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CHAPTER 7: ENGINEERING COST ANALYSIS AND ECONOMIC IMPACTS

Overview

This chapter summarizes the data sources and methodologies used to estimate 

engineering costs of attaining the alternative, more stringent levels for the ozone primary 

standards analyzed in this regulatory impact analysis (RIA). The chapter also provides estimates 

of the engineering costs of control strategies presented in Chapter 4 for the alternative standards 

of 70, 65, and 60 ppb. The discussion is presented as follows: Section 7.1 presents the costs 

associated with the application of known controls and is followed by discussions about the 

challenges of estimating costs for unknown controls (Section 7.2); costs associated with 

emissions reductions from unknown controls that are needed to demonstrate full attainment of 

the alternative standards analyzed (Section 7.3); total compliance cost estimates (Section 7.4); 

updated methodology (Section 7.5); economic impacts (Section 7.6); and the uncertainties and 

limitations associated with these components of the RIA (Section 7.7). 

The engineering costs described in this chapter generally include the costs of purchasing, 

installing, operating, and maintaining the referenced technologies. The costs associated with 

monitoring, testing, reporting, and record keeping for affected sources are not included in the 

annualized cost estimates. For a variety of reasons, actual control costs may vary from the 

estimates the EPA presents. As discussed throughout this document, 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 the EPA 

anticipates that state and local governments will consider programs that are best suited for local 

conditions. Also, the EPA recognizes the unknown emissions control portion of the engineering 

cost estimates (Section 7.3) reflects substantial uncertainty about the sectors and technologies

that might become available for cost-effective application in the future.

The engineering cost estimates are limited in their scope. This analysis focuses on the 

emissions reductions needed for attainment of a range of alternative revised standards. The EPA 

understands that some states will incur costs both designing State Implementation Plans (SIPs) 

for and implementing new control strategies to meet final revised standards. However, the EPA 
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does not know what specific actions states will take to design their SIPs to meet final revised 

standards. Therefore, we do not present estimated costs that government agencies may incur for 

managing the requirement, implementing these (or other) control strategies, or for offering 

incentives that may be necessary to encourage the implementation of specific 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.

7.1 Estimating Engineering Compliance Costs 

7.1.1 Methods and Data

After designing the hypothetical control strategy using the methodology discussed in 

Chapter 4, the EPA used the Control Strategy Tool (CoST) (U.S. EPA, 2014a) to estimate 

engineering control costs for non-electric generating unit (non-EGU point) point, nonpoint and 

mobile nonroad sources. CoST calculates engineering costs using one of two different methods: 

(1) an equation that incorporates key operating unit information, such as unit design capacity or 

stack flow rate, or (2) an average annualized cost-per-ton factor multiplied by the total tons of 

reduction of a pollutant. Most control cost information within CoST was developed based on the 

cost-per-ton approach because estimating engineering costs using an equation requires more 

detailed data, and parameters used in these equations may not be readily available or broadly

representative across sources within the emissions inventory. The cost equations used in CoST 

estimate annual, capital and/or operating and maintenance (O&M) costs and are used primarily 

for some larger sources such as industrial/commercial/institutional (ICI) boilers and petroleum 

refinery process heaters. Information on CoST control measures information, including cost-perton factors and cost equations can be found at www.epa.gov/ttnecas1/cost.htm. . Costs for 

selective reduction catalysts (SCR) applied as part of the analysis for reducing NOx at coal-fired 

electric generating units (EGUs) were estimated using documentation for the Integrated Planning 

Model (IPM) (Sargent & Lundy, 2013).
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Capital costs are converted to annual costs using the capital recovery factor (CRF).1

Where possible, calculations are used to calculate total annual control cost (TACC), which is a 

function of capital costs (CC) and O&M costs. The CRF incorporates the interest rate and 

equipment life (in years) of the control equipment. Operating costs are calculated as a function of 

annual O&M and other variable costs. The resulting TACC equation is TACC = (CRF * CC) + 

O&M. For more information on this cost methodology, refer to the EPA Air Pollution Control 

Cost Manual (U.S. EPA, 2003) and EPA’s Guidelines for Preparing Economic Analyses, 

Chapter 6 (US. EPA, 2014b).

Engineering costs will differ depending on the quantity of emissions reduced, emissions 

unit capacity, or stack flow, which can vary over time. Engineering costs will also differ in 

nominal terms by the year for which the costs are calculated (e.g., 2011$ versus 2008$).2 For 

capital investment, in order to attain standards in 2025 we assume capital investment occurs at 

the beginning of 2025. We make this simplifying assumption because we do not know what all 

firms making capital investments for control measures will do and when they will do it. Our 

estimates of annualized costs include annualized capital and annual O&M costs for those 

controls included in our known control strategy analysis. Our engineering cost analysis uses the 

equivalent uniform annual costs (EUAC) method, in which annualized costs are calculated based 

on the equipment life for the control measure and the interest rate incorporated into the CRF. 

Annualized costs represent an equal stream of yearly costs over the period the control technology 

is expected to operate. We make no presumption of additional capital investment in years beyond 

2025. The EUAC method is discussed in detail in the EPA Air Pollution Control Cost Manual 

(U.S. EPA, 2003). The controls applied and their respective engineering costs are described in 

the Chapter 7 Appendix.

7.1.2 Compliance Cost Estimates for Known Controls

In this section, we provide engineering cost estimates for the known controls identified in 

Chapter 4 that include control technologies for EGUs, non-EGU point, nonpoint and mobile 

 

1 The capital recovery factor formula is expressed as [r*(1+r)^n/[(1+r)^n -1]. Where r is the real rate of interest and 

n is the number of time periods. 

2 The engineering costs will not be any different in real (inflation-adjusted) terms if calculated in 2011 versus other 

year dollars, if the other-year dollars are properly adjusted. For this analysis, all costs are reported in real 2011 

dollars.
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nonroad sources. Onroad mobile source controls were not applied because they are largely 

addressed in existing rules such as the recent Tier 3 rule. Engineering costs generally refer to the 

equipment installation expense, the site preparation costs for the application, and annual 

operating and maintenance costs. Note that in many cases the application of these control 

strategies does not result in areas reaching attainment for the alternative ozone standards of 70, 

65, and 60 ppb and additional emission reductions beyond known controls are needed.

The EPA evaluated the costs of all known NOx controls contained in the CoST control 

measures database for this RIA and found that all nonpoint and nonroad sector controls were 

below $14,000 per ton of NOx emission reduction, and that the bulk of the non-EGU point source 

controls were below this cost. Overall, for all NOx controls prior to application of any cost cap, 

controls costing less than $14,000 per ton account for 96 percent of known emission reductions. 

Figure 7-1 represents the marginal cost curve for all the NOx control measures contained in the 

CoST database. This is an incomplete representation of the marginal abatement cost curve for all 

NOx abatement, because we do not have information on the control measures and costs for the 

remaining uncontrolled NOx emissions (see discussion in section 7.2). The controls above 

$14,000 were investigated and we determined that the higher cost controls were primarily due to 

errors in the cost equations for a few types of sources (mainly ICI Boilers and Process Heaters) 

for certain source sizes. We are taking steps to correct these equations for the final ozone RIA. 

As a result of the error mentioned above, a cost cap of $14,000 per ton of NOx emissions 

reduction for the non-EGU point source controls was applied, to remove the incorrectly applied 

controls from the analysis. A small number of NOx controls were applied for non-EGU point 

sources above $14,000 per ton but these had little impact on the overall emission reductions or 

control cost. A significant portion of the EGU SCR controls were above this level; no cost cap 

was applied to the EGU SCR controls. Note that control costs for California were lower than for 

other areas because there were no EGU SCR controls applied in California because there were 

no coal-fired utility boilers without SCR already in place. 

We intended to apply a similar cost cap but inadvertently applied a slightly higher cap of 

$15,000 per ton of VOC emission reduction. At the beginning of the analysis we were 

anticipating VOC reductions would play a relatively minor role in the analysis so we did not do a 
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separate marginal cost analysis for VOC. However, for the final ozone RIA we will conduct a 

separate analysis for VOC and will make costing decisions accordingly.

Figure 7-1. Marginal Costs for Known NOx Controls for All Source Sectors (EGU, nonEGU Point, Nonpoint, and Nonroad)

See Tables 7-1 through 7-3 for summaries of control costs from the application of known 

controls for alternative standards of 70, 65, and 60 ppb. Costs are listed by sector for both 

eastern and western U.S., except California and presented at 3 and 7 percent discount rates. Note 

that any incremental costs for known controls for California (post-2025) for alternative standards 

of 70, 65, and 60 ppb are zero because all known controls for California were applied in the 

demonstration of attainment for the baseline standard of 75 ppb.
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These numbers reflect the engineering costs annualized at discount rates of 3 percent and 

7 percent, which is to the extent possible consistent with the guidance provided in the Office of 

Management and Budget’s (OMB) (2003) Circular A-4. Discount rates refer to the rate at which 

capital costs are annualized.3 A higher discount, or interest, rate results in a larger annualized 

cost of capital estimate. It is important to note that it is not possible to estimate both 3 percent 

and 7 percent discount rates for a number of the controls included in this analysis. Because we 

obtain control cost data from many sources, we are not always able to obtain consistent data 

across original data sources.4If disaggregated control cost data is unavailable (i.e., where capital, 

equipment life value, and O&M costs are not separated out), EPA typically assumes that the 

estimated control costs are annualized using a 7 percent discount rate. When disaggregated 

control cost data is available (i.e., where capital, equipment life value, and O&M costs are 

explicit) we can recalculate costs using a 3 percent discount rate.

In addition, the EGU control costs were not estimated for either 3 or 7 percent. The 

interest rate used for this analysis reflects an internal rate of return of 11.51 percent for retrofit 

controls as described in the IPM v5.13 documentation (U.S. EPA, 2013).

For non-EGU point source controls, some disaggregated data is available, and we were 

able to calculate those costs at both 3 and 7 percent discount rates for those controls. For the 

alternative standards analyzed in this RIA, approximately 23 percent of known control costs are 

disaggregated at a level that could be discounted at 3 percent. Because we do not have 

disaggregated control cost data for any EGU, nonpoint, or nonroad source controls, total 

annualized costs for these sectors are assumed to be calculated using a 7 percent discount rate. 

Because we do not have a full set of costs at the 3 percent discount rate, the 3 percent columns in 

Tables 7-1 to 7-3 reflect the sum of some non-EGU point source controls at a 3 percent discount 

rate, some non-EGU point source controls at a 7 percent discount rate, and the other sectors at a 

7 percent discount rate. With the exception of the 3 percent Total Annualized Cost estimates in 

 

3

In this analysis, the discount rate refers to the interest rate used in the discounted cash flow analysis to determine 

the present value of future cash flows. A social discount rate is a discount rate used in computing the value of 

monies spent on social projects or investments, such as environmental protection. The social discount rate is directly 

analogous to the discount rate we use in the engineering cost analysis, as well as certain rates used in corporate 

finance (e.g., hurdle rate or a project appropriate discount rate), so the mathematics are identical.

4 Data sources can include states and technical studies, which do not always include the original data source.
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Tables 7-1 to 7-3, engineering cost estimates presented throughout this chapter and elsewhere in 

this document are based on a 7 percent discount rate.

The total annualized engineering costs associated with the application of known controls, 

incremental to the baseline and using a 7 percent discount rate, are approximately $1.6 billion for 

an alternative annual standard of 70 ppb, $4.2 billion for a 65 ppb alternative standard, and $4.4 

billion for a 60 ppb alternative standard. Costs of NOx controls in terms of dollars per ton of 

NOx reduction for the alternative standards analyses were approximately $12,000/ton on average

for the EGU sector with a range of $2,000/ton to $38,000/ton; $3,000/ton for the non-EGU point 

sector on average, with a range of $17 to $90,000/ton; $1,100/ton for the nonpoint sector on 

average ,with a range of $520 to $2,200/ton; and $4,600/ton for the nonroad sector on average 

with a range of $3,300/ton to $5,300/ton. The overall average cost range was $2,300 to

$3,000/ton for all sectors combined. 

As shown in Tables 7-1 through 7-3 below, the cost trend is increasing for some sectors 

and decreasing for others. The variation is small for most sectors and depends on the sources that 

happen to be in the geographic areas of control. In general, the same set of controls is being 

applied at each level of the alternative standards analyzed. The primary difference in the control 

strategies for the alternative standards is the greater size of the geographic area of control as the 

stringency of the alternative standards increases. Overall for all sectors as a whole, the average 

cost per ton is actually increasing slightly with increasing stringency of the alternative standard 

analyzed.

- U.S., except California (millions of 2011$)a

Geographic Area Emissions Sector Known Control Costs

7 Percent 

Discount Rate

3 Percent

Discount Rate

East

EGU 310b 310b

Non-EGU Point 640 620c

Nonpoint 610 610d

Nonroad 22 22d

Total 1,600 1,600e

West EGU - -

Non-EGU Point - -
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Geographic Area Emissions Sector Known Control Costs

Nonpoint - -

Nonroad - -

Total - -

Total Known Control Costs 1,600 1,600e

a All values are rounded to two significant figures.

b EGU control cost data is calculated using an 11.51 percent for retrofit controls.

c Non-EGU control cost data is calculated at a 3% interest where control cost equations are utilized.

d Nonpoint and nonroad control costs are calculated using a 7% interest rate because no 3% data exists.

e Because we obtain control cost data from many sources, we are not always able to obtain consistent data across 

original data sources. Where disaggregated control cost data is available (i.e., where capital, equipment life value, 

and O&M costs are explicit) we can calculate costs using a 3 percent discount rate. Therefore the cost estimate 

provided here is a summation of costs at 3 percent and 7 percent discount rates.

Table 7-2. Summary of Known Annualized Control Costs by Sector for 65 ppb for 2025

- U.S., except California (millions of 2011$)a

Geographic Area Emissions Sector Known Control Costs

7 Percent 

Discount Rate

3 Percent 

Discount Rate

East

EGU 1,500b 1,500b

Non-EGU Point 1,100 1,100c

Nonpoint 1,100 1,100d

Nonroad 53 53d

Total 3,800 3,800e

West

EGU 230b 230b

Non-EGU Point 86 86c

Nonpoint 87 87d

Nonroad 5.7 5.7d

Total 410 410e

Total Known Control Costs 4,200 4,200e

a All values are rounded to two significant figures.

b EGU control cost data is calculated using an 11.51 percent for retrofit controls.

c Non-EGU control cost data is calculated at a 3% interest where control cost equations are utilized.

d Nonpoint and nonroad control costs are calculated using a 7% interest rate because no 3% data exists.

e Because we obtain control cost data from many sources, we are not always able to obtain consistent data across 

original data sources. Where disaggregated control cost data is available (i.e., where capital, equipment life value, 

and O&M costs are explicit) we can calculate costs using a 3 percent discount rate. Therefore the cost estimate 

provided here is a summation of costs at 3 percent and 7 percent discount rates.

Table 7-3. Summary of Known Annualized Control Costs by Sector for 60 ppb for 2025

- U.S., except California (millions of 2011$)a

Geographic Area Emissions Sector Known Control Costs

7 Percent Discount Rate 3 Percent Discount 

Rate

East

EGU 1,500b 1,500b

Non-EGU Point 1,200 1,100c

Nonpoint 1,100 1,100d

Nonroad 53 53d

Total 3,800 3,700e
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Geographic Area Emissions Sector Known Control Costs

West 

EGU 400 400b

Non-EGU Point 98 97c

Nonpoint 88 88d

Nonroad 5.7 5.7d

Total 590 590e

Total Known Control Costs 4,400 4,400e

a All values are rounded to two significant figures.

b EGU control cost data is calculated using an 11.51 percent for retrofit controls.

c Non-EGU control cost data is calculated at a 3% interest where control cost equations are utilized.

d Nonpoint and nonroad control costs are calculated using a 7% interest rate because no 3% data exists.

e Because we obtain control cost data from many sources, we are not always able to obtain consistent data across 

original data sources. Where disaggregated control cost data is available (i.e., where capital, equipment life value, 

and O&M costs are explicit) we can calculate costs using a 3 percent discount rate. Therefore the cost estimate 

provided here is a summation of costs at 3 percent and 7 percent discount rates.

7.2 The Challenge of Estimating Costs for Unknown Controls

As described in Chapter 4, the known control measures were applied to EGU, non-EGU 

point, nonpoint (area), and nonroad mobile sources for demonstration of attainment with the 

current and alternative standards. Table 4-7 lists the specific control technologies applied in the 

known control analysis. There were several areas where known controls did not achieve enough 

emissions reductions to attain the alternative standards of 70, 65, and 60 ppb. To complete the 

analysis, the EPA then estimated the additional emissions reductions beyond known controls 

needed to reach attainment, also referred to as unknown controls. For information on the 

methodology used to develop the emissions reductions estimates, see Chapter 3. 

The estimation of engineering costs for unspecified emission reductions needed to reach 

attainment many years in the future is inherently a difficult task. This is because it is likely that 

the abatement supply function will shift out or change shape over time due to a variety of 

economic, technical, and regulatory influences. Our experience with Clean Air Act 

implementation shows that numerous factors, such as technical change and development of 

innovative strategies, can lead to emissions reductions that may not seem possible today, while 

potentially reducing costs over time. For example, facility-level data collected through the U.S. 

Census Bureau’s Pollution Abatement Costs and Expenditures (PACE) survey suggests that this 

may have happened in the manufacturing sector in recent decades. Based on surveys of 

approximately 20,000 plants classified in manufacturing industries,The the PACE data show 

during the 1994-2005 time period, a period of increasing regulatory stringency, spending on air 

pollution abatement as a percentage of revenues decreased for the manufacturing 
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sector.5 Although exogenous factors such as changes in economic conditions may have 

contributed to the relative share in costs of pollution abatement, it is also possible that 

technological change and innovation may have contributed to this relative decline. 

In addition to considering the potential for technological innovation, it is also important 

to understand that EPA’s control strategy tools largely focus on a limited set of emissions 

inventory sectors, whereas abatement opportunities exist in other sectors. EPA’s control strategy 

tools undergo continuous improvement, and as the need for additional abatement opportunities 

grows, more evaluation of uncontrolled emissions takes place. During these evaluations, 

additional abatement opportunities from applying identified controls typically are found.

This section discusses various factors that must be considered in developing a 

methodology for estimating the costs of unknown controls. First, we explain why the abatement 

supply curve from known controls presented in the previous section provides an incomplete 

picture of all currently available abatement opportunities. Second, we show how, as time passes 

and the EPA reviews NAAQS standards, relevant information is revealed in the current RIA 

development process that was not available to analysts developing RIAs for previous reviews, 

such as unforeseen regulatory programs or other exogenous factors that account for significant 

emissions reductions. Third, we discuss a related issue, that technical change may affect the 

marginal abatement cost curve. Additionally, we present evidence from the literature that 

regulatory action can act as a forcing function for technical change. Fourth, we discuss how 

regulatory costs can decrease over time as regulated entities gain experience reducing emissions 

and reduce per unit costs, commonly referred to as “learning by doing”. Fifth, we discuss how 

NOx offset prices could serve as reasonable proxies for the costs associated with emissions 

 

5 The Pollution Abatement Costs and Expenditures (PACE) survey collects facility-level data on pollution 

abatement capital expenditures and operating costs for compliance with local, state, and federal regulations and 

voluntary or market-driven pollution abatement activities. In 2005, the most recent year PACE data were collected, 

the U.S. manufacturing sector spent $3.9 billion dollars on air capital expenditures and incurred $8.6 billion dollars 

in operating costs for air pollution prevention and treatment. These figures represent less than 3% of total new 

capital expenditures and less than 0.18% of total revenue for the manufacturing sector, respectively. These 

percentages have declined since 1994, when air capital expenditures were less than 4% of total new capital 

expenditures and air pollution abatement operating costs were less than 0.2% of total revenue. Levinson (2009) finds 

that most of the pollution reductions in the U.S. come from changes in technology as opposed to changes in imports 

or changes in the types of domestically produced goods. He finds that even though manufacturing output increased 

by 24% from 1987 to 2001, emissions of four common air pollutants from the sector declined 25% over that time 

period and the most important factor contributing to the decrease in pollution is technical change or innovation.
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reductions from unknown controls. Finally, we describe how we use this information to help 

inform the unknown control cost methodology applied in section 7.3.

7.2.1 Incomplete Characterization of NOx Marginal Abatement Cost Curves

Underlying the selection of controls as described in Appendix 4A is the concept of the 

marginal abatement cost curve (MACC). The marginal abatement cost curve (MACC) is a 

representation of how the marginal cost of additional emissions abatement changes with 

increasing levels of abatement. Adding new technologies, or changing either the abatement 

amount or cost of the technology, will change the shape of the overall MACC. 

In developing engineering cost estimates in section 7.1, the focus was largely on end-ofpipe controls and only includes limited process-oriented control measures, such as switching to 

lower-emitting fuel or energy sources and the installation of energy efficiency measures. These 

measures can result in significant emissions abatement, but are not reflected in the marginal 

abatement cost curve based on traditional control measures. As a result, the MACC derived in 

the previous section from known controls represents an incomplete supply curve that partially 

captures the “true” abatement supply. An illustrative, hypothetical depiction of an “observed but 

incomplete” MACC and the “true” underlying MACC is presented in Figure 7-2. 
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Figure 7-2. Observed but incomplete MACC (solid line) based on known controls 

identified by current tools and complete MACC (dashed line) where gaps 

indicate abatement not identified by current tools

In the figure, the solid line traces out a hypothetical observed MACC, while the dashed line 

characterizes the combination of observed and unobserved abatement possibilities. The 

inclusion of the unobserved abatement pushes the abatement supply out.

Due to the incomplete characterization of the full range of the MACC, it is important to 

understand the composition of the cost information that is available to construct the partial 

MACC. The nature of available information on the cost of NOx abatement measures is 

somewhat complex. The highest cost per ton estimates are often associated with controls that 

achieve very small total reductions in NOx or are special cases. For example, in some cases, 

controls have been developed primarily to address other pollutant emissions, such as SO2, but 

achieve NOx reductions as a co-benefit. These controls are well characterized in the CoST 

database because they have been applied for SO2 control, but the degree to which sources would 

adopt those controls for NOx is uncertain, and it is unlikely that those very high per ton cost 

measures would be the efficient marginal abatement cost (MAC) level for the targeted level of 

NOx emissions reductions needed for attainment. In addition, there are some controls that have 
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been identified as applicable for some sources even though they have very high marginal costs 

per ton of NOx, because those controls are required to meet other provisions of the CAA. For 

example, LNB+SCR for process heaters is relatively common at refineries, mainly due to a New 

Source Review enforcement initiative that has been underway since 2001. These plants are 

being required to install the controls regardless of cost as part of the enforcement action, and thus 

the costs may not represent the actual marginal cost at the level of abatement needed to reach the 

NAAQS attainment targets.

Lack of information about the MAC for emissions reductions not characterized in CoST 

is not an indication that controlling those tons is necessarily more difficult than controlling NOx 

from other sources that are in the database, or that the MAC for those tons is necessarily higher 

than all of the costs of controls already in the database. Some sectors are controlled at a higher 

rate than others, and in those cases, getting additional NOx reductions may indeed require higher 

cost controls. For example, EGU NOx has been heavily controlled, and the additional SCR units 

applied in the analysis are relatively more expensive per ton than the typical SCRs that have been 

applied in past analyses. However, other sectors may not be as well-controlled, and lower cost 

controls may be available. 

7.2.2 Comparison of Baseline Emissions and Controls across Ozone NAAQS RIAs from 1997 

to 2014

While each ozone NAAQS analysis since 1997 has required at least some emissions 

reductions from controls that were unknown at the time of the analysis, evidence suggests that 

over time new information on exogenous factors affecting baseline emissions and emissions 

controls becomes available that can shift emissions reductions from the unknown to the known 

category. Some exogenous factors that might affect baseline emissions include changes in 

economic conditions that may affect production levels, as well as plant closures and openings. 

Baseline emissions may also be affected by EPA or state regulations that require specific 

controls that may not be fully characterized in the set of known controls applied in an earlier 

RIA, or by EPA or state regulations targeting other pollutants, e.g., air toxics, that may result in 

reductions in NOx or VOC as a co-benefit. For example, in the 1997 ozone NAAQS RIA, the 

NOx emissions reductions from the mobile source Tier 2 standards were not included as known 

controls, even though the RIA acknowledged the potential for these standards to provide 
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substantial cost effective controls. Likewise, the 2008 ozone NAAQS RIA did not include 

controls on EGUs reflecting the Mercury and Air Toxics Standards or the Clean Power Plan. As 

a result, emissions reductions from unknown controls were much higher in some regions of the 

U.S. than they are in this RIA. 

Furthermore, many of these emission reductions may be achieved at a cost less than was 

originally applied to emissions reductions from unknown tons. Several of the large NOxreducing regulations issued between the 1997 and 2008 RIAs had ex ante estimates of costs per 

ton of NOx reduced well below the $10,000 per ton value applied to emissions reductions from 

unknown controls in the 1997 Ozone NAAQS RIA. Table 7-4 provides information on the cost 

per ton for NOx reductions from five major NOx-reducing regulations. To the extent possible, 

we determined from the RIA for each regulation the projected emissions reductions in 2010 (or 

the closest year) andby the estimated costs in 2010. Costs were adjusted from the year reported 

in the RIAs to constant 2010 dollars. In some cases, only an annualized cost was reported. In 

those cases we divided the year specific emissions projection by the annualized cost, recognizing 

that this may under or overstate the actual year specific cost per ton. Where possible, we report 

the separate costs for NOx emissions reductions. However, for most programs, total costs which 

include reductions in multiple pollutants are reported. As such, the cost per ton of NOx alone is 

likely overstated. 

Table 7-4. Emissions and Cost Information for Major NOx Rules Issued Between 1997 and 

2008

Regulation

Projected NOx 

Emissions Reductions in 

2010 (thousands)

(A)

Total Annual Cost

in 2010

(Million 2010$)

(B)

Average Cost/Tons 

NOx Reduced

(2010$)

(C = B/A)

NOx SIP Calla

1,141 2,515 $2,204

Clean Air Interstate Ruleb

1,200 $3,034 $2,528

Tier 2 Standardsc

1,236 $5,256 $4,253

Heavy Duty Diesel Enginesd

403 $4,570 $11,340

Nonroad Diesele

203 (in 2015) $660 $3,251

a Costs and emissions reductions obtained from Table ES-2 in the Regulatory Impact Analysis for the NOx SIP Call, 

FIP, and Section 126 Petitions, Volume 2: Health and Welfare Benefits (U.S. EPA, 1998).

b Emissions reductions obtained from Table 7-2 and Costs obtained from Table 7-3 in the Regulatory Impact 

Analysis for the Final Clean Air Interstate Rule (U.S. EPA, 2005).

c Costs and emissions reductions obtained from Appendix VI-C in the Regulatory Impact Analysis - Control of Air 

Pollution from New Motor Vehicles: Tier 2 Motor Vehicle Emissions Standards and Gasoline Sulfur Control 

Requirements (U.S. EPA, 1999).
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d Emission reductions obtained from Table II.B-4, and costs obtained from Table V.D-1 in the Regulatory Impact 

Analysis: Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control Requirements (U.S. 

EPA, 2000)

e

.Emissions reductions obtained from Table 8.6-1 (NOx+NMHC), and costs obtained from Table 8.5-2 

(NOx+NMHC) in the Final Regulatory Impact Analysis: Control of Emissions from Nonroad Diesel Engines (U.S. 

EPA, 2004). In this RIA, no information was provided for NOx emissions alone, in all cases, NOx+non-methane 

hydrocarbons (NMHC) was provided. Calculated cost per ton is thus the average for NOx and NMHC emissions 

reductions, rather than just for NOx emissions reductions.

The NOx State Implementation Plan (the “NOx SIP call”) was partially represented in the 

1997 RIA. The other rules in Table 7-4 were not included in 1997 RIA, although the RIA notes 

that the Tier 2 standards may be a way to get additional reductions to meet the ozone NAAQS. 

Table 7-64 shows that for these five major regulations, which account for 4.1 million tons of 

NOx reductions, the expected average cost per ton ranged from about $2,200 to $11,300 per ton 

of NOx reduced. Only in the single case of the heavy duty diesel engine rule was did the cost 

per ton NOx reduced exceedexpected to be greater than the $10,000/ton value used for unknown 

controls in the 1997 RIA. This suggests that unknown controls may be implemented at lower 

cost than the highest point of the MACC for known controls anticipated in the RIA. not generally 

be at the high cost margin of the MACC but rather may be more typically inframarginal 

additions to the set of abatement activities.

Comparing the MACC over time and across analyses is complicated because of (1) 

differences in the regions or areas affected by the proposed changes to the ozone standards, (2) 

the information available at the time of the analyses, and (3) analytical assumptions made about 

the universe of sources that can be controlled. Table 7-45 provides information about 

assumptions used in generating the costs of control measures for the 1997, 2008, and 2014 RIAs. 
7-16

Table 7-45. Comparison of Key Assumptions Used in Developing Estimates of NOx Emissions Controls and Costs across 

Past and Current Ozone NAAQS Regulatory Impact Analyses a

1997 2008 2014

Sectors Excluded

No additional utility NOx controls beyond 

Title IV and OTAG recommendations. 

Some mobile source control measures 

excluded due to mismatch between 

attainment dates and implementation 

timelines for the control measures.

Utility NOx controls beyond 

baseline only applied in the East 

(including East TX)

On-road mobile sources. 

Geographic 

Definition of 

Control Areas

Exceeding county plus CMSA for county 

exceeding the standard. If no CMSA, just 

use the exceeding county

(12 areas in East, 7 areas in West)

Non-EGU point and area controls 

applied to counties exceeding the 

standard plus surrounding counties 

out to 200km. Some additional 

controls were placed on large point 

sources in counties touching the 

buffer.

For mobile controls, both local 

(within 200 km buffer) and 

statewide controls were applied. 

Counties outside the state in which 

the exceeding county resides are 

excluded. Controls were applied 

to all states in the OTC excepting 

VT.

NOx controls for 70 ppb were applied to counties 

exceeding the standard, then surrounding counties 

within 200 km that were also within state 

boundaries (Texas, California) and within OTC 

boundaries including counties closest to exceeding 

counties first (Northeast). Where more controls 

were needed they were applied to counties in other 

states within the region, nearest the county 

exceeding the standard (Oklahoma, Arkansas, 

Louisiana and Kansas for Houston). VOC controls 

for 70 ppb were applied to special areas and 

counties within 100 km from them (California 

North and South, Dallas, Houston, Baltimore, and 

New York City).

NOX controls for 65 and 60 ppb were applied in 

regions (California, Southwest, Central, Midwest, 

Northeast). VOC controls were applied in special 

areas plus counties within 100 km from these 

special areas (Denver, Dallas, Houston, Chicago, 

New York City)

Cost Cap

$10,000/ton (1990 dollars) – justification is 

that states generally have not chosen to 

require existing sources to apply control 

measures with incremental costs above the 

threshold, even in severe areas like the 

South Coast of CA. Sensitivity on 

$7,000/ton to $20,000/ton.

$23,000/ton (2006$) for non-EGU 

point and area sources – 98% of 

possible reductions are achieved at 

82% of total costs. Based on 

evaluation of marginal cost curves 

for all counties in control areas 

(1,300 counties).

For NOx: $14,000/ton for point non-EGU sources, 

although an error resulted in a small number of 

point non-EGU controls above $14,000/ton. No 

nonpoint (area) source NOx controls were above 

$14,000/ton so cost caps had no effect on nonpoint 

source controls. For ICI boilers, costs were 

calculated through equations without cost 

constraints.
7-17

1997 2008 2014

For VOC: $15,000/ton for point non-EGU and 

nonpoint (area) sources

Minimum 

Emission 

Reduction

Not clearly defined For NOx: 5 tons for point nonEGU and, non-point and small

sources

For VOC: 1 ton for point nonEGU and non-point

For NOx: 5 tons for point non-EGU and, non-point

and small sources

For VOC: 1 ton for point non-EGU and nonpoint10%

Minimum 

Emissions

Not clearly defined 50 tons for NOx 25 tons for NOxFor NOx: 5 tons for point nonEGU, non-point and small sources

For VOC: 1 ton for point non-EGU and non-point

Assumed 

Control 

Effectiveness (% 

of intended 

effect)

95 to 100 percent Variable Variable

Rule 

Penetrationb

Obtained from published reports from state 

and local agencies

75% for onroad and nonroad SCR 

and diesel particulate filters

75% penetration in CA and 25% in TX and 

Northeast for nonroad

a These analyses also included controls for VOC emissions, however, those controls were generally very local in nature. The current analysis is focused 

primarily on controlling NOx to meet the alternative ozone standards, with relatively modest VOC controls where they are expected to help reach attainment. 

Also, for the 1997 and 2008 RIAs, attainment of the PM standards in place at the time of the analysis was assumed, and as a result, some additional NOx 

measures were already in place.

b Percent of county-level mobile or area source inventory affected by control measure.
7-18

[Placeholder for additional qualitative and quantitative discussion] 

7.2.3 Impact of Technological Innovation and DiffusionChange

In general, the MACC at any particular point in time for a defined set of emitting sectors 

will be an increasing function of the level of abatement. That is, marginal costs are increasing as 

the amount of emissions are reduced. However, in regulatory analyses of NAAQS, we are 

typically assessing costs of abatement in a future year or years selected to represent 

implementation of the standards. As such, a MACC constructed based on currently available 

information on abatement opportunities will not be the best representation of a future MACC. 

MACC in the future can differ from MACC in the present due to technological innovation and 

diffusion, such aschange (either the introduction of new technologies or improvements in 

effectiveness or applicability of existing technologies). Additionally, environmental policy can 

create incentives and constraints that influence the rate and direction of technical change (Jaffe et 

al. 2002) as well as the rate of diffusion and adoption of the innovations (Sterner and Turnheim 

2009) . 

In the context of emissions controls examined in this RIA, technological innovation and 

diffusionchange can affect the MACC in several ways. The following bullets present some 

examples of the potential effects of technical change: 

Case 1: New control technologies can be developed that cost less than existing technologies. 

Case 2: A new control technology is developed to address an uncontrolled emissions source, at 

a higher marginal cost than existing technologies, but still lower than the cost threshold value.

Case 3: The efficiency of an existing control measure increases. In some cases, the control 

efficiency of a measure can be improved through technological advances. 

Case 4: The cost of an existing control measure decreases. 

Case 5: The applicability of an existing control measure to other emissions sources increases. 

Overall, these five cases describe ways that technological change can reduce both the 

amount of unidentified abatement needed, decrease the MAC, decrease average costs, and 

decrease total costs relative to the case where it is assumed that technological change does not 

occur in response to increased demand for abatement. It is also possible in cases where there is a 

strictly binding emissions reduction target that new technologies can be introduced and adopted 
7-19

with much higher marginal costs. However, if there are cost off-ramps, such as those provided by 

Section 185 of the CAA, those higher cost technologies will not be adopted. 

Regulatory policies can also help induce technological change when a standard cannot be 

met either (1) with existing technology or (2) with existing technology at an acceptable cost, but 

over time market demand will provide incentives for industry to invest in research and 

development of appropriate technologies. These incentives are discussed in Gerard and Lave 

(2005), who demonstrate that the 1970 Clean Air Act induced significant technical change that 

reduced emissions for 1975 and 1976 automobiles. Those mandated improvements went beyond 

the capabilities of existing technologies by using regulatory pressure to incentivize the 

development of catalytic converting technology in 1975. Induced technological change can 

correspond to Cases 1 through 3 above.

There are many other examples of low-emission technologies developed and/or 

commercialized over the past 15 or 20 years, such as:

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

2. Scrubbers that achieve 95 percent or greater SO2 control on boilers

3. Sophisticated new valve seals and leak detection equipment for refineries and chemical 

plants

4. Low or zero VOC paints, consumer products and cleaning processes

5. Chlorofluorocarbon (CFC) free air conditioners, refrigerators, and solvents

6. Water and powder-based coatings to replace petroleum-based formulations

7. Vehicles with lower emissions than believed possible in the late 1980s due to 

improvements in evaporative controls, catalyst design and fuel control systems for lightduty vehicles; and treatment devices and retrofit technologies for heavy-duty engines

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

9. Increasing market penetration of gas-electric hybrid vehicles and cleaner fuels

These technologies were not commercially available two decades ago, and some were not 

even in existence. Yet today, all of these technologies are on the market, and many are widely 

employed. Several are key components of major pollution regulatory programs. 

As Brunnermeier and Cohen (2003) demonstrate, there is a positive correlation, other 

things held constant, between environmental innovations (measured as the number of relevant 
7-20

environmental patent applications) and specific regulations imposed on an industry (measured in 

terms of the frequency of government compliance inspections). Lanjouw and Mody (1996) 

show empirically a positive relationship between responses to environmental regulations (i.e., 

increases in pollution abatement expenditure) and new technology (i.e., relevant patent 

applications) in the United States, Japan, and Germany. They show that in each of these 

countries, even though on different timelines, the share of environmental patents increased 

considerably in response to stricter environmental regulations. Similarly, Popp (2004) studied 

the relationship between environmental regulation and new technology focusing on SO2 and 

NOx. The study was performed using patent data from the United States, Japan, and Germany. 

Popp found that more stringent regulation enhanced domestic patenting by domestic inventors.

While regulation may influence the direction and intensity of emissions-related research 

and development activities, “crowding out” of investment resources may occur as resources are 

directed away from other opportunities, potentially leading to opportunity costs that offset 

savings resulting from research and development successes (Popp and Newell 2012). In a study 

that links energy-related patent activity and firm financial data, Popp and Newell (2012) find that 

while increases in alternative energy patents result in fewer patents for other energy 

technologies, this results is due to firm-level profit-maximizing behavior rather than constraints 

on the magnitude of research and development resources. Alternatively, Kneller and Manderson 

(2012) find evidence in the United Kingdom that environment-related research and development 

resulting from more stringent regulation may crowd out other research and development 

activities but that environment-related capital does not crowd out non-environmental capital.

capital.

fully controlled, e.g., in comparing existing emissions with uncontrolled emissions levels, is the 

percent of control close to 100 percent? In those cases, achieving additional reductions through 

technological change is likely to be more difficult and costly, because the benefits of investment 

in those technologies is smaller, due to smaller remaining potential for abatement. 

7.2.4 Experience Curves and Learning by Doing

What is known as “learning by doing” or “learning curve impacts” has also made it 

possible to achieve greater emissions reductions than had been feasible earlier, or reduce the 

costs of emissions control relative to original estimates. Learning curve impacts can be defined 
7-21

generally as the extent to which variable costs (of production and/or pollution control) decline as 

firms gain experience with a specific technology. This type of change corresponds to case 4 in 

the discussion of the ways technological change can affect the MACC that appeared earlier. Such 

impacts have been identified to occur in a number of studies conducted for various production 

processes. These impacts would manifest themselves as a lowering of expected costs for 

operation of technologies in the future below what they may otherwise have been. For example, 

Rubin et al. 2004 show that capital costs of Flue gas desulphurization (FGD) and selective 

catalytic reduction (SCR) systems have decreased over time as a result of research and

development activities and learning by doing, among other factors, and that failing to account for 

these technological dynamics can lead to incorrect estimates of future regulatory costs.

Rubin et al. (2012) also note that when technologies succeed, costs tend to fall over time. 

They offer the example of post-combustion SO2 and NOx combustion systems. After an increase 

in costs during an initial commercialization period, costs decreased by at least 50 percent over 

the course of two decades. Table 9.5 in the 1997 Ozone NAAQS RIA summarizes historical and 

projected “progress ratios” for existing technologies. These ratios show declining costs over 

time, due to learning by doing, economies of scale, reductions in O&M costs, and technological 

improvements in manufacturing processes. There are other discrete examples, for example prices 

of the catalyst used in operating SCR have dropped dramatically over time. From 1980 to 2005, 

catalyst prices dropped by roughly 85 percent (Cichanowicz, 2010). This follows the “learning 

curve,” which finds that production and implementation costs decrease as learning and repetitive 

use occurs. In addition, Table 3a.7 in Appendix 3a of the 2008 Ozone NAAQS RIA lists controls 

applied to new source types (Case 3). For example, SCR is now applicable to the cement 

manufacturing sector, and SNCR is now applicable to a large number of additional boiler source 

categories. In some cases, more effective controls were determined to be applicable where in 

past cases, less effective controls were applied. For example, for industrial and manufacturing 

incinerators, where previously SNCR was the NOx control technology, SCR was applied in 

2008, increasing the control efficiency from 45 percent to 90 percent.

The magnitude of learning curve impacts on pollution control costs has been estimated for 

a variety of sectors as part of the cost analyses done for the Direct Cost Estimates Report for the 
7-22

Second EPA Section 812 Prospective Analysis of the Clean Air Act Amendments of 1990.6In 

the Report, learning curve adjustments were included for those sectors and technologies for 

which learning curve data was available. For all technologies and industries, a default learning 

rate of 10 percent was adopted based on SAB advice. No adjustments were used for on-road and 

non-road controls. The 10 percent adjustment is a 10 percent cost reduction per doubling of 

emission reductions. The literature supports a rate of up to 20 percent for many technologies 

(Dutton and Thomas, 1984). The impact of this on costs in the Report was to reduce costs of 

local controls in nonattainment areas by 9.9 percent in 2020. 

A typical learning curve adjustment is to reduce either capital or operation and 

maintenance costs by a certain percentage given a doubling of output from that sector or for that 

technology. In other words, capital or operation and maintenance costs will be reduced by some 

percentage for every doubling of output for the given sector or technology. In addition, learning 

by doing may also lead to instances where existing control technologies are found to be 

applicable to additional sources. This corresponds to Case 5 in the discussion in section 7.2.1. 

For example, scrubber technologies applied to electric utilities have been adapted to apply to 

industrial boilers. As a result of this increased applicability due to learning, potential abatement 

has increased at a cost less than the cost threshold. For this RIA, however, we do not have the 

necessary data to properly generate control costs that reflect learning curve impacts.

7.2.5 Using Regional NOx Offset Prices to Estimate Costs of Unknown Emissions Controls

In ozone nonattainment areas, new sources interested in locating in that area and existing 

sources interested in expanding are required to offset any emissions increases. If those emissions 

increases are NOx emissions, the source typically purchases NOx emission reduction credits 

(ERCs), or offsets, from within that particular nonattainment area. Within nonattainment areas, 

offset prices fluctuate because of changes in the available supply of offsets and changes in 

demand for offsets. Offset supply increases when facilities shut down or when they make 

process or other changes that reduce emissions permanently. Offset demand depends on the 

 

6

Industrial Economics, Incorporated and E.H. Pechan and Associates, Direct Cost Estimates for the Clean Air Act 

Second Section 812 Prospective Analysis: Final Report, prepared for U.S. EPA, Office of Air and Radiation, 

February 2011. Available at http://www.epa.gov/cleanairactbenefits/feb11/costfullreport.pdf.
7-23

industrial base in a given area and fluctuates with changes in economic growth. For example, in 

the San Joaquin Valley, in recent years offset prices have increased because of increased oil and 

gas industry development. 

We identified historical NOx offset prices in several nonattainment areas, including the 

San Joaquin Valley and the South Coast in California, Houston, TX, and New York region. For 

the San Joaquin Valley Air Pollution Control District, we collected information on NOx offset 

prices using the California Air Resources Board’s Emission Reduction Offset Transaction Cost 

Summary Reports for 2002 through 20137. For the South Coast Air Quality Management 

District, we collected information on prices for perpetual NOx RECLAIM Trading Credit (RTC) 

for 2003 through 2012 from the Listing of Trade Registrations.

8

 Lastly, we collected 

information on NOx offset prices in the Houston-Galveston nonattainment area for 2010 through 

2013 from the Trade Report9 and the New York-New Jersey-Connecticut nonattainment area 

from 2000 through 2013 from industry representatives. 

Table 7-65 presents the price data we were able to collect for these four regions, adjusted 

to 2011 dollars using the Gross Domestic Product Implicit Price Deflator. The offset prices in 

this table are denominated in units of perpetual tons, or tons per year. The prices constitute 

average of the trades in the regions for the year given.

Table 7-65. Average NOx Offset Prices for Four Areas (2011$) a

Annualized NOx Offset Prices ($/ton)

San Joaquin 

Valley 

California South 

Coast Houston TX New York Region

2000 N/A N/A N/A 25,000

2001 N/A N/A N/A 12,000

2002 36,000 N/A N/A 12,000

2003 28,000 N/A N/A 12,000

2004 25,000 12,000 N/A 12,000

2005 25,000 31,000 N/A 11,000

2006 21,000 163,000 N/A 11,000

2007 21,000 206,000 N/A N/A

2008 48,000 210,000 N/A N/A

 

7 http://www.arb.ca.gov/nsr/erco/erco.htm

8 http://www.aqmd.gov/home/programs/business/about-reclaim/reclaim-trading-credits

9 http://www.tceq.state.tx.us/airquality/banking/mass_ect_prog.html
7-24

2009 58,000 128,000 N/A N/A

2010 62,000 98,000 36,000 N/A

2011 64,000 56,000 N/A N/A

2012 47,000 47,000 N/A N/A

2013 42,000 N/A 97,000 4,000

Average 40,000 106,000 66,000 12,000

Maximum 64,000 210,000 97,000 25,000

a All values are rounded to two significant figures.

The data series for the California regions are more complete than those for Houston and the New 

York region. We are working to obtain more complete data series for future analysis.

To more directly compare offset prices to potential annual costs for unidentified 

emissions controls, we annualized the tons per year prices using the same engineering cost 

equations as used in the main analysis to estimate annualized control cost. We converted the 

offset cost to an annual costs by using the capital recovery factor (CRF) discussed in Section 

7.1.1.

10

 In a capital cost context, the CRF incorporates the interest rate and lifetime of the 

purchased capital. In this instance, although the offsets are perpetual in nature, we assumed a 

lifetime of 20 years in order to make the cost basis more comparable to the control cost 

estimates. Also, we used 7 percent for the interest rate. Table 7-76 presents the average and 

maximum annualized NOx offset prices in 2011 dollars.

Table 7-76. Annualized NOx Offset Prices for Four Areas (2011$)a

Annualized NOx Offset Prices ($/ton)

San Joaquin 

Valley 

California South 

Coast Houston TX New York Region

Average $ 4,000 $ 10,000 $ 6,000 $ 1,000 

Maximum $ 6,000 $ 20,000 $ 9,000 $ 2,000 

a All values are rounded to two significant figures.

From an economic perspective, these offset prices may represent the shadow value of a 

ton of emissions. It is possible that these offset prices could serve as reasonable proxies for the 

costs associated with emissions reductions from unknown controls. The cost information 

 

10 The capital recovery factor formula is expressed as [r*(1+r)^n/(1+r)^n -1]. Where r is the real rate of interest and 

n is the number of time periods. 
7-25

informing the known control strategy traces out an incomplete marginal abatement cost curve in 

that, as discussed in Chapter 4, the controls used in the known control analysis are primarily endof-pipe technologies. The known control estimates for NOx do not account for other forms of 

abatement, switching to lower emitting fuels or increasing energy efficiency, for example. The 

estimates also do not account for institutional or market arrangements that allow firms to buy or 

sell emissions offsets in nonattainment regions with emissions constraints. These voluntary 

exchanges may enable abatement at lower costs than may otherwise be available. The benefit of 

these market transaction data is that the prices are revealed by the interaction of offset supply and 

demand in regions with differentiated characteristics and air quality profiles.

7.2.6 Conclusion

The preceding sections have discussed the ways in which various factors might affect the 

observed marginal abatement costs and the resulting total abatement costs estimated in this RIA. 

Based on past experience with Clean Air Act implementation, the EPA believes that it is 

reasonable to anticipate that the marginal cost of emissions reductions will decline over time due 

to technological improvements and more widespread adoption of previously considered niche 

control technologies as well as the development of innovative strategies.

11

 As the EPA 

continuously improves its data and tools, we expect to better characterize the currently 

unobserved pieces of the MACC. As a result of our consideration of these complexities, we are 

currently unable to quantitatively predict future shifts in the abatement supply curve because 

many factors are intertwined and data are incomplete or highly uncertain. 

7.3 Compliance Cost Estimates for Unknown Emissions Controls

This section presents the methodology and results for the costs of emissions reductions 

from unidentified controls needed for attainment of the alternative ozone standards. As 

discussed in Chapter 4, the application of the modeled control strategy was not successful in 

reaching full nationwide attainment of the alternate ozone standards. Many areas remained in 

nonattainment under all four alternate standard scenarios. Therefore, the engineering costs 

detailed in Section 7.1 represent only the costs of partial attainment. 

 

11 See Chapter 4, Section 4.5 for additional discussion of uncertainties associated with predicting technological 

advancements that may occur between now and 2025.
7-26

7.3.1 Methods

Prior to presenting the methodology for estimating costs for unspecified emission 

reductions in this RIA, it is important to provide information from EPA’s Science Advisory 

Board Council Advisory,12 dated June 8, 2007, on the issue of estimating costs of unidentified 

control measures:

 

12

 U.S. Environmental Protection Agency. June 2007. Advisory Council on Clean Air Compliance 

Analysis (COUNCIL), Council Advisory on OAR’s Direct Cost Report and Uncertainty 

Analysis Plan. Washington, DC.
7-27

812 Council Advisory, Direct Cost Report, Unidentified Measures (charge question 2.a)

“The Project Team has been unable to identify measures that yield sufficient emission 

reductions to comply with the National Ambient Air Quality Standards (NAAQS) and 

relies on unidentified pollution control measures to make up the difference. Emission 

reductions attributed to unidentified measures appear to account for a large share of 

emission reductions required for a few large metropolitan areas but a relatively small 

share of emission reductions in other locations and nationwide. 

“The Council agrees with the Project Team that there is little credibility and hence 

limited value to assigning costs to these unidentified measures. It suggests taking great 

care in reporting cost estimates in cases where unidentified measures account for a 

significant share of emission reductions. At a minimum, the components of the total cost 

associated with identified and unidentified measures should be clearly distinguished. In 

some cases, it may be preferable to not quantify the costs of unidentified measures and to 

simply report the quantity and share of emissions reductions attributed to these 

measures.

“When assigning costs to unidentified measures, the Council suggests that a simple, 

transparent method that is sensitive to the degree of uncertainty about these costs is best. 

Of the three approaches outlined, assuming a fixed cost/ton appears to be the simplest 

and most straightforward. Uncertainty might be represented using alternative fixed costs 

per ton of emissions avoided.”

While we have considered alternative methodologies to predict future abatement supply 

curves, we are currently unable to quantitatively predict future shifts in the supply curve with 

sufficient confidence to use in this RIA. For most NAAQS RIAs prepared during the past five 

years, EPA estimated the costs for unidentified controls using a pair of methodologies: what we 

termed a “fixed cost” approach, following the SAB advice, and a “hybrid” approach that has not 

yet been reviewed by the SAB. We now refer to the fixed-cost approach as the “average cost” 

approach because it more accurately characterizes the concepts underlying the approach. The 

average cost methodology uses an assumed national average cost per ton for unidentified 

controls needed for attainment, as well as two alternative assumed values employed for 

sensitivity analysis. The range of estimates reflects different assumptions about the cost of 

additional emissions reductions beyond those in the modeled control strategy. While we use a 

constant cost per ton of emissions reduction to estimate the costs of the emissions reductions 

beyond known controls, this does not imply that marginal costs are not increasing in needed 
7-28

emissions abatement. Rather, the average cost per ton is intended to capture what might be the 

total costs associated with the abatement of the emissions reductions from unknown controls.

The alternative estimates implicitly reflect different assumptions about the amount of

technological progress and innovation in emission reduction strategies. The average cost 

methodology reflects a view that because no cost data exists for unspecified future strategies, it is 

unclear whether approaches using hypothetical cost curves will be more accurate or less accurate 

in forecasting total national costs of unspecified controls than an average-cost approach that uses 

a range of national cost per ton values.

The hybrid cost methodology assumed increasing marginal costs of control along an 

upward-sloping marginal cost curve. The hybrid cost methodology assumed the rate of increase 

in the marginal costs of abatement is proportional to the weighted ratio of the amount of 

abatement using identified controls to the remaining needed abatement using unidentified 

controls.13 Under this approach, the relative costs of unspecified controls in different geographic 

areas reflected the expectation that average per-ton control costs are likely to be higher in areas 

needing a higher ratio of emissions reductions from unspecified and known controls. However, 

the weight, which reflecteds the anticipated degree of difficulty of achieving needed emissions 

reductions, and the ratios that informed the slope of the marginal abatement cost curve in 

previous NAAQS analyses were strong assumptions that have not been empirically tested.

When used to estimate costs for end-of-pipe technologies, the hybrid methodology 

assumed all emissions reductions come from the highest cost margin of the abatement supply 

curve which, as explained in the previous section, is unlikely for much of the unobserved 

abatement capacity in the present and future. For example, EPA’s control strategy tools largely 

focus on a limited set of emissions inventory sectors, whereas abatement opportunities exist in 

other sectors. When new abatement opportunities are identified in other sectors, they typically 

are not at the higher end of the cost curve. 

For areas needing significant additional emission reductions, much pollution abatement is 

likely needed from sources within regulated sectors that historically have not been intensively 

 

13 See, for example, Section 7.2 and Appendix &.A.2 is the December 2012 RIA for the final PM NAAQS, available 

at http://www.epa.gov/ttn/ecas/regdata/RIAs/finalria.pdf.
7-29

regulated. However, if national standards become more stringent, new regions or firms will be 

added to the regulated domain. These new entrants, with their relatively untapped abatement 

supply, will contribute to an outward shift in abatement supply. The newly regulated regions and 

firms will also face new incentives for technical change and innovation that may lower costs 

over the long run by developing new, more efficient compliance strategies. Because the point of 

departure for the hybrid approach cost curve is based on our current database, which includes 

only existing controls, it will systematically overstate future costs if any cost-reducing 

technological change occurs.

As noted in previous NAAQS analyses, the EPA continues to explore other sources of 

information to inform the estimates of extrapolated costs. For this RIA we examined the full set 

of known controls, examined evidence that suggests that over time new information and data 

emerges that shifts emissions reductions from the unknown to the known category, as well as 

explored whether NOx offset prices can serve as reasonable as reasonable proxies for the costs of 

emissions reductions not identified by current tools. 

Based upon deliberations informing this discussion, the EPA Council’s advice, and the 

requirements of E.O. 12866 and OMB circular A-4, which provides guidance on the estimation 

of benefits and costs of regulations, in this RIA, we follow the Council recommendations by

using an average cost per ton as a central estimate and conduct sensitivity analysis using 

alternative average costs to explore how sensitive total costs are to these assumptions. While the 

average cost methodology has limitations, we agree with the Council that the approach is both 

transparent and strikes a balance between the likelihood that some unidentified abatement would 

arise at lower segments of the identified cost curve while other sources of abatement may come 

at the higher cost margin.

While the known control analysis limited the application of controls with costs above 

$14,000 per ton, we examined the full set of controls available for application in regions needing 

emissions reductions. The MAC curves from this analysis are presented above in Section 7.1. 

For NOx controls, a total of 1.22 million tons of reductions are available, and about 1.18 million 

of these tons are available for less than $15,000 per ton. The known reductions available for less 

than $15,000 per ton represent about 96 percent of the total known reductions in areas needing 
7-30

emissions reductions to meet an alternative standard level. In addition, the average cost per ton 

across all of these abatement opportunities is about $3,400 per ton. As a result, we decided to 

use $15,000 per ton NOx as the main estimate for the extrapolated cost analysis. This assumed 

cost is representative of higher cost controls available in the analysis. The assumed value might

underestimate higher cost controls that regions may apply to meet the alternative standards. 

Alternatively, the assumed value might overestimate the ‘”unobserved” abatement discussed in 

Section 7.2. The results shown in Table 7-4 (per ton cost of NOx reductions for five major NOxreducing rules) and Table 7-7 (annualized per ton cost of NOs offsets in four regions) are 

indicative that the $15,000 per ton assumed average cost may be over-estimating the average 

value of the unidentified abatement.

Because of this uncertainty, we use alternative assumptions of the average cost in the 

Appendix, a first sensitivity analysis using an assumed cost of $10,000 per ton and a second 

sensitivity analysis using an assumed $20,000 per ton.14 This range is inclusive of the annualized 

NOx offset prices observed in recent years in the areas likely to need unknown controls to 

achieve the proposed standard, and if anything, suggests the central estimate of $15,000/ton is 

conservative. EPA requests comments on the methods presented to estimate emission reductions 

needed beyond known controls including the parameter estimate of $15,000/ton.

Because cost changes due to technological change will be available on a national-level, it 

makes sense to use national-level average cost per ton in the primary analysis. However, as 

indicated by the variation in NOx offset prices across regions shown in Table 7-510, regional 

factors may play a significant role in the estimation of control costs. As a result, the EPA will 

continue to explore alternative methodologies and sources of regional information that may make 

the average cost methodology more regionally specific for the RIA for the final rule.

 

14 As shown in Section 7.1, we also performed a similar analysis for VOC controls, which indicated that about 52 

percent of VOC controls available in the analysis for less than $15,000 per ton, with an average of about $12,000 

per ton. While a limited amount of extrapolated VOC emissions reductions were needed for the 60 ppb alternative 

level for the East (41,000 tons), we decided to use the same $15,000 per ton (with $10,000 and $20,000 per ton for 

the sensitivity analysis) for VOC controls for simplicity.
7-31

7.3.2 Unknown Compliance Cost Estimates

Table 7-78 presents the extrapolated control cost estimates for the East and West in 2025, 

except for California for the alternative standards using an assumed average cost of $15,000/ton. 

Values of $10,000/ton and $20,000/ton are used for the sensitivity analyses found in Appendix 

7.2. 

Table 7-87. Extrapolated Control Costs in 2025 by Alternative Standard for 2025 -- U.S., 

except California (millions of 2011$)

Alternative Level Geographic Area Extrapolated Cost

70 ppb

East 2,300

West -

Total 2,300

65 ppb

East 11,000

West -

Total 11,000

60 ppb

East 28,000

West 5,200

Total 34,000

a All values are rounded to two significant figures. Extrapolated costs are based on the average-cost methodology 

using a $15,000/ton assumed average cost.

Table 7-98 presents the extrapolated control cost estimates for post-2025 for California 

across the alternative standards using an assumed average cost of $15,000/ton. 

Table 7-98. Extrapolated Control Costs in 2025 by Alternative Standard for Post-2025 --

California (millions of 2011$)

Alternative Level Geographic Area Extrapolated Costs

70 ppb California 800

65 ppb California 1,600

60 ppb California 2,200

a All values are rounded to two significant figures. Extrapolated costs are based on the average-cost methodology 

using a $15,000/ton assumed average cost.

7.4 Total Compliance Cost Estimates

As discussed throughout this RIA, we present the primary costs and benefits estimates for 

2025. We assume that potential nonattainment areas everywhere in the U.S., excluding 
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California, will be designated such that they are required to reach attainment by 2025, and we 

developed our projected baselines for emissions, air quality, and populations for 2025. 

In estimating the incremental costs and benefits of potential alternative standards, we 

recognize that there are several areas that are not required to meet the existing ozone standard by 

2025. The Clean Air Act allows areas with more significant air quality problems to take 

additional time to reach the existing standard. Several areas in California are not required to 

meet the existing standard by 2025 and may not be required to meet a revised standard until

sometime between 2032 and 2038.15 We were not able to project emissions and air quality 

beyond 2025 for California, however, we adjusted baseline air quality to reflect mobile source 

emissions reductions for California that would occur between 2025 and 2030; these emissions 

reductions were the result of mobile source regulations expected to be fully implemented by 

2030. While there is uncertainty about the precise timing of emissions reductions and related 

costs for California, we assume costs occur through 2038. In addition, we model benefits for 

California using projected population demographics for 2038. 

 Because of the different timing for incurring costs and accruing benefits and for ease of 

discussion throughout the analyses, we refer to the different time periods for potential attainment 

as 2025 and post-2025 to reflect that (1) we did not project emissions and air quality for any year 

other than 2025; (2) for California, emissions controls and associated costs are assumed to occur 

through 2038; and (3) for California benefits are modeled using population demographics in 

2038. It is not straightforward to discount the post-2025 results for California to compare with 

or add to the 2025 results for the rest of the U.S. While we estimate benefits using 2038 

information, we do not have good information on precisely when the costs of controls will be 

incurred. Because of these differences in timing related to California attaining a revised 

standard, the supplementalseparate costs and benefits estimates for post-2025 should not be 

added to the primary estimates for 2025. 

 

15 The EPA will likely finalize designations for a revised ozone NAAQS in late 2017. Depending on the precise 

timing of the effective date of those designations, nonattainment areas classified as Severe 15 will likely have to 

attain sometime between late 2032 and early 2033 and nonattainment areas classified as Extreme will likely have 

to attain sometime between late 2037 and early 2038. 
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Tables 7-9 and 7-10 present summaries of the total national annual costs (known and 

extrapolated) of attaining the alternative standards of 70, 65, and 60 ppb. To calculate total cost 

estimates at a 3 percent discount rate and to include the extrapolated costs in those totals, we 

added the known control estimates at a 3 percent discount rate, where available, to the known 

control estimates at a 7 percent discount rate where the costs could not be determined for the 3 

percent rate; we added these to the extrapolated costs at a 7 percent discount rate. Table 7-109

presents the total national annual costs by alternative standard for 2025 for all of the U.S., except 

California. Table 7-110 presents the total national annual costs by alternative standard for post2025 for California. 

Table 7-109. Summary of Total Control Costs (Known and Extrapolated) by Alternative 

Level for 2025 - U.S., except California (millions of 2011$, 7% Discount Rate)a

Alternative Level Geographic Area Total Control Costs (Known and 

Extrapolated)

70 ppb

East 3,900

West -

Total $3,900

65 ppb

East 15,000

West 400

Total $15,000

60 ppb

East 33,000

West 5,800

Total $39,000

a All values are rounded to two significant figures. Extrapolated costs are based on the fixed-cost methodology.

Table 7-110. Summary of Total Control Costs (Known and Extrapolated) by Alternative 

Level for post-2025 - California (millions of 2011$, 7% Discount Rate)a

Alternative Level Geographic Area

Total Control Costs 

(Known and 

Extrapolated)

70 ppb California 800

65 ppb California 1,600

60 ppb California 2,200

a All values are rounded to two significant figures. Extrapolated costs are based on the fixed-cost methodology.
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7.5 Updated Methodology Presented in this RIA

The cost analysis presented in this chapter incorporates an array of methodological and 

technical updateschanges that the EPA has adopted since the previous review of the ozone 

standards in 2008 and proposed reconsideration in 2010. The updates to models, methods, and 

data are too numerous to be able to quantitatively estimate the impact of any of the updates 

individually. Therefore, we present the major updates below qualitatively. Many of these 

changes reflect updates to inputs to the cost analysis, but are discussed here for completeness. 

Below we note the aspects of this analysis that differ from the 2008 RIA as well as the 2010 

reconsideration RIA (U.S. EPA, 2010). A few overarching changes that are worth mentioning: 

the incremental costs and benefits for this analysis are measured from a baseline of the current 

75 ppb ozone standard; in the previous analysis the baseline was the 84 ppb ozone standard. 

Also, the currency year was updated from 2006$ to 2011$.

Emissions and Air Quality Updates

The base year emissions for this analysis are 2011, and the future analysis year is 2025 

(previously the base year was 2002 and the future analysis year was 2020). Key changes in the 

emission estimates include: increased accuracy of stationary source emissions estimates, updates 

in models and Annual Energy Outlook (AEO) projections for mobile sources and EGUs, 

inclusion of oil and gas sector emissions and numerous updates to the nonpoint emissions. In 

addition, from 2002 to 2011 there have been a number of changes in the energy system, cleaner 

mobile sources, and economic changes that have resulted in reduced emissions since the last 

ozone analysis. There are additional federal control programs are included in the emissions

projections to 2025, including Tier 3, MATS, and the Clean Power Plan. 

Air quality monitor design values were updated to reflect 2009 through 2013 air quality

in contrast the 2008 and 2010 analyses which used 2000 through 2004 air quality. As shown in 

Chapter 2 Figure 2-2, ozone design values are generally decreasing over time. For example, the 

figure shows that for the period of years from 2000 through 2004 the 90th percentile 

concentrations ranged from 85.9 to 102.8 ppb; the 75th percentile values for the same period 

ranged from 78.8 to 87.3 ppb. In contrast, the design values for the period of 2009 through 2013 

the 90th percentile concentrations ranged from 77 to 86.2 ppb and the 75th percentile 
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concentrations ranged from 70.8 to 81 ppb. These design values are the basis for future year air 

quality projections. A quick comparison across analyses reveals that in the 2008 analysis 89 

counties were projected to exceed the higher end of the proposed range of 70ppb in the future 

year (2020), while only 9 counties are projected to exceed 70 ppb in this analysis for 2025. The 

same is true for the lower end of the proposed range, in 2008 231 counties were projected to 

exceed 65 ppb and that number has decreased to 68 counties in this analysis.

As emissions decrease in the base year and air quality design values decrease, the result is

a smaller incremental change in air quality needed to meet the revised standards as compared to 

the 2008 and 2010 analyses. The smaller increment needed to achieve attainment also means 

that fewerless controls are needed across a reduced number ofless geographic areas. 

Control Strategy Updates

Many improvements were made in the non-EGU point control measures used in this 

analysis that make the data more accurate and defensible. These changes include: removal of 

incorrect links between control measures and SCCs; updates to cost equations where more 

recent data was available to improve their accuracy; inclusion of information that has recently 

become available concerning known and emerging technologies for reducing NOx emissions; 

and revising costs and control efficiencies from control measures in the dataset based on recently 

obtained information from industry and multi-jurisdictional organizations (e.g., Ozone Transport 

Commission and Lake Michigan Air Directors Consortium). In addition, a different mix of 

known control measures across EGU, mobile, nonpoint and non-EGU point were applied due to 

the recently promulgated rules mentioned above.

Costing methodology updates have occurred since previous ozone analyses, the ‘hybrid’ 

approach was not utilized to estimate costs of emission reductions needed beyond known 

controls. Holding cost methodology constant (average/fixed cost approach), Ffewer emissions

reductions were needed beyond known controls were applied in this analysis (keeping costing 

methodology constant, average cost approach) due to the increased application of known control 

measures mentioned above.
7-36

The above mentioned technical and methodological changes resulted in the lower cost 

estimates in this analysis. The most influential factors on the cost analysis were the lower 

number of exceeding counties and increased data accuracy of the known control measures. The 

effect of fewer exceeding counties is that fewerless emissions reductions are needed, and 

therefore the costs are lower. The effect of additional and lower-cost known control measures 

being applied is a lowering of the emissions reductions needed beyond known controls, which 

are typically the higher cost emissions reductions.

 7.6 Economic Impacts

7.6.1 Introduction

This section addresses the potential economic impacts of the illustrative control strategies 

for the potential alternative ozone standards. The control costs are uncertain for several reasons. 

The controls that the states ultimately choose to implement will likely differ from the illustrative 

control strategies for which costs are estimated in earlier sections of this chapter. The flexibility 

afforded to states by the Clean Air Act also allows them to adopt programs that include design 

elements that may mitigate or promote particular economic impacts based on their individual 

priorities. The cost estimates become more uncertain because of the length of time before they 

will be implemented. By the 2025 and post-2025 time frames, changes in technology, changes in 

implemented regulations, and changes in relative prices will all add to the uncertainty in the cost 

analysis. Finally, the portion of costs that is extrapolated is not allocated to particular sectors.

Economic impacts focus on the behavioral response to the costs imposed by a policy being 

analyzed. The responses typically analyzed are market changes in prices, quantities produced 

and purchased, changes in international trade, changes in profitability, facility closures, and 

employment. Often, these behavioral changes are used to estimate social costs if there is 

indication that the social costs differ from the estimate of control costs because behavioral 

change results in other ways of meeting the requirements (e.g., facilities choosing to reduce 

emissions by producing less rather than adding pollution control devices). 

The potential alternative ozone standards are anticipated to impact multiple markets in 

many times and places. Computable General Equilibrium (CGE) models are designed to address 

such problems. To support the Final Ozone NAAQS of March 2008 (Final Ozone NAAQS 
7-37

Regulatory Impact Analysis), among other rulemakings, the EPA used the Economic Model for 

Policy Analysis (EMPAX) to estimate the market impacts of the portion of the cost that was 

associated with the application of known controls (excluding the extrapolated costs). EMPAX is 

a dynamic computable general equilibrium (CGE) model that forecasts a new equilibrium for the 

entire economy after a policy intervention. While the external Council on Clean Air Compliance 

Analysis (Council) peer review of The Benefits and Costs of the Clean Air Act from 1990 to 

2020(Hammitt 2010) stated that inclusion of benefits in an economy-wide model, specifically 

adapted for use in that study, “represent[ed] a significant step forward in benefit-cost analysis,” 

EPA recognizes that serious technical challenges remain when attempting to evaluate the 

benefits and costs of potential regulatory actions using economy-wide models. Consistent with 

the Council’s advice regarding the importance of including benefit-side effects demonstrated by 

the Benefits and Costs of the Clean Air Act from 1990 to 2020, and the lack of available multiyear air quality projections needed to include these benefit-side effects, EPA has not conducted 

CGE modeling for this analysis. 

However, the EPA recognizes that serious technical challenges remain when attempting to 

evaluate the impacts of potential regulatory actions using economy-wide models. The EPA is 

therefore establishing a new Science Advisory Board (SAB) panel on economy-wide modeling 

to consider the technical merits and challenges of using this analytical tool to evaluate costs, 

benefits, and economic impacts in regulatory development. The EPA will use the 

recommendations and advice of this SAB panel as an input into its process for improving 

benefit-cost and economic impact analyses that are used to inform decision-making at the 

Agency. The panel will also be asked to identify potential paths forward for improvements that 

could address the challenges posed when economy-wide models are used to evaluate the effects 

of regulations.

The advice from the SAB panel formed specifically to address the subject of economywide modeling will not be available in time for this analysis. Given the ongoing SAB panel on 

economy-wide modeling, and the uncertain nature of costs, this section proceeds with a 

qualitative discussion of market impacts. 
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7.6.2 Summary of Market Impacts

Consider an added cost to produce a good associated with the pollution control required to 

reach the alternative ozone standards. Such a good is either one developed for the consumer 

(called a consumption good), or one used in the production of other goods for consumption 

(called an intermediate good). Some goods are both consumption and intermediate goods. First, 

consider the direct impact on the market facing the increased cost. In this case for the market 

facing the increased cost, the price will go up and the amount sold will go down. The magnitude 

of these shifts depends on a number of factors. The greater the unit cost increase relative to the 

price of the good the greater will be the changes. The more responsive a consumer is to a change 

in the price of a consumption good or the more responsive a purchase of an intermediate good is 

the greater will be the changes. For the alternative ozone standards, many goods will have direct 

changes in costs of production. This makes the assumption of isolated markets too simple. With 

multiple intermediate goods affected, then the intermediate goods and consumption goods they 

are used to produce are affected. As fewer intermediate goods and consumption goods are 

purchased at a higher price, other intermediate goods and consumption goods that serve as 

substitutes become more attractive and more are sold at a higher price. All of these market 

changes lead to changes in income, which can lead to changes in purchases of consumption 

goods. Quantities of intermediate goods used to reduce emissions would also change. 

Considering all of these changes, it is not possible to qualitatively conclude the direction of price 

and quantity changes for any single market. Any conclusions about changes in international 

trade, profits, closures, or social cost is impossible in a qualitative analysis.

7.7 Uncertainties and Limitations

The EPA acknowledges several important limitations of this analysis, which include the 

following:

Boundary of the cost analysis: In this engineering cost analysis we include only the impacts to 

the regulated industry, such as the costs for purchase, installation, operation, and maintenance of 

control equipment over the lifetime of the equipment. As mentioned above, recordkeeping, 

reporting, testing and monitoring costs are not included. In some cases, costs are estimated for 

changes to a process such as switching from one fuel to another less polluting fuel. Additional 
7-39

profit or income may be generated by industries supplying the regulated industry, especially for 

control equipment manufacturers, distributors, or service providers. These types of secondary 

impacts are not included in this engineering cost analysis.

Cost and effectiveness of control measures: Our application of control measures reflect 

average retrofit factors and equipment lives that are applied on a national scale. We do not 

account for regional or local variation in capital and annual cost items such as energy, labor, 

materials, and others. Our estimates of control measure costs may over- or under-estimate the 

costs depending on how the difficulty of actual retrofitting and equipment life compares with our 

control assumptions. In addition, our estimates of control efficiencies for the known controls 

assume that the control devices are properly installed and maintained. There is also variability in 

scale of application that is difficult to reflect for small area sources of emissions.

Discount rate: Because we obtain control cost data from many sources, we are not always able 

to obtain consistent data across original data sources. If disaggregated control cost data are 

unavailable (i.e., where capital, equipment life value, and operation and maintenance [O&M] 

costs are not separated out), the EPA typically assumes that the estimated control costs are 

annualized using a 7 percent discount rate. When disaggregated control cost data are available 

(i.e., where capital, equipment life value, and O&M costs are explicit), we can recalculate costs 

using a 3 percent discount rate. In general, we have some disaggregated data available for nonEGU point source controls, and we do not have any disaggregated control cost data for area 

source controls. In addition, these discount rates are consistent with OMB guidance, but the 

actual real discount rates may vary regionally or locally. 

Known control costs: We estimate that there is an accuracy range of +/- 30 percent for nonEGU point source control costs. This level of accuracy is described in the EPA Air Pollution 

Control Cost Manual, which is a basis for the estimation of non-EGU control cost estimates 

included in this RIA. This level of accuracy is consistent with either the budget or bid/tenderlevel of cost estimation as defined by the AACE International.16

 The accuracy for nonpoint 

 

16 AACE International. Recommended Practice No. 18R-97. Cost Estimate Classification System – As Applied in 

Engineering, Procurement, and Construction For the Process Industries. Revised on November 29, 2011. 

Available at http://www.aacei.org/non/rps/18R-97.pdf. 
7-40

control costs estimates has not been determined, but it is likely no more accurate than those for 

non-EGU point source control costs. 

Differences between ex ante and ex post compliance cost estimates: In comparing regulatory 

cost estimates before and after regulation, ex ante cost estimate predictions often overestimate or 

underestimate costs. Harrington et al. (2000) surveyed the predicted and actual costs of 28 

federal and state rules, including 21 issued by the U.S. Environmental Protection Agency and the 

Occupational Safety and Health Administration (OSHA). In 14 of the 28 rules, predicted total 

costs were overestimated, while analysts underestimated costs in three of the remaining rules. In 

EPA rules where per-unit costs were specifically evaluated, costs of regulations were 

overestimated in five cases, underestimated in four cases, and accurately estimated in four cases 

(Harrington et al. 2000). The collection of literature regarding the accuracy of cost estimates 

seems to reflect these splits. The “Retrospective Study of the Costs of EPA Regulations” found 

that several of the case studies17 suggested that cost estimates were over-estimated. However, 

the EPA stated in the report that the small number of regulatory actions covered and data and 

analytical challenges associated with the case studies limited the certainty of this conclusion.

Costs of unknown controls (extrapolated costs): In addition to the application of known 

controls, the EPA assumes the application of unidentified future controls that make possible the 

additional emissions reductions needed beyond known controls for attainment in the projection 

year for this analysis. 

7.8 References 

Brunnermeier, S.B., Cohen, M.A., 2003. Determinants of environmental innovation in US manufacturing industries. 

Journal of Environmental Economics and Management 45, 278-293.

Dutton, J. M., Thomas, A., 1984. Treating Progress Functions as a Managerial Opportunity. Academy of 

Management Review 9(2), 235-247.

Gerard, D., Lave, L.B., 2005. Implementing technology-forcing policies: The 1970 Clean Air Act Amendments and 

the introduction of advanced automotive emissions controls in the United States. Technological Forecasting and 

 

17 The four case studies in the 2014 Retrospective Study of the Costs of EPA Regulations examine five EPA 

regulations: the 2001/2004 National Emission Standards for Hazardous Air Pollutants and Effluent Limitations 

Guidelines, Pretreatment Standards, and New Source Performance Standards on the Pulp and Paper Industry; 

Critical Use Exemptions for Use of Methyl Bromide for Growing Open Field Fresh Strawberries in California for 

the 2004-2008 Seasons; the 2001 National Primary Drinking Water Regulations for Arsenic; and the 1998 

Locomotive Emission Standards.
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Social Change 72, 761-778.

Hammitt, J.K.,2010. Review of the final integrated report for the second section 812 prospective study of the 

benefits and costs of the clean air act. Available at 

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B005D46F1/$File/EPA-COUNCIL-11-001-unsigned.pdf.

Harrington, W., Morgenstern, R.D., Nelson, P., 2000. On the accuracy of regulatory cost estimates. Journal of 

Policy Analysis and Management 19, 297-322.

Jaffe, A., Newell, R., Stavins, R., 2002. Environmental Policy and Technological Change. Environmental and Resource 

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Kneller, R., Manderson, E., 2012. Environmental regulations and innovation activity in UK manufacturing

industries. Resource and Energy Economics 34, 211-235.

Levinson, A. Technology, 2009. International Trade, and Pollution from US Manufacturing. American Economic 

Review 99, 2177-2192.

Popp, D., 2006. International innovation and diffusion of air pollution control technologies: the effects of NOx and 

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Popp, D., Newell, R., 2012. Where does energy R&D come from? Examining crowding out from energy 

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Rubin, E.S., Yeh, S., Hounshell, D.A., Taylor, M.R., 2004. Experience curves for power plant emission control 

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Sargent & Lundy, L.L.C. 2013. IPM Model – Updates to Cost and Performance for APC Technologies, SCR Cost 

Development Methodology. Chicago, IL. Available at http://www.epa.gov/airmarkets/progsregs/epaipm/docs/v513/attachment5_3.pdf.U.S. Environmental Protection Agency (U.S. EPA). 1997. Regulatory Impact 

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of Air Quality Planning and Standards, Research Triangle Park, NC. Available at 

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and Standards, Research Triangle Park, NC. January. Available at <http://www.epa.gov/ttn/ecas/regdata/RIAs/s1-

supplemental_analysis_full.pdf>. 

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Integrated Planning Model. Office of Air Atmospheric Programs, Washington, DC. Available at 

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U.S. Environmental Protection Agency (U.S. EPA). 2014a. Control Strategy Tool (CoST) Documentation Report. 

Office of Air Quality Planning and Standards, Research Triangle Park, NC. Available at 

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Report of Four Case Studies. Available at http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0575.pdf/$file/EE0575.pdf.