**Comments on the**

**First External Review Draft of**

**"Air Quality Criteria for Ozone**

**and Related Photochemical Oxidants"**

**EPA 600/R-05//004bA, January 2005**

**Prepared for**

**General Motors Corporation**

**by**

**Jon M. Heuss**

**Air Improvement Resource, Inc.**

**April 26, 2005**

### Introduction 

Air Improvement Resource, Inc. (AIR) has reviewed the draft Criteria
Document (CD) with a focus on the policy relevant background of ozone,
the interpretation of epidemiologic studies of ozone, and the integrated
synthesis of information from controlled human studies, toxicology, and
epidemiology. In the following sections, we provide comments on each of
these topics.

There is a general issue with the way the Chapters and Annexes work
together. While the annexes tend to provide detailed information, when
that information is summarized in the main chapters there tends to be a
loss of important qualifiers or caveats in some cases. In addition,
there are cases where some of the most relevant material in the annex is
left out of the main chapter and the integrative synthesis. This
requires the reader to read the entire document carefully. This clearly
was not the intent of the authors when they included the extensive
annexes.

### Policy Relevant Background

The CD notes that there are many different sources and processes
contributing to background ozone that cannot be controlled. In addition,
the levels of ozone that are uncontrollable through regulation of U. S.
anthropogenic emissions vary substantially both spatially and
temporally.

In order to estimate the levels of uncontrollable ozone, the CD defines
a term denoted as policy relevant background (PRB). However, the
definition of policy relevant background given in the CD is too broad.
It omits consideration of the emissions from agricultural activities and
it omits consideration of the contribution to ozone from anthropogenic
emissions in Mexico and Canada. While there can be reductions in
emissions from agricultural activities, it would be impossible to drive
them to zero. The impact of Canadian and Mexican emissions is also
problematic because, even though the U. S. may have treaties with these
countries, zero anthropogenic emissions in these countries is not a
possible future outcome.

The CD states that the current definition implies that only Chemical
Transport Models (CTMs) can be used to evaluate or calculate the PRB.
However, the CD also states that there are issues with how well global
scale 3-D CTMs can simulate the cause of high ozone concentrations
measured at monitoring sites. Since the current ozone standards (1-hour
and 8-hour) are short-term concentrations with an extreme value
statistical form, the question comes down to how well global models can
simulate local short-term extreme events.

The CD indicates that it is problematic to use observations alone (page
AX3-157) to evaluate PRB because of the influence of transported ozone
from man-made emissions. However, the CD also indicates that the
simulation of stratospheric intrusions is notoriously difficult in
global models (AX3-157). Given the various problems and uncertainties
with the use if global models to estimate local maxima, it is also
problematic to use model calculations alone.

In order to evaluate the range and variability in PRB, the CD needs to
consider both observations and models. Since the ozone standards have
historically been defined as yearly extremes of daily maxima, the CD
should evaluate PRB for these statistical forms. When the agency
estimated background ozone during review of the federal ozone standard
in 1996/7, the agency's Staff Paper 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." (1996 OAQPS Staff Paper at page 20)

This is similar to the discussion on page AX3-50 except that the current
draft omits the word "usually." This is an important distinction because
there is a difference between the typical daily maximum of 0.03 to 0.05
and the yearly maximum of the daily maxima.

There is extensive discussion of yearly mean PRB ozone in the CD. The
1996 CD presented a range of from 0.02 to 0.035 ppm. In the current
draft, estimates that range from 0.015 to 0.040 are included in Table
3-8. Annual mean levels of background are an important consideration
when it comes to evaluating human exposure from background and in
interpreting the health studies. However, for control considerations,
because of the form of the ozone standard, the mean and the extremes of
the distribution of daily maxima are more appropriate. The CD should
include additional information on the distribution of the daily maxima.

**Issues with the Fiore et al. 2003 Modeling Study**

The CD relies on the Fiore et al. 2003 modeling study to estimate the
various components of background ozone. In fact, the bulk of the text in
Section AX3.9.2 is taken directly from the Fiore, et al. 2003 paper.
There are a number of problems with this approach. First, it is a model
calculation with a global transport model that was not designed to
specifically address the components of background.

The GEOS-CHEM model Fiore et al. used employs a coarse 2^o^ latitude by
2.5^o^ longitude horizontal grid that the authors acknowledge cannot
resolve the steep gradients in surface heating near coastal sites that
determine the depth of the mixed layer. The authors indicate that this
compromises the simulation over coastal urban environments. In addition,
the authors, in an earlier paper, listed the inability to resolve
topography in mountainous areas as another problem. The limitations of
the model in simulating coastal urban environments and the mountainous
west are important issues that are fully discussed in the CD.

Any global model contains many assumptions and simplifications that
simply cannot be fully evaluated. The GEOS-CHEM model is but one of a
number of such models. Fusco and Logan 2003[^1] evaluated the GEOS-CHEM
model and report that the model estimates somewhat higher production and
loss rates of ozone than other chemical transport models, as much as 15
to 30 %. Since the net photochemical production of ozone is determined
by the difference between these two large numbers (a large chemical
source term and a large chemical sink term), the net production cannot
be precisely determined. They note that differences in modeled
photochemical production and loss rates affect the relative importance
of the stratospheric source giving examples of other models that
indicate a much larger role for the stratospheric source in summer and
in winter. Adding to the complexity is that assumptions have to be made
about the cross-tropopause flux of ozone and ozone deposition at the
surface, quantities that each have significant uncertainty, too.

There are many other aspects of the chemical transport models that are
also highly uncertain. For example, there is disagreement over how many
ozone molecules are produced, on average, from each NO molecule emitted.
The recent NARSTO Synthesis Report[^2] indicates that more recent
studies have reduced the estimated ozone production efficiency from 7 to
10 molecules ozone per molecule NOx emitted down to 1 to 3. In addition,
the NARSTO report acknowledges there is substantial disagreement over
key factors such as the magnitude of U. S. biogenic VOC emissions
(uncertain by a factor of 2 or 3) and natural NOx emissions from soil
and lightning.

Fusco and Logan also express concern that with the accuracy of the
method imposed to simulate the annual flux of ozone across the
tropopause, noting that an incorrectly modeled seasonal cycle, as
appears likely in the case of the GEOS-CHEM model, could adversely
affect the response of the modeled ozone to the stratospheric flux. In
summary, there are a large number of questions concerning the
conclusions derived from the model, in general, and more specifically
for an application over the U. S.

The Fiore et al. study carried out three simulations: A standard
simulation attempting to reproduce the 2001 observations at rural and
remote CASTnet sites; a background simulation in which North American
man-made NOx, VOC, and CO are set to zero; and a natural ozone
simulation in which global man-made ozone precursors are set to zero and
methane was set to an estimated pre-industrial value.

The estimate of natural ozone with its dramatically lowered methane
value is not relevant to policy relevant background. The background
simulation is, in theory, relevant. However, the CD notes that one of
the potential causes of high ozone levels, stratospheric intrusions, is
notoriously difficult to simulate in global models. (pages AX3-157and
162) In addition, biogenic emissions from agriculture are not included
in the background simulation. There is also substantial uncertainty in
all the emission inputs included in the model. As noted above, there is
uncertainty due to the chemical formulation which is only a simplified
approximation of the chemical processes actually occurring in the
atmosphere. As noted above, the model estimates somewhat higher
production and loss rates of ozone than other chemical transport models.

The large grid size in the model is also problematic for getting the
regional and local ozone production right. The large grids mix or smear
precursor emissions from areas hundreds of kilometers on a side together
in ways that do not occur in the real world. Since ozone formation is
complex and non-linear, the model's mixing of emissions may result in
bias. This is one of the reasons why the CD indicates that "local maxima
and minima are difficult to reproduce with global models since processes
are averaged over an entire model grid cell." (Page AX2-116) The CD also
notes an underprediction bias at the upper end of the frequency
distribution probably related to sub-grid scale processes the model
cannot resolve. (Page 3-49)

The CD notes that a key question related to background is accounting for
the relatively high ozone levels measured at rural and remote western
sites particularly in the Spring. The Fiore et al. 2003 study addresses
this issue for Yellowstone Park data. The model simulation predicted
that regional pollution from North American man-made emissions
contributed 10 to 20 ppb to the highest observed concentrations in April
and May. This appears problematic. While the presence of a substantial
increment of regional ozone has been documented in the Eastern U. S.
where the population density and density of precursor emissions is
dramatically higher than in the western states (with the exception of
California), the calculation of such a large regional ozone signal in
Spring in the remote West is highly suspicious. The agency should not
rely solely on this one modeling study to define policy relevant
background.

# 

# 

# Data from Observations

Some data on 8-hour design values are given in the map in Figure 3-2.
However, the number of sites in the rural and remote western U. S. is
limited. There are additional data. As the USEPA went through the
attainment designation process for the new 8-hour standard, individual
states submitted their ozone data. Several western governors submitted
data from remote sites. For example, Governor Geringer of Wyoming[^3]
submitted data from the Pinedale ozone monitor in Bridger Teton National
Forest for which the yearly maximum 8-hour ozone ranged from 0.066 to
0.075 over the previous decade. Similarly data from a monitor at the
Yellowstone National Park Lake Lodge Area had yearly 8-hour maxima
ranging from 0.058 to 0.078 ppm. Another monitor in the Medicine Bow
National Forest had yearly ozone maxima from 0.069 to 0.084 ppm.

Many states submitted ozone data for the annual fourth highest 8-hour
average for comparison with the federal standard. Utah was one such
state. To estimate ozone levels in rural areas of Utah, Governor Leavitt
submitted data[^4] from National Park Service and other state monitoring
networks surrounding Utah. The data from Mesa Verde, Grand Canyon, and
Great Basin National Park Service sites and San Juan County in New
Mexico had federal 8-hour design values ranging from 0.069 ppm to 0.075
ppm.

To evaluate the yearly 8-hour maxima in the western U. S., we plotted
the yearly maxima from all the sites in the USEPA AIRS database for 2001
through 2003. The 8-hour daily maximum values were determined for each
site using the USEPA procedure. For each site, the yearly maximum of
those 8-hour daily maxima was plotted on a map of the United States
using different colors for yearly maxima in different ranges. The
following figures show that almost all the rural and remote sites in the
western half of the nation have yearly maxima that fall in the range of
0.06 to 0.08 ppm.

![](media/image1.wmf){width="6.500694444444444in"
height="4.596527777777778in"}

![](media/image2.wmf){width="6.500694444444444in"
height="4.596527777777778in"}![](media/image3.wmf){width="6.500694444444444in"
height="4.596527777777778in"}

The first through fifth highest daily maximum 8-hour average ozone
values through 2003 are available for national parks and monuments on
the USEPA's AIRNOW web site. The period of record varies for each site,
but for most there is about a decade or more of ozone 8-hour maxima.
These data also show 8-hour maxima in the same general range. For
example, the yearly 8-hour maxima from 1992 through 2003 range from
0.063 to 0.080 ppm at Canyonlands National Park in Southeast Utah where
the ozone monitoring season is months 5 through 9. The yearly 8-hour
maxima from 1983 through 2003 range from 0.058 to 0.080 ppm at Theodore
Roosevelt National Park in Western North Dakota where the ozone
monitoring season is also months 5 through 9. The yearly 8-hour maxima
from 1989 through 2003 range from 0.067 to 0.084 ppm at Chiricahua
National Monument in the Southeast corner of Arizona where the ozone
monitoring season is months 1 through 12.

There are some sites that have not recorded yearly 8-hour ozone levels
of 0.070 ppm or greater, such as Glacier National Park. However, the
ozone monitoring season is only months 6 through 9 at the Glacier site
and yearly peaks ranged from 0.049 to 0.065 ppm for years between 1989
and 2003 that met the USEPA data completeness test.

The widespread nature of yearly maxima 8-hour ozone concentrations of
0.06, 0.07 and higher at Western national parks and monuments that are
distant from large urban areas indicates the presence of a substantial
regional policy relevant background of ozone.

Additional evidence for a substantial policy relevant regional
background is given in the following plot that displays the average
number of 8-hour ozone days at or above 0.060 ppm by state and month for
monitors designated as rural in the USEPA AIRS database for the 22
states west of the Mississippi River. The plot displays the average
number of days on which one or more rural monitors in the particular
state registered an 0.060 ppm or higher 8-hour average for the years
2001 to 2003. The plot shows that there are a substantial number of days
at or above 0.060 ppm in states throughout the western U. S. Since the
number of monitors varies from state to state and the ozone monitoring
season also varies from place to place, direct comparisons between
states are not appropriate. However, the fact that there are many days
at or above 0.060 ppm starting in March, April, and May in states such
as Arizona, Utah, and New Mexico indicates the presence of a substantial
regional policy relevant background that is higher than the CD
acknowledges.

![](media/image4.wmf){width="6.043055555555555in"
height="4.399305555555555in"}

### Epidemiology 

**Lung Function**

Although there are several studies that report lung function effects,
the data is mixed. In particular, there are several studies in
California that report little or no effects. The Delfino study of
asthmatics in Alpine and the Linn study in Rubidoux, Upland and Torrance
are noted in the text and are of particular import given the fact that
Southern California ozone levels are the highest in the nation.

There is a particularly important study of asthmatic wheezy and healthy
children in Southern California that is not adequately discussed in the
chapter. The Health Effects Institute study by Avol et al.[^5] evaluated
potential acute respiratory effects of ambient ozone in the spring and
the summer. About 200 10 to 12 year old children from Lancaster, San
Dimas, Upland, Mira Loma, Riverside and Lake Arrowhead were studied in
the spring and late summer of 1994 with monitored hourly ozone levels
exceeding the federal 1-hour standard in each season and with peak
hourly levels up to 200 ppb in the summer period.

There was no discernible pattern of diurnal lung function changes by
season, by ozone level, or by health group. While there were individual
improvements and decrements in lung function observed, there was a
general tendency for improvement and not reductions in lung function.

There was also no consistent or clear role of ozone in producing changes
in reported symptoms or medication use. There were increased symptoms
and medication use on high ozone spring days but not high ozone summer
days. The spring results may have occurred because the subjects were
more sensitive in the spring or, as the HEI Review Committee suggests, a
result of enhanced response to allergens from springtime pollen blooms.
The review committee also noted that there was an increased frequency of
inhaler use on low ozone days in the summer but not on high ozone days.

The authors note that the failure to detect clear evidence of acute
pulmonary effects in the three groups may be due to the fact that ozone
levels were not sufficiently elevated during the study, although they
exceeded 80 ppb during the study. The authors note that the children in
their study, on average, did not spend the amount of time outdoors nor
did they spend the time exercising at the high levels used in the
chamber studies.

The Chapter should discuss the findings from the HEI study and integrate
it into a discussion of all the field studies of acute respiratory
effects.

The Brauer study is highlighted in the text. However, possible
confounding of ozone effects with coarse PM or coarse bioaerosols is not
mentioned. In any case, the interpretation of the lung function effects
for these heavily exercising outdoor workers needs to include
consideration of the neural mechanism. Although there was an attempt to
gather symptom data for these workers, no symptom results are given in
the paper.

# Symptoms and Inflammation

The results for respiratory symptoms are also mixed. The text
acknowledges that there are several studies of respiratory symptoms in
California that failed to detect symptom effects. The HEI study should
be discussed in this section, too.

The interpretation of symptom studies also needs to consider the neural
mechanism.

Since other pollutants are now thought to contribute to inflammatory
responses, the possibility for confounding by other pollutants needs to
be considered when evaluating inflammatory endpoints.

**Hospital Admissions and Emergency Department Visits**

While there are statistically significant associations reported for
respiratory hospital admissions in a variety of studies, there are also
studies where there was no association or a negative association. Most
studies evaluated associations with either total respiratory diseases or
with asthma. Total respiratory causes include asthma, pneumonia,
bronchitis, emphysema, respiratory cancers, and upper and lower
respiratory infections such as influenza. Chronic bronchitis and
emphysema are often combined to define chronic obstructive pulmonary
disease (COPD). In the recent California review, the staff acknowledged
that "no clear pattern is evident regarding associations of ozone with
specific respiratory disease outcomes."[^6]

In addition, the CD notes several key studies from California that
reported no association even though it is a high ozone area. For
example, Nauenberg and Basu 1999 evaluated associations between
asthma-related hospital admissions and exposure to PM10 and ozone. They
found no association between asthma and ozone even when seasonal
analyses were performed.

In a study that is not included in the CD, Van Den Eden et al.[^7]
carried out a study of hospital admissions in the Central Valley of
California using the GAM approach. Ozone had a negative association,
that is it was associated with a decreased risk of both acute
respiratory and chronic respiratory admissions.

While GAM studies, in general, are under a cloud, it is not clear
whether their results for ozone will be substantially altered by
re-analysis. Since studies such as the Van Den Eden studies have been
carried out in the high pollution areas of California, they should
definitely be re-analyzed to aid in the understanding of health effects.

If hospital admissions are affected by ozone, then it is likely that ED
visits would also be affected, and to a greater degree. However, the ED
results are less consistent, with effects apparent only in selected
sub-groups and at certain lags. The review of ED studies during the 2004
ozone standard review in California indicated that, of 20 studies, 16
reported at least one significant association involving ozone. Given
that studies without effects are difficult to publish and that these
studies often include multiple comparisons, it is not surprising that
there would be a number of positive associations in the literature.
However, the California review also acknowledged that there is no clear
pattern of association with specific respiratory disease outcomes.
Therefore, it is hard to accept this data as evidence of effects.

A significant number of other studies in the literature showed no
effects or inconsistent effects. The Hajat et al. 1999[^8] study of the
relationship between daily general practitioner consultations for asthma
and other lower respiratory diseases with air pollution in London is
omitted from the CD. Hajat et al. 1999 report that a consistently
negative association with ozone was observed in both disease categories.
Hajat et al. 1999 also evaluated seasonal models. In addition, the
Sunyer et al. 1997[^9] study of emergency admissions for asthma in four
European cities is omitted. They report the association between asthma
admissions and ozone for adults was heterogeneous among cities. For
children, they report no association was observed for ozone. They also
carried out seasonal analyses but found no consistent results for ozone.
With some studies omitted, it is not clear how representative the subset
of studies chosen for display actually is. Since the studies included in
the figures in chapter 7 are only a selected subset of all the studies
in a given area, one cannot rely on the figures to estimate how
consistent the literature is for a given health endpoint.

The issue whether reported ozone effects are specific to ozone is
important. The text list several hospital admissions studies that
reported ozone associations that were robust to inclusion of
co-pollutants. This is not a sufficient basis for drawing the conclusion
that the evidence is fairly supportive of independent effects. There is
no discussion of studies that reported differently or reported no
association in the first place. For asthma, bioaerosols are a prime
candidate as independent causal agents, but they are not measured in
most studies.

**School Absences**

The Gilliland et al. 2001 study of school absences is important but it
is the only study of its type. It is noted in the CD as being especially
valuable. However, as acknowledged in the CD, there is a question of
residual seasonal confounding for this study. Furthermore, a
substantially larger effect in low ozone communities versus the effect
in high ozone communities, a highly counterintuitive result,
necessitates additional explanation. Potential confounding by
bioaerosols was not evaluated in the study. Thus, it would be
particularly important to replicate the study in another cohort and over
all seasons. The many issues with model selection that have arisen in
recent years raise additional concerns that the result may not be
robust.

The large reported ozone effect on respiratory absences seems
disproportional to the lack of substantial effects on respiratory
symptoms seen in school children residing in the Basin. Chapter 7
acknowledges that there are several studies of respiratory symptoms in
California that failed to detect symptomatic effects. These include
Delfino et al. 1996, Delfino et al. 1997b, Linn et al. 1996, and Ostro
et al. 2001. There is a particularly important study of asthmatic,
wheezy, and healthy children in Southern California that is not
sufficiently discussed in Chapter 7. The Health Effects Institute study
by Avol et al.[^10] evaluated potential acute respiratory effects of
ambient ozone in the spring and the summer. About 200 10 to 12 year old
children from Lancaster, San Dimas, Upland, Mira Loma, Riverside and
Lake Arrowhead were studied in the spring and late summer of 1994 with
monitored hourly ozone levels exceeding the federal 1-hour standard in
each season and with peak hourly levels up to 200 ppb in the summer
period.

There was no consistent or clear role of ozone in producing changes in
reported symptoms or medication use. There was also no discernible
pattern of diurnal lung function changes by season, by ozone level, or
by health group. The authors note that failure to detect clear evidence
of acute pulmonary effects in the three groups may be due to
insufficient elevation of ozone levels during the study, although ozone
concentrations exceeded 80 ppb during the study. The authors note that
children in their study on average did not spend a comparable amount of
time outdoors or exercising at the high levels to the time used in the
chamber studies.

The lack of a substantial respiratory symptom signal in several Southern
California studies is inconsistent with the large effect on school
absences reported by Gilliland. This difference needs to be acknowledged
and discussed in the chapter.

#### Ozone/Mortality Analyses

The CD places significant emphasis on the question of ozone mortality
effects. It refers to a new NMMAPS analysis[^11] that extends the
previous analysis, with an effect estimate generally similar to that
previously reported. AIR has evaluated the Bell et al. 2004 study and
would like to point out a number of issues and concerns with
interpreting the results from this paper as causal.

The Bell et al. 2004 paper is the third major analysis of ozone and
mortality with the NMMAPS database. The first two analyses were
sponsored by the Health Effects Institute. The first study was carried
out with the General Additive Model (GAM) that was subsequently
identified as having statistical problems that led to a re-analysis of
selected studies. In the GAM study, selected ozone results were
presented. For lag 0 with 90 city data, there was no overall
ozone/mortality association although there were positive associations
for PM10, CO, NO~2~, and SO~2~. (Figure 9 of NMMAPSII[^12]). For the 20
largest cities, ozone was reported to have a positive combined
association in summer at lag 0 but a negative combined association in
winter, with a small negative association in year round data. (Figure 30
of NMMAPSII) For lags 0,1, and 2 in the 20 cities, ozone had a small
negative association in year round data at all three lags. (Figure 26 of
NMMAPSII). In addition, in a paper[^13] presenting the NMMAPS results
for the 20 largest cities, the single pollutant model ozone association
was negative in the six California cities included in the analysis.
Thus, there was little evidence of an ozone effect except for the summer
results, which were balanced by negative associations in winter
analyses.

In the second study, the HEI re-analysis[^14] using the Generalized
Linear Model (GLM), the investigators reported a negative combined
association of ozone with mortality in the winter for lag 0 and a
positive combined association in the summer, but with a small positive
association for lag 0 when all seasons were included. However, in
multi-pollutant models, the combined ozone effect was reduced and became
non-significant for lags 0, 1, and 2 for the summer data. (see Figure
7-25) Results for winter or all year in multi-pollutant models were not
reported. Overall, the NMMAPS analyses were focused on PM10 with limited
analyses reported for ozone or other pollutants. The re-analysis reduced
the overall PM10 association by about 40 % but it increased the overall
ozone association from slightly negative to slightly positive. In both
GAM and GLM analyses, a distinct difference between summer and winter
was reported with ozone having a positive association with mortality in
summer but negative in winter.

The Bell et al. 2004 paper extended the ozone mortality studies in
several ways but also omitted winter ozone results and limited the
analyses regarding other pollutants. While the additional analyses are
welcome and are discussed below, the omission of winter and
comprehensive multi-pollutant results is a serious deficiency in the
study. It is difficult to interpret the overall positive associations in
summer as causal when there are overall negative associations of ozone
with mortality in winter. It is also difficult to interpret the positive
ozone associations in summer as causal when the combined association is
reduced and non-significant when other pollutants are added into the mix
as reported in the second HEI analysis. Although Bell et al. 2004 is an
extension of the HEI NMMAPS ozone work, the paper neglects to mention
that ozone had a combined negative association with mortality in winter,
as reported in both the original GAM and the re-analyzed GLM work.

Whereas the HEI re-analysis reported ozone associations for single day
lags 0, 1, and 2, Bell et al. reports results for these three lags plus
lag 3 and a distributed lag model that includes the same day and the 6
previous days. As shown in their Figure 1, Bell et al. found the
strongest association for the same day (lag 0) with progressively
smaller associations through lag 3. Beyond lag 2 the individual day
associations were not significant. The effect from the distributed lag
model for a 10 ppb increase in ozone over the previous week is just
slightly higher than the effect for a 10 ppb increase on lag 0 and
lag 1. Thus, the Bell et al. analysis which considered more ozone lags
is consistent with the HEI analysis indicating the strongest association
is on day zero. This is problematic on two counts. First, since ozone
peaks in the afternoon, a same day association risks violating the
temporality requirement (that the exposure preceded the response).
Second, if there is a causal link between a 10 ppb increase in ozone on
the same day and premature death, it implies that ozone exposures that
are well within background levels are causing or contributing to death
immediately. There is nothing in the clinical or animal toxicology
literature that suggests this could be happening.

Bell et al. presented individual city results only from a second stage
analysis. This is reproduced as Figure 7-11 in the CD. In the first
stage analysis, however, there is a biologically implausible large range
(from negative to positive) in individual city results. The individual
city results for the summer in the HEI NMMAPS re-analysis were posted on
the Johns Hopkins website for lags 0, 1, and 2. As shown in those data,
the pattern of results for all three lags is the same, with a range of
ozone associations from about 3 % negative per 10 ppb increase in daily
ozone to 3 % positive association with a 10 ppb increase in daily ozone.
The interpretation of the positive associations in some cities as
adverse health effects would have to be balanced by an interpretation of
negative associations as health benefits. Since health benefits from
ozone exposure are implausible and the overall wide range of results is
equally implausible, interpreting these data as a causal effect of ozone
is problematic.

The results for lag 0, the day with the largest effect, and lags 1 and
2, which are more typical, are reproduced below. Note that only 7 of the
80 cities have statistically significant positive associations with
ozone for lag 0 in the summer. The Bell et al. paper masks the wide
range in individual city results by using a second stage Bayesian
analysis to derive the results presented in their Figure 2 (Figure 7-11
of the CD). The existence of a biologically implausible wide range of
results from individual cities is shown, however, in their Figure 3 in
which effects from -- 5 % per 10 ppb increase to + 10 % per 10 ppb
increase are reported. Even in the second stage analysis shown in their
Figure 2, only 6 of the individual cities have statistically significant
associations in single pollutant models.

![](media/image5.wmf)

![](media/image6.wmf){width="6.04375in" height="9.1in"}

![](media/image7.wmf){width="6.04375in" height="9.1in"}

Bell et al. report that their combined result was robust to exclusion of
high temperature days, to exclusion of high ozone days, to the use of
different ozone metrics from daily averages to 1-hour maxima, and to
inclusion of PM10 in the model. The combined ozone association was
similar for total deaths and for cardiovascular plus respiratory deaths.
The association was similar for all three age groups evaluated. If this
association is a real health effect, it implies that ozone is
contributing to cancer and diabetes deaths as much as cardiovascular and
respiratory deaths and to deaths in the younger and the aged population
equally. Yet given the negative association in winter, somehow the ozone
effect is strongly seasonal, being beneficial in winter. Given what we
know of air pollution health effects, this combination of results is not
plausible. The combined effect probably represents residual confounding
in a noisy ecologic analysis. For example, Lumley and Sheppard[^15]
caution that "estimation of very weak associations in the presence of
measurement error and strong confounding is inherently challenging.
Prudent epidemiologists should recognize that residual bias can dominate
their results."

If this reported association is causal, it likewise implies that ozone
levels well within background are linked to premature mortality. Since
the ozone exposures of the frail population (since they spend their time
indoors[^16]) will be roughly half or less than that measured at central
monitors, the paper implies that levels well below background (average
exposures of 10 to 15 ppb or 0.01 to 0.015 ppm) are causing mortality.
This is not biologically plausible. Bell et al. argue that the pattern
of association they observe would be anticipated for ozone since ozone
produces acute inflammatory responses in the lung. However, the doses of
ozone that result in initial inflammatory changes are considerably
elevated compared to the doses the frail population experiences indoors
on a day-to-day basis. As noted in the 1996 staff paper, 0.20 ppm is the
lowest level at which 1- to 3-hour exposures to ozone of subjects
engaged in very heavy exertion have induced biochemical indicators of
pulmonary inflammation. For 6- to 8-hour exposures of subjects engaged
in moderate exertion, the range of concentrations that induced this
effect is 0.08 to 0.10 ppm. Without heavy or sustained exercise, the
threshold for these physiological changes is substantially higher. In
evaluating the medical significance of these first inflammatory changes,
EPA indicated in the 1996 staff paper that their view, along with that
of medical experts they consulted, was that acute inflammatory
responses, when repeated, were a potential public health concern.

In contrast to the HEI NMMAPS analyses, which evaluated models including
other gases as potential confounders, the Bell et al. paper only looked
at PM10 as a potential confounder. Since there is greater concern over
fine PM than coarse PM as causing premature mortality, a test for
confounding by PM10 is not an adequate test even for just PM. Both
earlier HEI NMMAPS analyses evaluated a wider range of air pollutants as
confounders. As shown in Figure 7-25 of the CD, none of the combined
ozone effects in various multi-pollutant models were statistically
significant. In addition, in the Stieb et al.[^17] meta-analysis, a
comparison of ozone single-pollutant models with multi-pollutant models
including ozone was reported. The combined ozone association from single
pollutant models was reduced and became non-significant in
multi-pollutant models.

Bell et al. acknowledge that the ozone association they report may not
be from ozone per se but may represent the risk from the photochemical
pollution mixture more generally. This interpretation is also subject to
criticism. It is one possible explanation for the combined negative
association in winter but it does not explain the implausibly wide range
of negative and positive associations among cities in all seasons. Bell
et al. also raise the possibility that the ozone signal may be a
surrogate for other pollutants or the pollution mixture in general. For
all the reason enumerated above, it is premature to interpret the ozone
associations reported by Bell et al. as causal.

The CD also discusses the Gryparis et al. and Schwartz multi-city
studies. Both studies also reported a very wide range of individual city
associations ranging from negative to positive. For example, the
percentage increase in deaths for a 10 ppb increment in ozone ranged
from -- 3 % to + 1.5 % in the year round data as reported in 23 European
cities

## by Gryparis et al. (see their Figure 1) For the summer period, the range was from -- 2 % to + 2 % (see their Figure 2). In the Schwartz 2004 14-city study there was also a wide range in associations ranging from positive to negative (see his Figures 1 and 2). Schwartz notes the negative association in winter and suggests that it may reflect the negative association between wintertime ozone and primary air pollutants. He goes on then to ask "might not the positive association in the summer likewise reflect confounding with some other pollutant?" These and other possible explanations need to be rigorously considered in the CD.

## 

The CD also discusses several meta-analyses of ozone mortality
associations. There are problems with interpreting the WHO 2004
meta-analysis as a positive study. First, the WHO study reported no
association of respiratory mortality with ozone in the meta-analysis of
European studies. There were no statistically significant associations
of ozone with respiratory mortality in the 12 studies evaluated. The
overall risk was 1.000 per 10 μg/m^3^ (5 ppb) increase in ozone.
Instead, there was a weak signal of an association of ozone with
cardiovascular mortality. The finding of a cardiovascular but not
respiratory mortality signal from ozone in single pollutant models is
hard to explain as a causal relation. It is not coherent with the CD
conclusion that the ozone signal in hospital admissions is with
respiratory not cardiovascular admissions. In the WHO study, the
combined association of ozone with respiratory hospital admissions was
not statistically significant for the five cities available for
analysis.

## 

## Second, the WHO analysis evaluated the potential for publication bias and corrected its all-cause ozone/mortality association from 1.003 to 1.002 (95 % CI = 1.000- 1.003) using the trim and fill technique. The study discusses the issue of publication bias acknowledging that it is a common and possibly universal problem in our research culture. Furthermore, they note that there are particular reasons why it might occur in time series studies. These include the large number of associations evaluated and the possibility for a selection bias involving the results included in a paper. They also mention a lag selection bias that can be overcome with multi-city studies such as NMMAPS. They further point out that publication bias can result in false conclusions being drawn in the hazard identification stage of a risk assessment and result in an inflation of the magnitude of the health impacts. They also recognize that the methods of detecting publication bias are not without problems. 

## 

Another study that raised the issue of publication bias relative to
ozone health effects is Levy et al. 2001.[^18] Levy et al. describe
their review of the ozone health effects literature as providing weak
epidemiologic support for ozone mortality and as potentially biased
because it excludes studies that found ozone to be insignificant. After
listing a number of such studies and noting that nearly all the studies
found ozone not to be a predictor of mortality including all studies in
warmer climates, Levy et al. concludes this information must "...give
one pause in using our pooled estimate as a representative measure of
ozone mortality risks." They also discuss the difficulties of separating
temperature or weather and ozone effects, cautioning that "possible
confounding by weather leaves lingering doubt about whether the ozone
findings are causal, an issue that would be difficult to resolve
epidemiologically."

Ozone is the only pollutant for which NMMAPS seasonal results have been
published to date. The NMMAPS database is valuable because, by including
all the 90 largest U. S. cities with data, it avoids the issue of
publication bias. The wide range of ozone associations in the data,
using the same methodology, demonstrates the inherent noise or
variability in the data. The same wide pattern of mortality associations
ranging from strongly positive to strongly negative is observed in the
individual NMMAPS data for all the pollutants studied (PM10, ozone, CO,
NO~2~, and SO~2~) at all the lags studied.[^19] In the NMMAPS morbidity
study, only PM10 was evaluated in single pollutant models. However,
there was also an implausibly wide range in the 14-city hospital
admission associations with PM10 ranging from strongly positive to
strongly negative.

In summary, the wide range of individual city results in NMMAPS and
other multi-city studies, the overall negative winter association
demonstrated in NMMAPS, the lack of a significant summer combined
association for the 90 largest U. S. cities in NMMAPS multi-pollutant
models, and the several other concerns noted above that leave doubt
about causality. The only reported NMMAPS ozone results in
multi-pollutant models were for the summer. In each case, when other
pollutants were included, the ozone association was reduced and became
non-significant. (see Figure 7-25) If the ozone associations are not
robust to inclusion of other pollutants in the summer when there was a
combined positive association in single pollutant models, it is very
unlikely that they could be causal

# Model Selection issues

As discussed in the CD, there are many issues with time series studies.
As demonstrated above, there is a wide range of associations from
positive to negative in the NMMAPS 90-city summer ozone data in single
pollutant models. There is also a wide range of associations in the
other multi-city studies. Such a wide range is biologically implausible.

While there are some inverse or negative air pollution associations
reported in the literature, the NMMAPS study shows that there are many
more negative associations in the data than in the literature. When the
GAM issue was raised and many time series studies were re-analyzed,
Ito[^20] systematically re-analyzed the 1220 separate air pollution
mortality and morbidity associations that were included in the original
Lippmann et al. 2000 HEI study of Detroit. As shown below, in Figure 2
from Ito 2003, there was a wide range of negative and positive risks in
Detroit when all pollutants, lags, and endpoints were considered. Ito
showed in separate figures that the wide range of associations occurred
for each pollutant. Although the focus in the original Lippmann study,
as it is in almost all the published literature, was on the positive
associations, Ito's plot shows that there are many negative associations
in the data. Although there may be somewhat more positive associations
than negative associations, there is so much noise or variability in the
data, that identifying which positive associations may be real health
effects and which are not is beyond the capability of current methods.

![](media/image8.png)

Figure 2 from Ito 2003

Another important systematic analysis was carried out by Koop and Tole
2004[^21] who used Bayesian model averaging to evaluate model
uncertainty in time series analyses using an extensive set of pollutant
and meteorological variables from Toronto, Canada. They summarize their
results as follows:

> "Point estimates of the effect of numerous air pollutants all tend to
> be positive, albeit small. However, when model uncertainty is
> accounted for in the analysis, measures of uncertainty associated with
> these point estimates became very large. Indeed they became so large
> that the hypothesis that air pollution has no effect on mortality is
> not implausible. On the basis of these results, we recommend against
> the use of point estimates from time series data to set regulatory
> standards for air pollution exposure."

Importantly, the authors demonstrate that the results of a single model
based on a sequence of hypothesis tests will overestimate the certainty
of the results. This is not a new finding in the statistical literature
but it has not been carefully considered in the air pollution
literature. They use an example to show how the results of a single
regression "may lead researchers to make misleading inferences about
pollution-mortality effects, thereby seriously underestimating the true
uncertainty in the statistical evidence."

In the GAM re-analysis, the HEI Special Panel also concluded that model
selection issues such as specification of weather and degree of control
for time "introduce an element of uncertainty that has not been widely
appreciated previously." In fact, the Koop and Tole analysis is the kind
of analysis the Panel recommended to investigate the sensitivity of
results to model selection issues. By rigorously evaluating the
uncertainty with Bayesian model averaging, they show that there is much
greater uncertainty in the time series studies than commonly reported.

While the CD makes note of the Koop and Tole analysis on page 7-117, it
is basically dismissed. Because of the issues raised in Section 7.3.1.7
concerning model uncertainty and multiple testing, this paper is much
more important than acknowledged in the CD. It raises fundamental
questions concerning the utility of time series studies. These issues
need to be acknowledged and discussed in Chapter 7 and in the
integrative synthesis.

The summary on page 7-132 indicates that the usefulness of Bayesian
model averaging may be limited due to the large number of variables
typically considered in air pollution health effects and the high degree
of correlation among the air pollutants. This criticism is unwarranted.
These issues are important for traditional time series analyses. They
are inherent in the situation where meteorology drives the day-to-day
levels of pollutants and we have little a priori knowledge of causal
relationships. Bayesian methods are an important tool to address the
problems inherent in the traditional techniques.

Koop and Tole, as noted above, show that individual model results are
unreliable. In comments on the federal PM Criteria Document, AIR has
presented evidence[^22] that led us to same conclusion. By empirically
comparing the results of different time series studies of the same city
by different investigators, we showed that the results change, often
substantively. Subtle differences in model selection can shift the
strength of association with a given pollutant, can change the pollutant
or pollutants implicated by a given study, and can change the health
endpoints that are supposedly affected by the pollutant or pollutants.
In the second draft of the PM CD, EPA acknowledged this issue using
Philadelphia as an example. There are, however, many more examples in
the literature.

Thus, model uncertainty is greater than generally appreciated, there is
evidence for several major biases in the data in the literature, and
systematic studies do not implicate ozone any more than any other
pollutant. As EPA reviews the air quality standards for each pollutant
in turn, there is some evidence in the literature to implicate that
pollutant in premature mortality. The text spends a great deal of time
discussing the warm season ozone associations. However, the Stieb et al.
meta-analysis showed that warm season associations are stronger than
cold season associations for other pollutants too, so ozone is not
unique in that respect.

Instead of concentrating on the studies in the literature that report
positive associations, the authors of the Chapter should address
questions such as how there can be such a wide variation of ozone
associations both positive and negative in the data. It is not
biologically plausible that ozone would be causing mortality in some
cities in the summer and protecting against mortality in others.
Similarly, it is not plausible that ozone is dangerous in the summer and
protective in the winter.

The text (page 7-122) indicates that the range of ozone mortality
estimates is relatively narrow with 80 % of the studies being between 0
and 7 % increase per 40 ppb increase in 1-hour maximum ozone. However,
the full range of individual city results is more like - 8 to + 7 % in
Figure 7-10 and - 4 to + 17 % in figure 7-12. Even this range is
misleading, because the Figures present the combined result for NMMAPS
(and other multi-city studies) rather than the individual city results
which, for summer, varied from -- 12 % to + 12 % for a 40 ppb increase
in 24-hour ozone. This wide a range is not biologically plausible. The
authors of the strongest association, Vedal et al. 2003, highly qualify
their results noting that they are not biologically plausible and that
ozone may be acting as a surrogate for something else in the
meteorology-air pollution mix.

Another factor noted in the text that should be considered is the lack
of an ozone mortality signal such as the signal from the 1952 London
episode. The lack of a strong health effects signal from the extremely
high ozone concentrations measured in Southern California in the 1950's
and 1960's argues against a causal ozone mortality association. If a 40
ppb change in 1-hour ozone causes up to a 7 % increase in mortality, as
the Chapter suggests, or an even a larger increase as some studies in
the literature suggest, the mortality signal in the 1950's and 1960's
with 500 ppb 1-hour ozone concentrations would have been too large to
miss. In addition, the clinical studies suggest that there are
thresholds for the first effects, which are neurally mediated, that,
according the USEPA exposure analysis, are not exceeded for the majority
of the population the majority of the time, even at current ozone
levels.

### Integrative Synthesis

The draft integrative synthesis omits several important facts concerning
ozone exposure that are critical to interpreting the epidemiological
studies and evaluating them in light of the clinical and animal studies.
The draft does draw from Table AX3-6 which provides pooled distributions
of the ozone levels from monitors across the country. The median ozone
exposure in Metropolitan Statistical Areas (MSAs) is 0.032 ppm. Table
AX3-6 also indicates that the mean concentration is 0.033 ppm and that
90 % of the 1-hour ozone levels monitored in urban areas across the
country are below 0.062 ppm. These data are from the ozone monitoring
season which is typically April to October. Thus, even though many of
these areas are out of attainment of the ozone standard, the typical
day-to-day ambient ozone levels in cities are currently very low. In
fact, they are typically within the range of levels of policy relevant
background.

The air quality standards are designed to control ozone levels in the
upper tail of the distribution. The reductions documented in the CD, for
example a 29 % reduction in peak 1-hour concentrations from 1980 to
2003, represent a much larger reduction than apparent at first glance.
Since the peak yearly peak 1-hour concentrations in remote sites are in
the range of 0.06 to 0.075 ppm and the typical daily 1-hour peak is in
the range of 0.03 to 0.05 ppm, the percentage reduction in peak man-made
ozone is substantially larger than the reduction in peak levels of total
ground-level ozone.

The discussion of exposure assessments in Section 8-3 is particularly
disappointing. The reader of this section is not informed that indoor
exposures are typically only a fraction of outdoor exposures. The reader
is not informed that personal exposure monitoring confirms that the
exposure to ozone in the breathing zone of individuals, which is the
proximate cause of any ozone heath effects, is typically only a fraction
of the ozone level measured at monitors. In addition, the reader is not
informed that the ozone monitors, in many instances, are located outside
the breathing zone of the general population. These are important facts
that are well documented elsewhere in the CD and are crucial to the
evaluation of whether current ambient exposures can be causing premature
mortality.

The ratio of indoor/outdoor ozone levels is included in Table AX3-27.
Ratios of 0.5 and lower are common in this data. Additional information
on indoor and outdoor levels is included in Table 3-10. Personal
exposure measurements are summarized in Table AX3-32. In Chapter 7, it
is noted that for several indoor- outdoor studies, the indoor
concentrations were one-tenth the outdoor concentrations (Page 7-7). The
fact that ozone monitors are frequently located on rooftops in urban
settings, where they may overestimate the actual exposures of people
outdoors in streets and parks is noted on page 3-60. All these findings
are crucial to putting the ozone exposures of the population in context
and in perspective for the integrative synthesis.

The fundamental question is whether day-to-day changes in ambient ozone
within the range of 0.01 to 0.06 that are associated with personal
exposures that are within the range of 0.005 to 0.04 ppm are capable of
causing or contributing to premature mortality.

In controlled human exposures, the first effects on lung function occur
at 0.50 ppm in sedentary individuals. (Page 6-3) With increased levels
of physical activity and breathing rate, the threshold for the first
effects decreases. However, the thresholds for the first effects in
controlled studies are still considerably above the vast bulk of
personal exposures of the general population. During the 1996 review,
[^23] EPA staff concluded that the lowest range within which 1- to
3-hour exposures to ozone at heavy exertion produce group mean
statistically significant lung function decrements is 0.12 to 0.16 ppm.
They concluded that the lowest range for 6- to 8-hour exposures at
moderate exertion is 0.08 to 0.12 ppm. For respiratory symptoms, the
USEPA staff concluded that the lowest range for 1- to 3-hour exposures
at heavy exertion is 0.16 to 0.18 ppm and for 6-to 8-hour exposures at
moderate exertion, it is 0.08 to 0.12 ppm. For biochemical indicators of
pulmonary inflammation, the lowest level for short-term exposures was
noted as 0.20 ppm and the lowest level for 6- to 8-hour exposures was
0.08 to 0.10 ppm. The current draft does not draw specific conclusions
regarding these thresholds. However, the 2004 analysis of human studies
carried out by the state of California came to essentially the same
conclusions.

The exposure/exertion protocols used in the human clinical studies do
not mimic typical human behavior so the results must be mapped onto
realistic exposure/activity scenarios to determine the risk. The chance
of experiencing an exposure of concern requires that a person be outside
at the location of the high ozone and at the time of peak ozone. During
the 1996/1997 review of the federal ozone standard, USEPA staff
undertook an extensive exposure and risk analysis with input from CASAC.
To estimate the risk staff used the output of a probabilistic exposure
model together with concentration-response functions derived from the
clinical studies. The analysis, which is documented in the 1996 Staff
Paper, was very conservative as it assumed lung function decrements
started at 0.04 ppm, assumed no attenuation of effects, assumed that
that children experienced the same level of symptoms as adults
(available data suggests otherwise), ignored smoking status that would
attenuate responses in outdoor workers, and used human time/activity and
exertion data from California as well as other locations. The EPA
analysis also used an algorithm to assign ventilation rates based on
individuals who exercised regularly and were motivated to reach a high
ventilation rate. As a result, the Staff Paper acknowledged[^24] that
the analysis allows more high ventilation rates than would actually
occur in the populations of interest - outdoor workers, outdoor
children, etc.

# The 1996 exposure and risk analysis demonstrated that there will be a minimal number of days of ozone-related respiratory effects with 8-hour concentrations up to 0.09 ppm and employing statistical forms allowing up to 5 exceedances per year. The extreme value form of the current 8-hour standard, in itself, adds a substantial margin of safety in that it drastically limits the number of potential repeat exposures. 

Since the last EPA decision in 1997, a body of information on the
mechanism of ozone effects shows that the first effects of ozone
exposure -- decrements in the performance of lung function tests and
symptoms -- are caused by a neural reflex mechanism. This fact should be
considered carefully in the integrative synthesis as it may change the
interpretation of which responses are adverse and which are not.

Chapter 6 describes the body of studies that show that the first effects
of ozone are caused by reflex responses of vagal nerve receptors that
involuntarily inhibit maximal inspiratory effort. This response is the
body's reflexive reaction to the presence of an irritant gas and is
unrelated to sensations of discomfort. At somewhat higher exposures,
there are mild symptoms and sensations of discomfort that occur. These
are also transient and reversible.

At even higher exposures, the body's first cellular or biochemical
changes that are small and reversible occur. Even these changes which
are noted as the first indications of "inflammation" are physiological
processes that occur in all living organisms under the stimuli of daily
life. The first reported changes (that occur with heavy exercise after
1- to 3-hours above a threshold of 0.18 to 0.20 ppm) are well within the
range of physiological variability and should not, therefore, be
interpreted as unequivocal evidence of ozone adversity. They fall into
the category of biochemical markers that ATS indicates do not
necessarily imply adversity.

The new information on mechanisms shows that the lung function
decrements are decrements in the performance of the lung function test
(that requires maximal inspiratory effort) and not a change in lung
function of any clinical or pathological significance. That the acute
lung function decrements are not indicative of or related to long-term
changes in lung function is supported by the findings in Gauderman et
al. 2000 that there was no relation between ozone exposure and
childrens's lung function growth in areas of California with ozone
concentrations that are significantly above the current federal ozone
standards. While there are several other studies that suggest possible
effects of current and past ozone exposures on lung function growth, the
Gauderman et al. study is the most definitive because it was designed to
test the ozone lung function growth hypothesis and minimize the
influence of other air pollutants.

These new findings should also modify the interpretation of field
studies where effects of ambient ozone on pulmonary function (forced
expiratory volume, FEV1) are traditionally interpreted as serious
adverse effects that can lead to irreversible late consequences. This
applies especially to numerous epidemiological studies in which
pulmonary function tests were used as the major or only evidence of
ozone effects.

In addition to the ozone-induced decrements in pulmonary function,
numerous studies also report that ozone exposure of humans can cause
"acute inflammation of the respiratory tract." However, the majority of
these studies used only a statistical comparison of white blood cells or
other biochemical indicators of "inflammation," considered as signs of
respiratory cell injury in deep pulmonary airways, in the
bronchoalveolar lavage from humans before and after ozone exposure or in
comparative field studies. The effects were evaluated only by difference
between the exposed and unexposed groups without any attempt to analyze
the diurnal physiological variability of these cellular counts, or
without any discussion when this variability becomes a pathological
process leading to irreparable changes in pulmonary composition and
structure, and without any consideration of the clinical significance of
these statistical differences.

It should be also emphasized that the reported cellular changes
described as "inflammation" are physiological processes that occur in
all living organisms even under physiological stimuli of daily life and
should not be, therefore, interpreted as unequivocal evidence of ozone
adversity (Vostal et al., 1995[^25]). Moreover, the reported cellular or
biochemical changes are small and reversible and growing evidence shows
large intra- and inter-individual variability even in the pre-exposure
levels of these indicators. This suggests that the observed changes may
be well within the range of physiological variability (Koren et al.,
1989a, 1991). When expressed in absolute terms, these levels are far
from those of a developed pathological inflammatory process. In
addition, recent reports question the quantitation accuracy and
reliability of the bronchoalveolar lavage levels and their use as a
diagnostic tool in clinical medicine. The studies conclude "at present,
none of the known methods to determine alveolar fluid volume are able to
serve reliably as a basis for quantitative measurements" (von Wichert et
al., 1993[^26]). These accuracy concerns apply particularly to the
reported changes after prolonged exposures to near ambient
concentrations (0.08 ppm ozone -- Devlin et al., 1990,[^27] 1991, Koren
et al., 1989a, 1991) where the differences are extremely small and
unstable. Some studies were even unable to reproduce the neutrophil
response (Aris et al., 1993b). In light of this discussion, using these
data without more consideration of their clinical significance seems to
be premature.

The discussion in Section 8.4.8 does not put the results of the human
clinical studies and animal studies in perspective in terms of dose or
frequency of occurrence with the very low day-to-day exposures of either
the general population or the susceptible population. Biologic
plausibility involves both the kinds of effects seen and the doses that
cause the effects. The CD should not claim that "the body of
toxicological studies suggest plausible mechanisms for epidemiologic
findings" (page 8-45) unless the issue of dose plausibility is addressed
rigorously.

Section 8.4.10 indicates that "injury to lung tissue is the initial step
in mediating deleterious health effects of ozone and, in turn, activates
a cascade of events starting with inflammation..." However, there is no
discussion of the lack of evidence for injury or inflammation at ozone
exposures of 0.01 to 0.04 ppm during normal activity. The day-to-day
changes in personal exposures to ozone implicated by some
epidemiological studies do not trigger the vagal mechanism and do not
trigger inflammation. Responses that might lead to health effects only
occur with heavy exercise and then only is one is outside at the time
and place of maximum ozone. These are rare events in the general
population and even rarer for the susceptible population.

Chapter 5 notes that initiation of inflammation is an important
component of the defense process. (page 5-24) However, inflammation in
animal models occurs only at higher concentrations. It has not been
reported at animal exposures typical of the personal exposures of the
general population. Throughout Chapters 5 and 6, there are many
instances of attenuation of ozone responses with repeated exposures. In
a general sense, these are manifestations of the body's defense
mechanisms dealing with an irritant gas. Since the typical day-to-day
exposures implicated by the ozone mortality analyses are within the
range of background ozone, it is not likely that such low exposures are
casing or contributing to premature mortality.

As discussed in detail above in AIR comments on Chapter 7, there is much
greater uncertainty involved in interpreting the epidemiologic
literature on ozone than indicated in the CD. The wide range in
individual-city ozone associations from strongly positive to strongly
negative is not biologically plausible. Section 8.4.7.3 claims that
ozone mortality associations were robust to confounding by copollutants
and refers to several examples where PM10 did not substantially change
the risk estimates. In the Stieb et al.[^28] meta-analysis, a more
comprehensive analyses of multi-pollutant models including ozone was
reported. The combined ozone association from single pollutant models
was reduced and became non-significant in multi-pollutant models. In the
NMMAPS summer ozone analyses, the combined result from the 90-city study
was not significant in any of the multi-pollutant models, as shown in
Figure 7-25.

Given the many limitations in the mortality analyses that are described
in AIR comments on chapter 7, the greater than previously appreciated
uncertainty due to model selection issues, and the bias due to reliance
on single pollutant models, the preliminary conclusion that ozone
represents an independent risk factor for premature mortality cannot be
supported. The Chapter should be revised to fully acknowledge the
limitations of time series analyses and the growing skepticism in the
technical community as to its usefulness.

Chapter 8 contrasts the beneficial effects of stratospheric ozone with
the adverse effects of tropospheric ozone. (Page 8-1) However, it is
well-established that tropospheric ozone plays a part in the total
column of ozone that protects us from solar UV. There needs to be a
discussion of the possible beneficial effects of tropospheric ozone on
UV-induced health effects in Chapter 8. This topic is discussed in
Chapter 10 (Section 10.2) at some length and the conclusion is drawn
that the beneficial effects cannot be assessed. However, the health
effects involved are substantial health issues and the causal link to UV
is much better established than is the case for ozone mortality in
Chapter 7. Section 10.2 seems to go out of the way to stress the
uncertainties and the limitations in estimating beneficial effects
generally characterizing the impacts as small and uncertain. While this
may be true, it is also true of the adverse effects implied by many of
the epidemiological associations. The agency should discuss the evidence
for both adverse and beneficial effects with the same objectivity.

[^1]: A. Fusco and J. Logan, "Analysis of 1970-1995 trends in
    tropospheric ozone at Northern Hemisphere midlatitudes with the
    GEOS-CHEM model," J. Geophys. Res., **108**, No. D15, 4449 (2003).

[^2]: The NARSTO Synthesis Team, "An Assessment of Tropospheric Ozone
    Pollution: A North American Perspective," July 2000, pages 3-19 and
    3-31.

[^3]: See July 7, 2000 letter from Governor Jim Geringer to Ms. Rebecca
    Hanmer, Acting USEPA Region VIII Administrator and enclosures.

[^4]: See June 10, 2003 letter from Governor Michael Leavitt to Robbie
    Roberts, USEPA Region VIII Administrator and enclosures.

[^5]: E. Avol, et al., Acute effects of ambient ozone on asthmatics,
    wheezy, and healthy children, Health Effects Institute Report Number
    82, 1998.

[^6]: California Air Resources Board, Review of the California Ambient
    Air Quality Standard for Ozone, June 2004.

[^7]: Van Den Eden et al., 2002, Central Valley hospital admissions
    study for ARB, Final Report ARB Contract 97-303.

[^8]: S. Hajat et al., Thorax, **54**, 597-605, 1999.

[^9]: J. Sunyer et al., Thorax, **52**, 760-765, 1997.

[^10]: E. Avol, et al., Acute effects of ambient ozone on asthmatics,
    wheezy, and healthy children, Health Effects Institute Report Number
    82, 1998.

[^11]: M. L. Bell, et al., "Ozone and Short-term Mortality in 95 US
    Urban Communities, 1987-2000," JAMA, **292**, 2372-2378, 2004.

[^12]: J. M. Samet, et al., The National Morbidity, Mortality, and Air
    Pollution Study Part II: Morbidity and Mortality from Air Pollution
    in the United States, Health Effects Institute Research Report 94,
    Cambridge, MA, 2000.

[^13]: M. Daniel, et al., Am. J. Epidemiology,**152**, 397-406, 2000

[^14]: HEI Special Report, Revised Analyses of Time-Series Studies of
    Air Pollution and Health, Health Effects Institute, Cambridge, MA,
    May 2003, page 18.

[^15]: T. Lumley and L. Sheppard, Epidemiology, **14**, 13-14, 2003.

[^16]: See pages 7-128 to 7-130 of ARB Draft Review; Indoor/outdoor
    ratios typically range between 0.2 and 0.8 with several California
    studies reporting I/O ratios below 0.5.

[^17]: Stieb et al., J. Air & Waste Management Association, **52**,
    470-484, 2002; Stieb et al., J. Air & Waste Management Association,
    **53**, 258-261, 2003.

[^18]: J. I. Levy, et al., Environmental Health Perspectives, **109**,
    1215-1226 (2001).

[^19]: J. M. Heuss and J. J. Vostal, Comments on the Fourth External
    Review Draft of "Air Quality Criteria for Particulate Matter" EPA
    600/P-99/002aD, June 2003, Prepared for General Motors Corporation.
    August 28, 2003.

[^20]: K. Ito, in Health Effects Institute, Special Report: Revised
    Analyses of Time-Series Studies of Air Pollution and Health, May 5,
    2003.

[^21]: G. Koop and L. Tole, J. of Environmental Economics and
    Management, **47**, pages 30-54, 2004.

[^22]: See AIR, Inc. comments on 2^nd^, 3^rd^, and 4^th^ drafts USEPA PM
    Criteria Document.

[^23]: See USEPA Staff Paper at pages149-150.

[^24]: See U. S. Environmental Protection Agency, Review of National
    Ambient Air Quality Standard for Ozone: Assessment of Scientific and
    Technical Information, OAQPS Staff Paper, EPA-452/R-96-007, June
    1996 at page 102.

[^25]: Vostal, J.J., Heuss, J.M., Pezda, S.A., Ball, J.C., Paul, R.,
    Wimette, H.J.: "Implications of Emerging Scientific Ozone Data on
    Regulatory Decisions", Presentation at the 88^th^ Annual Meeting of
    Air & Waste Management Association, San Antonio, Texas, June 18-23,
    1995, Publ. 95-MP19.0l, Air & Waste Management Association,
    Pittsburgh, Pa, 1995.

[^26]: von Wichert, P., Klaus, J., Mueller, B. and W.M. Franck,
    "Bronchoalveolar Lavage: Quantitation of Intraalveolar Fluid?,"
    Amer. Rev. Resp. Dis., 147:148-152, 1993.

[^27]: Devlin, R.B., McDonnell, W.F., Koren, H.S. and Becker, S.,
    "Prolonged Exposure of Humans to 0.10 and 0.08 ppm Ozone Results in
    Inflammation in the Lung", Paper No. 90-150.2, at the 83^rd^ Air &
    Waste Management Association Annual Meeting, Pittsburgh, Pa, June
    24-29, 1990.

[^28]: Stieb et al., J. Air & Waste Management Association, **52**,
    470-484, 2002; Stieb et al., J. Air & Waste Management Association,
    **53**, 258-261, 2003.