pasture 

acres 55

Total change in 

acres 

EU .............................................................................................................................. 103 NR 103 

Brazil .......................................................................................................................... 58 ¥232 ¥175 

Rest of Non-USA ....................................................................................................... 211 NR 211 

Total Non-USA ................................................................................................... 372 ¥232 140 


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55NR stands for ‘‘not reported’’. Pasture acreage 

is only reported for Brazil in the FAPRI model. 

56Consistent with the methodology developed for 

the March 2010 RFS2 rule, for purposes of this 

lifecycle GHG analysis we use 100-year global 

warming potential (GWP) weighed emissions of 

carbon dioxide, methane, and nitrous oxide to 

calculated CO2e emissions. 

57EPA (2010). Renewable fuel standard program 

(RFS2) regulatory impact analysis. Washington, DC, 

US Environmental Protection Agency Office of 

Transportation Air Quality. EPA–420–R–10–006. 

58FAO, 2021. FAOSTAT Energy Use domain, 

FAO, Rome, Italy. Available at: http://www.fao.org/ 

faostat/en/#data/GN. Last accessed March 16, 2022. 

FAOSTAT Analytical Briefs can be found at: http:// 

www.fao.org/food-agriculture-statistics/datarelease/environment/en. Last accessed March 16, 

2022. 

4. Domestic Agricultural and Land Use 

Change GHG Emissions 

We used the results from the FASOM 

analysis to estimate domestic 

agricultural GHG emissions following 

the methodology developed for the 

March 2010 RFS2 rule. As noted above, 

for this proposed rule we used 

emissions factors from GREET–2020 for 

energy inputs and feedstock and coproduct transportation. Domestic 

agricultural GHG emissions include 

GHG emissions associated with changes 

in crop and livestock production. 

Overall, we estimate that increasing the 

consumption of hydrotreated canola oil 

biofuels in the U.S. would result in a net 

reduction in domestic agricultural GHG 

emissions of 40 grams of carbon 

dioxide-equivalent emissions (gCO2e) 

per pound of canola oil used as 

feedstock relative to scenario absent this 

hydrotreated canola oil biofuel 

production (‘‘gCO2e per pound of canola 

oil’’).56

The 40 gCO2e per pound of canola oil 

reduction in domestic agricultural GHG 

emissions has a handful of components. 

As discussed in Section II.C.2.ii, the 

FASOM results estimate a small shift 

away from corn production towards 

canola and wheat. This leads to a small 

net decline in farm input usage, 

resulting in a small estimated reduction 

in GHG emissions of about 1 gCO2e per 

pound of canola oil. The estimated net 

decrease in beef and chicken slaughter 

discussed in Section II.C.2.ii of this 

preamble is associated with a GHG 

emissions decrease of about 40 gCO2e 

per pound of canola oil. There is also a 

small increase in rice production in the 

U.S. (about 0.02 percent), leading to an 

increase of about 1 gCO2e per pound of 

canola oil from rice methane. As 

discussed above, our FASOM modeling 

results estimate that almost all the 

canola oil feedstock would be sourced 

outside of the U.S., and the relatively 

small effects on the domestic 

agricultural sector reflect this result. 

Domestic land use change GHG 

emissions are reported separately from 

domestic agricultural emissions. Based 

on the FASOM modeling discussed in 

Section IV.C.2 of this preamble, we 

estimate a net reduction in domestic 

land use change emissions of 77 gCO2e 

per pound of canola oil. It is based on 

the same methodology used for the 

March 2010 RFS rule whereby the land 

use change GHG emissions estimates 

from FASOM are considered over a 30- 

year period and then annualized (i.e., 

divided by 30 years). For a detailed 

description of how FASOM estimates 

land use change GHG emissions see 

Section 2.4.4.1 (‘‘Evaluation of Domestic 

Land Conversion GHG Emissions 

Impacts’’) of the Regulatory Impact 

Analysis for the March 2010 RFS2 

rule.57 FASOM estimates land 

conversions and associated changes in 

the biomass and soil carbon stocks. 

Given the many interactions simulated 

in FASOM it is difficult to summarize 

why domestic land use change GHG 

emissions are estimated to decline as a 

result of the modeled scenario. 

However, the reduction in emissions is 

consistent with the overall land use 

changes summarized in Table II.C.2.ii– 

7. Cropland area increases by 61 

thousand acres, which is usually 

associated with increased land use 

change GHG emissions, but this is offset 

by an increase of 32 thousand acres of 

forest area, which is associated with a 

net reduction in GHG emissions. 

5. International Agricultural and Land 

Use Change GHG Emissions 

We used the results from the FAPRI 

analysis to estimate international (i.e., 

non-U.S.) agricultural and land use 

change GHG emissions following the 

methodology developed for the March 

2010 RFS2 rule, except that, as 

described in this section, we updated 

our estimates of the GHG emissions 

associated with changes in international 

on-farm energy use. International 

agricultural sector GHG emissions are 

associated with estimated changes in 

crop and livestock production outside of 

the U.S. International land use change 

emissions are primarily changes in 

biomass and soil carbon associated with 

land use changes, but they also include 

non-CO2 emissions some cases (e.g., 

when land is cleared with fire). Overall, 

we estimate a small reduction of 5 

gCO2e per pound of canola oil 

associated with changes in international 

agriculture. 

The small reduction in GHG emission 

associated with international agriculture 

is the result of counterbalancing effects. 

We estimate that the modeled canola oil 

shock increases GHG emissions 

associated with international farm 

inputs (e.g., fertilizer, pesticide, energy) 

by 70 gCO2e per pound of canola oil. 

The canola shock is associated with 

changes in livestock production that 

reduce GHG emissions by 72 gCO2e per 

pound of canola oil. Changes in rice 

production results in a small decreased 

of 3 gCO2e per pound of canola oil. 

These changes largely balance each 

other out and result in an overall 

reduction in international agricultural 

emissions, not including land use 

change, of 5 gCO2e per pound of canola 

oil. These estimates are summarized 

along with the domestic estimates in 

Table II.C.8–1. The rest of this section 

describes our updates to estimate GHG 

emissions associated with changes in 

international on-farm energy use and 

then discusses the estimated 

international land use change GHG 

emissions. 

Based on our assessment of the 

information provided in the USCA 

petition, we updated the data sources 

used to estimate the changes in energy 

inputs and associated GHG emissions 

corresponding with changes in 

international crop production as 

estimated with the FAPRI model. The 

USCA petition stated, ‘‘For countries 

except Canada, EPA used International 

Energy Agency (IEA) data for energy use 

for the forest and agriculture sector and 

then divided that by the crop area. The 

energy use, based on this data, is 

overstated because it includes forestry 

energy use.’’ We confirmed that the IEA 

data used in our 2010 analysis to 

estimate changes in non-U.S. on-farm 

energy use included forestry energy use 

along with crop production energy use, 

and these data were then rolled into our 

estimates of energy use per acre of crop 

production for each region. We also 

found that the IEA data are aggregated 

so that forestry could not be excluded. 

We reviewed other available sources 

on energy use and found that the Food 

and Agriculture Organization of the 

United Nations (FAO) reports emissions 

data on the amount of energy used 

within the farm gate to operate 

machinery.58 The FAO also reports GHG 

emissions from aquaculture and fishing, 

but we exclude these data in order to 

exclusively estimate emissions from onfarm energy use energy use. The FAO 

data are available annually from 1970– 

2019 for over 200 countries. FAO 

reports emissions of carbon dioxide, 

methane, and nitrous oxide for seven 

different energy products (i.e., coal, 

electricity, fuel oil, gas-diesel oil, LPG, 

motor gasoline, and natural gas 

including LNG). After reviewing the 


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59For more information on these estimates see the 

memo to the docket titled, ‘‘Memo on Hydrotreated 

Canola Lifecycle GHG Calculation Workbooks.’’ 

60 ICAO (2021). CORSIA Eligible Fuels—Lifecycle 

Assessment Methodology. CORSIA Supporting 

Document. March 2021. Version 3. Table 43. Page 

65. 

61Natural Resources Canada. Last updated 

October 6, 2020. ‘‘Electricity Facts.’’ https://

www.cer-rec.gc.ca/en/data-analysis/energyContinued 

FAO farm energy use GHG emissions 

data, we believe they are an 

improvement compared to the IEA data 

used previously for the purposes of this 

analysis because they are more recent 

and exclude forestry energy use. For 

these reasons, we have updated our 

assumptions to use the FAO data for 

this analysis of canola oil renewable 

diesel. 

The FAO data report energy GHG 

emissions within the farm gate, 

including off-farm GHG emissions 

associated with generating electricity. 

Although the FAO estimates include offfarm GHG emissions associated with 

electricity generation, they exclude GHG 

emissions associated with producing the 

energy products and feedstocks for this 

electricity generation. For example, they 

exclude GHG emissions associated with 

natural gas production and distribution. 

In prior analyses, we adjusted the IEA 

estimates to include these upstream 

GHG emissions based on estimates from 

the GREET Model (version 1.8b) on the 

ratio of total lifecycle emissions to fuel 

use (or generation for electricity) 

emissions for each production. For this 

analysis of canola oil, we used the same 

approach but updated these ratios based 

on data from GREET–2020.59

The rest of this section discusses the 

international land use change GHG 

estimates. We estimate international 

land use change GHG emissions of 316 

gCO2e per pound of canola oil. We 

consider the uncertainty in the types of 

land converted and the emissions 

associated with those conversions and 

estimate a 95% confidence interval for 

international land use change emissions 

ranging from 131 to 529 gCO2e per 

pound of canola oil. 

International land use change GHG 

emissions were estimated following the 

methodology developed for the March 

2010 RFS2 rule. The FAPRI model 

estimates changes in harvested crop area 

by region as a result of the modeled 

canola oil biofuel scenarios. FAPRI also 

estimates changes in pasture area for 

five sub-regions of Brazil. For other 

regions, changes in pasture area are 

estimated based on FAPRI’s estimated 

changes in livestock production and 

FAO data on stocking rates (i.e., grazing 

animals per acre of pasture). In regions 

where the sum of changes in cropland 

or pasture are non-zero, we estimate 

changes in the areas of other land types 

based on land use change patterns in 

each region as estimated with satellite 

data. The estimated land use changes 

are then converted to GHG emissions 

based on land use change emissions 

factors estimated from a number of data 

sources following IPCC guidelines. 

International land use changes are 

estimated over 30 years and then 

annualized (i.e., divided by 30 years). 

For details on this methodology see 

Section 2.4.4.2 (‘‘International Land 

Conversion GHG Emissions Impacts’’) of 

the Regulatory Impact Analysis for the 

March 2010 RFS2 rule. 

Following the approach developed for 

the March 2010 RFS2 rule, we consider 

the uncertainty in the international land 

use change GHG estimates to produce a 

95% confidence interval. This 

uncertainty analysis considers two 

major components: (1) Uncertainty in 

the classification of land transitions 

with satellite data to determine the 

types of land affected by changes in 

cropland and pasture area in each 

region, and (2) uncertainty in the 

emissions factors used to translate the 

land conversions to GHG emissions. For 

more information about our evaluation 

of the uncertainty in international land 

use change GHG emissions see Section 

2.4.4.2.8 (‘‘Uncertainty Assessment for 

International Land Conversion GHG 

Emissions Impacts’’) of the RIA for the 

March 2010 RFS2 rule. 

We recognize that there are other 

uncertainties that could theoretically be 

estimated, for example uncertainties in 

the areas of cropland estimated by the 

FAPRI model. However, quantifying 

additional sources of uncertainty was 

not part of the modeling framework or 

methodology developed for the March 

2010 RFS2 rule, and would require the 

development of new methodologies and 

modeling approaches. Running multiple 

scenarios with the FAPRI model in 

order to systematically quantify 

parameter uncertainty would take a very 

long time and be impractical for this 

rule. As discussed in Section III., we 

consider the weight of available 

evidence when proposing RIN D-code 

eligibility for the evaluated pathways. In 

weighing the available evidence, we put 

the most weight on the quantified range 

of lifecycle GHG estimates but also 

recognize qualitatively that there are 

unquantified sources of uncertainty. 

6. Feedstock Processing 

After the canola seeds are harvested, 

they are transported to a crushing 

facility to separate the canola oil and 

meal. The most common process uses 

the solvent hexane. The canola seeds are 

first cleaned, heated, and flaked. The 

seeds are then cooked and screwpressed to remove most of the oil. To 

remove the remaining oil, the meal is 

saturated with hexane solvent, which is 

removed and then recycled back into 

the process. The oil is further refined to 

remove free fatty acids and other 

impurities. 

We estimate canola crushing GHG 

emissions following the methodology 

developed for the March 2010 RFS2 

rule. We estimate the total GHG 

emissions associated with canola 

crushing with no allocation to the 

canola meal co-product that is primarily 

used as livestock feed. The effects of 

using canola meal as feed are 

considered in the FASOM and FAPRI 

modeling described above. In lifecycle 

analysis terminology, this would be 

described as a system expansion 

approach as opposed to allocating 

emissions to the meal. 

The USCA petition included annual 

canola crushing input-output data from 

Canada that we used in our analysis. We 

believe these data are appropriate for 

our analysis because a large share of 

canola oil feedstock for the U.S. is likely 

to be sourced in Canada, and the 

Canadian extraction process is 

representative of extraction processes in 

other regions that are likely to crush 

canola to supply canola oil biofuel 

feedstock to the U.S. For example, data 

compiled by the United Nations 

International Civil Aviation 

Organization (ICAO) for canola crushing 

in Canada, Europe and the U.S. shows 

similar but smaller amounts of natural 

gas and electricity use per pound of 

canola oil extracted. 60 The USCA data 

reports average energy use of 1,310 Btu 

of per pound of canola oil extracted in 

Canada. For comparison the ICAO 

reports energy use of 790 to 1,220 Btu 

per pound of canola oil extracted. Based 

on this comparison, we believe that 

using the USCA data for canola crushing 

energy use is reasonable and somewhat 

conservative. 

Based on the USCA crushing data, we 

assume approximately 40 percent yield 

of canola oil per seed on a mass basis, 

and that natural gas and electricity are 

used for heat and power. We estimated 

the GHG emissions associated with the 

natural gas based on GREET–2020 

estimates for average North American 

natural gas production and use. For 

electricity, we used the GREET–2020 

emissions factor for average Canadian 

electricity. GREET includes 2012 data 

for the Canadian grid mix, which we 

updated based on 2018 data from 

Natural Resources Canada.61 Based on 


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markets/provincial-territorial-energy-profiles/ 

provincial-territorial-energy-profiles-canada.html#

:∼:text=More%20than%20half%20of%20the,and %20petroleum%20(Figure%202). Last Accessed 

March 16, 2022. 

these assumptions, we estimate GHG 

emissions from canola oil extraction of 

87 gCO2e per pound of canola oil. 

Recognizing that canola may be 

crushed in other regions, we considered 

the effects of canola crushing in the 

U.S., Europe and China to determine if 

crushing in other regions would affect 

our proposed determination that 

hydrotreated canola oil meets the 50% 

GHG reduction threshold. To evaluate 

this question, we used the same 

crushing input-output data from the 

USCA petition and considered regional 

differences in grid average electricity 

GHG emissions factors and GHG 

emissions associated with additional 

canola oil shipping. Although the U.S. 

grid is more GHG intensive than the 

Canadian grid, the effect of crushing in 

the U.S. compared to Canada is less 

than one gram CO2e per pound canola 

oil and we assume there would be no 

significant change in GHG emissions 

associated with canola oil transport. The 

average European grid is less GHG 

intensive than the Canadian grid but the 

effect on crushing in Europe compared 

to Canada is also less than on gram CO2e 

per pound of canola oil. If we consider 

canola oil shipping from Europe of 

4,000 nautical miles (e.g., Rotterdam to 

Houston) via ocean tanker fueled with 

bunker fuel, that adds approximately 13 

gCO2e per pound of canola oil, 

equivalent to approximately a one 

percent increase in GHG emissions 

relative to the petroleum baseline. 

Crushing in China and shipping 5,500 

nautical miles (e.g., Beijing to Los 

Angeles) would add approximately 18 

gCO2e per pound of canola oil, which is 

still equivalent to approximately a one 

percent increase in GHG emissions 

relative to the baseline. As an extremely 

conservative scenario, if we assume 

crushing in China with coal instead of 

natural gas for process energy and 5,500 

nautical miles of shipping, this adds 

approximately 139 gCO2e per pound of 

canola oil, or approximately 9% relative 

to the petroleum baseline. Even with 

these extremely conservative 

assumptions, renewable diesel and jet 

fuel still satisfy the 50% GHG reduction 

threshold when we use our mean 

estimate of international land use 

change GHG emissions (i.e., 55% to 

61% reduction for renewable diesel and 

51% to 59% reduction for renewable jet 

fuel). Overall, this shows that our 

proposed determinations are not 

sensitive to our assumption about where 

canola is crushed, and we believe that 

assuming canola crushing occurs in 

Canada is a reasonable approach for this 

analysis. 

7. Feedstock Transport 

There are three stages of feedstock 

transport considered in our lifecycle 

analysis. The transportation modes and 

distances for canola seed and oil in our 

analysis are from the GREET–2020 

model. First canola seeds are assumed 

to be transported 10 miles from the farm 

field to a collection point by mediumduty truck. The model then assumes 

seeds are then transported 40 miles to 

the crushing facility by heavy duty 

truck. After crushing, the oil is 

transported 80 miles by tanker truck to 

a hydrotreating facility. The trucks in 

this transportation chain are assumed to 

consume diesel fuel and we estimated 

the associated GHG emissions based on 

the GREET–2020 emissions factor for 

conventional diesel. Overall, we 

estimate GHG emissions of 15 gCO2e per 

pound of canola oil for seed transport 

and 13 gCO2e per pound of canola oil 

for canola oil transport. As discussed in 

Section IV.C.7, importing canola oil 

from Europe or China would increase 

oil shipping emissions but not to a large 

enough extent to change our proposed 

determinations that biofuels produced 

from hydrotreated canola oil meet the 

50 percent GHG reduction requirement. 

8. Summary of Upstream GHG 

Emissions 

Based on all of the modeled effects 

discussed above associated with 

producing canola oil feedstock 

including effects on domestic and 

international crop production, livestock 

production and land use, we can 

summarize the estimated lifecycle GHG 

emissions per pound of canola oil 

delivered to a hydrotreating production 

facility. These upstream GHG emissions 

(i.e., upstream of feedstock conversion 

to fuel) are summarized in Table II.C.8– 

1. A range of GHG emissions is 

presented based on our evaluation of the 

uncertainty associated with 

international land use change GHG 

emissions, as discussed in Section 

IV.C.5 of this preamble. 

TABLE II.C.8–1—ESTIMATED UPSTREAM GHG EMISSIONS ASSOCIATED WITH PRODUCING CANOLA OIL USED FOR

BIOFUEL PRODUCTION

[In grams of CO2-equivalent per pound canola oil] 

Emissions category Estimate 

Domestic farm inputs ................................................................................................................... ¥1 

Domestic Livestock ...................................................................................................................... ¥40 

Domestic Rice Methane .............................................................................................................. 1 

Domestic Land Use Change ....................................................................................................... ¥77 

International Farm Inputs ............................................................................................................. 70 

International Livestock ................................................................................................................. ¥72 

International Rice Methane .......................................................................................................... ¥3 

Seed transport ............................................................................................................................. 15 

Crushing ....................................................................................................................................... 87 

Oil Transport ................................................................................................................................ 13 

International Land Use Change Estimate ................................................................................... Mean Low High 

International Land Use Change ................................................................................................... 316 131 529 

Total ...................................................................................................................................... 305 118 517 

Note: The ‘‘Low’’ international land use change estimate represents the low-end of the 95% confidence interval and the ‘‘High’’ estimate represents the high-end of the 95% confidence interval. 


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62U.S. Energy Information Administration. 

(2021). ‘‘U.S. renewable diesel capacity could 

increase due to announced and developing 

projects.’’ July 29, 2021; U.S. Energy Information 

Administration. (2018). ‘‘Renewable diesel is 

increasingly used to meet California’s Low Carbon 

Fuel Standard.’’ November 13, 2021. 

63Wang, W.C., Tao, L., Markham, J., Zhang, Y., 

Tan, E., Batan, L., Warner, E., & Biddy, M. (2016). 

Review of Biojet Fuel Conversion Technologies. 

Report prepared by National Renewable Energy 

Laboratory. 

64Pearlson, M., et al. (2013). ‘‘A techno-economic 

review of hydroprocessed renewable esters and 

fatty acids for jet fuel production.’’ Biofuels, 

Bioproducts and Biorefining 7(1): 89–96. 65EPA. (2013). ‘‘Diamond Green Diesel Request 

for Fuel Pathway Determination under the RFS 

Program.’’ Office of Transportation and Air Quality. 

October 28, 2013. https://www.epa.gov/renewablefuel-standard-program/diamond-green-diesel-llcapproval. Last Accessed March 16, 2022. 

66EPA (2017). ‘‘Evaluation of Renewable Energy 

Group, Inc. Request for Fuel Pathway 

Determination under the RFS Program’’ April 13, 

2017. https://www.epa.gov/renewable-fuelstandard-program/reg-geismar-approval. Last 

Accessed March 16, 2022. EPA (2018). ‘‘Renewable 

Energy Group, Inc. Fuel Pathway Determination 

under the RFS Program’’ February 23, 2018. https:// 

www.epa.gov/renewable-fuel-standard-program/ 

reg-geismar-approval-0. Last Accessed March 16, 

2022. 

67EPA. (2021). ‘‘Koole-Neste Fuel Pathway 

Determination under the RFS Program.’’ Office of 

Transportation and Air Quality. July 12, 2021. 

https://www.epa.gov/system/files/documents/2021- 

08/koole-neste-deter-ltr-2021-07-12.pdf. Last 

Accessed March 16, 2022. 

68Wang et al. 2021. ‘‘Summary of Expansions and 

Updates in GREET 2021.’’ October 2021. ANL/ESD– 

21/16. 

9. Fuel Production 

Canola oil is converted to renewable 

diesel, jet fuel, naphtha, and LPG 

through a hydrotreating process, also 

sometimes referred to as 

hydroprocessing. The renewable diesel 

may also be used as heating oil, 

although this is unlikely based on recent 

market conditions such as strong 

demand for renewable diesel to satisfy 

low carbon fuel standards in California, 

Oregon and Washington.62 The process 

consists of catalytic reactions in the 

presence of hydrogen. The steps in a 

typical hydrotreating process often 

include a combination of 

hydrogenation, hydro-deoxygenation, 

decarboxylation and decarbonylation. 

The primary output of hydrotreating is 

renewable diesel, with estimates ranging 

from approximately 75 to 100 percent of 

the output based on the data sources 

discussed later in this proposal. Other 

outputs include jet fuel, naphtha, LPG, 

and propane. Hydrotreating facilities 

can process a wide range of vegetable oil 

feedstocks without significant 

operational changes. 

The hydrotreating process can be 

configured to maximize renewable jet 

fuel output instead of renewable diesel, 

but this requires additional hydrogen 

and other energy inputs. To maximize 

jet fuel output, the renewable diesel is 

subjected to additional refining, namely 

hydro-isomerization and hydrocracking. 

These processes involve the addition of 

more hydrogen to crack the longer 

carbon chain length diesel to shorter 

length jet fuel. Essentially, the diesel is 

cracked to produce jet fuel and naphtha. 

Overall, maximizing hydrotreating 

processes for jet fuel output results in 

higher production costs and GHG 

emissions per gallon relative to 

processes that are maximized for diesel 

output.63 As described later in this 

proposal, these effects are considered in 

our analysis. 

Several hydrotreating pathways have 

been evaluated and approved under the 

RFS program. In the March 2010 RFS2 

rule, we approved multiple pathways 

for renewable diesel produced from 

hydrotreated vegetable oils and biogenic 

waste fats, oils, and greases (FOG) as 

meeting the 50 percent GHG reduction 

requirement to qualify as biomass-based 

diesel and advanced biofuel. In the 2013 

Pathways I rule (78 FR 14190), we 

evaluated renewable diesel from 

camelina oil and reported the GHG 

emissions associated with the 

hydrotreating process used to convert 

the camelina oil to renewable diesel. 

That analysis relied on data published 

in Pearlson et al. (2013), a study that 

modeled the emissions and fuel 

production costs associated with of a 

commercial scale hydrotreating 

process.64 We also used the Pearlson et 

al. (2013) data in our analysis of 

hydrotreating for the 2018 distillers 

sorghum oil rule (83 FR 37735). 

In addition to evaluating generally 

applicable hydrotreating pathways, we 

have approved several facility-specific 

pathways for hydrotreating facilities. 

For the facility-specific analyses, we 

relied on data from the individual 

facilities, submitted under claims of CBI 

on their energy use and fuel yields. In 

October 2013, we approved a facilityspecific petition for renewable LPG and 

naphtha co-products produced from 

distillers’ corn oil at Diamond Green 

Diesel’s hydrotreating facility in 

Louisiana.65 In 2017 and 2018, we also 

approved pathways for LPG and 

naphtha produced from distillers’ corn 

oil and waste FOG at Renewable Energy 

Group’s hydrotreating facility in 

Louisiana.66 In July 2021, we approved 

a facility specific pathway for jointly 

filed petition from Koole and Neste for 

renewable diesel and jet fuel produced 

from waste FOG.67 We have also 

received additional facility-specific 

petitions for hydrotreating processes 

that are currently under review. In total, 

we have received hydrotreating data, 

claimed as CBI, from five different 

facilities through the petition process 

for new RFS pathways at 40 CFR 

80.1416. 

We estimated hydrotreating GHG 

emissions based on 12 sources of 

vegetable oil hydrotreating input-output 

data. Eight of the modeled processes 

primarily produce renewable diesel 

with co-products, varying by process, of 

naphtha, LPG, and jet fuel. Four of the 

modeled processes are configured to 

maximize jet fuel output with coproducts, varying by process, of 

renewable diesel, naphtha, and LPG. 

The eight data sources for 

hydrotreating processes that primarily 

produce renewable diesel include 

Pearlson et al. (2013), GREET–2021, 

aggregated data provided by the 

California Air Resources Board (CARB), 

and five facilities that submitted data 

under claims of CBI pursuant to the 

petition process. As mentioned above, 

Pearlson et al. (2013) is a peer-reviewed 

study that modeled a commercial scale 

hydrotreating process. The renewable 

diesel production data have been 

updated in the GREET–2021 model with 

operational data from 2018 and 2019 

from a survey of domestic renewable 

diesel producers conducted by Argonne 

National Laboratory and the National 

Biodiesel Board.68 The CARB provided 

data are the average inputs and outputs 

associated with the hydrotreating 

processes used to produce renewable 

diesel for use under the California Low 

Carbon Fuel Standard Program, as of 

June 2021. The data for five 

hydrotreating facilities submitted 

through new pathway petitions and 

claimed as CBI were submitted between 

2018 and 2020. 

The four data sources used to model 

hydrotreating processes configured to 

maximize jet fuel output are Pearlson et 

al. (2013), GREET–2021 and two from 

an analysis published by the 

International Civil Aviation 

Organization (ICAO) in 2021. The first 

data source is the ‘‘maximum jet fuel’’ 

scenario from Pearlson et al. (2013). The 

data in GREET–2021 for renewable jet 

fuel production through hydrotreating is 

unchanged from previous versions of 

GREET. We also evaluated two 

scenarios from ICAO (2021): One that is 

representative of U.S. hydrotreating and 

one that is representative of European 

hydrotreating. 

To estimate the GHG emissions 

associated with these hydrotreating 

processes, we used energy allocation to 

account for the fuel coproducts from the 

hydrotreating process. We estimated the 

total GHG emissions from the 


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69As discussed above, although we have 

evaluated the updated hydrotreating data from the 

GREET–2021 model, the rest of our analysis had 

already been conducted using emissions factors 

from the GREET–2020 model. We will update these 

emissions factors for the final rule, but we do not 

expect this to have a large enough impact on our 

estimates to affect the pathway approvals proposed 

in this rule. 

70See for example the March 2013 Pathways I 

rule (78 FR 14190) and the August 2018 sorghum 

oil rule (83 FR 37735). 

71U.S. Department of Energy. ‘‘The Hydrogen 

Analysis (H2A) Project.’’ https://

www.hydrogen.energy.gov/h2a_analysis.html. Last 

accessed March 16, 2022. 

hydrotreating process and allocated 

them to the renewable diesel, jet fuel, 

naphtha, LPG, and propane co-products 

on an energy basis. The propane is 

treated as a co-product in these 

calculations but is unlike the other coproducts because we do not expect it to 

be exported from the facility. For data 

sources that reported propane as an 

output, we assume that this propane is 

used at the facility as process fuel, and 

that this propane use is reflected in the 

input data reducing the amount of 

purchased natural gas. As a result of this 

energy allocation approach, all the coproducts are assigned equivalent 

emissions from the fuel production 

stage on a gCO2e per MJ basis. To 

translate energy use into GHG 

emissions, we used emissions factors for 

natural gas, electricity, and hydrogen 

from the GREET–2020 model 

representing the GHG emissions 

associated with the supply of these 

energy inputs in the U.S.69

In previous GHG analyses of 

hydrotreating processes, we assumed 

that some of the co-products (propane 

and in some cases LPG and naphtha) 

would not be used as RIN-generating 

fuels, and we included GHG reductions 

associated with these renewable coproducts displacing the use of 

equivalent conventional fuels.70 In 

contrast, the analysis for this proposed 

rule does not include GHG reductions 

associated with hydrotreating coproducts displacing other fuels. Instead, 

we use energy allocation for all the coproducts. We are taking this approach 

for four reasons. One, the USCA petition 

requests RIN eligibility for all of the coproducts except propane, so propane is 

the only co-product for which a 

displacement approach would be 

considered. Second, we believe that 

using energy allocation for all of the coproducts, including propane, provides a 

reasonably conservative estimate (i.e., 

tends to result in higher GHG estimates). 

Third, using energy allocation for coproducts the estimates do not depend 

on which co-products generate RINs, 

which is subject to change based on 

market and regulatory conditions. 

Fourth, we also note that the energy 

allocation approach results in GHG 

estimates that are more consistent across 

facilities compared to the displacement 

approach due to the variation in coproduct outputs across facilities. As an 

illustrative example of how much this 

assumption influences the estimates, if 

we assumed the propane co-product 

displaces natural gas the fuel 

production emissions for renewable 

diesel would decrease by an average of 

2.1 gCO2e per MJ, and up to 5.9 gCO2e 

per MJ, relative to the estimates in Table 

II.C.9–1 that are based on energy 

allocation for propane. For renewable jet 

fuel, the same displacement approach 

for propane co-product would reduce 

fuel production emissions by an average 

of 3 gCO2e per MJ, and up to 4.7 gCO2e 

per MJ, relative to the estimates in Table 

II.C.9–2 that are based on energy 

allocation for propane. We request 

comment on the use of energy allocation 

to evaluate co-products from 

hydrotreating processes. 

Hydrogen is major energy input to 

hydrotreating processes. We used the 

GREET–2020 emissions factor 

representing hydrogen produced from 

natural gas through a stream methane 

reforming process at central plants. 

Central plants are large hydrogen 

production facilities that produce 

greater than 50,000 kilograms of 

hydrogen per day.71 This is a 

conservative choice as GREET has lower 

GHG estimates for other sources of 

hydrogen. We believe this choice is 

reasonable and appropriate for this 

analysis as the proposed pathway would 

be available to renewable diesel plants 

irrespective of their hydrogen sources. 

The estimated lifecycle GHG 

emissions associated with hydrotreating 

processes that primarily produce 

renewable diesel are summarized in 

Table II.C.9–1. As shown in the table, 

the highest and lowest estimates are 

based on data from two of the facilityspecific petitions. The estimates based 

on data from Pearlson et al. (2013), 

GREET–2021 and CARB are within 1.2 

gCO2e/MJ of each other and between the 

estimates for individual facilities. 

TABLE II.C.9–1—GHG EMISSIONS ASSOCIATED WITH RENEWABLE DIESEL

PRODUCTION VIA HYDROTREATING

[In grams of CO2 equivalent per MJ] 

Hydrotreating data source Estimate 

Pearlson et al. (2013) ................. 10.8 

GREET–2021 ............................. 11.8 

CARB (2021) .............................. 12.0 

Facility 1 ..................................... 15.0 

Facility 2 ..................................... 10.4 

TABLE II.C.9–1—GHG EMISSIONS ASSOCIATED WITH RENEWABLE DIESEL

PRODUCTION VIA HYDROTREATING— 

Continued 

[In grams of CO2 equivalent per MJ] 

Hydrotreating data source Estimate 

Facility 3 ..................................... 13.7 

Facility 4 ..................................... 10.9 

Facility 5 ..................................... 14.4 

Range ......................................... 10.4–15.0 

The estimated lifecycle GHG 

emissions associated with hydrotreating 

processes configured to maximize jet 

fuel output are summarized in Table 

II.C.9–2. The estimate based on GREET– 

2021 is significantly greater than the 

other sources because it includes greater 

natural gas and hydrogen use per unit 

of jet fuel output. 

TABLE II.C.9–2—GHG EMISSIONS ASSOCIATED WITH RENEWABLE JET

FUEL PRODUCTION VIA

HYDROTREATING

[In grams of CO2 equivalent per MJ] 

Hydrotreating data source Estimate 

Pearlson et al. (2013) Maximized 

Jet ........................................... 12.9 

ICAO (2021) EU Jet ................... 14.7 

ICAO (2021) U.S. Jet ................. 12.7 

GREET–2021 Jet ....................... 20.7 

Range ......................................... 12.7–20.7 

Based on the analysis and data 

sources discussed above, we estimate 

the GHG emissions associated with the 

hydrotreating stage range from 10.4 to 

15.0 gCO2e/MJ for renewable diesel and 

12.7 to 20.7 gCO2e/MJ for jet fuel. As 

discussed in Section III, we consider the 

full range of hydrotreating GHG 

estimates in this proposal to approve 

these canola oil-based biofuel pathways. 

10. Fuel Distribution 

We estimated the GHG emissions 

associated with transporting the 

renewable diesel, jet fuel, naphtha, and 

LPG products to end users based on 

transportation and distribution data in 

GREET–2020. The renewable diesel and 

jet fuel are assumed to be transported by 

truck, rail, and barge. The naphtha and 

LPG are assumed to be transported 

primarily by pipeline and rail. The fuel 

distribution GHG estimates are 0.4 

gCO2e/MJ for renewable diesel and jet 

fuel and 0.6 gCO2e/MJ for renewable 

naphtha and LPG. 

11. Fuel Use 

For this analysis, we applied non-CO2

fuel use GHG emissions factors from 


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72Following the methodology developed for the 

March 2010 RFS2 rule after notice, public 

comment, and peer review, the carbon in the 

finished fuel derived from renewable biomass is 

treated as biologically derived carbon originating 

from the atmosphere. In the context of a full 

lifecycle analysis, the uptake of this carbon from the 

atmosphere by the renewable biomass and the CO2

emissions from combusting it cancel each other out. 

Therefore, instead of presenting both the carbon 

uptake and tailpipe CO2 emissions, we leave both 

out of the results. Note that our analysis also 

accounts for all significant indirect emissions, such 

as from land use changes, meaning we do not 

simply assume that biofuels are ‘‘carbon neutral.’’ 

GREET–2020.72 For renewable diesel, 

we used the factors for renewable diesel 

used in a compression ignition direct 

injection vehicle. For renewable jet fuel, 

we used the factors for hydrotreated 

renewable jet fuel consumed in a single 

aisle passenger aircraft. For renewable 

naphtha, we used the factors for 

renewable gasoline consumed in a 

spark-ignition vehicle and for LPG we 

used factors for a dedicated LPG 

vehicle. The fuel use GHG estimates are 

0.9 gCO2e/MJ for renewable diesel, 0.1 

gCO2e/MJ for renewable jet fuel, and 0.5 

gCO2e/MJ for renewable naphtha and 

LPG. 

12. Results of GHG Lifecycle Analysis 

Table II.C.12–1 reports our estimates 

of the lifecycle GHG emissions 

associated with renewable diesel 

produced from canola oil through a 

hydrotreating process, and the 

corresponding percent reduction 

relative to the petroleum baseline. Three 

sets of estimates are presented for 

canola oil renewable diesel. The 

emissions categories are aggregated to 

simplify the presentation of the table. 

Domestic and international agricultural 

emissions include emissions associated 

with changes in crop and livestock 

production. Feedstock processing (i.e., 

canola seed crushing) and feedstock 

seed and oil transport emissions are 

reported together. Downstream and use 

includes emissions from fuel 

distribution and fuel use. Land use 

change emissions include emissions 

from domestic and international land 

use changes. 

Our evaluation considers uncertainty 

in international land use change 

emissions based on the methodology 

used for the March 2010 RFS2 rule. The 

table includes a range of land use 

change estimates based on our analysis 

of this uncertainty. The first column 

includes results based on our average 

estimate of international land use 

change GHG emissions. We also report 

results for the low and high ends of our 

95 percent confidence interval for 

international land use change 

emissions. Ranges for domestic 

agriculture, international agriculture, 

feedstock transport and crushing, and 

fuel production are based on estimated 

ranges in the yield of finished fuel (in 

MJ of fuel produced per pound of canola 

oil feedstock). 

TABLE II.C.12–1—LIFECYCLE GHG EMISSIONS ASSOCIATED WITH RENEWABLE DIESEL PRODUCED FROM CANOLA OIL

THROUGH A HYDROTREATING PROCESS

[In grams of CO2 equivalent per MJ] 

Emissions category 2005 Diesel 

baseline 

Canola oil renewable diesel 

Domestic Agriculture ........................................................................................ 18 ¥2.5 to ¥2.2 

International Agriculture ................................................................................... ¥0.33 to ¥0.28 

Feedstock Transport & Crushing ..................................................................... 6.2 to 7.3 

Fuel Production ................................................................................................ 10.4 to 15.0 

Downstream & Use .......................................................................................... 75 1.3 

Land Use Change Estimate ............................................................................ ........................ Mean Low High 

Land Use Change ............................................................................................ ........................ 13.0 to 15.2 3.0 to 3.5 24.6 to 28.7 

Net Emissions .................................................................................................. 93 28.9 to 34 18.6 to 23.4 40.7 to 46.4 

% GHG Reduction Relative to Baseline .......................................................... ........................ 63% to 69% 75% to 80% 50% to 56% 

In many cases, when vegetable oils 

are hydrotreated to produce renewable 

diesel, there are co-product outputs of 

naphtha, LPG, and jet fuel. The GHG 

estimates for these co-product fuels 

differ slightly from the renewable diesel 

estimates presented in the table above 

based on differences in how they are 

transported to end users and end use 

emissions. The results for naphtha and 

LPG, based on the mean international 

land use change estimates, are 

summarized in Table II.C.12–2. 

TABLE II.C.12–2—LIFECYCLE GHG EMISSIONS ASSOCIATED WITH NAPHTHA AND LPG PRODUCED FROM CANOLA OIL

THROUGH A HYDROTREATING PROCESS

[In grams of CO2 equivalent per MJ] 

Naphtha LPG 

Lifecycle GHG Emissions ........................................................................................................................................ 28.7 to 33.9 28.7 to 33.9 

Percent Reduction Relative to Baseline .................................................................................................................. 64% to 69% 63% to 69% 

We do not present separate results of 

heating oil as it is not reported as an 

output for any of the hydrotreating 

processes evaluated. However, 

renewable diesel could be used as 

heating oil if market conditions change 

substantially. The GHG emissions 

associated with heating oil are therefore 

very similar to renewable diesel, 

although there may be small differences 

in GHG emissions associated with fuel 

distribution and use. 

As discussed above, canola oil 

hydrotreating processes that are set up 

to maximize jet fuel output require more 

processing and hydrogen, resulting in 

greater lifecycle GHG emissions. For 

example, our lifecycle GHG estimates 


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using hydrotreating input-output data 

from GREET–2021 are 31.0 gCO2e/MJ 

for renewable diesel and 38.2 gCO2e/MJ 

for renewable jet fuel, and our estimates 

based on hydrotreating data from 

Pearlson et al. (2013) are 29.5 gCO2e/MJ 

for renewable diesel and 30.5 gCO2e/MJ 

for renewable jet fuel. The range of 

lifecycle GHG estimates for canola oil 

renewable jet fuel are reported in Table 

II.C.12–3. 

TABLE II.C.12–3—LIFECYCLE GHG EMISSIONS ASSOCIATED WITH RENEWABLE JET FUEL PRODUCED FROM CANOLA OIL

THROUGH A HYDROTREATING PROCESS

[In grams of CO2 equivalent per MJ] 

Emissions category 2005 Diesel 

baseline 

Canola oil renewable jet fuel 

Domestic Agriculture ........................................................................................ 18 ¥2.4 to ¥2.2 

International Agriculture ................................................................................... ¥0.31 to ¥0.28 

Feedstock Transport & Crushing ..................................................................... 6.3 to 7.0 

Fuel Production ................................................................................................ 12.7 to 20.7 

Downstream & Use .......................................................................................... 75 0.5 

Land Use Change Estimate ............................................................................ ........................ Mean Low High 

Land Use Change (LUC) ................................................................................. ........................ 13.2 to 14.5 3.0 to 3.3 24.9 to 27.5 

Net Emissions .................................................................................................. 93 30.5 to 38.2 20.2 to 28 42.2 to 49.9 

% GHG Reduction Relative to Baseline .......................................................... ........................ 59% to 67% 70% to 78% 46% to 54% 

III. Consideration of Lifecycle Analysis 

Results 

We evaluated the lifecycle GHG 

emission associated with renewable 

diesel, jet fuel, naphtha and LPG 

produced from canola oil through a 

hydrotreating process. The purpose of 

this analysis was to determine whether 

these fuel pathways satisfy the statutory 

50 percent GHG reduction threshold 

under the RFS program for advanced 

biofuel and biomass-based diesel. Our 

approach to considering the lifecycle 

GHG estimates for purposes of threshold 

determinations is consistent with the 

‘‘weight of evidence’’ approach that we 

used for the March 2010 RFS2 rule. In 

the preamble to the March 2010 RFS2 

rule we said, ‘‘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.’’ 75 FR 

14785. In this section we consider the 

weight of the evidence and propose to 

make threshold determinations on this 

basis. 

Based on the range of lifecycle GHG 

emissions estimates presented above, 

the weight of available evidence, and 

our technical judgments, we propose to 

find that all the pathways evaluated 

would meet the 50 percent GHG 

reduction threshold required for 

advanced biofuel and biomass-based 

diesel. Our evaluation considers 

variability in hydrotreating processes 

and uncertainty in land use change 

emissions. 

When we consider the mean land use 

change GHG estimates, the entire range 

of GHG reduction results exceeds the 50 

percent GHG reduction requirement for 

all of the pathways evaluated. When we 

consider the high-end of the 95-percent 

confidence interval for international 

land use change GHG emissions and the 

hydrotreating process data with the 

highest GHG emissions, all the 

pathways evaluated except for jet fuel 

still exceed the 50 percent GHG 

reduction threshold. Thus, based on the 

range of estimated GHG reduction 

results and the weight of available 

evidence, we judge that there is a 

reasonable basis to be confident that the 

50% GHG reduction threshold will be 

achieved for renewable diesel, naphtha 

and LPG produced from canola oil 

through a hydrotreating process. 

When we consider the high-end of the 

95-percent confidence interval for 

international land use change GHG 

emissions and the hydrotreating process 

data with the highest GHG emissions, 

we estimate that jet fuel produced from 

canola oil results in a 46 percent 

reduction relative to the petroleum 

baseline. That is, the entire range of 

lifecycle GHG estimates for jet fuel does 

not exceed the 50 percent threshold. We 

follow the approach taken in the March 

2010 RFS2 rule for considering such 

information for purposes of proposing a 

threshold determination for jet fuel 

produced from canola oil. In that rule 

we said, ‘‘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.’’ 75 FR 14785. 

When we consider our mean 

estimates of international land use 

change GHG emissions, the estimated 

range of GHG reductions for canola oilbased jet fuel produced through 

hydrotreating is a 59% to 67% GHG 

reduction relative to the petroleum 

baseline. Given that this range, which is 

already based on reasonably 

conservative assumptions, exceeds the 

50% GHG reduction threshold, and 

considering the weight of evidence 

across all the available results, we judge 

that there is a reasonable basis to be 

confident that the 50% GHG reduction 

threshold will be achieved for canola oil 

jet fuel produced through a 

hydrotreating process. 

Based on the evaluation and results 

described above, we propose to add 

‘‘Canola/Rapeseed oil’’ to the Feedstock 

columns in rows G and I of table 1 to 

40 CFR 80.1426. This addition to row G 

would make renewable diesel, jet fuel, 

and heating oil produced through a 

hydrotreating process eligible for 

biomass-based diesel (D-code 4) RINs if 

the hydrotreating process does not coprocess renewable biomass and 

petroleum. This addition to row I would 

make naphtha and LPG produced from 

canola oil through a hydrotreating 

process eligible for advanced biofuel (Dcode 5) RINs. The RFS regulatory 

definition of biomass-based diesel at 40 


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Federal Register / Vol. 87, No. 74 / Monday, April 18, 2022 / Proposed Rules 22841 

73Freeman, C.J., et al. (2013). Initial assessment 

of US refineries for purposes of potential bio-based 

oil insertions, Pacific Northwest National Lab. 

(PNNL), Richland, WA; van Dyk, S., et al. (2019). 

‘‘Potential synergies of drop-in biofuel production 

with further co-processing at oil refineries.’’ 

Biofuels, Bioproducts and Biorefining 13(3): 760– 

775; Bezergianni, S., et al. (2018). ‘‘Refinery coprocessing of renewable feeds.’’ Progress in Energy 

and Combustion Science 68: 29–64. 

74ANL (2021). Summary of Expansions and 

Updates in GREET 2021, Energy Systems Division: 

58. 

75 Garraı ́n, D., et al. (2014). ‘‘Well-to-Tank 

environmental analysis of a renewable diesel fuel 

from vegetable oil through co-processing in a 

hydrotreatment unit.’’ Biomass and Bioenergy 63: 

239–249. 

CFR 80.1401 excludes naphtha and 

LPG. 

The GHG estimates reported in 

Section II.C.12 of this preamble are 

based on our evaluation of standalone 

hydrotreating processes that process 

only vegetable oil. While there is 

substantial hydrotreating capacity at 

refineries that is potentially suitable for 

co-processing canola oil or other 

vegetable oils with petroleum, there is 

currently relatively little production or 

detailed input-output data for coprocessing vegetable oil and petroleum 

in hydrotreating units.73 For example, a 

co-processing module was added to 

GREET for the first time with the release 

of GREET–2021, but it currently 

contains ‘‘placeholder parametric 

assumptions’’ that Argonne National 

Laboratory is planning to replace after 

additional research.74 The information 

that is available suggests that coprocessing vegetable oil in hydrotreating 

units will require relatively minor 

adjustments compared to hydrotreating 

units that do not co-process with 

petroleum. There are also very few 

lifecycle GHG estimates of this process 

in peer-reviewed journals. The one 

study we found in the literature 

evaluated a hydrotreating unit of a 

Colombian refinery with four different 

feed rates of soybean oil (8.1 to 12.5 

percent by mass) and reported similar 

input-output ratios as the standalone 

processes evaluated above in terms of 

hydrogen input, natural gas input, and 

fuel outputs per pound of feed.75 Given 

that the large majority of our GHG 

reduction estimates significantly exceed 

the 50 percent reduction threshold for 

biofuels produced from canola oil 

hydrotreated without co-processing (see 

Section II.C.12 of this preamble), we 

believe our estimates support a finding 

that canola oil-based fuels from 

hydrotreating processes that co-process 

canola oil with petroleum also meet the 

50 percent threshold. Thus, we propose 

to add ‘‘Canola/Rapeseed oil to the 

feedstock column of row H in table 1 to 

40 CFR 80.1426, which would make, if 

finalized, renewable diesel, jet fuel, 

naphtha, LPG and heating oil produced 

from canola oil through a hydrotreating 

process that includes co-processing with 

petroleum eligible for advanced biofuel 

(D-code 5) RINs. Note that based on the 

definition of biomass-based diesel at 

CAA 211(o), fuels produced through coprocessing renewable biomass and 

petroleum do not qualify as biomassbased diesel, but these fuels may qualify 

as advanced biofuels if they meet the 

GHG reduction and other statutory 

requirements. We request data and 

information on producing renewable 

fuel through hydrotreating processes 

that co-process canola oil and 

petroleum. We request comments on our 

proposal to make these co-processed 

fuels eligible for advanced biofuel (Dcode 5) RINs. 

IV. Summary 

Based on our GHG lifecycle 

evaluation described above, we propose 

to find that renewable diesel, jet fuel, 

naphtha, LPG, and heating oil produced 

from canola oil via a hydrotreating 

process meet the 50 percent GHG 

reduction threshold. This finding would 

support a determination that renewable 

diesel, jet fuel and heating oil produced 

from canola oil are eligible for biomassbased diesel (D-code 4) RINs if they are 

produced through a hydrotreating 

process that does not co-process 

renewable biomass and petroleum, and 

for advanced biofuel (D-code 5) RINs if 

they are produced through a process 

that does co-process renewable biomass 

and petroleum. This finding would also 

support a determination that naphtha 

and LPG production from canola oil 

through a hydrotreating process are 

eligible for advanced biofuel (D-code 5) 

RINs. EPA requests comment on these 

proposed pathways. 

V. Statutory & Executive Order Reviews 

Additional information about these 

statutes and Executive Orders can be 

found at https://www.epa.gov/lawsregulations/laws-and-executive-orders. 

A. Executive Order 12866: Regulatory 

Planning and Review and Executive 

Order 13563: Improving Regulation and 

Regulatory Review 

This proposed action is a significant 

regulatory action that was submitted to 

the Office of Management and Budget 

(OMB) for review. Any changes made in 

response to OMB recommendations 

have been documented in the docket. 

The GHG lifecycle analysis conducted 

for this proposed determination, 

‘‘Renewable Fuel Standard Program: 

Canola Oil Pathways to Renewable 

Diesel, Jet Fuel, Naphtha, Liquefied 

Petroleum Gas and Heating Oil,’’ is 

available in the docket. 

B. Paperwork Reduction Act (PRA) 

This proposed action would not 

impose any new information collection 

burden under the PRA. OMB has 

previously approved the information 

collection activities contained in the 

existing regulations and has assigned 

OMB control number 2060–0725. This 

proposed action would create new 

pathways by which to generate RINs for 

renewable fuels under the RFS program 

but creates no new information 

collection requirements for these 

additional pathways. 

C. Regulatory Flexibility Act (RFA) 

I certify that this proposed action 

would not have a significant economic 

impact on a substantial number of small 

entities under the RFA. In making this 

determination, EPA concludes that the 

impact of concern for this proposed rule 

is any significant adverse economic 

impact on small entities and that the 

agency is certifying that this proposed 

rule would not have a significant 

economic impact on a substantial 

number of small entities if the proposed 

rule would have no net burden. This 

proposed rule would enable canola oil 

producers and producers of biofuels 

from canola oil to participate in the RFS 

program, see CAA section 211(o), if they 

choose to do so to obtain economic 

benefits. We have therefore concluded 

that this proposed action would have no 

net regulatory burden for all directly 

regulated small entities. 

D. Unfunded Mandates Reform Act 

(UMRA) 

This proposed action does not contain 

an unfunded mandate of $100 million or 

more as described in UMRA, 2 U.S.C. 

1531–1538, and would not significantly 

or uniquely affect small governments. 

The proposed action would impose no 

enforceable duty on any state, local or 

tribal governments or the private sector. 

E. Executive Order 13132: Federalism 

This proposed action does not have 

federalism implications. It would 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. 

F. Executive Order 13175: Consultation 

and Coordination With Indian Tribal 

Governments 

This proposed action does not have 

tribal implications as specified in 

Executive Order 13175. This proposed 


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76For a recent discussion of such potential 

impacts, see Chapter 8 of the Draft Regulatory 

Impact Analysis for the RFS ‘‘Proposed Volume Standards for 2020, 2021, and 2022’’. EPA–HQ– 

OAR–2021–0324. 

rule would affect only producers of 

canola oil and producers of biofuels 

made from canola oil. Thus, Executive 

Order 13175 does not apply to this 

proposed action. 

G. Executive Order 13045: Protection of 

Children From Environmental Health 

and Safety Risks 

The EPA interprets Executive Order 

13045 as applying only to those 

regulatory actions that concern 

environmental health or safety risks that 

the EPA has reason to believe may 

disproportionately affect children, per 

the definition of ‘‘covered regulatory 

action’’ in section 2–202 of the 

Executive order. This proposed action is 

not subject to Executive Order 13045 

because it does not concern an 

environmental health risk or safety risk. 

H. Executive Order 13211: Actions 

Concerning Regulations That 

Significantly Affect Energy Supply, 

Distribution, or Use 

This proposed action is not a 

‘‘significant energy action’’ because it is 

not likely to have a significant adverse 

effect on the supply, distribution or use 

of energy. This proposed rule would 

enable canola oil producers and 

producers of biofuels from canola oil to 

participate in the RFS program, see CAA 

section 211(o), if they choose to do so. 

This may create additional supplies of 

energy, potentially leading to positive 

impacts on the energy system. This 

proposed rule would create no new 

burdens on the distribution or use of 

energy. 

I. National Technology Transfer and 

Advancement Act (NTTAA) 

This rulemaking does not involve 

technical standards. 

J. Executive Order 12898: Federal 

Actions To Address Environmental 

Justice in Minority Populations and 

Low-Income Populations 

The EPA believes that this proposed 

action is not subject to Executive Order 

12898 (59 FR 7629, February 16, 1994) 

because it does not establish an 

environmental health or safety standard. 

This proposed rule would give 

renewable fuel producers the ability to 

generate credits under the RFS program 

for the production of specified biofuels 

from canola oil. This proposed rule does 

not affect the level of protection 

provided to human health or the 

environment by applicable air quality 

standards. Future actions to set biofuel 

volume requirements may take into 

consideration the availability of this 

renewable fuel pathway for the 

production of biofuel from canola oil 

and thus may affect GHG emissions, air 

quality, water or soil quality, or fuel and 

food prices.76 However, this proposed 

action does not modify biofuel volume 

requirements and thus the EPA believes 

that the proposed rule to approve a new 

pathway, in and of itself, will not affect 

human health or the environment. 

VI. Statutory Authority 

Statutory authority for this action 

comes from CAA sections 114, 208, 211, 

and 301. 

List of Subjects in 40 CFR Part 80 

Environmental protection, 

Administrative practice and procedure, 

Air pollution control, Diesel fuel, Fuel 

additives, Gasoline, Imports, Oil 

imports, Petroleum, Renewable fuel. 

Michael S. Regan, 

Administrator. 

For the reasons set forth in the 

preamble, the EPA proposes to amend 

40 CFR part 80 as follows: 

PART 80—REGULATION OF FUELS 

AND FUEL ADDITIVES 

■ 1. The authority citation for part 80 

continues to read as follows: 

Authority: 42 U.S.C. 7414, 7521, 7542, 

7545, and 7601(a). 

Subpart M—Renewable Fuel Standard 

■ 2. Amend § 80.1401 by adding in 

alphabetical order the definition of 

‘‘Canola/rapeseed oil’’ to read as 

follows: 

§ 80.1401 Definitions. 

* * * * * 

Canola/Rapeseed oil means either of 

the following: 

(1) Canola oil is oil from the plants 

Brassica napus, Brassica rapa, Brassica 

juncea, Sinapis alba, or Sinapis arvensis 

which typically contains less than 2 

percent erucic acid in the component 

fatty acids obtained. 

(2) Rapeseed oil is the oil obtained 

from the plants Brassica napus, Brassica 

rapa, or Brassica juncea. 

* * * * * 

■ 3. Amend § 80.1426 by: 

■ a. Removing the text ‘‘Table 1 to this 

section’’ wherever it appears and 

adding, in its place, the text ‘‘table 1 to 

paragraph (f)(1) of this section’’; 

■ b. Removing the text ‘‘Table 1 to 

§ 80.1426’’ wherever it appears and 

adding, in its place, the text ‘‘table 1 to 

paragraph (f)(1) of this section’’; 

■ c. In paragraph (f)(1), removing the 

text ‘‘Tables 1 and 2 to this section’’ and 

adding in its place the text ‘‘tables 1 and 

2 to this paragraph (f)(1)’’; 

■ d. Redesignating table 1 to § 80.1426 

as table 1 to § 80.1426(f)(1); 

■ e. In newly redesignated table 1 to 

§ 80.1426(f)(1), revising the entries ‘‘G,’’ 

‘‘H,’’ and ‘‘I’’; 

■ f. Redesignating table 2 to § 80.1426 as 

table 2 to § 80.1426(f)(1). 

The revisions read as follows: 

§ 80.1426 How are RINs generated and 

assigned to batches of renewable fuel? 

* * * * * 

(f) * * * 

(1) * * * 

TABLE 1 TO § 80.1426(f)(1)—APPLICABLE D CODES FOR EACH FUEL PATHWAY FOR USE IN GENERATING RINS

Fuel type Feedstock Production process requirements D-code 

*******

G ....... Biodiesel, renewable 

diesel, jet fuel, and 

heating oil.

Canola/Rapeseed oil ........................................... One of the following: Transesterification with or 

without esterification pre-treatment, or 

Hydrotreating; excludes processes that coprocess renewable biomass and petroleum.

4 


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TABLE 1 TO § 80.1426(f)(1)—APPLICABLE D CODES FOR EACH FUEL PATHWAY FOR USE IN GENERATING RINS— 

Continued 

Fuel type Feedstock Production process requirements D-code 

H ....... Biodiesel, renewable 

diesel, jet fuel, and 

heating oil.

Soy bean oil; Oil from annual covercrops; Oil 

from algae grown photosynthetically; Biogenic 

waste oils/fats/greases; Non-food grade corn 

oil; Camelina sativa oil; Distillers sorghum oil; 

Canola/Rapeseed oil.

One of the following: Transesterification with or 

without esterification pre-treatment, or 

Hydrotreating; includes only processes that 

co-process renewable biomass and petroleum.

5 

I ......... Naphtha, LPG ............... Camelina sativa oil; Distillers sorghum oil; 

Canola/Rapeseed oil.

Hydrotreating ....................................................... 5 

* * * * * * * 

* * * * * 

[FR Doc. 2022–07598 Filed 4–15–22; 8:45 am] 

BILLING CODE 6560–50–P 

AGENCY FOR INTERNATIONAL 

DEVELOPMENT 

48 CFR Parts 726, 729, 731 and 752 

RIN 0412–AB04 

United States Agency for International 

Development (USAID) Acquisition 

Regulation (AIDAR): Foreign Tax 

Reporting, Conference Planning, and 

Trade and Investment Activities 

AGENCY: U.S. Agency for International 

Development. 

ACTION: Proposed rule. 

SUMMARY: The United States Agency for 

International Development (USAID) 

proposes to amend its Acquisition 

Regulation (AIDAR) regarding 

contractor requirements on foreign tax 

reporting, conference planning, and 

trade and investment activities. These 

revisions are intended to bring the 

AIDAR into compliance with revised 

Agency policies and procedures and 

statutory requirements. 

DATES: Interested parties should submit 

written comments at one of the 

addresses shown below on or before 

June 17, 2022 to be considered in the 

formation of the final rule. 

ADDRESSES: Submit comments, 

identified by the title of the action and 

Regulatory Information Number (RIN) 

through the Federal eRulemaking Portal 

at https://www.regulations.gov by 

following the instructions for submitting 

comments. Please include your name, 

company name (if any), and ‘‘0412– 

AB04’’ on any attachments. If your 

comment cannot be submitted using 

https://www.regulations.gov, please 

email the point of contact in the FOR

FURTHER INFORMATION CONTACT section of 

this document for alternate instructions. 

FOR FURTHER INFORMATION CONTACT: 

Kelly Miskowski, USAID/M/OAA/P, 

policymailbox@usaid.gov. 

SUPPLEMENTARY INFORMATION: 

A. Instructions 

All comments must be in writing and 

submitted through the method specified 

in the ADDRESSES section above. All 

submissions must include the title of 

the action and RIN for this rulemaking. 

Please include your name, title, 

organization, postal address, telephone 

number, and email address in the text 

of the message. 

All comments will be made available 

at http://www.regulations.gov for public 

review without change, including any 

personal information provided. We 

recommend that you do not submit 

information that you consider 

Confidential Business Information (CBI) 

or any information that is otherwise 

protected from disclosure by statute. 

USAID will only address substantive 

comments on the rule. USAID may not 

consider comments that are 

insubstantial or outside the scope of the 

proposed rule. 

B. Background 

Several parts in the AIDAR are 

outdated and no longer comply with 

statutory requirements or current agency 

policies and procedures. USAID 

proposes to amend the AIDAR as 

follows: 

1. 48 CFR part 726, subpart 726.71 

Relocation of U.S. Businesses, 

Assistance to Export Processing Zones, 

Internationally Recognized Workers’ 

Rights refers to agency Policy 

Determination (PD) 20, ‘‘Guidelines to 

Assure USAID Programs do not Result 

in the Loss of Jobs in the U.S.’’ PD 20 

was replaced in agency policy by 

Automated Directives System (ADS) 

Chapter 225, Program Principles for 

Trade and Investment Activities and the 

‘‘Impact on U.S. Jobs’’ and ‘‘Workers’ 

Rights.’’ ADS 225 is available at https:// 

www.usaid.gov/ads/policy/200/225. 

USAID proposes amending the AIDAR 

to revise subpart 726.71 to prescribe 

when to include a new clause in section 

752.226–70 in a solicitation and 

contract. 

ADS 225 mandates that requiring 

offices and planners perform the 

necessary analyses to ensure that 

USAID-funded ‘‘trade and investment’’ 

activities do not: (a) Provide financial 

incentives and other assistance for U.S. 

companies to relocate operations abroad 

if it is likely to result in the loss of U.S. 

jobs; (b) Contribute to violations of 

internationally recognized workers’ 

rights defined in 19 U.S.C. 2467(4); (c) 

Provide financial incentives for entities 

located outside the United States to 

relocate or transfer jobs from the United 

States to other countries or provide 

financial incentives that would 

adversely affect the labor force in the 

United States; and/or (d) Provide 

assistance for enforcement of certain 

rules if the enforcement would prohibit 

certain coal-fired or other powergeneration projects. If the analyses 

conclude that the activity is a ‘‘grayarea’’ as described in that chapter, and 

the contract statement of work includes 

either gray-area activities or investmentrelated activities where specific 

activities are not identified at the time 

of obligation but could be for 

investment-related activities, as 

described in ADS Chapter 225, then the 

requiring office will provide the 

contracting officer with a clause 

substantially the same as new section 

752.226–70 to include in the solicitation 

and resulting contract. 

2. USAID proposes to amend AIDAR 

Section 729.402–70 and the 

corresponding clause in 752.229–71 to 

update them to comply with current 

statutory requirements. The annual 

Department of State, Foreign 

Operations, and Related Programs 

Appropriations Act (SFOAA) mandates 

that agencies take certain actions to 

prevent taxation of foreign assistance 

provided with funds appropriated in an 

SFOAA, or to obtain full reimbursement 

of all taxes paid. 


khammond on DSKJM1Z7X2PROD with PROPOSALS