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 an
effect of the magnitude of the concentration than the length
of the exposure.
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 lack of hourly average concentrations
near the minimum detectable level and may or may not be biologically
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
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
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 concentrations were included in the integrated
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 can 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 detoxification processes, including their temporal variability
and relevance, are important and cannot be ignored when predicting
vegetation effects (Musselman et al., 2006; Heath et al., 2009).
As discussed in Musselman et al. (2006), the use of a "threshold"
in flux-based models will not serve as a methematical surrogate
for the detoxification process. An important paper by Wang et
al. (2015) appears to substantiate the conclusions of Heath et
While future research
should focus on the use of flux-based indices that include 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 exposure 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. 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
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. Recognizing
the limitations of applying exposure indices as dose surrogates,
at this time, the cumulative exposure index may still be the
best family of indices available for relating exposure and biological
Today, many vegetation scientists use cumulative
exposure indices that weights the higher hourly average concentrations
more than the mid- and lower-level values. The U.S. Forest Service
and Park Service are using the sigmoidally weighted W126 exposure
index to assess the potential impact of ozone on vegetation.
Heath R. L., Lefohn A. S., and Musselman
R. C. (2009). Temporal processes that contribute to nonlinearity
in vegetation responses to ozone exposure and dose. Atmospheric
Lefohn A.S. and Runeckles V.C. (1987) Establishing
a standard to protect vegetation - ozone exposure/dose considerations.
Atmos. Environ. 21:561-568.
Lefohn, A.S. and Musselman, R.C. (2005)
The Strengths and Weaknesses of Exposure- and Flux-Based Ozone
Indices for Predicting Vegetation Effects. Presented at the Critical
levels of ozone: further applying and developing the flux-based
concept. Obergurgl, Tyrol, Austria. November 15-19, 2005.
Lefohn A.S., Laurence J.A. and Kohut R.J.
(1988) A comparison of indices that describe the relationship
between exposure to ozone and reduction in the yield of agricultural
crops. Atmos. Environ. 22:1229-1240.
Musselman, R.C., Lefohn, A.S., Massman,
W.J., and Heath, R.L. (2006) A critical review and analysis of
the use of exposure- and flux-based ozone indices for predicting
vegetation effects. Atmos. Environ. (Accepted).
U.S. Environmental Protection Agency (1996)
Air quality criteria for ozone and related photochemical oxidants.
Environmental Protection Agency, Office of Air Quality Planning
and Standards, Research Triangle Park, NC. U.S. EPA report no.
Wang, L., Pang, J., Feng,
Z., Zhu, J., Kazuhiko, K. (2015) Diurnal variation of apoplastic
ascorbate in winter wheat leaves in relation to ozone detoxification.
Environmental Pollutution. 207:413-419.