1. Scientific Fact on the
W126
The W126 exposure index does not utilize a threshold value, but
weights all hourly average concentrations differentially with
an "S" shaped curve (i.e., sigmoidally weighted). When
Dr. Lefohn developed the W126 exposure index in 1985, he provided
significant weighting greater than zero for all hourly average
concentrations above 0.04 ppm. The use of an approximate zero
weighting for hourly average concentrations less than 0.04 ppm
was intentionally designed into the W126 so as to reflect near
background levels. The W126 was designed with weighting of approximately
1 for all hourly average concentrations equal to and above 0.10
ppm. The weighting of 1 at these concentrations was based on
informal discussions with vegetation researchers in California
whose vegetation experienced repeated occurrences of hourly values
equal to and above 0.10 ppm. At the time of the development of
the W126, it was recognized that additional research would be
needed to verify the weighting scheme. In 1997, Finnan et al.
(1997) compared the performance of different ozone indices in
exposure-response functions for spring wheat and reported that
the best performing index employed a sigmoid function with an
inflection point at 0.062 ppm, which was very near the W126 weighting
inflection point of 0.065 ppm. Additional information on the
W126 can be found in Lefohn and Runeckles (1987) and Lefohn et
al. (1988).
Clarifying Statement for
a Review Comment on the W126
One commenter indicated that the definition of a Sigmoid or "S"
shape in the W126 related to the general diurnal patterns of
hourly ozone concentrations occurring at low-elevation sites.
The commenter appeared to be confused. The sigmoidal weighting
scheme had nothing to do with the diurnal variation of ozone
concentrations at any specific monitoring site. The sigmoidal
weighting or "S" shape refers to the weighting of each
hourly average concentration independent of time of day.
2. Scientific Fact on
Temporal Processes in Vegetation Response to Ozone
Over the past several years, research attempted to link the relationship
among uptake, ozone exposure, and detoxification with plant effects.
Papers by Musselman and Massman (1999), Massman et al. (2000),
and Musselman et al. (2006) summarized research efforts to develop
a dose-response model that allowed for the establishment of a
standard to protect vegetation from ozone. The work by Massman
et al. (2000) was particularly intriguing because it developed
a model that related exposure and dose and stressed the importance
of defense mechanisms that varied as a function of time of day.
The authors believed that it was the change in the defense component
as a function of time of day that perhaps explained the biologically
based observation that the higher hourly average concentrations
should be weighted greater than the mid- and lower- values in
predicting vegetation damage from ozone. Massman et al. (2000)
and Massman (2004) stressed that the product of the overlapping
mathematical relationships of conductance, concentration, and
defense mechanisms resulted in a much different picture of potential
impact to vegetation than just the use of conductance and concentration
in predicting vegetation effects. Work published by Heath et
al. (2009) described the temporal processes that contribute to
nonlinearity in vegetation responses to ozone exposure and dose
(i.e., higher concentrations more important than mid- and lower-level
values). The authors presented additional important evidence
that reinforces the biological relevance of the W126 exposure
index for weighting the higher hourly average ozone concentrations
more than the mid- and lower-level concentrations for assessing
vegetation effects. The publication discussed the linkage of
the temporal variability of apoplastic ascorbate with the diurnal
variability of defense mechanisms in plants and compared this
variability with daily maximum ozone concentrations and diurnal
uptake and entry of ozone into the plant through stomata. The
paper integrated the three processes (i.e., uptake, ozone exposure,
and detoxification) and provided evidence that supported the
application of nonlinearity in vegetation responses to ozone
exposures and dose. One of the keys to nonlinearity, as described
by Heath et al. (2009), was the out-of-phase relationship among
uptake, exposure, and detoxification. More information about
the Heath et al. (2009) publication and abstract can be found
by clicking
here.
Clarifying Statement for
a Review Comment on Temporal Processes in Vegetation Response
to Ozone
It is stated in comments submitted to the EPA Docket that the
occurrence of the higher ambient ozone concentrations occur in
the afternoon and the canopy stomatal conductivity reaches a
maximum before noon and therefore, the peak hourly average ozone
concentrations occur when uptake is minimal and the peak concentrations
are not as important as the mid-level and low hourly average
ozone concentrations. This explanation is too simplified. Unfortunately,
this explanation, which was introduced in the 1990s, ignores
the importance of plant defense, which appears to be lower in
the afternoon (Heath et al. 2009), when the peak concentrations
occur. It is the combination of the temporal relationship between
stomatal conductivity, peak ozone concentrations, and defense
that results in the ultimate observed effect on vegetation. Heath
et al. (2009) describe the out-of-phase relationship among uptake,
exposure, and detoxification and provide additional evidence
for why the peak hourly average concentrations should be weighted
greater than the mid- and low-level concentrations. For more
information about the peer-reviewed materials discussing the
importance of the higher hourly average concentrations versus
the mid- and lower-levels, please click here.
3. Scientific Fact on Sensitivity
of Plants to Ozone at Night
Evidence exists, summarized by Musselman and Minnick (2000),
that stomates of many plant species open at night and therefore,
the potential exists for nocturnal ozone injury and damage to
plants. Winner et al. (1989), Matyssek et al. (1995), and Lee
and Hogsett (1999) also reported ozone uptake at night. This
was an important observation in that it implied that uptake rates
at night, although lower than the values observed during daylight
hours, had the potential for allowing ozone doses to affect vegetation
during this period. Furthermore, Musselman and Minnick (2000)
and Heath et al. (2009) suggested that plant defenses against
ozone were likely lower during the night.
Clarifying Statement for
a Review Comment on Sensitivity of Plants to Ozone at Night
The use of a 3-month maximum, 12-h W126 cumulative exposure index
focuses on the 8 AM until 7:59 PM period. In most cases the highest
ozone exposures occur during the 12-h period. However, at some
high-elevation monitoring sites, the highest exposures occur
during the late evening and early morning period. Thus, there
might be a tendency for the 3-month maximum, 12,-hW126 to underestimate
effects.
4. Scientific Fact on Importance
of Using a Concentration Weighted Cumulative Exposure Index for
Vegetation Response to Ozone
It has long been recognized that peak ozone concentrations are
an important factor when examining exposure indices and plant
injury (Heck et al., 1966). Stan and Schicker (1982) reported
that plants exposed to a series of successive short periods with
high concentrations suffered more injury than did those plants
that received a continuously uniform exposure, but at a lower
concentration, with all plants receiving equal total exposure.
Key research experiments that evaluate the importance of the
higher ozone concentrations in plant response have been performed
under (1) controlled conditions in the laboratory and in the
field and (2) uncontrolled conditions in the San Bernardino National
Forest. These studies provide a framework from which one can
develop relevant exposure-response models that provide a consistent
relationship between ozone conditions and vegetation biological
endpoints (Musselman et al., 2006). Using data from controlled
experimental studies, Lee et al. (1987, 1988), Lefohn et al.
(1988), Musselman et al. (1988), Tingey et al. (1989), and US
EPA (1996) concluded that the cumulative effects of peak hourly
ozone concentrations were of greater importance than seasonal
(i.e., long term) mean exposures in predicting vegetation damage.
Yet, concern has been expressed that the experiments reporting
the importance of the higher hourly average concentrations have
been performed under controlled fumigation conditions not representative
of actual field conditions and the results obtained from these
experiments may not provide realistic results that are applicable
for developing predictive models for assessing vegetation effects
in natural environments However, comparisons of chamber results
with field results have shown that ozone uptake in chambers may
be similar to that experienced under field conditions (US EPA,
2006). Complementing the controlled fumigation results supporting
the greater weighting of the peak hourly average ozone concentrations
are findings from the conifer forest ecosystem of the San Bernardino
National Forest in California. During the period 1950-1980, extremely
high ozone concentrations impacted the San Bernardino National
Forest (US EPA, 1996). However, over the past years, significant
reductions in the ozone concentrations have occurred in this
area and improvements have been reported in the health of the
forest (Musselman et al., 2006). These findings provide additional
evidence for the greater importance of the higher hourly average
concentrations than the mid and low values (Musselman et al.,
2006). The US EPA (2006) indicates that ozone effects in plants
(crops) are cumulative and metrics that accumulate hourly ozone
concentrations while weighting the higher concentrations have
a better statistical fit to growth and yield response than do
mean or peak indices. an et al. (1997) in their analysis concluded
that cumulative indices which employed continuous weighting functions
(allometric or sigmoid) or which censored concentrations above
threshold values performed best as they attributed increasing
weight to higher concentrations. Indices which simply summed
concentrations greater than or equal to a threshold value did
not perform as well as equal weight given to all concentrations
greater than the threshold value.
Clarifying Statement on
a Review Comment on Biological Basis for Use of a Cumulative
Concentration Weighted W126
One reviewer commented that the W126 index is a flawed indicator
that is not biologically based or scientifically valid and that
an evaluation of the application of the W126 exposure index indicated
that there was no consistent association between the level of
statistical significance achieved and the actual measured response.
The W126 exposure index is biologically based and is based on
the observation in both controlled and uncontrolled experiments
illustrating the higher hourly average concentrations should
be weighted greater than the mid- and low-level values. Finnan
et al. (1997) confirm the scientific basis for use of a concentrated
weighted cumulative index such as the W126 for plant response
to ozone. Identification of a cumulative exposure index optimum
for all plant species and all conditions does not appear to be
possible due to (1) the limited information for assessing the
relative performance of exposure indices for relating to vegetation
effects and (2) the inherent differences in how plants respond
to ozone (US EPA, 1996). However, some indices have been shown
to be less useful than others. US EPA (1996) concluded that indices
based on long-term averages were inadequate to differentiate
among the different types of exposure regimes. One would not
anticipate that any exposure index would be consistent in predicting
vegetation effects due to soil moisture content. Because plant
response is thought to be more closely related to ozone absorbed
into leaf tissue, recent research has been focused on flux-based
ozone parameters. Even though flux-based indices may appear to
be more biologically relevant than concentration-based indices,
there are limitations associated with their use (Musselman et
al., 2006; Heath et al., 2009). The current set of flux-based
indices assumes that the plant has no defense mechanism to detoxify
ozone. This is a serious limitation. Both exposure- and flux-based
metrics may overestimate plant response. At this time, flux-based
models that take into consideration detoxification mechanisms
(referred to as effective flux) provide the best approach to
relate ozone to plant response. However, because there is considerable
uncertainty in quantifying the various defense mechanisms, effective
flux at this time is difficult to quantify. The flux-based indices
also require plant species specific data on stomatal conductance,
data that are largely unavailable for most plant species in the
US. Without adequate effective-flux based models, exposure-based
ozone metrics appear to be the only practical measure for use
in relating ambient air quality standards to vegetation response
(Musselman et al., 2006).
5. Scientific Fact on Use
of 8-Hour Average versus Cumulative W126 Exposure Index
With the biological emphasis on the higher hourly average concentrations,
the use of a long-term average concentration mathematically smoothes
the peak exposures at most ozone monitoring sites across the
US. Identical multi-hour average (e.g., daily maximum 8-hour)
concentrations produce different responses, depending on the
hourly ozone concentration pattern. However, because the peak
exposures are important, at ozone monitoring sites that exhibit
a high frequency of occurrence of elevated hourly average ozone
concentrations (i.e., southern California), one would expect
a strong correlation between the "average" concentrations
and the vegetation response. Those experiments that contain a
large frequency of elevated ozone hourly average concentrations
would be expected to correlate experimental-period average concentrations
with effects.
Clarifying Statement on
Use of 8-Hour Average versus Cumulative W126 Exposure Index
One commenter focused on the results of Percy et al. (2006, 2009),
who used FACE open air exposures. Although the commenter inferred
that the W126 exposure index did not perform well in the Percy
et al. (2006) analysis, in fact, Percy et al. (2006) did not
include the W126 exposure index in their mathematical analysis.
In Percy et al. (2009), the authors reported that the best-performing
single exposure index was the W126, which outperformed the 4th
highest 8-h average concentration exposure index (Table 11.2
in Percy et al., 2009). However, upon carefully reviewing the
description of how the W126 was calculated by the authors, it
appears that the W126 may not have been properly calculated by
Percy et al. (2009) in their analysis. In footnote (e) of Table
11.2 in Percy et al. (2009) (page 280), the authors indicate
that the growing season W126 is calculated as the "concentration-weighted
sum of 24 h average hourly ozone concentrations."
It may be possible that the authors meant that they accumulated
the concentration-weighted sum over a 24-h period. However, this
is not what Percy et al. (2009) indicated in footnote "e".
If the authors determined a 24-h average concentration and then
weighted that value, then this is an incorrect calculation for
the W126 as described by Lefohn et al. (1988). The W126 is calculated
by weighting each hourly average ozone concentration with a sigmoidal
weighting between zero and one and summing the product of each
concentration multiplied by its sigmoidal weighting over the
period of time of interest. In footnote "e", Percy
et al. (2009) cite a Table 4 in Percy and Karnosky (2007) as
explaining the calculation of their determined W126. In reviewing
Percy and Karnosky (2007), there does not appear to be a Table
4. In their paper, Percy et al. (2009) do not appear to present
strong numerical evidence for ignoring their calculated W126
index. Musselman and Lefohn (2007) commented on the findings
of Percy et al. (2007), which was similar to the Percy et al.
(2006) paper that was delivered in Austria in 2005. Musselman
and Lefohn (2007) reported that it was important to note that
the study conclusions by Percy et al. (2007) were derived with
data from fumigation exposures with high hourly average concentrations
in the experimental chambers and the 8-h average concentrations
may be highly correlated with the frequent occurrences of these
elevated levels. The 4th highest 8-hour average concentrations
ranged as high as 94 ppb for the elevated fumigation exposure
regimes. The 1-hour maximum concentrations were approximately
100 ppb. This implies that at actual locations in the U.S. and
Canada that experience infrequent occurrences of elevated hourly
average ozone concentrations, the Percy et al. (2006, 2007) model
may not adequately relate the fourth highest 8-h average concentrations
with effects. It is important to note that the same commenter
also noted elsewhere in their comments the concern that open-top
chambers (OTCs) or open air exposures (FACE) are primarily univariate
studies with very limited number of treatments that cannot fully
explain the plant response surface and the stochastic (random)
relationships between cause and effects. Thus, the commenter
appeared to endorse the Percy (2006, 2009) results, while questioning
the relevance of the experimental data used in the Percy et al.
(2006, 2009) conclusions.
6. Scientific Fact on Understanding
and Calculation of the W126 Index
The concept of the W126 exposure index is to apply a weighting
that provides greater emphasis on the higher hourly average ozone
concentrations than on the mid- and low-level values. The calculation
is made by using a formula
that can be used in a spreadsheet to convert hourly ambient ozone
averages to weighted W126 values.
Clarifying Statement on
Review Comment on Understanding and Calculation of the W126
One commenter stated that the W126 exposure index is too complicated
to understand and that therefore the 8-hour standard should be
used as the secondary ozone standard. The equation of the W126
exposure index is simply programmed into a computer and used
to determine the relevant adjusted concentration-weighted hourly
ozone value. The key is that the W126 places greater biological
emphasis on the higher hourly average ozone concentrations than
the mid- and low-level values and it is not necessary for one
to understand the details associated with the mathematical equation
unless they are interested in further understanding the theory
behind the calculations. Almost all of the technical comments
indicated that the reviewers had been able to calculate the W126
index and understood the details associated with the mathematics.
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