DRIA) for the final rule and invite comment on these assumptions.
2. 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 $7.1 billion
dollars in 2022 (10.6%), relative to the AEO 2007 Reference Case.
3. 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 33%, relative to the 28% 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 263 million bushels (-9.9%)
to 2.4 billion bushels by 2022. In value terms, U.S. exports of corn
would fall by $487 million (-5.7%) to $8 billion in 2022.
    U.S. exports of soybeans would also decrease under this proposal.
FASOM estimates that U.S. exports of soybeans would decrease 96.6
million bushels (-9.3%) to 943 million bushels by 2022. In value terms,
U.S. exports of soybeans would decrease by $691 million (-6.7%) to $9.7
billion in 2022.

  Table IX.A.3-1--Reductions in U.S. Exports From the Reference Case in
                                  2022
------------------------------------------------------------------------
              Exports                      Change            % Change
------------------------------------------------------------------------
Corn in Bushels...................  263 million.........            -9.9
Soybeans in Bushels...............  96.6 million........            -9.3
------------------------------------------------------------------------
      Total Value of Exports               Change            % Change
------------------------------------------------------------------------
Corn (2006$)......................  $487 million........            -5.7
Soybeans (2006$)..................  $691 million........            -6.7
------------------------------------------------------------------------

    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.
Distillers dried grains with solubles (DDGS) are a byproduct of dry
milling ethanol production, and gluten meal and gluten feed are
byproducts of wet milling ethanol production. By 2022, FASOM predicts
ethanol byproducts used in feed would increase 19% to 30 million tons,
compared to 25 million tons under the Reference Case.

    Table IX.A.3-2--Percent Change in Ethanol Byproducts Use in Feed
                     Relative to the Reference Case
------------------------------------------------------------------------
                          Category                               2022
------------------------------------------------------------------------
Ethanol Byproducts.........................................          19%
------------------------------------------------------------------------

    The EISA cellulosic ethanol requirements result in the production
of residual agriculture products as well as dedicated energy crops. By
2022, FASOM predicts production of 90 million tons of corn residue and
18 million tons of switchgrass. Sugarcane bagasse for cellulosic
ethanol production increases by 15.7 million tons to 19.7 million tons
in 2022 relative to the Reference Case.
4. 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 price of U.S. farm land would also increase. Our
analysis shows that land prices would increase by about 21% by 2022,
relative to the Reference Case. FASOM estimates an increase of 3.2
million acre increase (3.9%) in harvested corn acres, relative to 83.4
million acres harvested under the Reference Case by 2022.\477\ Most of
the new corn acres come from a reduction in existing crop acres, such
as rice, wheat, and hay.
---------------------------------------------------------------------------

    \477\ Total U.S. planted acres increases to 92.2 million acres
from the Reference Case level of 89 million acres in 2022.
---------------------------------------------------------------------------

    Though demand for biodiesel increases, FASOM predicts a fall in
U.S. soybean acres harvested, assuming soybean-based biodiesel meets
the EISA GHG emission reduction thresholds. According to the model,
harvested soybean acres would decrease by approximately 0.4 million
acres (-0.5%), relative to the Reference Case acreage of 71.5 million
acres in 2022. Despite the decrease in soybean acres in 2022, soybean
oil production would increase by 0.4 million tons (4.0%) by 2022 over
the Reference Case. Additionally, FASOM predicts that soybean oil
exports would decrease 1.3 million tons by 2022 (-52%) relative to the
Reference Case.
    As the demand for cellulosic ethanol increases, most of the
production is derived from corn residue harvesting. As demand for
cellulosic ethanol from bagasse increases, sugarcane acres increase by
0.7 millions acres (55%) to 1.9 million acres by 2022. In addition,
some of the cellulosic ethanol comes from switchgrass, which is not
produced under the Reference Case. In the scenario analyzed, 2.8
million acres of switchgrass will be planted by 2022. As described in
Section V, for both the Reference Case and the Control Case, we assume
32 million acres would remain in the Conservation Reserve Program
(CRP). Therefore, some of the new corn, soybean, and switchgrass acres
may be indirectly coming from former CRP land that is not re-enrolled
in the program.

Table IX.A.4-1--Change in U.S. Crop Acres Relative to the Reference Case
                                 in 2022
                           [Millions of acres]
------------------------------------------------------------------------
                     Crop                          Change      % Change
------------------------------------------------------------------------
Corn..........................................          3.2          3.9
Soybeans......................................         -0.4         -0.5
Sugarcane.....................................          0.7           55
Switchgrass...................................          2.8          N/A
------------------------------------------------------------------------

    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
897 million pounds (3.4%) over the Reference Case nitrogen fertilizer
use of 26.2 billion pounds. In 2022, U.S. phosphorous fertilizer use
would increase by 496 million pounds (8.6%) relative to the Reference
Case level of 5.8 billion pounds.

 Table IX.A.4-2--Change in U.S. Fertilizer Use Relative to the Reference
                                  Case
                          [Millions of pounds]
------------------------------------------------------------------------
                  Fertilizer                       Change      % Change
------------------------------------------------------------------------
Nitrogen......................................          897          3.4
Phosphorous...................................          496          8.6
------------------------------------------------------------------------

5. Impact on U.S. Food Prices
    Due to higher commodity prices, FASOM estimates that U.S. food
costs \478\ would increase by roughly $10 per person per year by 2022,
relative to the Reference Case.\479\ Total effective farm gate food
costs would increase by $3.3 billion (0.2%) in 2022.\480\ 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.\481\
---------------------------------------------------------------------------

    \478\ 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.
    \479\ These estimates are based on U.S. Census population
projections of 318 million people in 2017 and 330 million people in
2022. See http://www.census.gov/population/www/projections/natsum.html.
    \480\ Farm Gate food prices refer to the prices that farmers are
paid for their commodities.
    \481\ See www.ers.usda.gov/Briefing/CPIFoodAndExpenditures/Data/table15.htm.
---------------------------------------------------------------------------

6. International Impacts
    Changes in the U.S. agriculture economy are likely to have effects
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 model to assess the impacts of the increased use of renewable
fuels in the U.S. on world agricultural markets.
    The FAPRI modeling shows that world corn prices would increase by
7.5% to $3.69 per bushel in 2022, relative to the Reference Case. The
impact on world soybean prices is somewhat smaller, increasing 5.6% to
$9.94 per bushel in 2022.
    Changes to the global commodity trade markets and world commodity
prices result in changes in international land use. The FAPRI model
provides international change in crop acres as a result of the RFS2
proposal. Brazil has the largest positive change in crop acres in 2022,
followed by the U.S., Nigeria, India, Paraguay, and China. The FAPRI
model estimates that Brazil crop acres increase by 3.1 million acres
(2.0%) to 153.6 million acres relative to the Reference Case. Total
U.S. acres increase by 2.3 million acres (1.0%) in 2022 to 232.6
million acres. Nigeria has an increase in crop acres of 1.5 million
acres (5.9%) to 27.3 million acres in 2022. India's total crop acres
increase by 1.0 million acres (0.3%) to 326 million acres in 2022.
Total crop acres in Paraguay increase by 0.8 million acres (6.9%) to 12
million acres. China's total crop acres increase by 0.4 million acres
(0.2%) to 257.8 million acres in 2022.
BILLING CODE 6560-50-P

[GRAPHIC] [TIFF OMITTED] TP26MY09.011

    The RFS2 proposal results in higher international commodity prices,
which would impact world food consumption.\482\ The FAPRI model
indicates that world consumption of corn for food would decrease by 1.1
million metric tons in 2022 relative to the Reference Case. Similarly,
the FAPRI model estimates that world consumption of wheat for food
would decrease by 0.6 million metric tons in 2022. World consumption of
oil for food (e.g., vegetable oils) decreases 1.8 million metric tons
by 2022. The model also estimates a small change in world meat
consumption, decreasing by 0.3 million metric tons in 2022. When
considering all the food uses included in the model, world food
consumption decreases by 0.9 million metric tons by 2022 (-0.04%).
While FAPRI provides estimates of changes in world food consumption,
estimating effects on global nutrition is beyond the scope of this
analysis.
---------------------------------------------------------------------------

    \482\ The food commodities included in the FAPRI model include
corn, wheat, sorghum, barley, soybeans, sugar, peanuts, oils, beef,
pork, poultry, and dairy products.

    Table IX.A.6-1--Change in World Food Consumption Relative to the
                             Reference Case
                        [Millions of metric tons]
------------------------------------------------------------------------
                          Category                               2022
------------------------------------------------------------------------
Corn.......................................................         -1.1
Wheat......................................................         -0.6
Vegetable Oils.............................................         -1.8
Meat.......................................................         -0.3
                                                            ------------
  Total Food...............................................         -0.9
------------------------------------------------------------------------

    Additional information on the U.S. agricultural sector and
international trade impacts of this proposal is described in more
detail in the DRIA (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
estimate the monetary value of the energy security benefits of the RFS2
mandated volumes in comparison to the Reference Case by estimating the
impact of the expanded use of renewable fuels on U.S. oil imports and
avoided U.S. oil import expenditures. In the second section, a
methodology is described for estimating the energy security benefits of
reduced U.S. oil imports. The final section summarizes the energy
security benefits to the U.S. associated with this proposal.
1. Implications of Reduced Petroleum Use on U.S. Imports
    In 2007, U.S. petroleum imports represented 19.5% of total U.S.
imports of all goods and services.\483\ In 2005, the United States
imported almost 60% of the petroleum it consumed. This compares roughly
to 35% of petroleum from imports in 1975.\484\ Transportation accounts
for 70% of the U.S. petroleum consumption. It is clear that petroleum
imports have a significant impact on the U.S. economy. Diversifying
transportation fuels in the U.S. is expected to lower U.S. petroleum
imports. To estimate the impacts of this proposal on the U.S.'s
dependence on

imported oil, we calculate avoided U.S. expenditures on petroleum
imports.
---------------------------------------------------------------------------

    \483\ Bureau of Economic Affairs: ``U.S. International
Transactions, Fourth Quarter of 2007'' by Elena L. Nguyen and
Jessica Melton Hanson, April 2008.
    \484\ Davis, Stacy C.; Diegel, Susan W., Transportation Energy
Data Book: 25th Edition, Oak Ridge National Laboratory, U.S.
Department of Energy, ORNL-6974, 2006.
---------------------------------------------------------------------------

    For the proposal, EPA analyzed two approaches to estimate the
reductions in U.S. petroleum imports. The first approach utilizes a
model of the U.S. energy sector, the National Energy Modeling System
(NEMS), to quantify the type and volume of reduced petroleum imports
based on supply and demand for specific fuels in a given year. The
National Energy Modeling System (NEMS) is a computer-based, energy-
economy modeling system of U.S. energy markets through the 2030 time
period. 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. NEMS is designed and implemented
by the Energy Information Administration (EIA) of the U.S. Department
of Energy (DOE). For this analysis, the NEMS model was run with the
2007 AEO levels of biofuels in the Reference Case compared with the
biofuel volume RFS2 requirements.
    Considering the regional nature of U.S. imports of petroleum
imports, a second approach was utilized as well to estimate the impacts
of the RFS2 proposal on U.S. oil imports. This approach is labeled
``Regional Gasoline Market'' approach. This approach makes the
assumption that one half of the ethanol market is in the Northeast
region of the U.S., which also comprises about half of the nation's
gasoline demand. For this analysis, it is estimated that ethanol would
displace imported gasoline or gasoline blend stocks in the Northeast,
but not elsewhere in the country. Therefore, to derive the portion of
the new renewable fuels which would offset U.S. petroleum imports (and
not impact domestic refinery production), we multiplied the total
volume of petroleum fuel displaced by 50 percent to represent that
portion of the ethanol which would be used in the Northeast, and 50
percent again to only account for that which would offset imports. The
rest of the ethanol, including half of the ethanol presumed to be used
in the Northeast, is presumed to offset domestic gasoline production,
which ultimately offsets crude oil inputs at refineries. Biodiesel and
renewable diesel are presumed to offset domestic diesel fuel
production.
    The results shown in Table IX.B.1-1 below reflect the net lifecycle
reductions in U.S. oil imports projected by NEMS. The net lifecycle
reductions include the upstream petroleum used to produce renewable
fuels, gasoline and diesel, as well as the petroleum directly used by
end-users.

    Table IX.B.1-1--Net Reductions in Oil Imports in 2022 (NEMS Model
                                Results)
                      [Millions of barrels per day]
------------------------------------------------------------------------
                   Category of reduction                         2022
------------------------------------------------------------------------
Imports of Finished Petroleum Products.....................        0.823
Imports of Crude Oil.......................................      (0.007)
Total Reduction............................................        0.815
Percent Reduction..........................................        6.15%
------------------------------------------------------------------------

    The NEMS model projects that for the year 2022 all of the reduction
in petroleum imports comes out of finished petroleum products. NEMS
projects that 91% of the reductions in 2022 come from reduced net
imports of crude oil and finished petroleum products (as compared to a
9% reduction in domestic U.S. production).
    The results shown in Table IX.B.1-2 below reflect the net lifecycle
reductions in U.S. oil imports projected by the use of the Regional
Gasoline Market approach detailed above.

Table IX.B.1-2--Net Reductions in Oil Imports in 2022 (Regional Gasoline
                        Market Approach Results)
                      [Millions of barrels per day]
------------------------------------------------------------------------
                   Category of reduction                         2022
------------------------------------------------------------------------
Imports of Finished Petroleum Products.....................        0.250
Imports of Crude Oil.......................................        0.637
Total Reduction............................................        0.887
Percent Reduction..........................................        6.17%
------------------------------------------------------------------------

    The Regional Gasoline Market approach projects that for 2022, 72%
of the petroleum supply displacement (on a volume basis) comes out of
reduced net crude oil imports, and 28% out of net imports of finished
petroleum products (excluding biofuels). Using our two approaches for
projecting total petroleum import reductions (the NEMS and the Regional
Gasoline Market), we estimate that petroleum product imports will fall
between 0.815 to 0.887 million barrels per day in 2022 as a result of
the RFS2 proposal.
    Using the NEMS model, we also calculated the change in expenditures
in both U.S. petroleum and ethanol imports with the RFS2 proposal and
compared these with the U.S. trade position measured as U.S. net
exports of all goods and services economy-wide. Changes in fuel
expenditures were estimated by multiplying the changes in gasoline,
diesel, and ethanol net imports by the respective AEO 2008 wholesale
gasoline and distillate price forecasts, and ethanol price forecasts
from the Food and Agricultural Policy Research Institute (FAPRI) for
the specific analysis years. In Table IX.B.1-3, the net expenditures in
reduced petroleum imports and increased ethanol imports are compared to
the total value of U.S. net exports of goods and services for the whole
economy for 2022. The U.S. net exports of goods and services estimates
are taken from Energy Information Administration's Annual Energy
Outlook 2008. We project that avoided expenditures on imported
petroleum products due to this proposal would be roughly $16 billion in
2022. Relative to the 2022 projection, the total avoided expenditures
on liquid transportation fuels are projected to be $12.4 billion with
the RFS2 proposal.

   Table IX.B.1-3--Changes in Expenditures on Transportation Fuel Net
                                 Imports
                           [Billions of 2006$]
------------------------------------------------------------------------
                         Category                               2022
------------------------------------------------------------------------
AEO Total Net Exports.....................................           16
Expenditures on Net Petroleum Imports.....................       (15.96)
Expenditures on Net Ethanol and Biodiesel Imports.........         3.52
Net Expenditures on Transportation Fuel Imports...........       (12.44)
------------------------------------------------------------------------

2. Energy Security Implications
    In order to understand the energy security implications of reducing
U.S. oil imports, EPA has worked with Oak Ridge National Laboratory
(ORNL), which has developed approaches for evaluating the social costs
and energy security implications of oil use. In a new study entitled
``The Energy Security Benefits of Reduced Oil Use, 2006-2015,''
completed in February, 2008, ORNL has updated and applied the
analytical approach used in the 1997 Report ``Oil Imports: An
Assessment of Benefits and Costs.'' 485 486 This new study
is included as part of the record in this rulemaking.\487\
---------------------------------------------------------------------------

    \485\ 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.
    \486\ 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.
    \487\ 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 approach developed by ORNL estimates the incremental benefits
to society, in dollars per barrel, of reducing U.S. oil imports, called
the ``oil premium.'' Since the 1997 publication of the ORNL Report,
changes in oil market conditions, both current and projected, suggest
that the magnitude of the oil premium has changed. Significant driving
factors that have been revised include: Oil prices, current and
anticipated levels of OPEC production, U.S. import levels, the
estimated responsiveness of regional oil supplies and demands to price,
and the likelihood of oil supply disruptions. For this analysis, oil
prices from the AEO 2007 were used. Using the ``oil premium'' approach,
the analysis calculates estimates of benefits of improved energy
security from reduced U.S. oil imports due to this proposal.
    When conducting this analysis, ORNL considered the full economic
cost of importing petroleum into the U.S. The full economic cost of
importing petroleum into the U.S. is defined for this analysis to
include two components in addition to the purchase price of petroleum
itself. These are: (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 ``demand'' or ``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 was excluded from this
analysis because its attribution to particular missions or activities
is difficult.
    Also excluded from the prior analysis was risk-shifting that might
occur as the U.S. reduces its dependency on petroleum and increases its
use of biofuels. The analysis to date focused on the potential for
biofuels to reduce oil imports, and the resulting implications of lower
imports for energy security. The Agency recognizes that as the U.S.
relies more heavily on biofuels, such as corn-based ethanol, there
could be adverse consequences from a supply-disruption associated with,
for example, a long-term drought. While the causal factors of a supply-
disruption from imported petroleum and, alternatively, biofuels, are
likely to be unrelated, diversifying the sources of U.S. transportation
fuel will provide energy security benefits. The Agency was not able to
conduct an analysis of biofuel supply disruption issue for this
proposal.
    Between today's proposal and the final rulemaking, EPA will attempt
to broaden our energy security analysis to incorporate estimates of
overall motor fuel supply and demand flexibility and reliability, and
impacts of possible agricultural sector market disruptions (for
example, a drought) for presentation in the final rule. The expanded
analysis will also consider how the use of biofuels can alter short and
long run elasticity (flexibility) in the motor fuel market, with
implications for robustness of the fuel system in the face of diverse
supply shocks. As part of this analysis, the Agency plans on analyzing
those factors that can cause shifts in the prices of biofuels, and the
impact these factors have on the energy security estimate.
    EPA sponsored an independent-expert peer review of the most recent
ORNL study. A report compiling the peer reviewers' comments is provided
in the docket.\488\ In addition, EPA has worked with ORNL to address
comments raised in the peer review and develop estimates of the energy
security benefits associated with a reduction in U.S. oil imports for
this proposal. In response to peer reviewer comments, EPA modified the
ORNL model by changing several key parameters involving OPEC supply
behavior, the responsiveness of oil demand and supply to a change in
the world oil price, and the responsiveness of U.S. economic output to
a change in the world oil price. EPA is soliciting comments on how to
incorporate additional peer reviewer comments into the ORNL energy
security analysis. (See the DRIA, Chapter 5, for more information on
how EPA responded to peer reviewer comments.)
---------------------------------------------------------------------------

    \488\ Peer Review Report Summary: Estimating the Energy Security
Benefits of Reduced U.S. Oil Imports, ICF, Inc., September 2007.
---------------------------------------------------------------------------

    With these changes for this proposal, ORNL has estimated that the
total energy security benefits associated with a reduction of imported
oil is $12.38/barrel. Based upon alternative sensitivities about OPEC
supply behavior and the responsiveness of oil demand and supply to a
change in the world oil price, the energy security premium ranged from
$7.65 to $17.23/barrel. Highlights of the analysis are described below.
a. Effect of Oil Use on Long-Run Oil Price, U.S. Import Costs, and
Economic Output
    The first component of the full 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. ORNL estimates this component of the energy
security benefit to be $7.65/barrel of U.S. oil imports reduced. A
number of the peer reviewers suggested a variety of ways OPEC and other
oil market participants might react to a decrease in the quantity of
oil purchased by the U.S. ORNL has attempted to reflect a variety of
possible market reactions in the analysis, but continues to evaluate
ways to more explicitly model OPEC and other market participants'
behavior. EPA welcomes comments on this issue. Based upon alternative
sensitivities about OPEC supply behavior, the price-responsiveness of
combined non-OPEC, non-U.S. supply and demand and a lower GDP
elasticity with respect to disrupted oil prices, the monopsony premium
ranged from $3.35-$12.45/barrel of U.S. imported oil reduced.
    EPA recognizes that as the world price of oil falls in response to
lower U.S. demand for oil, there is the potential for an increase in
oil use outside the U.S. This so-called international oil ``take back''
or ``rebound'' effect is hard to estimate. Given that oil consumption
patterns vary across countries, there will be different demand
responses to a change in the world price of crude oil. For example, in
Europe, the price of crude oil comprises a much smaller portion of the
overall fuel prices seen by consumers than in the U.S. Since Europeans
pay significantly more than their U.S. counterparts for transportation
fuels, a decline in the price of crude oil is likely to have a smaller
impact on demand. In many other countries, particularly developing
countries, such as China and India, oil is used more widely in
industrial and even electricity applications, although China and
India's energy picture is evolving rapidly. In addition, many countries
around the world subsidize

their oil consumption. It is not clear how oil consumption would change
due to changes in the market price of oil with the current pattern of
subsidies. Emerging trends in worldwide oil consumption patterns
illustrates the difficulty in trying to estimate the overall effect of
a reduction in world oil price. However, the Agency recognizes that
this effect is important to capture and is examining methodologies for
quantifying this effect. EPA is exploring the development of this
effect at the regional and country level in an effort to capture the
net effect of different drivers. For example, a lower world oil price
might encourage consumption of oil, but a country might deploy programs
and policies discouraging oil consumption, which would have the net
effect of lowering oil consumption to some level less than otherwise
would be expected. EPA solicits comments on how to estimate this
effect.
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), the largest stockpile of government-owned emergency
crude oil in the world, to respond; and the sensitivity of the U.S.
economy to sudden price increases. While 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 import levels or demand
flexibility can affect the magnitude of potential increases in oil
price due to supply disruptions. Disruptions are uncertain events, so
the costs of alternative possible disruptions are weighted by
disruption probabilities. The probabilities used by the ORNL study are
based on a 2005 Energy Modeling Forum \489\ synthesis of expert
judgment and are used to determine an expected value of disruption
costs, and the change in those expected costs given reduced U.S. oil
imports. ORNL estimates this component of the energy security benefit
to be $4.74/barrel of U.S. imported oil reduced. Based upon alternative
sensitivities about OPEC supply behavior, the price-responsiveness of
combined non-OPEC, non-U.S. supply and demand and a lower GDP
elasticity with respect to disrupted oil prices, the macroeconomic
disruption premium ranged from $2.64-$6.96/barrel of U.S. imported oil
reduced. EPA continues to review recent literature on the macroeconomic
disruption premium and welcomes comment on this issue.
---------------------------------------------------------------------------

    \489\ Stanford Energy Modeling Forum, Phillip C. Beccue and
Hillard G. Huntington, ``An Assessment of Oil Market Disruption
Risks,'' Final Report, EMF SR 8, October, 2005.
---------------------------------------------------------------------------

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 cost 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. 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.
    A majority of the peer reviewers agreed with the exclusion of
military expenditures from the current premium analysis primarily
because of the difficulty in defining and measuring how military
programs and expenditures might respond to incremental changes in U.S.
oil imports. One reviewer clearly opposed including military costs on
principle, and one peer reviewer clearly supported their inclusion if
they could be shown to vary with import levels. The matter of whether
military needs and programs can and do vary with U.S. oil imports or
consumption levels would require careful consideration and analysis. It
also calls for expertise in areas outside the scope of the peer review
such as national security and military affairs. EPA solicits comment in
this area.
d. Anticipated Future Effort
    Between the proposal and the final rule, EPA intends to undertake a
variety of actions to improve its energy security premium estimates.
For the monopsony premium, we intend to develop energy security
premiums with alternative AEO oil price cases (e.g., Reference, High,
Low), develop a dynamic analysis methodology (i.e., how the energy
security premium evolves through time), and assess and apply literature
on OPEC strategic behavior/gaming models where possible. For the
macroeconomic disruption impacts, EPA intends to examine recent
literature on the elasticity of GDP to the oil price. Based upon that
literature review, we intend to determine whether there is a difference
in macro disruption impacts in the pre-2000 and post-2000 time period.
Further, we intend to break down the macroeconomic disruption costs by
GDP losses and oil import costs.
    EPA solicits comments on the energy security analysis in a number
of areas. Specifically, EPA is requesting comment on its interpretation
of ORNL's results, ORNL's methodology, the monopsony effect, and the
macroeconomic disruption effect.
e. Total Energy Security Benefits
    Total annual energy security benefits associated with this proposal
were derived from the estimated reductions in imports of finished
petroleum products and crude oil using an energy security premium price
of $12.38/barrel of reduced U.S. oil imports. Based on these values, we
estimate that the total annual energy security benefits would be $3.7
billion in 2022 (in 2006 dollars).

C. Benefits of Reducing GHG Emissions

1. Introduction
    The wider use of renewable fuels from this proposal results in
reductions in greenhouse gas (GHG) emissions. Carbon dioxide
(CO2) and other GHGs mix well in the atmosphere, regardless
of the location of the source, with each unit of emissions affecting
global regional climates; and therefore, influencing regional
biophysical systems. The effects of changes in GHG emissions are felt
for decades to centuries given the atmospheric lifetimes of GHGs. This
section provides estimates for the marginal and total benefits that
could be monetized for the projected GHG emissions reductions of the
proposal. EPA requests comment on the approach utilized to estimate the
GHG benefits associated with the proposal.
2. Marginal GHG Benefits Estimates
    The projected net GHG emissions reductions associated with the
proposal reflect an incremental change to projected total global
emissions.

Therefore, as shown in Section VI.G, the projected global climate
signal will be small but discernable (i.e., incrementally lower
projected distribution of global mean surface temperatures). Given that
the climate response is projected to be a marginal change relative to
the baseline climate, it is conceptually appropriate to use an approach
that estimates the marginal value of changes in climate change impacts
over time as an estimate for the monetized marginal benefit of the GHG
emissions reductions projected for this proposal. The marginal value of
carbon is equal to the net present value of climate change impacts over
hundreds of years of one additional net global metric ton of GHGs
emitted to the atmosphere at a particular point in time. This marginal
value (i.e., cost) of carbon is sometimes referred to as the ``social
cost of carbon.''
    Based on the global implications of GHGs and the economic
principles that follow, EPA has developed ranges of global, as well as
U.S., marginal benefits estimates (Table IX.C.2-1).\490\ It is
important to note at the outset that the estimates are incomplete since
current methods are only able to reflect a partial accounting of the
climate change impacts identified by the IPCC (discussed more below).
Also, domestic estimates omit potential impacts on the United States
(e.g., economic or national security impacts) resulting from climate
change impacts in other countries. The global estimates were developed
from a survey analysis of the peer reviewed literature (i.e., meta
analysis). U.S. estimates, and a consistent set of global estimates,
were developed from a single model and are highly preliminary, under
evaluation, and likely to be revised. The latter set of estimates was
developed because the peer reviewed literature does not currently
provide regional (i.e., at the U.S. or China level) marginal benefits
estimates, and it was important to have a consistent set of regional
and global estimates. Ranges of estimates are provided to capture some
of the uncertainties associated with modeling climate change impacts.
---------------------------------------------------------------------------

    \490\ For background on economic principles and the marginal
benefit estimates, see Technical Support Document on Benefits of
Reducing GHG Emissions, U.S. Environmental Protection Agency, June
12, 2008, www.regulations.gov (search phrase ``Technical Support
Document on Benefits of Reducing GHG Emissions'').
---------------------------------------------------------------------------

    The range of estimates is wide due to the uncertainties relating to
socio-economic futures, climate responsiveness, impacts modeling, as
well as the choice of discount rate. For instance, for 2007 emission
reductions and a 2% discount rate the global meta analysis estimates
range from $-3 to $159/tCO2, while the U.S. estimates range
from $0 to $16/tCO2. For 2007 emission reductions and a 3%
discount rate, the global meta-estimates range from $-4 to $106/
tCO2, and the U.S. estimates range from $0 to $5/
tCO2.\491\ The global meta analysis mean values for 2007
emission reductions are $68 and $40/tCO2 for discount rates
of 2% and 3%, respectively (in 2006 real dollars), while the domestic
mean value from a single model are $4 and $1/tCO2 for the
same discount rates. The estimates for future year emission changes
will be higher as future marginal emissions increases are expected to
produce larger incremental damages as physical and economic systems
become more stressed as the magnitude of climate change increases.\492\
---------------------------------------------------------------------------

    \491\ See Table IX.C.1 for global (FUND) estimates consistent
with the U.S. estimates.
    \492\ The IPCC suggests an increase of 2-4% per year (IPCC WGII,
2007. Climate Change 2007--Impacts, Adaptation and Vulnerability.
Contribution of Working Group II to the Fourth Assessment Report of
the IPCC, http://www.ipcc.ch/. For Table IX.C.1., we assumed the
estimates increased at 3% per year. For the final rule, we
anticipate that we will explicitly estimate FUND marginal benefits
values for each emissions reduction year.

                Table IX.C.2-1--Marginal GHG Benefits Estimates for Discount Rates of 2%, 3%, and 7% and Year of Emissions Change in 2022
                                                         [All values are reported in 2006$/tCO2]
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                      2%                               3%                             7% \b\
                                                      --------------------------------------------------------------------------------------------------
                                                          Low      Central      High       Low      Central      High       Low      Central      High
--------------------------------------------------------------------------------------------------------------------------------------------------------
Meta global..........................................         -2        105        247         -2         62        165        n/a        n/a        n/a
FUND global..........................................         -4        136       1083         -4         26        206         -2         -1          9
FUND domestic........................................      \a\ 0          7         26      \a\ 0          2          9      \a\ 0      \a\ 0      \a\ 0
--------------------------------------------------------------------------------------------------------------------------------------------------------
\a\ These estimates, if explicitly estimated, may be greater than zero, especially in later years. They are currently reported as zero because the
  explicit estimates for an earlier year were zero and were grown at 3% per year. However, we do not anticipate that the explicit estimates for these
  later years would be significantly above zero given the magnitude of the current central estimates for discount rates of 2% and 3% and the effect of
  the high discount rate in the case of 7%.
\b\ Except for illustrative purposes, the marginal benefits estimates in the peer reviewed literature do not use consumption discount rates as high as
  7%.

    The meta analysis ranges were developed from the Tol (2008) meta
analysis. The meta analysis range only includes global estimates
generated by more recent peer reviewed studies (i.e., published after
1995). In addition, the ranges only consider regional aggregations
using simple summation and intergenerational consumption discount rates
of approximately 2% and 3%.\493\ Discount rates of 2% and 3% are
consistent with EPA and OMB guidance on intergenerational discount
rates (EPA, 2000; OMB, 2003).\494\ The estimated distributions of the
meta global estimates are right skewed with long right tails, which is
consistent with characterizations of the low probability high impact
damages (see the DRIA for the estimated probability density functions
by discount rate).\495\ The central meta estimates in Table IX.C.2-1
are means, and the low and high are the 5th and 95th percentiles. Means
are

presented because, as a central statistic, they better represent the
skewed shape of these distributions compared to medians.
---------------------------------------------------------------------------

    \493\ Tol (2008) is an update of the Tol (2005) meta analysis.
Tol (2005) was used in the IPCC Working Group II's Fourth Assessment
Report (IPCC WGII, 2007).
    \494\ OMB and EPA guidance on inter-generational discounting
suggests using a low but positive discount rate if there are
important intergenerational benefits/costs. Consumption discount
rates of 1-3% are given by OMB and 0.5-3% by EPA (OMB Circular A-4,
2003; EPA Guidelines for Preparing Economic Analyses, 2000).
    \495\ E.g., Webster, M., C. Forest, J.M. Reilly, M.H. Babiker,
D.W. Kicklighter, M. Mayer, R.G. Prinn, M. Sarofim, A.P. Sokolov,
P.H. Stone & C. Wang, 2003. Uncertainty Analysis of Climate Change
and Policy Response, Climatic Change 61(3): 295-320. Also, see
Weitzman, M., 2007, ``The Stern Review of the Economics of Climate
Change,'' Journal of Economic Literature. Weitzman, M., 2007,
``Structural Uncertainty and the Statistical Life in the Economics
of Catastrophic Climate Change,'' Working paper http://econweb.fas.harvard.edu/faculty/weitzman/papers/ValStatLifeClimate.pdf.
---------------------------------------------------------------------------

    The consistent domestic and global estimates were developed using
the FUND integrated assessment model (i.e., the Climate Framework for
Uncertainty, Negotiation, and Distribution).\496\ The ranges were
generated from sensitivity analyses where we varied assumptions with
respect to climate sensitivity (1.5 to 6.0 degrees Celsius),\497\ the
socio-economic and emissions baseline scenarios (the FUND default
baseline and three baselines from the Intergovernmental Panel on
Climate Change (IPCC) Special Report on Emissions Scenarios,
SRES),\498\ and the consumption discount rates of approximately 2%, 3%,
and 7%, where 2% and 3% are consistent with intergenerational
discounting.\499\ Furthermore, the model was calibrated to the EPA
value of a statistical life of $7.4 million (in 2006 real
dollars).\500\ The FUND global estimates are the sum of the regional
estimates within FUND. The FUND global and domestic central values in
Table IX.C.2-1 are weighted averages of the FUND estimates from the
sensitivity analysis (see the DRIA for details). The low and high
values are the low and high estimates across the sensitivity runs.
---------------------------------------------------------------------------

    \496\ FUND is a spatially and temporally consistent framework--
across regions of the world (e.g., U.S., China), impacts sectors,
and time. FUND explicitly models impacts sectors in 16 global
regions. FUND is one of the few models in the world that explicitly
models global and regional marginal benefits estimates. Numerous
applications of FUND have been published in the peer reviewed
literature dating back to 1997. See http://www.fnu.zmaw.de/FUND.5679.0.html.
    \497\ In IPCC reports, equilibrium climate sensitivity refers to
the equilibrium change in the annual mean global surface temperature
following a doubling of the atmospheric equivalent carbon dioxide
concentration. The IPCC states that climate sensitivity is
``likely'' to be in the range of 2 [deg]C to 4.5 [deg]C and
described 3 [deg]C as a ``best estimate'', which is the mode (or
most likely) value. The IPCC goes on to note that climate
sensitivity is ``very unlikely'' to be less than 1.5 [deg]C and
``values substantially higher than 4.5 [deg]C cannot be excluded.''
IPCC WGI, 2007, Climate Change 2007--The Physical Science Basis,
Contribution of Working Group I to the Fourth Assessment Report of
the IPCC, http://www.ipcc.ch/
    \498\ The IMAGE model SRES baseline data was used for the A1b,
A2, and B2 scenarios (IPCC, 2000. Special Report on Emissions
Scenarios. A special report of Working Group III of the
Intergovernmental Panel on Climate Change. Cambridge University
Press, Cambridge).
    \499\ The EPA guidance on intergenerational discounting states
that ``[e]conomic analyses should present a sensitivity analysis of
alternative discount rates, including discounting at two to three
percent and seven percent as in the intra-generational case, as well
as scenarios using rates in the interval one-half to three percent
as prescribed by optimal growth models.'' (EPA, 2000).
    \500\ This number may be updated to be consistent with recent
EPA regulatory impact analyses that have used a value of $6.4
million (in 2006 real dollars).
---------------------------------------------------------------------------

    From Table IX.C.2-1, we see that, in terms of the current monetized
benefits, the domestic marginal benefits are a fraction of the global
marginal benefits. Given uncertainties and omitted impacts, it is
difficult to estimate the actual ratio of total domestic benefits to
total global benefits. The estimates suggest that an emissions
reduction will have direct benefits for current and future U.S.
populations and large benefits for global populations. The long-run and
intergenerational implications of GHG emissions are evident in the
difference in results across discount rates. In the current modeling,
there are substantial long-run benefits (beyond the next two decades to
over 100 years) and some near-term benefits as well as negative effects
(e.g., agricultural productivity and heating demand). High discount
rates give less weight to the distant benefits in the net present value
calculations, and more weight to near-term effects. While not obvious
in Table IX.C.2-1, an additional unit of emissions in the higher
climate sensitivity scenarios, versus the lower climate sensitivity
scenarios, is estimated to have a proportionally larger effect on the
rest of the world compared to the U.S. (see more detailed results in
DRIA). These points are discussed more below.
3. Discussion of Marginal GHG Benefits Estimates
    This section briefly discusses important issues relevant to the
marginal benefits estimates in Table IX.C.2-1 (see the DRIA for more
extensive discussion). The broad range of estimates in Table IX.C.2-1
reflects some of the uncertainty associated with estimating monetized
marginal benefits of climate change. The meta analysis range reflects
differences in these assumptions as well as differences in the modeling
of changes in climate and impacts considered and how they were modeled.
EPA considers the meta analysis results to be more robust than the
single model estimates in that the meta results reflect uncertainties
in both models and assumptions.
    The current state-of-the-art for estimating benefits is important
to consider when evaluating policies. There are significant partially
unquantified and omitted impact categories not captured in the
estimates provided above. The IPCC WGII (2007) concluded that current
estimates are ``very likely'' to be underestimated because they do not
include significant impacts that have yet to be monetized.\501\ Current
estimates do not capture many of the main reasons for concern about
climate change, including nonmarket damages (e.g., species existence
value and the value of having the option for future use), the effects
of climate variability, risks of potential extreme weather (e.g.,
droughts, heavy rains and wind), socially contingent effects (such as
violent conflict or humanitarian crisis), and thresholds (or tipping
points) associated with species, ecosystems, and potential long-term
catastrophic events (e.g., collapse of the West Antarctic Ice Sheet,
slowing of the Atlantic Ocean Thermohaline Circulation).
Underestimation is even more likely when one considers that the current
trajectory for GHG emissions is higher than typically modeled, which
when combined with current regional population and income trajectories
that are more asymmetric than typically modeled, imply greater climate
change and vulnerability to climate change. See the DRIA for an
initial, partial list of impacts that are currently not modeled in the
FUND model and are thus not reflected in the FUND estimates. EPA is
planning to develop a full assessment of what is not currently being
captured in FUND for the final rule. In addition, EPA plans to quantify
omitted impacts and update impacts currently represented to the maximum
extent possible for the final rule.
---------------------------------------------------------------------------

    \501\ IPCC WGII, 2007. In the IPCC report, ``very likely'' was
defined as a greater than 90% likelihood based on expert judgment.
---------------------------------------------------------------------------

    The current estimates are also deterministic in that they do not
account for the value people have for changes in risk due to changes in
the likelihood of potential impacts associated with reductions in
CO2 and other GHG emissions (i.e., a risk premium). This is
an issue that has concerned Weitzman and other economists.\502\ We plan
to conduct a formal uncertainty analysis for the final rule to attempt
to account for, to the extent possible, these and other changes in
uncertainty.
---------------------------------------------------------------------------

    \502\ E.g, Webster et al., 2003; Weitzman, M., 2007. http://econweb.fas.harvard.edu/faculty/weitzman/papers/ValStatLifeClimate.pdf.
---------------------------------------------------------------------------

    The estimates in Table IX.C.2-1 are only relevant for incremental
policies relative to the projected baselines (that do not reflect
potential future climate policies) and there is substantial uncertainty
associated with the estimates themselves both in terms of what is being
modeled and what is not being modeled, with many uncertainties outside
of observed variability.\503\ Both

of these points are important for non-marginal emissions changes and
estimating total benefits. Also, the uncertainties inherent in this
kind of modeling, including the omissions of many important impacts
categories, present problems for approaches attempting to identify an
economically efficient level of GHG reductions and to positive net
benefit criteria in general, and point to the importance of considering
factors beyond monetized benefits and costs. In uncertain situations
such as that associated with climate, EPA typically recommends that
analysis consider a range of benefit and cost estimates, and the
potential implications of non-monetized and non-quantified benefits.
---------------------------------------------------------------------------

    \503\ Because some types of potential climate change impacts may
occur suddenly or begin to increase at a much faster rate, rather
than increasing gradually or smoothly, different approaches are
necessary for quantifying the benefits of ``large'' (non-
incremental) versus ``small'' (incremental) reductions in global
GHGs. Marginal benefits estimates, like those presented above, can
be useful for estimating benefits for small changes in emissions.
See the DRIA for additional discussion of this point. Note that even
small reductions in global GHG emissions are expected to reduce
climate change risks, including catastrophic risks.
---------------------------------------------------------------------------

    Economic principles suggest that global benefits should also be
considered when evaluating alternative GHG reduction policies.\504\
Typically, because the benefits and costs of most environmental
regulations are predominantly domestic, EPA focuses on benefits that
accrue to the U.S. population when quantifying the impacts of domestic
regulation. However, OMB's guidance for economic analysis of federal
regulations specifically allows for consideration of international
effects.\505\ GHGs are global and very long-run public goods, and
economic principles suggest that the full costs to society of emissions
should be considered in order to identify the policy that maximizes the
net benefits to society, i.e., achieves an efficient outcome (Nordhaus,
2006).\506\ As such, estimates of global benefits capture more of the
full value to society than domestic estimates and will result in higher
global net benefits for GHG reductions when considered.\507\
---------------------------------------------------------------------------

    \504\ Recently, the National Highway Traffic Safety
Administration (NHTSA) issued the final Environmental Impact
Statement for their proposed rulemaking for average fuel economy
standards for passenger cars and light trucks in which the preferred
alternative is based upon a domestic marginal benefit estimate for
carbon dioxide reductions. See Average Fuel Economy Standards,
Passenger Cars and Light Trucks, MY 2011-2015, Final Environmental
Impact Statement http://www.nhtsa.dot.gov/portal/site/nhtsa/menuitem.43ac99aefa80569eea57529cdba046a0/.
    \505\ OMB (2003), page 15.
    \506\ Nordhaus, W., 2006, ``Paul Samuelson and Global Public
Goods,'' in M. Szenberg, L. Ramrattan, and A. Gottesman (eds),
Samuelsonian Economics, Oxford.
    \507\ Both the United Kingdom and the European Commission
following these economic principles in consideration of the global
social cost of carbon (SCC) for valuing the benefits of GHG emission
reductions in regulatory impact assessments and cost-benefit
analyses (Watkiss et al. 2006).
---------------------------------------------------------------------------

    Furthermore, international effects of climate change may also
affect domestic benefits directly and indirectly to the extent U.S.
citizens value international impacts (e.g., for tourism reasons,
concerns for the existence of ecosystems, and/or concern for others);
U.S. international interests are affected (e.g., risks to U.S. national
security, or the U.S. economy from potential disruptions in other
nations); and/or domestic mitigation decisions affect the level of
mitigation and emissions changes in general in other countries (i.e.,
the benefits realized in the U.S. will depend on emissions changes in
the U.S. and internationally). The economics literature also suggests
that policies based on direct domestic benefits will result in little
appreciable reduction in global GHGs (e.g., Nordhaus, 1995).\508\ While
these marginal benefits estimates are not comprehensive or economically
optimal, the global estimates in Table IX.C.2-1 internalize a larger
portion of the global and intergenerational externalities of reducing a
unit of emissions.
---------------------------------------------------------------------------

    \508\ Nordhaus, William D. (1995). ``Locational Competition and
the Environment: Should Countries Harmonize Their Environmental
Policies?'' in Locational Competition in the World Economy,
Symposium 1994, ed., Horst Siebert, J. C. B. Mohr (Paul Siebeck),
Tuebingen, 1995.
---------------------------------------------------------------------------

    A key challenge facing EPA is the appropriate discount rate over
the longer timeframe relevant for GHGs. With the benefits of GHG
emissions reductions distributed over a very long time horizon, benefit
and cost estimations are likely to be very sensitive to the discount
rate. When considering climate change investments, they should be
compared to similar alternative investments (via the discount rate).
Changes in GHG emissions--both increases and reductions--are
essentially long-run investments in changes in climate and the
potential impacts from climate change, which includes the potential for
significant impacts from climate change, where the exact timing and
magnitude of these impacts are unknown.
    When there are important benefits or costs that affect multiple
generations of the population, EPA and OMB allow for low but positive
discount rates (e.g., 0.5-3% noted by U.S. EPA, 1-3% by OMB).\509\ In
this multi-generation context, the three percent discount rate is
consistent with observed interest rates from long-term investments
available to current generations (net of risk premiums) as well as
current estimates of the impacts of climate change that reflect
potential impacts on consumers. In addition, rates of three percent or
lower are consistent with long-run uncertainty in economic growth and
interest rates, considerations of issues associated with the transfer
of wealth between generations, and the risk of high impact climate
damages. Given the uncertain environment, analysis could also consider
evaluating uncertainty in the discount rate (e.g., Newell and Pizer,
2001, 2003).\510\
---------------------------------------------------------------------------

    \509\ EPA (U.S. Environmental Protection Agency), 2000.
Guidelines for Preparing Economic Analyses. EPA 240-R-00-003. See
also OMB (U.S. Office of Management and Budget), 2003. Circular A-4.
September 17, 2003. These documents are the guidance used when
preparing economic analyses for all EPA rulemakings.
    \510\ Newell, R. and W. Pizer, 2001. Discounting the benefits of
climate change mitigation: How much do uncertain rates increase
valuations? PEW Center on Global Climate Change, Washington, DC.
Newell, R. and W. Pizer, 2003. Discounting the distant future: how
much do uncertain rates increase valuations? Journal of
Environmental Economics and Management 46:52-71.
---------------------------------------------------------------------------

    For the final rulemaking, we will be developing and updating the
FUND model as best as possible based on the latest research and peer
reviewing the estimates. To improve upon our estimates, we hope to
evaluate several factors not currently captured in the proposed
estimates due to time constraints. For example, we will quantify
additional impact categories as is possible and provide a qualitative
evaluation of the implications of what is not monetized. We also plan
to conduct an uncertainty analysis, consider complementary bottom-up
analyses, and develop estimates of the marginal benefits associated
with non-CO2 GHGs relevant to the rule (e.g.,
CH4, N2O, and HFC-134a).\511\
---------------------------------------------------------------------------

    \511\ Due to differences in atmospheric lifetime and radiative
forcing, the marginal benefit values of non-CO2 GHG
reductions and their growth rates over time will not be the same as
the marginal benefits of CO2 emissions reductions (IPCC
WGII, 2007).
---------------------------------------------------------------------------

    EPA solicits comment on the appropriateness of using U.S. and
global values in quantifying the benefits of GHG reductions and the
appropriate application of benefits estimates given the state of the
art and overall uncertainties. We also seek comment on our estimates of
the global and U.S. marginal benefits of GHG emissions reductions that
EPA has developed, including the scientific and economic foundations,
the methods employed in developing the estimates, the discount

rates considered, current and proposed future consideration of
uncertainty in the estimates, marginal benefits estimates for non-
CO2 GHG emissions reductions, and potential opportunities
for improving the estimates. We are also interested in comments on
methods for quantifying benefits for non-incremental reductions in
global GHG emissions.
    Because the literature on SCC and our understanding of that
literature continues to evolve, EPA will continue to assess the best
available information on the social cost of carbon and climate
benefits, and may adjust its approaches to quantifying and presenting
information on these areas in future rulemakings.
4. Total Monetized GHG Benefits Estimates
    As described in Section VI.F, annualized equivalent GHG emissions
reductions associated with the RFS2 proposal in 2022 would be 160
million metric tons of CO2 equivalent (MMTCO2eq)
with a 2% discount rate, and 155 and 136 MMCO2eq with
discount rates of 3% and 7%, respectively. This section provides the
monetized total GHG benefits estimates associated with the proposal in
2022. As discussed above in Section IX.C.3, these estimates do not
include significant impacts that have yet to be monetized. Total
monetized benefits in 2022 are calculated by multiplying the marginal
benefits per metric ton of CO2 in that year by the
annualized equivalent emissions reductions. For the final rulemaking,
we plan to separate the emissions reductions by gas and use
CO2 and non-CO2 marginal benefits estimates. Non-
CO2 GHGs have different climate and atmospheric implications
and therefore different marginal climate impacts.
    Table IX.C.4-1 provides the estimated monetized GHG benefits of the
proposal for 2022. The large range of values in the Table reflects some
of the uncertainty captured in the range of monetized marginal benefits
estimates presented in Table IX.C.2-1.\512\ All values in this section
are presented in 2006 real dollars.
---------------------------------------------------------------------------

    \512\ EPA notes, however, that the Ninth Circuit recently
rejected an approach of assigning no monetized value to greenhouse
gas reductions resulting from vehicular fuel economy. Center for
Biodiversity v. NHTSA, F. 3d, (9th Cir. 2007).

                       Table IX.C.4-1--Monetized GHG Benefits of the Proposed Rule in 2022
                                                 [Billion 2006$]
----------------------------------------------------------------------------------------------------------------

----------------------------------------------------------------------------------------------------------------
                        Marginal benefit                                2%              3%              7%
----------------------------------------------------------------------------------------------------------------
Meta global...........................  Low.....................           -$0.3           -$0.3             n/a
                                        Central.................            16.8             9.6             n/a
                                        High....................            39.4            25.5             n/a
FUND global...........................  Low.....................            -0.6            -0.6            -0.3
                                        Central.................            21.7             4.0            -0.1
                                        High....................           172.8            31.9             1.2
FUND domestic.........................  Low.....................             0.0             0.0             0.0
                                        Central.................             1.1             0.3             0.0
                                        High....................             4.1             1.4             0.0
----------------------------------------------------------------------------------------------------------------

D. Co-pollutant Health and Environmental Impacts

    This section describes EPA's analysis of the co-pollutant health
and environmental impacts that can be expected to occur as a result of
this renewable fuels proposal throughout the period from initial
implementation through 2030. GHG emissions are predominantly the
byproduct of fossil fuel combustion processes that also produce
criteria and hazardous air pollutants. The fuels that are subject to
the proposed standard are also significant sources of mobile source air
pollution such as direct PM, NOX, VOCs and air toxics. The
proposed standard would affect exhaust and evaporative emissions of
these pollutants from vehicles and equipment. They would also affect
emissions from upstream sources such as fuel production, storage, and
distribution and agricultural emissions. Any decrease or increase in
ambient ozone, PM2.5, and air toxics associated with the
proposal would impact human health in the form of avoided or incurred
premature deaths and other serious human health effects, as well as
other important public health and welfare effects.
    As can be seen in Section II.B, we estimate that the proposal would
lead to both increased and decreased criteria and air toxic pollutant
emissions. Making predictions about human health and welfare impacts
based solely on emissions changes, however, is extremely difficult.
Full-scale photochemical modeling is necessary to provide the needed
spatial and temporal detail to more completely and accurately estimate
the changes in ambient levels of these pollutants. EPA typically
quantifies and monetizes the PM- and ozone-related health and
environmental impacts in its regulatory impact analyses (RIAs) when
possible. However, we were unable to do so in time for this proposal.
EPA attempts to make emissions and air quality modeling decisions early
in the analytical process so that we can complete the photochemical air
quality modeling and use that data to inform the health and
environmental impacts analysis. Resource and time constraints precluded
the Agency from completing this work in time for the proposal. EPA
will, however, provide a complete characterization of the health and
environmental impacts, both in terms of incidence and valuation, for
the final rulemaking.
    This section explains what PM- and ozone-related health and
environmental impacts EPA will quantify and monetize in the analysis
for the final rules. EPA will base its analysis on peer-reviewed
studies of air quality and health and welfare effects and peer-reviewed
studies of the monetary values of public health and welfare
improvements, and will be consistent with benefits analyses performed
for the recent analysis of the proposed Ozone NAAQS and the final PM
NAAQS analysis.513 514 These methods will be described in
detail in the DRIA prepared for the final rule.
---------------------------------------------------------------------------

    \513\ U.S. Environmental Protection Agency. July 2007.
Regulatory Impact Analysis of the Proposed Revisions to the National
Ambient Air Quality Standards for Ground-Level Ozone. Prepared by:
Office of Air and Radiation. EPA-452/R-07-008.
    \514\ U.S. Environmental Protection Agency. October 2006. Final
Regulatory Impact Analysis (RIA) for the Proposed National Ambient
Air Quality Standards for Particulate Matter. Prepared by: Office of
Air and Radiation.
---------------------------------------------------------------------------

    Though EPA is characterizing the changes in emissions associated
with toxic pollutants, we will not be able to

quantify or monetize the human health effects associated with air toxic
pollutants for either the proposal or the final rule analyses. This is
primarily because available tools and methods to assess air toxics risk
from mobile sources at the national scale are not adequate for
extrapolation to benefits assessment. In addition to inherent
limitations in the tools for national-scale modeling of air quality and
exposure, there is a lack of epidemiology data for air toxics in the
general population. For a more comprehensive discussion of these
limitations, please refer to the final Mobile Source Air Toxics
rule.\515\ Please refer to Section VII for more information about the
air toxics emissions impacts associated with the proposed standard.
---------------------------------------------------------------------------

    \515\ U.S. Environmental Protection Agency. February 2007.
Control of Hazardous Air Pollutants from Mobile Sources: Final
Regulatory Impact Analysis. Office of Air and Radiation. Office of
Transportation and Air Quality. EPA420-R-07-002.
---------------------------------------------------------------------------

1. Human Health and Environmental Impacts
    To model the ozone and PM air quality benefits of the final rules,
EPA will use the Community Multiscale Air Quality (CMAQ) model (see
Section VII.D.2 for a description of the CMAQ model). The modeled
ambient air quality data will serve as an input to the Environmental
Benefits Mapping and Analysis Program (BenMAP).\516\ BenMAP is a
computer program developed by EPA that integrates a number of the
modeling elements used in previous DRIAs (e.g., interpolation
functions, population projections, health impact functions, valuation
functions, analysis and pooling methods) to translate modeled air
concentration estimates into health effects incidence estimates and
monetized benefits estimates.
---------------------------------------------------------------------------

    \516\ Information on BenMAP, including downloads of the
software, can be found at http://www.epa.gov/ttn/ecas/benmodels.html.
---------------------------------------------------------------------------

    Table IX.D.1-1 lists the co-pollutant health effect exposure-
response functions (PM2.5 and ozone) we will use to quantify
the co-pollutant incidence impacts associated with the proposal.

    Table IX.D.1-1--Health Impact Functions Used in BenMAP to Estimate Impacts of PM2.5 and Ozone Reductions
----------------------------------------------------------------------------------------------------------------
             Endpoint                  Pollutant             Study                    Study population
----------------------------------------------------------------------------------------------------------------
Premature Mortality:
    Premature mortality--daily     O3                 Multi-city.........  All ages.
     time series.                                     Bell et al. (2004)--
                                                       Non-accidental.
                                   .................  Huang et al.
                                                       (2005)--Cardiopulm
                                                       onary.
                                   .................  Schwartz (2005)--
                                                       Non-accidental.
                                   .................  Meta-analyses:
                                   .................     Bell et al.
                                                          (2005)--All
                                                          cause.
                                   .................     Ito et al.
                                                          (2005)--Non-
                                                          accidental.
                                   .................     Levy et al.
                                                          (2005)--All
                                                          cause.
Premature mortality--cohort        PM2.5              Pope et al. (2002).  >29 years.
 study, all-cause.                                    Laden et al. (2006)  >25 years.
Premature mortality, total         PM2.5              Expert Elicitation   >24 years.
 exposures.                                            (IEc, 2006).
Premature mortality--all-cause...  PM2.5              Woodruff et al.      Infant (<1 year).
                                                       (1997).
Chronic Illness:
    Chronic Bronchitis...........  PM2.5              Abbey et al. (1995)  >26 years.
    Nonfatal heart attacks.......  PM2.5              Peters et al.        Adults (>18 years).
                                                       (2001).
Hospital Admissions:
    Respiratory..................  O3                 Pooled estimate....  >64 years.
                                   .................     Schwartz (1995)--
                                                          ICD 460-519
                                                          (all resp).
                                   .................     Schwartz (1994a;
                                                          1994b)--ICD 480-
                                                          486 (pneumonia).
                                   .................     Moolgavkar et
                                                          al. (1997)--ICD
                                                          480-487
                                                          (pneumonia).
                                   .................     Schwartz
                                                          (1994b)--ICD
                                                          491-492, 494-
                                                          496 (COPD).
                                   .................     Moolgavkar et
                                                          al. (1997)--ICD
                                                          490-496 (COPD).
                                   .................  Burnett et al.       <2 years.
                                                       (2001).
                                   PM2.5              Pooled estimate....  >64 years.
                                   .................     Moolgavkar
                                                          (2003)--ICD 490-
                                                          496 (COPD).
                                   .................     Ito (2003)--ICD
                                                          490-496 (COPD).
                                   PM2.5              Moolgavkar (2000)--  20-64 years.
                                                       ICD 490-496 (COPD).
                                   PM2.5              Ito (2003)--ICD 480- >64 years.
                                                       486 (pneumonia).
                                   PM2.5              Sheppard (2003)--    <65 years.
                                                       ICD 493 (asthma).
    Cardiovascular...............  PM2.5              Pooled estimate....  >64 years.
                                   .................     Moolgavkar
                                                          (2003)--ICD 390-
                                                          429 (all
                                                          Cardiovascular).
                                   .................     Ito (2003)--ICD
                                                          410-414, 427-
                                                          428 (ischemic
                                                          heart disease,
                                                          dysrhythmia,
                                                          heart failure).
                                   PM2.5              Moolgavkar (2000)--  20-64 years.
                                                       ICD 390-429 (all
                                                       Cardiovascular).
    Asthma-related ER visits.....  O3                 Pooled estimate....  5-34 years.
                                   .................     Jaffe et al.      All ages.
                                                          (2003).
                                   .................     Peel et al.       All ages.
                                                          (2005).
                                   .................     Wilson et al.
                                                          (2005).
                                   PM2.5              Norris et al.        0-18 years.
                                                       (1999).
Other Health Endpoints:

    Acute bronchitis.............  PM2.5              Dockery et al.       8-12 years.
                                                       (1996).
    Upper respiratory symptoms...  PM2.5              Pope et al. (1991).  Asthmatics, 9-11 years.
    Lower respiratory symptoms...  PM2.5              Schwartz and Neas    7-14 years.
                                                       (2000).
    Asthma exacerbations.........  PM2.5              Pooled estimate....  6-18 years.
                                   .................     Ostro et al.
                                                          (2001) (cough,
                                                          wheeze and
                                                          shortness of
                                                          breath).
                                   .................     Vedal et al.
                                                          (1998) (cough).
    Work loss days...............  PM2.5              Ostro (1987).......  18-65 years.
    School absence days..........  O3                 Pooled estimate....  5-17 years.
                                   .................     Gilliland et al.
                                                          (2001).
                                   .................     Chen et al.
                                                          (2000).
    Minor Restricted Activity      O3                 Ostro and            18-65 years.
     Days (MRADs).                                     Rothschild (1989).
                                   PM2.5              Ostro and            18-65 years.
                                                       Rothschild (1989).
----------------------------------------------------------------------------------------------------------------

2. Monetized Impacts
    Table IX.D.2-1 presents the monetary values we will apply to
changes in the incidence of health and welfare effects associated with
the RFS2 standard.

  Table IX.D.2-1--Valuation Metrics Used in BenMAP To Estimate Monetary
                                Benefits
------------------------------------------------------------------------
                                                           Valuation
           Endpoint                Valuation method         (2000$)
------------------------------------------------------------------------
Premature mortality...........  Assumed Mean VSL.....         $5,500,000
Chronic Illness
    Chronic Bronchitis........  WTP: Average Severity            340,482
    Myocardial Infarctions,     Medical Costs Over 5   .................
     Nonfatal.                   Years. Varies by age
                                 and discount rate.
                                 Russell (1998).
                                Medical Costs Over 5   .................
                                 Years. Varies by age
                                 and discount rate.
                                 Wittels (1990).
Hospital Admissions
    Respiratory, Age 65+......  COI: Medical Costs +              18,353
                                 Wage Lost.
    Respiratory, Ages 0-2.....  COI: Medical Costs...              7,741
    Chronic Lung Disease (less  COI: Medical Costs +              12,378
     Asthma).                    Wage Lost.
    Pneumonia.................  COI: Medical Costs +              14,693
                                 Wage Lost.
    Asthma....................  COI: Medical Costs +               6,634
                                 Wage Lost.
    Cardiovascular............  COI: Medical Costs +              22,778
                                 Wage Lost (20-64).
                                COI: Medical Costs +              21,191
                                 Wage Lost (65-99).
ER Visits, Asthma.............  COI: Smith et al.                    312
                                 (1997).
                                COI: Standford et al.                261
                                 (1999).
Other Health Endpoints
    Acute Bronchitis..........  WTP: 6 Day Illness,                  356
                                 CV Studies.
    Upper Respiratory Symptoms  WTP: 1 Day, CV                        25
                                 Studies.
    Lower Respiratory Symptoms  WTP: 1 Day, CV                        16
                                 Studies.
    Asthma Exacerbation.......  WTP: Bad Asthma Day,                  43
                                 Rowe and Chestnut
                                 (1986).
    Work Loss Days............  Median Daily Wage,     .................
                                 County-Specific.
    Minor Restricted Activity   WTP: 1 Day, CV                        51
     Days.                       Studies.
    School Absence Days.......  Median Daily Wage,                    75
                                 Women 25+.
    Worker Productivity.......  Median Daily Wage,     .................
                                 Outdoor Workers,
                                 County-Specific,
                                 Crocker and Horst
                                 (1981).
Environmental Endpoints         WTP: 86 Class I Areas  .................
 Recreational Visibility.
------------------------------------------------------------------------
Source: Dollar amounts for each valuation method were extracted from
  BenMAP version 2.4.5.

3. Other Unquantified Health and Environmental Impacts
    In addition to the co-pollutant health and environmental impacts we
will quantify for the analysis of the RFS2 standard, there are a number
of other health and human welfare endpoints that we will not be able to
quantify because of current limitations in the methods or available
data. These impacts are associated with emissions of air toxics
(including benzene, 1,3-butadiene, formaldehyde, acetaldehyde,
acrolein, and ethanol), ambient ozone, and ambient PM2.5
exposures. For example, we have not quantified a number of known or
suspected health effects linked with ozone and PM for which appropriate
health impact functions are not available or which do not provide
easily interpretable outcomes (i.e., changes in heart rate
variability). Additionally, we are currently unable to quantify a
number of known welfare effects, including reduced acid and particulate
deposition damage to cultural monuments and other materials, and
environmental benefits due to reductions of impacts of eutrophication
in coastal areas. For air toxics, the available tools and methods to
assess risk from mobile sources at the national scale are not adequate
for extrapolation to benefits assessment. In addition to inherent
limitations in the

tools for national-scale modeling of air toxics and exposure, there is
a lack of epidemiology data for air toxics in the general population.
Table IX.D.3-1 lists these unquantified health and environmental
impacts.

    Table IX.D.3-1--Unquantified and Non-Monetized Potential Effects
------------------------------------------------------------------------
                                             Effects not included in
           Pollutant/Effects                  analysis--changes in:
------------------------------------------------------------------------
Ozone Health \a\.......................  Chronic respiratory damage.
                                         Premature aging of the lungs.
                                         Non-asthma respiratory
                                          emergency room visits.
                                         Exposure to UVb ()
                                          \d\.
Ozone Welfare..........................  Yields for:
                                         --commercial forests.
                                         --some fruits and vegetables.
                                         --non-commercial crops.
                                         Damage to urban ornamental
                                          plants.
                                         Impacts on recreational demand
                                          from damaged forest
                                          aesthetics.
                                         Ecosystem functions.
                                         Exposure to UVb ().
PM Health \b\..........................  Premature mortality--short term
                                          exposures.\c\
                                         Low birth weight.
                                         Pulmonary function.
                                         Chronic respiratory diseases
                                          other than chronic bronchitis.
                                         Non-asthma respiratory
                                          emergency room visits.
                                         Exposure to UVb ().
PM Welfare.............................  Residential and recreational
                                          visibility in non-Class I
                                          areas.
                                         Soiling and materials damage.
                                         Damage to ecosystem functions.
                                         Exposure to UVb ().
Nitrogen and Sulfate Deposition Welfare  Commercial forests due to
                                          acidic sulfate and nitrate
                                          deposition.
                                         Commercial freshwater fishing
                                          due to acidic deposition.
                                         Recreation in terrestrial
                                          ecosystems due to acidic
                                          deposition.
                                         Existence values for currently
                                          healthy ecosystems.
                                         Commercial fishing,
                                          agriculture, and forests due
                                          to nitrogen deposition.
                                         Recreation in estuarine
                                          ecosystems due to nitrogen
                                          deposition.
                                         Ecosystem functions.
                                         Passive fertilization.
CO Health..............................  Behavioral effects.
Hydrocarbon (HC)/Toxics Health \e\.....  Cancer (benzene, 1,3-butadiene,
                                          formaldehyde, acetaldehyde,
                                          ethanol).
                                         Anemia (benzene).
                                         Disruption of production of
                                          blood components (benzene).
                                         Reduction in the number of
                                          blood platelets (benzene).
                                         Excessive bone marrow formation
                                          (benzene).
                                         Depression of lymphocyte counts
                                          (benzene).
                                         Reproductive and developmental
                                          effects (1,3-butadiene,
                                          ethanol).
                                         Irritation of eyes and mucus
                                          membranes (formaldehyde).
                                         Respiratory irritation
                                          (formaldehyde).
                                         Asthma attacks in asthmatics
                                          (formaldehyde).
                                         Asthma-like symptoms in non-
                                          asthmatics (formaldehyde).
                                         Irritation of the eyes, skin,
                                          and respiratory tract
                                          (acetaldehyde).
                                         Upper respiratory tract
                                          irritation and congestion
                                          (acrolein).
HC/Toxics Welfare \f\..................  Direct toxic effects to
                                          animals.
                                         Bioaccumulation in the food
                                          chain.
                                         Damage to ecosystem function.
                                         Odor.
------------------------------------------------------------------------
\a\ In addition to primary economic endpoints, there are a number of
  biological responses that have been associated with ozone health
  effects including increased airway responsiveness to stimuli,
  inflammation in the lung, acute inflammation and respiratory cell
  damage, and increased susceptibility to respiratory infection. The
  public health impact of these biological responses may be partly
  represented by our quantified endpoints.
\b\ In addition to primary economic endpoints, there are a number of
  biological responses that have been associated with PM health effects
  including morphological changes and altered host defense mechanisms.
  The public health impact of these biological responses may be partly
  represented by our quantified endpoints.
\c\ While some of the effects of short-term exposures are likely to be
  captured in the estimates, there may be premature mortality due to
  short-term exposure to PM not captured in the cohort studies used in
  this analysis. However, the PM mortality results derived from the
  expert elicitation do take into account premature mortality effects of
  short term exposures.
\d\ May result in benefits or disbenefits.
\e\ Many of the key hydrocarbons related to this rule are also hazardous
  air pollutants listed in the Clean Air Act. Please refer to Section
  VII.E.4 for additional information on the health effects of air
  toxics.
\f\ Please refer to Section VII.E for additional information on the
  welfare effects of air toxics.

    While there will be impacts associated with air toxic pollutant
emission changes that result from the RFS2 standard, we will not
attempt to monetize those impacts. This is primarily because currently
available tools and methods to assess air toxics risk from mobile
sources at the national scale are not adequate for extrapolation to
incidence estimations or benefits assessment. The best suite of tools
and methods currently available for assessment at the national scale
are those used in the National-Scale Air Toxics Assessment (NATA). The
EPA Science Advisory Board specifically commented in their review of
the 1996 NATA that these tools were not yet ready for use in a
national-scale benefits analysis, because they did not consider the
full distribution of exposure and risk, or address sub-chronic health
effects.\517\ While EPA has since improved the tools, there remain
critical limitations for estimating incidence and assessing benefits of
reducing mobile source air toxics. EPA continues to work to address
these limitations; however, we do not anticipate having methods and
tools available for national-scale application in time for the analysis
of the final rules. Please refer to the final Mobile Source Air Toxics
Rule RIA for more discussion.\518\
---------------------------------------------------------------------------

    \517\ Science Advisory Board. 2001. NATA--Evaluating the
National-Scale Air Toxics Assessment for 1996--an SAB Advisory.
http://www.epa.gov/ttn/atw/sab/sabrev.html.
    \518\ U.S. EPA. 2007. Control of Hazardous Air Pollutants From
Mobile Sources--Regulatory Impact Analysis. Assessment and Standards
Division. Office of Transportation and Air Quality. EPA420R-07-002.
February.
---------------------------------------------------------------------------

E. Economy-Wide Impacts

    It is anticipated that this proposed rulemaking will have impacts
on the U.S. economy that extend beyond the two sectors most directly
affected--the transportation and agriculture sectors. Consider how the
proposed rulemaking will affect the overall U.S. economy. By requiring
36 billion gallons of renewable transportation fuels in the U.S.
transportation sector by 2022, it is anticipated that the cost of motor
vehicle fuels will increase. This cost increase will impact all sectors
of the economy that use motor vehicles fuels, as intermediate inputs to
production. For example, manufacturing firms will see an increase in
their shipping costs. Households will also be impacted as consumers of
these goods, and directly as consumers of motor vehicle fuels.
Additionally, it is anticipated that the production of renewable fuels
will increase the demand for U.S. farm

products, and increase farm incomes. This will have ripple effects for
sectors that supply inputs to the U.S. farm sector (e.g. tractors), and
sectors that demand outputs from the farm sector. The sum of all of
these impacts will affect the total levels of output and consumption in
the U.S. economy. Because multiple markets beyond the transportation
sector will be affected by the proposed rulemaking, a general
equilibrium analysis is required to provide a more accurate picture of
the social cost of the policy than a partial equilibrium analysis. (A
partial equilibrium analysis looks at the impacts in one market of the
economy but does not attempt to capture the full interaction of a
policy change in all markets simultaneously, as a general equilibrium
model does).
    In order to estimate the impacts of the RFS2 rule on U.S. gross
domestic product (GDP) and consumption, EPA intends to use an economy-
wide, computable general equilibrium (CGE) model between proposal and
the final rule. This model will use detailed fuel sector cost estimates
provided in Section VIII as inputs to determine the economy-wide
impacts of the rulemaking. The economy-wide model to be utilized for
this analysis is the Intertemporal General Equilibrium Model (IGEM).
IGEM is a model of the U.S. economy with an emphasis on the energy and
environmental aspects. It is a dynamic model, which depicts growth of
the economy due to capital accumulation, technical change and
population change. It is a detailed multi-sector model covering thirty-
five industries of the U.S. economy. It also depicts changes in
consumption patterns due to demographic changes, price and income
effects. The substitution possibilities for both producers and
consumers in IGEM are driven by model parameters that are based on
observed market behavior revealed over the past forty to fifty years.
EPA seeks comment on the modeling approach to be utilized to estimate
the economy-wide impacts of the RFS2 proposal.
    An additional issue that arises is how biofuel subsidies are
considered from an economy-wide perspective. The Renewable Fuels
Standard, by encouraging the use of biofuels, will result in an
expansion of subsidy payments by the U.S. For example, each gallon of
corn-based ethanol sold in the U.S. qualifies for a $0.45/gallon
subsidy. One assumption that could be made is that biofuel subsidies,
which are a loss in revenue to the U.S. government, are offset by an
increase in taxes by the U.S. In this case, the Renewable Fuels
Standard program becomes revenue neutral. If taxes are raised to offset
the revenue loss from the subsidies, the taxes could have a
distortionary impact on the economy. For example, if taxes are raised
on labor and capital, then there will less output. To account for the
potential distortionary impacts of increased taxes, as a rule of thumb,
it is sometimes assumed that for each dollar of tax revenue raised,
there is a $0.25 loss in output in the economy. We intend to consider
the impact of the expansion of biofuel subsidies from the RFS2 in the
context of the economy-wide modeling.

X. Impacts on Water

A. Background

    As the production and price of corn and other biofuel feedstocks
increase, there may be substantial impacts to both water quality and
water quantity. To analyze the potential water-related impacts, EPA
focused on agricultural corn production for several reasons. Corn acres
have increased dramatically, 20% in 2007. Although corn acres declined
seven percent in 2008, total corn acres remained the second highest
since 1946.\519\ Corn has the highest fertilizer and pesticide use per
acre and accounts for the largest share of nitrogen fertilizer use
among all crops.\520\ Corn generally utilizes only 40 to 60% of the
applied nitrogen fertilizer. The remaining nitrogen is available to
leave the field and runoff to surface waters, leach into ground water,
or volatilize to the air where it can return to water through
depositional processes.
---------------------------------------------------------------------------

    \519\ U.S. Department of Agriculture, National Agricultural
Statistics Service, ``Acreage'', 2008, available online at: http://usda.mannlib.cornell.edu/usda/current/Acre/Acre-06-30-2008.pdf.
    \520\ Committee on Water Implications of Biofuels Production in
the United States, National Research Council, 2008, Water
implications of biofuels production in the United States, The
National Academies Press, Washington, DC, 88 p.
---------------------------------------------------------------------------

    There are three major pathways for contaminants to reach water from
agricultural lands: run off from the land's surface, subsurface tile
drains, or leaching to ground water. A variety of management factors
influence the potential for contaminants such as fertilizers, sediment,
and pesticides to reach water from agricultural lands. These factors
include nutrient and pesticide application rates and application
methods, use of conservation practices and crop rotations by farmers,
and acreage and intensity of tile drained lands.
    Historically, corn has been grown in rotation with other crops,
especially soybeans. As corn prices increase relative to prices for
other crops, more farmers are choosing to grow corn every year
(continuous corn). Continuous corn production results in significantly
greater nitrogen losses annually than a corn-soybean rotation and lower
yields per acre. In response, farmers may add higher rates of nitrogen
fertilizer to try to match yields of corn grown in rotation. Growing
continuous corn also increases the viability of pests such as corn
rootworm. Farmers may increase use of pesticides to control these
pests. As corn acres increase, use of the common herbicides like
atrazine and glyphosate (e.g. Roundup) may also increase.
    High corn prices may encourage farmers to grow corn on lands that
are marginal for row production such as hay land or pasture. Typically,
agricultural producers apply far less fertilizer and pesticide on
pasture land than land in row crops. Corn yield on these marginal lands
will be lower and may require higher fertilizer rates. However since
nitrogen fertilizer prices are tied to oil prices, fertilizer costs
have increased significantly recently. It is unclear how agricultural
producers have responded to these increases in both corn and fertilizer
prices. EPA solicits comments on the impact of corn and fertilizer
prices on nitrogen fertilizer use.
    Tile drainage is another important factor in determining the losses
of fertilizer from cropland. Tile drainage consists of subsurface tiles
or pipes that move water from wet soils to surface waters quickly so
crops can be planted. Tile drainage has transformed large expanses of
historic wetland soils into productive agriculture lands. However, the
tile drains also move fertilizers and pesticides more quickly to
surface waters without any of the attenuation that would occur if these
contaminants moved through soils or wetlands. The highest proportion of
tile drainage occurs in the Upper Mississippi and the Ohio-Tennessee
River basins.\521\
---------------------------------------------------------------------------

    \521\ U.S. Environmental Protection Agency, EPA Science Advisory
Board, Hypoxia in the northern Gulf of Mexico, EPA-SAB-08-003, 275
p, available online at: http://yosemite.epa.gov/sab/sabproduct.nsf/
C3D2F27094E03F90852573B800601D93/$File/EPA-SAB-08-
003complete.unsigned.pdf.
---------------------------------------------------------------------------

    The increase in corn production and prices may also have
significant impacts on voluntary conservation programs funded by the
U.S. Department of Agriculture (USDA) that are important to protect
water quality. As land values increase due to higher crop prices, USDA
payments may not keep up with the need for farmers and tenant farmers,
to make an adequate return. For example, farmland in Iowa increased an

average of 18% in 2007 from 2006 prices.
    Both land retirement programs like the Conservation Reserve Program
(CRP) and working land programs like the Environmental Quality
Incentives Program (EQIP) can be affected. Under CRP, USDA contracts
with farmers to take land out of agricultural production and plant
grasses or trees. Generally farmers put land into CRP because it is not
as productive and has other characteristics that make the cropland more
environmentally sensitive, such as high erosion rates. CRP provides
valuable environmental benefits both for water quality and for wildlife
habitat. Midwestern states, where much of U.S. corn is grown, tend to
have lower CRP reenrollment rates than the national average. Under
EQIP, USDA makes cost-share payments to farmers to implement
conservation practices. Some of the most cost-effective practices
include: Riparian buffers; crop rotation; appropriate rate, timing, and
method of fertilizer application; cover crops; and, on tile-drained
lands, treatment wetlands and controlled drainage. Producers may be
less willing to participate and require higher payments to offset
perceived loss of profits through implementation of conservation
practices.
1. Ecological Impacts
    Nitrogen and phosphorus enrichment due to human activities is one
of the leading problems facing our nation's lakes, reservoirs, and
estuaries. Nutrient enrichment also has negative impacts on aquatic
life in streams; adverse health effects on humans and domestic animals;
and impairs aesthetic and recreational use. Excess nutrients can lead
to excessive growth of algae in rivers and streams, and aquatic plants
in all waters. For example, declines in invertebrate community
structure have been correlated directly with increases in phosphorus
concentration. High concentrations of nitrogen in the form of ammonia
are known to be toxic to aquatic animals. Excessive levels of algae
have also been shown to be damaging to invertebrates. Finally, fish and
invertebrates will experience growth problems and can even die if
either oxygen is depleted or pH increases are severe; both of these
conditions are symptomatic of eutrophication. As a biologic system
becomes more enriched by nutrients, different species of algae may
spread and species composition can shift.
    Nutrient pollution is widespread. The most widely known examples of
significant nutrient impacts include the Gulf of Mexico and the
Chesapeake Bay. There are also known impacts in over 80 estuaries/bays,
and thousands of rivers, streams, and lakes. Waterbodies in virtually
every state and territory in the U.S. are impacted by nutrient-related
degradation. Reducing nutrient pollution is a priority for EPA. The
combustion of transportation fuels results in significant loadings of
nitrogen from air deposition to waterbodies around the country,
including the Chesapeake Bay, Long Island Sound, and Lake Tahoe.
2. Gulf of Mexico
    Production of corn for ethanol may exacerbate existing serious
water quality problems in the Gulf of Mexico. Nitrogen fertilizer
applications to corn are already the major source of total nitrogen
loadings to the Mississippi River. A large area of low oxygen, or
hypoxia, forms in the Gulf of Mexico every year, often called the
``dead zone.'' The primary cause of the hypoxia is excess nutrients
(nitrogen and phosphorus) from the Upper Midwest flowing into the
Mississippi River to the Gulf. These nutrients trigger excessive algal
growth (or eutrophication) resulting in reduced sunlight, loss of
aquatic habitat, and a decrease in oxygen dissolved in the water.
Hypoxia threatens commercial and recreational fisheries in the Gulf
because fish and other aquatic species cannot live in the low oxygen
waters.
    In 2008, the hypoxic zone was the second largest since measurements
began in 1985--8,000 square miles, an area larger than the state of
Massachusetts, and slightly larger than the 2007 measurement.\522\ The
Mississippi River/Gulf of Mexico Watershed Nutrient Task Force's ``Gulf
Hypoxia Action Plan 2008'' calls for a 45% reduction in both nitrogen
and phosphorus reaching the Gulf to reduce the size of the zone.\523\
An additional reduction in nitrogen and phosphorus reduction would be
necessary as a result of increased corn production for ethanol and
climate change impacts.
---------------------------------------------------------------------------

    \522\ Louisiana Universities Marine Consortium, 2008, `Dead
zone' again rivals record size, available online at: http://www.gulfhypoxia.net/research/shelfwidecruises/2008/PressRelease08.pdf.
    \523\ Mississippi River/Gulf of Mexico Watershed Nutrient Task
Force, 2008, Gulf hypoxia action plan 2008 for reducing, mitigating,
and controlling hypoxia in the northern Gulf of Mexico and improving
water quality in the Mississippi River basin, 61 p., Washington, DC,
available online at: http://www.epa.gov/msbasin/actionplan.htm.
---------------------------------------------------------------------------

    Alexander, et al.\524\ modeled the sources of nutrient loadings to
the Gulf of Mexico using the USGS SPARROW model. They estimated that
agricultural sources contribute more than 70% of the delivered nitrogen
and phosphorus. Corn and soybean production accounted for 52% of
nitrogen delivery and 25% of the phosphorus.
---------------------------------------------------------------------------

    \524\ Alexander, R.B., Smith, R.A., Schwarz, G.E., Boyer, E.W.,
Nolan, J.V., and Brakebill, J.W., 2008, Differences in phosphorus
and nitrogen delivery to the Gulf of Mexico from the Mississippi
River basin, Environmental Science and Technology, v. 42, no. 3, p.
822-830, available online at: http://pubs.acs.org/cgi-bin/abstract.cgi/esthag/2008/42/i03/abs/es0716103.html.
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    Several recent scientific reports have estimated the impact of
increasing corn acres for ethanol in the Gulf of Mexico watershed.
Donner and Kucharik's \525\ study showed increases in nitrogen export
to the Gulf as a result of increasing corn ethanol production from 2007
levels to 15 billion gallons in 2022. They concluded that the expansion
of corn-based ethanol production could make it almost impossible to
meet the Gulf of Mexico nitrogen reduction goals without a ``radical
shift'' in feed production, livestock diet, and management of
agricultural lands. The study estimated a mean dissolved inorganic
nitrogen load increase of 10 to 18% from 2007 to 2022 to meet the 15
billion gallon corn ethanol goal. EPA's Science Advisory Board report
to the Mississippi River/Gulf of Mexico Watershed Task Force estimated
that corn grown for ethanol will result in an additional national
annual loading of almost 300 million pounds of nitrogen. An estimated
80% of that nitrogen loading or 238 million pounds will occur in the
Mississippi-Atchafalaya River basin and contribute nitrogen to the
hypoxia in the Gulf of Mexico.\526\
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    \525\ Donner, S. D. and Kucharik, C. J., 2008, Corn-based
ethanol production compromises goal of reducing nitrogen export by
the Mississippi River, PNAS, v. 105, no. 11, p. 4513-4518, available
online at: http://www.pnas.org/content/105/11/4513.full.
    \526\ U.S. EPA, supra note 4.
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B. Upper Mississippi River Basin Analysis

    To provide a quantitative estimate of the impact of this proposal
and production of corn ethanol generally on water quality, EPA
conducted an analysis that modeled the changes in loadings of nitrogen,
phosphorus, and sediment from agricultural production in the Upper
Mississippi River Basin (UMRB). The UMRB drains approximately 189,000
square miles, including large parts of the states of Illinois, Iowa,
Minnesota, Missouri, and Wisconsin. Small portions of Indiana,
Michigan, and South Dakota are also within the basin. EPA selected the
UMRB because it is representative of the many potential issues
associated with ethanol production, including its connection to major
water quality

concerns such as Gulf of Mexico hypoxia, large corn production, and
numerous ethanol production plants. For more details on the analysis,
see Chapter 6 in the DRIA.
    On average the UMRB contributes about 39% of the total nitrogen
loads and 26% of the total phosphorus loads to the Gulf of Mexico.\527\
The high percentage of nitrogen from the UMRB is primarily due to the
large inputs of fertilizer for agriculture and the 60% of cropland that
is tile drained. Although nitrogen inputs to the UMRB in recent years
is fairly level, there is a 21% decline in net inputs from humans. The
Science Advisory Board report attributes this decline to higher amount
of nitrogen removed during harvest, due to higher crop yields. For the
same time period, phosphorus inputs increased 12%.
---------------------------------------------------------------------------

    \527\ Mississippi River/Gulf of Mexico Watershed Nutrient Task
Force, supra note 6.
---------------------------------------------------------------------------

1. SWAT Model
    EPA selected the SWAT (Soil and Water Assessment Tool) model to
assess nutrient loads from changes in agricultural production in the
UMRB. Models are the primary tool that can be used to predict future
impacts based on alternative scenarios. SWAT is a physical process
model developed to quantify the impact of land management practices in
large, complex watersheds.\528\
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    \528\ Gassman, P.W., Reyes, M.R., Green, C.H., Arnold, J.G.,
2007, The soil and water assessment tool: Historical development,
applications, and future research directions. Transactions of the
American Society of Agricultural and Biological Engineers, v. 50,
no. 4, p. 1211-1240. http://www.card.iastate.edu/environment/items/asabe_swat.pdf.
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2. Baseline Model Scenario
    In order to assess alternative potential future conditions within
the UMRB, EPA developed a SWAT model of a Baseline Scenario against
which to analyze the impact of increased corn production for biofuel.
For simplicity's sake, we refer to the baseline as 2005, but like most
water quality modeling, we had to use a range of data sets for the
inputs. As noted above corn acres did not increase significantly until
the 2007 crop year. While this baseline does not directly quantify the
impacts of this proposal on water quality, it is useful in
understanding the magnitude of the impacts of corn production for
biofuels. EPA plans to conduct additional analyses for the final rule
that will compare the reference case biofuel volumes to the RFS2
volumes.
    The SWAT model was applied (i.e., calibrated) to the UMRB using
1960 to 2001 weather data and flow and water quality data from 13 USGS
gages on the mainstem of the Mississippi River. The 42-year SWAT model
runs were performed and the results analyzed to establish runoff,
sediment, nitrogen, and phosphorous loadings from each of the 131 8-
digit HUC subwatersheds and the larger 4-digit subbasins, along with
the total outflow from the UMRB and at the various USGS gage sites
along the Mississippi River. These results provided the Baseline
Scenario model values to which the future alternatives are compared.
3. Alternative Scenarios
    SWAT scenario analyses were performed for the years 2010, 2015,
2020, and 2022 with corn ethanol volumes of 12 billion gallons a year
(BGY) for 2010, and 15 BGY for 2015 to 2022. These volumes were
adjusted for the UMRB based on a 42.3% ratio of ethanol production
capacity within the UMRB compared to national capacity. The resulting
UMRB ethanol production goals were converted into the corresponding
required corn production acreage, i.e. the extent of corn acreage
needed to meet those ethanol production goals. Annual increases in corn
yield of 1.23% were built into the future scenarios. Fewer corn acres
were needed to meet ethanol production goals after the 2015 scenario
due to those yield increases.
    Table X.B.3-1 and Table X.B.3-2 summarize the model outputs both
within the UMRB and at the outlet of the UMRB in the Mississippi River
at Grafton, Illinois for each of the four scenario years: 2010, 2015,
2020, and 2022. It is important to note that these results only
estimate loadings from the Upper Mississippi River basin, not the
entire Mississippi River watershed. As noted earlier, the UMRB
contributes about 39% of the total nitrogen loads and 26% of total
phosphorus loads to the Gulf of Mexico. Due to the timing of this
proposal, we were not able to assess the local impact in smaller
watersheds within the UMRB. Those impacts may be significantly
different. The decreasing nitrogen load over time is likely attributed
to the increased corn yield production, resulting in greater plant
uptake of nitrogen.

   Table X.B.3-1--Changes in Nutrient Loadings Within the Upper Mississippi River Basin From the 2005 Baseline
                                                    Scenario
----------------------------------------------------------------------------------------------------------------
                                                 2005 Baseline           2010       2015       2020       2022
----------------------------------------------------------------------------------------------------------------
Nitrogen................................  1897.0 million lbs........      +5.1%      +4.2%      +2.2%      +1.6%
Phosphorus..............................  176.6 million lbs.........      +2.3%      +1.1%      +0.6%      +0.4%
----------------------------------------------------------------------------------------------------------------

    About 24% of nitrogen and 25% of phosphorus leaving agricultural
fields was assimilated (taken by aquatic plants or volatilized) before
reaching the outlet of the UMRB. The assimilated nitrogen is not
necessarily eliminated as an environmental concern. Five percent or
more of the nitrogen can be converted to nitrous gas, a powerful
greenhouse gas that has 300 times the climate-warming potential of
carbon dioxide, the major greenhouse. Thus, a water pollutant becomes
an air pollutant until it is either captured through biological
sequestration or converted fully to elemental nitrogen.
    Total sediment outflow showed very little change over all
scenarios. This is likely due to the corn being modeled as well-managed
crop in terms of sediment loss, primarily due to the corn stover
remaining on the fields following harvest.

   Table X.B.3-2--Changes From the 2005 Baseline to the Mississippi River at Grafton, Illinois From the Upper
                                             Mississippi River Basin
----------------------------------------------------------------------------------------------------------------
                                                 2005 Baseline           2010       2015       2020       2022
----------------------------------------------------------------------------------------------------------------
Average corn yield (bushels/acre).......  141.......................        150        158        168        171

Nitrogen................................  1,433.5 million lbs.......      +5.5%      +4.7%      +2.5%      +1.8%
Phosphorus..............................  132.4 million lbs.........      +2.8%      +1.7%     +0.98%      +0.8%
Sediment................................  6.4 million tons..........      +0.5%      +0.3%      +0.2%      +0.1%
----------------------------------------------------------------------------------------------------------------

    After evaluating comments on this proposal, if time and resources
permit, EPA may conduct additional water quality analyses using the
SWAT model in the UMRB. Potential future analyses could include: (1)
Determination of the most sensitive assumptions in the model, (2) water
quality impacts from the changes in ethanol volumes between the
reference case and this proposal, (3) removing corn stover for
cellulosic ethanol, and (4) a case study of a smaller watershed to
evaluate local water quality impacts that are impossible to ascertain
at the scale of the UMRB.
    EPA solicits comments on the scenarios developed for this proposal
and additional future analyses. At this time, we are not able to assess
the impact of these additional loadings on the size of the Gulf of
Mexico hypoxia zone or water quality within the UMRB. EPA also solicits
comments on the significance of the modeled increases in nitrogen and
phosphorus loads.

C. Additional Water Issues

    Water quality and quantity impacts resulting from corn ethanol
production go beyond our ability to model. The following issues are
summarized to provide additional context about the broader range of
potential impacts. See Chapter 6 in the DRIA for more discussion of
these issues.
1. Chesapeake Bay Watershed
    Agricultural lands contribute more nutrients to the Chesapeake Bay
than any other land use. Chesapeake Bay Program partners have pledged
to significantly reduce nutrients to the Bay to meet water quality
goals. To estimate the increase in nutrient loads to the Bay from
changes to agricultural crop production from 2005 to 2008, the
Chesapeake Bay Program Watershed Model Phase 4.3 and Vortex models were
utilized. Total nitrogen loads increased by almost 2.4 million pounds
from an increase of almost 66,000 corn acres. As agriculture land use
shifts from hay and pasture to more intensively fertilized row crops,
this analysis estimates that nitrogen loads increase by 8.8 million
pounds.
2. Ethanol Production
    There are three principal sources of discharges to water from
ethanol plants: Reject water from water purification, cooling water
blowdown, and off-batch ethanol. Most ethanol facilities use on-site
wells to produce the process water for the ethanol process. Groundwater
sources are generally not suitable for process water because of their
mineral content. Therefore, the water must be treated, commonly by
reverse osmosis. For every two gallons of pure water produced, about a
gallon of brine is discharged as reject water from this process. Most
estimates of water consumption in ethanol production are based on the
use of clean process water and neglect the water discharged as reject
water.
    The largest source of wastewater discharge is reverse osmosis
reject water from process water purification. The reverse osmosis
process concentrates groundwater minerals to levels where they can have
water quality impacts. There is really no means of ``treating'' these
ions to reduce toxicity, other than further concentration and disposal,
or use of instream dilution. Some facilities have had to construct long
pipelines to get access to dilution so they can meet water quality
standards. Ethanol plants also discharge cooling water blowdown, where
some water is discharged to avoid the buildup of minerals in the
cooling system. These brines are similar to the reject water described
above. In addition, if off-batch ethanol product or process water is
discharged, the waste stream can have high Biochemical Oxygen Demand
(BOD) levels. BOD directly affects the amount of dissolved oxygen in
rivers and streams. The greater the BOD, the more rapidly oxygen is
depleted in the stream. The consequences of high BOD are the same as
those for low dissolved oxygen: Aquatic organisms become stressed,
suffocate, and die.
    Older generation production facilities used four to six gallons of