United States
                   Environmental Protection
                   Agency	
Atmospheric Research and
Exposure Assessment Laboratory
Research Triangle Park, NC 2771 1
                              'V
                   Research and Development
EPA/600/S3-89/071 Sept. 1989
v°/EPA         Project  Summary
                   Air  Quality Simulation  Model
                   Performance  for  One-Hour
                   Averages

                   G. E. Moore, T. E. Stoeckenius, Steve Hanna, and Dave Strimitas
                     If  a one-hour standard for sulfur
                  dioxide were promulgated, air quality
                  dispersion modeling in the vicinity of
                  major point sources  would be  an
                  important air  quality  management
                  tool.  Would  currently available
                  dispersion  models  be suitable for
                  use in demonstrating  attainment of
                  such a standard  in the vicinity of
                  large,  elevated, buoyant  point
                  sources such as utility power plants?
                  The results summarized in this report
                  suggest that using these models in
                  connection  with an hourly average
                  standard does  not  present  the
                  regulatory  community with any
                  significant  additional  uncertainties
                  that are not already being dealt with
                  in connection with the  current 3- and
                  24-hour standards. Predictions of
                  peak hourly average concentrations
                  unmatched  in  time  or location are
                  slightly  more  conservative on
                  average  than  corresponding
                  predictions  of  3-  and  24-hour
                  averages.  Although   certain
                  conditions not specifically, treated by
                  the models,  such as inversion break-
                  up fumigation, are known to occur
                  and  to  have  the potential  for
                  producing high ground-level impacts,
                  these conditions have  been  only
                  rarely observed in model evaluation
                  studies  and  do  not seem  to
                  contribute to  the bulk of the  50
                  highest concentrations. In fact, nearly
                  all of the highest  concentrations
                  observed  in the evaluation studies
                  examined  occurred under convective
                  conditions, which  are treated by the
                  existing  models.  Peak  model
                  predictions  under such conditions
match  reasonably  well  with the
highest  observed concentrations,
although large prediction errors can
occur  in  any  given  hour.
Consideration of situations involving
impacts  on elevated terrain or
building downwash phenomena have
been explicitly excluded. This review
of the results of model evaluation
studies was restricted to some fairly
simple analyses. Additional analyses
are   recommended.   Recom-
mendations  to improve model
formulations are made regarding the
treatment of plume  behavior in the
vicinity of the mixing height and the
simulation of plume dispersion within
the mixed  layer during convective
conditions.
   This Project Summary   was
developed by  EPA's Atmospheric
Research and  Exposure Assessment
Laboratory,  Research Triangle  Park,
NC, to announce key findings of the
research  project  that   is  fully
documented in  a separate  report of
the same title  (see Project Report
ordering information at back).

Introduction
  An analysis of the results of previous
dispersion model performance evaluation
studies has been conducted to ascertain
the suitability of  currently used models
for the prediction of hourly  average
concentrations.  This investigation was
motivated by the potential promulgation
of a statistical (expected exceedance) 1-
hour  S02 NAAQS. Implementation of
such a standard would rely largely on the
use of dispersion models  that are
capable of  accurately predicting the

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whole upper tail of the  distribution of
hourly average  S02 concentrations, not
just  the highest  or  second  highest
concentrations.
   Our analysis was confined to the study
of model performance  for  elevated,
buoyant point sources  of  the  type
typically associated with  fossil fuel-fired
power plants.  Such sources  represent
one  of  the  major  areas  of  model
application for  the prediction  of S02 air
quality impacts. We conducted analyses
designed to address the following issues:
     How well do models predict the 1,
     2	N highest concentrations
     irrespective  of  time or location
     matching?
     How well do models predict the 1,
     2,  . .  .  , N  highest  observed
     concentrations  when  observations
     and  predictions  are  matched in
     time but not location?
     How  well do  models  predict
     concentrations occurring  under
     specific  meteorological conditions?
     More  specifically, what meteoro-
     logical  conditions  produce  the
     highest observed concentrations?
     What conditions are associated with
     the largest discrepancies between
     observed   and    predicted
     concentrations?
   To answer the above questions, we
reviewed the  published  results of
previous model performance studies and,
whenever possible,  obtained  the
aerometric and meteorological data from
those studies for further analysis.

Model  Performance: Ability to
Predict Peak Concentrations
   Short  term  (1- to 24-hour average)
ambient  air  quality standards  are
designed to control the  magnitude and
frequency of occurrence of  peak ground-
level concentrations. Demonstrating that
the emissions from a major source do not
violate such standards often involves the
use of a dispersion model to  predict the
highest  concentrations occurring over a
one- to  five-year period in the vicinity of
the  source.  A  model's  ability to
accurately and precisely predict peak
concentrations  is  therefore  very
important. However, a model need not
necessarily predict the exact time and
location  of  the peak values as  this
information is not  usually  of  direct
relevance   to  the   attainment
demonstration.  On  the other  hand,
examining a model's ability to reproduce
the N highest observed concentrations
during the hours in which they occur (i.e.,
matching concentrations in time) provides
insight  into the  types  of meteorological
conditions  under  which  models  do
especially well or poorly and the reasons
for such performance. This information, in
turn, can be used as a guide to improving
models  and to the level of performance
that can be anticipated from a  given
model under a given situation.

Concentrations Unmatched in
Time or Location
  We  examined  the  performance  of
models  in  predicting  the  N  highest
concentrations  (typically  around  25)
regardless of  their time or  location  of
occurrence.  In  some cases,  only
comparisons of  the highest  and second
highest observed  and   predicted
concentrations  were  available. We
caution  the reader that it is difficult to
draw  generalizations  from  such
comparisons because  the  highest and
second  highest concentrations usually
have a large degree of variability.
  With  the exception  of the  Maryland
Power Plant Siting study (for which  a
value of  N = 50 was used), the CRSTER
and equivalent  models tend   to
overpredict   slightly  the   peak
concentrations  (N  less than  or equal to
25)  or produce no significant bias. TEM,
on the other hand, underpredicts at some
sites and produces no  significant bias at
others.  The only other  models for which
evaluation results are available from more
than one site are PPSP and MPSDM.
PPSP overpredicts  consistently  at  all
sites, in  some  cases  by  more than  a
factor  of two.  MPSDM also produced
significant overpredictions.

Model Performance for Hourly
Averages Compared with
Performance for 3- and 24-Hour
Averages
  Would  implementation  of  a  1-hour
average NAAQS for  S02 result  in
significantly greater modeling uncertainty
than currently  exists in demonstrating
attainment of the 3- and 24-hour NAAQS?
To answer this question, we  reviewed an
analysis of the  variation  in  model
performance  with  averaging time  by
Hayes. This study showed that the ratio
of  the  average  of the  25  highest
predictions to  the average of the  25
highest  observations (unmatched in time
or location) decreases with increasing
averaging time for all models included  in
the EPA Rural  Model  Evaluation  Study,
the CEQM model at EPRI PMV Kincaid,
and for  RAM  (but not  TEM) in the EPA
Urban Model Evaluation Study.  Results
for  ratios  of the highest and  second
highest concentrations were mixed. Thus,
models that overpredict peak 3-  and 24-
hour averages tend  to overpredict peak
hourly averages  by  a greater amount,
while models that underpredict  peak  3-
and 24-hour averages may overpredict
peak hourly averages. This suggests that,
at least as far as  bias goes,  shifting
emphasis from 3- and 24-hour averages
to 1-hour  averages  will  result in  more
conservative predictions  of peak
concentrations.
   The  study  also  examined  the
correlation between observations  and
predictions paired in  time but not location
as a function  of averaging  time at the
EPRI PMV Kincaid site using the CEQM
model.  The  results   indicate that
correlations for 3-hour averages are only
slightly  better than those for  hourly
averages,  while the  correlation  for 24-
hour averages is not  significantly different
from that of hourly  averages.  Thus, the
model's  skill  in  predicting  hourly
averages does not  appear  to be very
much worse  than it is for 3- and 24-hour
averages.

Concentrations Matched in Time
   A model's  ability to  predict  peak
concentrations can also be examined by
comparing  the  N  highest  observed
concentrations  with  the  highest
concentrations predicted during the same
hours  (i.e.,  compare  concentrations
matched in time  but not location for the
hours with  the   N  highest  observed
concentrations).  Such  a comparison
evaluated  the   model's  ability   to
reproduce  high observed concentrations
under  the  specific  meteorological
conditions  that cause them (exclusive  of
wind direction).
   As has  been  demonstrated by EPRI
and other  studies, correlations  between
time- matched observed  and predicted
concentrations are generally very low  or
not significantly  different  from  zero.
Correlations for just the hours with the 50
highest  observed  concentrations are not
significantly different from zero except for
the PPSP  and RTDM  models. Also, the
number of predictions falling within  a
factor of two of the  observations is less
than 32 percent except for  RTDM anc
PPSP.
   On the  basis of the above findings, we
conclude that the poor  model  skill  foi
time-paired observations and predictions
is primarily the result of two factors:
   1. Meteorological  inputs  to the
     dispersion  models do not reliably

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      represent atmospheric conditions
      occurring in a particular hour.
   2. Model formulations  are insufficient
      to  describe  the  actual  plume
      behaviors that lead  to the  highest
      observed concentrations.

 Model Performance Under
 Specific Dispersion Conditions
   One concern  with using  presently
 available dispersion models  to  perform
 attainment  demonstrations for an hourly
 average  ambient standard is  that these
 models may not adequately reproduce all
 of  the various types  of dispersion
 phenomena that can lead to  high hourly
 average  concentrations.  We performed
 several analyses in an  attempt to identify
 dispersion  conditions  and  plume
 behaviors that are associated  with high
 observed concentrations  and to  estimate
 how well the models perform under such
 conditions.

 Plume Behaviors and Dispersion
 Conditions Potentially Resulting
 in High Concentrations
   A great deal of meteorological and
 aerometric data is needed to adequately
 explain the specific dispersion conditions
 and plume behaviors that lead  to a high
 observed  hourly average  concentration.
 No model evaluation study carried out to
 date has  involved the  collection  of
 enough   data  to  allow  one  to
 unequivocally group  hours  with  high
 observed concentrations into a handful of
 well-defined categories  of  dispersion
 conditions and plume  behaviors. Enough
 information from previous theoretical,
 field,  and  laboratory studies is  now
 available to make it possible to  describe
 several general types of plume  behaviors
 and dispersion conditions that can, and in
 some cases have actually been observed
 to,  lead  to high ground-level  concen-
 trations or large discrepancies  between
 observed and  predicted concentrations in
 the  vicinity of elevated,  buoyant  point
 sources.  Plume  behaviors  considered
 are.  convective fumigation,  moderate
 wind  convection, bumping-loopmg,
 limited rise,  plume  penetration, and
 inversion  break-up  or  shoreline
 fumigation.

 Applicability of Model
 Formulations to Important
 Plume Behaviors
   No presently  available point source
Dispersion  model contains  all  of the
Algorithms  needed to make  accurate
predictions  under  all of the  plume
behaviors. There are, however, sufficient
differences between the models included
in our review to suggest that some may
be better  equipped  to  deal with these
phenomena than others.  For  example,
plume behaviors such  as  bumping-
looping and partial penetration in which
the  plume centerline  is near the mixing
height can prove to be difficult for  models
to reproduce accurately unless some sort
of  partial  penetration  algorithm is
included  in the  model.  Neither  the
CRSTER/MPTER/CEQM  or  SHORTZ
models have such an algorithm. These
models  assume a  zero  ground-level
impact  if  the plume  centerline is
predicted to be above the mixing height
and a perfect reflection of plume material
off of the inversion base otherwise. This
oversimplified approach can lead to large
prediction errors.
  Accurate estimates of  plume height
during  convectively  unstable  conditions
are  needed  to  produce  accurate
predictions of ground-level impacts.  The
plume  breakup/touchdown algorithm in
the  PPSP  model  represents  an
improvement over the standard  Briggs
formulas used in the  other  models that is
designed to meet this need.
  Models that rely  solely on the  PGT
stability  class  to estimate the  rate of
plume dispersion may have difficulty
differentiating  between the effects of
various  convective  and  mechanically
driven turbulepce phenomena  and may
use inaccurate" bispersion coefficients for
some hours  since the PGT classes are
based solely on wind speed, cloud cover,
and  solar zenith  angle.  Some  of the
models we reviewed (RTDM,  SHORTZ
and PPSP) have the capability of using
more direct measures of  turbulence
intensity  in   calculating dispersion
coefficients. If accurate  estimates of
turbulence intensities are available, these
models  should  produce   realistic
dispersion coefficients and concentration
predictions.

Dispersion Conditions
Associated with Highest
Observed Concentrations
  The highest observed  concentrations
frequently arise when a buoyant plume is
trapped  under  a strong  inversion  and
convective activity below  the  inversion
mixes relatively undiluted  material to the
ground.  High  observed concentrations
can also  occur when plume heights are
well below the mixing height and large-
scale  eddies rapidly  mix plume material
to the ground.
Dispersion Conditions
Associated with Over- and
Underpredictlons
   During the hours with the 50m highest
observations the largest overpredictions
tended  to occur  under  unstable
conditions  whereas underpredictions
were the general rule during neutral and
stable  conditions. The findings suggest
that  the largest  underpredictions  for
models other than PPSP and RTDM  are
primarily the  result  of  incorrect  plume
rise  treatment during strong  inversion
conditions indicative of  bumping/looping
behavior. The analysis  of the largest
over- predictions at selected sites shows
that  overpredictions generally  occur
under  unstable  light wind conditions
when the mixing  height is relatively high,
that is,  convective fumigation conditions.


Implications for Model
Applications in Connection with
a One-Hour Sulfur Dioxide
Standard
   If  an hourly average  NAAQS for SO2
were to be  promulgated, would  currently
available dispersion  models be  suitable
for use in demonstrating attainment of the
standard in  the vicinity of large,  elevated,
buoyant  point sources  as utility  power
plants? The results  suggest that  using
these  models in connection  with  an
hourly average standard  does not present
the  regulatory  community with  any
significant additional uncertainties that
are  not  already  being  dealt with  in
connection  with  the current 3- and  24-
hour NAAQS.  Predictions  of peak hourly
average  concentrations  unmatched  in
time or location  are   slightly more
conservative  on average   than
corresponding predictions of 3- and  24-
hour averages, and  model precision for
observations and predictions matched in
time  is no worse for hourly averages than
it is for longer averaging  times.
   Although  certain conditions  not
specifically  treated by the models, such
as inversion  break-up  and  Seabreeze
fumigation,  are  known to  occur and  to
have the potential for  producing high
ground-level  impacts  from  elevated
sources, we found that  these conditions
have been only rarely observed in model
evaluation studies and that they do  not
seem to contribute to the bulk of the 50
highest concentrations. In fact, nearly all
of the highest concentrations observed in
the  evaluation  studies  we  examined
occurred under  convective conditions,
which are treated by most of the models

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as Pasquill stability class A and B cases.
Peak  predictions under such  conditions
match reasonably well  with the highest
observed concentrations,  although large
prediction errors can  occur in any given
hour.  Thus, special dispersion situations
that might be of concern in modeling
peak  hourly  average concentrations do
not appear to occur frequently enough
around typical power plant sources  to
invalidate the use of currently available
dispersion  models.  In  reaching  this
conclusion,  we  have  explicitly  excluded
consideration of situations  involving
impacts on elevated  terrain  or  building
downwash phenomena.
   It  should  be  noted  that poor  time-
matched model performance may be due
at least in  part  to the fact that model
predictions represent  a  mean value over
an ensemble of similar meteorological
conditions while the observed  values
represent a single realization of an event
from the ensemble. It may be possible to
estimate  the  size of  the  contribution  of
this effect to the observed lack of model
skill  by comparing  observed  and
predicted concentrations  unmatched  in
time that belong to the same  ensemble.
        Ensembles could be defined in terms of
        simple model inputs (e.g., all hours of A
        stability, very light winds, and low mixing
        heights).
           Additionally,  we  recommend  that
        additional  data analyses and  possibly
        field studies  be  carried out to identify
        situations in which inversion break-up and
        Seabreeze fumigation  as  well as
        downwash  phenomena occur and  to
        characterize model performance under
        these conditions.

        Recommendations for
        Improvements in Model
        Formulations

           As  pointed out above,  one  of the
        principal  causes  of  poor  model
        performance is the apparently unrealistic
        treatment  of  plume  behavior  in  the
        vicinity of the mixing height. In particular,
        the overly  simplified  treatment  of the
        vertical profiles of  mean wind  and
        stability parameters used in  most models
        can lead to inaccurate estimates of plume
        height,  especially  in the  vicinity  of
        elevated inversions.  This  in  turn can
        result in inaccurate estimates of ground-
        level  concentrations.  For example, the
CRSTER/MPTER/CEQM  and  SHORT,
models assume  a zero  ground-leve
impact whenever the predicted plum
height  is greater than  the mixing heigh
Given  the inevitable  errors present  i
estimates of both of these quantities an
the fact that the plume rise is calculate
without regard to  the limitation  to  ris
imposed by  the elevated inversion, zer
ground-level  concentrations  are ofte
predicted when  in actuality substanti<
impacts are  occurring.  Substantic
reduction of  the number  of  cases  c
underprediction  could  be  achieve
through  the  use  of more  realisti
treatments of the interaction  of plume an<
inversions.
   Another   area  in which  mode
improvements are needed  is  in  th
simulation of plume dispersion  within th
mixed layer during  convective condition:
The commonly used  Pasquill stabilit
classes and dispersion parameters do nc
always accurately describe the  degree  c
lateral  and vertical  dispersion as well a
formulations  based on directly observe
stability parameters, such as u/w, or th
enhanced  lateral dispersion of  a plum
during  bumping-looping as  discussed b
Pierce.
     G. £.  Moore and  T. E. Stoeckenius  are with Systems Applicimhs, Inc.,  San
           Rafael,  CA  94903.  Steve  Hanna and Dave  Strimitas are- with Sigma
           Research Corp.,  Lexington, MA.
     D. Bruce Turner is the  EPA Project Officer (see below).       JA.
     The complete  report,  entitled "Air Quality  Simulation Model Performance  for
           One-Hour Averages, " (Order No. PB 89-233 506/AS; Cost: $21.95. 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 Ofgcer can be contacted at:
              Atmosph&rfc*Research and Exposure Assessment Laboratory
             -'      ........ "~"°'~ -    "     ~~
              Research Triangle Park, NC 27711
  United States
  Environmental Protection
  Agency
Center for Environmental Research
Information
Cincinnati OH 45268
  Official Business
  Penalty for Private Use $300

  EPA/600/S3-89/071
                                          10"  "BMCI

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