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 subm it comments on the Environmental Protection Agency's (EPA or the Agency) July 11, 2007 propos ed 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 impacte d 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 conf irms 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 incorrect ly 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 dat a, 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 unpublis hed re-analysis of the author’s original study employs an inappropriate statistical test a nd 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 st udies cited by EPA as sign ificant 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 appli ed 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 andstudies 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 s hould revise its risk estimates to include an integrated uncertainty analysis that addresses major sources of uncertainty.

• EPA’s assumption that most mortality health benef its 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, in cluded 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 toU.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 gr owing 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 curr ent 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 EP A’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 h ealth effects from exposure to ozone. Indeed, the clinical evidence suggests that the risks of adverse eff ects 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. Sp ecifically, EPA must explain why its earlier judgment regarding what is “requisite” to prot ect public health or we lfare should no longer govern. Given that scientific evidence shows th at 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 ev idence shows that the risks that do exist should not require tightening of the standard at this time; any tight ening would not be requis ite 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 exposur e to ozone that were not pres ent 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 oz one standards in the 1997 review:

The Criteria Document provides new evidence that notably enhances our understanding of short-term and pr olonged 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 Docu ment. There is also a significantbody of new epidemiological evidence of associations between shortterm and prolonged exposure to O 3 and effects such as premature mortality, hospital admissions and em ergency 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 fo r 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 O 3 on lung

function decrements and enhanced re spiratory symptoms in asthmatic individuals, school absences, and premature mortality.

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

These claims are incorrect. With the ex ception 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 w ith 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 Do cument (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 ex posure in 1997. Furthermore, as discussed later in these comments, the evidence concerning the concentration of ozone associated with producing these effects has al so not changed since 1997.

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

extensive amount of data and conc luded that a wide array of hea lth effects were attributed to short-term (1-3 hrs.) and long-te rm (6-8 hrs.) exposur e 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, transi ent 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-existi ng diseases, includi ng 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 functio n response due to gender (Table 7-3), hormonal factors (Table 7-4) and age (Table 7-5). EPA al so presented data on repeated exposure to ozone (Table 7-6). EPA reported that similar h ealth effects were observed following prolonged exposures to ozone at concentratio ns as low as 0.08 ppm and at lowe r levels of exercise than for short-term exposures. (1996 EPA Staff Pa per (SP) at 24 and 62 Fed. Reg. 38,855, 38,859 (July 18, 1997)). EPA noted that some of the studie s 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 th e results of epidemiology and field studies that evaluated impacts on emergency room visits, hospital admi ssions, and mortality (CD, chapter 7). EPA’s risk assessment in 1996 included evaluation of pu lmonary function decrements, lower respiratory symptoms, cough, and chest pain on deep inspir ation, in outdoor children and outdoor workers, and acute excess respiratory rela ted hospital admissions, including admissions of asthmatics.Exxon Mobil Corporation Comments - 3 In 2007, EPA again cites the same health eff ects and factors that influence response to ozone that are mentioned above, and in fact c ites 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 su pport effects at levels below those evaluated in 1997. In human clinical studies, the lowest con centration where these e ffects 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 th e many previously published studies conducted at 0.08 ppm. Due to serious limitati ons in the epidemiology studie s, described further in our comments, these studies are unable to ascertain th e concentration where effects begin to occur, or, if the effects reporte d 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 (“19 96 SP”), and Final Rule from the 1997 review,

with the health effects discussed in this review, show no apprecia ble 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 ha ve been published since 1997, including a number of epidemiological and a few human clinical studi es, 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 sup ported 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 O 3 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 O 3 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 O 3 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 O 3 exposure in asthmatic and nonasthmatic subjects suggest that asthmatics are at least as sensitive, if not more sensitive, to the acute effects of O 3 inhalation” (1996 CD at 7-25) (emphasis added).

“In the proposal notice, EPA stated that groups at increased risk of experiencing health effects from O 3 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 O 3 levels or moderate levels of exertion during prolonged periods of elevated ambient O 3 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 O 3 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 O 3 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 O 3 , 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 O 3 has not been shown to cause asthma, the available evidence suggests that O 3 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 FEV 1 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] FEV 1 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 O 3 exposure. This observation of large intersubject variability in response to

O 3 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 Increase d 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 in dividual responses to 0.08 ppm ozone exposure even though the average or mean response may be relatively small. (7 2 Fed. Reg. at 37,828). However, the presence of effects at 0.08 ppm a nd the concept of indivi dual variability in response to ozone was well understood and documente d in the 1997 review. In fact, in the 1997 final rule, EPA noted that the research found st atistically significant e ffects at 0.08 ppm with high individual variability: “it is recognized that some individuals are unusually responsive to

O 3 and may experience much greater functional a nd symptomatic effects from exposure to O 3 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 extende d in duration to be consider ed adverse.” (62 Fed. Reg. at 38,864). EPA supported this conclusion by noting th at 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 FEV 1 decreases as large as 40 to 50 percent at 6- or 8-hour exposures in the range of 0.08 to 0.10 ppm base d 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 activ ities and individuals with pre-existing respiratory di sease, including asthma and ch ronic obstructive lung disease ( see EPA’s 1997 Response to Comments, s ection b., Definition of sensitive populations, at 50-51). In fact, EPA’s conclusions on indi vidual sensitivity and responsiv eness, and populations at potential increased risk to ozone exposure are e quivalent 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 resu lts 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 statistica lly significant group mean decrea ses of 6.1 percent for 6-hour square wave exposures at 0.08 ppm ozone using a ventilation rate (V E ) of 20 l/min/m 2 . These responses are similar to the 6.2 percent decreas e Adams reported at 0.08 ppm in a previous chamber study conducted at the same V E (Adams, 2003). Further, these responses were only slightly less than the -7.4% net response (i ncluding +0.8% response to filtered air? (FA)) observed in a chamber exposure to 0.08 ppm ozone with exercise V E 20 l/min/m 2 by Horstman etExxon Mobil Corporation Comments - 6 al. (1990) and the -7.7% net response (includi ng 0.6% response to FA) observed by McDonnell

et al. (1991). Therefore, the findings by Ad ams (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 FEV 1.0 response of -1.5 percent for the square wave exposure at 0.06 ppm was not statistically differe nt 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 e ffects and exposure time effects. Upon obtaining a significant F value, the Scheffé post hoc test was applied to determine wh ich particular mean values were significantly different. In cont rast, EPA analyzed only the data at 6 hours using a t–test.

There are several concerns w ith 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 Adam s data in drawing conclusions regarding risks below 0.08 ppm (the so-called “Brown Me morandum”), the re-analysis was not published or peer reviewed. As a result, neither the scie ntific community nor the public was afforded an opportunity to appropriately revi ew the analysis. In fact, th e only documentation for the reanalysis is in an internal EPA memorandum that appeared in the ozone do cket 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 ri sks 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 sta tistical 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 evalua te 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, th e Brown Memorandum implies that the t-test is the preferred statistical test comm only applied by EPA in similar st udies: “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 FEV 1 between an air and an O 3 exposure.” Brown Memorandum at 4 (citing Hostman et al. 1990; McDonnell et al. 1991). TheExxon Mobil Corporation Comments - 7 references, however, are to two studies that are over 15 years ol d that do not reflect EPA practice for analyzing FEV 1 data.

A more thorough review of the st atistical tests used by EPA res earchers in clinical studies suggests just the opposite. In fact, all of the investigativ e 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 pro cedures based on ANOVA with repeat ed measures of subjects to

assess the statistical significance of their group m ean pulmonary function findings.

In a recent human chamber study in elde rly volunteers with Chronic obstructive pulmonary disease (COPD) exposed to condensed ambient particles, the ANOVA test with repeated measures on subjects was used to evalua te the statistical signifi cance 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 hum an clinical studies to evaluate FEV 1 responses, Dr. Devlin has again expressed preference for us ing the mixed model ANOVA to assess the data.

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

ventilation on FEV 1 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). Statis tical significance

of the coefficients derived fr om the mixed model was determin ed with the asymptotic covariance matrix of the estimated parameter values , rather than the simplis tic 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 pr ocedures used by Adams should not be viewed as “overly conservative” or in appropriate according to an undefined standard suggested by Brown/EPA-NCEA, as inferred in the Brown memorandum. Decisions, such as

choice of statistical model base d on undefined standards is arbi trary 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 anal yzing the pre- minus pos t- exposure lung function responses.” This statement is incorrect. There is no written doc umentation 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 disc ussion on this issue during the teleconference, one member, Dr. Fred Miller, expressed interest in using a different, poten tially less conservative post hoc test than the Sheffé te st. In fact, as described belo w, ExxonMobil Biomedical Sciences, Inc. has completed this reanalys is using the Dunnett’s post hoc te st, a less conservative post hoc test, both for the 6-hour only data and complete data set. The resu lts 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 theExxon Mobil Corporation Comments - 8 t-test. Further, the verbal opinion of one or even a few CASAC me mbers should not be

misconstrued as the collective vi ew of the CASAC.

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

studies over the t-te st 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 (c ontrol) group whereas th e t-test does not consider that effect. Suppose the FEV 1 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 si gnificant” compared to no change (a zero change), but it is not statisti cally different from the contro l 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 th e control group. Als o, the t-test does not control for the time effect in the absence of an exposure.

• The ANOVA test has greater st atistical power. The Brown Memorandum indicates that as the Type I Error decreases because of th e correction for multiple comparisons the Type II Error increases (the Power decreases). Ther e 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 fr eedom (df) associated with the estimated error variance increases so will the power (thi s is a statistical nice ty, but an important point). The ANOVA with its repeated meas ures aspect has a mu ch better (larger df) estimate of the error variance and, ther efore, is the more powerful method.

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

allows the researcher to de termine if there is a dose re sponse 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 T ype I error rate, the probability of finding at least one false

difference would be 1-0.95 90 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 erro r rate of 0.05. The other ex treme 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 Bonf erroni test (with an error rate of 0.0005) and the uncorrected test that yields an almost certain chance of ma king at least one false

claim of a difference. The Brown Memora ndum’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 6.6 th hour readings is not the appropr iate 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 th e 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 In c. 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 FEV 1 and the observed FEV 1 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 statis tically 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 adjust ed by Dunnett’s test (used for comparing

“treatment” means versus a single “control” value). Th e 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-analysi s was performed both using the 6-hour data only and the full data set of FEV 1 . 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 Brow n Memorandum. The re-analysis was also performed both with and without transforma tion of the residuals to make them much closer to being normally distributed. Based on an analysis of the re sponse pattern over the 6.6 hours of experimentation, the only statis tically significant percent changes in FEV 1 responses from the first period filtered air e xposures 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 we re observed for the 0.06 ppm exposures.

Finally, EPA’s assertion that the consid erable variability in the Adams study is potentially an indication of significant adverse h ealth outcomes is not supported by the data or the EPA re-analysis. The Brown Memorandum make s the argument that, while the mean change

in FEV 1 at 0.06 ppm ozone is small, the large variability in the responses is an indication that “... some [individuals] may experience di stinctly larger effects ...” w ith the implication that there might be more deleterious effects than what wa s observed in this study.. However, the large variability is a ch aracteristic of FEV 1 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, includ ing 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 FEV 1 to not be of clinical significance (W ang 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 th e 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 th e “hundreds of studies” when it promulgated a revised National Ambient Air Quality Standard for fine particles (PM 2.5 ). (71 Fed. Reg. 61,144, 61,151 (Oct. 17, 2006)). Not only does this raise th e issue of double counti ng 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-c alled “new” epidemiology information since 1997 is based on time series studies evaluating th e impacts of particulate matter on health.

B. EPA fails to articulate and follow the weight of the evidence or established causality criteria for evaluating epid emiology studies in drawing conclusions regarding causality.

In the proposed rule, EPA st ates that it focused only on health effects where ozone exposure is causal, likely causal, or highly suggestive of those e ffects. (72 Fed. Reg. at 37,823). However, EPA has not provided definitive criter ia 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 interp ret their data in the discussion section of their publications, or untested theories generated by EPA staff, to e xplain the results of sometimes implausible epidemiology findings. These hypotheses ar e then later used as fact, without further testing and re-testing to establish their credibili ty. 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 st udies have raised signifi cant 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 ra ise serious questions about their own results and on the time-series study design upon whic h the results were based. Vedel et al. state:Exxon Mobil Corporation Comments - 11 Because the absence of a concen tration-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 th at 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, ambi ent 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, confoundi ng by meteorology still seems plausible.

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

EPA should provide clear and speci fic scientific criteria to judge whether health effects reported from epidemiology studie s as well as other studies ar e causal, likely causal or highly suggestive. These criteria should be subject to review by a diverse exte rnal group comprised of expert scientists from the di sciplines of epidemiology, human clinical studies, toxicology, and exposure science. EPA should also look to the In ternational Agency for Research on Cancer’s

well-defined causal criteria for addressing carcinogenicity as an example. Once clearly established causal criteria are defined for pur poses of NAAQS deliberations, EPA can then conduct a weight of evidence evaluation to suppor t a conclusion regarding causality for specific health effects endpoints based on the data collec ted. Without clear crite ria on causality, EPA’s evaluation of epidemiology st udies will remain arbitrary.

C. Because of the many weaknesses in time series studies, more studies reporting the same result does not increa se the case for causality or show consistency.

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

determination increases as the number of studies c onsistently reporting a part icular health effect endpoints grows. (72 Fed. Reg. at 37,823). However, this is not scientif ically correct in the context of ozone time series morbidity and mortality studies, which constitute the vast majority of “new” studies relied on by EP A on the health effects of ozone . Time series studies on individual cities, which are exceedingly easy to perform and publish, are unlikely to provide anyExxon Mobil Corporation Comments - 12 new meaningful data on the health effects of ozone. These studies a ll 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 determini ng 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 consis tency in observational epidemiology studies, an article in Science quotes David Sa ckett 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 st ill bias.” (Taubes 1995 at 169).

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

studies are not consistent as clai med 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 di d not reach statistical significance. Comparison of the results also show unexplained differences in rankings and magnitude of results even though they are base d on the same underlying data from the National Mortality, Morbidity and Ai r 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 SeattleBell, 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 Resp iratory (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 cav eat any conclusion based on the systematic elements of confounding present in all of the ozone observati ons studies and the unexplained heterogeneity in results ac ross cities and authors.

D. The strength of the associations in oz one 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 shoul d be included along with the magnitude of the risk in determining the strength of association.

• The CDC statement is based largely on the sp ecific characteristics of the data in a Smoking and Health study and ca nnot 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 de signs. The studies on smoking include 29 retrospective case control studies and seven prospective cohort studi es. 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 ob servational 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 relati onship between the ambient oz one levels and positive or negative associations across cities, i.e. , there is no dose re sponse observed.

• Finally, the Hill causal criteria on causality, of ten 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 stre ngth of association. (Hill 1965). Rather, these guidelines clearly indica te 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 ra ndom 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 j udge the strength of an associa tion. Given the wide degree of heterogeneity in the results of ozone time-seri es studies across and within cities, EPA cannot

conclude that the results of these studies are “c onsistent” or that there is high precision in the results of these studies (see comments above).

Leading epidemiology experts have indicate d that magnitude of relative risks from observational epidemiology studies below 2-3 shoul d not be seriously considered. The Journal of Science (Taubes, 1995) interviewed leading ep idemiologists on the topi c of risk estimates from observational epidemiology studies. Some exam ples of their concerns are presented below:Exxon Mobil Corporation Comments - 15 • Michael Thun, Director of Analytic Ep idemiology 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 biologi cally implausible or if it’s a brand new finding.”

• Robert Temple, Director of Dr ug Evaluation at the Food and Drug Administration, put it bluntly “M y basic rule is if the rela tive risk isn’t at least three or four, forget it.”

• Sander Greenland, a University of California, Los Ange les, epidemiologist, was noted as stating “a study reporting a twofold in creased risk might then be worth taking seriously—‘but not that seriously.’”

• Dimitrios Trichopoulos, head of the Ep idemiology 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 ecolo gical epidemiology studies are on the order of

1.000-1.008 and are therefore very weak. EPA should revise this se ction to indicate that the strength of the associations in oz one 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 surrogat es 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, collectivel y, 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 mo st relevance for time-series studies. Id. Both of

these statements are not accu rate 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 publis hed prior to and after the last ozone NAAQS review in 1997. Th ese 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 que stions concerning the use of ambient monitorExxon 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 auth ors’ 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 am bient monitors are a better surrogate for personal exposure to PM 2.5 than to ozone; and (3) popu lations expected to be potentially susceptible to ozone, including children, the elderly, a nd 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 scientif ic publications, that measurements on ambient

monitors do not provide reliable estimates of personal ex posure 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 concentrati ons 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 ha ve 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-te rm 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 Ambi ent Ozone, Report of a Working Conference held in Rochester, New York, June 5-6, 2007 (“Ro chester 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 expos ure 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). La ter in their report, the Rocheste r 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 ar ea, 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 co ncentrations of co-pollutants, for example due to traffic density, within the study area.

(Rochester Report at 52)

. On time-series studies, th e 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 PM 2.5 or other pollutant exposures. Consequently, it may not be possible to distinguish between the health effects of ozone and those of fine pa rticles 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. Inst ead, EPA transforms the results of the studies by Sarnat et al.

and others to arrive at their conclusion that am bient monitors measurements provide an adequate “surrogate” for personal exposure. We challeng e EPA to provide the specific criteria by which they judge such measurements to be “adequate.”

EPA reports the results of the ambient ve rsus personal ozone correlations by Sarnat et al. in susceptible groups as “mixe d.” This is clearly not suppor ted 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 ar ea, 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 R 2 = 0.01, t value = 1.21, winter R 2 = 0.00, t value = 0.03). The authors concluded:

Ambient concentrations of gaseous pollutants cannot be considered as surrogates for their respective pers onal 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 ar ea including 20 healthy senior subjects and 23 school ch ildren. In winter, the large ma jority (over 95%) of the personal ozone samples were below the limit of detecti on (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 pers onal-ambient correlations greater than 0.8, the other 13 subjects had essentially ze ro 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 ambien t ozone and personal PM 2.5 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 oz one] may be better surrogates of personal PM 2.5 exposures (especially personal exposures to PM 2.5 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 surroga te 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 concentra tions were measured in 10 non-smoking senior adults living in Steubenville, Ohio. Again, th e 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 c onditions, the slope of the O 3 association (0.18) was small, suggesting on ly minor changes in exposure associated with a reasonable change in outdoor concentrations.” (Sarnat et al. 2006, at 652)

• “The low slopes and R 2 values suggest that ambient gas

concentrations are not suitable proxies of their respective personal exposure in time-series h ealth studies.” (Sarnat et al. 2006 at 653).

• “The results suggest that time-seri es health studies based on 24-hr ambient concentrations may not be able to identify the effects of gases on health, and be tter exposure surroga tes 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) (citati ons omitted). It is very difficult to understand how, from these data an d conclusions combined with th e 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 expect ed to occur. Further,

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

ambient monitor measurements can be used to iden tify 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 re ported in these studies are due to ozone exposure alone, or, to ascertain the c oncentration 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 ev aluate the personal to ambient ozone exposure relationship in healthy, elderly, and certain poten tially susceptible subgr oups. EPA should also

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

summarized as follows:

1) There is a very poor correlation between oz one measurements on ambient monitors and actual ozone exposure as measur ed from personal monitors;

2) The very poor correlation observed for individua ls for daily measurements also translates into a poor correlation across time;

3) The correlation is lower for cer tain potentially susceptible groups such as COPD patients and the elderly who spend little or no time outdoors;

4) Measurements on ambient monitors are ther efore a very poor surrogate for personal exposure in ozone time-series and panel studies; and

5) Ambient ozone measurements are a bette r surrogate for personal exposure to PM 2.5 than personal exposure to ozone, raising the conc ern that ozone time-series and panel study results are seriously confounded by exposure to PM 2.5

.

Overall, the EPA assertion that ozone measurements on ambient monitors are an adequate surrogate for personal oz one exposure in time se ries 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 signi ficant amount of time outdoors ( e.g. , hikers, outdoor workers) that employed personal monitoring. These studie s, however, reflect only a relatively smallExxon Mobil Corporation Comments - 20 portion of the population in cluded 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 individu als in the study were still exposed to multiple pollutants, which somehow must be unraveled through vari ous statistical analys es. 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 th at the exposure error in epidemiology studies (implying all epidemiology studies on air polluta nts) underestimates the individual exposure, thereby resulting in risk estimates that are bi ased downwards. (72 Fed. Reg. at 37,838). In arriving at this conclusion, EPA ignores the fi ndings by Brauer et al . (2002), who carefully

examined this issue in a paper entitled “Exposure Misc lassification and Threshold Concentrations in Time Series Analyses of Air Po llution Health Effects.” As noted in this paper, for pollutants with poor personal- ambient co rrelations (ozone was given as the primary example), it is not possible to accurately as sess concentration response relationships and thresholds in observational air pollution studies. Since ambient ozone measurements are a better surrogate for personal exposure to PM 2.5 than personal exposure to oz one, and the large majority

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

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

of PM 2.5

.

Some of the studies that EPA cites to support this unproven assertion ( e.g., Zeger et al. 2000) relate to exposure to PM 2.5 rather than ozone. Since the ambient to personal correlation is higher for ambient PM 2.5 and very low for ozone, exposur e misclassification studies on PM 2.5 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 polluta nt which demonstrates a very poor correlation between personal and ambient exposure. EPA s hould also delete the unsupported claim that the exposure error in ozone observational studies resu lts in an underestimate of individual exposure

and an “attenuation” of risks in ozone obser vational studies. As discussed above, these statements lack scientific support..

It is worthwhile to point ou t that one of the primary re asons for the poor correlation between ambient and personal ozone exposure is that ozone penetrates indoors is degraded on surfaces. The low indoor ozone concentrations, combin ed 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 Countin g” 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 0 3 mortality associations do not appear to be substantially changed in multipollutant models, including PM 10 and PM 2.5 .” 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 cons ideration of ozone and various fo rms of PM in multi-pollutant models. In reality, there are very few time-se ries or other observational studies that have

included PM 2.5 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 PM 2.5 because there were no routine daily PM 2.5 data available in the NMMAPS database. Adjustment for fine

PM using PM 2.5 annual data , as attempted by Bell et al. provides no real adjustment for the potential confounding effects of PM 2.5 in acute time series mortality studies. Using an annual average fails to capture the daily and seasonal fluctuations in both PM 2.5 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 a ny size fraction of PM. In that study, the authors “found that

associations between summer oz one 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 PM 2.5 in order to reduce the risk associated with acute and chronic cardiopulmonary mortality. As discussed above, it is well known that ambient levels of

PM 2.5 are highly correlated with ambient ozone. Th erefore, there is a very high likelihood that EPA is double-counting acute mortality risks for ozone and PM 2.5 – a pollutant that EPA separately regulates to redu ce 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, PM 10 and PM 2.5 are separate criteria pollutants with separate NAAQS and control strate gies. In discussing PM, EPA should indicate clearly what size fraction of PM they are referenc ing. The proposal should also be revised to note that the large majority of observational epidemiology studies that have been conducted, including the studies EP A considers “key studies”, have not addressed the question of confounding by PM 2.5

.

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 ep idemiology 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 newExxon 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 thes e studies cannot be used to sup port a revision of the standard.

In their previous review, EPA i ndicated that all the available field or pa nel studies shared

certain deficiencies. These included small numbers of subjects (which re duce statistical power), and the lack of time-activity measurements a nd significant data about individual response and their distribution. Furthermore, EPA stated that the independent effect of ambient ozone, as estimated by statistical models in epidemiologi cal studies, is difficult, at best, to clearly differentiate from those of co-po llutants because ozone may be acti ng only as an indicator of the toxic potency of the ambient mixt ure of pollutants. This, in co mbination with measurement error and uncontrolled associations with other factors, led EPA to the conclusion that these factors complicated the analytical findings about th e relationship among components of an ambient mixture and may not accurately disentangle the e ffects 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 ev en though they are stil l 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 eff ect study selection" in cluding a) selecting studies which report increasing ozone health effects associat ed with higher exposure and ignoring studies which report d ecreasing ozone health effect s 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 stat istical models and analyses wit hout 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 unr ealistic biologic plausibility;

• Reliance on single pollutant model results an d failing to note that no adjustment was made for other pollutants;

• Reliance on results that are not statistically significant;

• Uncertainty introduced by assuming that ambien t monitors provide an adequate surrogate for personal exposure to ozone;

• Variability and uncertainty introduced by usin g 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 st udies in favor of “positive” panel

studies.

The key field studies on asthmatics cited by EPA in their propos ed 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) repor ted 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 th e longitudinal study reported by Schildcrout et al. (2006). This was a study of asthma symptoms and inhale r use in 990 asthmatic children in eight North

American cities. No associa tion between exposure to ozone a nd 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 li mitations 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 st udies cited in the 2007 SP app ears 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 98 th percentile 8-hour maximum ozone levels were at or above 0.084 ppm in all eight cities in this st udy. The significant effects in single pollutant models were morning percent change in PEFR fo r 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 st udy’s overall approach and the methodology and measurement techniques used.

• Multiple lag times were used with no biol ogic justification. For an incidence of ≥ a 10 percent decline in PEFR, the authors repor t that associations for ozone were not statistically significant for 1, 2, 3, 5, or 6 day lags, but were signifi cant 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 biologica lly plausible. The results at 4 days also appear to drive the 1-5 days results. Picking one day amongs t the various lags used suggests lag mining and increases the likelihood that a positive effe ct was the result of chance alone. Instead of making note of the lack of associations at biologically pl ausible lag times, such as day 0 or 1, the authors instead focus on the resu lts at 4-day lag, and attempt to develop a biologic explanation to support it.

• Symptom score results were sign ificant for lag days 2, 4 and average lag of 1-4 days, but the authors focus on the single result at lag da y 4, ignoring the results at lag day 1 which was not statistically significant but more biolog ically 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 re duced and non-significant. Use of ambient monitors as a surrogate for personal expos ure, 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 SO 2 , NO 2 , PM 10 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 NO 2 in this study.

• While the authors suggest ozone showed st ronger 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 measur es 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 un likely to be due to ozone. Daily medication use may attenuate the association in the even ing, but outdoor activity would increase dose

and PEFR decline. Without information on these confounding variables, the authors’ explanation is speculative and lack plausibi lity. Furthermore, there is essentially no

correlation between ambient oz one and indoor ozone. The PEFR changes only occurredExxon 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 ch ange in PEFR and the 10 percent or greater decline to show significance on the same lag da ys. 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 bi ologically implausible lag times.

• Independent research results suggest that the PEFR and symptom score results are

unreliable because of recordi ng errors and potential “manuf acturing” of data. Kamps et
al . (2001) compared actual results from an electr onic peak flow meter with results from a self-recorded diary in a group of 40 asth matic children 5-16 years old. Among these affluent children only about 50 percent of the re sults 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 asthma tic children in the same age range, 7-14 years of age. This indicates the incorrect data entries coul d be off by about 50 percent or more. About 20 percent appear to be invented entries (PEF R value in written diary but no entry in the electronic recording). Becau se this study was hospital-based, with a wellmotivated, well-informed affluent population w ith 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 s uggest the PEFR results in Mortimer et al. (2002) are unreliable and the error rate is much larger than the effect measur e 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 po llution mixture. Reasons why such interpretations cannot be made include the following point s: 1) there are no significant associations between symptoms and ozone in multi -pollutant models; 2) the ozone associations observed in the single pollutant m odels 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 Scie nce Assessment for Ox ides of Nitrogen Health Criteria (August, 2007), EPA di smissed the results of Mortimer et al. (2002), which reported no effects for NO 2 . 2007 Integrated NOx Science Assessment at 3-16. EPA also rejected the results of eight ot her studies that employed self-a dministered 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 andExxon Mobil Corporation Comments - 26 Silverman, 2001). This may help explai n why, in contrast to studies with supervised measurements, none of the nine studies using home peak flow measurements reported any significant associations with ambient NO 2

. 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-adm inistered PEFR when the results report no association (NO 2 ), 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 PM 2.5 and ozone on respiratory symptoms and medication

use in children with asthma in Southern Ne w England. According to the EPA’s McCluney Memoranda, the 4 th highest ozone level in this area was 0.102 ppm. Gent et al. (2003) report that in asthmatics using mainte nance medication, a same-day, 8- hour ozone concentration of 63 ppb or higher was associated with a 30 percent increase in chest ti ghtness. 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 statistic ally 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 we re 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 PM 2.5 and medication non-users) only reported results for 1-hour O 3 exposures. The only co nsistent and significant associations were for chest tightness and SOB (to lesser extent) with significant associations in both single and co-pollu tant 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 bronchodilato r use and no associations among asthmatic children not using medication (non-users).

There are several con cerns with this study.

• The study did not control for relative humid ity. Independent studies, including the study by Ross et al. (2002) listed by EPA as a key study, ha ve 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 aExxon 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 le vels 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 indivi duals in the study is unknown and exposure misclassification is a pparent in this study. This makes it impossible to determine if effects are occurri ng 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 conf irm 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 confir m or validate the symptom rate) and provides some evidence that if the symptom associatio ns are correct the symptoms are not severe enough to seek relief.

• It is not clear why there were no e ffects observed among as thmatics not using

maintenance medication.

• There is no mention of a standardized questionnaire for assessing symptoms. A standardized questionnaire is essential to pr ovide assurance that th e 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 questi ons about the significance of the effect

measures.

Overall, because of the w eaknesses this study provides, it cannot be relied upon to support an independent eff ect of ozone on symptoms in asthmatic children.

Korrick et al. (1998 )

Korrick et al. (1998) evaluated the effects of ozone, PM 2.5 and strong ae rosol acidity on the pulmonary function of adult hikers in th e Mt. Washington area. EPA indicates the 4 th highest maximum ozone during the period of st udy 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, hist ory of physician-diagnosed asthma, severe wheeze symptoms over carrying a backpack, reaching the summit and mean ambient temperature during pre-hi ke and post-hike spirometry.

There are several concerns w ith the results of this study.

1 L. McCluney August 23, 2006 Memorandum, Development of descriptive statis tics 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 regr ession, and logistic regression.) This raises the question of multiple comparisons. To minimize the po ssibility of reporting findings that are due to chance alone, for this large number of compar isons, 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 FEV 1 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 FEV 1 reduction is only 0.5 percent, which is well below accepted cr iteria for biological significance.

• When adjustment for PM 2.5 and aerosol acidity were included, the pulmonary function changes attributed to ozone were not statis tically 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 PM 2.5 and ozone on the pulmonary effect s of hikers in the Great Smoky

Mountain National Park. The number of i ndividuals 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 comparab le 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 eleva tion level to which the hi kers climbed was also greater (1,538 versus 620 feet). In both st udies, the level of PM 2.5 was 15 ug/m 3

. Girardot et al. (2006) reported no statistically signif icant responses in pulmonary function associated with ozone exposure.

There is another way to view the on e-pollutant data results by Korrick et al. that offers an

alternate conclusion. An alternat ive analysis used in setting oc cupational exposure levels shows that the slope of the exposure response functio n 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 signi ficantly negative slope could be ve ry 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 d ecline of -5% or -10% is considered, consistent with American Thoracic Society’s guidelines for a clinic ally 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 He alth Effects From Exposure to Ozone at

or Below the Current Standard.

A. The evidence regarding the associatio n between ambient ozone exposure and respiratory hospital admissions has no t changed significan tly since the 1997

review.

The potential health effect relationship be tween ambient ozone and hospital admissions and emergency room visits was identified in the es tablishment of the existin g 8-hour standard. In the 1996 CD, EPA concluded that there was strong evidence that ambient oz one exposure can cause significant exacerbations of pre-existing di sease in the general pub lic (1996 CD at 7-191). In the 1996 SP, EPA noted that a number of ep idemiological studies have shown a consistent relationship between ambient exposure and acut e respiratory morbidity in the population (1996 SP at 40). Further, EPA noted that ozone air pollution can acc ount for a portion of summertime hospital admissions and emergency room visits for respiratory causes in asth matic individuals, as well as the general population. Id.

In 1996, EPA used concentration response func tions (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 fi nal rule, EPA indicated that the Administrator considered the results of the exposure and risk analyses, and key obser vations 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 st andard that would be requisite to protect public health with an adequate margin of safe ty. (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 vari ous respiratory hospitalization outcomes, when focusing particularly on results from warm seas on 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 Detr oit). 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 reducti ons in health risks associated with given reductions in ozone as a percentage of the baseline incidence. Where possible, EPA used county-specific mortality in cidence for the year 200 2 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 estimat ed 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 discu ssed 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 st andard. As discussed below, this important change appears arbitrary because it la cks adequate scientific support.

Because EPA concluded in 1996 that there was strong evidence that ozone exposure is associated with respiratory hos pital admissions, the new epidemio logy information included in this review does not significan tly alter the evidence for revisi ng 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. Re g. at 37,842). It is interesting to note that many of the studies ci ted 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 c onclude 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 th eir 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 con cerns 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 an alyses without corr espondingly adjusting the significance level;

• focusing on the single highe st result from amongst a se ries 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 unr ealistic biologic plausibility;

• relying on single pollutant m odel 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 admission s 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 asso ciation between oz one and hospital

admissions. Linn et al. (2000) note that their findings are supported by a timeExxon Mobil Corporation Comments - 31 series study of asthma admissions, which reported positive asso ciations 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 eval uating the effects of PM 2.5 air pollution. As a result, ozone was only included superficia lly as a co-pollutant. The study serves as an example to illustrate that the risk estimates in time-series

studies are in fact not ro bust to changes in various changes in the underlying timeseries statistical model. This study, al so 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 devel oping a statistical model that adequately accounts for meteorological factors in th e 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 a nd 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 admissi ons 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 be tween ambient carbon monoxide, nitrogen dioxide, PM 10 , and ozone, and hospital admissions for cardiopulmonary illnesses in metropolitan Los Angeles. Regressions were performed fo r 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 aut hors, ozone associations with hospital admissions were either less than zero (n egatively associated with ozone) or slightly positive but otherwise not statistically significant. Therefore, in their risk assessment, EPA failed to consider the negative coefficients and us ed the positive coefficients that failed to reach statistical significance. It is important to note that this study was co nducted in Los Angeles, which has some of the highest ozone levels report ed 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 stat istically significant asso ciations (Nauenberg et al. 1999).

Ito et al. (2003):

Ito et al. (2003) evaluated the associat ion between PM components (PM 10, PM 2.5 , PM 2.5-

10, sulfate, and H+) with daily mortality and morbidity in Detroit, Michigan. Levels of gaseousExxon 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, ge nerally, both the GAMs with stringent convergence criteria and GL Ms [Note: Needs definition.] resulted in smaller estimated relative risk than those reported in the original study. Further, sensitivity analyses using various weather models and de grees of freedom (df) of time trend smoothing

indicate that the extent of difference in RR esti mates 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 part icular, those at biologically plausi ble 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 betw een ozone and hospital admissions.

Schwartz et al. 1996:

Schwartz et al. (2006) provides a singl e estimate of hospital admissions in Cleveland associated with ambient ozone, PM, and sulf ur dioxide of 1.09, 1.12, and 1.24, respectively, for each 100 micrograms/m 3 increase in the pollutant . The publication by Schw artz et al. (1996) is actually a review paper on time-se ries methodologies. The pape r serves to illustrate the significant bias embedded in the c hoice 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, incl uding 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 prov ide the “correct” amount of control. However, the criteria for providing

the correct amount of control have not been de fined, and remain a recognized and significant problem in time-series anal ysis (HEI 2003). Schwartz et al. provide only their single recommended model and results without any info rmation on how alternative methods to adjust for seasonal, day-of-the-week, and weather factors may have influe nced the risk coefficients. Also, it is important to note th at this paper was published prio r 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 conv ergence criteria. Potential problems concerning use of the appropriate default convergence crit eria and time-varying smoothing functions that

have influenced the results of ma ny time-series data sets and studi es have not been explored in

this data set.

Burnett et al. (1997) :

Burnett et al. conducted a time-series study investig ating respiratory hospital admissions and air pollution in 16 Canadian cities for 10 years from April 1981 through 1991. 2 EPA reports the range of 4 th highest maximum ozone concentrations in these cities as 0.035-0.138 ppm. Ozone was the pollutant of interest with adjustments for SO 2 , NO 2 , CO, soiling index (a surrogate for PM) and dew point te mperature. The strongest associations identified were with

2 McCluney Memorandum indicates 4 th 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 fr om 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 result s were presented only for maximum hourly concentration measured on the day before admissi on (lag 1). For the co-pollutants the strongest associations were with lag 0, wh ich was the lag period used to control for potential confounding from pollutants. There were no associations with SO 2 and NO 2 . Soiling index was only

available for 11 cities so these co-variables were not included in adjust ments. Adjustments for temperature removed associations with ozone in two cities (Montreal, Vancouver). Results were presented for a 30 ppb increment in ozone, whic h is the difference between 95th percentile and the mean. Overall, the model shows a 3 percen t 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 st atistically significant

association between ozone and re spiratory diseases severe enough to require hosp italization at low concentrations in diverse climates and air po llution profiles (across th e 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 discu ssed 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 oz one are very small from an epidemiologic perspective and may be the result of unc ontrollable confounding bias. For instance,

while no association was observed for the wi nter, the positive asso ciation observed in spring were (RR=1.04), summer (1.05) and fa ll (1.03) with both spring and summer statistically significant (C I = 1.01-1.07 and 1.03-1.07 and 0.9 98-1.06, respectively). The RR for winter was 0.99 (0.96-1.03). These findings bring in to question the concept of “no threshold” for acute ozone mortality. Ho wever, fall and winter are similar in some respects. They have higher daily admission rates (16.3 and 17.1 per 10 6 compared to 11.1 for summer), similar 95th percentile ( 38 and 42 ppb) and mean ozone (21 and 26 ppb), respectively. In fact, ju st looking at the seasonal da ta and not the statistics, suggests no real differences in risk estim ates by season even though there are clear differences in ozone concentrations between spring/summer and fall/winter.

• Correlations of air pollutants and temperatur e 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 a nd 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 a ssociations between oz one and respiratory hospitalizations were reduced to non-signifi cance 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. Th e model results seem so mewhat fragile, for

when Montreal and Vancouver are removed from the model the RR are generally increased for most cities. Why would remo val of two out of 16 cities affect the

associations with ozone in the ot her 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 no t 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 significan t 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 auto correlation control methods and was conducted over a much shorter time period th an the other study. EPA conclude d that the sensitivity of the association reported in the one positive study to statistical modeling methods and to ozone concentration levels needed further investig ation. (1996 CD at 7-16 1). 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 repor ted Los Angeles in the study by Kinney and Ozkaynak (1991)), and daily mortality has been s uggested, the strength of any such association

remained unclear at that time of the 1 997 review. ( see 1996 CD at 7-161, and 1996 SP at 41-42). Furthermore, EPA indicated that while epidemio logy 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 pollu tants (see 1996 SP at 45)).

Since the last review, a number of additiona l time-series studies on acute mortality have been conducted. According to EPA, some of th e 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-se ries studies are now av ailable, 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 O 3 exposure directly or indi rectly 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 fo r this effect, acute mortality is assumed to be occurring at any ozone concentrati on 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 epid emiology evidence since 199 7, but instead on EPA’s willingness to base causal inferences (or ra ther hypotheses) on observational epidemiology studies without additional significant eviden ce, including strong ev idence 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 i ndividual cities, and the fa ct that the results for many of the individual cities did no t reach statistical significance. Ta ble 2 illustrates this point. The estimated percentage increas e 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 ranki ngs of the 19 cities (Spearman ra nk correlation coefficient 0.12).

More importantly, because the meta-analyses approach assumes homo geneity in the data from across the cities, the high va riability results in an underestim ate of the confid ence interval, or uncertainty, in the risk estimat es. This error in turn produces an overestimate of the statistical significance of the estimated risks. Abandoni ng the assumption of ho mogeneity would likely result in an increase in the variability and the re sulting confidence intervals. This in turn would reduce the statistical significan ce 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 m easured different outcomes and should not be expected to have equa l estimates, they are based on the same underlying data from NMMAPS

and should be of a similar or der 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 tw o measures is 0.12. After removing the three points at the far right of the plot , the rank correlation is still a n on-statistically significant 0.29.

Similarly, in Bell et al. (2005), the reported results for the 95 cities for the estimated percentage increase in the CVDR ESP 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 correspondi ng 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 ev en 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 Percen t 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 coho rt 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 inconsis tency of this result with the results reported

in the time-series studies.

EPA should develop a more scientifically bala nced interpretation of the entire evidence using the Hill criteria, as discussed below a nd summarized in Table 3. The following discussion focuses on causality issues related to acute mo rtality. However, many of the general concerns raised are equally applicable to evidence from ec ological studies evaluating morbidity effects.

1. Strength of Associations.

The Hill causal criter ia 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 be tween exposed and non-exposed, the more likely the association is causa l. More import antly, the effects of expos ure should be greaterExxon 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 epidemiol ogy is that relative risks >1.5-2 fold are necessary to suggest causal associ ation. 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 a ssociations can be seen between mort ality and respiratory morbidity and short-term exposure to ozone, even when consid ering 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 st ates that “the strength of association refers to the magnitude of the association and its stat istical 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 incons istent 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 st atistical power of eff ect 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 st rength of association and should be not presented in a discussi on on the strength of association.

EPA’s presents a contrary and incorrect vi ew, as presented in the proposed rule; EPA

should remove the discussions on robustness and c onsistency from the propos ed rule’s section on strength of associations. The final rule shou ld include a proper disc ussion of robustness and consistency and place these criteria in th e context of the H ill 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 le ss 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, co mplete 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 “publi cation bias” as well as other biases. The Bell study shows that adjustments for publication bi as 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 w ould 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. Fo r 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 reduc ed the effect estimate to ab out 1.004 or 1.003 based on the modelExxon 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 estima te to about 1.004. Adjustments for other biases such as publication bias, a different weather mode l, 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 mode l and publication bias are considered, the

associations become even weaker. It is reasonabl e 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 reasonab le to assume that ep idemiology 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 robust ness 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 depe ndent on sample size. The 2006 CD mentions statistical significance and precision regarding st rength of epidemiological evidence. (2006 CD at 7-3). But the magnitude of the effect estimat e is independent of statistical significance, and both significance and sample size are more appropria tely considered as a separate guideline for evaluating results.

Similarly, the statistical power of an epid emiology study, such as the ozone mortality studies can be somewhat misleading. If the samp le 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 near ly the same as the risk estimate. This is the case in the 95-city study where th e 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 exac tness of the data.

EPA incorrectly considers the mortality esti mates to be robust. The Agency defines robustness as stability in effect estimates ev aluating the impact of alternative models, model specifications for temporal trends and meteorol ogical 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 serv e as valid surrogate measures for aggregate personal exposure in time-series st udies. 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 a nd meteorological factors are critical, confounding for seasonal variability is “controll ed effectively by stratifying analyses by season.” (2006 CD at 7-24). Finally, EPA also believes that assess ment 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 ve ry low correlation between ambi ent and personal ozone exposure,

and the correlation varies across cities. For ex ample, 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 i nvalidates EPA’s key assumption that ambient measurements are a valid surrogate for aggreg ate 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 im portant 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 statis tical 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.” (H ill 1965). The more important que stion is the “fare,” including

evaluation of hidden uncertainties of measurement error, confounding, bias etc. Statistical precision (small p-value or narrow confidence inte rval) should not be equated with validity.

On the other hand, EPA ignores statistical sign ificance 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 comple tely ignores the results of studies reporting negative coefficients.

Hidden uncertainties include such things as confoundi ng 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 not es the high correlations of h eat and ozone in the summer

which makes it difficult to attr ibute individual effect s 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 differe nt 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 ri sks as were used to estimate PM risks. According to Ito, “adjustment for weather ma y not be appropriate because of the higher correlation of ozone with temperature than th e correlation of PM with temperature.” (Ito et al. 2005 at 446). Models with smoothe rs fit the data bette r but have greater concurvity so “modelExxon 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 fo r selecting the appropriate m odel or amount of smoothing to adjust for weather (HEI, 2003). Ito et al. (2005) confirms this, noti ng 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 uncerta inties 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 m odels may ascribe some of the real pollution effects to weather” (Ito et al. (2005) at 455). Therefore model unc ertainties should be taken into

account.

Goodman (2005) underscored the im portance of publication bias when he noted that risk estimates from single-city studies are biased up ward 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 singl e-city combined results relative to multi-city studies such as NMMAPS (Goodman 2005). This fu rther indicates the pres ence of “publication

bias” Bell et al. 2005). In general, the ozone meta-analy ses have limited usefulness or ability to inform because of differences in analytical methods and because most studies have not adequately addressed influential factors (~90% ar e 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 estimate s by drawing atte ntion to the “markedly different estimates” in the three ci ties analyzed by differe nt authors. (Ito et al. (2005) at 447). In Amsterdam, London and Santiago th e 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 pollutant s. EPA is incorrect for the following reasons:

First, very few of the existing time-se ries studies for ozone have included PM 2.5 as a potential confounder. Most of the existing studi es have evaluated potential confounding effects of “PM” using PM 10. It is well known that a much hi gher 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 PM 2.5 than personal exposure to ozone. Levy et al. (2005) one of the few authors attempting to evaluate potential confounding by PM 2.5 , indicated that much more work is needed to explore potential c onfounding of the ozone mortality relationship by

PM 2.5

.

One of the key studies selected by EPA fo r their mortality risk assessment, Hueng et al. (2004), observed significant confoun ding of the ozone mortality relationship when co-pollutantsExxon Mobil Corporation Comments - 41 such as NO 2 , PM 10 , SO 2 were included. In many cities, when these co-pollutants were included in the statistical model, ozone mortality coeffici ents were reduced to non-statistically significant levels. Thus, while the time-series studies indi cate possible small mortality signal air pollution, it is impossible to determine whic h component of air pollution is mo st responsible for this signal. In fact, based on these studies, one could legitimat ely conclude that much of the acute mortality

risk attributed to ozone is due to PM 2.5 or other pollutants such as NO 2 or SO 2 . At a minimum,

the Hill causal criteria for ade quate assessment of potential co nfounders 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 re mains a major confounder.

In our view, the results of th e recent meta-analyses have confirmed the important effect

of model selection in the results of ozone time-se ries 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 provi de evidence of disturbingly la rge publication bias and model selection bias” (Rochester Report 2007 at 43).

Several investigators have s hown that the choice of the degree of smoothing produces significantly different results. T hus 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-t o-city variations (difference between Detroit and St. Louis for example was 3.4 pe rcent) that are due in part to model choice, such as controlling for air conditioning. Model un certainties, such as these, could make 2-fold differences in risk estimates. According to th e 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 fo r 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 sm oothing term. According to the 2003 HEI review: “The best method for selecting the appropriat e degree of smoothing n eeded 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 se nse, is arbitrary. This uncertainty, however, must be considered in determining robustness.

As mentioned above, another pr oblem 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 grea test on hot, humid days. Ambient ozone concentrations are higher than personal exposures because peopl e spend most of their timeExxon Mobil Corporation Comments - 42 indoors (and in air conditioning on hot, humid days). Accordi ng 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 correla tion 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 eff ect 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 di fferences “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, ther e are no criteria for how confounders, such as temperature and weather, will be addressed. As a result, m odel selection becomes arbitrary despite its potential impact on the results. Fo r example, temporal tren ds and weather can have important effects on health. If there is no objec tive statistical test to determine whether these factors have been adequately cont rolled, there is no clear way to a ssure that the effect measured is due to ozone or a confounding bias. In the words of the 2003 HEI revi ew, it has been shown:

that for any continuous vari able, 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 im possible to adjust for tempor al trends without external information on the appropriate degr ees of freedom. This problem is one of the more serious difficulties in specifying the appropriate model. Th e lack of clear criteria for controlling for such an important confounder means that EPA cannot conc lude 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 th e magnitude of the effect estimates is relatively consistent across the results of recently published st udies 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, pla ces, circumstances and times. ( 72 Fed. Reg. at 37,840). EPA also

states that “consideration of c onsistency or heterogeneity of e ffects is appropria tely understood as an evaluation of the similarity or general conc ordance 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 ev idence 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 degr ee of heterogeneity for cities reported by di fferent 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 opposit e results was report ed in the original NMMAPS analyses. Therefore, the results of the NMMAPS anal yses are internally inconsistent.

Our view on the lack of consistency is shar ed 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 sc rutiny 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 heter ogeneity 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 de gree of heterogeneity ac ross 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 infl uence of model choice on effect estimates by drawing attention to the “markedly different estimate s” in the three cities analyzed by different authors. In Amst erdam, London and Santiago, the asso ciations were positive for one set of authors and negative for the other set of au thors. 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 mo rtality (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 rank ings among the 19 cities would be much closer than they are (the rank correlation is 0.12). Th e 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 m odels to produce the a ssociation. (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 bi as.” 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 si gn and magnitude of the signal. (Goodman et al. (2005) at 431). Thus, a consistent finding of pos itive associations may be due to a consistentExxon 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 insignific ant without reporting the results, presumably because “such findings may be less likely to be published.”

Furthermore, while EPA makes the point th at mostly positive studies with the same magnitude of effect estimate provide consistenc y, many of the positive coe fficients 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) hete rogeneity in effect estimates from the 48 cities they selected for their meta -analysis and that 19 per cent were negative.

The importance of the inconsistency is stresse d 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 associ ation between ozone and mortalit y, 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 diffe rent authors get similar results) fails to meet the criterion for consistency as differe nt authors get different results. The evidence is suggestive of a lack of consistency, which adds to the weight of evidence against a causa l association. Stated another way, repeatability, a tene t 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 deve lop 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 mo st 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 tim e of death on the day of death an d 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 mu ltiple 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 beenreported.” (at 442). Similarly, Goodman (2005) found that studies that reported only same day lags were approxi mately 50 percent higher thanExxon 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 tim es 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 st udies. 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 tim es in their evidence based evaluation of the ozone health effects, part icularly for morbidity health effects.

While EPA indicates that 0 a nd 1 day lags are most plausi ble, the Agency appears to ignore this important point in deciding to use distri buted lags out to 7 days in their assessment.

This undermines the value and credib ility of the risk assessment.

In developing its risk estimates, EPA appear s 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 hi gher effect estimates. EPA fails to provide a biological or scientific justif ication for this approach.

In the 2007 SP and risk assessment, EPA justifie s 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 Go odman (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 sing le-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 th e “best” model if that can be defined, but rather on the larg est positive association.

EPA’s selection of the largest positive associ ation amongst the various lag times used in ecological studies, and reliance on longer lag times can be attributed to th e 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 toxican t. 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 cardiovasc ular effects of ozone in an attempt to justify their conclusions fr om epidemiology studies on acute mortality. For example, in his comments on Chapter 8 of the Criteria Document (F eb. 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 ozoneExxon Mobil Corporation Comments - 46 mechanistically induces health effects is important, integration should

not be forced when the data are inade quate. In my view, this is the case with regard to the potential mechan isms 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 m echanisms 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 th e growing body of evidence of cardiovascular

effects from clinical and toxi cology studies that support the epidemiol ogy evidence, and the statements concerning the biological plausi bility of the epidemiology findings, should be removed from this proposal. Fu rther, the statements concerning how the clinical data support the array of longer lag times EPA uses in their ri sk assessment based on ecological studies (72 Fed. Reg. at 37,826) should also be removed. The only la g times that have biologi c plausibility fall in the range of no more than 1 day.

8. Concentration-Response Relati onships and Potential Thresholds.

On the important topic of whether a potentia l 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 eff ect can be found in the

clinical studies which are less vulnerable to mo del 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 an d toxicology studies. Fo r 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 h ealth effect endpoint, pr esumably related to a pulmonary mechanism of toxic action, below 50 ppb and down to “polic y 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 mortal ity below the range of 60-80 ppb.

Evidence of a potential threshold can also be se en 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 a nd toxicology studies.

In most of the time-series litera ture, much stronger associations ( i.e., steeper slopes of the concentration-response curves) in summer are obs erved when ozone levels are higher than in winter when ozone is lower; in most cities ther e was no association in the winter. For example, Levy (2005) reported an estimate of 0.43% increase in mortality per 10 ug/m 3 increase in 1-hour

ozone versus -0.02% in winter. Ambient ozone concentr ations 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 wint er concentrations is suggestive of a threshold. The general lack of association of ozone with mortality in the winter season byExxon 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 observ ed in summer ha s little to due with ozone exposure but rather is primarily due to high temper atures that are well known to cause mortality, and the inability of ozone time se ries 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 thes e studies. As noted in the a bove comments, ambient ozone measurements do not provide a va lid surrogate for aggregate pers onal 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 ecol ogic studies. EPA seems to be confusing the concept “it is not possible to determine threshol ds” 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 signifi cant 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 existe nce 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 incl uding asthmatics, persons with reactive airway disease, cardiovascular disease and obstructive airway di sease, have been exposed to ozone concentrations of 80 ppb or higher with no or only transient ch anges in lung function

health effects and little or no indi cation of cardiac hea lth effects. ( See 1996 CD, Table 7-2). Ozone is a pulmonary irritant and exposures pr oduce irritant health effects at much lower concentrations than those which could produce d eath. 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 backgro und 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) less er health effects for a unit exposur e 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. Furthe r, they report a higher relative risk per unit

ozone above the threshold. There are a numbe r of concerns worth noting in the findings by Kim

et al. (2004). First, higher effect es timates were reported in winter versus summer. This finding is opposite that normally observed. Second, Kim et al. did not consider PM 2.5 as a potential confounder. Rather, their analysis wa s based on consideration of only PM 10 which is known to

have a much lower correlation with ozone. Ther efore, much of the risk attributed to ozone, either above or below the “threshold”, c ould have been due to confounding with PM 2.5 . Finally their conclusion that a linear model may underes timate risks does not consider actual populationExxon Mobil Corporation Comments - 48 exposure, i.e., the number of people expos ed 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 fr om 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 knowl edge about potential underlying mechanisms remains limited and suggest a need for further experimental support.” (2 006 CD at 8-51). EPA should clearly note this lack of mechanistic supp ort in the proposed rule. EPA’s discussion of a biological plausibility is furthe r 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 cardiopulmonar y mortality from exposure to PM does not impact the signal for ozone. (72 Fed. Reg. at 3 7,839). 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 cardiopulm onary mortality alleged to be caused by PM. However, later on EPA asserts th at both ozone and PM cardiopulm onary 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 no t 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 elde rly would be most affected, in fact, the mortality association for the very elderly (>75 years) was not incr eased relative to the general population, or relative to younger age groups (<65 years). Rather , inexplicably, the 65-74 old age group had the highest mo rtality 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 la yer of uncertainty. Similarly, while ozone is a respiratory toxicant, the reported associ ations for respirat ory mortality are lower than those for cardiopulmonary mortality and generally not statistically significant . From a coherence perspective, this is counter to common knowle dge, practice, and observations, where one would expect agreement between the morbidity and mort ality findings. The strength of the ecological morbidity associations is about the same as t hose for mortality, arguing against coherence, which

should find that the incidences of morbidit y are greater than that for mortality.

The many uncertainties associated with EPA’s discussion of biologica l plausibility were recognized by CASAC. As discussed further in these comments, CASAC members Balmes andExxon Mobil Corporation Comments - 49 Gong, are correct in suggesting that EPA has overs tated the evidence on car diac effects of ozone (see discussion in # 7 above on la g structures). EPA should clear ly state that the available

evidence does not indicate cardiac-related mechan isms of action for ozone. Overall, EPA should conclude, based on the available evidence, that ther e is a lack of biological plausibility for the acute ozone mortality hypothesis, particularly at low levels.

Finally, EPA states that ozone acts not onl y 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 Oxid es 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 observationa l epidemiology studies. In th eir draft Integrated Science Assessment (ISA) of Oxides of Nitrogen, EPA indicat es “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 polluta nts” (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 up on 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 inconsis tency of this result with the results reported

in the time-series studies. A more balanced inte rpretation 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 weighi ng of the evidence should concl ude 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, NO 2 , and SO 2 . 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 th e Mechanisms Underlying Respiratory Morbidity

Provide Little New Information Re levant to What Was Known in 1997.

In the proposed rule, EPA make s several statements related to the mechanisms by which ozone produces short-term effects of ozone in he althy 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 pointsExxon 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 interpre ting the new

data that need to be corrected.

In the 2007 proposed rule, for example, EP A 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 chroni c 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 biol ogically plausible basis for considering the possibility that repeated inflam mation 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 conclude s that people with preexisting pulmonary disease are likely to be among those at increased risk from O 3 exposure.” (Fed. Reg. at 37,826) (emphasis added). This is not a sign ificant change from the 1997 review, where EPA stated that “[t]he major reason individua ls with preexisting respiratory disease [( e.g., those with COPD, ischemic heart disease)] may be of con cern is the likelihood that decrements in lung function or exercise capacity may ha ve 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 asthmatic s may exhibit large lung function decrements in response to O 3 exposure than healthy controls ” and “asthmatics present a diffe rential response profile for cellular, molecular, and biochemical parameters .” (72 Fed. Reg. at 37,826). However, in 1996, EPA made similar points, indicating that asthma tic subjects typically have increased airway responsiveness at baseline, and differences in baseline bronchial responsiveness between healthy

individuals and sensitiv e asthmatics that may be as much as 100-fold (1996 SP at 35). Furthermore, in 1996, EPA indicated that the clin ical 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 acut e effects of ozone inhalation .” (1996 CD at 7-25) (emphasis added).

Concerning asthma development, in 2007, EPA c oncluded that in cont rast to supportive evidence from chronic animal studies, epid emiologic studies of inflammation, new asthma development, and long-term function declines re main inconclusive. (2006 CD at 7-134). In 1996, EPA concluded that while ozone has not b een shown to cause asthma, the available evidence suggests that ozone may exacerba te 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 f ound to be particularly susceptible to O 3 effects on lungExxon Mobil Corporation Comments - 52 function and generally have grea ter lung function responses than older people.” (Fed. Reg. at 37,826). However, in 1996, EPA stated that “childr en 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 (citi ng 1996 CD, section 9.6)). Given the similarity of the points and conclusion s on asthma and potential mechanisms of action, EPA cannot report this information as new. EPA s hould 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 discussi on 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 clin ical studies in drawing conclusions regarding the appropriate lag time for po tential health effects from exposure

to ozone at lower levels.

In the proposed rule, EPA stat es that clinical studies th at 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 studi es of potentially su sceptible individuals such as those with asthma, COPD and hypert ension, only minimal transient lung function

decrements and inflammation are observed at 0. 08 ppm ozone. In contra st, EPA concludes fromExxon Mobil Corporation Comments - 53 time-series studies that any concentration of ozon e, 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 unlik ely to be responsible for the more serious morbidity effects ( e.g., hospital admissions), at leas t 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 provi de 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 in formation 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 plac es 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 downpl aying 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 acti on to explain positive morbidity and mortality associations at background levels in obser vational 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 st udies reporting effects at low background ozone levels. At higher levels (80 ppb and greater) where respiratory eff ects 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 he alth effects from ozone exposure is

new.

The current EPA proposal incorrectly incl udes various statements related to the mechanisms by which ozone produces short-term eff ects 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 broa d conclusions concerning the potential susceptibility of certain population subgroups to oz one 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 conc lusions were known to EPA and the scientific community at the time of the la st 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. Spec ific 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 st ructure and lung function and may lead to chroni c respiratory diseases such as fibrosis and emphysema.” This statement is very similar to the conclu sion drawn in 1997, when EPA concluded that aExxon 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 informa tion provided at least a biologically plausible basis for considering the possibi lity that repeated inflamma tion associated with exposure over a lifetime may result in sufficient damage to the respiratory tissues such that individual later in life may experi ence 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 ma jor 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 ha ve 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 decr ements in response to ozone exposure than health controls ” and “asthmatics present a di fferential response profile for cellular molecular, and biochemical parame ters.” However, in the 1997,review, EPA indicated that asthmatic subject s typically have increased airw ay responsiveness at baseline,

and differences in baseline bronchial res ponsiveness between healthy individuals and sensitive asthmatics may be as much as 100-fold (CD at 35). Furthermore, in 1996, EPA

indicated that the clin ical studies comparing the pulmona ry function responses following ozone exposure in asthmatic and nonasthmatic subjects sugge sted 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 c ontrast to supportive evidence from chronic animal studies, epidemiologic studies of infla mmation, new asthma development, and long-term function declines remain inconclusive (CD at 7-1 34). 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 As sociations 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 beginn ing 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 ex isting data are inconclusive or indicate no significant cardiovascular related findings.

In 1996, EPA reported that several animal st udies reported dramatic cardiovascular effects from ozone exposure (1 ppm for 3 hour s, or about 10 times the ambient standard) including a 53 percent d ecrease in heart rate and 29 percen t decrease in blood pressure. (1996 CD at 6-121). Uchiyama et al. (1986). Arrhythmias, including atroventricular block and premature atrial contractions, were also reporte d 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 th e 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 e xposure and cardiac physiologic health effect endpoints. EPA concludes that these data prov ide new information regarding mechanisms of action and the biological plausibi lity of acute mortality associa tions 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 cardi ovascular-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 fiel d 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 concl uded that ozone exposure induced no statistically significant changes in ca rdiac index, ventricular performance, pulmonary artery pressure, pulmonary and systemic vascul ar resistances, ECG, serum cardiac enzymes, plasma catecholamines and artrial na triuretic factor. Overall, Gong et al. (1998), abstract,

concluded that the results “did not indicat e major acute cardiovascular effects of O 3 either on the hypertensive or the control subjec ts.” 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 effe ct endpoints examined in this study, one change could easily be due to chance. Further, EPA CA SAC 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 (s ee 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 PM 2.5 and ozone on vascular function. The primary measure of vascular effect s used was the diameter of the brachial artery diameter (BAD). Healthy subjects were exposed for two hours to either filtered air or 150 ug/m 3

PM 2.5 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 repo rted. Several points limit the in terpretation and usefulness of this study. First, it is not possible to attribute the effects to PM or ozone. We note that the levels

of PM 2.5 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 e nd 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 re sults, the findings should be cons idered of borderl ine statistical significance. Finally, the clinical significance of the findings is que stionable. 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, EP A 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 eval uate the potential affect of PM 2.5 air pollution on

heart rate and heart rate variab ility in 21 53-87 year old active Boston residents. Continuous

measurement of PM 2.5 and PM 10 was provided via TEOM from a monitoring station 6 km (3.5 miles) from where the clinical data was co llected. Ambient levels of ozone (1-hr), NO 2 and SO 2 were taken from a compliance monitoring statio n 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 perfor med during a protocol involving five minutes rest, five minutes standing, five minutes of exercise outdoors, fi ve minutes recovery, and three minutes slow breathing. According to the invest igators, the slow breathing portion enabled them

to evaluate whether the effect s of pollution on heart rate variability (HRV-rMSSD, mean of the squared differences between adjacent normal RR inte rvals) were independent of respiratory rate.

Various different fixed effects st atistical 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 asso ciation was observed between 1- hour ozone and HRV whereas for model 3 the association was not statistically si gnificant. 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 pollu tion 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 dir ection of change is also opposite that observed in cardi ac rehabilitation patients admi nistered beta blockers.

• Ozone was only considered superfluously as a potential co-pollutant to PM 2.5 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 stat istically significant. The au thors 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, he alth 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 re ported during low breathing, the finding could easily be spurious and due to a lack of cont rol for heart rate factors.

• The small change in HRV lacks clinical si gnificance. As documen ted 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-defi brillators living in eas tern Massachusetts. The air pollutants evaluated included PM 10 , PM 2.5 , black carbon, CO, SO 2 , NO 2 , and ozone. The authors report mean ozone le vel as 18 ppb, with a maximum re ported as 59 ppb and 95% of 35 ppb. The air monitoring was performed in south Boston, with the expectation of SO 2 and NO 2 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 provi ded for using this range of lag times for all pollutants. Even with this range of lag time s, no statistically significant associations were reported for ozone for any of the lag times. As a result, this study pr ovides 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 st udy was to evaluate if elevat ed concentrations of ambient PM have been associated with increased hospi tal admissions for cardiovascular disease using a case cross-over design. From January to Ma y 1995, levels of gaseous pollutants, including

ozone were measured. The mean 1-hour ozone level reported in th e study was 19 ppb, with a 95% value of 46 ppb. A positive an d statistically significant asso ciation between levels of PM 2.5 2- and 24-hours prior to myocardi al 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 car diac 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 studie s on the potential cardiovascular effects of ozone have been publishe d since the last review, and that the findings, considering all the data, remain inconclusive. Th is is the only conclusion that can be justified given that two key studies, involvi ng human clinical assessments, indicate no consistent evidence or pattern of cardiovascular effects.

XI. EPA’s Risk Assessment is Flawed and Ov erestimates 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 asth matic children ages 0-12 who use maintenance medication. (2007 SP at 5-51). These es timates are based on the study by Gent et al. (2003). The key concerns with this study, and the EPA risk assessment, ar e 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 like ly risk is on the order

of 100-fold.

Many of the concerns with EPA’s risk a ssessment 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 measure d. 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 individua ls in the study is unknown. The resulting massive exposure mi sclassification 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 ot her 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 pr ovide assurance that th e symptom response is always the same over time and the between-individual interpretations are similar.

• In two pollutant models with PM 2.5 , 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 breat h, and bronchodilator use were also not statistically significant. With the excepti on of chest tightness, the only statistically significant associations were re ported 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 in crease 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 bronchodilato r use provides an objective estimate of effect. The lack of

association for bronchodilator use tends to disc redit 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 s eek relief, even in children presumed to have severe asthma.

• Positive associations were only reported in children using asthma maintenance

medication. No statistic ally significant associations were reporte d 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 th at those using asthma medication have more serious conditions. However, it is not cer tain that use of maintenance medication provides a clear distinction in di sease severity as asserted by the authors. Other factors,

such as access to health care, ability to pay for me dication, individual physician prescription tendencies, are also likely im portant 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 singl e ecological epidemiology study by Gent et al. (2003). Given the well known methodological problems with ecological air pollutionExxon 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 ri sk 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 co efficients 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 statistic ally 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 asse ssment, where EPA presents the incidence of chest tightness and wheeze at alternate st andards of 74 and 64 ppb, even though in the underlying data used for the risk assessment, a statistically signifi cant increase in these symptoms was not reported at those levels.

• EPA assumes that all 200,000 asthmatic childre n in Boston have severe asthma and are potentially at risk to ozone e xposure. In reality, there is ma rked difference in the severity of asthma across the population and only a sma ller 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), ther eby 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.

Total 1 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 ad missions provides no new information

that was not available in the 1997 review.

In the current risk assessme nt of hospital admissions, EPA us ed 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 us ed 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 ha ve never been corrected for either use of the default convergence criteria or altern ate smoothing functions . The study raises questions concerning the dependent nature of time-series model building and difficulties in providing the “adequate” amount of contro l for seasonal, day-of-the-week and weather

factors.

• The study by Linn et al. (2000) did not report statistically significa nt 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 respirat ory illnesses. Nonetheless, EPA used the positive, non-statistically significant risk coeffici ents in their risk assessment for hospital

admissions.

• The study by Ito et al. (2003) focused primarily on effect s of PM with little data for ozone. Further, the study was c onducted 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 string ent criteria were used with GAM or when GLM was used. Further, the co efficients were also reduced when various weather smoothers were employed. The lim ited results for ozone were inconsistent, varying from significant to non-significant, de pending 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 fo r an association between ozone and hospital admissions.

A summary of EPA’s 1997 and 2006 risk estim ates 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-CHE M. This effectiv ely increases the 2006

estimates.

• The estimates in 1997 are presented as incidence per 10 6 people per 100 ppb ozone. The 2006 estimates are presented as incidence per 10 5 of relevant population for ozone levels above background, in years 2004 and 2002. This ch ange in metric makes it difficult to compare risk results from 1997 to 2007.

• In 2006, EPA also considered the baseline in cidence of morbidity in various regions,

which was not done in 1997.Exxon Mobil Corporation Comments - 63 • In 1997, EPA did not appear to estimate ri sks in cities where the underlying risk

coefficients were not statisti cally significant. In 2006, EPA used risk coefficients from

studies that were not stat istically significant.

• In both 2006 and 1996, EPA used risk coeffici ents from non-biologic ally plausible lag times ( e.g., as long as 3-4 days).

• For the 1997 risk assessment, EPA consider ed all seasons. In 2006, EPA focused on seasonal (April to September) estimates, an a ssumption that should increase the resulting risk estimate. This decision appears wit hout explanation and reason that we can

understand.

• In both 1997 and 2006, EPA used risk coeffici ents 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 increase d. While the incidences in both 1997 and 2006 are generally low, the range of figur es 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 s howing greater health e ffects, 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 cons ideration during the process to evaluate the support for a standard "the attainment and maintena nce 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), mostof the estimates at biologically plausible lags (day 0 or 1) are negative, whereas thos e at less biologically plausible lags are positive. This illustrates the tenuou s and heterogeneous (inconsistent) nature of morbidity estimates, such as hospital admissions, de rived 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 studi es EPA used (see data from EPA tables 4-12 and D-13 below). The higher coeffici ents 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

O 3 /day/10 6 persons Relative Risk of 100 ppb ozone

1-hr max

NY City, NY a Thurston, 1992 All 1.4 (+/- 0.5) 1.14 (1.06-1.22)

Buffalo, NY a Thurston, 1992 All 3.1 (+/- 1.6) 1.25 (1.04-1.46)

Ontario, Canada a Burnett et al, 1994 All 1.4 (+/- 0.3) 1.10 (1.06-1.14)

Toronto, Canada a Thurston 1994 All 2.1 1.4 (+/- 0.8) 1.36 (1.13-1.59)

Montreal, Canada b Delfino, 1994 Pneumonia in elderly 1.4 (+/- 0.5) 1.22 (1.09—1.35)

Birmingham, AL c Schwartz, 1994a COPD in elderly 0.73 (+/- 0.54) 1.11 (0.97-1.26)

Birmingham, Al c Schwartz, 1994a Pneumonia in elderly 0.83 (+/- 0.33) 1.13 (0.92-1.39)

Detroit, MI c Schwartz, 1994b COPD in elderly 0.82 (+/- 0.26) 1.22 (1.12-1.35)

Detroit, MI c Schwartz, 1994b Pneumonia in elderly 0.90 (+/- 0.41) 1.25 (1.07-1.45)

Minneapolis, MN c Schwartz, 1994b Pneumonia in elderly 0.41 (+/- 0.19) 1.117 (1.03-1.39)

Minneapolis, MN c 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 st atistically significant in the underlying study.Exxon Mobil Corporation Comments - 65 C. EPA’s risk assessment of acute ozone mo rtality systematically overestimates

risks.

As discussed above, EPA has failed to esta blish a causal relationship between ambient exposure to ozone and acute mortality. There ar e serious concerns with the accuracy of the underlying concentration response functions and shap e of these functions at low concentrations. Moreover, the evidence supporting causality for acute mortality (clinical, toxicological, and epidemiology) is so weak and spurious, the hea lth effect endpoint should not be considered in making a decision on whether to revi se the standard. These concer ns 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 N AAQS. These key points are supported by the June 5, 2006 letter from CASAC at 3, as well as the findi ngs in the Rochester Report from review of

the health science on ozon e 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 es timate reductions in acute mortality associated ozone reductions above background levels in 12 ur ban areas. EPA employs several significant and often scientifically unsuppor table decisions and assumptions , all of which result in increasing the risk estimates. These a ssumptions are summarized briefly below.

1. Study selection - EPA’s decision to use result s 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 mo rtality 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 va rious European cities. But, EPA has made the scientifically questionable decision to ignor e these results in estimating the risk from mortality.

2. Study selection - Selective reliance on usually high coef ficients 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 Assessmen t, even though the co efficients 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 st udies which report no association.

3. Study selection Use of single model results (ozone onl y) when results from co-pollutant

models are available . For example, in the study by Ito et al. (2003), including PM 10 reduced the risks attributed to ozone. However, EPA placed more emphasis on the coefficients that were not adjusted for PM 10

.

4. Use of statistically insignificant studies - Use of positive but not st atistically significant

risk estimates and selective use of Bayesian shrinkage estimates . EPA uses Bayesian

estimates from Bell et al. (1995) for which the large major ity of cities (89/95) are positive but not statistically significant. Further, it is important to note that before the BayesianExxon Mobil Corporation Comments - 66 transformation was performed, between a third a nd half of the coefficients were negative, even without adjustment for PM 10 . 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 ex trapolate acute mortality to PRB levels of 15- 35 ppb . Even though EPA uses a sigmoidal con centration response function to assess pulmonary effects, EPA defaults to a more c onservative, 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 e xpressed “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 Re port at 49) Further, as described above, there are serious concerns with using am bient monitors to assess personal ozone exposure. Due to this serious problem, it is not possible to assess concentration response functions or thresholds. Also, the extens ive human clinical data for ozone provide evidence to strongly support th e use of a threshold-based ap proach to risk assessment.

5. Choosing to use a new ozone concen tration background definition and approach . As discussed further in our comments, correcti on of this assumption alone could eliminate over 95 percent of the risk re duction potential of revising th e 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 studi es and risk coefficients, combined with their no-threshold approach to risk assessmen t, new and unsupported assumption for ozone background levels, and its flawed roll back procedure, act together to significantly inflate the risk estimates by several orders of magnitude.

D. EPA fails to adequately address signific ant uncertainties in their assessment of acute mortality risks.

EPA claims that they have addressed the sour ces of uncertainty in its risk assessment of acute ozone mortality because statistical uncer tainty surrounding the Concentration-Response Function (CRF) is reflected in the confidence interval s. This is not correct. Contrary to EPA’s claim, the Agency has failed to consider se veral 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 onsample size. The increase in sample size (from combining many studies in the metaanalyses) so increased the statistical power of the studies that even minuscule effectExxon Mobil Corporation Comments - 67 estimates became statistically significant a nd were allowed to overshadow the more important hidden uncertainties. Hidden uncerta inties, such as the choice of statistical model, are a more important source of uncerta inty and have a significant impact on the effect estimates, generally to further re duce 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 consid er this uncertainty at all in the risk assessm ent. In the risk assessment, EPA assumes 100% probability th at 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 possibili ty 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 threshol d or non-linear effects . In the 2006 CD and 2007 SP, EPA indicates there is also uncertainty concer ning 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 availabl e epidemiologic eviden ce 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 a ll in their risk asse ssment (2007 Ozone Risk Assessment). To capture the full range of uncertainties for the existence of a possible threshold, EPA must consider alternate ri sk assessment approaches that assume a threshold exists. We suggest evaluating cu t 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 uncer tainties is to ignore the uncertainty by making a choosing instead to use a conservativ e assumption without proof that will lead to ever-increasing overestimates of risk. These uncertainties in clude (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 prefer ence for the results from single versus 2- or multipollutant time-series models even though: (1 ) the exposure data clearly demonstrate the potential for signifi cant confounding by PM 2.5 ; (2) few time-series st udies have evaluated confounding by PM 2.5 but rather focus on PM 10 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, NO 2 , and SO 2.

• 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 thes e studies could be in cluded in the riskExxon 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 positi ve, non-statistically sign ificant risk coefficients . Similarly, EPA has not addressed the uncertainty a ssociated with using a positive but nonstatistically significant risk coefficient for single cities within a multi-city study. These results could also be considered as repr esenting zero risk for purposes of risk

characterization. EPA has also not addresse d the issue of using results of seemingly high-end risk coefficients such as those from the cities in th e 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 signifi cantly increase or lowe r the risk reduction potential of revising the stan dard. Significant uncertainty exists over average and maxima ozone background levels. The proposal did not clearly explai n and establish the basis for the particular choice made in the proposal.

The overall uncertainty associated with selecti ng 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 al one renders the risk estimates as not useful for purposes of defining the NAAQS. The actual numbe rs 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 estim ate or Bell’s 2004 Bayesian shrinkage estimate. However, at a proposed lower standard of 74 ppb/4 th 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 al ternate standard of 74 ppb/4 th highest. The pattern is repeated for Chi cago, where the estimated risk ranges from 33- 314 at the existing standard, depe nding 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 th e most stringent alternate NAAQS (0.064 ppm/4 th
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 al low presenting such data to the resolution of two significant figures.Exxon Mobil Corporation Comments - 69 Overall, given the underlying unc ertainties in the concentra tion response functions and the shape of these functions at low concentrati ons, the incremental changes in health effects endpoints at alternate standards cannot be viewed as statical ly different or biologically meaningful. Hence, these estimates are not usef ul 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 an alysis 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 wh ere 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 chang es in air quality will affect health, and finally uncertainty about the economic and social value of the change in health outcomes. In form al 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 a nd 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 th e limited uncertainty addressed by EPA in the standard deviation. Uncertainty goes beyond the statistical confidence in tervals that EPA now reports. The OMB Circular calls upon EPA to c onduct a “formal probabilis tic analysis of the

relevant uncertainties.” (Id.)

The most efficient way to accomplish this goal would be to c onduct 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 formallyExxon Mobil Corporation Comments - 70 quantifies these uncertainties. To illu strate the usefulness and feasibility of a more rigorous treatment of uncertainty, we have prepared a partial integrated uncertainty analys is 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 pres ent 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 cumu lative impact they may have on our understanding of the risk.

The National Academy of Scie nces (NAS) has also recomme nded that EPA conduct risk assessments that directly account, quantitatively, for important sour ces of uncertainty. However, as stated in the Rochester Report, the risk as sessment EPA has failed to account, quantitatively for the important sources of uncertainty. Acco rding to the Rochester group, the sources of uncertainty that EPA has not included in any of th e risk estimate ranges that it provides includes: (1) uncertainty related to ep idemiology 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; an d (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 ca usal 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 sugge stive. (72 Fed. Reg. at 37862). However, these

differences are not reflected in any way, quantitatively, in the num eric 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 ri sk estimates. In fact, we find the reverse is the case, i.e., EPA places more importance on the acute mortality estim ates, 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 Nati onal 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 ava ilable 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 Nati onal Academy of Sciences (NAS), have promoted the use of quantitative approaches to addressing uncertainty in risk analysis for both hazard identification and exposure analys is. In its 1994 publication, Science and Judgment in Risk

Assessment , the NAS strongly recommended that EPA co nduct 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 believ es 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 pot entially 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 deci sion-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 uncerta in 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 ar e if the uncertainty (and hence the degree to which the risk estimat e 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 distri bution 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, th e 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 source s of uncertainty into its primary health benefits analyses, EPA shoul d 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 par ticularly 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 fo r 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 co mmittee 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 scientificExxon Mobil Corporation Comments - 73 data—such as the degree of complia nce 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 da ta 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 th at 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 polluta nts, 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 uncertain ties combine and the exte nt to which they affect estimates of risk at the current standard and the potential be nefits of tighteni ng the standard.

XIII. EPA’s Decision to Lower the Ozone Backgrou nd Levels From Levels Justified in the 1997 Review is Incorrect and Not Scientifically Supportable.

In the 1997 final ozone rule, EPA estimate d, 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 rega rding 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 am bient concentrations of O 3 from background sources, an 8–hour standard set at a 0.07 ppm level would be closer to peak background levels that infrequen tly occur in some areas due to nonanthropogenic sources of O 3 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-relevan t 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 defi nition 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 om its 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 ce ssation of human activities including the practiceExxon Mobil Corporation Comments - 74 of growing crops and raising animals in the Unit ed 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 em issions and ceasing human activities in these countries is not a po ssible 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 gr eatly due to a number of factors, including changes in biogenic emissions, te mperature, stratospheric ozone intrusions and international transport. In previous ozone reviews, EP A evaluated background con centrations of ozone primarily based on measured observations of oz one 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 evaluate d 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 mode led estimates of the extremes of PRB must be considered. In previous ozone reviews, bot h 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 O 3 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, th e 2006 CD discusses estimates of background

concentrations from both observations and mode ls, but the 2007 SP relies almost entirely on one global chemical trans port modeling study to model an es timated mean background. The CD, however, notes several important limitations of that study and th e need for additional work to

evaluate PRB with an ensemble of models comparing the mode l results with observations.

The large grids in the global model mix air pa rcels of different composition and origin in an unrealistic way, severely limiting its ability to accurately simulate local photochemical activity, intercontinental transport, and the imp act 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 va riability due to processe s that are not captured in the global models. Until th is is done, EPA should use a ra nge of background estimates from

observations. The failure of the final 2007 SP to provide in formation 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, co rrectly includes emission transport from sources outside North America. However, ne w data suggest that th e GOES-CHEM model may significantly underestimate the cont ribution of emissions from outsi de of North America. As a result, the model may significantly un der predict ozone background levels.

The GEOS-CHEM model provides estimates of ozone background concentr ations 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 i nventory and record keep ing. The magnitude of this increase since 2000, however, suggests that the GEOS-CHEM model may significantly

underestimate the level of NOx emissions and oz one attributable to sources outside North

America.

Tables 7-10 summarize changes from the 2000 (Trace-P) and 2006 (INTEX-B) emissions

inventories.

Table 7

S ummary 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 a nd 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 emission s in that year, pending re-calculation with actual activity statistics when they become available. C ontacts: 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 21 st 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 projec tions indicate that surface ozone levels are expected to “rise significantly throughout the 21 st Century.” (at 3437) with half the rise due to increases in

methane emissions and the other half due to incr eases in NOx emissions. She further notes that any warming of temperatures could make this c ontribution to background levels even higher. She notes that the projections exceed internati onally accepted environm ental criteria, ranging around 40 to 50 ppb. Vingarzan concludes:

Given that these values represent b ackground 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 a ll the more valid given that the IPCC projections are based on 2001 before the rapid increase in NOx emissions fr om Asia were recorded. The rapid increases suggest that background levels in North Amer ica may have already risen significantly from

emissions outside North American and that the GEOS-CHEM model ha s significantly under predicted their contribution.Exxon Mobil Corporation Comments - 77 XIV. EPA’s Assumed Level of Policy-Relevan t 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 an alysis 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 le vels (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 significan tly lowered its estimate of background ozone levels from .040 ppm used in 1997 to hourly valu es 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 propos ed 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 ther e are often limited to those in the

PRB definition.

(2007 SP at 2-54).

The maximum monthly diurnal av erage at Trinidad Head was .050 ppm. The differences in

ozone values between the GEOS-CHEM model for se lected 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 oz one standard is signifi cantly affected by the

choice of ozone level to be used in determini ng ozone background levels . In testimony before EPA’s CASAC on February 28, 2007, Dr. Allen S. Le fohn (A.S.L. & Associates) illustrated the

differences in absolute incidences of ozone non-accidental mortality between EPA’s proposed PRB using GEOS-CHEM and th e 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 tes timony reveals that increasing the PRB by just 5 ppb resulted in significant reductions in the es timates for absolute incidences of ozone nonaccidental mortality:

For the “84/4” [0.084 ppm ozone le vel with 4 exceedances], “74/4” [0.074 ppm ozone level with 4 excee dances], 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 O 3 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, a nd also demonstrated that if EPA had used a higher summer estimate of av erage ozone background levels of 0.04 ppm (which

was used in EPA’s 1997 review rather than th e lower value that EPA is using in the 2007 review), the estimated number of potential deaths and other hea lth effects projected at just attaining the current standard for the city of H ouston and Detroit would fall by over 95 percent. This sensitivity in the estimated risk w ill apply to tighter standards as well.

B. An Analysis of the Distribution of Ri sks 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 larg e portion of the risks that EPA is calculating is associated with 8-hour pe riods when ozone is less than 0.070 ppm. An analysis of the risk in

seven U.S. cities show that le ss 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 O 3 exposures andExxon Mobil Corporation Comments - 80 the occurrence of the health effects examined, such that the assessment

continues to indicate reductions in O 3 -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 O 3 exposures becomes increasingly uncertain at lower levels of exposure. Given all the information available to him at this time, the Administrator judges that the increasi ng 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 analys is 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 mortalit y in these cities can be attributed to ozone at ozone levels of pot ential concern. This suggests that attaining the current standard is amply pr otective 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 ba ckground is a demonstration that the bulk of estimated mortality comes from days with ozone c oncentrations that are very low. This is not biologically plausible.

Given all the issues noted above with EP A’s policy relevant background levels, the Agency should re-evaluat e its ozone background le vel 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 impor tance of this issue a nd 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 Unrealis tic 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 unr ealistic, and cannot be defended either as being “policy relevant” or as a “background” level. Given that EPA is not suggesting the elimination of all anthropomorphi c emissions from within the United States, including agricultural related emissions, the st andard 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 anthropo morphic 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 Studi es 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 poli cy of selectively using single-pollutant, singlecity results reporting the highest relative risk, while ignoring othe r results from the same city

which are lower or non-stat istically significant. EP A also uses Bayesian adjusted estimates for single cities in their risk assessment. While ma ny of these adjusted estimates were positive, the vast majority (89/95) were not statistically significant followi ng adjustment. Also, 1/3-1/2 of the coefficients for these cities were negati ve before the empirica l 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 fo r each of the cities, desp ite the fact that the ignored estimates are preferred from a scien tific viewpoint because they have employed

additional statistical treatments to address conf ounders 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 th e 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 ma rgin of safety. EPA’s task is to establish

standards that are “n either more nor less string ent than necessary” to prot ect public health. This does not mean zero-risk, but rather it means that th e standard must be set at a level that reduces risk sufficiently so as to protect public heal th 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 Admini strator to set standards that are “requisite to protect the public hea lth’ 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 protectin g 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 su ch 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 unde r Section 109 is to esta blish standards that are neither more nor less stringe nt than necessary for these pur poses. The Supreme Court has agreed with EPA that “requisite” under Secti on 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 w ould be more than necessary to pr otect 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 th ese 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 sta ndard was promulgated. Given EPA’s data showing limited risks from exposure to th e current standard and EPA’s an alysis of the studies, which shows greater uncertainty, not less, that the observed effect s are caused by ozone, EPA should

not lower the standard. As EPA st ates in the preamble, its task under Section 109 is “to establish

standards that are neither more nor less stringent than necess ary.” (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 change s in current policy that are not justified by the rulemaking record”). Given that EPA’s estimate of health risks has declined a nd our understanding of the uncertainty surrounding the result s of the health studies has in creased, 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 ha ve difficulty in complying with the current

standard within the next decade and invite s comment on page 37881 on whether EPA can count

the health benefits fr om 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 co nsider 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 populat ed 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 lo wering the primary standard may not be achieved. Given the lack of meaningful and discernable benefits fr om lowering the standard, the

Administrator should conclude that the current standard is requisi te to protect public health.Exxon Mobil Corporation Comments - 84 DETAILED COMMENTS REGARDING THE SECONDARY

STANDARD FOR OZONE

Overview

While ExxonMobil supports the long-term deve lopment and applicatio n of a cumulative form for the secondary standard because it is more biologically relevant, EPA lacks sufficient data to promulgate a new standa rd at this time. In addition, the information and analyses presented in the Criteria Document (CD), EP A Staff Paper (SP) and proposed rule do not demonstrate a greater ecological harm at the curren t standard or clear potential benefit from the proposed alternate W126 standard as compared to the current 8-hour standa rd. As a result, EPA has failed to adequately show why the alterna tive proposed standard is requisite to protect

welfare.

I. EPA Has Proposed the Use of an Altern ate Cumulative Seasonal Metric, the W126, Without a Companion Component to Account for Frequency of Ozone Peak

Occurrence.

Vegetation studies indicate that cumulative in dices are more biologically relevant for estimating potential ozone effects on vegetation. Cumulative indices, however, must consider the occurrence of peaks, as da ta indicate plant response to th e 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 NC LAN studies contain numerous hourly values greater than 100 ppb (Lefohn and Fo ley, 1992). Failure to include these values known to be key determinants of plant effects in the exposure-re sponse function is a significant oversight for a proposed national standard. The number of hour ly values greater th an 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 hou r-standard of 80 ppb. Therefore reliance on NCLAN data to support the conclu sion that exposures below an 8- hour standard would result in ozone impact has significant lim itations if the response function fails to consider these peak

concentrations.

A concentration response func tion should be developed that include components for both the cumulative seasonal ozone exposure and fr equency of hourly peak s. As suggested previously, actual exposure-respons e data should be made availa ble in addition to results of regression analysis, to transparen tly 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 th e 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 prot ection than the current 8-hour standard. Despite previous requests, EPA has not provided the concentration-respons e functions for the 8- hour form of the standard. Therefore a compara tive analysis of the rela tive protection affordedExxon Mobil Corporation Comments - 85 by an 8-hour form to that provided by the prop osed W126 form cannot be completed. The exposure assessment provided indicates that th e 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 stan dard would provide less protection. EPA should develop co ncentration 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 in cluded in the analysis. This is the only meaningful way to compare th e level of protection afforded by the different standards.

III. EPA Has Failed to Show That Adverse Ve getation Effects Are Occurring at

Ambient Ozone Levels at the Current Standard.

In the proposed rule, EPA states that its conclusions regarding th e inadequacy of the current standard “are based upon extensive vegetati on effects evidence, in particular field–based

evidence on biomass loss in seedlin gs, saplings and mature trees, and foliar injury incidence ... which demonstrates the occurrence of adverse vege tation effects at ambient levels of recent O 3 air quality, as well as evidence and exposure and risk-based an alyses indicating that adverse effects would be predicted to oc cur under air quality scenarios m eeting the current standard.” (72 Fed. Reg. at 37,798-99).

EPA is incorrect in concluding vegetation imp acts at the current standard. The newer field-based evidence EPA cites for ozone imp acts 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 exposur es provided appear to be su fficiently 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 m eeting the current standard.

A. Key studies cited by EPA fail to show ve getation 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 prov ide evidence of vegetation effects below the current

standard.

King et al. (2005)

King et al. (2005) describes the Free Air CO 2 Enrichment (FACE) study with ozone addition, and provided ozone conc entrations 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 ex ceeded for the ozone levels specified, as would the W126 values. This study does not demonstrate impact from ozone leve ls at or below the

current standard. Gregg et al. (2003)Exxon Mobil Corporation Comments - 86 Gregg et al. (2003) examined plant growth unde r an ambient ozone gradient and performed follow-up OTC exposures. The ambient areas where effects were reported had ozone concentrations that likely exceeded the curren t secondary standard: data for 2000 from the New York state website for two of the study ar eas (New York Botanical Gardens –NYBG and Millbrook) indicate 2000 annual mean ozone and the 4 th highest daily 8-hour ozone averaged over the past 3 years were NYBG - 16 ppb an d 80 ppb, respectively, and Millbrook 26 ppb ( versus 26 – 37 ppb for 1992-1994, the study years) an d 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 rath er as an annual seasonal 12-hour mean ozone. Also, whereas the highest ambient ozone expos ure 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 O 3 are sufficient to pr oduce biomass loss, it

does not address if these ambient levels fa ll 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 concentr ations were: ambient higher ozone sites seasonal sum over 12 hr/day = 47-70 ppm hr (5-43% leaves show injury); FACE expos ures 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); OT C 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 pl ots of elevated ozone, although the

levels in ozone addition treatment s are indicated to be representa tive of curren t conditions in many areas surrounding midwestern cities. The exposures s how episodic total seasonal exposures of 90 ppm-hr. The fi ve clones studied showed signifi cant variability in response to ozone, with one showing increase d growth under elevated ozone. The results of this study support the potential of ozone to impact vege tation, but again the ozone exposure level is sufficiently high to indicate that there were likel y multiple exceedances of the current standard in the studied exposure.

While these studies provide additional suppor t for ozone impact on vegetation, including

observance of ozone effects in fi eld settings without chambers, they do not provide support for the conclusion that ambient levels in complian ce with the current sta ndard would result in significant ozone impact.

B. Newer tree studies also fail to show ad verse vegetation effects below at the

current standard.Exxon Mobil Corporation Comments - 87 EPA indicates that the newer tree studies s upport the use of the existing concentrationresponse relationship based upon open top chambe r (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 stud ies with those from OTC studies is limited. Thus, these studies, while very informative, do not reduce the uncertainties in the OTC concentration-response f unctions. Isebrand et al. 2001, Karnosky et al. 1999 and 2005, and King et al. 2001 and 2005 do not prov ide 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 preven ts a direct comparison.

EPA should develop concentration-response fu nctions based upon the newer data in the same form as the existing ones, to allow dir ect 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 i ndicates 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 support s 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 Ta bles 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 visi ble injury at ambient levels that meet the current secondary standard fail to address po tential 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 mo isture 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 dr y periods in local areas decreasing incidence and severity of visible foliar inju ry (p. 7-61). These same cond itions 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 a dditional protection. EPA should provide the comparable W126 values and compare folia r injury at “non-b ackground” 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 f unction. Rather, EPA indicates new field based studies demonstrate plant growth and visible inju ry 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 informa tion was available to assess the potential need to update the OTC-based C-R (see earlier comme nts). However, as i ndicated earlier, the concentration-response relationships are flawed because they do not consider the frequency of peak occurrence. In ad dition, the exposures regi mes 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 ne wer studies indicate ozone effect s can occur, they do not shed much new light on the concentr ation-response functions.

EPA is proposing values for the secondary standard based upon the OTC concentrationresponse functions, not just using response direc tion 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 ti me, so it cannot be used to support the statement of consistent de leterious effects over time. Morgan et al. provide ranges of ozone impact for ozone concentrations in three average daily concentratio n categories: 30-59 pb, 60-79 ppb, 90-120 ppb. For the highest two categor ies and the upper range of the lowest category, it is likely that there were multip le exceedances of the current 8-hour secondary

standard. EPA should follow its own recommend ation included in footnote number 57 on page 37,889 and develop new concentrati on-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 unav ailable 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 me trics. EPA has failed to conduct a re-evaluation of the studies in order to report re sults in a consistent format.

In addition, EPA cites the recommendati ons 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 thei r basis. In particular, the basis for the recommendation to consider a 2 percent effect le vel 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 th e source of key information on crop and seedlingExxon Mobil Corporation Comments - 89 concentration – response, Lee and Hogsett (1996), is also not available. This document is an EPA report, and its release was re quested 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 co mmon metrics as appropriate, particularly to support the key points of its rulemaki ng. If available, a more detailed report of the consensus workshop should be released. If stud ies to support the recommendations cannot be provided, then the recommendations should be used with great cau tion. EPA should also make the Lee and Hogsett (1996) repor t available to the public.

G. EPA has failed to reduce key uncertaint ies 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 al so indicates that key uncertainties during the last rulemaking included the fact that an asso ciation between the daily maximum 8-hour ozone concentration and plant response had not been sp ecifically 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 pa rt, these EPA concerns du ring the last rulemaking remain the same today.

H. EPA’s exposure and risk-based analysis fa il to show that adverse effects can be expected at the existing standard.

The exposure characterization to support potential adverse eff ects 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 st andard, but exceed the W126. For risk characterization, as indicated earlier, the NC LAN-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 compar ed to biological variability.Exxon Mobil Corporation Comments: Reference 1 LIST OF REFERENCES

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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, 2007Exxon Mobil Corporation Comments ATTACHMENT A



### Some Additional Statistical Analyses of the FEV 1 

### Pulmonary Response Data From the W.C. Adams Data (2006)Exxon Mobil Corporation Comments: A- 1 Some Additional Statistical Analyses of the FEV 1 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 wher e 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, pres ented in randomized order with at least four days between sessions. Response data included se lf-reported symptoms, FVC and FEV 1 measures. The pulmonary measures were performed seven time s 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 O 3 (ppm) Peak O 3 (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 en dpoints (percent changes in FEV 1 , percent changes in FVC, and total symptom score), but only the percent changes in FEV 1 responses are discussed in this report. He analyzed the percent changes in FEV 1 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 chambe r study were replicated.

Based on analyses of the response pattern over the 6.6 hours of experiment ation, the only percent changes in FEV 1 responses that are statistically significant ly 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 indica ted the 0.08 ppm square wa ve and 0.08 ppm triangle wave exposures were different from the fresh air exposure.

The magnitude of the estimated changes for all indi viduals 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 wh ere no pre-determined hypotheses

were made. He concluded that for the percent changes in FEV 1 :

• No changes in hourly readings for Fresh Air (FA)

• The 0.04 ppm triangle exposure wa s not different from FA

• The 0.06 ppm triangle and square wave respons es 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 decrease d from pre-exposure

Plots of the data showing the observed FEV 1 values, and percent change in FEV 1 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 th e response scale is the same for all plots on the page but the scale ch anges from page-to-page.

The analyses in this report explore some diff erent 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 sligh tly 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

FEV 1 and the observed FEV 1 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 tabl e, 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 FEV 1 and the observed FEV 1 value with the pre-exposure response as a co-variate were essentially e quivalent and only the percent change in FEV 1 will be

discussed.

Two statistical requirements for the analysis are that –

1. the random effects are independently and norma lly distributed with mean zero and fixed

co-variance matrixExxon Mobil Corporation Comments: A- 3 2. the subject based errors are independently, id entically and normally distributed with mean

zero and fixed variance

The first requirement can be assessed by examin ing the distribution of the model residuals. A quantile-quantile plot of the residuals is show n in Figure 1 and because the observed residuals are not along the straight line as expected for norm ally distributed residuals , we conclude that the residuals are not normally distribu ted and the observations do not meet the assumptions required for the model. The drooping tail to the left i ndicates several observation s with responses more negative than the model predicted. These points are from subjects whos e percent change in

FEV 1 are seen in the plots to decline in the later time periods.

The second requirement can be approximately a ssessed 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 Anal y si s

Relative Change Analysis Unstructured Covariance Matrix QQ Plot of Residuals

2006 Data Anal y si s

Relative Change Analysis Unstructured Covariance Matrix Residuals by Sex and SubjectResiduals

-0.45 -0.40 -0.35 -0.30 -0.25 -0.20 -0.15 -0.10 -0.05 0.00 0.05 0.10 0.15

Se x a n d Subject I D f

_ C B f

_ D H f

_ H W f

_ J H f

_ K C f

_ K G f

_ K H f

_ K P f

_ K R f

_ L B f

_ L K f

_ M G f

_ M T h f

_ T L f

_ T S m

_ C N m

_ G C m

_ J E m

_ J L

a m

_ J L

o m

_ M A m

_ M L

a m

_ M L

u m

_ M T m

_ R B m

_ R M m

_ R M

c m

_ R V m

_ R Z

- H m

_ T P Figure 1- Quantile-Quantile Plot of Residuals

Figure 2- Box Plot of ResidualsExxon 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 just ification, and was not consider ed further. Second, several transformations were tried. Among them were the Blom transformation to normalized ranks, exponentiation, power transformations and combinati ons of these transforma tions. None of the

reasonable transformations resulte d in normally distributed residua ls. To fix the problem of identically and normally distributed residuals, a correction for heteroscedasticity was applied (Pinheiro and Bates 2002); but, the problem of he teroscedasticity was not resolved. Intermediate analyses under the various transformations and corrections gave results that were essentially

similar to the untransformed and uncorrected analyses. Therefor e, the following analyses are based on the analyses that do not exactly m eet 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 provi des 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 th e statistical assumptions of the analysis.

The findings of the new analyses were that there was a statistically significant difference in the percent changes in FEV 1 responses over time and by dose group . Comparisons of means of the ozone exposed groups against the FA initial read ing, 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 an d 6.6 hours rather than only at 4.6 hours as reported by Adams.

A comparison of the 0.06 and 0.08 protocols agai nst 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 th e variance is not a criterion for the model fit, so it is not always considered a repo rtable statistic. However, it is important to note

that there are other sources of variation in the FEV 1 response other than the ozone exposure, and

that the conclusions of the statis tical analysis are not strong.

The model predicted response for i ndividuals in Figure 3 shows that none of the predicted points shows more than about a 6 percen t decrement and the lower confiden ce 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 du ring the experiment (approximately 35 L/min).

Previous research has shown that moderate exercise at comparab le levels of ozone exposure is associated with greater transient FEV 1 decrements relative to resti ng subjects at the same ozone exposure levels. Therefore, the magnitude of th e decrements observed in these data would not be seen in the total populati on, 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 - TrianglePredicted % Change in FEV1 (L)

-10 -5 0 5

Time Period

123456 Figure 3- Model Predicted Change in FEV 1

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 FEV 1 value with the pre-exposure response as a co-variate indicated differences in exposure group we re statistically significant only at p<0.08 and not statistically significant at the usual 0.05 criterion. The analysis of percent change in FEV 1 indicated differences in exposure group were statistically significant at p<0.01. Both analyses showed a lack of normality in the residuals. As before, transf ormations and alternative analyses were conducted and the residuals remained not normally distributed. These alternative analyses provided approximately the same re sults as the original data, and th e 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 pe rcent change in FEV 1 will be discussed. Table 2 shows the least squares means of the percen t change in FEV 1 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 diff erences in individual subjects.Exxon Mobil Corporation Comments: A- 7 Table 2 Least Squares Means for Percent Change in FEV 1 and Dunnett Adjusted p-values

Protocol Wave Shape Mean O 3 (ppm) LS Mean Percent Change in FEV 1 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 FEV 1 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 experiment ation, the only percent changes in FEV 1 responses that are statistically significantly different from the firs t period FA exposures we re 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 r eadings indicated the 0.0 8 ppm square wave a nd 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, 2007Exxon 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 Simulta neous 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 FEV 1 over six to twelve months: what change is abnormal? J. Occup. Environ. Med. 2004 Jun; 46(6):591-5Exxon Mobil Corporation Comments: A- 9 2006 Data Anal y si s

Relative Change Analysis Unstructured Covariance Matrix QQ Plot of Residuals Addendum to the Statistica l Analyses of the FEV 1 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 anal yses were not normally distributed.

Recall that the normality of the residuals can be examined by looking at the qua ntile-quantile plot with the expectation that the resi duals should lie along a straight line.

Additionally, there is another numerical comparis on for testing normality that will be included

here. The statistical test is calle d the Shapiro-Wilk statistic. For data like those being tested here (n=1080) the Shapiro-Wilk statis tic 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 th ese 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 poi nts that were different from the initial FA

exposure were:Exxon Mobil Corporation Comments: A- 10 0.08 ppm square wave at 6 th period 0.08 ppm triangle wave at 4 th , 5 th and 6 th periods

These results were based on the relative change in FEV 1 from the pre-exposure values.

New Analyses

The new analysis discussed in this addendum used a slightly different stat istical analysis from that in the main report, but used the same data . The data were transf ormed by a transformation called Blom’s Transformation, which is based on th e normalized ranks of the observed data. The analysis was based on the observe d response at each exposure time point with the pre-exposure values as a co-variate (rather th an using the relative change).

The Blom Transformation is a fairly standard, but not particularly we ll-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 FEV 1 rather than the relative change.

The main result is that with th is analysis the residuals are mo re 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 Analysi s Covariance Analysis - Blom Transformed Data Unstructured Covariance Matrix QQ Plot of ResidualsExxon 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 di fferent 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 0.97 4, which is closer to the critical value of 0.996 (but still not normally distributed based on a stric tly 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 Anal y si s Covariance Analysis - Blom Transformed Data - Drop 1 Subject Unstructured Covariance Matrix QQ Plot of ResidualsExxon Mobil Corporation Comments: A- 12 Conclusion

We can do transformations and analyses that ma ke the residuals very much closer to being normally distributed, but the fina l 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 di fferent from the initial FA exposure were:

0.08 ppm square wave at 6 th period 0.08 ppm triangle wave at 4 th , 5 th and 6 th periodsExxon Mobil Corporation Comments: A- 13 

### Plots of Adams 2006 Data, By Sex [Responses Are Observed FEV 1 Data and the Relative Change From Pre-test]Exxon Mobil Corporation Comments: A-14sex=Female Exposure Group=(1) Filtered AirPosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

FEV1 (L)2345Time Period0123456sex=Female Exposure Group=(4) 0.06 ppm - SquarePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

FEV1 (L)2345Time Period0123456sex=Female Exposure Group=(5) 0.06 ppm - TrianglePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

FEV1 (L)2345Time Period0123456sex=Female Exposure Group=(6) 0.04 ppm - TrianglePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

FEV1 (L)2345Time Period0123456sex=Female Exposure Group=(2) 0.08 ppm - SquarePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

FEV1 (L)2345Time Period0123456sex=Female Exposure Group=(3) 0.08 ppm - TrianglePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

FEV1 (L)2345Time Period01234562006FEV1FemalesExxon Mobil Corporation Comments: A-15sex=Male Exposure Group=(1) Filtered AirPosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)23456Time Period0123456sex=Male Exposure Group=(4) 0.06 ppm - SquarePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)23456Time Period0123456sex=Male Exposure Group=(6) 0.04 ppm - TrianglePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)23456Time Period0123456sex=Male Exposure Group=(5) 0.06 ppm - TrianglePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)23456Time Period0123456sex=Male Exposure Group=(3) 0.08 ppm - TrianglePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)23456Time Period0123456sex=Male Exposure Group=(2) 0.08 ppm - SquarePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

FEV1 (L)23456Time Period01234562006FEV1MalesExxon Mobil Corporation Comments: A-16sex=Female Exposure Group=(1) Filtered AirPosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)-30-25-20-15-10-50510Time Period0123456sex=Female Exposure Group=(4) 0.06 ppm - SquarePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)-30-25-20-15-10-50510Time Period0123456sex=Female Exposure Group=(5) 0.06 ppm - TrianglePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)-30-25-20-15-10-50510Time Period0123456sex=Female Exposure Group=(6) 0.04 ppm - TrianglePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)-30-25-20-15-10-50510Time Period0123456sex=Female Exposure Group=(2) 0.08 ppm - SquarePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)-30-25-20-15-10-50510Time Period0123456sex=Female Exposure Group=(3) 0.08 ppm - TrianglePosition:CB DH HW JH KCKG KH KP KR LBLK MG MTh TL TS

Relative Change in FEV1 (%)-30-25-20-15-10-50510Time Period01234562006Relative Change in FEV1FemalesExxon Mobil Corporation Comments: A-17sex=Male Exposure Group=(1) Filtered AirPosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)-45-40-35-30-25-20-15-10-50510Time Period0123456sex=Male Exposure Group=(4) 0.06 ppm - SquarePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)-45-40-35-30-25-20-15-10-50510Time Period0123456sex=Male Exposure Group=(6) 0.04 ppm - TrianglePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)-45-40-35-30-25-20-15-10-50510Time Period0123456sex=Male Exposure Group=(5) 0.06 ppm - TrianglePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)-45-40-35-30-25-20-15-10-50510Time Period0123456sex=Male Exposure Group=(3) 0.08 ppm - TrianglePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)-45-40-35-30-25-20-15-10-50510Time Period0123456sex=Male Exposure Group=(2) 0.08 ppm - SquarePosition:CN GC JE JLa JLoMA MLa MLu MT RBRM RMc RV RZ-H TP

Relative Change in FEV1 (%)-45-40-35-30-25-20-15-10-50510Time Period01234562006Relative Change in FEV1MalesExxon Mobil Corporation Comments ATTACHMENT B



### Critical Evaluation of Additional Fiel d 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 A dditional Field Studies Cite d 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 effect s of ozone and aeroallergens on the respiratory health of 40 mild and severe asthmatic residents in East Moline, Illinois. EPA

indicates the 4 th highest maximum ozone level as 0.077 ppm . The pollutants c onsidered in the study included 8-hour ozone, PM 10 , 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 SO 2 and PM 10 were not included in the ozone pollutant m odels because of their lack of association with symptom sum and PEFR and th e small size of the study population.

There was no apparent associa tion between changes in morni ng PEFR and 8-hour ozone when maximum temperature and grass polle n 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 th e association for morni ng PERF, so with both pollen and spores in the model PEFR wa s 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, polle n and spores. There was a nonsignificant increase in asthma medication per 20 ppb increased in ozone. The association

between 8-hour ozone and evenin g changes in PEFR adjusted fo r pollen and spores showed significant reductions of 3.08 liter/m in at slightly increased.

Analysis : There are several concerns with this study.

• The authors stated that the fact that mo rning 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 th an at night. This does not appear to be an adequate explanation, but is more plausible than the ex planation offered by Mortimer

et al. for why the PEFR changes were in the morn ing but not in the evening, if ozone is a causal agent producing these reductions. In ot her studies, as noted above, the morning PEFR rather than the evening PEFR de monstrated 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 occu rs 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 4 th 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 contri butes to the inconsistency in the results observed. Unless personal exposure is used, se rious exposure misclassification will lead to inconsistent and incoherent results, rende ring the results of oz one 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 PM 10 , which is not as highly correlated with ozone as is PM 2.5. Including PM 2.5 in this study would likely result in a marked reduction of the ri sk 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 a pproximately an order of magnitude higher than ozone). This indicat es 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 th is 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 ab out 2 percent. But what these symptoms are is not reported.

• The magnitude of the reduction in evening PE FR 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 th ese changes are of biological or clinical significance as there was no signifi cant 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 sy mptom sum (or about 8 percent increase).

Delfino et al. (1998)

Description/Results: This is a longitudinal study evaluating the effects of PM 10 and ozone air pollution on symptom severity in pediatric asth matics in the San Diego area. EPA indicates the

4 th 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 statistica lly significant in 2-pollutant models with PM 10 . Most symptomsExxon 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 measur e of effect than the more common use of a dichotomous symptom based on pr esent or absent and without ra ting of severity. The overall

effect on the child was also considered more se nsitive than considera tion of single symptoms.

Analysis: There are a number of comments on this study:

• Ecologic measures of exposure were us ed, 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 comple tely 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 PM 2.5 , obliterated the signal from ozone. Even more

attenuation of risks for ozone would be expected if PM 2.5 , which is highly correlated with ozone, was included in the statis tical model. Effect estimates for various measures of

PM 10 were higher than for 1-hour and 8-hour ozone.

• The method of recording symptoms as sympto m sum appears to be an improvement over the simplistic presence or abse nce of a specific symptom with inclusion of biologically non-significant symptoms.

Brauer et al. (1996) 2

Description/Results: Brauer et al. (1996) evaluated the poten tial lung function (FEV 1 , FEV) effect in berry pickers exposed to ozone. From their air quality statistics, EPA listed the 4 th
highest maximum ozone concentration as 0.04 ppm. In the study itself, ambient ozone measurements were taken from an airport ap proximately 15 km from the study site. An

additional ozone monitor was located at the stud y 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 st udy 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 4 th 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 “ini tial” regressions, 25/52 s ubjects and 31/52 subjects showed a negative association with FEV 1 or FEV, respectively, a nd daily 1-hour ozone. The authors report that afternoon FEV 1 or FVC, and FEV 1 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 func tion level, as well as the morning FEV 1 , 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 FEV 1 (coefficient = 0 ml change per ppb ozone) and a nonsignificant association with FVC (-1 .7 ml per unit ozone).

Analysis : There are several concerns w ith the results of this study.

• There is some evidence of data mining in th e report. The progression of measurements, from “initial” to “main,” raises the question concerning multiple comparisons and analysis and whether or not the s econd set of analys is were planned de novo , or initiated after the first set of analysis indicated non-signifi cant results. In th e discussion section, the authors state that since cross-day ozone le vels were not associated with change in lung function, they investigated other approaches to evalua te 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 FEV 1 and FVC of 4 and 4.8 liters the maximum reductions associated with a 10 ppb change in O 3 is less than 1 percent. With a

coefficient of 0.0 for FEV 1 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 anal yses (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 occupationa l shift studies) is to assess th e change in lung function. In the main analysis of this st udy, cross-day lung function change is not significant for

either FEV 1 or FVC, with coefficients of 0.0 and -1.7 ml associated with ozone in the models also containing the variable s of temperature and date.

• Brauer et al. compared their results with four othe r studies. All us ed change in lung function parameter; Spektor ( 1988) also used evening FEV 1 in addition to change.

• The number of completed acceptable spirometric tests for FEV 1 and FVC are not the same, suggesting there were possible problem s 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 FEV 1 ) 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 morn ing. Loss of data is even greater for assessing FVC change, which need s both morning and afternoon data. About 30 percent of the possible maximum data point s are lost, and there are 20 percent fewer data points for change in FVC compared to change in FEV 1 . If consistent effort is not obtained with consistent coaching, the FEV an d 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 ma neuvers where effort may have not been maximum, which could produce a reduced FEV.

• Methods are incomplete as acceptability and re producibility of the tracings is not defined,

nor selection criteria of results. Thus th e validity of the lung function results is problematic.

• The authors report there was good agreement between the area-wid e and site-specific ozone measurements (R=0.92). However, the means were quite different (40 versus 26 ppb, respectively). In addition, while th e group mean personal exposures indicated reasonable agreement with ambient (mean diff erence 2.5 ppb), the values for individuals indicated significant exposure misclassifica tion 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 sy mptomatic school children in Uniontown, Pennsylvania. EPA

indicates the 4 th 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. Th e 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 meanExxon Mobil Corporation Comments: B- 6 Analysis : There are several concerns with this study.

• When ozone was considered with acid aer osol, the associati on for ozone was not statistically significant.

• The authors suggest the lack of an independe nt effect of ozone in the 4th model (2- pollutant model adjusted for proportion of tim e spent outside) "may be due to the low concentrations of ozone present during the study period." The ma ximum concentration was 87.5 ppb, the mean daily concentration 50 ppb. Given that these values are greater than the 30 ppb increment agai nst which the changes in PE FR are calculated, it would appear the range of ozone concentrations is adequate for assessing an association.

• The percent change is not clinically important a nd it is not clea r it is an adverse effect. An adverse effect might be a reversal of th e normal diurnal varia tion, 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 men tion of modification associated with ozone.

• This study has similar limitations to the other panel studies including no personal measures of exposure. More over, there is a high likelihoo d 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 th e beginning of exposure in the morning. The morning PEFR is presumably rela ted 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 hypothesi zed) 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 ot her field studies of children not cited as key by EPA. A number

of these recent studies are considered the de finitive 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 (FEV 1 ) was observed (Gauderman et al. 2000). Linn et al. (1996) reported no association between respiratory symptoms and ozone exposure in sc hool children in southe rn California. In this study, ozone exposure was assessed usi ng 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 pulmonaryExxon Mobil Corporation Comments: B- 7 function and lung growth in healthy childre n are not convincing. For this reason, EPA removed the quantification of symptoms in h ealthy 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 func tion (PEFR) in women who recently delivered babies. In this study, the relationship between daily changes in 24-hour PM 2.5 , PM 10 , fine sulfates, and strong ac id, and hourly ozone and morni ng 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 re gressed against normalized measurement of both morning and evening PEFR. Essentially at leas t one positive associati on was reported for all pollutants for at least one of the PEFR measurem ent times (morning or evening) and lag times. For ozone, statistically significant associations we re not reported for morning PEFR. Ozone was the only pollutant for which a positive associati on was reported with evening PEFR. At lag 0 and 3 days, but not 1 day lag, sta tistically 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 cumula tive-lag (7.65 l/min d ecrease 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 publicati on. Rather, data are provided for 3-day cumulative lags. The authors use the conventio n 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 diffe rent ways; three were normalized PEFR and were analyzed separately morning and eveni ng. The fourth was the difference between evening and morning performance. The sign ificance of the associ ations with each pollutant is summarized. Lag 0 is used for evening PEFRs and ▲ PEFR, and lag 1 for morning PEFRs.

Delta

Normalization PM 2.5 PM 10 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 0.75 5 0.207 0.244 0.051

▲ PEFR NS NS NS NS NS NS

3 Memorandum indicates 4 th 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 fi ndings 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 signifi cant (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 co ntrol 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 signifi cant 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 categor y (40.3-56.6 ppb 5-day ozone) th e 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 analys is 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-signifi cant 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 a ssociations of ozone with ▲ PEFR, the most appropriate measure for assessing acute changes in PEFR and E-R relationships with exposur e. If the other measures of change in PEFR are used, the decrements at ab out 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 statis tically significant.

The authors themselves note several limitations in cluding 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 furt her studies” would be

beneficial.Exxon Mobil Corporation Comments: B- 9 External evidence of weak associations, very sm all changes, biological imp lausibility with ozone exposure, inconsistent findings, and no associati ons with the PM – AM changes, provide support

for the view that the results on ozon e may be due to random variability.

In addition, personal exposures might be quite differe nt than concentrations gathered at a central

site. PM 2.5 and sulfate were said to adequately repres ent the inside and outside of homes in the region, despite 89 percent of subjects having air conditioning. Ozone wa s 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, ther efore, represent a more susceptible population.

ExxonMobil Biomedical Sciences, Inc. October 9, 2007Exxon 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 Pe ak Expiratory Flow Rate (PEFR)

Kamps et al. (2001) studied the re liability of data from peak fl ow diaries collected from 40 asthmatic children aged 6-15 years. The children were moderately severe asthmatic outpatients. Both patients and parents had received a compre hensive 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 thr ee 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 me ter 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 info rmation) group was told the mete r could record PEFR digitally and more accurately; EI (extended information) gr oup 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 Wri tten 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 th e 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 result s. While children aged 5-10 years could perform reproducible spirometric tests during home mon itoring, there was very wi de variation in the results. Results for younger children were not re producible. Also, a large number of results for

all children did not meet the crite ria 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 FEV 1Exxon Mobil Corporation Comments: C- 2 and FVC. However, the higher level of agreem ent 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 dete rmine 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 wr itten peak flow diaries and therefore producing poten tially unreliable peak flow rates include:

• Neas et al. (1995): 4th and 5th grad e kids; ~3-months (summe r) 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 ar eas >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 asse ssment of risk the ques tion is: At what ozone concentration is there a biologic ally significant reduct ion 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-para metric smoothing regression model is most appropriate and accurate and is the preferred analytical method. This method was used by Korrick et al. (1998) although th e results were not emphasized.

ii) What is the adverse effect level? EPA offered a graded classification for acute

reductions in FEV 1 of mild (<10%), moderate (10-20%) and severe (>20%) (ATS, 2000). ATS (2000) recommended that "r eversible 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 mo st 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 appropr iate way to display the data).

iv) If the data are not graphed, an x% a pproximate change can be estimated by calculating the % drop at different ozon e 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 asso ciation of acute changes in lung function ( e.g., FEV 1 , PEFR) with ozone or any other air pollutant invo lves 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 ad justs 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 diur nal 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 FEV 1

.

• Two potential outcome variables can be useful for assessing an association. Both involve regression analysis of cha nge by exposure. The most common is assessment of decrement in lung function asso ciated with measured exposur e. 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 me thods 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 me dian PEFR.” Presumably this is median PEFR for the entireExxon 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 % chan ge 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 baselin e 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 c oncept 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 me dian since daily median would be based on only two numbers. Use of median PFER incr eases 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 a ssociated with eveni ng PEFR; BS maximum temperature was negatively associated with morning PEFR. So it is problematic to

conclude the association is w ith ozone when it could be due in part or in full to other

factors.

• The source of a 10 percent decline as an adve rse effect is unclear, as definition of an adverse effect is usually based on a decremen t 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 decrem ent in function. Inte rpretation of this outcome variable is problematic.

Ross et al. (2002)

“Each individual's PEFR measurements were st andardized by the indivi dual’s” overall mean PEFR and change was measured as --

[PEFR (morning or evening) – over all mean PEFR / overall mean PEFR]Exxon Mobil Corporation Comments: C- 5 Morning and evening PEFR were presented as ch ange in PEFR (l/min) per inter-quartile ozone range. Ozone exposure consisted of 8-hour averag e daylight concentrati ons (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 dividi ng the child's mean and then multiplying by 300 (which is the overall mean L/min for a ll children). The equa tion appears to be:

[(PEFR (morning or evening) – Me an PEFR) / Mean PEFR] x 300 L/min

Only evening deviations were reported so presumab ly there were no significant associations with night-time ambient ozone concen trations (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 ma ke sense, unless the morning values are not

used in the calculation of overall mean.

• There was a trend for FEV 1 and FVC to increase 0.29 perc ent and 0.43 percent per week. PEFR was highly correlate d (r = 0.71) with FEV 1 , which may explain why adjusted deviation in evening PEFR increased 0.93 L/mi n/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 grea ter 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 underlin e 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 functi on is an inappropriate referent and reduces sensitivity, increases co nfounding, and does not provide guidelines for estimating an adverse effect leve l. This appears to be an ad hoc method not commonly used in similar designs such as shift st udies in studies of workers.Exxon Mobil Corporation Comments: C- 6 Brauer et al. (1996)

Morning and evening spirometry was administer ed 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 f unction. These included both FEV 1 and FVC. The discussion will only consider FEV 1 as methods were the same for both. The final model had the form:

FEV 1 = u (mean FEV) + ID1 (departure from overall mean) + ... (max hourly temp, maximum hourly O 3 , Julian data)

• evening FEV 1 does not assess change

• next day morning FEV 1 does not assess change

• ▲ FEV 1 [afternoon FEV 1 – morning FEV 1 ] does assess change and is the only spirometry

variable considered appropriate for assessing e xposure-response. There was no association with ozone (coefficient = 0) or te mperature, but there was an association with

date.

• ▲ FEV 1 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 s hould be considered simply an exploratory

variable and statis tical 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, wh ich 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 ot her pollutants are not in the model. However,

the reduction in %FEV 1 and %FVC are less than 5 percent at the highest exposure levels, and so there is no apparent adverse effect ev en 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 PM 2.5 , PM 10 , sulfate, acid, hourly ozone and temperature. Th e association between am bient air pollutants was analyzed using four different measures of PEFR . Three PEFR measures were normalized to “adjust for differences in subject height and ag e and to allow comparison of each subject to her own baseline,” and was done separately for mo rning 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 PEFRExxon Mobil Corporation Comments: C- 7 • Body size normalization PEFR = liters/min = [(daily PEFR – 2-wk average PEFR) / (avera ge 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 in crease in ozone exposure (about 0.8% or 3 liters/minute out of an averag e 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 reducti on in evening PEFR at 70 ppb would be 9.03 Liters/min, or about 2.5 percent ove rall 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 th an 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 de viation is about 2.5 percent.

• Brauer et al. (1996). The coefficient was 0.0 for ▲ FEV 1 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 ▲ FEV 1 slope in adjusted linear 2-pollutant ozone model was -0.048 (-0.112-0.016), which at 70 ppb is equi valent to a 3.4% reduction, indicating a non-adverse and non-significant effect in the ra nge of the ozone concentration data. Read from the graph, the reductions are ~2% a nd 2.8% from linear and non-parametric smooth regression respectively.

ExxonMobil Biomedical Sciences, Inc. October 9, 2007Exxon 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 resu lts 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 coefficient s estimated in epidemiological studies reflect a causal and not purely statistical association. Although we have repr oduced 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-deriv ed 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 t hat even this statistical evidence is suggesting a large chance that there is no risk at all from ozone. (Sta tistical 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 ozon e air quality data necessary to reproduce EPA’s risk estimates, and then reproduced EPA’s mo rtality risk estimates for those se ven 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 oz one 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 attribut able to days when 8-hour averages were above 70 ppb.

1 Although we could have reproduced the risk estimates based on th e national average risk coeffici ent that EPA also relied on fo r these
cities and for the other five cities in it s mortality risk estimates, we do not consider that a valid risk estimate and so we h ave chosen not to reproduce those risk estimates at all. Mo st importantly, that risk coefficient has incorrectly removed the true remaining vari ance in risk after complete use of the Bayesian hierarchical method of extracting info rmation 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 do cket at EPA-HQ-OAR-2005-0172-0021.1) explain the technical b asis 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 ar e 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 mortalit y risk due to ozone at exact attainment of the current standard would be based on the average of those three year s, as that is the distri bution of ozone concentration

that exactly attains the current standard. In contrast, for mo st of these five cities, the risks based on 2002 data

reflect a set of ozone concentrations that are worse t han 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 ye ars that vary above and below exact attainment, the percent of total non-accidental mortality that is attr ibutable 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 popu lation-weighted average risk over all seven of the cities analyzed is 0.02%.

The small mortality risk estimates presented above reflect t he fact that when an area is in exact attainment with the current standard, there will be very few days on wh ich 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 ov er-attaining the standard in some years. The resu lting effect – if using EPA’s air quality rollback assumptions – is that a standar d 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 we re based on 24-hour average epidemiologica l 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 w hen the maximum 8-hour ozone is 70 ppb or higher. Table 2 shows, as an example, the comparable result s 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-Accide ntal Mortality Associated with Short-Term Exposure to Ambient Ozone on Days When the Maximum 8-H our 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%AtlantaClevelandDetroitHoustonLos AngelesSacramentoSt. LouisPercent 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%AtlantaClevelandDetroitHoustonLos AngelesSacramentoSt. LouisPercent of Total Incidence (and 95% CI) Attributable to ozone > 0.08 ppm

Attributable to 0.07 ppm < ozone <= 0.08 ppmResults of CRA Sensitivity Analyses on Ozone Risk Assessment October 9, 2007 Page 4

Figure 2. Estimated Percent of Annual Non-Accide ntal Mortality Associated with Short-Term Exposure to Ambient Ozone on Days When the Maximum 8-H our 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%AtlantaClevelandDetroitHoustonLos AngelesSacramentoSt. LouisPercent 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

A

ttributable to Ozone > 70 ppb

Number of Effects

A

ttributable to Ozone > 70 ppb

Number of Effects

A

ttributable to Ozone > 70 ppb Percent of Total

Incidence

Percent of Total

Incidence

Percent of Total

Incidence 0

0

0

0Results of CRA Sensitivity Analyses on Ozone Risk Assessment October 9, 2007 Page 6

Sensitivity of EPA’s Risk Estimates to it s Decision to Change the PRB Assumption

The above details on EPA’s risk estimates were perform ed using exactly the same data and assumptions as EPA has used. One of those assumptions was the averag e 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 avera ge PRB (which is the fundam ental 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 estima tes, 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 derive d 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 coefficient s 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 pos itive 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 ex plored a couple of the many forms of uncertainty in assessing ozone health risks. The un certainties that we have explored a bove 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, assump tions 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 t he mere statistical variances that ar e reported with each of EPA’s risk estimates. I have submitted multiple comments to EPA during the course of the cu rrent NAAQS review that have argued for the need for its Risk Assessment to inclu de a probabilistic assessment that integrates all of these uncertainties into EPA’s summary statements on ri sk. 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-O AR-2005-0172-0049.1

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