United States
Environmental Protection
Agency
Environmental Sciences Research
Laboratory
Research Triangle Park NC 27711
Research and Development
EPA-600/S3-83-003 Mar. 1983
SERA Project Summary
Evaluation of the Empirical
Kinetic Modeling Approach
(EKMA)
J. R. Martinez, C. Maxwell, H. S. Janitz, and R. Bawol
During the period 15 September
through 12 October 1978, the U.S.
Environmental Protection Agency
(EPA) conducted a special program that
monitored air quality and meteorology
in the Houston, Texas area. The objec-
tives of the program were to obtain a
comprehensive data base suitable for
use with photochemical air-quality sim-
ulation models and to provide a detailed
body of data to be used to investigate
Houston's air quality in general and
photochemical oxidants (HOMS study)
and aerosols (HACS study) in particular.
The objectives of this contract were
(a) to evaluate the suitability of the
1978 Houston data base for photochem-
ical modeling application, (b) to analyze
spatial and temporal patterns of
pollutant concentrations, (c) to archive
data in a manner suitable for use with air
quality simulation models, (d) to
analyze and characterize the quality of
the gaseous pollutant measurements,
and (e) to use the data to evaluate the
performance of the EKMA photochem-
ical model. Results from the data
evaluation and archiving work were
reported in a three-volume report. Re-
sults from the EKMA evaluation work
are reported in this separate report.
The EKMA-related effort was to
evaluate the performance of EKMA
when it is used to estimate the
maximum ozone concentration that can
occur in an urban area and its environs.
The evaluation was conducted using
data for five U.S. cities: St. Louis,
Houston, Philadelphia, Los Angeles,
and Tulsa.
A novel statistical evaluation
procedure was developed to measure
the accuracy of the EKMA ozone
estimates. The accuracy parameter is
defined as the ratio of observed to
estimated ozone. The evaluation
procedure uses NMOC and NO, as
inputs to calculate the accuracy proba-
bility of the EKMA ozone estimate. The
full range of accuracy probabilities
associated with the EKMA ozone
estimates is displayed in graphical form
on the NMOC-NOx plane.
This Project Summary was developed
by EPA's Environmental Sciences Re-
search Laboratory, Research Triangle
Park, NC, to announce key findings of
the research project that is fully docu-
mented in a separate report of the same
title (see Project Report ordering infor-
mation at back).
Introduction
A common problem in air pollution
control requires estimating the reduction
in the level of 03 precursors, i.e.
nonmethane organic compounds
(NMOC) and nitrogen oxides (NOx),
needed to achieve a prescribed decrease
in O3concentration. To solve this problem,
a model that relates O3 to NMOC and NOX
is needed; the EKMA, developed by the
U.S. Environmental Protection Agency
(EPA), is one such model. The EKMA
model takes two forms: standard and city-
specific. The standard EKMA is based on
conditions that prevail in the Los Angeles
area; the city-specific version, as the
name implies, tailors the model to a
particular city. The objective of this study
is to assess the performance of EKMA
when it is used to estimate the maximum
ozone (O3) concentration that could occur
in an urban area and its environs.
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Specifically, the study quantitatively
measures EKMA's ability to predict
maximum 03, defines conditions under
which O3 estimates can achieve specific
accuracy levels, and examines the
application of EKMA as an estimator of
maximum O3.
Methodology
The first step in the evaluation process
identified and obtained the data bases for
the five cities of interest: St. Louis,
Missouri; Houston, Texas; Philadelphia,
Pennsylvania; Los Angeles, California;
and Tulsa, Oklahoma. For each city, the
model assessment procedure consisted
of three steps:
1. Review and analyze data and select
days for the evaluation data set.
2. Obtain ozone estimates using both
standard and city-specific EKMA.
3. Conduct a statistical evaluation of
EKMA performance as a predictor of
maximum O3.
The criteria for selecting days for the
evaluation data set comprised:
1. Data availability
2. The time of occurrence of the daily
ozone maximum
3. The prevalence of meteorological
(e.g., temperature, sunlight) and
NMOC, NOx conditions that are
necessary (but not necessarily
sufficient) for the 03 level to be at
least 1OO ppb.
The 100-ppb cutoff was chosen to ensure
that all days when the ozone national
ambient air quality standard (NAAQS) of
120 ppb was exceeded are included in the
evaluation.
The evaluation was designed to test
whether EKMA can be used to estimate
an upper bound for observed daily
maximum ozone concentrations. EKMA
estimates are an upper bound if they are
equal to or higher than the observed
maximum on every day. Assuming a ±20
percent error in the measurements of 03,
NMOC, and NOx, the premise was
adopted that EKMA estimates are an
upper bound if they are within ±20
percent of the observed O3 maximum
values. Estimates lower than the
observed O3 values by more than 20
percent mean that EKMA underpredicts;
estimates higher than the observed 03
values by more than 20 percent mean
that EKMA overpredicts. Besides deter-
mining whether EKMA, overall, is
overpredicting or underpredicting O3 air
quality, the investigators developed a
method for defining regions on the
NMOC-NOx plane where the EKMA
estimates attain prescribed levels of
predictive accuracy.
Results
The results of the St. Louis data
analysis indicate that both standard and
city-specific (C-S) EKMA can be used to
obtain ozone estimates that are upper
bounds for the observations. More
precisely, an estimate has a high proba-
bility of being an upper bound if its
(NMOC, NOx) coordinates fall in certain
specific areas of the NMOC-NOx plane. In
general, high NMOC and NOX lead to
upper bound estimates, and low NMOC
and NOx lead to underestimates. The C-S
EKMA's O3 estimates were generally
more accurate than the standard
EKMA's.
For both HAOS and HOMS sets of
Houston data, the EKMA substantially
overpredicted in the standard mode, and
underpredicted in the city-specific mode.
As a result, the probability of an accurate
prediction for the HAOS data was
generally low. In the city-specific case,
the multiple regression fit to the ratio of
observation -to- C-S-EKMA estimate had
a large standard error that is indicative of
a low-precision fit. In general, it appears
that in either mode the EKMA tends to be
a low-accuracy predictor of ozone for the
Houston area. To obtain an upper bound
for the maximum potential ozone in the
Houston area, the standard-EKMA mode
is the appropriate choice, because it has a
low probability of underestimating the
ozone level.
For Philadelphia, the standard and city-
specific EKMA ozone estimates were very
similar. However, in a reversal of roles
from the St. Louis and Houston cases,
the Philadelphia C-S estimates were
more accurate and displayed a lower
tendency toward underprediction than
did the standard-EKMA estimates.
However, in keeping with previous
results, the standard EKMA ozone
estimates showed a pronounced
tendency toward overprediction. Because
the city-specific EKMA yielded more
accurate estimates, and because its
upper-bound properties are similar to the
standard EKMA's it is recommended that
the city-specific EKMA, rather than the
standard EKMA, should be the method
used for application to the Philadelphia
area. This contrasts with the Houston
situation, in which the underpredictive
tendency of the city-specific EKMA
renders it useless for an upper-bound
type of analysis.
For Los Angeles, it was surprising that
the standard-EKMA yielded so many
underestimates, indicating that the worst-
case conditions supposedly embodied in
the standard EKMA do not in fact define a
worst case. The city-specific EKMA, by
contrast, yielded a large majority of over-
estimates. This suggests that the city-
specific EKMA is the operational mode of
choice for the purpose of obtaining an
upper bound for ozone, although the
magnitude of the overprediction can be
very large.
Finally, the small sample size precluded
drawing general conclusions about EKMA
performance in the Tulsa area; however,
a few cautionary remarks should none-
theless be made. In using the EKMA, it is
important to have a reasonably well-
defined source region. The Tulsa applica-
tion revealed that the source region was
either inadequately defined or it does not
exist. In either case, the use of EKMA in
the Tulsa context would be inappropriate.
Thus, any further attempts to apply the
EKMA to Tulsa should be preceded by an
investigation of the source distribution,
with the aim of determining whether the
source-region concept that underlies the
EKMA fits Tulsa's conditions.
Conclusions and
Recommendations
This study has:
1. Demonstrated the feasibility of using
the EKMA to estimate upper bounds
for daily maximum ozone, given the
concentration of NMOC and NOX.
2. Shown that the accuracy of the
EKMA ozone estimates is a function
of the position of the estimate on the
03 isopleth diagram, the position
being determined by the (NMOC,
NOx) coordinates.
3. Developed a general method for
evaluating EKMA performance as a
predictor of maximum ozone.
The results indicate that it is possible to
use the EKMA, in either the standard or
city-specific form, to estimate an upper
bound for daily maximum ozone, given
the concentration of NMOC and NOX.
However, for a certain range of values of
NMOC and NOX, the upper bound can be
very loose, and thus of limited
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usefulness. The EKMA also can produce
ozone estimates that are accurate to
within ±20 percent of the observations.
Estimates of this accuracy can be
obtained only for a restricted range of
values of NMOC and NOx. In some cases,
(e.g., St. Louis), the range of values of
NMOC and NOX that determines the
accuracy of the estimates is dependent in
turn on such other variables as
background ozone level and maximum
daily temperature.
The study's use of several distinct data
bases leads generally to the conclusions
discussed above. Nevertheless, the
numerical results are limited in scope, in
the sense that they strictly apply only to
the particular data sets examined. Unless
these data sets can be considered to be
representative of conditions in their
respective geographical areas, the
application of the findings derived in this
study to other geographical regions, or to
the same regions in other years, must be
regarded with caution. Such restrictions
are, of course, typical of most data-
analytic studies.
We regard the evaluation methodology
developed in the study as an important
contribution. The methods are general,
and the numerical results reported are
real-life examples of what can be
accomplished with these techniques. In
the future, the same methodology can be
applied to other data bases to extend and
generalize further the results reported
here, as recommended below.
We propose three extensions of the
current research:
1. Further evaluations of the EKMA,
using the methods developed in this
study. Specifically, evaluation should
be performed using data for other
years in St. Louis, Houston,
Philadelphia, and Los Angeles. Only
these four urban areas are
recommended, because the Tulsa
data base that is normally available is
not sufficiently detailed for such
analysis. Addition of some new areas
to the extended evaluation should
also be considered, provided that at
least two years of data are available
for each area.
2. Application of the results of this
study to the analysis and design of
ozone control strategies.
3. EPA sponsorship of an effort to
derive a general transformation
between standard and city-specific
EKMA ozone estimates.
J. R. Martinez. C. Maxwell, H. S. Janitz, and R. Bawol are with SRI International,
Menlo Park, CA 94025.
Basil Dimitriades is the EPA Project Officer (see below).
The complete report, entitled "Evaluation of the Empirical Kinetic Modeling
Approach (EKMA)." (Order No. PB83-165 191; Cost: $14.50, subject to change)
will be available only from:
National Technical Information Service
5285 Port Royal Road
Springfield, VA 22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Environmental Sciences Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
U.S. GOVERNMENT PRINTING OFFICE- 1983-659-017/7010
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