December 12 , 2011

MEMORANDUM TO: Air and Radiation Docket EPA

- HQ

- OAR

- 201 1

- 0 542 SUBJECT: Summary of Modeling Input s 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 input s and assumptions used for modeling the lifecy cle greenhouse gas (GHG) emissions associated with specified palm oil biodiesel and palm oil renewable diesel fuel production pathway s . Assumptions include crop y ields, energy use, energy

source s, fertilizer use, co - product production , and other important factors used in the lifecy cle anal ys is. Outline of this Document:
I. Sy stem 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 Scenario s III. References**I. System Boundaries**

The general s ys tem boundaries for lifecy cle GHG anal ys is of biofuels under the RFS program were determined as part of the March 26, 2010 final rule (EPA 2010). Apply ing these s ys tem boundaries to our analy sis of palm oil

- based biodiesel and renewable diesel was straightforward because the lifecy cle sy stems for the palm oil biofuels anal yz ed are similar to those of other biofuels that were anal yz ed in EPA (2010). Figure I

- 1 provides a simplified diagram of the palm oil biofuel lifecy cle

. 1 Our lifecy cle anal ys is considers the full fuel lifecy cle, including palm oil cultivation, feedstock transpor t, oil extraction and processing, biofuel production, fuel transport and distribution, and fuel use. At each stage co

- products are accounted for through s ys tem expansion or energy allocation. 2

**Figure I**
**- 1. Simplified Palm Oil**  **Biofuel Lifecycle System Diag**  **ram**

This document focuses on our assumptions related to the various stages in the palm oil biofuel lifecy cle, 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 treatm ent 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 Displacmentmarkets that was used for the final RFS2 rule: the Food and Agricultural Policy and Research Institute international models as maintained b y 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 y ield trends for palm oil and the volume scenarios considered. Both of t hese factors in our anal ys is are discussed below.

**I I.**  **Data and Assumptions**  This section includes a summary of key assumptions and data inputs used in our lifecy cle GHG assessment of palm oil

- based biofuels. As discussed in the EPA (2011) , our anal ys is focuses on palm oil production in I ndonesia and Malay sia. In this document, assumptions for palm oil production in other regions are commonl y aggregated into a “rest of world” category

. Our anal ys is considers direct and significant indirec t emissions related to the production and use of palm oil

- based biofuels. As such, we also consider ed GHG emissions impacts related to the production and use of other agricultural commodities (e.g., so ybeans, rapeseed, beef, poultry) that are indirectly

i mpacted by

an increase in palm oil

- based b iofuel production and use. For information on the data inputs and assumptions used to evaluate these other aspects of our anal ys is refer to the Regulatory I mpact Analy sis for the RFS2 final rule (EPA 2010a)

. Tabl e I

- 1 includes a list of acron yms 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 y ield trends are based on projections included in the FAPRI

- CARD model

. The FAPRI

CARD model uses historical data published in the USDA’s online P roduction, S upply and D istribution (PS&D) database 3 as well as data from Global Agricultural Information Network (GAIN) Reports published by USDA

- F AS. 4
**Table I**
**- 2.**  **Palm Oil Cultivation**  **Assumptions**

3 http://www.fas.usda.gov/psdonline/ 4 http://gain.fas.usda.gov/**Item Geographic Region**  **Assu mption**  **Units Source** 

Crop yield (2008) Indonesia 4.38 tCPO/ha FAPRI

- CAR D

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 g al/ h a/y r 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 y ields in Malay sia 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 y ield in Malay sia a s a n extension of the histor ical data trend forward to 2022. This is the yield project ion marked “EPA” in Figure II

- 2 and it is used in our analy sis. It is based on the same general approach as used for all of the crops in the RFS2 final rule anal ys is (EPA 2010a, Section 5.1.3 )

. Additionally , t he Malay sian Palm Oil Board (MPOB) provided us with data on palm oil y ields in 2009 and assumptions regarding projected replanting, expansion and clonal varieties (MPOB 2010) . As a check on the FAPRI

- CARD y ield proje ctions w e used the data provided in MPOB (2010) to d erive 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 yi elds in 2022, but the projection s in the interim years are different. The EPA projection grows at a linear rate of 0 .05 tCPO/ha/y r. In contrast, the projecti on based on MPOB data shows y ield declining for several ye ars before increasing after about 2013

. Yields could stagnate for several ye ars if growers delay replanting old plantations with new cultivars , perhaps in response to high vegetable oil prices or o ther reasons (USDA

- FAS 2011). Eventuall y, though, it will be in the economic interest of growers to replant with higher yielding cultivars. Since our anal ys is focuses on projecting impacts in 2022, the fact that both forecasts project the same average yi e lds in Ma lay sia in 2022 ( 5.0 tCPO/ha ) supports the robustness of our y ield 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 ( Hist or ical) Lin ea r (Yield ( Hist or ical))

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
EP A EP

A w/ MP OB da ta2. 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/y r . The trend line marked “EPA” in Figure 4 is the Indonesian pal m oil y ield projection used in our analy sis

. This projection is based on the same approach as used for all crops in the RFS2 final rule anal ys is (EPA 2010a, Section 5.1.3)

.

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

**Figure 4. Projecte**  **d Indonesian Palm Oil Yields (**  **tCPO/ha)**

5 The historical data w as 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**t o** **n n** **e s** **/ h** **e c** **t a** **r e** 

Yield ( Hist or ical) Lin ear (Yield ( His tor ical))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 lite rature and found that diesel use range s from 14

- 32 gal/ha/y r (RSPO). 6 After reviewing several data sources, Schmidt assumed average diesel use of 15.4 gal/ha/y r. Most recentl y, Unnasch et al. assumed diesel use of 18.5 gal/ha/ yr in their lifecycle asse ssment of palm oil biodiesel. Our anal ys is adopt s 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 anal ys is are based on data from the International Fertilizer Association (Heffer), as shown in are included in Table I

- 2. Our ass umptions fall within the range of values found in the literature for ty pical fertilizer application rates

. For example, (RSPO 2009) finds a range of nitrogen application rates ranging from 88.2 to 100 kg N/ha/y r, phosphorous application rates in the range of 28

- 45 kg P 2 O 5 /ha/y r, and potassium applications rates commonly between 172

- 252 kg K 2 O/ha/y r
. Based on MPOB survey data Unnasch et al. assumes 69.8 kg N/ha/ yr , 56 kg P 2 O 5 /ha/y r and 230 kg K 2 O/ha/y

r. Based on a literature review of data for mature plan tations Schmidt assumes 106 kg N/ha/y r, 73 kg P 2 O 5 /ha/y r and 210 kg K 2 O/ha/y

r. The onl y value used in our anal ys is that appears to fall outside of ty

pical ranges found in the literature is the potassium application rate in Indonesia (99 kg K 2 O/ha/ yr), whi ch is lower than the values cited above. We conducted sensitivity anal ys is on this value and found that increasing the Indonesian potassium application rate to 250 kg K 2 O/ha/y r would increase lifecy cle GHG emissions by less than 0.2% for palm oil

- based bi odiesel 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
EP APalm oil plantations use herbicides and pesticides to enhance crop performance. The most

commonly

used herbicide in Malay sia is gl yphosate (Unnasch et al.). Pesticide applications rates in our anal ys is are based on FAO data and shown in Table I

- 2

. The application rates assumed in our anal ys is 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 pes ticide and herbicide use at palm oil plantations represent a very small share of total lifecy cle 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 anal ys is. 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 anal ys is of palm oil mill operations is based on average practices in Indonesia and Malay sia.
**Table I**
**- 3.**  **Palm Oil Mill Assumptions**  **Item Assumpt**  **ion Units**  **Source** CPO yi eld 5.00 tFFb/tCPO Various sources including Schmidt and Subramaniam et al. PK y ield 0.27 tPK/tCPO Schmidt Biomass use for heat & power 2.62 mmBtu/tCPO Purchased electricit y Electricity generated onsite from oil palm biomass Various sources including Schmidt and Unnasch et al. Diesel use 1.18 g al / tCPO Subramaniam et al. POME y ield 3.00 tPOME/tCPO POME methane yi eld 18.22 m 3 CH 4 /tPOME We consulted a range of sources regarding CPO yields. Based on a survey of 12 Malaysian palm oil mills Subramaniam reports average yi eld of 5.07 tFFB/tCPO. 7 Schmidt reports CPO y ie ld of 5.01 tFFB/tCPO based on an average of national figures published b y the MPOB in 2005 and 2006. We also considered historic al 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 ass ume that CPO y ield 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 Oi l 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 9/1/2010The y ield of palm kernel co

- product is from Schmidt base d on Malay sian 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 oi l mills to purchase electricity from the grid. Our analy sis 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 amoun t of POME and POME methane generated per tonne of CPO produced at palm oil mills. We assume POME y ield of 0.6 tPOME/tFFB . Our assumption is based on the average of POME y ield found in Subramaniam’s survey of 12 M alay sian palm oil mills

. This is within t he range of values found in other relevant studies. For example , Schmidt assume s 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 Malay sian mill. Based o n the survey

of Malay sian palm oil mills cited above, we assume that on average 18.2 cubic meters of methane i s generated per tonne of POME ( m 3 CH 4 /tPOME). This is within the range of values estimated in the literature. For comparison, Schmidt also assum es 18.20 m 3 CH 4 /tPOME and Yacob et al. assumes 9 m 3 CH 4 /tPOME

. RSPO reviewed a variet y of studies and found that most estimate POME methane emissions of close to 18 m 3 CH 4 /tPOME . The one exception was Yacob et al. According to RSPO the low value estimate d by Yacob et al. can most likely be at tributed to the specific lay out of the treatment sy stem monitored. Although methane formation can vary

depending on the conditions at different water tr eatment facilities we have taken an industry

average approach in our anal ys is by rely ing on the average from the survey by Subramaniam which considers 12 mills in different geographic locations across Malay sia. As discussed in Section II.A.5 of the NODA preamble, our anal ys is acco unts f or industry average POME methane treatment practices at palm oil mills in Malay sia and I ndonesia. 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 2006II

- 4 summarizes data on POME treatment in Malay sia based on an MPOB industry survey (MPOB 2011).

**Table II**
**- 4.**  **Prevalence of POME Methane Capture in M**  **alaysia 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 onl y 29 Electricity

generation only 24 Steam Only 4 Combined heat and power 15 *I ncludes mills with POME methane capture projects under construction According to the Indonesian Palm Oil Board (I POB), there are currentl y 608 palm oil mils in I ndonesia. 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 electr icit y. 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 * In cludes mills with POME methane capture projects under construction Table II

- 6 summarizes key assumptions used in our anal ys is regarding POME methane capture and use. Our assessment uses the default biogas capture and use efficiencies speci fied 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 ourreview of relevant literature this is the most defensible assumption for our industry average anal ys is. For comparison, Schmidt assumes 92.2% methane capture based on a CDM project design form submitted for a single palm oil mill in I ndone sia. 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 effici encies ranging from 95% to 100%. We consider these capture efficiencies to be too high for industry average practices in Indonesia and Malay sia wh ere 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 undigeste d POME that leaves the s ys tem. As discussed above (Table II

- 4 and Table II

- 5) we assume that 27% of the mills that capture methane flare it onsite. Our anal ys is assumes that these facilities use enclosed flares with 90% methane destruction efficiency . This is based on the default assumption for enclosed flares in t he 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

averag e flare efficiency

is the most reasonable assumption for the purposes of our anal ys is. Because onl y 3% of palm oil mills are assumed to capture and flare methane, the conclusions drawn from our anal ys is are not very sensitive to assumed flare efficiencies

. We assume that 7% of palm oil mills capture and use methane to generate electricit y (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 us ing 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 ty

pical 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 ty pical 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 do cuments for CDM projects 2542, 2612, 3702, 2659, 2620 and 2644. 10 U.S. Environ mental Protection Agency (EPA). Em ission Reductions and Environmental and Energy Benefits for Landfill Gas Projects. Landfill Methane outreach Program, http://www.epa.gov/lmop/projects

- candidates/lfge

calculator.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 anal ys is of lifecy cle 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 ar e taken from the RFS2 final rule anal ys is (EPA 2010). Assumptions regarding the hy drotreating process to produce renewable diesel are based on Pearlson. For further details, t he lifecy cle anal ys is results spreadsheet available through the public d ocket i ncludes our calculations of lifecy cle GHG emissions associated with the conversion of crude palm oil into biodiesel and renewable diesel.
D. Feedstock and Fuel Transport Lifecy cle GHG emissions associated with feedstock and fuel transport are also includ ed in our anal ys is. Our analy sis of palm oil

- based biodiesel is based on a scenario in which palm oil is grown in Malay sia

. 11 The palm oil fruit is transported via heav y dut y truck s to the closest palm oil mill . Some of the trucks return with EFB for fiel d application and the rest are assumed to operate with empt y back haul. CPO is then trucked from the palm oil mill to a biodiesel production facilit y 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 scenari o 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 c alculated using factors from GRE ET. 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* * I ncludes empt y back haul

11 We assume that transport modes and distances w ould be similar for a scenario based in Indonesia.Similar to biodiesel, o ur anal ys is of palm oil

- based renewable diesel is based on a scenario in

which palm oil is grown in Malay sia. 12 The palm oil fruit is transported via heavy du ty 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 f acility in Singapore. Renewable diesel is subsequently ship ped 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 renewa

ble 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 Tra**  **nsport 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* * I ncludes empt y back haul
E

. Biofuel Use Tailpipe emissions associated with biodiesel use were estimate in the RFS2 final rule. As in the RFS2 rule, this analy sis 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 trans

esterification 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 biodiese l would result in a small change to the lifecy cle GHG emissions for biodiesel. Based on our modeling of the trans

- esterification process in the RFS2 final rule we estimate that the lifecy cle GHG emissions from combustion of biodiesel made with fossil meth anol rather than methanol derived from biomass would include approximately 4 k g of additional carbon dioxide

equivalent (CO2e) emissions per mmBtu of biodiesel. If we included the additional GHG emissions associated with the use of fossil methanol in biod iesel production in our lifecy cle GHG assessment of palm oil biodiesel it would not aff ect our threshold determinations for palm oil biodiesel . The emissions factor used for biodiesel use was also applied to renewable diesel in this analy sis.
**Table II**
**- 9.**  **Biodiesel Tailpipe Emissions**  **Item Assumption**  **Units Source**  CH 4 emissions 11 g/mmBtu biodiesel EPA (2010) N 2 O emissions 689

12 We assume that tra nsport modes and distances w ould be similar for a scenario based in Indonesia.CO 2 emission s 79,837

GHG emissions 80,537 gCO 2 e/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 lifecy cle GHG anal ys is

. (See Section I.A.3 of the NODA for more background regarding the s cenarios 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 ap proximately 1.46 million tonnes of CPO used as feedstock to produce palm oil

- based biofuels. For the purposes of our modeling we assume t hat exactly

half of this CPO volume is used to produce biodiesel and half is used to produce renewable diesel fuels vi a a h ydrotreating process. Based on the assumed y ields 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 rene wable 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 yi eld from a t yp ical h ydrotreating process maximized for diesel fuel prod uction 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 increa ses in crop acreage, and potential increases in crop y ields. 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 biofue l under the RFS program. 14
Historical Palm Oil Biodiesel Production and Imports to the United States : According to information provided b y Wilmar In ternational L td. (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 * I mports unknown for 2005 ** I mports 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, 2010To 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 fr om 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) ** I mports include re

- exports It must be noted that a large portion of the increase in palm oil biodiesel imports in 2007 and 200 8 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 biod iesel 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 ye ars 2006

- 2008 (EIA)

. The Emergency Economic Stabilization Act of 2008 (EESA) closed the loophole beginning on January 1, 2009. T herefore, we focus ed on the data from 2009 to gu ide our as sessment because it represents palm oil biodiesel supplies under more normal market conditions.
We use d our understanding of historical market share from palm oil biodiesel to help project future volumes. The Clean Air Act requires that, at a m inimum, the biomass

- based diesel standard require the use of 1 billion gallons per year in 2013 and bey ond. 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 coul d be possible from all feedstocks in 2022. If we assume tha t 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 that 100 million gallons of palm oil biodiesel could be sold or distributed in the Unite d States in 2022. We bel ieve 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 F ig ure 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**  **. Histori cal Crude Palm Oil Production (Thousand T**  **onnes) 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 soy bean oil. Recently , soy

bean oil has commanded a significant price premium over palm oil, ranging from approximately 10% to 30%. See Figure II

- 7 for th e percentage price premium for so yb ean oil compared to palm oil in recent ye ars. 19 **Figure II** 
**- 7**  **. Price Premium for Edible Soy bean Oil Compared to Palm Oil (P**  **ercent)**

18 FAPRI

- CARD model 19 Based on data from the FAPRI

- CARD model. FOB export prices at Rotterdam were used for soybean oil. CIF im port pr ices 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 50,00019801981198219831984198519861987198819891990199119921993199419951996199719981999200020012002200320042005200620072008 Indi a Indone si a Malay si a Res t of Wo rldBased solely on the price of palm oil versus soy bean oil we might expect palm o il to capture a majority share in the United State biodiesel market. However, the utilization of palm oil biodiesel in the U nited S tates is l imited to some degree because palm

- oil based biodiesel has a high cloud point which diminishes its value in colder climates. 20 Inthe European Union the cloud point limitations have been minimized through industry practices which maximize the use of palm oil feedstocks during warmer seasons. For exa mple, in the United Kingdom, palm oil biodiesel accounted for 12% of biodie sel consumption from April 2008 to April 2009, and 10% of b iodiesel 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 prac tices similar to their European counterparts, which would enable the United States to use a much larger volume of palm oil biodiesel . I ndeed, 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 U nited S tates biodiesel market in 2022 , especiall y if palm oil biodi esel 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 low est tem perature 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 A gency. Renewable Transportation Fuel Obligation (RTFO) Reports. http://www.renewablefuelsagency.gov.uk/carbon

- and

- sustainability/rtfo

- reports , accessed September 1 5, 2010 0% 5% 10% 15% 20% 25% 30% 35%

2005 2006 2007 2008Potential 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 highl y 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 renewa ble diesel is chemicall y ver y similar to petroleum

based 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 assu med that the fe edstocks 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 primaril y 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 co uld 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 volu me 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 scenario s for the RFS2 final ru le. Neste Oil produces a rene wable diesel fuel called NExBTL which can be produced from a range of edible and non

- edible oil feedstocks. Neste Oil currentl y produces NExBTL at facilities in Porvoo, Finland with production capacity of 100 million gallons per year (Mgy) and a recentl y opened plant in Singapore with capacity of 270 Mgy . They

are currentl y cl ose to completing another facility in Rotterdam, also with a capacit y of 270 Mgy. Neste Oil is also study ing the feasibility of an additional productio n facility to be based in United States

. 22 EPA is not aware of an y other companies that are planning to produce renewable diesel from palm oil for dis tribution in the United States. According to Neste Oil, the facilit y in Finland primarily uses palm oil a s a feedstock and ships its end product to Europe . The Rotterdam facility would also primarily

serve the large European demand f or diesel fuel. Neste Oil sees an opportunity to use the facility in Singapore to convert palm oil into NExBTLfor export to t he 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 roughl y 20% of their feedstocks from an imal fats and fish oils, and they are researching the use of algae, jatropha and other microbes. 23 D ue to uncertainty about the availability

of non

- edible oil feedstocks, however, it currentl y 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 ar e researched, http://www.nesteoil.com/default.asp?path=1,41,11991,12243,12139 , accessed September 20, 2010feedstock 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 reas onable to project that up to 2 03 million gallons of palm oil based r enewable diesel could be sold in the U nited 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 y ear of suppl y to the United States is a reasonable projection based on Neste Oil’s plans to primarily use the 270 Mgy

plant in Singapor e to ship NExBTLto the United States. To produce 2 03 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.
T hus, an incremental volume change of 4 14 million gallons of palm oil based biofuel by 2022, represent ing the projected volumes of 2 10 million gallons of palm oil biodiesel , plus 2 03 million gallons of palm oil based renewable diesel, provide s 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 suppl y of palm oil feedstocks to actu ally 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 4 14 million gallons of palm oil based biofuel b y 2022.
Pot ential Feedstock Availability and Uses: Palm oil is primarily used for food, with the remainder used for industrial purposes , e.g., bio diesel, 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 roughl y 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 h ave 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. I nstead, t he 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 4 14 million gallons of palm oil

based biofuel is a reasonable incremental volume for the purposes of our modeling. Increased Crop Yield and Acreage: The agricultural models used in our analy sis project increased palm oil y ields over time based on historical trends. ( Refer to the section on y ields above for more information ) . Increased yi elds allow for greater volumes of palm oil to be produced per a given amount of area. I n 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 r enewable fuel production that are consistent with the Clean Air Act definition of “renewable biomass,” it is noteworthy that this expansion alone , including yi eld

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

required to make 4 14 million gallons of palm oil based biofuel b y 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 m illion metric tons in 2022. 26 Producing 4 14 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 produ ct ion expands in order to meet any additional demand for palm oil biofuel in the United States . Based on the anal ys is summarized above, it is likely that global palm oil production would be adequate to supply 4 14 million gallons of p alm 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 yi elds 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. Referen**  **ces** California Climate Action Registry (CCAR). 2008. L ivestock Project Reporting Protocol: Capturing and destro yi ng methane from manure management s ys tems, Version 2.1, August, 2008

25 FAPRI

- CARD Model, Control Case for the RFS2 final rule 26 Ibid. -

2, 000 4, 000 6, 000 8, 000 10, 000 12, 000 14, 000 16, 000 18, 000 In done si a Malay si a Re st of W or ldCarbon Partners Asiatica (CPA). 2010. CDM Monitoring Reporting: Srijaroe n Palm Oil

Wastewater Treatment Project in Krabi Province, Thailand. UNFCCC Project Registered No. 2620. Monitoring Report No. 01 (Version 1.1). June 22, 2010. Clean Development Mechanism (CDM) Executive Board. Indicative simplified baseline and monitorin g methodologies for selected small

- scale CDM project activity categories: Methane recovery in wastewater treatment. UNFCCC/CCNUCC. III.H/Version 16 Energy I nformation Agency

(EIA). 2009. Short

- Term Energy Outlook Supplement: Biodiesel Supply and Consumpt ion in the Short

- Term Energy Outlook. U.S. Department of Energy . April 2009 Embassy of Indonesia. 2011. Email communication from Dr. Achmad Rachman, Agricultural Attaché, Embass y of Indonesia. May 31, 2011. Food and Agriculture Organization (FAO). 2009. FAOStat. Pesticide consumption. Retrieved from http://faostat.fao.org/site/424/default.aspx#ancor on 9/15/09 Food and Agricultural Policy and Research Institute international models as maintained by the Center for Agricultural and Rural Development at I ow a State University (FAPR

- CARD) Staff. 2010. Technical Report: An Anal ys is of EPA Renewable Fuel Scenarios with the FAPRI

– CARD International Models. January , 2010. Heffer, Patrick (2009). Assessment of Fertilizer Use by Crop at the Global Level, 2006/07

– 2007/08. I nternational Fertilizer I ndustry Association. Paris, France. Indonesian Palm Oil Board (IPOB), 2010. Facts of I ndonesian Oil Palm. First Edition. December 2010. Malay sian Palm Oil Board (MPOB). 2011. Report on Biogas Capture at Palm Oil Mills. April 28, 2011 Malay sian Palm Oil Board (MPOB). 2010. Additional I nformation Requested by United States Environmental Protection Agency : Agricultural Input Data: Inputs for RFS2. June 4, 2010 Pearlson, M., N. 2011. A Techno

- Economic and Environmental As sessment of Hy droprocessed Renewable Distillate Fuels. http://dspace.mit.edu/handle/1721.1/65508 Roundtable on Sustainable Palm Oil (RSPO). 2009. Greenhouse Gas Emissions from Palm Oil Production: L iterature review and proposals from the RSPO Working Grou p on Greenhouse Gases. Document prepared by Brinkman Consultancy

. Schmidt, Jannick. 2007. Life cy cle assessment of rapeseed oil and palm oil: Ph. D. thesis, Part 3: Life cy cle inventory

of rapeseed oil and palm oil. Department of Development and Planning Aalborg Universit y.Subramaniam, V., Ngan, M., A., May , C., Y., Sulaiman, N., M., N., 2008. Environmental

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- 315. Unnasch, S. S. T. Sanchez, and B. Riffel (2011) Well

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- FAS). 2011. Malay sia: Obstacles May

Reduce Future Palm Oil Production Growth. June 28, 2011. http://www.pecad.fas.usda.gov/highlights/2011/06/Malay sia/ U.S. Department of Agriculture Foreign Agricultural Service (USDA

- FAS). 2007. I ndonesia: Palm Oil Production Prospects Continue to Grow, http://www.pecad.fas.usda.gov/highlights/2007/12/I ndonesia_palmoil/ U.S. Environmental Protection Agency (EPA). 2011. Notice of Data Availability Concerning Renewable F uels Produced from Palm Oil Under the RFS Program

. U.S. Environmental Protection Agency (EPA). 2010. Regulation of Fuels and Fuel Additives: Changes to Renewable Fuel Standard Program; Final Rule. 75 FR 14670. March 26, 2010. U.S. Environmental Protectio n Agency (EPA). 2010a. Renewable Fuel Standard Program (RFS2) Regulatory

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- 2 U.S. Environmental Protection Agency (EPA). 2010c. Technical Support Document for Industrial Wastewater Treatment: Final Rule for Mandatory Reporting of Greenhouse Gases. June 2010, 6

- 3 Yaboc, Shahrakbah, et al. (2006), Baseline Study of Methane Emission from Anaerobic Ponds of Palm Oil Mill Efflu ent Treatment, Science of the Total Environment, Vol. 366 (2006), pgs 187

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