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Response to Selected Comments Associated with the W126 Exposure Index in Docket ID No. EPA-HQ-OAR-2005 -0172 reviewed at the URL:

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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Heath, R.L.; Lefohn, A.S.; Musselman, R.C. (2009). Temporal processes that contribute to nonlinearity in vegetation responses to ozone exposure and dose. Atmospheric Environment 43:2919-2928.

Heck, W.W.; Dunning, J.A.; Hindawi, I.J. (1966). Ozone: nonlinear relation of dose and injury in plants. Science 151, 577-578.

Lee, E.H.; Tingey, D.T.; Hogsett, W.E. (1987). Selection of the Best Exposure-response Model Using Various 7-h Ozone Exposure Statistics. US Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC.

Lee, E.H.; Tingey. D.T.; Hogsett, W.E. (1988). Evaluation of ozone exposure indices in exposure-response modeling. Environmental Pollution 53, 43-62.

Lee, E.H.; Hogsett, W.E. (1999). Role of concentration and time of day in developing ozone exposure indices for a secondary standard. J. Air & Waste Manage. Assoc. 49:669-681.

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Percy, K.; Nosal, M.; Heilman, W.; Dann, T.; Sober, J.; Legge, A.H.; Karnosky, D. (2007) New exposure-based metric approach for evaluating O3 risk to North American aspen forests. Environ. Pollut. 147:554-566.

Percy, K.E.; Nosal, M.; Heilman, W.; Sober, J.; Dann, T.; Karnosky, D.F. (2009) Ozone-exposure based growth response models for trembling aspen and white birch. In: Legge, A.H. ed. Air Quality and Ecological Effects. Relating Sources to Effects. Elsevier Science, Amsterdam, The Netherlands, p 269-293.

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