December 12, 2011

MEMORANDUM

TO: Air and Radiation Docket EPA-HQ-OAR-2011-0542

SUBJECT: Summary of Modeling Inputs and Assumptions for the Notice of Data 

Availability (NODA) Concerning Renewable Fuels Produced from Palm 

Oil under the Renewable Fuel Standard (RFS) Program

This memorandum provides information on the key inputs and assumptions used for modeling 

the lifecycle greenhouse gas (GHG) emissions associated with specified palm oil biodiesel and

palm oil renewable diesel fuel production pathways. Assumptions include crop yields, energy

use, energy sources, fertilizer use, co-product production, and other important factors used in the 

lifecycle analysis.

Outline of this Document:

I. System Boundaries

II. Data and Assumptions

A. Palm Oil Cultivation and Yield Trends

B. Palm Oil Mills

C. Biofuel Production

D. Feedstock and Fuel Transport

E. Biofuel Use

F. Volume Scenarios

III. References
I. System Boundaries

The general system boundaries for lifecycle GHG analysis of biofuels under the RFS program 

were determined as part of the March 26, 2010 final rule (EPA 2010). Applying these system 

boundaries to our analysis of palm oil-based biodiesel and renewable diesel was straightforward 

because the lifecycle systems for the palm oil biofuels analyzed are similar to those of other 

biofuels that were analyzed in EPA (2010). Figure I-1 provides a simplified diagram of the palm 

oil biofuel lifecycle.

1 Our lifecycle analysis considers the full fuel lifecycle, including palm oil 

cultivation, feedstock transport, oil extraction and processing, biofuel production, fuel transport 

and distribution, and fuel use. At each stage co-products are accounted for through system 

expansion or energy allocation.2

Figure I-1. Simplified Palm Oil Biofuel Lifecycle System Diagram

This document focuses on our assumptions related to the various stages in the palm oil biofuel 

lifecycle, including fuel and feedstock production and distribution. To analyze the indirect 

agricultural and land use change impacts, we used the same model of international agricultural 

 

1 The acronyms used in Figure I-1 are spelled out below in Table I-1

2

For more discussion on the treatment of co-products refer to Chapter 2 of the RFS2 Regulatory Impact Analysis 

(EPA 2010a).

Palm Oil 

Cultivation

Transport FFB

Palm Oil Mill Transport PK Palm Kernel 

Mill

Transport CPO

Biofuel 

Production

Indirect 

Agricultural and 

Land Use 

Change Impacts

Transport 

Biofuel Biofuel Use

Co-Product 

Displacment
markets that was used for the final RFS2 rule: the Food and Agricultural Policy and Research 

Institute international models as maintained by the Center for Agricultural and Rural 

Development at Iowa State University (the FAPRI-CARD model). For more discussion on our 

use of the FAPRI-CARD model refer to the palm oil NODA preamble (EPA 2011). Two key

inputs in the FAPRI-CARD modeling are the assumed yield trends for palm oil and the volume 

scenarios considered. Both of these factors in our analysis are discussed below.

II. Data and Assumptions

This section includes a summary of key assumptions and data inputs used in our lifecycle GHG 

assessment of palm oil-based biofuels. As discussed in the EPA (2011), our analysis focuses on 

palm oil production in Indonesia and Malaysia. In this document, assumptions for palm oil 

production in other regions are commonly aggregated into a “rest of world” category. Our 

analysis considers direct and significant indirect emissions related to the production and use of 

palm oil-based biofuels. As such, we also considered GHG emissions impacts related to the 

production and use of other agricultural commodities (e.g., soybeans, rapeseed, beef, poultry)

that are indirectly impacted by an increase in palm oil-based biofuel production and use. For 

information on the data inputs and assumptions used to evaluate these other aspects of our 

analysis refer to the Regulatory Impact Analysis for the RFS2 final rule (EPA 2010a). Table I-1 

includes a list of acronyms and units used in this document. 

Table I-1. Acronyms and Units

Acronyms Units

CPO Crude palm oil Btu British thermal units

EFB Empty fruit bunches of oil palm Gal Gallons

FFB Fresh fruit bunches of oil palm Ha Hectares

PK Palm kernel Kg Kilograms

PKO Palm kernel oil Lb Pounds

PKM Palm kernel meal M One million

POME Palm oil mill effluent m

3 Cubic meters

Mt or t Tonnes

yr Year

A. Palm Oil Cultivation and Yield Trends

Table I-2 summarizes key assumptions related to palm oil cultivation. Palm oil harvested area 

and yield trends are based on projections included in the FAPRI-CARD model. The FAPRICARD model uses historical data published in the USDA’s online Production, Supply and 

Distribution (PS&D) database3as well as data from Global Agricultural Information Network 

(GAIN) Reports published by USDA-FAS.4

Table I-2. Palm Oil Cultivation Assumptions

 

3

http://www.fas.usda.gov/psdonline/

4

http://gain.fas.usda.gov/
Item Geographic Region Assumption Units Source

Crop yield (2008) Indonesia 4.38 tCPO/ha FAPRI-CARD

Malaysia 4.32

Rest of World 1.67

Crop Yield (2022) Indonesia 5.06

Malaysia 5.00

Rest of World 1.93

Harvested acres 

(2008)

Indonesia 4.50 Mha

Malaysia 4.10

Rest of World 3.47

Diesel use (2022) Global 18.5 gal/ha/yr Unnasch et al.

Nitrogen fertilizer 

application (2022)

Indonesia 74.3 kg/ha/yr EPA (2010) based on Heffer

Malaysia 99.9

Rest of World 23.7

Phosphorous 

application (2022)

Indonesia 28.7

Malaysia 35.7

Rest of World 10.5

Potassium 

application (2022)

Indonesia 91.6

Malaysia 234.9

Rest of World 36.8

Herbicide (2022) Indonesia 0.02 EPA (2010) based on FAO

Malaysia 0.90

Rest of World 0.32

Insecticide (2022) Indonesia 0.01

Malaysia 0.16

Rest of World 0.09

Fungicide (2022) Indonesia 0.01

Malaysia 0.16

Rest of World 0.06

1. Palm Oil Yield Trends in Malaysia

Historical palm oil yields in Malaysia from 1990 to 2007 are shown in Figure II-1. This data is 

taken from the FAPRI-CARD model, which, as discussed above, uses information published by

USDA. The FAPRI-CARD model projects palm oil yield in Malaysia as an extension of the 

historical data trend forward to 2022. This is the yield projection marked “EPA” in Figure II-2 

and it is used in our analysis. It is based on the same general approach as used for all of the 

crops in the RFS2 final rule analysis (EPA 2010a, Section 5.1.3). 

Additionally, the Malaysian Palm Oil Board (MPOB) provided us with data on palm oil yields in 

2009 and assumptions regarding projected replanting, expansion and clonal varieties (MPOB 

2010). As a check on the FAPRI-CARD yield projections we used the data provided in MPOB 

(2010) to derive the alternative projection labeled “EPA w/ MPOB data” in Figure II-2. 

Figure II-1. Historical Malaysian Palm Oil Yields (tCPO/ha)
Figure II-2. Projected Malaysia Palm Oil Yields (tCPO/ha)

In Figure II-2, both of the projections reach the same conclusion regarding average palm oil 

yields in 2022, but the projections in the interim years are different. The EPA projection grows 

at a linear rate of 0.05 tCPO/ha/yr. In contrast, the projection based on MPOB data shows yield 

declining for several years before increasing after about 2013. Yields could stagnate for several 

years if growers delay replanting old plantations with new cultivars, perhaps in response to high 

vegetable oil prices or other reasons (USDA-FAS 2011). Eventually, though, it will be in the 

economic interest of growers to replant with higher yielding cultivars. Since our analysis focuses 

on projecting impacts in 2022, the fact that both forecasts project the same average yields in 

Malaysia in 2022 (5.0 tCPO/ha) supports the robustness of our yield projections.

y = 0.05x - 100.66

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Yield (Historical) Linear (Yield (Historical))

0.0

1.0

2.0

3.0

4.0

5.0

6.0

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

EPA EPA w/ MPOB data
2. Palm Oil Yield Trends in Indonesia

Figure II-3 shows Indonesian palm oil yields from 1993 to 2007 based on data in the 

FAPRI-CARD model, with the trend estimated for the same period.5 Projections for the future 

start in 2008 (see Figure II-4). Extrapolating the linear trend in the historical data, the slope for 

the projection period is 0.05 tCPO/ha/yr. The trend line marked “EPA” in Figure 4 is the 

Indonesian palm oil yield projection used in our analysis. This projection is based on the same 

approach as used for all crops in the RFS2 final rule analysis (EPA 2010a, Section 5.1.3).

Figure 3. Historical Indonesian Palm Oil Yields (tCPO/ha)

Figure 4. Projected Indonesian Palm Oil Yields (tCPO/ha)

 

5 The historical data was taken from the FAPRI-CARD model.

y = 0.05x - 110.15

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

tonnes / hectare

Yield (Historical) Linear (Yield (Historical))
4. Palm Oil Crop Inputs

Palm oil plantations use diesel fuel to power agricultural machinery for maintenance, harvesting 

and other procedures. The Roundtable on Sustainable Palm Oil (RSPO) reviewed relevant 

literature and found that diesel use ranges from 14-32 gal/ha/yr (RSPO).6 After reviewing 

several data sources, Schmidt assumed average diesel use of 15.4 gal/ha/yr. Most recently, 

Unnasch et al. assumed diesel use of 18.5 gal/ha/yr in their lifecycle assessment of palm oil 

biodiesel. Our analysis adopts the assumption from Unnasch et al., which falls with the range 

found in the other studies mentioned above.

Common palm oil fertilizer inputs comprise nitrogen fertilizers (i.e., ammonium nitrate, 

ammonium sulphate, urea or ammonium chloride) phosphorous and potassium chloride (RSPO). 

The fertilizer application rates used in our analysis are based on data from the International 

Fertilizer Association (Heffer), as shown in are included in Table I-2. Our assumptions fall 

within the range of values found in the literature for typical fertilizer application rates. For 

example, (RSPO 2009) finds a range of nitrogen application rates ranging from 88.2 to 100 kg 

N/ha/yr, phosphorous application rates in the range of 28-45 kg P2O5/ha/yr, and potassium 

applications rates commonly between 172-252 kg K2O/ha/yr. Based on MPOB survey data 

Unnasch et al. assumes 69.8 kg N/ha/yr, 56 kg P2O5/ha/yr and 230 kg K2O/ha/yr. Based on a 

literature review of data for mature plantations Schmidt assumes 106 kg N/ha/yr, 73 kg 

P2O5/ha/yr and 210 kg K2O/ha/yr. The only value used in our analysis that appears to fall 

outside of typical ranges found in the literature is the potassium application rate in Indonesia (99 

kg K2O/ha/yr), which is lower than the values cited above. We conducted sensitivity analysis on 

this value and found that increasing the Indonesian potassium application rate to 250 kg 

K2O/ha/yr would increase lifecycle GHG emissions by less than 0.2% for palm oil-based 

biodiesel and renewable diesel.

 

6 Based on the recommended range from page 9 of RSPO converted to gal/ha/yr using the diesel GHG emissions 

factors and fuel specifications from EPA (2010)

0.0

1.0

2.0

3.0

4.0

5.0

6.0

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022

EPA
Palm oil plantations use herbicides and pesticides to enhance crop performance. The most 

commonly used herbicide in Malaysia is glyphosate (Unnasch et al.). Pesticide applications rates 

in our analysis are based on FAO data and shown in Table I-2. The application rates assumed in 

our analysis are somewhat lower than the rates cited in the literature. For example, Unnasch et 

al. assumes 2.59 kg herbicide/ha/yr and 0.58 kg insecticide/ha/yr. GHG emissions associated 

with pesticide and herbicide use at palm oil plantations represent a very small share of total 

lifecycle GHG emissions related to the production and use of palm oil biofuels. As such, we 

have determined that the application rates based on FAO are suitable for use in our analysis.

A. Palm Oil Mills

Table I-3 summarizes our assumptions for palm oil mill operations, where palm fruit is crushed 

to produce CPO. As discussed in the NODA preamble, our analysis of palm oil mill operations 

is based on average practices in Indonesia and Malaysia. 

Table I-3. Palm Oil Mill Assumptions

Item Assumption Units Source

CPO yield 5.00 tFFb/tCPO Various sources 

including Schmidt and 

Subramaniam et al.

PK yield 0.27 tPK/tCPO Schmidt

Biomass use for heat 

& power

2.62 mmBtu/tCPO

Purchased electricity Electricity generated onsite from oil palm 

biomass

Various sources 

including Schmidt and 

Unnasch et al.

Diesel use 1.18 gal / tCPO Subramaniam et al.

POME yield 3.00 tPOME/tCPO

POME methane yield 18.22 m

3 CH4/tPOME

We consulted a range of sources regarding CPO yields. Based on a survey of 12 Malaysian palm 

oil mills Subramaniam reports average yield of 5.07 tFFB/tCPO.7 Schmidt reports CPO yield of 

5.01 tFFB/tCPO based on an average of national figures published by the MPOB in 2005 and 

2006. We also considered historical data posted on MPOB’s website,

8

summarized in Figure I-1. 

The MPOB data shows a slow trend toward more efficient CPO extraction per tonne of FFB 

processed. Based on this information we assume that CPO yield will be 5.00 tCPO/tFFB in 

2022.

Figure II. Malaysian Crude Palm Oil Extraction Yield Over Time (tFFb/tCPO)

 

7

Subramaniam, V., Ngan, M., A., May, C., Y., Sulaiman, N., M., N., 2008. Environmental Performance of the 

Milling Process of Malaysian Palm Oil Using the Life Cycle Assessment Approach. American Journal of 

Environmental Sciences 4 (4): 310-315.

8 MPOB Economics and Industry Development Division, http://161.142.157.5/v1/input.asp?pid=ext, accessed 

9/1/2010
The yield of palm kernel co-product is from Schmidt based on Malaysian national figures. Other 

co-products from the milling process include meso-carp fiber, shells, EFB and POME. We 

assume that EFB is returned to the field for use as fertilizer. Shells and fiber are burned at the 

mill for heat and power, which negates the need for palm oil mills to purchase electricity from 

the grid. Our analysis accounts for the small amount of diesel fuel used at palm oil mills for 

maintenance equipment, start-up and other purposes (Subramaniam).

Table II-3 also includes our assumptions about the amount of POME and POME methane 

generated per tonne of CPO produced at palm oil mills. We assume POME yield of 0.6 

tPOME/tFFB. Our assumption is based on the average of POME yield found in Subramaniam’s 

survey of 12 Malaysian palm oil mills. This is within the range of values found in other relevant 

studies. For example, Schmidt assumes 0.67 tPOME/tFFB based on MPOB data from 2005 

through 2006, and Yacob et al. assumes 0.5 tPOME/tFFB based on one year of measured data 

from a single Malaysian mill. 

Based on the survey of Malaysian palm oil mills cited above, we assume that on average 18.2 

cubic meters of methane is generated per tonne of POME (m

3 CH4/tPOME). This is within the 

range of values estimated in the literature. For comparison, Schmidt also assumes 18.20 m

3

CH4/tPOME and Yacob et al. assumes 9 m

3 CH4/tPOME. RSPO reviewed a variety of studies 

and found that most estimate POME methane emissions of close to 18 m

3CH4/tPOME. The one 

exception was Yacob et al. According to RSPO the low value estimated by Yacob et al. can most 

likely be attributed to the specific lay out of the treatment system monitored. Although methane 

formation can vary depending on the conditions at different water treatment facilities we have 

taken an industry average approach in our analysis by relying on the average from the survey by

Subramaniam which considers 12 mills in different geographic locations across Malaysia.

As discussed in Section II.A.5 of the NODA preamble, our analysis accounts for industry

average POME methane treatment practices at palm oil mills in Malaysia and Indonesia. Table 

4.70 

4.80 

4.90 

5.00 

5.10 

5.20 

5.30 

5.40 

5.50 

1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
II-4 summarizes data on POME treatment in Malaysia based on an MPOB industry survey

(MPOB 2011). 

Table II-4. Prevalence of POME Methane Capture in Malaysia

Item Assumption Units Source

Number of palm oil mills 422 Palm oil mills MPOB (2011)

Mills without POME methane capture 350

Mills with POME methane capture* 72

Of the mills with POME methane capture

Mills with covered lagoon digesters 27

Mills with closed digester tanks 45

Use of captured POME methane

Flaring only 29

Electricity generation only 24

Steam Only 4

Combined heat and power 15

*Includes mills with POME methane capture projects under construction

According to the Indonesian Palm Oil Board (IPOB), there are currently 608 palm oil 

mils in Indonesia. The NODA preamble explains that data from the Embassy of Indonesia 

indicates that 3.5% of these mills have operational POME methane capture projects in place, and 

that an additional 2% of the mills have such projects under construction. Additionally, the 

Embassy states that all of these projects will use covered lagoons to capture the methane, and 

that the captured methane will be used to generate electricity. Based on this data, Table II-5 

summarizes our assumptions regarding POME methane capture at Indonesian palm oil mills.

Table. II-5. Prevalence of POME Methane Capture in Indonesia

Item Assumption Units Source

Number of palm oil mills 608 Palm oil mills IPOB

Mills without POME methane 

capture

575 Embassy of 

Indonesia

Mills with POME methane 

capture*

33

Of the mills with POME methane 

capture

Mills with covered lagoon 

digesters

33

Use of captured POME methane

Electricity generation only 33

* Includes mills with POME methane capture projects under construction

Table II-6 summarizes key assumptions used in our analysis regarding POME methane capture 

and use. Our assessment uses the default biogas capture and use efficiencies specified in the 

approved United Nations Framework Convention on Climate Change’s (UNFCCC) Clean 

Development Mechanism (CDM) guidelines which instruct project applicants to assume a 

default biogas collection efficiency of 90% for such projects at palm oil mills. Based on our 
review of relevant literature this is the most defensible assumption for our industry average 

analysis. For comparison, Schmidt assumes 92.2% methane capture based on a CDM project 

design form submitted for a single palm oil mill in Indonesia. Our review of similar project 

design forms gives methane capture efficiencies ranging from 87% to 95%.9 The design forms 

use default assumptions because there is a lack of reliable field measurements that can be used. 

For comparison, EPA (2010b) assumes that industrial wastewater treatment facilities in the 

United States achieve biogas collection efficiencies ranging from 95% to 100%. We consider 

these capture efficiencies to be too high for industry average practices in Indonesia and Malaysia 

where the projects tend to be smaller in scale and use less advanced technologies. We also 

assume, based on CDM guidance, that an additional one percent of the methane is released from 

undigested POME that leaves the system.

As discussed above (Table II-4 and Table II-5) we assume that 27% of the mills that capture 

methane flare it onsite. Our analysis assumes that these facilities use enclosed flares with 90% 

methane destruction efficiency. This is based on the default assumption for enclosed flares in the 

approved CDM methodology for methane recovery in wastewater treatment. For comparison, 

test data from California reports enclosed flare efficiency of 99.5% (CCAR). EPA (2010c)

instructs domestic waste water treatment facilities to report GHG emissions assuming that flare 

efficiency is the lesser of the manufacturer’s specified destruction efficiency and 99%. The 

CDM also provides a default factor of 50% efficiency for open flares. Our review of CDM 

project documents indicates that enclosed flares are most commonly used at mills that destroy

captured methane. To account for the smaller share of mills that might use open flares, and 

based on uncertainties related to weather conditions and flare maintenance, we conclude that 

assuming 90% industry average flare efficiency is the most reasonable assumption for the 

purposes of our analysis. Because only 3% of palm oil mills are assumed to capture and flare 

methane, the conclusions drawn from our analysis are not very sensitive to assumed flare 

efficiencies.

We assume that 7% of palm oil mills capture and use methane to generate electricity (Table II-4 

and Table II-5). For these mills we assume 34% electricity generator efficiency based on 

monitoring data from a palm oil mill with a reciprocating engine using biogas with 

approximately 60% methane content (CPA). For comparison, Schmidt assumes 40% turbine 

efficiency but no justification is provided for the assumption. As another comparison, an EPA 

benefits calculation tool for landfill gas projects assumes 29% generation efficiency based on a 

weighted average of typical efficiencies for engines, gas turbines, boilers and steam turbines.10 

In sum, our assumption, which is based on actual monitoring data, is within the reasonable range 

of typical electricity generation efficiencies for similar biogas to energy projects.

Table II-6. POME Methane Capture and Use Assumptions

Item Assumption Source

Covered lagoon methane capture efficiency 90% CDM

 

9 Based on a review of project design documents for CDM projects 2542, 2612, 3702, 2659, 2620 and 2644.

10 U.S. Environmental Protection Agency (EPA). Emission Reductions and Environmental and Energy Benefits for 

Landfill Gas Projects. Landfill Methane outreach Program, http://www.epa.gov/lmop/projects-candidates/lfgecalculator.html accessed June 2011
Item Assumption Source

Closed tank methane capture efficiency 90%

Enclosed flare methane destruction efficiency 90%

Electricity generation efficiency 34% CPA

C. Biofuel Production

Our analysis of lifecycle GHG emissions associated with biodiesel and renewable diesel 

production is discussed in detail in Section II.B and II.C of the palm oil NODA preamble. 

Assumptions regarding the trans-esterification process to produce biodiesel are taken from the 

RFS2 final rule analysis (EPA 2010). Assumptions regarding the hydrotreating process to 

produce renewable diesel are based on Pearlson. For further details, the lifecycle analysis results 

spreadsheet available through the public docket includes our calculations of lifecycle GHG 

emissions associated with the conversion of crude palm oil into biodiesel and renewable diesel.

D. Feedstock and Fuel Transport

Lifecycle GHG emissions associated with feedstock and fuel transport are also included in our 

analysis. Our analysis of palm oil-based biodiesel is based on a scenario in which palm oil is 

grown in Malaysia.

11

 The palm oil fruit is transported via heavy duty trucks to the closest palm 

oil mill. Some of the trucks return with EFB for field application and the rest are assumed to 

operate with empty back haul. CPO is then trucked from the palm oil mill to a biodiesel 

production facility in the same country. Biodiesel subsequently is trucked from the production 

facility to a shipping port, where it is loaded onto an ocean tanker for transport to the United 

States. Biodiesel is then trucked to a bulk distribution terminal for blending, and then to a retail 

distributor. Emissions from feedstock and fuel transport would be greater in a scenario in which 

CPO is transported to the U.S. for conversion to biodiesel because biodiesel is has greater energy

density than CPO.

Key assumptions regarding biodiesel feedstock and fuel transport are included in Table II-7. The 

distances and transport modes are based on Unnasch et al. GHG emissions associated with each 

tonne-mile of transport were calculated using factors from GREET. For more details on our 

calculations refer to the results spreadsheet available through the public docket.

Table II-7. Biodiesel Feedstock and Fuel Transport Assumptions

Cargo Transport Stage Transport Mode Distance (miles)

FFB Field to Palm Oil Mill Medium Duty Truck 34*

EFB Palm Oil Mill to Field Medium Duty Truck 34

CPO Palm Oil Mill to Fuel Production Facility Heavy Duty Truck 100*

Biodiesel Fuel Production Facility to Port Heavy Duty Truck 300*

Biodiesel Port in S.E. Asia to U.S. Port Ocean Tanker 9000

Biodiesel U.S. Port to Bulk Distribution Terminal Heavy Duty Truck 100*

Biodiesel Bulk Distribution Terminal to Distributor Heavy Duty Truck 180*

* Includes empty back haul

 

11 We assume that transport modes and distances would be similar for a scenario based in Indonesia.
Similar to biodiesel, our analysis of palm oil-based renewable diesel is based on a scenario in 

which palm oil is grown in Malaysia.12 The palm oil fruit is transported via heavy duty truck to 

the closest palm oil mill. Some of the trucks return with EFB for field application and the rest are 

assumed to operate with empty back haul. CPO is then trucked from the palm oil mill to a port 

for transport to a renewable diesel production facility in Singapore. Renewable diesel is 

subsequently shipped from Singapore to the United States. Renewable diesel is then trucked to a 

bulk distribution terminal for blending, and then to a retail distributor. Emissions from feedstock 

and fuel transport would be greater in a scenario in which CPO is transported to the U.S. for 

conversion to renewable diesel because renewable diesel has greater energy density than CPO. 

Key assumptions regarding renewable diesel feedstock and fuel transport are included in Table 

II-8. 

Table II-8. Renewable Diesel Feedstock and Fuel Transport Assumptions

Cargo Transport Stage Transport Mode Distance (miles)

FFB Field to Palm Oil Mill Medium Duty Truck 34*

EFB Palm Oil Mill to Field Medium Duty Truck 34

CPO Palm Oil Mill to Port Heavy Duty Truck 300*

CPO Port to Fuel Production Facility Ocean Tanker 575

Renewable Diesel Fuel Production Facility to U.S. Port Ocean Tanker 9000

Renewable Diesel U.S. Port to Bulk Distribution Terminal Heavy Duty Truck 100*

Renewable Diesel Bulk Distribution Terminal to Distributor Heavy Duty Truck 180*

* Includes empty back haul

E. Biofuel Use

Tailpipe emissions associated with biodiesel use were estimate in the RFS2 final rule. As in the 

RFS2 rule, this analysis treats all of the biodiesel fuel carbon as biologically derived carbon 

originating from the atmosphere. This would be the case where the methanol used in the transesterification process was produced from biomass. If the methanol instead is produced from 

natural gas, the net carbon dioxide emissions from the combustion of fossil derived methanol in 

biodiesel would result in a small change to the lifecycle GHG emissions for biodiesel. Based on 

our modeling of the trans-esterification process in the RFS2 final rule we estimate that the 

lifecycle GHG emissions from combustion of biodiesel made with fossil methanol rather than 

methanol derived from biomass would include approximately 4 kg of additional carbon dioxideequivalent (CO2e) emissions per mmBtu of biodiesel. If we included the additional GHG 

emissions associated with the use of fossil methanol in biodiesel production in our lifecycle 

GHG assessment of palm oil biodiesel it would not affect our threshold determinations for palm 

oil biodiesel. The emissions factor used for biodiesel use was also applied to renewable diesel in 

this analysis.

Table II-9. Biodiesel Tailpipe Emissions

Item Assumption Units Source

CH4 emissions 11 g/mmBtu biodiesel EPA (2010)

N2O emissions 689

 

12 We assume that transport modes and distances would be similar for a scenario based in Indonesia.
CO2 emissions 79,837

GHG emissions 80,537 gCO2e/gal biodiesel

F. Volume Scenarios

This section describes our rationale for assuming an incremental volume of approximately 414

Mgal of palm oil based biofuel in 2022 for the purposes of our modeling for lifecycle GHG 

analysis. (See Section I.A.3 of the NODA for more background regarding the scenarios 

modeled.) The modeled scenario includes an incremental increase in the use of biodiesel and 

renewable diesel in the U.S. in 2022, with volumes steadily ramping up over the time period. 

The modeled scenario assumes an incremental increase of approximately 1.46 million tonnes of 

CPO used as feedstock to produce palm oil-based biofuels. For the purposes of our modeling we 

assume that exactly half of this CPO volume is used to produce biodiesel and half is used to 

produce renewable diesel fuels via a hydrotreating process. Based on the assumed yields of 

biodiesel and renewable, the modeled scenario includes an incremental increase of 210 Mgal of 

palm oil biodiesel and 203 Mgal of palm oil renewable diesel fuel used in the United States.

13

 

The renewable diesel fuel volumes include 170 Mgal of palm oil-based diesel fuel and 33 Mgal 

of palm oil-based jet fuel. The split between palm oil-based diesel and jet fuel is based on the 

yield from a typical hydrotreating process maximized for diesel fuel production according to 

Pearlson. We determined this volume scenario to be reasonable based on evaluation of historical 

production, potential feedstock availability and competitive uses (e.g., for food or export instead 

of for domestic fuel), potential increases in crop acreage, and potential increases in crop yields. 

These volume scenarios are reasonable when we make the counter-factual assumption that palm 

oil-based biofuels (biodiesel and renewable diesel) qualify as biomass-based diesel or advanced 

biofuel under the RFS program.14 

Historical Palm Oil Biodiesel Production and Imports to the United States: According to 

information provided by Wilmar International Ltd. (Wilmar) and other biodiesel industry

stakeholders, production and imports of palm oil biodiesel from 2006 to 2009 ranged from 26 

million gallons to 160 million gallons per annum. See Table II-10 for annual production and 

import estimates. 15 

Table II-10. Historical Palm Oil Biodiesel Production and Imports (Mgal) 

Year U.S. Production U.S. Imports** Total

2005 4 * 4

2006 11 15 26

2007 20 108 128

2008 63 97 160

2009 14 19 33

2010 (Jan. – Sep.) 8 8

* Imports unknown for 2005

** Imports include re-exports

 

13 Totals do not sum to 414 million gallons due to rounding error.

14 All of the statements that follow about reasonable volume projections include this assumption.

15 Communication with Wilmar, September 7, 2010
To put this in perspective, United States production and imports of palm oil biodiesel made up 

48% of total domestic biodiesel production and use in 2008 and 6.0% in 2009. See Table II-11

for estimates of the annual share of biodiesel consumption from palm oil biodiesel imports and 

production from EIA. 

Table II-11. United States Biodiesel and Palm Oil Biodiesel Consumption (Mgal) 

Year U.S. Biodiesel 

Consumption

U.S. Palm Oil 

Biodiesel Production 

and Imports**

% of U.S. Biodiesel 

Production and 

Import from Palm Oil 

Biodiesel

2006* 238 26 11%

2007* 327 128 39%

2008* 335 160 48%

2009 536 33 6%

* Potentially distorted by Blender Tax Credit (see explanation below)

** Imports include re-exports

It must be noted that a large portion of the increase in palm oil biodiesel imports in 2007 and 

2008 was not consumed within the United States, but was exported because of a loophole created 

by the biodiesel tax credit. Beginning in 2004, the Blender Tax Credit (BTC), often referred to 

as “splash and dash,” provided a $1.00-per-gallon tax credit to shippers who blended 

(“splashed”) a small amount of conventional diesel (as little as 0.1 percent) with a tanker of 

biodiesel in the United States and then re-exported (“dashed”) the blended fuel to other markets. 

Due to the loophole the percentages in the last column in Table 2 are artificially high for the 

years 2006-2008 (EIA). The Emergency Economic Stabilization Act of 2008 (EESA) closed the 

loophole beginning on January 1, 2009. Therefore, we focused on the data from 2009 to guide 

our assessment because it represents palm oil biodiesel supplies under more normal market 

conditions.

We used our understanding of historical market share from palm oil biodiesel to help project 

future volumes. The Clean Air Act requires that, at a minimum, the biomass-based diesel 

standard require the use of 1 billion gallons per year in 2013 and beyond.16 We anticipate, 

however, that additional biodiesel could potentially be used to meet the required volumes for the

advanced biofuel category, thus exceeding the 1 billion gallon minimum from the biomass-based 

diesel standard.17 For the final RFS2 rule, we had assumed 1.67 billion gallons of biodiesel use 

could be possible from all feedstocks in 2022. If we assume that in 2022 palm oil biodiesel will 

maintain a similar share of the biodiesel market as it did in 2009 (i.e., 6% of 1.67 billion gallons

of biodiesel in 2022), it appears that100 million gallons of palm oil biodiesel could be sold or 

distributed in the United States in 2022. We believe there is good reason that palm oil biodiesel 

could significantly improve its share of the domestic biodiesel market (i.e., exceed 6%) over time 

given the recent and projected rapid expansion in crude palm oil production (See Figure II-6) and 

the competitive price of palm oil compared to other virgin plant oils (See Figure II-7).

 

16 EPA is authorized to require larger volumes after considering the factors specified in Clean Air Act 

211(o)(2)(B)(ii). 

17 Assuming no waivers, the advanced biofuels standard for 2022 is 21 bgal: 1bgal is biomass-based diesel, 16 bgal 

is cellulosic biofuels, the remaining 4 bgal is un-specified advanced biofuels.
Figure II-6. Historical Crude Palm Oil Production (Thousand Tonnes)18

Palm oil has the potential to be a very competitive biodiesel feedstock because it tends to be 

cheaper than other edible oils such as soybean oil. Recently, soybean oil has commanded a 

significant price premium over palm oil, ranging from approximately 10% to 30%. See Figure 

II-7 for the percentage price premium for soybean oil compared to palm oil in recent years.19

Figure II-7. Price Premium for Edible Soybean Oil Compared to Palm Oil (Percent)

 

18 FAPRI-CARD model

19 Based on data from the FAPRI-CARD model. FOB export prices at Rotterdam were used for soybean oil. CIF 

import prices at Rotterdam were used for palm oil.

-

5,000 

10,000 

15,000 

20,000 

25,000 

30,000 

35,000 

40,000 

45,000 

50,000 

198

0

198119821983198

4

198519861987198

8

1989199019911992199319941995199619971998199920

0

0

20

01

20

02

20

03

20

0

4

20

05

20

06

20

07

20

0

8

India Indonesia Malaysia Rest of World
Based solely on the price of palm oil versus soybean oil we might expect palm oil to capture a 

majority share in the United State biodiesel market. However, the utilization of palm oil 

biodiesel in the United States is limited to some degree because palm-oil based biodiesel has a 

high cloud point which diminishes its value in colder climates.20 In the European Union the 

cloud point limitations have been minimized through industry practices which maximize the use 

of palm oil feedstocks during warmer seasons. For example, in the United Kingdom, palm oil 

biodiesel accounted for 12% of biodiesel consumption from April 2008 to April 2009, and 10% 

of biodiesel consumption from April 2009 to April 2010.21 

As the United States biodiesel market expands and diversifies its use of feedstocks it is 

reasonable to except that blenders could adopt practices similar to their European counterparts, 

which would enable the United States to use a much larger volume of palm oil biodiesel. Indeed, 

fuel suppliers in the United States would have a strong incentive to use increasing volumes of 

palm oil biodiesel if it were both less expensive than other crop-based alternatives and qualified 

as eligible for biomass-based diesel or advanced biofuel RINs under the RFS program. 

Based on the information from palm oil and biodiesel producers such as Wilmar and Neste Oil, 

recent trends and economics, and the share of palm oil used in the United Kingdom in 2008, it 

appears reasonable to assume that palm oil-based biodiesel could account for 12% of the United 

States biodiesel market in 2022, especially if palm oil biodiesel were to be qualified as eligible 

for biomass-based diesel or advanced biofuel RINs under the RFS program. For the final RFS2 

rule we had assumed 1.67 billion gallons could be possible from all biodiesel feedstocks in 2022. 

If we assume that palm oil biodiesel could account for 12% of the biodiesel market in 2022 it 

appears that as a reasonable estimate an incremental volume of 210 million gallons of palm oil 

biodiesel could be sold or distributed in the United States in 2022.

 

20 The cloud point is the lowest temperature at which a liquid will pour or flow under prescribed conditions. It is a 

rough indication of the lowest temperature at which oil is readily pumpable.

21 Renewable Fuels Agency. Renewable Transportation Fuel Obligation (RTFO) Reports. 

http://www.renewablefuelsagency.gov.uk/carbon-and-sustainability/rtfo-reports, accessed September 15, 2010

0%

5%

10%

15%

20%

25%

30%

35%

2005 2006 2007 2008
Potential Supply of Palm Oil-Based Renewable Diesel Fuel: In addition to its use as a biodiesel 

feedstock, palm oil is also a potential feedstock for renewable diesel production. If it qualifies as 

an advanced biofuel under the RFS program palm oil could be a highly competitive feedstock for 

renewable diesel because of its relatively low price compared to other edible oils (see discussion 

above). In addition, the high cloud point of palm oil is not a limitation when it is converted into 

renewable diesel. (This is because renewable diesel is chemically very similar to petroleumbased diesel fuel).

In the RFS2 final rule we projected a set of reasonable fuel volumes based on our best estimate 

of likely fuels that could come to market. For renewable diesel, we assumed that the feedstocks 

used would be from fats, waste oils, and waste greases. The reasoning was that biodiesel 

producers would use the available supplies of virgin plant oils, because trans-esterification is 

better suited for processing virgin oils, which would leave waste fats, oils and greases for 

renewable diesel producers (EPA 2010a). The assessment was primarily based on projected 

biodiesel and renewable diesel capacity in the United States. At that time we did not evaluate the 

volumes of renewable diesel that could be supplied from palm oil if it were to qualify as 

biomass-based diesel. Considering the limited availability of waste fats, oils and greases for use 

as biofuel feedstocks, our volume scenarios for the RFS2 rule considered 150 million gallons of 

renewable diesel production. Based on information from Neste Oil it appears that palm oil could 

be a significant feedstock for renewable diesel that we did not anticipate in our volume scenarios

for the RFS2 final rule.

Neste Oil produces a renewable diesel fuel called NExBTL which can be produced from a range 

of edible and non-edible oil feedstocks. Neste Oil currently produces NExBTL at facilities in 

Porvoo, Finland with production capacity of 100 million gallons per year (Mgy) and a recently 

opened plant in Singapore with capacity of 270 Mgy. They are currently close to completing 

another facility in Rotterdam, also with a capacity of 270 Mgy. Neste Oil is also studying the 

feasibility of an additional production facility to be based in United States.

22

 EPA is not aware 

of any other companies that are planning to produce renewable diesel from palm oil for 

distribution in the United States.

According to Neste Oil, the facility in Finland primarily uses palm oil as a feedstock and ships its 

end product to Europe. The Rotterdam facility would also primarily serve the large European

demand for diesel fuel. Neste Oil sees an opportunity to use the facility in Singapore to convert 

palm oil into NExBTL for export to the United States. 

Neste Oil’s corporate goal is to diversify their feedstock sources and shift away from edible oils 

such as palm oil by 2020, subject to feedstock availability. For example, they currently derive 

roughly 20% of their feedstocks from animal fats and fish oils, and they are researching the use 

of algae, jatropha and other microbes.23 Due to uncertainty about the availability of non-edible 

oil feedstocks, however, it currently appears likely that palm oil will continue to be a significant 

 

22 Neste Oil, NExBTL plant to Singapore, http://www.nesteoil.com/default.asp?path=1,41,540,2384,7906,13931, 

accessed September 15, 2010

23 Neste Oil, New raw materials are researched, http://www.nesteoil.com/default.asp?path=1,41,11991,12243,12139, 

accessed September 20, 2010
feedstock for renewable diesel fuel in 2022, especially if it were to qualify as advanced biofuel 

under the RFS program.

Based on Neste Oil’s publicly announced business plans, it is reasonable to project that up to 203 

million gallons of palm oil based renewable diesel could be sold in the United States in 2022. 

There would be strong incentives for Neste Oil to exploit the United States market if NExBTL

were to be qualified for biomass-based diesel or advanced biofuel RINs under the RFS2 

program. 210 million gallons per year of supply to the United States is a reasonable projection

based on Neste Oil’s plans to primarily use the 270 Mgy plant in Singapore to ship NExBTL to 

the United States. To produce 203 million gallons of renewable diesel the Singapore plant, 

which is located in the world’s largest palm oil producing region, would need to derive 

approximately 80% of its feedstocks from palm oil. 

Thus, an incremental volume change of 414 million gallons of palm oil based biofuel by 2022, 

representing the projected volumes of 210 million gallons of palm oil biodiesel, plus 203 million 

gallons of palm oil based renewable diesel, provides a reasonable estimate of the incremental 

increase in palm oil biofuel production in 2022 for purposes of our modeling effort.24 

While we described above the market demand potential for palm oil biofuels, there must also be 

enough supply of palm oil feedstocks to actually produce the volumes demanded. The following 

sections evaluate the factors that influence the volume of crude palm oil available and show that, 

given these factors, it is reasonable to assume 414 million gallons of palm oil based biofuel by 

2022.

Potential Feedstock Availability and Uses: Palm oil is primarily used for food, with the 

remainder used for industrial purposes, e.g., biodiesel, consumer products (USDA-FAS 2007). 

As noted, about 33 million gallons of palm oil biodiesel was supplied to the United States in 

2009. World production of palm oil in 2009 was approximately 45 million metric tons, or 

roughly 99 billion pounds. Assuming a conversion yield of 7.6 pounds of palm oil per gallon of 

biodiesel about 250 million pounds of palm oil would have been needed to produce 33 million 

gallons of palm oil biodiesel. This amount is only about 0.25% of world palm oil production. 

Thus, the amount of palm oil based biofuel used in the United States is not limited by world 

palm oil supplies. Instead, the limiting factors include the demand for palm oil for food and the 

relative economics and chemical properties of palm oil as a biofuel feedstock as compared to 

other feedstock options. As discussed above, considering the relative prices of palm oil and the 

characteristics of palm oil as a biofuel feedstock, we believe 414 million gallons of palm oilbased biofuel is a reasonable incremental volume for the purposes of our modeling.

Increased Crop Yield and Acreage: The agricultural models used in our analysis project 

increased palm oil yields over time based on historical trends. (Refer to the section on yields 

above for more information). Increased yields allow for greater volumes of palm oil to be 

produced per a given amount of area. In addition, the models also project expansion of total 

palm oil crop acreage (See Figure II-8). While not all of this expanded acreage may be eligible 

to grow feedstocks for renewable fuel production that are consistent with the Clean Air Act 

definition of “renewable biomass,” it is noteworthy that this expansion alone, including yield 

 

24 The total volumes do not sum properly due to rounding error.
growth, has the potential to add far more than the amount of crude palm oil that would be 

required to make 414 million gallons of palm oil based biofuel by 2022.

Figure II-8. Projected Oil Palm Harvested Area (thousand hectares)25

In the absence of additional demand for palm oil biofuel to contribute to the RFS volumes, the 

global palm oil production is projected to reach 65 million metric tons in 2022.26 Producing 414

million gallons of palm oil biofuel would require about 1.46 million metric tons of crude palm 

oil, or about 2.25% of global palm oil supplies in 2022. This percentage would be even lower if 

total palm oil production expands in order to meet any additional demand for palm oil biofuel in 

the United States. Based on the analysis summarized above, it is likely that global palm oil 

production would be adequate to supply 414 million gallons of palm oil based biofuel to the 

United States in 2022. 

Therefore, our evaluation of existing palm oil production and the projected increase in 

production from improving yields and expanded acres supports a conclusion that an incremental 

volume of 414 million gallons of palm oil biofuel by 2022 is a reasonably attainable estimate for 

modeling purposes. We have discussed this volume assumption with industry and USDA 

representatives, and they have agreed that this assumption is reasonable.

III. References

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25 FAPRI-CARD Model, Control Case for the RFS2 final rule

26 Ibid.

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