7

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CHAPTER 7 : ENGINEERING COST ANA LYSIS AND ECONOMIC I MPACTS

Overview This chapter summarizes the data sources and m ethodologies used to estimate engineering costs of attaining the alternative, more stringent levels for the ozone primary
standard s 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 al ternative 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 un known 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 method ology (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, op erating, 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 va ry 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 re cognizes 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 cos t estimates are limited in their scop e. This analysis focuses on the
emission s reductions needed for attainment of a range of alternative revised standards . The EPA
understands th at some states will incur costs both designing State Implementation Plans (SI Ps) for and implementing new control strategies to meet final revised standard s . However, the EPA7

- 2

does not know what specific actions states will take to design their SIPs to meet final revised
standards

. T herefore
, 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 no t 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 des igning the hypothetical control strategy usi ng 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 a nd
mobile nonroad sources. CoST calculates engineering costs using one of t wo 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 fa ctor 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 use d in these equations may not be readily available or broadly representative across sources within the emissions inventory. The cost equations used in CoST
estimat e 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 proces s heaters

. Information on CoST control measures information, including cost

- per

ton factors and cost equations can be fou nd at www.epa.gov/ttnecas1/cost.htm.

. Costs for selective reduction catalysts (SCR) applied as part of the analysis for reducing NO x at coal

- fired electric generating units (EGUs) were estimated using documentation for the Integrated Planning Model (IPM) ( Sargent & Lundy , 2013).7

- 3

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 emi ssions reduced, emis sions 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 o rder to attain standards in 2025 we as sume 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 an d when they will do it. O ur estimate s 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 calcula ted 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 add itional capital investment in years b eyond
2025 . The EUAC method is discussed in detail in the EPA Air Pollution Control Cost Manual (U.S. EPA, 2003). The controls a pplied 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 estim ates for the known controls i dentified in Chapter 4 that include control technologi es for EGUs, non

- EGU point, nonpoint and mobile

1 T he capital recovery factor formula is expressed as [ r*(1+r)^n/ [ (1+r)^n

- 1]. Where r i s 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) ter ms if calculated in 2011 versus other year dollars, if the other

- year dolla rs are properly adjusted. For this analysis, all costs are reported in real 2011 dollars.7

- 4

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 a ttainment for the alternative ozone standards of 70, 65, and 60 ppb and additional emission reductions beyond kn own controls are needed

.

The EPA evaluated the costs of all known NO x 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 NO x emission reduction, and t hat the bulk of the non

- EGU point source controls were below this cost. Overall, for all NO x c ontrols 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 represen ts 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 NO x emissions
reduction for the non

- EGU po int source controls was applied, to remove the incorrectly applied controls from the analysis. A small number of NO x controls were applied for non

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

co ntrol 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 Calif ornia because there were
no coal

- fired utility boilers without SCR already in place.

W e intended to apply a similar cost cap but inadvertently applied a slightly higher cap of $15,000 per ton of VOC emission reduction. At t he beginning of the analysis we were anti cipating VOC reductions would play a relatively minor role in the analysis so we did not do a7

- 5

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 ac cordingly.

Figure 7

- 1. Marginal Costs for Known NO x Controls for All Source Sectors (EGU, non

EGU Point, Nonpoint, and Nonroad)

See Table s 7

- 1 through 7

- 3 for summar ies 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 rate s

. 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.7

- 6

These numbers reflect the engi neering 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. D iscount rates refer to the rate at which capit al costs are an nualized. 3 A higher discount, or interest, rate results in a larger annualized cost of capital estimate. I t 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 inc luded in this analysis

. Because we obtain control cost data from many sou rces, we are not always able to obtain consistent data across original d ata sources. 4 If 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 explic it) we can recalculate costs using a 3 percent discount rate.

In addition, the EGU control costs we re not estimated for either 3 or 7 percent. The
interest rate used for this analys i s reflects an internal rate of return of 11.51 percent for ret rofit

contro ls 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 th ose control s . For the
alternati ve 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 o f some non

- EGU point source control s at a 3 percent discount
rate, some non

- EGU point source control s 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 estimate s 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 s o cial 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.7

- 7

T able s 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 associate d with the application of known controls,
incremental to t he baseline and using a 7 percent discount rate, are approximately $1.6 b illion for
an alte rnative annual standard of 70 ppb, $4.2 b illion for a 65 ppb alternative standard, and $4.4 billion for a 60 ppb alternative standard. C osts of NO x controls in term s of dollars per ton of
NO x 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, 6 00/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 sec tors combined.

As shown in Tables 7

- 1 through 7

- 3 below, t he 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 o f 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 310 b 310 b

Non

- EGU Point 640 620 c Nonpoint 610 610 d Nonroad 22 22 d Total 1,600 1,600 e

West EGU

- - Non

- EGU Point

- -7

- 8 Geographic Area Emissions Sector Known Control Costs Nonpoint

- - Nonroad

- - Total

- - Total Known Control Costs 1,600 1,600 e

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 t o 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 b y 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 1,500 b 1,500 b Non

- EGU Point 1,100 1,100 c Nonpoint 1,100 1,100 d Nonroad 53 53 d Total 3,800 3,800 e

West EGU 230 b 230 b Non

- EGU Point 86 86 c Nonpoint 87 87 d Nonroad 5.7 5.7 d Total 410 410 e Total Known Control Costs 4,200 4,200 e

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 t o 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 b y 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 1,500 b 1,500 b
Non

- EGU Point 1,200 1,100 c Nonpoint 1,100 1,100 d Nonroad 53 53 d Total 3,800 3,700 e7

- 9 Geographic Area Emissions Sector Known Control Costs

West EGU 400 400 b
Non

- EGU Point 98 97 c Nonpoint 88 88 d Nonroad 5.7 5.7 d Total 590 590 e Total Known Control Costs 4,400 4,400 e

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 t o 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 Es timating Costs for Unknown Controls As described in Chapter 4, the known control measures were applied to EGU, n on

- EGU point, nonpoint (area), and n onroad 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
emission s reductions to attain the alternative standards of 70, 65, and 60 ppb. To complete the analysis, th e EPA then estimated the additional emission s reductions beyond known controls
needed to reach attainment , also referred to as unknown controls. For information on the methodology used to develop the emission s reductions estimates, see Chapter 3

.

The esti mation of engineering costs for unspecified emission reductions needed to reach attainment many years in the future is inherently a difficult task. This is because i t is likely that the abatement supply function will shift out or change shape over time du e 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 no t 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 manufacturi ng sector in recent decades. Based on survey s of approximately 20,000 plants classified in manufacturing industries, T he 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 manufacturing7

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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 chang e 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
invento ry 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 t hese 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, releva nt 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 ho w 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 co sts associated with emissions

5 The Pollution Abatement Costs and Expenditures (PACE) survey collects facility

- level data on pollution abatem ent 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, t he U.S. manufacturing sector spe nt $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. Le vinson (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.7

- 11

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 Cu rves 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 chang es 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 estim ates in section 7.1, the focus w as largely on end

- of

pipe 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 abateme nt, 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” abatem ent supply. An illustrative, hypothetical depiction of an “observed but incomplete” MACC and the “true” underlying MACC is presented in Figure 7

- 2.7

- 12

Figure 7

- 2. Observed but incomplete MACC (solid line) based on known controls

identified by current too ls 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 con struct 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 c ases. For example, in some cases, controls have been developed primarily to address other pollutant emissions, such as SO 2 , but
achieve NOx reductions as a co

- benefit. These controls are well characterized in the CoST database because they have been appl ied for SO 2 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 emi ssions reductions needed for attainment. In addition, there are some controls that have7

- 13

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 provisi ons 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 C oST 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 datab ase. 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 an alysis 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 Contr ols 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 exogen ous 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, a s 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 e arlier 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 stand ards were not included as known controls, even though the RIA acknowledged the potential for these standards to provide7

- 14

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, ma ny 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 NOx

reducing regulations issued between the 1997 and 2008 RIAs had ex ante estimates of costs per

to n 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 th e extent possible, we determined from the RIA for each regulation the projected emissions reductions in 2010 (or the closest year) and by 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 separa te 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/Ton s

NOx Reduced (2010$)
(C = B/A) NOx SIP Call a 1,141 2,515 $ 2,204 Clean Air Interstate Rule b 1,200 $3,034 $2,528 Tier 2 Standards c 1,236 $5,256 $4,253 Heavy Duty Diesel Engines d 403 $4,570 $11,340 Nonroad Diesel e 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 Ai r 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 Requ irements (U.S. EPA, 1999).7

- 15 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 provi ded 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 oz one NAAQS

. Table 7

- 6 4 shows that for these five major re gulations, which account for 4. 1 million tons o f NOx reductions, the expected average cost per ton ranged from about $ 2,2 00 to $1 1 , 3 00 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 exceed expected to be greater than the $10,000/ton value used for un known
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 control s 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) an alytical assumptions made about
the universe of sources that can be controlled. Table 7

- 4 5 provides information about assumptions used in generating the costs of control measures for the 1997, 2008, and 2014 RIAs.

### 7

- 16

Table 7

- 4 5

. 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 re commendations.

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 counti es 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. Co unties 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 th e 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).

NO X 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 Cit y)

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 non

EGU and
, non

- point and small

sources For VOC: 1 ton for point non

EGU 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 non

point 10%

Minimum Emissions Not clearly defined 50 tons for NOx 25 tons for NOx For NOx: 5 tons for point non

EGU, 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 Penetration b Obtained from published reports f rom 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 cu rrent analysis is focused primarily on controlling NOx to meet the alternative ozone standards, with relatively modest VOC control s 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 r esult, 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 T

echnological Innovation and Diffusion C hange
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 anal yses 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 b est representation of a future MACC. MACC in the future can differ from MACC in the present due to technological innovation and diffusion, such as change (either the introduction of new technologies or improvements in effectiveness or applicability of exis ting 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
diffusion change 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 tha n 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 ch ange 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 adopted7

- 19

with much higher marginal costs. However, if t here 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 C ases 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 SO 2 control on boilers
3. Sophisticated new valve seals and leak detection equipment for refineries and chemical plan t s 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 light

duty vehicles; and treatment devices and retrofit technologies for heavy

- duty engines
8. Idle

- reduction technolo gies for engines, including truck stop electrification efforts
9. Increasing m arket penetration of gas

- electric hybrid vehicles and clean er fuels
These technologies were not commercially available two decades ago, and some were not
even in existence. Yet toda y, all of these technologies are on the market, and many are widely employed. Several are key compo nents of major pollution regulatory programs.

As Brunnermeier and Cohen (2003 ) demonstrate, there is a positive correla tion, other things held constant, between environmental innovations (measured as the number of relevant7

- 20

environmental patent applications) and specific regulations imposed on an industry (measured in terms of the frequency of government compliance inspecti ons). 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 applicatio ns) 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 SO 2 and
NO x . The study was performed using patent data from the United States, Japan, and Germany. Popp found that more stringent regulation enhan ced 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

sav i ngs resulting from research and development successes ( Popp and Newell 20 12 )

. In a study
that links energy

- rel a ted 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 resul t s is due to firm

- level prof i t

- maximi z ing behavior rather than constraints on the magnitude of research an d development resources. Alternatively
, Kneller and Manderson (2012) find evidence in the United Kingdom that environment

- related research and development resulting from more stringent regulati o n may crowd out other research and development
activities but that environment

- r e lated 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 a dditional 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 Do ing 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 emission s control relative to original estimates. Learning curve impacts can be defined7

- 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 technologic al 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 i mpacts would manifest themselves as a lowering of expected costs for operation of tech nologies 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, a m ong 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 SO 2 and NO x combustion systems. After an increase in costs during an initial commercialization period, costs decreased by at least 50 percent ov er the course of two decades. Table 9.5 in the 1997 Ozone NAAQS RIA summarize s 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 control s applied to new source types (C ase 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 applica ble 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 the7

- 22

S econd EPA Section 812 Prospective Analysis of the Cle an Air Act Amendments of 1990. 6 In
the R eport, 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 b ased 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 (Dutto n 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 ce rtain 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 C ase 5 in the discussion in section 7.2.1. For example, scrubber technologies applied to electric utilit ies 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 properl y 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 interest ed in expanding are required to offset any emissions increases. If those emissions
increases are NO x emissions, the source typically purchases NO x emission reduction credits (ERCs), or offsets, from within that particular nonattainment area. Within nonat tainment 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 an d 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/co stfullreport.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 NO x 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 infor mation on NO x offset prices using the California Air Resources Board’s Emission Reduction Offset Transaction Cost Summary Reports for 2002 through 2013 7 . For the South Coast Air Quality Management District, we collected information on prices for perpetual NO x 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 Report 9 and the New Yo rk

- New Jersey

- Connecticut nonattainment area from 2000 through 2013 from industry representatives.

Table 7

- 6 5 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

- 6 5

. Average NO x 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.html7

- 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 a nnual 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 th e capital recovery factor (CRF) discussed in Section
7.1.1

. 10 In a capital cost context, t he CRF incorporates the inte rest 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

- 7 6 presents the aver age and
maximum annualized NO x offset prices in 2011 dollars.

Table 7

- 7 6

. 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. Th e cost information

10 T he capital recovery factor formula is expressed as [r*(1+r)^n/(1+r)^n

- 1]. Where r i s 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 end

of

- pipe technologies. The known control es timates for NO x 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 emissio ns 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 result ing total abatement costs estimated in this RIA.
B ased 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 imp rovements 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 co sts 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 techno logical 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 A dvisory 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. Washing ton, 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 red uctions 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

a ssociated 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

a nd 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 confi dence 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 t hat has not yet been reviewed by the SAB. We no w refer to the fixed

- cost approach as the “aver age 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 needed7

- 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 b e 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 us ing unidentified
controls. 13 Under this approach, the relative costs of unspecified controls in different geographic
areas reflect ed the expectation that average per

- ton control costs are likely to be higher in areas needing a higher ratio of emission s red uctions from unspecified and known controls. However, the weight, which reflect ed s 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

assume d 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 opportun ities 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 n eeded 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 u ntapped 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 effic ient 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 ne w 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 curr ent 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 Co uncil recommendations b y using a n average cost per ton as a central estimate and conduct sensitivity analysis using
alternative average cost s 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 t his 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 $1 5,000 per ton represent about 96 percent of the total known reductions in areas needing7

- 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 NOx

reduc ing rules) and Table 7

- 7 (annualized per ton cost of NO s 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 alte rnative 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 reduc tions 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

- 5 10 , regional factors may play a significant role in the estimation of control costs. As a result, t he EPA will continue to explore alternative methodologies and sources of regional information that may make
the average cost methodology more region ally 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 al ternative 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

- 7 8 presents the ex trapolated 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 a nalyses found in Appendi x 7.2.

Table 7

- 8 7

. Extrapolated Control Costs in 2025 by Alternative Standard for 2025

-- U.S.,

except California (millions of 201 1$)

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

- 9 8 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

- 9 8

. Extrapolated Control Costs in 2025 by Alternative Standard for Post

- 2025

--

Californi a (millions of 201 1$)

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, w e present the primary costs and benefits estimates for
2025. We assume that potential nonattainment areas everywhere in th e U.S., excluding7

- 32

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 p otential 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 exi sting 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 imp lemented by
2030. W hile there is uncertainty about the precise timing of e missions 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 f or 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 p roject 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

. I t is not stra ightforward to discount the post

- 2025 results for C alifornia to compare with
or add to the 2025 results for the rest of the U.S. W hile we estimate benefits using 2038 information, we do not have good information on precisely when the costs of control s wil l be
incurred

. Because of these differences in timing related to Ca lifornia attaining a revised standard, the supplemental separate 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 li kely have to attain sometime between late 2037 and early 2038.7

- 33

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

- 10 9 presents the total national annual costs by alternative standard for 2025 for all of the U.S., except
California. Table 7

- 1 1 0 presents the total national annual costs by alternative standard for post

2025 for Californi a.

Table 7

- 10 9

. 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 5,8 00 Total $39,000

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

- cost methodology.

Table 7

- 1 1 0

. 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.7

- 34

7.5 Updated Methodology Presented in this RIA The cost analysis presented in this chapter incorporates an array of methodological and
technical updates changes 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, bu t 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 ch anges that are worth mentioning :
t he 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 emi ssions 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. T here are a dditional federal control programs are included in the emission s 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 200 4 air quality . As shown in Chapter 2 Figure 2

- 2, ozone design values are generally decreasing over tim e

. For example, the figure show s that for the period of years from 2000 through 2004 the 90 th percentile
concentrations ranged from 85.9 to 102.8 ppb; the 75 th 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 90 th percentile concentrations ranged from 77 to 86.2 ppb and the 75 th percentile7

- 35

concentrations ranged from 70.8 t o 81 ppb

. These design values are the basis for future year air quality projections. A quick comparison across anal yses reveals that in the 2008 analysis 89 counties were projected to exceed the higher end of the proposed range of 70ppb in the future

yea r (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 a nalysis.

As emissions decrease in the base year and air quality design values decrease, the result is
a smaller increment al 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 fewer less controls are needed across a reduced number of less geographic areas

.
Control Strategy Updates

Many improvements were made in the non

- EGU point control measures used in this

a nalysis 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 informati on that has recently become available concerning kno wn 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

- jur isdictional organizations (e.g., Ozone Transport
Commission and L ake 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 rul es 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)
, F f ewer emission s reductions were needed beyond known controls were applied in this analysis (keeping costing methodology constan t, average cost approach) due to the increased application of known control
measures mentioned a bove.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 c ontrol measures. The effect of fewer exceeding counties is that fewer less emission s 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 emission s redu ctions 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 alternat ive 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 ch apter. 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 unc ertain 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. F inally, 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, qua ntities 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 est imate 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 ar e 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 NAAQS7

- 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 dynam ic 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 challenge s 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 multi

year 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 chall enges 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 challen ges 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 ana lyses 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 economy

wide 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 procee ds with a qualitative discussion of market impacts.7

- 38

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 increas ed 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 wi ll 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 intermed iate 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, w hich 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 ch anges 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 anal ysis , which include the following:

Boundary of the c ost a nalysis : 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 th e 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. Addition al7

- 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 s uch 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 esti mates 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 r ate : B ecause 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 maintenanc e [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 ar e explicit), we can recalculate costs using a 3 percent discount rate. In general, we have some disaggregated data available for non

EGU point source controls, and we do not have any disaggregated control cost data for area source controls. In addition, th ese 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 non

EGU point source control costs. This level o f 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/tender

level of cost estima tion 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 rule s, 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 regar ding 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 studies 17 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 Sta tes. 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 P ollutants and Effluent Limitations Guidelines, Pretreatment Standards, and New Source Performance Standards on the Pulp and Paper I ndustry; Critical Use Exemptions for Use of Methyl Bromide for Growing Open Field F resh Strawberries in California for the 20 04

- 2008 S easons; the 2001 National Primary Drinking Water Regulations for Arsenic; and the 1998 Locomotive Emission Standards.7

- 41

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 http://yosemite.epa.gov/sab/sa bproduct.nsf/9288428b8eeea4c885257242006935a3/1E6218DE3BFF682E852577F B005D46F1/$File/EPA

- COUNCIL

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- unsigned.pdf.
Harrington, W., Morgenstern, R.D., Nelson, P., 2000. On the accuracy of regulatory cost estimates. Journal of Policy Analysis and Manageme nt 19, 297

- 322.
Jaffe, A., Newell, R., Stavins, R., 2002. Environmental Policy and Technological Change. Environmental and Resource Economics 22, 41

- 70.
Kneller, R., Manderson, E., 2012. Environmental regulations and innovation activity in UK manufacturing industries. Resource and Energy Economics 34, 211

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Levinson, A. Technology, 2009. International Trade, and Pollution from US Manufacturing . American Economic Review 99 , 2177

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. Popp, D., 2006. International innovation and diffusion of air pollution control technologies: the effects of NO x and SO 2 regulation in the US, Japan, and Germany. Journal of Environmental Economics and Management 51, 46

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Popp, D., Newell, R., 2012. Where does energy R&D come from? Examining crowding out from energy R& amp;D. Energy Economics 34, 980

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Rubin, E.S., Yeh, S., Hounshell, D.A., Taylor, M.R., 2004. Experience curves for power plant emission control technologies. International Journal of Energy Technology and Policy 2, 52

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Sargent & Lundy, L.L.C. 2013. I PM Model

– Updates to Cost and Performance for APC Technologies, SCR Cost Development Methodology. Chicago, IL. Available at http://www.epa.gov/airmarkets/progsregs/epa

ipm/docs/v513/attachment5_3.pdf .U.S. Environmental Protection Agency (U.S. EPA). 1997. Regulatory Impact Analyses for the Particulate Matter and Ozone National Ambient Air Quality Standards and Proposed Regional Haze Rule. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Available at http://www.epa.gov/ttn/oarpg/naaq sfin/ria.html

. Sterner, T., Turnheim, B., 2009. Innovation and diffusion of environmental technology: Industrial NOx abatement in Sweden under refunded emission payments. Ecological Economics 68, 2996

- 3006.
U.S. Environmental Protection Agency (U.S. EPA). 2003. EPA Air Pollution Control Cost Manual. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Available at http://epa.gov/ttn/catc/products.html#cccinfo

. U.S. Environmental Protection Agency (U.S. EPA). 2008. Final Ozone NAAQS Reg ulatory Impact Analysis. Office of Air Quality Planning and Standards, Research Triangle Park, NC. Available at http://www.epa.gov/ttn/ecas/regdata/RIAs/452_R_08_003.pdf

.

U.S. Environmental Pro tection Agency (U.S. EPA). 2010 . Regulatory Impact Analysis (RI A) for the Proposed Reconsideration of the ozone National Ambient Air Quality Standards (NAAQS). Office of Air Quality Planning and Standards, Research Triangle Park, NC. January. Available at <http://www.epa.gov/ttn/ecas/regdata/RIAs/s1

- supplemental_analy sis_full.pdf>.

U.S. Environmental Protection Agency (U.S. EPA). 2013. Documentation for EPA Base Case v.5.13 Using the Integrated Planning Model. Office of Air Atmospheric Programs, Washington, DC. Available at http://www.epa.gov/powersectormodeling/BaseC asev513.html

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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 http://www.epa.gov/ttnecas1/cost.htm

.
U.S. Envir onmental Protection Agency (U.S. EPA). 2014b. Guidelines for Preparing Economic Analyses, Chapter 6. Available at http://yosemite.epa.gov/ee/epa/eed.nsf/webpages/Guidelines.html#download

. U.S. Environmental Protection Agency (U.S. EPA). 2014c. Retrospectiv e Study of the Costs of EPA Regulations: A Report of Four Case Studies. Available at http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE

- 0575.pdf/$file/EE

0575.pdf

.