United States      Office of Air Quality      EPA-450/4-81-005a
           Environmental Protection  Planning and Standards     January 1981
           Agency        Research Triangle Park NC 27711

           Air
&ER&     Application  Of The
           Empirical Kinetic
           Modeling Approach
           To Urban Areas
           Volume I:  San Francisco/
           Sacramento

-------
                                   EPA-450/4-81-005a
Application  Of The  Empirical Kinetic
 Modeling Approach To  Urban Areas

Volume I:  San Francisco/Sacramento
                        by

              G.Z. Whitten, H. Hogo and R.G. Johnson

               Systems Applications, Incorporated
                   950 Northgate Drive
                 San Rafael, California 94903
                  Contract No. 68-02-3376
               EPA Project Officer: Gerald L. Gipson
                      Prepared for

            U.S. ENVIRONMENTAL PROTECTION AGENCY
                Office of Air, Noise and Radiation
             Office of Air Quality Planning and Standards
            Research Triangle Park, North Carolina 27711

                     January 1981

-------
                                 DISCLAIMER
This document  is  issued by the Environmental Protection Agency to report
technical data of  interest to a  limited number of readers.  Copies  are
available free of  charge to Federal employees, current EPA contractors  and
grantees, and nonprofit organizations - in  limited quantities - from the
Library Services Office (MD-35), U.S. Environmental  Protection Agency,
Research Triangle  Park, North Carolina 27711; or, for a fee, from the
National Technical  Information Service, 5285 Port Royal Road, Springfield,
Virginia  22161.

This report was furnished to the Environmental Protection Agency by
Systems Applications,  Incorporated, 950 Northgate Drive, San Rafael,
California 94903,  in fulfillment of Contract No. 68-02-3376.  The contents
of this report are  reproduced herein as received from Systems
Applications,  Incorporated.  The opinions,  findings  and conclusions
expressed are those of the author and not necessarily those of the
Environmental Protection Agency.

                     Publication No.  EPA-450/4-81-005a
32R/1

                                 ii

-------
                                 CONTENTS



DISCLAIMER	    i i

LIST OF ILLUSTRATIONS	     v

LIST OF TABLES	   vii

LIST OF EXHIBITS	    ix

    1   INTRODUCTION	.-	     1
        1.1  Background and Objectives	     2

    2   SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS	     4

        2.1  Summary	     4
        2.2  Conclusions	     4
        2.3  Recommendations	     6

    3   TRAJECTORY MODEL APPLICATIONS	     9

        3.1  San Francisco Applications	     9
             3.1.1  Model  Definition	    11
             3.1.2  San Francisco Case Studies	    18
             3.1.3  Summary of Results for San Francisco
                    Case Studies	    31
        3.2  Sacramento Applications	    33
             3.2.1  Model  Definition	    35
             3.2.2  Sacramento Case Studies	    43
             3.2.3  Summary of Results for Sacramento
                    Case Studies	    51

    4   SENSITIVITY STUDIES	    57

        4.1  The San Francisco Region	    58
             4.1.1  Initial Conditions	    58
             4.1.2  Mixing Heights	    58
             4.1.3  Emissions Vector	    60
             4.1.4  Model  Size	    60
        4.2  The Sacramento Region	    63
32R/1
                                  m

-------
    5   EKMA APPLICATIONS	    66

        5.1  Considerations Related to the Use of
             Isopleth Diagrams	    67
             5.1.1  Fixed Monitoring Sites	    67
             5.1.2  Uneven Changes in Emissions	    67
             5.1.3  Transported Pollutants	    68
        5.2  San Francisco Applications	    68
             5.2.1  Basic Comparisons between LIRAQ and EKMA	    68
             5.2.2  Further Investigations...	    74
        5.3  Sacramento Application	    86

REFERENCES	   103
32^/1
                                  iv

-------
                               ILLUSTRATIONS



    1   Trajectory 1 for 26 July 1973	    19

    2   Trajectory 2 for 26 July 1973	    21

    3   Trajectory 1 for 20 August 1973	    23

    4   Trajectory 2 for 20 August 1973	    25

    5   Trajectory 1 for 24 July 1974	    27

    6   Trajectory 2 for 24 July 1974	    29

    7   Locations of Monitoring Sites in the  Sacramento Area	    34

    8   Trajectory Used for 24 August 1976	    44

    9   Comparison of Ozone between Station Observations
        and Model Predictions for City-Specific EKMA
        for 24 August 1976—Sacramento	    49

   10   Trajectory Used for 28 June 1976	    50

   11   Comparison of Ozone between Station Observations
        and Model Predictions for 28 June 1976—Sacramento	    54

   12   Effects of Inversion Heights on Maximum Ozone
        Produced:  26 June 1973, Trajectory 1	    61

   13   Effects of Wind Speed across San Francisco on
        Ozone Production:   26 June 1973	    62

   14   Effects of Trajectory Width on Maximum Ozone:
        26 July 1973	    64

   15   Isopleth for 26 July 1973:  Trajectory 1—HC/NOX
        Ratio = 10/1	    71
32R/1

-------
   16   Level III Trajectory for San Francisco--26 July 1973	    72

   17   Isopleth for 26 July 1973:  Trajectory 1—HC/NOX
        Ratio = 1/1	    77

   18   Isopleth for 26 July 1973:  Trajectory 1--HC/NOX
        Ratio = 100/1	    78

   19   Isopleth for 20 August 1973:  Trajectory 1	    80

   20   Isopleth for 24 July 1974:  Trajectory 2	    81

   21   New-Style Isopleth (1,1) for 26 July 1973:
        Trajectory 1	    84

   22   New-Style Isopleth (1,1) for 26 July 1973:
        Trajectory 1 Using the Carbon-Bond Mechanism	    87

   23   Map of the Hypothetical Urban Area Used to Study
        Transportation Control Strategies	    88

   24   Trajectory Used for the Control-Strategy Runs  	    90

   25   City-Specific EKMA Isopleth for the Control-Strategy
        Calculations	    95

   26   Level III Trajectory for Hypothetical Region:
        24 August 1976	   100
32R/1

                                 vi

-------
                                  TABLES



    1   Input Data for the San Francisco Trajectories	    14

    2   Summary of Results for the San Francisco Case Studies	    32

    3   OZIPM/CBM Emissions and Mixing-Height Inputs for
        24 August 1976	    45

    4   Initial Conditions for Calculations of 24 August 1976	    46

    5   Comparison of the SAI Trajectory Model and the OZIPM/CBM
        Calculations for 24 August 1976 for NOX, PAR, ARO,
        and Ozone	    47

    6   Emission Rates and Mixing Heights Used in the
        OZIPM/CBM Calculations for 28 June 1976	    52

    7   Initial Conditions Used in the City-Specific EKMA
        Calculations of 28 June 1976	    53

    8   Comparison of Ozone Predictions for Four Different
        Models on 28 June 1976 and 24 August 1976 in
        Sacramento	    55

    9   Values for Maximum Ozone Versus Values for Initial
        Condi tions	    59

   10   Control-Strategy Comparisons for San Francisco
        between LIRAQ and EKMA Applications	    70

   11   Initial Conditions Used in the Level  III EKMA
        Calculations for 26 July 1973 in the San Francisco
        Region	    75
32R/1

                                  vii

-------
   12   Sensitivity of Control-Strategy Evaluation to HC/NOX
        Ratio for Trajectory 1--26 July 1973	    79

   13   Sensitivity of Control-Strategy Evaluation to
        Traj ectory Path	    83

   14   Control-Strategy Comparisons Using a New-Style Isopleth....    85

   15   SAI Airshed Model Predicted Peak Ozone Concentrations
        Computed for Different Control  Strategies in the
        Hypothetical Region 	    89

   16   Emission Rates and Mixing Heights Used in EKMA
        Applications to Hypothetical Region Control Strategies	    91

   17   Trajectory Model Outputs Used as Inputs for the
        EKMA Simul ations	    92

   18   Comparison of Maximum Predicted Ozone for the SAI
        Airshed, SAI Trajectory, OZIPM/CBM, and City-Specific
        EKMA Models:  Base-Case Conditions Used for the
        Control-Strategies Study of the Hypothetical Region	    93

   19   Control-Strategy Study Total Emissions Resulting
        from a 30 Percent Reduction in Mobile HC and NOX
        Emissions	    96

   20   Comparison of Maximum Ozone Predictions between the
        Trajectory Model, OZIPM/CBM, and City-Specific
        EKMA with Different Control Scenarios	    97

   21   Initial  Conditions Used in the Level III EKMA
        Calculations for Hypothetical Region for 24 August 1976
        Meteorol ogy 	    98
32&/1

                                 viii

-------
                                 EXHIBITS
    1   Q-tapes and Q-files Provided to the EPA by the BAAQMD	    10
32^/1



                                 ix

-------
                              1    INTRODUCTION
     The Environmental Protection Agency  (EPA) has developed  a method for
estimating the emission controls that will be needed to meet  the  National
Ambient Air Quality Standard (NAAQS) for  ozone (03) concentrations  in
urban areas.  This method, known as the Empirical Kinetic Modeling
Approach (EKMA), uses an  isopleth diagram for ozone concentrations  that  is
related to hydrocarbon (HC) and nitrogen  oxide (NOX) precursor levels.
Each point on the isopleth diagram represents the maximum one-hour  ozone
level reached as a result of the specific HC and NOX combination  described
by the abscissa and ordinate values of the isopleth diagram.  The ozone
value generated from each HC and NOX combination is obtained  by a com-
puter-based trajectory model—OZIPP (Whitten and Hogo, 1978a).  OZIPP con-
tains many simplifying assumptions that are designed to strike a  balance
between factors such as the state of knowledge, data availability,  com-
puter size, predictive accuracy, and overall cost.

     This report presents the results of  one of several studies that
evaluate the EKMA.  The approach taken in this particular evaluation of
the EKMA uses gridded input files that were previously prepared for use
with large, sophisticated airshed models  of the grid variety.  One  of
these models—LIRAQ--was  used to prepare  an Air Quality Maintenance Plan
(AQMP) for the San Francisco urban area (BAAQMD, 1979).  The  other—the
SAI Urban Airshed Model—had been used in a mobile-source-control evalua-
tion study conducted for  the California Department of Transportation (DOT)
(Reynolds et al., 1979) in the Sacramento region.  When the gridded data
from these more sophisticated models are  input to the OZIPP trajectory
model, the results can be compared with those of the other models to form
one basis for evaluating  the EKMA.

     This study also compared the OZIPP trajectory simulations either with
observed data or with predictions made by the other models on the basis of
change in emissions values.  In addition, parts of this study involved
alternative input assumptions and changes to the model definitions  so that
both sensitive parameters and improvements to the EKMA could  be evaluated.
32R/2

-------
1.1   Background and Objectives

     For several years the Office of Research and Development of the  EPA
has sponsored a coordinated program consisting of fundamental chemical
research, smog chamber experimentation, and model development.  The
objective of this program is to develop mathematical models capable of
simulating the dynamics of the chemical reactions and dispersion of the
gaseous pollutants found in the lower troposphere.  These atmospheric
models are to be used both to gain an understanding of  air pollution  and
to predict the probable outcome of control scenarios.   To this end, the
EPA Office of Air Quality Planning and Standards (OAQPS) has embarked on
an extensive program of model comparison and evaluation.

     The specific purpose of the OAQPS program is to assess the suita-
bility of available photochemical oxidant modeling approaches for use by
states as planning tools in ozone air quality planning  and management.
The program includes comparisons and evaluations of the various approaches
for typical U.S. cities.  As part of the program, large, detailed data
bases are being assembled for several example cities.

     The primary objective of this study is to evaluate one such approach-
—the EKMA—through the application of the photochemical trajectory model
that forms its basis.  This model is used to generate isopleth diagrams of
constant urban ozone maximums as a function of the morning precursor
levels of nonmethane hydrocarbons (NMHC) and nitrogen oxides.  The EKMA
method uses these results to estimate, in a relative manner, the precursor
control requirements necessary to reduce ozone levels below the National
Ambient Air Quality Standard for ozone.  The method was developed for use
at several levels of sophistication, depending on the extent of input data
available.  If the basic model is fundamentally sound,  the simulated
results should approach the observed values as the availability of
detailed data increases.

     The EPA has prepared highly detailed data concerning precursor
emissions, meteorology, and ambient air quality for Tulsa and Philadelphia
to test various air quality simulation models such as the OZIPP and the
SAI Urban Airshed Model.  In addition, there are data bases already
available for St. Louis, Los Angeles, San Francisco, and Sacramento.
Because some models are grid-based and thus designed to reproduce spatial
and temporal variations within the  metropolitan airshed, detailed
information files are required.  The availability of detailed data and of
the results from parallel studies using sophisticated models offers the
following advantages for making an in-depth study of the EKMA:

     >  The simple application of the OZIPP trajectory model,
        using either the actual available data inputs or the


32R/2

-------
        corresponding data simulated in other models,  should
        generate results that can be compared both with ambient
        air data and with the results of the other models.  The
        timing of results regarding data such as the ozone
        maximums and precursor decay should also be comparable.

        Tests of the sensitivity of the results to variations  in
        the input data can demonstrate important data  requirements
        for successful application of OZIPP.  This information
        should be useful in determining cost effectiveness for
        future uses.  The results of the sensitivity study are
        also useful for improving the trajectory model in case the
        present version does not adequately simulate observed
        ambient data or the simulations of more complex models.

        The application of the EKMA procedures to air  quality
        planning demonstrates the utility of the EKMA  compared
        with that of methods based either on simpler models (such
        as a rollback model) or on more complex models (such as
        the SAI Urban Airshed Model).

        The potential effectiveness of OZIPP model improvements
        can be assessed using the results of the complex models as
        a standard.
32R/2

-------
                   SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS
2.1   SUMMARY

     We have evaluated the EKMA by comparing OZIPP  with  other models  pre-
viously applied to the San Francisco and Sacramento regions.  The  study
was carried out at several levels, beginning with the  trajectory model
that forms the basis of the EKMA and ending with the control-strategy
predictions that result from employing the EKMA methodology.  In the  San
Francisco region OZIPP was compared with the LIRAQ  model, which was used
for the 1979 Air Quality Maintenance Plan  (AQMP).   In  the Sacramento
region comparisons were made with the SAI Airshed Model, which has been
applied in a study for the Department of Transportation  (Reynolds  et  al.,
1979).

     The basic OZIPP model is a simple, moving-air-parcel, or trajectory,
model that uses a detailed chemical mechanism for the  surrogate propylene
and butane hydrocarbons.  Time-dependent, precursor-emissions factors can
be treated, along with expansion of the air parcel, and  entrainment is
treated by assuming that constant concentrations exist outside the parcel.
2.2   CONCLUSIONS

     The primary emphasis of this comparison study was directed toward the
discovery of features in the trajectory model that could explain dif-
ferences in the results of OZIPP from those of  some other model.  To that
end, most of the OZIPP simulations utilized initial conditions derived
from the model used for comparison purposes.  Thus, for the most part, the
study used the LIRAQ and Airshed Model data files to generate appropriate
OZIPP inputs.  Although the utilization of these files tends to circumvent
the issue of normal-source data preparation, the comparison of models  is
clarified by use of common data bases.  Furthermore, costs are mini-
mized.  For some of the OZIPP simulations, we used air quality data rather
than information common to the comparison model.  This step allowed the
categorization of overall differences as either effects resulting from the
data utilized or those attributable to specific features of the models.
32R/2

-------
     This study,  and  a  similar  study  by Whitten  and  Hogo  (1981)  using  Los
Angeles data, show that OZIPP can  provide  results  that  are  often quite
similar to those  of the more complex  models.   By carefully  separating  the
models according  to specific formulation differences and  through careful
analysis of  intermediate results,  the most important feature  in  formula-
tion that produced different results  between  two models could  often  be
isolated.  Even though  the  absolute values predicted by the OZIPP trajec-
tory model may be significantly different  from those of the more complex
models (one  of the main differences is often  a result of  the  different
chemical mechanisms employed),  the isopleth applications  of the  EKMA
(which uses  the trajectory  model results in a relative  fashion)  typically
show control predictions corresponding to  those  of the  more complex
models.

     In the  comparison  of the EKMA results with  those of  the  LIRAQ model
for the San  Francisco region, primary attention  was  given to  the tra-
jectory leading to the  design ozone of the AQMP.  Although  there are
uncertainties associated with deriving any specific  trajectory path, in
this study the air parcel that  eventually  affects  the site  of  maximum
ozone concentration (Livermore) apparently originates at  0800  PDT over the
Pacific Ocean just south of San Francisco.  This trajectory is discussed
in detail in section  3.2.   It was  found that  the precursor  loading for
this trajectory and for several others was extremely sensitive to wind
speed because of  widely varying emissions  density  in the  area.

     Another sensitive  input was the  size  of  the air parcel.   The emis-
sions files  used  in the LIRAQ studies were for 5-km  grids.  Using a  narrow
size (<5 km) for  the  width  of the  EKMA trajectory  made  the  results
sensitive to the  exact  choice of a path between, or  over, the  grid squares
of the LIRAQ inventory.  Sometimes the emissions density  changed by  more
than two orders of magnitude between  adjacent  grid squares.   For most
cases, a 10-km width  produced reasonable and  similar results  for slightly
different trajectory  paths.  Some  trajectories were  15  km wide,  roughly
coinciding with the size of the city  of San Francisco proper,  the main
source of the emissions.

     The SAI Airshed, or grid,  Model  served as the basis  of the  Sacramento
study.  SAI trajectory model simulations were  made using  recreated input
files from the earlier  grid model  study.   In  some  instances,  important
differences between grid and trajectory model  results could not  be
resolved.  For these cases, the study focused  largely on  comparing the
OZIPP results with those of the SAI trajectory model  (rather than the  grid
model) because the trajectory model was used  to  generate  input data  for
OZIPP.  Obtaining data directly from  the trajectory  model eliminated many
uncertainties in the model  comparisons, such  as  those related  to model
size, wind speed, or mixing depths.   Differences due to model  formulation
32R/2

-------
thus became more apparent than those of the LIRAQ  comparisons.  The most
sensitive differences, both absolutely and relatively, were found  in  the
chemical mechanisms.                        '

     The SAI models used in the Sacramento study employed  an early version
of the Carbon-Bond Mechanism  (CBM)  (Whitten, Hogo,  and Killus,  1980).   In
general, the CBM chemistry generated higher absolute  levels of  ozone  than
the standard EKMA chemistry.  In the control-prediction  phase,  the two
chemistries predicted similar results when HC  and  NOX were simultaneously
reduced; but the CBM chemistry predicted more  ozone reduction than the
standard EKMA chemistry when  HC reductions only were  involved.  Although
the OZIPP model and the SAI trajectory model are much different in terms
of complexity (apart from chemistry), these factors apparently  did not
play a significant role for the Sacramento area.   Thus,  such factors  as
multilevel mixing, eddy diffusion,  elevated emissions, and variable
concentrations aloft were found to  be unimportant  when common input data
were used.
2.3   RECOMMENDATIONS

     The following considerations are suggested for future  studies:

     >  For cases in which differences in control-strategy
        predictions are found to be related to differences  in the
        chemistry employed in various models, it  is important to
        investigate the chemical reactions that produce these
        differences.  If appropriate smog chamber experiments that
        would validate one or the other types of  mechanisms can be
        identified, these experiments should be performed.

     >  A generic concept can be associated with  the EKMA that
        goes beyond its present formulation and uses.  Develop-
        mental work on the EKMA should continue to update its
        formulation and improve its utility.  Specifically, the
        following steps are suggested:

        -  This study demonstrates that significant differences in
           both absolute model results and in predicted control
           requirements can sometimes occur when  the Carbon-Bond
           Mechanism is substituted for the propylene/butane
           chemistry currently used in OZIPP.  Further studies
           should be undertaken to investigate and resolve
           potential discrepancies between the two mechanisms.
32R/2

-------
        -  Credibility of the EKMA could be enhanced  by  providing
           a means for considering urban hydrocarbon  reactivity.
           Either the latter should be related to  the propylene
           reactivity used  in OZIPP, or the chemical  mechanism
           utilized  in the  OZIPP  should be changed to be compat-
           ible with available reactivity information.

        -  Isopleths based  on emissions inventories might be
           further developed to perhaps replace the present
           initial-condition-based isopleths.  Urban  HC  and NOX
           measurements are often not relevant to  the initial
           conditions that  are appropriate to a city-specific
           trajectory, as this study demonstrated  for several of
           the San Francisco trajectories.

        -  The mixing-depth algorithm should be improved so that
           the changes with time  correspond to observations rather
           than produce a constant-dilution factor.

        -  The transported  pollutants, both in the surface layer
           and aloft, might be varied according to the level of
           control of emissions.  The variance could  be  controll-
           able by the user.  The current procedure necessitates
           two separate isopleth  diagrams.  (Again, further
           development would be necessary to incorporate this
           refinement.)

        -  The regular city-specific algorithm might  be  modified
           to allow optional starting times in place  of  the
           present 0800 PDT starting time.  Earlier starting times
           would emphasize dependence on an emissions  inventory,
           whereas later starting times might emphasize  dependence
           on initial conditions.

        Modifications to the current version of the EKMA have also
        been suggested in other studies.  Although  such  sugges-
        tions have not been addressed in this study,  their
        implementation might also be considered.

        -  The two-stage approach (in which stationary-source
           emissions are held constant in the first stage and
           mobile-source emissions are held constant  in  the second
           stage) might be further developed so that  local
           districts can use EKMA isopleths to make the  control
           predictions for stationary emissions.
32R/2

-------
        -  Point-source emissions might  be  handled  so  that  the
           interaction with all possible urban  HC/NOX  concentra-
           tions could be evaluated  as part  of  a new source review
           procedure.

        -  Percent cutback diagrams  (PCD) might be  added  to the
           OZIPP code so that both the isopleth and  the PCD are
           generated.

        -  Temperature changes, deposition,  variable reactivities,
           nitrate chemistry, and sulfate chemistry  can also  be
           added to OZIPP.  Isopleths of species other than ozone
           can also be generated by  OZIPP.

        -  Statistical packages can  be combined with the  EKMA to
           generate the probable number  of  exceedances resulting
           from various control scenarios.

     >  The use of more complex models such  as  the  SAI Airshed
        Model should be accompanied  by the  use  of the  EKMA, both
        for absolute trajectory simulations  along the  path  to the
        major ozone peaks and for control-strategy  guidance from
        the isopleth diagrams.  The  studies  performed  to  date show
        that unless the wind fields  are  complicated  by such
        factors as wind shear, the two types of models normally
        give similar results.  In the absence of complex  meteoro-
        logical factors, important differences  in results would
        indicate the existence of problems  in one or both of  the
        models that should be investigated.
32R/2

-------
                         TRAJECTORY MODEL APPLICATIONS
     This section focuses on applying an  EKMA-type trajectory model  to
predict absolute values of ozone.  Predictions were made for several  cases
in San Francisco and Sacramento.  The predicted ozone  levels were  compared
with observed concentrations, when these  were available, and with  predic-
tions of more complex models.  The results can be used to  assess the
fundamentals of the formulation model and to identify  important differen-
ces between models.
3.1   San Francisco Applications

     The 1979 air quality maintenance plan for the  Bay Area Air  Quality
Management District (BAAQMD) was developed using the  Livermore Regional
Air Quality  (LIRAQ) Model (BAAQMD, 1979).  During this study, sufficient
air quality, emissions, and meteorological data were  collected to  permit
application  of the OZIPP-type trajectory model.  The  trajectory  model
predictions  could then be compared with both observed data and the LIRAQ
predictions.  Furthermore, the control strategies tested  using the LIRAQ
model could  be tested using the EKMA technique to compare its utility  with
that of the  more complex LIRAQ model.  (The control strategy tests are
addressed in greater detail in chapter 5.)

     The LIRAQ model was used to simulate the distribution of photochemi-
cal pollutants in the BAAQMD on two days—26 July and 20 August  1973.  The
data necessary for applying the LIRAQ model on these  two days are  avail-
able on tapes supplied by the BAAQMD and are identified in exhibit 1.
Many of these data have also been reported by Feldstein et al. (1979)  and
others.  Using the data for these two days, we undertook  specific  case
studies using the OZIPP-type trajectory model.  Case  studies for one
additional day (24 July 1974) were also performed,  even though the results
could not be compared with those of the LIRAQ model,  but only with
observed air quality data.

     In the  discussion that follows, the LIRAQ model  and the OZIPP-type
trajectory model are first described.  Then, specific case studies are
discussed.   Finally, the overall results are summarized.
32R/2

-------
Attention:
John Siuuerhiys (MD-14)



SHIPPING LIST
Q-TAPES AND Q- FILES PROVIDED TO EPA, PUR BAAQMD-ABAG CONTRACT
BAAQMD Assigned File
Q-Tape Namber Number
1 1
2
3
4
S



2 1
2
3
4
3 1
2
3
4
5
4 1
2
3
4
5
S 1
2
3
4
5
6
6 1
2
3
4
S
6
7 1
2
3
4
S
6
S 1
2
3
4

9 1
2
3
4
S


10 1
2
3
4
S

Description of Q-Files, in Order on Q-T«pe
QSRUN. July 26, 1973
QSOR, 1975 Baseline, Region 1. S Kms
QICON, July 26, 1973
QGEO
QRAD, July 26, 1973
Nota Bene; CEO repeated on Q-Tape 9,
QSOR for 75 Baseline, Region 1, 5 Kms.
is repeated on Q-Tape 7.
QTRANO, July 26, 1973
QTRAN1, July 26, 1973
QTRAN2, July 26, 1973
QTRAN3, July 26, 1973
QICON, Nov S-6, 1976
QTRANO, Nov 5-6, 1976
QTRAN1, Nov 5-6, 1976
QTRAN2, Nov S-6, 1976
QTRAN3, Nov 5-6, 1976
QICON, July 24, 1974
QTRANO, July 24, 1974
QTRAN1, July 24, 1974
QTRAN2, July 24, 1974
QTRAN3, July 24, 1974
QSOR, 2000 Baseline, Region 1, 5 Kms
POP, 2000 Baseline, Region 1, 5 Kms
AIR, 2000 Baseline, Region 1 , S Kms
CAR, 2000 Baseline, Region 1, 5 Kms
PNT, 2000 Baseline, Region 1, S Kms
SKY, 2000 Baseline, Region 1, S Kms
QSOR, 1985 Baseline, Region 1, 5 Kms
POP, 1985 Baseline, Region 1, 5 Kms
AIR, 1985 Baseline, Region 1. 5 Kms
CAR, 1985 Baseline, Region 1, S Kms
PNT, 1985 Baseline, Region 1 , 5 Kms
SKY, 1985 Baseline, Region 1 , 5 Kms
QSOR, 1975 Baseline, Region 1 , 5 Kms
POP, 1975 Baseline, Region 1, 5 Kms
AIR, 1975 Baseline, Region 1 , 5 Kms
CAR, 1975 Baseline, Region 1 , 5 Kms
PNT, 1975 Baseline, Region 1 , 5 Kms
SKY, 1975 Baseline. Region 1. S Kms
QMRUN, July 24, 1974
QMET, July 24, 1974
QMRUN, Nov S-6. 1976
QMET, Nov 5-6, 1976
Nota Bene; These are all MASCON inputs.
QGEO
QMRUN, Aug 20, 1973
QMET, Aug 20, 1973
QMRUN, July 26, 1973
QMET. July 26, 1973
Nota Bene; These are all MASCON inputs.
QGEO repeated on Q-Tape 1. QGEOs identical.
QSRUN, Aug 20, 1973
QICON, Aug 20, 1973
QTRANO, Aug 20, 1973
QTRAN1, Aug 20, 1973
QTRAN2, Aug 20, 1973
             EXHIBIT 1.   Q-TAPES AND  Q-FILES  PROVIDED TO THE EPA BY THE
                         BAAQMD
32R 3
                                      10

-------
3.1.1   Model Definition

     The LIRAQ model is of the grid variety, providing estimates of
pollutant concentrations as a function of time throughout the modeling
region.  The model mathematically simulates the complex physical and
chemical interactions taking place in the atmosphere, employing a  lumped
parameter chemical mechanism to describe the photochemical reactions
taking place.  Specifically, the model predicts instantaneous pollutant
concentrations in single-layer grids superimposed on the modeling
region.  Surface concentrations are estimated by an analytic function.
For a more detailed description of the model, the reader is referred to
the study of MacCracken and Sauter (1975).

     The intent of applying the OZIPP-type trajectory model is to  follow
the evolution of photochemical pollutants, particularly ozone, along the
air parcel trajectory leading to an observed, peak ozone concentration.
This approach is consistent with that which the EPA has termed a Level  II
analysis (Federal Register, 1979).  The standard EKMA trajectory model
contained in the computer program OZIPP (Whitten and Hogo, 1978a)  was not
applicable to such an analysis; however, the subsequent program OZIPM
(Whitten and Hogo, 1978b), contains options that facilitate such applica-
tions and, thus, was used in this study.

     The OZIPP model was based on the reactions of high initial precursor
concentrations in a major urban-source region.  The model follows  the
original air parcel throughout the day as it travels to a suburban site
where ozone maximums have been observed.  This conceptual pattern  was
similar to the pattern of ozone development seen in the smog chamber
experiments used to validate the OZIPP model (Dimitriades 1977; Dodge,
1977).  The OZIPM model permits the use of alternative starting times and
hourly mixing height inputs that are more representative of the conditions
considered in this study.  This version of the model also provides the
option of replacing the standard EKMA chemistry with other mechanisms.  As
described later, this option was used in some portions of the study.

     The detailed trajectory model approach using the OZIPM model  requires
the definition of numerous variables, including the air parcel trajectory
leading to a peak ozone level; initial pollutant concentrations within the
air parcel; the diurnal variation in mixing height; emissions occurring
along the trajectory path; pollutant concentrations above the mixed layer
that may later be entrained into the surface-based mixed layer; and
chemical reactivity.  The procedures for defining these variables  are
described in the following subsections.
32R/2                             11

-------
3.1.1.1   Trajectory

     To specify trajectories describing the  leading  of  air  parcels  to
elevated ozone levels, first, the two highest observed  ozone  concentra-
tions for each of the three study days were  obtained from the LIRAQ QICON
(the file containing observed air quality data).   Wind-field  maps were
then created using the LIRAQ QMET input files for  these days.   For
example, on 26 July 1973, the maximum ozone  level  was 0.176 ppm at
Livermore at 1700 PDT.  According to the LIRAQ  surface  wind-field maps,
the direction and speed for the previous hour (1600  to  1700 PDT) at
Livermore was 25 km/hr at 250°.  The location of the air parcel  at  1600
PDT was thus determined by moving 25 km from Livermore  at an  angle  of
250°.  This procedure was repeated for each  preceding hour  until the
parcel reached the ocean.

     In this case, the trajectory ending at  Livermore had passed over
South San Francisco in the morning.  According  to  the QMET  file  for this
day, wind vectors were to the north and south of the trajectory.  The
peninsula to the south of San Francisco is a source  of  high emissions and
the composition of the air parcel is thus extremely  sensitive to the speed
with which it travels across the peninsula.  Because the trajectory passed
directly over the San Francisco International Airport (SFO),  wind speed
data from the airport were used with the QMET data to determine  the
trajectory path across the peninsula.

     By definition, then, the trajectory path ended  at  a point  of high
ozone concentration.  However, additional concentration  values  also were
available from the closest monitoring station for  the hour  during which
the trajectory passed by.  The contour lines presented  in the LIRAQ
reports (see MacCracken and Sauter, 1975) show  that,  at  least,  the  ozone
levels simulated in the LIRAQ model do not have many steep  gradients.
Therefore, the nearest station value and LIRAQ  model  predictions could
also be compared to the OZIPM predictions along the  trajectory  path.
3.1.1.2   Initial Concentrations

     All trajectory paths studied for the San Francisco  area  appeared  to
originate over the Pacific Ocean.  Thus, initial concentrations were
considered to be insignificant and, therefore, were  assumed to be  at
background levels.  Sensitivity of model predictions to  this  assumption  is
further evaluated in chapter 4.
32R/2                               12

-------
3.1.1.3   Mixing Heights

     Mixing heights were obtained from the LIRAQ QTRAN  files.   Since  these
data are presented for three-hour periods only, values  for the  remaining
hours were obtained by linear  interpolation.  Thus,  a mixing  height for
0800 PDT would be two-thirds of the 0700 PDT value plus  one-third  of  the
1000 PDT value.  The mixing heights used in this study  are given  in table
1.

     The mixing layer typically increases in thickness  as the warm surface
air erodes the inversion layer.  Under such conditions  air is entrained
from aloft that, in turn,  increases the volume of the conceptual  air
parcel of the OZIPM trajectory model.  Under some circumstances the change
in mixing height may not be a  result of entrainment  from aloft.   For
instance, an air mass moving at high velocity would  initially tend to flow
over a stagnant air mass.  Also, in areas of convergent  wind  flow  such  as
in the case of air passing from open terrain into a  canyon, mixing height
cari be pushed up from the  sides.  In this type of change in mixing
height—narrowing of the sides of an air parcel, accompanied  by an
increase in the height of  the  air parcel—the volume of  the air parcel  may
not change.  Since changes in  the mixing height in the  OZIPM  model  are
intended to represent a change in volume for the moving  air parcel,
changes in mixing height that  do not reflect a change in volume should  not
be included as input data.  Unfortunately, the wind  flow in complex
terrain is not easily separated into mixing-height changes, either those
accompanied by entrainment of  air from the sides or  those accompanied by
entrainment of air from aloft.  Although entrainment of  air into  the  sides
of the EKMA model could be treated as entrainment from  aloft, the  basic
concepts behind the OZIPM model suggest that such air is considered to
contain concentrations identical with those of the model parcel itself.
Therefore, the data related to  air entrained from the  sides  would
normally be ignored along with any changes in volume associated with  such
phenomena.
3.1.1.4   Emissions

     The version of OZIPP that is available in the OZIPM computer  code
contains options for post-0800 emissions of both HC and NOX.  For  vir-
tually all the trajectories used in this study,  initial conditions  were
not significant, and the emissions occurring along the trajectory  were
responsible for the ozone maximums.  The OZIPM model  uses post-initial
emissions input data in the form of fractions related to the  initial
concentrations.  If the initial HC concentration was  1 ppm, emissions
during some subsequent hour sufficient to add an additional 1 ppmC  would
merely be included in OZIPM as 1.0 for that hour.  If the inversion height


32R/2
                                   13

-------
                   TABLE 1.  INPUT DATA FOR THE SAN FRANCISCO TRAJECTORIES
                                  (a)  Initial  Concentrations
                   Species
                   NOX
                   NMOC
                   Oo
                        Transported
                           Surface

                            0.001
                            0.01
                            0.0
                                Pollutants
                                 Aloft

                                 0.01
                                 0.05
                                 0.04
                   N02/NOX =  0.5.
                   Surface hydrocarbon  reactivity:  standard OZIPP conditions.
                   Aloft  hydrocarbon reactivity:  standard OZIPP conditions.
                26 July 1973
                 (b) Emission Hydrocarbon Reactivities

                               20 August 1973	
                                               24 July 1974
Species  Trajectory 1  Trajectory 2  Trajectory 1   Trajectory 2   Trajectory  1   Trajectory  2
PROP
BUT
FORM
ACET
0.221
0.779
0.008
0.012
0.203
0.797
0.007
0.011
0.223
0.777
0.007
0.011
0.275
0.725
0.008
0.012
0.226
0.774
0.008
0.012
0.225
0.773
0.008
0.013
                                      (c) Mixing Height
                                             (m)
                  Date
      26 July 1973—trajectory 1
      26 July 1973—trajectory 2
      20 August 1973—trajectory 1
      20 August 1973—trajectory 2
      24 July 1974—trajectory 1
      24 July 1974—trajectory 2
                          Morning Mixing  Height
                          	PDT	

                                100 at 0800
                                 60 at 0800
                                204 at 0800
                                142 at 0800
                                 50 at 0800
                                 50 at 0800
                                     Afternoon  Mixing  Height
                                    	PDT	

                                            137 at 1300
                                            750 at 1700
                                            730 at 1500
                                            410 at 1600
                                            250 at 1700
                                            670 at 1600
         3zR/m
                                             14

-------
                           TABLE 1 (Continued)






                              (d) Emissions




                        26 July  1973—Trajectory 1
Time
(PDT)
1000
1100
1200
1300
1400
1500
1600
1700
26 July
Time
(PDT)
1300
1400
1500
1600
1700
20 August
Time
(PDT)
0700
0800
0900
1000
1100
1200
1300
1400
1500
NOx
(ppm)
0.019
0.043
0.001
0.037
0.0001
0.0007
0.0015
0.0038
HC
(ppmC)
0.172
0.457
0.198
0.491
0.006
0.046
0.042
0.034
1973— Trajectory 2
NOX
(ppm)
0.0028
0.0594
0.0597
0.0241
0.0214
HC
(ppmC)
0.0481
0.8337
0.7324
0.2483
0.336
1973— Trajectory 1
NOX
(ppm)
0.0089
0.0262
0.0002
0.0080
0.0103
0.0056
0.0038
0.0038
0.0042
HC
(ppmC)
0.0546
0.2304
0.0490
0.1223
0.0569
0.0494
0.1575
0.1559
0.0628
32R/m                             15

-------
                           TABLE 1  (Concluded)






                       20 August 1973—Trajectory  2
Time
(PDT)
1100
1200
1300
1400
1500
1600
1700
24 July
Time
(PDT)
1200
1300
1400
1500
1600
1700
24 July
Time
(PDT)
1000
1100
1200
1300
1400
1500
1600
1700
NOX
(ppm)
0.0159
0.0002
0.0052
0.0219
0.0001
0.0086
0.0524
HC
(ppmC)
0.1849
0.0007
0.0002
0.0041
0.0001
0.0011
0.0032
1974 — Trajectory 1
NOX
(ppm)
0.0055
0.0919
0.0712
0.0400
0.0233
0.0150
HC
(ppmC)
0.1452
0.960
1.402
0.4207
0.1145
0.1283
1974— Trajectory 2
NOX
(PPm)
0.0079
0.0828
0.0207
0.0268
0.0123
0.0183
0.0627
0.0591
HC
(ppmC)
0.139
0.859
0.180
0.200
0.252
0.372
0.694
0.479
32R/lt                            16

-------
changed between the time of the initial condition and the time of subse-
quent emissions, the computer code would automatically adjust the emis-
sions factor.

     The LIRAQ QSOR input file for 1975 was used to determine the source
emissions.  The data in this file, expressed in units of gm/sec/grid-cell,
with 5-km grid cells, were converted to ppm using the following
information:
             grams
moles _ 	
liter   sec-grid cell

          value in
          QSOR file
 mole
 gram
                          M W
 3600 sec
     fir
    t
one hour
to second
conversion
                       inversion
                       height in
                         meters
                                                              1000
 convert
to liters
  ppm =
      _ moles   24.4 a
10
          ter    mole
                 ideal
                  gas

     The LIRAQ emissions inventory was prepared by dividing all emissions
of hydrocarbons into three categories (propylene, butane, and aldehydes)
for use in the LIRAQ chemical mechanism (see MacCracken and Sauter,
1975).  Therefore, the alkane and alkene values were multiplied by 4
(i.e., butane) and 3 (i.e., propylene), respectively, to obtain units in
ppmC.  The alkane, alkene, and aldehyde values were added for each hour to
obtain the hourly hydrocarbon emissions.  The reactivities used are given
in table 1.

     The width of the trajectory was determined by the emissions grad-
ient.  In one case, there was as much as a factor of 100 between grid
cells, and a 15-km-wide trajectory was used.
3.1.1.5   Pollutant Concentrations Aloft

     Aircraft data (see MacCracken and Sauter, 1975, pp. 871-948) were
used to determine the concentrations aloft.  The values used were the
average of the measured quantities obtained when the aircraft was above
the OZIPM trajectory.  Because hydrocarbon data for 1977 were not avail-
able, data for 1974 were used.  The concentrations used are given in table
1.
szR/2
           17

-------
3.1.1.6   Chemistry

      In all cases, the  standard EKMA chemistry was  employed,  but  the
reactivity and aldehyde fractions were taken from the  LIRAQ  input files.
The effects of considering a different chemical  mechanism  for  evaluating  a
control strategy are addressed in chapter  5.
3.1.2   San Francisco Case Studies

     The six trajectories developed for the  San  Francisco  region  are
illustrated in figures l(a) through 6(a).  In each  case  the final  destina-
tion was chosen to coincide with  a monitoring station.   Figures l(b)
through 6(b) illustrate the results of the six trajectory  model runs  for
this region.  The HC emission profiles used  in the  OZIPM computer  code  are
also shown, along with observed ozone "Values and  those computed by the
LIRAQ model.

     The main emphasis in this study was applied  to the  26 July 1973
trajectory shown in figure 1.  This trajectory was  chosen  because  it
represented the trajectory to the highest observed  ozone concentration  for
the prototype meteorology day modeled in the LIRAQ  study.  According  to
our analysis of available wind data, the air parcel  that eventually
affects the Livermore area originates at 0800 PDT over the ocean  just
south of the city of San Francisco.  Between 0900 and about 1000  hours,
the trajectory passes over the San Francisco peninsula where emissions
from four major freeways and San  Francisco International Airport  are  added
to the emissions from the industrial area of South  San Francisco.   The  air
parcel then passes over the bay and veers south  along the  east shore  where
freeways and industrial emissions from the Oakland  area  are entrained and,
finally, moves east through a canyon into the Livermore  Valley.   As
documented in chapter 4, the model results are extremely sensitive to wind
speed because of the precursor emissions injected along  the trajectory.

     The simulation results for trajectory 2, 26  July 1973, are shown in
figure 2.  There is a dip in the  simulated ozone  profile at 1600  PDT
because of a large and sudden increase in mixing  height  (163 to 700 m in
one hour).  One complication in comparing LIRAQ  and the  OZIPM stems from
the analytical  function used in the LIRAQ model  to  simulate vertical
gradients in concentration.  Evidently, the  analytic function used in the
LIRAQ model to account for vertical mixing allows the simulated ground
concentrations to respond more slowly to rapid changes in  the mixing  depth
than is the case in the OZIPM model, which assumes  instantaneous mixing
throughout the mixed layer.
32R/2

                                   18

-------
                                                                Rl'C
                                                             PSE
                                                                      •IP.:".
   570    £90
UTM Coordinate
                             (a)   Trajectory Path
                    FIGURE 1.  TRAJECTORY 1 FOR 26 JULY 1973
                                                                  650
32R 3
                                     '19

-------
                              (uidd)
32R 3
                                           20

-------
4300
4290
42BD
4270
4260
4250
4240
4230
4220
0)
re 4210
c
"2 4200
0
" 4190
= 4160
4170
4160
4150
5140
4130
5120
4110
4100
£TC
—
-
-
-
-
C
J.riBB
" \
" /N

- ,/^v
—
-
-
-





I !
0 510
                                       -FPL
                                                                  • RTC
                                                                      4PJTT
                                                               'f'SE
                             •IV5N    -tDIi"
                                             DFB
                                                 rRTl
                                                    + rl^SL)
                                           r-;:-N  -tr?s
                       1300
     i^
                      rue
                       PDT  IsFH   '  ^
                            X        **.\
                   -KDFM
530
550
                                     570     590     610
                                    UTM Coordinate
                                (a)  Trajectory Path

                     FIGURE 2.  TRAJECTORY 2 FOR 26 JULY  1973
 »DDL
  1  __j	L_
630    650
32R 3
                                        21

-------
32R 3
                                                                                                    O)
                                                                                                    cc
                                                                                                    c
                                                                                                    O
                                                                                                         a;
U
c
o
o
                                                     22

-------
                                     FPL
                                                           ••PSE
                                   570    590    610
                                  UTM Coordinate
630
650
                               (a)  Trajectory Path
                    FIGURE 3.  TRAJECTORY  1 FOR 20 AUGUST 1973
32R 3
                                        23

-------
32R 3
                                           24

-------
                                                       REI!
                                                           r-SE
                                                                 p>rr
•S4200

54190
[90
510
530    550
                                  570    590
                                  UTM Coordinate
        »DGL
 J	|_
610    630
650
                                (a)  Trajectory Path
                     FIGURE 4.   TRAJECTORY 2 FOR 20 AUGUST 1973
32R 3
                                          25

-------
                                                                                       OJ
                                                                                       c
                                                                                       o
                                                                                       
-------
0)
4-»

(O
s-
o
O
                                       FPL
                                                             ••PS£
    109JJ),
                                                       ^K'.
510    530    550    570    590    610    630    650

                       UTM  Coordinate



                   (a)  Trajectory  Path



        FIGURE  5.  TRAJECTORY 1  FOR  24 JULY 1974
  32R  3
                                          27

-------
                                                                                                             to
                                                                                                             OJ
                                                                                                            CCL
                                                                                                             re

                                                                                                             3
                                                                                                  I—  -r-    (/)
                                                                                                                  T3
                                                                                                                   0)
=3

O
                                                                                                                   O
                                                                                                                  O
                                                                                                                  UJ
                                                                                                                  a:
32R  3
                                                             28

-------
                                      FBL
                                                                   RMT
                                                            'PSE
                                                                     HfiCT
610     630
                                                                 650
                                    UTM Coordinate
                                (a)  Trajectory Path
                     FIGURE 6.   TRAJECTORY 2 FOR 24 JULY 1974
32R 3
                                         29

-------
o

o

o
         I/O
         CO
         o
                     (UJdd)
                                                        9UOZQ
   O
   CVJ
     •

   O


   o
     •

   C\f
                                    o
                                    «—I
                                     •

                                    o
                                                                                       o
                                                                                       o
                                                                                        o
                                                                                        o
                                                                                        vo
                                                                                       o
                                                                                       o
                                                                                       in
                                                                                       o
                                                                                       o
                                                                                       O  >i
                                                                                       O  (O
                                                                                       CO  O
                                                                                                 in
                                                                                                 O)
                                                                                                o:
                                                                                                 (O
                                                                                           o   ,±
                                                                                           I   I
                                                                                                     O)
                                                                                                     •o
                                                                                                     o
                                                                                            o
                                                                                           o
                                                                                           vo
                                                                                       o
                                                                                       o
                                                                                       CM
                                                                                       o
                                                                                       o
                                                                                       o
                           (aidd)
32R 3
                                                       30

-------
     The simulation results for trajectory 1, 20  August  1973,  are  shown  in
figure 3 and are similar to the results for the 26  July  1973 trajectory
shown in figure 1 in that the injection of precursors  is strongly  depen-
dent on the choice of wind speed.  The sparseness of wind-speed  data  in
the LIRAQ files and the difficulty of accurately  interpreting  the  LIRAQ
wind fields introduce large uncertainties as to the path and timing of the
trajectory.  The sensitivity to wind speed is discussed  in  section 4.

     The results for trajectory 2, 20 August 1973,  shown in figure 4,
demonstrate a close agreement between the LIRAQ and OZIPM models and  the
observed ozone profile.

     The trajectories of 24 July 1974, which are  shown in figures  5 and  6,
cannot be compared for the LIRAQ and OZIPM models because the  results of
the former are not available.  The trajectory illustrated in figure 5
shows a drop in the ozone at 1600 PDT due to a sudden  increase in  the
mixing height (96 to 242 m in one hour as is the  case  for trajectory  2 of
26^July 1973).  The most important change, which  would increase  the
simulated ozone for the trajectory results shown  in figure  6,  would be a
path slightly more to the west than the one shown.  The  emissions  density
on either side of the OZIPM model is quite different from that of  the
trajectory path, because the path determined from the  LIRAQ wind fields
follows the edge of the bay.  This type of "path" sensitivity  is also
demonstrated in section 4 for the 26 July 1973 trajectory shown  in figure
1.
3.1.3   Summary of Results for San Francisco Case Studies

     Table 2 summarizes the results of the case studies just described.
The series of six trajectories for the San Francisco region represents  a
severe test for a simple type of model such as that employed in  OZIPM.
Special care was required in using the options built into the model
because of the terrain features, wind patterns, and varied emissions
densities found and because of the lack of dependence on initial condi-
tions.  As discussed later in chapter 4, several factors were involved  in
preparing the input data, which also required careful analysis.  Neverthe-
less, the input data selected appear to provide a reasonable level of
success when the OZIPM results are compared with either observed data or
the LIRAQ results.

     Primary attention was given to trajectory 1 of 26 July 1973; thus,
the poor results obtained for trajectory 2 of 24 July 1974 might be
partially due to the failure to consider refinements to the obviously
sensitive input data.  However, the lack of a LIRAQ simulation for that
day eliminated a principal standard of comparison and, therefore, our
efforts were concentrated elsewhere.

32R/2

                                   31

-------
      TABLE 2. SUMMARY OF RESULTS FOR THE SAN FRANCISCO  CASE  STUDIES
Date
26 July 1973
20 August 1973
24 July 1974

Trajectory
No.
1
2
1
2
1
2

Observed
0.18
0.10
0.08
0.20
0.20
Maximum 03
(ppm)
OZIPM-Predicted
0.20
0.06
0.12
0.09
0.19
0.12

LIRAQ-Predicted
0.19
0.08
0.04
0.07
NA*
NA*
NA = not applicable
                                 32

-------
     When examining the results shown  in table 1,  it  should  be  noted  that
instantaneous values are given for the models, but  an hourly average  value
is given for the observed data.  However,  as noted  earlier and  illustrated
in the trajectory model results shown  in the figures, ozone  tends to  vary
rather slowly near the peaks.  The results shown  in the figures  should
also be compared for timing effects.   For  instance, figure 5(b)  shows that
the OZIPM-simulated ozone peak occurs  an hour before  the  observed peak.
The terrain near the peak could involve some convergent wind flow, which
would raise the mixing height without  diluting it;  thus,  the mixing height
used in OZIPM for that time (1600 to 1700  hours) might have  been inapprop-
riate.  This trajectory does, in fact, follow a path  similar to  that  of
the 26 July 1973 trajectory 1 path discussed earlier.  The results
presented in figure 6(b) for trajectory 2  of 24 July  1974 also  show that
the timing and peak value might be much closer to that of the observed
ozone level if convergent flow effects had been involved  during  the
previous two hours.  However, again, this  possibility was not pursued.
3.2   SACRAMENTO APPLICATIONS

     Air quality modeling of the Sacramento region was  performed  using  a
sophisticated three-dimensional grid model (the SAI Airshed Model)  as
described by Reynolds et al. (1979).   In that study two 1976 ozone-episode
days were modeled (28 June  and 24 August).  Detailed descriptions of the
inputs to the Airshed Model were presented in that study.  In this  study,
we compared the results of  Reynolds et al. with the OZIPM/CBM trajectory
model results and those of  the regular city-specific OZIPP.

     Figure 7 shows the Sacramento modeling region and  the available moni-
toring stations.  The modeling region  is 50 km on each  side and is  divided
into a 625-grid square with each grid cell 2 km on a side.  The modeling
region consists of four vertical levels.  The first three levels  are kept
within the mixed layer until around noon.

     In this study, we compared the results of Reynolds et al. with those
of a series of less complex models.  If we arrange these models on  the
basis of model complexity,  with a high degree of commonality among the
models, comparisons of results between adjacent models  can be made  in a
way that minimizes the number of model differences involved.  A similarity
in the results of adjacent  models would indicate that for the particular
case studied, the differences in complexity were not important.
  By model complexity we mean the spatial and temporal detail with which
  the modeling is executed and also the detail with which the physical and
  chemical processes are represented.

32R/2

                                   33

-------
                             LEGEND
                      * AIR MONITORING SITES
                      • SURFACE WIND MEASUREMENTS

                      • VERTICAL TEMPERATURE SOUNDING

                        VERTICAL HIND SOUNDING
                       SACRAMENTO
                        METROPOLITAN
                        AIRPORT
                              McCLELLAN
                            LI AIR FORCE BASE ~ ~~"
                                                                     HATHER AIR
                                                                     FORCE BASE
                                                                      A AIR MONITORIHG SITES
                                                                             ROSEVILLE
                                                                             NORTHGATC
                                                                             SACTO APCD
                                                                             CALIF ARB
                                                                             HEADOUVIEU
                                                                             RANCHO SECO
         FIGURE  7.   LOCATIONS OF MONITORING SITES  IN  THE SACRAMENTO AREA
32R 3
34

-------
Correspondingly, a  large difference  in results  would  apparently indicate
that the features uniquely addressed by the more  complex model  were
significant for that case.

     The discussion that follows first describes  the  models  that  were
applied and highlights important differences between  them.   Details  are
then presented for  two case studies  performed for  the Sacramento  area.
The final section of this chapter summarizes the  results of  these studies.
3.2.1   Model Definition
     The following  list briefly describes the  series  of  four  models  used
in this study.  They are described  in greater  detail  in  the discussions
that compare them.  Some models are distinguished  only by  the mode of
application.

     >   The SAI Urban Airshed Model.  This model  is  similar  in
         concept to the LIRAQ model applied to San  Francisco.

     >   The SAI trajectory model.  In terms of  inputs,  computa-
         tions, and results at points along a  selected trajectory
         this model differs from the Airshed Model  only  through
         the elimination of horizontal dispersion  and convergent
         and divergent winds.

     >   An EKMA-style model (OZIPM/CBM), which  uses  the same
         chemistry  (Carbon-Bond) and mixing heights as the SAI
         trajectory model.  (In this case, the model  is  the same
         as the OZIPM model described for the  San  Francisco study,
         except that the regular EKMA chemistry  has been replaced
         with the Carbon-Bond chemistry.)

     >   The regular city-specific OZIPP model incorporating  the
         standard EKMA chemistry.

     In this section we wish to highlight the  major differences  among  the
models.
32R/2

                                   35

-------
3.2.1.1   Comparison of  the  SAI Grid  and Trajectory Models

     These models were designed to complement  each  other  and,  therefore,
many algorithms  are  identical for both models  (several  subroutines  of  the
computer codes are actually  shared);  furthermore, they  use  the same input
files.  The trajectory model begins on a square  of  the  grid model  at  a
specific time.   The  path of  the trajectory  is  then  determined  solely  by
the wind speed and direction in the lowest  level of the grid-model
files.  Because  the  other  levels  in the grid model  often  advect with
velocities that  are  different from this lowest level, the two  models  often
generate different results as the simulations  progress  in time.  Neverthe-
less, the trajectory model provides an inexpensive  method for  testing
parts of the grid model.

     A special feature of  the trajectory model  is its ability  to be
operated backward in time.   This feature was used to generate  the  tra-
jectories used in this study.  The time and location of either the
observed or the  simulated  ozone maximum were used to start  the backward
trajectory to 0600 hours.  Thus, the  forward trajectories always arrived
at the desired spot  at the proper time for  comparison with  either  observa-
tions or grid-model  results.  Changes  in emissions  often  lead  to changes
in the time and  location of  maximum ozone concentrations.  Small  changes
in times of maximum  ozone  concentration at  some  specific  monitoring site
can be associated with rather large differences  in  the  location of  the
origin, and in the actual  pathway taken by, the  air parcel  producing  the
specific ozone maximum.  Therefore, when compared with  a  grid  model,  any
trajectory model used as a tool for control strategies  possesses  the
inherent shortcoming of  being incapable of  accounting for these changes.


3.2.1.2   Comparison of  the  SAI Trajectory  Model and the  OZIPM/CBM  Model

     The following similarities and differences  exist between  the  tra-
jectory model and the OZIPM/CBM developed for  this  comparison:

     >  Chemistry.   Both models used  in this study  employ Carbon-
        Bond chemistry identical to that of the  Airshed Model.
        However, the photolytic constants are  computed  differently
        in the OZIPM/CBM and SAI models.  For  this  study, we
        modified the regular OZIPM/CBM values  for N02 photolysis
        using a  constant factor so that all models  agreed at 1300
        PDT.  In the Airshed Model and trajectory model,  the rates
  Detailed discussions of this comparison are available elsewhere  (see
  Reynolds et al., 1979).

32R/2

                                   36

-------
        of all other photolytic reactions vary with  N02  photoly-
        sis, with a fixed ratio for each; but in the OZIPM/CBM  the
        photolysis rates vary independently.  Aldehyde photolysis
        was adjusted in the OZIPM/CBM to give agreement  between
        the models at 1100 PDT.

        Actually, these differences in photolysis  rates  constitute
        an advantage in sophistication for the OZIPM/CBM.  The  N02
        photolysis rates normally  used in the OZIPM/CBM  are  some-
        what lower than those used in the SAI models because  the
        latter formerly used an algorithm based on older data.
        Incidentally, the SAI models are now being updated to the
        OZIPM/CBM N02 photolysis rates, which are  those  recom-
        mended by Demerjian, Schere, and Peterson  (1980).  Since
        the purpose of the present study was to compare  the
        OZIPM/CBM with previously  computed results of the Airshed
        Model, we were forced to alter the OZIPM/CBM models  to
        eliminate this difference  rather than wait for the older
        SAI studies to be rerun with the newer photolysis rates
        for N02.

        The use of fixed ratios to N02 photolysis  in the SAI
        models in place of the variable ratios used  in the
        OZIPM/CBM model may lead to some minor differences in
        chemistry.  The ratios are at a maximum at solar noon and
        a minimum at sunrise and sunset (Whitten,  Killus, and
        Hogo, 1980).  The photolysis rates for aldehydes change
        more with solar zenith angle than the N02  photolysis  rate
        does because aldehydes photolyze at the short wavelength
        end of the solar spectrum, whereas N02 photolyzes nearer
        the long wavelength end of the ultraviolet spectrum.  The
        short ultraviolet wavelengths are more affected  by the
        ozone in the stratosphere  than the longer  wavelengths.  At
        high zenith angles (morning and evening),  the solar  rays
        must pass through a thicker layer of ozone.  Therefore,
        the ratio of aldehyde photolysis to N02 photolysis varies
        throughout the day, reaching a maximum at  solar  noon.   For
        this particular study, the OZIPM/CBM aldehyde photolysis
        values were multiplied by  a constant value throughout each
        day so that the models agreed at 1100 PDT.   Therefore,  in
        the early morning the photolysis rate of the aldehydes  in
        the OZIPM/CBM would be somewhat less than  that used  in  the
        SAI models.

        For this particular study, we chose to modify the OZIPM/-
        CBM to make it as much like the Airshed Model and trajec-
        tory model as possible.  By removing all possible
32R/2
                                   37

-------
        potential variables between models, we  hoped  to  be  able  to
        better compare the fundamentals  underlying  these  models.
        The CBM version of OZIPM/CBM  has  normally been applied to
        assist users of the Airshed Model to estimate potential
        control scenarios.  For such  applications the photolysis
        adjustments discussed here are normal.   Perhaps  for this
        study an additional series of tests with OZIPM/CBM  using
        the regular EKMA photolysis rates would  have  been helpful,
        but they were not performed during that  phase of  this
        contract.

     >  Reactivity.  The SAI trajectory  model and Airshed Model
        are operated with reactivity  splits that vary with  each
        source category.  However, the OZIPM/CBM does not have
        this feature; instead, reactivity is assumed  to  be
        constant for all hydrocarbon  emissions  throughout the
        day.  For this study, the OZIPM  computer code was modified
        so that three different hydrocarbon reactivities  could be
        used: one for the initial conditions, one for the aged
        hydrocarbons aloft, and one for  the emissions that  occur
        throughout the day.  Hence, the  only differences  in reac-
        tivity were in the temporal variations  aloft  and  in the
        variable emissions used in the SAI models compared  with
        the fixed reactivities employed  in the  emissions  for the
        OZIPM models.  The reactivities  used in  the OZIPM/CBM were
        determined from averages of emissions used  in the tra-
        jectory model; for averaging the  hydrocarbons aloft, a
        weighting factor was used each hour that was  equal  to the
        positive change in mixing height.

        In a sense, the N02/NOX ratio also acts  as  a  reactivity
        effect.  The OZIPM/CBM uses a fixed ratio of  N02/NOX (10
        percent) for all NOX emissions,  whereas  the SAI models
        allow this ratio to vary according to their source  cate-
        gory (the average ratio is typically about  5  percent).  At
        this time, we have not attempted  either  to  change the
        OZIPM/CBM or to fix the ratio in  the SAI model,  because we
        feel the difference is trivial.  For NOX aloft, the
        OZIPM/CBM uses pure N02, which is close  to  typical  values
        found in the trajectory model simulations because the
        N02/NOX ratio is almost always greater  than 0.85; often,
        the values are greater than 0.99.

     >  Integration Scheme.  The OZIPM/CBM uses  a Gear-type method
        without any steady-state approximations, whereas  the
        trajectory model uses the same Crank-Nicholson finite


32R/2

                                   38

-------
        differencing scheme and steady-state  approximations  that
        are used in the Airshed Model.  Again, this difference  in
        model sophistication is opposite from the  direction
        intended by our series of models.  However, our previous
        tests using smog chamber experiments  suggest  that the dif-
        ferences introduced by the numerical  integration schemes
        should be minimal.

     >  Vertical Layers.  The Airshed Model and trajectory model
        share the same vertical layers and algorithms for numeri-
        cal integration, but additional contributions are intro-
        duced into the Airshed Model for convergent or divergent
        winds.  The OZIPM/CBM, of course,  is  limited  to providing
        calculations of the mixed layer as a  whole, but fixed
        concentrations in the layer aloft  can be introduced  as  the
        mixing height rises.  The SAI models  account  for mixing
        within the mixed layer, mixing within the  inversion  layer,
        and eddy diffusion among all layers.  The  OZIPM/CBM
        assumes instantaneous mixing within the entire mixed
        layer, and no eddy diffusion is considered across the
        boundary defined by the mixing height.

        In our comparison studies, the effectiveness  of multi-
        layers and eddy diffusion was one  of  the central issues to
        be evaluated in this region of our model series.  A
        problem that we tried to avoid, which does confound  the
        comparison, is the entrainment of  pollutants  from aloft.
        The OZIPM/CBM requires fixed concentrations aloft, so
        these must be chosen from some "proper" average of the
        time-dependent concentrations computed in  the SAI trajec-
        tory model.  With the average value used in this study  we
        attempted to weight most heavily the  concentrations
        entrained when the mixing height rises most signifi-
        cantly.  A more complex weighting  scheme might involve  the
        time when the greatest effect on the  chemistry occurs;
        however, this effect was not evaluated.  Concentrations
        aloft are not considered for the time before  the inversion
        rises or after it has reached some maximum.   As the  mixing
        lid drops late in the afternoon, the  only  process affect-
        ing the surface layer from concentrations  aloft is eddy
        diffusion.  Eddy diffusion is treated in the Airshed Model
        and trajectory model, but is neglected in  the OZIPM/CBM.

     >  Mixing height.  All  models used in the OZIPM/CBM that are
        based on the OZIPM computer code,  as well  as  the Airshed
        Model  and trajectory model, can use identical mixing


32R/2
                                   39

-------
        heights with values that vary  linearly  in  time  between
        specified values at each hour.

     >  Temperature.  The temperature  varies .in the  Airshed  Model
        and trajectory model, but the  OZIPM/CBM currently  employs
        a fixed temperature.  This difference can  be  signifi-
        cant.  Temperature affects both vertical diffusion and
        chemistry in the SAI models, but  it can affect  only
        chemistry in the OZIPM/CBM because vertical mixing is
        assumed to occur instantaneously  within the mixed  layer.

     >  Emissions.  The Airshed Model  and trajectory  model allow
        for emissions into all layers; the OZIPM/CBM  treats  all
        emissions in the mixing layer  alike and does  not directly
        address emissions above the mixing layer.  For  the layer
        aloft in the OZIPM/CBM, the emissions must be accounted
        for in the determination of the fixed concentrations
        aloft.  The sum of the emissions  used in the  lower layers
        of the trajectory model was used  for the mixing  layer  in
        the OZIPM-CBM.  For this study, the OZIPM  computer code
        was modified to treat emissions in an absolute  fashion
        rather than as a multiple of the  initial conditions.  This
        was implemented by using the transported surface layer
        inputs as the initial concentrations.  The normal  initial
        concentrations (the CALC mode  in  OZIPM) were  specified  as
        1.0 for both HC and NOX, but these values  were  not added
        as initial concentrations.  They  were used only  for
        emission fraction development  because emissions  are
        expressed relative to these values in the  OZIPM  code.

     >  Emissions for the SAI models are  given as  total moles
        emitted into each cell during  each hour.   To  arrive  at
        values appropriate for the OZIPM/CBM we used  the following
        conversion procedure:  the mixing volumes  of  the trajec-
        tory model and the OZIPM/CBM were assumed  to  be ^equal
      "  below the mixing height, such  that

                         V =  A x  Zmix     ,

        where A is the area of the horizontal cross-section  of  the
        air parcel defined in trajectory model simulations,  and
        Zm.jx is the mixing height.  If the volume  is  expressed  in
        cubic centimeters, the moles emitted in one hour (the
        number available from the trajectory model computer
        output) can be divided by this volume to give moles-cm
32R/2


                                   40

-------
        units.  This,  in turn, can readily be converted to the
        OZIPM-CBM units of concentration, ppm, by  using a conver-
        sion factor of 2.445 x 10^ ppm moles'^ cm^, which is
        technically correct for a perfect gas at 298 K and 1
        atmosphere of  pressure.  The numbers calculated at this
        point are almost directly applicable to the OZIPM/CBM
        model.  First, the use of 1.0 for the initial concentra-
        tions of HC and NOX in the CALC mode implies that each
        one-hour emissions number would be the concentration added
        during the hour if the mixing height were  the same as the
        initial value  ZQ.  However, the computer codes are written
        so that, at each instant in time, the emissions factor  is
        multiplied by  ZQ/Zmix,  Therefore, the Zmix drops out and
        the actual numbers (En) used are merely

                   En  = A x 2.445  x  1010/Z0

        where A and ZQ are expressed in centimeters.

        In this particular study, it was occasionally necessary to
        use special emissions factors.  These factors were used
        for those cases in which the trajectory model employed
        substantial initial conditions for the first two layers
        (up to 100 m)  even though the mixing height was only 50
        m.  Since there was typically an order-of-magnitude
        difference in  concentration between the initial conditions
        below 100 m and the layers above this level, there was no
        way to compute a reasonable average value  to be used in
        the OZIPM/CBM for the layer aloft.  Therefore, the initial
        conditions between 50 and 100 m used in the SAI models
        were treated as emissions in the OZIPM/CBM.  These
        "emissions" were added to the normal emission during the
        hour when the mixed layer in the SAI models jumped from 50
        to 100 m.  For these cases the appropriate OZIPM/CBM
        emissions factors merely add to the normal emissions,
        since the initial mixing height is 50 m and the height
        added is also  50 m.
3.2.1.3   Comparison of the OZIPM/CBM with the Standard City-Specific
          EKMA (QZIPP)

     The obvious intention of this comparison was to evaluate only the
differences between the Carbon-Bond chemistry used in the SAI models and
the standard propylene/butane chemistry used in OZIPP.  Although the OZIPM
computer program was specifically written to handle such comparisons, some


32R/2

                                   41

-------
complications were  introduced when the OZIPP was  operated  with  the  pro-
pylene/butane chemistry.  The Carbon-Bond chemistry  used  in  this  study
assumes that formaldehyde and ketones represent half  of the  total alde-
hydes found in the  simulation, whereas the formaldehyde in the  city-
specific EKMA is only 40 percent of the total  amount  of aldehydes.  The
photolysis rates used in the Airshed Model runs are  based  on a  theoretical
solar radiation function that does not contain the updated NC^  absorption
cross-sections.  The city-specific EKMA simulations  use the  latest  NC>2
cross-sections, which are approximately 13 percent lower  than those used
in the Airshed Model.

     The reactivity  of the two mechanisms was  not typically  adjusted  in
this study.  The total HC concentrations and emissions rates were identi-
cal for these two models, but the standard EKMA propylene/butane  chemistry
was typically used with the standard 25 percent propylene, 75 percent
butane, and 5 percent aldehyde reactivity.

     Another difference between the OZIPM/CBM  and the regular city-
specific EKMA is the use of variable mixing-height inputs  in the  former,
more sophisticated,  version.  In the OZIPM/CBM, instantaneous mixing
heights are computed by linear interpolations  between hourly input  values
rather than by the OZIPP method, which uses an exponential interpolation
between the morning  and afternoon mixing heights.  The exponential
increase in mixing height with time provides a constant dilution  factor.
In addition to the  potential problems associated  with the  assumed shape of
the mixing-height time profile, the standard OZIPP cannot  consider  a
decrease in mixing  height that may follow an increase, nor can  it consider
a resumption in mixing-height growth following a  decrease  or a  pause.

     In terms of modeling complexity, these models can be  classified
according to the levels of analysis described  in  the  1980  Federal Register
notice on ozone modeling:

     >  SAI Airshed Model-Level I analysis using  a complex grid
        model.

     >  SAI trajectory model-Level I analysis  using  a complex
        trajectory model.

     >  OZIPM/CBM-Level II analysis using a simplified trajectory
        model.

     >  City-Specific EKMA-Level III analysis.
32R/2
                                   42

-------
3.2.2   Sacramento  Case  Studies

     As previously  described,  the  SAI  Airshed  Model  was  applied  in
Sacramento for two  days--28 June and 24 August 1976.   The  SAI  trajectory
model was run for each day to  establish the  air  parcel trajectory leading
to each ozone maximum.   Next,  the  results  of the SAI  trajectory  model  run
were then used to develop the  necessary input  for the OZIPM/CBM  (i.e.,
Level II) model.  Finally, portions of the results from  this model
simulation were used to  develop some inputs  for  the  last model  in the
series—the city-specific EKMA.  Each  case study is  described  below.
3.2.2.1   Trajectory  Calculations  for  24  August  1976

     The  peak observed ozone  level  for  24 August 1976  was  0.13  ppm,  and
the SAI Airshed Model also predicted this level.  The  meteorology for  that
date consisted of relatively  uncomplicated wind  fields (i.e.,  low wind
shear and little divergence).  The  SAI  trajectory model  was  first run  to
determine the trajectory  path to the maximum  ozone predicted by the  SAI
Airshed Model; and the calculated  trajectory  is  shown  in figure 8.   The
detailed  meteorological and emissions  data used  as input for the SAI
trajectory model calculations are  discussed in Reynolds  et al.  (1979).
For this  trajectory,  the  model predicted  a peak  ozone  level  (i.e., maximum
one-hour  average) of  0.13 ppm, which,  as  previously noted, agreed with
both the  observed level and with the prediction  of the more  complex  SAI
Airshed Model.

     The  SAI trajectory model simulation  served  as the basis for develop-
ing inputs for the OZIPM/CBM model  simulation.   From the SAI trajectory
model output, we obtained the emission  rates  and meteorology (i.e.,  mixing
heights)  for each hour along the trajectory path.   These data,  used  to
derive inputs to the  OZIPM/CBM, are summarized in  table  3.   The emission
fractions, based on a column area  of 4  km , were derived in  accordance
with the  procedure described in the previous  section.  The initial
conditions used in the OZIPM/CBM simulation are  summarized in the top
portion of table 4, along with the  hydrocarbon reactivities.   (Note  that
in this table, pollutants transported  in  the  surface layer actually  refer
to initial concentrations, as was  described in the previous  section.)  For
this particular trajectory, the OZIPM/CBM predicted a  peak ozone concen-
tration of 0.14 ppm,  slightly higher than that predicted by  the two  more
complex models.  Table 5  shows that the NOX,  PAR,  ARO, and ozone concen-
tration profiles for  the  SAI trajectory model and  the  OZIPM/CBM agree
fairly well.  This agreement implies that such factors as  multilevel
mixing, eddy diffusion, and elevated emissions are not particularly
critical  in this application.
32R/2

                                   43

-------
                               I t  C t * D
                       A AIR N3NITOR1NG SITES
                       • SURFAC£ WIND MEASUREHNTS

                       • VERTICAL TEMPERATURE SOUNDING
                       1- VERTICAL HIND SOUNDING
                        SACRAMENTO
                          METROPOLITAN
                          AIRPORT
                                HcCLELLAN
                                AIR FORCE
                                                                       HATHER AIR
                                                                       FORCE BASE
                                                                        A AIR MONITORING SITES
                                                                               ROSEVILLE
                                                                               NORTHGATC
                                                                               SACTO APCD
                                                                               CALIF ARB
                                                                               HEADOWVIEW
                                                                               RANCHO SECO
                                             Times  (PDT)
                       FIGURE  8.   TRAJECTORY  USED  FOR 24 AUGUST 1976
32R  3
                                                     44

-------
TABLE 3.   OZIPM/CBM EMISSIONS AND MIXING-HEIGHT INPUTS
           FOR 24 AUGUST 1976
                                      Mixing
                                      Heights
                                      (meters)

                                          50
                                          50
                                         100
                                         150
                                         225
                                         300
                                         650
                                         800
                                         800
                                         800
                                         800
                                         800
  Taken from the SAI trajectory model  calculation.

Time
(PDT)
0600
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
Emi
NOX
(ppm)
0.
0.00198
0.03287
0.144
0.12225
0.0194
0.0074
0.0287
0.0089
0.01267
0.00709
0.01112
ssions
HC
(PPmC)
0.
0.0031
0.2008
0.904
0.556
0.157
0.123
0.0574
0.038
0.0463
0.0336
0.0766
                          45

-------
     TABLE 4.   INITIAL CONDITIONS FOR CALCULATIONS OF 24 AUGUST 1976

                               (a)   OZIPM/CBM
Transported
Pollutants
Surface*
Aloft
N02/NOX
0.518
1.000
NOX
(ppm)
0.0386
0.00263
HC
(ppmC)
0.1594
0.0552
03
(ppm)
0.0017
0.0259
                         Hydrocarbon Reactivities:



OLE
PAR
ARO
CARB
Emissions
(percent)
of total)
3.8
67.2
25.8
3.2
Surface
(percent)
of total)
1.6
60.2
22.09
16.06
Aloft
(percent)
of total)
9.0
60.66
25.7
10.48
                         (b) City-Specific EKMA
                                      ->- Species
Transported
Pollutants
Surface'
Aloft
NOX
(ppm)
0.0372
0.0026
HC
(ppmC)
0.1881
0.0552
°3
(ppm)
0.0095
0.026
              N02/NOX = 0.572.

              Standard reactivity.
                Taken from the SAI trajectory model calculations.
                Transported pollutants in the surface layer refer to total
                initial conditions (i.e., local generation plus background
                plus any possible transported levels).
32R/m
46

-------
       TABLE  5.    COMPARISON OF THE SAI TRAJECTORY MODEL AND THE OZIPM/CBM CALCULATIONS
                  FOR 24 AUGUST 1976 FOR N0x, PAR, ARO, AND OZONE
Time
(PDT)
0600
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
NU
Trajectory
0.039
0.040
0.037
0.068
0.071
0.053
0.033
0.024
0.016
0.015
0.013
0.013
X
DZIPM/CBM
0.039
0.041
0.037
0.071
0.071
0.052
0.023
0.017
0.015
0.013
0.012
0.011
KA
Trajectory
0.096
0.097
0.143
0.285
0.283
0.234
0.173
0.139
0.113
0.113
0.112
0.114
K
OZIPM/CBM
0.096
0.098
0.133
0.299
0.293
0.242
0.135
0.114
0.112
0.112
0.111
0.112
AK
Trajectory
0.018
0.018
0.026
0.055
0.053
0.041
0.028
0.020
0.015
0.013
0.012
0.011
0
OZIPM/CBM
0.018
0.018
0.025
0.056
0.052
0.040
0.020
0.015
0.013
0.011
0.010
0.009
U
Trajectory
0.002
0.006
0.010
0.011
0.020
0.041
0.061
0.078
0.089
0.108
0.121
0.129
3
OZIPM/CBM
0.002
0.00004
0.009
0.013
0.027
0.053
0.063
0.078
0.100
0.117
0.130
0.139
32R/14
                                           47

-------
     The results of the OZIPM/CBM  simulation were  used  to  provide  inputs
for the city-specific OZIPP simulation.  The lower  portion  of  table  4
shows the initial conditions used  in the simulation.  City-specific  OZIPP
calculations require an initial and final mixing height.   These  values
were 50 m and 800 m, and the inversion height  lasted  from  0800 to  1300
PDT.  For OZIPP calculations we used standard  reactivity (i.e.,  25 percent
propylene) for the hydrocarbon emissions splits and initial  conditions.
Figure 9 shows the results of the  OZIPM/CBM calculation, including the
station observations and the OZIPM/CBM predictions.   The comparison
between ozone observations and the OZIPM/CBM calculations  shows  that they
are similar in temporal behavior.  The ozone predicted  by  the  city-
specific OZIPP model was lower than the observed ozone  concentration by
about 7 percent.
3.2.2.2   Trajectory Calculations for  28  June  1976

     OZIPM/CBM calculations for the 24 August  1976  trajectory  just
discussed were fairly straightforward  because  of  the  lack  of wind shear.
In contrast, the winds for 28 June 1976 contained high  wind shears.   The
results and even the actual "paths" to ozone maximums can  be quite
different for the Airshed Model and trajectory model  if wind shear  or any
horizontal dispersion occurs in the Airshed Model.  The trajectory
calculations for 28 June attempt to address the problems of wind shear and
horizontal dispersion because these factors can be  important in compari-
sons of trajectory and grid modeling results.

     We used the trajectory model to generate  a back-trajectory from  the
point of maximum ozone.  Even though this trajectory model employs  the
same number and size of the vertical layers as the  Airshed Model, the
computer algorithm that is used to run the back-trajectories follows  only
the surface winds of the grid model.  The wind shear within the mixing
layer was significant for this day, and ignoring  the winds in  the second
layer generated a back-trajectory that would have been  inappropriate  since
the surface winds did not pass over any major  emissions.   Because good
mixing typically occurs within the mixed  layer, we  modified the computer
algorithm of the trajectory model to average the  winds  within  the mixed
layer and used the average value instead  of the surface wind value  only.
This produced the trajectory shown in figure 10,  which  led to  an ozone
prediction of 0.15 ppm at 1700 PDT.

     The maximum observed ozone of 0.16 ppm occurred near  Northgate at
1500 PDT; the Airshed Model predicted a maximum of  0.15 ppm at 1600 PDT
between Northgate and Roseville.  Since the trajectory  model predicted an
ozone peak of 0.15 ppm at 1700 PDT, an hour later than  the prediction  of
the Airshed Model, we could not readily compare the EKMA models (OZIPM/CBM


32R/2

                                   48

-------

o
o
o
o
^ i
o
o

o
°0
§

o

o
0

o

o


0
0
o
0
o
o

o
§

o
o
o
o
o
o
0
o
* ^?
o
o
0
o
c/o °
g o
K^H ®
•SI— Q
^ ~ 4 §
_,, iix o
Q- O- Ci
g ^ §o
z: ^ §
5! UJ O
< o ®
o
g
o
Q
o !
e » * n a w —
r N e co >o « o
• • * • * • •
s
o
, O
• co



o
• 0
r—



o
g



o
0
in




o
o

1 —





o
o ^-«
oo i—
r— Q
0-
o;
E
O -r-
O 1—
00
r—



O
0




O
o
o

0
o
o*^
o




o
§
o

)

^
s:
UJ
o
u_
»— t
0
[ ! )
D.
oo
1

1 —
1 — 1
C£.
O
u.
oo
O
I-H
O
Q
UJ
o:
D-
_J
UJ
^^1
o
2:
Q
"^
^^

oo
•z.
0
I—H
I—
<
UJ
oo
CO
o
zz
o
1__
^^
h- O
00 h-
•z.
•ZL UJ
UJ S
K* O
LU eC
CQ 00
1
1 1 \ \

O P*-.
O i—
U. 1—
O 00
o •=>
oo ca:
o: <^-
ca: oo
D-
0 0
O U-

CTl
1 1 1
en
o
                            ONOKU  C.M&
32R 3
49

-------
                         AIR KWlITORlNG SITCS
                         SURFACE WIND HEASUREfCNTS

                         VERTICAL TEMPERATURE SOUNDING

                         VERTICAL HIND SOUNDING
                       TIME =  PDT
                       SACRAMENTO
                         METROPOLITAN
                         AIRPORT
                               NcCUELLAN
                               AIRVORCE BASE
                                                3
                                             0900
                                                  1000
                                                                      HATHER AIR
                                                                      FORC£ BASE
                                                                          AIR MONITORING SITES
                                                                              MSEVILIE
                                                                              MORTHGAT[
                                                                              SACTO APCD
                                                                              CALIF ARB
                                                                              KADOUVIEU
                                                                              RANCMO SECO
                        FIGURE  10.    TRAJECTORY  USED  FOR 28  JUNE  1976
32R  3
                                                     50

-------
or city-specific) with the airshed predictions.   Instead,  we  compared  the
predictions of the OZIPP-type models to the trajectory model  predictions
only.

     From the trajectory model results, we obtained  the  emissions  rates
and mixing height information needed to perform  the  OZIPM/CBM calculations
as discussed for the 24 August 1976 calculations.  Table  6 shows the
emissions rates and mixing heights used in the OZIPM/CBM  calculations.
The top portion of table 7 shows the initial conditions  used  in the
OZIPM/CBM calculations.  The OZIPM/CBM simulation  resulted in a peak ozone
concentration of 0.16 ppm, which, like the 24 August simulation, was
slightly higher than the SAI trajectory model predicted.

     As for the cases previously discussed, the  inputs for the city-
specific EKMA were derived from the OZIPM/CBM simulation.   To provide  a
direct comparison between the models, 0800 PDT OZIPM/CBM  conditions were
taken as the initial conditions for the city-specific OZIPP simulation.

      Figure 11 shows the results of the city-specific OZIPP  calculation
for ozone.  The observed ozone at the monitoring  stations  along (or near)
the trajectory is also shown in this figure.  Unfortunately,  the trajec-
tory passed over only a few stations, and these  do not record the  ozone
maximum; therefore, we were unable to compare the  observed ozone maximum
with the model-predicted ozone maximum.  The city-specific OZIPP simula-
tion was carried out for 10 hours, from 0800 PDT  to  1800  PDT, whereas  the
trajectory model ran from 0600 PDT to 1700 PDT.   The trajectory model
predicted an ozone level of 0.15 ppm at 1700 PDT.  The OZIPM/CBM,  a model
that is more general (i.e., it employs a variable mechanism,  variable
mixing heights, etc.), predicted an ozone level  of 0.167  ppm  at 1700
PDT.  The city-specific EKMA (standard OZIPP) predicted  an ozone of 0.13
at 1800 PDT.
3.2.3   Summary of Results for Sacramento Case Studies

     Table 8 summarizes the results of the case  studies just described.
The important conclusion reached in this part of the  study  is that  the
simple OZIPP-type trajectory model can produce simulations  that  agree very
closely with the simulations of highly sophisticated  models such  as the
SAI Airshed Model and the SAI trajectory model.  Indeed,  the present study
involved the use of extremely detailed input data common  to all models;
yet, the main differences in results were due to the  differences  in
chemistry between the OZIPM/CBM and the OZIPP model with  the regular
propylene/butane chemical mechanism.
32R/2

                                   51

-------
        TABLE  6.    EMISSION  RATES  AND  MIXING  HEIGHTS  USED  ]N  THE
                    OZIPM/CBM CALCULATIONS  FOR 28  JUNE 1976*
                                                     Mixing
                                                    Heights
                                                    (meters)

                                                       150
                                                       150
                                                       220
                                                       250
                                                       280
                                                       310
                                                       370
                                                       460
                                                       600
                                                       800
                                                       800
                                                       800
                Taken from SAI trajectory model calculations.
Emissions
Time
(PDT)
0600
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
NOX
(ppm/hr)
0.
0.00067
0.00217
0.01171
0.01466
0.02545
0.02618
0.0333
0.04198
0.03253
0.03584
0.02019
HC
(ppmC/hr)
0.
0.0011
0.008
0.0388
0.07805
0.1173
0.10678
0.09757
0.20355
0.13898
0.10951
0.04486
32R/14                              52

-------
TABLE 7.   INITIAL CONDITIONS USED IN THE CITY-SPECIFIC EKMA
           CALCULATIONS OF 28 JUNE 1976*
                        (a)  OZIPM/CBM
Transported
Pollutants
Surface
Aloft
N02/NOX
0.845
1.000
NOX
(ppm)
0.0457
0.0025
HC
(ppmC)
0.2899
0.0541
°3
(ppm)
0.0019
0.649
                   Hydrocarbon Reactlvlties:
 OLE
 PAR
 ARO
 CARB
Emissions
(percent
of total)
4.0
67.5
26.0
2.5
Surface
(percent
of total )
2.6
48.6
13.0
35.7
Aloft
(percent
of total )
0.9
63.8
25.8
9.6
                    (b)   City-Specific  EKMA
Transported
Pollutants
Surface
Aloft

NOX
(ppm)
0.0319
0.002
Species
HC
(ppmC)
0.218
0.054

°3
(ppm)
0.035
0.065
        N02/NOX = 0.773

        Standard reactivity.
  Taken from the SAI trajectory model calculations.
                            53

-------






•





•






•





•




•













et
H-

O

O
..,
fy'
UJ
CO
o
*
(•—"- +
J-
»
mt
»


O
o
o
§0
o
o
0
o
o
o
§
o
0
o
o
0
o
o
o
0
o
0







<












00
UJ
3
^£
^>

o
•
t^
o

0
UJ
C£
0.
o
•m-i + MM + MM.!.
C5 —
^ *^
o ©






H





•






•



o
§
8
o
8
o

o
0 H
o
o
8
o
o
O H
0
o
o
o
o
o
0
o
8
o
o
•


o

o
0

^°0
o

— O , tt C5 <
O> >£> •* CJ C
© © © © c
©*©'©'©«
k S
o
00


o
. ^2
fill"




o
k 0
UD
"~




, 0
0
Ln
'


0
• ™jT
r~


0
o
i- co
r~



o
• s




.§



o
• 0
0





o
•5?
0

o
' §
^
?
»




























^^
1—
Q
0.
N_X

_E
h—

























                                                                                                           I
                                                                                                           I
                                                                                                         UD
                                                                                                         r>-
                                                                                                         en
                                                                                                          00
                                                                                                          CM
                                                                                                          CO
                                                                                                          •z.
                                                                                                          o
                                                                                                          I— t
                                                                                                          t—
                                                                                                          o
                                                                                                          LU
                                                                                                          o:
                                                                                                          D-
                                                                                                          Q
                                                                                                          o
                                                                                                          co

                                                                                                          o
                                                                                                          co
                                                                                                          CO
                                                                                                          o
                                                                                                          GO
                                                                                                          CO

                                                                                                          UJ

                                                                                                          o
                                                                                                          tvl
                                                                                                          o
                                                                                                          2:0
                                                                                                          Oh-
                                                                                                          CLQ:
                                                                                                          2:0
                                                                                                          0<
                                                                                                         o:
                                                                                                         rs
                                                                                                         CJ3
                                            ONO
32R 3
                                                   54

-------
           oo
                                                §
                                                CO
           •a:
           c\j

           o
           vo
           r^.
           CTi
                             >    X
               ro    CM
               t—*    f—(

               O    O
           UJ
ro
•-D
CO
OJ

2:
o
oo
1
1 1 1
1.LJ
o
o

f—
•y*

UJ
a:
6) tO O
§ OJ Q-
t- Q. -^^
0
-
*~ 1

ro
z o
CD
O E ^-
^ 1 1
a. •>- n.
«— i X • —
hsl ro
o z:


vc
^^
C3




o
*j . — .
-^ (—
0) «3 D
E O) Q-
•^ Q. ^

O
o
f^
»— 4
0
oo




CTi
n
t-H
•
0





§
r-*
«-H
                            >>
                            s-
                            O
 O  Q)
 0) T5
                                     El
                                     DJ
                            •"-> O -^  Dj
                            "O S  X ^3
                                                CTi
                                                CVJ
           oo
           z:
           o
                                          O
                                          O
                                          VD
                    O
                    O
           o:
           Q.
                                  ro
                                 O
               IT)    PO
               t—I    «-H


               O    O
                .
           O LU
             .
           o oo
           00
                              •o o
                            o  
                               E  c
                              *^-  o
                                 o -IH
              io    m
              »—*    t—t

              <3    C3
           CO

           UJ
           _l
           CO
      O) t£>
      4-> r-^
      
-------
     Whereas the complicated emissions data  constituted  the  unique  feature
of the San Francisco study, the highlight of the  Sacramento  study  is  the
complex wind shear of the 28 June 1976 simulations.   The simple  averaging
of wind data for the two cells within the mixing  layer simulated in the
SAI grid model seemed to generate reasonable ozone  levels  in the trajec-
tory models.  Therefore, the studies of the  simple  trajectory models
conducted to date appear to show that if the precursor levels of HC and
NOX were similar in either the complex or simple  models,  the chemical
mechanism, especially if it's the same mechanism, tends  to simulate
similar levels of ozone.  Although this conclusion  seems obvious, obtain-
ing similar precursor levels for the complex and  simple  models is by  no
means straightforward.

     The present study involved the use of detailed computer outputs  from
the SAI Airshed Model and the trajectory model.   These outputs served  as
sources of input, standards of performance,  and guides to the treatment of
inputs.  Of course, typical applications of  the EKMA  would not be made  in
such an environment.  However, the indications of this study are that
careful application of a simple model such as the OZIPP-type trajectory
model can lead to reasonable ozone simulations.   If the  local  situation
indicates complex problems such as diverse emissions  densities or wind
shear, extra care is warranted.  In the following section we explore  the
sensitivity to some of the situations previously  discussed;  in section  5
we use isopleths to examine the relative applications of EKMA.
32R/2

                                   56

-------
                              SENSITIVITY STUDIES
     In this evaluation, the emphasis on  sensitivity  is  related  to
performance in an absolute  sense  rather than  in  the relative  sense  that  is
used in the control-strategy application  of the  EKMA.  Therefore, we  are
concerned with the absolute ozone  values  simulated by  the  simple OZIPP
trajectory model.  In the San Francisco region sensitivity to  OZIPP
parameters and inputs was emphasized, whereas  in the  Sacramento  study
(discussed later in this chapter)  sensitivity  to differences  between
models was emphasized.

     We did not use a systematic  approach to  selecting the input para-
meters of OZIPM; instead, we emphasized the regional  aspects  of  the cities
studied.  For example, the  EKMA procedure for  predicting control require-
ments necessitates a knowledge of  the initial  (0600 to 0900)  HC/NOX
ratio.  Yet, the application of the model to  the San  Francisco region
indicates that the initial  HC/NOX  ratio,  or more important, the  initial
concentrations of HC and NOX, do  not affect the  simulated  maximum ozone
values.  Hence, the use of  observed HC/NOX ratios may  be questionable for
the isopleth application of the EKMA to San Francisco, even though  the
trajectory model used in the approach can provide reasonable  simulations
of episode ozone levels in  the area.  The conclusion that  observed  HC/NOX
data for San Francisco are  questionable hinges on the  accuracy of the
trajectories determined for this  study, the central issue  being  the origin
of all trajectories in the  Pacific Ocean  at 0800.  When  some  trajectories
starting in the city at 0800 were  investigated,  the combination  of
observed wind velocities and low  HC/NOX ratios in both the observations
and the emissions inventory produced ozone peaks late  in the  day far
downwind of the region.  These trajectories had  passed the monitoring
sites before the occurrence of the observed maximum ozone  concentra-
tions.  Since there were no monitoring sites with which  to test  the model,
the trajectories were not studied  further.  Trajectories that  originate  in
the urban core and arrive at the monitoring site at the  proper time do not
necessarily coincide with trajectories derived from surface wind measure-
ments.  However, it must be emphasized that significant  uncertainties are
associated with the latter, especially in areas  of complex wind  flow.
32R/2

                                   57

-------
4.1   THE SAN FRANCISCO REGION


4.1.1   Initial Conditions

     The main inputs to the OZIPP or the OZIPM  that  control  the  ozone
development for the San Francisco trajectories  are the emissions and
mixing-height profiles.  According to our  analysis,  all  trajectories that
lead to high ozone formation originate over the Pacific  Ocean.   To
illustrate the lack of sensitivity to initial conditions,  the trajectory
to Livermore was simulated using a wide range of initial concentrations
and ratios for HC and NOX from  26 July 1973.  The results  are shown  in
table 9.  The emissions profiles were recomputed for  each  calculation so
that the absolute level of precursor concentrations  caused by emissions
was identical for all the cases.  Similar  insensitivity  to initial
conditions would be seen in the other San  Francisco  trajectories since
they all originate over the ocean.  This is not a case for generally
ignoring initial conditions in  OZIPP models, because  other cities do not
often experience the wind velocities and clean  upwind air  found  in San
Francisco.  The point we wish to emphasize here is that  the  OZIPP-type
model can still give reasonable results in spite of  this lack of sensiti-
vity to initial conditions.


4.1.2   Mixing Heights

     The mixing-height profiles, typically available  directly from the
LIRAQ files, were investigated  for sensitivity  in two ways.  First, the
necessity of using the OZIPM option of hourly mixing-height  data was
explored relative to using the  normal city-specific  EKMA version in OZIPP,
in which only initial and final mixing heights  are used.   This area of
sensitivity proved to be irrelevant for this study,  because  the  change in
mixing height with time could,  in general, be closely simulated  by the
proper choice of initial and final mixing heights for the  standard OZIPP
input parameters.  In other studies, such  as those of Whitten and Hogo
(1981), trajectories have been  considered  in which the shape of  the mixing
height with time could not be adequately simulated using the standard
OZIPP parameters.  The second method involved the concept  of mixing height
itself (discussed in detail in the previous chapter).  The LIRAQ simula-
tion of 26 July 1973 was used extensively by the BAAQMD  for  the  AQMP.  The
main trajectory studied here, on the basis of the meteorological  data
found in the LIRAQ files, arrived at the site of maximum observed ozone--
Livermore—on that date.  Because of the significance of this trajectory,
special treatment of the OZIPM  input data for mixing heights seemed
appropriate.  However, determination of the "proper" mixing  height data
was not pursued beyond the following sensitivity study.  Several  mixing


32R/2
                                  58

-------
TABLE 9.  VALUES FOR MAXIMUM OZONE VERSUS VALUES FOR INITIAL CONDITIONS*
                    NOX          HC         Maximum
                   (ppm)        (ppmC)         Ozone

                   0.003        0.03         0.197
                   0.003        0.01         0.196
                   0.003        0.003        0.194
                   0.001        0.03         0.198
                   0.001        0.01         0.196
                   0.001        0.003        0.195
                   0.0003      0.03         0.197
                   0.0003      0.01 -       0.195
                   0.0003      0.003        0.195
                   * 26  July 1973  trajectory No.  1.
                                  59

-------
heights were adjusted for the  later  stages  of  the  day  when  the  air  parcel
passed through a canyon area into the Livermore  valley where  the  ozone
maximum was observed.  Results using the different  mixing-height  profiles
or vectors are shown in figure 12.
4.1.3   Emissions Vector  (Wind Speed)

     Sensitivity to mixing-height  input data  is  rather  straightforward  in
the OZIPM model.  Precursor concentrations  are reduced  linearly  as  the
mixing heights are increased relative to the  initial mixing  height.   Ozone
is reduced, but less than linearly, with dilution  (Fox, Kamens,  and
Jeffries, 1975).  In some cases, a large concentration  of  ozone  aloft can
actually lead to increases in ozone as the  mixing  height rises.

     Sensitivity to the emissions-profile data actually involves input
preparation factors such  as wind speed and  model  size.  The  wind-speed
factor was of paramount importance  for the  San Francisco trajectories
because this area is characterized  by sharply contrasting  emissions  den-
sities.  The dominant westerly winds typically bring clean air  into  the
area from the Pacific Ocean.  The  city itself lies  on the  northern  end  of
a peninsula and is thus surrounded  by water on three sides.  The peninsula
is a heavily populated suburban area.  Across San  Francisco  Bay,  to  the
east of the city, are the large urban and suburban  areas of  Oakland.  Just
to the east of this populated area  are hills.  Hence, a typical  air  parcel
in this area is subjected to sharply contrasting  emissions levels.   If  a
low wind speed is associated with  the air parcel,  the time spent over
areas of high emissions is much longer.

     For areas such as Los Angeles, there is  much  less  contrast  in emis-
sions levels along a trajectory path once the air  parcel reaches land.
Wind speed would be less critical  for an air  parcel passing  over a  large
area of uniform emissions density.  Hence,  wind  speed in the San Francisco
region is much more important than  it is in the  Los Angeles  region.

     This sensitivity to wind speed is demonstrated in  the 26 July  1973
trajectory to Livermore by using twice the  reported speed  during the
morning hours.  Figure 13 shows that a significant  change  is noted  in the
ozone profiles for different assumed wind speeds.
4.1.4   Model Size

     The grid squares of the LIRAQ model were of 5-km  size, the  value that
we used to define the narrowest width of the OZIPM trajectory model.
Since the path determined by our analysis of the LIRAQ wind data did not


32R/2

                                   60

-------
                O
                CM
      rv.   LO
      p^.   CD
      CTi   CM


       II    II
CD    CD   CD


LU    LU   LU
Z    Z   Z


•ZL    -ZL   -Z.
o    o   o
»—I    *—(   I—t


o:    ix   o:
LU    LU   LU
>    >   >
                                                                                                              o
                                                                                                              o
                                                                                                              o
                                                                                                              o
                                                                                                              ID
                                                                                                              O
                                                                                                              o
                                                                                                              in
                                                            o
                                                            o
                                                                                                                         O
                                                                                                                         IVI

                                                                                                                         O
                                                                                                              o
                                                                                                              o
                                                                                                                  O
                                                                                                                  CL.
                                                                                                               O  1X3
                                                                                                               O O
                                                                                                                   O)
                                                                                                               O
                                                                                                               o
                                                                                                               CM
                                                                                                               O
                                                                                                               O
                                                                                                               O
                                                                                                               o
                                                                                                               o
                                                            CD
                                                            I—" >-
                                                            LU o:
                                                            z o

                                                            Z CJ
                                                            O LU
                                                                                                                             a:
                                                              i CO
                                                                                                                          U_ CTi

                                                                                                                          O i—
                                                                                                                          t/) LU
                                                                                                                          LU "
                                                                                                                          U-
                                                            LU CM
                                                                                                                          CM
                                                                                                                          CXL
                                                                                                                          ^>
                                                                                                                          CD
o
I—(
  •

o
                                                                                                               O
                                                                                                               o
                                                                                                               01
                                                                                                               o
                                              (iudd)
32R  3
      61

-------
                                                                                                                   O
                                                                                                                   O
                                                                      \
                                                                        \
                                                                         \
                                                                          \
                                                                            \
                                                                              \
                                                                    O
                                                                    O
                                                                    LD
                                                                                \
                                                                                   \
                                                                                     \
                                                                                       \
                                                                                         •»
                                                                                            »
                                                                                              •*
                                                                                                                   O
                                                                                                                   O
                                                                                                                   co
                                                                                                  \
                                                                                                     \
                                                                                O
                                                                                O
                                                                                o:
                                                                                D-
                                                                                o
                                                                                l^sl
                                                                                O
                                                                                 O
                                                                                 O
                                                                                                         \
                                                                                                            \
                                                                                                              N
                                                                       O
                                                                       Q_
                                                                                                                   O
                                                                                                                   O
                                                                                                                                C/5
                                                                                                                                O
                                                                                                                                o:
                                                                                                                                o
                                                                                                                                el
                                                                                                                                CL
                                                                                                                                OO
           in
             •

           CO
                                                                                                                   O
                                                                                                                   O
                 in
                  i/o
                  O
           tn    i—<
           O    3
                                                                                                                                u- o
                                                                                 oo u
                                                                                 »— z
                                                                                 UJCV
           GO
                  cc.
                  UJ
                                                                                                                                CO
                                                                    O
                                                                    O
                                                                                                                    o
                                                                                                                    o
   o
   in
32R  3
o
*»•
  t
o
o
PO
o
CM
  •
O
o
^H
  •
O
                                         (iudd)
                                                                62

-------
generally follow the regular grid pattern of the  LIRAQ model,  we  deter-
mined the emission  information for the OZIPM inputs  by including  adjacent
grid-square information when the trajectory path  width overlapped the
LIRAQ grid squares.  The adjacent information was  averaged  using  simple
linear weighting.

     Although the adjacent grid trajectories produce  large  differences  in
ozone concentrations, the 15-km trajectory produces  results  similar  to
those for the central 5-km trajectory, as shown in figure 14.  The size  of
San Francisco—roughly 15 km—tends to place an upper limit  on the nominal
size of a reasonable model.  Also for this sensitivity analysis,  the paths
of the trajectories were "forced" to follow the central, or  standard,
path.  Actually, an analysis of the wind patterns  indicates  that  the path
to the north of the standard path turned toward the  north and  crossed San
Francisco Bay; thus, the high urban emissions did  not affect the  Livermore
valley.  Therefore, this sensitivity analysis involves more  than  a simple
change in width:  the high value of 0.48 ppm ozone predicted for  the
adjacent trajectory to the north reflects a sensitivity to  path definition
as well.
4.2   THE SACRAMENTO REGION

     The SAI Airshed Model and trajectory model had previously  been
applied to this area and, therefore, detailed  inputs  and outputs  were
readily available and familiar to us.  This  access enabled  us to  conduct  a
comparison study emphasizing individual differences between the SAI models
and OZIPP-type models.  A similar study was  recently  completed  for the  Los
Angeles area by Whitten and Hogo (1981).  The  present evaluation  involved
a series of four models that varied in complexity from the  SAI  Airshed
Model to the regular city-specific EKMA trajectory model found  in the
OZIPP computer code.  Two were OZIPP-type models, one was the regular
OZIPP model, and the fourth was based on the OZIPM version  and  was further
divided as follows:

     >  The city-specific model employing variable, instead of
        constant, dilution rates.  The OZIPM computer code  was
        needed for this exercise.

     >  The OZIPM model using variable dilution rates and the same
        Carbon-Bond chemistry used in the Sacramento  airshed
        modeling study (i.e., OZIPM/CBM).

     >  An OZIPP-type model that we have called OZIPM/CBM.  Along
        with the variable dilution and CBM chemistry  additions,
        the starting time is changed to be early enough in  the


32R/2

                                   63

-------
                                  \    \\
o   o 





                                                                >-
                                                                10

                                                                CM
                                                                UJ

                                                                O

                                                                g
                                                                a:
                                                                o
                                                                o
                                                                UJ
                                                    C3
'•udd)
                              auozo
                          64

-------
        morning to maximize the  influence  of  the  emissions
        inventory.   In the regular,  city-specific OZIPP,  the  0800
        starting time  is  intended  to maximize the influence of  the
        0600 to 0900 precursor concentrations.

     The model series  was  intended to  demonstrate the  sensitivity of
OZIPP-type models to three factors:  dilution, chemistry, and starting
time.  Although different  starting times were used in  practice,  the
comparisons of this  study  remove such  a difference.  The  model  employing  a
starting time of 0800  PDT  used initial conditions that were generated  at
0800 by the model that was started earlier.   The  model  that had  been
started earlier could, therefore,  conceivably be  restarted at 0800 to
produce the same result produced by  the continuous model  version.  The
differences between models due to  the  dilution factor  (variable  versus
constant) were also  unimportant  in this study because  the shapes of the
variable dilution curves could,  in general, be closely approximated by
using a constant dilution  rate.  For instance, a  calculation was made for
24 August 1976 in Sacramento using the city-specific inputs with both
variable dilution and  constant dilution rates, but no  difference in ozone
predictions occurred between the two simulations.

     As indicated in chapter 3 of  this report, though  starting  time and
variable dilution factors  did not  show any  important sensitivity for the
Sacramento case, the change in chemical mechanism did  have a noticeable
effect.  More ozone was generated  by the CBM  chemistry than by  the
standard EKMA chemistry, an effect that is consistent  with the  results
reported by Whitten  and Hogo (1981).  That study  further  demonstrated that
the standard EKMA chemistry could  be easily modified to significantly
increase the calculated peak ozone.  The only real option available in the
standard OZIPP model with  which to enhance ozone  is reactivity,  since the
other options are limited  by observations.  The computer  code was also
slightly modified to accept higher photolysis  rates for aldehydes.  Both
of the adjustments (reactivity and higher photolysis rates) merely
accelerated the production rate of simulated  ozone during the morning
hours (which was already higher for  the standard  EKMA  chemistry  than for
the CBM chemistry), but the final  ozone peak  was  not significantly
enhanced.  No attempts to modify the CBM chemistry were made because all
models (the grid, trajectory, and OZIPM/CBM models) using it produced
results whose differences  (when they occurred) could be explained by
factors other than chemistry.

     An important aspect of the differences in chemistry  is found in the
control requirements predicted by the two chemical mechanisms.   This
aspect is discussed in the next section, which details  EKMA applica-
tions.  Absolute differences in simulated peak ozone between the mecha-
nisms are often less important when  they are  used  with  the relative method
of EKMA.


32R/2
                                   65

-------
                               EKMA APPLICATIONS
     When the EKMA  is applied to  an urban  area,  isopleth  diagrams,
observed HC/NOX ratios,  and observed ozone maximums  are  used  to  estimate
the emissions control requirements that are necessary  to  achieve  compli-
ance with the ozone standard.  The isopleth diagrams for  use  in  EKMA
applications are constructed by interpolating between  multiple simulations
of a specific trajectory model.   Normally, the ordinate  and abscissa  of
the isopleth diagrams represent the initial conditions of HC  and  NOX  con-
centrations used in the  trajectory model simulations.  The EKMA  isopleth
lines represent constant maximum  one-hour  ozone  simulated by  the  tra-
jectory model from the ordinate and abscissa value for initial condi-
tions.  These diagrams are constructed by  the OZIPP  and  OZIPM computer
programs.

     In previous sections of this report,  we discussed versions  of  the
OZIPP trajectory model as it was  applied in the  absolute  sense.   That is,
we were concerned with the absolute value  of ozone predicted  by  the model
from given initial precursors, emissions,  and meteorological  factors.
When the trajectory model is used via the  isopleth diagram, the  model  is
used in a relative fashion.  The  starting  point  on the diagram is the
intersection of the ozone isopleth line corresponding  to  the  observed
ozone maximum with the radial line corresponding to  the  observed  HC/NOX
ratio for 0600 to 0900 hours.  The ordinate and  abscissa  values  are
intended to relate to percentage  changes in the  HC and NOX emissions
inventories.

     In this section we  discuss the uncertainties associated  with the
construction and use of the EKMA  isopleth  diagrams.  Whereas  we  previously
compared (in an absolute sense) individual trajectory  model simulations
with those of various other models and with observations,  in  this section
we compare (in a relative sense)  the changes in  ozone  predicted  by  various
models on the basis of percentage changes  in emissions.
32R/2
                                    66

-------
5.1   CONSIDERATIONS RELATED TO THE USE OF ISOPLETH DIAGRAMS
5.1.1  Fixed Monitoring Sites

     The time and location of maximum observed ozone concentrations can
change as a result of a change in emissions only.  Grid models typically
show such effects.  The probability of the coincidence of monitoring sites
and the actual location of maximum ozone concentrations can either
increase or decrease as a result of changes in emissions.  The proper
deployment of several monitoring sites and the application of numerous
trajectory paths can, to some extent, mitigate this problem.  The use of a
grid model is also helpful.

     Another related problem occurs when winds vary in direction during
the course of a day because the air arriving at a monitoring site can
originate at several different locations.  If the proposed control
strategy alters the time of occurrence of the ozone maximum, the base
trajectory utilized to construct the isopleth diagram then becomes
inappropriate for the monitoring site.  When the wind directions are
constant throughout the day, a change in ozone peak timing merely leng-
thens or shortens the path to the monitoring site.
5.1.2   Uneven Changes in Emissions

     Mobile-source emissions are, for the most part, regulated at the
federal level, whereas stationary sources are more often subject to local
control.  Therefore, because the federal controls may be different from
the local requirements and because some areas are dominated by mobile
sources and others stationary sources, the uniform control of either HC or
NOX is rarely even in time and space.  Individual trajectory-model
simulations might provide acceptable levels of accuracy for the base-case
year and the future year because these models can typically alter the
timewise distribution of emissions input data.  However, the isopleth
approach requires some uniform emission pattern for all points on the
diagram.

     Depending on the level of sophistication, some trajectory models can
also account for changes in hydrocarbon reactivity along the trajectory
path.  However, in constructing isopleth diagrams, considering changes in
both emissions patterns and reactivity is beyond the scope of the present
algorithms.
32R/2
                                    67

-------
5.1.3   Transported Pollutants

     The regular city-specific EKMA  isopleth  algorithm  uses the  same
amounts of transported pollutants for all points of the diagram.  In
practice, the regulation of mobile emissions  at the federal level  would
modify the transportation of pollutants.  It  was shown  by Whitten  and  Hogo
(1981) that on the basis of the EKMA, significant differences  in  control
requirements can result from different assumptions about the transported
pollutants in the surface layer and  the  layer aloft.  The latest  guide-
lines for using the EKMA suggest employing two  isopleth diagrams  to deal
with this problem.
5.2   SAN FRANCISCO APPLICATIONS

     The AQMP (1979), using the LIRAQ model, offers a unique means  of
evaluating the EKMA.  The control-strategy LIRAQ predictions for various
scenarios can be directly contrasted with comparable EKMA predictions.  We
have also included brief discussions of two other topics involving  the  use
of EKMA in the San Francisco region:

     >  Isopleths prepared from some of the widely differing
        initial conditions discussed in section 4, which demon-
        strated a lack of sensitivity to initial conditions (see
        table 9).

     >  A comparison of isopleths using the CBM and the standard
        EKMA chemical mechanisms.

     >  A comparison of isopleths generated assuming different
        trajectories.
5.2.1   Basic Comparisons between LIRAQ and EKMA

     Several control scenarios were described in the AQMP (1979).  For
cases in which comparisons could be made with the EKMA, we constructed
isopleth diagrams and applied various estimates of predicted ozone
concentrations using the EKMA technique.  In this section, attention  is
focused on those EKMA applications:

     >  The OZIPM trajectory analysis described in chapter 3
        (i.e., a Level II analysis).

     >  A basic city-specific EKMA analysis using current guide-
        lines for a Level III analysis (EPA, 1980).
32R/2
                                    68

-------
        A basic city-specific EKMA analysis  in which the  Carbon-
        Bond Mechanism was substituted for the standard
        propylene/butane chemistry contained  in OZIPP.
Table 10 shows the comparative results for the different  scenarios  applied
in the LIRAQ analysis.  A discussion of these results follows.

     For the LIRAQ evaluations, 26 June 1973 was selected  as the  prototype
meteorological day.  The trajectory corresponding to the  prototype  day was
shown earlier in figure 1.  The OZIPM computer code was used to construct
the isopleth shown in figure 15 since the starting times  and hourly mixing
height inputs were not the standard ones assumed for the  city-specific
EKMA.  The results indicate that the Level II predictions  are generally
less sensitive to changes in hydrocarbons and/or NOX than  are the LIRAQ
predictions.  Because of the fundamental differences in the two models,
explanations for these differences cannot be postulated.   However,  the
sensitivity of Level II predictions is addressed in the next section.

     The isopleth approach is, in effect, confined to one  trajectory path,
whereas the grid models cover essentially all possible trajectories in
space and time.  Thus, the worst case found over the entire gridded area
would normally be found in the grid model rather than (for this case) in
three trajectory paths.  This reasoning leads to some surprising  compari-
sons of LIRAQ (grid) and EKMA (trajectory) results.  For  20, 40,  and 60
percent HC reduction scenarios, plus the scenarios combined using reduc-
tions of 40 percent HC and 20 percent NOX, the ozone predictions  from
LIRAQ are lower than those from the EKMA.  The remaining  three scenarios
(80 percent HC reduction, and 40 percent NOX reduction) reflect a situa-
tion in which the worst case over the gridded area is higher than,  or
equal to, the worst case along the specific trajectory.

     Two additional isopleth diagrams for 26 July 1973 were constructed to
reflect the current guidelines for a city-specific EKMA analysis  (i.e., a
Level III analysis).  In this approach, a trajectory is followed  from the
urban core to the site of the observed peak ozone level (EPA, 1980).  The
isopleth diagram shown in figure 16(a) was constructed using the  city-
specific EKMA program (i.e., OZIPP), which reflects the standard
propylene/butane chemistry contained in city-specific EKMA.  Figure 16(b)
was constructed using the Carbon-Bond Mechanism rather than the standard
chemistry.  The inputs for both diagrams, which are summarized in table
11, correspond to conditions for 26 July 1973.

     The HC/NOX ratio for the Level III applications was derived  from
0600-to-0900-hour-averaged HC and NOX observations taken  at the downtown
San Francisco monitoring station (MacCracken and Sauter,  1975).   The
monitoring station reported total hydrocarbons only, but methane


32R/2
                                   69

-------
       TABLE 10.   CONTROL-STRATEGY COMPARISONS FOR SAN FRANCISCO BETWEEN LIRAQ AND EKMA APPLICATIONS
Reduction
(percent)
HC
Models Studied N0x


0
0


20
0


40
0


60
0


80
0


40
20


80
40


0
40
LIRAQ predictions
0.189   0.140   0.082    0.069    0.055   0.119    0.064    0.2]
        (-26%)  (-5758)   (-63%)   (-7158)  (-37%)   (-66%}   (+23
OZIPM (Level II)
(based on 0.189 max.)
0.189   0.161   0.145    0.102    0.036   0.141    0.062    0.1£
        (-15%)  (-23%)   (-46%)   (-81%)  (-25%)   (-67%)   (-15
Level III EKMA (based on
0.189 max.)
0.189   0.130   0.080   <0.080   <0.080   0.10     0.08     0.2-5
        (-31%)  (-57%)   «-57%)  «-57%) (-47%)   (-57%)   (+31
Level III EKMA using CBM
(based on 0.189 max.)
0.189   0.112   <0.08    <0.08    <0.08   0.08     <0.08    0.31
        (-4155)  «-57%)  «-57%)  «-57%) (-57%)   «-57%)  (+66
  The predicted ozone level is shown for each control scenario in addition to the percentage change from the
  base-case level (i.e., no HC or NOX reductions).
        32R/m
                                                    70

-------
                                                                                                                          II

                                                                                                                          o
                                                                                                                         car
                                                                                                                         a:.
                                                                                                                         o


                                                                                                                         LLJ


                                                                                                                         ce:
                                                                                                                         (—





                                                                                                                         cr>
                                                                                                                         10
                                                                                                                         CVJ
                                                                                                                         D:
                                                                                                                         o
                                                                                                                         O
                                                                                                                         oo
                                                                                                                         in
32R  3
                                                      (iudd)
                                                              71

-------
99'0
                                                                        co
                                                                        r-
                                                                        >-
                                                                        _J
                                                                        ZD
                                                                        O

                                                                        ^O
                                                                        C\J
                                                                        I

                                                                        o
                                                                    5^
                                                                    LU

                                                                    O
                                                                    o   u~>
                                                                    d>
                                                                    CL  OL
                                                                    00   O
                                                                     I   U-
                                                                    &-   C_)
                                                                    (O   LJ-I
                                                                    I—   o
                                                                        o:
                                                                        ^>
                                                                        o
                                                 rro     00-0°
                        Hdd'XCM
                                 72

-------
LL'O
99 •"£)
SS'O
WO     ££'0

    Wdd'X0N
ZZ'Q
                                                                       CO

                                                                       c
                                                                       o
                                                                       QJ
                                                                       c
                                                                       o
                                                                       CD
                                                                       I
                                                                       c
                                                                       o
                                                                       ro
                                                                       o
                                                                       o
                                                                       d)
                                                                       ex
                                                                       >*,
                                                                       *->
                                                                       •i—
                                                                       o
tro
00-0°
                                                                  •D
                                                                  
                                                                       0)
                                                                           o
                                                                           o
                                                                           CJ
   32R 3
                              73

-------
concentrations were usually between  1.3  and  1.9  ppmC.   For  the  average
0600-to-0900-NMHC concentration, we  assumed  that  the methane  concentration
was 1.6 ppmC.  The calculated design HC/NOX  ratio for  San Francisco  is
3.3.  This low value  is similar to the low values estimated by  de Mandel
et al. (1979), who reported in their study that  typical  HC/NOX  ratios were
between 1.2 and 1.7 for the five worst ozone episode days.

     The emission rates presented in table 11 were taken from ARB
(1976).  However, information concerning hydrocarbon emissions  reactivity
is needed to utilize  the Carbon-Bond Mechanism.   Even  though  this infor-
mation was not readily available, we decided to  use the  same  reactivity as
that of the LIRAQ model.  This resulted  in an OLE fraction  of 18.1
percent, PAR fraction of 80.4 percent, and CARB  fraction of 1.6 percent.
Since the LIRAQ model does not contain any aromatics,  we set  the ARO
fraction to zero.  Without aromatics the hydrocarbon reactivity value used
in this study may not reflect the true urban emissions  mixture, nor  does
it reflect a typical  reactivity for  the  use  of the Carbon-Bond  Mechanism.

     The control strategy comparisons shown  in table 10  reveal  that  the
city-specific EKMA predictions using the standard EKMA  chemistry most
nearly parallel those obtained using the LIRAQ model.   When the Carbon-
Bond Mechanism is used, the sensitivity  of ozone  predictions  to changes in
emissions is greater.
5.2.2   Further Investigations

     In this section, we describe the results of  some  additional  analyses
performed to assess the sensitivity of control strategy predictions using
the EKMA.  First, the sensitivity to the HC/NOX ratio  under particular
conditions is examined.  Second, the sensitivity  of control estimates to
particular trajectory path conditions is explored.  Finally,  an  alterna-
tive method for generating isopleth diagrams and  evaluating control
strategies is presented.

     In section 4.1.1, we indicated that the predicted peak ozone  levels
for trajectory 1, 26 July 1973, were insensitive  to the assumed  initial
conditions.  Likewise, the control predictions for this special  case
should be insensitive to the HC/NOX ratio.  As described earlier,  the
emissions input vectors were constructed from the LIRAQ emissions  inven-
tory.  For the sensitivity study concerning the insignificance of  the
initial conditions (see table 9), we altered the  emissions vectors to
maintain constant contributions from the emissions regardless of  the
initial values or ratios of HC and NOX.  We also  demonstrated that entire
isopleth diagrams used with widely varying design HC/NOX ratios  can be
32R/2
                                   74

-------
  TABLE 11.   INITIAL CONDITIONS USED  IN THE LEVEL  III  EKMA  CALCULATIONS
              FOR 26 JULY 1973  IN THE  SAN FRANCISCO REGION

                          (a)   Initial Conditions
                    Species
                    NOX
                    NMOC
                    Oo
                Transported Pollutants
                Surface       Aloft
                0.0 ppm
                0.0 ppmC
                0.0 ppm
            0.0 ppm
            0.0 ppmC
            0.04 ppm
           N02/NOX = 0.25.
           Hydrocarbon reactivity:  standard OZIPP conditions,
           Morning mixing height:  150 m at 0800 PDT.
           Afternoon mixing height:  977 m at 1600 PDT.
           0600 to 0900 hours HC/NOX = 3.3.
           0600 to 0900 hours NMOC = 0.4 ppmC.
           0600 to 0900 hours NOX = 0.12 ppm.
           Design 03 = 0.19 ppm at 1600 PDT near Livermore.
     County
  San Francisco
  Alameda
                            (b) County  Emissions
      ROC
   (tons/day)

      97.7
     187
   NOX
(tons/day)

   83.0
  131.0
 Area
(km2)

 116.55
1898.5
   Density
 (kg/hr km2)
 ROC      NOX

31.69    26.92
 3.72     2.61
                           (c)  Emissions  Fraction
     Time
     (PDT)
   0800-0900
   0900-1000
   1000-1100
   1100-1200
   1200-1300
   1300-1400
   1400-1500
   1500-1600
      Trajectory
San Francisco/Alameda
Alameda
Alameda
Alameda
Alameda
Alameda
Alameda
Alameda
        ROC Fractions

            0.496
            0.104
            0.104
            0.104
            0.104
            0.104
            0.104
            0.104
          NOY Fractions
              0.434
              0.0767
              0.0767
              0.0767
              0.0767
              0.0767
              0.0767
              0.0767
32R/14
                                   75

-------
constructed and can produce consistent results  if the HC/NOX ratio
employed is the one upon which the emissions vector was constructed.  Four
key points result from the investigation of this special trajectory:

     >  The EKMA can still be used as a control strategy tool,
        provided that the special emissions input vectors and
        design HC/NOX ratios are consistent.

     >  The observed HC/NOX ratio is not needed.

     >  The underlying effective HC/NOX ratio is found in the
        emissions inventory.

     >  The isopleth-derived control implications are directly
        related to the emissions themselves rather than to the
        results of typical applications (where the initial
        conditions of precursors dominate the model).

     Two additional isopleth diagrams were constructed to illustrate the
technique developed for trajectories (such as those we found in San
Francisco) that are not sensitive to initial conditions.  The base-case
isopleth diagram chosen was the one shown earlier in figure 15 in which
the initial condition HC/NOX ratio used in the base trajectory (i.e., the
26 July 1973 trajectory originally shown in figure 1) is 10/1.  As
previously described, the design ozone value must be located on this
HC/NOX ratio line when this technique is used.  The diagrams are shown in
figures 17 and 18.  The initial-condition base HC/NOX ratio lines to be
used for these diagrams are 1/1 and 100/1, respectively.  These diagrams
were constructed using the technique described earlier for showing
insensitivity to initial conditions—that is, the emissions vectors were
recomputed so that the contributions of emissions to the model concentra-
tions in the base-case trajectory were all the same.  The trajectory model
results were presented earlier in table 9 and were discussed in section
4.  The control implications of these additional diagrams, shown in table
12, demonstrate that consistent utilization of emissions inventory
information produces consistent isopleth-derived results, provided that
the proper HC/NOX ratio (i.e., the ratio used to construct the emissions
vector) is utilized with the design 03 when initial conditions are not
important.

     Recall from chapter 3 that the OZIPM model (i.e., the Level II
analysis) was applied to several other trajectories in addition to the
basic 26 July 1973 trajectory that corresponds to the prototype conditions
modeled using the LIRAQ.  Two additional isopleths were developed for the
trajectories shown in figures 3 and 5:  trajectory 1 for 20 August 1973,
and trajectory 2 for 24 July 1974, respectively.  The two diagrams are
shown in figures 19 and 20.  The LIRAQ control scenarios were evaluated


32R/2                              -c
                                   /D

-------
                                                                                                      II

                                                                                                     o
                                                                                                     eC
                                                                                                     Qi
                                                                                                     O

                                                                                                     O
                                                                                                     Lul
                                                                                                     ra
                                                                                                     eC
                                                                                                     c:
                                                                                                     ro
                                                                                                     10
                                                                                                     CO

                                                                                                     o;
                                                                                                     o
                                                                                                     UJ
                                                                                                     _i
                                                                                                     ex.
                                                                                                     O
                                                                                                     oo
                                   (Uldd)
32R 3
                                                  77

-------
                                                                                                       o
                                                                                                       o
                                                                                                       II

                                                                                                      o
                                                                                                      o

                                                                                                      o
                                                                                                      «£.
                                                                                                      CC
                                                                                                       CO
                                                                                                       >-
                                                                                                       _J
                                                                                                       rD
                                                                                                       ••3
                                                                                                      a:
                                                                                                      o
                                                                                                      D-
                                                                                                      o
                                                                                                      oo
                                                                                                       oo
                                                                                                      Ul
                                                                                                      D;

                                                                                                      o
                                     (uidd)
32R 3
                                                   78

-------
       TABLE 12.  SENSITIVITY OF CONTROL-STRATEGY EVALUATION TO HC/NOX RATIO FOR TRAJECTORY 1—26 JULY 1973
        Cases Studied
Reduction
(percent)
HC
NO
X


0
0



20
0



40
0



60
0



80
0



40
20



80
40



0
40

OZIPM (Level II)
(based on 0.189 max.)
trajectory for 26 July 1973;
HC/NOx = 100

City-specific using OZIPM
(based on 0.189 max.) 1975
trajectory for 26 July 1973;
NC/NOx = 1.0
0.189   0.165   0.146   0.105    0.040    0.145   0.063
                          0.16C
0.189   0.169   0.142   0.098
0.036
0.143   0.060
0.16C
        32R/m
                                                    79

-------
                                                                                                  O
                                                                                                  UJ
                                                                                                  oo
                                                                                                  O
                                                                                                  CM
                                                                                                  O
                                                                                                  u.

                                                                                                  :r
                                                                                                  O.
                                                                                                  O
                                                                                                  oo
                                     (uidd)
32R  3
                                                  80

-------
                                                                                                            CM
                                                                                                            O
                                                                                                            UJ
                                                                                                            *o
                                                                                                            <£.
                                                                                                            cx:
                                                                                                            >-
                                                                                                            _]
                                                                                                            ra
                                                                                                            o

                                                                                                            *a-
                                                                                                            CM

                                                                                                            C£
                                                                                                            O
                                                                                                            LJ_

                                                                                                            a:
                                                                                                            I—
                                                                                                            UJ
                                                                                                            _i
                                                                                                            D-
                                                                                                            O
                                                                                                            00
                                                                                                            O
                                                                                                            CM
32R 3
(uidd)
                                                     81

-------
using the EKMA technique with these diagrams.  For these  calculations,  the
HC/NOX ratio corresponded to that of the assumed  initial  conditions,  but
an ozone maximum of 0.189 ppm was selected to compare more easily  the EKMA
predictions based on the different trajectories.  Table 13 contains the
control calculations for these two new trajectories, as well  as  those for
the basic 26 July 1973 trajectory (i.e., trajectory 1).   The  results
demonstrate that control estimates can be sensitive to trajectory  path, as
might be expected.  Interestingly, some predictions using these  new
trajectories agree more closely with the LIRAQ results than do the
trajectories previously discussed.

     In the recent study by Whitten and Hogo (1981), a new type  of EKMA
isopleth was introduced that uses the emissions inventories for  NOX and HC
as the ordinate and abscissa of the diagram.  The (1,1) point of such  a
diagram corresponds to the trajectory simulation  using the present
emissions inventory.  Figure 21 shows the isopleth of 26  July 1973 in
which the (1,1) point is the trajectory shown in  figure 1.  The  HC/NOx
ratio to be used with the new diagram is the diagonal line through the
(1,1) point.  Using this HC/NOX line and the 0.189 ppm design, 03~value
ozone predictions were computed using the regular procedures.  The results
are shown in table 14.

     Note that the design ozone and the simulated ozone at the (1,1)  point
do not need to be the same.  The new method is used exactly as the
original EKMA except that the HC/NOX ratio line through the (1,1)  point is
used in place of the observed 0600-to-0900-hour concentration ratio.
Thus, the new method in effect substitutes the emissions  inventory
information for the 0600-to-0900-hour observed data.  The similarity  of
these results to those of the regular city-specific isopleth  shown in
figure 15 is to be expected in this case because  the initial  conditions
are not important.  The intended advantages of using the  new  type  of
isopleth are the elimination of the initial HC/NOX ratio  data require-
ment.  The initial conditions can be handled in one of two ways  as can  the
concentrations aloft.  In one method the concentrations are rolled back
(or ahead) away from the (1,1) point of the diagram when  the  isopleth
diagram is constructed.  The initial conditions are thus  treated as
concentrations transported in the surface layer.  In the  other method,  the
initial conditions are still handled as surface-transported pollutants,
but they are held constant over the entire isopleth diagram.  Then,
another diagram is constructed in which the expected future concentrations
are held constant.  This is actually the current method for handling
present and future transported pollutants contained in the OZIPP computer
code used in the Level III applications of the EKMA.  Thus, the  initial
conditions may still be important, and their importance can be treated
using this new method.
32R/2
                                   82

-------
                 TABLE 13.  SENSITIVITY OF CONTROL-STRATEGY EVALUATION TO TRAJECTORY PATH



Cases Studied

Reduction
(percent)
HC
NO
X


0
0



20
0



40
0



60
0



60
0



40
20



80
40



0
40

OZIPM (Level II)
Trajectory 1 for
26 July 1973

City-specific using OZIPM
(based on 0.189 max.) 1975
trajectory for 24 July 1974

City-specific using OZIPM
(based on 0.189 max.) 1975
trajectory for 20 August 1973

Average for 3 OZIPM runs
0.189   0.161   0.145   0.102    0.036    0.141   0.062    0.161
0.189   0.162   0.127   0.070    <0.02    0.135   0.048    0.17;
0.189   0.168   0.128   0.082    0.043    0.132   0.058    0.18!
0.189   0.164   0.133   0.085    0.03     0.136   0.056    0.172
        32R/14
                                                   83

-------
                                                                                              LU
                                                                                              rD
                                                                                              «C
                                                                                              a:
                                                                                              CO

                                                                                              01
                                                                                              «—i

                                                                                              >-
                                                                                              _i
                                                                                              ^5
                                                                                              •-3
                                                                                              o;
                                                                                              o
                                                                                               a.
                                                                                               o
                                                                                               >-
                                                                                               I—


                                                                                                I
                                                                                               CM
                                (mdd)
32R  3
84

-------
                     TABLE 14.   CONTROL-STRATEGY COMPARISONS  USING  A  NEW-STYLE  ISOPLETH



Models Studied

Reduction
(percent)
HC
N0v
X


0
0



20
0



40
0



60
0



80
0



40
20



80
40



0
40

LIRAQ predictions

OZIPM (Level II)
Trajectory 1 for
26 July 1973;
new-style isopleth

OZIPM/CBM (Level II)
Trajectory 1 for
26 July 1973;
new-style isopleth
0.189   0.140   0.082   0.069    0.055    0.119    0.064     0.23!
0.189   0.165   0.125   0.075    >0.02    0.132   0.063     0.16!
0.189   0.161   0.12    0.078    0.038    0.134   0.053    0.172
        32R/1H
                                                   85

-------
     We have also used this new-style diagram with  the  new  Carbon-Bond
Mechanism, which was employed by Whitten and Hogo (1981).   The  diagram
generated using the trajectory of 26 July 1973 with the CBM chemistry  is
presented in figure 22, and the control-scenario results are  included  in
table 14.  Although the CBM chemistry generates more  simulated  ozone than
the regular EKMA chemistry for the  (1,1) point, the control-scenario
predictions (which are based on EKMA-style relative application to  a
single-design 03) turn out to be quite similar except for the case  of 80
percent HC/40 percent NOX combined  control.
5.3   SACRAMENTO APPLICATION

     Part of the task of the original SAI Airshed Model  study  of  the
Sacramento region was to examine the effects of controlling mobile-source
emissions (Reynolds et al., 1979).  In order to perform  the desired con-
trol simulations in the original study, the Sacramento region  was rotated
to form a special air quality control region (AQCR)  in which the  main
highway runs in an east-west direction.  Figure 23  shows this  special
modeling region.  Meteorology for 24 August 1976 was  used  for  the study.
The wind fields for that day were also rotated in such a way that the
predominant wind flow was  from west to east, parallel to the main high-
way.  The modeling region  was expanded to contain 729 grid cells,  each
3 km in length.  The total region size is 81 km by  81 km.  The original
emissions inventory was increased to reflect the dimensions of the new
region and a rotation scheme having the same emissions density as the
original region.

     Seven control strategies were defined, and airshed  simulations were
performed for these strategies on the rotated region.  Table 15 shows the
control strategies that were evaluated and the Airshed Model's predicted
peak ozone concentration for each.  Note that several of the control
strategies cannot be easily simulated with the EKMA.  Therefore,  only the
first two control strategies listed in table 15 (30 percent reduction in
mobile-source HC and NOX emissions, and 30 percent  reduction in mobile-
source HC only) were evaluated with the EKMA.

     Because of the special rotation of the modeling  region, new  base-case
evalulations had to be made using the SAI trajectory model, OZIPM/CBM, and
city-specfic EKMA.  As was done for the Sacramento  simulations described
in chapter 3, the trajectory path leading to the maximum ozone concentra-
tion was defined with the  SAI trajectory model (shown in figure 24).  From
the trajectory model outputs, inputs for the OZIPM/CBM simulations were
generated, and the inputs  for the city-specific EKMA  (OZIPP) model were
then generated using the results of the OZIPM/CBM simulations.  Tables 16
and 17 summarize the inputs for each model.  Table  18 compares the
predicted maximum ozone for the four models.


32R/2
                                   86

-------
                                                                                                           oo
                                                                                                           t—I
                                                                                                           o
                                                                                                           CO
                                                                                                           o
                                                                                                           CQ
                                                                                                           o;
                                                                                                           et
                                                                                                           CD
                                                                                                           Z
                                                                                                           HH

                                                                                                           oo
                                                                                                           CJ
                                                                                                           UJ
                                                                                                           •-D
                                                                                                           
-------
                                   REGIONAL
                                   AIRPORT
                                 CENTRAL BUSINESS  DISTRICT
            FIGURE 23.  MAP OF THE  HYPOTHETICAL URBAN AREA USED
                       TO STUDY  TRANSPORTATION CONTROL STRATEGIES
32R 3

-------
 TABLE 15.  SAI AIRSHED  MODEL  PREDICTED  PEAK  OZONE  CONCENTRATIONS COMPUTED
            FOR DIFFERENT  CONTROL  STRATEGIES  IN  THE HYPOTHETICAL
            REGION  (base-case  predicted  peak  ozone  = 17  pphm)
                                                        Peak  Ozone
                                                        Predicted
  	Control Strategy Simulation	     (pphm)

  (la)  Reduction of all mobile source emissions by        15
        30 percent

  (Ib)  Reduction of mobile emissions of  HC  by 30          13
        percent

  (2a)  30 percent reduction in mobile, emissions           17
        along a corridor parallel to prevailing wind

  (2b)  30 percent reduction in mobile emissions           17
        along a corridor perpendicular to prevailing
        wind

  (2c)  30 percent reduction in mobile emissions in        16
        the central business district

  (3a)  Use of 3-hour running-average emissions            17

  (3b)  Delaying of all emissions by 3 hours               10
32R/14

                                   89

-------
                                    REGIONAL
                                    AIRPORT
                                 CENTRAL  BUSINESS DISTRICT
                                 1QOO 1100

                             0900\     \ 1200
                                                               1700  PDT
             FIGURE  24.  TRAJECTORY USED FOR THE CONTROL-STRATEGY
                        RUNS (MODIFIED SACRAMENTO REGION)
32R 3
                                    90

-------
TABLE 16.   EMISSION RATES AND MIXING HEIGHTS USED  IN
            EKMA APPLICATIONS TO HYPOTHETICAL REGION
            CONTROL STRATEGIES*
Time
(PDT)
0600
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
NO
(ppm/hr)
0.0133
0.0641
0.0629
0.06958
0.05804
0.0792
0.08836
0.0798
0.098
0.0677
0.0099
__
HC
(ppmC/hr)
0.039
0.3719
0.4171
0.493
0.2904
0.2239
0.1759
0.258
0.2445
0.1116
0.01728
__
Mixing Heights
(meters)
50
50
100
150
225
300
450
600
800
800
800
800
  Taken from the SAI trajectory model calculations.
                         91

-------
       TABLE 17.  TRAJECTORY  MODEL  OUTPUTS  USED  AS  INPUTS  FOR  THE
                  EKMA SIMULATIONS

      (a)   Initial Conditions  and Hydrocarbon Reactivities  Used  in  the
            OZIPM/CBM Control  Base-Case Run  (starting time  =  0600 PDT)*
                               Transported Pollutants
                Species        Surface           Aloft

                NOX          0.003 ppm        0.003  ppm
                HC           0.057 ppmC       0.055  ppmC
                03           0.019 ppm        0.026  ppm


                          Hydrocarbon  Reactivities

              Species       Surface       Aloft    Emissions

              OLE
              PAR
              ARO
              CARB
      (b)  Initial Conditions Used in City-Specific EKMA Calculations
           of Hypothetical Control Runs (starting time = 0800 PDT)

                                      Transported  Pollutants
0.014
0.616
0.282
0.088
0.009
0.607
0.257
0.105
0.041
0.698
0.239
0.023
                   Species           Surface            Aloft

                   NOX             0.041 ppm          0.003  ppm
                   HC              0.248 ppmC         0.055  ppmC
                   03              0.009 ppm          0.026  ppm
                   N02/NOX = 0.556.
                   Propylene reactivity = 0.25.
                   Dilution:  initial mixing height = 100 m;
                   final mixing height = 800 m.
         Taken from the SAI trajectory model calculation,
32R/14

                                   92

-------
TABLE 18.  COMPARISON OF MAXIMUM PREDICTED OZONE FOR THE SAI AIRSHED,
           SAI TRAJECTORY, OZIPM/CBM, AND CITY-SPECIFIC EKMA MODELS:
           BASE-CASE CONDITIONS USED FOR THE CONTROL-STRATEGIES
           STUDY OF THE HYPOTHETICAL REGION
                                          Maximum
                 	Model	    	(ppm)
                 SAI Airshed                 0.17
                 SAI trajectory              0.12
                 OZIPM/CBM                   0.12
                 City-specific EKMA          0.13
                                 93

-------
     The comparison of predicted maximum ozone  shows  that  the  trajectory
model and the two EKMA models give similar results, whereas  the Airshed
Model prediction is approximately 40 percent higher than that  of  the
trajectory model.  The special "rotated" emissions grid constructed for
the study turned out not to be compatible with  the SAI trajectory model
computer code.  Several attempts to construct a compatible emissions  grid
failed to produce one that reproduced  in the trajectory model  the con-
centrations that were seen in the original study.  Since the precursor
concentrations were low in the trajectory model simulations, low  ozone
values were expected.  Unfortunately,  time and  cost constraints precluded
the resolution of this emissions inventory problem.

     The two control strategies were evaluated  directly with SAI  trajec-
tory model simulations reflecting the  assumed emission reductions.  For
the EKMA applications, isopleths were  generated to evaluate  the strate-
gies.  Figure 25 shows the isopleth generated for the city-specific EKMA
application.  The regional, initial HC/NOX ratio of 7.2 is taken  from
Reynolds, et al. (1979).  The initial  HC/NOX ratio, determined from the
initial conditions for this specific trajectory is approximately  6/1.
However, we used the HC/NOX ratio of 7.2 because this value  was derived
for the EKMA as it is more normally applied.  Since a 30 percent  reduction
was made in mobile emissions only, we  needed to determine  the  reduction in
total emissions (sum of mobile and stationary sources).  From  the Airshed
Model emissions inventory containing the reduced mobile emissions and the
trajectory path, we found the emissions for each hour along  the trajectory
path (see table 19).  From the new emissions rates, we determined the
level of control of HC and NOX emissions from all sources  to be reductions
of 19.6 percent HC and 16.3 percent NOX.  Since the SAI Airshed Model and
the SAI trajectory model did not predict similar ozone maximums,  we
decided to use the ozone maximum of 0.12 ppm predicted by  the  trajectory
model as the design ozone value.

     The EKMA predictions resulting from application  of the  two control
strategies are presented in table 20.  Controlling of HC mobile emissions
only shows a 20 percent difference in  predicted maximum ozone  between the
trajectory model and the city-specific EKMA model.  This discrepancy
appears to be a result of the different chemistry used in  the  two models
because the CBM-EKMA simulation, with  the same  inputs as those of the
city-specific EKMA run, predicted an ozone maximum much closer to that of
the trajectory model.

     Further investigations were made  using Level III EKMA guidelines.
From the initial conditions presented  in table  21, and from  emissions
rates of ARB (1979), we generated two  diagrams  (one using  the  standard
EKMA chemistry, the other using Carbon-Bond chemistry).  For the  CBM
isopleth we used the same hydrocarbon  reactivity as is presented  in table
17.  The isopleth diagram generated using the standard EKMA  chemistry is


32R/2
                                   94

-------
                                                                                                                     X
                                                                                                   in
                                                                                                   c
                                                                                                   o
                                                                                                  •r—
                                                                                                   (S)
                                                                                                   vt


                                                                                                   OJ

                                                                                                    -o    
 c u
•I- i-
    (U
 C D.
 O
•r- O
4-> CO
 o —
 3
•o c
 a; o
C
O
                                                                                                                    u
                                                                                                                    3
                                                                                                                      O IO -U
                                                                                                   4->^ -- > O  +J     O
                                                                                                   U >>•!-  (J O -r-
                                                                                                   QJ i— X3  a> ni -a
                                                                                                   •r-j c  a)  -"-3     a>
                                                                                                   (O O  I-  IO -E  S-
                                                                                                   $-     Q. S- •!->  Q.
                                                                                                   •!-»<_>     -MO
                                                                                                      ZEcX.     -Q ^
                                                                                                   I— <    ^"  I-H    y8
                                                                                                   ca: q- S  <: 4- S
                                                                                                   to o LU  c/> o tu
                                                                                                         CM  CO
             oo
             •z.
             o
             I—I

             g

             o

             o
                                                                                                                                C3
                                                                                                                                UJ
                                                                                                                                00
                                                                                                                                 I
                                                                                                                                o
                                                                                                                                o
 CU ^     CO
 U CU     U
 S- S-     t-
 QJ O-    Ol
 O-        O-



CO T3  XCO
«— O O	
             0.
             o
                                                                                                                                UJ
                                                                                                                                Q.
                                                                                                                                oo
                        tn
                        CVJ
                        o:
                        Z3
                        CD
                                     •(iudd)   ON
32R  3
                                                               95

-------
TABLE 19.   CONTROL-STRATEGY STUDY TOTAL EMISSIONS
            RESULTING FROM A 30 PERCENT REDUCTION
            IN MOBILE HC AND NOX EMISSIONS
                    NOX           HC
                 (ppm/hr)     (ppmC/hr)
        0600       1.004       0.0384
        0700       0.0463      0.2882
        0800       0.0455      0.3076
        0900       0.052       0.3808
        1000       0.0456      0.2327
        1100       0.0694      0.1826
        1200       0.0803      0.184
        1300       0.0688      0.2097
        1400       0.0875      0.1952
        1500       0.0622      0.0895
        1600       0.0088      0.0163
        1700
                        96

-------
    TABLE 20.  COMPARISON OF MAXIMUM OZONE PREDICTIONS BETWEEN THE
               TRAJECTORY MODEL, OZIPM/CBM, AND CITY-SPECIFIC EKMA
               WITH DIFFERENT CONTROL SCENARIOS (design 03 = 0.12 ppm)
           Model
Trajectory model

OZIPM/CBM

City-specific EKMA

Level III EKMA

Level III EKMA using CBM I

Level III EKMA using CBM II
                                 Predicted 03—
                              30 Percent Reduction
                              in Mobile Emissions
                                 of HC and NO
0.103 (-14%)

0.097 (-19%)

0.108 (-10%)

0.104 (-13%)

0.10 (-17%)

0.101 (-16%)
                     Predicted 03~-
                  30 Percent Reduction
                  in Mobile Emissions
                       of HC Only
0.09 (-25%)

0.086 (-28%)

0.114 (-5%)

0.105 (-13%)

0.084 (-30%)

0.082 (-32%)
                                  97

-------
 TABLE 21.  INITIAL CONDITIONS USED  IN THE LEVEL  III  EKMA  CALCULATIONS  FOR
            HYPOTHETICAL REGION FOR  24 AUGUST  1976  METEOROLOGY  (emissions
            based on Sacramento County for 1976)
                          (a)  Initial Conditions
                    Species
                    NOX
                    NMOC
                    Oo
             Transported Pollutants
              Surface       Aloft
             0.0 ppm
             0.0 ppmC
             0.0 ppm
            0.0 ppm
            0.0 ppmC
            0.2 ppm
           N02/NOX = 0.25.
           Hydrocarbon reactivity:
           Morning mixing height:
           Afternoon mixing height:
                 standard OZIPP conditions,
                150 m at 0800 PDT.
                  800 m at 1400 PDT.
           0600 to 0900 hour HC/NOX =7.2.
           0600 to 0900 hour NMOC = 0.248 ppmC.
           0600 to 0900 hour NOX = 0.035 ppm.
           Design 03 = 0.12 ppm at 1700 PDT.
     County
  Sacramento
                            (b) County  Emissions
   ROC
(tons/day)

   119.7
   NOX
(tons/day)
   70.9
 Area
(km2)

2525.24
  Density
(kg/hr km2)
         NO,
        1.29
                           (c) Emissions Fraction
     Time
     (PDT)
   0800-0900
   0900-1000
   1000-1100
   1100-1200
   1200-1300
   1300-1400
   1400-1500
   1500-1600
Trajectory

Sacramento
Sacramento
Sacramento
Sacramento
Sacramento
Sacramento
Sacramento
Sacramento
   ROC Fractions

       0.081
       0.081
       0.081
       0.081
       0.081
       0.081
       0.081
       0.081
         NOY Fractions

             0.130
             0.130
             0.130
             0.130
             0.130
             0.130
             0.130
             0.130
32R/H+
                                   98

-------
shown in figure 26(a); the  isopleth  diagram  with  Carbon-Bond  chemistry is
shown in figure 26(b).  The ozone predictions  using  the  two diagrams  are
shown in table 20.  For the 30  percent  control  of mobile emissions of HC,
the Level III CBM-EKMA using both the old  and  new versions of the Carbon-
Bond Mechanism [figures 26(b) and 26(c]  predicts  a lower ozone value  than
the standard Level III EKMA, as was  true for the  case  that compared the
CBM-EKMA with the city-specific EKMA.   Thus, we see  that the  standard EKMA
chemistry is less responsive to hydrocarbon  controls.  Yet, when  both HC
and NOX emissions are reduced,  the standard  EKMA  models  (city-specific and
Level-Ill) and the carbon-based trajectory model  and OZIPM/CBM all  give
similar results.
32R/2
                                   99

-------
                 OZ-Q    9fo    zro
                                             o
                                             \r>
                                               t_) Ijj
                                                                  fO
                                                                  01
                                                                  cu
                                                                  o;
                                                                     CT)
                                                                     oo
                                                                     CD
                                                                     CSJ
                                                                     CI3
                                                                     LjJ
                                                                     a:
                                                                     C_J
                                                                     o
                                                                     a.
                                                                     31

                                                                     C£
                                                                     O
                                                                     CE:
                                                                     o
                                                                     UJ

                                                                     3
                                                                     a:
                                                                     CM
GZ'O
OZ'O
sro    zro
    Hdd'XBN
90
oo-cP
  32R 3
                                   100

-------
      zro
               oro   80-Q
                 J	_J
                                     ZO'O
             Ol'O    80-0    90'0
                                                             •a
                                                             O)
                                                             c
                                                             O
                                                             O
                                                             to
                                                             CM
H'O
zro
ZO'O
00-0°
                        Wdd'XBN
32R 3
                              101

-------
            oro   scro   go'o   wo
     zro
oro
80'0    90'0
   Wdd'X0N
WO    ZO'O    OO'O0
32R 3
                102

-------
                                REFERENCES
ARB (1979), "Emissions Inventory, 1976," California State Air Resources
     Board, Sacramento, California.

ARB (1976), "Emissions Inventory, 1973," California State Air Resources
     Board, Sacramento, California.

BAAQMD (1979), "1979 Bay Area Air Quality Plan," Association of Bay Area
     Governments, Bay Area Air Quality Management District, Metropolitan
     Transportation Commission, San Francisco, California.

de Mandel, R. E. (1979), "Comparisons of EPA Rollback, Empirical/Kinetic,
     and Physicochemical Oxidant Prediction Relationships in the San
     Francisco Bay Area," J. Air Pollut. Control Assoc., Vol. 29, No. 4,
     pp. 352-358.

Demerjian, K. L., K. L. Schere, and J. T. Peterson (1980), "Theoretical
     Estimates:  Actinic (Spherically Integrated) Flux and Photolytic Rate
     Constants of Atmospheric Species in the Lower Troposphere," in
     Advances in Environmental Science and Technology, Vol. 9 (John Wiley
     and Sons, New York, New York).

Dimitriades, B. (1977), "An Alternate to the Appendix-J Method for
     Calculating Oxidant and N02-Related Control Requirements," Proc:
     International Conference on Photochemical Oxidant Pollution and Its
     Control, Vol. II, EPA-600/3-77-001b, pp. 871-879, U.S. Environmental
     Protection Agency, Research Triangle Park, North Carolina.

Dodge, M. C. (1977), "Combined Use of Modeling Techniques and Smog Chamber
     Data to Derive Ozone-Precursor Relationships," Proceedings:  Inter-
     national Conference on Photochemical Oxidant Pollution and Its
     Control, Vol. II, EPA-600/3-77-001b, Environmental Protection Agency,
     Research Triangle Park, North Carolina.

EPA (1980), "Guidelines for Use of the City-Specific EKMA in Preparing
     Ozone SIPs," EPA-450/80-027, Research Triangle Park, North Carolina.

Federal Register (6 November 1980) 73-696.


32R/2                              103

-------
Feldstein, M., et al. (1979), "Anatomy of an Air Quality Maintenance
     Plan," J. Air Pollut. Control Assoc., Vol. 29, pp. 339-363.

Fox, D. L., R. Kamens, and H. E. Jeffries (1975),  "Photochemical Smog
     Systems:  Effect of Dilution on Ozone Formation," Science, Vol. 188,
     pp. 1113-1114.

MacCracken, M. C., and G. D. Sauter (1975), "Development of an Air
     Pollution Model for the San Francisco Bay Area, Vol. 2.  Appendixes,"
     UCRL-51920, Lawrence Livermore Laboratory, University of California,
     Livermore.

Reynolds, S. D., et  al. (1979), "Photochemical Modeling of Transportation
     Control Strategies—Volume I.  Model Development, Performance
     Evaluation, and Strategy Assessment," DOT Report FHWA-RD-78-173.

Whitten, G. Z., and  H. Hogo (1981), "Evaluation of the EKMA Performance,"
     10R-EF80-73R, Systems Applications, Inc., San Rafael, California.

Whitten, G. Z., H. Hogo, and J. P. Killus (1980),  "The Carbon-Bond
     Mechanism:  A Condensed Kinetic Mechanism for Photochemical Smog,"
     Environ. Sci. Techno!., Vol. 14, pp. 690-700.

Whitten, G. Z., J. P. Killus, and H. Hogo (1980),  "Modeling of Simulated
     Photochemical Smog with Kinetic Mechanisms,"  EPA-600/3-80-028,
     Systems Applications, Inc., San Rafael, California.

Whitten, G. Z., and  H. Hogo (1978a), "User's Manual for Kinetics Model and
     Ozone Isopleth  Plotting Package," EPA-600/8-78-014a, U.S. Environ-
     mental Protection Agency, Research Triangle Park, North Carolina.

Whitten, G. Z., and  H. Hogo (1978b), "User's Manual for Ozone Isopleth
     Plotting with Optional Mechanisms (OZIPM)," EF78-30, Systems Applica-
     tions, Inc., San Rafael, California.
32R/2
                                   104

-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO. 2.
EPA-450/4-81-005a
4. TITLE AND SUBTITLE
APPLICATION OF THE EMPIRICAL KINETIC MODELING APPROACH
TO URBAN AREAS
Volume 1: San Francisco/Sacramento
7. AUTHOR(S)
G. Z. Whitten, H. Hogo, and R. G. Johnson
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Systems Applications, Inc.
950 Northgate Drive
San Rafael, California 94903
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
MDAD, AMTB, MD-14
Research Triangle Park, North Carolina 27711
3. RECIPIENT'S ACCESSION NO.
5. REPORT DATE
January 1981 (preparation)
6. PERFORMING ORGANIZATION CODE
8. PERFORMING ORGANIZATION REPORT NC
SAI No. 32R-EF80-139
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-02-3376
13. TYPE OF REPORT AND PERIOD COVEREC
Final
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
EPA Project Officer: Gerald L. Gipson
16 ABSTRACT
The  EKMA  was  evaluated  by comparison with more complex models using common data
bases  for the San  Francisco and Sacramento areas.  The basic model  used in the EKMA
is a simple,  moving-air-parcel, or trajectory, model  that uses a detailed chemical
mechanism for the  surrogate propylene and butane hydrocarbons.  Time-dependent,
precursor-emission  factors can  be  treated, along with expansion of  the air parcel,
but  entrapment  is  treated by assuming that constant  concentrations exist outside
the  parcel.   This  basic model  is used to generate ozone isopleth diagrams for
estimating ozone response to hydrocarbon and nitrogen oxide controls.  The
comparison study  involved several  levels of the EKMA  system, from parts of the basic
model  to  control strategy predictions.  For the San Francisco area, the EKMA was
compared  with the  LIRAQ model,  which had been used for the 1979 AQMP.  For the
Sacramento area, the  EKMA was  compared with the SAI Airshed Model.   When carefully
applied,  the  EKMA  produced results that typically agreed with the more complex
models.   However,  the evaluation confirmed that care  must be exercised in applying
the  model  to  situations involving  wind shear, complex terrain features, and highly
nonuniform emission densities,  and that caution must  be used in interpreting the
results of model applications  to situations involving these factors.
17. KEY WORDS AND DOCUMENT ANALYSIS ~~
a. DESCRIPTORS
Ozone
Control Strategies
Photochemical Pollutants
Models
EKMA
OZIPP
18. DISTRIBUTION STATEMENT
Unlimited
b. IDENTIFIERS/OPEN ENDED TERMS

19. SECURITY CLASS (This Report/
20 SECURITY CLASS (This page)
c. COSATl Field/Group

21. NO. OF PAGES
114
22. PRICE
EPA Form 2220-1 (Rev. 4-77)   PREVIOUS EDITION is OBSOLETE
                                        105

-------