reliability, at the national level. This is also the case at the
regional level, with small capacity changes in RFC (early retirement)
and SPP (avoided retirement). Option 4 also has a slight impact on
electricity prices across all NERC regions, with increases of no more
than 0.3 percent and a 0.1 percent reduction in the MRO region. At the
national level, variable production costs--fuel and variable O&M--
increase by $0.18 per MWh or 0.6 percent. While variable costs increase
in all NERC regions, the change varies by region ranging from $0.03 per
MWh in NPCC and WECC to $0.29 in RFC. As expected for Option 4, which
is more expensive than Option 3, the increase in total annual costs for
the electric power sector is greater than under Option 3. At the
national level, total annual costs increase by $1.9 billion (0.9
percent). As discussed in greater detail in Chapter 5 of the RIA
document, the largest shares of this increase occur in variable O&M
capital costs increase by a much smaller amount. As discussed above,
EPA expects the impacts of Options 3a and 3b to be smaller than those
of Option 3, and the impacts of Option 4a to be between those of
Options 3 and 4.
b. Impact on Existing Steam Electric Plants
    EPA used IPM V4.10 results for 2030 to assess the potential impact
of the regulatory options on steam electric plants. In contrast to the
previously described electricity market-level

analysis, which sought to assess the impact of the proposed ELGs
regulatory options on the entire electric power sector, the purpose of
this second analysis is to assess impacts on steam electric plants
specifically.
    Table XI-6 reports results for steam electric plants, as a group.
In this case, EPA looked at the following metrics IPM produces: (1)
Incremental early retirements and capacity closures, calculated as the
difference between capacity under the regulatory options and capacity
under the baseline, which includes both full plant closures and partial
plant closures (i.e., unit closures) in aggregate capacity terms; (2)
incremental capacity closures as a percentage of baseline capacity; (3)
post-compliance change in electricity generation; (4) post-compliance
changes in variable production costs per MWh, calculated as the sum of
total fuel and variable O&M costs divided by net generation; and (5)
changes in annual costs (fuel, variable O&M, fixed O&M, and capital.
Items (1) and (2) are instrumental in determining the economic
achievability of various regulatory options.

                        Table XI-6--Impact of Market Model Analysis Options on Steam Electric Plants as a Group at the Year 2030
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                  Incremental early retirements/                          Change in
                                                                           closures \a\              Change in total      variable      Change in annual
                 NERC region                      Baseline     ------------------------------------  generation (GWh   production cost   costs (million
                                                capacity (MW)                       % of Baseline        or % of       (2010$/MWh or %    2010$ or % of
                                                                  Capacity (MW)       capacity          baseline)       of baseline)        baseline)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Option 3:
    ERCOT...................................            32,275                 0               0.0          -83 0.0%        $0.09 0.3%          $35 0.5%
    FRCC....................................            32,227                 0               0.0           -25 0.0          0.11 0.3            27 0.4
    MRO.....................................            34,899                 0               0.0            83 0.0        -0.02 -0.1            26 0.3
    NPCC....................................            16,629                 0               0.0            -3 0.0          0.07 0.2             9 0.2
    RFC.....................................           122,205                 0               0.0           234 0.0          0.15 0.5           225 0.7
    SERC....................................           131,895                 0               0.0       -1,140 -0.2          0.24 0.8           283 0.8
    SPP.....................................            31,269              -102              -0.3         -123 -0.1          0.04 0.1            15 0.2
    WECC....................................            54,494                 0               0.0           103 0.0          0.05 0.2            22 0.2
                                             -----------------------------------------------------------------------------------------------------------
        Total...............................           455,894              -102               0.0          -954 0.0          0.13 0.5           642 0.6
--------------------------------------------------------------------------------------------------------------------------------------------------------
Option 4:
    ERCOT...................................            32,275                 0               0.0         -227 -0.1          0.16 0.5            66 1.0
    FRCC....................................            32,227                 0               0.0            78 0.1          0.05 0.1            27 0.4
    MRO.....................................            34,899                 0               0.0           212 0.1          0.12 0.5           108 1.4
    NPCC....................................            16,629              -431              -2.6            -4 0.0          0.10 0.3            29 0.7
    RFC.....................................           122,205               681               0.6       -2,351 -0.3          0.38 1.3           561 1.8
    SERC....................................           131,895                 0               0.1       -2,178 -0.3          0.43 1.5           607 1.8
    SPP.....................................            31,269               -30              -0.1         -510 -0.3          0.16 0.6            59 0.9
    WECC....................................            54,494                 0               0.0            63 0.0          0.07 0.3            46 0.4
                                             -----------------------------------------------------------------------------------------------------------
        Total...............................           455,894               317               0.1       -4,916 -0.2          0.28 1.0         1,504 1.4
--------------------------------------------------------------------------------------------------------------------------------------------------------
\a\ Values for incremental early retirements or closures represent change relative to the baseline run. IPM may show partial (i.e., unit) or full plant
  early retirements (closures) for a given option. It may also show avoided closures (negative closure values) in which a unit or plant that is
  projected to close in the baseline, is estimated to continue operating in the post-compliance case. Avoided closures may occur among plants that incur
  no compliance costs or for which compliance costs are low relative to other steam electric plants. \77\

---------------------------------------------------------------------------

    \77\ Given the design of IPM, unit-level and thereby plant-level
projections are presented as an indicator of overall regulatory
impact rather than a prediction of future unit- or plant-specific
compliance actions.
---------------------------------------------------------------------------

    Under Option 3, the net change in total capacity for steam electric
plants is very small; this is similar to prior findings when
considering the electricity market as a whole. For the group of steam
electric plants, total capacity increases by 106 MW (not shown in Table
XI-6, see RIA for details) or approximately 0.02 percent of the 455,894
MW baseline capacity. This results in part from avoided capacity
closures of 102 MW in the SPP region. Option 3 results in no closures,
full (plant) or partial (unit), in the other seven regions.
    The change in total generation is an indicator of how steam
electric plants fare, relative to the rest of the electricity market.
While at the market level there is essentially no projected change in
total electricity generation,\78\ for steam electric plants, total
available capacity and electricity generation at the national level is
projected to fall by less than 0.1 percent. At the regional level, five
NERC regions--ERCOT, NPCC, RFC, SERC, and SPP--are projected to
experience a reduction in electricity generation from steam electric
plants, ranging from 3 GWh in NPCC (less than 0.01 percent) to 1,140
GWh in RFC (0.2 percent). The other three NERC regions are each
projected to experience a very modest increase in electricity
generation from steam electric plants of less than 0.1 percent.
---------------------------------------------------------------------------

    \78\ At the national level, the demand for electricity does not
change between the baseline and the analyzed regulatory options
(generation within the regions is allowed to vary) because meeting
demand is an exogenous constraint imposed by the model.
---------------------------------------------------------------------------

    Finally, at the national level, variable production costs at steam
electric plants increase by approximately 0.5 percent. These effects
vary by region from about -0.1 percent in MRO to 0.8 percent in SERC.
These findings of very small national and regional effects in these
impact metrics confirm EPA's assessment that Option 3 can be expected
to have little economic consequence in national and regional
electricity markets.
    Results of the analysis for Option 4 show almost no change in
either total generating capacity or electricity generation for the
electric power sector as whole, and steam electric generating capacity
and electricity generation fall slightly by 306 MW (0.07 percent) (not
shown in Table XI-6, see RIA for

details) and 4,916 GWh (0.2 percent), respectively. The steam electric
capacity reduction includes early retirement and avoided retirement of
generating units with the net effect of the two types of changes being
capacity losses. Thus, under the analysis for Option 4, 14 generating
units close (1,125 MW) and 5 generating units avoid closure (808 MW),
leading to an estimated net closure of nine generating units (317 MW,
see Table XI-6). All 14 units that are projected to close in this
scenario are located within six plants that are projected to continue
operating. In other words, Option 4 is not projected to result in any
full plant closures.\79\
---------------------------------------------------------------------------

    \79\ Given the design of IPM, unit-level and thereby plant-level
projections are presented as an indicator of overall regulatory
impact rather than a prediction of future unit- or plant-specific
compliance actions.
---------------------------------------------------------------------------

    Findings for the change in total costs and variable production
costs under Option 4 also exceed those under Option 3. There is a 1.4
percent increase in total costs at the national level, with SERC
recording the largest increase of 1.8 percent. As detailed in Chapter 5
of the RIA document, at the national level, the increase in total costs
occurs in fixed and variable O&M (3.2 percent and 9.3 percent,
respectively) while fuel costs and capital costs decline (0.4 percent
and 3.2 percent, respectively). At the national level, variable
production costs increase by 1.0 percent, with SERC recording the
highest increase of 1.5 percent. As for impacts on national and
regional markets, EPA expects the impacts on steam electric plants of
Options 3a and 3b to be smaller than those of Option 3, and the impacts
of Option 4a to be between those of Options 3 and 4.
c. Impact on Individual Steam Electric Plants Incurring Compliance
Costs Under This Rulemaking
    Results for the group of steam electric plants as a whole may mask
shifts in economic performance among individual plants incurring
compliance costs associated with the proposed ELGs. To assess potential
plant-level effects, EPA analyzed plant-specific changes between the
base case and the post-compliance cases for the following metrics: (1)
Capacity utilization (defined as annual generation (in MWh) divided by
[capacity (MW) times 8,760 hours]) (2) electricity generation, and (3)
variable production costs per MWh, defined as variable O&M cost plus
fuel cost divided by net generation.
    Table XI-7 presents the estimated number of plants incurring
compliance costs with specific degrees of change in operations and
financial performance for the two regulatory options EPA analyzed using
IPM. Metrics of interest include the number of plants with reductions
in capacity utilization or generation (on left side of the table), and
the number of plants with increases in variable production costs (on
right side of the table).

Table XI-7--Impact of Market Model Analysis Options on Individual Steam Electric Plants Incurring Compliance Costs at the Year 2030--Number of Plants by
                                                                    Impact Magnitude
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                Reduction                                            Increase
                Economic measures                ---------------------------------------  No Change  ---------------------------------------   N/A \b\
                                                     >= 3%     >=1 and <3%      <1%                       <1%      >=1 and <3%     >= 3%
--------------------------------------------------------------------------------------------------------------------------------------------------------
                    Option 3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Change in Capacity Utilization \a\..............            6            7           62          438           41            4            6          101
Change in Generation............................           15            3           53          443           38            4            8          101
Change in Variable Production Costs/MWh.........            2            3          183           72          239           28           23          115
--------------------------------------------------------------------------------------------------------------------------------------------------------
                    Option 4
--------------------------------------------------------------------------------------------------------------------------------------------------------
Change in Capacity Utilization \a\..............            6            4          131          291          113            7            9          104
Change in Generation............................           12            4          118          302          104            6           15          104
Change in Variable Production Costs/MWh.........            2            2          136           46          225           99           37          118
--------------------------------------------------------------------------------------------------------------------------------------------------------
\a\ The change in capacity utilization is the difference between the capacity utilization percentages in the base case and post-compliance cases. For
  all other measures, the change is expressed as the percentage change between the base case and post-compliance values.
\b\ Plants with status changes in either baseline or post-compliance scenario have been excluded from these calculations. For example, for a plant that
  is projected to close in the post-compliance case, the reduction in variable costs per MWh of generated electricity would be 100 percent.
  Specifically, there are 23 full baseline plant closures, 77 partial baseline plant closures, and 1 avoided plant closure under Option 3. There are 23
  full baseline plant closures, 72 partial baseline plant closures, 3 avoided plant closures, and 6 partial policy plant closures under Option 4.

    For Option 3, the analysis of changes in individual plants
indicates that most plants experience only slight effects--no change,
or less than a 1 percent reduction or 1 percent increase. Only 13
plants (2 percent) are estimated to incur a reduction in capacity
utilization exceeding 1 percent and 18 plants (3 percent) incur a
reduction in generation exceeding 1 percent. The estimated change in
variable production costs is higher; 51 plants (8 percent) incur an
increase in variable production costs exceeding 1 percent; for 23 of
these plants, this increase exceeds 3 percent.
    Results for Option 4 show greater effects as compared to Option 3.
While the difference in the policy impact on capacity utilization and
generation is small, the difference in policy impact on variable costs
is greater. The reduction in capacity utilization and generation is
estimated to exceed 1 percent for 10 and 16 plants (approximately 2
percent), respectively. The increase in variable production costs is
estimated to exceed 1 percent for 136 plants, 99 of which have an
increase between 1 and 3 percent.
    As for the market and industry-level results discussed above, EPA
expects the impacts of Options 3a and 3b to be smaller than those of
Option 3, and the impacts of Option 4a to be between those of Options 3
and 4.
3. Summary of Economic Impacts for Existing Sources
    EPA performed cost and economic impact assessment in two parts. The
first set of cost and economic impact analyses--including entity-level
impacts at both the plant and parent company levels--reflects baseline
operating characteristics of plants incurring compliance costs and
assumes no changes in those baseline operating characteristics (e.g.,
level of electricity generation and revenue) as a result of the
requirements of the proposed regulatory options. They can serve as
screening-level indicators of the relative cost of different regulatory
options to plants, owning entities, or consumers, but are not
determinative in terms of

assessing the economic achievability of various regulatory options.
    The second set of analyses look at broader electricity market
impacts taking into account the interconnection of regional and
national electricity markets, for the full industry, for steam electric
plants only, and at the distribution of impacts at the plant level.
This second analysis provides insight on the impacts of the proposed
ELGs on steam electric plants, as well as the electricity market as a
whole, including generation capacity closure, and changes in generation
and wholesale electricity prices. Results of the Market Model for
Option 3 show no incremental plant closures (complete or partial) and
relatively small changes in production costs. This analysis shows that
Option 3 for existing steam electric plants is economically achievable.
This same conclusion applies to Options 3a and 3b since the costs of
these options are less than those of Option 3.
    The Market Model analysis of Option 4 shows slightly higher, but
still relatively small, impacts on steam electric generation and
individual plants as compared to Option 3. For example, the results
show incremental partial capacity retirements of 317 MW at the national
level (1.4 percent relative to the baseline without the proposed ELGs),
no full plant retirements, and greater increases in production costs
(1.0 percent), as compared to Option 3. Given these impacts, and since
the impacts of Option 4a would fall between those of Options 3 and 4,
EPA believes that Option 4a is also economically achievable.
4. Summary of Economic Impacts for New Sources
    Electric power generating units that meet the definition of a new
source would be required to meet the proposed NSPS or PSNS. EPA
developed estimated compliance costs for new units using a methodology
similar to that used to develop compliance costs for existing plants,
with the notable exception that EPA did not develop new unit compliance
costs that are plant specific, which would require EPA to predict which
plants will construct new units.
    EPA assessed the possible impact of incremental costs associated
with this proposal for new units in two ways: (1) As part of its
analysis using IPM discussed in Section XI.D.3; and (2) by comparing
the incremental costs for new units to the overall cost of building and
operating new scrubbed coal units.
    EPA estimated the incremental capital and fixed O&M costs for each
new electricity generating coal unit projected to come online in IPM.
The Agency estimated variable O&M costs assuming that any new unit
would operate, on average, 330 days per year. IPM takes these
additional regulatory costs into account when trying to determine the
least costly means of meeting the total electricity demand. Results of
the IPM analysis are summarized in Section XI.D.3 of this preamble and
discussed in detail in Chapter 5 of the RIA document. IPM results show
no barrier to new generation capacity for 2025-2034 as a result of
compliance with the preferred NSPS/PSNS regulatory options (Option 4).
The model estimates no change in coal steam capacity relative to the
baseline, and small increases in generation capacity from other steam
(0.3 percent), combustion turbine (0.3 percent), other non-steam (less
than 0.1 percent), and combined cycle (less than 0.1 percent)
units.\80\
---------------------------------------------------------------------------

    \80\ Other steam generation includes biomass, landfill gas,
fossil waste, municipal solid waste, non-solid waste, tires, and
geothermal. Other non-steam generation includes wind, solar, pumped
storage, and fuel cell.
---------------------------------------------------------------------------

    As a separate analysis, EPA also compared total compliance costs to
the total cost of building and operating a new coal unit on an
annualized basis. EPA obtained the overnight \81\ capital and O&M costs
of building and operating a new scrubbed coal unit used in the Energy
Information Administration's Annual Energy Outlook 2011; these costs
were estimated for a new dual-unit plant with a total generation
capacity of 1,300 MW. Table XI-8 shows capital and O&M costs of
building and operating a new coal unit and contrasts these costs with
the incremental costs associated with the preferred option (i.e.,
Option 4 for new sources).
---------------------------------------------------------------------------

    \81\ As defined by the Energy Information Administration,
``overnight cost'' is an estimate of the cost at which a plant could
be constructed assuming that the entire process from planning
through completion could be accomplished in a single day. This
concept is useful to avoid any impact of project delays and of
financing issues and assumptions on estimated costs.

    Table XI-8--Comparison of Incremental Compliance Costs with Costs for New Coal-Fired Steam Electric Units
----------------------------------------------------------------------------------------------------------------
                                                         Costs of new coal     Incremental
                     Cost component                          generation      compliance costs    Percent of new
                                                           ($2010/MW) \a\     ($2010/MW) \b\    generation cost
----------------------------------------------------------------------------------------------------------------
Capital................................................         $2,981,947    $19,911-$21,773            0.7-0.7
Annual O&M.............................................             66,427       2,281-$3,093            3.4-4.7
                                                        --------------------------------------------------------
Total Annualized Costs.................................            329,487       4,037-$5,013            1.2-1.5
----------------------------------------------------------------------------------------------------------------
\a\ Source: New unit total cost value from Table 8.2 EIA NEMS Electricity Market Module. AEO 2011 Documentation.
  Available at http://www.eia.gov/forecasts/aeo/assumptions/pdf/electricity.pdf. Capital costs are based on the
  total overnight costs for new scrubbed coal dual-unit plant, 1,300 MW capacity coming online in 2014. EPA
  restated costs in 2010 dollars. Total annual O&M costs assume 90% capacity utilization.
\b\ Incremental costs for new 1300 MW unit for Option 4. Range represents the costs for a new unit at an
  existing plant (lower bound) and new unit at newly constructed plant (upper bound).

    The comparison suggests that compliance with the proposed ELGs
represents a relatively small fraction of overnight capital costs of a
new unit (less than 1 percent) and a somewhat higher, but still small
(less than 5 percent), fraction of non-fuel O&M costs. On an annualized
basis, compliance costs for the proposed ELGs are 1.2 to 1.5 percent of
annualized costs for a new plant.
    Based on these two separate assessments, EPA finds no evidence that
the incremental compliance costs associated with the proposed NSPS/PSNS
present a barrier to entry.
5. Assessment of Potential Electricity Price Effects
    EPA assessed the potential electricity price effects of this
proposed rule in two ways: (1) an assessment of the potential annual
increase in household electricity costs and (2) an assessment of the
potential annual increase in electricity costs per MWh of total
electricity sales.

The analysis assumes, for analytic convenience as a worst-case
scenario, that all compliance costs will be passed through on a pre-tax
basis as increased electricity prices as opposed to the treatment in
the plant- and entity-level analyses discussed in Section XI.D.1 above,
which assume that none of the compliance costs will be passed to
consumers through electricity rate increases.
a. Cost to Residential Households
    Using the assumptions outlined above, EPA estimated the potential
annual increase in electricity costs per household, by North American
Electric Reliability Corporation (NERC) region. The analysis uses the
total annualized pre-tax compliance cost per megawatt hour (MWh) for
the year 2014 (in 2010 dollars), in conjunction with the reported total
electricity sales quantity for each NERC region for 2009. This analysis
also uses the quantity of residential electricity sales per household
in 2009. To calculate the average cost per household, by region, EPA
divided total compliance costs for each NERC region by the reported
total MWh of sales within the region. The potential annual cost impact
per household was then calculated by multiplying the estimated average
cost per MWh by the average MWh per household, by NERC region.\82\
Details of this analysis are presented in Chapter 7 of the RIA.
---------------------------------------------------------------------------

    \82\ Some NERC regions have been re-defined over the past few
years. The NERC region definitions used in this proposed rule
analyses vary by analysis depending on which region definition
aligns better with the data elements underlying the analysis.
---------------------------------------------------------------------------

    Table XI-9 summarizes the annual household impact results for each
regulatory option, by NERC region. The results for Option 3a show the
average annual cost per residential household increasing by $0 to $1.69
depending on the region, with a national average of $0.48. This
represents a monthly increase of $0.04 for the typical household. For
Option 3b, the results show the average annual cost per residential
household increasing by $0 to $2.29, with a national average of $0.75,
or $0.06 per month. For Option 3, the average annual cost per
residential household increases by $0 to $4.40, with a national average
of $1.59, or $0.13 per month. Finally, for Option 4a, the average
annual cost per residential household increases by $0 to $7.22,
depending on the region, with a national average of $2.69, or $0.22 per
month.

  Table XI-9--Average Annual Cost Burden per Residential Household in 2014 by Regulatory Option and NERC Region
                                                   [2010$] \a\
----------------------------------------------------------------------------------------------------------------
                                   Option    Option                                  Option
           NERC Region               3a        3b     Option 1  Option 2  Option 3     4a     Option 4  Option 5
----------------------------------------------------------------------------------------------------------------
ASCC............................     $0.00     $0.00     $0.00     $0.00     $0.00     $0.00     $0.00     $0.00
ECAR............................      1.69      2.29      1.82      2.71      4.40      7.22     10.08     16.86
ERCOT...........................      0.00      0.42      1.22      1.73      1.73      2.60      2.79      5.76
FRCC............................      0.00      0.00      0.18      0.67      0.67      0.67      0.99      4.32
HICC............................      0.00      0.00      0.00      0.00      0.00      0.00      0.00      0.00
MAAC............................      0.00      0.00      0.06      0.32      0.32      0.97      2.04      3.52
MAIN............................      0.31      0.31      0.48      0.69      1.01      2.55      4.63      6.16
MAPP............................      0.01      0.01      0.97      1.30      1.32      2.04      3.23      5.58
NPCC............................      0.00      0.00      0.03      0.08      0.08      0.08      0.49      0.67
SERC............................      1.09      2.00      1.63      2.19      3.28      4.98      6.47     10.81
SPP.............................      0.05      0.14      0.61      0.96      1.01      2.85      4.43      6.30
WECC............................      0.05      0.05      0.02      0.03      0.08      0.23      0.53      0.59
U.S.............................      0.48      0.75      0.75      1.12      1.59      2.69      3.89      6.46
----------------------------------------------------------------------------------------------------------------
\a\ The rate impact analysis maintains the counterfactual, conservative assumption of 100 percent pass-through
  to electricity consumers.

    As stated above, this analysis assumes that all of the compliance
costs (100 percent) will be passed onto consumers through increased
electricity rates. However, plants and owning entities are likely to
absorb some of these costs, thereby reducing the impact of the proposed
ELGs on electricity consumers. At the same time, EPA recognizes that
electric generators that operate as regulated public utilities are
generally permitted to pass on environmental compliance costs as rate
increases to consumers. To evaluate the sensitivity of the results to
the pass-through assumption, EPA analyzed alternative scenarios
including cases where only half (50 percent) of the incremental
compliance costs are passed onto consumers. Appendix B of the RIA
report presents the results of this sensitivity analysis. The results
show smaller impacts on electricity rates, commensurate with the
smaller fraction of the compliance costs that are passed onto
consumers.
b. Compliance Costs per Unit of Electricity Sales
    As an additional measure of the potential electricity price effects
associated with the proposed ELGs, EPA also assessed the potential
increase in electricity prices to all consumer groups (residential,
commercial, industrial, and transportation), again making a
counterfactual, conservative assumption of a 100 percent pass-through
of compliance costs. This assessment uses as its basis the cost of the
regulatory options per unit of electricity sold.
    EPA used two data inputs in this analysis (1) total pre-tax
compliance cost by NERC region, and (2) estimated total electricity
sales for 2014, by NERC region. The Agency summed sample-weighted pre-
tax annualized compliance costs as of 2014 over complying plants by
NERC region to calculate the total estimated annual cost in each
region. EPA then calculated the approximate average price impact per
unit of electricity consumption by dividing total compliance costs by
the reported total MWh of sales in each NERC region. Details of this
analysis are presented in Chapter 7 of the RIA report.
    As reported in Table XI-10, on average, across the United States,
Option 5 results in the highest increased compliance cost of
0.059[cent] per kWh. Annualized compliance costs (in dollars per KWh
sales) associated with Option 3a range from 0[cent] to 0.016[cent],
depending on the region, with a national average of

0.004[cent] per KWh. For Option 3b, annualized compliance costs range
from 0[cent] to 0.022[cent], with a national average of 0.007[cent] per
KWh, whereas Option 3 has a range of 0[cent] to 0.042[cent] per kWh and
a national average of 0.015[cent] per kWh and Option 4a has a range of
0[cent] to 0.068[cent] per kWh and a national average of 0.025[cent]
per kWh. To determine the potential significance of these compliance
costs on electricity prices, EPA compared the per kWh compliance cost
to baseline electricity prices by consuming sector, and for the average
of the sectors. Across the United States and consuming sectors, Option
3a is estimated to result in the smallest electricity price increase,
0.05 percent; the other preferred BAT and PSES options, Options 3b, 3
and 4a, have estimated increases of 0.08 percent, 0.16 percent and 0.27
percent, respectively.

     Table XI-10--Compliance Cost per Unit of Electricity Sales in 2014 by Regulatory Option and NERC Region
                                           [2010 [cent]/KWh Sales] \a\
----------------------------------------------------------------------------------------------------------------
                                   Option    Option                                  Option
           NERC Region               3a        3b     Option 1  Option 2  Option 3     4a     Option 4  Option 5
----------------------------------------------------------------------------------------------------------------
ASCC............................     0.000     0.000     0.000     0.000     0.000     0.000     0.000     0.000
ECAR............................     0.016     0.022     0.017     0.026     0.042     0.068     0.095     0.159
ERCOT...........................     0.000     0.003     0.009     0.012     0.012     0.019     0.020     0.041
FRCC............................     0.000     0.000     0.001     0.005     0.005     0.005     0.007     0.032
HICC............................     0.000     0.000     0.000     0.000     0.000     0.000     0.000     0.000
MAAC............................     0.000     0.000     0.001     0.003     0.003     0.010     0.021     0.036
MAIN............................     0.003     0.003     0.005     0.008     0.011     0.028     0.051     0.068
MAPP............................     0.000     0.000     0.009     0.012     0.013     0.019     0.031     0.053
NPCC............................     0.000     0.000     0.000     0.001     0.001     0.001     0.007     0.009
SERC............................     0.008     0.014     0.012     0.016     0.023     0.035     0.046     0.076
SPP.............................     0.000     0.001     0.005     0.008     0.008     0.023     0.036     0.051
WECC............................     0.001     0.001     0.000     0.000     0.001     0.002     0.006     0.006
U.S.............................     0.004     0.007     0.007     0.010     0.015     0.025     0.036     0.059
----------------------------------------------------------------------------------------------------------------
\a\ This analysis makes a counterfactual, conservative assumption of 100 percent pass-through to electricity
  consumers.

    As mentioned in the previous section, EPA ran alternative scenarios
using an assumption that only half (50 percent) of the incremental
compliance costs are passed onto consumers. The results of these
alternative scenarios showed commensurately smaller impacts on
compliance costs per unit of electricity sold (see Appendix B of the
RIA report).

E. Employment Effects

    EPA assessed the potential for employment impacts at the national
level for the eight regulatory options considered in this action.
1. Methodology
    The employment effects analysis estimates employment changes only
in the directly regulated electric power industry sector at the
national level. This analysis focuses on the longer-term, on-going
employment effects of meeting compliance requirements, and accounts for
all compliance costs, regardless of their time, duration, or frequency
of occurrence. Morgenstern, Pizer and Shih (2000) explore both
theoretically and empirically the relationship between employment and
compliance costs of environmental regulation. Morgenstern et al.
identify three separate components of the employment change within a
regulated industry in response to a regulation. First, complying with
environmental regulations causes higher production costs which raises
market prices, higher prices reduce consumption (and production)
reducing demand for labor within the regulated industry (``demand
effect''). Second, as costs go up, to produce the same level of output,
plants add more capital and labor. For example, pollution abatement
activities require additional labor services to produce the same level
of output (``cost effect''). Third, post-regulation production
technologies may be more or less labor intensive (i.e., more/less labor
is required per dollar of output) (``factor-shift effect''). The demand
effect is unambiguously negative, the cost effect is unambiguously
positive and the factor-shift effect could be positive or negative
making the total effect theoretically indeterminate. In addition,
Morgenstern et al. also estimate an empirical model for four highly
polluting/regulated industries to examine the effect of higher
abatement costs from regulation on employment. They conclude that
increased abatement expenditures generally do not cause a significant
change in employment. More specifically, their results show that, on
average across their industries, each additional $1 million spending on
pollution abatement (in $1987 dollars) results in a (statistically
insignificant) net increase of 1.5 jobs (95 percent confidence
interval: -2.9 to + 6.0).
2. Findings
    Table XI-11 presents the estimated change, based on the Morgenstern
et al. results, in employment in the electric power industry due to the
proposed ELGs under each of the eight regulatory options. The table
lists the options in increasing order of employment effects. Overall,
in the aggregate and by a specific employment effect, Option 1 is
projected to have the smallest effect and Option 5 is projected to have
the largest effect on employment. The Demand Effect is projected to
result in a decline in the number of jobs, while the Cost Effect and
Factor Shift Effect are projected to result in an increase in the
number of jobs.
    EPA estimated an average annual increase of 168 jobs under proposed
Option 3a for existing sources. For proposed Option 3b, the average
annual increase is estimated at 255 jobs, whereas Options 3 and 4a have
estimated increases of 519 jobs and 865 jobs, respectively. Because the
electric utility industry is more capital intensive and less labor
intensive than the industries examined in Morganstern, Pizer and Shih,
in addition to the employment estimates being statistically not
distinguishable from the effect being zero, the estimates presented
here are likely to be over-estimated. Chapter 6 of the RIA report
describes the methodologies and results in greater detail.

Table XI-11--Results of Ongoing Employment Effects on the Electric Power
                  Industry Sector (Number of Jobs) a b
------------------------------------------------------------------------
                                                            Total annual
                                                               average
         Regulatory option             Employment effect     employment
                                                               effect
------------------------------------------------------------------------
Option 3a.........................  Cost..................           262
                                    Factor Shift..........           291
                                    Demand................          -386
                                   -------------------------------------
                                       Total..............           168
------------------------------------------------------------------------
Option 1..........................  Cost..................           380
                                    Factor Shift..........           421
                                    Demand................          -559
                                   -------------------------------------
                                       Total..............           243
------------------------------------------------------------------------
Option 3b.........................  Cost..................           399
                                    Factor Shift..........           441
                                    Demand................          -586
                                   -------------------------------------
                                       Total..............           255
------------------------------------------------------------------------
Option 2..........................  Cost..................           548
                                    Factor Shift..........           607
                                    Demand................          -806
                                   -------------------------------------
                                       Total..............           548
------------------------------------------------------------------------
Option 3                            Cost..................           810
                                    Factor Shift..........           897
                                    Demand................        -1,192
                                   -------------------------------------
                                       Total..............           519
------------------------------------------------------------------------
Option 4a.........................  Cost..................         1,351
                                    Factor Shift..........         1,496
                                    Demand................        -1,988
                                   -------------------------------------
                                       Total..............           865
------------------------------------------------------------------------
Option 4..........................  Cost..................         1,956
                                    Factor Shift..........         2,166
                                    Demand................        -2,878
                                   -------------------------------------
                                       Total..............         1,253
------------------------------------------------------------------------
Option 5..........................  Cost..................         3,298
                                    Factor Shift..........         3,653
                                    Demand................        -4,852
                                   -------------------------------------
                                       Total..............         2,112
------------------------------------------------------------------------
\a\ Source: Morgenstern, Pizer, and Shih (2002).
\c\ Coefficients from Table III, p. 427, for the Cost, Demand, Factor
  Shift and Total Effects were multiplied by the annualized cost of the
  proposed ELGs calculated as part of the social cost analysis (see
  Section XI.C) during the 24-year analysis period and re-stated in 1987
  dollars, by the coefficient for the net increase in jobs.
 Number of jobs is the average number of production workers plus other
  employees. The definition for employment used by the U.S. Census
  Bureau's Annual Survey of Manufacturers can be found here: http://www.census.gov/manufacturing/asm/definitions/index.html.

XII. Cost-Effectiveness Analysis

    EPA performed a cost-effectiveness analysis of the regulatory
options for existing plants. EPA often uses cost-effectiveness analysis
in the development/revision of effluent limitations guidelines and
standards to evaluate the relative efficiency of alternative regulatory
options in removing toxic pollutants from the effluent discharges to
the nation's waters. Although not required by the Clean Water Act,
cost-effectiveness analysis is a useful tool for evaluating regulatory
options that address toxic pollutants.

A. Methodology

    The cost-effectiveness of a regulatory option is defined as the
incremental annual cost (in 1981 constant dollars) per incremental
toxic-weighted pollutant removals for that option. This definition
includes the following concepts:
    Toxic-weighted removals. Pollutants differ in their toxicity.
Therefore, the estimated reductions in pollution discharges, or
pollutant removals, are adjusted for toxicity by multiplying the
estimated removal quantity for each pollutant by a normalizing toxic
weight (toxic weighting factor). The toxic weight for each pollutant
measures its toxicity relative to copper, with more toxic pollutants
having higher toxic weights. The use of toxic weights allows the
removals of different pollutants to be expressed on a constant toxicity
basis as toxic pound-equivalents (lb-eq). The removal quantities for
the different pollutants can then be summed to yield an aggregate
measure of the reduction in toxicity-normalized pollutant discharges
that is achieved by a regulatory option. The cost-effectiveness
analysis does not address the removal of conventional pollutants (e.g.,
total suspended solids) or nutrients (nitrogen, phosphorus), nor does
it address the removal of bulk parameters, such as COD. In the case of
indirect dischargers, the removal also accounts for the effectiveness
of treatment at publicly owned treatment works (POTW) and reflects the
toxic-weighted pounds remaining after POTW treatment.
    Annual costs. The costs used in the cost-effectiveness analysis are
the estimated annualized pre-tax costs to comply with the alternative
regulatory options (refer to Section XI for a discussion of the
annualized compliance costs). These costs to plants to remove the
pollutants will be less because the costs are tax deductible. The
annual costs include the annualized capital outlays for equipment and
recurring expenses for operating and maintaining compliance equipment,
meeting monitoring requirements, etc.
    Incremental calculations. The incremental values are the changes in
total annual compliance costs and changes in pollutant removals as one
moves to a regulatory option from the next less stringent regulatory
option, or from the baseline for the least stringent option analyzed,
where regulatory options are ranked by increasing levels of toxic-
weighted removals. The resulting cost-effectiveness values for a given
option are, therefore, expressed relative to another option or, for the
least stringent option considered, relative to the baseline.
    The result of the cost-effectiveness calculation represents the
unit cost of removing the next pound-equivalent of pollutants and is
expressed in constant 1981 dollars per toxic pound-equivalent removed
($/lb-eq) to allow comparisons with the reported cost effectiveness of
other effluent guidelines, which use 1981 dollars.
    EPA performed the cost-effectiveness analysis for the eight
regulatory options for the proposed Steam Electric ELGs separately for
existing direct dischargers (subject to BAT) and indirect dischargers
(subject to PSES). The following sections summarize the results. Note
that the same plant may be categorized as a direct discharger for one
of the wastestreams it generates and as an indirect discharger for
another.

B. Cost-Effectiveness Analysis for Direct Dischargers

    Table XII-1 summarizes the cost-effectiveness analysis for the BAT
regulatory options applicable to direct dischargers. The table lists
the options in increasing order of total annual toxic-weighted
pollutant removals.

                                  Table XII-1--Cost-Effectiveness of Removing Toxic Pollutants for Direct Dischargers a
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                     Annual pre-tax compliance costs     Total annual toxic-weighted     Cost effectiveness  (1981$/lb-
                                                            (million, 1981$)           pollutant removals (000 lb-eq)                  eq)
                                                   -----------------------------------------------------------------------------------------------------
                      Option                                                                                Incremental
                                                      Option total     Incremental      Option total     Incremental      Option cost          cost
                                                          cost             cost           removals         removals      effectiveness    effectiveness
--------------------------------------------------------------------------------------------------------------------------------------------------------
Option 1..........................................           $105.6           $105.6        1,530,719        1,530,719              $69              $69
Option 3a.........................................             67.5            -38.1        2,488,470          957,751               27              -40
Option 2..........................................            156.0             88.5        2,603,628          115,158               60              768
Option 3b.........................................            106.3            -49.7        3,396,653          793,025               31              -63
Option 3..........................................            223.5            117.2        5,092,098        1,695,445               44               69
Option 4a.........................................            378.7            155.2        6,664,693        1,572,595               57               99
Option 4..........................................            547.9            169.2        7,831,298        1,166,605               70              145
Option 5..........................................            906.5            358.5        8,200,804          369,506              111              970
--------------------------------------------------------------------------------------------------------------------------------------------------------
\a\ Options are ranked by increasing levels of total annual toxic-weighted removals.

    As shown in Table XII-1, the proposed technology bases for BAT have
a cost-effectiveness ratio of $27/lb-eq, $31/lb-eq, $44/lb-eq, and $57/
lb-eq, respectively for Options 3a, 3b, 3 and 4a ($1981). These cost-
effectiveness ratios are well within the range of cost-effectiveness
ratios for BAT of other industries. A review of approximately 25 of the
most recently promulgated or revised BAT limitations shows BAT cost-
effectiveness ranging from less than $1/lb-eq (Inorganic Chemicals) to
$404/lb-eq (Electrical and Electronic Components), in 1981 dollars.

C. Cost-Effectiveness Analysis for Indirect Dischargers

    Table XII-2 summarizes the cost-effectiveness analysis for the PSES
regulatory options applicable to indirect dischargers. Toxic-weighted
pollutant removals for indirect dischargers account for POTW removal
efficiencies. The table lists the options in increasing order of total
annual toxic-weighted pollutant removals.

                                 Table XII-2--Cost-Effectiveness of Removing Toxic Pollutants for Indirect Dischargersa
--------------------------------------------------------------------------------------------------------------------------------------------------------
                                                     Annual pre-tax compliance costs     Total annual toxic-weighted    Cost effectiveness (1981$/lb-eq)
                                                            (million, 1981$)           pollutant removals (000 lb-eq)  ---------------------------------
                      Option                       --------------------------------------------------------------------                    Incremental
                                                      Option total     Incremental      Option total     Incremental      Option cost          cost
                                                          cost             cost           removals         removals      effectiveness    effectiveness
--------------------------------------------------------------------------------------------------------------------------------------------------------
Option 3a.........................................             $0.0             $0.0                0                0  ...............  ...............
Option 3b.........................................              0.0              0.0                0                0  ...............  ...............
Option 1..........................................              1.2              1.2            3,540            3,540             $345             $345
Option 2..........................................              2.0              0.7           11,711            8,171              168               92
Option 3..........................................              2.0              0.0           11,711                0              168  ...............
Option 4a.........................................              2.0              0.0           11,711                0              168  ...............
Option 4..........................................              3.6              1.6           15,532            3,821              233              430
Option 5..........................................              8.1              4.5           18,297            2,765              445            1,636
--------------------------------------------------------------------------------------------------------------------------------------------------------
\a\ Options are ranked by increasing levels of total annual toxic-weighted removals.

    As shown in Table XII-2, there are no indirect dischargers that
would incur compliance costs or result in incremental pollutant
removals under Options 3a and 3b, whereas Options 3 and 4a both have a
cost effectiveness of $168/lb-eq ($1981). The cost-effectiveness of
Options 3 and 4a is within the range of cost-effectiveness for PSES of
other industries. A review of approximately 25 of the most recently
promulgated or revised categorical pretreatment standards shows PSES
cost-effectiveness ranging from less than $1/lb-eq (Inorganic
Chemicals) to $380/lb-eq (Transportation Equipment Cleaning), in 1981
dollars.

XIII. Environmental Assessment

    This section describes the environmental assessment conducted in
support of this rulemaking. The environmental assessment reviewed
currently available literature on the documented environmental and
human health impacts of combustion wastewaters and conducted modeling
to determine the cumulative impacts caused by the universe of steam
electric power plants proposed to be regulated under this effluent
limitations guidelines and standards. Modeling calculated both the
impacts at baseline conditions (current conditions), and the
improvements that will result after implementation of the different
potential control options. The environmental improvements discussed in
Section XIII.A below are those for the preferred BAT and PSES
regulatory options (Option 3a, Option 3b, Option 3, and Option 4a).
    A complete review of the scientific literature and a full
description of EPA's modeling analysis (including the results for all
other control options) are provided in the Environmental Assessment of
the Proposed Effluent Limitations Guidelines and Standards for the
Steam Electric Power Generating Point Source Category.
    Current scientific literature indicates that combustion wastewaters
such as fly ash and bottom ash transport water, FGD wastewater, and
combustion residual leachate are toxic wastes and are causing
significant detrimental environmental and human health impacts.
Documented environmental impacts from exposure to these wastes reveals
that the threat posed to human health, wildlife and the environment is
a widespread problem that is not isolated to a few unique locations or
circumstances. Documented instances of drinking water maximum
contaminant

level (MCL) exceedances near steam electric power plants and the
issuance of fish advisories in waters that receive combustion
wastewater indicates the likely threat of human health impacts from
these wastestreams (see Section 3.4.2 of the Environmental Assessment).
In addition, one recent study provides confirming empirical evidence
that toxic wastes are currently damaging aquatic life and accumulating
in the environment and will only get worse.\83\
---------------------------------------------------------------------------

    \83\ Ruhl, L., A. Vengosh, G.S. Dwyer, H. Hsu-Kim, G. Schwartz,
A. Romanski, and S.D. Smith. 2012. The Impact of Coal Combustion
Residue Effluent on Water Resources: A North Carolina Example.
Environmental Science and Technology. DCN SE01984.
---------------------------------------------------------------------------

    Ecological impacts include both acute (e.g., fish kills) and
chronic effects (e.g., malformations, and metabolic, hormonal, and
behavioral disorders) upon biota within the receiving water and the
surrounding environment. Bioaccumulative toxic metals (e.g., selenium,
mercury, and arsenic) are commonly cited as the primary cause for
ecological damage following exposure to combustion wastewater. Selenium
is the most frequently cited metal associated with environmental
impacts following exposure to combustion wastewater discharges.
Documented selenium-related impacts include lethal effects such as fish
kills and sublethal effects such as histopathological changes (i.e.,
accumulation of trace elements in tissue) and damage to reproductive
and developmental success. Other metals in combustion wastewater
discharges such as arsenic, cadmium, chromium, copper, and lead have
also been documented as causing sublethal effects such as changes to
morphology (e.g., fin erosion, oral deformities), behavior (e.g.,
swimming ability, ability to catch prey, ability to escape from
predators), and metabolism that can negatively affect long-term
survival. Combined, these impacts can drastically alter aquatic
populations and communities and the surrounding ecosystems that rely on
them.
    Recovery of the environment from exposure to combustion wastewater
discharges can be extremely slow due to the accumulation and continued
cycling of contaminants within the ecosystem and the potential to alter
ecological processes, such as population diversity and community
dynamics in the surrounding ecosystems. The ability of aquatic and
adjacent terrestrial environments to recover from even short periods of
exposure to these wastes depends on, among other factors, the distance
from the discharge, the pollutant loadings, pollutant residence time,
and the time elapsed since exposure. In particular, accumulation of
metals in sediments can make recovery of aquatic systems following
exposure to combustion wastewater discharges exceptionally slow due to
the potential for resuspension in the water column and for benthic
organisms to provide a pathway for exposure long after discharges have
ended. In addition, metals such as selenium and arsenic bioaccumulate
in organisms exposed to combustion wastewater discharges further
complicating the potential magnitude of impacts these wastes pose.
    EPA identified several cases in the literature where metals from
combustion wastewater discharges bioaccumulated to toxic levels in
organisms inhabiting aquatic environments even with low concentrations
of these contaminants. The strong bioaccumulative properties of the
pollutants, in conjunction with long residence times, emphasize the
threat these wastes present to the local environment as many of the
impacts may not be fully realized for years to come.
    In addition to the bioaccumulative and toxic properties of the
pollutants in combustion wastewaters, the total pollutant loadings
associated with these discharges are large (see Section IX). EPA
estimates that discharges from steam electric power plants alone
contribute 50 to 60 percent of the reported toxic-weighted pollutant
loadings of the combined discharges of all industrial categories
currently regulated in the U.S. Further, many steam electric power
plants discharge to sensitive environments where pollutant loadings
contribute to reduced water quality (e.g., Great Lakes, valuable
estuaries, 303(d) listed waters, drinking water sources, and waters
with fish consumption advisories).
    EPA has determined that 25 percent of surface waters that receive
combustion wastewater discharges are impaired for a pollutant
associated with combustion wastewater; 38 percent of surface waters are
under a fish advisory for a pollutant associated with combustion
wastewater. In addition to the concurrence of combustion wastewater
discharges in close proximity to sensitive environments, EPA has
identified over 120 steam electric power plants with documented
environmental impacts to surface water and ground water environments
following exposure to combustion wastewater, which is further evidence
these wastes are of great concern. While in the past these cases may
have been assumed to be anomalies, an increasing amount of evidence
indicates that the characteristics contributing to the documented
impact (e.g., size of the pollutant loadings, type of pollutant present
in the waste, plant operations, and wastewater handling techniques) are
common among power plant discharge locations. Further, as explained
earlier, these documented impacts do not yet reflect the increased
pollutant loadings associated with increasing use of air pollution
controls. This, when coupled with the potential for long-term
persistent impacts due to bioaccumulative pollutants, indicates that
these impacts most likely are occurring in other locations around the
country even though they have not yet been documented. This suggests
that the magnitude of the environmental impact of combustion wastewater
discharges is potentially greater than the literature estimates.
    In addition, EPA has identified other potential impacts from
combustion wastewater discharges. Steam electric plants also discharge
bromide in large quantities. Bromide in wastewater discharges from
steam electric plants located upstream from a drinking water intake has
been associated with the formation of trihalomethanes (THMs) and
haloacetic acids (HAAs) when it is exposed to chlorination disinfection
processes in drinking water treatment plants. Bromate, a disinfection
byproduct (DBP) associated with drinking water treatment plants that
employ ozonation may also increase under the influence of increased
bromide in the source water. Human exposure to THMs and DBPs in
chlorinated drinking water is associated with bladder cancer.
    Based on the documented environmental impacts discussed in the
literature, EPA identified several key environmental and human health
concerns and pathways of exposure to evaluate in the environmental
assessment. These included changes in surface water, sediment, and
ground water quality; toxic effects on aquatic life; toxic metal
bioaccumulation in fish and in piscivorous wildlife (e.g., minks and
bald eagles); toxic metal bioaccumulation in fish consumed by humans;
and contamination of ground water drinking water resources.
    EPA developed a three-part receiving water model to quantify
changes in plant-specific impacts to surface waters, wildlife, and
human health from pollutant reductions associated with the regulatory
options discussed in Section VIII for a subset of evaluated
wastestreams from steam electric power plants (i.e., fly ash and bottom
ash transport water, FGD wastewater, and leachate). EPA considered the
type of

receiving waters commonly impacted by steam electric power plants and
the pollutants typically found in the evaluated wastestreams in
selecting the appropriate methodologies for the quantitative
Environmental Assessment analysis. EPA designed the model to quantify
the environmental impact within rivers/streams and lakes/ponds
(including reservoirs) based on the finding that 94 percent of the
power plant outfalls discharge to these types of surface waters. EPA
focused the modeling on toxic metals due to the total mass loadings
discharged, potential for toxic effects to wildlife and human health,
and potential for bioaccumulation within the ecosystem. EPA addressed
environmental impacts from nutrients, in a separate analysis discussed
in Section XIII.E.
    EPA's environmental assessment modeling includes three interrelated
models: 1) a receiving water-scale water quality model; 2) a receiving
water-scale wildlife model; and 3) a receiving water-scale human health
model. Each of these models evaluates changes in environmental and
human health effects under baseline conditions and five of the
regulatory options discussed in Section VIII of this preamble (Options
1, 2, 3, 4, and 5). The receiving water-scale water quality model
estimates the concentration of metals (i.e., arsenic, cadmium, chromium
VI, copper, lead, mercury, nickel, selenium, thallium, zinc) in the
surface waters and sediments in the immediate discharge zone (i.e.,
approximately one to 10 kilometers [km] from the outfall) for steam
electric power plants with direct discharge loadings included in the
costs and loadings analysis (see Section IX). EPA compared modeled
receiving water concentrations based on pollutant loadings from the
evaluated wastestreams against National Recommended Water Quality
Criteria (NRWQC) and Maximum Contaminant Levels (MCLs) to assess
changes in receiving water quality. The wildlife model evaluates the
potential impact that water and sediment concentrations pose to aquatic
life, calculates the metal concentrations in exposed fish populations,
and evaluates the potential impact to wildlife (minks and eagles) from
consumption of fish. The human health model calculates potential threat
to cause non-cancer health effects and cancer risks to human
populations from the consumption of fish exposed to discharges of the
evaluated wastestreams. In addition to the immediate receiving water
analysis, EPA modeled receiving water concentrations downstream from
steam electric discharges using EPA's Risk-Screening Environmental
Indicators (RSEI) model and used the wildlife and human health models
to calculate metal concentrations in exposed fish populations and human
exposure doses from fish consumption in surface waters downstream from
steam electric discharges. EPA compared downstream receiving water
concentrations, fish tissue concentrations, and human exposure to water
quality, wildlife, and non-cancer and cancer benchmarks to assess the
number of improved river miles associated with the different options
for this proposed rule.
    EPA did not perform modeling to evaluate changes in environmental
and human health effects under Option 3a, Option 3b, or Option 4a. To
estimate the environmental improvements under these three options, the
Agency compared their pollutant load reductions to those of Option 3
(whose reductions would be greater than those of Option 3a and Option
3b, and less than those of Option 4a) and applied corresponding
adjustments to the modeled environmental improvements under Option 3 to
approximate those of the three un-modeled options.
    EPA expects a number of environmental and ecological improvements
and reduced impacts to wildlife and human receptors to result from
reductions in effluent loadings examined for the different options
discussed in this proposed rule. In particular, the Environmental
Assessment evaluated the following: a) improvements in water quality,
b) reduction in impacts to wildlife, c) reduction in number of
receiving waters with potential human health cancer risks, d)
reductions in number of receiving waters with potential to cause non-
cancer human health effects, e) reduction in nutrient impacts, f)
reduction in other environmental impacts, and g) unquantified
environmental improvements.

A. Improvements in Surface Water and Ground Water Quality

    The reduced pollutant loadings associated with the preferred
options (Option 3a, Option 3b, Option 3, and Option 4a) would lead to
reduced contamination levels in surface waters and sediments. EPA
estimated that reduced pollutant loadings to surface waters associated
with Option 3a would significantly improve water quality by reducing
metal concentrations by up to 33 percent on average within the
immediate receiving waters. Option 3b, Option 3, and Option 4a would
achieve average reductions of up to 36 percent, 48 percent, and 60
percent, respectively. The pollutants with the greatest number of water
quality standard (NRWQC or MCL) exceedances under baseline pollutant
loadings include: total arsenic, total thallium, dissolved cadmium, and
total selenium. EPA determined that 49 percent of the immediate
receiving waters exceeded a water quality standard under baseline
loadings. EPA estimates the number of immediate receiving waters with
aquatic life exceedances, which are driven by dissolved cadmium and
total selenium concentrations, would be reduced by up to 29 percent for
both Option 3a and Option 3b, up to 35 percent for Option 3, and up to
55 percent for Option 4a under the post-compliance pollutant loadings.
EPA also estimates that the number of immediate receiving waters with
human health water quality standards exceedances, primarily driven by
total arsenic and total thallium concentrations, would be reduced by up
to 14 percent for Option 3a, up to 15 percent for Option 3b, up to 18
percent for Option 3, and up to 41 percent for Option 4a.
    Selenium was one of the primary pollutants identified in the
literature as causing documented environmental impacts to fish and
wildlife. EPA calculates that total selenium receiving water
concentrations would be reduced by 33 percent on average under Option
3a, 36 percent on average under Option 3b, 48 percent on average under
Option 3, and 60 percent on average under Option 4a. This would reduce
the number of immediate receiving waters exceeding the freshwater
chronic criteria for selenium by 38 percent under Option 3a, 40 percent
under Option 3b, 55 percent under Option 3, and 67 percent under Option
4a. EPA estimates that up to 3,643 river miles (Option 3a), 3,862 river
miles (Option 3b), 4,830 river miles (Option 3), and 6,633 river miles
(Option 4a) downstream from steam electric discharges would no longer
exceed aquatic life and human health NRWQC or MCL standards under the
post-compliance pollutant loadings.
    The preferred options would both reduce ground water contamination
levels and improve the availability of ground water resources by
reducing the future leaching of pollutants from steam electric
impoundments to groundwater aquifers. Section XIV provides additional
details on the benefits analysis of these ground water improvements.

B. Reduced Impacts to Wildlife

    EPA calculates that the number of immediate receiving waterbodies
with potential impacts to wildlife would be

reduced by up to 23 percent under Option 3a, up to 24 percent under
Option 3b, up to 30 percent under Option 3, and up to 51 percent under
Option 4a. EPA developed the receiving waters wildlife model to
quantify the impacts to wildlife that consume fish exposed to steam
electric discharges. EPA selected minks and eagles as representative
indicator species to evaluate the impact discharges of the evaluated
wastestreams posed to birds and mammals that consume fish. EPA selected
minks and eagles based on their national population distribution and
the fact that a majority of their diet is comprised of fish. EPA
modeled fish tissue concentrations for the immediate and downstream
receiving waters and compared those concentrations to no effect hazard
concentrations (NEHC) benchmarks developed by the U.S. Geological
Survey (USGS) that indicate potential impacts to piscivorous (i.e.,
fish eating) wildlife. The NEHC benchmarks developed by the USGS are
based on ``no observed adverse effect levels'' (NOAELs), which were
derived from adult dietary exposure or tissue concentration studies and
based primarily on reproductive endpoints.
    EPA determined that combustion wastewater discharges into lakes
pose the greatest risk to piscivorous wildlife, with approximately 78
percent of lakes compared to 39 percent of rivers exceeding a NEHC
benchmark for minks or eagles under baseline pollutant loadings.
Mercury and selenium, and to a lesser extent cadmium and zinc, were the
primary pollutants with greatest number of receiving waters with
wildlife NEHC benchmark exceedances. EPA estimates that the preferred
options would reduce the number of immediate receiving waters exceeding
the mercury NEHC for minks and eagles by up to 24 percent under Option
3a, up to 26 percent under Option 3b, up to 33 percent under Option 3,
and up to 52 percent under Option 4a. For selenium, EPA estimates that
the number of immediate receiving waters exceeding the selenium NEHC
would be reduced by up to 29 percent under Option 3a, up to 31 percent
under Option 3b, up to 42 percent under Option 3, and up to 56 percent
under Option 4a. This indicates that the preferred options would reduce
the bioaccumulative impact of the evaluated wastestreams in the broader
ecosystem. EPA estimates that up to 4,135 river miles (Option 3a), up
to 4,360 river miles (Option 3b), up to 5,300 river miles (Option 3),
and up to 8,206 river miles (Option 4a) downstream from steam electric
discharges would no longer exceed a NEHC benchmark for minks or eagles
under the post-compliance pollutant loadings.
    In addition, EPA estimates that the upgrades to water quality
(i.e., reductions in aquatic life NRWQC exceedances) discussed above
would improve aquatic and wildlife habitats in the immediate and
downstream receiving waters from steam electric discharges. EPA
determined that these water quality and habitat improvements would
enhance efforts to protect threatened and endangered species. EPA
identified eight species with a high vulnerability to changes in water
quality whose recovery would be expected to be enhanced by the post-
compliance pollutant loading reductions associated with the preferred
options.

C. Reduced Human Health Cancer Risk

    EPA estimates that reductions in arsenic loadings from the
preferred options would result in a reduction in potential cancer risks
to humans that consume fish exposed to discharges of the evaluated
wastestreams. The human health model calculates the potential cancer
risk for select age groups and consumption categories (i.e., child and
adult recreational fishers and child and adult subsistence fishers)
based on assumptions of arsenic bioaccumulation in fish exposed to
discharges of the evaluated wastestreams. Under baseline pollutant
loadings, EPA determined that up to 9 percent of immediate receiving
waters contain fish contaminated with inorganic arsenic that would
present cancer risks above the 1-in-a-million threshold for one or more
of the cohorts evaluated. EPA determined that, depending on the cohort,
immediate receiving waters with cancer risks above the 1-in-a-million
threshold would be reduced by up to 40 percent (Option 3a), up to 60
percent (Option 3b and Option 3), and up to 80 percent (Option 4a)
under post-compliance loadings. In addition, EPA estimates that up to
266 river miles, depending on the cohort, downstream from the steam
electric discharges contain fish contaminated with inorganic arsenic
that would present cancer risks above the 1-in-a-million threshold.
Under the post-compliance pollutant loadings associated with the
preferred options, EPA estimates that up to 111 river miles (Option
3a), up to 116 river miles (Option 3b), up to 133 river miles (Option
3), and up to 169 river miles (Option 4a) downstream from steam
electric discharges would no longer contain fish contaminated with
inorganic arsenic that would present cancer risks above the 1-in-a-
million threshold for adult subsistence fishers.

D. Reduced Threat of Non-Cancer Human Health Effects

    Exposure to metals poses risk of systemic and other effects to
humans, including effects on the circulatory, respiratory, or digestive
systems and neurological and developmental effects. The preferred
options are estimated to reduce the number of receiving waters with
potential to cause non-cancer health effects in humans who consume fish
exposed to discharges of the evaluated wastestreams. The human health
model calculates the number of immediate receiving waters with the
potential to cause non-cancer health effects in select age groups and
consumption categories (i.e., child and adult recreational fishers and
child and adult subsistence fishers) based on assumptions of metal
bioaccumulation in fish exposed to discharges of the evaluated
wastestreams. Depending on the cohort, EPA calculates that exceedances
of non-cancer reference doses from the consumption of fish would
decrease in up to 19 percent of surface waters (Option 3a), up to 21
percent of surface waters (Option 3b), up to 26 percent of surface
waters (Option 3), and up to 53 percent of surface waters (Option 4a)
immediately receiving discharges of the evaluated wastestreams. Non-
cancer risks are driven by mercury (as methylmercury), total thallium,
and total selenium, and to a lesser degree, total cadmium pollutant
loadings. Under baseline pollutant loadings, the average daily dose
from the consumption of fish in up to 65 percent of immediate receiving
waters exceeds the non-cancer reference dose for mercury depending on
the cohort. Under post-compliance loadings, exceedances of the non-
cancer mercury reference dose would decrease in up to 21 percent
(Option 3a), up to 22 percent (Option 3b), up to 29 percent (Option 3),
and up to 49 percent (Option 4a) of immediate receiving waters,
depending on the cohort. In addition, exceedances of total thallium and
total selenium non-cancer reference doses would decrease in up to 14
and 50 percent of immediate receiving waters (Option 3a and Option 3b),
up to 18 and 69 percent of immediate receiving waters (Option 3), and
up to 43 and 77 percent of immediate receiving waters (Option 4a),
respectively. EPA also estimates that, under the post-compliance
pollutant loadings, exceedances of non-cancer reference doses from the
consumption of fish would decrease in up to 4,084 river miles
downstream (Option 3a), up to 4,316 river miles downstream (Option 3b),
up to 5,400 river miles downstream

(Option 3), and up to 8,087 river miles downstream (Option 4a) for one
or more of the cohorts.
    In addition to the assessment of non-cancer reference dose
exceedances described above, EPA also evaluated the adverse health
effects to children who consume fish contaminated with lead from
combustion wastewater. EPA estimated the reduction in lead exposure to
pre-school children via consumption of contaminated fish tissue and
determined that the preferred options would reduce the associated
intelligence quotient (IQ) loss among children who live in recreational
angler and subsistence fisher households. The preferred options would
also be expected to reduce the incidence of other health effects
associated with lead exposure among children, including slowed or
decayed growth, delinquent and anti-social behavior, metabolic effects,
impaired hemesynthesis, anemia, impaired hearing, and cancer. The
preferred options would also reduce the IQ loss among children exposed
in-utero to mercury from maternal fish consumption in populations
exposed to immediate and downstream receiving waters from steam
electric discharges. Section XIV.B.1.a provides additional details on
the benefits analysis of these reduced IQ losses.
    EPA expects that the preferred options would result in additional
non-cancer human health effects beyond those described above, including
reduced health hazards due to exposure to contaminants in waters that
are used for recreational purposes (e.g., swimming).

E. Reduced Nutrient Impacts

    The primary concern with nutrients in steam electric discharges is
the potential for adverse nutrient impacts to occur in water-bodies
that receive discharges from multiple plants. Nine percent of surface
waters receiving steam electric wastewater discharges are impaired for
nutrients. While the current concentration of nitrogen present in steam
electric discharges from any individual power plant is relatively low,
the total nitrogen loadings from a single plant can be significant due
to large wastewater discharge flow rates. Total nutrient loadings from
multiple power plants is especially a concern on water bodies that are
nutrient impaired or in watersheds that contribute to downstream
nutrient problems.
    Excessive nutrient loadings to receiving waters can significantly
affect the ecological stability of freshwater and saltwater aquatic
systems. Nutrient over-enrichment of surface waters can stimulate
excessive plant growth that can obstruct sunlight penetration and
increase turbidity, which can result in the death of bottom-dwelling
aquatic plants. Higher nutrient loadings from steam electric discharges
could result in the eutrophication of waters and the formation of
hazardous algal blooms. An additional concern with nutrients in steam
electric discharges is the potential for the total nitrogen loadings
from plants to increase in the future as air pollution limits become
stricter and the use of air pollution controls increases.
    EPA projects that the preferred options would reduce total nutrient
loadings by 39 percent (Option 3a), by 41 percent (Option 3b), by 53
percent (Option 3), and by 66 percent (Option 4a) and improve overall
water quality. EPA used the SPARROW (SPAtially Referenced Regressions
On Watershed attributes) model to calculate immediate receiving water
concentrations under baseline conditions and under five of the
regulatory options discussed in Section VIII of this preamble (Options
1, 2, 3, 4, and 5) to analyze benefits related to improvements in water
quality. EPA used these concentrations to develop sub-indices for a
water quality index (WQI), a value that translates water quality
measurements, gathered for multiple parameters that represent various
aspects of water quality, into a single numerical indicator. Section
XIV provides additional details on the water quality benefits analysis
of nutrient reductions.

F. Unquantified Environmental and Human Health Improvements

    The above environmental assessment focused on the quantification of
environmental improvements within rivers and lakes from post-compliance
pollutant loading reductions for toxic metals and excessive nutrients.
While extensive, the environmental improvements quantified do not
encompass the full range of improvements anticipated to result from the
preferred options simply because some of the improvements have no
method for measuring a quantifiable or monetizable improvement. EPA
expects post-compliance pollutant loading reductions from the preferred
options to result in much greater improvements to wildlife, human
health and environmental health by reducing the:
     Loadings of bioaccumulative metals to the broader
ecosystem resulting in the reduction of long-term exposures and
sublethal ecological effects;
     Sublethal chronic effects of toxic metals on aquatic life
not captured by the NRWQC;
     Impacts to aquatic and aquatic-dependant wildlife
population diversity and community structures;
     Exposure of wildlife to pollutants through direct contact
with combustion residuals impoundments and constructed wetlands built
as treatment systems at steam electric power plants;
     Adverse health effects in adults resulting from exposure
to lead from consumption of contaminated fish tissue; and
     Potential for the formation of hazardous algal blooms.
    Data limitations prevented appropriately modeling the scale and
complexity of the ecosystem processes potentially impacted by
combustion wastewater, resulting in the inability to quantify the
improvements listed. However, documented case studies in the literature
reinforce that these impacts are common in the environments surrounding
steam electric power plants and fully support the conclusion that
reducing pollutant loadings will improve overall environmental, human
health and wildlife health.
    Although the Environmental Assessment quantifies impacts to
wildlife that consume fish contaminated with metals from combustion
wastewater, it does not capture the full range of exposure pathways
through which bioaccumulative metals can enter the surrounding food
web. Wildlife can encounter toxic bioaccumulative metals from
discharges of the evaluated wastestreams from a variety of exposure
pathways such as direct exposure, drinking water, consumption of
contaminated vegetation, and consumption of contaminated prey other
than fish. Therefore, the quantified improvements underestimate the
complete loadings of bioaccumulative metals that can impact wildlife in
the ecosystem. EPA anticipates that the post-compliance pollutant
loading reductions associated with the preferred options would lower
the total amount of toxic bioaccumulative metals entering the food web
near steam electric power plants.
    EPA also expects the estimated reduction in pollutant loadings to
lower the occurrence of sublethal effects associated with many of the
pollutants in combustion wastewater that may not be captured by
comparisons with NRWQC for aquatic life. Chronic effects such as
changes in metabolic rates, decreased growth rates, changes in
morphology (e.g., fin erosion, oral deformities), and behavior (e.g.,
swimming ability, ability to catch prey, ability to escape from
predators) that

can negatively affect long-term survival, are well documented in the
literature in environments near steam electric power plants. Reductions
in organism survival rates from the chronic effects such as
abnormalities can alter interspecies relationships (e.g., declines in
the abundance or quality of prey) and prolong ecosystem recovery.
However, these effects were not quantified in the environmental
assessment and improvements to wildlife health and survival from the
preferred options are, therefore, underestimated. EPA was unable to
quantify changes to aquatic and wildlife population diversity and
community dynamics; however, population effects (i.e., decline in
number and type of organisms present) attributed to exposure to
combustion wastewater are well documented in the literature. Changes in
aquatic populations can alter the structure of aquatic communities and
cause cascading effects within the food web that result in long-term
impacts to ecosystem dynamics. EPA expects that post-compliance
pollutant loading reductions associated with the preferred options
would lower the stressors that can cause alterations in population and
community dynamics and improve the overall function of ecosystems
surrounding steam electric power plants, as well as help resolve issues
faced in other national ecosystem protection programs such as the Great
Lakes program, the National Estuaries program and the 303(d) impaired
waters program.
    EPA anticipates that the expected post-compliance pollutant loading
reductions associated with the preferred options would also decrease
the environmental impacts to wildlife exposed to pollutants through
direct contact with combustion residuals impoundments and constructed
wetlands at steam electric power plants. Documented case studies
demonstrate that wildlife living in close proximity to combustion
residuals impoundments exhibit elevated levels of arsenic, cadmium,
chromium, lead, mercury, selenium, strontium, and vanadium. Multiple
studies have linked attractive nuisance areas (contaminated areas at a
steam electric power plant, such as combustion wastewater surface
impoundments, that are attractive to wildlife (place for nesting)) to
diminished reproductive success. EPA expects that the post-compliance
pollutant loadings would decrease the exposure of wildlife populations
to toxic pollutants and reduce the risks for impacts on reproductive
success.

G. Other Secondary Improvements

    EPA anticipates that other secondary, or ancillary, improvements
would occur to other resources that are associated directly or
indirectly as a result of the preferred options. These would include
aesthetic and recreational improvements, reduced economic impacts such
as clean up and treatment costs in response to contamination or
impoundment failures, reduced injury associated with pond failures,
reduced water usage and reduced air emissions. Section XIV provides
additional details on the benefits of these other secondary
improvements.

XIV. Benefit Analysis

    This section summarizes EPA's estimates of the national
environmental benefits expected to result from reduction in pollutant
discharges described in Section IX and the resultant environmental
effects summarized in Section XIII. The Benefit and Cost Analysis for
the Proposed Effluent Limitations Guidelines and Standards for the
Steam Electric Power Generating Point Source Category (BCA) report
provides additional details on benefits methodologies and analysis,
including uncertainties and limitations.

A. Categories of Benefits Analyzed

    Table XIV-1 summarizes benefit categories associated with this
proposed rule and notes which categories EPA was able to quantify and
monetize. Analyzed benefits fall within six broad categories: human
health benefits, ecological conditions and recreational use benefits
from surface water quality improvements, market and productivity
benefits, air-related benefits, groundwater quality benefits, and water
withdrawal benefits. Within these broad categories, EPA was able to
assess benefits with varying degrees of completeness and rigor. Where
possible, EPA quantified the expected effects and estimated monetary
values. However, data limitations and gaps in the understanding of how
society values certain water quality changes prevent EPA from
quantifying and/or monetizing some benefit categories.

                          Table XIV-1--Benefit Categories Associated With Proposed ELGs
----------------------------------------------------------------------------------------------------------------
                                                                                Neither
                    Benefit category                       Quantified and     Quantified but     quantified nor
                                                             monetized        not monetized        monetized
----------------------------------------------------------------------------------------------------------------
                        1. Human Health Benefits from Surface Water Quality Improvements
----------------------------------------------------------------------------------------------------------------
Reduced incidence of cancer from arsenic exposure via                   X   .................  .................
 fish consumption......................................
Reduced non-cancer adverse health effects (e.g.,         .................                 X   .................
 reproductive, immunological, neurological,
 circulatory, or respiratory toxicity) due to exposure
 to arsenic from fish consumption......................
Reduced IQ loss in children from lead exposure via fish                 X   .................  .................
 consumption...........................................
Reduced need for specialized education for children                     X   .................  .................
 from lead exposure via fish consumption...............
Reduced adverse health effects in adults from exposure   .................  .................                 X
 to lead from fish consumption.........................
Reduced in-utero mercury exposure via maternal fish                     X   .................  .................
 consumption...........................................
Reduced health hazards from exposure to pollutants in    .................  .................                 X
 waters used recreationally (e.g., swimming)...........
----------------------------------------------------------------------------------------------------------------
         2. Ecological Conditions and Recreational Use Benefits from Surface Water Quality Improvements
----------------------------------------------------------------------------------------------------------------
Benefits from improvements in surface water quality,                    X   .................  .................
 including: improved aquatic and wildlife habitat;
 enhanced water-based recreation, including fishing,
 swimming, boating, and near-water activities;
 increased aesthetic benefits, such as enhancement of
 adjoining site amenities (e.g., residing, working,
 traveling, and owning property near the water\a\; and
 non-use value (i.e., existence, option, and bequest
 value from improved ecosystem health)\a\..............

Benefits from improved protection of threatened and                     X   .................  .................
 endangered species....................................
Reduced sediment contamination.........................  .................  .................                 X
----------------------------------------------------------------------------------------------------------------
                                         3. Groundwater Quality Benefits
----------------------------------------------------------------------------------------------------------------
Reduced groundwater contamination......................                 X   .................  .................
----------------------------------------------------------------------------------------------------------------
                                       4. Market and Productivity Benefits
----------------------------------------------------------------------------------------------------------------
Reduced impoundment failures (monetized benefits                        X   .................  .................
 include avoided cleanup costs and environmental
 damages; non-quantified benefits include avoided
 injury)...............................................
Reduced water treatment costs for municipal drinking     .................  .................                 X
 water, irrigation water, and industrial process.......
Improved commercial fisheries yields...................  .................  .................                 X
Increased tourism and participation in water-based       .................  .................                 X
 recreation............................................
Increased property values from water quality             .................  .................                 X
 improvements..........................................
----------------------------------------------------------------------------------------------------------------
                                             5. Air-Related Benefits
----------------------------------------------------------------------------------------------------------------
Reduced mortality from exposure to NOX, SO2 and                         X   .................  .................
 particulate matter (PM2.5)............................
Avoided climate change impacts from CO2 emissions......                 X   .................  .................
----------------------------------------------------------------------------------------------------------------
                                   6. Benefits from Reduced Water Withdrawals
----------------------------------------------------------------------------------------------------------------
Increased availability of groundwater resources........                 X   .................  .................
----------------------------------------------------------------------------------------------------------------
a. These values are implicit in the total willingness to pay (WTP) for water quality improvements.

    The following section discusses EPA's analysis of the benefits that
the Agency was able to quantify and monetize (identified in the second
column of Table XIV-1). The proposed rule would also result in
additional benefits that the Agency was not able to monetize. See the
Benefits and Cost Analysis Document for information about these non-
monetized benefits.
    EPA estimated benefits for five of the eight regulatory options
discussed in this preamble (Options 1, 2, 3, 4, and 5). EPA did not
estimate the benefits of Options 3a, 3b and 4a. However, EPA used its
understanding of the wastestreams and treatment technologies for these
options, along with projections of pollutant reductions for all eight
options, to estimate total monetized benefits for Options 3a, 3b, and
4a. However, EPA is less confident that this approach would yield
reasonable estimates if applied to the individual categories of
benefits (water quality, air emissions, avoided impoundment failure
cleanup costs, etc) and so has not done so. For these more granular
benefits categories, estimates are provided only for Options 1, 2, 3,
4, and 5. Again, these can serve as upper and lower bounds for the
individual categories of benefits of Options 3a, 3b, and 4a.
Specifically, monetized benefits for Options 3a and 3b are likely to be
between those for Options 2 and 3. Similarly, monetized benefits for
Option 4a are likely to be between those for Options 3 and 4.

B. Quantification and Monetization of Benefits

1. Human Health Benefits From Surface Water Quality Improvements
    Reduced pollutant discharges from steam electric plants generate
human health benefits in a number of ways. Pollutants commonly
discharged in Steam Electric plant wastewater streams include
conventional and toxic pollutants such as arsenic, cadmium, chromium,
copper, lead, mercury, selenium, and zinc (steam electric pollutants).
Exposure to these pollutants via consumption of fish from affected
waterways can cause a wide variety of adverse health effects, including
cancer, kidney damage, nervous system damage, fatigue, irritability,
liver damage, circulatory damage, vomiting, diarrhea, brain damage, IQ
loss, and many others. Because the proposed ELGs would reduce
discharges of steam electric pollutants into receiving waterways and
downstream areas, they are likely to result in decreased incidences of
associated illnesses.
    Due to data limitations and uncertainties, EPA is able to monetize
only a small subset of the health benefits associated with decreased
pollutant discharges from steam electric plants. EPA analyzed the
following measures of human health-related benefits: reduced cancer
risk due to arsenic exposure from fish consumption, reduced lead-
related IQ loss in children from fish consumption, and reduced mercury-
related IQ loss in children exposed in-utero due to maternal fish
consumption. EPA monetized these human health benefits by estimating
the change in the expected number of individuals experiencing adverse
human health effects in the populations exposed to steam electric
discharges under various regulatory options and valuing these changes
using a variety of nonmarket approaches (e.g., cost of illness).
a. Monetized Human Health Benefits
    EPA quantified and monetized the following four categories of human
health benefits:
     Benefits from Reduced Incidence of Cancer from Arsenic
Exposure via Fish Consumption. EPA assessed changes in the incidence of
cancer cases from consumption of arsenic in the tissue of fish caught
in waters affected by steam electric plant discharges. For the baseline
and each regulatory option, EPA estimated cancer risk from the
consumption of arsenic-contaminated fish for recreational and
subsistence anglers and their families. EPA used data on the
populations living within 100 miles of affected waterbodies, state-
specific average fishing rates, presence of fish consumption
advisories, the availability of substitute fishing

locations, and average household size to estimate the exposed
population for each steam electric facility. To identify the change in
number of cancer cases caused by arsenic in this population, EPA used a
cancer slope factor (CSF) from EPA's Integrated Risk Information System
(IRIS) of 1.5 per mg/kg-day and different fish consumption rates for
recreational and subsistence anglers and age cohorts. The Agency valued
changes in incidence of cancer cases using a value of a statistical
life (VSL) of $8.0 million (2010$), with projections adjusted to
account for income growth. This estimate does not include estimates of
willingness to pay (WTP) to avoid illness prior to death.
     Benefits from Reduced IQ Loss in Children from Lead
Exposure via Fish Consumption. Children's rapid rate of development
makes them more susceptible to neurobehavioral effects from lead
exposure. The neurobehavioral effects on children from lead exposure
include hyperactivity, behavioral and attention difficulties, delayed
mental development, and motor and perceptual skill deficits. EPA
assessed benefits of reduced lead exposure from consumption of
contaminated fish tissue and the associated IQ loss among children aged
0 to 7. EPA estimated blood-lead levels using EPA's Integrated
Exposure, Uptake, and Biokinetic (IEUBK) Model based on daily lead
ingestion rates among children from birth to the seventh birthday.
Based on blood lead concentrations for children in recreational and
subsistence anglers' families, EPA assessed neurobehavioral effects on
children using an established dose response relationship between blood
lead concentrations and IQ loss. Avoided neurological and cognitive
damages are expressed as an increase in overall IQ points in the
exposed population. EPA monetized the estimated changes in IQ scores
based on the impact of additional IQ points on individuals' future
earnings. EPA assumed that each IQ point is worth between $1,156
(following Schwarz (1994) and discounting future earnings at 7 percent)
and $13,651 (following Salkever (1995) and discounting future earnings
at 3 percent).
     Benefits from Reduced Need for Specialized Education for
Children from Lead Exposure via Fish Consumption. EPA also quantified
the reduced incidences of especially high blood-lead levels (above 20
mg/dL) and low IQ scores (<70, or two standard deviations below the
mean), and monetized the avoided costs associated with compensatory
education that an individual would otherwise need. For this analysis,
EPA used the IEUBK model to estimate how many children in the exposed
population would have blood lead concentrations above 20 mg/dL, and
assumed that 20 percent of those children would have IQ scores below
70. Based on education cost data from the United States Department of
Education, EPA assumed that the incremental cost of special education
for these individuals and ages 7 through 18 would be approximately
$157,000 per child at 3 percent discount rate, and $125,500 per child
at 7 percent discount rate.
     Benefits of Reduced In-utero Mercury Exposure via Maternal
Fish Consumption. Mercury is a highly toxic pollutant that presents
serious health risks to adults and children, even in very small doses.
Health effects can include damage to the brain, kidneys, heart, and
especially nervous system. These impacts are particularly harmful for
children, who can experience profound and permanent developmental and
neurological delays as a result of exposure in-utero. EPA estimated the
IQ-related benefits associated with reduced in-utero mercury exposure
from maternal fish consumption in exposed populations. EPA used data on
the populations living within 100 miles of affected waterbodies, state-
specific average fishing rates, presence of fish consumption
advisories, the availability of substitute fishing locations, average
household size, the number of women of childbearing age, and state-
specific birth rates to estimate the number of births in the exposed
population. Based on a dose-response function developed by Axelrad et
al. (2007), EPA assigned a 0.18 point IQ loss for each 1 ppm increase
in maternal hair mercury. To translate the daily mercury ingestion rate
by women of childbearing age in the exposed populations to hair mercury
concentrations, EPA used a conversion rate derived by Swartout and Rice
(2000). Including decreased lifetime earnings and avoided education
costs, EPA assumed that the value of an IQ point is between $1,156 and
$13,651 over the life of each individual.
    Table XIV-2 summarizes monetized human health benefits associated
with five of the eight regulatory options considered in this proposed
rule using 3 percent and 7 percent discount rates. As mentioned above,
EPA did not monetize the human health benefits associated with Options
3a, 3b and 4a. EPA expects the benefits of Option 4a to be between
those of Options 3 and 4.

                                                                          Table XIV-2--Annualized Human Health Benefits
                                                                                [million 2010$] c
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
  Human health benefit category              Option 1                        Option 2                        Option 3                        Option 4                        Option 5
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                                                3% Discount Rate
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Benefits from Reduced Incidence   <$0.1.........................  <$0.1.........................  $0.1..........................  $0.2..........................  $0.2
 of Cancer from Arsenic Exposure
 via Fish Consumption.
Benefits from Reduced IQ Loss in  $0.1 ($0.1 to $0.1)...........  $0.1 ($0.1 to $0.1)...........  $2.7 ($2.2 to $3.2)...........  $6.7 ($5.6 to $7.9)...........  $6.7 ($6.5 to $7.9)
 Children from Lead Exposure via
 Fish Consumption a.

Benefits from Reduced Need for    <$0.1 (<$0.1 to <$0.1)........  <$0.1 (<$0.1 to <$0.1)........  <$0.1 (<$0.1 to <$0.1)........  $0.1 ($0.1 to $0.1)...........  $0.1 ($0.1 to $0.1)
 Specialized Education for
 Children from Lead Exposure via
 Fish Consumption.
Benefits of Reduced In-utero      $3.8 ($3.2 to $4.5)...........  $3.9 ($3.2 to $4.6)...........  $5.0 ($4.1 to $5.8)...........  $10.2 ($8.4 to $12.1).........  $10.2 ($8.4 to $12/1)
 Mercury Exposure via Maternal
 Fish Consumption a.
                                 ---------------------------------------------------------------------------------------------------------------------------------------------------------------
    Total Human Health Benefits   $3.9 ($3.21 to $4.59).........  $4.0 ($3.28 to $4.69).........  $7.7 ($6.4 to $9.11)..........  $17. ($14.2 to $20.2).........  $17. ($14.2 to $20.2)
     b.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
                                                        7% Discount Rate
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Benefits from Reduced Incidence   <$0.1.........................  <$0.1.........................  $0.1..........................  $0.1..........................  $0.1
 of Cancer from Arsenic Exposure
 via Fish Consumption.
Benefits from Reduced IQ Loss in  <$0.1 (<$0.1 to <$0.1)........  <$0.1 (<$0.1 to <$0.1)........  $0.2 ($0.2 to $0.3)...........  $0.6 ($0.4 to $0.8)...........  $0.6 ($0.4 to $0.8)
 Children from Lead Exposure via
 Fish Consumption a.
Benefits from Reduced Need for    <$0.1 (<$0.1 to <$0.1)........  <$0.1 (<$0.1 to <$0.1)........  <$0.1 (<$0.1 to <$0.1)........  <$0.1 (<$0.1 to <$0.1)........  <$0.1 (<$0.1 to <$0.1)
 Specialized Education for
 Children from Lead Exposure via
 Fish Consumption.
Benefits of Reduced In-utero      $0.3 ($0.2 to $0.5)...........  $0.4 ($0.2 to $0.5)...........  $0.4 ($0.3 to $0.6)...........  $0.9 ($0.6 to $1.2)...........  $0.9 ($0.6 to $1.2)
 Mercury Exposure via Maternal
 Fish Consumption a.
                                 ---------------------------------------------------------------------------------------------------------------------------------------------------------------
    Total Human Health Benefits   $0.4 ($0.2 to $0.5)...........  $0.4 ($0.2 to $0.5)...........  $0.7 ($0.5 to $1.0)...........  $1.6 ($1.1 to $2.1)...........  $1.6 ($1.1 to $2.1)
     b.
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
a Low end assumes that the loss of one IQ point results in the loss of 1.76% of lifetime earnings (following Schwartz, 1994); high end assumes that the loss of one IQ point results in the loss
  of 2.38% of lifetime earnings (following Salkever, 1995).
b Totals may not add up due to independent rounding.
c EPA did not estimate the benefits of Options 3a, 3b and 4a. EPA expects the benefits of Option 4a to be between those of Options 3 and 4.

b. Reduced Exceedances of Health-Based AWQC
    EPA expects that additional health benefits will arise from reduced
discharges of steam electric pollutants; however, monetary valuation of
these other health benefits is not currently possible due to lack of
data on a dose-response relationship between pollutant ingestion rate
and potential adverse health effects. To provide an additional measure
of the potential health benefits of the proposed ELGs, EPA estimated
the effect of steam electric plant discharges on the occurrence of
pollutant concentrations in affected waterways that exceed human
health-based ambient water quality criteria (AWQCs).\84\ Pollutant
concentrations in excess of these values indicate potential risks to
human health. This analysis and its findings are not additive to the
preceding analyses of change in cancer or lead-related health risks but
are another way of quantitatively characterizing possible benefit
categories.
---------------------------------------------------------------------------

    \84\ Including AWQCs for the protection of human health through
consumption of organisms and water.
---------------------------------------------------------------------------

    EPA estimates that in-stream concentrations of steam electric
pollutants (i.e., arsenic, cadmium, chromium, copper, lead, mercury,
nickel, selenium, thallium, and zinc) exceed human health criteria for
consumption of water and organisms for at least one pollutant in 146
receiving reaches nationwide in the baseline. Depending on the
regulatory option, EPA expects that the proposed rule would eliminate
the occurrence of concentrations in excess of human health criteria for
consumption of water and organisms for 0 to 98 of the contaminated
reaches, and reduce the number of exceedances in 9 to 27 reaches.
Option 3 is estimated to

eliminate exceedances in 27 receiving reaches, out of the 146 receiving
reaches with exceedances in the baseline, while Option 4 is estimated
to reduce exceedances in 98 reaches and eliminate exceedances
altogether in 24 of those reaches. EPA did not quantitatively analyze
the change in exceedances for Options 3a, 3b and 4a. However, EPA
expects the effects of Option 4a to be between those of Options 3 and 4
(i.e., reduce or eliminate exceedances in between 27 and 98 receiving
reaches).
2. Improved Ecological Conditions and Recreational Use Benefits From
Surface Water Quality Improvements
    EPA expects the proposed ELGs to provide ecological benefits by
improving ecosystems (aquatic and terrestrial) affected by the electric
power industry's effluent discharges. Benefits associated with changes
in aquatic life include restoration of sensitive species, recovery of
diseased species, changes in taste-and odor-producing algae, changes in
dissolved oxygen (DO), increased assimilative capacity of affected
waterways, and improved related recreational activities. Activities
such as fishing, swimming, wildlife viewing, camping, waterfowl
hunting, and boating may be enhanced when risks to aquatic life and
perceivable water quality effects associated with pollutants are
reduced. The magnitude of these benefits depends on the regulatory
option.
    EPA was able to monetize several categories of ecological benefits
associated with this proposed rule, including recreational use and
nonuse (i.e., existence, bequest, and altruistic) benefits from
improvements in the health of aquatic environments, and nonuse benefits
from increased populations of threatened and endangered species. As
shown in Table XIV-1, the Agency quantified and monetized two main
benefit subcategories, discussed below: (1) Benefits from improvements
in surface water quality, and (2) benefits from improved protection of
threatened and endangered (T&E) species.
a. Improvements in Surface Water Quality
    EPA expects these proposed ELGs to improve aquatic species habitats
by reducing concentrations of toxic contaminants such as arsenic,
cadmium, chromium, lead, mercury, nickel, selenium, and zinc in water.
The rule is also expected to reduce nitrogen and phosphorus
concentrations. These improvements would be expected to enhance the
quality and value of water-based recreation. For example, some of the
streams that were not usable for recreation under the baseline
discharge conditions may become usable following implementation of the
rule, thereby expanding options for recreational users. Streams that
have been used for recreation under the baseline conditions can become
more attractive for users by making recreational trips even more
enjoyable. Individuals may also take trips more frequently if they
enjoy their recreational activities more. These proposed ELGs are also
expected to generate nonuse benefits from bequest, altruism, and
existence motivations. Individuals may value the knowledge that water
quality is being maintained, ecosystems are being protected, and
species populations are healthy, independently of their use.
    To calculate baseline and post-compliance water quality, EPA
utilized a water quality index (WQI) that translates water quality
measurements, gathered for multiple parameters that are indicative of
various aspects of water quality, into a single numerical indicator
that reflects achievement of quality consistent with certain uses. The
WQI provides the link between specific pollutant levels, as reflected
in individual parameters, and the presence of aquatic species and
suitability for particular recreational uses. Traditionally, WQIs are
based on conventional pollutants (e.g., TSS, BOD, and fecal coliform)
and nutrients (nitrogen and phosphorus). To account for water quality
improvements resulting from reductions in toxic pollutants, EPA
expanded the set of WQI parameters to include metals. The metals sub-
index follows an approach developed by the Canadian Council of
Ministers of the Environment (CCME) and uses the number of AWQC
exceedances for a given waterbody in the baseline and/or under a given
regulatory option.\85\ EPA assigned all parameters in the index an
equal weight of 1/7th following other studies that use equal weights
for all index parameters (Cude 2001, CCME 2001, and Carruthers and
Wazniak 2003).
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    \85\ There may be between 0 and 8 exceedances per waterbody
(freshwater chronic AWQC values are available for arsenic, cadmium,
chromium, lead, mercury, nickel, selenium, and zinc).
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    EPA calculated baseline and post compliance WQI values for reaches
affected by steam electric plant discharges. Baseline and post
compliance water quality data were taken from several sources including
USGS's SPARROW model, EPA's Risk-Screening Environmental Indicators
(RSEI) model, EPA's STORET data warehouse, and estimated in-stream
concentrations of steam electric pollutants. These sources provide
water quality for stream networks defined according to the medium-
resolution NHD or RF1. EPA conducted the benefits analysis at the level
of RF1 reaches and mapped NHD data to the appropriate RF1, as needed,
depending on the data source. EPA estimates that 3,945 reach miles
would improve under Option 1 for existing sources, 12,683 miles under
Option 2, 15,682 miles under Option 3, 22,447 reach miles under Option
4, and 22,441 reach miles under Option 5. EPA did not estimate the
number of reach miles that would improve under Option 4a but expects
improvements to be between those of Options 3 and 4 (i.e., between
15,682 and 22,447 reach miles).
    EPA estimated monetized benefit values using a meta-regression of
surface water valuation studies originally developed for the Effluent
Guidelines and Standards for the Construction and Development Point
Source Category (U.S. EPA, 2009). EPA used two benefit functions for
each reach; one for households within a 100-mile radius of the reach
that may have user values and one for nonuser households, located in
the same state as the reach, but outside the 100-mile radius. Each
benefit function was estimated for the years between 2014 and 2040,
although benefits start accruing in 2017 when certain plants would be
expected to start installing control technologies under this proposal
(i.e., no benefits are assumed for 2014-2016). EPA estimated total
benefits for each group--users and nonusers--as follows:
     The Agency first estimated annual household WTP values for
a given reach and year using the meta-analysis regression. WTP values
are a function of (1) reach-specific baseline and change in water
quality values in a given year and (2) median household income values
estimated for a given state or buffer zone in that year. For this
analysis, two benefit functions were used for each reach in a given
year; one for households that may have user values (households located
within 100 miles of the reach) and one for nonuser households
(households located with the same state as the reach, but outside the
100-mile buffer).
     To estimate total WTP values, the Agency multiplied annual
household WTP values by the percent of total reach miles within the
state or buffer and the total number of households within the state or
buffer for a given year.
     EPA then discounted total WTP values to 2014, the expected

promulgation year of the rule, and annualized them using a 3 and 7
percent discount rate.
    A challenge for meta-analysis is developing a framework that both
controls for differences in studies and can be used for meaningfully
predicting benefits associated with regulatory options. In earlier
benefits estimation for effluent guidelines, EPA often relied on the
Carson and Mitchell (1993) water quality values. These values come from
a survey that was one of the first major stated preference efforts,
fielded in the early 1980s. The study reported values for all of the
nation's waters, using the same WQI that is used in the meta-analysis.
When EPA used the Carson and Mitchell values, the Agency was able to
tailor its benefits estimates to its regulations in two important
dimensions: the level of water quality improvement, and the percent of
the nation's waters being improved. EPA is basing this benefits
analysis on the meta-analysis because stated preference methodology and
practices have advanced considerably since the Carson and Mitchell
study (although methodological issues continue to be debated in the
stated preference literature), more studies have been conducted, and
changes in individuals' preferences and income may well result in
changing water quality values.
    A trade-off, however, in using the meta-analysis is the difficulty
in representing the percent of the nation's waters that are being
improved, in addition to combining the results of studies encompassing
a variety of water quality improvements, geographic scales, and
resource characteristics that has led to both expected results and
results that are counterintuitive. To provide perspective on these
different approaches to measure water quality improvement benefits, EPA
is also reporting the water quality values obtained by applying the
Carson and Mitchell values. In 2011 dollars, using a 3 percent discount
rate, these values are: for Option 1, $0.5 million; for Option 2, $2.9
million; for Option 3, $4.5 million; for Option 4, $12.9 million; and
for Option 5, $12.7 million. EPA requests comment on its reliance on
the meta-analysis values rather than the Carson and Mitchell values (or
some other values) as the basis for estimating water quality benefits
of the proposed rule. Commenters should address methodological
strengths and weaknesses of any suggested approach, and explain the
basis for their recommendation.
b. Benefits to Threatened and Endangered (T&E) Species
    To assess the potential for impacts on threatened and endangered
(T&E) species (both aquatic and terrestrial), EPA constructed a
database of waterbodies currently exceeding wildlife-based AWQC but
expected to have no wildlife AWQC exceedances as a result of the
proposed ELGs. EPA then assessed the overlap between this geographic
database and the known locations of approximately 530 T&E species. Once
species overlapping waterbodies of interest were identified, EPA
examined their life history traits to categorize species by the
potential for population impacts likely to occur as a result of changes
in water quality. T&E species with high probability of life-history
effects were further screened to identify those species for which water
quality was identified as a factor for listing under the Endangered
Species Act (ESA) or as a limiting factor within species recovery
plans. Because of this analysis, EPA identified seven fish species and
one dragonfly species that may experience changes in population growth
rates as a result of the proposed ELGs. EPA did not identify data
sufficient to explicitly model the effects of changes in water quality
on population growth rates for these species. Therefore, to estimate
total population increases resulting from the proposed ELGs, EPA
assumed minimal increases in population size of 0.5, 1, or 1.5 percent.
To estimate monetary benefits to T&E species, EPA weighted these
population growth estimates by the percent of reaches used by T&E
species that are expected to meet wildlife-based AWQC because of the
proposed ELGs.
    The T&E species expected to benefit from the rule include two
species of sturgeon and five species of small minnows. All of these
species have nonuse values including existence, bequest, altruistic,
and ecological service values apart from human uses or motives.
    To estimate the potential economic values of increased T&E species
populations affected by the proposed ELGs, EPA used a benefit function
transfer approach based on a meta-analysis of 31 stated preference
studies eliciting WTP for these changes (Richardson and Loomis 2009).
This meta-analysis is based on studies conducted in the United States
that valued threatened, rare, or endangered fish, bird, reptile, or
mammal species. Because the underlying meta-data does not include
insect valuation studies, EPA was unable to monetize any benefits for
potential population increases of Hine's Emerald Dragonfly due to the
proposed rule. For each state containing T&E species estimated to show