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 Choose a consistent discount rate

A single discount rate should be used when comparing costs and benefits that occur in the same year. 

Because of limited cost data, the EPA uses a 7 percent discount rate to estimate costs for most 

technologies. In some of the analysis the EPA calculates costs using a 3 percent discount rate for the 

control technologies that have sufficient data. The benefits are reported using a 3 percent and 7 

percent discount rate. The EPA argues that this approach follows OMB guidelines. However, while 

OMB advocates the use of 3 percent and 7 percent discount rates, this does not mean that different 

discount rates should be used in a single estimate of net benefits. In fact, it is not possible to interpret 

net benefits that are estimated using different discount rates when the benefits occur in the same year 

as the costs. Furthermore, it is not appropriate to report cost estimates for known controls when a 

share of those costs has been estimated using a 3 percent discount rate, and the remainder of those 

costs have been estimated using a 7 percent discount rate. See Arrow et al. (2012) for a discussion of 

the problem of using different discount rates when costs and benefits occur in the same year, in the 

context of the social cost of carbon. For these reasons, commenters invite discussion with EPA about 

producing internally consistent cost estimates using a 3 percent discount rate and reporting net 

benefits that do not mix discount rates.

 For the final RIA quantify, to the extent possible, the sources of the differences between the 2010 

RIA and the 2014 RIA

There will likely be considerable public interest in the difference between the net benefits estimated 

in 2010 and 2014. The EPA should provide a quantitative analysis of the reasons why the estimated 

costs and benefits differ between the 2010 RIA and the 2014 RIA. Whereas the 2010 RIA indicated 

negative net benefits under a wide range of assumptions for 70 ppb, the 2014 RIA indicates positive 

net benefits for 70 ppb. The 2014 RIA reports net benefits of $2.5 to $9.1 billion (7 percent discount 

rate) if the standard were set at 70 ppb rather than the current standard of 75 ppb. The 2010 RIA 

reports a change in net benefits of -$24 to $16 billion if the standard had been set at 70 ppb rather 

than 75 ppb (to facilitate the comparison between the two RIA’s, throughout this discussion we 

compare 70 ppb and 75 ppb, noting that the baseline in the 2010 RIA was 84 ppb). Thus, the 2010 

RIA indicated that there was a significant likelihood that net benefits of 70 ppb would turn out to be 

negative, when compared with 75 ppb. In contrast, the range of net benefits in 2014 does not include 

levels below zero. 

Lower estimated costs explain most of the change between 2010 and 2014. In 2014, the estimated 

annual cost of achieving 70 ppb from a baseline of 75 ppb is $3.9 billion. In 2010, the additional 

annual cost of achieving 70 ppb, compared to 75 ppb, is $11.4 billion to $19.4 billion (using the two 

endpoints of the reported cost ranges). Thus, estimated costs have fallen by 66 to 80 percent. In 

contrast, the estimated annual benefit is $6.4 to $13 billion (7 percent discount rate) in the 2014 RIA, 

and -$4.5 to $27.5 billion in the 2010 RIA. Thus, the range of benefits has narrowed between 2010 

and 2014, and on average expected benefits are just a few billion dollars lower in 2014 than in 2010.

In Section 7.5 of the RIA, the EPA provides four explanations for the lower 2014 cost estimates:

1. Changing the baseline starting point from 84 to 75 ppb, reducing the amount of emissions 

reductions needed and associated costs of attainment
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2. Shifting the baseline year from 2020 to 2025, allowing for more time for Federal measures to 

work and for areas to reach attainment

3. Identifying additional known controls that are less expensive than unknown controls

4. Fewer counties exceeding the alternative standards analyzed, and fewer emissions reductions are 

needed for attainment

Reason 1 does not explain the lower cost estimate that was calculated above, because these 

calculations compared 70 and 75 ppb. Reasons 2-4 must therefore explain this reduction, and the EPA 

could quantify the relative importance of these explanations. For example, it would be straightforward 

(although it would take some work) to compare concentration levels in 2020 and 2025 to assess the 

importance of changing the baseline year. A decomposition of the cost change from the 2010 RIA to 

the 2014 RIA into these three categories would help reconcile the notable difference between these 

quantitates.

 Provide confidence intervals for ozone benefits estimates in the Executive Summary

The short-term health benefits from lower ozone levels are based on results from two studies, Smith 

et al. (2009) and Zanobetti and Schwartz (2008). Although the results of these studies are consistent 

with the results from earlier studies, there remains statistical uncertainty about the size of the 

mortality effect, as well as uncertainty about the relevance of these results for the specific ozone 

concentrations considered in this rulemaking. Chapter 5 contains a lengthy discussion of the 

uncertainty associated with the health benefits estimates, but the Executive Summary and Chapter 5 

should present a clearer summary of the implications of both types of uncertainty.

Although Zanobetti and Schwartz report a statistically significant effect of ozone concentrations on 

mortality, there is some statistical uncertainty. The study reports a 0.32 percent decrease in mortality 

for each 10 ppb decrease in summer 8-hour ozone concentrations, with a 95 percent confidence 

interval of (0.20, 0.43). The analysis is based on pooled data from 48 cities; but the city-by-city 

analysis shows almost no significant effects, with the exceptions of New York City, Phoenix, and 

Boulder. In Washington, DC there is a statistically significant mortality decrease associated with a 

10-ppb increase. To make the statistical uncertainty more transparent, the 95 percent confidence 

intervals reported in Table 5-19 should also be reported in the Executive Summary. 

There is also some ambiguity about the relevance of the statistical results for low ozone 

concentrations. For example, Zanobetti and Schwartz do not completely document the range of ozone 

levels that statistically identify the estimated mortality effects, but the study mentions that Los 

Angeles has the highest 75th-percentile value of 8-hr ozone, with a value of 75.9 ppb. This value does 

not preclude the possibility that the mortality effect is being estimated primarily from higher ozone 

levels—i.e., levels that would be irrelevant to a reduction from 75 ppb to 70 ppb or lower. Put another 

way, if the statistical evidence is based entirely on data from cities that had higher concentrations, the 

findings of this paper could, in principle, be consistent with an absence of mortality effects caused by 

a reduction from 75 ppb to 70 ppb. In the draft proposed rule, the EPA discounts epidemiological 

studies for precisely this reason—that the effects estimated in these studies may be based on ozone 

variation at levels above those being considered for the new standards. This apparent inconsistency 

could be reconciled by re-estimating the mortality effects using the same data as were used in the 

referenced studies, except restricting the samples to observations with ozone concentrations expected 

to occur under hypothetical standards of 70 or 75 ppb. This does not necessarily require dropping all 

observations with concentrations above these levels, but it could require dropping some of the 
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extremely high values; a more thorough analysis would be necessary for determining the appropriate 

sample. Although the proposed rule must be published very soon, the EPA could complete this 

analysis in time for the final rule, and could announce its intention to do so in the proposed rule.

 In the final rule RIA, conduct an ex post analysis of Tier 3 emissions reductions

Tier 2 and 3 vehicle standards, as well as sulfur requirements for fuels, are expected to substantially 

reduce NOx emissions from on-road light-duty vehicles. The RIA for Tier 2 projects annual NOx 

emissions reductions of 3 million tons by 2020 and the Tier 3 RIA projects an additional 329,000 tons 

of NOx reduced annually by 2030 (the Tier 3 figures include reductions from both light-duty and 

heavy-duty vehicles). For comparison, light-duty NOx emissions in 2000 were 3.5 million tons, and 

the Tier 2 RIA predicted 2020 NOx emissions of 4.5 million tons in the business-as-usual case. 

These projected emissions reductions account for a large share of the reductions needed to achieve 75 

ppb. The EPA estimates that, to achieve 75 ppb, total NOx emissions would have to decrease from 13 

million tons in 2011 to 7.4 million tons in 2025—i.e., a decrease of 5.6 million tons. To achieve 70 

ppb in 2025, NOx emissions would have to decrease by an additional 640,000 tons. The EPA projects 

on-road vehicle emissions reductions to account for 70 percent of the NOx emissions reduction 

needed to meet 75 ppb, and 63 percent of the emissions reductions needed to meet 70 ppb. 

Furthermore, light-duty vehicles would account for most of the on-road emissions reductions. Thus, 

Tier 2 and Tier 3 play crucial roles in meeting ozone standards of 70 or 75 ppb. 

The projected emissions reductions under Tier 2 and Tier 3 depend on numerous assumptions, such as 

future vehicle miles traveled and the turnover of the vehicle stock (because the tailpipe standards 

apply only to new vehicles). In principle, these assumptions could yield emissions projections that 

turn out to be lower or higher than actual emissions. If Tier 2 and Tier 3 cause greater emissions 

reductions than projected, for instance, meeting any given ozone standard would be less costly than 

suggested by the RIA.

Given the importance of light-duty emissions reductions for meeting ozone standards, an ex post 

analysis of the vehicle tailpipe standards would be valuable. Such an analysis could help improve the 

quality of the cost estimates for future PM and ozone NAAQS rulemakings, which will similarly rely 

on forecasts of vehicle emissions. Such an analysis would be consistent with Executive Order 13563, 

which requires agencies to conduct “periodic review of existing significant regulations.” The 

proposed rule could announce EPA’s intention to conduct such a retrospective analysis, and solicit 

comment on the data that would be needed.

 Provide empirical support for the application of known controls

The known controls are applied in proportion to emissions from each sector. This assumption is 

simple and it could be validated by comparing with actual historical State Implementation Plans for 

past NAAQS.

 Discuss the effect of lower ozone standards on PM concentrations

Reducing NOx emissions to meet ozone standards also reduces PM concentrations because NOx is a 

precursor to PM. Consequently, the EPA includes the associated health benefits of lower PM 
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concentrations when estimating the benefits of lower ozone concentrations. The inclusion of cobenefits is consistent with recent RIAs, such as the RIA for the proposed Clean Power Plan.

However, it may be inappropriate to attribute some of these PM decreases to the ozone standard. 

Instead, as below, a reduction in NOx emissions to meet the ozone standards makes it easier to attain 

the PM NAAQS. The NOx emissions reductions therefore result in lower abatement costs of reaching 

the PM NAAQS, and not greater health benefits.

The PM standards that were finalized in 2012 reduce the primary standard from 15 to 12 micrograms 

per cubic meter. To meet the standards, states with non-attainment areas could require businesses to 

adopt a variety of technologies that would ultimately reduce PM concentrations, such as requiring 

technologies that reduce NOx emissions from power plants and technologies that reduce direct PM 

emissions like fabric filters. The estimated annual cost of meeting the lower PM standards is $53 to 

$350 million, and some of the costs include the adoption of technologies that reduce direct PM 

emissions from point sources other than power plants.

To the extent that states would otherwise use direct PM technologies to meet the PM standards, the 

ozone RIA may mischaracterize the effects of lower ozone standards on PM concentrations and 

public health. The average cost of PM technologies such as electrostatic precipitators range from 

roughly $50 to $1,000 per metric ton of PM emissions. Consider a hypothetical area that is in nonattainment for the new PM standards and that would be in non-attainment for an ozone standard of 70 

ppb, but would be in attainment for 75 ppb. Suppose that, if the ozone standards were left at 75 ppb, 

the state would require sources in that area to install direct PM control technologies, at a cost of $50 

to $1000 per metric ton of PM emissions. Alternatively, consider what happens if the ozone standards 

are reduced to 70 ppb. The same state would require NOx emitters to install NOx control technologies 

sufficient to attain the ozone standard. But, these NOx technologies would also reduce PM levels, 

which would effectively mean that the state does not have to impose such stringent PM technology 

requirements than if the NOx technologies had not been installed. Consequently, the lower ozone 

standard causes ozone levels to fall, but does not cause PM levels to fall by as much as reported in the 

RIA. Therefore, the PM co-benefits would not be as large as reported. However, because the ozone 

standard would obviate the need to install direct PM technologies, there would be real cost savings 

that are also not included in the RIA.

In short, by not taking the 2012 PM standards into account, the ozone RIA overstates the health 

benefits of tighter ozone standards, and simultaneously understates the cost savings. The first effect 

causes net benefits to be over-estimated, and the second causes net benefits to be under-estimated. 

Because the direct PM technologies are highly cost effective (meaning that the value of the health 

benefits from lower PM exceeds the cost of PM abatement), the magnitude of the under-estimate in 

the ozone RIA likely exceeds the over-estimate, meaning that net benefits in the ozone RIA are 

probably over-estimated. The ozone RIA should acknowledge and discuss these issues, and ideally 

account for them in the RIA for the final standards.

 Report net benefits by region

Figure ES-2 shows that only a few counties would exceed an ozone standard of 70 ppb. These 

counties (excluding the California counties with extreme non-attainment status) are located in Texas 

and the New York City area. If a lower standard is adopted, the non-attainment group would expand 

to include scattered counties in other regions, such as the Southwest and Midwest. 
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Because non-attainment areas are not geographically dispersed, the costs of reducing the ozone 

standard from 75 ppb to 70 ppb would likely be heavily geographically concentrated, as indicated in 

Chapter 4. In the simulation the EPA uses to estimate compliance costs, standards below 75 ppb are 

met by applying technologies within a certain fixed region surrounding the non-attainment areas only. 

The benefits of lower standards may be more widespread than costs, however, because of ozone 

transport. Application of the NOx abatement technologies near the non-attainment areas would affect 

ozone and PM levels in other areas, including areas that already meet the PM and ozone standards. 

The reductions in ozone and PM concentrations would generate health benefits in those additional 

regions.

Because the costs may be more geographically concentrated than the benefits, the EPA should 

provide some geographic information about the costs, benefits, and net benefits. Of course, the 

geographic variation of the ozone benefits could be illustrated, but not the PM co-benefits. 

 In the final rule RIA, validate projections of economic activity, vehicle use, and population

The forecasted emissions depend on future economic activity, vehicle use, and population, all of 

which are very difficult to predict. Future immigration patterns, for example, will influence the 

population levels in the non-attaining counties, and various immigration policies could alter these 

flows dramatically. It would be instructive to see how the computed health benefits change under 

different assumptions about immigration.

More broadly, given the uncertainty in predicting these future outcomes and their centrality in 

computing the benefits, it would be helpful to present estimates of the confidence intervals 

surrounding these estimates. Chapter 5 contains a long discussion of uncertainty about the 

concentration-response function and other issues in the academic literature that affect how the EPA 

estimates the effect of ozone concentrations on health. However, projections of population, VMT, and 

economic activity play an important role in estimating the overall health benefits because a) they 

determine the extent of pollution reductions that will be needed to meet each level of the proposed 

NAAQS and b) they affect the spatial distribution of the population, which in turn affects benefits 

because ozone concentrations do not decrease uniformly across regions.

Vehicle miles travelled (VMT), for instance, has been declining in recent years despite earlier 

projections that they would continue to rise. These sorts of forecast errors are unavoidable, but a 

measure of how this uncertainty is contributing to uncertainty in benefits would make the resulting 

values easier to interpret. Like the uncertainty in the PM health benefits, it would be straightforward 

to measure or estimate this form of uncertainty based on a statistical model predicting VMT as a

function of factors such as vehicle fuel economy, income, population, etc. (see, for example, research 

by Ken Small and others cited in the CAFE RIA). Error in the VMT forecast would then have to be 

propagated through the analysis, requiring say several hundred runs to generate confidence intervals. 

As a first step, it may be desirable to assess the effect of VMT uncertainty and 

immigration/population uncertainty independently of other sources of uncertainty.

 In the final rule RIA, provide a clearer sense of the nature of unknown costs by including 

examples of previously unknown technologies and conducting a simple case study
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The EPA defines two categories of emissions control technologies: “known” and “unknown.” The 

results show that unknown controls play an increasingly important role as the standards are reduced 

from 70 ppb to 60 ppb and the known controls are exhausted. The unknown controls also account for 

all of the emissions reductions for California. Furthermore, the EPA argues in Chapter 7 that 

technological change will cause new technologies to emerge that are not currently “known”. 

This has generated public criticism that the RIA relies on future technological change that is not 

guaranteed to happen, and fueled public misunderstanding of the term “unknown,” which suggests to 

the uninitiated that all of these technologies are literally unknown and yet to be invented. The 

importance of the unknown controls in total costs creates two issues: first, the cost estimates are 

highly uncertain; and second, following from the first, the cost estimates are much more exposed to 

public criticism than if all of the costs were known.

The EPA provides a few examples of unknown controls that could be used in practice, such as fuel 

switching, but the EPA does not provide any sense of whether these approaches would be 

quantitatively important. To strengthen this argument, the EPA could provide further discussion and 

analysis to address these issues in the final rule. First, the EPA could describe technologies that are 

now known (i.e., at the time of the rulemaking) that were unknown in the 2010 RIA. Table 7-4 partly 

addresses this issue, but the analysis could be sharper. For example, many of the technologies that are 

described in the Tier 3 RIA were unknown technologies in the 2010 RIA. The EPA could quantify the 

NOx emissions reductions that these technologies would yield under Tier 3. This quantity may turn 

out to be a significant share of the unknown costs in the previous RIA. This comparison of Tier 3 

reductions and previously unknown reductions would provide a clearer sense to the public that the 

term unknown technologies does not mean that the mobile source technologies do not exist, just that 

they have yet been part of an existing federal regulation. So, in other words, if the Tier 3 technologies 

were somehow known at the time of the previous NAAQS RIA, the share of known costs would have 

been much larger, and the overall cost estimates much smaller, than was presented in that RIA. EPA 

makes this point qualitatively, but providing some quantitative estimates would help the public 

understand the practical meaning of the term unknown technologies.

Second, the EPA could provide a simple case study of a hypothetical policy that would use 

“unknown” controls. For example, suppose a hypothetical state introduces a vehicle retirement 

program that aims at removing from the road older cars that have higher NOx emissions rates. The 

EPA could estimate the costs of such a policy using analysis reported in the existing literature, which 

would avoid the need for an extensive and time-consuming cost-benefit analysis. This would provide 

some additional information for the public about the possible costs of implementing state SIPs, and 

reduce the mystery surrounding the term unknown technologies. 

 Clarify the implications of failing to account for NOx abatement technologies that would be used 

to meet other NAAQS

Chapter 1 states that “The baseline for this analysis does not assume emissions controls that might be 

implemented to meet the other NAAQS for PM2.5, NO2, or SO2.” Presumably, the baseline also does 

not include full attainment with the other NAAQS. Therefore, under this assumption, the baseline 

accounts for NOx abatement technologies that would be used to meet various national rules that are 

included in the baseline, such as the Clean Power Plan. But abatement technologies that would be 

used to meet the other NAAQS, whose costs and benefits have been estimated in previous 

rulemakings, would still be available to meet the ozone NAAQS. The argument provided in Chapter 1 
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for omitting these technologies from the baseline is that the data and modeling in the previous 

analyses are outdated.

At first glance, this assumption would appear to cause costs to be under-estimated because 

technologies that are assumed to be available for meeting the ozone standards would in fact already 

have been used to meet other standards. However, if those technologies were accounted for in the 

baseline, then the NOx emissions reductions from those abatement technologies would also be 

accounted for, in which case less additional abatement would be needed to meet the ozone standards. 

Therefore, assuming that the other NAAQS are not included in the baseline, these two effects would 

cancel and omitting these technologies from the baseline would not affect the cost estimates. The RIA 

should explain this point to avoid confusing the public and also clarify that the other NAAQS are not 

included in the baseline for the purposes of estimating benefits, either.

 Provide evidence of the quality of the fit between ozone concentrations and NOx emissions

Chapter 3 describes a process for estimating the relationship between NOx emissions, VOC 

emissions, and ozone concentrations. Ozone sensitivity factors were estimated using the modeled 

response of ozone to changes in NOx and VOC emissions. The changes in NOx emissions needed to 

meet 60, 65, and 70 ppb were calculated using these sensitivity factors.

According to the equations in Chapter 3, the sensitivity factors are constants, in which case the ozone 

concentration is a linear function of NOx emissions. The discussion in Chapter 2 points out that NOx 

emissions have highly nonlinear effects on ozone concentrations, however. Therefore, the approach to 

estimating the emissions reductions needed to meet the lower ozone standards must be taken as an 

approximation. That’s fine given the modeling challenges to relaxing this assumption, but can the 

EPA provide some supporting evidence that the approximation is reasonable in the neighborhood of 

the relevant NOx emissions and ozone concentrations, and for the specific areas that are predicted to 

be in non-attainment?

 Executive Summary

Please present more detailed cost tables from Chapter 7 in this section.

Suggest deleting “supplemental” in characterizing CA analysis.

 Chapter 5

Would you clarify exactly what air quality modeling was done to assess the reduction in 

secondary PM formation?

To what extent were the income elasticities changed from previous rulemakings?

5-53 – 5-54: We suggest that using Graff Zivin and Neidell (2012) to assess worker productivity 

may not be appropriate without understanding the generalizability of the study results. We 

suggest that EPA use the previous discussion regarding the nascent literature on the effect of 

ozone on worker productivity.
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 Chapter 7

Is EPA able to separate unknown emissions reductions into reductions from unknown sources 

but potentially known technology (e.g., area sources) vs unknown technology?

Has EPA considered incorporating existing regulations that might potentially govern area 

sources (e.g., energy efficiency regulations for ovens in commercial bakeries)?

Please explain why the average cost of known controls for EGUs is declining from 70 ppb to 65 

ppb?

Please explain why the average cost of known controls for non-EGU point sources and area 

sources appear to be largely constant with increasing stringency. Shouldn’t they be increasing?

Why is $15,000/ton a reasonable estimate for unknown emission costs when there are known 

technologies with costs that are significantly higher than $15,000/ton (e.g., $90,000/ton)? We 

Suggest articulating this point further. Does $15,000/ton depend on EPA’s assumption about 

likely compliance behavior?

Suggest articulating learning by doing literature into learning by doing literature and technology 

diffusion literature (around 7-20).

Suggest acknowledging that there are opportunity costs associated with regulation directed 

R&D vs the counterfactual R&D (around 7-18).

7-1: Please report costs associated with monitoring provisions of this NPRM.

7-9: Was PACE a pilot study scale survey?

 Chapter 8

8-14: Wouldn’t economic growth also be reflected in the income growth as well?

 Chapter 9

Section 9.2: Please include the monitoring related burden in this section.

Table 9-1: Please provide a footnote clarifying what “other or multiracial” constitutes.

Table 9-2: Please provide a footnote clarifying what “low income” constitutes.

 Chapter 10

Table 10-1: Are the results labor impacts per SCR? If so, please clarify. Also given the 

magnitude of the effects and the speculative nature of the inquiry, the commenter suggests 

deleting the upstream effects.

Table 10-3: Are the results labor impacts per boiler? If so, please clarify.

Table 10-4: Are the results labor impacts per cement kiln? If so, please clarify.

 Background Ozone 

(2-11) 2.4 See suggested edit in red. Natural sources of ozone precursor emissions such as wildfires, 

prescribed fire, lightning, and vegetation can lead to ozone formation by chemical reactions with 

other natural sources. 
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(2-16) The additional 2007 modeling confirms that background ozone, while generally not 

approaching levels of the ozone standard, can comprise a considerable fraction of total seasonal mean 

ozone across the U.S (EPA, 2014c). 

Some commenters note that it is relevant for the public and areas potentially affected by the standards 

for assessing the confidence in the model and calculation effort to know the areas that don’t meet this 

generality. Please add a map to that reflects this fact.

(2-17) The Policy Assessment for the Review of the Ozone National Ambient Air Quality Standards

(US EPA, 2014c) concluded that “anthropogenic sources within the U.S. are largely responsible for 

4

th highest 8-hour daily maximum O3 concentrations” based on modeling using a 2007 base year and 

the two distinct modeling methodologies described above. 

Some commenters note that 2007 is not an NEI year and that it would be helpful to provide a 

description of the approach taken for wildfire, prescribed fire and agricultural emissions in this

assessment. 

(2-17) These infrequent episodes usually occur in relation to a specific event, and occur more often in 

specific geographical locations, such as at high elevations or wildfire prone areas during the local dry 

season. 

Some commenters note that as the wildfire contribution is not constant and increasing significantly, 

the potential for these assumptions to change would be appropriate to document here.

(3A-1) Biogenic and fire emissions were held constant for all emissions cases and were based on 

2011-specific data. Table 3-1 shows the modeled 2011 and 2025 NOX and VOC emissions by sector.

Please specify what types of fire is being discussed here. Based on the commenter’s understanding of 

the RIA modeling, this used the 2011 National Emission Inventory and included the full fire 

inventory comprised of wildfire, prescribed fire and agricultural burning for both base case 

background and held constant as background for the 2025 projection. The Fires category is included 

in the Table 3-1 which we assume reflects controllable sources as we don’t see the biogenic category 

there. Why is fire in this table? The trends in increasing wildfire and temperature appear not to be 

considered here. With these trends as well as general temperature effect on ozone production stated 

elsewhere, please add some discussion of the potential of these factors leading to uncertainty in the 

outcome and background. Increasing temperature will also affect biogenic emissions as well and 

should be considered as increased uncertainty which could lead to chronic nonattainment. 

(3A-1) A summary of total Anthropogenic NOx and VOC emissions by region from the 2025 base 

case and explicit emissions control cases is given in Table 3-3. 

In the table it is footnoted that fire emissions are omitted. Won’t this emission exclusion affect the 

background? That will affect the costs of meeting the control scenario. 

(3A-55) A variety of influences including transport from California and other regional transport, crossborder pollution from Mexico, and exceptional events (e.g., wildfires and stratospheric intrusions) 

could contribute to ozone concentrations at the 26 sites. Each of these contributors is described further 

below, along with the Clean Air Act provisions that offer varying degrees of regulatory relief. The 

commenter’s understanding of the RIA modeling is that it used the 2011 National Emission Inventory 
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and included the full fire inventory comprised of wildfire, prescribed fire and agricultural burning for 

both base case background and held constant as background for the 2025 projection. If this is correct, 

this sentence should include discussion of this assumption. 

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

to 2014 (7-12) 7.2.2 

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

controls that were unknown at the time of the analysis, evidence suggests that over time new 

information on exogenous factors affecting baseline emissions and emissions controls becomes 

available that can shift emissions reductions from the unknown to the known category. However, that 

is limited as the standard gets closer to background levels in each county. The closer the standard is 

to background levels, the less ability state planners will have to maintain attainment with the 

standards. For those counties out of attainment primarily due to background levels, it will become 

progressively more difficult to achieve compliance with known or unknown controls due to lack of 

sources to regulate.

(7-18) One factor to consider is the degree to which a particular sector is likely to be close to 

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

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

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

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

As mentioned earlier, the tighter the standard is relative to background levels, the less 

potential technological advances will provide to state planners as they develop 

implementation plans to demonstrate how they will come into compliance with the standards. 

In some cases, when the contribution of sources to emission levels in excess of the standard 

is insignificant compared to background levels from natural sources (wildfires and prescribed 

fires) or from international emissions, the assumption of unknown controls to achieve 

compliance may be unrealistic. In those cases, chronic nonattainment with the standards may 

become the norm.

(7-23) See suggested edit in red... As the EPA continuously improves its data and tools, we 

expect to better characterize the currently unobserved pieces of the MACC. In addition, EPA 

will include consideration of the number of identifiable sources that may be controlled 

relative to background levels as a contravening factor in how the MACC may be shifted 

outwards with technological change. The costs of control (known or unknown) will become 

steeper the closer the standards is set relative to uncontrollable background levels. 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. 

(7-25) See suggested edit in red....The hybrid cost methodology assumed increasing 

marginal costs of control along an upward-sloping marginal cost curve. The hybrid approach 

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 
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abatement using unidentified controls.1 Under this approach, the relative costs of unspecified 

controls in different geographic areas reflect the expectation that average per-ton control 

costs are likely to be higher in areas needing a higher ratio of emission reductions from 

unspecified and known controls. However, the weight, which reflects 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. Until now, EPA has not considered the relationship 

between the degree to which the standard is set relative to the background levels in a county. 

While similar, that is slightly different than our previous consideration of how many tons of 

reductions were needed from unknown relative to known controls. We now weight the 

hybrid costs on the percentage of emissions from known sources relative to background. The 

logic being that in nonattainment counties that have a high percentage of emissions coming 

from uncontrollable background sources relative to all other sources, the costs of control will 

be extremely high.

(7-27) See suggested edit in red....Because of this uncertainty, we use alternative 

assumptions of the average cost in the Appendix, a first sensitivity analysis using an assumed 

cost of $10,000 per ton and a second sensitivity analysis using an assumed $20,000 per ton.2

Then using the ratio of all known source contributions relative to uncontrollable background 

sources, we adjust the $20,000 per ton upper bound upwards to reflect the difficulty some 

counties may encounter in meeting attainment when there simply are not very many 

controllable sources relative to uncontrollable sources. 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 

15K is conservative. 

(7-31) See suggested addition below in red....4. Emission Reductions Needed Beyond 

Known Controls: Less emission reductions needed beyond known controls applied in this 

analysis (keeping costing methodology constant, fixed cost approach) due to the increased 

application of known control measures mentioned above.

5. Proportion of known sources to uncontrollable background levels: for the upper bound 

the proportion of known source contributions to uncontrollable background sources was 

considered as a means to reflect the difficulty in demonstrating attainment when the standard 

is set close to the background levels in that county.

 

1 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.

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

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

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

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

the sensitivity analysis) for VOC controls for simplicity.
Summary of Interagency Working Comments on Draft Language under 

EO12866/13563 Interagency Review. Subject to Further Policy Review.

12

 Can EPA please clarify why there is not much difference between the health benefit values at 3% 

and 7%?

 When EPA discusses the proposed decision on the secondary NAAQS, rather than phrasing the 

proposed level as “within a range identical to the proposed range for the primary standard,” why 

doesn’t EPA instead refer to the numeric range (65 to 70)? This may strengthen the agency’s 

case that the proposed secondary standard reflects a careful step-by-step analysis of whether a 

given 8-hour level (65-70) can achieve the appropriate seasonal/cumulative average outcome and 

may help avoid the misimpression that EPA is trying to achieve a pre-determined outcome of not 

setting a separate secondary standard. 

 Page 5-5 (top of page) – EPA states that causal and likely causal relationships were quantified 

with confidence. It may be helpful to provide a few sentences explaining how “suggestive” 

relationships were handled in analysis. Additionally, in Table 5-3, it would improve transparency 

and readability if EPA were to provide basic information about the causality statement (causal,

likely causal, suggestive) determined for each health effect. 

 Section 8, Comparison of Costs and Benefits, seems to focus largely on costs and is very light on 

a discussion of health benefits. Section 8.4 in particular, Key Observations from the Analysis, 

does not include any information about health benefits. Minor comment: every page in Section 8 

is number page 8-14. This should be corrected.