United States
                  Environmental Protection
                  Agency	
                          *«•;.'
Atmospheric Research and
Exposure Assessment Laboratory  -, fc/ *
Research Triangle Park NC 27711    f / >'
                  Research and Development
EPA/600/S3-89/082 Apr. 1990
f/EPA         Project  Summary
                  The  Role of Grid-Based,
                  Reactive Air  Quality  Modeling  in
                  Policy  Analysis: Perspectives
                  and  Implications,  as
                  Drawn from a  Case Study

                  Philip M. Roth, Charles L. Blanchard, and Steven D. Reynolds
                    A primary objective of this study is
                  to improve the understanding of the
                  role of performance  quality  in
                  determining a model's acceptability
                  and usefulness to the policy maker,
                  and  thus to aid in developing
                  soundly-based expectations of  the
                  modeling process. The vehicle for
                  pursuing this objective Is examining
                  the historical evolution of the Urban
                  Airshed Model (UAM) - a grid-based
                  photochemical model, whose basic
                  formulation Is similar to the Regional
                  Acid Deposition Model (RADM) - and
                  its application to  policy analysis in
                  the  South Coast  Air  Basin of
                  California. A derivative objective Is to
                  draw implications  from the  findings
                  to aid  In appraising the merits  of
                  future pursuits, notably the mounting
                  of comprehensive  field programs to
                  support the evaluation  of regional
                  acid deposition models.
                   In the technical report,  we:  (1)
                  describe the UAM, (2) examine Its
                  predictive capability thrugh  scrutiny
                  of historical performance statistics,
                  (3) assess its degree of acceptance
                  in the scientific and regulatory com-
                  munities, based on information and
                  viewpoints solicited  through ques-
                  tionnaires and  interviews,   (4)
                  examine the influence on the policy-
                  making community  of the  UAM
                  studies  and, (5)  based on these
                  "findings,"  attempt to develop a
                  perspective on the expectations of
current  regional  acid  deposition
models.
   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
  During the 1980s the National Acid
Precipitation Assessment Program sup-
ported the development of the Regional
Acid  Deposition Model (RADM).  The
technical  community urged that sound
performance evaluation be a part of the
overall development process  and, con-
sequently,  that a comprehensive data
collection program  be supported finan-
cially. They also expressed concerns that
policy makers may hold overly optimistic
expectations of performance of the
RADM at its current stage of develop-
ment  and of time-to-availability  of the
model for unrestricted use.
  One means of developing  a realistic
portrayal of the  model evaluation  and
acceptance process is to examine the
experiences of the past.  In  1970,
Systems Applications Inc. began devel-
opment  of the Urban Airshed  Model
(UAM),  a  grid-based photochemical

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model  of ozone formation on  an urban
scale.  A recent version of that  original
model  is now  in widespread  use. The
history of the UAM's continuing develop-
ment, sporadic evaluation, and frequent
application  is  of  particular relevance
since the DAM is a complex, grid-based
"chemical"  model  similar   in  basic
formulation  to the RADM.
   A primary objective of this study is to
gain an improved  understanding of the
importance  of quality of performance in
determining a model's  acceptability and
usefulness  to  the  policy  maker. We
hoped  to learn some lessons  from the
DAM experience  and present  them for
others  to  consider in  planning and
executing RADM-related activities. The
vehicle for  pursuing this objective  is to
examine the  historical  evolution  of the
(JAM and its application  to policy analysis
in the South Coast Air Basin of  California
over a  period of years.  A derivative
objective is  to draw implications from the
findings that  may be  of   value  in
appraising the merits of future pursuits,
notably  the mounting of expensive field
programs to  support the  evaluation  of
regional acid deposition  models. The
technical report offers insight gained from
the study  of one  model's use  that is
intended to  aid  the  policy  maker  in
developing  soundly-based expectations
of the modeling process.


Procedure
   In this study we surveyed  both the
performance  evaluation history  of the
UAM  and  the degree  of acceptance
achieved by  the model  in the  policy-
making  and scientific communities. We
first  examined  and  interpreted
performance statistics for the model over
the history  of its development. We then
interviewed  three categories of  interested
and informed parties: (1) members  of
the contemporaneous  scientific commu-
nity whose  pursuits  led them to become
familiar   with  the  UAM   and  its
development history, (2) industry repre-
sentatives,  and (3)  regulatory  agency
staff and policy makers who have had to
assess the  merits of using the  results of
the UAM.  The broad  questions to  be
answered by these interviews were:
•  Was the model acceptable?
•  Did  its degree of acceptability  change
   over time?
•  How was  model acceptability related
   to model performance?
Based  on the findings of these efforts,  we
developed  a "subjective history" of the
perception  of model performance and of
model acceptance.
Results and Discussion

   Analysis of time trends in performance
statistics for the UAM suggest that (1) the
tendency  toward underprediction of
ozone concentrations  decreased   with
time over fifteen years of testing, but the
range in estimates of bias at a particular
time were  high and  remained relatively
unchanged  with time, and (2) the average
error  in prediction decreased with  time,
but even in recent times  displayed  a
significant range in variation.
   Analysis of  interviews of thirty
individuals  who have been associated
with  UAM-use  in  policy analysis in the
South Coast Air Basin suggests that (1)
performance  of the UAM  was "good
enough  for  estimates to be considered"
in  the policy  context,  but not "good
enough to  provide  a  high degree of
confidence  in the model," (2) increased
acceptance of  the UAM  was not related
to  improved performance with time (or to
perceived performance),  (3)  interviewees'
increased acceptance of the model  was
related to improved understanding of the
model's capabilities and limitations, (4)
interviewees are prepared to accept mod-
el  use in assessing the relative effects of
alternative control scenarios, but not in
quantitative evaluation of specific mea-
sures, and (5) interviewees favor in-
creased emphasis on acquisition  of better
input data and  more comprehensive  data
bases for supporting model evaluation.


Conclusions
   Modeling   is  most  appropriately
conceived as  a continuing  process of
model development,  collection  of data,
testing,  diagnostic analysis,  modification
and  improvement of the  model,  and
repetition of the cycle. Performance eval-
uation is an essential,   though  not the
only,  element in establishing confidence
in  a models' value.  Sensitivity analyses
are considered as   important  as   per-
formance evaluations for assessing the
accuracy and reliability of a model.
   Acceptance of  a model by regulatory
and industrial communities appears to be
linked as much or more to understanding
the model as it is to the results of  per-
formance evaluations. Key ingredients in
gaining familiarity with  a  model  and
establishing an  understanding  of the
model's strengths and limitations are:
•  dialogues with  modelers, in lay terms,
   about the  model -  its  formulation,
   limitations, and attributes.
•  discussions of  results of performance
   evaluations, including at  the  stage of
   diagnostic assessment, when possible
   problems and  "cures" were conte
   plated.
•  discussions  of sensitivity  analysi
   when  model behavior could be  si
   jectively compared  with expectatic
   based on individual knowledge and 1
   degree  of conformity with  the
   expectations could be examined.
   For complex  atmospheric  modeli
systems, experience suggests that  1
process of acceptance requires seve
cycles of development and testing a
that the overall time required to achie
model acceptance,  based on  quality
performance,  may be  fifteen  to twei
years. While  this admittedly subject!
time  estimate may not  be welcomi
knowledge  gained during the process
development, data acquisition, and di<
nostic analysis is generally  of  cons
erable value.

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  Philip M. Roth is a private consultant in San Anselmo, CA 94960;  Charles L
        Blanchard is with Princeton University, Princeton, NJ 08544; and Steven D.
        Reynolds is with Systems Applications, Inc., San Rafael, CA 94903.
  Robin L Dennis is the EPA Project Officer (see below).
  The complete  report,  entitled "The Role of Grid-Based,  Reactive Air Quality
        Modeling in Policy Analysis: Perspectives and Implications, as Drawn from
        a  Case Study,"  (Order No. PB 90-187 2041 AS; Cost: $23.00,  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:
           Atmospheric Research and Exposure Assessment Laboratory
           U.S.  Environmental Protection Agency
           Research Triangle Park NC 27711
United States
Environmental Protection
Agency
Center for Environmental Research
Information
Cincinnati OH 45268
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