#  Chapter 5: Cost Estimates

## Synopsis

This chapter summarizes the data sources and methodology used to
estimate the costs of attaining the alternative more stringent levels
for the ozone primary standard analyzed in this RIA (bounds of the
proposed range, 0.075 and 0.070 ppm, and the more stringent alternative
of 0.065 ppm.[^1]). First, the chapter presents cost estimates for the
hypothetical control strategy outlined in Chapter 3 (which uses
currently available known and supplemental controls). Second, the
chapter presents an analysis of the economic impacts of the hypothetical
national control strategy using currently available controls. Finally,
the chapter presents a range of estimates for the costs of the
additional tons of emissions that need to be extrapolated to move from
predicted ozone concentrations following the known control strategy to
attainment of the alternate standards analyzed (methodology and numbers
discussed in Chapter 4).

As noted in Chapter 3, EPA first modeled a hypothetical control strategy
aimed at attaining a tighter standard of 0.070 ppm in 2020. These
controls were insufficient to bring all areas into attainment with 0.070
ppm, and EPA then developed methodology to estimate additional tons of
emissions needed to attain the bounds of the proposed range, 0.075 and
0.070 ppm, and the tighter alternative of 0.065 ppm. This chapter
presents the costs associated with each portion of the control analysis,
clearly identifying the relative costs of modeled versus extrapolated
emissions reductions as well as providing an estimate of the total cost
of reaching attainment nationwide. Section 5.1 summarizes the
methodology and the engineering costs associated with applying known and
supplemental controls to partially attain a 0.070 ppm alternative
standard, incremental to reaching the current baseline (effectively
0.084ppm) in 2020. Section 5.2 describes the full economic impact that
could be expected to result from the application of these known and
supplemental controls. This economic impact analysis (EIA) is the study
of the way in which the direct benefits and costs of a regulation affect
the local, regional, or national economy. It attempts to measure the
consequences that the regulation will have on considerations such as
local or regional employment patterns, wage levels, business activity,
tourism, housing, and even migration patterns.

Section 5.3 describes the methodology used to estimate the cost of
extrapolated tons needed to reach attainment of the bounds of the
proposed alternative standard (0.070 and 0.075 ppm, as well as the more
stringent alternative of 0.065ppm) and provides estimates of how much
additional cost will be associated with moving from the modeled partial
attainment scenario to the nationwide attainment scenario (see Chapter 4
for discussion of extrapolated tons needed to attain 0.075, 0.070, and
0.065ppm. In general, EPA increased the tons required for each area
using the same impact/ton estimate ( 5 ppb = 50,000 tons) and
extrapolated cost approaches in order to estimate additional costs for
reaching a standard level of 0.065 ppm as well as estimate cost savings
for the 0.075 ppm standard level (compared to the 0.070 ppm case).

Section 5.4 then combines the results from Sections 5.1, 5.2, and 5.3 to
describe the total estimated cost of reaching attainment nationwide,
including both the full economic costs of modeled controls for reaching
partial attainment (including engineering costs plus social costs),and
the additional costs of tons of extrapolated emissions reductions needed
to reach attainment.

The costs described in this chapter generally include the costs of
purchasing, installing, and operating the referenced technologies. For a
variety of reasons, actual control costs may vary from the estimates EPA
presents here. As discussed throughout this report, the technologies and
control strategies selected for analysis are illustrative of one way in
which nonattainment areas could meet a revised standard. There are
numerous ways to construct and evaluate potential control programs that
would bring areas into attainment with alternative standards, and EPA
anticipates that state and local governments will consider programs that
are best suited for local conditions. Furthermore, based on past
experience EPA believes that it is reasonable to anticipate that the
marginal cost of control will decline over time due to technological
improvements and more widespread adoption of previously niche control
technologies. Also, EPA recognizes the extrapolated portion of the cost
estimates reflects substantial uncertainty about which sectors, and
which technologies, might become available for cost-effective
application in the future.

It is also important to recognize that the cost estimates are limited in
their scope. Because we are not certain of the specific actions that
states will take to design State Implementation Plans to meet the
revised standards, we do not present estimated costs that government
agencies may incur for managing the requirement and implementation of
these control strategies or for offering incentives that may be
necessary to encourage or motivate the implementation of the
technologies, especially for technologies that are not necessarily
market driven. This analysis does not assume specific control measures
that would be required in order to implement these technologies on a
regional or local level.

## 

## 5.1 Modeled Controls 

### 

*5.1.1 Sector methodology*

### 5.1.1.1 Non-EGU Point and Area Sources: AirControlNET

After designing a national hypothetical control strategy to meet an
alternative standard of 0.070 ppm using the methodology discussed in
Chapter 3 (see sub-section 3.2.1), EPA used AirControlNET to estimate
engineering control costs. AirControlNET calculates costs using three
different methods: (1) by multiplying an average annualized cost-per-ton
estimate against the total tons of a pollutant reduced to derive a total
cost estimate; (2) by calculating cost by using an equation that
incorporates information regarding key plant information; or (3) by
using both cost per ton and cost equations. Most control cost
information within AirControlNET has been developed based on the
cost-per-ton approach. This is because estimating cost using an equation
requires more data, and parameters used in other non-cost per ton
methods may not be readily available or broadly representative across
sources within the emissions inventory. The costing equations used in
AirControlNET require either plant capacity or stack flow to determine
annual, capital and/or operating and maintenance (O&M) costs. Capital
costs are converted to annual costs, in dollars per ton, using the
capital recovery factor.[^2] Applied controls and their respective costs
are provided in Appendix 6.

The control strategy for Non-EGU Point and Area Sources incorporated
cost-per-ton caps. These caps were pollutant specific and applicable
only in the eastern U.S. portion of the analysis. For reductions of NOx
emissions the cap was \$16,000/ton, this was based upon the approximate
benefit per ton of reductions in NOx, as well as an examination of the
marginal cost curve for NOx reductions from these sectors. There were
two controls whose cost per ton was greater than this cap, due to the
large capital component of installing these controls. A similar process
was followed for reductions from VOCs. The marginal cost curve was
analyzed, and there was a clear break in the curve at approximately
\$6,000/ton. At this cap, over sixty percent of the possible reductions
are being controlled at less than thirty percent of the total cost of
the VOC reductions.

Supplemental control measures are those controls that are 1) applied in
these analyses but are not found in AirControlNET, and 2) are in
AirControlNET but whose data have been modified to better approximate
their applicability to source categories in 2020. The controls and
associated data such as control cost estimates not found in
AirControlNET are taken from technical reports prepared to support
preliminary 8-hour ozone State Implementation Plans (SIPs) prepared by
States and from various reports prepared by the staffs of various local
air quality regulatory agencies (e.g. Bay Area Air Quality Management
District). The reports that are the sources of additional controls data
are included within footnotes in the chapter 3 appendix. Modification of
control data, including percent reduction levels and control cost data,
in AirControlNET occurred as a result of a review of the nonEGU point
and area NOx control measures by technical staff in EPA\'s Sector
Policies and Programs Division (SPPD). These changes supplied by the
SPPD review are provided later on in the chapter 3 appendix.
Supplemental controls were needed to achieve the highest possible
emission reduction.

5.1.1.2 EGU Sources: The Integrated Planning Model

Costs for the electric power sector are estimated using the Integrated
Planning Model (IPM). The model determines the least-cost means of
meeting energy and peak demand requirements over a specified period,
while complying with specified constraints, including air pollution
regulations, transmission bottlenecks, fuel market restrictions, and
plant-specific operational constraints. IPM is unique in its ability to
provide an assessment that integrates power, environmental, and fuel
markets. The model accounts for key operating or regulatory constraints
(e.g. emission limits, transmission capabilities, renewable generation
requirements, fuel market constraints) that are placed on the power,
emissions, and fuel markets. IPM is particularly well-suited to consider
complex treatment of emission regulations involving trading and banking
of emission allowances, as well as traditional command-and-control
emission policies.[^3] Applied controls and their respective costs are
provided in Appendix 6.?

#### 5.1.1.3 Onroad and Nonroad Mobile Sources 

Cost information for mobile source controls was taken from studies
conducted by EPA for previous rulemakings and studies conducted for
development of voluntary and local measures that could be used by state
or local programs to assist in improving air quality. Applied controls
and their respective costs are provided in Appendix 6.?

## *5.1.2 Known Controls--- Cost by Sector*

In this section, we provide engineering cost estimates of the control
strategies identified in Chapter 3 that include control technologies on
non-EGU stationary sources, area sources, EGUs, and onroad and nonroad
mobile sources. Engineering costs generally refer to the capital
equipment expense, the site preparation costs for the application, and
annual operating and maintenance costs. The economic impact analysis,
following in section 5.2, also provides a more in-depth evaluation of
how these engineering costs will impact society through a distributional
analysis of changes in price and production levels in affected
industries, and who will bear the burden of the regulatory costs
(consumers or suppliers).

The total annualized cost of control in each sector in the control
scenario is provided in Table 5.1. These numbers reflect the engineering
costs across sectors annualized at an interest rate of 7 percent for
control measures applied to non-EGU point, area, and mobile sources.[^4]
This interest rate is consistent with the guidance provided in the
Office of Management and Budget's (OMB's) (2003) Circular A-4. Also
consistent with that guidance, we provide annualized control costs for
non-EGU point, area, and mobile sources at a 3 percent interest rate to
show the sensitivity of our annualized control costs to the choice of
interest rate.

The total annualized engineering costs associated with the application
of known and supplemental controls to reach a revised 0.70 ppm standard,
incremental to the current standard, are approximately \$3.9 billion.

Table 5.1 Comparison of Known Control Costs Nationwide, by sector, for a
0.070 ppm control scenario (millions of 1999 dollars)[^5]

+------------------------------------------+---------------------------+
| **Source Category**                      | **0.070 ppm control       |
|                                          | strategy**                |
+------------------------------------------+---------------------------+
| A. Electric Generating Units (EGU)       |                           |
| Sector                                   |                           |
+------------------------------------------+---------------------------+
| > *Controls for NOx Cap-and-Trade        | *\$200*                   |
| > Program and Local Measures in          |                           |
| > Projected Nonattainment Areas*         |                           |
+------------------------------------------+---------------------------+
| > **Total**                              | **\$200**                 |
+------------------------------------------+---------------------------+
| B. Onroad                                | \$920                     |
+------------------------------------------+---------------------------+
| C. Nonroad                               | \$160                     |
+------------------------------------------+---------------------------+
| > **Total**                              | **\$1,080**               |
+------------------------------------------+---------------------------+
| D. Non-EGU Sector                        |                           |
+------------------------------------------+---------------------------+
| *Point Sources (Ex: Pulp & Paper, Iron & | *\$2,700*                 |
| Steel,*                                  |                           |
|                                          |                           |
| *Cement, Chemical Manu.)*                |                           |
+------------------------------------------+---------------------------+
| E. Area Sector                           |                           |
+------------------------------------------+---------------------------+
| *Area Sources (Ex: Res. Woodstoves,      | *\$320*                   |
| Agriculture)*                            |                           |
+------------------------------------------+---------------------------+
| > **Total**                              | **\$3,020**               |
+------------------------------------------+---------------------------+
| **Total Annualized Costs**               | **\$4,300**               |
|                                          |                           |
| **(using a 7% interest rate)**           |                           |
+------------------------------------------+---------------------------+
| **Total Annualized Costs**               | **\$3,565**               |
|                                          |                           |
| **(using a 3% interest rate)**[^6]       |                           |
+------------------------------------------+---------------------------+

#### *5.1.3 Limitations and Uncertainties Associated with Engineering Cost Estimates*

EPA bases its estimates of emissions control costs on the best available
information from engineering studies of air pollution controls and has
developed a reliable modeling framework for analyzing the cost,
emissions changes, and other impacts of regulatory controls. The
annualized cost estimates of the private compliance costs are meant to
show the increase in production (engineering) costs to the various
affected sectors in our control strategy analyses. To estimate these
annualized costs, EPA uses conventional and widely-accepted approaches
that are commonplace for estimating engineering costs in annual terms.
However, our cost analysis is subject to uncertainties and limitations.

There are some unquantified costs that are not adequately captured in
this illustrative analysis. These costs include the costs of federal and
State administration of control programs, which we believe are less than
the alternative of States developing approvable SIPs, securing EPA
approval of those SIPs, and Federal/State enforcement. Additionally,
control measure costs referred to as \"no cost\" may require limited
government agency resources for administration and oversight of the
program not included in this analysis; those costs are generally
outweighed by the saving to the industrial, commercial, or private
sector. The Agency also did not consider transactional costs and/or
effects on labor supply in the illustrative analysis.

The direct engineering costs estimated in this RIA do not reflect the
actual impact of these illustrative controls on consumers. Given some
price elasticity of demand for products whose consumption is affected by
the implementation of these illustrative controls, the actual impact to
consumers will be less than that implied by the direct engineering
controls. The greater the price elasticity of demand for a given
affected product, the more rising costs will reduce demand for that
product by a consumer.

From another vantage point, the illustrative analysis does not take into
account the potential for advancements in the capabilities of pollution
control technologies as well as reductions in their costs over time.
This is discussed further later in this chapter.

**5.2 Economic Impact Analysis**

This section presents the economic impact results of the control
strategy developed by EPA for the purpose of providing an approach of
actions that could be taken to meet attainment of 8-Hour 0.070 ppm ozone
alternate standard. Given the possible impacts of this guidance on
manufacturing industries, the transportation sector, electricity
generators, consumers, and U.S. Gross Domestic Product (GDP) as a whole,
we believe it is important to gauge the extent to which other parts of
the economy might also be affected by the implementation of the 0.070
ppm ozone standard. Therefore, an analysis of the economy-wide effects
of implementing the alternate standard is conducted by applying
estimated direct costs to EPA's computable general equilibrium model
(EMPAX-CGE). As the chapter will show, the social costs for this
standard are slightly greater than the engineering costs applied to the
CGE model.

This section contains four considerations that assist in interpreting
the economic impacts and relating these impacts to the attainment costs
presented in Section 5.1.

## The selection criteria for the 0.070 ppm ozone control strategy, and its related compliance costs, is designed to select the least cost controls, from an engineering cost standpoint, that generate the highest ozone reductions, but not necessarily the lowest economic impact. Therefore, although the control strategy is selected to reduce ozone at the lowest engineering cost, it does not represent the lowest impact strategy from a social cost standpoint. Thus, while this economic impact analysis presents results for the control strategy approach detailed in Chapter 3 of the RIA, it should not be viewed as the only economic impact estimate of the ozone 0.70 ppm standard or even as the approach with the lowest social cost. Instead, the results should be viewed as guidance or useful information for states preparing their implementation plans. It is likely that states will design implementation plans that present an alternative control strategy and in some cases design plans that take into account secondary impacts to industries and consumers within their borders. In such a case, the end result would be a set of SIPs that are more economically optimal and may have lower industry impacts than those described below. 

(a) The costs analyzed in this economic impact chapter include only the
    modeled engineering costs detailed in Chapter 3. Not included in
    estimating economic impacts, are the extrapolated cost estimates
    detailed in Chapter 4. Since the extrapolated cost estimates are not
    associated with specific controls on specific sectors it is not
    possible to estimate the economic impacts of this portion of the
    cost estimate. Therefore, the direct costs for the scenario to be
    analyzed are roughly \$3.9 billion (1999 dollars) in 2020 for the
    ozone 0.70 ppm. Since a large portion of the attainment costs are
    not included, social cost estimates will likely underestimate the
    impact these standards will have on the economy.

(b) As noted previously, we are extrapolating the costs of meeting the
    0.075 and 0.065 ppm alternatives. Extrapolating does not allow us to
    directly predict the control strategy used to attain these levels as
    was done for the 0.070 ppm alternative. Thus, it is not possible to
    calculate the economic cost for these options.

(c) In the interest of learning how possible changes in
    manufactured-goods prices might affect businesses and households,
    along with how changes in electricity/energy prices might affect
    industry groups that are large energy users, EPA employed the
    "EMPAX-CGE" computable general equilibrium (CGE) model, which has
    been peer reviewed and used in recent analyses of the Clean Air
    Interstate Rule (CAIR), the Clean Air Visibility Rule (CAVR), and
    the PM NAAQS. As with similar models, EMPAX-CGE focuses on the
    cost-side of spillover effects on the economy. This implies its
    estimated industry-sector impacts from modeled controls may be
    overstated because EMPAX-CGE is not configured to capture the
    beneficial economic consequences of the increased labor availability
    and productivity expected to result from air quality improvements.
    If these labor productivity improvements were included, the small
    production output decreases projected by the model might be
    partially or entirely offset. EPA continues to investigate the
    feasibility of incorporating labor productivity gains and other
    beneficial effects of air quality improvements in CGE models.

*5.2.1 Background*

To complement the analysis of effects on specific manufacturing sectors
as described in the control strategy in chapter 3, the macroeconomic
implications of the ozone 0.070 ppm standard has been estimated using
EPA's EMPAX-CGE model. The focus of this component of the analysis is on
examining the sectoral and regional distribution of economic effects
across the U.S. economy. This section briefly discusses the EMPAX model
and the approach used to incorporate findings from other models in
EMPAX-CGE.

EMPAX was first developed in 2000 to support economic analysis of EPA's
maximum achievable control technology (MACT) rules for combustion
sources (reciprocating internal combustion engines, boilers, and
turbines). The initial framework consisted of a national multimarket
partial-equilibrium model with linkages only between manufacturing
industries and the energy sector. Modified versions of EMPAX were
subsequently used to analyze economic impacts of strategies for
improving air quality in the Southern Appalachian mountain region as
part of efforts associated with the Southern Appalachian Mountain
Initiative (SAMI).

Recent work on EMPAX has extended its scope to cover all aspects of the
U.S. economy at a regional level in either static or dynamic modes.
Although major regulations directly affect a large number of industries,
substantial indirect impacts can also result from changes in production,
input use, income, and household consumption patterns. Consequently,
EMPAX now includes economic linkages among all industrial and energy
sectors as well as households that supply factors of production such as
labor and purchase goods (i.e., a CGE framework). This gives the version
of EMPAX called EMPAX-CGE the ability to trace economic impacts as they
are transmitted throughout the economy and allows it to provide critical
insights to policy makers evaluating the magnitude and distribution of
costs associated with environmental policies. The dynamic version of
EMPAX-CGE employed in this analysis, and its data sources, is described
in past analyses of the CAIR and PM NAAQS, and also in publicly
available documentation on the EPA website (see Ross et al., 2005).

EMPAX-CGE can be used to analyze a wide array of policy issues and is
capable of estimating how a change in a single part (or multiple parts)
of the economy will influence producers and consumers across the United
States. However, some types of policies, including the Ozone National
Ambient Air Quality Standard, are difficult to capture adequately within
a CGE structure because of the boiler- and firm-specific nature of
emission reduction costs. Consequently, an interface has been developed
that allows linkages between EMPAX-CGE and the detailed technology
models discussed in Chapter 3. These linkages give the combined modeling
system the advantages of technology detail and broad macroeconomic
coverage, thereby permitting EMPAX-CGE to investigate economy-wide
policy implications.

As discussed in section 5.1, the models used in developing the control
strategy estimate cost changes by industry and region of the United
States for the sectors of the economy affected by the proposed alternate
ozone standard. In order for EMPAX-CGE to effectively incorporate these
additional costs, they have to be expressed in terms of the productive
inputs used in CGE models (i.e., capital, labor, and material inputs
produced by other industries). Rather than assume the costs represent a
proportional scaling up of all inputs, Nestor and Pasurka (1995) data on
purchases made by industries for environmental-protection reasons are
used to allocate these additional expenditures across inputs within
EMPAX-CGE. Once these expenditures are specified, the incremental costs
from the technology models can be used to adjust the production
technologies in the CGE model. Additional linkages are made between
EMPAX-CGE and IPM to handle specific IPM findings related to resource
costs and fuel consumption in electricity generation.[^7]

## *5.2.2 Results for Ozone Alternate Standard (0.070 ppm)*

This section compares attainment of the ozone 0.070 ppm standard
incremental to the current 8-Hour standard (0.084 ppm, effectively....)
baseline. Impacts are measured assuming a 2020 implementation year and
are the result of engineering costs described in section 5.1 Thus, the
following graphs compare the ozone 0.070 ppm standard to an economic
growth path that incorporates impacts from our baseline (including CAIR,
CAMR, CAVR, PM~2.5~ NAAQS 15/35), and ozone current standard through the
year 2020.

### [Projected Impacts on U.S. Industries of Incremental Costs of Reaching Tighter Standard]{.underline}

Impacts of the ozone 0.070 ppm standard on manufacturing costs can
affect output and prices of all industries in the EMPAX-CGE model. These
effects may increase or decrease output and/or revenue, depending on
their implications for production costs and technologies and shifts in
household demands. In general, the impacts on industries will be
dependent on the control strategy and follow a pattern similar to the
stringency of the ozone standard.

As shown in Figure 5.1, impacts on industrial output quantities are
generally small across all industries for ozone 0.070 ppm. Outside of
the energy-intensive sectors (EIS), estimated changes in output of
manufactured goods are less than two one-hundredths of one percent
(0.02%). Effects on energy producers are somewhat higher and can be
positive or negative, which limits any spillover effects to other
businesses and households.

As described in chapter 3, selected control options for the ozone 0.070
ppm standard involve additional actions by electric utilities, which
tend to slightly increase coal consumption (influencing U.S. coal
production) and reduce natural gas use. Other energy industries also
engage in additional measures, which can affect energy users such as the
EIS sectors. Cement, chemicals and glass production are influenced by
direct control costs on their respective industries and any changes in
energy markets. Note, however, that across energy-intensive industries
as a group, output quantities decline on average by less than a quarter
of a percent (\<0.25%).

Figure 5.2 shows how these changes in output quantities (or units)
compares to changes in gross output revenues, where revenue changes
include the effects of changes in both quantity and output prices (which
reflect changes in production costs). While additional gross revenues
may not imply that net revenues have increased for a given industry,
Figure 5.2 is useful in illustrating the overall changes occurring in
the economy in dollar terms.

Revenues in energy-producing industries follow changes in output
quantity relatively closely as there are only limited changes in energy
prices, which are not sufficient to reverse any quantity/price effects.
There are some minor differences between declines in energy-intensive
production and potential increases in gross revenues. Particularly for
cement, output declines are accompanied with a rise in production costs
that results in gross revenues increasing in the industry, although this
effect across the entire economy is on the order of \$250 million. At
the other end of the spectrum, the sheer size of the services industry
in the U.S. means that, even though there are essential no changes in
output (-0.01%), when expressed in revenue terms there is a \$5 billion
decline in gross revenues. This occurs because the base output of the
services industry against which these percentage declines are measured
is more than \$18 trillion in 2020.

**Fig 5.1 Ozone 0.070 ppm Standard Impacts on U.S. Domestic Output
Quantity, 2020**

![](media/image1.wmf){width="6.583333333333333in" height="4.5125in"}

Source: EMPAX-CGE

**Fig 5.2 Ozone 0.070 ppm Standard Impacts on U.S. Domestic Gross Output
Revenues, 2020**

![](media/image2.wmf){width="6.461805555555555in" height="4.41875in"}

Source: EMPAX-CGE

### [Projected Impacts on Regional Energy-Intensive Industries]{.underline}

Regional effects will tend to show variation that does not appear at the
national level. To examine how such variations might occur in response
to the ozone alternate standard; this analysis presents findings for an
East-West split of the United States.[^8] Since changes in output for
most industries are essentially unaffected, Figures 5.3 and 5.4 focus on
regional results for the energy-intensive industries in EMPAX-CGE.

As with the U.S. average results from Figure 5.4, even though the
energy-intensive sectors show more regional variation, based on
differences in production methods and changes in manufacturing costs,
the majority of the impacts are less than one tenth of one percent
(\<0.10%). However, there are measurable impacts in the output of
specific industries. Under the 0.070 ozone Standard, energy-intensive
output tends to be redistributed slightly from East to West as decreases
in cement and glass manufacturing output in the East are offset by
increases in the West.[^9]

**Fig 5.3 Ozone 0.070 ppm Standard Impacts on Regional Energy-Intensive
Output Quantities, 2020**

## ![](media/image3.wmf){width="6.433333333333334in" height="4.399305555555555in"}

Source: EMPAX-CGE

Expressing the findings in dollar terms helps normalize the changes
across the country by implicitly including a measure of the absolute
size of each industry in each region of the country. Thus, the decrease
in the quantity of cement shown in the East in Figure 5.3 is larger than
a relative increase in the West, leading to an overall decline for the
U.S. Figure 5.4 expresses these changes in dollar, or gross revenue,
terms, which help offset these differences in industry size across
regions (however, the revenue terms also combine quantity and price
effects as discussed above). In gross revenue terms, the changes in
Figure 5.4 show somewhat less variation than the quantity changes in
Figure 5.3. For cement, gross revenues are somewhat higher in both the
East and West, while output quantities have declined slightly in the
East as the result of changes in production costs. The additional
production in the West leads to additional revenues as some production
moves around the nation, although this effect is reduced for cement in
particular as its interregional trade is limited by transportation
costs.

**Fig 5.4 Ozone 0.070 ppm Standard Impacts on Regional Energy-Intensive
Gross Output Revenues, 2020**

![](media/image4.wmf){width="6.338888888888889in"
height="4.334722222222222in"}

Source: EMPAX-CGE

Similar to the energy-intensive sectors, energy production shows more
regional variation than can be seen in the U.S. results in Figures 5.1
and 5.2. However, all impacts are less than one half of one percent
(\<0.50%). Under the 0.070 ozone Standard, coal consumption by electric
utilities tends to increase slightly in 2020, while natural gas use
falls, leading to comparable adjustments in regional production. The
crude oil and petroleum refining industries react to the alternative
standard by minor reductions in output, although refining in the West
rises since it has a small comparative advantage over the East as fewer
refiners need to install additional controls. In gross revenue terms,
the changes in Figure 5.6 show somewhat less variation than the quantity
changes in Figure 5.5. Coal revenues rise with the increase in
production, and natural gas falls. Along with adjustments in the
production technologies used in electricity (based on the IPM findings),
which affect generation costs and output levels, overall demand for
electricity rises as businesses purchase additional electricity to run
the controls installed to meet the ozone alternative standard. This
leads also leads to an increase in electricity output revenues.

**Fig 5.5 Ozone 0.070 ppm Standard Impacts on Regional Energy Output
Quantities, 2020**

## ![](media/image5.wmf){width="5.513194444444444in" height="3.770138888888889in"}

Source: EMPAX-CGE

**Fig 5.6 Ozone 0.070 ppm Standard Impacts on Regional Energy Gross
Output Revenues, 2020**

![](media/image6.wmf){width="5.513194444444444in"
height="3.770138888888889in"}

Source: EMPAX-CGE

When examining such findings, however, it is important to note that
these impacts and redistributions are directly related to the specific
control option assumed in this illustrative analysis. As previously
stated, these results represent the impact of an approach presented by
EPA that could make progress towards attainment under the alternate
standard. While EPA is providing this analysis as guidance for States,
it is expected that States will evaluate the best strategies for
achieving compliance and may choose options that could significantly
alter these regional effects. Therefore, SIPs will most likely be
different than the strategy developed in this RIA and could be designed
to alleviate any disproportionate impacts on sensitive industries. For
example, given the impact on glass and cement production, assumed with
this scenario, affected States may well design SIP strategies that
mitigate the impact on these particular industries, perhaps distributing
costs more uniformly among all sectors.

### [Projected Impacts on GDP]{.underline}

The combination of economic interactions affecting business and
household behavior will be reflected in the changes in GDP estimated by
a CGE model. Given that this cost-based approach to analyzing the ozone
0.070 standard does not reflect its benefits to the environment, public
health, and labor productivity, CGE models (including EMPAX-CGE) will
tend to over estimate declines in total production in the United States.
Potentially offsetting these benefits are attainments costs that have
not been included in this analysis mainly due to their lack of direct
industry cost information. Consequently, these results can be considered
incomplete because they do not reflect potential productivity benefits
of the ozone Standard or the full cost of attainment. The impacts on GDP
should be viewed as an approximation of the social costs of the modeled
controls applied for the alternate standard and are provided here for
illustration.

Figure 5.7 illustrates GDP in the EMPAX-CGE model's baseline forecast
and the 0.070 ozone policy case. As shown, the estimated GDP impact is
negligible and, in fact, it is not possible to adjust the scale of the
graph to the point where the two lines do not overlap. Projected
decrease in GDP for the ozone 0.070 standard is roughly 0.04 percent
(0.04%), respectively, for the year 2020. This is equivalent to a \$7.1
billion decrease in GDP during the implementation year. In absolute
terms, these estimated implications for U.S. GDP are extremely small
relative to the total size of the economy. Even these small costs could
be reduced if the CGE analyses were extended to include benefits
associated with the ozone standard such as improvements in labor
productivity from environmental improvements.

**Fig 5.7 Change in U.S. GDP Compared to EMPAX-CGE Baseline**

![](media/image7.wmf){width="6.338888888888889in"
height="4.334722222222222in"}

Source: Department of Energy, Energy Information Administrations;
EMPAX-CGE

Results of the macroeconomic analysis generally show small nation-wide
impacts of the ozone 0.070 ppm standard on manufacturing and energy
industries, as well as small regional impacts. The standard generates a
0.04 percent (0.04%) decrease in GDP in 2020. On average, industries
show less than one-half of one percent (\<0.5%)decrease in output with
the exception of cement and glass manufacturing in some regions of the
country, which have output reductions of one to two percent (1-2%).
However, as stated above, a large portion of the attainment costs are
not inputted into EMPAX-CGE. Furthermore, the model does not incorporate
productivity benefits resulting from air quality improvements.
Therefore, as a result of these two potentially offsetting conditions,
it is difficult for EPA to determine if the results presented here
overstate or understate the impacts on industry output and U.S. GDP.

**5.3 Extrapolated Costs**

This section presents the results and methodology behind the
extrapolated cost calculations of reaching full attainment of the 0.075,
0.070, and 0.065 ppm ozone alternate standards. As discussed in Chapter
3, the application of 0.070 ppm control strategies was not successful in
reaching nationwide full attainment of the alternate ozone standards.
Many areas remained in non-attainment in all three alternate standards;
therefore the engineering costs detailed in Section 5.1 represent only
the costs of partial attainment.

It is important to emphasize the challenge EPA faced in estimating costs
of controls that do not yet exist. The estimation of the costs of
unidentified controls needed to reach attainment is inherently a
difficult issue. The degree to which unspecified controls are needed to
achieve attainment depends upon other variables in the analysis, such as
attainment date assumptions. We will better understand the true scope of
the issue in the future as states do the detailed area-by-area analysis
to determine available controls and attainment dates that are
appropriate under the Clean Air Act, which we do not attempt to
determine in this analysis.

In this draft RIA we use three different approaches to estimating the
costs of unspecified control measures. This reflects the difficulty in
defining a "best" approach to this issue. Our approaches have yet to be
peer reviewed. Our approaches reflect a range of views about the likely
cost of future technologies and strategies that reduce air pollutant
emissions. \[The higher-cost estimation approaches are implicitly more
pessimistic about prospects for technological advances that avoid large
increases in the cost per ton of emission reduction relative to controls
employed in the past.\] A separate section discusses historical
experience which has shown numerous technological advances in emission
reduction technologies, and provides a few examples of today's emerging
technologies. (See Section 5.5.) We will continue to consider these
issues between now and the publication of the final RIA for the final
ozone NAAQS rule.

Due to the level of uncertainty related to the extrapolated costs, two
approaches were applied. This section provides the additional costs of
reaching nationwide full attainment of the alternate ozone standards
utilizing three approaches: a lower bound fixed cost per ton approach
based on where the majority of the cost of the known control measures
where found, an upper bound fixed cost per ton approach based on the
cost of the last few known control measures used and an increasing
marginal cost approach similar to that used in the PM NAAQS RIA. Prior
to presenting the aforementioned full attainment costs, a detailed
description of the methodology of each approach is provided.

*5.3.1 Increasing Marginal Cost Methodology*

This approach stems from the assumption that each unit of incremental
reduction in non-attainment areas will result in an increase in cost per
ton or marginal cost of abatement. Therefore, EPA estimated constantly
increasing marginal cost curves for emission reductions using cost per
ton values from control strategy data in representative non-attainment
areas. These curves were then used to estimate a cost of full attainment
using the emission reduction targets detailed in Chapter 4 of this
report.

5.3.1.1 Marginal Cost Regions

EPA grouped the non-attainment areas described in Chapter 4 along with
their emission reduction targets into six regions of the country (Table
5.2) in order to acquire sufficient and representative data for deriving
the slopes of the marginal cost curves. As a way of maintaining some
consistency with the modeled controls and the economic impact analysis,
the six regions were loosely based on EMPAX-CGE regions[^10] with a few
exceptions.

-   Nonattainment areas in Virginia were grouped with the Northeast due
    to the fact that Northern Virginia is part of the Ozone Transport
    Region (OTR) which makes up the Northeast. Resources were not
    available to disaggregate states by counties.

-   Nonattainment areas in Louisiana were grouped with Texas and
    Oklahoma (Plains region) due to the similarity in industry mix among
    those states.

-   California was separated from the rest of the west due to the
    severity of the ozone problem in the state, the glide path targets
    unique to the state, and because EPA determined the rest of the west
    was not an ideal representation of California.

  --------------------------------- -------------------------------------
  **Table 5.2 Regions and Slopes    
  for Extrapolated Costs**          

  **Region**                        **Marginal Cost Slope**

  Northeast (OTR)                   0.035

  Midwest                           0.045

  Southeast                         0.036

  Plains (TX/LA)                    0.033

  West (Not CA)                     0.152

  CA                                0.211
  --------------------------------- -------------------------------------

5.3.1.2 Derivation of the Marginal Cost Slopes

Due to the efficaciousness and efficiency of NOx controls compared to
VOC controls, control strategy cost per ton data was acquired for each
region using a selection criteria defined in Table 5.3 and applied in
Ordinary Least Squares regression equations. Results of these equations
provided the slope for the marginal cost curves. For each equation, the
dependant variable (**Y** = cost/ton) and was regressed conditional to
(**X** = cumulative emissions reductions).[^11]

***Y** = c + β**X** + е*

*c* = constant

*β* = slope

*е* = residual

The intent of the regression equations was not necessarily to accurately
capture the relation between cost/ton and cumulative reductions but
instead it was to identify a slope that would provide a rough
approximation of an increasing cost/ton rate as related to cumulative
emission reductions. This slope would then provide an increasing
cost/ton rate in the extrapolated portion of the costs that was
equivalent to the rate observed under the modeled costs.

+-----------------------------------------------------------------------+
| **Table 5.3 Data Selection Criteria for Extrapolated Costs**          |
+-----------------------------------------------------------------------+
| 1\) Determine if area has sufficient NOx emissions remaining to reach |
| attainment                                                            |
+-----------------------------------------------------------------------+
| 2\) If area has sufficient NOx remaining to reach attainment, then    |
| use NOx cost/ton data due to their cost effectiveness compared VOC    |
| controls                                                              |
+-----------------------------------------------------------------------+
| 3\) If area does not have sufficient NOx emissions to reach           |
| attainment, then include VOC controls in the data set if:             |
|                                                                       |
| -   VOC controls were part of the control strategy for the area in    |
|     question                                                          |
|                                                                       |
| -   VOC controls would significantly alter the value of a NOx based   |
|     slope for the marginal cost curve                                 |
+-----------------------------------------------------------------------+

Note: Data analysis demonstrated that VOC control data would only be
needed for California. Due to

lack of available ozone data, NOx controls from California also include
control cost from the PM NAAQS

RIA control strategies.

5.3.1.3 Calculating Extrapolated Costs Using Marginal Cost Approach

Once the slope of the marginal cost curve was derived, the extrapolation
was calculated by multiplying that slope with the emission reduction
target and adding that value to the highest of the observed cost/ton
value (Figure 5.8). For this illustrative analysis, the highest of the
observed cost/ton values was roughly \$15,267/ton which represented the
intercept of the marginal cost equation. Total costs could then be
estimated by adding the area under the marginal cost curve in Figure 5.8
or by taking the integral of the marginal cost function and inputting
the emission reduction target into the equation for total cost.[^12]

2.  *Fixed Cost per Ton Values*

Similar to the 1997 Ozone NAAQS RIA, a fixed cost/ton value was also
applied to estimate the extrapolated costs of nationwide full
attainment. Total costs for each non-attainment area was calculated by
multiplying the fixed cost/ton value with the emission reduction targets
for each region. For this particular illustrative analysis, a pair of
fixed cost/ton values was used to calculate costs.

1.  Fixed Cost/Ton Methodology

NOx control strategy data for the East and West were examined for
'clustering' within their individual distributions. Cost/ton data for
the east and west were stratified into thousands (Ex. \$0-\$1000,
\$1000-\$2000,...) with individual source counts aggregated within each
interval. California was separated from the west so source cost/ton
counts were conducted separately for the state. This was the result of
limited ozone NOx data availability for the state, the low number of NOx
emissions remaining for CA, and the inclusion of VOC controls as well as
NOx controls from PM NAAQS RIA control strategies which were required to
resolve these data and emissions issues.

For the East, 90% of the controls were below \$6,000/ton. As a result,
the control cost closest to \$6,000/ton (\$6,012) was selected to
represent to lower estimate of the Eastern fixed cost/ton approach. For
the West, 94% of the controls had a cost/ton value below \$4,000/ton.
Therefore, \$4,213 was selected as the lower estimate for the western
fixed cost/ton approach. For California, the lower estimate was \$9,035
using the same method but including VOC and PM NAAQS NOx control data
from the PM NAAQS RIA hypothetical control scenario.

In addition to a lower fixed cost/ton estimate, an upper fixed cost/ton
value was used for calculating extrapolated costs. This upper value as
estimated at \$15,267 for all regions for the following reasons.

-   This value represented the highest, in terms of cost/ton, of the
    controls applied in the east which made up the majority of the
    modeled controls for the ozone standard.

-   In the case of the West, the next highest controls were roughly
    \$35,000 and \$39,000 per ton. Controls with these costs were
    determined to be significantly less feasible to implement compared
    other controls.

-   This value provides a consistent platform from which to incorporate
    and compare marginal cost values derived using the increasing
    marginal cost approach.

    2.  *Results*

Tables 5.4 to 5.6 provide the extrapolated cost values for full
attainment of the 0.075, 0.070, 0.065 ppm standards in each area
applying the increasing marginal cost approach as well as the two fixed
cost/ton values. The reader should be aware of the following
stipulations prior to making inferences from the extrapolated costs
presented in the following tables.

-   The two extrapolated cost approaches provide nothing more than three
    rough estimates of potential costs with the marginal cost approach
    providing the highest value. Neither result includes a probability
    or a link to sectors where reductions will be attained. Therefore,
    there are no expected values within this range of outcomes and no
    assumptions made about the types of controls that would be applied
    in 2020.

-   0.070 ppm extrapolated costs were estimated using data from the
    0.070 ppm control strategy. Therefore, although the degree of
    uncertainty is still significant, these results can be expected to
    have a higher level of confidence than results of the 0.075 and
    0.065 ppm alternate standards.

-   The use of the 0.070 ppm control strategy as a starting point for
    extrapolating the 0.075 ppm standard resulted in over attainment of
    0.075 ppm in some areas. For over attaining areas, cost savings and
    emission increases were extrapolated using the impact/ton estimates
    derived in Chapter 4 and their appropriate emission targets until
    reaching the 0.075 ppm standard.

-   Several new non-attainment counties were added to the analysis as a
    result of moving to the 0.065 ppm alternate standard. Most of these
    counties were in states within the 0.070 ppm control strategy region
    described in Chapter 3. Therefore, no additional controls were
    available and costs had to be extrapolated using the same impact/ton
    estimates applied in the 0.070 ppm estimates. Two new states were
    added to the non-attainment region (KS and AL). Since controls were
    available for these states, AirControlNET was used to identify
    controls that would achieve the required emission reduction targets.

  ------------------------------- ---------------- --------------- -----------------
  **[Table 5.4 Extrapolated Costs                                  
  of Meeting the 0.075 ppm                                         
  Standard (\$ M)]{.underline}**                                   

  **[Extrapolated Costs for 075   **MC Curve       **Lower Fixed   **Upper Fixed
  Standard]{.underline}**         Estimate**       Cost/Ton        Cost/Ton
                                                   Estimate**      Estimate\***

  *[Extrapolated                  ** **            ** **           ** **
  Costs]{.underline}*                                              

  CA -- Los Angeles**\*\***       \$0              \$0             \$0

  CA -- Kern County**\*\***       \$0              \$0             \$0

  Houston / Dallas                \$1,254          \$400           \$1,008

  Ozone Transport Region          \$1,307          \$443           \$1,114

  Lake Michigan region            \$1,310          \$449           \$1,130

  Richmond / Norfolk              \$790            \$297           \$748

  Detroit                         \$396            \$152           \$382

  Phoenix                         \$282            \$72            \$260

  Denver                          \$160            \$42            \$153

  Cleveland/Columbus/Cincinnati   \$92             \$36            \$92

  Atlanta                         \$15             \$6             \$15

                                                                    

  *Total Cost*                    \$5,606          \$1,896          

  * *                                                               

  *[Extrapolated Cost                                               
  Savi+ngs]{.underline}*                                           

  Baton Rouge, LA                 (\$225)          (\$91)           

  Indianapolis, IN                (\$209)          (\$85)           

  Louisville, KY-IN               (\$284)          (\$115)          

  St. Louis, MO-IL                (\$30)           (\$12)           

                                                                    

  *Total Cost Savings*            (\$748)          (\$303)          

  * *                                                               

  Total Extrapolated Cost         \$4,858          \$1,593          
  ------------------------------- ---------------- --------------- -----------------

-   \*Due to the limited amount of controls in the modeled control
    strategy which had this value, deducting this amount would likely
    result in an over estimate of the savings.

-   \*\* Los Angeles and Kern Counties have expected attainment dates
    after 2020. This analysis counts the portion of reductions expected
    by 2020 or earlier.

  ------------------------------- ------------------ -------------- ----------------
  **[Table 5.5 Extrapolated Costs                                   
  of Meeting the 0.070 ppm                                          
  Standard (\$ M)]{.underline}**                                    

  **[Extrapolated Costs for 0.070 **MC Curve         **Lower Fixed  **Upper Fixed
  Standard]{.underline}**         Estimate**         Cost/Ton       Cost/Ton
                                                     Estimate**     Estimate**

  CA -- Los Angeles \*\*          \$0                \$0            \$0

  CA -- Kern County\*\*           \$823              \$181          \$305

  Houston / Dallas                \$2,299            \$703          \$1,771

  Ozone Transport Region          \$2,310            \$746          \$1,878

  Lake Michigan region            \$2,334            \$752          \$1,893

  Richmond / Norfolk              \$1,683            \$600          \$1,511

  Detroit                         \$1,272            \$455          \$1,145

  Phoenix                         \$1,364            \$282          \$1,023

  Denver                          \$1,190            \$253          \$916

  Cleveland/Columbus/Cincinnati   \$926              \$339          \$855

  Atlanta                         \$825              \$309          \$779

  St. Louis                       \$785              \$291          \$733

  Indianapolis                    \$579              \$218          \$550

  Baton Rouge                     \$555              \$212          \$534

  Louisville                      \$491              \$188          \$473

  Memphis                         \$313              \$121          \$305

  Charlotte                       \$217              \$85           \$214

  Salt Lake City                  \$211              \$55           \$198

  Las Vegas                       \$177              \$46           \$168

  Tampa                           \$77               \$30           \$76

  **Total Extrapolated Cost**     **\$18,435**       **\$5,867**    **\$15,328**
  ------------------------------- ------------------ -------------- ----------------

-   \*\*Los Angeles and Kern Counties have expected attainment dates
    after 2020. This analysis counts the portion of reductions expected
    by 2020 or earlier.

  ------------------------------- ------------------- -------------- --------------
  **[Table 5.6 Extrapolated Costs                                    
  of Meeting the 0.065 ppm                                           
  Standard (\$ M)]{.underline}**                                     

  **[Extrapolated Costs for 065                                       
  Standard]{.underline}**                                            

                                  **MC Curve          **Lower Fixed  **Upper Fixed
                                  Estimate**          Cost/Ton       Cost/Ton
                                                      Estimate**     Estimate**

  CA -- Los Angeles\*\*           \$0                 \$0            \$0

  CA -- Kern County\*\*           \$2,230             \$452          \$763

  Houston / Dallas                \$3,427             \$1,006        \$2,534

  Ozone Transport Region          \$3,401             \$1,049        \$2,641

  Lake Michigan region            \$3,471             \$1,055        \$2,656

  Richmond / Norfolk              \$2,663             \$903          \$2,275

  Detroit                         \$2,260             \$758          \$1,908

  Phoenix                         \$2,827             \$493          \$1,786

  Denver                          \$2,599             \$463          \$1,679

  Cleveland/Columbus/Cincinnati   \$1,871             \$643          \$1,618

  Atlanta                         \$1,726             \$612          \$1,542

  St. Louis                       \$1,712             \$594          \$1,496

  Indianapolis                    \$1,479             \$521          \$1,313

  Baton Rouge                     \$1,417             \$515          \$1,298

  Louisville                      \$1,355             \$491          \$1,237

  Memphis                         \$1,157             \$424          \$1,069

  Charlotte                       \$1,051             \$388          \$977

  Salt Lake City                  \$1,263             \$265          \$962

  Las Vegas                       \$1,214             \$257          \$931

  Tampa                           \$894               \$333          \$840

  Jackson, MS                     \$757               \$285          \$718

  New Mexico areas (Farmington /  \$819               \$185          \$672
  Las Cruces)                                                        

  OK areas (Tulsa, Marshall)      \$704               \$267          \$672

  Huntington, WV-KY               \$639               \$242          \$611

  El Paso, TX                     \$538               \$206          \$519

  Kansas City, MO/KS              \$325               \$142          \$317

  Little Rock, AR                 \$442               \$170          \$427

  Mobile AL                       \$70                \$70           \$70

  Columbia, SC                    \$154               \$61           \$153

                                                                      

  **Extrapolated Total**          **\$42,465**        **\$12,851**   **\$33,684**
  ------------------------------- ------------------- -------------- --------------

-   \*\*Los Angeles and Kern Counties have expected attainment dates
    after 2020. This analysis counts the portion of reductions expected
    by 2020 or earlier.

**5.4 Summary of costs**

Table 5.7 presents a summary of the total cost of attaining 0.075,
0.070, and 0.065 ppm standards. This summary includes the costs
presented above from the modeled controls, the economic impact analysis
and the extrapolated costs. The range presented in the extrapolated
costs and the grand total indicate the upper and lower bound cost
estimates.

Table 5.7 Total Costs of Attainment in 2020 for Different Levels of the
Ozone Standard

  ------------------------ ------------- ---------------- ----------------
                           *Level of                      
                           Standard in                    
                           2020*                          

                           0.065 ppm     0.070 ppm        0.075 ppm

  Modeled Social Costs\*   \$7.1         \$7.1            \$7.1
  (\$B)                                                   

  Extrapolated Costs (\$B) \$13 to \$42  \$5.9 to \$18    \$1.6 to \$4.9

  Grand Total (\$B)        \$20 to \$50  \$13 to \$26     \$8.5 to \$12
  ------------------------ ------------- ---------------- ----------------

\*Modeled social costs includes both the modeled costs presented in
table 5.1, as well as the economic impact costs presented in section
5.2.

**5.5 Technology Innovation and Regulatory Cost Estimates**

During the history of the Clean Air Act, technological innovation and
"learning by doing" often have made it possible to achieve greater
emissions reductions that once were thought infeasible, or have reduced
the costs of emission control in relation to original estimates.
Innovative companies have successfully responded to the regulatory
challenges and market opportunities provided by the Act, producing
breakthrough technologies for multiple sectors. Studies have suggested
that costs of a number of EPA programs have been less than originally
estimated due in part to inadequate inability to predict and account for
future technological innovation in regulatory impact analyses.

A constantly increasing abatement cost curve similar to the one utilized
for estimating extrapolated costs in this RIA is likely to induce the
type of innovation that would result in lower costs than estimated early
in this chapter. Breakthrough technologies in control equipment would
result in an outward shift in the marginal cost curve, reducing marginal
costs, and thus deviate from the assumption of one constantly increasing
marginal cost curve. In addition, elevated abatement costs may result in
significant increases in the cost of production and would likely induce
production efficiencies, in particular those related to energy inputs,
which would lower emissions from the production side.

**Examples of Technological Advances in Pollution Control**

There are numerous examples of low-emission technologies developed
and/or commercialized over the past 15 or 20 years, such as:

-   Selective catalytic reduction (SCR) and ultra-low NOx burners for
    NOx emissions

-   Scrubbers which achieve 95% and even greater SO2 control on boilers

-   Sophisticated new valve seals and leak detection equipment for
    refineries and chemical plans

-   Low or zero VOC paints, consumer products and cleaning processes

-   CFC-free air conditioners, refrigerators, and solvents

-   Water and power-based coatings to replace petroleum-based
    formulations

-   Vehicles far cleaner than believed possible in the late 1980s due to
    improvements in evaporative controls, catalyst design and fuel
    control systems for light-duty vehicles; and treatment devices and
    retrofit technologies for heavy-duty engines

-   Continued development of activated carbon injection (ACI) technology
    for control of mercury from electric generating units

-   Development of integrated gasification combined cycle (IGCC) and
    ultra-super critical pulverized coal technologies for electricity
    generation

-   Idle-reduction technologies for engines, including truck stop
    electrification efforts

-   Market penetration of gas-electric hybrid vehicles, biodiesel and
    other clean fuels

**Influence on Regulatory Cost Estimates**

Studies indicate that it is not uncommon for pre-regulatory cost
estimates to be higher than later estimates, in part because of
inability to predict technological advances.

-   *Multi-rule study:* Harrington et al. of Resources for the Future
    conducted an analysis of the costs of 25 EPA and OSHA rules in 2000,
    and found a tendency for predicted costs to overstate actual
    implementation costs. Costs were overpredicted in 12 cases and
    underpredicted in 6 cases, with overestimates occurring more
    frequently in the larger rules. Difficulty of predicting
    technological innovation was one of several reasons cited for the
    overestimates.[^13]

-   *Acid Rain SO2 Trading Program*: Recent cost estimates of the Acid
    Rain SO2 trading program by Resources for the Future (RFF) and MIT
    have been as much as 83 percent lower than originally projected by
    EPA.[^14] Note that the original EPA cost analysis also relied on an
    optimization model like IPM. The ex ante numbers in 1989 were an
    overestimate in part because of unforeseen technological
    improvements.

-   *EPA Fuel Control Rules:* A 2002 study of cost estimates for EPA
    vehicle and fuels rules conducted by OTAQ found a general pattern
    that "all ex ante estimates tended to exceed actual price impacts,
    with the EPA estimates exceeding actual prices by the smallest
    amount." An example focusing on fuel rules is provided:

**Table 5.8 Comparison of Inflation-Adjusted Estimated Costs and Actual
Price Changes**

**for EPA Fuel Control Rules**[^15]

  ---------------------- ---------------------- ---------- ----------- ----------- ----------------
  ** **                  **Inflation-adjusted                                      **Actual Price
                         Cost Estimates                                            Changes
                         (c/gal)**                                                 (c/gal)**

                         **EPA**                **DOE**    **API**     **Other**    

  **Gasoline**                                                                      

  Phase 2 RVP Control    1.1                               1.8                     0.5
  (7.8 RVP - Summer)                                                               
  (1995\$)                                                                         

  Reformulated Gasoline  3.1-5.1                3.4-4.1    8.2-14.0    7.4 (CRA)   2.2
  Phase 1 (1997\$)                                                                 

  Reformulated Gasoline  4.6-6.8                7.6-10.2   10.8-19.4   12          7.2 (5.1, when
  Phase 2 (Summer)                                                                 corrected to 5yr
  (2000\$)                                                                         MTBE price)

  30 ppm sulfur gasoline 1.7-1.9                2.9-3.4    2.6         5.7 (NPRA), N/A
  (Tier 2)                                                             3.1 (AIAM)  

  **Diesel**                                                                        

  500 ppm sulfur highway 1.9-2.4                                       3.3 (NPRA)  2.2
  diesel fuel (1997\$)                                                             

  15 ppm sulfur highway  4.5                    4.2-6.0    6.2         4.2-6.1     N/A
  diesel fuel                                                          (NPRA)      
  ---------------------- ---------------------- ---------- ----------- ----------- ----------------

-   *CFC Phase-Out:* Number range CHAPTEREPA used a combination of
    regulatory, market based (i.e., a cap-and-trade system among
    manufacturers), and voluntary approaches to phase out the most
    harmful ozone depleting substances. This was done more efficiently
    than either EPA or industry originally anticipated. The phaseout for
    Class I substances was implemented 4-6 years faster, included 13
    more chemicals, and cost 30 percent less than was predicted at the
    time the 1990 Clean Air Act Amendments were enacted.[^16]

    3.  **References**

Anderson, J.F., and Sherwood, T., 2002. "Comparison of EPA and Other
Estimates of Mobile Source Rule Costs to Actual Price Changes," U.S.
Environmental Protection Agency.

Babiker, M.H., and T.F. Rutherford. 1997. "Input Output and General
Equilibrium Estimates of Embodied CO2: A Data Set and Static Framework
for Assessment." University of Colorado at Boulder, Working Paper 97 2.
Available at <http://debreu.colorado.edu/papers/gtaptext.html>.

Babiker, M.H., J.M. Reilly, M. Mayer, R.S. Eckaus, I.S. Wing, and R.C.
Hyman. 2001. "The MIT Emissions Prediction and CO2 Policy Analysis
(EPPA) Model: Revisions, Sensitivities, and Comparisons of Results." MIT
Joint Program on the Science and Policy of Global Change, Report No. 71.
Available at <http://web.mit.edu/globalchange/www/eppa.html>.

Bovenberg, L.A., and L.H. Goulder. 1996. "Optimal Environmental Taxation
in the Presence of Other Taxes: General Equilibrium Analysis." American
Economic Review 86(4):985-1000. Available at
\<http://www.aeaweb.org/aer/\>.

Brooke, A., D. Kendrick, A. Meeraus, and R. Raman. 1998. GAMS: A User's
Guide. GAMS Development Corporation. Available at
[http://www.gams.com](http://www.gams.com/).

Carlson, Curtis, Dallas R. Burtraw, Maureen, Cropper, and Karen L.
Palmer. 2000. "SulfurDioxide Control by Electric Utilities: What Are the
Gains from Trade?" *Journal of Political Economy* 108(#6):1292-1326.

Ellerman, Denny. January 2003. Ex Post Evaluation of Tradable Permits:
The U.S. SO2

Cap-and-Trade Program. Massachusetts Institute of Technology Center for
Energy and Environmental Policy Research.

Feenberg, D., and E. Coutts. 1993. "An Introduction to the TAXSIM
Model." Journal of Policy Analysis and Management 12(1):189 194.
Available at http://www.nber.org/\~taxsim/.

## Fullerton, D., and D. Rogers. 1993. "Who Bears the Lifetime Tax Burden?" Washington, DC: The Brookings Institute. Available at http://bookstore.brookings.edu/ book_details.asp?product%5Fid=10403.

## Goulder, L.H., and R.C. Williams. 2003. "The Substantial Bias from Ignoring General Equilibrium Effects in Estimating Excess Burden, and a Practical Solution." Journal of Political Economy 111:898 927. Available at [**http://www.journals.uchicago.edu/JPE/home.html**](http://www.journals.uchicago.edu/JPE/home.html)

Harrington, W., R.D. Morgenstern, and P. Nelson. 2000. "On the Accuracy
of Regulatory Cost Estimates." *Journal of Policy Analysis and
Management* 19(2):297-322.

Minnesota IMPLAN Group. 2003. State Level Data for 2000. Available from
<http://www.implan.com/index.html>.

Nestor, D.V., and C.A. Pasurka. 1995. The U.S. Environmental Protection
Industry: A Proposed Framework for Assessment. U.S. Environmental
Protection Agency, Office of Policy, Planning, and Evaluation. EPA
230-R-95-001. Available at
http://yosemite.epa.gov/ee/epa/eermfile.nsf/11f680ff78df42f585256b45007e6235/41b8b642ab9371df852564500004b543/\$FILE/EE
0217A 1.pdf.

U.S. Department of Energy, Energy Information Administration. Undated
(b). State Energy Price and Expenditure Report. Washington DC. Available
at http://www.eia.doe.gov/emeu/states/price_multistate.html.

## 

## U.S. Department of Energy, Energy Information Administration. 2001. Manufacturing Energy Consumption Survey 1998. Washington DC. Available at http://www.eia.doe.gov/emeu/mecs/. 

## 

## U.S. Department of Energy, Energy Information Administration. January 2003. Annual Energy Outlook 2003. DOE/EIA 0383(2003). Washington DC. Available at http://www.eia.doe.gov/oiaf/archive/aeo03/pdf/0383(2003).pdf.

## 

## U.S. Department of Energy, Energy Information Administration. January 2004. Annual Energy Outlook 2004. DOE/EIA-0383(2003). Washington, DC. Available at http://www.eia.doe.gov/oiaf/aeo/pdf/0383 (2001).

[^1]: The less stringent alternative analyzed, which is the current
    standard, or baseline, would not require additional costs and
    therefore costs for that level are not presented in this RIA.

[^2]: For more information on this cost methodology and the role of
    AirControlNext, see Section 6 of the 2006 PM RIA, AirControlNET 4.1
    Control Measures Documentation (Pechan, 2006b), or
    <http://www.epa.gov/ttn/catc/products.html#cccinfo>

[^3]: Detailed information on IPM is available in Section 6 of the 2006
    PM RIA or at http://www.epa.gov/airmarkets/epa-ipm

[^4]: A different plant-specific interest rate is applied in estimating
    control costs within IPM. See PM RIA for details.

[^5]: All estimates provided reflect the cost of a control strategy for
    0.070 ppm, incremental to a 2020 baseline of compliance with the
    current standard of 0.084 ppm.

[^6]: ^?^ Total annualized costs are 3% are calculated for controls
    where there is a capital component.

[^7]: See Appendix E in the RIA for the Final CAIR rule for additional
    discussion of these IPM-EMPAX linkages
    (<http://www.epa.gov/interstateairquality/technical.html>).

[^8]: For more detailed regional impact figures, please see the appendix
    for this chapter. See the CAIR and PM NAAQS analyses, and Ross et
    al. (2005), for discussions of regional definitions.

[^9]: Redistribution of production will also tend to occur among states
    in each region, with some states' increasing

    output to offset any declines in neighboring states.

[^10]: For more information on EMPAX-CGE regions, see appendix NEED
    NUMBER. Data sets used to calculate the slopes of the marginal cost
    curve were not based on EMPAX-CGE modeling. The only similarity with
    EMPAX-CGE is the regional breakdown. Therefore, the extrapolated
    costs do not represent social costs in any way nor are they linked
    to the CGE baseline data, structure, or sector detail. Linking
    extrapolated costs to individual sectors is beyond the scope of this
    analysis.

[^11]: EPA recognizes that these regression equations may be
    misspecified. As stated above, the objective was not to accurately
    capture the relation between control cost/ton and emission reduction
    for statistical or economic inference purposes. These equations
    represent the most statistically adequate models that could be
    specified given the data, time, and resource constraints.

[^12]: *Total Cost = \$15,267x + (β*/2)x^2^, where x = emission
    reduction target

[^13]: Harrington et al., 2000.

[^14]: Carlson et al., 2000; Ellerman, 2003.

[^15]: Anderson et al., 2002.

[^16]: Holmstead, 2002.