U.S. plants to date, we expect the feedstock being used there may be
made available at a lower cost than we are projecting here for yellow
grease.

 Table VII.A.2-3--Summary of Cost for Biodiesel and Renewable Diesel for
                           Policy Case in 2022
                                 [2007$]
------------------------------------------------------------------------
                                                               Fuel
             Fuel/feedstock                  Feedstock      production
                                           price  ($/lb)   cost  ($/gal)
------------------------------------------------------------------------
Biodiesel/soy oil.......................        0.33 \a\            2.73
Biodiesel/corn oil extraction at ethanol        0.17 \a\            1.90
 plants.................................
Biodiesel/yellow grease or other                0.23 \b\            2.43
 rendered fats..........................
Biodiesel/algae or other advanced virgin        0.58 \c\        4.52 \d\
 oil feedstock..........................
Renewable diesel/yellow grease or other         0.23 \b\            2.42
 rendered fats..........................
------------------------------------------------------------------------
\a\ Taken from outputs of FASOM model.
\b\ Derived from outputs of FASOM model, assuming 70% value of soy oil.
\c\ Derived from figures in a Technical Memo by Ryan Davis of NREL
  entitled ``Techno-economic analysis of microalgae-derived biofuel
  production'' (available in docket).
\d\ This production cost assumes this advanced feedstock has very low
  free fatty acid content.

B. Biofuel Distribution Costs

    Our analysis of the costs associated with distributing the volume
of biofuels that we project will be used under RFS2 focuses on: (1) The
capital cost of making the necessary upgrades to the fuel distribution
infrastructure system directly related to handling these fuels, and (2)
the ongoing additional freight costs associated with shipping renewable
fuels to the point where they are blended with petroleum-based
fuels.\322\ The following sections outline our estimates of the
distribution costs for the additional volumes of ethanol, cellulosic
distillate fuel, renewable diesel fuel, and biodiesel that we project
would be used in response to the RFS2 standards under the three control
scenarios that we analyzed relative to the two reference cases.\323\
---------------------------------------------------------------------------

    \322\ The anticipated ways that the renewable fuels projected to
be used in response to the EISA will be distributed is discussed in
Section IV.C. of today's preamble.
    \323\ Please refer to Section 4.2 of the RIA for additional
discussion of how these estimates were derived.
---------------------------------------------------------------------------

    A discussion of the capability of the transportation system to
accommodate the volumes of renewable fuels projected to be used under
RFS2 is contained in Section IV.C. of today's preamble and 1.6 of the
RIA. There will be ancillary costs associated with upgrading the basic
rail, marine, and road transportation nets to handle the increase in
freight volume due to the RFS2. We have not sought to quantify these
ancillary costs because (1) the growth in freight traffic that is
attributable to RFS2 represents a small fraction of the total
anticipated increase in freight tonnage (approximately 3% of rail
traffic by 2022, see Section IV.C.1), and (2) we do not believe there
is an adequate way to estimate such non-direct costs.
1. Ethanol Distribution Costs
    The capital costs to upgrade the distribution system to handle the
increased volumes of ethanol vary substantially under the three control
scenarios that we analyzed. Table VII.B.1-1 contains our estimates of
the fuel distribution infrastructure capital costs to support the use
of the additional ethanol that we project will be used under the three
use scenarios by 2022 relative to the RFS1 reference case forecast of
7.05 BGY.\324\ The total estimated capital costs under our primary case
are estimated at $7.90 billion which when amortized equates to
approximately 6 cents per gallon of the additional ethanol volume that
would be used in 2022 in response to the RFS2 standards relative to the
RFS1 reference case.\325\ Capital costs under the low-ethanol and high-
ethanol scenarios are estimated at $5.47 billion and $11.92 billion
respectively. This equates to 6 and 5 cents per gallon respectively
relative to the RFS1 reference case.
---------------------------------------------------------------------------

    \324\ See Section IV.C. of today's preamble for discussion of
the upgrades we project will be needed to the distribution system to
handle the increase in ethanol volumes under EISA. The derivation of
these estimates is discussed in Section 4.2 of the RIA.
    \325\ These capital costs will be incurred incrementally through
2022 as ethanol volumes increase. Capital costs for tank trucks were
amortized over 10 years with a 7% cost of capital. Other capital
costs were amortized over 15 years with a 7% return on capital.

   Table VII.B.1-1--Estimated Ethanol Distribution Infrastructure Capital Costs Under the RFS1 Reference Case
----------------------------------------------------------------------------------------------------------------
                                                                                Million $
                                                                 -----------------------------------------------
                                                                    Low-ethanol       Primary      High-ethanol
                                                                     scenario        scenario        scenario
----------------------------------------------------------------------------------------------------------------
Fixed Facilities:
    Marine Import Facilities....................................              49              53              63
    Marine Facilities for Shipment Inside U.S...................              98             130             186
    Unit Train Receipt Facilities...............................             444             586             838
    Manifest Rail Receipt Facilities............................              15              20              28
Petroleum Terminals:
    Terminal Storage Tanks......................................             859           1,243           2,073
    Blending & Misc. Equipment..................................           1,006           1,064           1,144
    E85 Retail..................................................           1,957           3,293           4,973
Mobile Facilities:
    Rail Cars...................................................             884           1,279           2,218
    Barges......................................................              53              77             133
    Tank Trucks.................................................             107             154             268
                                                                 -----------------------------------------------

        Total Capital Costs (Million $).........................           5,471           7,898          11,922
                                                                 -----------------------------------------------
        Total Capital Costs (cents per gallon ethanol)..........               6               6               5
----------------------------------------------------------------------------------------------------------------

    Table VII.B.1-2 contains our estimates of the fuel distribution
infrastructure costs to support the use of the additional ethanol that
we project will be used under the three use scenarios by 2022 relative
to the AEO reference case forecast of 13.18 BGY. The total estimated
capital costs under our primary case are estimated at $5.50 billion
which when amortized equates to approximately 7 cents per gallon of the
additional ethanol volume that would be used in 2022 in response to the
RFS2 standards relative to the AEO reference case. Capital costs under
the low-ethanol and high-ethanol scenarios are estimated at $3.02
billion and $9.93 billion respectively. This equates to 8 and 6 cents
per gallon respectively relative to the AEO reference case.

    Table VII.B.1-2--Estimated Ethanol Distribution Infrastructure Capital Costs Under the AEO Reference Case
----------------------------------------------------------------------------------------------------------------
                                                                                Million $
                                                                 -----------------------------------------------
                                                                    Low-ethanol       Primary      High-ethanol
                                                                     scenario        scenario        scenario
----------------------------------------------------------------------------------------------------------------
Fixed Facilities:
    Marine Import Facilities....................................              49              53              63
    Marine Facilities for Shipment Inside U.S...................              76             100             144
    Unit Train Receipt Facilities...............................             238             434             748
    Manifest Rail Receipt Facilities............................               7              12              21
Petroleum Terminals:
    Terminal Storage Tanks......................................             355             739           1,568
    Blending & Misc. Equipment..................................             345             411             503
    E85 Retail..................................................           1,526           2,863           4,893
Mobile Facilities:
    Rail Cars...................................................             309             522           1,133
    Barges......................................................              16              38              63
    Tank Trucks.................................................              68             103             194
                                                                 -----------------------------------------------
        Total Capital Costs (Million $).........................           3,025           5,505           9,935
                                                                 -----------------------------------------------
        Total Capital Costs (cents per gallon ethanol)..........               8               7               6
----------------------------------------------------------------------------------------------------------------

    We estimate that ethanol freight costs under the primary and high-
ethanol scenarios would be 13 cents per gallon on a national average
basis. Ethanol freight costs under the high-ethanol scenario are
estimated at 12 cents per gallon. These estimates are based on an
analysis conducted for EPA by Oak Ridge National Laboratory (ORNL)
which were modified to reflect projected higher transportation fuel
costs in the future, the likely installation of fewer unit train
receipt facilities than that projected by ORNL based on industry
comments, and to conform to the ethanol volumes under the three control
scenarios analyzed in today's rule.\326\ The ORNL analysis contains
detailed projections of which transportation modes and combination of
modes (e.g. unit train to barge) are best suited for delivery of
ethanol to specific markets considering ethanol source and end use
locations, the current configuration and projected evolution of the
distribution system, and cost considerations for the different
transportation modes.
---------------------------------------------------------------------------

    \326\ ``Analysis of Fuel Ethanol Transportation Activity and
Potential Distribution Constraints'', prepared for EPA by Oak Ridge
National Laboratory, March 2009. The ORNL analysis indicates that
ethanol freight costs decrease somewhat with increasing ethanol
volume. See Section 4.2 of the RIA for additional discussion of the
estimation of ethanol freight costs.
---------------------------------------------------------------------------

    Summing the freight and capital costs estimates results in an
estimate of 19 cents per gallon for ethanol distribution costs for our
primary and low-ethanol scenarios under the RFS1 reference case. Total
ethanol distribution costs under the RFS1 reference case for the high-
ethanol scenario are estimated at 17 cents per gallon. Under the AEO
reference case, total ethanol distribution costs are estimated at 21,
20, and 18 cents per gallon respectively for the low-ethanol, primary,
and high-ethanol scenarios.
    As discussed in Section IV.C. of today's preamble, ASTM
International is considering a change to specification on the minimum
ethanol content in E85 to facilitate the manufacture of E85 at
terminals which meets minimum volatility specifications using commonly-
available finished gasoline. If the current difficulties in blending
E85 to meet minimum volatility specifications can not be resolved by
lowering the minimum ethanol concentration of E85, high vapor pressure
blendstocks will need to be supplied to approximately two thirds of
petroleum terminals for blending with E85.\327\ This would necessitate
the

installation of new blending/storage equipment at petroleum terminals
and additional butane tank cars and tank trucks. The capital costs for
such facilities would be $2.2 billion, $1.4 billion, and $0.6 billion
under the high-ethanol, primary, and low-ethanol scenarios respectively
under both reference cases. By amortizing these capital costs and
adding in butane freight costs, we estimate that the need to supply
special blendstocks at terminals for E85 blending would add
approximately 1 cent per gallon to ethanol distribution costs for all
three analysis scenarios relative to the RFS1 reference case. Relative
to the AEO reference case, the additional cost would be approximately 2
cents per gallon under the primary and low-ethanol scenarios, and
approximately 1 cent per gallon under the high-ethanol scenario.
---------------------------------------------------------------------------

    \327\ If this is the case, EPA would need to reconsider its
policies regarding what blendstocks can be used at petroleum
terminals in the manufacture of E85.
---------------------------------------------------------------------------

    In the NPRM, we estimated that half of the new ethanol rail receipt
capability needed to support the use of the projected ethanol volumes
under the EISA would be installed at petroleum terminals, and half
would be installed at rail terminals. Based on input from industry and
a study conducted for us by ORNL, we now believe that all unit train
receipt facilities will be installed at new dedicated locations.\328\
This change results in the need for additional tank truck receipt
equipment at terminals and additional tank trucks to carry ethanol from
rail to petroleum terminals compared to the NPRM. However, we also
received additional input from industry on the cost of unit train
facilities which indicates that such facilities are not as costly as we
projected in the NPRM. We also increased the average E85 facility cost
relative to the NPRM to reflect the likely need for additional E85
dispensers and a larger underground storage tank to maintain sufficient
throughput per facility.\329\
---------------------------------------------------------------------------

    \328\ ``Analysis of Fuel Ethanol Transportation Activity and
Potential Distribution Constraints'', prepared for EPA by Oak Ridge
National Laboratory (ORNL), March 2009.
    \329\ This is a sensitivity case that was evaluated in the NPRM.
---------------------------------------------------------------------------

2. Cellulosic Distillate and Renewable Diesel Distribution Costs
    We chose to evaluate the distribution costs for cellulosic
distillate and renewable diesel together because the same
considerations apply to their handling in the fuel distribution system
and because the projected volume of renewable diesel fuel is relatively
small.
    Table VII.B.2-1 contains our estimates of the fuel distribution
infrastructure capital costs to support the use of the cellulosic
distillate and renewable diesel fuel that we project will be used under
the three use scenarios by 2022 under the RFS1 reference case.\330\ The
total estimated capital costs by 2022 under our primary and low-ethanol
scenarios are estimated at $1.38 billion and $2.00 billion respectively
under the RFS1 reference case.
---------------------------------------------------------------------------

    \330\ See Section IV.C. of today's preamble for discussion of
the upgrades we project will be needed to the distribution system to
handle the increase in ethanol volumes under EISA. The derivation of
these estimates is discussed in Section 1.6 of the RIA.

 Table VII.B.2-1--Estimated Cellulosic Distillate Fuel Distribution Infrastructure Capital Costs Under the RFS1
                                                 Reference Case
----------------------------------------------------------------------------------------------------------------
                                                                                Million $
                                                                 -----------------------------------------------
                                                                    Low-ethanol       Primary      High-ethanol
                                                                     scenario        scenario          case
----------------------------------------------------------------------------------------------------------------
Fixed Facilities:
    Marine Facilities for Shipment Inside US....................              87              56               -
    Unit Train Receipt Facilities...............................             394             253  ..............
    Manifest Rail Receipt Facilities............................              13               8  ..............
Petroleum Terminals:
    Terminal Storage Tanks......................................             218             154  ..............
    Blending & Misc. Equipment..................................             361             252  ..............
Mobile Facilities:
    Rail Cars...................................................             784             552  ..............
    Barges......................................................              47              33  ..............
    Tank Trucks.................................................              95  ..............  ..............
                                                                 -----------------------------------------------
        Total Capital Costs (Million $).........................           1,999           1,375            \NA\
                                                                 -----------------------------------------------
        Total Capital Costs (cents per gallon of cellulosic                    2               2            \NA\
         distillate fuel).......................................
----------------------------------------------------------------------------------------------------------------

    Table VII.B.2-2 contains our estimates of the infrastructure
changes and associated capital costs to support the use of the
cellulosic distillate and renewable diesel fuel that we project will be
used under the three use scenarios by 2022 under the AEO reference
case. Total capital costs are estimated at $1.02 and $1.46 billion for
the primary and low-ethanol scenarios respectively under the AEO
reference case. The difference in estimated capital costs for the two
control scenarios under the two reference scenarios is obscured by
rounding when translating these costs to a cents-per-gallon basis. When
amortized, these capital costs equate to approximately 2 cents per
gallon for both control scenarios under both reference cases.\331\
---------------------------------------------------------------------------

    \331\ These capital costs will be incurred incrementally through
2022 as ethanol volumes increase. Capital costs for tank trucks were
amortized over 10 years with a 7% cost of capital. Other capital
costs were amortized over 15 years with a 7% return on capital.

  Table VII.B.2-2--Estimated Cellulosic Distillate Fuel Distribution Infrastructure Capital Costs Under the AEO
                                                 Reference Case
----------------------------------------------------------------------------------------------------------------
                                                                                Million $
                                                                 -----------------------------------------------
                                                                    Low-ethanol       Primary      High-ethanol
                                                                     scenario        scenario          case
----------------------------------------------------------------------------------------------------------------
Fixed Facilities:
    Marine Facilities for Shipment Inside US....................              67              43  ..............
    Unit Train Receipt Facilities...............................             511             315  ..............
    Manifest Rail Receipt Facilities............................              15               9  ..............
Petroleum Terminals:
    Terminal Storage Tanks......................................             218             154  ..............
    Blending & Misc. Equipment..................................             304             223  ..............
Mobile Facilities:
    Rail Cars...................................................             784             552  ..............
    Barges......................................................              47              33  ..............
    Tank Trucks.................................................              90              63  ..............
                                                                 -----------------------------------------------
        Total Capital Costs (Million $).........................           2,036           1,392              NA
                                                                 -----------------------------------------------
Total Capital Costs (cents per gallon of cellulosic distillate                 2               2              NA
 fuel)..........................................................
----------------------------------------------------------------------------------------------------------------

    We estimate that cellulosic distillate freight costs would be 13
cents per gallon on a national average basis under both the primary and
low-ethanol scenarios. This estimate is based on the application to
cellulosic distillate freight costs of an analysis conducted for EPA by
Oak Ridge National Laboratory (ORNL) of ethanol freight costs.\332\ The
underlying premise is that both ethanol and cellulosic distillate fuel
would be handled by the same types of distribution facilities on the
journey to petroleum terminals.\333\ Summing the freight and capital
costs results in an estimated 15 cents per gallon in total distribution
costs for both the primary and low-ethanol scenarios under both
reference cases.
---------------------------------------------------------------------------

    \332\ ``Analysis of Fuel Ethanol Transportation Activity and
Potential Distribution Constraints'', prepared for EPA by Oak Ridge
National Laboratory, March 2009. See Section 4.2 of the RIA for
additional discussion of the estimation of cellulosic distillate
freight costs.
    \333\ The same unit train and manifest rail receipt facilities
would be used to handle shipments of both fuels.
---------------------------------------------------------------------------

    The ethanol and cellulosic distillate distribution cost estimates
are based on the projections of the location of biofuel production
facilities and end use areas contained in the NPRM. The extent to which
new biofuel production facilities are more dispersed than projected in
the NPRM, distribution costs for ethanol from new production facilities
and for all cellulosic distillate facilities may tend be lower than
those projected by this analysis as the fuel has more opportunity to be
used locally. This would potentially be a greater benefit in lowering
cellulosic distillate distribution costs than overall ethanol
distribution costs given the large number of ethanol production
facilities currently located in the Midwest. Cellulosic distillate
costs should also tend to be lower than those for ethanol because
cellulosic distillate fuel blends are compatible with existing
petroleum distribution equipment, whereas there are special
considerations associated with the distribution of ethanol. The most
notable of these considerations is the need for special fuel retail
equipment for E85 (as evidenced in Table VII.B.1-1). Thus, the
cellulosic distillate distribution costs estimated here are likely to
be conservative.
3. Biodiesel Distribution Costs
    Table VII.B.3-1 contains our estimates of the infrastructure
changes and associated capital costs to support the use of the
additional biodiesel that we project will be used under RFS2 by 2022
relative to the RFS reference case of 300 MGY by 2022.\334\ The total
capital costs are estimated at $1.2 billion which equates to
approximately 10 cents per gallon of additional biodiesel volume.\335\
---------------------------------------------------------------------------

    \334\ We project that by 2022 300 MGY of biodiesel would be used
under the RFS1 reference case, 380 MGY of biodiesel would be used
under the RFS reference case and that a total of 1.67 BGY of
biodiesel would be used under the EISA. Biodiesel use is projected
to be the same under all three of analysis scenarios.
    \335\ These capital costs will be incurred incrementally through
2022 as biodiesel volumes increase. Capital costs for tank trucks
were amortized over 10 years with a 7% cost of capital. Other
capital costs were amortized over 15 years with a 7% return on
capital.

Table VII.B.3-1--Estimated Biodiesel Distribution Infrastructure Capital
                   Costs Under the RFS1 Reference Case
------------------------------------------------------------------------
                                                               Million $
------------------------------------------------------------------------
Fixed Facilities:
Petroleum Terminals:
  Storage Tanks.............................................         411
  Blending & Misc. Equipment................................         612
Mobile Facilities:
  Rail Cars.................................................         111
  Barges....................................................          53
  Tank Trucks...............................................          25
                                                             -----------
    Total Capital Costs (Million $).........................       1,212
                                                             -----------
Total Capital Costs (cents per gallon of biodiesel).........          10
------------------------------------------------------------------------

    Table VII.B.3-2 contains our estimates of the infrastructure
changes and associated capital costs to support the use of the
additional biodiesel that we project will be used under RFS2 by 2022
relative to the AEO reference case of 380 MGY. The total capital costs
are estimated at $1.1 billion which equates to approximately 10 cents
per gallon of additional biodiesel volume.

Table VII.B.3-2--Estimated Biodiesel Distribution Infrastructure Capital
                   Costs Under the AEO Reference Case
------------------------------------------------------------------------
                                                               Million $
------------------------------------------------------------------------
Fixed Facilities:
Petroleum Terminals:
  Storage Tanks.............................................         387
  Blending & Misc. Equipment................................         576
Mobile Facilities:
  Rail Cars.................................................         105
  Barges....................................................          50

  Tank Trucks...............................................          24
                                                             -----------
    Total Capital Costs (Million $).........................       1,141
                                                             -----------
Total Capital Costs (cents per gallon of biodiesel).........          10
------------------------------------------------------------------------

    We estimate that biodiesel freight costs would be 10 cents per
gallon on a national average basis. State biodiesel use requirements
and biodiesel production locations were taken into account in
formulating this estimate.\336\ The biodiesel blend ratio was estimated
to vary between 2 and 5%. Adding the estimated freight costs to the
amortized capital costs results in an estimate of total biodiesel
distribution costs of 20 cents per gallon under both the RFS1 and AEO
reference cases.
---------------------------------------------------------------------------

    \336\ See Section 4.2 of the RIA for a discussion of our
derivation of biodiesel distribution costs.
---------------------------------------------------------------------------

C. Reduced U.S. Refining Demand

    As renewable and alternative fuel use increases, the volume of
petroleum-based products, such has gasoline and diesel fuel, would
decrease. This reduction in finished refinery petroleum products
results in reduced refinery industry costs. The reduced costs would
essentially be the volume of fuel displaced multiplied by the cost for
producing the fuel. There is also a reduction in capital costs as
investment in new refinery capacity is displaced by investments in
renewable and alternative fuels capacity.
    Although we conducted refinery modeling for estimating the cost of
blending ethanol (see Section VII.B), we did not rely on the refinery
model results for estimating the volume of displaced petroleum as other
economic factors also come into play. Instead we conducted an energy
balance around the increased use of renewable fuels, estimating the
energy-equivalent volume of gasoline or diesel fuel displaced. This
allowed us to more easily apply our best estimates for how much of the
petroleum would displace imports of finished products versus crude oil
for our energy security analysis which is discussed in Section VIII.B
of this preamble.
    As part of this petroleum displacement analysis, we accounted for
the change in petroleum demanded by upstream processes related to
additional production of the renewable fuels as well as reduced
production of petroleum fuels. For example, growing corn used for
ethanol production requires the use of diesel fuel in tractors, which
reduces the volume of petroleum displaced by the ethanol. Similarly,
the refining of crude oil uses by-product hydrocarbons for heating
within the refinery, therefore the overall effect of reduced gasoline
and diesel fuel consumption is actually greater because of the
additional upstream effect. We used the lifecycle petroleum demand
estimates provided for in the GREET model to account for the upstream
consumption of petroleum for each of the renewable and alternative
fuels, as well as for gasoline and diesel fuel. Although there may be
some renewable fuel used for upstream energy, we assumed that this
entire volume is petroleum because the volume of renewable and
alternative fuels is fixed by the RFS2 standard.
    We assumed that a portion of the gasoline displaced by ethanol
would have been produced from domestic refineries causing reduced
demand from U.S. refineries, while the rest of the additional ethanol
displaces imported gasoline or gasoline blendstocks which does not
affect domestic refining sector costs. To estimate the portion of new
ethanol which displaces U.S. refinery production we relied on some
Markal refinery modeling conducted for us by DOE. The Markal refinery
model models all the refinery sectors of the world and thus can do a
fair job estimating how renewable fuels would impact imports of
finished gasoline and gasoline blendstocks. The Markal refinery model
estimated that \2/3\rds of a reduction in petroleum gasoline demand
would be met by a reduction in imported gasoline or gasoline
blendstocks, while the other \1/3\rd would be met by reduced refining
production by the U.S. refining sector. In the case of biodiesel and
renewable diesel, all of it is presumed to offset domestic diesel fuel
production. For ethanol, biodiesel and renewable diesel, the amount of
petroleum fuel displaced is estimated based on the relative energy
contents of the renewable fuels to the fuels which they are displacing.
The savings due to lower imported gasoline and diesel fuel is accounted
for in the energy security analysis contained in Section VIII.B.
    For estimating the U.S. refinery industry cost reductions, we
multiplied the estimated volume of domestic gasoline and diesel fuel
displaced by the projected wholesale price for each of these fuels in
2022, which are $3.42 per gallon for gasoline, and $3.83 per gallon for
diesel fuel. For the volume of petroleum displaced upstream, we valued
it using the wholesale diesel fuel price. Table VII.C-1 shows the net
volumetric impact on the petroleum portion of gasoline and diesel fuel
demand, as well as the reduced refining industry costs for 2022.

 Table VII.C-1--Changes in U.S. Refinery Industry Volumes and Costs for Increased Renewable Fuel Volumes in 2022
                                     Relative to the AEO 2007 Reference Case
                                                 [2007 dollars]
----------------------------------------------------------------------------------------------------------------
                                                 Low ethanol case      Primary case  (mid-    High ethanol case
                                             ------------------------     ethanol case)    ---------------------
                                                                     ----------------------
                                                Bil gals     Bil $     Bil gals    Bil $     Bil gals    Bil $
----------------------------------------------------------------------------------------------------------------
Upstream:
    Petroleum...............................         0.34        1.3       0.34        1.3       0.33        1.3
End Use:
    Gasoline................................         -0.9       -3.1       -2.0       -6.8       -4.4      -15.0

    Diesel Fuel.............................        -10.1      -38.7       -7.5      -28.7       -1.3       -5.0
                                             -------------------------------------------------------------------
        Total...............................        -10.7      -40.5       -9.2      -34.2       -5.4      -18.7
----------------------------------------------------------------------------------------------------------------

    For the primary control case relative to the AEO 2007 reference
case, this analysis estimates that the increased volumes of renewable
fuel would reduce the gasoline and diesel fuel production volume of US
refineries by 9.2 billion gallons in 2022, which would reduce their raw
material purchases and production costs by $34 billion dollars.
Accounting for all the petroleum displaced (domestic and foreign), the
increased volumes of renewable fuel caused by the RFS 2 fuels program
are estimated to reduce gasoline and diesel fuel demand by 13.2 billion
gallons.

D. Total Estimated Cost Impacts

    The previous sections of this chapter presented estimates of the
cost of producing and distributing corn-based and cellulosic-based
ethanol, cellulosic diesel fuel, imported ethanol, biodiesel, and
renewable diesel. In this section, we briefly summarize the methodology
used and the results of our analysis to estimate the cost and other
implications for increased use of renewable fuels to displace gasoline
and diesel fuel. An important aspect of this analysis is refinery
modeling which primarily was used to estimate the costs of blending
ethanol into gasoline, as well as the overall refinery industry impacts
of the fuel program. A detailed discussion of how the renewable fuel
volumes affect refinery gasoline production volumes and cost is
contained in Chapter 4 of the RIA.
1. Refinery Modeling Methodology
    The refinery modeling was conducted in three distinct steps. The
first step involved the establishment of a 2004 base case which
calibrated the refinery model against 2004 volumes, gasoline quality,
and refinery capital in place. The EPA and ASTM fuel quality
constraints in effect by 2004 are imposed on the products.
    For the second step, we established two year 2022 future year
reference cases which based their energy demand off of the 2009 Annual
Energy Outlook (AEO). One of the reference cases assumes business-as-
usual demand growth from the AEO 2007 reference case discussed in
Section IV.A.1. The other utilized the RFS1 reference case. The
refinery modeling results are based on $116 per barrel crude oil prices
which are the 2022 projected prices by EIA in its 2009 AEO. We also
modeled the implementation of several new environmental programs that
will have required changes in fuel quality by 2022, including the 30
part per million (ppm) average gasoline sulfur standard, the 15 ppm cap
standards on highway and nonroad diesel fuel, the Mobile Source Air
Toxics (MSAT) 0.62 volume percent benzene standard. We also modeled the
implementation of EPAct of 2005, which by rescinding the reformulated
gasoline oxygenate standard, resulted in the discontinued use of MTBE,
and a large increase in the amount of ethanol blended into reformulated
gasoline. We also modeled the EISA Energy Bill corporate average fuel
economy (caf[eacute]) standards in the reference case because it will
be phasing-in, and affect the phase-in of the RFS2.
    The third step, or the control cases, involved the modeling of
three different possible renewable fuels volumes. The three different
volumes were designed to capture the additional use of corn ethanol and
biodiesel and a range of cellulosic ethanol and cellulosic diesel fuel
volumes. The volumes that we assessed in our analysis are summarized in
Section IV.A above.
    The price of ethanol and E85 used in the refinery modeling is a
critical determinant of the overall economics of using ethanol. Ethanol
was priced initially based on the historical average price spread
between regular grade conventional gasoline and ethanol, but then
adjusted post-modeling to reflect the projected production cost for
both corn and cellulosic-based ethanol. The refinery modeling assumed
that all ethanol added to gasoline for E10 is match-blended for octane
by refiners in the reference and control cases. For the control case,
E85 was assumed to be priced lower than gasoline to reflect its lower
energy content, longer refueling time and lower availability (see
Chapter 4 of the RIA for a detailed discussion for how we projected E85
prices). For the refinery modeling, E85 was assumed to be blended with
gasoline blendstock designed for blending with E10, and with butane to
bring the RVP of E85 up to that allowed by ASTM International standards
for E85. Thus, unlike current practices today where E85 is blended at
85% in the summer and E70 in the winter, we assumed that E85 is blended
at 85% year-round. As E85 specifications are still under consideration
by ASTM, this assumption may differ from future procedures. E85 use in
any one market is limited to levels which we estimated would reflect
the ability of FFV vehicles in the area to consume the E85 volume. Our
costs also include the incremental costs of producing flexible fuel
vehicles (FFVs) over that of conventionally fueled vehicles.
    The refinery model was provided some flexibility and also was
constrained with respect to the applicable gasoline volatility
standards for blending up E10. The refinery model allowed conventional
gasoline and most low RVP control programs to increase by 1.0 pounds
per square inch (psi) in Reid Vapor Pressure (RVP) waiver during the
summer. However, wintertime conventional gasoline was assumed to comply
with the wintertime ASTM RVP and Volume/Liquid (V/L) standards.
    The costs for producing, distributing and using biodiesel and
renewable diesel are accounted for outside the refinery modeling. Their
production and distribution costs are estimated first, compared to the
costs of producing diesel fuel, and then are added to the costs
estimated by the refinery cost model for blending the ethanol.
2. Overall Impact on Fuel Cost
    Utilizing the refinery modeling output conducted for today's final
rule, we calculated the costs for each control case, which represented
the three different renewable fuels scenarios in 2022, relative to the
AEO 2007 and RFS1 reference cases. The costs are reported separately
for blending ethanol into gasoline, as E10 and E85, and for blending
cellulosic diesel fuel, biodiesel and renewable diesel into petroleum-
based diesel fuel. These costs do not include the biofuel consumption
tax subsidies. The costs are based on 2007 dollars and the capital
costs are amortized at seven percent return on investment (ROI) before
taxes.
    Tables VII.D.2-1 and VII.D.2-2 summarize the costs for each of the
three control cases, including the aggregated total for all the fuel
changes and the per-gallon costs, relative to the AEO 2007 and RFS1
reference cases, respectively. This estimate of costs reflects the
changes in gasoline that are occurring with the expanded use of
renewable and alternative fuels. These costs include the labor, utility
and other operating costs, fixed costs and the capital costs for all
the fuel changes expected. These cost estimates do not account for the
various tax subsidies. The per-gallon costs are derived by dividing the
total costs over all U.S. gasoline and diesel fuel projected to be
consumed in 2022. These costs are only for the incremental renewable
fuel volumes beyond the volumes modeled in the two reference cases.

Table VII.D.2-1--Estimated Fuel Costs of Increased Volumes of Renewable Fuel in 2022 Incremental to the AEO 2007
                                                 Reference Case
                                       [2007 dollars, 7% ROI before taxes]
----------------------------------------------------------------------------------------------------------------
                                                                                Primary case
                                                                  Low ethanol    (mid-ethanol    High ethanol
                                                                     case            case)           case
---------------------------------------------------------------------------------------------------------------
Gasoline Impacts:
    $billion/yr...............................................           -0.67           -3.31           -5.90
    c/gal.....................................................           -0.48           -2.35           -4.08
Diesel Fuel Impacts:
    $billion/yr...............................................          -11.7            -8.5            -1.27
    c/gal.....................................................          -16.4           -12.1            -1.79
Total Impact:
    $billion/yr...............................................          -12.4           -11.8            -7.17
----------------------------------------------------------------------------------------------------------------

    Incremental to the AEO 2007 reference case, our analysis shows that
for the low ethanol case which models mostly cellulosic diesel instead
of cellulosic ethanol, the gasoline and diesel fuel costs are projected
to decrease by $0.7 billion and $11.70 billion, respectively, for a
total savings of $12.4 billion. Expressed as per-gallon costs, these
fuel changes would decrease the cost of producing gasoline and diesel
fuel by 0.5 and 16.4 cents per gallon, respectively.
    For our primary case which models a mix of cellulosic diesel fuel
and cellulosic ethanol, the gasoline and diesel fuel costs are
projected to decrease by $3.3 billion and $8.5 billion, respectively,
for a total savings of $11.8 billion. Expressed as per-gallon costs,
these fuel changes would decrease the cost of producing gasoline and
diesel fuel by 2.4 and 12.1 cents per gallon, respectively.
    For the high ethanol case where the cellulosic biofuel is
cellulosic ethanol (as in the proposal), the gasoline and diesel fuel
costs are projected to decrease by $5.9 billion and $1.3 billion,
respectively, for a total savings of $7.2 billion. Expressed as per-
gallon costs, these fuel changes would decrease the cost of producing
gasoline and diesel fuel by 4.1 and 1.8 cents per gallon, respectively.
    Crude oil prices have been very volatile over the last several
years which raises uncertainty about future crude oil prices. Because
our cost model was created to be able to assess the cost of the program
at a higher crude oil price, we can also assess the cost at other crude
oil prices. As a sensitivity, we varied crude oil prices in our model
to find the break-even (no cost) point of the RFS2 program. Using our
cost model we estimate that, for the primary control case relative to
the AEO 2007 reference case, the RFS2 program (total of gasoline and
diesel fuel costs) would break-even at a 2022 crude oil price of $88
per barrel. Thus, in 2022 if crude oil is priced lower than $88 per
barrel, the RFS2 program would cost money; if crude oil is priced
higher than $88 per barrel, the RFS2 program would result in a cost
savings.

  Table VII.D.2-2--Estimated Fuel Costs of Increased Volumes of Renewable Fuel in 2022 Incremental to the RFS1
                                                 Reference Case
                                       [2007 dollars, 7% ROI before taxes]
----------------------------------------------------------------------------------------------------------------
                                                                                Primary case
                                                                  Low ethanol    (mid-ethanol    High ethanol
                                                                     case            case)           case
---------------------------------------------------------------------------------------------------------------
Gasoline Impacts:
    $billion/yr...............................................           -3.12           -5.63           -7.79
    c/gal.....................................................           -2.24           -4.00           -5.38
Diesel Fuel Impacts:
    $billion/yr...............................................          -11.7            -8.6            -1.35
    c/gal.....................................................          -16.5           -12.1            -1.90
Total Impact:
    $billion/yr...............................................          -14.8           -14.2            -9.14
----------------------------------------------------------------------------------------------------------------

    Incremental to the RFS1 reference case, our analysis shows that for
the low ethanol case which models mostly cellulosic diesel instead of
cellulosic ethanol, the gasoline and diesel fuel costs are projected to
decrease by $3.1 billion and $11.70 billion, respectively, for a total
savings of $14.8 billion. Expressed as per-gallon costs, these fuel
changes would decrease the cost of producing gasoline and diesel fuel
by 2.4 and 16.5 cents per gallon, respectively.
    For our primary case which models a mix of cellulosic diesel fuel
and cellulosic ethanol, the gasoline and diesel fuel costs are
projected to decrease by $5.6 billion and $8.6 billion, respectively,
for a total savings of $14.2.billion. Expressed as per-gallon costs,
these fuel changes would decrease the cost of producing gasoline and
diesel fuel by 4.0 and 12.1 cents per gallon, respectively.
    For the high ethanol case where the cellulosic biofuel is
cellulosic ethanol (as in the proposal), the gasoline and diesel fuel
costs are projected to decrease by $7.8 billion and $1.4 billion,
respectively, for a total savings of $9.1 billion. Expressed as per-
gallon costs, these fuel changes would decrease the cost of producing
gasoline and diesel fuel by 5.4 and 1.9 cents per gallon, respectively.
    Both the gasoline and diesel fuel costs are negative because of the
relatively high crude oil prices estimated by EIA for the year 2022.
Given the higher projected crude oil prices and these savings, it is
difficult to quantify how

much of the increase in renewable fuels and the associated savings is
due to the RFS 2 program versus what would have happened regardless in
the marketplace. However, even with the high crude oil prices as
projected by EIA, some or perhaps even most of the investments in these
emerging renewable fuels technologies may not occur without the RFS 2
program in place. The reason for this is that investors are hesitant to
invest in emerging technologies when the threat remains for a drop in
the price of crude oil leaving their investment dollars stranded. The
RFS2 program provides certainty for investors to invest in renewable
fuel technologies.
    There are two important reasons why the diesel fuel costs are more
negative than the gasoline costs when comparing the low ethanol case
(high cellulosic diesel case) to the high ethanol case: (1) Cellulosic
ethanol costs include the costs for fuel flexible vehicles, while
vehicles using cellulosic diesel fuel are not expected to require any
vehicle modifications, hence there is no additional estimated cost, (2)
the crude oil price adjustment based on crude oil and finished gasoline
and diesel fuel price data from 2002 to 2008 increases the estimated
production cost for petroleum diesel fuel more so than for gasoline--
therefore cellulosic diesel shows a greater cost savings. If the diesel
fuel prices do not increase more than gasoline prices with higher crude
oil prices, then the significantly higher savings for renewable diesel
fuel over that for renewable ethanol would be less than that modeled
here.
    The increased use of renewable and alternative fuels would require
capital investments in corn and cellulosic ethanol plants, and
renewable diesel fuel plants. In addition to producing the fuels,
storage and distribution facilities along the whole distribution chain,
including at retail, will have to be constructed for these new fuels.
Conversely, as these renewable and alternative fuels are being
produced, they supplant gasoline and diesel fuel demand which results
in less new investments in refineries compared to business-as-usual. In
Table VII.D.2-3, we list the total incremental capital investments that
we project would be made for this RFS2 rulemaking incremental to the
RFS1 reference case (refer to Chapter 4 of the RIA for more detail).

    Table VII.D.2-3--Total Projected U.S. Capital Investments To Meet the Increased Volumes of Renewable Fuel
                          [Incremental to the AEO 2007 reference case, billion dollars]
----------------------------------------------------------------------------------------------------------------
                                                                                Primary case
           Cost type                       Plant type               Low ethanol    (mid-ethanol    High ethanol
                                                                       case            case)           case
----------------------------------------------------------------------------------------------------------------
Production Costs..............  Corn Ethanol....................             3.9             3.9             3.9
                                Cellulosic Ethanol..............               0            14.3            48.3
                                Cellulosic Diesel \a\...........            96.5            68.0               0
                                Renewable Diesel and Algae......             1.1             1.1             1.1
Distribution Costs............  All Ethanol.....................             5.6             8.2            11.9
                                Cellulosic and Renewable Diesel              2.0             1.4  ..............
                                 Fuel.
                                Biodiesel.......................             1.2             1.2             1.2
                                FFV Costs.......................             0.8             1.8             6.1
                                Refining........................           -10.7            -9.4            -4.1
                                                                 -----------------------------------------------
    Total Capital Investments.  ................................           110.4            90.5            68.4
----------------------------------------------------------------------------------------------------------------
\a\ Cellulosic diesel fuel is assumed to be produced by BTL plants which is a very capital intensive technology.
  If some or even most of this volume comes from other cellulosic diesel fuel technologies which are less
  capital intensive, the capital costs attributed to cellulosic diesel would be much lower.

    Table VII.D.2-3 shows that the total U.S. capital investments
attributed to this program ranges from $71 to $111 billion in 2022 for
the high ethanol to low ethanol cases. The capital investments made for
renewable fuels technologies are much more than the decrease in
refining industry capital investments because (1) a large part of the
decrease in petroleum gasoline supply was from reduced imports, (2)
renewable fuels technologies are more capital intensive per gallon of
fuel produced than incremental increases in gasoline and diesel fuel
production at refineries, and (3) ethanol and biodiesel require
considerable distribution and retail infrastructure investments.

VIII. Economic Impacts and Benefits

A. Agricultural and Forestry Impacts

    EPA used two principal tools to model the potential domestic and
international impacts of the RFS2 on the U.S. and global agricultural
sectors. The Forest and Agricultural Sector Optimization Model (FASOM),
developed by Professor Bruce McCarl of Texas A&M University and others,
provides detailed information on the domestic agricultural and forestry
sectors, as well as greenhouse gas impacts of renewable fuels. The Food
and Agricultural Policy Research Institute (FAPRI) at Iowa State
University and the University of Missouri-Columbia maintains a number
of econometric models that are capable of providing detailed
information on impacts on international agricultural markets from the
wider use of renewable fuels in the U.S. EPA worked directly with the
Center for Agriculture and Rural Development (CARD) at Iowa State
University to implement the FAPRI model to analyze the impacts of the
RFS2 on the global agriculture sector. Thus, this model will henceforth
be referred to as the FAPRI-CARD model.
    FASOM is a long-term economic model of the U.S. agriculture and
forestry sectors that attempts to maximize total revenues for producers
while meeting the demands of consumers. FASOM can be utilized to
estimate which crops, livestock, forest stands, and processed
agricultural and forestry products would be produced in the U.S. given
RFS2 biofuel requirements. In each model simulation, crops compete for
price sensitive inputs such as land and labor at the regional level and
the cost of these and other inputs are used to determine the price and
level of production of primary commodities (e.g., field crops,
livestock, and biofuel products). FASOM also estimates prices using
costs associated with the processing of primary commodities into
secondary products (e.g., converting livestock to meat and

dairy, crushing soybeans to soybean meal and oil, etc.). FASOM does not
capture short-term fluctuations (i.e., month-to-month, annual) in
prices and production, however, as it is designed to identify long-term
trends (i.e., five to ten years).
    There are a few notable changes that have been made to both the
FASOM and FAPRI-CARD models, as well as to some of the underlying
assumptions used in the agro-economic analysis since the release of the
proposed rulemaking analysis. These changes were made as a result of
further research and consultation with experts, as well as in response
to comments received during the public comment period following the
release of the proposed rulemaking. In regards to the FASOM model, the
first major change made to the model is the inclusion of the full
interaction between the forestry and agriculture sectors, as discussed
in the NPRM and supported by comments received. For the proposed
rulemaking, the FASOM model was only capable of modeling the changes in
the agriculture sector alone. In terms of land use, the only land use
that could be examined was cropland and pasture use. With the
incorporation of a forestry sector that dynamically interacts with the
agriculture, we are able to examine how crop and forest acres compete
for land in response to changes in policy. Also, similar to the
agriculture sector, the forestry sector has its own set of forestry
products, including logging and milling residues that are available for
the production of cellulosic ethanol.
    The second major change to the FASOM model is the addition of a
full accounting of major land types in the U.S., including cropland,
cropland pasture, forestland, forest pasture, rangeland, acres enrolled
in the Conservation Reserve Program (CRP), and developed land. These
changes address comments raised by peer reviewers and the general
public that we should more explicitly link the interaction between
livestock, pasture land, cropland, and forest land, as well as have a
detailed accounting of acres in the U.S. across different land uses.
Cropland is actively managed cropland, used for both traditional crops
(e.g., corn and soybeans) and dedicated energy crops (e.g.,
switchgrass). Cropland pasture is managed pasture land used for
livestock production, but which can also be converted to cropland
production. Forestland contains a number of sub-categories, tracking
the number of acres both newly and continually harvested (reforested),
the number of acres harvested and converted to other land uses
(afforested), as well as the amount of forest acres on public land.
Forest pasture is unmanaged pasture land with varying amounts of tree
cover that can be used for livestock production. A portion of this land
may be used for timber harvest. Rangeland is unmanaged land that can be
used for livestock grazing production. While the amount of rangeland
idled or used for production may vary, rangeland may not be used for
any other purpose than for cattle grazing.
    A third major change in the FASOM model is the adoption of updated
cellulosic ethanol conversion rates. We updated the cellulosic ethanol
conversion rates based on new data provided by the National Renewable
Energy Laboratory (NREL). The new analysis by NREL simplified and
updated the conversion yields of the different types of feedstocks. As
a result of these changes, the gallons per ton yields for switchgrass
and several other feedstocks increased from the values used in the
proposal, while the yields for corn residue and several other
feedstocks decreased slightly from the NPRM values. In addition, we
also updated our feedstock production yields based on new work
conducted by the Pacific Northwest National Laboratory (PNNL).\337\
This analysis increased the tons per acre yields for several dedicated
energy crops. These changes increased the amount of cellulosic ethanol
projected to come from energy crops. Additional details on the FASOM
model changes can be found in Chapter 5 of the RIA.
---------------------------------------------------------------------------

    \337\ Thomson, A.M., R.C. Izarrualde, T.O. West, D.J. Parrish,
D.D. Tyler, and J.R. Williams. 2009. Simulating Potential
Switchgrass Production in the United States. PNNL-19072. College
Park, MD: Pacific Northwest National Laboratory.
---------------------------------------------------------------------------

    The FAPRI-CARD models are econometric models covering many
agricultural commodities. These models capture the biological,
technical, and economic relationships among key variables within a
particular commodity and across commodities. They are based on
historical data analysis, current academic research, and a reliance on
accepted economic, agronomic, and biological relationships in
agricultural production and markets. The international modeling system
includes international grains, oilseeds, ethanol, sugar, and livestock
models. In general, for each commodity sector, the economic
relationship that supply equals demand is maintained by determining a
market-clearing price for the commodity. In countries where domestic
prices are not solved endogenously, these prices are modeled as a
function of the world price using a price transmission equation. Since
econometric models for each sector can be linked, changes in one
commodity sector will impact other sectors. Elasticity values for
supply and demand responses are based on econometric analysis and on
consensus estimates.
    As one of the largest and fastest developing countries in the
world, a major producer and exporter of sugar ethanol, and in
possession of one of the world's largest carbon sinks, the Amazon,
Brazil is acknowledged to be an important part of our analysis in terms
of indirect land use change. For the proposal's analysis, the FAPRI-
CARD model analyzed Brazil at a national level as any other non-US
nation in the model, covering only crop area and commodity prices.
Comments and feedback received indicated the importance of analyzing
Brazil at a regional level, given its diverse natural lands across the
country, and to also closely examine livestock production in terms of
land use.
    In response to these comments, the FAPRI-CARD model now includes an
integrated Brazil module that provides additional detail on
agricultural land use in Brazil for six geographic regions. The new
Brazil module explicitly models the competition between cropland and
pastureland used for livestock production in each region. In addition,
the Brazil module allows for region-specific agriculture practices such
as double cropping and livestock intensification in response to higher
commodity prices. The addition of the Brazil module allows for a more
refined analysis of land use change and economic impacts in Brazil than
what was able to be done for the proposal's analysis.
    Another topic that we received comments on was in regards to price-
induced yields. Namely that with an increase in price for a particular
crop, seed producers and/or farmers have a greater incentive to
increase yields for that particular crop in order to maximize revenue.
In the analysis for proposal, the FAPRI-CARD model did not include
impacts of commodity price changes on yields. For the final rulemaking,
the FAPRI-CARD model now includes feedback from changes in commodity
prices on yields. The elasticities for these responses are based on an
econometric analysis of historical data on yield and price changes for
various commodities. Additional details on the FAPRI-CARD modeling
updates can be found in Chapter 5 of the RIA.
    In the NPRM, we specifically requested comments on our assumptions
regarding distiller grain with solubles (DGS) replacement rates.

For the proposal, we assumed that one pound of DGS replaced one pound
of total of corn and soybean meal for all fed animals. We received
numerous comments on this assumption. Many commenters suggested that we
adopt the replacement rates included in the recent research by Argonne
National Laboratory (ANL) and others.\338\ The ANL study found that one
pound of DGS can be used to replace 1.196 pounds total of corn and
soybean meal for various fed animals due to the higher nutritional
content of DGS per pound compared to corn and soybean meal. For the
final rulemaking analysis, these replacement rates are incorporated in
both the FASOM and FAPRI-CARD models, and are treated as a maximum
replacement rate possibility that is fully phased in by 2015. In
addition, the maximum inclusion rates for DGS in an animal's diet have
also been incorporated into the models. Given these parameters, each
agriculture sector model determines the total quantity of DGS used in
feed based on relative prices for competing feed sources.
---------------------------------------------------------------------------

    \338\ Salil Arora, May Wu, and Michael Wang, ``Update of
Distillers Grains Displacement Ratios for Corn Ethanol Life-Cycle
Analysis,'' September 2008. See http://www.transportation.anl.gov/
pdfs/AF/527.pdf.
---------------------------------------------------------------------------

    In addition, both FASOM and FAPRI-CARD now explicitly model corn
oil from the dry mill ethanol extraction process as a new source of
biodiesel. Based on engineering research (refer to Section VII.A)
regarding expected technological adoption, it is estimated that 70% of
dry mill ethanol plants will withdraw corn oil via extraction (from
DGS), resulting in corn oil that is non-food grade and can only be used
as a biodiesel source; 20% will withdraw corn oil via fractionation
(prior to the creation of DGS), resulting in corn oil that is food-
grade; and 10% will do neither extraction or fractionation. Based on
this research, both the FASOM and FAPRI-CARD models are estimating that
approximately 681 million gallons of biodiesel can be produced from
non-food grade corn oil from extraction by 2022 in the Control Case.
Additional information regarding these changes to the FASOM and FAPRI-
CARD models can be found in RIA Chapter 5.
1. Biofuel Volumes Modeled
    For the agricultural sector analysis using the FASOM and FAPRI-CARD
models of the RFS2 biofuel volumes, we assumed 15 billion gallons
(Bgal) of corn ethanol would be produced for use as transportation fuel
by 2022, an increase of 2.7 Bgal from the Reference Case. Also, we
modeled 1.7 Bgal of biodiesel use as fuel in 2022, an increase of 1.3
Bgal from the Reference Case. In addition, we modeled an increase of 16
Bgal of cellulosic ethanol in 2022. In FASOM, this volume consists of
4.9 billion gallons of cellulosic ethanol coming from corn residue in
2022, 7.9 billion gallons from switchgrass, 0.6 billion gallons from
sugarcane bagasse, and 0.1 billion gallons from forestry residues.
    Given the nature of the models, there are some limitations on what
each model may explicitly model as a biofuel feedstock source. For
example, since FASOM is a domestic agricultural sector model it cannot
be utilized to examine the impacts of the wider use of biofuel imports
into the U.S. Similarly, the FAPRI-CARD model does not explicitly model
the forestry sector in the U.S. and therefore does not include biofuels
produced from the U.S. forestry sector. Also, neither of the two models
used for this analysis--FASOM or FAPRI-CARD--include biofuels derived
from domestic municipal solid waste. Thus, for the RFS2 agricultural
sector analysis, these biofuel sources are analyzed outside of the
agricultural sector models.
    All of the results presented in this section are relative to the
AEO 2007 Reference Case renewable fuel volumes, which include 12.3 Bgal
of grain-based ethanol, 0.4 Bgal of biodiesel, and 0.3 Bgal of
cellulosic ethanol in 2022. The domestic figures are provided by FASOM,
and all of the international numbers are provided by FAPRI-CARD. The
detailed FASOM results, detailed FAPRI-CARD results, and additional
sensitivity analyses are described in more detail in the RIA.

        Table VIII.A.1-1--Ethanol Source Volumes Modeled in 2022
                          [Billions of gallons]
------------------------------------------------------------------------
                                     AEO 2007
          Ethanol source            reference     Control       Change
                                       case         case
------------------------------------------------------------------------
Corn Ethanol.....................         12.3         15.0          2.7
Corn Residue Cellulosic Ethanol *            0          4.9          4.9
Sugarcane Bagasse Cellulosic               0.2          0.6          0.4
 Ethanol *.......................
Switchgrass Cellulosic Ethanol *.            0          7.9          7.9
Forestry Residue Cellulosic                  0          0.1          0.1
 Ethanol *.......................
Net Imports of Sugarcane Ethanol           0.6          2.2          1.6
 **..............................
Other Ethano ***.................          0.1          2.6          2.5
------------------------------------------------------------------------
 * Cellulosic Ethanol feedstocks are not explicitly modeled in FAPRI-
  CARD.
** Net Imports of Sugarcane Ethanol is not explicitly modeled in FASOM.
*** Includes MSW, which is not explicitly modeled by either FASOM or
  FAPRI-CARD.

       Table VIII.A.1-2--Biodiesel Source Volumes Modeled in 2022
                          [Millions of gallons]
------------------------------------------------------------------------
                                     AEO 2007
         Biodiesel source           reference     Control       Change
                                       case         case
------------------------------------------------------------------------
Soybean Oil......................        119.9        659.4        539.5
Corn Oil (Dry Mill Extraction)...          0.4        681.3        680.8
Animal Fats......................         93.9        126.9         33.0
Yellow Grease....................        170.9        253.1         82.3
------------------------------------------------------------------------

2. Commodity Price Changes
    For the scenario modeled, FASOM predicts that in 2022 U.S. corn
prices would increase by $0.27 per bushel (8.2%) above the Reference
Case price of $3.32 per bushel. By 2022, U.S. soybean prices would
increase by $1.02 per bushel (10.3%) above the Reference Case price of
$9.85 per bushel. In 2022, U.S. soybean oil prices would increase
$183.32 per ton (37.9%) above the Reference Case price of $483.10 per
ton. Hardwood lumber prices are unaffected by the increase in biofuel
demand, however softwood lumber prices increase by $0.46 per board foot
(0.1%) in 2022 to $386 per board foot. Additional price impacts are
included in Section 5 of the RIA.

   Table VIII.A.2-1--Change in U.S. Commodity Prices From the AEO 2007
                             Reference Case
                                 [2007$]
------------------------------------------------------------------------
            Commodity                       Change             % Change
------------------------------------------------------------------------
Corn.............................  0.27/bushel.............          8.2
Soybeans.........................  1.02/bushel.............         10.3
Soybean Oil......................  183.32/ton..............         37.9
Hardwood Lumber..................  0.00/board foot.........            0
Softwood Lumber..................  0.46/board foot.........          0.1
------------------------------------------------------------------------

    By 2022, the price of switchgrass would increase by $20.12 per wet
ton to the Control Case price of $40.85 per wet ton. Additionally, the
farm gate feedstock price of corn residue would increase by $29.48 per
wet ton to the Control Case price of $34.49 per wet ton. The price of
sugarcane bagasse would increase $23.27 to the Control Case price of
$29.70 per wet ton by 2022. Softwood logging residue prices would
increase $8.99 per wet ton to $18.37 per wet ton in the Control Case in
2022. Similarly, the price of hardwood logging residues would increase
by $17.85 per wet ton to the Control Case price of $23.22 per wet ton
in 2022. These prices do not include the storage, handling, or delivery
costs, which would result in a delivered price to the ethanol facility
of at least twice the farm gate cost, depending on the region.

  Table VIII.A.2-2--Change in U.S. Cellulosic Feedstock Prices From the
                         AEO 2007 Reference Case
                                 [2007$]
------------------------------------------------------------------------
            Commodity             Control case price        Change
------------------------------------------------------------------------
Switchgrass.....................  $40.85/wet ton....  $20.12/wet ton.
Corn Residue....................  34.49/wet ton.....  29.48/wet ton.
Sugarcane Bagasse...............  29.70/wet ton.....  23.27/wet ton.
Softwood Logging Residue........  18.37/wet ton.....  8.99/wet ton.
Hardwood Logging Residue........  23.22.............  17.85/wet ton.
------------------------------------------------------------------------

3. Impacts on U.S. Farm Income
    The increase in renewable fuel production provides a significant
increase in net farm income to the U.S. agricultural sector. FASOM
predicts that net U.S. farm income would increase by $13 billion
dollars in 2022 (36%), relative to the AEO 2007 Reference Case.
4. Commodity Use Changes
    Changes in the consumption patterns of U.S. corn can be seen by the
increasing percentage of corn used for ethanol. FASOM estimates the
amount of domestically produced corn used for ethanol in 2022 would
increase to 40.5%, relative to the 33.2% usage rate under the Reference
Case.
    The rising price of corn and soybeans in the U.S. would also have a
direct impact on how corn is used. Higher domestic corn prices would
lead to lower U.S. exports as the world markets shift to other sources
of these products or expand the use of substitute grains. FASOM
estimates that U.S. corn exports would drop 188 million bushels (-8.2%)
to 2.1 billion bushels by 2022. In value terms, U.S. exports of corn
would fall by $57 million (-0.8%) to $7.5 billion in 2022. U.S. exports
of soybeans would also decrease due to the increased use of renewable
fuels. FASOM estimates that U.S. exports of soybeans would decrease 135
million bushels (-13.6%) to 858 million bushels by 2022. In value
terms, U.S. exports of soybeans would decrease by $453 million (-4.6%)
to $9.3 billion in 2022.

  Table VIII.A.4-1--Change in U.S. Exports From the AEO 2007 Reference
                              Case in 2022
------------------------------------------------------------------------
                                                    Change
                                                  (millions)   % Change
------------------------------------------------------------------------
                                 Exports
------------------------------------------------------------------------
Corn in Bushels.................................        -188        -8.2
Soybeans in Bushels.............................        -135       -13.6
------------------------------------------------------------------------
                         Total Value of Exports
------------------------------------------------------------------------
Corn (2007$)....................................       - $57        -0.8
Soybeans (2007$)................................      - $453        -4.6
------------------------------------------------------------------------

    Lumber production in the U.S. is affected as well, as forestry
acres decrease as a result of expanding crop acres (see below). In
2022, hardwood lumber production increases by 0.2%, and softwood
production decreases by -0.2%.

 Table VIII.A.4-2--Percent Change in U.S. Lumber Production From the AEO
                       2007 Reference Case in 2022
------------------------------------------------------------------------
                          Commodity                            % Change
------------------------------------------------------------------------
Hardwood Lumber.............................................         0.2

Softwood Lumber.............................................        -0.2
------------------------------------------------------------------------

    Higher U.S. demand for corn for ethanol production would cause a
decrease in the use of corn for U.S. livestock feed. Substitutes are
available for corn as a feedstock, and this market is price sensitive.
Several ethanol processing byproducts could also be used to replace a
portion of the corn used as feed, depending on the type of animal. One
of the major byproducts of the ethanol production process that can be
used as a feed source, and as a substitute for corn and soybean meal,
is distiller grains with solubles (DGS). DGS are a by-product of the
dry mill ethanol production process. As discussed above, the
replacement rates of DGs for corn and soybean meal in the diets of fed
animals is higher than what was used in the proposal based on the
latest scientific research regarding nutritional content of feed
sources. In addition, as discussed above and in Chapter VI, there are
new processes for withdrawing corn oil from the dry mill ethanol
production process. Therefore, we are now modeling two types of DGS:
Those that are created during the extraction/fractionation process
(fractionated DGS), and those created in plants that do not conduct
fractionation or extraction (traditional DGS). In addition, other
byproducts that can be used as feed substitutes include gluten meal and
gluten feed, which are byproducts of wet milling ethanol production. In
2022, traditional DGS used in feed decreases by 27.5 million tons from
the Reference Case to 6.5 million tons in the Control Case. However,
the use of fractionated DGS increases by 32.7 million tons from 20
thousand tons used in the Reference Case in 2022. Gluten meal used in
feed decreases by 0.1 million tons (-4.5%) to 2.1 million tons in the
Control Case. Gluten feed use increases by 0.3 million tons (6.4%) in
2022 to 4.8 million tons in the Control Case. By 2022, FASOM predicts
total ethanol byproducts used in feed would increase by 5.4 million
tons (13.2%) to 46.1 million tons, compared to 40.8 million tons under
the Reference Case.

 Table VIII.A.4-3--Change in Ethanol Byproducts Use in Feed Relative to
                       the AEO 2007 Reference Case
                           [Millions of tons]
------------------------------------------------------------------------
                                                    Control
                    Category                         case       Change
------------------------------------------------------------------------
DGS (Traditional)...............................         6.5       -27.5
DGS (Fractionated)..............................        32.7        32.7
Gluten Meal.....................................         2.1        -0.1
Gluten Feed.....................................         4.8         0.3
                                                 -----------------------
  Total Ethanol Byproducts......................        46.1         5.4
------------------------------------------------------------------------

    The EISA cellulosic ethanol requirements result in the production
of residual agriculture and forestry products, as well as dedicated
energy crops. By 2022, FASOM predicts production of 97.4 million tons
of switchgrass and 59.9 million tons of corn residue. Sugarcane bagasse
for cellulosic ethanol production increases by 6 million tons to 9.6
million tons in 2022 relative to the Reference Case. In addition, FASOM
predicts production of 1.7 million tons of forestry residues for
cellulosic ethanol production.
5. U.S. Land Use Changes
    Higher U.S. corn prices would have a direct impact on the value of
U.S. agricultural land. As demand for corn and other farm products
increases, the amount of land devoted to cropland production would
increase. FASOM estimates an increase of 3.6 million acres (4.6%) in
harvested corn acres, relative to 77.9 million acres harvested under
the Reference Case by 2022.\339\ Most of the new corn acres come from a
reduction in existing crop acres, such as rice, wheat, and hay.
---------------------------------------------------------------------------

    \339\ Total U.S. planted corn acres increases to 87.1 million
acres from the Reference Case level of 83.5 million acres in 2022.
---------------------------------------------------------------------------

    Though demand for biodiesel increases, FASOM predicts a fall in
U.S. soybean acres harvested. According to the model, harvested soybean
acres would decrease by approximately 1.4 million acres (-2.1%),
relative to the Reference Case acreage of 68.1 million acres in 2022.
Despite the decrease in soybean acres in 2022, soybean oil production
would increase by 0.5 million tons (4.7%) by 2022 over the Reference
Case. This occurs due to the decrease in soybean exports mentioned
above. Additionally, FASOM predicts that soybean oil exports would
decrease 1.2 million tons by 2022 (-51%) relative to the Reference
Case.
    As the demand for cellulosic ethanol increases, most of the
production is derived from switchgrass. By 2022, switchgrass acres from
nearly zero acres in the Reference Case, to 12.5 million acres in the
Control Case as demand for cellulosic ethanol increases between cases.
Similarly, as demand for cellulosic ethanol from bagasse increases,
sugarcane acres increase by 0.1 million acres (20%) to 0.9 million
acres by 2022. Although we received comments suggesting that acres
enrolled in the Conservation Reserve Program (CRP) may decrease below
the 32 million acres assumed in the NPRM, we did not revise this
assumption for several reasons. First, the commodity price changes
predicted by FASOM are relatively modest and would therefore have a
limited impact on the decision to re-enroll in the program. Second, the
CRP program is designed to allow for increased payment if land rental
rates increase. Therefore, for the reasons outlined in the NPRM, we
believe the assumption that CRP acres will not drop below 32 million
acres is a plausible future projection.

  Table VIII.A.5-1--Change in U.S. Crop Acres Relative to the AEO 2007
                         Reference Case in 2022
                           [Millions of acres]
------------------------------------------------------------------------
                      Crop                          Change     % Change
------------------------------------------------------------------------
Corn............................................         3.6         4.6
Soybeans........................................        -1.4        -2.1
Sugarcane.......................................         0.1          20
Switchgrass.....................................        12.5      20,000
------------------------------------------------------------------------

    With the increase in biofuel demand that results from the
implementation of the RFS2 policy, there is an increase of 3.1 million
acres are dedicated towards crop production. This increase in crop
acres results in a decrease of -1.9 million pasture acres, an increase
of 1.1 million acres of forest pasture, and a decrease of 1.2 million
forestry acres.

  Table VIII.A.5-2--Change in U.S. Crop Acres Relative to the AEO 2007
                         Reference Case in 2022
                           [Millions of acres]
------------------------------------------------------------------------
                    Land type                       Change     % Change
------------------------------------------------------------------------
Cropland........................................         3.1         1.0
Cropland Pasture................................        -1.9        -5.8
Forest Pasture..................................         1.1         0.7
Forestry........................................        -1.2        -0.3
------------------------------------------------------------------------

    The additional demand for corn and other crops for biofuel
production also results in increased use of fertilizer in the U.S. In
2022, FASOM estimates that U.S. nitrogen fertilizer use would increase
1.5 billion pounds (5.7%) over

the Reference Case nitrogen fertilizer use of 26.2 billion pounds. In
2022, U.S. phosphorous fertilizer use would increase by 714 million
pounds (12.7%) relative to the Reference Case level of 5.6 billion
pounds.

Table VIII.A.5-3--Change in U.S. Fertilizer Use Relative to the AEO 2007
                             Reference Case
                          [Millions of pounds]
------------------------------------------------------------------------
                   Fertilizer                       Change     % Change
------------------------------------------------------------------------
Nitrogen........................................       1,501         5.7
Phosphorous.....................................         714        12.7
------------------------------------------------------------------------

6. Impact on U.S. Food Prices
    Due to higher commodity prices, FASOM estimates that U.S. food
costs \340\ would increase by roughly $10 per person per year by 2022,
relative to the Reference Case.\341\ Total effective farm gate food
costs would increase by $3.6 billion (0.2%) in 2022.\342\ To put these
changes in perspective, average U.S. per capita food expenditures in
2007 were $3,778 or approximately 10% of personal disposable income.
The total amount spent on food in the U.S. in 2007 was $1.14 trillion
dollars.\343\
---------------------------------------------------------------------------

    \340\ FASOM does not calculate changes in price to the consumer
directly. The proxy for aggregate food price change is an indexed
value of all food prices at the farm gate. It should be noted,
however, that according to USDA, approximately 80% of consumer food
expenditures are a result of handling after it leaves the farm
(e.g., processing, packaging, storage, marketing, and distribution).
These costs consist of a complex set of variables, and do not
necessarily change in proportion to an increase in farm gate costs.
In fact, these intermediate steps can absorb price increases to some
extent, suggesting that only a portion of farm gate price changes
are typically reflected at the retail level. See http://
www.ers.usda.gov/publications/foodreview/septdec00/FRsept00e.pdf.
    \341\ These estimates are based on U.S. Census population
projections of 331 million people in 2017 and 348 million people in
2022. See http://www.census.gov/population/www/projections/
summarytables.html.
    \342\ Farm Gate food prices refer to the prices that farmers are
paid for their commodities.
    \343\ See www.ers.usda.gov/Briefing/CPIFoodAndExpenditures/Data/
table15.htm.
---------------------------------------------------------------------------

7. International Impacts
    Changes in the U.S. agriculture economy are likely to have affects
in other countries around the world in terms of trade, land use, and
the global price and consumption of fuel and food. We utilized the
FAPRI-CARD model to assess the impacts of the increased use of
renewable fuels in the U.S. on world agricultural markets.
    The FAPRI-CARD modeling shows that world corn prices would increase
by $0.12 per bushel (3.1%) to $3.88 per bushel in 2022, relative to the
Reference Case. The impact on world soybean prices is somewhat smaller,
increasing $0.08 per bushel (0.8%) to $9.63 per bushel in 2022.
    This increase in international commodity prices has a direct impact
on world food consumption.\344\ The FAPRI-CARD model indicates that
world consumption of corn for food would decrease by 0.6 million metric
tons in 2022 relative to the Reference Case. Similarly, the FAPRI-CARD
model estimates that world consumption of oil for food (e.g., vegetable
oils) decreases by 1.7 million metric tons by 2022. Wheat consumption
is not estimated to change substantially in 2022. The model also
estimates a small change in world meat consumption, decreasing by -0.1
million metric tons in 2022. When considering all the food uses
included in the model, world food consumption decreases by 2.4 million
metric tons by 2022 (-0.11%). While FAPRI-CARD provides estimates of
changes in world food consumption, estimating effects on global
nutrition is beyond the scope of this analysis.
---------------------------------------------------------------------------

    \344\ The food commodities included in the FAPRI model include
corn, wheat, sorghum, barley, soybeans, sugar, peanuts, oils, beef,
pork, poultry, and dairy products.

 Table VIII.A.7-1--Change in World Food Consumption Relative to the AEO
                           2007 Reference Case
                        [Millions of metric tons]
------------------------------------------------------------------------
                            Category                               2022
------------------------------------------------------------------------
Corn...........................................................     -0.6
Wheat..........................................................      0.0
Vegetable Oils.................................................     -1.7
Meat...........................................................     -0.1
                                                                --------
  Total Food...................................................     -2.4
------------------------------------------------------------------------

    Additional information on the U.S. agricultural and forestry
sectors, as well as international trade impacts are described in more
detail in the RIA (Chapter 5).

B. Energy Security Impacts

    Increasing usage of renewable fuels helps to reduce U.S. petroleum
imports. A reduction of U.S. petroleum imports reduces both financial
and strategic risks associated with a potential disruption in supply or
a spike in cost of a particular energy source. This reduction in risks
is a measure of improved U.S. energy security. In this section, we
detail an updated methodology for estimating the energy security
benefits of reduced U.S. oil imports which explicitly includes biofuels
and, based upon this updated approach, we estimate the monetary value
of the energy security benefits of the RFS2 required renewable fuel
volumes.
1. Implications of Reduced Petroleum Use on U.S. Imports
    In 2008, U.S. petroleum import expenditures represented 21% of
total U.S. imports of all goods and services.\345\ In 2008, the U.S.
imported 66% of the petroleum it consumed, and the transportation
sector accounted for 70% of total U.S. petroleum consumption. This
compares to approximately 37% of petroleum from imports and 55%
consumption of petroleum in the transportation sector in 1975.\346\ It
is clear that petroleum imports have a significant impact on the U.S.
economy. Requiring the wider use of renewable fuels in the U.S. is
expected to lower U.S. petroleum imports.
---------------------------------------------------------------------------

    \345\ Source: U.S. Bureau of Economic Analysis, U.S.
International Transactions Accounts Data, as shown on June 24, 2009.
    \346\ Source: U.S. Department of Energy, Annual Energy Review
2008, Report No. DOE/EIA-0384(2008), Tables 5.1 and 5.13c, June 26,
2009.
---------------------------------------------------------------------------

    For this final rule, EPA estimated the reductions in U.S. petroleum
imports using a modified version of the National Energy Modeling System
(EPA-NEMS). EPA-NEMS is an energy-economy modeling system of U.S.
energy markets through the 2030 time period. EPA-NEMS projects U.S.
production, imports, conversion, consumption, and prices of energy;
subject to assumptions on world energy markets, resource availability
and costs, behavioral and technological choice criteria, cost and
performance characteristics of energy technologies, and demographics.
For this analysis, the 2009 NEMS model was modified to use the 2007
(pre-EISA) Annual Energy Outlook (AEO) levels of biofuels in the
Reference Case. These results were compared to our Control Case, which
assumes the renewable fuel volumes required by EISA will be met by
2022. The reductions in U.S. oil imports projected by EPA-NEMS as a
result of the RFS2 is approximately 0.9 million barrels per day, which
amounts to about $41.5 billion in lower crude oil and refined product
import payments in 2022.
2. Energy Security Implications
    In order to understand the energy security implications of the
increased use of renewable fuels, EPA used the Oil

Security Metrics Model 347 348 (OSMM), developed and
maintained by Oak Ridge National Laboratory. This model examines the
future economic costs of oil imports and oil supply disruptions to the
U.S., grouping costs into (1) the higher costs for oil imports
resulting from the effect of U.S. import demand on the world oil price
and OPEC market power (i.e., the ``import demand'' or ``monopsony''
costs); and (2) the expected cost of reductions in U.S. economic output
and disruption of the U.S. economy caused by sudden disruptions in the
supply of imported oil to the U.S. (i.e., macroeconomic disruption/
adjustment costs). Beginning with Reference projections for the oil and
liquid fuel markets from the EIA's 2009 AEO, the OSMM compares costs
under those futures with selected cases under differing energy policies
and technology mixes. It provides measures of expected costs and risk
by probabilistic simulation through 2022. Uncertainty is inherent in
energy security analysis, and it is explicitly represented for long-run
future oil market conditions, disruption events, and key parameters.
---------------------------------------------------------------------------

    \347\ The OSMM methods are consistent with the recommended
methodologies of the National Resource Council's (NRC's) (2005)
Committee on Prospective Benefits of DOE's Energy Efficiency and
Fossil Energy R&D Programs. The OSMM defines and implements a method
that makes use of the NRC's typology of prospective benefits and
methodological framework, satisfies the NRC's criteria for
prospective benefits evaluation, and permits measurement of
prospective energy security benefits for policies and technologies
related to oil. It has been used to estimate the prospective oil
security benefits of Department of Energy's Energy Efficiency and
Renewable Energy R&D programs, and is also applicable to other
strategies and policies aimed at changing the level and composition
of U.S. petroleum demand. To evaluate the RFS2, the OSMM was
modified to include supplies and demand of biofuels (principally
ethanol) as well as petroleum.
    \348\ Leiby, P.N., Energy Security Impacts of Renewable Fuel Use
Under the RFS2 Rule--Methodology, Oak Ridge National Laboratory,
January 19, 2010.
---------------------------------------------------------------------------

    An important aspect of the OSMM is that it explicitly addresses the
energy security implications of the wider use of biofuels as
transportation fuels in the U.S. Increased use of biofuels not only
results in changes in the levels of U.S. oil imports and consumption,
but also can alter key supply and demand oil elasticities. The
elasticities are significant for energy security since they measure the
potential for substitution away from oil, in the long and short-run,
depending on how oil prices evolve and whether oil supply disruptions
occur. Also, the OSMM accounts for the potential of supply disruptions
from biofuels. For example, there could be a drought in the U.S. that
could cause a reduction in the supply of key agricultural feedstocks
(i.e., corn) that are used to make ethanol. To the extent that supply
disruptions in feedstocks used to make biofuels are correlated with oil
supply disruptions, the energy security benefits of biofuels may be
lessened, by substituting one fuel with supply disruptions for another.
For this analysis, the energy security implications of the wider use of
biofuels in the U.S. are broken down between biofuels produced
domestically (e.g., ethanol made from corn/switchgrass, soy-based
biodiesel) and imported biofuels (e.g., ethanol made from sugarcane).
    For the proposed RFS2 rule, EPA worked with Oak Ridge National
Laboratory (ORNL), which has developed approaches for evaluating the
social costs and energy security implications of oil use. In the study
entitled ``The Energy Security Benefits of Reduced Oil Use, 2006-
2015,'' completed in March, 2008, ORNL updated and applied the
analytical approach used in the 1997 Report ``Oil Imports: An
Assessment of Benefits and Costs.'' 349 350 This study is
included as part of the record in this rulemaking.\351\ This study
underwent a Peer Review, sponsored by the Agency.
---------------------------------------------------------------------------

    \349\ Leiby, Paul N., Donald W. Jones, T. Randall Curlee, and
Russell Lee, Oil Imports: An Assessment of Benefits and Costs, ORNL-
6851, Oak Ridge National Laboratory, November, 1997.
    \350\ The 1997 ORNL paper was cited and its results used in DOT/
NHTSA's rules establishing CAFE standards for 2008 through 2011
model year light trucks. See DOT/NHTSA, Final Regulatory Impacts
Analysis: Corporate Average Fuel Economy and CAFE Reform MY 2008-
2011, March 2006.
    \351\ Leiby, Paul N. ``Estimating the Energy Security Benefits
of Reduced U.S. Oil Imports,'' Oak Ridge National Laboratory, ORNL/
TM-2007/028, Final Report, 2008.
---------------------------------------------------------------------------

    The prior approach that ORNL has developed estimates the
incremental benefits to society, in dollars per barrel, of reducing
U.S. oil imports, called the ``oil import premium''. With OSMM, ORNL
uses a consistent approach, estimating the incremental cost to the U.S.
of the increased use of renewable fuels required by EISA, and reporting
that cost in dollars per barrel of biofuel. In this case, these
increased volumes alter both the U.S. oil import and consumption
levels, while introducing a substitute fuel and altering demand
responsiveness. As before, OSMM considers the economic cost of
importing petroleum into the U.S. The economic cost of importing
petroleum into the U.S. was defined as (1) the higher costs for oil
imports resulting from the effect of U.S. import demand on the world
oil price and OPEC market power (i.e., ``monopsony'' costs); and (2)
the risk of reductions in U.S. economic output and disruption of the
U.S. economy caused by sudden disruptions in the supply of imported oil
to the U.S. (i.e., macroeconomic disruption/adjustment costs).
Maintaining a U.S. military presence to help secure stable oil supply
from potentially vulnerable regions of the world is also a measure of
energy security, but has been excluded from this analysis because its
attribution to particular military missions or activities is difficult.
a. Effect of Oil Use on Long-Run Oil Price, U.S. Import Costs, and
Economic Output
    The first component of the economic costs of importing petroleum
into the U.S. follows from the effect of U.S. import demand on the
world oil price over the long-run. Because the U.S. is a sufficiently
large purchaser of foreign oil supplies, its purchases can affect the
world oil price. This monopsony power means that increases in U.S.
petroleum demand can cause the world price of crude oil to rise, and
conversely, that reduced U.S. petroleum demand can reduce the world
price of crude oil. Thus, one benefit of decreasing U.S. oil purchases
is the potential decrease in the crude oil price paid for all crude oil
purchased.
    In the case of the RFS2, increasing U.S. demand for biofuels
partially offsets the U.S. oil market import cost reduction. The offset
is because the RFS2 results in a modest increases in biofuels imported
to the U.S. (1.6 billion gallons in 2022), and a modest increase in the
world ethanol price (from $1.48/gallon to $1.61/gallon, a $0.13/gallon
increase in 2022). Thus, the biofuels that the U.S. had imported would
be higher priced, partially offsetting the reduction in U.S. oil import
costs. The ORNL estimates this monopsony component of the energy
security benefit (oil market and biofuel market impacts combined) is
$7.86/barrel of biofuel (2007$) for the year 2022, as shown in Table
VIII.B.2-1. Based upon the 90 percent confidence interval, the
monopsony portion of the energy security benefit ranges from $5.37 to
$10.71/barrel of biofuel in the year 2022.
b. Short-Run Disruption Premium From Expected Costs of Sudden Supply
Disruptions
    The second component of the external economic costs resulting from
U.S. oil imports arises from the vulnerability of the U.S. economy to
oil shocks. The cost of shocks depends on their likelihood, size, and
length; the capabilities of the market and U.S. Strategic Petroleum

Reserve (SPR) to respond; and the sensitivity of the U.S. economy to
sudden price increases. The total vulnerability of the U.S. economy to
oil price shocks depends on the levels of both U.S. petroleum
consumption and imports. Variation in oil consumption levels can change
the sensitivity of the economy to oil price shocks, and variation in
import levels or demand flexibility can affect the magnitude of
potential increases in oil price due to supply disruptions
    A major strength of the OSMM is that it addresses risk-shifting
that might occur as the U.S. reduces its dependency on petroleum and
increases its use of biofuels, which the other ``oil premium model''
could not. The prior ``oil premium'' analysis focused only on the
potential for biofuels to reduce U.S. oil imports, and the resulting
implications of lower U.S. oil imports for energy security. As the U.S.
relies more heavily on biofuels, such as corn-based ethanol, there
could be adverse consequences from a supply-disruption perspective
associated with, for example, a long-term drought. Alternatively, a
supply disruption of petroleum will more likely be caused by
geopolitical factors rather than extreme weather conditions. Hence, the
causal factors of a supply-disruption from imported petroleum and,
alternatively, biofuels, are likely to be unrelated. Thus, diversifying
the sources of U.S. transportation fuel is expected to provide energy
security benefits. Biofuel supply disruptions are represented based on
the historical volatility of yields for biofuel feedstocks or similar
crops. The ORNL estimates this macroeconomic/disruption component of
the energy security benefit (oil market and biofuel market impacts
combined) is $6.56/barrel (2007$) for the year 2022, as shown in Table
VIII.B.2-1. Based upon the 90 percent confidence interval, the
macroeconomic/disruption component of the energy security benefit
ranges from $0.94 to $12.23/barrel of biofuel in the year 2022.

  Table VIII.B.2-1--Energy Security Benefits of The Volumes Required by
                              RFS2 in 2022
                      [2007$ per barrel of biofuel]
------------------------------------------------------------------------
                       Component                            Estimate
------------------------------------------------------------------------
Monopsony.............................................              7.86
                                                            (5.37-10.71)
Macroeconomic Disruption..............................              6.56
                                                            (0.94-12.23)
                                                       -----------------
  Total...............................................             14.42
                                                            (6.31-22.95)
------------------------------------------------------------------------

c. Costs of Existing U.S. Energy Security Policies
    Another often-identified component of the full economic costs of
U.S. oil imports is the costs to the U.S. taxpayers of existing U.S.
energy security policies. The two primary examples are maintaining a
military presence to help secure stable oil supply from potentially
vulnerable regions of the world and maintaining the SPR to provide
buffer supplies and help protect the U.S. economy from the consequences
of global oil supply disruptions.
    U.S. military costs are excluded from the analysis performed by
ORNL because their attribution to particular missions or activities is
difficult. Most military forces serve a broad range of security and
foreign policy objectives. Attempts to attribute some share of U.S.
military costs to oil imports are further challenged by the need to
estimate how those costs might vary with incremental variations in U.S.
oil imports. In the peer review of the energy security analysis that
the Agency commissioned, a majority of peer reviewers believed that
U.S. military costs should be excluded absence a widely agreed
methodology for estimating this component of U.S. energy security.
Similarly, while the costs for building and maintaining the SPR are
more clearly related to U.S. oil use and imports, historically these
costs have not varied in response to changes in U.S. oil import levels.
Thus, while SPR is factored into the ORNL analysis, the cost of
maintaining the SPR is excluded.
    Some commenters felt that the Agency should attempt to monetize
U.S. military costs and include these costs in the energy security
analysis, while other commenters agreed with the Agency that these
costs should be excluded. The Agency did not receive any new analysis
or methodological approach from commenters which could be used to
monetize U.S. military costs in a meaningful or credible manner. Since
U.S. military impacts are not factored into the energy security
analysis, they are also excluded from the lifecycle GHG analysis.
3. Combining Energy Security and Other Benefits
    The literature on the energy security for the last two decades has
routinely combined the monopsony and the macroeconomic disruption
components when calculating the total value of the energy security
premium. However, in the context of using a global value for the Social
Cost of Carbon (SCC) the question arises: how should the energy
security premium be used when some benefits from the increased use of
renewable fuels, such as the benefits of reducing greenhouse gas
emissions, are calculated at a global level? Monopsony benefits
represent avoided payments by the U.S. to oil producers in foreign
countries that result from a decrease in the world oil price as the
U.S. decreases its consumption of imported oil (net of increased
imported biofuel payments by the U.S.). Although there is clearly a
benefit to the U.S. when considered from the domestic perspective, the
decrease in price due to decreased demand in the U.S. also represents a
loss to other countries. Given the redistributive nature of this
effect, do the negative effects on other countries ``net out'' the
positive impacts to the U.S.? If this is the case, then, the monopsony
portion of the energy security premium should be excluded from the net
benefits calculation. Based on this reasoning, EPA's estimates of net
benefits for the increased use of renewable fuels required by EISA
exclude the portion of energy security benefits stemming from the U.S.
exercising its monopsony power in oil markets. Thus, EPA only includes
the macroeconomic disruption/adjustment cost portion of the energy
security premium.
    However, even when the global value for greenhouse gas reduction
benefits is used, a strong argument can be made that the monopsony
benefits should be included in net benefits calculation. Maintaining
the earth's climate is a global public good and as such requires that a
global perspective be taken on the benefits of GHG mitigation by all
nations, including the U.S. The global SCC is used in these
calculations, not because the global net benefits of the increased use
of renewable fuels are being computed (they are not), but rather
because in the context of a global public good, the global marginal
benefit is the correct benefit against which domestic costs are to be
compared. In other words, using the global SCC does not transform the
calculation from a domestic (i.e., U.S.) to a global one. Rather, the
domestic perspective is maintained while recognizing that the impacts
from domestic GHG emissions are truly global in nature.
    Energy security, on the other hand, is broadly defined as
protecting the U.S. economy against circumstances that threaten
significant short- and long-term increases in energy costs. Energy
security is inherently a domestic benefit. However, the use of the
domestic monopsony benefit is not necessarily in conflict with the use
of the global SCC, because the global SCC represents the benefits
against which

the costs associated with our (i.e., the U.S.'s) domestic mitigation
efforts should be judged. In addition, the U.S. values both maintaining
the earth's climate and providing for its own energy security. If this
reasoning holds, the two benefits--the global benefits of reducing
greenhouse gas emissions and the full energy security premium,
including the monopsony benefits--should be counted in the net benefits
estimates. In the final analysis, the Agency determined that the first
argument is more compelling and therefore has determined that using
only the macroeconomic disruption component of the energy security
benefit is the appropriate metric for this rule.
4. Total Energy Security Benefits
    In 2022, total annual energy security benefits are estimated for
the difference between the renewable fuel volumes in the Primary
Control Case (30.50 billion gallons) and the AEO2007 Reference Case
(13.56 billion gallons). Total annual energy security benefits are
calculated by multiplying the change in renewable fuel volumes (16.94
billion gallons or 403 million barrels) and the macroeconomic
disruption/adjustment portion of the energy security premium ($6.56/
barrel of renewable fuels). The estimated total energy security benefit
is $2.6 billion (2007$) for the year 2022. The estimated total energy
security benefit using the macroeconomic disruption/adjustment portion
of the energy security benefit in 2022 ranges from $379 million to $4.9
billion based upon the 90 percent confidence intervals.

C. Benefits of Reducing GHG Emissions

1. Introduction
    This section presents estimates of the economic benefits that could
be monetized for the reductions in GHG emissions projected to occur
through the increased use of renewable fuels required by EISA. The
total benefit estimates were calculated by multiplying a marginal
dollar value (i.e., cost per ton) of carbon emissions, also referred to
as ``social cost of carbon'' (SCC), by the anticipated level of
emissions reductions in tons.
    The SCC values underlying the benefits estimates for this rule
represent U.S. government-wide interim values for SCC. As discussed
below, federal agencies will use these interim values to assess some of
the economic benefits of GHG reductions while an interagency workgroup
develops SCC values for use in the long-term. The interim values should
not be viewed as an expectation about the results of the longer-term
process. Although these values were not used in the NPRM, some
commenters raised issues with these values and the methodology used to
develop them in response to their publication elsewhere. Many of these
issues are being examined by the interagency workgroup.
    The rest of this Preamble section will provide the basis for the
interim SCC values, and the estimates of the total climate-related
benefits of the increased use of renewable fuels that follow from these
interim values. As discussed below, the interim dollar estimates of the
SCC represent a partial accounting of climate change impacts.
    In addition to the quantitative account presented in this section,
a qualitative appraisal of climate-related impacts is published in
Section V of today's rule and in other recent climate change analyses.
For example, EPA's Endangerment and Cause or Contribute Findings for
Greenhouse Gases under Section 202(a) of the Clean Air Act and the
accompanying Technical Support Document (TSD) presents a summary of
impacts and risks of climate change projected in the absence of actions
to mitigate GHG emissions.\352\ The TSD synthesizes major findings from
the best available scientific assessments of the scientific literature
that have gone through rigorous and transparent peer review, including
the major assessment reports of both the Intergovernmental Panel on
Climate Change (IPCC) and the U.S. Climate Change Science Program
(CCSP).
---------------------------------------------------------------------------

    \352\ See Federal Register/Vol. 74, No. 2398/Wednesday, December
16, 2009/Rules and Regulations at http://frwebgate4.access.gpo.gov/
cgi-bin/PDFgate.cgi?WAISdocID=969788398047+0+2+0&WAISaction=retrieve
or http://epa.gov/climatechange/endangerment.html.
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2. Derivation of Interim Social Cost of Carbon Values
    The ``social cost of carbon'' (SCC) is intended to be a monetary
measure of the incremental damage resulting from carbon dioxide
(CO2) emissions, including (but not limited to) net
agricultural productivity loss, human health effects, property damages
from sea level rise, and changes in ecosystem services. Any effort to
quantify and to monetize the consequences associated with climate
change will raise serious questions of science, economics, and ethics.
But with full regard for the limits of both quantification and
monetization of impacts, the SCC can be used to provide an estimate of
the social benefits of reductions in GHG emissions.
    For at least three reasons, any particular figure will be
contestable. First, scientific and economic knowledge about the impacts
of climate change continues to grow. With new and better information
about relevant questions, including the cost, burdens, and possibility
of adaptation, current estimates will inevitably change over time.
Second, some of the likely and potential damages from climate change--
for example, the loss of endangered species--are generally not included
in current SCC estimates. These omissions may turn out to be
significant in the sense that they may mean that the best current
estimates are too low. As noted by the IPCC Fourth Assessment Report,
``It is very likely that globally aggregated figures underestimate the
damage costs because they cannot include many non-quantifiable
impacts.'' Third, when economic efficiency criteria, under specific
assumptions, are juxtaposed with ethical considerations, the outcome
may be controversial. These ethical considerations, including those
involving the treatment of future generations, should and will also
play a role in judgments about the SCC (see in particular the
discussion of the discount rate, below).
    To date, SCC estimates presented in recent regulatory documents
have varied within and among agencies, including DOT, DOE, and EPA. For
example, a regulation proposed by DOT in 2008 assumed a value of $7 per
metric tonne CO2 \353\ (2006$) for 2011 emission reductions
(with a range of $0-14 for sensitivity analysis). One of the
regulations proposed by DOE in 2009 used a range of $0-$20 (2007$).
Both of these ranges were designed to reflect the value of damages to
the United States resulting from carbon emissions, or the ``domestic''
SCC. In the final MY2011 CAFE EIS, DOT used both a domestic SCC value
of $2/t-CO2 and a global SCC value of $33/t-CO2
(with sensitivity analysis at $80/t-CO2) (in 2006 dollars
for 2007 emissions), increasing at 2.4% per year thereafter. The final
MY2011 CAFE rule also presented a range from $2 to $80/t-
CO2.
---------------------------------------------------------------------------

    \353\ For the purposes of this discussion, we present all values
of the SCC as the cost per metric tonne of CO2 emissions.
Some discussions of the SCC in the literature use an alternative
presentation of a dollar per metric ton of carbon. The standard
adjustment factor is 3.67, which means, for example, that a SCC of
$10 per ton of CO2 would be equivalent to a cost of
$36.70 for a ton of carbon emitted. Unless otherwise indicated, a
``ton'' refers to a metric ton.
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    In the May 2009 proposal leading to today's final rule, EPA
identified preliminary SCC estimates that spanned three orders of
magnitude. EPA's May

2009 proposal also presented preliminary global SCC estimates developed
from a survey analysis of the peer reviewed literature (i.e., meta
analysis). The global mean values from the meta analysis were $68 and
$40/t-CO2 for discount rates of 2% and 3% respectively (in
2006 real dollars for 2007 emissions).\354\
---------------------------------------------------------------------------

    \354\ 74 FR 25094 (May 26, 2009).
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    Since publication of the May 2009 proposal, a federal interagency
working group has established a methodology for selecting a range of
interim SCC estimates for use in regulatory analyses. Today's final
rule uses the five values for the SCC that are the outcome of this
process. A complete description of the methodology used to generate
this interim set of SCC estimates can be found in the RIA for this rule
and in multiple other published rules, including a proposal to limit
vehicle greenhouse gas emissions that requests public comment on the
estimates and underlying methodology.\355\
---------------------------------------------------------------------------

    \355\ Federal Register 40 CFR Parts 86 and 600, September 28,
2009 ``Proposed Rulemaking To Establish Light-Duty Vehicle
Greenhouse Gas Emission Standards and Corporate Average Fuel Economy
Standards; Proposed Rule''.
---------------------------------------------------------------------------

    It should be emphasized that the analysis here is preliminary.
These interim estimates are being used for the short-term while an
interagency group develops a more comprehensive characterization of the
distribution of SCC values for future economic and regulatory analyses.
The interim values should not be viewed as an expectation about the
results of the longer-term process.
    This process will allow the workgroup to explore questions raised
in the May 2009 proposal as they are relevant to the development of SCC
values for use in the long-term. The workgroup may evaluate factors not
currently captured in today's estimates due to time constraints, such
as the quantification of additional impact categories where possible
and an uncertainty analysis. The Administration will seek comment on
all of the scientific, economic, and ethical issues before establishing
improved estimates for use in future rulemakings.
    The outcomes of the Administration's process to develop interim
values are judgments in favor of a) global rather than domestic values,
b) an annual growth rate of 3%, and c) interim global SCC estimates for
2007 (in 2007 dollars) of $56, $34, $20, $10, and $5 per metric ton of
CO2. As noted, this is an emphatically interim SCC value.
The judgments herein will be subject to further scrutiny and
exploration.
3. Application of Interim SCC Estimates to GHG Emissions Reductions
    While no single rule or action can independently achieve the deep
worldwide emissions reductions necessary to halt and reverse the growth
of GHGs, the combined effects of multiple strategies to reduce GHG
emissions domestically and abroad could make a major difference in the
climate change impacts experienced by future generations.\356\ The
projected net GHG emissions reductions associated with the increased
use of renewable fuels reflect an incremental change to projected total
global emissions. Given that the climate response is projected to be a
marginal change relative to the baseline climate, we estimate the
marginal value of changes in climate change impacts over time and use
this value to measure the monetized marginal benefits of the GHG
emissions reductions projected for the increased renewable fuel volumes
required by EISA.
---------------------------------------------------------------------------

    \356\ The Supreme Court recognized in Massachusetts v. EPA that
a single action will not on its own achieve all needed GHG
reductions, noting that ``[a]gencies, like legislatures, do not
generally resolve massive problems in one fell regulatory swoop.''
See Massachusetts v. EPA, 549 U.S. at 524 (2007).
---------------------------------------------------------------------------

    Accordingly, EPA has used the set of interim, global SCC values
described above to estimate the benefits of the increased use of
renewable fuels. The interim SCC values for emissions in 2007, which
reflect the Administration's interim interpretation of the current
literature, are $5, $10, $20, $34, and $56, in 2007 dollars, and are
based on a CO2 emissions change of 1 metric ton in 2007.
Table VIII.C.3-1 presents the interim SCC values for both the years
2007 and 2022 in 2007 dollars.

                                         Table VIII.C.3-1--Interim SCC Schedule (2007$ per metric tonne of CO2)
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                5% (Newell-      Average SCC from                        3% (Newell-
                           Year                                    5%              Pizer)*           3% and 5%              3%              Pizer)*
--------------------------------------------------------------------------------------------------------------------------------------------------------
2007.....................................................                 $5                $10                $20                $34                $56
2022.....................................................                  8                 16                 30                 53                 88
--------------------------------------------------------------------------------------------------------------------------------------------------------
Note: The SCC values are dollar-year and emissions-year specific. These values are presented in 2007$, for individual year of emissions. To determine
  values for other years not presented in the table, use a 3% per year growth rate. SCC values represent only a partial accounting for climate impacts.
* SCC values are adjusted based on Newell and Pizer (2003) to account to future uncertainty in discount rates.

    Table VIII.C.3-2 provides, for the low, base, and high cases, the
average annual GHG emissions reductions in 2022. The annualized
emissions reductions are multiplied by the SCC estimates for 2022 from
Table VIII.C.3-1 to produce the average annual monetized benefit from
the emissions reductions for CO2-equivalent GHGs. This is
equivalent to taking the time stream of emissions from the increase in
renewable fuel volumes, multiplying them by the SCC (which is
increasing at a rate of 3 percent per year), and then discounting the
stream of benefits by 3 percent.

    Table VIII.C.3-2--Average Annual Emissions Reduction (Million Metric Tonnes CO2-e) and Monetized Benefits
                                             (Million 2007$) in 2022
----------------------------------------------------------------------------------------------------------------
                                                                     Low case        Base case       High case
----------------------------------------------------------------------------------------------------------------
Emissions Reductions............................................         136.104         138.411         140.291
5%..............................................................          $1,089          $1,107          $1,122
5% (Newell-Pizer)...............................................          $2,178          $2,215          $2,245
Average SCC from 3% and 5%......................................          $4,138          $4,208          $4,265
3%..............................................................          $7,186          $7,308          $7,407

3% (Newell-Pizer)...............................................         $11,976         $12,179         $12,344
----------------------------------------------------------------------------------------------------------------

    Table VIII.C.3-3 provides, for the high, base, and low cases, the
monetized benefits from the emissions reductions from the increase in
renewable fuel volumes for CO2-equivalent GHGs in 2022. The
SCC estimates for 2022 increase at a rate of 3 percent per year, and