Exxon Mobil Corporation 

13501 Katy Freeway 

Houston, Texas 77079-1398 

 

 

October 09, 2007 

Comments on EPA’s Proposed “National 

Ambient Air Quality Standards for Ozone” 

72 Fed Reg. 37,818 (July 11, 2007) 

VIA ELECTRONIC FILING

U.S. Environmental Protection Agency 

Air and Radiation Docket 

EPA West Building, Room 3334 

1301 Constitution Avenue, NW 

Washington, DC 20460 

Attn: Docket No. EPA-HQ-OAR-2005-0172 

Dear Sir or Madam: 

ExxonMobil appreciates the opportunity to submit comments on the Environmental Protection 

Agency's (EPA or the Agency) July 11, 2007 proposed rule to revise the Ozone National Ambient 

Air Quality Standards (NAAQS). 

ExxonMobil operates seven refineries in the U.S., six of which we own and one in which we hold a 

50 percent ownership interest. These seven refineries have a combined crude oil processing 

capacity of approximately 2.0 million barrels per day. ExxonMobil operates around 30 marketing 

terminals that distribute gasoline, diesel fuel and other petroleum products, and about 12,000 

branded retail outlets in 46 states and the District of Columbia. ExxonMobil is also a major 

chemical producer in the U.S. with 15 manufacturing facilities. A number of these facilities are 

located in areas designated as nonattainment for the current ozone standards. We, therefore, 

have considerable interest in and will be impacted by the manner in which the Agency reviews and 

revises the ozone standards. 

A detailed and careful review of the scientific evidence as reflected in the Criteria Document (CD), 

Staff Paper (SP) and in this proposed rule confirms that the existing primary and secondary 

standards for ozone are requisite to protect public health with an adequate margin of safety and to 

protect welfare in accordance with the requirements of Section 109 of the Clean Air Act (CAA). 

The following is a summary of our detailed comments, which are provided in the attachment. 
U.S. Environmental Protection Agency 

Docket No. EPA-HQ-OAR-2005-0172 

October 9, 2007 

Page 2

Primary Standard

The new clinical, epidemiology, and toxicology studies published since 1997 do not identify 

new health effects and largely confirm the uncertainties present in the 1997 Review. 

• In the 1997 Review, EPA relied primarily upon clinical studies, the most reliable form of health 

evidence. In this 2007 Review, EPA incorrectly claims coherence, consistency, and 

robustness in the epidemiology evidence to justify greater reliance on this form of evidence. 

Based primarily on the epidemiology data, EPA now concludes that health effects are likely 

occurring below the current standard and that the standard should be revised. Given the 

many confirmed weaknesses in the epidemiology data, EPA is incorrect in relying on this data 

in making judgments about the presence of health effects below the current standard. The 

epidemiology data present in this review do not show greater consistency and coherence than 

the data in the 1997 Review. 

• The 1997 Review examined several clinical studies at 0.08 ppm and higher. Only two new 

clinical studies since 1997 (Adams (2002, 2006)) examined health effects below 0.08 ppm. 

The results of these studies do not support the presence of health effects below 0.08 ppm. As 

described in our detailed comments, EPA’s unpublished re-analysis of the author’s original 

study employs an inappropriate statistical test and focuses on a small subset of the data from 

the study. EPA should not cite this re-analysis until it has been published and peer reviewed. 

• The 1997 Review concluded that time-series epidemiology studies were too uncertain to 

establish a causal relationship of health effects from exposure to ozone at levels equivalent to 

the current 8-hour standard. New time-series studies remain unacceptably uncertain due to 

inadequate controls for confounders (including other pollutants such as particulate matter), low 

and highly unstable relative risk results, and the significant likelihood of exposure 

misclassification. New evidence since 1997 confirms that ambient monitors are a poor 

surrogate for personal exposure. Given the many problems of time-series studies, they should 

not be used in making either scientific or policy-related conclusions regarding the health 

effects of ozone. 

• In the 1997 Review, EPA indicated that panel or field epidemiology studies suffered from many 

of the same exposure-related limitations as the time-series studies. In this 2007 Review, EPA 

overlooks these and other limitations, including the use of less accurate, self-reported 

measures of effects. Most of the field studies cited by EPA as significant rely on ambient 

monitors and self-administered respiratory measurements. These problems render the field 

studies unreliable for determining if effects occur below the current standard, or any other 

threshold level. 

• The 1997 Review evaluated the potential risk of increased hospital admissions. Since 1997, 

only a few new studies on hospital admissions have been published. Most of the new studies, 

including those conducted in areas with high ozone levels (Linn et al. (2000), Los Angeles), 

report no statistically significant increase in hospital admissions attributed to ozone. 

Therefore, the new data on hospital admissions do not support a revision in the primary 

standard. 
U.S. Environmental Protection Agency 

Docket No. EPA-HQ-OAR-2005-0172 

October 9, 2007 

Page 3

• The scientific evidence included in this review on acute mortality does not show causality from 

exposure to ozone. Contrary to EPA statements in the CD and SP, the results of the ozone 

mortality studies are not consistent, but are highly heterogeneous and sensitive to the choice 

of statistical models used. EPA’s data show that 89 of 95 single-city mortality estimates were 

not statistically significant after EPA applied an averaging adjustment, and up to one third 

were negative (incorrectly implying ozone health benefits) before the adjustment was applied. 

The use of ambient monitors, with their very poor correlation to personal exposure for ozone, 

raises the possibility that the reported acute mortality associations may in fact be due to other 

pollutants. 

EPA’s risk assessment for acute mortality is not supportable scientifically and should be 

removed from the final rule. 

• Because of the many weaknesses in the acute mortality epidemiology studies, the data are too 

uncertain to be used to derive risk estimates. In its letter of June 5, 2006, Clean Air Science 

Advisory Committee (CASAC) raised serious concerns with the utility of acute mortality 

estimates based on time-series studies. EPA should remove the acute mortality risk 

assessment from the proposed rule because it suggests greater certainty in the science than 

is now present.

• EPA’s risk assessment on acute mortality overstates any potential risk due to the selective 

reliance on: (1) positive studies with high risk coefficients while ignoring negative studies and 

studies with lower risk coefficients; (2) single-pollutant model results when results from copollutant models are available; (3) use of linear exposure models to extrapolate risks down to 

unrealistic and unachievable levels of ozone (15 to 35 ppb); and (4) use of an arbitrary and 

unachievable low ozone background level. EPA should revise its risk estimates to include an 

integrated uncertainty analysis that addresses major sources of uncertainty. 

• EPA’s assumption that most mortality health benefits will occur below ozone levels of 40 ppb 

lacks scientific support and is at odds with the results of clinical studies. A detailed analysis by 

CRA International of EPA’s risk assessment, included in the attached comments, shows that 

the current standard provides very significant protection against both potential mortality and 

morbidity risks at ozone levels down to 70 ppb. 

EPA’s reliance on an arbitrarily low policy-relevant background inflates the risk estimates 

and is not supportable. 

• EPA’s estimate of ozone policy-relevant background (PRB) is inappropriate because it: 

(1) excludes all anthropogenic-related U.S. emissions including agricultural-related emissions; 

and (2) excludes all anthropogenic emissions from Canada and Mexico. Given that states 

cannot eliminate all anthropogenic emissions and do not have control over emissions from 

Canada and Mexico, EPA’s definition and application of policy-relevant background is not 

realistic or supportable.

• In the 1997 Review, EPA relied on monitoring data from pristine areas of the country in 

determining ozone background concentrations from non-anthropogenic sources and 

international transport outside North America. In this 2007 Review, EPA is now relying on 

modeled estimates of background concentrations, even though EPA concedes that the 

modeled concentrations fail to accurately predict maximum ozone levels – which are key to 
U.S. Environmental Protection Agency 

Docket No. EPA-HQ-OAR-2005-0172 

October 9, 2007 

Page 4

assessing the role of ozone background concentrations. CASAC appropriately questioned the 

basis for EPA’s revised estimate of ozone background concentrations in its March 2007 letter. 

• EPA has also failed to take into account the growing international transport of emissions from 

outside North America. Recent data indicate that NOx emissions from Asia have grown by 

over 50 percent since 2001, the year EPA uses to model ozone background levels. 

Projections by independent researchers suggest that significant increases will continue well 

into the future as the result of growth in vehicle and stationary source emissions from China, 

India and other major emitting countries. EPA’s failure to adequately account for this growth 

further suggests that EPA has underestimated ozone background levels. 

• CRA International’s analysis also shows that raising the background concentration to levels 

used in the 1997 Review would eliminate over 95 percent of the estimated mortality and 

respiratory health benefits from tightening the ozone standard. 

The current primary standard is requisite to protect public health with an adequate margin 

of safety. 

• Section 109 of the CAA requires the Administrator to set a primary standard, the attainment 

and maintenance of which, in the judgment of the Administrator, are requisite to protect the 

public health with an adequate margin of safety. EPA’s task is to establish standards that are 

“neither more nor less stringent than necessary” to protect public health; this does not mean 

zero-risk, but rather at a level that reduces risk sufficiently so as to protect public health with 

an adequate margin of safety. Whitman v. American Trucking Ass’ns, Inc., 531 U.S. 457, 473 

(2001). 

• In exercising his judgment to revise the existing NAAQS, the Administrator must provide a 

reasonable analysis for the change. Specifically, EPA must explain why its earlier judgment 

regarding what is requisite to protect public health or welfare no longer governs. To reverse its 

position in the face of precedent that is not persuasively distinguished is arbitrary and 

capricious. Motor Vehicle Mfr.’s Ass’n v. State Farm Mut. Auto. Ins. Co., 463 U.S. 29, 42 

(1983) (presumption “against changes in current policy that are not justified by the rulemaking 

record”). 

• Given that EPA’s estimate of health risks from minor changes in pulmonary function are lower 

than they estimated in 1997 and the uncertainty surrounding the results of the health risks 

from epidemiology studies has remained the same, EPA cannot persuasively justify why it 

must depart from its 1997 decision that the current standard is requisite to protect public 

health. 

Secondary Standard

 

EPA does not have sufficient information at this time to establish a cumulative seasonal 

standard for the secondary ozone standard. 

• Vegetation studies indicate that cumulative indices, such as the W126, are more biologically 

relevant for estimating vegetation effects than the current 8-hour standard. However: 
U.S. Environmental Protection Agency 

Docket No. EPA-HQ-OAR-2005-0172 

October 9, 2007 

Page 5

- EPA has not presented sufficient information to conclude that there are vegetation effects 

from exposure to ozone at the current standard. An examination of key studies cited by 

EPA indicates that the reported seasonal or mean ozone exposures could include multiple 

days with 8-hour concentrations above the current standard. In addition, field studies often 

fail to control for potential confounders, such as reduced soil moisture. 

- EPA has failed to resolve key uncertainties from the 1997 Review over the effects of ozone 

at the current standard. These include field testing the effect of daily maximum 8-hour 

ozone concentrations on plant response, and assessing the impacts of attaining the 8-hour 

standard in rural and remote areas. These uncertainties remain in this review. 

- EPA has proposed the use of an alternate cumulative seasonal metric, the W126, without 

adequately accounting for the frequency of peak ozone concentrations. Failure to account 

for peak values, known to be a key determinant of plant response, is a significant oversight. 

As a result of this omission, there is no way of knowing whether the W126 standard affords 

a requisite level of plant protection. 

• Inconsistent use and reporting of measurement data and occasional reference to unavailable 

information has limited public and scientific review of the basis for EPA’s proposed secondary 

standard. In future reviews, EPA should increase transparency by ensuring that all key 

studies and analyses are made available, and by allowing the public greater access to 

workshop proceedings and technical support documents. 

Conclusion

In conclusion, in making a policy decision that is based on the science and considers all of the 

factors discussed above, including the continued uncertainty in the science, the likelihood of no 

additional health benefits from tightening the standard, and the overall acceptability of the level of 

risks posed by the existing standard, the Administrator should judge the current primary standard 

to be requisite to protect the public health with an adequate margin of safety. Furthermore, EPA 

does not have sufficient information at this time to establish a cumulative seasonal standard for the 

secondary ozone standard. 

If you would like to discuss these comments in more detail, please contact me at 281-870-6112. 

 

Respectfully submitted, 

 

 Doug Deason 

 Environmental Advisor 

 Downstream and Chemical SH&E 

 

 

cc: Dr. David J. McKee, Health and Environmental Impacts Division, 

 Office of Air Quality Planning and Standards, U.S. EPA 

 (mckee.dave@epa.gov) 
Exxon Mobil Corporation Comments 

Detailed Comments of 

ExxonMobil Corporation on EPA’s Proposed Rule on 

the Ozone National Ambient Air Quality Standards 

72 Fed. Reg. 37,818 (July 11, 2007) 

Submitted October 9, 2007 

DETAILED COMMENTS REGARDING THE PRIMARY STANDARD 

FOR OZONE 

Overview

 New evidence since the 1997 review of the ozone standard has not changed EPA’s 

fundamental understanding of the health effects from exposure to ozone. Indeed, the clinical 

evidence suggests that the risks of adverse effects at the current standard may be less than 

assumed in the 1997 Review. Major uncertainties regarding causality and risk levels remain in 

the epidemiology evidence. 

 In exercising his judgment to revise the existing NAAQS, the Administrator must provide 

a reasonable explanation for the change. Specifically, EPA must explain why its earlier 

judgment regarding what is “requisite” to protect public health or welfare should no longer 

govern. Given that scientific evidence shows that health risks are less than they had been 

understood to be, EPA cannot persuasively say why it must depart from its 1997 decision that the 

current standard is requisite to protect public health. 

 Moreover, the scientific evidence shows that the risks that do exist should not require 

tightening of the standard at this time; any tightening would not be requisite to the protection of 

public health.

I. The New Data Since the 1997 Review Do Not Show an Increase in Risks or 

Additional Health Benefit From Tightening the Standard. 

 EPA incorrectly claims that there are new health effect endpoints of concern in this 

review that are caused by exposure to ozone that were not present in the 1997 Review. In the 

proposed rule, EPA repeatedly claims “new” health effects data on ozone that were not present 

when EPA last reviewed the ozone standards in the 1997 review: 

The Criteria Document provides new evidence that notably enhances our 

understanding of short-term and prolonged exposure effects, including 

effects on lung function, symptoms, and inflammatory effects reported in 

controlled exposure studies. These studies support and extend the 

findings of the previous Criteria Document. There is also a significant 

body of new epidemiological evidence of associations between shortterm and prolonged exposure to O3 and effects such as premature 

mortality, hospital admissions and emergency department visits for 

respiratory (e.g., asthma) causes. 
Exxon Mobil Corporation Comments - 2 

(72 Fed. Reg. 37,818, 37,827 (July 11, 2007)). 

The Criteria Document prepared for this review emphasizes a large 

number of epidemiological studies published since the last review with 

these and additional health [effects] endpoints, including the effects of 

acute (short term and prolonged) and chronic exposures to O3 on lung 

function decrements and enhanced respiratory symptoms in asthmatic 

individuals, school absences, and premature mortality. 

(72 Fed. Reg. at 37,825). 

 These claims are incorrect. With the exception of new endpoints for which causality has 

not been demonstrated (acute mortality and school absences), EPA does not cite any “new” 

health endpoints that were not associated with ozone exposure in 1997. Causality for acute 

mortality remains highly controversial at best, and in our opinion, unproven. Furthermore, EPA 

did not find in the 2006 Criteria Document (CD) and 2007 Staff Paper (SP) that school absences 

are not causally linked to ozone exposure. (See generally, 2006 at 7-65; SP at 3-88, Table 5-2 at 

5-10). Aside from these unproven health effects, EPA does not cite any “new” health effects 

endpoints that were not associated with ozone exposure in 1997. Furthermore, as discussed later 

in these comments, the evidence concerning the concentration of ozone associated with 

producing these effects has also not changed since 1997. 

In 1996 and in the 1997 Ozone NAAQS Final rule decision record, EPA examined an 

extensive amount of data and concluded that a wide array of health effects were attributed to 

short-term (1-3 hrs.) and long-term (6-8 hrs.) exposure to ozone at levels as low as 0.08 ppm. 

The acute health effects induced by short-term exposures to ozone concentrations as low as 

0.12 ppm generally occur while subjects are engaged in heavy exercise. They include pulmonary 

function responses, transient respiratory symptoms, effects on exercise performance, increased 

airway responsiveness, increased susceptibility to respiratory infection and transient pulmonary 

inflammation. The studies used to support these health effects were conducted in both healthy 

people and those with pre-existing diseases, including asthma, chronic obstructive pulmonary 

disease (COPD), and heart disease (see 1996 CD, table 7-2). In the 1996 CD, EPA also 

presented data on differential pulmonary function response due to gender (Table 7-3), hormonal 

factors (Table 7-4) and age (Table 7-5). EPA also presented data on repeated exposure to ozone 

(Table 7-6). EPA reported that similar health effects were observed following prolonged 

exposures to ozone at concentrations as low as 0.08 ppm and at lower levels of exercise than for 

short-term exposures. (1996 EPA Staff Paper (SP) at 24 and 62 Fed. Reg. 38,855, 38,859 (July 

18, 1997)). EPA noted that some of the studies reporting effects at 0.08 ppm included Follinsbee 

et al. (1991, 1994), Gong et al. (1986), Hazucha et al. (1992), Horstman et al. (1990, 1995), 

Horvath et al. (1991), Koren et al. (1988, 1989, and 1991), Lin et al. (1994), and McDonnell et 

al. (1991). 

In 1996, EPA also reported on the results of epidemiology and field studies that evaluated 

impacts on emergency room visits, hospital admissions, and mortality (CD, chapter 7). EPA’s 

risk assessment in 1996 included evaluation of pulmonary function decrements, lower respiratory 

symptoms, cough, and chest pain on deep inspiration, in outdoor children and outdoor workers, 

and acute excess respiratory related hospital admissions, including admissions of asthmatics. 
Exxon Mobil Corporation Comments - 3 

In 2007, EPA again cites the same health effects and factors that influence response to 

ozone that are mentioned above, and in fact cites many references which are pre-1997. Since 

1997, while there have been a number of additional human clinical and epidemiological studies 

reported, none of the studies provide data to support effects at levels below those evaluated in 

1997. In human clinical studies, the lowest concentration where these effects occur remains at 

0.08 ppm. Moreover, the human clinical studies that assessed exposures at 0.08 ppm that EPA 

cites as significant (McDonnell 1996; Ultman 2004; and Adams 2002, 2006) report the same 

spectrum of effects that were reported in the many previously published studies conducted at 

0.08 ppm. Due to serious limitations in the epidemiology studies, described further in our 

comments, these studies are unable to ascertain the concentration where effects begin to occur, 

or, if the effects reported are due to ozone alone. 

 A side-by-side comparison in Table 1 below, of the key health effects included in the 

Criteria Document (“1996 CD”), Staff Paper (“1996 SP”), and Final Rule from the 1997 review, 

with the health effects discussed in this review, show no appreciable difference in the 

understanding of the significance of each of the health endpoints in question. While a number of 

new studies on the health effects of ozone have been published since 1997, including a number 

of epidemiological and a few human clinical studies, the main conclusions on the health effects 

produced by ozone have not changed substantially, either qualitatively or quantitatively. EPA’s 

claim of new health effects since 1997 is not supported and should be corrected in the final rule. 

Table 1 

Comparative Statements Showing Similarity of Understanding 

of Affects in the 1997 and Current Reviews 

Statements from Current Review Statements from 1997 Review 

inflammation as a contributor to respiratory disease 

“Repeated respiratory inflammation state can lead to a 

chronic inflammatory state with altered lung structure and 

lung function and may lead to chronic respiratory diseases 

such as fibrosis and emphysema (EPA, 2006a, section 

8.6.2).” (72 Fed. Reg. at 37,825). 

“single, acute (1-4 hour) exposure to > 0.08 to 0.1 ppm 

ozone of subject engaged moderate to heavy exercises 

could induce cellular and biochemical changes suggestive 

of pulmonary inflammation and lung permeability (1996 

CD at 7-187).” 

“The currently available information provides at least a 

biologically plausible basis for considering the possibility 

that repeated inflammation associated with exposure to O3

over a lifetime may result in sufficient damage to the 

respiratory tissue such that individuals later in life may 

experience a reduced quality of life.” (62 Fed. Reg. at 

38,859) 

increased susceptibility in those with pre-existing respiratory disease 

“Based on new evidence from animal, human clinical, and 

epidemiological studies the [CD] concludes that people 

with preexisting pulmonary disease are likely to be among 

those at increased risk from O3 exposure.” (72 Fed. Reg. at 

37,826)(emphasis added). 

“the major reason individuals with preexisting respiratory 

disease [(e.g. those with COPD, ischemic heart disease)] 

may be of concern is the likelihood that decrements in lung 

function or exercise capacity may have greater clinical 

importance to the individual than similar changes in healthy 

persons.” (1996 SP at 58). 

increased susceptibility in those with asthma 

“Evidence from controlled human exposure studies 

indicates that asthmatics may exhibit larger lung function 

decrements in response to O3 exposure than healthy 

controls” and “asthmatics present a differential response 

profile for cellular, molecular and biochemical parameters.” 

(72 Fed. Reg. at 37,826) 

“asthmatic subjects ... characteristically have increased 

airway responsiveness at baseline, ... and the difference in 

baseline airway responsiveness between healthy and mild 

asthmatics subjects may be as much as 100-fold.” (1996 

CD at 7-186). 
Exxon Mobil Corporation Comments - 4 

“[the clinical studies] comparing the pulmonary function 

responses following O3 exposure in asthmatic and 

nonasthmatic subjects suggest that asthmatics are at least as 

sensitive, if not more sensitive, to the acute effects of O3

inhalation” (1996 CD at 7-25) (emphasis added). 

“In the proposal notice, EPA stated that groups at increased 

risk of experiencing health effects from O3 exposure, 

include active children and outdoor workers who regularly 

engage in outdoor activities that involve heavy levels of 

exertion during short-term periods of elevated ambient O3 

levels or moderate levels of exertion during prolonged 

periods of elevated ambient O3 levels. Also, individuals 

characterized as having pre-existing respiratory disease 

(e.g., asthma or chronic obstructive lung disease), may be at 

increased risk.” (EPA, Responses to Significant Comments 

on the 1996 Proposed Rule on the National Ambient Air 

Quality Standards for Ozone (December 13, 1996; 61 Fed. 

Reg. 65,716 at 50). 

pulmonary function responses in children with asthma versus older people 

 “Children with and without asthma were found to be 

particularly susceptible to O3 effects on lung function and 

generally have greater lung function responses than older 

people.” (72 Fed. Reg. at 37,826). 

“children respond to low-level O3 exposures in a manner 

comparable to that of young adults, ... while older persons 

exhibit a decreased sensitivity relative to young adults 

(1996 SP at 55). 

“A number of epidemiological studies have shown a 

consistent relationship between ambient oxidant exposure 

and acute respiratory morbidity in the population. 

Decreased lung function and increased respiratory 

symptoms, including exacerbation of asthma, occur with 

increasing ambient O3, especially in children.” (1996 SP at 

40)(emphasis added). 

ozone and development of the condition of asthma 

“In contrast to supportive evidence from chronic animal 

studies, epidemiologic studies of inflammation, new asthma 

development, and long-term function declines remain 

inconclusive.” (2006 CD at 7-134). 

“While O3 has not been shown to cause asthma, the 

available evidence suggests that O3 may exacerbate 

asthma.” (62 Fed. Reg. at 38,864 ). 

intersubject variability in pulmonary function responses 

“among the more important of the recent studies that 

examine changes in FEV1 in large numbers of subjects over 

a range of 1-2 hours at exposure levels of 0.080 to 0.40 

ppm were studies by McDonnell et al. (1997) and Ultman 

et al. (2004). These studies observed considerable 

intersubject variability... .” (72 Fed. Reg. at 37,827). 

“while average responses may be relatively small at the 

0.080 ppm exposure level, some individuals experience 

more severe effects that may be clinically significant” (72 

Fed. Reg. at 37,828) 

“the most sensitive individuals experienc[e] FEV1

decreases as large as 40 to 50 percent at 6- to 8-hour 

exposures in the range of 0.08 to 0.10 ppm in controlled 

human studies” (62 Fed. Reg. at 38,860). 

“Bates et al. (1972) noted that variation in sensitivity and 

response was evident for various symptoms and pulmonary 

functions assessed following O3 exposure. This 

observation of large intersubject variability in response to 

O3 also has been reported by numerous other investigators 

(Adams et al.,, (1981); Folinsbee et al. (1978); McDonnell 

et al. (1983): Kulle et al. (1985)).” (1996 CD at 7-13). 
Exxon Mobil Corporation Comments - 5 

II. New Human Clinical Data Have Not Increased the Certainty or Level of Risk Since 

1997 and Do Not Support a Revision to the Ozone Standard. 

A. New Clinical Data Have Not Altered EPA’s Understanding of the Risks 

From Ozone Exposure 

In the proposed rule, EPA appears to place significant weight on new studies that confirm 

clinical effects at 0.08 ppm. Specifically, EPA cites clinical data from McDonnell (1996) as 

providing new evidence on the significance of individual responses to 0.08 ppm ozone exposure 

even though the average or mean response may be relatively small. (72 Fed. Reg. at 37,828). 

However, the presence of effects at 0.08 ppm and the concept of individual variability in 

response to ozone was well understood and documented in the 1997 review. In fact, in the 1997 

final rule, EPA noted that the research found statistically significant effects at 0.08 ppm with 

high individual variability: “it is recognized that some individuals are unusually responsive to 

O3 and may experience much greater functional and symptomatic effects from exposure to O3

than the average individual.” (62 Fed. Reg. at 38,859). Specifically, on lung function responses, 

EPA concluded that “while group mean response in clinical studies at the lowest exposure level 

tested of 0.08 ppm are typically small or mild in nature, responses of some sensitive individuals 

are sufficiently severe and extended in duration to be considered adverse.” (62 Fed. Reg. at 

38,864). EPA supported this conclusion by noting that the observation of large inter-subject 

variability in response to ozone was reported in numerous human clinical studies including those 

by Adams et al. (1981), Folinsbee et al. (1978), McDonnell et al. (1983), and Kulle et al. (1985). 

(1996 CD at 7-13). Inter-subject variability was also reflected in EPA’s 1997 review, where the 

most sensitive individual experience FEV1 decreases as large as 40 to 50 percent at 6- or 8-hour 

exposures in the range of 0.08 to 0.10 ppm based on data from controlled human studies. (62 

Fed. Reg. at 38,859). 

In the 1997 review, EPA indicated that those at risk of experiencing acute effects include 

active children and outdoor workers who regularly engage in outdoor activities and individuals 

with pre-existing respiratory disease, including asthma and chronic obstructive lung disease (see

EPA’s 1997 Response to Comments, section b., Definition of sensitive populations, at 50-51). In 

fact, EPA’s conclusions on individual sensitivity and responsiveness, and populations at 

potential increased risk to ozone exposure are equivalent to the conclusions they reached in 

1997, and should be noted as such in the final rule. 

B. The Administrator is correct in judging the data from Adams (2002, 2006) on 

ozone levels below 80 ppb as being too limited to support a revised standard. 

In the proposed rule, EPA discusses the results of the human clinical studies by Adams 

(2002, 2006) and EPA’s re-analysis of the data from these studies. (72 Fed. Reg. at 37,828). 

Adams (2006) reported statistically significant group mean decreases of 6.1 percent for 6-hour 

square wave exposures at 0.08 ppm ozone using a ventilation rate (VE) of 20 l/min/m2

. These 

responses are similar to the 6.2 percent decrease Adams reported at 0.08 ppm in a previous 

chamber study conducted at the same VE (Adams, 2003). Further, these responses were only 

slightly less than the -7.4% net response (including +0.8% response to filtered air? (FA)) 

observed in a chamber exposure to 0.08 ppm ozone with exercise VE 20 l/min/m2 by Horstman et 
Exxon Mobil Corporation Comments - 6 

al. (1990) and the -7.7% net response (including 0.6% response to FA) observed by McDonnell 

et al. (1991). Therefore, the findings by Adams (2006, 2002) at 0.08 ppm provide no new 

information on ozone that was not known at the time of EPA’s last review. In addition, however, 

Adams reported that the group mean FEV1.0 response of -1.5 percent for the square wave 

exposure at 0.06 ppm was not statistically different than the value for FA (+1.35%). Adams 

analyzed the data using a 2-way analysis of variance (ANOVA) with repeated measures, which 

tested for gas concentration effects and exposure time effects. Upon obtaining a significant F 

value, the Scheffé post hoc test was applied to determine which particular mean values were 

significantly different. In contrast, EPA analyzed only the data at 6 hours using a t–test. 

There are several concerns with EPA’s re-analysis. 

1. EPA is relying on an unpublished internal analysis that conflicts with the 

author’s original conclusions. 

Although EPA cites a re-analysis of the Adams data in drawing conclusions regarding 

risks below 0.08 ppm (the so-called “Brown Memorandum”), the re-analysis was not published 

or peer reviewed. As a result, neither the scientific community nor the public was afforded an 

opportunity to appropriately review the analysis. In fact, the only documentation for the reanalysis is in an internal EPA memorandum that appeared in the ozone docket after the close of 

the SP from this review (“2007 SP”). Given the lack of adequate scrutiny by the scientific 

community and the public, EPA should not rely on the Brown Memorandum in drawing 

conclusions regarding risks below 0.080 ppm. 

2. The ANOVA statistical test employed by Adams is preferred over the 

statistical test used in EPA’s re-analysis. 

 The original Adams 2006 paper employs a statistical test, called the ANOVA. This test 

allows the researcher to consider all the data in drawing conclusions about statistical 

significance. This is important because the protocol for the Adams (2002, 2006) studies included 

pulmonary function measurements each hour from 1-6 hours. The selection of the use of the 

ANOVA was based on the study objective, which was to evaluate square versus V wave 

responses. Attempting to evaluate individual variability was not an objective of the Adams 

(2002, 2006) studies. In contrast, the EPA re-analysis used the t-test. Brown indicates the 

selection of this test was based on the requirement to minimize type I error (falsely reject the 

null, i.e., maximize the potential to find a significant difference). With the t-test, it is not 

possible to evaluate data for multiple time points simultaneously. Rather, EPA’s re-analysis 

focused only on the data at six hours. 

One of the important issues raised in the Brown Memorandum is the appropriateness of 

the statistical test employed by the Agency in its re-analysis compared to the statistical test used 

by the author. In selecting the paired t-test, the Brown Memorandum implies that the t-test is the 

preferred statistical test commonly applied by EPA in similar studies: “Studies conducted by 

EPA in Chapel Hill, NC, have commonly utilized a paired t-test to assess the statistical 

significance (p ≤ 0.05) of pre- to post-exposure changes in FEV1 between an air and an O3

exposure.” Brown Memorandum at 4 (citing Hostman et al. 1990; McDonnell et al. 1991). The 
Exxon Mobil Corporation Comments - 7 

references, however, are to two studies that are over 15 years old that do not reflect EPA practice 

for analyzing FEV1 data. 

A more thorough review of the statistical tests used by EPA researchers in clinical studies 

suggests just the opposite. In fact, all of the investigative teams performing ozone human 

clinical studies, including those in Research Triangle Park, have used statistical procedures 

similar to those used by Adams et al. to analyze their data. For example, Liu et al. (1999), Gong 

et al. (1998), Renaud et al. (1997), Torres et al. (1997), Linn et al. (1983), and Kulle et al.

(1985) all used statistical procedures based on ANOVA with repeated measures of subjects to 

assess the statistical significance of their group mean pulmonary function findings. 

In a recent human chamber study in elderly volunteers with Chronic obstructive 

pulmonary disease (COPD) exposed to condensed ambient particles, the ANOVA test with 

repeated measures on subjects was used to evaluate the statistical significance of the pulmonary 

function data (Gong et al. 2004). One of the authors of this study was Dr. Robert Devlin, who is 

the lead human clinical studies scientist working at EPA Research Triangle Park, NC. In fact, in 

a recent proposal for conducting new ozone human clinical studies to evaluate FEV1 responses, 

Dr. Devlin has again expressed preference for using the mixed model ANOVA to assess the data. 

In a study designed to evaluate the effects of ozone concentration, exposure duration and 

ventilation on FEV1 changes, McDonnell and Horstman et al. (1997), the same researchers cited 

in the Brown Memorandum as always using the t-test, explicitly modeled the variance structure 

using a sophisticated “mixed models” approach (McDonnell et al. 1997). Statistical significance 

of the coefficients derived from the mixed model was determined with the asymptotic covariance matrix of the estimated parameter values, rather than the simplistic approach suggested 

in the Brown Memorandum. It is very clear that these EPA investigators do not routinely 

employ the simple t-test to evaluate time varying ozone pulmonary function data, as stated in the 

Brown Memorandum. Therefore, in our view, the statistical procedures used by Adams should 

not be viewed as “overly conservative” or inappropriate according to an undefined standard 

suggested by Brown/EPA-NCEA, as inferred in the Brown memorandum. Decisions, such as 

choice of statistical model based on undefined standards is arbitrary and not scientifically 

supportable. 

 

Brown also states that “the CASAC Panel members also supported the use of the paired t 

test approach as the preferred method for analyzing the pre- minus post- exposure lung function 

responses.” This statement is incorrect. There is no written documentation that CASAC 

expressed preference for the use of the t-test. The minutes from the March 5, 2007 

teleconference where this topic was discussed, or any of the CASAC letters, do not mention this 

recommendation. Further, during the verbal discussion on this issue during the teleconference, 

one member, Dr. Fred Miller, expressed interest in using a different, potentially less conservative 

post hoc test than the Sheffé test. In fact, as described below, ExxonMobil Biomedical Sciences, 

Inc. has completed this reanalysis using the Dunnett’s post hoc test, a less conservative post hoc 

test, both for the 6-hour only data and complete data set. The results confirm the findings in the 

original report. The only other CASAC view on this came from Dr. Sverre Vedel, who 

expressed serious concern for over-reliance on the responses for two individuals. Nowhere 

during the conversation on this issue was there a consensus expressed by CASAC for use of the 
Exxon Mobil Corporation Comments - 8 

t-test. Further, the verbal opinion of one or even a few CASAC members should not be 

misconstrued as the collective view of the CASAC. 

There are several reasons why the ANOVA is the preferred test for analyzing clinical 

studies over the t-test recommended in the Brown Memorandum: 

• The fundamental reason for using the ANOVA is that it addresses the effect of time in the 

chamber by considering the filtered air (control) group whereas the t-test does not 

consider that effect. Suppose the FEV1 decrement over the experiment for the control 

group is six units and the decrement for the high exposure group is five units, it may be 

that the 5-unit decrement is “statistically significant” compared to no change (a zero 

change), but it is not statistically different from the control group decrement of six units. 

The t-test only compares the decrement against a zero change whereas the ANOVA 

compares it against a change relative to the control group. Also, the t-test does not 

control for the time effect in the absence of an exposure. 

• The ANOVA test has greater statistical power. The Brown Memorandum indicates that 

as the Type I Error decreases because of the correction for multiple comparisons the Type 

II Error increases (the Power decreases). There is another important idea in the relation: 

the sample size (n). As n increases the power will increase for a fixed Type I Error. 

More exactly, as the number of degrees of freedom (df) associated with the estimated 

error variance increases so will the power (this is a statistical nicety, but an important 

point). The ANOVA with its repeated measures aspect has a much better (larger df) 

estimate of the error variance and, therefore, is the more powerful method. 

• The ANOVA also considers the time course of the exposure (the repeated measures) and 

allows the researcher to determine if there is a dose response by comparing among the 

exposure groups. 

• The discussion of multiple comparisons presented in the third paragraph from the end of 

the Brown Memorandum is misleading at best. As noted, there are up to 90 comparisons 

that can be made and the Scheffé method is a method that was developed to avoid an 

inflated Type I error rate (falsely claiming a difference when a difference does not exist). 

If there were no differences among the group means and each of the 90 comparisons were 

carried out at the usual 0.05 Type I error rate, the probability of finding at least one false 

difference would be 1-0.9590 or 0.99; that means if there were really no differences there 

is a 99 percent chance of erroneously finding at least one difference when the test is done 

at the standard Type I error rate of 0.05. The other extreme is represented by the 

Bonferroni correction method that sets the Type I error rate at a value that results in an 

overall error rate of 0.05. This is correctly calculated as 1-(1-0.05)1/90 or about 100 times 

smaller than the standard 0.05. Both extremes are clearly useless. Because of these 

extremes, Scheffé developed his method that makes reasonable choices and provides a 

middle course between the extremes of a Bonferroni test (with an error rate of 0.0005) 

and the uncorrected test that yields an almost certain chance of making at least one false 

claim of a difference. The Brown Memorandum’s use of the Bonferroni example is 

misleading at best. Therefore, in our view, re-analyzing the data from Adams using the t-
Exxon Mobil Corporation Comments - 9 

test of the pre- and 6.6th hour readings is not the appropriate approach to analyze these 

data. 

• The implied assertion in the Brown Memorandum is that the Sheffé post hoc test used by 

Adams is conservative and was used by the author to minimize the likelihood of 

observing a difference between groups, and is not supported by a further re-analysis of 

the data. 

To evaluate whether a different and “less conservative” post hoc test would change the 

results, ExxonMobil Biomedical Sciences Inc. performed a further re-analysis of the 

Adams data (Nicolich 2007, Attachment A to these comments). The re-analysis was 

based on a mixed model repeated measures analysis (Pinheiro and Bates 2002) and 

considered the percent change in FEV1 and the observed FEV1 value with the pre-exposure 

response as a co-variate. (The former is a ratio measure and the latter is a difference 

measure.) When there is a statistically significant effect in the analysis of a variance table, 

the comparisons are against the initial reading for the filtered air (protocol 1) with the 

multiple comparison significance level adjusted by Dunnett’s test (used for comparing 

“treatment” means versus a single “control” value). The Dunnett’s test is not as 

conservative as Scheffé’s test or as extreme as individual t-tests, but is tailored to the 

current question (Hsu 1992). The re-analysis was performed both using the 6-hour data 

only and the full data set of FEV1. Given the design of the study, it is more appropriate 

to use the full data set and not discard data than it is to selectively analyze data at the 6-

hour time point, as was done in the Brown Memorandum. The re-analysis was also 

performed both with and without transformation of the residuals to make them much 

closer to being normally distributed. Based on an analysis of the response pattern over the 

6.6 hours of experimentation, the only statistically significant percent changes in FEV1

responses from the first period filtered air exposures were the 0.08 ppm triangle exposure at 

4.6, 5.6 and 6.6 hours, and the 0.08 ppm square wave exposure at 6.6 hours. No 

statistically significant differences were observed for the 0.06 ppm exposures. 

 Finally, EPA’s assertion that the considerable variability in the Adams study is 

potentially an indication of significant adverse health outcomes is not supported by the data or 

the EPA re-analysis. The Brown Memorandum makes the argument that, while the mean change 

in FEV1 at 0.06 ppm ozone is small, the large variability in the responses is an indication that “... 

some [individuals] may experience distinctly larger effects ...” with the implication that there 

might be more deleterious effects than what was observed in this study.. However, the large 

variability is a characteristic of FEV1 measures: the percent change responses for the filtered air 

group in 2002 was –6.6 to 12.4 and, for the 2006 group –5.0 to 8.6. This is an indication that the 

natural variability is large even in unexposed groups. Further, the level of variability observed in 

the studies by Adams is similar to that reported in other studies, including those published prior 

to the current review (see above discussion on individual variability). For these reasons, the 

American Thoracic Society (ATS) considers a decline of less than 15 percent in FEV1 to not be 

of clinical significance (Wang and Petsonk 2004). 

Because of the significant flaws in the Brown Memorandum, EPA should delete all 

references to the speculative results of their re-analysis from the studies by Adams (2002, 2006) 

based on the Brown re-analysis. 
Exxon Mobil Corporation Comments - 10 

III. New Epidemiology Studies Do Not Provide Evidence of Causality or Further 

Support for the Need To Revise the Standard. 

 

A. EPA overstates the importance of the new observational epidemiology 

studies on ozone. 

In the proposed rule, EPA states there are over 100 epidemiology studies on ozone. (72 

Fed. Reg. at 37,823). However, in most of these studies, ozone was not the primary pollutant 

investigated, but was included superficially as a co-pollutant for a study on a different pollutant. 

In many of these studies, there was only minimal consideration and analysis of the effects of 

ozone versus the other pollutants (mostly particulate matter (PM)). Furthermore, many of these 

studies were the same ones EPA cited among the “hundreds of studies” when it promulgated a 

revised National Ambient Air Quality Standard for fine particles (PM2.5). (71 Fed. Reg. 61,144, 

61,151 (Oct. 17, 2006)). Not only does this raise the issue of double counting of potential risks 

and health benefits, discussed in more detail later, but also fails to recognize the shortcoming of 

basing conclusions on a study that considered ozone only superficially as a co-pollutant rather 

than as the primary pollutant being assessed. In their 1997 review, EPA also stated that 

“numerous” epidemiology studies have reported excess admissions and emergency department 

visits for respiratory causes. (62 Fed. Reg. at 38,864). 

EPA should clarify that much of the so-called “new” epidemiology information since 

1997 is based on time series studies evaluating the impacts of particulate matter on health. 

B. EPA fails to articulate and follow the weight of the evidence or established 

causality criteria for evaluating epidemiology studies in drawing conclusions 

regarding causality. 

In the proposed rule, EPA states that it focused only on health effects where ozone 

exposure is causal, likely causal, or highly suggestive of those effects. (72 Fed. Reg. at 37,823). 

However, EPA has not provided definitive criteria to distinguish between these important 

categories in the proposed rule, the 2007 SP or the 2006 CD. As a result, EPA’s process for 

determining causality is not defined and overly influenced by selective interpretation of the 

results of observational epidemiology studies. In many instances, EPA relies on untested 

theories raised by investigators struggling to interpret their data in the discussion section of their 

publications, or untested theories generated by EPA staff, to explain the results of sometimes 

implausible epidemiology findings. These hypotheses are then later used as fact, without further 

testing and re-testing to establish their credibility. This approach conflicts with the basis 

scientific process. 

On the other hand, in several instances, EPA relies on epidemiology studies for showing 

causality when the authors of those very same studies have raised significant questions regarding 

causality. For example, in the study by Vedel et al. (2003) which EPA cites as evidence for 

effects below the current standard, the authors raise serious questions about their own results and 

on the time-series study design upon which the results were based. Vedel et al. state: 
Exxon Mobil Corporation Comments - 11 

 Because the absence of a concentration-response threshold for 

most air pollutants seems biologically implausible, consideration should 

be given to possible reasons that time-series studies seem to be unable to 

detect such thresholds. First, a “blurring” of a threshold might be 

expected if the use of ambient pollutant concentrations measured with a 

few pollution monitors results in error in the measurement of exposure. 

... Recent findings of a simulation study based on actual ambient and 

personal monitoring data suggest that measurement error can have a 

substantial effect on the ability to detect a threshold. ... 

 Second, ambient concentrations of air pollutants may be acting 

as a surrogate measure of exposure to other agents or to specific 

pollution sources that are in fact responsible for the observed effects. ... 

 Third, because meteorology is a strong determinant of air 

pollutant concentrations in an urban setting, with variation in pollutant 

emissions being relatively minor, ambient pollutant concentrations might 

conceivably also be acting as surrogate measures of meteorological 

factors. If some of the observed effects of the pollutants are due to 

meteorology rather than to the pollutants themselves, again, a threshold 

for the pollutants might not be observable. ... 

 Given the multitude of adverse health effects attributed to 

changes in meteorology, confounding by meteorology still seems 

plausible. 

(Vedal et al., 2003, at 49-51). 

EPA should provide clear and specific scientific criteria to judge whether health effects 

reported from epidemiology studies as well as other studies are causal, likely causal or highly 

suggestive. These criteria should be subject to review by a diverse external group comprised of 

expert scientists from the disciplines of epidemiology, human clinical studies, toxicology, and 

exposure science. EPA should also look to the International Agency for Research on Cancer’s 

well-defined causal criteria for addressing carcinogenicity as an example. Once clearly 

established causal criteria are defined for purposes of NAAQS deliberations, EPA can then 

conduct a weight of evidence evaluation to support a conclusion regarding causality for specific 

health effects endpoints based on the data collected. Without clear criteria on causality, EPA’s 

evaluation of epidemiology studies will remain arbitrary. 

C. Because of the many weaknesses in time series studies, more studies 

reporting the same result does not increase the case for causality or show 

consistency. 

In the proposed rule, EPA incorrectly asserts that the confidence in a weight of evidence 

determination increases as the number of studies consistently reporting a particular health effect 

endpoints grows. (72 Fed. Reg. at 37,823). However, this is not scientifically correct in the 

context of ozone time series morbidity and mortality studies, which constitute the vast majority 

of “new” studies relied on by EPA on the health effects of ozone. Time series studies on 

individual cities, which are exceedingly easy to perform and publish, are unlikely to provide any 
Exxon Mobil Corporation Comments - 12 

new meaningful data on the health effects of ozone. These studies all suffer from the same 

scientific weaknesses, including the lack of correlation between ambient and personal exposure 

and various model specification factors. 

This very point was made by the Center for Disease Control (CDC) in the report cited by 

EPA in the proposed rule (72 Fed. Reg. at 37,838) on the role of statistical strength along with 

the magnitude of risk in determining the strength of association: 

In observational studies, however, increasing the number of studies may 

reduce the random component of uncertainty, but not necessarily the 

systematic component attributable to confounding. Without 

randomization, there is no mathematic basis to assume that imbalance in 

known confounders will decrease with an increase in the number of 

studies. 

(CDC 2004 at 20). Also, on the issue of consistency in observational epidemiology studies, an 

article in Science quotes David Sackett of Oxford University: “If the studies have the same 

design and ‘if there’s an inherent bias,’ ... it wouldn’t make any difference how many times it’s 

replicated. Bias times 12 is still bias.” (Taubes 1995 at 169). 

 Further, as discussed later in our comments, the results of the ozone acute mortality 

studies are not consistent as claimed by EPA. All of the authors of the three meta analyses cited 

by EPA noted the high degree of heterogeneity or variability in the estimates from individual 

cities and the fact that the results for many of the individual cities did not reach statistical 

significance. Comparison of the results also show unexplained differences in rankings and 

magnitude of results even though they are based on the same underlying data from the National 

Mortality, Morbidity and Air Pollution study (NMMAPS). 
Exxon Mobil Corporation Comments - 13 

Atlanta

Chicago

Cleveland

Dallas/Fort Worth

Detroit

Houston

Los Angeles

Miami

New York

Oakland

Philadelphia

Phoenix

Pittsburgh

San Antonio

San Bernardino

San Diego

San Jos

Santa Ana/Anaheim

Seattle

Bell, Est % Change Total Mortality per 10 ppb O3

0.0

0.5

1.0

1.5

2.0

Huang, Est % Change CVDRESP Mortality per 10 ppb O3

-4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9

Figure 1 

Figure 1 shows a comparison of City Specific Estimate of Percent Change in Total (Bell, et al.

(2005) or Cardiovascular and Respiratory (CVDRESP) Mortality (Huang, et al. (2005)) per 10-

ppb change in ozone levels for the 19 largest NMMAPS Cities. Note the range of estimated 

percent change for mortality is 0 to 1.8, while for cardiovascular and respiratory mortality it is – 3 

to 8 percent. 

 For the reasons cited above, EPA is incorrect in concluding that confidence in a specific 

health effect increases with the number of observational studies. At a minimum, with regard to 

the ozone time-series studies, EPA should caveat any conclusion based on the systematic 

elements of confounding present in all of the ozone observations studies and the unexplained 

heterogeneity in results across cities and authors. 

D. The strength of the associations in ozone ecological epidemiology studies are 

very weak by traditionally accepted criteria. 

Throughout the text of the proposed rule, EPA incorrectly states that, in epidemiology 

studies, the strength of association refers to both the magnitude of the association and its 

statistical strength, which includes assessment of both effects estimate size and precision. (See, 
Exxon Mobil Corporation Comments - 14 

e.g., 72 Fed. Reg. at 37,823 and 37,838). To justify this position, EPA references a report by 

CDC on Smoking and Health. EPA is incorrect in drawing this conclusion and its reliance on the 

CDC report for the following reasons: 

• The CDC reference does not mention the word “precision.” 

• The discussion of this topic in the CDC report consists of one simple paragraph, with no 

documentation on why statistical strength should be included along with the magnitude of 

the risk in determining the strength of association. 

• The CDC statement is based largely on the specific characteristics of the data in a 

Smoking and Health study and cannot be generalized. Much of the epidemiology data 

considered by CDC on smoking comes from studies where the exposure metrics are 

much more precise than the observational studies considered by EPA on ozone, and from 

epidemiology studies with stronger designs. The studies on smoking include 29 

retrospective case control studies and seven prospective cohort studies. Further, a dose 

response was observed in all of the studies. This contrasts with the ozone epidemiology 

database, where all of the key studies are observational in nature, the key prospective 

cohort study (Pope et al. (2002) at 1132-1141) indicates no mortality signal for ozone, 

and there is no clear relationship between the ambient ozone levels and positive or 

negative associations across cities, i.e., there is no dose response observed. 

• Finally, the Hill causal criteria on causality, often referred to as the gold standard for 

evaluating epidemiology studies, do not include statistical strength with the magnitude of 

the risk for purposes of determining the strength of association. (Hill 1965). Rather, 

these guidelines clearly indicate the greater the magnitude of the association, the more 

likely an association is causal. In his essay, Sir Bradford Hill cites as examples increases 

as high as 200-fold for scrotal cancer, and as low as 2-fold for coronary thrombosis in 

smokers versus non-smokers. 

 The statistical significance of the association and statistical power of effect estimates are 

not considerations about the strength of the association. Rather, they are considerations about 

whether the results could be due to chance or random error. These items are best considered 

under robustness. Similarly, consistency is not related to strength of association and should not 

be considered as criteria to judge the strength of an association. Given the wide degree of 

heterogeneity in the results of ozone time-series studies across and within cities, EPA cannot 

conclude that the results of these studies are “consistent” or that there is high precision in the 

results of these studies (see comments above). 

Leading epidemiology experts have indicated that magnitude of relative risks from 

observational epidemiology studies below 2-3 should not be seriously considered. The Journal 

of Science (Taubes, 1995) interviewed leading epidemiologists on the topic of risk estimates 

from observational epidemiology studies. Some examples of their concerns are presented below: 
Exxon Mobil Corporation Comments - 15 

• Michael Thun, Director of Analytic Epidemiology for the American Cancer 

Society, stated “With epidemiology you can tell a little thing from a big thing. 

What’s very hard to do is to tell a little thing from nothing at all.” 

• Marcia Angell with the New England Journal of Medicine stated, “[W]e are 

looking for a relative risk of three or more [before accepting a paper for 

publication], particularly if it is biologically implausible or if it’s a brand new 

finding.” 

• Robert Temple, Director of Drug Evaluation at the Food and Drug 

Administration, put it bluntly “My basic rule is if the relative risk isn’t at least 

three or four, forget it.” 

• Sander Greenland, a University of California, Los Angeles, epidemiologist, was 

noted as stating “a study reporting a twofold increased risk might then be worth 

taking seriously—‘but not that seriously.’” 

• Dimitrios Trichopoulos, head of the Epidemiology Department at the Harvard 

School of Public Health, opted for a 4-fold risk increase as the lower limit. 

In contrast, the associations in ozone ecological epidemiology studies are on the order of 

1.000-1.008 and are therefore very weak. EPA should revise this section to indicate that the 

strength of the associations in ozone ecological epidemiology studies are very weak by 

traditionally accepted criteria and are, therefore, subject to hidden uncertainties and confounding 

bias. 

IV. Ozone Time-Series Studies Are Fundamentally Flawed Due To the Weak 

Correlation Between Ambient Monitors and Personal Exposures. 

A. The literature is clear in showing that measures of ozone in the air from 

ambient monitors are inadequate surrogates for unknown personal exposure 

to ozone. 

In the proposed rule, EPA states that only a limited number of studies have examined the 

relationship between ambient ozone concentrations and personal exposure to ozone. (72 Fed. 

Reg. at 37,838). EPA further states that, collectively, the available studies, including the studies 

by Sarnat et al. (2001, 2005), provide supportive evidence that ambient ozone concentrations 

from central monitors may serve as valid surrogate measures for mean personal exposures 

experienced by the population, which is of most relevance for time-series studies. Id. Both of 

these statements are not accurate and are not supported by the available data. 

Contrary to EPA’s statement that there are only limited studies on this topic, the literature 

contains numerous published studies on this topic, including studies published prior to and after 

the last ozone NAAQS review in 1997. These studies include those by Brauer et al. (1989, 

2002), Linaker et al. (2000), Liu et al. (1997), and Patterson et al. (2000). Further, recent studies 

were conducted to specifically answer key questions concerning the use of ambient monitor 
Exxon Mobil Corporation Comments - 16 

measurements in time-series studies, including Sarnat et al. (2001, 2005, and 2006) and 

Koutrakis (2006). 

The results of these studies and the authors’ conclusions are consistent. They 

demonstrate that: (1) most personal ozone exposures are so low as to be not detectable at a level 

of 5 ppb resulting in very low correlation between concentrations reported from central ambient 

monitors and personal monitors; (2) ozone measurements on ambient monitors are a better 

surrogate for personal exposure to PM2.5 than to ozone; and (3) populations expected to be 

potentially susceptible to ozone, including children, the elderly, and those with COPD, are at the 

low end of the population exposure distribution. 

This has led to the overwhelming view in the wider exposure science community, 

documented in the results of numerous scientific publications, that measurements on ambient 

monitors do not provide reliable estimates of personal exposure for use in time-series studies. 

Unsurprisingly, this view was also expressed by the Clean Air Scientific Advisory Committee 

(CASAC) in its June 5, 2006 letter to EPA (a point that was incorrectly omitted from the 

proposed rule at 72 Fed. Reg. at 37,836, footnote 19): 

[O]f particular importance for the ozone time-series studies, there can be 

no correlation between personal concentrations of ozone measured over 

time and concentrations measured at central outdoor sites. The 

population that would be expected to be potentially susceptible to dying 

from exposure to ozone is likely to have ozone exposures that are at the 

lower end of the ozone population exposure distribution, in which case 

this population would be exposed to very low concentrations of ozone 

indeed, and especially so in winter. Therefore it seems unlikely that the 

observed associations between short-term ozone concentrations and daily 

mortality are due solely to ozone itself. 

(June 2006 CASAC letter at 3-4). 

 A panel of ten scientists reviewed the available science on ozone, holding a workshop 

conference in June of 2007 and issuing a report entitled Critical Considerations in Evaluating 

Scientific Evidence of Health Effects of Ambient Ozone, Report of a Working Conference held 

in Rochester, New York, June 5-6, 2007 (“Rochester Report”). The Rochester group, which 

notably included the authors of one of the largest ambient/personal exposure studies, provided 

the following view on this topic: 

Considering that several panel exposure studies have shown substantial 

inter- and intra personal variability in personal exposure/ambient 

concentration ratios, reliance on ambient monitors, especially for large 

geographic areas and for populations that do no spend a high proportion 

of the study period outdoors, may be inadequate and can introduce 

considerable bias. The impact of this exposure error is more severe on 

panel studies that examine a relatively small number of subjects as 

compared to that for population studies. 
Exxon Mobil Corporation Comments - 17 

(Rochester Report at 22). Later in their report, the Rochester group specifically cites problems 

with the panel studies of by Mortimer et al. (2000) and Gent et al. (2003), two studies that EPA 

places great importance in. 

 

Mortimer et al. (2000) and Gent et al. (2003), used ambient monitoring 

network data to assess exposures of study subjects dispersed over 

relatively large areas. In the case of Mortimer et al. (2003), all ambient 

monitors in the county were averaged for each of 8 urban study 

locations, in an approach similar to that employed in daily time series 

studies of mortality. Gent et al. (2003) used the average of all available 

ambient monitoring data in a large (6691 sq mile) study area to assess 

exposures. In these studies, as well as those with similar designs (Naeher 

et al., 1999) and exposure assessment approaches, major concerns pertain 

to their ability to accurately ascertain exposure to ozone relative to other 

co-pollutants. For example, neither design considers exposure 

heterogeneity within the study area, although it is well-known that ozone 

concentrations will, for example, be reduced in areas with high traffic 

density due to quenching by NO emissions. Similarly, these designs also 

do not consider heterogeneity in concentrations of co-pollutants, for 

example due to traffic density, within the study area. 

(Rochester Report at 52). On time-series studies, the Rochester group noted: 

[W]hen interpreting the results of the ozone time series health studies, it 

is important to keep in mind that during the summer outdoor ozone can 

be a surrogate of personal PM2.5 or other pollutant exposures. 

Consequently, it may not be possible to distinguish between the health 

effects of ozone and those of fine particles or other pollutants when using 

ambient measurements of ozone during the summer season. 

 (Rochester Report at 22). EPA ignores all of the conclusions in the published papers, as 

well as the advice of CASAC. Instead, EPA transforms the results of the studies by Sarnat et al. 

and others to arrive at their conclusion that ambient monitors measurements provide an adequate 

“surrogate” for personal exposure. We challenge EPA to provide the specific criteria by which 

they judge such measurements to be “adequate.” 

 EPA reports the results of the ambient versus personal ozone correlations by Sarnat et al.

in susceptible groups as “mixed.” This is clearly not supported by the data and authors 

conclusions. 

In Sarnat et al. (2001), personal multi-pollutant exposures and corresponding ambient 

concentrations were measured for 56 subjects living in the Boston area, including 20 older 

adults, 21 children, and 13 individuals with COPD. There was no correlation between ambient 

and personal ozone exposure in summer or winter (summer R2

 = 0.01, t value = 1.21, winter R2 = 

0.00, t value = 0.03). The authors concluded: 

Ambient concentrations of gaseous pollutants cannot be considered as 

surrogates for their respective personal exposures without site-specific 

evidence to support that assumption. 
Exxon Mobil Corporation Comments - 18 

(Sarnat et al., 2001, at 1060). 

In Sarnat et al. (2005), personal multi-pollutant exposures and corresponding ambient 

concentrations were measured in 43 subjects living in the Baltimore area including 20 healthy 

senior subjects and 23 school children. In winter, the large majority (over 95%) of the personal 

ozone samples were below the limit of detection (LOD) of 5.5 ppb, even when the corresponding 

ambient concentrations were all above the limit of LOD. As a result, there was no correlation 

between ambient and personal ozone exposure in winter (regression slope = 0.04, (5% CI 0.00-

0.07). In summer, while 8 of 21 subjects had personal-ambient correlations greater than 0.8, the 

other 13 subjects had essentially zero personal-ambient correlation resulting in a very low group 

regression slope of 0.27 (95%CI = 0.18-0.37). In contrast, much higher correlations were 

reported between ambient ozone and personal PM2.5 values (regression slope = 0.47, 95% CI 

0.37-0.57). This led the authors to conclude: 

[O]ur results support the earlier findings that summertime gaseous 

pollutant concentrations [like ozone] may be better surrogates of 

personal PM2.5 exposures (especially personal exposures to PM2.5 of 

ambient origin) than they are surrogates of personal exposure to the 

gases themselves. 

(Sarnat et al. 2005 at 385). 

Nowhere in the above studies, or in the HEI report that forms the basis for the 

publications (Koutrakis et al. 2005) do the authors provide any indication that ambient ozone 

measurements provide an adequate surrogate for personal exposure to ozone. 

 

In a third study by Sarnat et al. (2006) not cited by EPA, personal multi-pollutant 

exposures and corresponding ambient concentrations were measured in 10 non-smoking senior 

adults living in Steubenville, Ohio. Again, the personal-ambient ozone regression slope was 

very low (0.15 +/-0.02). This led Sarnat et al. to the following conclusions: 

• “Even in well-ventilated conditions, the slope of the O3 association 

(0.18) was small, suggesting only minor changes in exposure 

associated with a reasonable change in outdoor concentrations.” 

(Sarnat et al. 2006, at 652) 

• “The low slopes and R2

 values suggest that ambient gas 

concentrations are not suitable proxies of their respective personal 

exposure in time-series health studies.” (Sarnat et al. 2006 at 653). 

• “The results suggest that time-series health studies based on 24-hr 

ambient concentrations may not be able to identify the effects of 

gases on health, and better exposure surrogates are needed.” 

(Sarnat et al. 2006 at 654). 
Exxon Mobil Corporation Comments - 19 

This may be explained by findings in Sarnat et al.’s prior findings: 

In many respects, these weak associations were not surprising given 

findings from earlier single-pollutant exposure studies which showed 

similarly strong longitudinal personal-ambient associations for 

particulate matter ... and weak associations for the gases .... 

 (Sarnat et al. 2001, at 1059) (emphasis added) (citations omitted). It is very difficult to 

understand how, from these data and conclusions combined with the wider literature on this topic 

that, EPA can conclude that the adequacy of ambient ozone measurements as surrogates for 

personal exposure in time-series epidemiology studies is sufficient to allow these studies to be 

useful in determining causality or the level where potential effects are expected to occur. Further, 

it is difficult to understand how EPA concludes that ecologic epidemiology studies relying on 

ambient monitor measurements can be used to identify effects attributed to ozone alone. In our 

view, due to severe exposure misclassification in time series and panel studies of ozone, it is not 

possible to conclude that any health effects reported in these studies are due to ozone exposure 

alone, or, to ascertain the concentration where effects are expected to occur. 

Because of the overall importance of this topic, EPA must correctly note in the proposal 

that there are adequate published data to evaluate the personal to ambient ozone exposure 

relationship in healthy, elderly, and certain potentially susceptible subgroups. EPA should also 

state that the data and conclusions from these published studies are consistent and can be 

summarized as follows: 

1) There is a very poor correlation between ozone measurements on ambient monitors and 

actual ozone exposure as measured from personal monitors; 

2) The very poor correlation observed for individuals for daily measurements also translates 

into a poor correlation across time; 

3) The correlation is lower for certain potentially susceptible groups such as COPD patients 

and the elderly who spend little or no time outdoors; 

4) Measurements on ambient monitors are therefore a very poor surrogate for personal 

exposure in ozone time-series and panel studies; and 

5) Ambient ozone measurements are a better surrogate for personal exposure to PM2.5 than 

personal exposure to ozone, raising the concern that ozone time-series and panel study 

results are seriously confounded by exposure to PM2.5. 

 Overall, the EPA assertion that ozone measurements on ambient monitors are an 

adequate surrogate for personal ozone exposure in time series and panel studies is not proven and 

is rejected by the actual data. 

 The single exception to the above discussion is the few panel studies in outdoor workers 

or other groups spending a significant amount of time outdoors (e.g., hikers, outdoor workers) 

that employed personal monitoring. These studies, however, reflect only a relatively small 
Exxon Mobil Corporation Comments - 20 

portion of the population included in the many panel studies that are cited by EPA as further 

evidence of causality and which are used by EPA to assess risk. Also, while the exposure metric 

in these studies was more precise, the individuals in the study were still exposed to multiple 

pollutants, which somehow must be unraveled through various statistical analyses. Further, as 

mentioned below, in the case of the study cited by EPA on hikers reporting a positive 

association, another study of very similar design failed to report an association. 

B. EPA incorrectly concludes that the exposure error in ozone epidemiology 

studies results in an underestimate of risk. 

In the proposed rule, EPA further assets that the exposure error in epidemiology studies 

(implying all epidemiology studies on air pollutants) underestimates the individual exposure, 

thereby resulting in risk estimates that are biased downwards. (72 Fed. Reg. at 37,838). In 

arriving at this conclusion, EPA ignores the findings by Brauer et al. (2002), who carefully 

examined this issue in a paper entitled “Exposure Misclassification and Threshold 

Concentrations in Time Series Analyses of Air Pollution Health Effects.” As noted in this paper, 

for pollutants with poor personal- ambient correlations (ozone was given as the primary 

example), it is not possible to accurately assess concentration response relationships and 

thresholds in observational air pollution studies. Since ambient ozone measurements are a better 

surrogate for personal exposure to PM2.5 than personal exposure to ozone, and the large majority 

of observational studies include no adjustment for the potential confounding effect of fine PM, 

the risk estimates from these studies are not “attenuated” but are rather confounded by the effects 

of PM2.5. 

Some of the studies that EPA cites to support this unproven assertion (e.g., Zeger et al.

2000) relate to exposure to PM2.5 rather than ozone. Since the ambient to personal correlation is 

higher for ambient PM2.5 and very low for ozone, exposure misclassification studies on PM2.5 

have no meaning or utility for evaluating exposure misclassification in ozone time-series studies. 

EPA should omit any reference in this section to studies that relate to PM exposure as they 

provide no useful information for ozone, a pollutant which demonstrates a very poor correlation 

between personal and ambient exposure. EPA should also delete the unsupported claim that the 

exposure error in ozone observational studies results in an underestimate of individual exposure 

and an “attenuation” of risks in ozone observational studies. As discussed above, these 

statements lack scientific support.. 

It is worthwhile to point out that one of the primary reasons for the poor correlation 

between ambient and personal ozone exposure is that ozone penetrates indoors is degraded on 

surfaces. The low indoor ozone concentrations, combined with the fact that people spend a great 

percentage of their time indoors, results in poor ambient to personal correlations for this 

pollutant. 

 
Exxon Mobil Corporation Comments - 21 

V. Because Fine Particulate Matter is a Major Confounder in Ozone Epidemiology 

Studies, the Proposal is “Double Counting” Potential Risks That Are Currently 

Being Addressed Under the Fine PM NAAQS. 

In the Proposed Rule, EPA further asserts that “the results from numerous multi-city and 

single–city studies indicate that 03 mortality associations do not appear to be substantially 

changed in multipollutant models, including PM10 and PM2.5.” 72 Fed. Reg. at 37,839. 

In order to arrive at this conclusion, EPA would need to have results from a number of 

studies that actually included consideration of ozone and various forms of PM in multi-pollutant 

models. In reality, there are very few time-series or other observational studies that have 

included PM2.5 with ozone. The key studies upon which EPA relies on for its risk assessment 

(Bell et al. and NMMAPS) do not include adequate adjustment for the effects of PM2.5 because 

there were no routine daily PM2.5 data available in the NMMAPS database. Adjustment for fine 

PM using PM2.5 annual data, as attempted by Bell et al. provides no real adjustment for the 

potential confounding effects of PM2.5 in acute time series mortality studies. Using an annual 

average fails to capture the daily and seasonal fluctuations in both PM2.5 and ozone levels that 

tend to occur in a parallel fashion. These daily and seasonal fluctuations are critical to timeseries analysis. EPA also incorrectly cites the results from Huang et al. (2005) to support this 

view . Huang et al. (2005) is one of the few studies that attempts to make any adjustment for the 

potential confounding affect of any size fraction of PM. In that study, the authors “found that 

associations between summer ozone and CVDRESP [(cardiovascular and respiratory)] mortality 

are sensitive to the confounding adjustment for PM 10.” (Huang et al. 2005, at summary). . 

EPA is currently controlling PM2.5 in order to reduce the risk associated with acute and 

chronic cardiopulmonary mortality. As discussed above, it is well known that ambient levels of 

PM2.5 are highly correlated with ambient ozone. Therefore, there is a very high likelihood that 

EPA is double-counting acute mortality risks for ozone and PM2.5 – a pollutant that EPA 

separately regulates to reduce acute mortality risks. 

EPA should delete from their proposal all language that references control or 

consideration of “PM” without referencing the size of the PM in question. Such language 

appears throughout the proposal. “PM” is not a criteria pollutant. Rather, PM10 and PM2.5 are 

separate criteria pollutants with separate NAAQS and control strategies. In discussing PM, EPA 

should indicate clearly what size fraction of PM they are referencing. The proposal should also 

be revised to note that the large majority of observational epidemiology studies that have been 

conducted, including the studies EPA considers “key studies”, have not addressed the question of 

confounding by PM2.5. 

VI. Panel Studies Fail to Provide Clear and Convincing Evidence of Potential Risk 

From Exposure to Ozone at Levels Below the Current Standard.

EPA relies on selective analyses of certain epidemiology studies (“field or panel studies”) 

and further selective data within these studies in drawing conclusions regarding potential risks 

from exposure to ozone below the current standard. Further, EPA overlooks the fact that the new 
Exxon Mobil Corporation Comments - 22 

panel studies suffer from many of the same weaknesses in these studies cited by EPA in 1997. 

In our view, the results of these studies cannot be used to support a revision of the standard. 

In their previous review, EPA indicated that all the available field or panel studies shared 

certain deficiencies. These included small numbers of subjects (which reduce statistical power), 

and the lack of time-activity measurements and significant data about individual response and 

their distribution. Furthermore, EPA stated that the independent effect of ambient ozone, as 

estimated by statistical models in epidemiological studies, is difficult, at best, to clearly 

differentiate from those of co-pollutants because ozone may be acting only as an indicator of the 

toxic potency of the ambient mixture of pollutants. This, in combination with measurement error 

and uncontrolled associations with other factors, led EPA to the conclusion that these factors 

complicated the analytical findings about the relationship among components of an ambient 

mixture and may not accurately disentangle the effects of ozone in a biologically appropriate 

fashion (1996 CD at 7-137). 

In the 2006 CD and 2007 SP and proposed rule, EPA ignores these important general 

methodological problems with the panel studies even though they are still applicable. These 

concerns, which appear to various degrees in the observational and panel studies cited by EPA, 

can be grouped as follows: 

• Study selection errors we'll call "positive effect study selection" including a) selecting 

studies which report increasing ozone health effects associated with higher exposure and 

ignoring studies which report decreasing ozone health effects with higher exposure b) 

within a study selecting only the data which report a increase in ozone health effects as 

ozone exposure increases and ignoring data which report a decrease in ozone health 

effects as ozone exposure increases. 

• The use of multiple statistical models and analyses without correspondingly adjusting the 

significance level; 

• Focus on the single highest result from amongst a series of results obtained through using 

multiple models and analyses (e.g., multiple smoothing functions, lags etc.) while 

ignoring all other results; 

• Use of results from lags with unrealistic biologic plausibility; 

• Reliance on single pollutant model results and failing to note that no adjustment was 

made for other pollutants; 

• Reliance on results that are not statistically significant; 

• Uncertainty introduced by assuming that ambient monitors provide an adequate surrogate 

for personal exposure to ozone; 

• Variability and uncertainty introduced by using self-administered peak expiratory flow 

rate (PEFR) as the key measure of pulmonary function effects; 
Exxon Mobil Corporation Comments - 23 

• Use of either morning or evening PEFR versus cross-day PEFR; and 

• Reliance on PEFR decreases on the order of 1 to 2 percent which have no clinical 

significance. 

A. EPA has ignored “non-positive” panel studies in favor of “positive” panel 

studies. 

 The key field studies on asthmatics cited by EPA in their proposed rule include the 

longitudinal studies by Mortimer et al. (2002) and Gent et al. (2003). (72 Fed. Reg. at 37,865). 

The studies by Ross et al. (2002) and Delfino et al. (1998) are also cited in the 2007 SP. (2007 

SP at 3-56). All of the panel studies on asthmatics selected by EPA relied on use of ambient 

monitors as a substitute for personal exposure. The single field study on asthmatics using 

personal exposure (Delfino et al. 1997) reported no association between ozone exposure and 

pulmonary function changes in asthmatics. This study is excluded from the EPA compilation of 

key studies. Also, EPA fails to cite the longitudinal study reported by Schildcrout et al. (2006). 

This was a study of asthma symptoms and inhaler use in 990 asthmatic children in eight North 

American cities. No association between exposure to ozone and symptoms or inhaler use was 

observed. 

 EPA cites the study on hikers by Korrick et al. (1998) as a key study. (72 Fed. Reg. at 

37,828). After providing multiple adjustments, these authors report a very small change in lung 

function associated with ozone exposure. However, as further discussed below, EPA fails to cite 

the study by Girardot et al. (2006). This study used a very similar design to that employed by 

Korrick et al. (1998), but did not report a significant association between ozone exposure and 

change in lung function. 

B. A critical review of the key panel studies cited by EPA underscores the 

weaknesses of panel studies and their limitations in determining risk from 

exposure to ozone levels below the current standard. 

 A critical review of the key panel studies cited by EPA in the proposal, Mortimer et al.

(2002), Gent et al. (2003) and Korrick et al. (1998) is provided below. A critical evaluation of 

some of the additional field studies cited in the 2007 SP appears in Attachment B. 

Mortimer et al. (2002)

 EPA places great reliance on the study by Mortimer et al. (2002). Attachment C provides 

a fully analysis of the concerns with peak expiratory flow rate (PERF) self-reported 

measurements. This was a longitudinal study that measured PEFR, and increased symptoms in 

asthmatic children in eight U.S. cities. The 98th percentile 8-hour maximum ozone levels were at 

or above 0.084 ppm in all eight cities in this study. The significant effects in single pollutant 

models were morning percent change in PEFR for lag day 3 and average 1-5 days; >10 percent 

decline in PEFR for lag day 4 and average days 1-5; and increased symptom incidence for lag 

days 2, 4 and average days 1-4. 
Exxon Mobil Corporation Comments - 24 

 There are several concerns with the study’s overall approach and the methodology and 

measurement techniques used. 

• Multiple lag times were used with no biologic justification. For an incidence of ≥ a 10 

percent decline in PEFR, the authors report that associations for ozone were not 

statistically significant for 1, 2, 3, 5, or 6 day lags, but were significant for a 4-day lag 

and average 1-5 day lag. An effect of ozone at this specific lag time, particularly at 4 days 

versus 0- or 1-day, is not biologically plausible. The results at 4 days also appear to drive 

the 1-5 days results. Picking one day amongst the various lags used suggests lag mining 

and increases the likelihood that a positive effect was the result of chance alone. Instead 

of making note of the lack of associations at biologically plausible lag times, such as day 

0 or 1, the authors instead focus on the results at 4-day lag, and attempt to develop a 

biologic explanation to support it. 

• Symptom score results were significant for lag days 2, 4 and average lag of 1-4 days, but 

the authors focus on the single result at lag day 4, ignoring the results at lag day 1 which 

was not statistically significant but more biologically plausible, as well the results at 3-, 

5-, and 6-day lag, which were not statistically significant. In multi-pollutant models, the 

risk ratios (RR) for symptom scores were reduced and non-significant. Use of ambient 

monitors as a surrogate for personal exposure, and the use of self-reported PEFR 

measurements, with high inherent variability, adds to the uncertainty of the results. 

• Co-pollutants had higher RRs than ozone both in single pollutant models and in the 

multi-pollutant models for symptom scores. Further, when SO2, NO2, PM10 were 

included with ozone in a multi-pollutant model for morning asthma symptoms, the 

relative risk for ozone was not elevated (RR=1.00, CI 0.75-1.43). The strongest signal 

for symptoms was observed for NO2 in this study. 

• While the authors suggest ozone showed stronger associations for PEFR than copollutants, no multi-pollutant models for PEFR were reported. Therefore, potential 

confounding by other pollutants is not addressed. As a result, the conclusion that ozone 

showed the strongest association for PEFR is not supported by the study results. 

• PEFR effects were limited to morning measures and were not significant for the evening 

measures. This raises an additional question. The authors assert that morning values are 

better indicators of susceptible asthmatics and that the lack of association with evening 

measures may be due to the use of asthma medication during the day and may reflect 

misclassification due to an inability to adjust for time the child spent outdoors or 

exercising. This logic does not provide an adequate rationale for explaining the 

differences between morning and evening effects. Ozone exposure at night is 

significantly less, so the morning effect is unlikely to be due to ozone. Daily medication 

use may attenuate the association in the evening, but outdoor activity would increase dose 

and PEFR decline. Without information on these confounding variables, the authors’ 

explanation is speculative and lack plausibility. Furthermore, there is essentially no 

correlation between ambient ozone and indoor ozone. The PEFR changes only occurred 
Exxon Mobil Corporation Comments - 25 

in the morning after no exposure to ozone all night long. Night is the one time during the 

day when activities for this age group can be assumed to be largely indoors and sleeping.. 

• It seems plausible to expect the percent change in PEFR and the 10 percent or greater 

decline to show significance on the same lag days. The authors, however, report that they 

are significant on different days, namely lags 3 and 4, respectively. As stated above, both 

of these associations occur at biologically implausible lag times. 

• Independent research results suggest that the PEFR and symptom score results are 

unreliable because of recording errors and potential “manufacturing” of data. Kamps et 

al. (2001) compared actual results from an electronic peak flow meter with results from a 

self-recorded diary in a group of 40 asthmatic children 5-16 years old. Among these 

affluent children only about 50 percent of the results in the diary were correct (the same 

as the electronic recording), about 25 percent of the diary entries were recorded 

incorrectly (not the same as the electronic recording and the differences could be as great 

as >160 liters/min). Brand et al. (1999) reported mean morning and evening PEFR 

values of 281 and 305 liters/min among asthmatic children in the same age range, 7-14 

years of age. This indicates the incorrect data entries could be off by about 50 percent or 

more. About 20 percent appear to be invented entries (PEFR value in written diary but 

no entry in the electronic recording). Because this study was hospital-based, with a wellmotivated, well-informed affluent population with relatively stable, moderately severe, 

persistent asthma, more reliable results might be expected. Redline et al. (1996) reported 

similar problems of unreliability among U.S. Hispanic and African-American inner-city 

children 5-9 years old. These studies suggest the PEFR results in Mortimer et al. (2002) 

are unreliable and the error rate is much larger than the effect measure of daily changes in 

daily PEFR, which is <1 percent or even the measurement of a 10 percent or greater 

decline in PEFR. 

 From these data, it is impossible to ascertain that an actual association for ozone exists, 

or, if ozone is the pollutant of concern from amongst the air pollution mixture. Reasons why 

such interpretations cannot be made include the following points: 1) there are no significant 

associations between symptoms and ozone in multi-pollutant models; 2) the ozone associations 

observed in the single pollutant models may be due to correlations with the other pollutants; 3) 

ozone has smaller RRs than co-pollutants in both single pollutant and multi-pollutant models; 4) 

the study relies on ambient monitors; and 5) the PEFR values are self-reported and have been 

shown by independent analysis to have an unacceptably high rate of error. 

 Finally, we find it surprising that EPA places so much emphasis on the results of 

Mortimer et al. (2002). In their draft Integrated Science Assessment for Oxides of Nitrogen 

Health Criteria (August, 2007), EPA dismissed the results of Mortimer et al. (2002), which 

reported no effects for NO2. 2007 Integrated NOx Science Assessment at 3-16. EPA also 

rejected the results of eight other studies that employed self-administered PEFR and failed to 

report a positive association. Id. The reason EPA provided for dismissing the results was as 

follows: 

Reliable data are notoriously difficult to come by using [home use] 

portable peak flow measuring devices (for example, see Wensley and 
Exxon Mobil Corporation Comments - 26 

Silverman, 2001). This may help explain why, in contrast to studies with 

supervised measurements, none of the nine studies using home peak flow 

measurements reported any significant associations with ambient NO2. 

Id. 

 It should be noted that the study by Mortimer et al. (2002) is listed amongst the nine 

studies that EPA rejected. 

 We find it inconsistent that EPA dismisses studies using self-administered PEFR when 

the results report no association (NO2), but place high reliance on the exact same study when 

they report small positive associations for another pollutant (Ozone). 

Gent et al. (2003)

EPA also places high importance on the longitudinal study by Gent et al.,. (2003), a study 

that examines the potential affects of PM2.5 and ozone on respiratory symptoms and medication 

use in children with asthma in Southern New England. According to the EPA’s McCluney 

Memoranda, the 4th highest ozone level in this area was 0.102 ppm. Gent et al. (2003) report 

that in asthmatics using maintenance medication, a same-day, 8-hour ozone concentration of 63 

ppb or higher was associated with a 30 percent increase in chest tightness. However, the results 

were marginally statistically significant [odds ratio (OR) 1.30, Confidence Interval 1.00-1.68] 

and the linear trend across all concentrations was not statistically significant (p = 0.99). 

Previous-day levels of 53 and 63 ppb or higher were also associated with increased chest 

tightness and shortness of breath respectively and linear trends were significant. RRs at >63 ppb 

was 1.11 and nearly significant (CI 1.00-1.24) and trend was nearly linear (p = 0.07). 

Chest tightness and shortness of breath (SOB) were the only symptoms with significant 

associations and the previous day 1-hour exposures showed similar strength of associations as 

the 8-hour associations. The remaining analyses (co-pollutant models with PM2.5 and medication 

non-users) only reported results for 1-hour O3 exposures. The only consistent and significant 

associations were for chest tightness and SOB (to lesser extent) with significant associations in 

both single and co-pollutant models and for both same day and previous day 1-hour ozone (and 

previous day 8-hour ozone). (see Figure 1 for chest tightness results.) SOB showed similar 

trends but associations were not as strong and the models fit the data less well. There were no 

associations with bronchodilator use and no associations among asthmatic children not using 

medication (non-users). 

There are several concerns with this study. 

 

• The study did not control for relative humidity. Independent studies, including the study 

by Ross et al. (2002) listed by EPA as a key study, have shown that this variable alone 

has been associated with pulmonary function changes. Maximum daily temperature was 

the only weather variable included in the logistic regression models. 

• There are serious concerns about the method used to assess exposure in the study. As 

explained previously, the ambient ozone measurements used have been shown to be a 
Exxon Mobil Corporation Comments - 27 

very poor substitute for personal ozone exposure. Furthermore, the exposure metric used 

in this study was the average 8- or 1-hour ozone levels from 14 area-wide ambient 

monitors spread over a 52-mile area. There was a wide variation in levels across this area 

(range 47-97 ppb) and no link was made between the residence of the child in the study 

and individual monitor. Therefore, the true exposure of the individuals in the study is 

unknown and exposure misclassification is apparent in this study. This makes it 

impossible to determine if effects are occurring above or below any stated concentration 

level. 

• The symptoms were all self-reported and are completely subjective. An objective 

measure of effect, bronchodialator use, did not validate or confirm the increase in 

symptoms. Bronchodilator use provides a more objective estimate of effect. The lack of 

association (i.e., no increased bronchodilator use with increased ozone concentrations) 

tends to discredit (or at least not confirm or validate the symptom rate) and provides 

some evidence that if the symptom associations are correct the symptoms are not severe 

enough to seek relief. 

• It is not clear why there were no effects observed among asthmatics not using 

maintenance medication. 

• There is no mention of a standardized questionnaire for assessing symptoms. A 

standardized questionnaire is essential to provide assurance that the symptom response is 

always the same over time and the between-individual interpretations are similar. 

Without information on the administration and standardization of questions, and lack of 

confirmation by objective data, it raises questions about the significance of the effect 

measures. 

 Overall, because of the weaknesses this study provides, it cannot be relied upon to 

support an independent effect of ozone on symptoms in asthmatic children. 

Korrick et al. (1998) 

 Korrick et al. (1998) evaluated the effects of ozone, PM2.5 and strong aerosol acidity on 

the pulmonary function of adult hikers in the Mt. Washington area. EPA indicates the 4th highest 

maximum ozone during the period of study as 0.087 ppm (1991) and 0.072 ppm (1992).1 After 

adjusting for multiple confounding factors, they report a very small decrease in pulmonary 

function attributed to ozone. The complex set of variables the authors state they adjusted for 

include age, hours hiked, sex, former versus never smoker status, history of physician-diagnosed 

asthma, severe wheeze symptoms over carrying a backpack, reaching the summit and mean 

ambient temperature during pre-hike and post-hike spirometry. 

 There are several concerns with the results of this study. 

 

1

 L. McCluney August 23, 2006 Memorandum, Development of descriptive statistics for 8-hour daily maximum 

ozone data from epidemiologic studies (“McCluney Memorandum”). 
Exxon Mobil Corporation Comments - 28 

• It is not clear from the publication how some of the adjustments, such as severe wheeze 

or carrying a backpack, or reaching the summit, were made. This is critical since the 

adjustments can have a major influence on the results. 

• The authors used five different statistical models to assess the relationship between ozone 

and pulmonary function changes (quintile analysis, non-parametric smoothing linear 

regression, piecewise linear regression, and logistic regression.) This raises the question 

of multiple comparisons. To minimize the possibility of reporting findings that are due to 

chance alone, for this large number of comparisons, the authors should have used a more 

stringent level of statistical significance (p < 0.01). 

• The authors used the convention of change per 50 ppb ozone rather than the normally 

used concentration of 10 ppb ozone. For example, the mean FEV1 change attributed to 

50 ppb ozone is 2.6 percent. This change is not biologically significant or meaningful. 

Using the normal convention of change per 10 ppb ozone, the FEV1 reduction is only 0.5 

percent, which is well below accepted criteria for biological significance. 

• When adjustment for PM2.5 and aerosol acidity were included, the pulmonary function 

changes attributed to ozone were not statistically significant. Therefore, this study 

provides no evidence for an ozone-specific or independent change in pulmonary function. 

• The results by Korrick et al. (1998) are not confirmed by the results of Girardot et al.

(2006), a study using a very similar design. Girardot et al. (2006) evaluated the effects of 

ambient PM2.5 and ozone on the pulmonary effects of hikers in the Great Smoky 

Mountain National Park. The number of individuals in the study, the measures of 

pulmonary function, the number of study days, the methods used to assess exposure, and 

general methods of analysis were comparable in both studies. The only meaningful 

differences were related to the larger number of pulmonary function measurements 

excluded and slightly longer hiking time (5.0 versus 8.0 hours) in the study by Girardot et 

al. (2006). Also, the ozone levels were slightly higher in the study by Girardot et al.

(2006) (48 versus 40 ppb) and the elevation level to which the hikers climbed was also 

greater (1,538 versus 620 feet). In both studies, the level of PM2.5 was 15 ug/m3

. 

Girardot et al. (2006) reported no statistically significant responses in pulmonary function 

associated with ozone exposure. 

There is another way to view the one-pollutant data results by Korrick et al. that offers an 

alternate conclusion. An alternative analysis used in setting occupational exposure levels shows 

that the slope of the exposure response function is essentially flat up to 40 ppb, where it shows 

negative slope. This is the reason the slope is steeper at concentrations >40 ppb. The 

significance test used by Korrick et al. is whether the slope is significantly different than zero 

change. Using this test, a significantly negative slope could be very small. The graphic display 

of these data indicate at the highest exposure level (74ppb is maximum) there is about a 2% 

decline in ▲FEV% (and ▲FVC %). At the lowest exposures of ~20 ppb, ▲FEV% is close to 

0% change. If a group decline of -5% or -10% is considered, consistent with American Thoracic 

Society’s guidelines for a clinically significant effect, these data do not suggest a group effect in 

the range of the exposures (below about 70 ppb). 
Exxon Mobil Corporation Comments - 29 

VII. New Studies of Emergency Department Visits and Hospital Admissions Do Not 

Provide Additional Evidence to Support Health Effects From Exposure to Ozone at 

or Below the Current Standard. 

A. The evidence regarding the association between ambient ozone exposure and 

respiratory hospital admissions has not changed significantly since the 1997 

review. 

The potential health effect relationship between ambient ozone and hospital admissions 

and emergency room visits was identified in the establishment of the existing 8-hour standard. 

In the 1996 CD, EPA concluded that there was strong evidence that ambient ozone exposure can 

cause significant exacerbations of pre-existing disease in the general public (1996 CD at 7-191). 

In the 1996 SP, EPA noted that a number of epidemiological studies have shown a consistent 

relationship between ambient exposure and acute respiratory morbidity in the population (1996 

SP at 40). Further, EPA noted that ozone air pollution can account for a portion of summertime 

hospital admissions and emergency room visits for respiratory causes in asthmatic individuals, as 

well as the general population. Id. 

In 1996, EPA used concentration response functions (CRFs) from the studies published 

by Thurston et al. (1992 and 1994), Schwartz et al. (1992 and 1994 a,b,c), Burnett (1994) and 

Delfino et al. (1994), and a linear exposure response model, to estimate excess hospital 

admissions above a background level of 40 ppb. EPA estimated that ozone may account for 

roughly one to three excess summertime respiratory hospital admissions (asthma, pneumonia, 

COPD) per 100 ppb ozone per million persons. The risk assessment in the 1996 review 

presented estimates for excess respiratory-related hospital admissions related to ozone 

concentrations in New York City. In the 1997 final rule, EPA indicated that the Administrator 

considered the results of the exposure and risk analyses, and key observations and conclusions 

from these analyses in putting effects considered adverse to individuals into a broader public 

health perspective and in making judgments about the level of a standard that would be requisite 

to protect public health with an adequate margin of safety. (62 Fed. Reg. at 38,856). EPA also 

noted that there was no discernible threshold at or below which health effects would not occur. 

(62 Fed. Reg. at 38,864). 

In 2006, EPA again concluded that “positive and robust associations” were found 

between ambient ozone concentrations and various respiratory hospitalization outcomes, when 

focusing particularly on results from warm season analysis (2006 CD at 7-175 and 8-77). In the 

risk assessment conducted in 2006, EPA estimated hospital admissions for respiratory illnesses 

(age 30+ in Los Angeles, age 65+ in Cleveland, all ages in New York), asthma related (all ages 

in New York) and pneumonia (age 65+ in Detroit). The concentration response functions 

(CRFs) EPA used for their 2006 risk assessment for hospital admissions were derived from the 

studies by Thurston (1992), Schwartz et al. (1996), Linn et al. (2000), and Ito et al. (2003). 

Using a log linear concentration response model, EPA estimated reductions in health risks 

associated with given reductions in ozone as a percentage of the baseline incidence. Where 

possible, EPA used county-specific mortality incidence for the year 2002 from CDC (2005) (see 

Table 5-6 of the 2007 SP). Instead of using a Policy Relevant Background (PRB) of 40 ppb, 
Exxon Mobil Corporation Comments - 30 

EPA estimated hospital admissions above estimated monthly background levels for 12 urban 

areas using simulations from the GEOS-CHEM model. The ozone concentrations were 

generally in the range of 15-35 ppb. As discussed later on in these comments, the decision to 

change the PRB definition used in the 1997 rule accounts for over 95% of the risk reduction 

estimated by EPA from lowering the primary standard. As discussed below, this important 

change appears arbitrary because it lacks adequate scientific support. 

Because EPA concluded in 1996 that there was strong evidence that ozone exposure is 

associated with respiratory hospital admissions, the new epidemiology information included in 

this review does not significantly alter the evidence for revising the standard beyond the 1997 

revision. Figure 1 in the proposed rule presents the results of effect estimates from various 

observational studies grouped by health effect endpoints. (72 Fed. Reg. at 37,842). It is 

interesting to note that many of the studies cited were reported at or before 1997. Second, the 

risk estimates for the studies reported post-1997 are not different from those reported before 

1997. Therefore, from this figure, one could conclude that the risks for respiratory hospital 

admissions presented by ambient exposure to ozone have not changed since 1997. As a result, 

EPA should clearly state that their conclusions concerning the associations between ambient 

ozone exposure and respiratory hospital admissions have not changed since 1997. 

B. The observational epidemiology studies on hospital admissions suffer from 

the similar scientific concerns as the field studies. 

Ozone observational epidemiology studies on hospital admissions suffer from the similar 

scientific concerns as per the field studies. These include: 

• using multiple statistical models and analyses without correspondingly adjusting 

the significance level; 

• focusing on the single highest result from amongst a series of results obtained 

through using multiple models and analyses (e.g., multiple smoothing functions, 

lags etc.) while ignoring all other results; 

• using results from lags with unrealistic biologic plausibility; 

• relying on single pollutant model results and failing to note that no adjustment 

was made for other pollutants; 

• relying on results that are not statistically significant; and 

• the uncertainty introduced by assuming that ambient monitors provide an 

adequate substitute for personal exposure to ozone. 

A critical review of the four key studies on hospital admissions that EPA has used in their 

current risk assessment is included below. 

• One of these studies (Thurston et al. (1992)) was used by EPA in their last review 

and provides no new information. 

• A second study by Linn et al. (2000) was conducted in Los Angeles, which has 

some of the highest ozone levels in the United States. However, Linn et al. (2000) 

report no statistically significant association between ozone and hospital 

admissions. Linn et al. (2000) note that their findings are supported by a time 
Exxon Mobil Corporation Comments - 31 

series study of asthma admissions, which reported positive associations with PM 

but not ozone (Nauenberg et al. 1999). Linn et al. suggests that “the tendency of 

ozone to decrease indoors, where most people spend most of their time, might 

attenuate morbidity/ozone relationships.” 

• A third study by Ito et al. (2003) focused on evaluating the effects of PM2.5 air 

pollution. As a result, ozone was only included superficially as a co-pollutant. 

The study serves as an example to illustrate that the risk estimates in time-series 

studies are in fact not robust to changes in various changes in the underlying timeseries statistical model. This study, also one of the few to consider potential 

confounding by PM, serves to illustrate how including fine PM reduces the ozone 

risk estimates. 

• The fourth study by Schwartz et al. (1996), also available at the time of the last 

review, illustrates the difficultly in developing a statistical model that adequately 

accounts for meteorological factors in the case of ozone, a pollutant whose 

ambient levels are driven by high temperatures. 

Thurston et al. (1992): 

The study suggests that risks may be due to the confounding pollutants and not ozone. 

Thurston et al. (1992) evaluated the association between ambient hydrogen ion (H+), sulfate, and 

ozone on daily hospital admissions for total respiratory causes and asthma in Buffalo and New 

York City. Regressions were performed for the summer months. Ozone was reported as having 

the highest mean estimates for asthma admissions but H+ consistently showed the highest 

relative risk estimates. Because the results from this study were also used in the 1996 Risk 

Assessment, the use of these data adds nothing to EPA’s knowledge base for this review. 

Linn et al. (2000): 

Linn et al. (2000) evaluated the association between ambient carbon monoxide, nitrogen 

dioxide, PM10, and ozone, and hospital admissions for cardiopulmonary illnesses in metropolitan 

Los Angeles. Regressions were performed for the entire population and for subgroups defined 

by season, region or personal characteristics. Carbon monoxide demonstrated the strongest 

relationship with hospital admissions. As clearly noted by the authors, ozone associations with 

hospital admissions were either less than zero (negatively associated with ozone) or slightly 

positive but otherwise not statistically significant. Therefore, in their risk assessment, EPA 

failed to consider the negative coefficients and used the positive coefficients that failed to reach 

statistical significance. It is important to note that this study was conducted in Los Angeles, 

which has some of the highest ozone levels reported in the United States. The authors noted that 

the results of their study was in agreement with a similar time-series study that examined the 

potential association between ambient ozone and hospital admissions in asthmatics in Los 

Angeles, which also failed to report statistically significant associations (Nauenberg et al. 1999). 

Ito et al. (2003): 

Ito et al. (2003) evaluated the association between PM components (PM10, PM2.5, PM2.5-

10, sulfate, and H+) with daily mortality and morbidity in Detroit, Michigan. Levels of gaseous 
Exxon Mobil Corporation Comments - 32 

pollutants including sulfur dioxide, nitrogen dioxide, and ozone were also available. This study 

was part of the HEI-sponsored re-analysis of time-series studies conducted subsequent to 

discovery of the generalized additive models (GAMs). Ito et al. reported that, generally, both the 

GAMs with stringent convergence criteria and GLMs [Note: Needs definition.] resulted in 

smaller estimated relative risk than those reported in the original study. Further, sensitivity 

analyses using various weather models and degrees of freedom (df) of time trend smoothing 

indicate that the extent of difference in RR estimates across different model specifications can be 

larger and more serious than that caused by the GAM convergence criteria. Since the study 

focused on evaluating various forms of PM, only limited results are presented for ozone. 

However, for both hospital admissions, pneumonia and COPD, half of the coefficients were not 

statistically significant. In particular, those at biologically plausible lag times of 0- or 1-day lag 

were not significant. This is reflected in the various risk estimates that EPA presented, which 

vary from -1.8 to +1.5% for pneumonia, and -0.9 to +0.9% for COPD. This study provides no 

clear evidence for an association between ozone and hospital admissions. 

Schwartz et al. 1996:

Schwartz et al. (2006) provides a single estimate of hospital admissions in Cleveland 

associated with ambient ozone, PM, and sulfur dioxide of 1.09, 1.12, and 1.24, respectively, for 

each 100 micrograms/m3 increase in the pollutant. The publication by Schwartz et al. (1996) is 

actually a review paper on time-series methodologies. The paper serves to illustrate the 

significant bias embedded in the choice of models, and the difficulties in adequately adjusting for 

seasonal, day-of-the-week and weather factors. Schwartz et al. indicate that “care must be taken 

to use diagnostics, including plots, to avoid over and under control. Over adjustment for these 

factors can result in associations for air pollution that are not statistically significant. Therefore, 

the analyst needs to provide the “correct” amount of control. However, the criteria for providing 

the correct amount of control have not been defined, and remain a recognized and significant 

problem in time-series analysis (HEI 2003). Schwartz et al. provide only their single 

recommended model and results without any information on how alternative methods to adjust 

for seasonal, day-of-the-week, and weather factors may have influenced the risk coefficients. 

Also, it is important to note that this paper was published prior to the discovery of the GAM 

problems, which were also evaluated by HEI in 2003. Therefore, the estimates are unadjusted 

for possible influences of the use of default convergence criteria. Potential problems concerning 

use of the appropriate default convergence criteria and time-varying smoothing functions that 

have influenced the results of many time-series data sets and studies have not been explored in 

this data set. 

Burnett et al. (1997): 

Burnett et al. conducted a time-series study investigating respiratory hospital admissions 

and air pollution in 16 Canadian cities for 10 years from April 1981 through 1991. 2 EPA reports 

the range of 4th highest maximum ozone concentrations in these cities as 0.035-0.138 ppm. 

Ozone was the pollutant of interest with adjustments for SO2, NO2, CO, soiling index (a 

surrogate for PM) and dew point temperature. The strongest associations identified were with 

 

2

 McCluney Memorandum indicates 4th highest ozone level in study was below the current 8-hour NAAQS in some 

cities in this study. 
Exxon Mobil Corporation Comments - 33 

maximum hourly ozone concentration (selected from daily average, 8:00 a.m.-8:00 p.m. average, 

maximum 8-hr running average) and for lag 1 (day before admission) that were selected from 

lags 0, 2, 0+1, 0+1+2 and 1+2. Thus results were presented only for maximum hourly 

concentration measured on the day before admission (lag 1). For the co-pollutants the strongest 

associations were with lag 0, which was the lag period used to control for potential confounding 

from pollutants. There were no associations with SO2 and NO2. Soiling index was only 

available for 11 cities so these co-variables were not included in adjustments. Adjustments for 

temperature removed associations with ozone in two cities (Montreal, Vancouver). Results were 

presented for a 30 ppb increment in ozone, which is the difference between 95th percentile and 

the mean. Overall, the model shows a 3 percent increase in admissions per 30 ppb increment in 

hourly ozone. 

The overall association with ozone was 1.031 in the multi-pollutant model containing CO 

and dew point temperature (DP). The authors conclude there was a statistically significant 

association between ozone and respiratory diseases severe enough to require hospitalization at 

low concentrations in diverse climates and air pollution profiles (across the breadth of Canada) in 

summer but not other seasons. 

 This study suffers from several serious limitations that undermine the authors’ 

conclusions: 

• All of the general limitations of ozone time-series studies discussed above are present 

given their design, including use of ambient monitors with poor known correlation to 

personal exposures, and concerns with ozone time-series model specification. 

• All of the relative risks attributed to ozone are very small from an epidemiologic 

perspective and may be the result of uncontrollable confounding bias. For instance, 

while no association was observed for the winter, the positive association observed in 

spring were (RR=1.04), summer (1.05) and fall (1.03) with both spring and summer 

statistically significant (CI = 1.01-1.07 and 1.03-1.07 and 0.998-1.06, respectively). The 

RR for winter was 0.99 (0.96-1.03). These findings bring into question the concept of 

“no threshold” for acute ozone mortality. However, fall and winter are similar in some 

respects. They have higher daily admission rates (16.3 and 17.1 per 106

 compared to 

11.1 for summer), similar 95th percentile (38 and 42 ppb) and mean ozone (21 and 26 

ppb), respectively. In fact, just looking at the seasonal data and not the statistics, 

suggests no real differences in risk estimates by season even though there are clear 

differences in ozone concentrations between spring/summer and fall/winter. 

• Correlations of air pollutants and temperature with summer ozone are low and sometimes 

negative in the study. The magnitude of the confounding effect from these factors is not 

known. A confounding effect can be quite small and still have an effect. For example, 

the authors comment that in Montreal and Vancouver the unadjusted RRs were 1.02 and 

adjustment for dew point eliminated the associations even though the correlation was low 

(~0.23). 
Exxon Mobil Corporation Comments - 34 

• There was no apparent age effect as might be expected. The relative risks were similar 

for those over 65 (RR = 1.04) and those under 65 (RR = 1.045). 

 

• The authors cite several studies where associations between ozone and respiratory 

hospitalizations were reduced to non-significance after controlling for weather and/or 

other pollutants. Dew point in the Burnett et al. model eliminated the association in 

Montreal and Vancouver but only changed the ozone associations slightly (usually 

reduced associations) in the other cities. The model results seem somewhat fragile, for 

when Montreal and Vancouver are removed from the model the RR are generally 

increased for most cities. Why would removal of two out of 16 cities affect the 

associations with ozone in the other 14 individual cities? 

 

VIII. New Evidence on Acute Mortality Suffers From the Same Weaknesses as the 

Evidence in 1997 and Fails To Support Causality. 

A. The evidence on acute mortality has not changed; EPA’s interpretation of 

the evidence has without a reasonable explanation for the change or 

reference to clear criteria. 

In the 1996 CD and 1996 SP, EPA concluded that one of the two most useful studies on 

this topic, Kinney and Ozkaynak (1991), indicated statistically significant effects by ozone on 

short-term (acute) human mortality. However, the other relevant study on short-term (acute) 

mortality, Dockery et al. (1992), did not show any ozone association. The Dockery et al. (1992) 

study employed more extensive climate and autocorrelation control methods and was conducted 

over a much shorter time period than the other study. EPA concluded that the sensitivity of the 

association reported in the one positive study to statistical modeling methods and to ozone 

concentration levels needed further investigation. (1996 CD at 7-161). Thus, although an 

association between ambient ozone exposure in areas with very high ozone levels (1-hour 

maximum ozone values of 0.2 ppm were reported Los Angeles in the study by Kinney and 

Ozkaynak (1991)), and daily mortality has been suggested, the strength of any such association 

remained unclear at that time of the 1997 review. (see 1996 CD at 7-161, and 1996 SP at 41-42). 

Furthermore, EPA indicated that while epidemiology studies can provide associations which may 

suggest causal relationship, such studies alone cannot provide clear causal relationships due to 

the presence of confounding variables (e.g., heat, humidity, other pollutants (see 1996 SP at 45)). 

Since the last review, a number of additional time-series studies on acute mortality have 

been conducted. According to EPA, some of the more important studies include those reported 

by Bell et al. (2004), Huang et al. (2005), and Schwartz et al. (2005). (72 Fed. Reg. at 37,866). 

Also, a number of meta-analyses of ozone time-series studies are now available, including Bell et 

al. (2005), Ito et al. (2005) and Levy et al. (2005). Based on this information, EPA has 

concluded it is “highly suggestive that short-term O3 exposure directly or indirectly contributes to 

nonaccidental and cardiopulmonary mortality.” (72 Fed. Reg. at 37,866). These studies are 

examined in the following sections. 

 

Further, EPA concluded there is no threshold for this effect, acute mortality is assumed to 

be occurring at any ozone concentration even as low as 10 ppb (SP at 3-32). 
Exxon Mobil Corporation Comments - 35 

EPA’s new conclusion regarding the risk of mortality from exposure to ozone is not 

based on a change in the quality of the epidemiology evidence since 1997, but instead on EPA’s 

willingness to base causal inferences (or rather hypotheses) on observational epidemiology 

studies without additional significant evidence, including strong evidence on biological 

mechanism. 

B. EPA is incorrect in concluding that the mortality studies are consistent and 

add to the coherence of the data ; this treatment is not supported by the 

evidence. 

EPA incorrectly concludes that the results of the ozone acute mortality studies are 

consistent. All of the authors of the three meta-analyses cited by EPA note the high degree of 

heterogeneity or variability in the estimates from individual cities, and the fact that the results for 

many of the individual cities did not reach statistical significance. Table 2 illustrates this point. 

The estimated percentage increase in CVDRESP mortality (per 10 ppb increase in ozone during 

June through September) in the 19 largest cities in the NMMAPS study ranged from –3 to 8 

(over an order of magnitude range), and the estimated increase for total mortality in the same 

cities ranged from 0 to 1.7 (per 10 ppb increase in ozone during the full year), with little or no 

similarity in the relative rankings of the 19 cities (Spearman rank correlation coefficient 0.12). 

More importantly, because the meta-analyses approach assumes homogeneity in the data 

from across the cities, the high variability results in an underestimate of the confidence interval, 

or uncertainty, in the risk estimates. This error in turn produces an overestimate of the statistical 

significance of the estimated risks. Abandoning the assumption of homogeneity would likely 

result in an increase in the variability and the resulting confidence intervals. This in turn would 

reduce the statistical significance of the estimated risks. 

There was also significant heterogeneity in the estimated increases in the CVDRESP 

mortality and total mortality as reported in the papers by Huang et al. (2005) and Bell et al.

(2005), and a lack of consistency in the relative rankings of the two sources of mortality in the 

two papers. Even though the two papers measured different outcomes and should not be 

expected to have equal estimates, they are based on the same underlying data from NMMAPS 

and should be of a similar order of magnitude and produce a similar ranking of sources of 

mortality across the cities. However, they do not have either characteristic (see Figure 1). As 

noted above, the rank correlation between the two measures is 0.12. After removing the three 

points at the far right of the plot, the rank correlation is still a non-statistically significant 0.29. 

Similarly, in Bell et al. (2005), the reported results for the 95 cities for the estimated 

percentage increase in the CVDRESP mortality (per 10 ppb increase in ozone during the year) is 

0.65 with a 95 percent confidence interval of 0.28, 0.94; the corresponding value for the 19 

largest cities as reported in Huang et al. (2005) was 1.25 with a 95 percent confidence interval of 

0.47, 2.03 (per 10 ppb increase in ozone during June through September). The estimated value 

for the 19 cities is double that of the 95 cities even though both papers used a similar method of 

analysis, but different ozone measuring seasons. 
Exxon Mobil Corporation Comments - 36 

Table 2 

Illustration of Heterogeneity of Results Within a Study, 

And Study-to-Study Variability 

City Specific Estimate of Percent Change in Total or CVDRESP 

Mortality Per 10-ppb Change in Ozone Levels, With (95% CI) 

City CVDRESP Mortality 

(Huang et al. 2005) 

Total Mortality 

(Bell et al. 2004) 

Santa Ana/Anaheim -3.03 (-6.40, 0.35) 0.31 (-0.25, 0.63) 

San Bernardino -0.98 (-3.87, 1.91) 0.61 (-0.34, 1.58) 

Chicago -0.39 (-2.38, 1.69) 0.91 (0.20, 1.57) 

Pittsburgh -0.05 (-3.17, 3.07) 0.77 (-0.19, 1.67) 

Phoenix 0.05 (-3.71, 3.81) 0.83 (-0.20, 1.78) 

San Antonio 0.22 (-3.84, 4.28) 0.01 (-0.84, 1.11) 

Miami 0.68 (-3.51, 4.86) 0.37 (-0.19, 0.56) 

Atlanta 0.77 (-3.45, 4.99) 0.20 (-0.72, 1.34) 

Los Angeles 0.79 (-0.69, 2.28) 0.20 (-0.30, 0.87) 

Houston 1.11 (-1.62, 3.84) 0.83 (0.02, 1.55) 

San Diego 1.58 (-1.50, 4.67) 0.12 (-0.65, 1.02) 

Detroit 1.88 (-1.52, 5.27) 0.77 (-0.22, 1.75) 

New York 2.33 (0.93, 3.73) 1.71 (1.09, 2.31) 

Dallas / Fort Worth 2.35 (0.05, 4.66) 1.10 (0.40, 1.76) 

Philadelphia 2.42 (-0.22, 5.07) 1.27 (0.34, 2.12) 

Cleveland 2.49 (-0.62, 5.60) 0.61 (-0.37, 1.66) 

Oakland 7.97 (0.58 , 15.36) 0.53 (-0.54, 1.79) 

Seattle 8.08 (2.94 , 13.21) 0.45 (-0.62, 1.61) 

San Jose 8.18 (0.61 , 15.75) 0.58 (-0.50, 1.67)

Negative values imply ozone exposure decreased acute mortality risk. 

C. EPA’s Case for Causality Fails When Evaluated Against Established 

 Scientific Criteria for Causality. 

The evidence supporting the causality of "acute mortality from exposure to ozone" 

remains weak, consistent with EPA’s conclusion in 1997. EPA has failed to account for 

significant uncertainties in the time-series data and the lack of clear evidence of a biological 

mechanism of action. In the key chronic cohort study upon which EPA placed great reliance in 

their assessment of fine PM (Pope et al. (2002) at 1139), no chronic mortality is reported for 

ozone. EPA makes no attempt to explain the inconsistency of this result with the results reported 

in the time-series studies. 

EPA should develop a more scientifically balanced interpretation of the entire evidence 

using the Hill criteria, as discussed below and summarized in Table 3. The following discussion 

focuses on causality issues related to acute mortality. However, many of the general concerns 

raised are equally applicable to evidence from ecological studies evaluating morbidity effects. 

 1. Strength of Associations. 

The Hill causal criteria Hill, A. (1965) are often considered the gold standard for 

evaluating epidemiology studies and provide some objective guidelines. According to the Hill 

causal criteria, the greater the magnitude of the risk ratio between exposed and non-exposed, the 

more likely the association is causal. More importantly, the effects of exposure should be greater 
Exxon Mobil Corporation Comments - 37 

than the potential effects of hidden uncertainty or the risk estimates will be inaccurate due to 

probable confounding and bias. A rough guideline in traditional epidemiology is that relative 

risks >1.5-2 fold are necessary to suggest causal association. Relative risks less than this are 

likely due to confounding. But a risk could be low and still infer causality if other criteria in the 

guidelines are satisfied. 

In reviewing the mortality data, EPA states that a pattern of positive and often 

statistically significant associations can be seen between mortality and respiratory morbidity and 

short-term exposure to ozone, even when considering both the magnitude and statistical strength 

of the associations. According to EPA, even though the magnitude of the effect estimates found 

between ozone and various health outcomes are generally small in size (magnitude), they are 

relatively consistent between studies. Further, EPA states that “the strength of association refers 

to the magnitude of the association and its statistical strength, which includes assessment of both 

effects estimate size and precision.” (72 Fed. Reg. at 37,823 and 37,837-38) 

This view directly conflicts with and is inconsistent with the Hill causal criteria. EPA in 

the CD and Staff Paper and July 11 proposal does not use the Hill causal criteria nor propose 

alternatives widely accepted in the health sciences community that can be referenced. 

Statistical significance of the association and statistical power of effect estimates are not 

considerations about the strength. They are considerations about whether the results could be 

due to chance or random error. These items are more appropriately included in a separate 

discussion on robustness. Similarly, consistency is not related to the strength of association and 

should be not presented in a discussion on the strength of association. 

EPA’s presents a contrary and incorrect view, as presented in the proposed rule; EPA 

should remove the discussions on robustness and consistency from the proposed rule’s section on 

strength of associations. The final rule should include a proper discussion of robustness and 

consistency and place these criteria in the context of the Hill causal criteria. 

The relative risks of the ozone mortality studies are in the range of 1.000-1.008 and are 

therefore very weak. Associations of less than 1 percent (i.e., 1.01) are particularly susceptible to 

hidden uncertainties of confounding and bias. To accurately estimate an effect in the 1.001 to 

1.008 range, there must be essentially complete control of all confounding and bias. In 

epidemiology studies of acute mortality, complete control is not possible. 

Furthermore, based on the work by Bell et al. (2005), the 1.008 risk estimate from the 

meta-analyses is biased due to probable “publication bias” as well as other biases. The Bell 

study shows that adjustments for publication bias assessed by multi-city analysis suggest an 

overall effects estimate is about 1.0025, or about 1/3 the quoted estimate of 1.008. If lags of 1 or 

2 days were used, the overall estimate would be reduced to less than 1.002 (Bell et al. 2005). 

Bell’s conclusion in 2005 is supported by other studies. Ito et al. (Ito et al. 2005) also 

reported several effect estimates besides 1.008. For example, 1.006 was an estimated effect level 

when PM was in the model. Selection of a different weather model could produce a 2-fold 

change in estimate, which reduced the effect estimate to about 1.004 or 1.003 based on the model 
Exxon Mobil Corporation Comments - 38 

used in the NMMAPS analysis. Similarly, Levy et al. (2005), reported that using 1-2 day lags 

instead of a 0-day lag reduced the effect estimate to about 1.004. Adjustments for other biases 

such as publication bias, a different weather model, and other pollutants would likely reduce this 

estimate even further. 

In conclusion, based on the Hill causal criteria, the associations between ambient ozone 

concentrations and acute mortality are very weak and do not support a causal association. If 

important factors such as lags, weather model and publication bias are considered, the 

associations become even weaker. It is reasonable to conclude that precision of an estimate in 

epidemiology studies (especially ecological studies) is something less than three and perhaps two 

significant figures. Given the inherent uncertainties and limitations in controlling for 

confounding, it is reasonable to assume that epidemiology results cannot ensure the precision of 

an estimate below 1 or 2 percent significance. The results reported by the acute mortality 

epidemiology studies suggest no association as the rounded-off estimates are 1.0 or 1.00 percent. 

 2. Robustness of Associations.

Considerations of robustness should consider two types of uncertainty: statistical 

uncertainty and hidden uncertainty. Statistical uncertainty is an evaluation of whether the 

findings are due to chance and is largely dependent on sample size. The 2006 CD mentions 

statistical significance and precision regarding strength of epidemiological evidence. (2006 CD 

at 7-3). But the magnitude of the effect estimate is independent of statistical significance, and 

both significance and sample size are more appropriately considered as a separate guideline for 

evaluating results. 

Similarly, the statistical power of an epidemiology study, such as the ozone mortality 

studies can be somewhat misleading. If the sample size is very large, then minuscule risk 

estimates of no plausible biological significance could be considered important and overpower 

hidden uncertainties. Evidence of minuscule risk and lack of biological significance can be seen 

when the upper or lower confidence interval is nearly the same as the risk estimate. This is the 

case in the 95-city study where the rounded-off risk estimate with 95 percent confidence interval 

is 1.01 (1.00-1.01). These confidence bounds provide a false sense of the exactness of the data. 

EPA incorrectly considers the mortality estimates to be robust. The Agency defines

robustness as stability in effect estimates evaluating the impact of alternative models, model 

specifications for temporal trends and meteorological factors, and potential confounding by copollutants. (See generally, 72 Fed. Reg. at 37,837). In judging the mortality results to be robust, 

EPA concludes that ambient concentrations serve as valid surrogate measures for aggregate 

personal exposure in time-series studies. EPA states that the ambient concentrations generally 

overestimate true personal exposure so the risk estimate is biased toward the null. EPA also finds 

that while adjustments for temporal trends and meteorological factors are critical, confounding 

for seasonal variability is “controlled effectively by stratifying analyses by season.” (2006 CD at 

7-24). Finally, EPA also believes that assessment of confounding by co-pollutants indicates 

adjustments for PM do not substantially change the risk estimates. (2006 CD 7-100 to 7-103) 
Exxon Mobil Corporation Comments - 39 

EPA’s conclusion regarding robustness is not supported by the data on ozone or 

established scientific guidelines. As described in detail in our comments, EPA’s own data from 

HEI sponsored studies (Sarnat et al. (2001, 2005, 2006)) presented to EPA and CASAC clearly 

demonstrate that there is a very low correlation between ambient and personal ozone exposure, 

and the correlation varies across cities. For example, the correlation was less than 20 percent in 

Boston and less than 10 percent in Baltimore. The wider published literature supports the low 

correlation. In our view, this invalidates EPA’s key assumption that ambient measurements are a 

valid surrogate for aggregate personal exposure. 

On the one hand, EPA overstates the importance of statistical significance in determining 

causality. Reporting only confidence intervals implies random sampling errors are the only 

uncertainties worth measuring or reporting. The p-value does not provide an answer for a causal 

question. While statistical significance is an important factor, it does not provide the final word 

on causality. Demonstrating statistical significance is not necessary for establishing causality. 

Similarly, demonstrating statistical significance is not sufficient for establishing causality. 

Therefore, overemphasis of statistical significance should be avoided as systemic error is usually 

greater than random error. As has been noted “the glitter of the t table diverts attention from the 

inadequacies of the fare.” (Hill 1965). The more important question is the “fare,” including 

evaluation of hidden uncertainties of measurement error, confounding, bias etc. Statistical 

precision (small p-value or narrow confidence interval) should not be equated with validity. 

On the other hand, EPA ignores statistical significance in their risk assessment. They 

routinely use results of epidemiology studies where the results are not statistically significant, but 

positive. In their risk assessment, EPA completely ignores the results of studies reporting 

negative coefficients. 

Hidden uncertainties include such things as confounding from co-pollutants, model 

choice (e.g., effect of smoothing in weather models, effect of different lags etc.), publication bias 

from choosing the largest effect in single studies (versus less subjectivity in model choice in 

multi-city studies) etc. These hidden uncertainties are more important than a precise statistical 

test, especially when sources of error are of greater magnitude than random error (Phillips et al.

(2004)). While it is still not possible to accurately quantify the hidden uncertainties in many of 

the ozone mortality studies, the series of meta-analyses on ozone mortality and some of the 

lessons from PM time-series studies indicate important hidden limitations that EPA has not 

adequately addressed. 

In Bates (2005), the author notes the high correlations of heat and ozone in the summer 

which makes it difficult to attribute individual effects to one or the other exposure. Ito et al.

make these limitations more explicit. According to Ito et al. (2005), weather adjustment models 

alone can change effect estimates by a factor of 2. Further, confounding of ozone-mortality 

associations in time-series studies are different from those of PM but may be even more 

problematic because of the unexplored analytical methods. Most of the time-series studies used 

the same regression designs to estimated ozone risks as were used to estimate PM risks. 

According to Ito, “adjustment for weather may not be appropriate because of the higher 

correlation of ozone with temperature than the correlation of PM with temperature.” (Ito et al.

2005 at 446). Models with smoothers fit the data better but have greater concurvity so “model 
Exxon Mobil Corporation Comments - 40 

validations are needed.” (Ito et al. (2005) at 455) In its 2003 review, HEI concluded that there is 

no objective or feasible method for selecting the appropriate model or amount of smoothing to 

adjust for weather (HEI, 2003). Ito et al. (2005) confirms this, noting differences of 1.1 percent 

between four different weather models and 0.4 percent differences between smoothing models 

with 12 df/y and 26 df/y. These hidden uncertainties on model choice exceed the reported effect 

estimates. Ito goes on to state that: “Statistical properties aside, it is not clear whether these 

models actually adjust for weather effects. Because daily fluctuations of weather and air 

pollution are related, it is possible that these models may ascribe some of the real pollution 

effects to weather” (Ito et al. (2005) at 455). Therefore model uncertainties should be taken into 

account. 

Goodman (2005) underscored the importance of publication bias when he noted that risk 

estimates from single-city studies are biased upward about 3-fold because of “cherry-picking” 

the strongest signal. According to Goodman, meta-analysis is particularly subject to bias as 

shown by the elevated effect estimates of single-city combined results relative to multi-city 

studies such as NMMAPS (Goodman 2005). This further indicates the presence of “publication 

bias” Bell et al. 2005). In general, the ozone meta-analyses have limited usefulness or ability to 

inform because of differences in analytical methods and because most studies have not 

adequately addressed influential factors (~90% are not applicable to use for regulations because 

substantial uncertainties remain) (Levy et al. 2005). 

On the other hand, single-city studies must be used with “caution” or not at all because 

they have about a 3-fold upward bias due to model choice (Bell et al. 2005). Ito et al. (2005), at 

455, noted the large influence of model choice on effect estimates by drawing attention to the 

“markedly different estimates” in the three cities analyzed by different authors. (Ito et al. (2005) 

at 447). In Amsterdam, London and Santiago the associations were positive for one set of 

authors and negative for the other set of authors (Ito et al. 2005). This clearly underscored the 

importance and potential bias in model selection. 

 3. Confounding by Co-Pollutants. 

EPA concludes in this section that the ozone effect estimates for mortality are robust to 

and independent of the effect of other pollutants. EPA is incorrect for the following reasons: 

First, very few of the existing time-series studies for ozone have included PM2.5 as a 

potential confounder. Most of the existing studies have evaluated potential confounding effects 

of “PM” using PM10. It is well known that a much higher correlation is observed for fine PM 

and ozone versus coarse PM, particularly in summer when ozone risk coefficients for mortality 

are higher. Further, exposure studies indicate that ambient ozone measurements are a better 

surrogate for personal exposure to PM2.5 than personal exposure to ozone. Levy et al. (2005) one 

of the few authors attempting to evaluate potential confounding by PM2.5, indicated that much 

more work is needed to explore potential confounding of the ozone mortality relationship by 

PM2.5. 

One of the key studies selected by EPA for their mortality risk assessment, Hueng et al.

(2004), observed significant confounding of the ozone mortality relationship when co-pollutants 
Exxon Mobil Corporation Comments - 41 

such as NO2, PM10, SO2 were included. In many cities, when these co-pollutants were included 

in the statistical model, ozone mortality coefficients were reduced to non-statistically significant 

levels. Thus, while the time-series studies indicate possible small mortality signal air pollution, 

it is impossible to determine which component of air pollution is most responsible for this signal. 

In fact, based on these studies, one could legitimately conclude that much of the acute mortality 

risk attributed to ozone is due to PM2.5 or other pollutants such as NO2 or SO2. At a minimum, 

the Hill causal criteria for adequate assessment of potential confounders has not been met. 

 4. Model Specification. 

EPA concludes that ozone effects on various health outcomes are robust to various model 

specifications. The data, however, suggests just the opposite, that model selection has a pivotal 

role in the results and remains a major confounder. 

In our view, the results of the recent meta-analyses have confirmed the important effect 

of model selection in the results of ozone time-series studies, in direct contradiction to the 2007 

SP’s position on the robustness of the models. Our view is shared by the Rochester group, who 

concluded “the meta-analyses provide evidence of disturbingly large publication bias and model 

selection bias” (Rochester Report 2007 at 43). 

Several investigators have shown that the choice of the degree of smoothing produces 

significantly different results. Thus results are not independent of model choice. For example, 

Ito et al. (2005) found a difference of 1.1 percent between quintile weather models and 4-

smoothing weather models, and a difference of 0.4 percent between smoothing models with 12 

df/year and 26 df/year. These same authors also found large city-to-city variations (difference 

between Detroit and St. Louis for example was 3.4 percent) that are due in part to model choice, 

such as controlling for air conditioning. Model uncertainties, such as these, could make 2-fold 

differences in risk estimates. According to the authors of the study, since these differences are 

often greater than the risk estimates themselves it was not clear whether these models “actually 

adjust for weather effects.” (Ito et al. 2005). 

A central issue in determining the model for analyses in time-series studies of air 

pollution is determining the appropriate degree of smoothing time. Overly aggressive smoothing 

may allow residual confounding, whereas inadequate smoothing may allow some or all of the air 

pollution effect to be incorporated into the smoothing term. According to the 2003 HEI review: 

“The best method for selecting the appropriate degree of smoothing needed to control any 

confounding bias remains to be determined. Furthermore, ... there is no gold standard for 

determining the appropriate degree of smoothing.” (HEI 2003 at iv). Determining the 

appropriate degree of smoothing is a matter of model choice by the investigator without clear-cut 

or standardized methods to follow and, in this sense, is arbitrary. This uncertainty, however, 

must be considered in determining robustness. 

As mentioned above, another problem relating to model choice is the decision to include 

or not include air conditioning as an ecological variable in the model. Air conditioning is of 

special importance as ozone formation is greatest on hot, humid days. Ambient ozone 

concentrations are higher than personal exposures because people spend most of their time 
Exxon Mobil Corporation Comments - 42 

indoors (and in air conditioning on hot, humid days). According to the Bates (2005) study, air 

conditioning reduces ambient ozone concentrations by approximately 85 percent, often to below 

the detection limit. As a result, Ito et al. (2005) at 455, conclude that access to air conditioning 

undermines even further the already poor correlation between ambient and personal exposure to 

ozone. Levy et al. (2005) at 463, confirm this point when their study found that ozoneassociated mortality/10 ppb 24-hour average decreases from 1.56 to 0% when air conditioning 

prevalence in a city increases from 0 to 60%. 

The importance and potential effect of model selection may even be greater in ozonemortality associations due to the complexities and differences in the ozone time-series studies 

compared to studies on PM. According to Ito et al. (2005), at 446, these differences “may make 

it difficult to interpret ozone effects of mortality.” 

Problems of model specificity are also related to investigator choices, such as to select 

the strongest signal. As discussed above, there are no criteria for how confounders, such as 

temperature and weather, will be addressed. As a result, model selection becomes arbitrary 

despite its potential impact on the results. For example, temporal trends and weather can have 

important effects on health. If there is no objective statistical test to determine whether these 

factors have been adequately controlled, there is no clear way to assure that the effect measured 

is due to ozone or a confounding bias. In the words of the 2003 HEI review, it has been shown: 

that for any continuous variable, no strictly data-based (i.e., statistical) 

method can exist by which to choose a sufficient number of degrees of 

freedom to insure that the amount of residual confounding due to that 

variable is small. This means that no matter what statistical method one 

uses to select the degrees of freedom, it is always logically possible that 

even if the true effect of pollution is null, the estimated effect is far from 

null due to confounding bias. 

(HEI 2003 at 267). Thus, it is impossible to adjust for temporal trends without external 

information on the appropriate degrees of freedom. This problem is one of the more serious 

difficulties in specifying the appropriate model. The lack of clear criteria for controlling for such 

an important confounder means that EPA cannot conclude that the results are robust or make 

inferences on causality based on these studies. Instead the results are dependent on model 

selection which becomes arbitrary in the absence of clear criteria. 

 5. Consistency. 

In several instances EPA emphasizes that the magnitude of the effect estimates is 

relatively consistent across the results of recently published studies of associations between 

short-term ozone exposure and mortality. As described by EPA, consistency relates to the 

persistence of an association between exposure and outcome in multiple studies of adequate 

power in different persons, places, circumstances and times. (72 Fed. Reg. at 37,840). EPA also 

states that “consideration of consistency or heterogeneity of effects is appropriately understood 

as an evaluation of the similarity or general concordance of results, rather than an expectation of 

finding quantitative results with a very narrow range.” Id. (quoting 2006 CD at 8-41). The 

consistency of results is cited by EPA as evidence of an effect from ozone exposure. 
Exxon Mobil Corporation Comments - 43 

A careful examination of the data, however, does not support EPA’s conclusion regarding 

consistency. There is a high degree of heterogeneity for cities reported by different authors, even 

when using the same underlying database (e.g., NNMAPS results by Huang versus Bell). There 

is also a high degree of heterogeneity cities in multi-city studies. Some of the areas with the 

highest ozone levels, such as Los Angeles and Atlanta, show highly insignificant Bayesian 

coefficients. While most authors report larger effect estimates in summer months, the study by 

Bell et al. which EPA places great reliance on, reports larger effect estimates for the full-year 

analysis, even though the opposite results was reported in the original NMMAPS analyses. 

Therefore, the results of the NMMAPS analyses are internally inconsistent. 

Our view on the lack of consistency is shared by the Rochester group, that concluded: 

“Despite the impression given in EPA’s criteria document and staff paper that these results are 

very consistent across different studies, closer scrutiny shows this not to be the case, even when 

the results are standardized with respect to ozone metric used.” (Rochester Report at 47). 

Ito et al. (2005) noted the large city-to-city variation in the cities included in their 

analyses. They report a large index of heterogeneity of 77 percent that would preclude any 

combining of the data into one final number as was done in their paper, even though they do 

report a combined result. The range of the estimated percent excess deaths was from 

approximately –9 to +9%. A similarly high degree of heterogeneity across cities was also 

observed in the study by Huang et al. (2005) (see Table 2). Ito et al.’s comment in the 

discussion that their results “are fairly consistent with results from other recent meta-analyses” 

ignores the important condition that the meta-analytic results are based on inappropriate, or 

heterogeneous, data. Other meta-analyses also suffer from the same condition as seen in the 

results of Huang et al. (2005) shown in Table 2. 

 As noted above, Ito et al. (2005) also noted the large influence of model choice on effect 

estimates by drawing attention to the “markedly different estimates” in the three cities analyzed 

by different authors. In Amsterdam, London and Santiago, the associations were positive for one 

set of authors and negative for the other set of authors. Further evidence of an inconsistent 

pattern for individual cities reported by different authors is illustrated by comparing the results 

from Bell et al. (2005) and Huang et al. (2005) (see Table 2). Although Huang et al. considered 

cardiovascular and respiratory mortality (per 10 ppb increase in ozone during June through 

September), and Bell et al. considered mortality (per 10 ppb increase in ozone during the full 

year), it would be expected that the relative rankings among the 19 cities would be much closer 

than they are (the rank correlation is 0.12). The results reported in Table 2, however, fail to 

show this consistency. 

Consistent findings of positive associations may not help to confirm a likely health effect 

but may instead be due to consistent choice models to produce the association. (Goodman et al.

(2005), at 430). Goodman et al. 2005 noted that “depending on the study published, singleestimate single-site analyses is an invitation to bias.” The most plausible explanation for the bias 

is that investigators “tend to report the analysis that produces the strongest signal” and make 

model choices that positively affect the sign and magnitude of the signal. (Goodman et al.

(2005) at 431). Thus, a consistent finding of positive associations may be due to a consistent 
Exxon Mobil Corporation Comments - 44 

choice of “cherry-picking” models to produce positive findings. This is possible because there 

are “innumerable model choices.” Id. Levy et al. (2005), at 465, noted that there were multiple 

studies where ozone was statistically insignificant without reporting the results, presumably 

because “such findings may be less likely to be published.” 

Furthermore, while EPA makes the point that mostly positive studies with the same 

magnitude of effect estimate provide consistency, many of the positive coefficients in some of 

the key studies, such as Bell et al. (2004), were not statistically significant. In their metaanalysis, Bell et al. (2005) noted that the hypothesis of homogeneity was rejected for both U.S. 

cities and all cities. Ito et al. (2005) found high (77 percent) heterogeneity in effect estimates 

from the 48 cities they selected for their meta-analysis and that 19 percent were negative. 

The importance of the inconsistency is stressed by several researchers, including Gryparis 

et al. (2004) who examined the association between ozone and mortality in 23 European cities. 

For the full-year analyses, approximately half of the cities showed negative coefficients and in 

the summer, about a third of the cities had negative coefficients. In their combined analysis, the 

authors report a positive association between ozone and mortality, but express caution for using 

the results for a health impact assessment. 

The combination of these results suggests that despite the bias for positive associations, a 

substantial fraction of the studies are negative and there is a lack of homogeneity. The direct test 

of consistency of results (a test to see if different authors get similar results) fails to meet the 

criterion for consistency as different authors get different results. The evidence is suggestive of a 

lack of consistency, which adds to the weight of evidence against a causal association. Stated 

another way, repeatability, a tenet of sound science, is not met in the data on acute mortality and 

ozone. 

 6. Temporality. 

Temporality is defined by EPA as the occurrence of a cause before its purported effect, 

and is most relevant to studies of diseases that develop over time. (2005 PM, SP at 3-30). In the 

proposed rule, EPA suggests that for acute health outcome of cardiovascular mortality 

associations reported on 0-3 day lags are expected. (72 Fed. Reg. at 37,826). 

Same day lags in time-series studies have inherent problems of exposure 

misclassification error. If death occurs early in the day then most of the exposure occurs after 

the health event, so the exposure is irrelevant to the effect. In the ecological time-series studies 

there is no information on the time of death on the day of death and so no feasible way to adjust 

for exposures occurring after death. 

Selection of lag period may also be related to publication bias. Bell et al. (2005) found 

that single time-series studies that reported multiple lags had 40-50% smaller effect estimates 

than those that reported only one lag. According to Bell et al., this suggested that “the lag with 

the highest effect is more likely to have been reported.” (at 442). Similarly, Goodman (2005) 

found that studies that reported only same day lags were approximately 50 percent higher than 
Exxon Mobil Corporation Comments - 45 

those studies with 1 day or higher lags. Levy et al. (2005) at 464, found a 0.14 percent lower 

effect per day of lag above zero (Goodman 2005). 

 The reporting of results from different lag times in different studies appears to be a major 

weakness of the ozone time series studies, especially since there is no clear biological answer or 

conclusion that can be drawn from previous studies. For this reason Goodman (2005) suggests 

that single-city studies should be avoided until there is agreement and standardization of how 

these studies should be analyzed and reported. 

 7. Lag Structure in Ozone Mortality Studies. 

 

According to EPA, results from single day lags or distributed lags are appropriate to use 

in developing risk estimates. However, EPA also uses much longer lag times in their evidence 

based evaluation of the ozone health effects, particularly for morbidity health effects. 

While EPA indicates that 0 and 1 day lags are most plausible, the Agency appears to 

ignore this important point in deciding to use distributed lags out to 7 days in their assessment. 

This undermines the value and credibility of the risk assessment. 

In developing its risk estimates, EPA appears to rely on both single-day lag results as 

well as distributed-lag results. EPA’s decision to use both single-day lags and distributed-lags in 

its risk assessment raises serious concerns of lag-mining. In both sets of studies, results appear 

to be selected largely on whether they report higher effect estimates. EPA fails to provide a 

biological or scientific justification for this approach. 

In the 2007 SP and risk assessment, EPA justifies the inclusion of distributed lag times by 

indicating that the use of studies with single-day lags underestimates potential effects. This is 

incorrect. As pointed out by Goodman (2005), since there is no a priori biologic model for 

estimating a plausible lag or latency, the approach generally taken is to pick the largest or 

strongest effect estimate. As a result, the single-point estimate derived from this approach is 

biased upward, not downward as suggested by EPA. As Ito et al. (2005), at 455, noted, “the 

combined estimates may be biased upward because the ‘optimal’ or ‘best’ lags were chosen.” 

Unfortunately, the “best” estimate is not based on biology nor on the “best” model if that can be 

defined, but rather on the largest positive association. 

EPA’s selection of the largest positive association amongst the various lag times used in 

ecological studies, and reliance on longer lag times can be attributed to the Agency’s failure to 

identify biologically-based lags that consider the mechanistic cause of action of potential ozone 

related health effect. Ozone is a well known respirator toxicant. However, as indicated by 

CASAC members John Balmes and Henry Gong, EPA has significantly over interpreted and 

misinterpreted the findings from recent studies that evaluated the cardiovascular effects of ozone 

in an attempt to justify their conclusions from epidemiology studies on acute mortality. For 

example, in his comments on Chapter 8 of the Criteria Document (Feb. 2006 CASAC Letter at 

D-5), Dr. Balmes stated: 

While the goal of trying to integrate results from both experimental and 

epidemiological studies into coherent concepts about how ozone 
Exxon Mobil Corporation Comments - 46 

mechanistically induces health effects is important, integration should 

not be forced when the data are inadequate. In my view, this is the case 

with regard to the potential mechanisms of the cardiovascular morbidity 

and mortality effects that may be associated with exposure to ambient 

ozone. For example, the mild effect on arterial oxygen tension observed 

by Gong et al. is over emphasized as a likely cause of myocardial 

ischemia among the general population. In my judgment, the state of 

knowledge about the potential mechanisms of ozone-related 

cardiovascular toxicity is insufficient to support the results of 

epidemiological studies that linked ambient ozone to cardiovascular 

morbidity and mortality. 

Therefore, all of the discussion about the growing body of evidence of cardiovascular 

effects from clinical and toxicology studies that support the epidemiology evidence, and the 

statements concerning the biological plausibility of the epidemiology findings, should be 

removed from this proposal. Further, the statements concerning how the clinical data support the 

array of longer lag times EPA uses in their risk assessment based on ecological studies (72 Fed. 

Reg. at 37,826) should also be removed. The only lag times that have biologic plausibility fall in 

the range of no more than 1 day. 

 8. Concentration-Response Relationships and Potential Thresholds. 

On the important topic of whether a potential threshold for acute mortality exists, EPA 

incorrectly concludes that there is insufficient evidence to support the use of a threshold in 

quantitative risk assessment. Clear evidence of a potential threshold effect can be found in the 

clinical studies which are less vulnerable to model selection and other confounders. Non linear 

exposure responses, with much higher effects at higher concentrations, and no effects at lower 

concentrations, are observed in human clinical and toxicology studies. For this reason, EPA has 

identified thresholds below which minor pulmonary function changes will not be extrapolated. It 

is inconsistent for EPA to not extrapolate minor pulmonary function changes below 50 ppb, but 

to extrapolate mortality, a much more serious health effect endpoint, presumably related to a 

pulmonary mechanism of toxic action, below 50 ppb and down to “policy relevant background” 

(PRB) levels. EPA must use the extensive human clinical and mechanistic data to derive 

biologically based cutoffs for extrapolating acute mortality. In our view, there is no scientific 

evidence to extrapolate mortality below the range of 60-80 ppb. 

Evidence of a potential threshold can also be seen in the time series literature. In many 

studies, the mortality exposure response function is non-linear and exhibits a threshold, as 

expected from the extensive exposure response data from human clinical and toxicology studies. 

In most of the time-series literature, much stronger associations (i.e., steeper slopes of the 

concentration-response curves) in summer are observed when ozone levels are higher than in 

winter when ozone is lower; in most cities there was no association in the winter. For example, 

Levy (2005) reported an estimate of 0.43% increase in mortality per 10 ug/m3

 increase in 1-hour 

ozone versus -0.02% in winter. Ambient ozone concentrations in winter are lower and with a 

narrower range than in summer. If ozone effects are “independent” of temperature as suggested 

by Bates (2005), then the lack of an association at the lower winter concentrations is suggestive 

of a threshold. The general lack of association of ozone with mortality in the winter season by 
Exxon Mobil Corporation Comments - 47 

most studies (Ito et al. 2005; Levy et al. 2005) is suggestive of a threshold. EPA also completely 

dismisses the alternate hypothesis that the acute mortality observed in summer has little to due 

with ozone exposure but rather is primarily due to high temperatures that are well known to 

cause mortality, and the inability of ozone time series models to accurately specify weather. 

The failure of time-series studies to provide clear evidence of a threshold can be linked to 

the general weaknesses of these studies. As noted in the above comments, ambient ozone 

measurements do not provide a valid surrogate for aggregate personal ozone exposure. For this 

reason, Brauer et al. (2002) reported that for pollutants exhibiting low correlation between 

ambient and personal exposure, such as ozone, it is not possible to determine thresholds in 

ecological air pollution studies. Thus, it is not possible for EPA to reach the conclusion that 

thresholds have not been observed in ozone ecologic studies. EPA seems to be confusing the 

concept “it is not possible to determine thresholds” with the concept “thresholds have not been 

observed.” 

Furthermore, EPA appears to have misinterpreted the results by Vedal et al. (2003). 

While these authors report statistically significant findings of acute mortality at 23 ppb ozone, 

they raise the concern that the association may be due to other factors in the air pollution mix 

such as particulates. Additionally, they raised the concern that measurement error attributed to 

use of a few ambient monitors may blur the existence of a threshold. They also noted that air 

pollutants may be a surrogate for meteorological factors. None of these factors are mentioned in 

the EPA summary of this paper. 

Susceptible subgroups of the population including asthmatics, persons with reactive 

airway disease, cardiovascular disease and obstructive airway disease, have been exposed to 

ozone concentrations of 80 ppb or higher with no or only transient changes in lung function 

health effects and little or no indication of cardiac health effects. (See 1996 CD, Table 7-2). 

Ozone is a pulmonary irritant and exposures produce irritant health effects at much lower 

concentrations than those which could produce death. The lack of less severe and transient 

pulmonary irritant effects at concentrations of 80 ppb is a strong argument against the hypothesis 

that current ambient concentrations, down to policy relevant background levels are causing 

death. EPA is using, and the data support, an “S” shaped concentration response function for 

pulmonary function changes, which is one of the most sensitive measures of ozone exposure in 

contrast to the linear dose-response function used for mortality. For clarity, S-shaped ozone 

concentration and health effect concentration function shapes recognize the concepts of a) 

thresholds for effects and b) lesser health effects for a unit exposure at lower levels of exposures. 

As noted by EPA, Kim et al. (2004) report thresholds for acute ozone mortality at 20-30 

ppb in a time-series study of Seoul, Korea. Further, they report a higher relative risk per unit 

ozone above the threshold. There are a number of concerns worth noting in the findings by Kim 

et al. (2004). First, higher effect estimates were reported in winter versus summer. This finding 

is opposite that normally observed. Second, Kim et al. did not consider PM2.5 as a potential 

confounder. Rather, their analysis was based on consideration of only PM10 which is known to 

have a much lower correlation with ozone. Therefore, much of the risk attributed to ozone, 

either above or below the “threshold”, could have been due to confounding with PM2.5. Finally 

their conclusion that a linear model may underestimate risks does not consider actual population 
Exxon Mobil Corporation Comments - 48 

exposure, i.e., the number of people exposed under the threshold, or how a risk assessment 

considers the issue of PRB. Rather, this conclusion is based only on a small increase in relative 

risk observed above the threshold, which is not unexpected in a threshold model. 

 9. Biological Plausibility and Coherence of Evidence. 

Although EPA’s conclusions regarding risks from ozone implies confirming evidence of 

biological plausibility, the rule and supporting documentation remains vague on the issue. In the 

proposed rule, EPA provides a generic list of various biological and physiological effects 

associated with ozone exposure. 72 Fed. Reg. at 37,840. There is no indication at what exposure 

levels these findings are evident, or how they may relate to the acute mortality with a no 

threshold hypothesis. Despite the lack of this information, the Agency infers that coherence has 

been established, based on morbidity findings and toxicology data. 

Presenting a list of plausible mechanisms does not equate to a proven mechanism of toxic 

action. In the 2006 CD, EPA states “our knowledge about potential underlying mechanisms 

remains limited and suggest a need for further experimental support.” (2006 CD at 8-51). EPA 

should clearly note this lack of mechanistic support in the proposed rule. EPA’s discussion of a 

biological plausibility is further weakened by inconsistencies. On the one hand, EPA states that 

exposure to ambient PM is assumed by EPA to cause cardiopulmonary mortality. However, 

according to EPA, the signal for cardiopulmonary mortality from exposure to PM does not 

impact the signal for ozone. (72 Fed. Reg. at 37,839). As a result, one must assume that the 

cardiopulmonary mortality alleged to be caused by ozone occurs through a completely different 

biological mechanism of action than the cardiopulmonary mortality alleged to be caused by PM. 

However, later on EPA asserts that both ozone and PM cardiopulmonary mortality is attributed 

to the same cardiac measures of effect such as “reduced heart rate variability.” (2006 Ozone SP 

at 3-5; 2005 PM SP at 3-32). This position is not consistent and further suggests that the Agency 

does not have clear evidence of biological mechanism of action for the alleged ozone 

cardiopulmonary mortality. 

While one could presume that the very elderly would be most affected, in fact, the 

mortality association for the very elderly (>75 years) was not increased relative to the general 

population, or relative to younger age groups (<65 years). Rather, inexplicably, the 65-74 old 

age group had the highest mortality association (Bell et al. 2004). Further, while the morbidity 

risks such as pulmonary function changes are based on plausible scientific evidence, the 

morbidity findings from ecological epidemiology studies (hospital and emergency rooms visits) 

are much less certain, creating yet an additional layer of uncertainty. Similarly, while ozone is a 

respiratory toxicant, the reported associations for respiratory mortality are lower than those for 

cardiopulmonary mortality and generally not statistically significant. From a coherence 

perspective, this is counter to common knowledge, practice, and observations, where one would 

expect agreement between the morbidity and mortality findings. The strength of the ecological 

morbidity associations is about the same as those for mortality, arguing against coherence, which 

should find that the incidences of morbidity are greater than that for mortality. 

The many uncertainties associated with EPA’s discussion of biological plausibility were 

recognized by CASAC. As discussed further in these comments, CASAC members Balmes and 
Exxon Mobil Corporation Comments - 49 

Gong, are correct in suggesting that EPA has overstated the evidence on cardiac effects of ozone 

(see discussion in # 7 above on lag structures). EPA should clearly state that the available 

evidence does not indicate cardiac-related mechanisms of action for ozone. Overall, EPA should 

conclude, based on the available evidence, that there is a lack of biological plausibility for the 

acute ozone mortality hypothesis, particularly at low levels. 

Finally, EPA states that ozone acts not only alone but as a “surrogate” for the air 

pollution mixture. (72 Fed. Reg. at 37,841). This is very similar to the statement EPA used in 

their Draft Integrated Science Assessment for Oxides of Nitrogen and Sulfur Oxides and it is an 

admission by EPA that is not possible to separate out the effects of ozone from other gaseous 

pollutants and PM, in observational epidemiology studies. In their draft Integrated Science 

Assessment (ISA) of Oxides of Nitrogen, EPA indicates “It is difficult to determine from these 

new studies is NO2 is the causal agent of if NO2 is a marker for the effects of another traffic 

related pollutant or mix of pollutants” (Draft ISA for Oxides of Nitrogen, at 5-14). Similarly, in 

their ISA for Sulfur Oxides, EPA indicates “SO2 might be acting as a marker for other mortalityassociated pollutants.” (Draft ISA for Sulfur Oxides, at 5-13). In this manner, EPA is double 

and triple counting the effects of air pollution each time it uses a single pollutant as the 

“surrogate” for the air pollution mixture. 

 10. Overall Conclusions on Causality For Acute Mortality. 

The evidence supporting acute mortality from exposure to ozone remains weak, 

consistent with the evidence EPA relied upon in 1997. EPA has failed to account for significant 

uncertainties in the time-series data and the lack of clear evidence of a biological mechanism of 

action. In the key chronic cohort study upon which EPA placed great reliance in their 

assessment of fine PM (Pope et al. (2002) at 1132-1141), no chronic mortality is reported for 

ozone. EPA makes no attempt to explain the inconsistency of this result with the results reported 

in the time-series studies. A more balanced interpretation would lead to the overall conclusion 

that causality has not been established. EPA should develop a more scientifically balanced 

interpretation of the entire evidence using the Hill criteria, as presented below in Table 3. A 

fuller and more careful weighing of the evidence should conclude significantly less certainty 

regarding mortality risks from exposure to ozone. 
Exxon Mobil Corporation Comments - 50 

Table 3 

Overall Evidence For a Causal Relationship For Acute Ozone Mortality

Hill Causal Criteria 

Evidence Assessment 

via Published 

Documents 

Strength of Evidence 

via Interpretation of 

Published Documents 

Comments 

Strength of Association Very Weak Inadequate RR 1.00-1.08 Does not meet Hill causal criteria or that of 

current epidemiology experts that recommend values of at 

least 1.5-2.0 in ecological studies 

Robustness 

exposure error 

Confounding by 

pollutants 

Model specification 

concerns 

Very high 

Very likely 

Moderate-High 

Inadequate 

Inadequate 

Inadequate 

Ambient measurements are a very poor substitute for 

aggregate personal exposure. 

Fine PM highly correlated with ozone and alleged to cause 

the same effects. Coarse PM controlled in most studies. 

Existing weather specification inadequate and produces 2-

fold change in risks. Seasonality not adequately specified. 

Air conditioning is significant risk modifier 

Consistency Low Inadequate High city to city heterogeneity within multi-city studies. 

High author to author heterogeneity in single city results. 

Cities with lowest ozone levels tend to have highest risks 

per unit ozone and vice versa. Does not meet Hill causal 

criteria for consistency. 

Temporality Sufficient? Limited Strongest signal at lag 0 is biologically plausible but may 

indicate effect proceeds exposure 

Lag Structure Variable, not defined Inadequate Multiple single day and distributed lags used 

interchangeably. Biologically based lags not established. 

Specificity None. Inadequate Ozone presumed to cause the same general affect (acute all 

cause or cardiopulmonary mortality) as other pollutants 

including PM, NO2, and SO2. Does not meet the Hill causal 

criteria. 

Biological Plausibility Not established Inadequate Not supported by very extensive human clinical database. 

No biological mechanism to explain acute mortality. 

Plausibility especially low at low ozone concentrations. 

Coherence Low Limited Pulmonary function effects are transient and not expected 

to result in mortality. Morbidity risks from ecological 

studies (hospital admissions, emergency room visits) are 

less certain and strength of association’s in some cases is 

about the same as per mortality. Respiratory mortality is 

not statistically significant. Mortality risks are not higher 

for the very elderly. PM does not modify ozone 

cardiopulmonary mortality but alleged to be mediated by 

similar cardiac effects (e.g. decreased heart rate 

variability). 

Overall Inadequate Causality clearly not established. 

IX. “New” Studies Regarding the Mechanisms Underlying Respiratory Morbidity

Provide Little New Information Relevant to What Was Known in 1997. 

In the proposed rule, EPA makes several statements related to the mechanisms by which 

ozone produces short-term effects of ozone in healthy subjects and those with asthma and other 

respiratory diseases. (72 Fed. Reg. at 37,825-27). The information is presented in a manner that 

indicates all of this information is new. In fact, most of the information cited in this section was 

known at the time of the last ozone NAAQS review in 1997. Given the similarity of the points 
Exxon Mobil Corporation Comments - 51 

and conclusions on these issues in both the 1997 and current review, EPA cannot report this 

information as new. EPA should delete the text of this section, or, clearly cite the information as 

known at the time of the last review. EPA also makes a number or errors in interpreting the new 

data that need to be corrected. 

In the 2007 proposed rule, for example, EPA states that based on new evidence, 

“repeated respiratory inflammation can lead to a chronic inflammatory state with altered lung 

structure and lung function and may lead to chronic respiratory diseases such as fibrosis and 

emphysema.” (72 Fed. Reg. at 37,825). However, in 1996, EPA concluded that a single, acute 

(1-4 hour) exposure to > 0.08 to 0.1 ppm ozone with a subject engaged in moderate to heavy 

exercises could induce cellular and biochemical changes suggestive of pulmonary inflammation 

and lung permeability. (2006 CD at 8-22). Further, in 1996 EPA concluded that the currently 

available information provided at least a biologically plausible basis for considering the 

possibility that repeated inflammation associated with exposure over a lifetime may result in 

sufficient damage to the respiratory tissues such that an individual later in life may experience a 

reduced quality of life. (62 Fed. Reg. at 38,859). 

In the 2007 proposed rule, EPA states that “based on new evidence from animal, human 

clinical and epidemiological studies, the 2006 CD concludes that people with preexisting 

pulmonary disease are likely to be among those at increased risk from O3 exposure.” (Fed. Reg. 

at 37,826) (emphasis added). This is not a significant change from the 1997 review, where EPA 

stated that “[t]he major reason individuals with preexisting respiratory disease [(e.g., those with 

COPD, ischemic heart disease)] may be of concern is the likelihood that decrements in lung 

function or exercise capacity may have greater clinical importance to the individual than similar 

changes in healthy persons. (1996 SP at 58). 

In the 2007 proposal, EPA states that “new evidence” from controlled human exposure 

studies “indicate that asthmatics may exhibit large lung function decrements in response to O3

exposure than healthy controls” and “asthmatics present a differential response profile for 

cellular, molecular, and biochemical parameters.” (72 Fed. Reg. at 37,826). However, in 1996, 

EPA made similar points, indicating that asthmatic subjects typically have increased airway 

responsiveness at baseline, and differences in baseline bronchial responsiveness between healthy 

individuals and sensitive asthmatics that may be as much as 100-fold (1996 SP at 35). 

Furthermore, in 1996, EPA indicated that the clinical studies comparing the pulmonary function 

responses following ozone exposure in asthmatic and non-asthmatic subjects suggested “that 

asthmatics are at least as sensitive, if not more sensitive, to the acute effects of ozone inhalation.” 

(1996 CD at 7-25) (emphasis added). 

Concerning asthma development, in 2007, EPA concluded that in contrast to supportive 

evidence from chronic animal studies, epidemiologic studies of inflammation, new asthma 

development, and long-term function declines remain inconclusive. (2006 CD at 7-134). In 

1996, EPA concluded that while ozone has not been shown to cause asthma, the available 

evidence suggests that ozone may exacerbate asthma (62 Fed. Reg. at 38,864). 

In the 2007 proposal, EPA states that there are new data to support the conclusion that 

“children with and without asthma were found to be particularly susceptible to O3 effects on lung 
Exxon Mobil Corporation Comments - 52 

function and generally have greater lung function responses than older people.” (Fed. Reg. at 

37,826). However, in 1996, EPA stated that “children respond to low-level ozone exposures in a 

manner comparable to that of young adults, albeit without symptoms, while older persons exhibit 

a decreased sensitivity relative to young adults.” (1996 SP at 55 (citing 1996 CD, section 9.6)). 

Given the similarity of the points and conclusions on asthma and potential mechanisms of action, 

EPA cannot report this information as new. EPA should delete the text of this section or clearly 

cite the information as known at the time of the last review. 

A. The new epidemiology data do not show that the elderly are more susceptible 

to ozone effects. 

In the proposed rule, EPA presents a discussion concerning the age-related differences in 

mortality observed in epidemiology studies. (72 Fed. Reg. at 37,826). EPA concludes that the 

data support a conclusion that the elderly (age 65 or greater) are more susceptible. The evidence 

included in the 2006 CD, however, fails to support this conclusion. In the multi-city study by 

Bell et al. (2004) upon which EPA places great reliance, both for purposes of determining 

causality and for risk assessment, the results of the analysis segmented separately by age group 

do not support the conclusion that higher effects are observed in the elderly. The following 

statement appears on page 2374-5 of Bell et al. 

Effects of ozone on mortality for 3 age groups (<65, 65-75, and ≥ 75 

years) were estimated separately by using the constrained distributed-lag 

model to investigate whether the elderly are particularly susceptible to 

the effects of ozone on mortality. Effect estimates for the 65-74 year age 

category were 0.70% (95% PI, 0.28-1.12%) for a 10-ppb increase in 

daily ozone, whereas estimates for the youngest and eldest groups were 

similar to the overall estimate for the total population, at 0.50% (95% PI, 

0.10-0.92%) and 0.52% (95% PI, 0.18-0.87%), respectively. 

Given the Bell study and the lack of evidence to the contrary, EPA should correctly note 

in the rule that the data are unclear with regard to the increased susceptibility of the elderly to 

acute ozone mortality 

B. EPA incorrectly relies on human clinical studies in drawing conclusions 

regarding the appropriate lag time for potential health effects from exposure 

to ozone at lower levels. 

In the proposed rule, EPA states that clinical studies that provide information about 

mechanisms of the initial response to ozone (e.g., lung function decrements, inflammation and 

injury to the lung) also inform the selection of appropriate lag times to analyze in epidemiology 

studies, which they consider to be in the range of 0-2 days. (72 Fed. Reg. at 37,826). This 

conclusion, however, as it applies to time series studies of acute morbidity and mortality at lower

ozone levels is not supported by the data. 

In ozone human clinical studies, including studies of potentially susceptible individuals 

such as those with asthma, COPD and hypertension, only minimal transient lung function 

decrements and inflammation are observed at 0.08 ppm ozone. In contrast, EPA concludes from 
Exxon Mobil Corporation Comments - 53 

time-series studies that any concentration of ozone, even background levels of ozone between15-

40 ppm, result in morbidity and mortality. It is unclear, at best, how minor pulmonary function 

changes could be the mechanism of action responsible for acute mortality at these low 

concentrations. Transient and minor pulmonary function changes are unlikely to be responsible 

for the more serious morbidity effects (e.g., hospital admissions), at least not at levels of 15-40 

ppm, especially since such effects could be caused through a cardiovascular mechanism of 

action. However, as described above, the data on potential cardiovascular effects are limited, 

and the existing data from these studies provide no clear guidance for guiding lag times in 

epidemiology studies. As a result, neither the human clinical studies on lung effects nor the 

limited studies on cardiovascular effects provide information relevant to guide the selection of 

lag times in time-series studies of morbidity and mortality at lower ozone levels. 

Finally, we note that EPA failed to follow its own guidance on lag times in evaluating the 

epidemiology evidence. For example, EPA places high reliance on the results of Mortimer et al.

(2002) who report effects at 3 and 4 days lag or 1-5 days via distributed-lag whereas results at 

“biologically more plausible” days 0 and 1 not statistically significant were ignored (72 Fed. 

Reg. at 37,826). Instead of downplaying the significance of this study, EPA consistently relied 

upon the study in drawing conclusions regarding health effects from exposure to ozone. Rather 

than claiming, as the proposal does that human clinical studies on lung effects provided guidance 

for determining appropriate lag times for epidemiology studies, the proposed rule should be 

revised to state that the mechanism(s) of action to explain positive morbidity and mortality 

associations at background levels in observational epidemiology studies remains unknown. 

Therefore, the existing human clinical data do not provide evidence to guide the determination of 

appropriate lag times to use in epidemiology studies reporting effects at low background ozone 

levels. At higher levels (80 ppb and greater) where respiratory effects may be evident, lag times 

of 0-2 days may be considered appropriate. 

C. EPA incorrectly suggests that much of the information on potential 

mechanisms of action for short-term health effects from ozone exposure is 

new. 

The current EPA proposal incorrectly includes various statements related to the 

mechanisms by which ozone produces short-term effects of ozone as if this information was not 

available during the 1997 review. In fact, most of the information cited in these sections was 

known at the time of the last review. EPA also makes broad conclusions concerning the 

potential susceptibility of certain population subgroups to ozone exposure, in particular 

asthmatics, that are intended to make the reader believe that these conclusions are based on the 

extensive “new” data. Again, all of these conclusions were known to EPA and the scientific 

community at the time of the last NAAQS review. (See Table 1 for side-by-side comparison). 

EPA should clearly acknowledge in the proposed rule that the conclusions are not newly 

discovered since the last review. Specific examples include the following: 

• In their 2007 proposed rule, EPA states that based on new evidence, “repeated respiratory 

inflammatory state can lead to chronic inflammatory state with later lung structure and lung 

function and may lead to chronic respiratory diseases such as fibrosis and emphysema.” 

This statement is very similar to the conclusion drawn in 1997, when EPA concluded that a 
Exxon Mobil Corporation Comments - 54 

single, acute (1-4 hour) exposure to > 0.08 to 0.1 ppm ozone of subject engaged in moderate 

to heavy exercises could induce cellular and biochemical changes suggestive of pulmonary 

inflammation and lung permeability (CD, p. 8-22). Further, in the 1997 review , EPA 

concluded that the currently available information provided at least a biologically plausible 

basis for considering the possibility that repeated inflammation associated with exposure 

over a lifetime may result in sufficient damage to the respiratory tissues such that individual 

later in life may experience a reduced quality of life (Fed. Reg. at 38,859). 

• In their 2007 proposed rule, EPA further states that “based on new evidence from animal, 

human, clinical and epidemiological studies, the CD concludes that people with preexisting 

pulmonary disease are likely to be among those at increased risk from ozone exposure.” 

However, in 1997, EPA stated that “the major reason individuals with preexisting 

respiratory diseases (e.g., those with COPD, ischemic hart disease) may be of concern is the 

likelihood that decrements in lung function or exercise capacity may have greater clinical 

significance to the individual than similar changes in healthy persons” (SP at 58). 

• EPA states in this review that “new evidence from controlled human exposure studies 

indicate that asthmatics may exhibit large lung function decrements in response to ozone 

exposure than health controls” and “asthmatics present a differential response profile for 

cellular molecular, and biochemical parameters.” However, in the 1997,review, EPA 

indicated that asthmatic subjects typically have increased airway responsiveness at baseline, 

and differences in baseline bronchial responsiveness between healthy individuals and 

sensitive asthmatics may be as much as 100-fold (CD at 35). Furthermore, in 1996, EPA 

indicated that the clinical studies comparing the pulmonary function responses following 

ozone exposure in asthmatic and nonasthmatic subjects suggested that asthmatics are at least 

as sensitive, if not more sensitive, to the acute effects of ozone inhalation (CD at 7-23). 

The similarity of statements and conclusions in this review compared to the 1997 review show 

that EPA is incorrect in claiming that there is new information on mechanisms of action or 

sensitive subpopulations. 

D. EPA’s conclusion concerning exposure to ozone and asthma development has 

 not changed fundamentally since 1997. 

In this review, EPA concludes that in contrast to supportive evidence from chronic 

animal studies, epidemiologic studies of inflammation, new asthma development, and long-term 

function declines remain inconclusive (CD at 7-134). This appears to be very similar to what 

EPA concluded in 1996, where EPA found that while ozone has not been shown to cause asthma, 

the available evidence suggests that ozone may exacerbate asthma (Fed. Reg. at 38,864). EPA 

should clearly state that their position concerning exposure to ozone and asthma development 

has no fundamental changes since 1997. 
Exxon Mobil Corporation Comments - 55 

X. New Animal Data on Cardiovascular-Related Health effects endpoints Are Far too 

Limited and Inconclusive to Support a Mechanism of Action For the 

Cardiovascular Morbidity and Mortality Associations Reported in Observational 

Epidemiology Studies. 

In the proposed rule, EPA states that since the last review, an emerging body of animal 

toxicology and human clinical evidence is beginning to suggest mechanisms that may mediate 

acute ozone cardiovascular effects. (72 Fed. Reg. at 37,825-26). We disagree with this 

conclusion. As described in more detail below, the available data on the cardiovascular effects 

of ozone are very limited, and much of the existing data are inconclusive or indicate no 

significant cardiovascular related findings. 

In 1996, EPA reported that several animal studies reported dramatic cardiovascular 

effects from ozone exposure (1 ppm for 3 hours, or about 10 times the ambient standard) 

including a 53 percent decrease in heart rate and 29 percent decrease in blood pressure. (1996 

CD at 6-121). Uchiyama et al. (1986). Arrhythmias, including atroventricular block and 

premature atrial contractions, were also reported frequently in these studies. However, in 

interpreting the significance of these data, EPA appeared to rely on the summary by Watkinson 

and Gordon (1993) who questioned the relevance of these parameters in the rat as compared to 

humans. 

In 2006, EPA states that new animal studies published during the past decade offer added 

evidence of the relationship between ozone exposure and cardiac physiologic health effect 

endpoints. EPA concludes that these data provide new information regarding mechanisms of 

action and the biological plausibility of acute mortality associations reported in epidemiology 

studies (2006 Draft SP at 3-2) Further, EPA concluded that the evidence from toxicology, 

human controlled exposure, and epidemiology studies is highly suggestive that ozone can 

directly and/or indirectly contribute to cardiovascular-related morbidity. (2006 CD at 8-77). 

The data EPA cites to support these conclusions include data from the human clinical study by 

Gong et al. (1998) and Brook et al., (2002), and epidemiology field studies such as Peters et al.

(2000, 2001) and Gold (2000). (2007 SP at 3-26; 2006 CD at 7-63). 

 Concerning the study by Gong et al. (1998), the authors concluded that ozone exposure 

induced no statistically significant changes in cardiac index, ventricular performance, pulmonary 

artery pressure, pulmonary and systemic vascular resistances, ECG, serum cardiac enzymes, 

plasma catecholamines and artrial natriuretic factor. Overall, Gong et al. (1998), abstract, 

concluded that the results “did not indicate major acute cardiovascular effects of O3 either on the 

hypertensive or the control subjects.” EPA ignores the lack of findings and the fact that the 

authors’ conclusions focus on a single, nearly non-statistically significant change in rate-pressure 

product. Given the large number of health effect endpoints examined in this study, one change 

could easily be due to chance. Further, EPA CASAC member John Balmes plus the lead author 

of the study Henry Gong, expressed concerns for EPA’s overstating the results of this study, and 

the case for cardiovascular effects in general (see quotes by John Balmes in the discussion of lag 

times). 
Exxon Mobil Corporation Comments - 56 

 Brook et al. (2002). Investigated the effects of inhalation of PM2.5 and ozone on vascular 

function. The primary measure of vascular effects used was the diameter of the brachial artery 

diameter (BAD). Healthy subjects were exposed for two hours to either filtered air or 150 ug/m3

PM2.5 and 120 ppb ozone. A small change in mean BAD (0.09 +/- 0.15 mm, p <0.03) in the 

PM/ozone exposed group was reported. Several points limit the interpretation and usefulness of 

this study. First, it is not possible to attribute the effects to PM or ozone. We note that the levels 

of PM2.5 used were ten times higher than the annual standard and five times higher than the 24-

hour standard, whereas the level of ozone used was at the higher end of the ambient range. It 

seems likely that the effects were more due to PM exposure than ozone exposure. Second, given 

the very high variability in results, the findings should be considered of borderline statistical 

significance. Finally, the clinical significance of the findings is questionable. For example, cigar 

smoking causes a BAD decrease of 10 percent. Passive smoking causes a BAD decrease of 8 

percent. Simply taking a blood pressure reading produces a BAD decrease of 6 percent. Women 

taking hormone therapy have reported BAD decreases of 2 percent. Overall, the small changes 

in BAD appear to be well within normal ranges. 

 Concerning the epidemiology field studies, EPA lists three references from studies on 

cardiac measures of effect Gold et al. (2000) and Peters et al. (2000, 2001). (McCluney 

Memorandum at 2. As described below, these data provide little or no support for a cardiacrelated mechanism of toxicity for ozone. 

Gold et al. (2000)

The objective of the study was to evaluate the potential affect of PM2.5 air pollution on 

heart rate and heart rate variability in 21 53-87 year old active Boston residents. Continuous 

measurement of PM2.5 and PM10 was provided via TEOM from a monitoring station 6 km (3.5 

miles) from where the clinical data was collected. Ambient levels of ozone (1-hr), NO2 and SO2

were taken from a compliance monitoring station 4.8 miles from the study site. Subjects were 

tested from June through September from 9:00 a.m. to 2:00 p.m., Monday through Friday. 

Continuous holter counter monitoring was performed during a protocol involving five minutes 

rest, five minutes standing, five minutes of exercise outdoors, five minutes recovery, and three 

minutes slow breathing. According to the investigators, the slow breathing portion enabled them 

to evaluate whether the effects of pollution on heart rate variability (HRV-rMSSD, mean of the 

squared differences between adjacent normal RR intervals) were independent of respiratory rate. 

Various different fixed effects statistical models were used to assess the data. A second set of 

random-effects models were used to evaluate the sensitivity of air pollution to the choice of 

model and to define the primary effects and interactions with air pollution and subject 

characteristics, whose individual effects could not be evaluated in a fixed-effects model. 

During the first rest period, no statistically significant association was observed between 

1-hour ozone and HRV for both statistical models employed. During the slow breathing period, 

a statistically significant association was observed between 1-hour ozone and HRV whereas for 

model 3 the association was not statistically significant. The mean 24-hour ozone level in the 

study was reported as 26 ppb, with a range of 5-56 ppb. Concentration response was not 

evaluated in the study. 
Exxon Mobil Corporation Comments - 57 

 There are several concerns with the findings from this study. 

• The direction of the change in HRV (decrease in r-MSSD) is opposite that observed in 

other studies for which EPA has stated air pollution was associated with changes in HRV. 

In the Utah study of PM (Pope et al. 1995) that EPA claims is coherent with the 

toxicology data, PM air pollution was reported to increase r-MSSD. In this study, the 

authors claim both PM and ozone decreased r-MSSD. The direction of change is also 

opposite that observed in cardiac rehabilitation patients administered beta blockers. 

• Ozone was only considered superfluously as a potential co-pollutant to PM2.5 in this 

study. Only very limited analysis of the effects of ozone alone was performed. 

• Only 1 of 4 model comparisons, two with r-mssd during the first rest and two with r-mssd 

during slow breathing, was statistically significant. The authors provide no explanation 

on the relative accuracy of any of the statistical models used. 

• It is not clear from the study whether the statistical approach used controlled for 

individual factors (e.g., medication use, smoking history, health status) that have a much 

greater influence on HRV versus the small potential impact of air pollution. 

• It is also not clear whether the approach of assessing HRV during resting truly controls 

for the well known impact of heart rate on HRV measurements. Since the only positive 

association for ozone was reported during low breathing, the finding could easily be 

spurious and due to a lack of control for heart rate factors. 

• The small change in HRV lacks clinical significance. As documented in our previous 

comments on the CD, many normal activities result in changes in HRV of the magnitude 

reported in this study. 

Peters et al. (2000)

The objective of this study was to evaluate if “air pollution incidents” are associated with 

cardiac arrhythmias in 100 patients with cardio-defibrillators living in eastern Massachusetts. 

The air pollutants evaluated included PM10, PM2.5, black carbon, CO, SO2, NO2, and ozone. The 

authors report mean ozone level as 18 ppb, with a maximum reported as 59 ppb and 95% of 35 

ppb. The air monitoring was performed in south Boston, with the expectation of SO2 and NO2

that were measured in Chelsea, approximately 7.5 kilometers north of south Boston. Five 

different lag times, same day, previous day, 2-, 3-, and 5-day mean, were assessed for all 

pollutants. No biological justification was provided for using this range of lag times for all 

pollutants. Even with this range of lag times, no statistically significant associations were 

reported for ozone for any of the lag times. As a result, this study provides no evidence to 

support a cardiac-related mechanism of action for ozone, and cannot be used to support a 

revision of the standard. 

 
Exxon Mobil Corporation Comments - 58 

Peters et al. (2001)

 The primary objective of this study was to evaluate if elevated concentrations of ambient 

PM have been associated with increased hospital admissions for cardiovascular disease using a 

case cross-over design. From January to May 1995, levels of gaseous pollutants, including 

ozone were measured. The mean 1-hour ozone level reported in the study was 19 ppb, with a 

95% value of 46 ppb. A positive and statistically significant association between levels of PM2.5

2- and 24-hours prior to myocardial infarction was reported. The coefficients for 2- and 24-hour 

ozone were not statistically significant. Therefore, this study, like the Peters et al. (2000), 

provides no evidence to support a cardiac related mechanism for ozone. 

 Given the new studies which fail to find a cardiovascular effect from ozone exposure, 

EPA is incorrect in stating that this is “an emerging body of ... evidence.” (72 Fed. Reg. at 

37,825). Instead, EPA should correctly note that only a few new studies on the potential 

cardiovascular effects of ozone have been published since the last review, and that the findings, 

considering all the data, remain inconclusive. This is the only conclusion that can be justified 

given that two key studies, involving human clinical assessments, indicate no consistent evidence 

or pattern of cardiovascular effects. 

XI. EPA’s Risk Assessment is Flawed and Overestimates the Risk Under the Current 

Standard and Fail to Account For Significant Uncertainties. 

 In our view, the EPA risk assessment for respiratory symptoms in asthmatic children, 

hospital admissions for respiratory causes, and acute cardiopulmonary mortality is seriously 

flawed and significantly overestimates the risk from meeting the current standard. This 

conclusion is supported by the findings of the Rochester group, wherein the panel states: 

“The risk assessment used by the EPA to inform policy judgments in 

proposing the ozone NAAQS is flawed.” Rochester Report at 5. 

 We present below our main concerns with the EPA risk assessment. 

A. EPA’s risk assessment on asthmatic children systematically overestimates 

risks. 

In the 2007 SP, EPA presents risk estimates for three respiratory symptoms—wheeze, 

chest tightness, and shortness of breath—in asthmatic children ages 0-12 who use maintenance 

medication. (2007 SP at 5-51). These estimates are based on the study by Gent et al. (2003). 

The key concerns with this study, and the EPA risk assessment, are summarized below. It is 

clear, based on the impact of various EPA assumptions and decisions used that the EPA 

approach systematically overestimates the risks. The overestimate of likely risk is on the order 

of 100-fold. 

Many of the concerns with EPA’s risk assessment of asthmatic children are based on 

weaknesses in the Gent et al. study on which it is based. Key issues include the following: 
Exxon Mobil Corporation Comments - 59 

• Personal exposure to ozone was not measured. Rather, the exposure metric was areawide monitors over a 6691 square mile area. There was wide variability in the ozone 

levels across this area (47-97 ppb). The true exposure to individuals in the study is 

unknown. The resulting massive exposure misclassification renders it impossible to 

determine whether or not ozone exposure is related to the respiratory symptoms and if 

effects are occurring at or below certain ozone concentrations, as asserted by the authors. 

• There was no control for potential impact of relative humidity or pollen counts which are 

known to impact asthmatics. Control for other metrological impacts is not well described 

and thus uncertain at best. 

• There is no mention of a standardized questionnaire for assessing symptoms. A 

standardized questionnaire is essential to provide assurance that the symptom response is 

always the same over time and the between-individual interpretations are similar. 

• In two pollutant models with PM2.5, Gent et al. report no significant association between 

ozone exposure and cough. The large majority of coefficients for the other symptoms, 

wheeze, chest tightness, shortness of breath, and bronchodilator use were also not 

statistically significant. With the exception of chest tightness, the only statistically 

significant associations were reported with a same day lag, raising the possibility that the 

symptoms occurred before the exposure. 

• It is not clear why there is a hint of an increase in the occurrence of respiratory symptoms 

while the corresponding association for bronchodilator use was only marginally 

statistically significant in 1 of the 2 lag periods used. Symptoms are a subjective measure 

of effect whereas bronchodilator use provides an objective estimate of effect. The lack of 

association for bronchodilator use tends to discredit or at least fails to validate the 

subjective increase in symptoms. The lack of association with bronchodilator use also 

provides evidence that the symptoms were not serious enough to seek relief, even in 

children presumed to have severe asthma. 

• Positive associations were only reported in children using asthma maintenance 

medication. No statistically significant associations were reported for asthmatic children 

not using maintenance medication. The reasons for this are unclear, but are presumed by 

the authors to be related to the assumption that those using asthma medication have more 

serious conditions. However, it is not certain that use of maintenance medication 

provides a clear distinction in disease severity as asserted by the authors. Other factors, 

such as access to health care, ability to pay for medication, individual physician 

prescription tendencies, are also likely important in determining whether or not an 

individual uses asthma medications. 

Table 4 summarizes the major concerns with EPA’s risk assessment based on Gent et al. (2003): 

• The risk assessment is based on a single ecological epidemiology study by Gent et al.

(2003). Given the well known methodological problems with ecological air pollution 
Exxon Mobil Corporation Comments - 60 

studies and existence of publication bias, we question the approach of relying on the 

results of a single ecological study to conduct this key part of the EPA risk assessment. 

• Given the differences in time activity patterns and exposure in warmer versus colder 

climates, the results of the risk assessment for Boston should not be extrapolated to the 

wider U.S. population. 

• In their risk assessment, EPA assumes that asthmatic children spend the same amount of 

time outdoors as other children. Actual data indicate this assumption is not accurate.. 

Therefore, in their risk assessment, EPA incorrectly overestimates ozone exposure in 

asthmatic children without a scientific foundation. 

• In their risk assessment, EPA only chooses coefficients that are statistically significant 

 while ignoring the majority that are not statistically significant. 

• The study by Gent et al. was conducted in an area that is clearly not in compliance with 

the existing ozone standards. During the 183 days of study, the 1-hour standard of 120 

ppb and the 8-hour standard of 80 ppb were exceeded 1 and 10 times, respectively. 

• EPA fails to recognize that in the study by Gent et al. statistical significance was only 

reported at higher ozone levels, i.e., there was an apparent threshold below which the 

associations were not statistically significant. These thresholds were <51 ppb for chest 

tightness and wheeze and <73 ppb for shortness of breath and bronchodilator use. This 

failure is carried through the EPA risk assessment, where EPA presents the incidence of 

chest tightness and wheeze at alternate standards of 74 and 64 ppb, even though in the 

underlying data used for the risk assessment, a statistically significant increase in these 

symptoms was not reported at those levels. 

• EPA assumes that all 200,000 asthmatic children in Boston have severe asthma and are 

potentially at risk to ozone exposure. In reality, there is marked difference in the severity 

of asthma across the population and only a smaller percentage of children have severe 

asthma. This difference in "degree of asthma condition" makes a difference in the ozone 

exposure and health effect response. Also, the data from Gent et al. clearly indicated 

that those children with what they presume to have a milder condition did not respond to 

ozone exposure. 

• EPA extrapolates risks down to and through actual background levels using arbitrarily 

low policy relevant background (PRB), thereby inflating the risk estimates. 
Exxon Mobil Corporation Comments - 61 

Table 4 

Key Factors Influencing the EPA Risk Assessment for 

Respiratory Symptoms in Asthmatic Children 

Factor EPA Approach Impact on Risk Estimates 

Use of a single study Use without qualification Likely increase (overestimate) due to well known 

publication bias in ecological epidemiology studies. 

Based on publication bias impacts on PM studies, 

estimate 1.5-2 fold over-estimate of risks. 

Assume ozone exposure to 

asthmatic children is equal to other 

children even though actual data 

indicate otherwise 

Use without qualification Increase risk estimates; estimated impact at least 2-

fold 

Health data are taken from data 

where ozone levels are higher and 

out of compliance 

Use without qualification Increase 

Concentration response functions do 

not control for other potential 

confounders including relative 

humidity and pollen counts 

Use without qualification Increase; estimated impact at least 2-fold based on 

reports for risks attributed to relative humidity and 

pollen 

Existence of both significant and 

non significant coefficient’s 

Use only positive 

coefficients 

Increase; magnitude of over-estimate is difficult to 

determine but expected to be similar to that for 

publication bias 

Extrapolation of risks to levels 

below those reporting effects in the 

study using no threshold 

Performed without 

qualification 

Increase; estimated impact at least 2-fold 

Effects reported only in most severe 

asthmatics. 

 Assume effects occur in 

all asthmatic children 

regardless of how severe 

their condition is. 

Increase; estimated impact at least 5-fold 

Policy relevant background Use arbitrarily low level 

as “central” value, then 

calculate range above 

and below this level 

Increase; estimate impact at least 2-fold. 

Total1 No consideration of the 

above factors with 

exception of PRB 

Risks are over-estimated by a factor of at least 100-

fold. 

 1

Considing only those factors for which some quantitative estimate of the impact was possible. 

 

B. EPA’s risk assessment of hospital admissions provides no new information 

that was not available in the 1997 review. 

 In the current risk assessment of hospital admissions, EPA used results from four timeseries studies, Thurston et al. (1992), Schwartz et al. (1996), Linn et al. (2000) and Ito et al.

(2003). U.S. Environmental Protection Agency, Ozone Health Risk Assessment for Selected 

Urban Areas, EPA 452/R-07-001, Jan. 2007 (“2007 Ozone Risk Assessment”). Several of these 

studies were also used in the 1996 review. 

• The study by Thurston et al. (1992) was the same study EPA used in 1996. As such, this 

study provides no new evidence for consideration in 2006. 
Exxon Mobil Corporation Comments - 62 

• The study by Schwartz et al. (1996) was available at the time of the last review and 

therefore adds no additional information in 2006. The study was published prior to the 

discovery of the GAM problems. The results have never been corrected for either use of 

the default convergence criteria or alternate smoothing functions. The study raises 

questions concerning the dependent nature of time-series model building and difficulties 

in providing the “adequate” amount of control for seasonal, day-of-the-week and weather 

factors. 

• The study by Linn et al. (2000) did not report statistically significant associations for 

ozone. Since this study was conducted in Los Angeles where ozone levels are very high, 

the results from Linn et al. provide data to support the conclusion that ozone is not

associated with hospital admission for respiratory illnesses. Nonetheless, EPA used the 

positive, non-statistically significant risk coefficients in their risk assessment for hospital 

admissions. 

• The study by Ito et al. (2003) focused primarily on effects of PM with little data for 

ozone. Further, the study was conducted as part of the HEI effort to evaluate the results 

of time-series studies subsequent to discovery of the GAM problems. The coefficients in 

this study were in fact markedly reduced when the more stringent criteria were used with 

GAM or when GLM was used. Further, the coefficients were also reduced when various 

weather smoothers were employed. The limited results for ozone were inconsistent, 

varying from significant to non-significant, depending on the lag time used. The results 

at biologically relevant lag times of 0- and 1-day were not statistically significant. 

Therefore, the results of Ito et al. do not provide support for an association between 

ozone and hospital admissions. 

A summary of EPA’s 1997 and 2006 risk estimates for respiratory hospital admissions 

are presented in Tables 5 and 6, respectively. The risk ratios and coefficient’s from the 

epidemiology studies EPA used in 1997 were quite similar to those used in 2006. In fact, as 

mentioned above, some of the exact same studies were used. However, since the methodology 

EPA used to calculate risks in 2006 differs markedly from the methodology used in 1997, it is 

somewhat misleading to directly compare the risk figures. The following are the key differences 

in the methodologies used: 

• In 1997, EPA used an ozone background level of 40 ppb. In 2006, EPA used much lower 

background levels modeled from GEOS-CHEM. This effectively increases the 2006 

estimates. 

• The estimates in 1997 are presented as incidence per 106

 people per 100 ppb ozone. The 

2006 estimates are presented as incidence per 105

 of relevant population for ozone levels 

above background, in years 2004 and 2002. This change in metric makes it difficult to 

compare risk results from 1997 to 2007. 

• In 2006, EPA also considered the baseline incidence of morbidity in various regions, 

which was not done in 1997. 
Exxon Mobil Corporation Comments - 63 

• In 1997, EPA did not appear to estimate risks in cities where the underlying risk 

coefficients were not statistically significant. In 2006, EPA used risk coefficients from 

studies that were not statistically significant. 

• In both 2006 and 1996, EPA used risk coefficients from non-biologically plausible lag 

times (e.g., as long as 3-4 days). 

• For the 1997 risk assessment, EPA considered all seasons. In 2006, EPA focused on 

seasonal (April to September) estimates, an assumption that should increase the resulting 

risk estimate. This decision appears without explanation and reason that we can 

understand. 

• In both 1997 and 2006, EPA used risk coefficients that were not adjusted for potential 

confounding effects of other pollutants, even though in 2006 adjusted coefficients were 

available in the new studies. This continues the use of risk assessments with a 

fundamental flaw, not recognizing confounding. 

A careful comparison of the 1997 and 2006 risk estimates in Table 5 confirms that the 

risks for hospital admissions have not increased. While the incidences in both 1997 and 2006 are 

generally low, the range of figures in 2006 is higher due to changes in key assumptions put into 

action prior to completing confirming science). This can be illustrated by comparing the 

difference in estimates for New York, which are based on the same underlying data Thurston et 

al. (1992). The results in 2006 are higher than in 1997. A key assumption driving this higher 

risk estimate was not new data showing greater health effects, but rather EPA’s decision to lower 

background ozone levels. (As discussed later in these comments, there is no basis for lowering 

the background levels. In fact, there is more justification now for raising background levels.) 

This change to a new choice for background ozone appears to us without adequate explanation 

and reason and considering the implications for consideration during the process to evaluate the 

support for a standard "the attainment and maintenance of which is requisite to protect the public 

health". 

The estimated incidences in 2006 are generally much more variable, even changing from 

negative (implying ozone exposure reduces the incidence of hospital admissions) to positive, 

depending on only the lag time considered. In the study by Ito (2003), most of the estimates at 

biologically plausible lags (day 0 or 1) are negative, whereas those at less biologically plausible 

lags are positive. This illustrates the tenuous and heterogeneous (inconsistent) nature of 

morbidity estimates, such as hospital admissions, derived from the results of time-series studies. 

Also, part of the higher variability in estimates in 2006 is attributed to EPA’s use of high-end 

risk coefficients from the underlying studies (e.g., Schwartz 1996), which are about 5- 10-fold 

higher than the coefficients from the other studies EPA used (see data from EPA tables 4-12 and 

D-13 below). The higher coefficients result in higher estimates of hospital admissions per unit 

population estimates. 
Exxon Mobil Corporation Comments - 64 

Table 5 

Summary of Effect Estimates For Ozone 

in Recent Time Series Studies of Respiratory Hospital Admission 

(Table V-16, EPA Staff Paper, 1997) 

Location Reference Respiratory Adm. 

Category 

Effect Size (=/-SE) 

Admissions/100 ppb 

O3/day/106 persons 

Relative Risk of 100 

ppb ozone 

1-hr max 

NY City, NYa Thurston, 1992 All 1.4 (+/- 0.5) 1.14 (1.06-1.22) 

Buffalo, NYa Thurston, 1992 All 3.1 (+/- 1.6) 1.25 (1.04-1.46) 

Ontario, Canadaa Burnett et al, 1994 All 1.4 (+/- 0.3) 1.10 (1.06-1.14) 

Toronto, Canadaa Thurston 1994 All 2.1 1.4 (+/- 0.8) 1.36 (1.13-1.59) 

Montreal, Canadab Delfino, 1994 Pneumonia in elderly 1.4 (+/- 0.5) 1.22 (1.09—1.35) 

Birmingham, ALc Schwartz, 1994a COPD in elderly 0.73 (+/- 0.54) 1.11 (0.97-1.26) 

Birmingham, Alc Schwartz, 1994a Pneumonia in elderly 0.83 (+/- 0.33) 1.13 (0.92-1.39) 

Detroit, MIc Schwartz, 1994b COPD in elderly 0.82 (+/- 0.26) 1.22 (1.12-1.35) 

Detroit, MIc Schwartz, 1994b Pneumonia in elderly 0.90 (+/- 0.41) 1.25 (1.07-1.45) 

Minneapolis, MNc Schwartz, 1994b Pneumonia in elderly 0.41 (+/- 0.19) 1.117 (1.03-1.39) 

Minneapolis, MNc Schwartz, 1994b COPD in elderly - Not significant 

Table 6 

Estimated Incidences of Respiratory Hospital Admissions 

(Tables 4-12 and D-13, EPA Ozone Health Risk Assessment for Urban Areas, 2006) 

Location Reference 

Respiratory 

Admission 

Category 

Incidence/100,000 of 

Relevant Population 

at Ozone Levels 

Above Policy 

Relevant Background, 

2004 

Risk 

Coefficient 

Exposure 

Metric Lag 

New York Thurston, 

1992 

All 5.6 ( 14-98) 1.3 E-08 1-hr max 3 day 

New York Thurston, 

1992 

Asthma 4.8 (1-8.5) 1.17E-08 1-hr max 1 day 

Cleveland Schwartz, 

1996 

All 27 (6.9-46.8) 0.00169 1-hr max 1-2 day 

average 

Los 

Angeles 

Linn, 2000 All 0.9 -0.4-2.1)a 

0.5 (-0.7-1.8)a

0.00110 

0.000060 

24 hr ave 0 day 

spring 

0day 

summer 

Detroit Ito, 2003 All 6 (0.5-1.6) 0.00093 24 hr ave 0 day 

Detroit Ito, 2003 Pneumonia -9 (-10.5-27.5) 

-2.6 (-22.6-16.5) 

+3.1 (-16.7-22.1) 

+9.o (-10.5-27.5) 

-0.00218 

-0.00054 

0.00066 

0.00190 

24 hr ave 0-day 

1-day 

2-day 

3-day 

Detroit Ito, 2003 COPD -7.1 (-25.6-10.4) 

6.8 (-11-23.7) 

-1.0 (-19.5-16.5) 

0.4 (-18-17.8) 

-0.00191 

0.00187 

-0.00027 

0.00011 

24 hr ave 0-day 

1-day 

2-day 

3-day 

 Incidence based on coefficients not reported as statistically significant in the underlying study. 
Exxon Mobil Corporation Comments - 65 

C. EPA’s risk assessment of acute ozone mortality systematically overestimates 

risks. 

As discussed above, EPA has failed to establish a causal relationship between ambient 

exposure to ozone and acute mortality. There are serious concerns with the accuracy of the 

underlying concentration response functions and shape of these functions at low concentrations. 

Moreover, the evidence supporting causality for acute mortality (clinical, toxicological, and 

epidemiology) is so weak and spurious, the health effect endpoint should not be considered in 

making a decision on whether to revise the standard. These concerns are sufficiently serious to 

conclude that the mortality risk estimates are not reliable and, therefore, should not be considered 

in determining the appropriate level of the NAAQS. These key points are supported by the June 

5, 2006 letter from CASAC at 3, as well as the findings in the Rochester Report from review of 

the health science on ozone by the Rochester group, see, e.g., Rochester Report at 63, 74. 

In the 2007 Ozone Risk Assessment for Acute Mortality, EPA uses concentration 

response functions (CFRs) from Bell et al. (2004), Huang et al. (2004), and Schwartz et al.

(2004), and a linear exposure response model to estimate reductions in acute mortality associated 

ozone reductions above background levels in 12 urban areas. EPA employs several significant 

and often scientifically unsupportable decisions and assumptions, all of which result in 

increasing the risk estimates. These assumptions are summarized briefly below. 

1. Study selection - EPA’s decision to use results of positive studies but ignore the results 

from negative studies. Kinney et al. (1995) and Moolvgavkar et al. (2000) report no 

association between ozone and mortality in Los Angeles; Zmirou et al. (1998) report no 

positive associations in Lyon, Paris or London; and Gryparis et al. (2004) report no 

association between ozone and mortality in various European cities. But, EPA has made 

the scientifically questionable decision to ignore these results in estimating the risk from 

mortality. 

2. Study selection - Selective reliance on usually high coefficients from studies reporting 

higher end risk estimates. For example, EPA used the results from Schwartz et al. (1996) 

for Cleveland in the 2007 Ozone Risk Assessment, even though the coefficients reported 

in this study are about an order of magnitude higher than all other results. Reliance on 

this coefficient results in risk estimate that is not reflective of even the results from other 

positive studies, let alone the many studies which report no association. 

3. Study selection Use of single model results (ozone only) when results from co-pollutant 

models are available. For example, in the study by Ito et al. (2003), including PM10

reduced the risks attributed to ozone. However, EPA placed more emphasis on the 

coefficients that were not adjusted for PM10. 

4. Use of statistically insignificant studies - Use of positive but not statistically significant 

risk estimates and selective use of Bayesian shrinkage estimates. EPA uses Bayesian 

estimates from Bell et al. (1995) for which the large majority of cities (89/95) are positive 

but not statistically significant. Further, it is important to note that before the Bayesian 
Exxon Mobil Corporation Comments - 66 

transformation was performed, between a third and half of the coefficients were negative, 

even without adjustment for PM10. Use of the Bayesian estimates essentially results in a 

net increase of many of the single-city coefficients versus those reported before the 

adjustment was applied. 

 Use of linear exposure response model to extrapolate acute mortality to PRB levels of 15-

35 ppb. Even though EPA uses a sigmoidal concentration response function to assess 

pulmonary effects, EPA defaults to a more conservative, health protective linear model to 

assess a more serious health effect endpoint, acute mortality. EPA based this decision on 

results of time-series mortality studies. In particular, EPA places great importance on the 

results of Bell et al. (2006). The Rochester group expressed “we have doubts about the 

methodology [used in Bell et al. 2006] and feel that judgment should be reserved on this 

conclusion at the present time.” (Rochester Report at 49) Further, as described above, 

there are serious concerns with using ambient monitors to assess personal ozone 

exposure. Due to this serious problem, it is not possible to assess concentration response 

functions or thresholds. Also, the extensive human clinical data for ozone provide 

evidence to strongly support the use of a threshold-based approach to risk assessment. 

5. Choosing to use a new ozone concentration background definition and approach. As 

discussed further in our comments, correction of this assumption alone could eliminate 

over 95 percent of the risk reduction potential of revising the standard. By EPA’s own 

analysis, most of the acute mortality risk is associated with biologically implausible 

ozone levels of 15-35 ppb. 

6. Use of a flawed rollback assumption. Use of a rollback assumption that ozone 

concentrations will be reduced substantially even on moderate and low ozone days as a 

result of a standard whose form addresses only the peak days. 

Based on our analysis, EPA’s bias in selecting studies and risk coefficients, combined with their 

no-threshold approach to risk assessment, new and unsupported assumption for ozone 

background levels, and its flawed rollback procedure, act together to significantly inflate the risk 

estimates by several orders of magnitude.

D. EPA fails to adequately address significant uncertainties in their assessment 

of acute mortality risks. 

EPA claims that they have addressed the sources of uncertainty in its risk assessment of 

acute ozone mortality because statistical uncertainty surrounding the Concentration-Response 

Function (CRF) is reflected in the confidence intervals. This is not correct. Contrary to EPA’s 

claim, the Agency has failed to consider several important sources of uncertainty. 

• Statistical uncertainty considers whether the findings are due to chance (p value or 

confidence intervals), and is the only source of uncertainty that is considered by EPA. 

However, it is not the most important source of uncertainty and is largely dependent on 

sample size. The increase in sample size (from combining many studies in the metaanalyses) so increased the statistical power of the studies that even minuscule effect 
Exxon Mobil Corporation Comments - 67 

estimates became statistically significant and were allowed to overshadow the more 

important hidden uncertainties. Hidden uncertainties, such as the choice of statistical 

model, are a more important source of uncertainty and have a significant impact on the 

effect estimates, generally to further reduce the strength of the associations. 

• Existence of a causal relationship: While EPA indicates that there is uncertainty in 

whether or not a causal relationship has been established for acute ozone mortality, the 

Agency does not consider this uncertainty at all in the risk assessment. In the risk 

assessment, EPA assumes 100% probability that the associations are causal. As 

summarized above, and as indicated by CASAC, the causal relationship is far from 

conclusive. To capture the full range of uncertainties, EPA should present a risk 

assessment based on the possibility that causality has not been established for acute 

ozone mortality. Given that the Regulatory Impact Analysis (RIA) for ozone accounted 

for this uncertainty it is not clear why the risk assessment itself fails to do the same. 

• Potential for a threshold or non-linear effects. In the 2006 CD and 2007 SP, EPA 

indicates there is also uncertainty concerning the shape of the CRF for acute ozone 

mortality, specifically whether it is linear at low concentrations with no threshold. EPA 

states that it recognizes that the available epidemiologic evidence neither supports nor 

refutes the existence of thresholds at population levels. However, even though EPA 

states that the evidence for the linear no-threshold approach is based on “limited” data, 

EPA does not consider this uncertainty at all in their risk assessment (2007 Ozone Risk 

Assessment). To capture the full range of uncertainties for the existence of a possible 

threshold, EPA must consider alternate risk assessment approaches that assume a 

threshold exists. We suggest evaluating cut points of 80, 70, and 60 ppb below which 

acute ozone mortality cannot be quantified. 

• Concentration-Response Functions. EPA has also not resolved key uncertainties in the 

concentration response functions that have a marked influence on the risk estimates. As 

discussed above, EPA’s response to these uncertainties is to ignore the uncertainty by 

making a choosing instead to use a conservative assumption without proof that will lead 

to ever-increasing overestimates of risk. These uncertainties include (a) using risk 

estimates from single-city studies which are known to be influenced by publication bias 

versus those from Bayesian shrinkage estimates for the same city derived from multi-city 

studies (the latter tend to obscure sources of heterogeneity , (b) the use of non-threshold 

CRF, and (c) the continued preference for the results from single versus 2- or multipollutant time-series models even though: (1) the exposure data clearly demonstrate the 

potential for significant confounding by PM2.5; (2) few time-series studies have evaluated 

confounding by PM2.5 but rather focus on PM10 which is known not to correlate with 

ozone; and (3) the limited analysis done with 2- pollutant models actually demonstrates 

significant confounding by co-pollutants including PM, NO2, and SO2.

• Uncertainty from excluding “negative” studies. Similarly, EPA has also not addressed 

the uncertainty associated with ignoring the results of time-series studies which do not 

report positive findings. The results of these studies could be included in the risk 
Exxon Mobil Corporation Comments - 68 

assessment through the use of an integrated uncertainty analysis that would weigh and 

combine all results, not just the positive results selected by EPA. 

• Uncertainty from using positive, non-statistically significant risk coefficients. Similarly, 

EPA has not addressed the uncertainty associated with using a positive but nonstatistically significant risk coefficient for single cities within a multi-city study. These 

results could also be considered as representing zero risk for purposes of risk 

characterization. EPA has also not addressed the issue of using results of seemingly 

high-end risk coefficients such as those from the cities in the study by Schwartz et al.

(2004). 

• Uncertainty from not knowing the true ozone background levels. As discussed below, the 

choice of an ozone background level can significantly increase or lower the risk reduction 

potential of revising the standard. Significant uncertainty exists over average and 

maxima ozone background levels. The proposal did not clearly explain and establish the 

basis for the particular choice made in the proposal. 

The overall uncertainty associated with selecting which data set to consider, even with the 

limited range of data EPA has considered, is much greater than the incremental change produced 

at alternate ozone standards. This uncertainty alone renders the risk estimates as not useful for 

purposes of defining the NAAQS. The actual numbers in the various tables highlight this 

concern. For example, in Table 5C-13 for Atlanta, the estimated risk of potential non-accidental 

mortality attributed to ozone at the current standard in 2004 varies from 5 to 9 depending on 

which “key” study one selects, i.e., Bell’s 2004 single-city estimate or Bell’s 2004 Bayesian 

shrinkage estimate. However, at a proposed lower standard of 74 ppb/4th highest, the estimated 

risk changes only from 5 to 4, or from 9 to 7, using the single-city and shrinkage estimates, 

respectively. 

For Houston, the estimated risk varies from 11 to 70 at the current standard, depending 

on whether data from Bell et al. (2004) or Schwartz (2004) are used. These values only change 

incrementally, for example, from 11 to 8 using the data from Bell at an alternate standard of 74 

ppb/4th highest. The pattern is repeated for Chicago, where the estimated risk ranges from 33-

314 at the existing standard, depending on the data set used, but changes only incrementally at 

alternate lower standards. 

Similarly, for morbidity health effect endpoints such as hospital admissions, the 

uncertainties resulting from the accuracy of underlying concentration response functions are 

enormous as compared to the incremental changes at alternate standards. For example, Table 5-8 

shows a “gradual reduction” in the hospital admission cases per 100,000 from 4.6 cases upon just 

meeting the current NAAQS to 3.0 cases for the most stringent alternate NAAQS (0.064 ppm/4th

highest). Given all the uncertainties in ozone time-series studies, in our view, there is no 

statistical or biological difference in these values. Further, the underlying epidemiologic data are 

not nearly accurate enough to allow presenting such data to the resolution of two significant 

figures. 
Exxon Mobil Corporation Comments - 69 

Overall, given the underlying uncertainties in the concentration response functions and 

the shape of these functions at low concentrations, the incremental changes in health effects 

endpoints at alternate standards cannot be viewed as statically different or biologically 

meaningful. Hence, these estimates are not useful for determining the appropriate level of the 

NAAQS. 

XII. EPA Has Failed to Adhere to OMB Guidance and NAS Recommendations By Not 

Conducting an Integrated Uncertainty Analysis to Fully Account for the 

Uncertainties Present in the Risk Assessment. 

OMB Circular A-4 requires an uncertainty analysis in the Regulatory Impact Analysis 

(RIA) for rules that exceed an annual cost of a billion dollars. (OMB Circular A-4 at 39-41). In a 

complex rule, such as this one, the Circular calls for a more quantitative probabilistic analysis of 

the uncertainties. : 

Apply a formal probabilistic analysis of the relevant uncertainties 

possibly using simulation models and/or expert judgment as revealed, for 

example, through Delphi methods. Such a formal analytical approach is 

appropriate for complex rules where there are large, multiple 

uncertainties whose analysis raises technical challenges, or where the 

effects cascade; it is required for rules that exceed the $1 billion annual 

threshold. For example, in the analysis of regulations addressing air 

pollution, there is uncertainty about the effects of the rule on future 

emissions, uncertainty about how the change in emissions will affect air 

quality, uncertainty about how changes in air quality will affect health, 

and finally uncertainty about the economic and social value of the 

change in health outcomes. In formal probabilistic assessments, expert 

solicitation is a useful way to fill key gaps in your ability to assess 

uncertainty. In general, experts can be used to quantify the probability 

distributions of key parameters and relationships. These solicitations, 

combined with other sources of data, can be combined in Monte Carlo 

simulations to derive a probability distribution of benefits and costs.

(OMB Circular A-4 at 41). 

The uncertainties raised by OMB far exceed the limited uncertainty addressed by EPA in the 

standard deviation. Uncertainty goes beyond the statistical confidence intervals that EPA now 

reports. The OMB Circular calls upon EPA to conduct a “formal probabilistic analysis of the 

relevant uncertainties.” (Id.) 

The most efficient way to accomplish this goal would be to conduct an integrated 

uncertainty analysis as recommended by Dr. Anne Smith and Dr. David Riker from CRA 

International. In comments submitted on EPA’s Draft Ozone Health Risk Assessment, Smith 

and Riker call upon EPA to conduct an integrated uncertainty analysis: 

EPA’s overall methodology substantially understates, and even obscures, 

the true degree of uncertainty about the health risks from ambient ozone. 

EPA should provide an integrated uncertainty analysis that formally 
Exxon Mobil Corporation Comments - 70 

quantifies these uncertainties. To illustrate the usefulness and feasibility 

of a more rigorous treatment of uncertainty, we have prepared a partial 

integrated uncertainty analysis that incorporates several of the key 

uncertainties ignored in the Second Draft RA. (Page 3) 

 An integrated uncertainty analysis would be the most effective way for the Agency to 

address the many significant uncertainties present in the science in a meaningful way. 

Qualitative discussions, while useful, place an enormous burden on the decision maker to 

understand how the uncertainties affect one another and the cumulative impact they may have on 

our understanding of the risk. 

The National Academy of Sciences (NAS) has also recommended that EPA conduct risk 

assessments that directly account, quantitatively, for important sources of uncertainty. However, 

as stated in the Rochester Report, the risk assessment EPA has failed to account, quantitatively 

for the important sources of uncertainty. According to the Rochester group, the sources of 

uncertainty that EPA has not included in any of the risk estimate ranges that it provides includes: 

(1) uncertainty related to epidemiology model selection bias; (2) uncertainty related to 

epidemiology models, for example, uncertainty in how to control for other confounding effects 

of weather and other pollutants; and (3) uncertainty in whether or not causality is established. 

(Rochester Report at 73-74). 

 On this latter point, EPA claims they placed greater weight for those health effect 

endpoints they considered as causal or likely causal based on the integrative synthesis of the 

entire body of evidence, whereas EPA claims they placed less weight on evidence for 

associations that were judged to be only suggestive. (72 Fed. Reg. at 37862). However, these 

differences are not reflected in any way, quantitatively, in the numeric risk estimates presented 

by EPA. Further, the key differences in causal evidence are not reflected in any way in any of 

the verbal discussion of the risk estimates. In fact, we find the reverse is the case, i.e., EPA 

places more importance on the acute mortality estimates, even though this health effect endpoint 

was judged by EPA to be “highly suggestive” versus causal or likely causal. 

EPA should follow the advice of the National Research Council on the assessment of 

uncertainties: 

EPA should begin to move the assessment of uncertainties from its 

ancillary analyses into its primary analyses by conducting probabilistic, 

multiple-source uncertainty analysis. This shift will require specification 

of probability distributions for major sources of uncertainty. These 

distributions should be based on available data and expert judgment. 

(NAS 2002 at 14). 

Although the results of benefit analysis may appear to be less certain, 

EPA should describe the uncertainty as completely and realistically as 

possible, recognizing that regulatory action might be necessary in the 

presence of substantial uncertainty. 

(NAS 2002 at 15) 
Exxon Mobil Corporation Comments - 71 

Many groups, including the National Academy of Sciences (NAS), have promoted the 

use of quantitative approaches to addressing uncertainty in risk analysis for both hazard 

identification and exposure analysis. In its 1994 publication, Science and Judgment in Risk 

Assessment, the NAS strongly recommended that EPA conduct a more formalized analysis of 

uncertainty: 

Ten years later, however, EPA has made little headway in replacing a 

risk-assessment “culture” based on “magic numbers” with one based on 

information about the range of risk values consistent with our current 

knowledge and lack thereof. 

... 

In direct contrast, the committee believes that uncertainty analysis is the 

only way to combat the “false sense of certainty,” which is caused by a 

refusal to acknowledge and (attempt to) quantify the uncertainty in risk 

predictions. 

(NAS 1994 at 161). 

 In this same publication, the NAS went on to emphasize the poor decision making 

that can result from risk assessments that fail to adequately address uncertainty: 

Risk assessments that do not include sufficient attention to uncertainty 

are vulnerable to four common and potentially serious pitfalls (adapted 

from Finkel, 1990): 

1. They do not allow for optimal weighing of the probabilities and 

consequences of error for policy-makers so that informed riskmanagement decisions can be made. An adequate risk 

characterization will clarify the extent of uncertainty in the estimates 

so that better-informed choices can be made. 

2. They do not permit a reliable comparison of alternative decisions, so 

that appropriate priorities can be established by policy-makers 

comparing several different risks. 

3. They fail to communicate to decision-makers and the public the 

range of control options that would be compatible with different 

assessments of the true state of nature. This makes informed dialogue 

between assessors and stakeholders less likely, and can cause erosion 

of credibility as stakeholders react to the overconfidence inherent in 

risk assessments that produce only point estimates. 

4. They preclude the opportunity for identifying research initiatives that 

might reduce uncertainty and thereby reduce the probability or the 

impact of being caught by surprise. 
Exxon Mobil Corporation Comments - 72 

Perhaps most fundamentally, without uncertainty analysis it can be quite 

difficult to determine the conservatism of an estimate. In an ideal risk 

assessment, a complete uncertainty analysis would provide a risk 

manager with the ability to estimate risk for each person in a given 

population in both actual and projected scenarios of exposures; it would 

also estimate the uncertainty in each prediction in quantitative, 

probabilistic terms. But even a less exhaustive treatment of uncertainty 

will serve a very important purpose: it can reveal whether the point 

estimate used to summarize the uncertain risk is “conservative,” and if 

so, to what extent. Although the choice of the “level of conservatism” is 

a risk-management prerogative, managers might be operating in the dark 

about how “conservative” these choices are if the uncertainty (and hence 

the degree to which the risk estimate used may fall above or below the 

true value) is ignored or assumed, rather than calculated. (Page 166 to 

167). 

(NAS 1994 at 166-167). 

In 2002, the NAS repeated this recommendation in its publication, Estimating the Public 

Health Benefits of Proposed Air Pollution Regulations. The NAS concluded with the following 

recommendation: 

• EPA should begin to move the assessment of uncertainties from its 

ancillary analyses to its primary analyses. This shift will require the 

specification of a probability distribution for each uncertainty source 

that is added to the primary analysis and, as necessary, the 

specification of joint distributions for the uncertainty sources that are 

not independent of each other. Expert judgment, as well as data, will 

be required to specify these distributions. Although the effect on the 

mean of the resulting probability distribution might increase, 

decrease, or remain the same, the effect on the spread of the 

distribution will be a predictable widening and, therefore, a more 

realistic depiction of the overall uncertainty in the analysis. 

• As it incorporates additional sources of uncertainty into its primary 

health benefits analyses, EPA should consider conducting analyses to 

determine which uncertainty sources have the greatest influence on 

the mean and spread of the probability distribution. The need for 

these sensitivity analyses will be particularly great for distributions 

that are based on expert judgment. The uncertainty sources that have 

the greatest consequences for decision-making, including those that 

have the greatest impact on the spread of the distribution, should be 

given high priority for additional research. 

• Because the incorporation of expert judgment when data are 

unavailable will influence the estimates of health benefits as well as 

the uncertainty analyses, the committee also recommends that EPA 

clearly distinguish between data-derived estimates of some 

components—such as the concentration-response function—and 

expert opinions about other components that are lacking in scientific 
Exxon Mobil Corporation Comments - 73 

data—such as the degree of compliance with a particular regulation 

30 years into the future. In this way, policy-makers will better 

understand how existing data and expert judgment combine to 

produce estimates and where new data would be most valuable.

(NAS 2002 at 146-147).

 For almost twenty years, the NAS has consistently urged EPA to conduct a more 

quantitative analysis of uncertainty in complex risk assessments that involve major uncertainties. 

In the review of the ozone standard, there are several major sources of uncertainty, including 

model selection bias, role of confounders, including other pollutants, and the shape of the doseresponse curve. These uncertainties are not accounted for in EPA’s measure of statistical 

variance. Without an integrated uncertainty analysis, there is no way for the decision maker to 

understand how the uncertainties combine and the extent to which they affect estimates of risk at 

the current standard and the potential benefits of tightening the standard. 

 

XIII. EPA’s Decision to Lower the Ozone Background Levels From Levels Justified in the 

1997 Review is Incorrect and Not Scientifically Supportable. 

 In the 1997 final ozone rule, EPA estimated, based on monitoring data, that background 

levels from natural sources could be close to .07 ppm. (62 Fed. Reg. at 38,868). This fact was 

important to EPA’s decision regarding the level of ozone deemed requisite to protect public 

health with an ample margin of safety: 

3) As many commenters have noted, based on information in the Criteria 

Document with regard to ambient concentrations of O3 from background 

sources, an 8–hour standard set at a 0.07 ppm level would be closer to 

peak background levels that infrequently occur in some areas due to nonanthropogenic sources of O3 precursors, and thus more likely to be 

inappropriately targeted in some areas on such sources. After taking into 

account the public comments, and for the reasons outlined above, the 

Administrator finds that a standard set at a level of 0.07 ppm is not

requisite to protect public health with an adequate margin of safety. 

Id. EPA’s consideration of background levels under the proposed rule was flawed and 

underestimates the Policy Relevant Background (PRB). 

A. EPA’s definition of policy-relevant background incorrectly excludes 

anthropogenic emissions from Canada and Mexico. 

The Agency defines a PRB as those concentrations that would result in the U.S. in the 

absence of anthropogenic emissions in North America; i.e., leaving no room for ozone caused 

from human activities. (2007 SP at 2-48). However, EPA’s definition of PRB used here is 

flawed for several reasons. The model exercise EPA relied on omits the contribution from the 

emissions from agricultural activities, and it omits consideration of the contribution to ozone 

from anthropogenic emissions in Mexico and Canada. While there can be reductions in 

emissions from agricultural activities, as with other human activities, it would be impossible to 

drive them to zero. No one contemplates the cessation of human activities including the practice 
Exxon Mobil Corporation Comments - 74 

of growing crops and raising animals in the United States. Omitting the impact of Canadian and 

Mexican emissions is also problematic because, even though the United States may have treaties 

with these countries, zero anthropogenic emissions and ceasing human activities in these 

countries is not a possible future outcome.

B. In previous reviews, both means and extremes of background were 

evaluated. The 2006 CD indicates that the global model EPA relied on in the 

current review is unable to simulate local maxima. 

 Uncontrollable ozone levels can fluctuate greatly due to a number of factors, including 

changes in biogenic emissions, temperature, stratospheric ozone intrusions and international 

transport. In previous ozone reviews, EPA evaluated background concentrations of ozone 

primarily based on measured observations of ozone and other compounds in remote locations.

Because of the form of the standard, the ozone background levels related to the extremes of the 

distribution of the daily maxima, as well as the means, must be evaluated. Ideally, this means 

that background concentrations must be evaluated for each ozone metric being considered for the 

primary and secondary standards. Since extreme value forms of the ozone standard are being 

proposed, then measured ozone values or modeled estimates of the extremes of PRB must be 

considered. In previous ozone reviews, both the means and extremes of background were 

evaluated. For example, the Agency’s SP in the previous review concluded: 

...a reasonable estimate of the background O3 concentrations near sea 

level in the U.S. for a 1-hour daily maximum during the summer is 

usually in the range of 0.03 to 0.05 ppm. At clean sites in the western U. 

S., the maximum annual hourly values are in the range of 0.06 to 0.075 

ppm. 

(2006 SP at 20). In the current review, the 2006 CD discusses estimates of background 

concentrations from both observations and models, but the 2007 SP relies almost entirely on one 

global chemical transport modeling study to model an estimated mean background. The CD, 

however, notes several important limitations of that study and the need for additional work to 

evaluate PRB with an ensemble of models comparing the model results with observations. 

The large grids in the global model mix air parcels of different composition and origin in 

an unrealistic way, severely limiting its ability to accurately simulate local photochemical 

activity, intercontinental transport, and the impact of stratospheric air inserted into the 

troposphere. The 2006 CD notes the need to include models with greater resolution to 

understand variability on shorter time scales and variability due to processes that are not captured 

in the global models. Until this is done, EPA should use a range of background estimates from 

observations. The failure of the final 2007 SP to provide information on the extremes of 

background is a serious omission. 
Exxon Mobil Corporation Comments - 75 

C. Uncontrollable background levels from ozone transport have increased since 

2001 -- the year the GEOS-CHEM model was run -- and are likely to 

increase significantly over time as emissions in Asia increase. 

EPA’s assumed PRB, as defined by EPA, correctly includes emission transport from 

sources outside North America. However, new data suggest that the GOES-CHEM model may 

significantly underestimate the contribution of emissions from outside of North America. As a 

result, the model may significantly under predict ozone background levels. 

The GEOS-CHEM model provides estimates of ozone background concentrations for the year 

2001. Data compiled under the Center for Global and Regional Environmental Research (see 

Table 8) show that estimates of nitrogen oxide emissions have increased by over 60 percent 

from Asia since 2000. The authors note that some of this increase is due to growth in emissions 

while some is due to improvements in emission inventory and record keeping. The magnitude of 

this increase since 2000, however, suggests that the GEOS-CHEM model may significantly 

underestimate the level of NOx emissions and ozone attributable to sources outside North 

America. 

Tables 7-10 summarize changes from the 2000 (Trace-P) and 2006 (INTEX-B) emissions 

inventories. 

Table 7 

Summary of Changes to CO Emissions 

 Power Industry Residential Transportation Total 

China Total N/A 316.3% 27.0% -11.3% 66.9% 

Other East Asia Total N/A -26.1% -17.1% -22.7% -21.7% 

Southeast Asia Total N/A 70.8% 14.4% 55.3% 30.9% 

South Asia Total N/A 48.4% 9.2% 34.2% 20.4% 

Asia Total N/A 204.2% 17.2% 8.7% 41.1% 

Table 8 

Summary of Changes to NOx Emissions 

 Power Industry Residential Transportation Total 

China Total 108.7% 92.5% 66.0% 93.7% 97.8% 

Other East Asia Total -0.1% 16.5% -39.8% 5.9% 4.3% 

Southeast Asia Total 203.8% 103.3% 16.0% 37.8% 80.3% 

South Asia Total 25.8% 54.4% 4.7% 12.2% 22.4% 

Asia Total 90.7% 72.8% 22.6% 40.3% 61.8% 

Table 9 

Summary of Changes to NMVOC Emissions

 Power Industry Residential Transportation Total 

China Total 956.4% 116.5% 35.5% 24.7% 57.7% 

Other East Asia Total 392.7% 38.1% -69.8% -4.5% 3.3% 

Southeast Asia Total 75.1% 28.3% 19.1% 39.3% 27.3% 

South Asia Total 43.2% 37.8% 13.1% 38.0% 25.3% 

Asia Total 541.2% 70.2% 18.0% 29.7% 35.7% 
Exxon Mobil Corporation Comments - 76 

Table 10 

Summary of Changes to OC Emissions

 Power Industry Residential Transportation Total 

China Total 9.5% 1728.3% 1.3% 95.1% 21.1% 

Other East Asia Total -99.9% -62.3% 4.6% -2.8% -9.2% 

Southeast Asia Total -27.8% 9.9% 14.2% 59.9% 15.3% 

South Asia Total 1372.2% 1271.9% -51.6% 17.2% -43.3% 

Asia Total 43.0% 1032.3% -17.4% 41.1% -6.6% 

IMPORTANT NOTE: The emission changes between the two inventories reflect a combination of: (a) actual growth 

in emissions due to increasing economic development, (b) the effects of replacing the TRACE-P inventory by local 

inventories in several countries, and (c) improvements and corrections made to the original TRACE-P inventory. 

The changes should not be viewed solely as real emissions growth. The 2006 inventory values are considered to be a 

reasonable reflection of the absolute magnitude of emissions in that year, pending re-calculation with actual activity 

statistics when they become available. Contacts: dstreets@anl.gov; zhangq@anl.gov 

Independent research by Roxane Vingarzan, A Review of Surface Ozone Background Levels and 

Trends, (Atompsheric Environment 38 (2004) 3431-3442) confirms the significance of Asian 

emissions on North American ozone levels: 

 

Model sensitivity studies indicate that the rise in NOx emissions account 

for the greatest increase in background ozone levels over the past three 

decades. A substantial component of the background ozone 

concentration in western North America may be due to long-range 

transport of Asian pollution, especially during the spring months. Model 

projections using IPCC emission scenarios for the 21st century indicate 

that background ozone may rise to levels that would exceed 

internationally accepted environmental criteria for human health and the 

environment. 

Vingarzan notes that the IPCC projections indicate that surface ozone levels are expected to “rise 

significantly throughout the 21st Century.” (at 3437) with half the rise due to increases in 

methane emissions and the other half due to increases in NOx emissions. She further notes that 

any warming of temperatures could make this contribution to background levels even higher. 

She notes that the projections exceed internationally accepted environmental criteria, ranging 

around 40 to 50 ppb. Vingarzan concludes: 

Given that these values represent background conditions, any additional 

ozone production associated with smog episodes would make it very 

difficult to achieve a clean air standard of < 80 ppb over most populated 

regions (IPCC, 2001) 

Vingarzan’s conclusions appear all the more valid given that the IPCC projections are based on 

2001 before the rapid increase in NOx emissions from Asia were recorded. The rapid increases 

suggest that background levels in North America may have already risen significantly from 

emissions outside North American and that the GEOS-CHEM model has significantly under 

predicted their contribution. 
Exxon Mobil Corporation Comments - 77 

XIV. EPA’s Assumed Level of Policy-Relevant Background Overestimates the Potential 

Risk Reduction and the Benefit From Tightening the Ozone Standard. 

A. Morbidity and mortality health benefits are highly sensitive to EPA's choice 

of ozone background levels. 

Absent acute mortality benefits, EPA’s current analysis estimates annual public health benefits 

of less than $200 million per year from revising the standard (2007 RIA at 6-2). Even this 

estimate, however, is likely to significantly overestimate non-mortality health benefits due in 

large part to changes in EPA’s assumed background levels for ozone. As described above, the 

choice of ozone level to be used in determining background levels (both average and peak levels) 

play a key role in determining the potential health risk benefits from lowering the ozone 

standard. 

Recent monitored values of ozone in our nation’s pristine parks are routinely in the 0.04 

to 0.06 ppm range. In the 2007 SP, EPA significantly lowered its estimate of background ozone 

levels from .040 ppm used in 1997 to hourly values that range from 0.15 to 0.035 (at 5-92). The 

Agency did this by replacing monitored values in the United States with modeled values from a 

global model called GEOS-CHEM. EPA’s Clean Air Scientific Advisory Committee raised 

concerns about EPA’s proposed estimate of background. 

Finally, with respect to policy-relevant background (PRB), the Ozone 

Panel wishes to point out that the Final Ozone Staff Paper does not 

provide a sufficient base of evidence from the peer-reviewed literature to 

suggest that the current approach to determining a PRB is the best 

method to make this estimation. 

(Mar. 2007 CASAC letter at 2). 

In the final SP, EPA acknowledges that a policy relevant background monitoring site 

does exist in the U.S. 

The comparisons at Trinidad Head are especially relevant because 

sources of the O3 [ozone] found there are often limited to those in the 

PRB definition. 

(2007 SP at 2-54). 

The maximum monthly diurnal average at Trinidad Head was .050 ppm. The differences in 

ozone values between the GEOS-CHEM model for selected cities and monitored values at the 

Trinidad site are shown in Figure 2 from Dr. Lefohn’s February 28, 2007 CASAC testimony: 
Exxon Mobil Corporation Comments - 78 

Figure 2

 The health benefits estimate for a lower ozone standard is significantly affected by the 

choice of ozone level to be used in determining ozone background levels . In testimony before 

EPA’s CASAC on February 28, 2007, Dr. Allen S. Lefohn (A.S.L. & Associates) illustrated the 

differences in absolute incidences of ozone non-accidental mortality between EPA’s proposed 

PRB using GEOS-CHEM and the proposed PRB plus 5 ppb (i.e., 25 versus 30 ppb). This was 

accomplished by graphing the results of EPA’s own sensitivity analyses included in Appendix I 

of EPA’s Risk Assessment. Dr. Lefohn’s testimony reveals that increasing the PRB by just 5 

ppb resulted in significant reductions in the estimates for absolute incidences of ozone nonaccidental mortality: 

For the “84/4” [0.084 ppm ozone level with 4 exceedances], “74/4” 

[0.074 ppm ozone level with 4 exceedances], and “64/4” [0.064 ppm 

ozone level with 4 exceedances] options, there was a 62%, 72% and 86% 

reduction in the estimates when 5 ppb was added to PRB for the absolute 

incidences of O3 non-accidental mortality, respectively. 

(Lefohn, A.S. 2007, at 12). 
Exxon Mobil Corporation Comments - 79 

Figure 3

Source: Lefohn, A.S. (2007) at 15. 

 The sensitivity of health risk benefits (mortality and non-mortality) to PRB was 

confirmed by a CRA International (Attachment D) on mortality and non-mortality risk. CRA 

reproduced the sensitivities that EPA (and Dr. Lefohn) reported, and also demonstrated that if 

EPA had used a higher summer estimate of average ozone background levels of 0.04 ppm (which 

was used in EPA’s 1997 review rather than the lower value that EPA is using in the 2007 

review), the estimated number of potential deaths and other health effects projected at just 

attaining the current standard for the city of Houston and Detroit would fall by over 95 percent. 

This sensitivity in the estimated risk will apply to tighter standards as well. 

B. An Analysis of the Distribution of Risks Show That the Current Standard is 

Protective of Public Health.

According to the attached CRA analysis a major reason for this significantly reduced 

estimate of health benefits is that a very large portion of the risks that EPA is calculating is 

associated with 8-hour periods when ozone is less than 0.070 ppm. An analysis of the risk in 

seven U.S. cities show that less than 0.08 percent of the total non-accidental mortality in these 

cities is due to ozone exposure at levels that exceed 0.070 ppm. According to EPA, exposure to 

ozone at lower levels is of less public health concern: 

The Administrator particularly notes that as lower standard levels are 

modeled, including a standard set at a level below 0.070 ppm, the risk 

assessment continues to assume a causal link between O3 exposures and 
Exxon Mobil Corporation Comments - 80 

the occurrence of the health effects examined, such that the assessment 

continues to indicate reductions in O3-related risks upon meeting a lower 

standard level. As discussed above, however, the Administrator 

recognizes that evidence of a causal relationship between adverse health 

effects and O3 exposures becomes increasingly uncertain at lower levels 

of exposure. Given all the information available to him at this time, the 

Administrator judges that the increasing uncertainty of the existence and 

magnitude of additional public health protection that standards below 

0.070 ppm might provide suggests that such lower standard levels would 

likely be below what is necessary to protect public health an adequate 

margin of safety. (72 Fed. Reg. at 37,880). 

This statement, when coupled with the analysis by CRA International, suggests that most 

of the estimated risk remaining from attaining the current standard comes from exposure below 

ozone levels of concern. Only a tine fraction of the non-accidental mortality in these cities can 

be attributed to ozone at ozone levels of potential concern. This suggests that attaining the 

current standard is amply protective of public health. 

The approach of extrapolating mortality down to an unrealistically low PRB results in a 

large percentage of the estimated risk projected to occur at ozone levels at or below 40 ppb. 

This sensitivity to 0.005 ppm changes in background is a demonstration that the bulk of 

estimated mortality comes from days with ozone concentrations that are very low. This is not 

biologically plausible. 

 

Given all the issues noted above with EPA’s policy relevant background levels, the 

Agency should re-evaluate its ozone background level choice and then re-evaluate the estimated 

risk reduction. Only then can the adequacy of the current standard be evaluated on a sound 

basis. The proposed rule recognizes the importance of this issue and indicates additional 

sensitivity analyses to background will be carried out. (72 Fed. Reg. at 37,857 n.40). 

XV. The Theoretical Basis for EPA’s Estimate of Policy Relevant Background is Not 

Supportable Under the Clean Air Act Because it Assumes a Level of Potential 

Emission Reductions That is Unrealistic and Unrepresentative of Actual 

Background Levels.

EPA’s estimate of health benefits from lowering the ozone standard is based on a 

definition of policy relevant background that assumes that there are zero anthropogenic 

emissions from the United States, Canada, and Mexico. This is unrealistic, and cannot be 

defended either as being “policy relevant” or as a “background” level. Given that EPA is not 

suggesting the elimination of all anthropomorphic emissions from within the United States, 

including agricultural related emissions, the standard implied in the definition of PRB is 

unrealistic and unachievable, even as a theoretical construct. Further, since the United 

States can not require Canada and Mexico to eliminate their anthropomorphic emissions, how 

can EPA establish a background level that is premised on that very thing? 
Exxon Mobil Corporation Comments - 81 

XVI. EPA’s Risk Estimates From Exposure to Ozone are Arbitrary Because the Agency 

Relies on a Biased Subset of Studies With Less Scientific Merit. 

EPA’s risk estimates included in the Risk Analysis and reported in the SP do not reflect 

the full range of risk estimates developed for each city and included in the CD. Instead, for 

purposes of estimating risk, EPA continues its policy of selectively using single-pollutant, singlecity results reporting the highest relative risk, while ignoring other results from the same city 

which are lower or non-statistically significant. EPA also uses Bayesian adjusted estimates for 

single cities in their risk assessment. While many of these adjusted estimates were positive, the 

vast majority (89/95) were not statistically significant following adjustment. Also, 1/3-1/2 of 

the coefficients for these cities were negative before the empirical Bayes model averaging 

adjustment was applied. This approach must be considered arbitrary because it fails to give any 

weight to the other risk estimates developed for each of the cities, despite the fact that the 

ignored estimates are preferred from a scientific viewpoint because they have employed 

additional statistical treatments to address confounders such as weather, co-pollutants or model 

biases. 

XVII. The Current Standard is Requisite to Protect Public Health With an Ample 

Margin of Safety. 

A. EPA correctly concludes that requisite to protect public health does not 

mean zero risk but rather risks that are considered safe and tolerable in 

today’s society. 

Section 109 of the Clean Air Act requires the Administrator to set a primary standard 

for the attainment and maintenance of which, in the judgment of the Administrator, are requisite 

to protect the public health with an adequate margin of safety. EPA’s task is to establish 

standards that are “neither more nor less stringent than necessary” to protect public health. This 

does not mean zero-risk, but rather it means that the standard must be set at a level that reduces 

risk sufficiently so as to protect public health with an adequate margin of safety. 

In the preamble, EPA quotes Justice Breyer in explaining that the standard does not 

have to be set at a level that assures zero risk, but rather at a level at which risks are generally 

accepted within similar contexts. 

Section 109(b)(1) directs the Administrator to set standards that are 

“requisite to protect the public health’ with ’an adequate margin of 

safety.” But these words do not describe a world that is free of all risk -- 

an impossible and undesirable objective. ... Nor are the words 

“requisite” and “public health” to be understood independent of context. 

We consider football equipment ’safe’ even if its use entails a level of 

risk that would make drinking water “unsafe” for consumption. And 

what counts as “requisite” to protecting the public health will similarly 

vary with background circumstances, such as the public's ordinary 

tolerance of the particular health risk in the particular context at issue. 

The Administrator can consider such background circumstances when 

“deciding what risks are acceptable in the world in which we live.” 
Exxon Mobil Corporation Comments - 82 

(72 Fed. Reg. at 37,820 (quoting Whitman, 531 U.S. at 494-95) (citations omitted)). 

As EPA states in the preamble, its task under Section 109 is to establish standards that 

are neither more nor less stringent than necessary for these purposes. The Supreme Court has 

agreed with EPA that “requisite” under Section 109 means “sufficient, but not more than 

necessary.” Whitman, 531 U.S. at 473. Lowering the standard from that established in 1997 

would result in controls that would be more than necessary to protect public health, and therefore 

not “requisite” within the meaning of the statute. 

 The material presented in the CD and Staff Paper do not support EPA’s proposal to 

lower the standard. As discussed further in these comments, EPA’s own assessment of the risks 

fails to show an increase in risk from exposure to ozone. In fact, much of the evidence supports 

the conclusion that the risk from ozone at the level of the existing standard is less than what the 

risk was believed to be when the existing standard was promulgated. Given EPA’s data showing 

limited risks from exposure to the current standard and EPA’s analysis of the studies, which 

shows greater uncertainty, not less, that the observed effects are caused by ozone, EPA should 

not lower the standard. As EPA states in the preamble, its task under Section 109 is “to establish 

standards that are neither more nor less stringent than necessary.” (72 Fed. Reg. at 37,820). 

 In exercising his judgment to revise the existing NAAQS, the Administrator must 

provide a reasonable analysis for the change. Specifically, EPA must explain why its earlier 

judgment regarding what is requisite to protect public health or welfare no longer governs. To 

reverse its position in the face of precedent that is not persuasively distinguished is arbitrary and 

capricious. Motor Vehicle Mfr.’s Ass’n v. State Farm Mut. Auto. Ins. Co., 463 U.S. 29, 42 

(1983) (presumption “against changes in current policy that are not justified by the rulemaking 

record”). Given that EPA’s estimate of health risks has declined and our understanding of the 

uncertainty surrounding the results of the health studies has increased, EPA cannot persuasively 

say why it must depart from its 1997 decision that the current standard is requisite to protect 

public health. 

B. Given the Difficulty Many Areas Are Having Meeting the Current Standard, 

the Estimated Benefits of Further Reductions in the Ozone Standard May 

Not Be Achievable. 

 EPA correctly notes that some cities will have difficulty in complying with the current 

standard within the next decade and invites comment on page 37881 on whether EPA can count 

the health benefits from these reductions: 

As a related concern, a number of areas – including some of the cities 

involved in the risk assessment – will have difficulty in complying with 

the current 8-hour standard within the next decade. As a result, the full 

public health gains in these areas from a more stringent 8-hour standard 

are unlikely to be realized for a number of years. In light of the fact that 

these public health gains may not fully materialize within the attainment 

date structure set forth in the Clean Air Act, some commenters question 

whether the Agency can or should consider these projected gains as a 

health based criterion for its decisionmaking. EPA requests comment on 

this view. 
Exxon Mobil Corporation Comments - 83 

(72 Fed. Reg. at 37,881). 

 Indeed, there are several major, highly populated metropolitan areas that will not be able 

to achieve the current standard for many years even if all activity subject to a state’s regulatory 

authority under the Clean Air Act is eliminated. This means that a significant portion of the 

already small estimated health benefits from lowering the primary standard may not be achieved. 

Given the lack of meaningful and discernable benefits from lowering the standard, the 

Administrator should conclude that the current standard is requisite to protect public health.
Exxon Mobil Corporation Comments - 84 

DETAILED COMMENTS REGARDING THE SECONDARY 

STANDARD FOR OZONE 

Overview

While ExxonMobil supports the long-term development and application of a cumulative 

form for the secondary standard because it is more biologically relevant, EPA lacks sufficient 

data to promulgate a new standard at this time. In addition, the information and analyses 

presented in the Criteria Document (CD), EPA Staff Paper (SP) and proposed rule do not 

demonstrate a greater ecological harm at the current standard or clear potential benefit from the 

proposed alternate W126 standard as compared to the current 8-hour standard. As a result, EPA 

has failed to adequately show why the alternative proposed standard is requisite to protect 

welfare. 

I. EPA Has Proposed the Use of an Alternate Cumulative Seasonal Metric, the W126, 

Without a Companion Component to Account for Frequency of Ozone Peak 

Occurrence. 

 Vegetation studies indicate that cumulative indices are more biologically relevant for 

estimating potential ozone effects on vegetation. Cumulative indices, however, must consider 

the occurrence of peaks, as data indicate plant response to the same cumulative exposure can 

differ depending upon the occurrence of ozone peaks (2006 CD at AX9-169; Musselman et al.

2006). This is particularly important to EPA’s proposed standard, as the concentration response 

function is based primarily upon analysis of National Crop Loss Assessment Network (NCLAN) 

data. Researchers have documented that the NCLAN studies contain numerous hourly values 

greater than 100 ppb (Lefohn and Foley, 1992). Failure to include these values known to be key 

determinants of plant effects in the exposure-response function is a significant oversight for a 

proposed national standard. The number of hourly values greater than 100 ppb (up to 407 for 

data sets in Table III of Lefohn and Foley, 1992) indicate that many of the NCLAN exposures 

would have multiple exceedances of an 8 hour-standard of 80 ppb. Therefore reliance on 

NCLAN data to support the conclusion that exposures below an 8-hour standard would result in 

ozone impact has significant limitations if the response function fails to consider these peak 

concentrations. 

A concentration response function should be developed that include components for both 

the cumulative seasonal ozone exposure and frequency of hourly peaks. As suggested 

previously, actual exposure-response data should be made available in addition to results of 

regression analysis, to transparently indicate the exposure domain covered by the dataset, and its 

ability to represent current ambient exposure levels. 

II. EPA Has Failed to Show That the Currently Proposed W126 Standard Would 

Result in Additional Protection Than the Current 8-Hour Secondary Standard. 

The proposed rule (and the CD and SP on which it is based) fail to show that the W126 as 

currently proposed would provide additional protection than the current 8-hour standard. 

Despite previous requests, EPA has not provided the concentration-response functions for the 8- 

hour form of the standard. Therefore a comparative analysis of the relative protection afforded 
Exxon Mobil Corporation Comments - 85 

by an 8-hour form to that provided by the proposed W126 form cannot be completed. The 

exposure assessment provided indicates that the proposed W126 values may be exceeded when 

the 8-hour standard is met. However, because there is not a simple correlation between the 

W126 form and the 8-hour form, and because the proposed W126 form fails to include a factor 

for peak frequency, EPA has failed to show that the current 8-hour standard would provide less 

protection. EPA should develop concentration response relationships using the 8-hour form of 

the standard for the same datasets that form the basis for the proposed W126 standard. 

Frequency of peak occurrence should also be included in the analysis. This is the only 

meaningful way to compare the level of protection afforded by the different standards. 

III. EPA Has Failed to Show That Adverse Vegetation Effects Are Occurring at 

Ambient Ozone Levels at the Current Standard. 

In the proposed rule, EPA states that its conclusions regarding the inadequacy of the 

current standard “are based upon extensive vegetation effects evidence, in particular field–based 

evidence on biomass loss in seedlings, saplings and mature trees, and foliar injury incidence ... 

which demonstrates the occurrence of adverse vegetation effects at ambient levels of recent O3

air quality, as well as evidence and exposure and risk-based analyses indicating that adverse 

effects would be predicted to occur under air quality scenarios meeting the current standard.” 

(72 Fed. Reg. at 37,798-99). 

EPA is incorrect in concluding vegetation impacts at the current standard. The newer 

field-based evidence EPA cites for ozone impacts on seedlings, saplings and mature trees 

indicates ozone impacts but at exposures that are likely in exceedance of the current secondary 

standard. The analysis is not transparent because different indices are not directly correlated, but 

the mean or seasonal ozone exposures provided appear to be sufficiently high that they would 

include multiple days with an 8-hour daily maximum average exceeding 80 ppb. Therefore, 

while these studies demonstrate ozone impact, they do not appear to provide additional evidence 

for adverse vegetation impacts under air quality scenarios meeting the current standard. 

A. Key studies cited by EPA fail to show vegetation effects at ozone levels below 

the current standard. 

 An examination of the key studies cited by EPA, Gregg et al. (2003); Karnosky et al.

(2005); King et al. (2005), do not provide evidence of vegetation effects below the current 

standard. 

King et al. (2005)

 King et al. (2005) describes the Free Air CO2 Enrichment (FACE) study with ozone 

addition, and provided ozone concentrations as seasonal daily averages (49-55 ppb) and total 

seasonal sums (81-97 ppm-hrs for 4.5 to 5 months). Given expected daily fluctuations, it is 

likely that the current secondary standard was exceeded for the ozone levels specified, as would 

the W126 values. This study does not demonstrate impact from ozone levels at or below the 

current standard. 

Gregg et al. (2003)
Exxon Mobil Corporation Comments - 86 

 Gregg et al. (2003) examined plant growth under an ambient ozone gradient and 

performed follow-up OTC exposures. The ambient areas where effects were reported had ozone 

concentrations that likely exceeded the current secondary standard: data for 2000 from the New 

York state website for two of the study areas (New York Botanical Gardens –NYBG and 

Millbrook) indicate 2000 annual mean ozone and the 4th highest daily 8-hour ozone averaged 

over the past 3 years were NYBG - 16 ppb and 80 ppb, respectively, and Millbrook 26 ppb 

(versus 26 – 37 ppb for 1992-1994, the study years) and 87 ppb, respectively (NY DEC, 2002). 

In Gregg et al. the ambient concentrations are NOT presented as exceedance of 8-hour daily 

average or even as a cumulative metric, but rather as an annual seasonal 12-hour mean ozone. 

Also, whereas the highest ambient ozone exposure was a 12-hour growing season mean of ~47 

ppb, the confirmatory OTC study was at a 12-hour growing season mean of 59 ppb. Whereas the 

data of Gregg et al. indicate that ambient levels of O3 are sufficient to produce biomass loss, it 

does not address if these ambient levels fall above or below the current standard. 

Karnosky et al. (1999)

 Karnosky et al. (1999) reports foliar injury in two higher ozone ambient sites and no 

injury in one low ozone site. Symptoms were worse in FACE plots than in ambient gradient 

sites. Ozone exposure concentrations were: ambient higher ozone sites seasonal sum over 

12 hr/day = 47-70 ppm hr (5-43% leaves show injury); FACE exposures with symptoms - 

seasonal sum over 12/hr day = 57-61 ppm hr, 12 hr seasonal mean = 54-56 ppb, and 24 hr 

AOT40 = 27-31 ppm-hrs (11-55% leaves show injury); OTC exposures that produced 

symptoms - seasonal sum over 12 hr/day = 50-60 ppm hr (50 percent leaves show injury of 

sensitive clones). These exposures are likely to include exceedances of the current secondary 

standard. 

Isebrand et al. (2001)

 Isebrand et al. (2001) reports results for FACE plots of elevated ozone, although the 

levels in ozone addition treatments are indicated to be representative of current conditions in 

many areas surrounding midwestern cities. The exposures show episodic total seasonal 

exposures of 90 ppm-hr. The five clones studied showed significant variability in response to 

ozone, with one showing increased growth under elevated ozone. The results of this study 

support the potential of ozone to impact vegetation, but again the ozone exposure level is 

sufficiently high to indicate that there were likely multiple exceedances of the current standard in 

the studied exposure. 

While these studies provide additional support for ozone impact on vegetation, including 

observance of ozone effects in field settings without chambers, they do not provide support for 

the conclusion that ambient levels in compliance with the current standard would result in 

significant ozone impact. 

B. Newer tree studies also fail to show adverse vegetation effects below at the 

current standard. 
Exxon Mobil Corporation Comments - 87 

EPA indicates that the newer tree studies support the use of the existing concentrationresponse relationship based upon open top chamber (OTC) studies. The FACE and gradient 

studies show that ozone can impact tree species, but specific provision and/or comparison of the 

concentration-response functions from these studies with those from OTC studies is limited. 

Thus, these studies, while very informative, do not reduce the uncertainties in the OTC 

concentration-response functions. Isebrand et al. 2001, Karnosky et al. 1999 and 2005, and 

King et al. 2001 and 2005 do not provide concentration-response functions. Gregg et al. (2001) 

provides a figure of shoot biomass versus 12-hour seasonal mean ozone, but does not include a 

regression equation, which prevents a direct comparison. 

EPA should develop concentration-response functions based upon the newer data in the 

same form as the existing ones, to allow direct comparison. EPA should clarify in the proposed 

rule that the newer studies did not present concentration-relationships directly comparable to 

existing ones. 

C. EPA fails to provide evidence of a carry-over effect from exposure to ozone. 

Several times in the proposed rule, EPA indicates the potential for a compounding effect 

of ozone exposures on perennial species, including studies that document carryover effects. (72 

Fed. Reg. at 37,898). EPA fails to provide documentation that supports this claim. Neither the 

proposal nor the CD and SP reference studies that provide evidence of carry-over effects. The 

multiple-year studies on tree species cited by EPA do not demonstrate a carry-over or 

compounding effect, but rather that ozone resulted in a similar percent change across study years 

(Figure 4 in Isebrand et al. 2001; Figure 2 in King et al. 2005; attached Tables 1-3 developed 

from data in King et al. 2005). EPA should conduct analyses on other available data sets to 

determine if the results of the two studies cited above are generally representative. 

D. Field data indicating visible injury at ambient levels that meet the current 

secondary standard fail to address potential confounders or assess whether 

the W126 standard would provide additional protection. 

While EPA is correct in stating that the field data indicate some level of visible ozone 

injury at ambient levels that meet the current secondary standard (Jacobson, 1977), EPA has not 

addressed potential confounders, such as soil moisture or related the visible foliar injury 

symptoms to other vegetation effects. EPA also indicates a major confounder for ozone induced 

visible foliar injury is soil moisture – with dry periods in local areas decreasing incidence and 

severity of visible foliar injury (p. 7-61). These same conditions would favor higher ozone 

levels. Furthermore, the W126 values for these sites are not provided, so it cannot be assessed if 

the proposed W126 standard would provide additional protection. EPA should provide the 

comparable W126 values and compare foliar injury at “non-background” sites with 

“background” sites, to better understand the impact of ozone exposures above background levels. 

E. Concentration-response functions should be developed for new studies and 

updated to include recent air quality conditions. 
Exxon Mobil Corporation Comments - 88 

In the proposed rule, EPA suggests that the new information does not compel changes in 

the current OTC-based, concentration-response function. Rather, EPA indicates new field based 

studies demonstrate plant growth and visible injury similar in nature and magnitude to OTC, 

lending support that OTC conditions do not fundamentally change plant response. EPA also 

indicates that Morgan et al. 2003 shows consistent deleterious effects of ozone exposures on 

soybean from 1973-2001. 

Limited new concentration-response information was available to assess the potential 

need to update the OTC-based C-R (see earlier comments). However, as indicated earlier, the 

concentration-response relationships are flawed because they do not consider the frequency of 

peak occurrence. In addition, the exposures regimes used in the NCLAN studies that form the 

basis for crop concentration-response functions are not representative of current ambient ozone 

exposures. Note, while the newer studies indicate ozone effects can occur, they do not shed 

much new light on the concentration-response functions. 

EPA is proposing values for the secondary standard based upon the OTC concentrationresponse functions, not just using response direction or relative magnitude. Thus the newer 

studies do not seem to provide much support or refute the OTC C-R. Finally, the Morgan et al.

2003 meta-analysis is not presented by year and provides results by time, so it cannot be used to 

support the statement of consistent deleterious effects over time. Morgan et al. provide ranges of 

ozone impact for ozone concentrations in three average daily concentration categories: 30-59 pb, 

60-79 ppb, 90-120 ppb. For the highest two categories and the upper range of the lowest 

category, it is likely that there were multiple exceedances of the current 8-hour secondary 

standard. EPA should follow its own recommendation included in footnote number 57 on page 

37,889 and develop new concentration-response functions for new studies that are updated to 

meet recent air quality conditions. 

F. EPA has not provided sufficient public review in the review of the science 

and has failed to provide a transparent scientific basis for revising the 

secondary standard. 

The basis for a regulatory standard should be transparent. Inconsistent use and reporting 

of metrics and, in some cases, reference to unavailable information, result in a general lack of 

transparency in the science supporting a revised secondary standard. The studies presented differ 

in metrics and some studies fail to present all metrics. EPA has failed to conduct a re-evaluation 

of the studies in order to report results in a consistent format. 

In addition, EPA cites the recommendations of a consensus workshop (Heck and 

Cowling 1997) several times. However, this workshop was by invitation only, and 

documentation is not available to the public. The reference cited is short and provides consensus 

recommendations, but without details as to their basis. In particular, the basis for the 

recommendation to consider a 2 percent effect level to be significant is not provided. It is not 

clear how this effect level could be experimentally determined, if it is discernible from biological 

variability, or what references suggest the potential compounding effect over multiple years, 

given the results of Isebrand et al. (2001) and King et al. (2005) cited above. An additional 

reference cited in the SP (section 7.5.1) as the source of key information on crop and seedling 
Exxon Mobil Corporation Comments - 89 

concentration – response, Lee and Hogsett (1996), is also not available. This document is an 

EPA report, and its release was requested in previous comments to EPA. However, it could not 

be found on a search of the EPA website or a specific search of EPA publications. 

EPA should provide re-analysis of data and reporting in common metrics as appropriate, 

particularly to support the key points of its rulemaking. If available, a more detailed report of the 

consensus workshop should be released. If studies to support the recommendations cannot be 

provided, then the recommendations should be used with great caution. EPA should also make 

the Lee and Hogsett (1996) report available to the public. 

 

G. EPA has failed to reduce key uncertainties from the 1997 Review over the 

effect of the current standard. 

EPA acknowledges that other factors can result in orders of magnitude greater impact on 

yield than ozone (72 Fed. Reg. at 37,898). EPA also indicates that key uncertainties during the 

last rulemaking included the fact that an association between the daily maximum 8-hour ozone 

concentration and plant response had not been specifically tested in the field, and that the 

impacts of attaining the 8-hour standard could not be characterized due to limited monitoring 

data in rural and remote areas. For the most part, these EPA concerns during the last rulemaking 

remain the same today. 

H. EPA’s exposure and risk-based analysis fail to show that adverse effects can 

be expected at the existing standard. 

 The exposure characterization to support potential adverse effects at the existing standard 

was based on a rollback analysis, which indicated areas which meet the 8-hour standard may 

exceed the W126. This analysis, however, is not the same as demonstrating that ozone impact 

will occur in areas that meet the 8-hour standard, but exceed the W126. For risk 

characterization, as indicated earlier, the NCLAN-based W126 dose response used is flawed 

because it does not include peak occurrence. Also, yield losses predicted in the Abt analysis are 

for the most part small compared to biological variability. 
 Exxon Mobil Corporation Comments: Reference 1 

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Exxon Mobil Corporation Comments 

Attachments 

Attachment A Mark Nicolich, Some Additional Statistical 

Analyses of the FEV1 Pulmonary Response 

Data From the W.C. Adams Data (2006), 

April 24, 2007 

Attachment B ExxonMobil Biomedical Sciences, Inc., 

Critical Evaluation of Additional Field 

Studies Cited in the EPA Staff Paper (in 

addition to the studies by Mortimer, Gent 

and Korrick), October 9, 2007 

Attachment C ExxonMobil Biomedical Sciences, Inc., 

Concerns With the Reliability of Peak 

Expiratory Flow Rate (PEFR), October 9, 

2007 

Attachment D CRA Memorandum on Results of 

Sensitivity Analyses on Ozone Risk 

Assessment, October 9, 2007 
Exxon Mobil Corporation Comments 

ATTACHMENT A

Some Additional Statistical Analyses of the FEV1 Pulmonary 

Response Data From the W.C. Adams Data (2006) 
 Exxon Mobil Corporation Comments: A-1 

Some Additional Statistical Analyses of the FEV1 Pulmonary 

Response Data From the W.C. Adams Data (2006) 

Introduction

Adams (2006) published the results of a well-conducted study of 30 young adults, 15 of each 

gender, who participated in a chamber study where they were exposed to different levels of 

ozone while performing moderate exercise. The study was over a 6.6-hour period with six 

different exposure protocols, presented in randomized order with at least four days between 

sessions. Response data included self-reported symptoms, FVC and FEV1 measures. The 

pulmonary measures were performed seven times during the experiment: before exposure, and 

during the last three minutes of hours 1, 2, 3, 4.6, 5.6, and 6.6. The lunch period was between 

hours 3 and 3.6. Details are in Adams, 2006. 

The 6 exposure protocols are shown in Table 1. 

Table 1 

Exposure Protocols 

Protocol 

Wave 

Shape 

Mean O3 

(ppm) 

Peak O3 

(ppm) 

TID* 

(ppm-L) 

Hourly Exposures 

(ppm) 

1 square 0 0 5.8 0 

2 square 0.08 0.08 960 0.08 

3 triangle 0.08 0.15 969 0.03, 0.07, 0.010, 0.15, 0.08, 0.05 

4 square 0.06 0.06 719 0.06 

5 triangle 0.06 0.09 722 0.04, 0.07, 0.09, 0.07, 0.05, 0.04 

6 triangle 0.04 0.05 483 0.03, 0.04, 0.05, 0.05, 0.04, 0.03 

 * TID = total inhaled dose 

Adams (2006) analyzed several endpoints (percent changes in FEV1, percent changes in FVC, 

and total symptom score), but only the percent changes in FEV1 responses are discussed in this 

report. He analyzed the percent changes in FEV1 data using a 2-way repeated measures analysis 

Conclusion

Based on the additional statistical analyses detailed in this report, we have shown that the basic results 

of Adams (2006) ozone chamber study were replicated. 

Based on analyses of the response pattern over the 6.6 hours of experimentation, the only percent 

changes in FEV1 responses that are statistically significantly different from the first period fresh air 

exposures were the 0.08 ppm triangle exposure at hours 4.6, 5.6 and 6.6 hours and the 0.08 ppm 

square wave exposure at 6.6 hours. 

The analysis of only the 6.6 hour readings indicated the 0.08 ppm square wave and 0.08 ppm triangle 

wave exposures were different from the fresh air exposure. 

The magnitude of the estimated changes for all individuals in all exposure groups are less than the 15 

percent decrement considered to be clinically significant by the American Thoracic Society. 
 Exxon Mobil Corporation Comments: A-2 

of variance (ANOVA) method and tested individual mean values with Scheffé’s post hoc test 

when the ANOVA indicated a significant F value. This procedure is appropriate for the 

exploratory investigations the study was designed for and where no pre-determined hypotheses 

were made. He concluded that for the percent changes in FEV1: 

• No changes in hourly readings for Fresh Air (FA) 

• The 0.04 ppm triangle exposure was not different from FA 

• The 0.06 ppm triangle and square wave responses were not different from each other 

• The 0.06 ppm triangle and square wave responses were not significantly greater than FA at 

6.6 hours 

• The 0.08 ppm triangle response at 4.6 hours was significantly decreased from pre-exposure, 

but not at subsequent times 

• The 0.08 ppm square response at 6.6 hours was significantly decreased from pre-exposure 

Plots of the data showing the observed FEV1 values, and percent change in FEV1 from preexposure values, for each subject at each time point and for each protocol are provided in 

Appendix I. The subjects are separated by sex and the response scale is the same for all plots on 

the page but the scale changes from page-to-page. 

The analyses in this report explore some different questions and analysis methods from what 

Adams covered. This report will consider: (1) the response pattern over time for the six 

exposure protocols, and (2) the 6.6-hour response differences among the six exposure protocols. 

Response Pattern Analyses

The response pattern analyses are based on a slightly different statistical analysis and explore 

other hypotheses than those in the Adams (2006) paper. The analyses are based on a mixed 

model repeated measures analysis (Pinheiro and Bates 2002) and consider the percent change in 

FEV1 and the observed FEV1 value with the pre-exposure response as a co-variate. The former is a 

ratio measure and the latter is a difference measure. When there is a statistically significant effect 

in the analysis of variance table, the comparisons are against the initial reading for the FA (protocol 

1) with the multiple comparison significance level adjusted by Dunnett’s test (used for comparing 

‘treatment’ means versus a single ‘control’ value). Dunnett’s test is not as conservative as 

Scheffé’s test or as extreme as individual t-tests, but is tailored to the current question (Hsu 

1992). 

The analyses for the percent change in FEV1 and the observed FEV1 value with the pre-exposure 

response as a co-variate were essentially equivalent and only the percent change in FEV1 will be 

discussed. 

Two statistical requirements for the analysis are that – 

 

1. the random effects are independently and normally distributed with mean zero and fixed 

co-variance matrix 
 Exxon Mobil Corporation Comments: A-3 

2. the subject based errors are independently, identically and normally distributed with mean 

zero and fixed variance 

 

The first requirement can be assessed by examining the distribution of the model residuals. A 

quantile-quantile plot of the residuals is shown in Figure 1 and because the observed residuals 

are not along the straight line as expected for normally distributed residuals, we conclude that the 

residuals are not normally distributed and the observations do not meet the assumptions required 

for the model. The drooping tail to the left indicates several observations with responses more 

negative than the model predicted. These points are from subjects whose percent change in 

FEV1 are seen in the plots to decline in the later time periods. 

The second requirement can be approximately assessed by examining the model residuals for 

each subject and sex. A box plot of the residuals is shown in Figure 2. The pattern of observed 

residuals are not similar in central value or range, so we conclude that the subject-based errors 

are not independently, identically and normally distributed and the subjects do not meet the 

assumptions required for the model. 
 Exxon Mobil Corporation Comments: A-4 

2006 Data Analysis Relative Change Analysis Unstructured Covariance Matrix

QQ Plot of Residuals

2006 Data Analysis

Relative Change Analysis Unstructured Covariance Matrix

Residuals by Sex and Subject

Residuals

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Figure 1- Quantile-Quantile Plot of Residuals

Figure 2- Box Plot of Residuals 
 Exxon Mobil Corporation Comments: A-5 

To attempt to fix the problem of non-normality of the residuals two methods were employed. 

First, single-data points or a subject’s full response record were removed to try to achieve 

normality of the residuals. This method was not successful because too many points had to be 

removed without a reasonable justification, and was not considered further. Second, several 

transformations were tried. Among them were the Blom transformation to normalized ranks, 

exponentiation, power transformations and combinations of these transformations. None of the 

reasonable transformations resulted in normally distributed residuals. To fix the problem of 

identically and normally distributed residuals, a correction for heteroscedasticity was applied 

(Pinheiro and Bates 2002); but, the problem of heteroscedasticity was not resolved. Intermediate 

analyses under the various transformations and corrections gave results that were essentially 

similar to the untransformed and uncorrected analyses. Therefore, the following analyses are 

based on the analyses that do not exactly meet the requirements; however, several data 

transformations and alternative analysis methods provided approximately similar conclusions and 

therefore we can assume the results are essentially correct, but the significance levels may not be 

exactly correct. Additionally, an Addendum provides support for the robustness of the results 

based on a quantitative assessment of the normality of the residuals under transformations and the 

results based on deleting one subject to meet the statistical assumptions of the analysis. 

The findings of the new analyses were that there was a statistically significant difference in the 

percent changes in FEV1 responses over time and by dose group. Comparisons of means of the 

ozone exposed groups against the FA initial reading, based on the Dunnett adjustment, indicated 

results similar to those found by Adams. The only difference was that the present analysis 

indicated differences in the 0.08 ppm triangle exposure at 4.6, 5.6 and 6.6 hours rather than only at 

4.6 hours as reported by Adams. 

A comparison of the 0.06 and 0.08 protocols against the 0.04 triangle exposure, instead of the FA 

protocol, indicated similar results. 

While the reported differences are statistically significant it should be noted that the model 

accounted for only 21 percent of the variance. The reduction of the variance is not a criterion for 

the model fit, so it is not always considered a reportable statistic. However, it is important to note 

that there are other sources of variation in the FEV1 response other than the ozone exposure, and 

that the conclusions of the statistical analysis are not strong. 

The model predicted response for individuals in Figure 3 shows that none of the predicted points 

shows more than about a 6 percent decrement and the lower confidence intervals (not shown) are 

all greater than 10 percent and, therefore, do not include the 15 percent decrement considered to be 

of clinical significance by the ATS (Wang and Petsonk 2004). 

The subjects are engaged in moderate exercise during the experiment (approximately 35 L/min). 

Previous research has shown that moderate exercise at comparable levels of ozone exposure is 

associated with greater transient FEV1 decrements relative to resting subjects at the same ozone 

exposure levels. Therefore, the magnitude of the decrements observed in these data would not 

be seen in the total population, but only among those engaged in moderate exercise. 
 Exxon Mobil Corporation Comments: A-6 

Relative Change Analysis Unstructured Covariance Matrix

Predicted Means

Protocol: (1) Fresh Air (2) 0.08 ppm - Square

(3) 0.08 ppm - Triangle (4) 0.06 ppm - Square

(5) 0.06 ppm - Triangle (6) 0.04 ppm - Triangle

Predicted % Change in FEV1 (L)

-10

-5

0

5

Time Period

123456

Figure 3- Model Predicted Change in FEV1

6.6 Hour (Post-Experiment) Response Analyses

Separate post-experiment data analyses were not performed by Adams (2006) because they are 

included as a subset of the full analyses that he presented. The analyses of the 6.6 hour data are 

presented here for completeness, although this was not part of the original Adams protocol. The 

analyses are based on the same two methods noted in the response pattern analyses except that 

only one time period is considered. 

The analyses for the observed FEV1 value with the pre-exposure response as a co-variate indicated 

differences in exposure group were statistically significant only at p<0.08 and not statistically 

significant at the usual 0.05 criterion. The analysis of percent change in FEV1 indicated 

differences in exposure group were statistically significant at p<0.01. Both analyses showed a lack 

of normality in the residuals. As before, transformations and alternative analyses were conducted 

and the residuals remained not normally distributed. These alternative analyses provided 

approximately the same results as the original data, and the discussion will continue with the 

understanding that the significance levels may not be exact because of the failure to meet the 

normality assumption. 

In the following, the percent change in FEV1 will be discussed. Table 2 shows the least squares 

means of the percent change in FEV1 for the six protocols, and the Dunnett adjusted p-value for the 

test of the difference in response between the FA protocol and the others. The least squares means 

are estimated means that account for differences in individual subjects. 
 Exxon Mobil Corporation Comments: A-7 

Table 2 

Least Squares Means for Percent Change in FEV1 and Dunnett Adjusted p-values 

Protocol 

Wave 

Shape 

Mean O3 

(ppm) 

LS Mean Percent 

Change in FEV1

p-value for difference 

from Fresh Air 

1 square 0 1.3 

2 square 0.08 -4.7 <0.01 

3 triangle 0.08 -5.6 <0.01 

4 square 0.06 -1.5 0.23 

5 triangle 0.06 -1.4 0.26 

6 triangle 0.04 1.1 0.99 

The percent changes in FEV1 at both 0.08 exposure responses at 6.6 hours were statistically 

significantly different from the FA exposures. 

Conclusion

In summary, the basic results of Adams (2006) were replicated. Based on analyses of the response 

pattern over the 6.6 hours of experimentation, the only percent changes in FEV1 responses that are 

statistically significantly different from the first period FA exposures were the 0.08 ppm triangle 

exposure at 4.6, 5.6 and 6.6 hours and the 0.08 ppm square wave exposure at 6.6 hours. The 

analysis of only the 6.6 hour readings indicated the 0.08 ppm square wave and 0.08 ppm triangle 

wave exposures were different from FA exposure. The magnitude of the estimated changes for all 

individuals in all exposure groups are less than the 15 percent decrement considered to be 

clinically significant by the American Thoracic Society. In both analyses the significance levels 

are only approximately accurate because in the analyses the residuals were not normally 

distributed. 

Mark Nicolich 

April 24, 2007
 Exxon Mobil Corporation Comments: A-8 

References: 

Adams, W.C., Comparison of chamber 6.6-h exposures to 0.04-0.08 ozone via square-wave and 

triangular profiles on pulmonary responses, Inhalation Toxicology 18, 2006, pp. 127-136. 

Blom, G., Statistical Estimates and Transformed Beta Variables, J. Wiley and Sons, NY, 1958. 

Hsu, J.C. (1992), The Factor Analytic Approach to Simultaneous Inference in the General Linear 

Model, Journal of Computational and Graphical Statistics, 1, 151 - 168. 

Pinheiro, J.C. and Bates, D.M., Mixed-Effects Models in S and S-PLUS, Springer-Verlag, NY, 

2002 

Wang M.L. and Petsonk, E.L., Repeated measures of FEV1 over six to twelve months: what 

change is abnormal? J. Occup. Environ. Med. 2004 Jun; 46(6):591-5 
 Exxon Mobil Corporation Comments: A-9 

2006 Data Analysis Relative Change Analysis Unstructured Covariance Matrix

QQ Plot of Residuals

Addendum to the Statistical Analyses of the FEV1 Pulmonary 

Response Data From the W.C. Adams Data (2006) 

This addendum will show the summary results from the main analysis are stable (robust) even 

though the residuals from the main analyses were not normally distributed. 

Recall that the normality of the residuals can be examined by looking at the quantile-quantile 

plot with the expectation that the residuals should lie along a straight line. 

Additionally, there is another numerical comparison for testing normality that will be included 

here. The statistical test is called the Shapiro-Wilk statistic. For data like those being tested here 

(n=1080) the Shapiro-Wilk statistic should be larger than 0.996 to have the residuals normally 

distributed. 

Original Analysis

Recall. 

Figure A1- Quantile-Quantile Plot of Residuals Original Analyses 

The Shapiro-Wilk statistic for these data is 0.877 and is an indication the residuals are very far 

from being normally distributed. 

Recall also that the exposure groups and time points that were different from the initial FA 

exposure were: 
 Exxon Mobil Corporation Comments: A-10 

0.08 ppm square wave at 6th period 

0.08 ppm triangle wave at 4th, 5th and 6th periods 

These results were based on the relative change in FEV1 from the pre-exposure values. 

New Analyses

The new analysis discussed in this addendum used a slightly different statistical analysis from 

that in the main report, but used the same data. The data were transformed by a transformation 

called Blom’s Transformation, which is based on the normalized ranks of the observed data. The 

analysis was based on the observed response at each exposure time point with the pre-exposure 

values as a co-variate (rather than using the relative change). 

The Blom Transformation is a fairly standard, but not particularly well-known, transformation 

that is not controversial and is part of the Statistical Analysis System (SAS) standard statistical 

package. The co-variance analysis is also an accepted analysis and essentially is analyzing the 

change in FEV1 rather than the relative change. 

The main result is that with this analysis the residuals are more normally distributed (still not 

statistically so, but very much closer). The quantile-quantile plot looks like: 

Figure A2- Quantile-Quantile Plot of Residuals – 

Blom Transformed Data and Co-variance Analysis 

2006 Data Analysis Covariance Analysis - Blom Transformed Data Unstructured Covariance Matrix

QQ Plot of Residuals
 Exxon Mobil Corporation Comments: A-11 

The Shapiro-Wilk statistic for these data is 0.935, which is an indication the residuals are much 

closer to being normally distributed. 

The exposure groups and time points that were different from the initial FA exposure are the 

same as in the initial analyses. 

There was one subject whose residuals accounted for several of the droopy points at the lower 

left of Figure 2. The analysis was re-run without that one subject and the quantile-quantile plot 

looks like: 

Figure A3- Quantile-Quantile Plot of Residuals – 

Blom Transformed Data and Co-variance Analysis 

Drop 1 Subject 

The Shapiro-Wilk statistic for these data is 0.974, which is closer to the critical value of 0.996 

(but still not normally distributed based on a strictly interpreted test of statistical significance). 

And again, the exposure groups and time points that were different from the initial FA exposure 

are the same as in the initial analyses. 

2006 Data Analysis Covariance Analysis - Blom Transformed Data - Drop 1 Subject Unstructured Covariance Matrix

QQ Plot of Residuals
 Exxon Mobil Corporation Comments: A-12 

Conclusion

We can do transformations and analyses that make the residuals very much closer to being 

normally distributed, but the final result does not change from the original report (based on pvalues from the Dunnett test for multiple comparisons as in the initial report): 

Final result -- 

the exposure groups and time points that were different from the initial FA exposure were: 

0.08 ppm square wave at 6th period 

0.08 ppm triangle wave at 4th, 5th and 6th periods 
 Exxon Mobil Corporation Comments: A-13 

Plots of Adams 2006 Data, By Sex 

[Responses Are Observed FEV1 Data and the Relative Change From Pre-test] 
Exxon Mobil Corpo

sex=Female Exposure Group=(1) Filtered Air

Position: CB DH HW JH KC

KG KH KP KR LBLK MG MTh TL TS

FEV1 (L)

2345

Time Period

0123456

sex=Female Exposure Group=(4) 0.06 ppm - Square

Position: CB DH HW JH KC

KG KH KP KR LBLK MG MTh TL TS

FEV1 (L)

2345

Time Period

0123456

sex=Female Exposure Group=(5) 0.06 ppm - Triangle

Position: CB DH HW JH KC

KG KH KP KR LBLK MG MTh TL TS

FEV1 (L)

2345

Time Period

0123456

sex=Female Exposure Group=(6) 0.04 ppm - Triangle

Position: CB DH HW JH KC

KG KH KP KR LBLK MG MTh TL TS

FEV1 (L)

2345

Time Period

0123456

sex=Female Exposure Gr

Position: CB DH 

KG KH LK MG 

FEV1 (L)

2345

Time 

012

sex=Female Exposure Gro

Position: CB DH 

KG KH LK MG 

FEV1 (L)

2345

Time 

012

2006 

FEV1 

Females
Exxon Mobil Corpo

sex=Male Exposure Group=(1) Filtered Air

Position: CN GC JE JLa JLo

MA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)

23456

Time Period

0123456

sex=Male Exposure Group=(4) 0.06 ppm - Square

Position: CN GC JE JLa JLo

MA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)

23456

Time Period

0123456

sex=Male Exposure Group=(6) 0.04 ppm - Triangle

Position: CN GC JE JLa JLo

MA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)

23456

Time Period

0123456

sex=Male Exposure Group=(5) 0.06 ppm - Triangle

Position: CN GC JE JLa JLo

MA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)

23456

Time Period

0123456

sex=Male Exposure Group

Position: CN GC 

MA MLa RM RMc 

FEV1 (L)

23456

Time 

012

sex=Male Exposure Group=

Position: CN GC 

MA MLa RM RMc 

FEV1 (L)

23456

Time 

012

2006 

FEV1 

Males
Exxon Mobil Corpo

sex=Female Exposure Group=(1) Filtered Air

Position: CB DH HW JH KC

KG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)

-30-25-20-15-10

-5

05

10

Time Period

0123456

sex=Female Exposure Group=(4) 0.06 ppm - Square

Position: CB DH HW JH KC

KG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)

-30-25-20-15-10

-5

05

10

Time Period

0123456

sex=Female Exposure Group=(5) 0.06 ppm - Triangle

Position: CB DH HW JH KC

KG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)

-30-25-20-15-10

-5

05

10

Time Period

0123456

sex=Female Exposure Group=(6) 0.04 ppm - Triangle

Position: CB DH HW JH KC

KG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)

-30-25-20-15-10

-5

05

10

Time Period

0123456

sex=Female Exposure Grou

Position: CB DH 

KG KH LK MG 

Relative Change in FEV1 (%)

-30-25-20-15-10

-5

05

10

Tim

012

sex=Female Exposure Group

Position: CB DH 

KG KH LK MG 

Relative Change in FEV1 (%)

-30-25-20-15-10

-5

05

10

Tim

012

2006 

Relative Change in FEV1

Females
Exxon Mobil Corpo

sex=Male Exposure Group=(1) Filtered Air

Position: CN GC JE JLa JLo

MA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)

-45-40-35-30-25-20-15-10

-5

05

10

Time Period

0123456

sex=Male Exposure Group=(4) 0.06 ppm - Square

Position: CN GC JE JLa JLo

MA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)

-45-40-35-30-25-20-15-10

-5

05

10

Time Period

0123456

sex=Male Exposure Group=(6) 0.04 ppm - Triangle

Position: CN GC JE JLa JLo

MA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)

-45-40-35-30-25-20-15-10

-5

05

10

Time Period

0123456

sex=Male Exposure Group=(5) 0.06 ppm - Triangle

Position: CN GC JE JLa JLo

MA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)

-45-40-35-30-25-20-15-10

-5

05

10

Time Period

0123456

sex=Male Exposure Group

Position: CN GC 

MA MLa RM RMc 

Relative Change in FEV1 (%)

-45-40-35-30-25-20-15-10

-5

05

10

Tim

012

sex=Male Exposure Group=

Position: CN GC 

MA MLa RM RMc 

Relative Change in FEV1 (%)

-45-40-35-30-25-20-15-10

-5

05

10

Tim

012

2006 

Relative Change in FEV1 

Males
Exxon Mobil Corporation Comments 

ATTACHMENT B

Critical Evaluation of Additional Field Studies Cited in the EPA Staff Paper 

(in addition to the studies by Mortimer, Gent and Korrick) 
Exxon Mobil Corporation Comments: B-1 

 

Critical Evaluation of Additional Field Studies Cited in the EPA Staff Paper 

(in addition to the studies by Mortimer, Gent and Korrick) 

I. Field Studies of Asthmatics. 

Ross et al. (2002) 1

Description/Results: Ross et al. (2002) evaluated potential effects of ozone and aeroallergens on 

the respiratory health of 40 mild and severe asthmatic residents in East Moline, Illinois. EPA 

indicates the 4th highest maximum ozone level as 0.077 ppm. The pollutants considered in the 

study included 8-hour ozone, PM10, and sulfur dioxide. Effect measures included morning and 

evening PEFR and symptoms scores and asthma medication use. Only single ozone pollutant 

models without aeroallergens and weather variables were used in this study. Presumably SO2

and PM10 were not included in the ozone pollutant models because of their lack of association 

with symptom sum and PEFR and the small size of the study population. 

There was no apparent association between changes in morning PEFR and 8-hour ozone when 

maximum temperature and grass pollen were included in the statistical model as the decrease in 

PEFR was not significant (- 0.50 liters/min with 95% CI of -3.45, +2.45) per 20 ppb increase in 

ozone. Aeroallergen levels further reduced the association for morning PERF, so with both 

pollen and spores in the model PEFR was non-significantly increased 0.29 (-2.66, +3.23). 

There were significant associations between ozone and increased symptom sum for both the 

morning and evening and after adjustments for weather, pollen and spores. There was a nonsignificant increase in asthma medication per 20 ppb increased in ozone. The association 

between 8-hour ozone and evening changes in PEFR adjusted for pollen and spores showed 

significant reductions of 3.08 liter/min at slightly increased. 

Analysis: There are several concerns with this study. 

• The authors stated that the fact that morning PEFR was not associated with ozone 

whereas evening PEFR was could reflect the fact that the participants’ exposure to 

outdoor ozone was likely greater during the day than at night. This does not appear to be 

an adequate explanation, but is more plausible than the explanation offered by Mortimer 

et al. for why the PEFR changes were in the morning but not in the evening, if ozone is a 

causal agent producing these reductions. In other studies, as noted above, the morning 

PEFR rather than the evening PEFR demonstrated a statistically significant albeit small 

change (Mortimer et al. 2002). Mortimer et al. (2002) claim that the fact that they 

observed effects in the morning rather than the evening makes more biological sense, 

since the most severe bronchoconstriction occurs in the morning. As described in our 

analysis of Mortimer et al., this does provide an adequate rationale since ozone exposure 

in the evening is generally much lower. Further, Mortimer et al. claim that the lack of 

evening effects may reflect exposure misclassification and inability to adjust for the time 

 1

 Memorandum indicates 4th highest ozone level in study was below the current 8-hour NAAQS. 
Exxon Mobil Corporation Comments: B-2 

a child spends outdoors. On this point, we would tend to agree. The exposure 

misclassification in ozone panel studies contributes to the inconsistency in the results 

observed. Unless personal exposure is used, serious exposure misclassification will lead 

to inconsistent and incoherent results, rendering the results of ozone panel studies based 

on ambient monitors of questionable utility. 

• Only single pollutant models were used. Most other studies of ozone which have used 2- 

pollutant models with a metric of PM have markedly reduced the statistical significance 

of respiratory health effects attributed to ozone. This reduction has been demonstrated 

using PM10, which is not as highly correlated with ozone as is PM2.5. Including PM2.5 in 

this study would likely result in a marked reduction of the risk estimate attributed to 

ozone. 

• The study reported very high positive risk estimates (i.e., beneficial to health) for 

Alternaira, Cladosorium and mold spores (+15, +24, and +31%, respectively). For other 

aeroallergens, the impacts on PEFR were more negative and typical, and large compared 

with ozone (e.g., the impact of aeroallergens is approximately an order of magnitude 

higher than ozone). This indicates that the potential for aeroallergens to modify the effect 

of ozone was not well-controlled in this study. 

• The authors note the misclassification of PEFR and symptoms because of the high 

number of invented or retrospective entries, which they suggest is likely to bias study 

results toward nonsignificance. The effect of this misclassification bias needs to be tested 

to determine the magnitude and direction of the bias. 

• The symptom sum is difficult to interpret as few details are provided regarding the 

methods and actual symptoms being assessed. If the maximum symptom score is 3, the 

increased symptom rate appears to increase about 2 percent. But what these symptoms 

are is not reported. 

• The magnitude of the reduction in evening PEFR was 3.l liters/min or about 0.8 percent 

per 20 ppb increase in ozone, or half this (1.5 liter/min or 0.4%) using the normal 

convention of a 10 ppb increase. It is not clear that any of these changes are of biological 

or clinical significance as there was no significant increase in use of asthma medication 

associated with estimated ozone exposure. On the other hand, pollens were associated 

with about a 0.23 unit significant increase in symptom sum (or about 8 percent increase). 

Delfino et al. (1998)

Description/Results: This is a longitudinal study evaluating the effects of PM10 and ozone air 

pollution on symptom severity in pediatric asthmatics in the San Diego area. EPA indicates the 

4th highest maximum ozone level as 0.107 ppm. Subjects were divided into more and less 

frequently symptomatic children. In single pollutant models, there was a statistically significant 

association between current day ozone and symptoms of asthma. However, the associations with 

ozone were not statistically significant in 2-pollutant models with PM10. Most symptoms 
Exxon Mobil Corporation Comments: B-3 

reported were grade 2, which caused discomfort but did not interfere with daily activities or 

sleep. 

The symptom sum was considered a better measure of effect than the more common use of a 

dichotomous symptom based on present or absent and without rating of severity. The overall 

effect on the child was also considered more sensitive than consideration of single symptoms. 

Analysis: There are a number of comments on this study: 

• Ecologic measures of exposure were used, raising the question of exposure 

misclassification 

• Multiple lag times (1-6 days plus distributed-lags) were employed with biologic 

justification, raising the question of multiple comparisons. 

• The associations in single-pollutant models for ozone were stronger in the subgroup of 

children with less frequent symptoms of asthma, which is counter-intuitive. The 

associations in single pollutant models were only observed in children not using asthma 

medication. This finding is completely opposite that reported by Gent et al. (2002). 

• There was no apparent effect in 2-pollutant models, and subjectivity without validation of 

symptom occurrence. The inclusion of coarse PM, which demonstrates a much lower 

correlation with ozone than PM2.5, obliterated the signal from ozone. Even more 

attenuation of risks for ozone would be expected if PM2.5, which is highly correlated with 

ozone, was included in the statistical model. Effect estimates for various measures of 

PM10 were higher than for 1-hour and 8-hour ozone. 

• The method of recording symptoms as symptom sum appears to be an improvement over 

the simplistic presence or absence of a specific symptom with inclusion of biologically 

non-significant symptoms. 

Brauer et al. (1996) 2

Description/Results: Brauer et al. (1996) evaluated the potential lung function (FEV1, FEV) 

effect in berry pickers exposed to ozone. From their air quality statistics, EPA listed the 4th

highest maximum ozone concentration as 0.04 ppm. In the study itself, ambient ozone 

measurements were taken from an airport approximately 15 km from the study site. An 

additional ozone monitor was located at the study site for approximately three weeks during the 

study period. To validate the ability of the airport ambient monitor to assess exposure, 15 

workers were selected for personal monitoring on 23 d in the study period. Spirometry was 

performed 7 days/week, twice daily, during the study period. Since the full exposure data were 

only available for the airport ozone measurement, these data were used for the regressions with 

the spirometry data. 

 2

 Memorandum indicates 4th highest ozone level in study was below the current 8-hour NAAQS. 
Exxon Mobil Corporation Comments: B-4 

The heart rate observed in these workers indicated exertion levels 36 percent higher than resting 

rates. In what the authors described as “initial” regressions, 25/52 subjects and 31/52 subjects 

showed a negative association with FEV1 or FEV, respectively, and daily 1-hour ozone. The 

authors report that afternoon FEV1 or FVC, and FEV1 or FVC on the morning of the next day, 

were significantly associated with maximum temperature and maximum ozone. Also, after 

“correcting” for an individual’s mean function level, as well as the morning FEV1, showed a 

similar trend. When the authors removed days with ozone greater than 70, 60, 50, or 40 ppb, the 

coefficients decreased until they became no longer significant at 30 ppb. Ozone was not 

significantly associated with decreased lung function on the morning of the same day and there 

was no association with change in FEV1 (coefficient = 0 ml change per ppb ozone) and a nonsignificant association with FVC (-1.7 ml per unit ozone). 

Analysis: There are several concerns with the results of this study. 

• There is some evidence of data mining in the report. The progression of measurements, 

from “initial” to “main,” raises the question concerning multiple comparisons and 

analysis and whether or not the second set of analysis were planned de novo, or initiated 

after the first set of analysis indicated non-significant results. In the discussion section, 

the authors state that since cross-day ozone levels were not associated with change in 

lung function, they investigated other approaches to evaluate the data, including whether 

or not an association could be observed when the values were corrected for morning lung 

function level. 

• The coefficients (reductions) are small. Assuming FEV1 and FVC of 4 and 4.8 liters the 

maximum reductions associated with a 10 ppb change in O3 is less than 1 percent. With a 

coefficient of 0.0 for FEV1 an ozone concentration greater than 70 ppb would not 

increase airway obstruction according to the model. For FVC there would be a 

nonsignificant 119 ml (or ~2.5%) reduction. 

 

• There are ten or so different types of analyses (or method of estimating lung function 

change). The most intuitive and usual way to assess exposure effects on cross day lung 

function (at least in occupational shift studies) is to assess the change in lung function. In 

the main analysis of this study, cross-day lung function change is not significant for 

either FEV1 or FVC, with coefficients of 0.0 and -1.7 ml associated with ozone in the 

models also containing the variables of temperature and date. 

• Brauer et al. compared their results with four other studies. All used change in lung 

function parameter; Spektor (1988) also used evening FEV1 in addition to change. 

• The number of completed acceptable spirometric tests for FEV1 and FVC are not the 

same, suggesting there were possible problems in administrating the spirometry. 

Possible n ~ 1800 Morning Afternoon Change 

FEV1: n (% of total) 1687 (93.7) 1516 (84.2% 1278 (71%) 

FVC: n (% of FEV1) 1568 (93%) 1327 (84.6% 1025 (80%) 
Exxon Mobil Corporation Comments: B-5 

• About 7 percent of the morning tests were missing or invalid, and there are about 10 

percent fewer FEV data points in the afternoon than in the morning. Loss of data is even 

greater for assessing FVC change, which needs both morning and afternoon data. About 

30 percent of the possible maximum data points are lost, and there are 20 percent fewer 

data points for change in FVC compared to change in FEV1. If consistent effort is not 

obtained with consistent coaching, the FEV and FVC will be biased low. The problem 

appears to be worse in the afternoon. Fewer results for FVC than for FEV suggest 

possible extraction of FEV results from maneuvers where effort may have not been 

maximum, which could produce a reduced FEV. 

• Methods are incomplete as acceptability and reproducibility of the tracings is not defined, 

nor selection criteria of results. Thus the validity of the lung function results is 

problematic. 

• The authors report there was good agreement between the area-wide and site-specific 

ozone measurements (R=0.92). However, the means were quite different (40 versus 

26 ppb, respectively). In addition, while the group mean personal exposures indicated 

reasonable agreement with ambient (mean difference 2.5 ppb), the values for individuals 

indicated significant exposure misclassification existed at an individual level. 

III. Field Studies in Healthy Children. 

Neas et al. (1995)

Description/Results: Neas et al. (1995) reported an association between evening PEFR and 

ambient ozone in healthy non symptomatic school children in Uniontown, Pennsylvania. EPA 

indicates the 4th highest maximum ozone concentration as 0.087 ppm. Ambient ozone exposure 

levels were weighted by time spent outdoors. There were several analyses involving 12-hour 

(8:00 a.m.-8:00 p.m.) ambient concentrations. PEFR changes were based on deviation from 

overall mean, which overall was 330 L/min. The PEFR change was based on a 30 ppb increase 

in ozone. There are several results summarized: 

Model PERF Deviation 

From Mean 

~% 

Reduction PERF 

Unweighted 12-hour mean ozone -2.24 (-4.43 to -0.05) -0.7% 

Weighted by hrs spent outside -2.79 (-6.69 to -1.12) -0.8% 

2-pollutant model (acid PM) -0.92 (-3.26 to 1.40) -0.3% (NS) 

2-pollutant model (acid PM) adjusted for proportion 

of time spent outside 

-0.2 -0.06% (NS) 

Child-specific model 

 3 children with 

 significant drops (-10 L/m) 

 3 children with significant increases (+10 L/m) 

-2.32 (-5.60 to 0.96) -0.7% (NS) 

# % reduction estimate based on 300 L/min study mean 
Exxon Mobil Corporation Comments: B-6 

Analysis: There are several concerns with this study. 

• When ozone was considered with acid aerosol, the association for ozone was not 

statistically significant. 

• The authors suggest the lack of an independent effect of ozone in the 4th model (2-

pollutant model adjusted for proportion of time spent outside) "may be due to the low 

concentrations of ozone present during the study period." The maximum concentration 

was 87.5 ppb, the mean daily concentration 50 ppb. Given that these values are greater 

than the 30 ppb increment against which the changes in PEFR are calculated, it would 

appear the range of ozone concentrations is adequate for assessing an association. 

• The percent change is not clinically important and it is not clear it is an adverse effect. 

An adverse effect might be a reversal of the normal diurnal variation, which is higher 

PEFR values in the evening compared to in the morning. The diurnal variation was lower 

when PM acidity was increased, but no mention of modification associated with ozone. 

 

• This study has similar limitations to the other panel studies including no personal 

measures of exposure. Moreover, there is a high likelihood of PEFR measurement and 

reporting errors suggesting the outcome measure is too much in error to be very useful. 

• The measure of PEFR was the deviation of the evening PEFR from the child’s average 

PEFR over the study period. It is not clear that this way of estimating change is 

appropriate for estimating an association with ozone or any pollutant. Only the evening 

PEFR varies as the mean is a constant. But both morning and evening PEFR change 

daily, so each child starts from a different point at the beginning of exposure in the 

morning. The morning PEFR is presumably related to daily variation and not to pollutant 

concentrations during the night. The evening PEFR is related to day exposures and the 

starting point in the morning which is assumed (or hypothesized) to not be related to 

exposure effects. As a result, it is difficult to determine if the reported deviation is due to 

pollutant or whether it is just normal day-to-day morning variation. Since no completion 

of experiments was done consistent with the scientific method to clear up the confusion, 

added experimental methods and data analysis should be planned in the future to address 

these questions. 

 

• There are a number of other field studies of children not cited as key by EPA. A number 

of these recent studies are considered the definitive studies on the potential effect of air 

pollution on the health of children. In a study specifically designed to assess the 

independent effects of ozone on lung function growth in children by minimizing ozone’s 

correlation with other co-pollutants, no effect on lung function growth (FEV1) was 

observed (Gauderman et al. 2000). Linn et al. (1996) reported no association between 

respiratory symptoms and ozone exposure in school children in southern California. In 

this study, ozone exposure was assessed using personal monitors. Hoek and Brunekreef 

(1995) also did not report an association between ambient ozone levels and prevalence or 

incidence of respiratory symptoms in children living in two rural towns in the 

Netherlands. Overall, the data-on-data on potential effects of ozone on pulmonary 
Exxon Mobil Corporation Comments: B-7 

function and lung growth in healthy children are not convincing. For this reason, EPA 

removed the quantification of symptoms in healthy children from their risk assessment. 

IV. Field Studies in Non-Smoking Women Who Recently Delivered Babies. 

Naeher et al. (1999) 3

Description/Results: Naeher et al. (1999) evaluated lung function (PEFR) in women who 

recently delivered babies. In this study, the relationship between daily changes in 24-hour PM2.5, 

PM10, fine sulfates, and strong acid, and hourly ozone and morning or evening PEFR over a 2-

week period in the summer were evaluated. For each pollutant, seven different lag times (0, 1, 3, 

5, 3-, 5-, and 7-day averages) were used and regressed against normalized measurement of both 

morning and evening PEFR. Essentially at least one positive association was reported for all 

pollutants for at least one of the PEFR measurement times (morning or evening) and lag times. 

For ozone, statistically significant associations were not reported for morning PEFR. Ozone was 

the only pollutant for which a positive association was reported with evening PEFR. At lag 0 

and 3 days, but not 1 day lag, statistically significant associations were reported with evening 

PEFR. In the summary and abstract the authors report that the exposure related to evening PEFR 

showing the greatest effect was 5-day cumulative-lag (7.65 l/min decrease per 30 ppb ozone 

increase). 

Analysis: There are a number of concerns with this study. 

• While the authors report that the exposure related to evening PEFR showing the greatest 

effect was 5-day cumulative-lag, the report does not include data from the 5-day 

cumulative lags in the table or publication. Rather, data are provided for 3-day 

cumulative lags. The authors use the convention of change per 30 ppb ozone rather than 

10 ppb ozone. Expressed as change per 10 ppb ozone, the “maximum” ozone effect is 

7.55 l/min or 0.5%. 

• Changes in PEFR were defined in four different ways; three were normalized PEFR and 

were analyzed separately morning and evening. The fourth was the difference between 

evening and morning performance. The significance of the associations with each 

pollutant is summarized. Lag 0 is used for evening PEFRs and ▲PEFR, and lag 1 for 

morning PEFRs. 

Delta 

Normalization PM2.5 PM10 Coarse PM H+ Sulfate Ozone 

AM PEFR 

Lag 0 

Lag 1 

0.03 

0.065 

0.02 

0.047 

0.049 

0.045

0.011 

0.122 

0.097 

0.083 

0.257 

0.105 

PM PEFR 0.24 0.28 0.755 0.207 0.244 0.051 

 

▲PEFR NS NS NS NS NS NS 

 3

 Memorandum indicates 4th highest ozone level in study was below the current 8-hour NAAQS. 
Exxon Mobil Corporation Comments: B-8 

• The results appear to be largely random findings based on statistical significance alone. 

When all lags were included (i.e., Table 3 in the Naeher et al.) there are 100 comparisons 

and nine statistically significant (p<0.05) associations. As seen in the authors’ Table 3 

there were nine significant associations. Exposure on lag 0 occurs after the AM PEFR, 

so one would expect no association. However 4 of the 9 significant associations occurred 

on lag 0 for morning PEFR (see Table above). Thus, the association between AM PEFR 

and lag 0 exposures should be considered a control exposure, so one would expect five 

statistically significant associations by chance alone. [Note: There were more 

comparisons than this as Figure 2 shows an ozone E-R analysis that used a 5-day 

exposure variable, which does not appear in Table 3.] 

• The percent changes based on the delta PEFR from Table 3 all show a decrement (or 

improvements) of between 1 and 5 percent. For ozone the increment in exposure was 

30 ppb. The delta PEFR percent changes for ozone assumed (or hypothesize) linearity in 

the E-R regression model. But a linear regression model does not appear to be 

appropriate as the quartile exposure response (E-R) for ozone and PM PEFR is linear if 

the second quartile value is ignored as shown in Figure 2 in Naeher et al. We suggest 

added study work to confirm the hypothesis. 

• The text appears to indicate the only significant E-R trends are with 5-day ozone for 

morning PEFR, for all three normalized PEFR but not for ▲PEFR. Figure 2 indicates in 

the highest exposure category (40.3-56.6 ppb 5-day ozone) the reduction in normalized 

PM PEFR cannot be read. At about 50 ppb 5-day ozone there is less than a 1 percent 

decrement in normalized PM PEFR (0.4% with CI of + 0.65 to -0.85)%. This is not 

statistically significant according to this analysis and in any case is not an adverse effect. 

• The only ozone result in the discussion notes that a 30 ppb increment in 24-hour average 

ozone was associated with a decrease of 2.49 L/min (-0.01 to 5.01) decrement in PM 

PEFR. This is a non-significant decrement of about 0.5% (-0.002 to +1.09). At 50 ppb 

(mid-point of highest exposure category) the decrement in PM PEFR is about 0.9 percent 

and non-significant. 

• The level of decrease in PEFR is not biologically significant. 

In summary, there are no associations of ozone with ▲PEFR, the most appropriate measure for 

assessing acute changes in PEFR and E-R relationships with exposure. If the other measures of 

change in PEFR are used, the decrements at about 50 ppb are small (lower than 2 percent taking 

into account upper confidence limit). Given the many analyses and the potential for some 

significant results due to chance, it is difficult to determine whether or not the associations 

should be counted as statistically significant. 

The authors themselves note several limitations including errors in reporting PEFR and multiple 

statistical comparisons. They indicate there were more significant effects than expected on the 

basis of chance alone, so no correction was made but “confirmation in further studies” would be 

beneficial. 
Exxon Mobil Corporation Comments: B-9 

External evidence of weak associations, very small changes, biological implausibility with ozone 

exposure, inconsistent findings, and no associations with the PM – AM changes, provide support 

for the view that the results on ozone may be due to random variability. 

In addition, personal exposures might be quite different than concentrations gathered at a central 

site. PM2.5 and sulfate were said to adequately represent the inside and outside of homes in the 

region, despite 89 percent of subjects having air conditioning. Ozone was not mentioned, but it 

is known that ambient ozone concentrations are not correlated with indoor ozone. 

Finally, the study population only included women who may have slightly greater airway 

reactivity than men, so E-R may be different for healthy males. On the other hand, female 

subjects may exhibit higher reactivity and, therefore, represent a more susceptible population. 

ExxonMobil Biomedical Sciences, Inc. 

October 9, 2007 

 
 Exxon Mobil Corporation Comments 

ATTACHMENT C

Concerns With the Reliability of Peak Expiratory Flow Rate (PEFR) 
 Exxon Mobil Corporation Comments: C-1 

Concerns With the Reliability of Peak Expiratory Flow Rate (PEFR) 

Kamps et al. (2001) studied the reliability of data from peak flow diaries collected from 40 

asthmatic children aged 6-15 years. The children were moderately severe asthmatic outpatients. 

Both patients and parents had received a comprehensive education program and most had used a 

peak flow meter previously. They appeared to be well-motivated to comply with treatment. 

Study subjects were instructed to perform three peak flow measurements in the morning and 

evening and record the highest of the three attempts in a written diary for four weeks. Unknown 

to patients and parents the electronic peak flow meter contained an electronic chip that held in 

memory all the peak flow data, which was compared with the results in the written diary. There 

were two groups: BI = (basic information) group was told the meter could record PEFR digitally 

and more accurately; EI (extended information) group was also told the results would be used for 

making adjustments in treatment. Similar results were obtained from both groups so only the 

results from the BI group are reported. 

Compliance With Collection of PERF Data 

Reported compliance from the diary 96.6% 

Actual compliance from microchip 73.4% 

Actual compliance from week 1 to week 4 82.1% to 63% 

Accuracy of Peak Flow Values: Overall (Week 1 to Week 4) 

Correct 49.1% to (56.4% to 39%) 

Incorrect 22.7% (24.6% to 22.8%) 

Missing 5.8% (7.9% to 5.2%) 

Self-invented 22.4% (11.1% to 32.9%) 

Differences in Peak Flow Between Written and Electronically Recorded PERF 

Range of mean differences per patient -72 to + 34 liters/min 

Range of maximum differences -168 to +163 liters/min 

Compliance and accuracy were even worse in a similar study of 65 Hispanic or AfricanAmerican asthmatics 5-9 years, 40 percent of whom were at or below the poverty level. Redline 

et al. (1996). 

These results of Kamp et al. (2001) suggest PEFR data based on peak flow diaries are potentially 

unreliable. This study indicates compliance and accuracy show substantial declines over a 

period of a month or less. 

Pelkone et al. (1999) report similar results. While children aged 5-10 years could perform 

reproducible spirometric tests during home monitoring, there was very wide variation in the 

results. Results for younger children were not reproducible. Also, a large number of results for 

all children did not meet the criteria of acceptable reproducibility. 

Many other studies also raise concerns about the inaccuracy of PEFR measurements, and 

conclude that PEFR measurements are not useful for managing the administration of 

maintenance mediation by asthmatics (Diner et al. (2001); Sly et al. (2001); Wenseley et al.

(2004); Kotses et al. (2006); Tierney et al. (2004)). One study (Mortimer et al. (2003)) reported 

better agreement between self-administered PEFR measurements and clinic administered FEV1
 Exxon Mobil Corporation Comments: C-2 

and FVC. However, the higher level of agreement was realized by having experienced reviewers 

check the raw data and reject unacceptable data PEFR values. Also, the study only evaluated 

compliance over a 2-week period. The data from Kamps et al. (2001) indicate a decreasing 

compliance trend with time through the 4-week period of their study. 

In evaluating the studies used by EPA to determine PEFR outcomes associated ozone may be 

even more unreliable over longer time periods and in less-motivated study populations. 

Panel studies apparently using PEFR data from unsupervised written peak flow diaries and 

therefore producing potentially unreliable peak flow rates include: 

• Neas et al. (1995): 4th and 5th grade kids; ~3-months (summer) study period; reported 

compliance was only 84 percent in this study, so reliability of PEFR is potentially less 

than in Kamps et al. (2001). 

• Ross et al. (2002): 7-month study period; 32 percent drop-out rate 

• Mortimer et al. (2002): inner-city kids 4-9 in areas >30% below poverty level; 3-month 

study period, 2.5 percent of readings implausible and rejected. 

 

Exposure-Response (E-R) Analyses

In general the linear slope of the E-R analysis is calculated for some unit of ozone concentration 

(e.g., inter-quartile, 50 ppb, 10 ppb). But in the assessment of risk the question is: At what ozone 

concentration is there a biologically significant reduction in pulmonary function? That is, is 

there a 15 percent reduction in PEFR that occurs in this study and, if so, at what concentration? 

There are several considerations: 

i) Is the relationship linear or non-linear? A non-parametric smoothing regression 

model is most appropriate and accurate and is the preferred analytical method. This 

method was used by Korrick et al. (1998) although the results were not emphasized. 

 

ii) What is the adverse effect level? EPA offered a graded classification for acute 

reductions in FEV1 of mild (<10%), moderate (10-20%) and severe (>20%) (ATS, 

2000). ATS (2000) recommended that "reversible loss of lung function in 

combination with the presence of symptoms should be considered as adverse." This 

recommendation was considered consistent with EPA's graded scale. 

iii) The slope by itself is not completely appropriate for estimating the adverse effect 

level as the change at the lowest concentration may be negative or positive. To 

illustrate, the data in a graph is the most useful method as both linearity and the 

level at which an adverse effect occurs can be assessed (see Figure 1 in Korrick et 

al. (1998) for an example of an appropriate way to display the data). 

iv) If the data are not graphed, an x% approximate change can be estimated by 

calculating the % drop at different ozone concentrations, staying within the 

exposure range of each study. 
 Exxon Mobil Corporation Comments: C-3 

Estimates For Acute Changes in Lung Function

The most appropriate way to assess the association of acute changes in lung function (e.g., FEV1, 

PEFR) with ozone or any other air pollutant involves measuring the change in function over the 

period of exposure. The change in function can be either % change or absolute change. Percent 

change will be used for illustration. 

Exposure to ozone is usually measured over the day, so the change in lung function should be 

from morning to evening. The calculation is: 

[(evening PEFR) - (morning PEFR) / (morning PEFR)] x 100. 

Some aspects of the measure: 

• Change estimated in this manner is used in workplace shift studies and chamber studies 

and is an accepted method for assessing acute changes associated with short-term 

exposure. 

• Each person acts as their own control so no external control group with inherent 

uncontrollable differences is needed. 

• Each person acting as their own control adjusts for day-to-day variation in morning 

baseline performance caused by factors other than exposure. 

• The change will be negative if there is a reduction in performance over the exposure 

period, unless the change is smaller than diurnal variation where morning values increase 

during the day so evening lung function may be greater than morning, depending on the 

times of testing. 

• An adverse individual change is considered to be 15 percent reduction in PEFR and 10 

percent reduction in FEV1. 

• Two potential outcome variables can be useful for assessing an association. Both involve 

regression analysis of change by exposure. The most common is assessment of 

decrement in lung function associated with measured exposure. An additional option is 

to consider incidence of an adverse effect by exposure (e.g., % change >10 or 15%). 

Some of the panel studies use methods that are inappropriate for estimating a decrement in lung 

function associated with acute exposure. The methods used in the important panel studies are 

summarized: 

Mortimer et al. (2002)

Both % change and incidence of >10% decline. Percent change was defined as “daily per cent 

change from the diary-specific median PEFR.” Presumably this is median PEFR for the entire 
 Exxon Mobil Corporation Comments: C-4 

study period, although it does not say. Since this was done for morning and evening, the 

calculation appears to be: 

[[PEFR (morning or evening) - PEFR (median)] / (median)] x 100 

However, the results indicate a negative % change for both morning and evening, which would 

make both morning and evening PEFR larger than the median. 

This method of estimating change using a median PEFR from the entire study period has several 

limitations: 

• The median PEFR is an inappropriate baseline for assessing change because it does not 

adjust for all those factors that affect day-to-day variation in PEFR and significantly 

diminishes the individual-as-own-control concept and as a result loses sensitivity and 

increasing confounding effects. 

• Exposure is based on day concentrations with essentially no exposure during the night 

and prior to the morning PEFR. 

• Morning effects begin with lag 1 (the day before) so there is ~13-hour gap between 

previous exposure estimates and morning PEFR. Evening effects are measured at the end 

of the day so evening is closer in time to the measured exposure outcomes. 

• Presumably median PEFR relates to study median since daily median would be based on 

only two numbers. Use of median PFER increases the potential confounding effect of 

daily individual changes in PEFR caused by daily changes in individual health status or 

seasonal changes over the summer (e.g., temperature, RH, pollen). For example, Ross et 

al. (2002) reported that RH was negatively associated with evening PEFR; BS maximum 

temperature was negatively associated with morning PEFR. So it is problematic to 

conclude the association is with ozone when it could be due in part or in full to other 

factors. 

• The source of a 10 percent decline as an adverse effect is unclear, as definition of an 

adverse effect is usually based on a decrement in function over the period of exposure as 

discussed above and not by using a static statistic such as overall median. Deviation from 

a median or mean does not measure decrement in function. Interpretation of this 

outcome variable is problematic. 

Ross et al. (2002)

“Each individual's PEFR measurements were standardized by the individual’s” overall mean 

PEFR and change was measured as -- 

[PEFR (morning or evening) – overall mean PEFR / overall mean PEFR] 
 Exxon Mobil Corporation Comments: C-5 

Morning and evening PEFR were presented as change in PEFR (l/min) per inter-quartile ozone 

range. Ozone exposure consisted of 8-hour average daylight concentrations (20 ppb). Morning 

PEFR was collected 06:00-10:00 and evening PEFR 1900-2300. 

The change is similar to Mortimer et al. except the mean is used instead of the median and the 

absolute value (in L/min) is used instead of percent. This outcome measure has the same 

limitations noted for Mortimer et al. 

Neas et al. (1995, 1999) 

The outcome variable was deviation of each PEFR measurement from the child's mean PEFR. 

The daily change was calculated by subtracting overall mean from the maximum daily value. 

The deviations were normalized for size by dividing the child's mean and then multiplying by 

300 (which is the overall mean L/min for all children). The equation appears to be: 

[(PEFR (morning or evening) – Mean PEFR) / Mean PEFR] x 300 L/min 

Only evening deviations were reported so presumably there were no significant associations with 

night-time ambient ozone concentrations (2000-0800). Ambient daylight concentrations (0800-

2000) averaged 50 ppb. 

The PEFR change parameter has the same problems as in Mortimer et al. and Ross et al. and is 

an inappropriate method for assessing change. Some data are presented that amplify the 

limitations of this methodology for assessing change in PEFR: 

• If the maximum evening PEFR is less than the overall mean PEFR (which is likely if 

both morning and evening values are used), the reported change in PEFR should be 

positive. But all the reported changes are negative, indicating the overall mean PEFR is 

greater than the maximum. This does not make sense, unless the morning values are not 

used in the calculation of overall mean. 

 

• There was a trend for FEV1 and FVC to increase 0.29 percent and 0.43 percent per week. 

PEFR was highly correlated (r = 0.71) with FEV1, which may explain why adjusted 

deviation in evening PEFR increased 0.93 L/min/week (0.30%). Figure 2 in the report 

indicates a maximum weekly mean deviation of about 9 L/min and maximum decrease of 

about 11 L/min. These weekly changes are greater than the daily changes reported to be 

associated with ozone concentration. It is likely these reported weekly changes also 

occur on a daily basis. These data underline the necessity of using each individual as 

their own control for each day, which is not achieved in these studies where deviation 

from mean or median is used instead. 

The effect of using a deviation from the median or average lung function is an inappropriate 

referent and reduces sensitivity, increases confounding, and does not provide guidelines for 

estimating an adverse effect level. This appears to be an ad hoc method not commonly used in 

similar designs such as shift studies in studies of workers. 
 Exxon Mobil Corporation Comments: C-6 

Brauer et al. (1996)

Morning and evening spirometry was administered to farm workers. There was a 2-stage 

analysis, the second included ozone, temperature and date. Several variables were used to assess 

possible effects of ozone on lung function. These included both FEV1 and FVC. The discussion 

will only consider FEV1 as methods were the same for both. The final model had the form: 

FEV1 = u (mean FEV) + ID1 (departure from overall mean) + ... 

(max hourly temp, maximum hourly O3, Julian data)

• evening FEV1 does not assess change 

 

• next day morning FEV1 does not assess change 

• ▲FEV1 [afternoon FEV1 – morning FEV1] does assess change and is the only spirometry 

variable considered appropriate for assessing exposure-response. There was no 

association with ozone (coefficient = 0) or temperature, but there was an association with 

date. 

• ▲FEV1 corrected for morning level was added because there was no association with 

ozone. No details were provided to indicate how this correction was made so we do not 

know how it was calculated. This parameter should be considered simply an exploratory 

variable and statistical tests should not be used. It is not useful for interpreting results 

because it was added after the analysis of data outlined in the protocol. 

Korrick et al. (1998)

These authors use % change for all the pulmonary function variables, which is the appropriate 

parameter. For the 2-pollutant model the coefficients of the slope of the E-R curve are not 

significant, but are statistically significant when other pollutants are not in the model. However, 

the reduction in %FEV1 and %FVC are less than 5 percent at the highest exposure levels, and so 

there is no apparent adverse effect even if the slope is significant. 

Naeher et al. (1999)

In this study, subjects collected PEFR data in a recording from both morning and evening for a 

2-week period in the summer. Exposure variables included 24-hour averages of PM2.5, PM10, 

sulfate, acid, hourly ozone and temperature. The association between ambient air pollutants was 

analyzed using four different measures of PEFR. Three PEFR measures were normalized to 

“adjust for differences in subject height and age and to allow comparison of each subject to her 

own baseline,” and was done separately for morning and evening. A fourth measure was 

▲PEFR = liters/min. 

• Delta normalized PEFR or daily ▲PEFR was done separately for morning and evening 

as defined as: daily PEFR – average PEFR 
 Exxon Mobil Corporation Comments: C-7 

• Body size normalization PEFR = liters/min = 

 [(daily PEFR – 2-wk average PEFR) / (average PEFR)] x 460 Liters/min where 460 is the 

average PEFR of all study subjects 

• Z score normalization PEFR = no units 

[(daily PEFR – average PEFR) / (S.D. of all subject’s PEFR)] 

• ▲PEFR = evening PEFR – morning PEFR in liters/min. 

Changes in Pulmonary Function Are Small and Clinically Insignificant

• Mortimer et al. (2002). The group changes in PEFR are less than 1 percent. The largest 

reduction in plausible range (i.e., lowest confidence interval) is a 1.05 percent reduction 

or 10.5 percent of the lowest adverse effect defined by the authors. A slope for 

▲PEFR% was not calculated. 

 

• Ross et al. (2002). The authors indicated the change in PEFR was small. The estimated 

change was less than 1 percent per 20 ppb increase in ozone exposure (about 0.8% or 3 

liters/minute out of an average of 358 L/min). A slope for ▲PEFR% was not calculated. 

Maximum 8-hour ozone was 78 ppb. Using the evening slope of -0.129 liters/min as a 

substitute for % change, the average reduction in evening PEFR at 70 ppb would be 9.03 

Liters/min, or about 2.5 percent overall reduction in evening PEFR. 

• Neas et al. (1995). The authors reported there was an average 1.1 percent change from 

morning to evening. This is considerably less than an acute adverse reduction of 10-15 

percent PEFR. In absolute terms it is 3.3 Liters/min. A slope for ▲PEFR% was not 

calculated. 

• If evening deviation of PEFR is substituted for ▲PEFR%, there is an estimated reduction 

of 7.4 liters/min at 80 ppb 12-hour ozone (maximum = 87.5 ppb). Baseline PEFR was 

300 liters/min, so the evening deviation is about 2.5 percent.

• Brauer et al. (1996). The coefficient was 0.0 for ▲FEV1 so there was no association with 

ozone. The coefficient was -1.7 for ▲FVC or a reduction of 119 ml (or 2.6% at a 

baseline FVC of 4.5 Liters) and ozone concentration of 70 ppb. 

• Korrick et al. (1998): The E-R ▲FEV1 slope in adjusted linear 2-pollutant ozone model 

was -0.048 (-0.112-0.016), which at 70 ppb is equivalent to a 3.4% reduction, indicating a 

non-adverse and non-significant effect in the range of the ozone concentration data. Read 

from the graph, the reductions are ~2% and 2.8% from linear and non-parametric smooth 

regression respectively. 

ExxonMobil Biomedical Sciences, Inc. 

October 9, 2007 
 Exxon Mobil Corporation Comments 

ATTACHMENT D

CRA Memorandum on Results of Sensitivity Analyses 

on Ozone Risk Assessment 
Memorandum 

To: Doug Deason CRA No. D10760-00 

From: Anne Smith 

Date: October 9, 2007 

cc: Larry Gephart 

Subject: RESULTS OF CRA SENSITIVITY ANALYSES ON OZONE RISK ASSESSMENT 

This memorandum summarizes the results of several sensitivity analyses that CRA has performed on EPA’s 

estimates for ozone health risks. The act of quantifying the following mortality or morbidity risks due to ozone 

implies a presumption that the risk coefficients estimated in epidemiological studies reflect a causal and not 

purely statistical association. Although we have reproduced EPA’s risk estimates, and report underlying details 

and sensitivities in those estimates, this does not mean that we agree that any of these relationships are 

actually causal in nature. If the epidemiologically-derived risk coefficients are not causal, then all of the risks 

would be zero, even in the face of a positive relative risk coefficient. 

Causality cannot be determined from statistical evidence alone. However, most of the risk estimates that we 

show below are statistically insignificant. This means that even this statistical evidence is suggesting a large 

chance that there is no risk at all from ozone. (Statistical insignificance exist in every case where the 95% 

confidence ranges include a negative component.) 

Portion of EPA’s Risk Estimates Attributable to Ozone above 70 ppb on 8-Hour Average Basis 

In the first sets of re-analyses, CRA obtained the ozone air quality data necessary to reproduce EPA’s risk 

estimates, and then reproduced EPA’s mortality risk estimates for those seven cities where EPA had used cityspecific risk coefficients from Bell et al. (2004).1 After demonstrating that we could reproduce EPA’s own 

estimates, we then backed out the portion of the total ozone risk estimate that was attributable to days when the 

maximum 8-hour ozone average was 70 ppb or higher. We found that only a very small portion of the risk 

reported by EPA for attainment of the current ozone NAAQS was attributable to days when 8-hour averages 

were above 70 ppb. 

 

1 Although we could have reproduced the risk estimates based on the national average risk coefficient that EPA also relied on for these 

cities and for the other five cities in its mortality risk estimates, we do not consider that a valid risk estimate and so we have chosen not to 

reproduce those risk estimates at all. Most importantly, that risk coefficient has incorrectly removed the true remaining variance in risk after 

complete use of the Bayesian hierarchical method of extracting information from all of the cities in a multi-city study. CRA’s comments on 

EPA’s Draft Risk Assessment dated January 18, 2006 (in the ozone docket at EPA-HQ-OAR-2005-0172-0021.1) explain the technical basis 

for this statement (see pp. 7-11 of those comments). 
Results of CRA Sensitivity Analyses on Ozone Risk Assessment 

October 9, 2007 

Page 2 

Figure 1 shows the percent of annual deaths that are estimated to be hastened by ozone on days with a 

maximum 8-hour average that exceeds 70 ppb, based on the data for 2002 and 2004, after ozone for the three 

years 2002-2004 has been rolled back to the point where these years as a group are in exact attainment with 

the current standard. 

A better representation of the annual increase in mortality risk due to ozone at exact attainment of the current 

standard would be based on the average of those three years, as that is the distribution of ozone concentration 

that exactly attains the current standard. In contrast, for most of these five cities, the risks based on 2002 data 

reflect a set of ozone concentrations that are worse than the current standard would require on average, and 

the risks based on 2004 data are better than exact attainment. Figure 2 provides the average percent increase 

in mortality risk for 2002 and 2004 data, which is a better representation of the annual average risk remaining at 

the current standard attributable to days that exceed 70 ppb. Table 1 summarizes the information in Figure 2, 

showing what these percentages of incidence mean in absolute terms. 

Even if one considers the results for the individual years that vary above and below exact attainment, the 

percent of total non-accidental mortality that is attributable to ozone being greater than an average of 70 ppb 

over an 8-hour period would be less than about 0.13% (i.e., Cleveland in 2002). Note, however, that even 

Cleveland has a 0.00% risk in the other year (2004), so that in a truly “just attaining” year (e.g., something more 

like the average year case), the risk remaining at the current standard is 0.07% in Cleveland’s case, and is 

0.04% or less in all the other cities analyzed. The population-weighted average risk over all seven of the cities 

analyzed is 0.02%. 

The small mortality risk estimates presented above reflect the fact that when an area is in exact attainment with 

the current standard, there will be very few days on which the (maximum) 8-hour average exceeds 70 ppb, 

even with the range of weather over the years 2002-2004. Achieving exact attainment means that the risk of 

weather variability must be offset by over-attaining the standard in some years. The resulting effect – if using 

EPA’s air quality rollback assumptions – is that a standard of 84 ppb (4 exceedances) would actually provide 

very significant protection against exposures to ozone below the standard down to 70 ppb. 

The portion of risk that is attributable to days with risks above 70 ppb (8-hour average) is the same for all of 

EPA’s health risk calculations that were based on 24-hour average epidemiological studies. This is because it 

is a function of the ozone concentration distribution that was observed in 2002-2004, and this is the same no 

matter what health endpoint one is considering. Thus, we also find that only the same small portion of 

estimated morbidity impacts are attributable to days when the maximum 8-hour ozone is 70 ppb or higher. 

Table 2 shows, as an example, the comparable results for hospital admissions for pneumonia and COPD that 

EPA estimated for Detroit. 
Results of CRA Sensitivity Analyses on Ozone Risk Assessment 

October 9, 2007 

Page 3 

Figure 1. Estimated Percent of Annual Non-Accidental Mortality Associated with Short-Term Exposure 

to Ambient Ozone on Days When the Maximum 8-Hour Average Exceeds 70 ppb When Just Attaining 

the Current 84 ppb Standard – for 2004 and 2002 Air Quality Separately

Based on Adjusting 2004 Air Quality Data

-0.60%

-0.40%

-0.20%

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

Atlanta

Cleveland

Detroit

Houston

Los Angeles

Sacramento

St. Louis

Percent of Total Incidence (and 95% CI)

Attributable to ozone > 0.08 ppm

Attributable to 0.07 ppm < ozone <= 0.08 ppm

Based on Adjusting 2002 Air Quality Data

-0.60%

-0.40%

-0.20%

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

Atlanta

Cleveland

Detroit

Houston

Los Angeles

Sacramento

St. Louis

Percent of Total Incidence (and 95% CI)

Attributable to ozone > 0.08 ppm

Attributable to 0.07 ppm < ozone <= 0.08 ppm
Results of CRA Sensitivity Analyses on Ozone Risk Assessment 

October 9, 2007 

Page 4 

Figure 2. Estimated Percent of Annual Non-Accidental Mortality Associated with Short-Term Exposure 

to Ambient Ozone on Days When the Maximum 8-Hour Average Exceeds 70 ppb When Just Attaining 

the Current 84 ppb Standard – for Average of 2002 and 2004

Based on Adjusting 2002 and 2004 Air Quality Data

-0.60%

-0.40%

-0.20%

0.00%

0.20%

0.40%

0.60%

0.80%

1.00%

Atlanta

Cleveland

Detroit

Houston

Los Angeles

Sacramento

St. Louis

Percent of Total Incidence (and 95% CI)

Attributable to ozone > 0.08 ppm

Attributable to 0.07 ppm < ozone <= 0.08 ppm

Table 1. Total Annual Non-Accidental Deaths by Risk Analysis City and Number of Those Deaths 

Attributed to Days When the Maximum 8-Hour Average Ozone Level Exceeds 70 ppb When Just 

Attaining the Current 84 ppb Standard (for Average of 2002 and 2004 Data; 95% Confidence Intervals in 

Parentheses) 

 

Total Non-Accidental 

Deaths per Year 

Numbers of Deaths 

Attributable to Ozone > 

70 ppb 

Percent of Mortality 

Incidence 

Atlanta 9,233 2 

(-8 , 11) 

0.02% 

(-0.08, 0.12%) 

Cleveland 14,749 10 

(-6 , 25) 

0.07% 

(-0.04, 0.17%) 

Detroit 18,817 7 

(-2 , 16) 

0.04% 

(-0.01, 0.08%) 

Houston 18,122 4 

(0 , 7) 

0.02% 

(0.00, 0.04%) 

Los Angeles 54,157 0 

(0 , 0) 

0.00% 

(0.00, 0.0%) 

Sacramento 8,390 1 

(-3 , 5) 

0.01% 

(-0.04, 0.06%) 

St. Louis 3,992 1 

(-2 , 4) 

0.03% 

(-0.04, 0.10%) 
Results of CRA Sensitivity Analyses on Ozone Risk Assessment 

October 9, 2007 

Page 5 

Table 2. Total Annual Hospitalizations Estimated for Detroit that Are Attributable to Days When the 

Maximum 8-Hour Average Ozone Level Exceeds 70 ppb When Just Attaining the Current 84 ppb 

Standard (Based on Ito (2003); 95% Confidence Intervals in Parentheses) 

Year 2004

Morbidity Effect Days Lag

Total Incidence 

Per Year

Hospital Admissions (unscheduled), pneumonia 0-day lag 5129

(0 , 0) (0% , 0%)

Hospital Admissions (unscheduled), pneumonia 1-day lag 5129

(0 , 0) (0% , 0%)

Hospital Admissions (unscheduled), pneumonia 2-day lag 5129

(0 , 0) (0% , 0%)

Hospital Admissions (unscheduled), pneumonia 3-day lag 5129

(0 , 0) (0% , 0%)

Hospital Admissions (unscheduled), COPD 0-day lag 3951

(0 , 0) (0% , 0%)

Hospital Admissions (unscheduled), COPD 1-day lag 3951

(0 , 0) (0% , 0%)

Hospital Admissions (unscheduled), COPD 2-day lag 3951

(0 , 0) (0% , 0%)

Hospital Admissions (unscheduled), COPD 3-day lag 3951

(0 , 0) (0% , 0%)

Year 2002

Morbidity Effect Days Lag

Total Incidence 

Per Year

Hospital Admissions (unscheduled), pneumonia 0-day lag 5129

(-33 , 9) (-0.65% , 0.18%)

Hospital Admissions (unscheduled), pneumonia 1-day lag 5129

(-24 , 17) (-0.47% , 0.33%)

Hospital Admissions (unscheduled), pneumonia 2-day lag 5129

(-18 , 22) (-0.35% , 0.43%)

Hospital Admissions (unscheduled), pneumonia 3-day lag 5129

(-11 , 27) (-0.21% , 0.53%)

Hospital Admissions (unscheduled), COPD 0-day lag 3951

(-28 , 11) (-0.7% , 0.27%)

Hospital Admissions (unscheduled), COPD 1-day lag 3951

(-12 , 24) (-0.29% , 0.59%)

Hospital Admissions (unscheduled), COPD 2-day lag 3951

(-21 , 17) (-0.53% , 0.42%)

Hospital Admissions (unscheduled), COPD 3-day lag 3951

(-19 , 18) (-0.49% , 0.45%)

Average of Year 2002 and 2004

Morbidity Effect Days Lag

Total Incidence 

Per Year

Hospital Admissions (unscheduled), pneumonia 0-day lag 5129

(-17 , 5) (-0.33%, 0.09%)

Hospital Admissions (unscheduled), pneumonia 1-day lag 5129

(-12 , 8) (-0.24%, 0.16%)

Hospital Admissions (unscheduled), pneumonia 2-day lag 5129

(-9 , 11) (-0.17%, 0.22%)

Hospital Admissions (unscheduled), pneumonia 3-day lag 5129

(-6 , 14) (-0.11%, 0.27%)

Hospital Admissions (unscheduled), COPD 0-day lag 3951

(-14 , 5) (-0.35%, 0.13%)

Hospital Admissions (unscheduled), COPD 1-day lag 3951

(-6 , 12) (-0.15%, 0.3%)

Hospital Admissions (unscheduled), COPD 2-day lag 3951

(-11 , 8) (-0.27%, 0.21%)

Hospital Admissions (unscheduled), COPD 3-day lag 3951

(-10 , 9) (-0.24%, 0.23%)

Note: Upper and lower bounds shown in parentheses are based on the risk factor's 95% confidence interval.

0.01%

0.18%

-0.19%

0.18%

-0.03%

0.00%

-0.22%

-0.05%

0.06%

7

-1

0

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

0.00%

-11

-3

9

-8

3

0

0

0

0

-0.09%

0.09%

-0.01%

0.01%

-0.11%

-0.03%

0.03%

0.09%

-4

4

-1

0

-6

-1

2

5

Number of Effects 

Attributable to Ozone > 

70 ppb

Number of Effects 

Attributable to Ozone > 

70 ppb

Number of Effects 

Attributable to Ozone > 

70 ppb

Percent of Total 

Incidence

Percent of Total 

Incidence

Percent of Total 

Incidence

0

0

0

0
Results of CRA Sensitivity Analyses on Ozone Risk Assessment 

October 9, 2007 

Page 6 

Sensitivity of EPA’s Risk Estimates to its Decision to Change the PRB Assumption 

The above details on EPA’s risk estimates were performed using exactly the same data and assumptions as 

EPA has used. One of those assumptions was the average Policy Relevant Background (PRB) level. This is 

an assumption because there is an extremely limited amount of evidence on what the actual PRB value is that 

matches its definition. EPA changed its assumed value for PRB in the 2006 risk assessment compared to its 

1997 risk assessment. At present, the PRB value is based on modeled results using the GEOS-CHEM model, 

and it varies by month and location. The daily average PRB (which is the fundamental assumption that went 

into all of the mortality risk calculations ranges from 14 ppb to 34 ppb, depending on the city and the month. In 

1997, EPA based the assumption on monitored rather than modeled data, and used 40 ppb for all cities and all 

months. 

EPA’s epidemiologically-based risk estimates, including the mortality risk estimates, are highly sensitive to this 

change in the PRB assumption. In fact, if EPA had performed its 2006 risk analysis exactly as it has done, 

except for using the same PRB assumption as it used in 1997, its mortality risk estimates would have been 

about 10 times smaller. Table 3 compares the city-specific mortality risk estimates (attributable to all exposures 

levels above PRB) using EPA’s GEOS-CHEM derived PRB assumptions, and using the earlier 40 ppb 

assumption. 

Table 3. Sensitivity of EPA’s Current Mortality Risk Estimates to Use of PRB Used in 1997 

(Risks Estimated Using City-Specific Risk Coefficients from Bell et al. (2004), at Exact Attainment of the 

Current Ozone NAAQS, Average of 2002 and 2004 Data)

 

Numbers of Deaths 

Attributable to Ozone > 

GEOS-CHEM PRB 

Numbers of Deaths 

Attributable to Ozone > 

40 ppb PRB 

Percent Reduction If 

Using 40 ppb Rather 

than GEOS-CHEM for 

PRB Assumption 

Atlanta 

 6.5 0.3 95% 

Cleveland 

 37.4 4.3 88% 

Detroit 

37.9 1.8 95% 

Houston 

 22.7 1.5 94% 

Los Angeles 

 38.5 0.1 >99% 

Sacramento 

11.0 0.2 98% 

St. Louis 

4.4 0.3 93% 
Results of CRA Sensitivity Analyses on Ozone Risk Assessment 

October 9, 2007 

Page 7 

Conclusions: Need for Integrated Uncertainty Analysis 

All of the risks reported above have relied on city-specific risk coefficients only. These reveal a substantial 

degree of statistical uncertainty for mortality and for the subset of morbidity endpoints that we reanalyzed. In 

fact, almost all of the above estimates are statistically insignificant, meaning that they each imply a substantial 

probability that there is actually no risk at all. This is evident in the fact that the confidence intervals shown in 

the tables and figures above all extend as much into the negative range as in the positive range, and the overall 

effect is that each of the point estimates provided is actually much better described as a wide range of 

uncertainty that is nearly centered on zero. 

The sensitivity analyses that we have reported in this memo show a very large degree of further uncertainty in 

the EPA risk estimates. It is noteworthy that we have only explored a couple of the many forms of uncertainty in 

assessing ozone health risks. The uncertainties that we have explored above are those related to the PRB 

assumption and those that are related to the possibility that risk estimates should not be treated as causal for 

ambient concentrations that fall below 70 ppb on an 8-hour average basis. While these are important sources 

of uncertainty, there are many more associated with choices such as how to address epidemiological model 

design, publication bias, the role of co-pollutants, assumptions about how standards will alter the distribution of 

ozone concentrations, and even whether the presumption of causality is correct. All of these uncertainties are 

far more significant concerns than the mere statistical variances that are reported with each of EPA’s risk 

estimates. I have submitted multiple comments to EPA during the course of the current NAAQS review that 

have argued for the need for its Risk Assessment to include a probabilistic assessment that integrates all of 

these uncertainties into EPA’s summary statements on risk. EPA has not done this, and I believe the sensitivity 

analyses reported in this memo highlight the continued need to do so. 

The following are the references for the written comments submitted to EPA in the course of this ozone NAAQS 

review cycle in which I have explained the importance and need for integrated uncertainty analysis in further 

detail: 

• Smith, A. Comments on EPA’s Draft “Ozone Health Assessment Plan”, prepared for the Utility Air 

Regulatory Group and submitted in official comments to EPA, May 3, 2005. 

• Riker, D. and A. Smith. Remarks to CASAC on EPA’s Draft “Ozone Health Risk Assessment”, 

prepared for Southern Company, December 1, 2005. 

• Riker, D. and A. Smith. Comments on EPA’s Draft Ozone Health Risk Assessment, prepared for the 

Utility Air Regulatory Group and Southern Company, January 17, 2006. EPA-HQ-OAR-2005-0172-

0021.1 

• Riker, D. and A. Smith. Comments on EPA’s Draft Ozone Health Risk Assessment, prepared for the 

Utility Air Regulatory Group, September 18, 2006. EPA-HQ-OAR-2005-0172-0049.1 

/as