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, as well as the accumulation of enhanced
hourly average ozone concentrations. Many scientists continue
to cite the magnitude of 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. In some cases, the seasonal average of the daily maximum
of the 8-h average concentration has been used in assessing vegetation
injury and damage. For example, the cumulative 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
stating 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 in the US ozone
rulemaking process many years ago 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 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 no peaks. 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 (e.g., 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 limitations.
Depending upon the threshold concentration used, the parameter
ignored the hourly mean concentrations below the selected threshold.
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, which weighted the higher hourly average ozone concentrations
more than the lower values and summed the product of weighted
concentration multiplied by time, over the duration of the exposure.
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 weighted 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
concluded that the use of cumulative indices to describe exposures
of ozone for predicting tree effects and agricultural crop effects
appeared 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) appeared 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, as well as flux-based 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. Results published in the literature under experimental
and ambient forest conditions in the 1980s and 1990s provide
researchers with clear guidance about 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 evaluated to better
understand the limitations associated with the adequacy of the
predictive capability of these models. Research results have
indicated the importance of the diurnal variability of detoxification
in vegetation and how the selection of constant thresholds over
time in flux-based models to represent detoxification is not
necessarily 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
than the higher hourly average concentrations. For example, in
the United States, the U.S. EPA, U.S. Forest Service, and National
Park Service continue to use the sigmoidally weighted W126 exposure
index to assess the potential impact of ozone on vegetation.
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