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Biologically Meaningful Characterization

Before one can characterize hourly average concentrations in a biologically meaningful way, it is necessary to understand the relationship between exposure and vegetation effects. The search for an exposure index that relates well with plant response has been the subject of intensive discussion in the research community. Both the magnitude of a pollutant's concentration and the length of exposure are important considerations when attempting to develop a realistic exposure index. Evidence exists in the literature to indicate that the magnitude of vegetation responses to air pollution is more related to the magnitude of the concentration than the length of the exposure. In other words, the concept of Haber's Rule of concentration multiplied by time is a constant in relation to dose does not apply when assessing the effects of ozone dose on vegetation. The observation is the same for human health as noted by Silverman et al. (1976), Drechsler-Parks (1990), Hazucha et al. (1992), Adams (2003, 2006), Hazucha and Lefohn (2007), and Lefohn et al. (2010). Should you wish to read more about this subject, there is a discussion in Section 2.4 in Lefohn (2020).

Several different types of exposure indices have been proposed. Both the 6-h and 7-h long-term seasonal mean ozone exposure parameter have been used to relate vegetation effects with exposure. The 7-h (0900-1559h) mean, calculated over an experimental period, was adopted as the statistic of choice by the U.S. EPA's National Crop Loss Assessment Network (NCLAN) program. Toward the end of the program, NCLAN redesigned its experimental protocol and applied proportional additions of ozone to its crops for 12-h periods.

The use of a long-term average concentration, such as the 7- or 12-h average, for describing concentration exposures does not provide accurate descriptions of exposures that actually occur. For example, some high-elevation sites exhibit ozone exposure characteristics that are distinctly different from those observed at lower elevation sites. The long-term averages calculated at some high-elevation sites tend to be higher than the long-term averages at lower elevation sites. The higher long-term averages reflect the infrequent number of hourly average concentrations near the minimum detectable level and the magnitude of the long-term average may or may not be biologically significant for either vegetation or human health effects. An important aspect that is overlooked is that it is important when citing long-term average values and relating them to biological effects, the integration period used to average the hourly average concentrations is important. Many scientists continue to cite 7-h or 12-h average concentrations for specific experiments without specifying the period of the averaging (e.g., 3-months, 6-month, etc.) when attempting to assess vegetation effects. The period of the averaging time is important because a 12-h average of 50 ppb over a 1-month period will elicit a very different vegetation effect than a 12-h average of 50 ppb over a 6-month period. Simply saying that a 12-h 50 ppb average elicits a 20% yield reduction is irrelevant without citing the number of months of exposure. As explained below, the use of a 7- or 12-h daily average accumulated over a period of time is not an appropriate metric to use in assessing vegetation effects. This was discussed by the US EPA (1986).

From the middle 1960s through the middle 1980s, studies published in the literature identified short-term, high concentration (i.e., episodic) ozone exposures as important components of agricultural crop effects and trees. The short-term, high concentration exposures were identified by many researchers as being more important than long-term, low concentration exposures.

As additional evidence began to mount that higher concentrations of ozone should be given more weight than lower concentrations, concerns about the use of a long-term average to summarize exposures of ozone began appearing in the literature. Specific concerns were focused on the fact that the use of a long-term average failed to consider the impact of peak concentrations. The 7-h seasonal mean contained all hourly concentrations between 0900-1559h; this long-term average treated all concentrations within the fixed window in a similar manner. An infinite number of hourly distributions within the 0900-1559h window could be used to generate the same 7-h seasonal mean, ranging from those containing many peaks to those containing none. It was pointed out in the literature that it was possible for two air sampling sites with the same daytime arithmetic mean ozone concentration to experience different estimated crop reductions.

In the late 1980s, the focus of attention turned from the use of long-term seasonal means to cumulative indices (i.e., exposure parameters that sum the products of concentrations multiplied by time over an exposure period using a threshold concentration). The use of the cumulative exposure index with a threshold concentration had some limitations. Depending upon the threshold concentration used, the parameter ignored the lower hourly mean concentrations. However, the parameters appeared to relate ozone exposure with observed functional change at monitoring sites that experienced (1) repeated high concentration exposures from day-to-day and (2) relatively short periods between episodes.

Recognizing the disadvantage of using a threshold concentration with the cumulative index, a modification was suggested that applied differential weighting to the hourly mean concentrations of ozone and summing over time. Lefohn and Runeckles (1987) proposed a sigmoidal weighting function that was used in developing a cumulative integrated exposure index. The sigmoidal weighting function was multiplied by each of the hourly mean concentrations; thus, the lower, less biologically effective hourly average concentrations were included in the integrated exposure summation, but were provided less weight than the higher concentrations.

The form of the sigmoidally weighted index was tested using NCLAN data. Lefohn et al. (1988) showed that exposure indices that weight peak concentrations of ozone differently than lower concentrations of an exposure regime could be used in the development of exposure-response functions.

Based on evidence published in the literature, as well as special analytical studies sponsored by the U.S. EPA (1996), many in the research community have concluded that the use of cumulative indices to describe exposures of ozone for predicting trees and agricultural crop effects appears to be a more rational approach than the use of long-term seasonal averages.

Exposure-based metrics are traditionally used to relate O3 to vegetation response. Flux-based models have been developed to predict the effects of O3 on vegetation. Because plant response is more closely related to O3 absorbed into leaf tissue than to exposure, it is often assumed that flux-based models offer less uncertainty in predicting vegetation effects than the use of exposure-based metrics. Lefohn and Musselman (2005) and Musselman et al. (2006) discussed the advantages and limitations associated with the use of flux-based models for predicting vegetation effects. An important aspect associated with adequately predicting the effects of O3 on vegetation is identification and quantification of the detoxification processes. The daily and seasonal temporal variability associated with detoxification processes are important and cannot be ignored when using flux-based models to predict vegetation effects (Musselman et al., 2006; Heath et al., 2009). As discussed in Musselman et al. (2006), the use of a constant (i.e., threshold) in flux-based models cannot adequately serve as a methematical surrogate for detoxification considerations. An important paper by Goumenaki et al. (2021) appears to substantiate the observations described in Heath et al. (2009).

While future research continues to focus on the use of flux-based indices that include daily and seasonal temporal variability associated with detoxificaton processes, it is important to continue to identify the family of cumulative indices that best describe the relationship between ozone exposure and vegetation effects. One needs to be aware that both exposure indices and flux-based indices will continue to produce inconsistent results when trying to predict growth losses. Most exposure indices are insensitive to diurnal periods of maximum sensitivity of the plant. The sensitivity of vegetation as a function of the time of day has not been well defined and is an important consideration for both exposure indices, as well as flux-based indices. In addition, as described in the literature, the distribution patterns of the hourly average concentrations for some high-elevation and low-elevation sites are different. Most cumulative-type and other exposure indices, as well as flux-based indices cannot adequately describe some of the subtle differences in the two different types of exposure regimes. Besides sensitivity, the majority of exposure indices used today do not address (1) the amount and chemical form of the pollutant that enters the target organism (i.e., stomata considerations), (2) the length of the exposure within each episodic event, or (3) the time between exposures (i.e., the respite or recovery time). It is unclear how important sensitivity and the amount and chemical form of the pollutant that enters the target organism are in an overall weighting scheme when predicting vegetation effects. If both the sensitivity of the target organism and the actual dose that enters the organism are as important as ambient air pollutant exposure, then a given pollutant exposure will elicit varying biological responses at different times for the same crop. While recognizing the limitations of applying exposure indices as dose surrogates, at this time, the cumulative exposure index appears to be the best family of indices available for relating exposure and biological response. Resultes published in the literature under experimental and ambient forest conditions in the 1980s and 1990s provide researchers with clear guidance on the importance of the weighting of the higher hourly average ozone concentrations in comparison to the mid- and low-level values (please see Section 2 of Lefohn et al., 2018 for a list of studies). Models that question the fundamental principle of the importance of the higher hourly average ozone concentrations should be further investigated to better understand the limitations associated with the adequacy of the predictive capability of these models. Recent research results have indicated the importance of the diurnal variability of detoxification and how the selection of constant thresholds in flux-based models to represent detoxification may not be appropriate. Clearly, more work is required in this important research area.

Today, many vegetation scientists use cumulative exposure indices that weight the higher hourly average concentrations more than the mid- and lower-level values. The mid- and low-level concentrations are not ignored, but rather weighted differently that the higher hourly average concentrations. The U.S. EPA, U.S. Forest Service, and National Park Service use the sigmoidally weighted W126 exposure index to assess the potential impact of ozone on vegetation.


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