Dispersion Of Pollutants Near Highways Data Analysis And Model Evaluation


United States
Environmental Protection
Agency
Environmental Sciences Research
Laboratory
Research Triangle Park NC 27711
EPA-600/4-79-011
February 1979
Research and Development
Dispersion of
Pollutants Near
Highways
Data  Analysis and
Model  Evaluation

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This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia  22161.

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                                                 EPA-600/4-79-011
                                                 February 1979
     DISPERSION OF POLLUTANTS NEAR HIGHWAYS
       Data Analysis and Model Evaluation
                       by

S. Trivikrama Rao, Michael Keenan, Gopal Sistala
                       and
                  Perry Samson
New York Department of Environmental Conservation
                  50 Wolf Road
             Albany, New York 12233
           R-803881-01 and R-804579-01
                Project Officer

               William B. Peters en
        Meteorology & Assessment Division
   Environmental Sciences Research Laboratory
       Research Triangle Park, N.C. 27711
   ENVIRONMENTAL SCIENCES RESEARCH LABORATORY
       OFFICE OF RESEARCH AND DEVELOPMENT
      U. S. ENVIRONMENTAL PROTECTION AGENCY
       RESEARCH TRIANGLE PARK, N. C. 27711
      U.G. environmental  Protection Agency
      r<-9ion V, Library
      230 South Dearborn Street
      Chicago,  Illinois  60604

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                                DISCLAIMER
     This report has been reviewed by the Environmental Sciences Research
Laboratory, U. S. Environmental Protection Agency, and approved for
publication.  Approval does not signify that the contents necessarily
reflect the views and policies of the U. S. Environmental Protection
Agency, nor does mention of trade names or commercial products constitute
endorsement or recommendation for use.
                     U,S. Environmental Protection Agency
                                      11

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                                   ABSTRACT
     The primary objective of this investigation is to examine the validity of
various assumptions underlying mathematical modeling of pollutant dispersion
near at-grade highways, and to determine the simulation capability of various
dispersion models.  In this regard, the data base generated in the ROAD project
(see Rao et al, 1978a) is utilized to study the micrometeorological character.
istics adjacent to the highway and to evaluate four numerical and four Gaussian
highway dispersion models.

     Analysis of the particulate data reveal that although about 30% of the
automobiles at the site had catalytic converters, there is no significant
contribution of sulfur or sulfate due to the automobiles.  The average ratio
of sulfate to sulfur is 3.22, indicating that most of the sulfur (if not all)
is in the form of sulfate.  The highway traffic is found to be the dominant
source for lead.  Analysis of the turbulence measurements at the site indicate
that the range of frequencies affected by the traffic appears to be 0.1 to 1.0
Hz, corresponding to eddy sizes of the order of a few meters.  Even under quite
stable atmospheric conditions, no organized convections due to vehicle exhaust
heat can be distinguished in the spectral structure.  The aerodynamic drag due
to moving vehicles on the highway is manifested by a pronounced acceleration
of wind in the lowest 8 meters, especially in the cases of wind flow nearly
parallel to the highway.  The impact of traffic-induced turbulence highway
dispersion on the near-roadway dispersion of air pollutants is assessed.

     Of the eight models evaluated, the best performance is given by the
General Motors model for this set of data; it showed the highest explanation of
variance (r^), and had a. slope close to unity for all cases, when unstable
stability was used.  As should be expected, all 8 models generally performed
best for the perpendicular wind-road orientations.  The comparison of parallel
wind cases indicates that here the General Motors model was markedly better than
the other models.  For this simple line source, the numerical models and the
Gaussian models performed about the same.  Finally, the dispersion parameters
used in the Gaussian models are evaluated.  The dispersion parameter values
observed in this experiment are close to those specified in the EPA-HIWAY model
for the stability 2 category.  It is suggested that the dispersion parameters
may be specified in terms of wind fluctuation statistics rather than a power
law relation for estimating dispersion near highways.



This report was submitted in  fulfillment of grant  number R-803881-01 and
R-804579-01 by the  New York  State  Department of  Environmental Conservation
under the sponsorship of the  U.S.  Environmental  Protection Agency.  This
report covers a period from  July 1976  to December  1978, and work was
completed as of December 1978.
                                      in

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                                CONTENTS

Abstract	  Hi
Figures	   vi
Tables	   ix
Acknowledgment ........... 	 ...  xii

   1.  Introduction. ....... 	 .........  1
   2.  Data Management & Analysis	  2
            Traffic data	2
            Farticulate data ..................  4
            Carbon monoxide data	12
            Meteorological data	19
            Tracer gas data	20
            Micrometeorological data ..............29
   3.  Model Evaluation.	42
            Highway models 	 ........43
            Model predictions	.............48
            Dispersion parameters. .... 	 82
   4.  Summary & Conclusions ..................94

References	96
Appendix I	99
Appendix II	108

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                                  FIGURES

Number                                                                  Page

  1    Schematic of meteorology and air quality sampling
         locations 	      3

  2    Scatter diagram showing the computer and film traffic
         data at the site	      5

  3    Comparison between computer traffic counts and film
         traffic counts for each direction 	      6

  4    Hourly traffic volumes for the weekdays, Saturday
         and Sunday in each direction	      9

  5    a) Pollution roses for sulfur at 2m height (left) and
          5m height (right) at various receptor locations
          adjacent to the highway	     13
       b) same as (a) except for lead	     14

  6    a) Composite concentrations and the difference in
          concentrations between the two nearest receptors to
          the highway of fine suspended particulates (FSP) as
          a function of wind direction	     15
       b) same as (a) except for sulfur	     16
       c) same as (a) except for lead	     17

  7    Horizontal (in m/sec) and vertical wind fields (in cm/sec)
         over the roadway for selected cases of perpendicular,
         oblique and parallel wind-road orientation  	     21

  8    Circuit followed by tracer-release vehicles indicating
         location of the sampling plane and length of
         gas release     	     22

  9    Downwind and vertical profiles of averaged SFg
         concentrations normalized by the nearest downwind
         roadside receptor concentration for perpendicular
         and parallel wind-road orientations   	     26

 10    a) Downwind and vertical profiles of SFg concentrations
          normalized by the emission rate, Q, and mean wind speed,
          U for perpendicular cases  	     27
                                    VI

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                                   FIGURES

Number                                                                   Pagt

  10    b) Same as (a) except for parallel cases    	      28

  11    a) Normalized cospectra of along-wind (u) and vertical
           wind (w) components for runs 3 and 11 (stable
           atmospheric conditions).   f is the non-dimensional
           frequency defined as f =  nz  where n is the dimensional
                                    U
           frequency, z is the height of the measurement,  and U is
           the mean wind speed.  Run 11 is a case of high  traffic
           compared to run 3    	      32
        b) Normalized spectra for the cross-wind (v) component  ...      32
        c) Normalized cospectra of u and w components for  runs
           7 and 8 (neutral atmospheric conditions).  Run  8 is
           a case of advection from the highway while run  7 is not  .      33
        d) Normalized spectra of the along-wind (u)  component ....      33

  12    a) to c) Difference spectra for u, v, w components,
           respectively, between unstable case runs  1 and  2   ....      35
        d) to f) Difference spectra for u, v, w components,
           respectively, between stable case runs 11 and 3    ....      35

  13    a) to c) Normalized w, T spectra and wT cospectrum for
           run 2 (unstable case)	      36
        d) to f) Normalized w, T spectra and wT cospectrum for
           run 10 (stable case), VAR is the variance of w  or T  ...      36

  14    a) Normalized heat and momentum fluxes for run 11
           (stable case) in a semi-log representation   	      39
        b) same as (a) except for heated plume taken over
           Lake Ontario under stable ambient conditions 	      39

  15    Observed wind profiles for the various runs  in Table 6  ...      40

  16    DANARD model layout.   Included in the diagram is the
          distribution of diffusivity values_(as suggested by
          Danard,  1972) used in this study.  V-VT  represents
          temperature advection   	      45

  17    Convergence values for DANARD model as a function  of
          cross-road wind speed.  The model efflux,  E,  was always
          greater than model influx, I,  at convergence.  The
          numbers next to the date points represent  total  wind
          speed for the run and indicate that the scatter  is
          influenced by the magnitude of Kz which is a function
          of total wind speed below  10m and outside  of the
          mixing cell   	      47
                                     VII

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                                   FIGURES

Humber                                                                   page

  18    a) and b) Scatter plot showing the HIWAY model
           predictions and observations.  The 1:1 line is
           also drawn in the diagram.  The points below the
           line indicate overprediction and above the line
           underprediction	     56

  19    a) and b) saae as Fig. 18 except for GM model   	     58

  20    a) and b) saae as Fig. 18 except for CALINE-2 model	     60

  21    a) and b) sane as Fig. 18 except for AIRPOL model	     62

  22    Saae as Fig. 18 except for DANARD model	     65

  23    a) and b) saae as Fig. 18 except for MROAD2 model	     66

  24    a) and b) aaae as Fig. 18 except for ROADS model	     68

  25    a) and b) same as Fig. 18 except for RAGLAND model	     70

  26    Cumulative frequency distributions for lead at 9A.
          Solid line is for the observed data, x's denote GM
          model predictions, A's denote HIWAY stability 2
          predictions, and o's denote HIWAY neutral predictions.
          The total number of data points is 84   	     81

  27    Sigma-r values computed in this study as compared with
          those specified in the GM model   	     85

  28    Comparison of computed vertical dispersion parameters
          and those specified in the HIWAY model	     86

  29    Vertical dispersion parameter as a function of downwind
          distance from the source, computed from observed SFg
          concentrations and those derived from the aw measurements
          with an averaging time of 25 sec and a sampling time of
          one hour.  Also indicated in the diagram are vertical
          dispersion parameters specified in the GM and HIWAY
          models.     	     88

  30    Comparison of sigma values obtained from the SFg
          and CO data   	     89

  31    Plot of av/uu  versus the bulk Richardson number	     92
                                     Vlll

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                                      TABLES

Number

  1   Composite hourly traffic volumes derived from the computer counts. . .  7

  2   Observed particulate pollutants data at various receptor locations
        adjacent to the highway.  Included in the tables are the mean,
        standard deviations (Sd),  and total number of samples at each
        receptor location .............. . ..... . ..... 11

  3   Meteorological and emissions summary for the SFg experiments.  The
        stability indicated for Pasquill-Turner was obtained from Islip
        airport observations.  The local stability estimates were made
        using the temperature gradients and the wind speeds measured at
        the site.  The runs are classified as parallel (+ 30° from the
        highway axis), and perpendicular (60  to 90  from the highway
        axis) and represented by the symbols =, / and JL respectively .... 24

  4   Observed tracer gas concentrations at various receptor locations  ... 25

  5   Summary of the experimental conditions for the sonic anemometer
        runs.  IT is the mean horizontal wind speed and T7 is the mean
        vertical speed.  TET and TWT are the total number of vehicles
        in the eastbound and westbound directions, respectively. QU and
        crw are the standard deviations of the along-wind and vertical
        components of wind velocity,  uw and wT are the surface stress
        and heat flux averaged over the sampling period. ..........31

  6   Summary of experimental conditions for the wind profile runs.  TET
        and TWT are the total number of vehicles in the eastbound and
        westbound directions, respectively.  FLUCT indicates that the wind
        direction is fluctuating ......................40
      Statistical results of linear regressions between observed
        concentrations and predicted concentrations of Gaussian models
        for perpendicular (A), oblique (B), and parallel (C) wind- road
        orientation angles.  Statistical parameters ares  explained
        variance (r^), slope (b), intercept (a), and standard error of
        estimate for observed to predicted (So/p).  N is the sample size . . 49

      Same as Table 1 except for numerical models.  Run 1020R1 is not
        included in the model evaluation because of convergence problems . . 50

      Statistical results of linear regressions between normalized
        measured concentrations and the corresponding normalized pre-
        dictions of Gaussian models* ................... .52
                                      IX

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                                      TABLES

Number                                                                      Page

 10   Same as Table 9 except for numerical models	«, ® « <, .   53

 11   Ratio of predicted to observed concentrations at the roadside
        receptor for each Gaussian model as a function of wind-road
        orientation angle.  Numbers greater than unity indicate over-
        prediction by the model. . . .	...0*,..**   54

 12   Same as Table 11 except for numerical models	« .««,.„.«   55

 13   Regression statistics for KIWAY model predictions with stabilities
        2 and 4, and measurements of GO. .............e..e   73

 14   Effect of wind speed and direction on HIWAY model CO predictions
        using stability 2.  This table presents the regression statistics.   74

 15   Emission factors used in the particulate model evaluation. «,.«..   75

 16   Breakdown of the vehicle population used in the emission program
        for particulate modeling .....................   75

 17   Comparison of HIWAY and GM model predictions with the observed
        particulate data.  The critical r2 for 400 data points at the 1%
        level is 0.032 and the student's T value from the statistical
        tables at 1% level is 296	e.«.«   77

 18   Regression statistics for lead as a function of wind-road
        orientation angle.  The critical r2 for 100 data points at the 1%
        level is 0.07 and the student's T value at the 1% level is 2.6 . .   78

 19   Regression statistics for lead as a function of wind-road
        orientation angle.  The critical r2 for 80 data points at the 1%
        level is 0.08 and the student's T value at the 1% level is 2.6 . .   79

 20   Regression statistics for lead between normalized model predictions
        and measurements.  The critical r2 for 500 data points at the 1%
        level is 0.013 and the corresponding T value is 2.6	   80

 21   Regression statistics for lead for two receptors at different
        heights.  The critical r2 for 180 data points at the 17, level is
        0.04 and the T value at 17. level is 2.6	   80

 22   Range of diffusivities used by the four numerical models tested
        in this study for neutral stability conditions with a surface
        roughness of 1m.  Note DANARD's 1C. is actually cross-road
        diffusivity while the values given for RAGLAND are cross-wind.
        The cross-wind diffusivity for MROAD2 is not specified in the
        literature	   83

 23   Percentage of occurrence of each stability class based on airport data 93

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                                      TABLES

Number                                                                      Page
 24   Percentage of occurrence  of each stability class  based on Chock1s
        stability classification. .  	  .  	  .....93

 25   Percentage of occurrence  of each stability class  based on revised
        method	93
                                     xi

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                                 ACKNOWLEDGMENTS

     The authors are grateful to many of the staff members of the Division of
Air Resources for their support in this project.  Thanks are extended to
Mr. A.Ro Peddada for his help in the data processing and analysis.  Special
thanks are to Robert Eskridge, William Petersen, and Bruce Turner of the U«S«
Environmental Protection Agency for giving the authors an opportunity to
discuss the results with them.  Their comments have been extremely valuable in
the preparation of this report.  The authors would like to thank Mrs. Catherine
Cassidy and Miss Nancy Gardner for typing this report, and Mrs. Carol Clas for
drafting the diagrams.

     The cooperation of Mr. Ronald Piracci of the New York State Department of
Transportation, and Dr. Ulrich Czapski of the State University of New York at
Albany is gratefully acknowledged.
                                     XII

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                                    SECTION 1

                                   INTRODUCTION

     In the preparation of implementation plans, indicating how air quality
standards will be met and maintained, highway sources have received consider-
able attention since motor vehicles are important sources of carbon monoxide,
hydrocarbons, and oxides of nitrogen.  Environmental impact statements for
such highways come under close and highly critical scrutiny by federal, state,
and local air pollution control agencies, whose concurrence on the accept-
ability of air quality impacts is a prerequisite to approval of federal-aid
highway funding.  Mathematical modeling techniques are being widely used to
predict the levels of pollutant concentrations adjacent to highways.  However,
the accuracy and applicability of various mathematical dispersion models are
largely unknown due to lack of sufficient testing of the models with field
data.  Lack of confidence in the accuracy of modeling results, and lack of
data acquisition standards and model validation, has been a major stumbling
block in obtaining approvals.  In order to evaluate the simulation capability
of the models for at-grade roadways, a detailed data base consisting of carbon
monoxide, sulfate, lead and total particulates, traffic counts, and meteoro-
logical variables were collected during the period October 1976 through May
1977 at a location on the Long Island Expressway (1-495).  In addition, several
tracer gas experiments were conducted as part of this field project.  A com-
plete account of the experimental set-up and data collection procedures is
given in Rao et al (1978a).

     The major objective of this investigation is to analyze the above data
base to examine the validity of various assumptions underlying mathematical
modeling of pollutant dispersion near at-grade highways and to determine the
simulation capability of various mathematical dispersion models.  Special
attention is given to identification of the effects of local turbulence sources
on the dispersion of pollutants.  In particular, the effect of traffic on the
turbulent structure is assessed, and the time and space scales of the eddies
generated by the traffic are inferred.  This report describes the data manage-
ment and analysis techniques in section 2.  Various dispersion models are
tested against the data base in section 3.  The results of this study are
summarized in section 4.  The data on carbon monoxide and meteorological
conditions used in this analysis are given in Appendix I.  The particulate
data along with the pertinent information are presented in Appendix II.

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                                    SECTION 2

                           DATA MANAGEMENT AND ANALYSIS

     The aerometric and traffic data analyzed in the study were obtained
adjacent to the Long Island Expressway near Huntington, New York.  The location
of various meteorological and air quality measuring sensors is shown in Fig. 1.
The data collection procedures are briefly described here.  The reader is
referred to Rao et al (1978a) for a complete description of the instrumentation
used and the data acquisition techniques followed.

TRAFFIC DATA

     Each lane on the expressway had a pair of induction loops imbedded in the
pavement.  A separation distance of 3.5m between loops was used.  These loops
were connected to loop-?detectors.  Each sensor was polled via interface
circuitry by the on-site minicomputer periodically for the presence of vehicles.
The length and speed of each vehicle was computed from this information and
classified into 5 length and 10 speed categories for each direction.  A time-
lapse photography system was used once a week as a further check on the traffic
measurements made by the computer.

     Of the 32 films taken during the study, 20 were judged to be satisfactory
for analysis.  The others suffered from unclear pictures, improper camera place-
ments, or failure of the timing mechanism to work properly.  Altogether, 450
ten-minute counts were derived from the 20 films.  These were analyzed for
vehicle count and mix for the time of day by direction.  The 450 ten-minute
counts are comprised of westbound data from 7:50 am to 4:40 pm and eastbound
data from 9:10 am to 1:40 pm.  This yielded 80 unique ten-minute intervals.  A
weighted average coefficient of variation for traffic volume was computed using
the average of the ratios of standard deviation to mean, weighted by the number
of observations in a given interval.  However, in the calculation of the
standard deviation for each interval, seven of these intervals were ignored
since they had only a single observation.  Thus, the film data analyzed had 73
usable intervals, composed of 443 observations, which yielded a weighted aver-
age coefficient of variation of 0.08.

     The computer counts for total traffic by direction  for the period between
November 24, 1976 to December 22, 1976 were also analyzed.  This data period
was selected since the loop-detectors often malfunctioned afterwards.  These
data were segmented into weekday  (Monday through Friday), Saturday and Sunday
groupings and analyzed for composite vehicle count for ten-minute intervals.
A review of these results showed  existence of similar daily traffic patterns
from Monday, 6 am to Friday, 6 pm.  The weekday computer traffic had 3,856
ten-minute vehicle counts for the 288 intervals (i.e. 144 ten-minute periods
for 24 hours times the two traffic flow directions).  These data yielded a
                                       2

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weighted average coefficient of variation of 0.12*  If this data base was
reduced to the sane 73 segments as used in the film analysis, the weighted
average coefficient of variation became 0.08.  The number of observations for
the computer data was 1,041, compared to 443 for the film data.

     A linear regression between the two data bases was performed.  Using the
mean total traffic volumes for each of the joint weekday intervals, the
regression equation was FT1M = -7.5 + 1.01 * COMPUTER with an explained vari-
ance of 0.96 (See Figs. 2 & 3).  The total traffic from the film for these
periods was 36,501 while the composite from the computer was 36,761.  From the
above statistics, it can be judged that the mean computer counts are representa-
tive of the actual traffic volumes determined by photographic analysis.

     tealysis of the weekend traffic data showed its pattern to be different
       from the weekday traffic to warrant separate composite data.  It is
        that the computer based weekend data are representative of the actual
traffic en the highway since the weekday traffic surrounding them agreed with
the composite film data taken throughout the study.  Table 1 lists the com-
posite hourly traffic -volumes found from the computer counts.  The average
tMlikiliiy daily traffic on the Long Island Expressway near the experimental site
was found to be approximately 107,000 vehicles.  The weekday, Saturday and
Ssnday hourly traffic voluwes for each direction of the experimental site are
          in Figure 4.
PABnCOLATE DATA

     Eight dichotomous samplers, manufactured by the Environmental Research
Corporation, were employed to sample ambient particulates  in two  size  ranges,
greater and less than 3.5pn in diameter.  Six samplers were  located  at heights
of  2m and 5m on towers 5, 9, and 11 (see Fig. 1).  The remaining  two were
located at 2ea h*fght OB towers 3 and 12.  Particulate measurements were taken
five days per week for a duration of 2 hours during the morning and  evening
peak traffic periods.  Fluoropore filters (0.5um pore size and 47mm  in diameter)
     used to sample particulates in both size ranges.
     Filters for the dichotomous  samplers were weighed  before  and after each
run with a Mettier M-5 Microbalance under constant  temperature and humidity
conditions to determine the particulars mass.  Further  analysis of these
filters for lead and sulfur were made using  a Sieraen's  Model VRS wavelength
dispersive x-ray fluorescence  (xrf) spectrometer.   A molybdenum target tube
powered by a IU4 generator was employed throughout  this study.  Each parti-
culate sample was analyzed for both lead and sulfur using lithium fluoride
(200) and graphite crystals, respectively.   The  calibration standards for this
phase of the analysis are described in Rao et al (1978a).  Final data process-
ing was made on a Hewlett-Packard Model 9130 programmable calculator.

     Following the analysis of sulfur and lead by xrf techniques, the particu-
late filters were analyzed for anions of interest by ion chromatography.  The
samples were extracted in 6 milliliters of a solution of 0.0030M sodium
bicarbonate and 0.0024M sodium carbonate.  The samples  were then loaded into
a  sample tray for introduction into a Dionex Model  10 ion chromatograph to
determine the concentrations of chloride, fluoride, bromide, nitrate, and

-------
  1000
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 100
          100
200    300   4TXT    Kr\r\  '  r.*~  '   I    '   I   i    i •
       aw   400    500    600    TOO   800    900
                       COMPUTER  COMPOSITE COUNTS
                     VEHICLES PER TEN MINUTE PERIOD


      Figure 2  Scatter diagram showing the  computer and film traffic
                data at the site.
                                                                      1000

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                        Sunday in each  direction.
                                                9
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sulfate anions.  Further details on the experimental procedures can be found
in Keenan et al (1978).

     In addition to the particulate measurement from the dichotomous samplers,
total suspended particulates (TSP) were collected on a 24-hour basis with six
hi-volume air samplers as a part of the study for the Federal Highway Adminis-
tration,  Three samplers were located at 9A, 11A and 13A on the south side,
and at 1A, 3A and 5A on the north side of the highway.  The filters were
weighed before and after exposure and the 24-hour concentrations of TSP were
computed.  These data were collected from February 27, 1977 through May 27,
1977.  Some of these filters were analyzed for lead concentrations.  These
data are available through the Federal Highway Administration, Washington,
D.C.

     As a special project, the dichotomous samplers collected suspended
particulates on nuclepore filters.  Elemental concentrations were measured
using instrumental neutron activation analysis and X-ray Fluorescence.  Na,
K, Mn, Cu, Zn, Ga, Br, Sr, and Sb are primarily associated with the <3.5um
(fine) fraction.  In this fraction, the most abundant elements are Br, K, and
Zn (all above 1200 ng/m^ air).  Si, Ca, Ti, and Fe are the only elements
measured in this work associated primarily with the >3.5um (coarse) fraction.
Some of the elemental abundances in the fine fraction are (in percent):  Na,
100; K, 95-100; Mn, 89-98; Cu, 83-95; and Br, 89-100.  A study of size distri-
bution in <.3.5um fraction is planned using scanning electron microscopy.  No
significant differences in elemental concentrations in samples collected at
2 and 5m above the ground on the upwind side are observed.  However, on the
downwind side Si, K, Ti, V, Mn, Fe, Br, Rb, and Sr in the coarse fraction show
somewhat higher concentrations for the 2m level samples.

Observed Features

     In order to establish the reliability of the data base for each of the
pollutants, the analyzed fine particle data were averaged for each sampling
position and the results are given in Table 2.  Position 12A has fewer samples
than the rest because this sampler was used to replace the other samplers when
they malfunctioned.  It is interesting to note that the concentrations of sul-
fur, and, to a fair degree, sulfate remain constant at all receptors in the
sampling plane.  On the other hand, the concentration of lead shows a signi-
ficant enhancement at the two roadside receptors (5A and 9A), and decreases
with increasing distance from the highway.  Some of the upwind lead concentra-
tions were reported as less than a threshold value  (generally 0.6pgm  ) and
were assumed equal to the threshold value for all subsequent analyses.  The
increase in concentration of particulates at the two farthest receptors from
the highway, 3A and 12A, is probably due to fugitive dust, introduced by a
dirt farm road about  10m north of the receptor 3A and the dirt road providing
access to the  trailer near 12A.  The average ratio of sulfate to sulfur is
found  to be 3,22,  indicating  that within experimental error all the sulfur
detected  from  the  filters was in the form of sulfate.

     In order  to determine the source of the pollutants observed at the road-
side receptors, pollution roses have been developed.  The wind direction at
the  8m level of the median tower 7 was used to relate the pollutant concentra-

                                     10
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tions to wind direction.  The wind components parallel and perpendicular to
the highway were computed and averaged over each period the samples were run.
From this a resultant wind direction was obtained for comparison with result-
ing pollutant concentrations.  Figs. 5a and 5b show the directional contribu-
tion of sulfur and lead to the observed concentrations.  The variation in
magnitude and directional dependence of sulfur concentrations between receptors
is quite small as seen in Fig. 5a.  These concentrations demonstrate no
apparent relationship to the wind-road orientation angle.  The observed con-
centrations at all receptor locations seem to indicate the back ground levels.
The maximum concentrations are most likely to occur whenever the wind direction
is northeast or southwest.  It is possible that large point sources situated
along those directions or regional transport patterns could contribute
significantly to the concentrations observed at these receptors.  Contrary
to the sulfur roses, lead, indicated in Fig. 5b, shows a pronounced decrease
in concentration as the distance from the highway increases.  Also, the lead
roses show a strong dependence between wind direction and receptor-roadway
location, with highest concentrations coming from the highway.

     The observed concentrations of fine suspended particulates (FSP), sulfur,
and lead at the two receptors closest to the highway, 5A and 9A, and the
difference between these receptors by wind sectors are plotted in Figs. 6a,b,& c
as a function of wind direction.  Here, a wind direction of 180° (southerly)
and 0° or 360° (northerly) indicate that the wind flow is perpendicular to the
highway.  90° (easterly) and 270° (westerly) represent wind flow parallel to
the highway.  From these diagrams, it is evident that while the highway is an
important source for particulates (contributing up to 20ugm~3), and the
dominant source for lead (contributing up to 4ugm-3), the sulfur concentration
due to the highway is at the very most 0.2ugm~".

     As a maximum, 30% of the cars on the expressway were equipped with
catalytic converters and, therefore, used unleaded gasoline.  Assuming that
these cars had a sulfate emission rate of approximately 0.003gm/mile/vehicle,
while the rest of the vehicles had a lead emission rate of approximately
0.06gm/mlle/vehicle, the lead emission rate on the roadway would be on the
order of 50 times greater than the sulfate emission rate.  This would account
for the negligible amount of sulfate and significant lead concentrations
observed near the expressway.

CARBON MONOXIDE DATA

     The locations of CO measurements are indicated in Fig. 1.  Sampling was
done using non-dispersive infrared  (NDIR) carbon monoxide analyzers, manu-
factured by the Beckman Corporation.  Samples were drawn from each specific
location through teflon tubing into mixing chambers at a fixed sampling rate.
The chamber's volume was designed to dampen rapid variations in the concen-
tration within the sampling  interval without masking any long-period changes.
After passage through the averaging chamber, the sample was pumped into the
monitor.  The electronic output  signal was then transmitted to the data
acquisition system.  All NDIR's  were calibrated and zeroed automatically  at
least 3-times a day.

     For tower 9, a profile  system was designed so that a single NDIR could

                                      12
-------
             2  METERS
                                          SULFUR
                                                -3
5  METERS
     11
     12
Figure 5a  Pollution roses  for sulfur at 2m height (left) and 5m height
          (right)  at various receptor locations adjacent to the highway.
                          13
-------
        2 METERS
                                    LEAD
                                     5 pgm
                                         -3
5 METERS
11
12
         Figure 5b  Same as (a) except for lead,
                      14
-------
      -20
                  60
120
180
240
300
360
                              WIND  ANGLE
Figure  6a  Composite concentrations and  the difference in  concentrations
          between the  two nearest receptors to the highway of fine
          suspended particulates (FSP)  as a function of wind direction.
                                 15
-------
to
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 21
 U.
     2.0-
     1.0-
    0.6-
   -0.6
                        120     180      240


                           WIND ANGLE
           Figure 6b  Same as (a) except for sulfur.
300     360
                             16
-------
                           240     300     360
              WIND ANGLE
Figure 6c  Same as (a) except for lead .
                17
-------
measure the concentrations at four points in a vertical line during a five-
minute sampling cycle.  Flow for these four averaging chambers was produced
by either of two pumps, separated by three-way solenoids controlled by the
computer.  Matched flow meters were used throughout the system to assure the
same constant  flow for each chamber at all times.  The main pump drew the
samples through a collection tank and was used to maintain uniform flows
through the chambers when those particular lines were not being analyzed by
the NDIR.  During analysis a solenoid was activated which closed that chamber's
port to the collection tank and opened another port to the sampling pump and
NDIR.  Therefore, at any one time, three samples flowed to the collection
tank while the fourth went to the NDIR.  The minicomputer switched through
4 channels each cycle period; one channel every 75 sec.  Thus, for each ten-
minute period, the average for each channel was made using two readings, off-
set from each  other by five minutes.

     The CO data, collected during the operation of the profile system, was
edited for modeling purposes.  The four measurements per NDIR were averaged
for each ten-minute period, and the standard deviation was computed.  Hourly
averages and their standard deviations using 24 values per hour were deter-
mined for each probe, except those on tower 9.  For the profile system, only
six readings per probe were available for the hourly computations.  A large
standard deviation in comparison to the hourly average would be due to either
a sampling system malfunction or a change in conditions during the sampling
period, for example, wind shift, traffic back-up, zero-span cycle, and so
forth.  A review of the ten-minute values indicated which of these to be the
case.  The hourly data management computer program also indicated how many
ten-minute periods were used, since zero and span values were excluded.  The
average value  was discarded unless at least four consecutive time periods were
used.  The ten-minute averages, as well as the individual reading, were used
to determine the zero and span values.  These, in turn, were used to make any
necessary adjustments to the averaged values.

     Since systematic differences appeared to exist between the NDIR»s, it was
decided that probes 4A, 5A, and 6A (and probes 8A, 9A, and 10A) could not be
treated as separate points, but were best grouped together.  Although the before
and after zero and span values were available, the small difference in concen-
tration among  these locations could not be consistently determined even with
these adjustments.  Each set of three near-roadway measurements were, therefore,
used to better define a single representative shoulder concentration.  Thus,
the eleven sampling points were reduced to seven, namely, 3A, 5A, 7A, 9A, 9B,
9C and 9D.

     If the ground level probe 9A needed correction either due to the zero-
span drift, or inconsistency with 8A and 10A, the vertical concentrations
were also changed accordingly.  If any of the seven sampling points had a
missing measurement, due to improper operation of the NDIR during a given
hour, the data for that hour were discarded.  Finally, the hourly averages
for the above  seven locations were reviewed to ascertain  that the cross-plane
profile was consistent.  If,  for example, the 3A concentration was  greater
than 5A and 9A concentrations, the data  for that hour were discarded.  With
these  screening procedures, a valid data base of GO was developed.  These data
were used to evaluate  the KEWAY model.
                                      18
-------
METEOROLOGICAL DATA

     Since dispersion parameters derived from meteorological data are critical
in determining pollutant concentrations within 100m of the highway, multiple
measurements of meteorology were made.  Four Gill three-component anemometers
were installed at a height of 8m on towers 5, 7, 9, and 11.  Seven Climet
sensors were located at various positions as shown in Fig. 1.  Temperature
and temperature difference measuring systems, manufactured by Meteorology
Research, Inc., were located on tower 11.  In addition, solar radiation,
relative humidity and precipitation were also measured.

Kinematic Analysis of Wind Structure

     Most of the mathematical dispersion models give importance to the initial
mixing, induced by the moving traffic on the roadway, in determining dispersion
of pollutants.  It is important to understand the induced mean motions as well
as the turbulent fluxes of momentum and heat on the roadway to arrive at a
meaningful parameterization of the traffic-generated turbulence.  In instances
of low ambient winds, traffic flow may result in mean vertical motion fields
near the roadway; whereas at high wind speeds, the roadway could act as an
abrupt change in surface roughness which may also result in induced vertical
motions.
     The wind speed and direction, measured at eight locations adjacent to the
roadway, were averaged for the duration of each tracer run and the cross-road
component of wind was computed.  Since the roadway is a straight segment at the
sampling location and the terrain is fairly homogeneous, the induced vertical
motions can be computed from the derivative of the cross-road component assuming
that derivatives of the parallel-road components are negligible.  To compute
vertical motion fields in a vertical plane perpendicular to the highway, it is
necessary to objectively interpolate the measured values to a grid superimposed
onto the plane.  A grid size of 31 x 25 is chosen along the X - Z plane with
x = 1.67m and z = 0.67m.  A modified version of the Guardaddo and Sommers  (1977)
objective first-guess analysis algorithm is used to compute an initial field.
This field is then fitted to the grid using the bi-cubic spline analysis
described by Sommers (1977).  This modified approach takes each measured point
and constructs an axis in the x and z directions, computing first-guess values
at each intersection with a fixed grid line.  These first-guess values are
computed using an elliptical weighting function skewed heavily in the x (hori-
zontal) direction so as to maintain horizontal continuity of winds.  Weighting
W^j at a particular grid intersection, i, for a known point j, at a distance
 f   O      f\
 xij  + z±*   is computed as

                                       (II
                                      -Q
Xii  v2   .  a..2
with the elliptical constant  a  arbitrarily  set  to  25.   Once  values  had  been
estimated  for  an  axis  (x or z)  at  each  grid intersection,  the  estimates are
                                      19
-------
corrected to agree aore accurately with the observed value(s) on that axis
using a Legendre polynomial.  This procedure is continued until a row and
column have been generated for each known data point.  Each fixed grid row is
then splined using the first-guess values to obtain estimates at each fixed
grid point.  This process is then repeated for each column.  Given two esti-
mates (by row and by column) at each grid point, the values are averaged to
arrive at the estimate of the scalar field.

     The above technique lends itself to analysis of horizontal divergence on
the plane since the spline operation also yields estimates of the first and
second derivatives at each fixed grid point.  The cross-road derivatives are
available directly from the spline of the rows.  The vertical motion field can
then be computed by assuming the atmosphere within the grid to be incompress-
ible.  Thus, the vertical motion as a function of height, w(z), can be computed
from the equation


                       w(z) = w(z -
where the subscript denotes the derivative in x and the notation /U \ is the
                                                                 \  /
average of U  over the layer (z - Az) to z.

     Kinematic vertical motion fields are then generated for each run using the
computed cross-road component at the 2m, 8m and 16m levels of towers 5 and 9  and
the 2m and 8m levels of tower 7 in the median.  The wind speed at the surface
was set to zero.  Figs. 7a and 7b shows two perpendicular runs, one with weak
basic flow from north and the other with stronger flow from north.  In both
cases, vertical motions exist but the signs are reversed.  Similar results are
found for oblique winds, as shown in Figs. 7c and 7d.  For parallel wind cases,
however, the traffic- induced winds typically forced convergence into the road-
way at low levels which is compensated by upward vertical motions above the
roadway (see Figs. 7e and 7f).

TRACER GAS DATA

     The tracer selected in this experiment was 99.9% pure instrument grade
sulfur hexafluoride (SFg) gas.  The gas was contained in T-size cylinders with
typical single stage regulators and gauges for tank and release pressure.  This
was modified by an additional valve and pressure gauge with a flow meter, cali-
brated for operation at 75 psig, so as to establish and monitor the SFg release
rate.

     Simulation of a line source was achieved by releasing gas at a constant
rate near the tail pipes of six station wagons.  They were driven in the middle
lane at 88 km/hr in both directions.  The end points of release are 845m east
and 315m west of the sampling plane.  The test-track for the tracer gas vehicles
is shown in Fig. 8.  All six vehicles were spaced at roughly equal intervals
and made at least 8 laps around the circuit.  Sampling of tracer gas was done
for an hour's duration at several locations (see Fig. 1) across the plane by
means of small capacity pumps connected to five-layer mylar bags via acrylic
tubes.  Samples were analyzed immediately after the experiment with an electron
capture gas chromatograph.
                                      20
-------
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                  TOWER NUMBER
                                                       TOWER NUMBER
Figure 7   Horizontal  (in m/sec) and  vertical wind fields  (in  cm/sec) over
           the roadway  for selected cases of perpendicular,  oblique and
           parallel wind-road orientation .
                                     21
-------
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Figure 8  Circuit followed by tracer-release vehicles  indicating

          location of the sampling plane and length of gas  release-
                                22
-------
     A total of 23 tracer runs were made over three one-week periods.  The
runs reflect a wide range of wind speeds and directions.  The meteorological
conditions along with the total emissions for the runs are summarized in Table
3.  From the routine cloud cover and wind speed measurements taken at the Is lip
airport (about 25km from the site), Pasquill-Turner stabilities were determined
for the periods of interest.  The local stabilities were obtained from the
temperature gradients and wind speed measurements at the site.  The observed
tracer gas concentrations at various receptor locations in each of the tracer
runs are presented in Table 4.

Observed Features

     The observed SF§ concentrations, normalized by the concentration at the
2m height of the nearest roadside receptor (5A or 9A), for perpendicular
(60°<9<90°), and parallel (0<0<30°) conditions are presented in Fig. 9 as
a function of downwind distance from the highway.  The angle 0 is the wind-
road orientation angle with 0° being parallel to the highway.  Also, the
vertical profile of the normalized concentrations at the downwind tower (5 or
9) is included in the diagram.  Two important features are apparent in Fig. 9:

(a)  Under parallel wind-road orientations, the concentration reduced to about
     45% of the maximum (averaged over all cases) at about 42m from the median,
     whereas it reduces only to around 65% of maximum for perpendicular wind-
     road orientations.  At 80m distance, average reduction in concentration
     is approximately 77% of the maximum for parallel wind conditions, while
     it is about 60% for the perpendicular cases.

(b)  The concentration decreases more rapidly with height in the perpendicular
     wind situations than in parallel wind conditions.

     The above features are to be expected since under parallel wind conditions,
there will be a buildup of pollutant levels in close proximity to the highway
as cross-highway advection would be smaller.  The isolines of concentration
will be "stretched" in the vertical direction because vertical diffusion due
to atmospheric eddy motion and vehicle-induced turbulence will become the
important mechanisms for ventilation.  Under perpendicular wind-road orienta-
tions, the transport term (cross-highway advection) becomes dominant resulting
in a slower decrease of concentration with downwind distance.

     The tracer gas concentrations, normalized by the line-source release rate,
Q, and mean wind speed, U, for the cases of perpendicular and parallel wind-
road orientations are presented in Figs. lOa through lOd.  Although there is
much variation in the magnitude of downwind concentrations in Figs. lOa and lOc,
the general trend of the concentration profile is similar.  The vertical profile
of normalized concentrations for the perpendicular wind cases (Figs. lOb and
lOd) indicate that at 8m height the concentrations have little variation from
run to run.  However, for parallel wind cases, there is still a large variation
in the concentrations at that height.  In both cases the values at 16m height
show little variation.

     Two other interesting features are evident from Figs. lOa and lOcj first,
for the perpendicular case in contrast to the parallel case, the spread in
magnitude at a given receptor is considerably less.  Second, the ratio of the

                                     23
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                                               8  10  12  14  16
                              HEIGHT AT THE ROADSIDE RECEPTOR (m )
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                                         O Perpendicular  Wind*
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               ROADWAY

              <0     20     30     40     50     60     70

                 DISTANCE  FROM THE MEDIAN CENTER (m)
80
  Figure  9  Downwind  and  vertical profiles of averaged SFg concen-
            trations  normalized  by  the nearest downwind roadside
            receptor  concentration  for perpendicular and parellel
            wind-road orientations •
                                   26
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maximum to minimum at a given receptor location is found to be approximately
constant in the perpendicular case, while it increases with increasing down-
wind distance in the parallel case.

     The observed variations in the magnitude of the downwind concentrations
cannot be attributed to varying atmospheric stability since almost all the
tracer runs were conducted under near neutral atmospheric conditions (see
liable 3).  One possible explanation for the observed variations may be the
grouping of the runs according to the wind-road angle (30° spread).  The upper
and lower bound curves in Fig. lOa correspond to wind-road angles of 64° and
90° respectively.  In Fig. lOc, the two extreme curves for parallel winds
correspond to westerly (9° with respect to the road) and easterly (8° with
respect to the road) and may represent the differing length of emissions input
in the two directions.  Also, varying flow patterns and diffusivities induced
by inhomogeneties in the surface roughness parameter and traffic flow patterns
could account for the above variations.

MICRQMETEOROLOGICAL DATA

     Due to incomplete understanding of dispersion on the microscale, as
well as mathematical expediency, various assumptions and simplications are made
in the formulation of the dispersion model.  It is well known that the micro-
scale structure of atmospheric motions over a homogeneous underlying surface
are describable by similarity theories.  However, mechanical turbulence
generated by the moving vehicles, change in surface roughness, and, perhaps,
thermal input from automobile exhaust complicate the flow.  In addition,
aerodynamic drag along the direction of the moving traffic could have a
significant effect on the surface layer structure.  Significant deviations
from the similarity laws could occur under the above conditions.

     While there have been a number of theoretical and experimental studies of
flow over homogeneous surfaces, there have been only a few field studies under
the complex situations outlined above.  The major emphasis of this microscale
study was on the evaluation of the influence of the traffic on the turbulent
structure of the surface layer.  Special attention was given to the identifi-
cation of the effects of local turbulence sources on the dispersion of
pollutants.  To this end, time series of wind and temperature were obtained by
a three-component sonic anemometer and copper-constantan thermocouples adjacent
to the highway.  Eddy fluxes of heat and momentum were computed under different
atmospheric conditions.  Spectral distributions of these parameters were
obtained using the Fast Fourier Transform technique.  The flow characteristics
in the surface layer are inferred from the mean wind profiles adjacent to the
highway.

     A three-component sonic anemometer, manufactured by Kaijo Denki Ltd.
Model 311, was mounted for selected periods of times on towers 2, 9, and 11 at
a height of 3m on a 3m extension arm.  Temperature fluctuations were measured
by ultra fast copper-constantan thermocouples at approximately the center of
the sonic antenna.  Two wind profiler systems, manufactured by the Thornthwaite
Associates, were located on extension arms, 1m away from the tower, at heights
of 1.5, 2, 3, 5, 8 and llm on tower, and of 2, 3, 5, and 8m on tower 3.  The
constructional and operational details of the sonic anemometer have been
described in the literature (see Japan-U«S« Joint Study Group Report, 1971).

                                      29
-------
Procedures outlined by Kaimal et al (1968) for data acquisition were followed.
In particular, corrections for overestimation and zero drift inherent in the
instrument were incorporated into the data reduction routine.  The signals as
well as the output of the Honeywell Accudata amplifier for the Thermocouple
temperature fluctuations were recorded on a Honeywell Model 5600 recorder.
This recorder, a 14-channel frequency modulated version, has ample frequency
response with a 10 to 1 signal to noise ratio.  A zero reference voltage was
recorded with each run to provide a reference check in the playback mode.

     The antenna head of the sonic anemometer was oriented for each run such
that the mean wind was centered between the two horizontal pulse paths.  A
total of 36 hourly runs were obtained with as many different variations of
wind direction, atmospheric stability and traffic speed and volume as possible.
Analog records of the three wind components (u, v, w) and temperature (T)  were
digitized by a Hewlett-Packard digital data acquisition system at a sampling
rate of 20 readings/second and processed according to the techniques outlined
in Gzapski and Mumford (1975).  Spectra of the three wind components and
temperature, and cospectra of u, w and wT were computed using the Fast Fourier
Transform technique described by Rao and Ketchum (1975).  No corrections for
line-averaging (see Kaimal et al, 1968) were made for these spectra since
inspection of the computer plots showed little effect in the frequency ranges
of interest.  Tilt errors and errors due to mean vertical motion were removed,
however, following the method given by Hyson et al (1977).

     Mean wind profiles were determined by averaging over at least seven
consecutive 15 min averages of wind speed at each level.  Uniformity of data
was ascertained by checking that deviations between individual 15 min samples
were paralleled by similar changes at other levels.  Also, comparison among
wind profiles from different runs under similar conditions of wind direction,
stability, and traffic volume were made to ensure the consistency of data.

     Of the 36 runs of three-component wind fluctuations analyzed, 22 were
selected as representative of different conditions.  The fluctuation statistics
along with pertinent information on atmospheric stability, traffic speed and
volume, wind speed and direction are presented in Table 5.  The wind directions
tabulated are given with respect to the highway (0° and 180° represent perpen-
dicular wind to the road while 90° and 270° represent parallel wind to the
road).  Three stability classes are used to describe the atmospheric conditions.
These were obtained from the measurements of cloud cover, wind speed, radition
and temperature differences recorded at the site.

Spectra and Cospectra

     Selected spectra and cospectra showing the influence of traffic are
presented in Fig. 11.  Fig. lla presents cospectrum for uw, representing the
turbulent transport of momentum or shearing stress, for runs 3 and 11, where
run 11 is a case of relatively high traffic compared to run 3 (both cases are
with advection from the highway toward the instrument).  Both runs are taken
in the early morning hours under quite stable atmospheric conditions.  Fig. lib
is a spectrum of cross wind fluctuation, v, for the same two runs.  The uw
cospectrum  for runs 7 and 8 are shown in Fig. lie.  In this case, run 8 is a
situation with advection from the highway towards the instrument whereas run  7
is not.  The spectra of the along-wind component, u, for runs 7 and 8 are shown
                                      30
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                                                     33
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in Fig. lid.  Inspection of these spectra reveals a striking augmentation of the
high frequency portion of the variance for the situations where the wind flow
has been over relatively high and fast moving traffic.  According to the
theoretical predictions and observations of surface layer turbulence (Kaimal
et al, 1972) and experimental studies of a surface anamoly (Czapski and Mumford,
1975), the maximum spectral power should occur at lower frequencies, when
stability is decreased, which is also quite evident in our results.  However,
the high frequency part of all spectra should nearly coincide under proper
non-dimensionalization.  Moreover, in conditions of equilibrium between
turbulent kinetic energy production by Reynolds stresses and dissipation by
viscous forces, an extended range of the spectrum should conform to the laws
of inertial subrange.  The fall-off rates of spectral power for the inertial
subrange, transformed to -2/3 for the spectra and -4/3 for the cospectra when
the abscissa is nondimensionalized as f = ££ and the ordinate as n$(n)/variance,
are drawn in the diagrams.                u

     In order to isolate the contribution of the moving traffic to the turbulent
energy, spectra with and without traffic influence are compared under otherwise
similar atmospheric conditions.  The traffic-induced turbulence spectra are
derived by subtracting the dimensional energy spectrum for run 2 from run 1.
Both runs 1 and 2 have similar ambient atmospheric conditions except that run 1
has traffic influence superimposed on the ambient atmosphere.  The spectral
differences for all three components of wind velocity for unstable atmospheric
conditions are presented in Figs. 12a to 12c.  Here A0(n), the difference in
the energy of each wind component, is plotted against the frequency, n.  It is
interesting to see that all three difference spectra exhibit a log-normal shape
with a maximum difference around 0.25Hz.  For the stable case, the difference
spectra for runs 3 and 11 (see Figs. 12d to 12f) also show a log-normal type
distribution.  Again, under neutral atmospheric conditions, the difference
spectra were found to be log-normal.  A log-normal behavior suggests that the
traffic-induced eddies are distributed over a wide size range.  This probably
is due to the break-up of the larger eddies, introduced by the traffic near
0.25Hz, into smaller size eddies.  The range of frequencies affected by the
traffic seems to be 0.1 to l.OHz.

     The difference in the spectral power of vertical component of wind is
considerably lower in the unstable case compared to the stable case (see Figs.
12c and 12f).  This suggests that the energy input of the traffic-induced
turbulence is more significant under stable atmospheric conditions.  The
interactions across the spectrum of vertical motions induced by buoyancy
(larger scale) with motions induced by the local sources could account for the
observed predominance of energy in the higher frequencies under stable situa-
tions.  In non-isotropic turbulence, such interactions are likely to affect a
transfer of energy to the larger scales.  In the stable case, however, under
near isotropic conditions, interactions between motions of similar frequencies
could occur.  These can lead to a constructive type of interference thereby
producing the observed broad peak in Fig. 12f.

     Fig. 13 presents the temperature and vertical velocity spectra, and wT
cospectra for two selected situations.  Run 2 represents an unstable situation
with no advection from the highway, whereas run 10 is a stable situation with
advection from the highway.  The influence of stability on the frequency of
maximum spectral power (Fig. 13a against 13d), namely, a shift by one order of

                                      34
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       10
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           RUN 2
                            -3/3
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Figures 13a to 13c.
Normalized w, T spectra  and wT cospectrum for run 2
(unstable case).  (13d  to 13f)   Normalized w, T spectra
and wT cospectrum for  run 10 (stable case), Var is the
variance of w or  T.
                                    36
-------
magnitude, is distinct.  While the temperature spectrum for run 2 (Fig. 13b)
conforms to -2/3 law, it is interesting to see that the temperature spectrum
for run 10 (Fig. 13e) significantly deviates from the -2/3 relationship.  This
may be attributed to the traffic-induced turbulence.  The covariance between
w and T is well organized in the unstable situation (Fig. 13c) compared to
the stable case (Fig. 13f).  Moreover, as one would expect the heat flux is
downwind in the stable situation (see Table 5, run 10) and upward in the
unstable case.

     If there were significant heat input from automobile exhaust to induce
byoyancy, one would expect to observe upward heat flux in any spectral range
corresponding to the convective motions.  The heat and momentum fluxes are
shown together in a semi-log representation for the stable atmospheric con-
ditions in Fig. 14.  The overall heat flux for run 11, representative of
stable conditions, in Fig. 14a is downward as indicated above.  To enable the
reader to see how the cospectrum of a situation with well-defined convective
elements looks like, this cospectrum is compared to the cospectrum obtained
over a heated water plume in Lake Ontario (see Fig. 14b), taken from Czapski
and Mumford (1975), when the general conditions over the lake were stable.
Examination of Fig. 14b reveals close correspondence of both wT and uw co-
spectra.  In particular, one can readily see that at a given frequency, each
positive peak in the wT cospectrum is associated with a negative peak in the
uw cospectrum.  The implication of this feature is that the same scales, and
thus, mechanisms are simultaneously transporting momentum and heat.  This
indicates the existence of organized convection which occurs at rather well-
defined frequencies.  Lack of such organization in Fig. 14a suggests that there
are no significant convective motions induced due to the waste heat emissions
from the automobile exhaust under stable atmospheric conditions.  It appears
that any heat input from vehicle exhaust is quickly destroyed by the mechanical
turbulence generated by the moving traffic.

Mean Wind Profiles

     Only simultaneous measurements of wind profiles on both sides of the
highway are presented.  The wind profiles for all the eleven cases are shown
in Fig. 15.  Table 6 summarizes the meteorological and traffic data during
which the wind profiles were taken.  In column 4 of Table 6, one can see that
the wind direction on tower 9 at the 2m height varies only between 270° and
330°, whereas at 15m the variation is 265° to 75°.  This is obviously due to
the channeling effect induced by the moving traffic and the highway configura-
tion.

     The most striking effect of the traffic on the wind profiles is the
aerodynamic drag of the moving vehicles, and this feature is evident (see
Fig. 15) in a comparison of the profiles from tower 9 (5m from the southern
edge of the road) with those from tower 3 at a distance of 21m to the north
side of the highway.  Runs 4, 5, and 6, which represent wind orientations
parallel to the road, exhibit strongly accelerated winds at the lower levels
of tower 9.  At the levels above 8m, the profiles at the two towers tend to
become parallel.  In the cases of perpendicular flow to the highway (runs 2 and
8), the features are not as pronounced especially with increasing wind speeds.


                                      37
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                                                      40
-------
The wind speeds at tower 3 are uniformly higher, probably because of  its some-
what higher elevation.  Runs 1, 3, 7, 9, 10 and 11, representing wind at
oblique angles with respect to the highway, show profile distortion to varying
degrees.
                                     41
-------
                                  SECTION 3

                              MODEL EVALUATION

     A dispersion model is a theoretical, mathematical framework which trans-
lates emissions and meteorological data into air quality estimates.  Since
atmospheric motions on the scales of interest for dispersion studies are
highly turbulent and influenced by many local factors, development of a
mathematical model has always been a complex theoretical problem. Nonetheless,
several mathematical models have been formulated to simulate the motor
vehicle's impact on air quality based on various assumptions about atmospheric
structure.  Basically, these models fall into two types; Gaussian and
numerical.  Gaussian models are based on neglecting any effect of changes in
wind speed or direction, or of atmospheric stability over the period of
simulation; a so-called "Quasi-steady state atmosphere."  In addition, spread
of the pollutant plume is assumed to be such that pollutant concentrations
vary according to a normal (Gaussian) distribution along both the horizontal
and vertical lines perpendicular to the (steady) wind direction.  It is also
assumed that there is a total reflection of pollutant spread at the earth's
surface.  The degree of plume spread is denoted by the standard deviations of
pollutant concentrations, ^y and GZ, which are functions of atmospheric
stability and distances from the source.  The currently used values of these
parameters were determined originally by Gifford (1959), and Pasquill (1961)
for open countryside, and by McElroy and Pooler (1968) for urban areas.  The
values of ay and cz were determined only to a minimum downwind fetch of 100m,
and usually are simply extrapolated to shorter distances as needed.  Recently
Bowne (1974) presented curves which are projected to 1m downwind according to
a value of initial surface roughness.  Based on experimental data, Chock
(1977) developed sigma curves that are applicable to the dispersion of pol-
lutants from roadways.  However, these Gaussian models have several weaknesses
and concerns about the limitations of the Gaussian models have led to the
development of more sophisticated models, such as numerical models.

     Numerical models invoke assumptions which are much less limiting in
scope.  The conservation of mass equation is solved by finite-difference
approximations.  These methods may become extremely complex.  However, they
might eventually lead to a versatile and more accurate model for predicting
the transport and diffusion of matter in the atmosphere and are adaptable to
the inclusion of chemical reactions.  In addition to the mathematical prob-
lems associated with the modeling of the diffusion process, lack of sufficient
field data has inhibited our understanding of atmospheric motions on this
micro-scale.  The data gathered in this study are particularly useful to
evaluate various mathemetical dispersion models.  In this section, the simu-
lation capability of four Gaussian models, viz, HIWAY (Zimmerman and Thompson,
1975), GM (Chock, 1977) AIRPOL4A (Carpenter and Clemana, 1975), CALINE 2

                                     42
-------
 (Ward et al, 1976); and four numerical models, namely, DANAKD (Danard, 1972),
 MROAD2  (Kirsch and Mason, 1975), RAGLAND (Ragland and Peirce, 1975), and
 ROADS (Filter, 1976) are evaluated using the tracer gas data.  The dispersion
 parameters in two of the Gaussian models (GM and HIWAY) are compared to those
 obtained by solving the Gaussian equation for known source strength, meteoro-
 logical conditions, and measured concentrations of tracer gas.  Finally, the
 impact of the traffic-induced turbulence on the dispersion of pollutants near
 highways is discussed.

 HIGHWAY MODELS

     The various dispersion models tested with the tracer gas data base are
 briefly described below.  A complete description on the formulation of the
 model can be found in the papers published by the model designers (see above
 references).

 EPA-HIWAY Model

     The HIWAY model uses multiple evaluation of a steady state Gaussian
 equation to predict air pollution concentrations at receptor locations
 adjacent to a highway in a relatively flat terrain.  A highway is simulated
 with an increasing number of point sources with the total contribution of all
 points computed by a trapezoidal integration of the Gaussian point source
 equation over a finite length until the solution converges.  The concentra-
 tion from a line source is given by
                            C = s_  \  f d-L
                                U   0

where q is the emission rate per unit length, U is the wind speed, D is the
length of the line source and f is the point source dispersion function. The
dispersion parameters CTy and CTZ in the Gaussian plume equation are specified
at each downwind distance as a function of atmospheric stability and distance.
Mechanical mixing over the highway is simulated by specifying a set of initial
dispersion parameters.

California - CALINE2 Model

     This model is based on the Gaussian plume theory together with concepts
of a box model.  It uses a separate equation for computing pollutant concen-
rations under cross-wind and parallel-wind to the highway configurations.  The
model assumes that the pollutants are well mixed over the roadway up to a
fixed height.  This region is referred to as the "mixing cell."  The downwind
concentrations from the roadway are determined by using both continuous line
source and continuous point source equations.  The model uses Pasquill disper-
sion parameter curves which are modified to handle downwind distances of less
than 100m from the source.

AIRPOL-4A Model

     This model adopts the technique of segmentation in conjunction with an

                                      43
-------
appropriate numerical method to evaluate the Gaussian  integral.  The model is
capable of predicting concentrations for both upwind as well  as  downwind of  a
roadway at any desired sampling intervals for wind speeds  greater  than  or
equal to zero.
General Motors (GM) Model

     This model uses an infinite Gaussian line source  approach.
concentrations are computed from the equation
                                                  Pollutant
          c =
    Q      f     ,  /g + H0\
^u,Qi  rxp  ~2r°rv
                                            + exp
                                                           -Ho
Here Q is the emission rate per unit length,  U^  is  a  sum of  effective  cross-
road wind speed and wind speed correction factor, HQ  is  the  plume height. The
effect of lateral and vertical dispersion on  the distribution  of concentration
is incorporated by specifying tfz as a function of both downwind distance  and
wind-road orientation angle.  Chock (1977) suggests that &z  is of the  form
CTZ = (a 4- bx)c where a, b, c are functions of atmospheric stability, which
are determined empirically, and x is the distance from the source.

MROAD 2 Model

     This is an Eulerian two-dimensional grid model which numerically  solves
the conservation of mass equation.   The model allows  for the existence of
several line sources (all assumed to be perpendicular to the plane  in  the
model) including elevated highways.  There is also  a  provision to include
topography adjacent to the roadway.  Mixing of pollutants is assumed to be
uniform to 3.3m above each road bed.  Wind profiles are  described as a
function of atmospheric stability,  but can be specified  by the user.   The
model can accept wind direction and speed for up to eight locations.   The
final wind field is based on the solution of  a potential field and  is  fitted
to the measured velocities via a least-squares fit.

DANAKD Model

     DANARD is a two-dimensional Eulerian model  whi- h solves the mass  con-
servation equation according to the numerical methoos outlined by Dufort  and
Frankel (1953).  The grid is fixed in the horizontal, extending from -150m
to +150m from the center of the roadway.  The vertical grid  is confined to
10 cells between the surface (assumed flat) and  the mixing height.  The pol-
lutants are assumed to be mixed uniformly within the  3m  layer  above the road-
way, but the user can specify the diffusivity value desired  over the highway
(Danard suggests a value of 20m^/sec).  The user must also specify  the
diffusivities (Kx, Kz) at the 10m height.  Model inputs  include a wind speed
value V at the 10m height and a cross-road component  at  the  same level.   If
the mixing height is greater than 10m, the model requires additional wind
measurements at higher levels.

     This model has been modified to accommodate mixing  over 3 lanes in each
direction with a wide median as required by our  experimental site.  Fig.  16
                                     44
-------
   100
I 10-
o
UJ
x
                                 Kz«3,6,9  mz/$ec

                                 for~V-VT<,*, >0
                          V2
                                         ln(Z/Zo)


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    -75
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        DISTANCE FROM THE MEDIAN (m)
75
   Figure 16  DANARD model layout.   Included  in the diagram is the distribution
            of diffusivity values  (as suggested by Danard, 1972) used in this
            study.  V'AT represents temperature advection.
                                   45
-------
shows the model layout with the Kz values suggested by Danard.  There are
three lanes over which Kx = Kz = 20m^/sec with corresponding linear transition
zones.  The source terms are allowed to exist only at two grid points
corresponding to the middle lanes of the two directions.

     The model is designed to iterate until the outflow of pollutants from
the model is within a critical percentage of the influx from the roadway.
Unfortunately, this technique is not found to be sufficient for use in this
study.  Therefore, the model is allowed to iterate until the outflow converged
to a constant value.  This constant is found to be always larger than the
inflow.  The magnitude of the excess outflow is between l-47o and found to be
a function of cross-road wind speed and the total wind speed.  Fig. 17 demon-
strates this relationship for our test runs.  It should be noted that with
increasing cross-road wind speed the excess outflow value at convergence
tends toward a value between 2.4% and 2.8%.  At low cross-road wind speeds
the excess outflow value is quite variable, apparently a function of the total
wind speed (which determines Kz for z < 10m away from the roadway) .  Danard
does not permit cross-road wind speeds less than 1 m/sec, probably because of
these convergence problems.  Interestingly enough, using only one lane as set
up in Danard1 s original model with emissions extending over several grid
points, the results will converge to an equality between influx and outflow,

RAGLAND Model

     The model of Ragland and Peirce (1975) solves the continuity equation

               u be - _b /ky bc\ - _b  / Kz be \ = 0
                 bx   by     6y    bz (    bz
Where u = u (z) is the wind speed in the x direction as a function of height
and c is the pollutant concentration.

     The eddy diffusivities are defined for neutral stability following
Lettau (1959) as

                Kz = k u* z   for z < 100m

where k is the von Karman constant ( 0.4) and u* is the friction velocity
defined in terms of the geostrophic drag coefficient and geostrophic wind
speed.

     The continuity equation is solved for two cases using an efficient matrix
inversion technique under the same boundary conditions as imposed by Danard
(1972) except that Danard fs cross-road diffusivity value KX is replaced by the
more appropriate cross-wind diffusivity Ky.  The model predicts for oblique
and perpendicular cases by ignoring lateral diffusion /Ky bc\ and computing
                                                      \    byj
an effective advective wind speed equal to V Sin 0. In the parallel case the
model solves the equation in three-dimensions including lateral diffusion.
                                      46
-------
       0.03
       0.02
  H
   I
  UJ
       0.01
                                              4.6«
                                                    5.0
                                                            6.6
                                                      6.5
                          2.3
                        3. 1
7.5
                              6.4
                            6.0
           0       10      2.0      3.0      4.0      5.0      6.0

                   PERPENDICULAR WIND COMPONENT {m/*ec)

Figure 17   Convergence values for DANARD model  as a function of cross-road'
           wind  speed.  The model efflux, E,  was always  greater than model
           influx,  I, at convergence.  The numbers next  to  the date points
           represent total wind speed for the run and  indicate that the
           scatter  is influenced by the magnitude of K  which is a function
           of  total wind speed below 10m and  outside of  the mixing cell.
                                   47
-------
ROADS Model

     This is a two-dimensional conservation of mass model.  It computes the
average stability class and generates a vertical profile of cross-road wind
speed for each observation.  The winds at a reference level are then averaged
to obtain a reference cross-road wind speed.  The horizontal cross-road wind
speeds are then computed for all grid points on the basis of the reference
wind speed and the vertical profile.  Vertical velocity generated due to the
presence of terrain features are also computed.  The vertical velocities,
which decay with height, are then specified at each grid point.  The horizon-
tal velocity departures from these values are also adjusted with distance in
a specified manner.

     The model determines the steady-state concentrations of pollutants by
numerically solving the equations governing atmospheric advection and diffu-
sion and chemical reactions.  In each time step, the pollutants are first
advected and diffused horizontally then advected and diffused vertically, and
finally allowed to react to modify the pollutant mix.  Lax-Wendroff finite-
difference scheme is used to solve the advection-diffusion equation
numerically.

MODEL PREDICTIONS

Tracer Gas (SFfc) Data

     All the eight models, described above, were used to predict concentra-
tions at downwind receptors corresponding to the SFg sampling points.
Stability estimates made from Islip airport data (about 25km from the site)
indicated most tracer periods to be in neutral stability while stability
parameters such as bulk Richardson number, wind angle fluctuations, and
vertical temperature gradients based on data observed at the site indicated
most of the run periods to be in unstable conditions (See Table 3).  This
would seem to indicate that the locally generated turbulence modifies the
ambient conditions and tends to decrease the atmospheric stability.  All the
dispersion models were run for both neutral and unstable stability conditions
(stabilities 4 and 2, respectively, according to Pasqui11-Turner classifi-
cation) .

     The SFg runs were divided into three sets; perpendicular (wind 60° to
90° from the axis of the highway), oblique (30° to 60° from the axis), and
parallel (0° to 30° from the axis).  For each classification of wind-road
orientation, linear regression analysis was performed between the measured
concentrations and those predicted by each model.  The results of these
ensemble regressions for Gaussian and numerical models are listed in Tables 7
and 8, respectively, which show the explained variance (r^), the slope (b),
the intercept (a), and the standard error of estimate (So/p) for observed (0)
versus predicted (P).  In the case of the DANARD model, only results of the
neutral case are presented in Table 8 since there is little change in the
predicted concentrations between neutral and unstable categories.  The total
sample size, N, of 133 has a critical correlation rcrit) Q.01 at tne ^° l£vel
of 0.22.   Thus, all the models are highly correlated with the data which


                                     48
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reflects the trivial result that all models predict decreasing concentrations
away from the highway as observations indicate.  A comparison of explained
variance from model to model, however, illustrates the relative ability of
each model to reproduce the observed concentration field.

     Summarizing Table 7, it is evident that the GM model performed the best
for this set of data.  It showed the highest explanation of variance (r^) and
had a slope close to unity for all cases when unstable stability was used. In
general, all models predicted best for the perpendicular case which should be
expected since this is the simplest case where the magnitude of diffusion
terms become less important.  The comparison of parallel wind cases indicated
that the GM model predictions are markedly better than predictions of the
other models.  The numerical models in all cases did no better than the
Gaussian models (see Table 8) for this simple roadway configuration.  It is
interesting to see that while Gaussian models gave good correlation when
unstable classification is used, the numerical models yield good correlation
for neutral stability classification.  This suggests that the eddy diffusivity
values in the numerical models and dispersion parameters in the Gaussian
models need further examination.

     The simulation capability of the advection-diffusion process of each of
these models could be evaluated by comparing the normalized downwind concen-
trations to their corresponding model predictions.  The predicted and observed
concentrations for each run were normalized by its corresponding maximum
concentration per run, thus removing the model's dependence on wind speed and
emission rate.  Tables 9 and 10 list the results of the linear regression
between the observed and predicted normalized concentrations after eliminating
mutual values of unity.  When all the data are considered, HIWAY, GM, DANARD,
and MROAD2 fit the observed profile data well.  This implies that the disper-
sion formulations used in these models are more consistent with the ambient
conditions at the site.  The ratio of predicted to observed concentration for
the nearest downwind road side receptor for the eight models are listed in
Tables 11 and 12.  Since the nearest downwind road side receptor has the
highest concentration, the minimum and maximum ratios in Tables 11 and 12
provide a range of under to over prediction for each model.  In particular,
in the case of HIWAY for neutral stability the range is a factor of 6 between
minimum and maximum values (for parallel wind cases), while in the case of
GM model it is only 1.5.

     The simulation capability of each of the Gaussian models tested is
summarized in Figs.  18 to 21.  The scatter plot showing the HIWAY model pre-
diction and measurement is indicated in Figs. 18a and b.  A one-to-one
correspondence line (observed = predicted) is drawn in the diagram to facili-
tate comparison between observed and predicted.  As indicated earlier,  the
HIWAY model using unstable stability (Fig. 18a) predicts concentrations quite
well for perpendicular and oblique wind-road angles.   The model tends to
overpredict in the parallel wind situations.  The GM model predictions shown
in Figs. 19a and b are in excellent agreement with measurements.  In particular,
the model predicts best for parallel wind conditions. CALINE2 model is seen
(Fig.  20a) to consistently underpredict independent of the wind-road orienta-
tion angle using stability 2.  For stability 4, the model tends to underpredict


                                      51
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(Fig. 20b) only in the perpendicular case.  The AIRPOL model has a greater
tendency to underpredict than CALINE2 (Fig. 21a) for the less stable case.

     All the numerical models tested (see Figs. 22 to 25) tend to overpredict.
The major exception to this was the results of the model MROAD2 for stability
2 which consistently underpredicts.  The ROADS model always overpredicts
independent of wind-road angle.  Although the explained variance in the case
of the numerical models is similar to that of HIWAY and GM, the scatter plots
reveal that the numerical models seem to consistently overpredict.

     From these diagrams it is evident that the GM model provides the best
simulation for this set of data.  The simulation capability of HIWAY and GM is
about the same for perpendicular and oblique wind-road angles.  This suggests
that HIWAY needs further refinement to properly describe the dispersion during
parallel wind cases.

Carbon Monoxide (CO) Data

     The wind measurements from location 7C and temperature data gathered for
those hours which passed the CO editing checks were retrieved from the com-
puter diskettes.  Since the data from the traffic counters were unreliable for
the profile sampling period, a synthetic traffic data base was created with a
sufficient confidence based on on-site traffic film analysis.  The CO data was
segmented into 5 categories: weekday, Monday morning, Friday night, Saturday
and Sunday.  The hourly traffic volumes used are those shown in Table 1.
Analysis of the traffic films indicated that the mean percentage of light duty
vehicles was 90% (+ 3%) with light duty trucks comprising 10% (+ 2%) of these.
Heavy duty gasoline powered vehicles were 65% (+ 77,) of the heavy duty vehi-
cles.  Since the vehicle speeds are required for emission factors, the
December 1976 traffic speeds, as well as in-traffic measurements taken through-
out the study period were reviewed.  All hours for both directions were
assigned to the average speed of 55 mph, except the following weekday hours:

                Direction             Time             Speed (mph)

                  West             6 am - 8 am             30
                  West                9 am                 50
                  East                2 pm                 50
                  East                3 pm                 30
                  East                4 pm                 20
                  East                5 pm                 25
                  East                6 pm                 40

     AP-42, Supplement 5, emission factors were used in conjunction with the
HIWAY model and predictions were made for stabilities 2 and 4.  Each sampling
data set was adjusted by having the background removed from each measurement.
Least-square regression analysis was performed between the model predictions
and the background-removed measurements.  If either value of a pair was zero,
that pair was not used.  Various data sub-sets were also examined, as well as
comparison of normalized values.  The normalization is done by dividing each
measured value by the maximum concentration measured for that hour.


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                         70
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                          71
-------
     Table 13 presents the results of regression analysis for both stabil-
ities 2 and 4.  For comparison purposes, the regression statistics for the
CO data collected during the tracer study are:

            OBS = 0.77 + 0.53 x PRE.,  r2 = 0.30,  N = 101.

Thus, much of the decrease in the explained variance may be attributed to the
uncertainty introduced in the estimation of the actual emission, as well as
inaccuracy in sample analysis.  As can be seen, the results with stability 2
have a better correlation and slope compared to those with stability 4.  The
model predictions with stability 2 were further examined for the effects of
wind speed and direction.  Table 14 lists the regression statistics.  It is
observed that only the runs for the wind speed group of 2 to 5m/sec show any
significant change from the overall statistics.  In general, for wind speeds
less than 2m/sec, the correlation is poor and the slope is too low.  In the
wind speed range 2 to 5m/sec, the correlation is greatly improved and the
slope is close to unity.  When the data are segregated as a function of wind-
road orientation, we see little change in the computed regression coefficients.
It is interesting to see that the regression coefficients for normalized data
are significantly high and are independent of the wind-road orientation. This
suggests that the HIWAY model handles the physics of the dispersion problem
quite well.  This would seem to indicate that if the dispersion parameters
used in the model were chosen properly such that they represent the atmos-
pheric conditions near a highway, it can be expected that the model would be
capable of reproducing the air pollution concentrations near highways quite
well.

Particulate Data

     Two Gaussian models, HIWAY and GM, were used to simulate the dispersion
of particulates from the highways.  Table 15 lists the various emission
factors used in the emission program.  The total number of trucks on the
highway was at most 13% of the total traffic.  The split between the heavy
duty gasoline and heavy duty diesel trucks was 2 to 1 respectively, while the
light duty trucks comprised 10% of the light duty traffic.  Vehicle registra-
tion data as well as the films and visual traffic counts indicated that at
most 30% of the light duty vehicles were 1975 or later models.  Therefore,
conservatively 30% of the light duty vehicle population had catalyst equipped
engines.  Table 16 summarizes the above vehicle population used for the
emission programs.

     The above two dispersion models were run utilizing the meteorological
data obtained at a height of 8m on the median tower 7.  Since the particulate
data base was collected for various sampling durations (1 1/2 to 2 1/2 hours),
the meteorological data were averaged over the appropriate sampling interval.
From the observed meteorological data at the site and at the Islip airport
(about 25km from the site), the atmospheric stability was found to range from
neutral (Pasquill-Turner classification of the airport data) to unstable
(bulk Richardson number estimates using the on-site data).  Hence, the HIWAY
model was run for neutral stability (HW 4), and unstable stability (HW 2),
for all the available data.  On the other hand, the GM model was run only for

                                     72
-------
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TABLE 14  EFFECT OF WIND SPEED AND DIRECTION ON HIWAY MODEL CO
          PREDICTIONS USING STABILITY 2.   THIS TABLE PRESENTS
          THE REGRESSION STATISTICS
Direction
Perpendicular
Oblique
Parallel
Wind Speed
(m/sec)
less than 2
2 to 5
greater than 5
2 to 5m/sec Winds
Perpendicular
Oblique
Parallel
r2
0.29
0.27
0.26
2
0.29
0.42
0.36
r2
0.49
0.38
0.53
a
0.93
1.00
0.79
a
0.97
0.47
0.34
a
0.33
0.56
0.31
b
0.45
0.33
0.33
b
0.27
0.90
1.39
b
1.29
0.98
0.81
N
391
287
362
N
386
560
94
N
174
156
230
                               74
-------
                         Emission Factor     Vehicle Type
   Lead                        0.06           LDV1. LDT1, & HDG
       •


   Particulars                0.5A           LDV & LDT

                              1.21           HDG

                              1.61           HDD
                                0


   Sulfate                     0.003          LDV2, LDT2
                    1 - non-catalyst vehicles only


                    2 - catalyst vehicles only





TABLE 15  EMISSION  FACTORS USED  IN THE PARTICIPATE MODEL EVALUATION
                                              Percent of Total

        Vehicle Type                               Traffic


        LDV (Ron Catalyst)                          54.8


        LDV (Catalyst)                  .            23.5




        LDT (Non Catalyst)                           6.1


        LDT (Catalyst)                               2.6




        EDG                   .                   .    8.7


        HDD                  .                        4.3
TABLE 16  BREAKDOWN OF THE VEHICLE POPULATION  USED  IN THE EMISSION

          PROGRAM FOR PARTICULATE MODELING
                              75
-------
neutral stability since there was little difference between the predictions
for neutral and unstable cases.

     The comparison between the observed and predicted concentration of
sulfate, lead and particulates for the two models is presented in Table 17.
It is evident from the table that there is no significant correlation between
the model predictions and the measurements except for lead.  Further analysis
was carried out to study the dependence of the lead predictions on the wind
speed and wind-road orientation angle.  Again, the data were divided into   |
three sub-sets, namely, cases with wind speed less than 2m/sec, 2 to 5m/sec,
and greater than 5m/sec.  The model predictions and measurements are compared
and the results summarized in Table 18.  It can be seen that the HIWAY model's
predictive capability improves with increasing wind speed.  For low wind
speeds, the GM model performed better than HIWAY.  Next, the models were run
segregating the lead data by wind-road orientation angle and the regression
statistics are presented in Table 19.  In general, as the orientation angle
increases (as the wind becomes more perpendicular to the highway), the
predictions improve.

     In order to establish the applicability of the dispersion parameters
used in the two models, data from each run were normalized by observed maxi-
mum concentration for that run and compared to the normalized concentrations
predicted by the models.  Normalization removes the models' dependence on
wind speed and emissions and allows a direct comparison of the concentration
profiles.  Table 20 lists the results of this analysis, which show that the
dispersion mechanism is treated somewhat better by the HIWAY model using
unstable stability than the GM model.

     The model comparisons are summarized in cumulative frequency distribu-
tions of observed and predicted concentrations of lead at receptor location
9A in Figure 26.  It is evident from this plot that HIWAY using neutral
stability overpredicts lead levels 50% of the time, while for unstable
stability the overprediction is reduced to 20% of the time.  On the other
hand, the GM model appears to predict the concentrations at the nearest
roadside receptor.  However, comparisons of cumulative plots for 9B (not
shown here) indicate that both models overpredict approximately 30% of the
time.  Although the agreement between the cumulative distributions of observed
and the GM predictions appear to be good, it should be borne in mind that
there need not be a one-to-one correspondence between a predicted and the
corresponding measured value in Figure 26.  This is reflected in the results
of the regression analysis for the set of observations from which the cumu-
lative plots were developed (N = 84, r^ = 0.14, slope = 0.35, intercept = 2.3,
and Student's T value = 3.6).

     The lack of significant correlations between the predicted and measured
concentrations for these pollutants could, in general, be due to the dif-
ference in the transport characteristics between gaseous and particulate
matter.  Also, the dispersion models assume quasi-steady wind and traffic
conditions, which are not satisfied over the entire sampling period.  In the
case of particulates the observed data is from the fine particle filters only,
which corresponds to particles less than 3.5 ^m, while the model predictions

                                     76
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-------
Model
GM
HW2
HW4
Explained
Variance
r2
0.52
0.62
0.40
Standard
Error of
Estimate
0.21
0.19
0.24
Intercept
-0.05
-0.12
0.10
Slope
0.93
1.04
0.69
Computed
T
Value
23.5
28.8
18.6
Number
of Data
Points
509


TABLE 20  REGRESSION STATISTICS FOR LEAD BETWEEN NORMALIZED MODEL PREDICTIONS
          AND MEASUREMENTS.   THE CRITICAL r  FOR 500 DATA POINTS AT THE 1%
          LEVEL IS 0.013 AND THE CORRESPONDING T VALUE IS 2.6
Height
(m)
2


5


Model
GM
HW2
HW4
GM
HU2
HW4
Explained
Variance
r2
0.43
0.33
0.19
0.19
0.25
0.14
Standard
Error of
Estimate
1.3
1.4
1.5
1.0
1.0
1.1
Intercept
0.82
1.49
1.82
0.97
0.97
1.27
Slope
0.71
0.38
0.16
0.36
0.32
0.14
Computed
T
Value
15.4
12.4
8.7
6.7
7.9
5.4
Number
of Data
Points
320


189


  TABLE 21   REGRESSION STATISTICS FOR LEAD FOR TWO RECEPTORS AT DIFFERENT HEIGHTS.
             THE CRITICAL r  FOR 180 DATA POINTS AT THE 1% LEVEL IS 0.04 AND THE
             T VALUE AT 1% LEVEL IS 2.6
                                 80
-------
   12 A
J»
rs  O-
i*1
\^t  5

I  4
   3
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   I
A   •
       AA   •
    (0090807060S04030

                           CUMULATIVE FREQUENCY (%)
                                                     20
10
      Figure 26  Cumulative frequency distributions for lead  at 9A.  Solid line
                is for the observed data,  x's denote GM model predictions, A's
                denote HIWAY  stability 2 predictions, and o's denote HIWAY
                neutral predictions.  The  total number of data points is  84.
                                       81
-------
are formulated for the total particulates.   Bradway et al (1978)  reported
that 23% to 327o of hi-vol total particulates by mass are collected on the
fine filter of a dichotomous sampler, depending on the height of sampling.
Hence, this would result in the model overprediction as observed in Table 17.
The regressions between measured and predicted for lead at the two receptor
heights are presented in Table 21.  It can be seen that both models behave
better at the 2m height, with a marked reduction in the explained variance
and slope for the GM model at the 5m level.  Therefore, the sigma values
used in the models should be reevaluated.

                           DISPERSION PARAMETERS

     In the Gaussian diffusion models, atmospheric turbulence, topographic
features, wind speed, sampling interval, and other meteorological variables
are all represented by the two parameters,  °y and az.  The existing Gaussian
models prescribe ay and az as functions of the atmospheric stability which is
arbitrarily divided into six or seven stability classes in terms of readily
observable features like surface wind, incoming solar radiation and/or degree
of cloudiness, all assumed to be in-variant over an hour.  Diffusion in
numerical models is parameterized by use of eddy diffusivity values Kx, Ky,
and Kz along the three axes, representing the diffusivity in the downwind,
crosswind and vertical directions.  The many conditions that govern the fate
of pollutant emissions like the micrometeorology of the terrain, the modifi-
cation of the eddy diffusivity coefficients due to a heat-island effect,
etc., can be taken into account in these numerical models.  These complex
models, however, require the specification of a great deal of detailed
information on the eddy diffusivity and wind profiles and their behavior
under different atmospheric stability conditions.  Such detailed data is
presently nowhere available.  Therefore, the various eddy diffusivity values
for different stabilities have been assumed without factual basis.  The
magnitudes of these parameters vary from model to model.  Consequently,
choosing values which are physically realistic would be expected to improve
the simulation capability of the model.

     The diffusivity values used in each of the numerical models tested are
compared in Table 22,  for neutral atmospheric stability and roughness length
of 1m.  It should be noted that Danard's values are consistently higher than
either of the other three models, with a difference of close to two orders of
magnitude over the roadway.  Also, none of these models deal with the vehicle-
induced turbulence near the highway.

     The dispersion values in the Gaussian models, on the other hand, are
essentially the standard deviations of the plume spread along the cross wind
direction (ay) and vertical direction (<^z).  The values for these parameters
are specified as a function of atmospheric stability and downwind distance
from the source.  Since the source strength in the tracer gas experiments is
known, and measurements of concentrations at various receptors and meteoro-
logical conditions during the experiment are available, the vertical diffu-
sion coefficient can be computed from the line source equation :
                                    82
-------
Model
RAGLAND
DANARD
MROAD 2
ROADS
Height
(m). ,
2
10
16
2
10
16
2
10
16
2
10
16
Kj. (in2 sec'1)
Min
0.05
0.27
0.43
0.42
0.63
3.00
0.07
0.50
0.86
0.06
0.32
0.52
Max
0.31
1.56
2.50
20.00
5.21
9.00
0.55
4.18
7.13
0.54
2.70
4.32
2 -1
VLy (m sec A)
Min
0.03
0.14
0.22
0.42
0.63
3.00

0.06
0.32
0.52
Max
0.16
0.78
1.25
20.00
5.21
9.00

0.54
2.70
4.32
TABLE 22  RANGE OF DIFFUSIVITIES USED BY THE FOUR NUMERICAL MODELS TESTED
          IN THIS STUDY FOR NEUTRAL STABILITY CONDITIONS WITH A SURFACE
          ROUGHNESS OF 1m.  NOTE DANARD'S Kv IS ACTUALLY CROSS-ROAD DIFFU-
          SIVITY WHILE THE VALUES GIVEN FOR^RAGLAND ARE CROSS-WIND.  THE
          CROSS-WIND DIFFUSIVITY FOR MROAD2 IS NOT SPECIFIED IN THE LIT-
          ERATURE.
                                        83
-------
                   c =
                                       Q
                                  u  sin  9 0",
                     «>   <-TlS
where C is the observed concentration, u is the mean wind speed,  6 is the
angle between wind direction and the orientation of the road,  z is the height
of receptor, and °z is the vertical diffusion parameter.   At each tower loca-
tion, since Gz is not a function of height and the wind is uniform in the
layer (Gaussian assumptions), az is evaluated from the relation
                                          2
                            2 -
                                      - 2
where 22 and z-^ are two levels at which C£ and C^ are the observed concentra-
tions.  Again,  CTZ as a function of downwind distance (x) is evaluated through
the relation
             C (at X,)
             C (at X2)
QJ
           exp
                       -2-
                 2 a,
                           °~
J2,x, -
                                            , x2
                            2,X
since we know the values of CT.
     at x, and the other variables.
                                   Also CTz values
are obtained from the GM model using the formulation (Chock, 1977).
                             = [a + bx f(e)J
f (©
                                     P
                                        e-90
                                          90
Where a, b, c, (3 and r are the empirical constants, 9 the wind-road angle and
x the downwind distance.

     Figure 27 is a plot comparing the °z values from the GM model to the
computed values.  It is evident from this diagram that T.he agreement between
the GM values and the computed values is quite good for 9>30°.  For 6<30°
(parallel winds) the GM values are consistently higher than the computed
values.  This is due to the fact that, in parallel wind cases, distance from
the median was used as the downwind distance x, rather than the effective
downwind distance.  The computed values for the perpendicular wind-road
orientation (60°<6<90°) are compared to those specified in the HIWAY model
under stability 2 (unstable) in Fig. 28.  It should be mentioned that most of
the tracer experiments periods were under neutral stability as per Pasquill-
Turner classification, while from Fig. 28 and from Table 3 it is clear that
the unstable stability classification is in good agreement with the observed
data for the HIWAY model.  The az values for oblique and parallel cases cannot
be computed from HIWAY since in these cases CTy has also to be taken into
account.
                                     84
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                                 85
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         s
         o
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         o
         UJ


         o.
         S
         o
         o
             10
             8-
6-
             2
                               IDEAL

                                FIT
                     24      6      8      IO     12


               HIWAY-SIGMA (°z) FOR STABILITY-2 (m)
Figure 28  Comparison of computed vertical dispersion  parameters
           and those specified in the HIWAY model.
                                86
-------
     Fig. 29 is a plot of the variation of the calculated sigma with downwind
distance for perpendicular (60°<6<90°) wind road angles.  Also plotted for
comparison are the sigma values from GM (neutral) and HIWAY (stability 2).
The scatter is to be anticipated since the perpendicular case data set ranges
from 60° to 90° wind-road angle while the GM and HIWAY values are computed
for 90°.  This implies that a simple linear equation of the form °z = a + bx
could represent the variation of CTZ with downwind distance for wind-road
angles in the range of 60° to 90°.  In addition, sigma values are computed
from the standard deviation of the elevation angle (°M) as follows.  From the
three component wind measurements at the roadway we obtain
(V
                                t.s
where the subscripts t,s represent the sampling period and the averaging time
respectively, CTw measurements are available for averaging times of 1, 5, 10
and 25 sec. for a sampling period of 10 minutes.  The (a0)s values are
averaged for the corresponding one hour SFg sampling periods since the vari-
ability in °0 between each 10 min. interval is quite small, and the (CTz)t s
are obtained from the relation (Pasquill, 1976)

                            (az)t,S  =  (°0)t,SX

where x is the downwind distance and the subscript t,s are the one hour
sampling time and the appropriate averaging time respectively.

     A linear regression between the calculated dispersion values and the
dispersion values obtained using the standard deviation of elevation angle
indicated an explained variance of 0.92 and an intercept of 1.17 for 1 sec.
averaging time; and an explained variance of 0.89 and an intercept of 1.14
for 25 sec. averaging time.  The values plotted in Fig. 29 are those obtained
with an averaging time of 25 sec. for two cases of perpendicular wind con-
ditions.  Incidentally, the intercepts obtained, representative of the initial
dispersion values, are in the range of initial dispersion values specified by
the GM model ( rather than az ~ ax**, commonly used in the
existing Gaussian highway models.

     Another independent way to confirm the consistency of the calculated
sigma values is to compare the sigma values computed from the concurrently
observed carbon monoxide concentrations.  Fig. 30 compares the sigma values
from both carbon monoxide and tracer data.  When all data points are consid-
ered, the explained variance is 0.78 and the slope is unity.  This suggests
that the dispersion of SF6 is similar to that of CO.  Hence, the models
validated using SFg as a tracer gas can be confidently applied for modeling
carbon monoxide.
                                       87
-------
• • °

* *^
\ \
\o\
^ \ O i^
V \
• ilc CX3
\ L
\ X
w \ \
CO (VJ 0
o ^~ »cL c^P
™^ i *^ ™
<5 \ \
o: m «> \ .
Jfj -y rr ~ *f N*
~\ /^ ^ A
3 ^ ° "i * \
§£« s] o«^
tf\ — % ^ *- «. > » \
^^ — / i? *~ JO O \
Q UJ _J ^ CM O j> >i0
^J "^ ^*- || || II > T
*~ ^ > ^"** w x M

2 ^ $ & \ ^
00x6 )<«h .
O 
i i \ \
i^ cfc •
^* 55
|[
o ^
u
• o


O
• oo

1
cr
UJ
j-
LJ
0 0
CO _
^
Q
UJ
UJ
I
H
S
O
cr
.0 U_
^~
UJ
o
z
<
w
Q

.0
OJ

^•N
cu — —
           VW9IS
                                                                               OJ   I
                                                                               O  Oi
                                                                               S-  i-
                                                                               33
                                                                               O  i/)
                                                                               CO  fO
                                                                                  O)
 E
 O
 S-
                                                                                 G
                                                                                  O)
 co  a;

5  -M

    E

 i_  "~
 3  T3
 O  CU

CU E
0 O
E S-
ro 4-
-i->
CO "O
•i- a>
T^3 ^>
-o T
c cu
•r- T3
s
E cu
S co
0 0
•a -E
-(->
14 —
O "O
E ro
0
•i- CO
CU -r-
E O
O CU
a.
4— co
O
co
CU i-
_E CU
4J CU
E
CD ro
E i_
•r- ro
r— CL
Q.
E E
ro o
CO •!—
CO
cu
~o ^^
E CO
                                                                              4-  ro
                                                                                  i.
                                                                               ro  -t->
                                                                                  E
                                                                               CO  CU
                                                                               ro  u

                                                                               s-  o
                                                                               
                                                                               E  S-
                                                                               o  cu
                                                                              •r—  CO
                                                                               CO  -Q
                                                                               S-  O
                                                                               ai
                                                                               a. E
                                                                               CO  O
        O

        co  ro
           o
       LO •!-
       CM -t->
           S-
       4-  CU
        O  >

        a>  cu
        E  S-
           ro
        CJ: ro
        E  s-
       •i-  en
        en ro
        ro T-
        s- -o
        cu
        >  cu co
        ro -E i—
          4-> CU

        ro  E o
                                                                              -o  4- -E
                                                                              t—  T3
                                                                               ro  cu
                                                                               O  -!->
 s-  E
 cu  o
>•  o
                                                                              en
                                                                              CM
                                                                               cu
                                                                               S-
                                                                               cn
                                                                                         •o
                                                                                         cu
                                                                                         ro
                                                                                      CO  O
                                                                                      c -o -a
                                                                                      cu  c c:
88
-------
   30
   25
UJ
Q 20
x
o
o
OQ
QC.
O

<
2

CO
   15
   10-
        0.82
        0.70
        0.82
        0.78
                 x
                 A
                 O
Perpendicular  ( JL)
Oblique
Parallel
All
U)
( = )
                       10
                                15
                    20
                 25
30
                             SIGMA  SF6  (m)
    Figure  30   Comparison of sigma values obtained from  the  SFfi and
               CO data.
                                    89
-------
Impact of Traffic-Induced Turbulence on Near-Roadway Dispersion

     As indicated in the previous section, from a comparison of spectral
distributions with and without traffic influence, it appears that significant
input of turbulence energy occurs at natural frequencies around 0.25 Hz.  The
size of traffic-generated eddies., under the assumption of frozen turbulence
(Taylor's hypothesis), is then on the order of 4 to 8m horizontally.

     If we follow the general concepts of diffusion, expressed by a mean eddy
diffusion coefficient multiplied by a concentration gradient, this K (for the
vertical component) can be written as (Pasquill, 1974)

                           Kz  =  C % \m

Where C is a constant, CTW is the standard deviation of the vertical wind
component, and \m is the wave length at which maximum spectral power occurs.
In reality, of course, Kz and CTW are integral values of all the Fourier com-
ponents in the spectrum, and Xm is taken as representative for this spectrum.
The shape of the spectrum, and, hence, \m are supposed to be dependent on the
atmospheric stability.  The stability dependence of Kz, either as a function
of the Richardson number or of the Monin-Obukhov length has been extensively
treated in the literature.  In the case of traffic-generated turbulence,
however, there is an augmentation of turbulent energy at wave lengths well
below Xm.  These turbulent eddies will be important for the near-roadway
diffusion, but cannot be properly represented in Kz.  Therefore, for the
purpose of near-roadway dispersion a representation has to be sought, in
which KZ is modified as Kz total = Kz + AK, where AK is a decreasing function
of height and downwind distance from the source.  In the Gaussian formulations
the dispersion parameters may also be modified in the similar manner.

     AK at a given downwind distance from the source can be estimated from
AK = Cn Aaw\n  where AK is the contribution from the locally generated turbu-
lence to K, A CTW is the increment of variance in the spectral range for which
An is the representative "eddy size";  C  is the corresponding constant.
Calculation of AK at a distance of 5m from the edge of the highway indicates
that AK contribution to the total diffusivity in the unstable cases is about
3-4% of Kz while the AK contribution is about 40-100% in the stable case.
Consequently there will be a maximum (x^x) distance downwind from the high-
way upto which both atmospheric stability (natural turbulence) and traffic
(locally generated turbulence) will govern the pollutant dispersion.  For
distances greater than x^x, only atmospheric stability will determine the
diffusion process.

     A second mechanism which will severely affect the dispersion process
close to the highway, is the aerodynamic drag due to the moving vehicles. The
fact that wind profiles are distorted mainly if the wind has a component
parallel to the highway, means that there is an altered dispersion in the
direction of the road.  It is possible that if the wake effects behind the
moving vehicles are considered in the model formulation, the predictive capa-
bility of the model could be greatly improved.  The implications of locally
generated turbulence on the dispersion of pollutants are given in Rao et al
(1978b).

                                     90
-------
Atmospheric Stability Determination

     In the Gaussian models the dispersion parameters ®y and az  are expressed
as a function of the atmospheric stability class and downwind distance.  It
is common practice for model predictions to use the stability class, obtained
from the nearby airport, which is derived from surface wind speed, cloud
cover and ceiling height observations of the National Weather Service offices.
A comparison is made between the stability classes determined from the Islip
airport data and the experimental site data.  The former is based on the
standard Pasquill method and is available on an hourly basis.  The latter is
determined from bulk Richardson number.  An attempt is made to relate the
airport stability to the site stability and °0.  The road side stability,
based on bulk Richardson number, was determined from the equation

                         RiB  =  gz1z2 ATk       x 100
                                Tk (Z2 -Z].) UR

for each hour, where z>i = 16m and z-^ = 5m, T^ and AT^ being the temperature
and temperature difference respectively  aind  U^ the wind speed.   The °0
value for each hour was obtained from CTW/UH using a 1 sec averaging time
from the 8m height Gill sensor in the median.

     Data for the months of Jan., Feb., Mar., were segregated according to
the hourly Pasquill stability classes (based on the airport data). Table 23
list  the percentage of occurrence for each stability class used in the
analysis from the airport data which comprised 666 £ases.  The bulk Richardson
number calculations were restricted to windspeeds (Ug) > 1.0m sec"-*-.  CT0 and
the bulk Richardson number for all the six stability classes are plotted in
Figure 31.  There is a considerable amount of scatter in the range of a0
values for a given stability class.  Based on this diagram and following the
arbitrary classification of Chock (1978) the data was divided into three
stability classes and the percentage of occurrence of each class is listed
in Table 24.  Clearly the range of bulk Richardson numbers in the neutral
stability class is too narrow.  Hence, a new method of classification, based
on the observed range of the bulk Richardson number in Fig. 31,  is given in
Table 25.  The airport data in Table 23 indicates that 50% of the time
neutral stability is prevalent while from Table 25 the percentage of occur-
rence of neutral stability drops to about 257».  This is due to the restricted
range imposed on the value of the bulk Richardson number.  It is evident from
Fig. 31 that the scatter in the bulk Richardson number values for a given
airport stability class is quite large.  The scheme outlined in Table 25
appears to be in reasonable agreement with the data in Table 23 when classes
5 and 6 are combined together in each of the Tables.  This implies that under
stable conditions both schemes of classification are quite valid.  However,
at least 307« of the hours classified as neutral stability based on the
airport data are unstable at the site.
                                     91
-------
                                                                          -o
CO
CO
• a o + • <
-j 
-------
                       7o of Occurrence
Stability
Class
1
2
3
4
5
6
7, of
Occurrence
0.3
0.9
9.0
53.0
26.3
10.5
                     TOTAL No.  of cases  is 666

TABLE 23  PERCENTAGE OF OCCURRENCE OF EACH STABILITY CLASS BASED ON
          AIRPORT DATA
      Stability
  Range of Rg
70 of Occurrence
      Unstable
      Neutral
      Stable
     >  0.1
0.07 >  Ru >-0.1
     >  0.07
      54.6
       3.8
      41.6
TABLE  24   PERCENTAGE OF OCCURRENCE OF EACH STABILITY CLASS BASED ON
           CHOCK'S  STABILITY CLASSIFICATION
Stability Class
1 & 2
3
4
5
6
Range of Rg
< -1.5
-1.5 < RB < -0.05
-0.05 < RB < 1.0
1.0 < RB < 1.5
RB > 1.5
7o of Occurrence
15.2
32.8
25.1
3.6
23.3
 TABLE 25  PERCENTAGE OF OCCURRENCE OF EACH STABILITY CLASS BASED ON
           REVISED METHOD
                             93
-------
                                    SECTION 4

                             SUMMARY AND CONCLUSIONS

     The management and analysis techniques of the aerometric and traffic data
collected in this study were presented in section 2.  Although the later
traffic measurements with the detector loops imbedded in each lane of the high-
way were found to be unreliable, the availability of traffic films enabled a
reasonable estimate of the traffic patterns of the highway.  Most of the
problems encountered in the traffic data are due to the variations in the
sensitivity of the loop detectors.  It was found that although the traffic
measurement system is based on sound techniques, the applicability of this for
continuous long-period data acquisition is questionable.  For future studies,
it is recommended that on- site traffic films be made and analyzed for traffic
counts and classification.  On a periodic basis, these two sets of data must be
compared to ensure proper operation of the traffic detection system.  Based on
the analysis of all the data collected and the results of the model evaluation,
the following conclusions can be drawn:

(1)  With the present mix of catalyst equipped vehicles (about 30% of total
     population) over the Long Island expressway, the contribution of sulfate
     from the roadway is negligible.  Therefore, the sulfur and sulfate con-
     centrations adjacent to the Long Island expressway are indicative of the
     mesoscale environment at the site.

(2)  The sulfate (as S)/sulfur (as S) ratio of 1.07, found at the site for all
     samples, indicates that within the limits of sampling error, all of the
     sulfur exists as sulfate.

(3)  The main source of lead at the site is the highway.  The significant
     increase in lead concentration due to the roadway suggests that the lead
     concentration in an urban situation (e.g. street canyons) could pose an
     air quality problem when a national ambient lead standard is set.  Also,
     the highway is an important source for particulates.
(4)  Under parallel wind- road orientations, the pollutant concentration
     in this case) falls off to 50% of the maximum at about 20m from the edge
     of the highway.  For a road-side receptor, the concentration drops off by
     607o at 8m height.  There is a convergence of traffic- induced winds at low
     levels resulting in vertical motions on the roadway.

(5)  Under perpendicular wind-road orientations, the pollutant concentration
     (SFfc, in this case) falls off to 50% of the maximum at a distance of 40m
     from the roadedge.  For a road-side receptor, the concentration drops off
     by 80% at 8m height.  Traffic- induced winds generally resulted in vertical
     motions over the highway.
                                      94
-------
(6)   With significant moving  traffic  over  the  highway,  there  is  noticeable
     augmentation of turbulent  kinetic  energy.   This  turbulent energy appears
     to be dominant at mean frequencies of 0.1  to  l.OHz,  corresponding to
     eddy sizes  of a few meters,  and  is probably due  to multiple wakes
     generated by the traffic.

(7)   As revealed from a comparison of mean wind profiles  close to the highway
     and at 21m distance from the highway,  the  aerodynamic  drag  due  to the
     moving vehicles is significant.  These effects are manifested by an
     acceleration of wind in  the  lowest 8m in  cases of wind directions nearly
     parallel to the highway.

(8)   In contrast to the findings  of Dabberdt (1976),  and  Chock  (1977), no
     organized convection can be  distinguished  in  the spectral structure,     '.'•
     even under  quite stable  atmospheric conditions.

(9)   Of the eight models tested with  the tracer data, only  the predictions
     from the GM model are in excellent agreement  with the  observations.  HIWAY
     model appears to predict the concentration profiles  quite well  indicating
     that the physics of the  diffusion  process  is  handled properly in the model.
     Taking explained variance  as a measure of performance, the  numerical models
     performed about the same as  the  above Gaussian models.  In  general, all
     the numerical models tested  here overpredict  the concentrations.

(10) The good correlation between the dispersion parameter  values calculated
     from SF6 data and CO data  suggests that the dispersion of CO is similar
     to that of SF^; hence, SF^ tracer  can be  confidently used to validate  CO
     dispersion models.

(11) Incorporation of vehicle-induced turbulence in  the dispersion models,
     could significantly improve  a dispersion  model's simulation capability.

(12) The classical Pasquill-Turner stability classification may  not  properly
     represent the stability conditions near the roadways.  It  is suggested
     that the atmospheric stability adjacent to the  highways  may be  determined
     through Richardson number  (or bulk Richardson number)  or wind fluctuation
     data obtained at the site.  Although  most tracer periods were conducted
     under near neutral atmospheric conditions as  per the Pasquill-Turner
     typing, the on-site measurements indicated mostly unstable.   This indicates
     that the mechanical turbulence due to the moving vehicles on the highway,
     tends to decrease the atmospheric  stability immediately  downwind of the
     highway.

(13) It is found that the dispersion  parameter az  obtained  from  the  standard
     deviation of the elevation angle (j^) is  in good agreement  with the
     sigma's used by GM and HIWAY (unstable category) models, as well as
     the values  calculated from the observed concentration  profiles.  Hence,
     it is suggested that for highway dispersion problems with  a typical
     sampling time of one-hour, the dispersion parameters may be defined in
     terms of wind fluctuation  (CTW or QQ)  rather than a power law relation
     with downwind distance from the  source.


                                     95
-------
                                   REFERENCES

1.   Bowne, N»E«;  "Diffusion Rates", J. of the Air Poll. Control Association,
     24, 1974,  PP 832-835.

2.   Bradway, R»M«, F. Record, and W,E. Belanger;  "Monitoring and Modeling of
     Resuspended Roadway Dust Near Urban Arterials",  57th Annual Transportation
     Research Board Meeting, Washington, D,C,, Session 25, 1978.

3.   Carpenter, W«A«, and G«G» Clemana;  "Analysis and Comparative Evaluation of
     AIRPOL-4",  Virginia Highway and Transportation Research Council Report,
     VHRTC75-R55, Charlottesvilie, Virginia,  1975.

4,   Chock, D«P«;  "A Simple Line-Source Model for Dispersion Near Roadways",
     GM Research Publication,  GMR-2407, 1977,  PP 19.

5.   Czapski, U,H«, and W,E. Mumford;  "Heat Transfer From a Thermal Effluent",
     ASME Publication,  75-HT-24, 1975.

6.   Dabberdt, W.F.;  "Experimental Studies of Near-Roadway Dispersion",  Proc.
     of 69th APCA Annual Meeting, Portland, Oregon,  1976.

7.   Danard, M,B»;  "Numerical Modeling of Carbon Monoxide Concentrations Near
     a Highway",  J. Appl. Meteor., 11, 1972,  PP 947-957.

8.   Dufort, E.G., and S.P. Frankel;  "Stability Conditions in the Numerical
     Treatment of Parabolic Differential Equations", Math. Tables and Other
     Aids to Computation, 7, 1973,  PP 135.

9.   Gifford, F*A.;  "Statistical Properties of a Fluctuating Plume Model",
     Adv. in Geophysics, Academic Press, 6, 1959,  T^ 117-137.

10.  Guardado, J.L,, and W.T, Sommers;  "Interpolation of Unevenly Spaced Data
     Using a Parabolic Leapfrog Correction Method and Cubic Splines",  U«S,D«A.
     Forest Service Research Note,  PSW-324, Pacific Southwest Forest and
     Range Exp. Stn., Berkeley, Calif., 1977, P 5.

11.  Hyson, P., J»R. Garratt,__and R.J. Francy;  "Algebraic and Electronic
     Corrections of Measured uw Covariance in the Lower Atmosphere", J. Appl.
     Meteor., 16, 1977,  PP 43-47.

12.  Japan-U«S. Joint Study Group;  "Development of Sonic Anemometer and its
     Application to the Study of Atmospheric Surface Layers", Disaster
     Prevention Research Institute,  Kyoto, Japan,  1971.


                                       96
-------
13.  Kaimal, J.C.,  J.C. Wyngaard, and D,A, Hangers;  "Derived Power Spectra
     from a Three-Component Sonic Anemometer", J. Appl. Meteor., 7, 1968,
     PP 827-836.

14.  Kaimal, J.C,,  J,C. Wyngaard, Y. Isumi, and O.R, Cote;  "Spectral
     Characteristics of Surface Layer Turbulence",  Quart. J. Roy. Meteor.
     Soc., 98, 1972,  PP 563-589.

15.  Keenan, M»T.,  G. Sistla,  A.R. Peddada, P,J, Samson, and S,T, Rao;
     "Sulfate and Lead Concentrations Adjacent to the Long Island Expressway",
     Proceedings of the Questions of Sulfates Conference, APCA, April, 1978.

16.  Kirsch, J.W.,  and B.F, Mason;  "Mathematical Models for Air Pollution
     Studies Involving the Oregon 1205 Highway Project, Systems, Science and
     Software Report",  SSS-R-76-2744,  La Jolla, California,  1975.

17.  McElroy, J»L«, and F. Pooler;  "St. Louis Dispersion Study, Vol. II
     Analysis",  USDHEW Report  AP-53,  1968.

18.  Pasquill, F;  "Atmospheric Diffusion",  2nd Ed., John Wiley & Sons, New
     York, 1974, P  429.

19.  Pasquill, F;  "The Estimation of Windborne Material", Meteor. Magazine,
     90,   1961,   PP 33-49.

20.  Fitter, R»L.;   "User's Manual ROADS, PSMOG, VIS 1", Oregon Graduate Center,
     Beaverton,  Oregon,  1976.

21.  Ragland, K,W,, and J»J. Peirce;  "Boundary Layer Model for Air Pollutant
     Concentrations Due to Highway Traffic",  J. Air Poll. Control Assoc.,
     25,   1975,   PP 48-51.

22.  Rao,  S.T.,  M.  Chen, M. Keenan, G. Sistla, R. Peddada, G. Wotzak, and N.
     Kolak;  "Dispersion of Pollutants Near Highways:  Experimental Design and
     Data Acquisition Procedures",  EPA-600-4-78-037,  1978a,  P 55.

23.  Rao,  S.T.,  and C.B. Ketchum;  "Spectral Characteristics of Baroclinic
     Annulus Waves",  J. Atm.  Sci.,  32, 4, 1975,  PP 698-711.

24.  Sommers, W.T,;  "Data Interpolation by Cubic Splines",  USDA Forest
     Service Research Note, PSW-313,  Pacific Southwest Forest and Range Exp.
     Stn., Berkeley, Calif.  1977, P 5.

25.  Ward, C.E., A,J. Ranzieri, and E.G. Shirley;  "CALINE 2 - An Improved
     Microscale  Model for the  Dispersion of Air Pollutants From a Line Source",
     Federal Highway Admin. Report,  FHWA RD-77-74,  Washington, D.C., 1976.

26.  Zimmerman,  J.R», and R»S. Thompson;  "User's Guide for HIWAY, A Highway
     Air  Pollution  Model",  EPA-650/4-74-008,  1975.
                                     97
-------
                                                       y
                                Appendix I


     Appendix I contains the 318 CO data-hours used for modeling.  The Julian
date is followed by the starting time of the hour of interest.  The wind
speed is in m/sec, while the direction is in degrees.   A northerly wind would
be 0 or 360° (and is perpendicular to the highway) while an easterly parallel
wind is 90°.  The temperature is in °F.  The CO concentrations are in ppm.
The stability is classified using the Pasquill Gifford schemes and is from
the Islip airport.
                                                        v1
                                                       .' \.
                                                      n6  o
                                                      O  J      o
                                                       - ^      AO
                                                 V
                                    99
-------
\e

DAV
97
97
97
97
97
97
^7
>l
97
98
98
96
9d
98
9d
96
98
99
99
99
99
99
99v,
99
100
100
100
100
100
100
r^j^ "\
I Ov
tfjO
IOU
1QO
100"
101
101
rw.
loi
101

HR
b
6
7
8
9
10
15
16
17
6
7
13
14
15
16
17
18
14
1 5
16
17
18
21
22
6
7
8
10
14
15
16
17
18
21
22
0
1
2
6
7

rfS
l.d
2.2
3.7
3.7
3.6
3.3
4.2
3.9
3.8
3.0
4.9
8.4
9.4
8.0
8.9
7.7
6.5
4.4
5. 1
4.3
3. 7
2.4
.0
.6
2.4
3.2
4.4
2.9
3.9
J.4
4.0
3.4
2.0
.3
.2
1.3
.4
.5
3.4
2.3

*UIH
284.
2/6.
295.
298.
298.
2/6.
242.
206.
206.
267.
291.
316.
324.
319.
324.
323.
322.
310.
316.
327.
332.
334.
12.
17.
295.
303.
322.
324.
295.
283.
224.
226.
230.
2D6.
61.
39.
37.
4.
105.
J25.

ItMP
30. "
31.
32.
34.
35.
36.
42.
40.
38.
4J.
42.
40.
39.
3d.
37.
36.
34.
37.
39.
39.
39.
3d.
30.
28.
34.
37.
39.
44.
51.
52.
47.
45.
43.
3d.
37.
36.
35.
33.
39.
40.
r/
3A
.5
1.5
.6
.0
,t>
1.0
2.0
2.6
2.4
1.0
.9
.6
.6
.6
.0
.6
.0
.3
.3
.3
.3
.5
2.0
2.0
.9
.6
.3
.3
.4
.4
1.1
1.4
2.0
3.3
3.6
3.3
2.d
3.0
J.3
2.3
. t
DA
1.7
3.7
1.4
1.2
1.0
1.7
3.4
4.3
3.2
3.3
3.0
.7
.8
.9
.7
.7
. /
.6
.5
.5
.3
.6
1.9
2.3
1.0
.6
.4
.6
1.0
1 .0
1.8
2.4
3.8
4.1
3.9
3.3
2.9
2.9
3.6
5.1
V
X
7A
1 .8
3.3
2.6
2.0
1.6
2.1
2.3
3.9
2.4
2.4
1.9
1.0
.9
.9
.d
.8
.7
1.1
1.0
1 .0
1.1
1.4
3.3
3.4
1.2
.8
.7
.2
.5
.2
.8
. t
.6
4.3
b.4
3.9
3..I
3.0
J.I
1.4

-9A
1.6
2.3
2.D
2.2
2.0
2.1
.9
.1
.0
.d
2.0
.5
.5
2.1
2.2
1.7
2.0
J.D
1.0
1 .6
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93
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JTAB
4
4
4
4
4
4
4
4
4
4
3
4
4
4
4
4
4
4
4
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4
4
4
4
4
4
4
3
4
4
4
4
4
6
6
6
6
6
4
3
  100
-------
UAY
TtMH
3 A   5A   7A   PA   9B   9C   9D  STAB
101
101
101
101
101
101
101
101
101
102
102
102
102
102
102
102
102
102
102
102
103
103
103
103
103
103
103
103
103
103
103
103
103
104
104
104
104
104
104
104
8
9
10
13
14
16
17
Itt
21
6
7
6
9
10
15
16
1 /
18
21
22
5
6
7
8
9
10
14
15
J6
17
18
21
22
5
6
7
8
9
10
16
3.3
4.1
3.9
4.0
4.1
2.9
2.6
1.9
1.4
1 .3
3.7
3.3
3.2
3.7
4.7
4.3
3.4
2.0
I. a
.7
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2.1
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4.2
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6.4
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3
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6
4
4
4
4
4
4
4
4
4
4
5
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6
3
2
3
3
3
4
    101
-------
DAY  HR   WS
TtMF
3A   5A   7A   PA   9B   9C   9iJ   STAB
104
104
iU4
J04
105
JOb
10D
JOb
lOb
JOD
103
105
lOb
JOb
10t)
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JOb
105
JOb
J06
J06
106
106
106
106
J06
106
106
JO/
107
107
107
J07
107
108
108
108
108
108
108
17
18
21
22
0
1
2
5
6
7
9
10
13
14
16
17
18
21
22
0
1
5
6
7
8
9
JO
13
14
16
17
18
21
22
0
1
5
6
7
8
6.2
4.9
3.2
3.6
4.7
3.4
4.3
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2.b
2.1
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3.7
3.3
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4.6
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3.6
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61. -
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6
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3
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4
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6
5
5
5
5
4
4
4
   102
-------
DAY  HH    US  rtOIR THMF    3A   DA    /A   -9A   913   9C    90  STAb
108
108
108
109
10s>
109
109
109
109
109
109
109
109
109
109
109
109
109
109
109
1 10
1 10
1 10
1 10
1 10
1 10
1 10
MO
1 10
1 10
1 1 1
1 1 1
1 1 1
1 i 1
1 1 1
1 1 1
1 12
1 12
1 12
1 12
9
10
21
0
1
2
5
6
7
8
9
JO
J3
14
15
16
17
Ib
21
22
0
1
13
14
Ib
16
17
18
.21
22
0
1
2
8
9
10
8
13
Ib
16
1.3
1 .0
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1.7
2.1
3.1
3.2
2.0
2.7
3.2
3.d
3. 1
4.0
4.2
3.2
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1.1
1.2
1.0
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1 .5
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288.
309.
199.
8.
7.
30.
30.
26.
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38.
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160.
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279.
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1.7
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3.4
3.6
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3.2
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2.4
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1.8
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2.4
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4
3
6
6
6
6
6
3
3
4
3
3
4
4
4
4
4
4
6
5
6
6
4
4
4
4
4
4
6
6
6
6
:>
3
3
3
2
2
4
3
                               103
-------
DAY  HR   WS  WDIH TtMH   3A   5A   7A   9A   9B   9C   9D  STAB
12
12
13
13
13
13
13
13
13
13
13
14
14
14
14
14
15
Ib
15
15
16
10
16
16
16
16
16
16
16
J6
J6
16
16
17
17
17
17
17
17
17
17
18
6
/
8
9
JO
13
16
17
18
7
8
9
.10
22
14
13
17
22
5
7
8
9
10
13
14
15
16
1 7
18
21
22
5
7
8
9
10
13
14
.6
.7
.9
1.2
1.7
.6
.6
.3
3.9
.0
4.0
2.0
1.9
2.6
2.7
5.2
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2.0
1.7
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.6
.6
.2
.5
.6
.3
.6
2.5
2.0
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1.0
1. 1
2.2
1.3
2.7
273.
274.
227.
238.
235.
226.
209.
264.
107.
4.
107.
108.
108.
108.
108.
34.
232.
208.
201 .
213.
143.
167.
197.
198.
199.
139.
174.
184.
189.
Id9.
193.
209.
196.
122.
198.
218.
189.
209.
199.
213.
65.
63.
61.
65.
67.
70.
72.
70.
51.
49.
48.
44.
44.
44.
43.
40.
51.
50.
49.
41.
42.
44.
45.
43.
45.
46.
47.
46.
44.
44.
43.
43.
43.
42.
44.
46.
49.
50.
46.
50.
3.2
2.7
1.1
1.9
2.2
2.1
1.7
1.3
.9
.5
.6
.2
.2
.3
.3
.2
1 .d
3.2
3.5
1.9
2.5
4.2
2.6
1.6
1.2
1.6
2.0
2.1
2.3
1 .6
1. 1
1.6
1.3
2.4
2.9
2.4
1.8
1.1
1.9
1 .6
4.6
4.3
2.9
3.9
3.9
4.0
3.7
2.2
2.9
2.5
2.7
.3
.5
.5
.0
.4
3.5
5.5
5.7
3.4
5.1
7.3
4.6
3.3
2.6
2.9
3.3
3.8
4.0
2.9
1 .9
2.4
2.0
4.8
6.5
4.2
3.2
2.1
3.3
3.2
4.4
3.8
1.4
2.0
2.5
2.6
2.6
2.6
2.4
2.3
2.3
.1
.2
.3
.7
. 1
2.5
4.8
6.2
2.3
1.8
3.9 ,
3. I
1.8
1.4
2.3
2.7
4.2
5.2
3.6
2.3
2.1
1.9
1.8
3.5
3.2
2.6
1.7
2.1
2.5
./
.5
.7
.0
.1
.4
.4
.1
.3
.6
.6
.2
.4
.6
.9
. 1
2.6
1.2
2.4
.1
.2
2.9
1 .3
.9
.6
.9
.9
.7
.7
.3
.5
.7
• 3
.9
1.7
J.D
1.2
.7
1.0
.7
J./
1.6
.8
1.0
1 . 1
1 .4
1.2
1.2
1 .1
!.!>
1.3
.9
1.0
1 .2
1 .3
.0
2.2
2.1
2.4
1.7
1.2
2.4
1.8
.8
.6
.7
.8
.6
.6
.4
.6
.7
.7
.7
1.3
1.4
J.I
.7
.9
.7
.7
.5
.6
.1
. 1
. 1
.1
.2
.0
.2
.0
.6
.6
.7
1 .0
.4
1 .8
2. 1
2.4
.4
.8
2.0
.1.8
.9
.6
.7
.7
.7
.7
.6
.4
.6
.6
.5
1.1
1.2
.9
.6
.8
.9
.5
.3
.6
.1
. 1
.1
.8
1.2
.9
.9
.9
.6
.5
.3
.6
.3
1.2
1 .9
2.4
1.3
.6
1.7
1.8
.9
.4
.7
.8
.6
.6
.4
.6
.6
.6
.4
.8
1 .1
.9
.5
.8
.7
4
4
4
3
4
3
3
4
4
4
4
4
4
4
4
<+
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
6
4
4
4
4
4
4
4
                              104
-------
DAY  HR
TEMH   3A
5A
7A   9 A
9B
                      9C   9D  STAd
17
Id
18
18
18
19
J9
19
19
19
19
19
19
19
19
19
19
120
120
120
120
120
120
120
120
120
120
121
121
121
121
12 1
121
121
121
129
131
131
131
131
22
7
6
9
10
7
8
9
10
13
J4
15
16
17
18
21
22
0
1
8
9
10
13
14
15
16
22
0
1
2
5
7
8
9
10
8
6
7
14
15
1.2
3.7
3.1
3.2
2.4
5.d
4.5
5.2
4.9
4.6
4.6
4.6
.3
3.3
2.5
.2
.4
.8
1.3
1.5
.5
.4
3.0
2.7
3.7
3.5
1.0
.2
.3
.6
.0
.3
1.5
2.3
3.3
1.5
1.7
1.8
2.6
2.1
219.
225.
237.
241 .
249.
35b.
337.
353.
33b.
323.
323.
318.
5.
312.
321 .
7.
349.
318.
273.
16.
14.
337.
201.
195.
207.
207.
20b.
247.
220.
10.
127.
240.
234.
237.
223.
318.
282.
282.
282.
282.
45.
52.
53.
55.
57.
38.
40.
42.
44.
51.
53.
54.
55.
55.
53.
41.
39.
39.
42.
52.
55.
57.
60.
61.
59.
56.
46.
44.
43.
40.
38.
54.
60.
64.
66.
40.
48.
52.
61 .
62.
2.3
2.7
2.8
2.0
2.9
. 1
.2
.2
.1
.3
.2
.3
.3
.3
.3
3.3
4.0
3./
3.0
.3
.2
.2
.3
.6
.4
.5
.8
.8
2.1
2.5
1.7
1.7
1.8
1.5
1.3
.4
.2
.0
.3
.3
3.3
5.1
4.6
2.8
4.4
.6
.6
.6
.5
.3
.4
.4
.4
.4
.5
3.5
4.1
3.8
3.3
.0
1.2
1.0
2.7
2.8
2.6
2.8
3.0
2.3
2.4
2.6
2.2
2.9
3.2
3.2
2.9
1.3
.6
.5
.4
.4
2.2
2.5
2.7
2.9
3.8
1.6
1.3
1.0
.7
.8
.9
.9
.7
.8
.1.0
3.8
4.7
4.3
4.1
2.1
1 .9
1 .8
2.3
2.4
2.1
2.8
1.7
2.4
2.3
2.7
3.1
3.2
2.7
2.7
2.2
4.1
4.1
2.5
.8
1.2
1.7
1.0
1.3
1.4
2.2
2.0
I./
1.5
1.3
1.9
2.6
4.6
3.6
4.2
3.3
4.4
5.0
4.9
4.0
2.4
2.0
2.4
1.1
.9
.7
.4
1.2
2.2
1.9
3.1
3.4
2.8
1.6
1.2
.6
5.1
3.3
2.3
2.4
3.5
.5
.0
.2
.3
2.2
.2
.2
.d
.8
1.3
1.4
2.3
1.7
2.3
2.2
3.9
4.5
4.7
4.0
l.d
l.D
2.0
1.0
.9
.8
.4
1.1
2.2
2.2
2.8
3.3
2.5
1.7
1.0
.6
3.6
2.4
1.6
1.2
1. /
1.2
1.0
1.2
1.4
2.1
.3
.4
.2
.2
.5
.4
.7
.4
.7
.7
3.2
4.1
3.5
3.5
.7
.8
.8
1.0
.9
.7
.5
1.0
1.8
2.0
2.5
3.0
2.3
1.7
1.1
.5
2.3
1.0
.5
.3
.5
.0
.0
.2
.2
.8
.1
. .2
.2
.2
.3
.2
.2
.3
.3
.3
2.4
3.4
3.0
1 .0
.4
.4
.4
.9
.9
.8
.4
.9
1.3
1.6
1.7
2.7
2.1
1.7
.9
.6
J.8
.3
.1
.1
.2
4
4
3
4
4
4
4
4
4
4
4
4
4
4
4
4
4
6
4
4
4
4
4
4
4
4
6
6
5
6
6
3
3
2
2
3
4
4
4
4
105
-------
DAY  riR
3 A   5A   7A   9 A   9d   9C   9D  STAB
131
131
U2
132
132
.132
132
132
132
132
132
132
133
133
133
133
133
133
133
134
134
134
l->4
134
134
134
134
134
J34
135
135
135
135
135
135
135
135
135
135
135
.16
17
e
9
10
12
14
15
16
J7
21
22
0
1
4
6
7
b
9
12
13
14
15
16
17
18
20
21
22
0
1
6
9
12
13
J4
15
16
17
21
1 .D
J.3
2.D
2.2
2.7
2.4
2.J
1.5
l.J
.6
.7
1.9
1.7
2.8
J.d
3.2
4.5
4.5
5.3
5.5
3.6
5.1
D.3
5.2
4.4
2.9
.3
1.5
3.2
1 .6
1.3
3.5
3.9
4.3
J.d
3.6
3.0
1.7
.6
.8
230.
279.
282.
281.
2d3.
282.
281.
281.
279.
2/3.
275.
281.
286.
292.
278.
284.
300.
312.
329.
345.
343.
337.
336.
340.
343.
349.
21 .
7.
5.
7.
J8.
356.
356.
355.
359.
355.
353.
339.
338.
2J2.
62.
61.
63.
65.
67.
70.
69.
6/.
66.
64.
62.
64.
61.
61 .
D8.
61 .
63.
65.
6O.
60.
62.
63.
64.
64.
63.
OJ.
51 .
49.
50.
4b.
46.
50.
58.
62.
64.
65.
66.
67.
66.
52.
.2
.2
.4
.6
l.J
1.1
2.1
2.4
2.8
3.4
3.4
1.7
1.0
.4
.6
.9
.7
.4
.2
.3
.2
.1
.1
.1
.1
.2
2.2
2.8
.8
.7
.6
.2
.4
.1
.2
.1
.1
.2
.2
2.1
.5
.4
1 .1
1.0
1.2
1.9
3.4
4.2
5.1
5.3
3.5
1.7
1.2
.5
2.0
2.3
1 .3
.6
.4
,b
• J
.b
.4
.4
.4
.5
2.4
2.9
1 .1
.8
.8
.3
.4
.4
.5
.4
.5
.7
1.1
4.2
1 .3
1.2
2.6
2.0
2.1
1.7
2.4
3. 1
4.5
4.6
4.5
2.5
1.8
.6
2.2
3.9
3. 1
1 .8
1. 1
.8
.8
.8
.8
.7
.9
1.3
3.6
3.8
1.5
1.5
.4
.0
.9
.2
.4
.7
.9
2.J
2.7
2.3
3.D
3.2
3.0
2.6
2.4
1 .6
.7
.3
.7
.9
4.3
3.2
2.1
.9
1.4
3.7
3.0
2.3
1 .D
4.6
4.7
2.2
I./
1.7
1 .8
2.1
4.7
5.1
2.6
2.4
1.8
.8
1.4
1.7
2.0
2.3
2.1
2.3
2.9
1.0
1.7
1.8
2.2
2.0
1.5
.4
.6
.5
.7
.9
3.9
2.6
2.1
.7
1.4
2.9
2.3
1.6
1.0
.6
.7
1.0
1.0
.9
.9
1.4
4. 1
4.6
2.0
1.9
1.0
.4
.7
.0
.2
.4
.4
.8
2.3
.9
.3
.4
1.2
1.4
l.J
1.0
.6
.5
.8
.8
3.4
.9
.8
.5
.1
.9
.3
.7
.3
.3
.3
.2
.2
.2
.2
.4
3.1
3.3
.9
.9
.8
. 1
.2
.2
.4
.3
.5
.6
1.0
.6
.2
.2
.6
.9
.7
.7
.i>
.4
.7
.8
3.1
1.6
1.2
.4
.6
1.0
.7
.3
. 1
.2
.2
. 1
.1
.2
.1
.2
2.3
2.4
.7
.6
.6
.1
.2
.2
.2
.1
.3
.3
.3
.6
4
4
4
4
4
3
4
4
4
4
6
6
6
6
5
4
3
3
4
3
3
4
4
4
4
4
4
4
5
6
6
4
4
3
3
4
4
4
4
6
   106
-------
DAY  HR   WS   rfDIR  Tt*U>   3A   5A    7A    9 A    9B   9C   9D  STAB
135
136
136
136
136
136
136
136
136
136
136
136
136
136
136
137
137
137
137
137
137
137
137
137
137
137
137
137
137
138
138
138
138
140
140
140
140
140
22
1
6
7
8
9
J2
13
14
15
16
J7
18
20
21
0
6
6
9
12
13
14
15
16
17
18
20
21
22
0
1
6
7
12
13
15
16
17
.6
.2
.0
.1
.1
1.3
2.0
2.0
3.9
2.8
3.4
2.8
J.6
.6
.4
.1
.8
.3
.7
2.3
2.7
4.1
3.9
3.2
2.3
1.7
.8
1.1
1.5
1.7
1.5
.9
1.9
2.8
3.1
3.2
3.3
3.5
224.
203.
300.
286.
246.
249.
297.
290.
221.
214.
221.
222.
218.
209.
213.
241 .
243.
258.
289.
296.
240.
225.
226.
220.
215.
216.
208.
230.
251.
271.
284.
293.
308.
209.
213.
2J8.
209.
210.
51.
46.
51.
57.
63.
66.
72.
74.
69.
68.
68.
66.
63.
56.
56.
58.
60.
70.
74.
82.
83.
81.
79.
77.
74.
71.
64.
66.
67.
69.
70.
72.
74.
68.
68.
64.
62.
60.
.2.3
' 1.0
1.1
2.5
1.9
2.0
1.4
.3
1.5
2.0
1.7
1.3
1.2
2.4
2.0
1.7
4.8
3.5
2.0
.2
1 .3
1 .V
2.2
2.5
2.6
2.2
2.4
3.0
4.3
2.8
1.5
1.7
1.4
3.7
3.8
4.6
4.4
3.3
3.4
1.5
2.6
4.6
.3.5
3.3
2.2
1.5
2.6
3.3
3.4
2.6
2.6
3.0
2.7
1.7
6.9
4.9
3.2
1 .6
2.8
3.7
4.0
4.3
3.5
3.3
3.3
3.6
4.5
3.1
2.0
4.8
2.7
4.1
4.3
5.1
4.8
4.3
2.2
.9
5.3
6.7
4.2
2.9
2.3
1.9
2.5
3.9
4.3
2.9
2.6
2.9
2.5
1.5
3.7
4.1
3.2
2.4
3.2
3. /
4.4
5.8
3.9
3.9
2.9
3.0
3.9
3.4
2.1
5.4
5.3
2.2
2.3
3.2
3.9
3.0
.9
./
4./
5.6
4.1
2.7
2.9
2.9
.2
.3
.2
.0
.1
.8
.4
.8
1.9
3.4
3.2
3.3
2.5
.8
.6
.6
.4
.4
.8
.9
2.4
3.7
2.5
5.0
5.3
1.1
.9
.8
.7
.4
.8
.7
4.3 .
5.3 <
3.8 ,
2.6 <
2.5
2.0
1.2
1.3
I.I
.9
.9
1 .6
1.3
.8
1.9
3.2
2.1
2.1
2.1
.8
.6
.6
.4
.2
.7
.9
2.4 ,
3.5 .
2.1
4.3 .
4.5
.9
.9
.8
.6
.5
.8
.5
J.4
1.4
J.O
2.3
.8
.2
.1
.3
.1
.0
.1
.7
.3
.9
.7
2.7
>. 1
.8
.7
.8
.6
.4
.4
.2
.6
.9
2.3
3.0
1.8
3. 1
3.1
1.0
1.0
.7
.6
.4
.6
.5
2.7
3.5
2.3
2.1
1 .4
.8
1.1
1.2
1.1
.9
1.0
1.7
1 .3
.9
1 .7
2.4
1 .5
1 .3
1 .2
1.7
1.5
1.5
1.5
1.2
1.8
2.1
1.9
2.3
1.5
1.7
1.4
.9
.8
.8
.6
.5
b
5
4
4
4
4
3
J
4
4
4
3
4
5
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
4
4
4
4
4
4
4
                              107
-------
                                Appendix II


     Appendix II contains the 147 dichotomous sampler runs used for modeling.
The data comes in blocks of 13 lines.  The first number in each line is the
run identification number.  It is the month and day (October, 1976 to May,
1977), followed by whether it was the first or second run of the day.  On
the first line the run number is followed by the wind direction in degrees,
using the same reference system as the CO data; next is the wind speed in
m/sec.  Then the temperature is listed in °C.  The next two numbers are the
times of the day which bracket the sampling interval.  The last four numbers
are the traffic estimates in vehicles per hour, for westbound light duty
and heavy duty, and eastbound light duty and heavy duty.  The next twelve
lines are the data for the six pollutants.  The first line is the fine
fraction, while the second is the coarse.  The six are:

                           1  particulate weight
                           2  sulphate
                           3  sulphur
                           4  lead
                           5  chloride
                           6  nitrate

The unit are in ^g/m^.  A -888 indicates that the p ."-'tion was never sampled
or the filter not analyzed, while a -999 indicates the analysis yielded an
unreportable result.  A minus before any other number indicates the result
was reported as less than that value.  The columns correspond to the
following positions:  3A, 5B, 5A, 9A, 9B, 11A, 11B, 12A, 13A.
                                   108
-------
10081
.10081
10081
10081
ICXJ8J
10081
JOO81
10081
10081
1008)
J008I
10081
10081
10142
10142
10142
10142
10142
10142
10142
10142
JOJ42
10142
10142
10142
10142
10151
10151
10151
10151
10151
IOJ51
10151
10151
10151
10151
10151
10151
10151
189. 2.07 19.1 9-1 0 MUD 2913 435 1921 261
1
1
2
2
3
3
4
4
5
5
6
6
3
1
1
2
2
3
3
4
4
5
5
6
6
-888.O-888.0 65.0 46.0 37.0 48.0 30.0 41.0 39.0
-868.0-888.0 28.0 23.0 21.0 32.0 20.0 30.0 21.0
-888.0-88d.O 8.9 8.7 8.9 8.6 d.9 8.2 d.6
-888.0-888.0 .3 .6 1.1-999.0 .6 1.6 1.0
-88d.O-88d.O 2.9 3.2 2.9 3.1 3.2 3.0 3.0
-88d. 0-888.0 .2 -.1 -.1 .2 -.1 .2 -.1
-888.0-888.0 6.9 1.0 1.0 -.7 1.0 .9 1.5
-888.O-888.0 -.8 -.6 -.6 -.7 -. / -.7 -.6
-888.0-88d.O 1.3 .8 1.0 J .0 1.0 1.0 1.1
-888^0-888.0 2.4 .9 1.0 1.3 1.2 1.3 1.1
-888.0-883.0 .3 .b .3-999.0 . 2-999. O-999.0
-888.0-88d.O 1.4 .3 1.3 .7 .9 1.8 1.1
17. 5.44 12.3 14*30 16^20 2737 4093850 5/5
198.0-888.0 11.0 2J.O 9.0 12.0 12.0 '3.0 6.0
19.0-88d.O 19.0 3.0 9.0 6.0 26.0 Jb.O 19.0
-999.0-888.0 1.5 1.3 1.1 1.2 1.2 1.3 .9
.2-88d.O-V99. 0-999. 0-999.0 .3 .2 .4 .2
-.1-888.0 .4 .3 .2 .2 .4 .5 .4
-.l-86d.O -.1 -.1 -.1 -.1 -.1 -.1 -.1
-.8-88d.O 1.1 5.0 2.9 2.d .9 2.8 1.9
-.8-888.0 -.7 -.7 -.8 -.8 -.9 -.9 1.2
.5-888.0 .4 1.1 .6 .6 .5 .4 .5
.4-888.0 .4 .5 .6 .5 .6 ./ .7
-999. 0-888. 0-999. O- 999. 0-999. 0-999. 0-999. 0-999. 0-999.0
-99*. 0-888. 0-999. 0-999. 0-999. 0-999.0 .3-999.0-999.0
239. 1.53 3.0 7*20 9« 0 454b 6dO 2381 356
1
1
2
2
3
3
4
4
5
5
6
6
22J. 0-888.0 66.0 54.0 27.0 42.0 32.0 36.0 21.0
18.0-888.0 33.0 18.0 9.0 22.0 22.0 27.0 12.0
-999.0-888.0 5.2-999.0 6.3 5.2 5.4 4.9 5.1
-999. 0-88d. 0-999. 0-99V.O . 5-999. O-999.0 .6 .6
,7-88d.O 1.6-999.0 J.8 1.7 1.7 2.2 l.d
-.1-888.0 -.J -.1 -.1 -.1 -.1 -.1 .1
-.9-88d.O 10.0-999.0 1.8 2.7 2.4 2.4 2.7
,9-8dd.O 1.0 1.0 -.9 1.0 .9 -.8 .9
.9-88d.O 1.8-999.0-999.0 .8 .7 .9 .7
.4-888.0 1.2 .5 .8 1.5 1.1 1.7 2.6
-999.0-888.0 .5-999.0-999.0 .5 .7 .5 .6
.5-88d.O-999.0 .2 .3-999.0 .4-999.0 .3
109
-------
IOJ8J    333.    4.74    7.8  14*30  17t  0  2/12  405 3987  596
1018!   I   -888.0  16.0  26.0  41.0  IV.0   6.0-999.0  17.O-888.0
JOJ8I   I   -888.0  lo.O  29.0  26.0  22.0  19.0  II.0   6.0-d88.0
10161
10181
10161
10181
10181
10181
10181
10181
10181
10161
1OJ9I
10191
10191
1019J
1019J
10191
10191
10J9I
10191
10191
10191
10191
10191
2
2
3
3
4
4
5
5
6
6

1
1
2
2
3
3
4
4
5
5
6
6
-888
-886
-886
-888
-86d
-886
-888
-886
-888
-888
92.
-88d
-886
-88d
-883
-888
-88d
-883
-888
-886
-886
-886
-88d
.0 1
.0
.0
.0
.0 -1
.0 -1
.0
.0
.0
.0
1 .10
.0 32
.0 13
.0 1
.0-999
.0
.0
.0 2
.0
.0
.0
.0
.0
.7-999.0
.4
.6
.1
.0
.0
.6
.5
.2
1.4 1.5
.9- 999. 0-999.0
.5
-.1
.8
-.7
.7
.7
.2
.5 ,t>
-.1 -.1
5.3 2.2
-1.0 1.3
.9 .4
.5 .7
• 2-9V9.0
.3-999.0-999.0-999.0

.0
.0
.6
6.2
46.0
13.0
1.8
.U-999.0
.6
.1
.9
.9
.6
.3
.1
.7
-.1
5.0
-.9
1.0
.4
.3
.2-999.0
8*30 11*30
24.0 20.0
12.0 10.0
.3 1.9
.4 .D
.8 .6
-.1 -.1
6.3 1.9
-.6 -.9
.6 .4
.5 .6
.2-999.0
.2-999.0
1.8
.4
.6
.1
2.5
1 .0
1.4
.6
.9
.2
.6
-.1
2.3
-1 .2
.6
.5
1 .
*
•
** •
2.
1.
.
.
.2-999.0
.3-999.0
2915
16.0
12.0
1.6
436
20.0
10.0
2.2
1929
19.
10.
2.
.2-999.0-999.
.6
-.1
-.9
-.6
.6
.3
.1
.1
.6
-.1
1 .4
1 .3
.5
.3
.2
.2
.
-.
1 .
™ •
•
•
•
-999.
3-803
3-688
5-686
1-888
0-668
3-886
D-888
5-888
2-688
2-888
2db
0-638
0-d83
2-d8ti
0-Jdd
7-388
1-888
2-668
5-888
5-688
4-888
2-888
0-388
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0

.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
10192   210.   1.73    7.3  12*50  16*20  2376  355 2680  400
10192  I     33.0  45.0-999.0  20.0   8.0  13.0  14.0-888.0-686.0
10192  1'    30.0  31.0  23.0  20.0  12.0  29.0  19.0-888.0-836.0
10192  2     1.7   1.8   1.7   1.4   1.5   1.8   1.4-888.0-888.0
10192  2  -999.O-999.0    .3    .2    .2    .4-999.0-888.O-388.0
10192  3      .6    .7    .6    .6    .6    .7    .5-888.0-888.0
10192  3     -.1    -.1    .1   -.1    .1   -.1   -.1-888.0-868.0
10192  4     4.5   3.3   6.7    .9   -.8   1.0    .9-888.0-888.0
10192  4     1.1    1.2   1.1   -.7    .3  -1.0    .9-888.0-888.0
10192  5      .6    .7   J.0    .3    .6    .4    .4-888.0-688.0
J0192  5      ./    .6    .6    .4    .4    .6    .6-888.0-888.0
10192  6      .2    .4    .3    .3    .3    .3    .2-888.0-888.0
10192  6  -999.0-999.O-999.0    .2-999.0-999.0-999.0-888.0-686.0
                              110
-------
10201
.10201
10201
10201
10201
J020J
10201
10201
10201
10201
10201
10201
10201
1021
1021
1021
1021
1021
1021
1021
1021
1021
1021
1021
J02I
1021
10212
10212
10212
10212
10212
10212
10212
10212
10212
10212
10212
10212
10212

1
1
2
2
3
3
4
4
5
5
6
6

1
1
2
2
3
3
4
4
5
5
6
6

1
1
2
2
3
3
4
4
5
5
6
6
40. 1.92 JO. 2 9HO II 120 2802 419 1916 2d6
37.0 42.0 63.0 43.0 24.0 20.0 1 9.0-888.0-d88 .0
16.0 12.0 21.0 20.0 18.0 9.0 8.0-888.0-888.0
3.1 3.1 3.5 3.1 2.d 3.1 3.2-888.0-d8d.O
-999.0 .4 .5-999.0 .4 .4 .5-888.0-388.0
J.3 1.2 1.4 1.2 1.0 1.2 1.3-888.0-888.0
.2 .2 .1 .2 .2 .1 . 1-888. 0-38d.O
5.2 /.I 9.1 4.8 3.0 1.7 1.3-888.0-888.0
.9 -.9 -.7 -.8 -.6 -.9 -.8-888.0-888.0
1.0 1.0 1.3 J .0 .8 .7 .5-888.0-388.0
1.3 1.4 l.J 1.4 1.2 1.3 1.3-888.0-888.0
.2-999.0 .4 .2 .2-999.0 .3-888.0-338.0
.6 .5 .5-999.0 .6 .6 .8-888.0-888.0
103. 6.81 11.4 9* 0 11 120 2d68 428 1921 237
38.0 27.0 25.0 33.0 18.0 22.0 22.0-888.0-888.0
4.0 17.0 13.0-999.0 11.0 11.0 11.0-888.0-888.0
6.0 4.9 5.1 4.8 4.6 4.6 5.3-888.0-3d8.0
-999.0-999.0-999.0-999.0-999.0-999.0 .4-888.0-888.0
2.1 2.1 2.0 1.9 1.9 1.9 2.1-888.0-888.0
.1 .1 -.1 -.1 -.1 -.1 .1-888.0-888.0
-.8 -*7 1.5 3.5 1.5 1.9 I .4-883.0-388.0
-.3 -.7 -.8 -.8 -.8 -.8 -.8-888.0-838.0
.5 1.0 .7 .4 1.3 .6 .7-888.0-838.0
.3 .4 .6 .3 .4 .4 .5-888.0-388.0
.1 .2-999.0 .1-999.0-999.0 .2-888. O-388.0
-999. 0-99^. 0-999.0 .2-999.0-999.0-999.0-888.0-888.0
J03. 5.66 IJ.7 J3I30 Ibi50 2554 382 J139 469
33.0 19.0 43.0 39.0 33.0 40.0 17.0-888.0-886.0
19.0 7.0 22.0 14. 0 12.0 10.0-999.0-888.0-888.0
7.8 .7 6.6 7.3 6.8 7.1 7.0-888.0-888.0
.4-999.0 .5-999.0-999.0 .4-999.0-888.0-888.0
2.7 .b 2.7 2.4 2.4 2.5 2.7-888.0-888.0
.2 -.1 .2 -.1 -.1 -.1 .1-888.0-888.0
-1.0 .9 4.8 4.9 2.5 3.0 2 . 7-888. 0-8dd .0
-.6 -.9 -.9 1.2 1.0 1.0 -.7-888.O-388.0
.3 .4 .5 .6 .7 .4 .8-888.0-888.0
.3 .3 .7 .5 .5 .5 .8-888.0-888.0
-999.0-999.0 .2 .2 .1-999.0 .2-888.0-888.0
-999.0-999.0-999.0-999.0-999.0-999.0-999.0-888.0-388.0
111
-------
10221
10221
10221
10221
10221
10221
10221
10221
10221
10221
10221
10221
J0221
1092
1092
1092
1092
1092
1092
1.092
1092
1092
1092
1092
1092
1092
101
101
101
101
101
101
101
101
. 101
101
101
101
101
29J. 5.83 6.3 8«50 IH30 2915
1 37.0 33.0 38.0 43.0 26.0 37.0
1 25.0 Ib.O 14.0 J 8. 0-999.0 23.0
2 6.3 6.1 5.9 6.4 6.2 6.7
436 1929 238
38.0-888.0-888.0
14. 0-88d. 0-888.0
6.7-888.0-888.0
2 -999.0-999.0-999.0-999.0 .4-999.0-999.0-888.0-888.0
3 2.2 1.8 2.1 2.1 2.2 2.3
3 .1 -.1 .2 .2 .1 -.1
4 -.9 - .0 4.3 5.9 4.5 3.2
4 -.9 - .0 -.8 -.8 1.4 -.9
5 1.0 .6 .9 .8 .8 .7
5 .9 .0 .8 .6 .4 .5
6 -999.0 .0 .6 .* .4 .6
6 -999.0 .2-999.D-999.0 .3-999.0
234. 1.85 J.4 14120 16«30 2736
1 4J.O 49.0 48.0 30.0 23.0 19.0
1 80.0 14.0 96.0 35.O 49.0 19.0
2 -999.0 4.1 3.7 3.6 3.1 3.5
2.2-888.0-888.0
.1-888.0-888.0
2.1-888.0-888.0
-.9-888.0-888.0
.7-888.0-888.0
.9-888.0-888.0
.5-888.O-888.0
..J-888.O-888.0
409 3820 571
34.0 42.0-888.0
J 6. 0-999. 0-888.0
J.6 .7-888.0
2 21.5-999.0 17.9 7.1 9.2 2. 8-999. 0-999. 0-d8b.O
3 1.0 .2 1.3 1.2 1.1 1.2
3 6.3 .1 4.3 2.1 2.7 1.1
4 3.J 7.1 7.3 -1.0 -1.0 .9
4 1.9 -.6 2.7 1.3 -.7 .6
5 -999.0 1.2 1.7 1.0 .7 .5
5 .7-999.0 1.5 .6 .5 .6
6 -999.0 .9-999.0 .8-999.0-999.0
6 .9-999.0 1.5-999.0-999.0-999.0
270. 1.06 1.1 8*10 9«40 3d45
1 81.0 84.0 92.0 61.0 69.0 5d»0
1 49.0 68.0 64.0 199.0 53.0 122.0
2 8.2 7.7 9.0 6.6 7.1 7.5
2 -999.0 4.4 18.8 29.9-999.0 18.3
3 2.8 2.2 2.1 J.8 1.9 2.3
3 3.2 1.6 5.1 7.4 5.1 5.1
4 4.8 5.3 8.1 2.3 2.9 3.1
4 7.3 7.8 1.2 10.6 -1.0 1.7
5 4.7 4.7 6.1 3.4 2.9 3.7
5 1.5 1.0 1.2 2.5 1.0 .8
6 2.4 2.2 2.7 1.8 1.8 2.2
6 1.3-999.0 2.3 2.4-999.0-999.0
1.4 .^-388.0
.2 1.0-888.0
-.9 -1.0-888.0
.6 2.0-388.0
.5 .6-888.0
.6 .7-888.0
. 7-999. O-888.0
.3-999.0-888.0
5/4 225D 337
50.0 94.0-388.0
54.0 49.O-888.0
7.2 4.2-888.0
9.1 17.4-888.0
2.1 1.2-888.0
3.2 5.0-888.0
1.7 -1.6-888.0
3.8 1.1-888.0
3.3 2.7-888.0
2.4 J. 1-888.0
2.0 1.9-888.0
2.6 2.2-d88.0
112
-------
1
1
1
1
1
1
J
1
1
1
1
1
J
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
201
201
201
201
201
201
201
201
201
201
201
201
201
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2092
2092
2092
2092
2092
2092
2092
2092
2092
2092
2092
2092
2092

1
1
2
2
3
3
4
4
5
5
6
6

1
1
2
2
3
3
4
4
5
5
6
6

1
1
2
2
3
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4
4
5
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6
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305.
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8>30 12110 2870 429 1992
0 60.0 77.0 46.0 28.0 46
0 28.0 29.0 29.0 18.0 32
3 5.5 6.1 b. 1-999.0 4
0-999.0 .4-999.0 .6-999
7 .8 1.5 1.5 1.6 1
1 .6 -.1 -.1 -.1
b 5.0 3.1 1.7 2.0 2
0 -.4 .8 .4 -.4
9 .6 .6 .5-999.0
6 .3 .4 .3 .3
4 .3 .6 .6-999.0
5 .4 .5 .4 .4
13»bO I6«rj 2664 398 3453
0 42.0 2.0 27.0 43.0 29
0 23.0 16.0 52.0 30.0 33
0 5.0 4.8-999.0-999.0 5
0-999.0-999.0-999.0-999.0-999
6 1 .5 1 .4 1 .4 1 .4 1
1 -.1 -.1 -.1 -.1
6 -.7 -.7 -.6 -.7
0 -./ -.7 -.6 -.7
2 .6 .7 .7 .4
7 .6 .5 .7 .7
4 .4 .6 .7-999.0
3-999.0 .4 .5-999.0-999
13120 lb*30 2488 372 2928
0 23.0 7.0 9.0 9.0 8
0 19.0 2.0 11.0 2.0 8
4 2.8-999.0 2.3 2.2 2
0-999.0-999.0-999.0 .4-999
8 .8 .3 .8 .3
1 -.1 -.1 -.1 -.1
9 4.3 1.7 2.1 1.7 2
9 -.8 -.8 -.9 -.9
0 1.4 1.8 1.1 1.0 1
9 J.7 1.6 1.6 1.0 1
2-999.0-999.0-999.0-999.0
O- 999 . 0- 999 . 0-9 99 . 0- 999 . 0- 9 99
298
.0-888
.0-888
.9-388
.0-888
.b-388
.1-888
.2-888
.4-888
.4-888
.5-888
.5-888
.5-888
516
.0-888
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.1-388
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.3-888
.O-888
438
.0-888
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.3-388
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.8-388
.1-888
.2-888
.7-388
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.2-388
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2012   296.   6.24   -3.0  J4i 0  J7i 0  267b  400 3762  562
20J2  I     17.0  49.0  15.0  3b.O  26.0  24.0  19.0  24.0-868.0
2012  I   -883.0-888.0-888.0-888.0-886.0-883.0-886.0-888.0-888.0
20.12  2     5.5   6.3   6.0   b.8   5.6   5.5   6.0   6.2-888.0
20J2  2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2012  3     J.5   J.7   J.6   J.5   J.6   1.5   1.7   1.4-888.0
2012  3  -888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
20J2  4     -.5     .6     .9   4.1   2.4   2.0   2.4   1.9-bdb.O
2012  4  -888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
2012  5       .5     .6     .6   1.1     .6     .8     .6     .8-388.0
2012  5  -883.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-886.0
20J2  6  -999.0     .3-999.0    .3     .3-999.0-999.0-999.0-388.0
2012  6  -888.0-888.0-888.0-868.0-888.0-888.0-888.0-888.0-888.0
2021   309.   5.42   -4.6   8140   I1«3J  2968   444  1961   293
2021   1    24.0   19.0   9.0  30.0   16.0  23.0   20.0  22.0-888.0
2021   I  -888.0-b38.0-388.0-888.0-888.0-883.0-888.0-888.0-888.0
2U2J   2      1.4   3.1   3.4   4.1   3.7    3.1    3.8   3.9-888.0
202J   2  -883.0-863.0-888.0-86B. 0-888.0-868.0-868.0-888.0-888.0
2021   3       .9     .9     .9     .8     .9     .9     .9    .9-383.0
2021   3  -888.0-888.0-888.0-888.0-838.0-888.0-883.0-888.0-388.0
2021   4     -.4   -.4     .7   3.2    1.6    2.2    1.1   1.7-838.0
2021   4  -888.0-888.0-388.0-888.0-888.0-888.0-883.0-88b.0-888.0
2021   5       .7     .4     .5   1.0     .7     .6     .6    .7-388.0
2021   5  -883.0-883.0-388.0-883.0-888.0-888.0-888.0-888.0-888.0
2021   6  -999.0-999.0     .9     .3     .3     .3-999.0    .2-888.0
2021   6  -888.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-388.0
2022   317.    5.37    -1.6   13140   I6»JO  2629  393 3379  50D
2022   1     J4.0 '  J4.0  13.0  11.0  26.0  i5.0-888.0-888.0-838.0
2022   I  -888.0-883.0-888.0-888.0-888.0-88d. 0-888.0-888.0-388.0
2022   2       .7   2.0   2.1    2.4   1.8   1.8-883.0-888.0-888.0
2022   2  -883.0-886.0-888.0-888.0-888.0-888.0-838.0-888.0-888.0
2022   3       .5     .5    .6    .5    .4    .6-883.0-886.0-688.0
2022   3  -888.0-883.0-888.0-86b.0-888.0-888.0-883.0-888.0-388.0
2022   4      -.5   -.6   -.6   3.4    .9   1 .4-866.0-886.0-388.0
2022   4  -888.0-886.0-868.O-886.0-888.0-888.0-888.0-888.0-388.0
2022   5       .6     .7    .6    .9    .6    .6-888.0-888.0-838.0
2022   5  -888.0-886.0-888.0-888.0-888.0-688.0-866.0-888.0-388.0
2022   6  -999.0     .4-999.0    .2-999.0-999.0-883.0-888.0-680.0
2022   6  -883.0-883.0-888.0-888.0-888.0-880.0-888.0-888.0-868.0
                               124
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2031   240.   4.11   -1.8   8i20   111 0   3234   483  2046   306
2031  1     32.0   ID.O  51.0  26.0  27.0   17.0   31.0-888.0-388.0
2031  I   -888.0-888.0-888.0-88d.0-888.0-888.0-883.0-888.0-388.0
2031  2     6.7   6.7   7.3   O.3   2.5   5.3    7.3-888.0-838.0
2031  2  -888.0-8 8d. 0-888.0-888.0-838.0-888. 0-888. 0-888.0-888.0
2031  3     1.9   1.9   2.0   2.0   2.0   1.8    2.O-8d8.0-388.0
2031  3  -888.0-888.0-388.0-888.0-888.0-888.O-880.0-838.0-388.0
203J  4     2.3   2.4   5.5   -.6   -.6   -.5     .8-888.0-888.0
2031  4  -888.0-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2031  5      .9   1.2   1.4     .7     .6     .6     .6-888.0-888.0
2031  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2031  6      .9   l.b   1.5    1.0     .8     .7     .8-888.0-388.0
2031  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2081   340.   4.36   -b.2    8»bO   11 UO   2987  446 1941   290
2081  1     29.0-888.0  24.0  38.0   25.0   31.0  23.0-888.0-388.J
2081  1   -8d8.O-888.0-888.0-888.0-888.0-888.0-88ci.0-888.0-888.0
2081  2     4.5-888.0   4.2    4.d    4.3    4.1    4./-888.0-838.0
2081  2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2081  3     1.3-880.0   1.3    1.3    1.4    1.3   I.6-888.O-888.0
2081  3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2081  4     -.5-888.0   -.5    4.4    2.0    2.2   1.9-888.0-888.0
2081  4  -8£3.0-883.0-388.0-883.0-888.0-888.0-888.0-888.0-388.0
2081  5     1.9-888.0     .8    3.0     .9     .9    .6-888.0-388.0
2081  5  -888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2081  6       .2-883.0-999.0     .3     .2-999.O-999.0-888.0-386.0
2081  6  -883.0-88d.0-388.0-888.0-888.0-883.O-888.0-888.0-838.0
2082   339.    3.80    -1.7-  JU50  14*10  2141   3202136  319
2082   I     19.0-883.0  17.0   35.0  26.0  23.0  21.0-888.0-388.0
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2082   2     3.6-88d.O   3.9    3.5   4.0   3.2   3.5-888.0-388.0
2082   2  -888.0-888.0-388.0-888.0-888.0-888.0-888.0-888.0-888.0
2082   3      I.3-888.0   1.2    I.I   1.3    .9   1.3-888.0-888«0
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2082   4     -.5-88d.O    .5    3.6   1.3   1.9   1.6-888.0-388.0
2082   4  -888.0-883.0-888.0-86fa.0-888.0-888.O-888.O-888.0-388.0
2082   5       .7-883.0    .7    1.9   1.3    .8    .7-888.0-388.0
2082   5  -838.0-883.0-888.0-888.0-888.0-888.0-883.0-888.O-388.0
2082   6  -999.0-883.0-999.0     .I-999.O-999.0-999.0-888.0-388.0
2082   6  -888.0-883.0-888.0-888.0-888.0-888.0-388.0-888.0-388.0
                              125
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2091   227.   2.71
2091  I    71.0-883
2091  I  -838.0-888
2091  2    12.8-886
209J  2  -836.0-886
2091  3     4.J-88d
2091  3  -863.0-868
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2151   316.   4.13    2.0   »i 0  JH20  2d66  426  1921  2d7
2151  1     36.0  43.0  38.0  54.0  42.0  51.0  45.0-888.0-d8d.O
2151  I   -883.0-888. 0-888.0-888.0-888.0-888. 0-8dd.O-888.0-dd8.0
2151  2  -99V.0  10.3  10.9   11.3   8. /  M.I  1 I . 7-888.0-dd8.0
2151  2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2151  3     3.5   3.2   3.5   3.6   3.1    3.8    3.6-888.0-888.0
2J51  3  -888.0-888.0-388.0-888.0-888.0-888.0-88d.0-888.0-888.0
2151  4      .8    .d   1.3   4.4   1.6   2.6    2.3-888.0-888.0
2151  4  -888.O-88d.0-888.0-888.O-838.0-88d.0-888.0-888.O-8d8.0
2J5J  5      .7   i.l   1.2   1.3   1.0   1.1    1.4-888.0-888.0
2151  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2151  6     1.0    .7   1.2   1.4   1.1     .8    1.5-888.0-888.0
2151  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2152   324.   5.27     1.6   I2«50   I5«30  2404  3592782  416
2152  I     17.0  24.0  23.0  26.0  23.0  27.0  17.0-888.0-388.0
2152  1   -88d.0-88d.0-888.0-888.0-888.0-88d.0-88d.0-888.0-888.0
2152  2     5.0   4.7   5.3   5.4   4.9   6.0-999.0-888.0-888.0
2152  2  -88d.0-888.0-888.0-888.0-888.0-8fad.0-8dd.0-888.0-888.0
2152  3     1.6   1.4   1.6   1.7    1.3   1.5    1.2-888.0-88d.O
2152  3  -836.0-88d.0-d88.0-888.0-888.0-888.0-888.0-888.0-ddd.O
2152  4     -.4   -.4   -.4   J.9     .5   1.7    1.0-888.0-888.0
2152  4  -888.0-888.0-888.0-888.0-888.0-88d.0-88d.0-888.0-dd8.0
2152  5       .7     .9     .9   1.0     .8   1.0-999.0-888.0-888.0
2152  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
2152  6  -999.0     .2     .1   1.5-999.D   1.0-999.0-888.0-888.0
2152  6  -88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-d88.0
2161   332.   2.53   -7.2    8i50   IUJO   2987   446 1941   29J
2161   1    39.0  41.0   29.0  36.0   29.0   34.0   25.0-888.0-888.0
2161   1  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-d88.0
2161   2  -999.0   4.7    5.5    5.6    5.6    2.2    5.6-888.0-888.0
2J6J   2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2161   3      1.8     .6    2.0    5.2    2.1    2.8    2.'1-888.0-888.0
2J61   3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2161   4     -.5     .6    2.0    3.2    2.1    2.8    2.1-888.0-ddd.O
2161   4  -88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2161   5       .9   J.I    1.1    1.2    1.0     .6     .9-888.0-888.0
2161   5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2161   6  -999.0     .5-999.0     .3     .3-999.0-999.0-888.0-388.0
2J61   6  -888.0-888.0-888.0-888. Q-888. 0-888. 0-888.0-888.0-888.0
                              127
-------
2162   3JO.   3.45   -5.2  M 150  I4HO  2141  3202138  31V
2162  1    IV.0  33.0  18.0  38.0  24.0  2/.0  24.0-888.0-888.0
2162  I  -888.0-888.0-888.0-888.0-888.0-888.O-883.O-888.0-888.0
2)62  2     4.9   4.8   5.1   5.2   5.0   4.0   5.J-888.0-888.0
2162  2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2162  3     J.5   1.4   1.6   1.8   1.6   1.5   1.6-888.0-888.0
2162  3  -888.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0
2162  4      .5    .8    .8   3.5   1.9   2.0   J.6-888.0-888.0
2162  4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2162  5     J.O   J.I   J.O   1.3   J.O   1.0     .9-838.0-888.0
2162  5  -888.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0
2162  6  -99V.0    .5    .2    .4     .3     .3     .3-888.0-888.0
2162  6  -888. 0-888. 0-888. 0-888. 0-888. 0-888.0-888.0-888. 0-888.0
2171   330.   5.93   -7.8   9«20   J2HO  2588  387  1908   28b
2171  1    22.0  21.0  21.0  30.0   15.0  33.0-888.0 33.0-888.0
21/1  1  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2171  2     3.7   4.5   4.5   4.8   3.6   4.4-888.0   4.3-888.0
2171  2  -888.0-888.0-888.0-888.Q-888.0-888.0-888.0-888.0-888.0
2171  3      1.5   1.6   1.5   1.3   1.5   1.3-888.0   1.5-888.0
217J  3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2171  4     -.3   -.4   -.3   3.0     .9   2.0-888.0   l.6-d8b.O
217)  4  -888.0-888.0-888.0-888.0-888.0-888.0-88d.0-888.0-888.0
2171  5       .7     .8     .7     .7     .4     ,6-88d.O   1.0-888.0
2171  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2171  6  -999.0     .6-999.0     .8     .2     .3-888.0-999.0-388.0
2171  6  -888.0-888.0-888.0-888.0-888.0-388.0-888.0-888.0-888.0
 2181     19.     .89    -7.7    7i  0   9*30  4383  O55 2284  341
 2181   1    32.0  41.0  41.0  71.0  51.0  41.0  58.0  55.0-888.0
 2181   1   -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
 2181   2      7.1    7.5   6.1    7.3   5.7    .1   2.7   7.4-888.0
 2181   2   -888.0-888.0-888.O-888.0-888.0-888.0-888.0-888.O-888.0
 2181   3      2.4   2.b   2.3   2.4   2.0   2.1   2.1   2.3-888.0
 2181   3   -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
 2181   4      1.6   2.3   3.6   8.9   4.8   4.4   4.1   4.0-888.0
 2181   4   -888.0-888.0-888.0-888.0-888.0-388.0-888.0-888.0-888.0
 2181   5       .7   1.1    .8   1.8   I.I   J.O   1.0    .9-388.0
 2181   5   -888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
 2181   6       .3-999.0-999.0    .4-999.0    .3-999.0    .1-888.0
 2181   6   -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
                             128
-------
2221   225.   5.84    2.3  J3i20  J5«20  2461  368 2814  420
2221  1     32.0  46.0  43.0  37.0  32.0  34.0  33.0  35.0-88d.O
2221  I   -888. 0-888. 0-888.0-888.0-888.0-886.0-683.0-888.0-d8d.O
2221  2     5.9   d.O   6.4   6.3   6.3   6.5   5.1   6.4-688.0
2221  2  -868.0-886.0-888.0-888.0-888.0-886.0-886.0-888.0-886.0
2221  3     2.2   2.3   2.2   2.1   2.1   2.2   2.0   1.6-8b8.0
2221  3  -888.0-888.0-888.0-868.0-888.0-686.0-888.0-888.0-680.0
2221  4     1.7   2.1   3.8   -. /   -.7   -.7   -.6   -.7-888.0
2221  4  -888.0-886.0-888.O-868.0-888.0-888.0-888.0-888.0-868.0
2221  5     J.I   2.6   1.5   1.7   1.6   1.4   1.1   1.7-688.0
2221  5  -888.0-808.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2221  6     J.4   2.7   1.5   1.8   J.4   1.6   1.4   2.0-886.0
2221  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2231    48.   2.76    6.5   8«30   NUO  298 /   446  I94J  290
2231  J    66.0  64.0  79.0  99.0  88.0  89.0   96.0  87.0-688.0
2231  1  -886.0-868.0-888.0-886.0-686.0-688.0-866.0-868.0-688.0
2231  2    15.1  18.0  18.6  16.1  17.4  16.1   12.6   17.6-886.0
2231  2  -883.0-863.0-888.0-888.O-868.0-888.0-868.0-888.0-686.0
2231  3     4.6*   D.8   6.1   4.9   5.4   D.O    4.4    5./-6dd.O
2231  3  -868.0-866.0-86b.0-888.0-888.0-88d.0-866.0-688.0-68c5.0
2231  4     I./   2.0   2.6   5.2   3.8   3.8    3.2    3.9-dda.O
2231  4  -888.0-888.0-688.0-888.0-868.0-888.0-888.0-888.0-888.0
2231  5     1.5   2.3   1.5   3.7   2.5   1.7    1.5    1.8-688.0
2231  5  -888.0-888.0-888.0-888.0-888.0-886.O-888.0-888.0-866.0
2231  6     1.9   3.8   2.3   2.5   1.9   2.J    2.0    2.1-888.0
2231  6  -868.0-888.0-888.0-888.0-888.0-886.O-888.0-888.0-888.0
2232    62.   2.78     8.6   II i50   14HO   2141   320 2138  31V
2232   I    68.0  84.0   79.0   97.0   85.J   86.0   92.0  8^.0-868.0
2232   1  -888.0-886.0-888.0-886.0-888.0-888.0-888.0-888.0-888.0
2232   2    15.1   18.6   18.8   J5.8   17.0   J6.1   12.0  17.2-888.0
2232   2  -866.0-888.0-888.0-888.0-688.0-888.0-888.0-886.0-888.0
2232   3     4.6   5.8    6.1    4.8    5.3    5.0    4.2   5.6-688.0
2232   3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-688.0
2232   4      1.7   2.0    2.6    5.1    3.7    3.8    3.0   3.8-888.0
2232   4  -888.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-868.0
2232   5      1.5   2.3    1.5    3.6    2.4    1.7    J.5   1.8-888.0
2232   5  -888.0-888.0-888.0-888.0-888.0-886.0-888.0-888.0-886.0
2232   6      1.9   3.8    2.3    2.4    1.8    2.1    1.9   2.0-688.0
2232   6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-868.0-886.0
                             129
-------
2241    82.   3.35    2.4   8*50  IU20  2*40  439 1940  290
2241  J     29.0  38.0  37.0  60.0  45.J  39.0  38.0  46.O-d8d.O
2241  1   -868.0-8dd.0-888.0-888.0-888.0-888.0-888.0-888.0-ddd.0
2241  2    10.4  11.4  JO.4  10.4  10.8   9.7   8.8  11.1-888.0
2241  2  -888.0-888.0-888.0-888.O-888.0-88d.O-88d.0-888.0-ddd.O
2241  3     2.7   2.9   3.3   3.6   3.4   3.3   3.0   3.5-d8b.O
2241  3  -888.0-8dd.0-d88.0-888.0-888.J-88b.0-883.0-888.0-ddd.O
2241  4      .5     .8   1.6   7.1   3.7   3.4   2.1   2.0-ddd.O
2241  4  -888.0-888.0-888.0-888.0-888.0-8tfd.0-88d.0-888.0-d88.U
2241  5     2.6   5.6   2.4   2.2   2.4   2.4   3.0   2.3-888.0
2241  5  -888.0-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2241  6  -999.0-999.0   J.3   1.2   J.I   J.0     .9    1.3-888.0
2241  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
2242    d5.   3.96    3.1   IHDO   I4HO  2141  320 2138  319
2242  1    35.0  5J.O  47.0  58.0  41.0  57.0  45.0  37.0-ddd.O
2242  1  -8d8.J-88d.O-ddd.O-88d.0-888.0-888.0-888.0-888.0-8dd.O
2242  2     d./  J2.4  10.1  JO.O    7.9   8.3   9.7    9.0-d88.0
2242  2  -8dd.0-ddd.0-838.0-888.0-888.0-88d.0-ddd.0-88d.0-dd8.0
2242  3     3.0   2.5   3.2   3.0    3.0   2.9   3.0    2.5-ddd.G
2242  3  -83d.0-88d.0-888.0-888.0-888.0-88d.0-88d.0-888.0-ddd.O
2242  4       .6     .9   2.1   b.3    3.2   2.8   2.7    1.5-888.0
2242  4  -8dd.0-888.0-d88.0-888.0-888.0-888.0-888.0-888.0-odd.0
2242  5     3.2   4.2   2.7   4.7    3.9   3.3   3.6    3.4-8d8.0
2242  5  -8dd.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-838.0
2242  6  -999.0   1.9    1.4    1.3    1.7     .9     .9    l.2-88d.O
2242  6  -88d.0-8dd.0-888.0-888.0-888.O-888.0-888.O-888.0-8d8.0
 2281    3N.    5.48     3.8   J3i50  I6HO   2664  398 3453  516
 2281   1    24.0   22.0   26.0  36.0   29.0   2D.O  24.0-888.0-888.0
 2281   I  -888.0-888.0-888.0-888.0-888.0-888.0-888.O-888.0-d8d.O
 2281   2     5.J   5.3    b.4   6.4    5.5    5.6-999.0-888.O-ddd.O
 2281   2 -888.0-888.0-888.0-888.O-888.0-888.0-888.0-888.0-88d.O
 2281   3     1.8    1.8    1.8   2.0    J.9    J.9   1.8-888.0-888.0
 2281   3 -888.0-888.0-888.0-888.O-888.0-888.0-888.0-888.O-888.0
 2281   4      .5     .4     .7   4.0    J .5    J.9   J .5-888.0-888.0
 228J   4 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-.888.0-388.0
 2281   5      .4     .5     .9    .5     .5     .4-999.0-888.0-888.0
 2281   5 -883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-8dd.O
 2281   6 -999.0-999.0-999. 0-999.0-999.0-999.0-999.0-888.0-888.0
 2281   6 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
                             130
-------
301    285.   4.75    2.1   8*5J   1U20  2940  439  1940
301    I    39.0  44.0  43.0  53.0  48.0  40.0  38.0-888.0-888.0
301    I  -888.0-88d.0-888.0-888.0-888.0-88d.0-888.0-888.0-d8d.O
301   2     d.6   3.7   8.8-999.0   7.7    7.9    7.6-888.0-888.0
301   2  -888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-88d.O
301   3     2.8   2.6   2.6   2.8   2.4    2.4    2.5-838.0-388.0
301   3  -888.0-888.0-888.0-888.0-888.0-88d.0-88d.0-888.0-888.0
301   4     1.3   2.3   3.8   4.1   2.4    2.2    1.9-888.0-888.0
301   4  -88d.0-88d.0-d88.0-888.0-888.0-888.0-888.O-888.0-d88.0
301   5       .6     .7     .9-999.0     .6     .7     .6-888.0-888.0
301   5  -888.0-888.0-888.0-888.0-888.J-888.0-888.0-888.0-888.0
301   6       .6     .8     .8-999.0     .8     .8     .6-888.0-888.0
301   6  -888.0-883.0-888.0-888.0-888.0-883.0-888.0-888.0-888.0
3012   282.    D.93     5.4   12*60   IbHO   2350   351  2616   391
3012   1    31.0   40.0   44.0  43.0   36.0   32.0   3 I.0-888.0-3^8.0
.3012   1  -888.0-888.0-886.0-888.0-888.J-888.0-8dd.0-888.0-dd8.0
3012   2     6.6   6.0    6.5   6.4    6.0    6.3   6.1-888.0-d8d.O
3012   2  -883.0-886.0-388.0-888.0-888.0-388.0-88tt.0-880.0-888.0
3012   3     2.1   2.0    2.1    2.0    l.d    1.9    I.8-888.0-8dd.O
3012   3  -888.0-883.0-ddd.0-888.0-888.0-886.0-888.0-888.0-ddd.O
3012   4     J.I   2.0    3.3   2.9    1.8    1.8    1.5-888.0-888.0
3012   4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
3012   5       .9     .7     .6    .8     .6     .6     .6-888.O-dd8.0
3012   5  -888.0-888.0-388.0-888.0-838.0-888.0-888.0-888.0-8d8.0
.3012   6       .4     .8     .8-999.0-999.0-999.0     .2-888.O-388.0
3012   6  -883.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
 3022    297.    4.81     4.8  13*50  16*30  2666  398 35o5  533
 3022   1    40.0  23.0  25.0  54.0  44.J  32.0  21.0-888.0-888.0
 3022   1  -883.J-88d.O-d88.0-868.0-888.0-888.0-883.0-838.0-888.0
 3022   2     J.2   1.9   2.5   1.5   3.1   3.2   2.2-888.0-888.0
 3022   2 -88d.O-88d.0-388.0-888.0-888.0-383.0-886.0-888.0-386.0
 3022   3      .7    .8    .8    .8    .8    .7    .7-888.0-388.0
 3022   3 -883.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-3d8.0
 3022   4     1.0    .5   1.7   4.6   3.3   2.4    ,d-888.0-38d.O
 3022   4 -888.0-888.0-888.0-888.0-888.J-888.0-888.0-888.0-888.0
 3022   5      .5    .5    .5    .9    .6    .8    .4-888.0-388.0
 3022   5 -888.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-838.0
 3022   6 -999.0-999.0    .2-999.0-999.0    .2-999.0-888.0-388.0
 3022   6 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-dd8.0
                              131
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3031   290.   3.23
3031  J    51.0  62
3031  I  -886.0-88J
3031  2     9.1   V
3031  2  -868.0-888
3031  3     2.9   2
3031  3  -886.0-686
3031  4     1.2   I
3031  4  -888.0-88d
3031  5       .d   I
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3031  6     1.7   2
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3232  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
3232  6  -999.0-999.0-999.0    .6-999.0-999.0-999.0-999.0-888.0
3232  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.O-888.0
329J   236.   2.90    11.3    7J 0   9*40   4320   645  2264   33d
3291   I    49.0  50.0  b2.0  34.0  31.0   34.0   42.0  31.0-888.0
3291   I  -888.0-886.0-888.0-888.0-888.J-888.0-888.0-888.0-888.0
329J   2     6.0   3.3   4.9   4.7   3.6    4.2    1.3   3.8-888.0
3291   2  -888.0-888.0-388.0-888.O-888.O-888.0-888.0-888.0-888.0
3291   3     1.7   1.7   1.7   1.6   1.4    1.4    1.1    1.6-888.0
329J   3  -888.0-888.0-888.0-888.O-888.0-888.0-888.0-888.O-888.0
3291   4     3.2   3.4   5.4   1.0   1.2    1.0     .9    .9-888.0
3291   4  -888.0-888.0-888.O-888.O-888.0-888.0-888.0-888.0-888.0
3291   5     2.8   3.6   3.0   2.3   2.3    2.0    2.8   2.6-888.0
329J   5  -888.0-888.0-888.0-888.O-888.0-888.0-888.0-888.0-888.0
3291   6     1.3   2.2     .6   1.4     ./    J.b     .9    .9-888.0
329J   6  -888.0-888.0-888.0-888.0-888.O-888.O-888.0-888.0-d88.0
                              137
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3292   214.   3.26   20.0  13*50  J6i30  2666  J98 3565  533
3292  I    44.0  51.0  53.0  44.0  40.0  42.0  42.0  44.0-388.0
3292  I  -883.0-883.0-888.0-888.0-888.0-888.0-888.0-88b.O-888.0
3292  2     6.6   6.6   6.7   6.7   3.3   6.8   3.3   6.7-388.0
3292  2  -888.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0-880.0
3292  3     2.3   2.1   2.2   2.3   2.3   2.1   1.8   2.3-388.0
3292  3  -888.0-883.0-888.0-888.O-888.0-888.0-888.0-888.0-888.0
3292  4     2.8   1.9   3.7   -.6   -.6   -.6   -.6   -.5-388.0
3292  4  -883.0-888.0-888.0-888.0-838.0-888.0-88^.0-888.0-888.0
3292  5       .7     .6     .6     .4     .6     .3     .4     .4-888.0
3292  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
3292  6     1.5   2.6   1.5   2.b   J.8   1.7   I.9   2.0-888.0
3292  6  -883.O-888.0-888.0-888.0-888.0-888.0-888.0-888.0-838.0
3301   202.    I.10    ID.9    7*50   10*10   3a21   571  21/2  324
3301   1    67.0  35.0   81.0   66.0   62.0   52.0   49.0  60.0-388.0
3301   1  -888.0-883.0-888.0-888.0-888.0-88d.O-888.J-888.0-388.0
3301   2     11.6  J2.9   12.5   12.0   11.9   11.6    /.6  12.1-388.0
3301   2  -883.0-888.0-888.0-888.0-888.0-888.0-838.0-888.0-888.0
3301   3     3.6   3.8    3.5    3.6    3.5    3.b    2.5   3.6-388.0
3301   3  -833.0-883.0-888.0-883.0-888.0-388.0-888.0-888.0-388.J
3301   4     4.3   6.1    7.4    4.3    2.9    2.9    1.4   2.1-838.0
3301   4  -888.0-883.0-838.0-888.0-888.0-888.0-888.0-888.0-388.0
3301   5      I./   2.4    5.0    J.7    1.7    J.b    2.0   1.4-888.0
3301   b  -888.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0
3301   6      1.3   3.1    2.3    1.8    J.b    1.6    1.6   1.5-388.0
3301   6  -888.0-883.0-888.0-888.O-888.0-888.0-883.0-888.0-888.0
 3302    200.    3.29   13.6  12*  0  14*40  2227  333 2264  333
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 3302   1  -888.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0-888.0
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 3302   3     3.5   3.3   3.9   3.4   3.1   3.3   2.5   3.2-888.0
 3302   3 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
 3302   4     2.1   1.2   3.0  -.6   -.6   -.6   -.6   -.6-888.0
 3302   4 -883.0-888.0-d88.0-8b8.O-888.0-883.0-888.0-888.0-888.0
 3302   5     1.8    .9   1.2    .9   1.2   1.3   J.I   1.2-388.0
 3302   5 -888.O-888.0-a88.0-888.0-888.0-888.O-883.0-888.0-888.0
 3302   6      .3    .5-999.0    .5-999.0    .5    .3-999.0-338.0
 3302   6 -883.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0-880.0
                              138
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3  -838.0-888.0-888.0-888.0-888.0-888.0-ddd.0-888.0-dd8.0
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4  -888.0-88d.O-888.0-888.0-888.0-888.0-888.0-888.0-888.0
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5  -883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.U
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3312   325.   9.85   12.4   I2«50   15*10  2350  351 2616  391
3312  1    18.0  22.0   13.0  31.0  15.0  36.0  27.0  22.0-dd8.0
3312  1  -888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
3312  2     2.4   1.9   3.2   2.3   2.9   2.1-999.0   3.0-888.0
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3312  3      .9     .9    .9   1.0     .9   1.0     .9   I.0-dd8.0
3312  3  -88d.0-888.0-838.0-888.0-888.0-888.0-888.0-888.0-888.0
3312  4     -.6   -.0   -.6   2.0   -.6     .7     .5    ,6-d88.0
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4112   188.   3.27    9.3  J4i50  I/HO  2/02  4044177  624
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4J2J  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
 4122    308.    4.59    28.0  11«5O  J4i  0  2113  3162123  317
 4122   1    49.0  66.0  72.0  69,0-888.0-888.0  63.0  54.0-888.0
 4122   1  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
 4122   2     9.2  10.0  JO.5  10.3-888.0-888.0   8.0   9.5-888.0
 4122   2 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
 4122   3     3.0  2.9   3.4   3.1-888.0-888.0   2.4   3.1-888.0
 4122   3 -888.0-888.0-888. 0-888.0-888.0-888.0-888.O-888.0-888.0
 4122   4     -.7  -.7   J.O   4.0-888.0-888.0   1.3   1.7-888.0
 4122   4 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
 4122   5      .5    .5    .5    .6-888.0-888.0    .5    .5-888.0
 4122   5 -888*0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
 4122   6 -999.0    .7-999.0    .8-888.0-888.0    .4-999.0-888.0
 4122   6 -888.0-888.0-888.0-888.0-888.O-888.0-888.0-888.0-888.0
                              142
-------
4J4J   332.   5.70   J3.4   8«40  M«20  .2995  448 J974  295
4141  I     24.0  19.0  17.0  29.0  20.0  22.0  38.0  27.0-888.0
4141  J   -886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4J4J  2     3.0   3.0-999.0   2.9   3.0   2.J   1.0   3.2-888.0
4J4J  2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4J4J  3      .8    .8    .8   I.I    .6    .7    .7    .6-868.0
4J4I  3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4141  4     -.7   -.7   -.7   2.8    .6   2.0   -.6   1.0-888.0
4141  4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4J4I  5     J.3   1.1-999.0    .5    .5    .2    .5    .6-688.0
414J  5  -883.0-886.0-888.O-888.0-888.0-888.0-886.0-888.0-888.0
4J4J  6  -999.0-999.0-999.0-999.0-999.0    .1-999.0    .6-888.0
4141  6  -888.0-888.0-686.0-888.0-888.0-888.0-888.0-886.0-888.0
4142   328.   7.88    17.0   I2«50  15i 0  2326  348 2537  3/9
4142   1    46.0  30.0  23.0  21.0  21.0  20.0  80.0  22.0-888.0
4142   1  -888.0-886.0-888.0-888.0-888.0-686.0-888.0-888.0-888.0
4142   2      1.6   2.4   2.1   2.5   2.4   2.0    1.9   2.7-888.0
4142   2  -886.0-888.0-888.0-886.0-836.0-888.0-888.0-888.0-688.0
4142   3       .5     .6    .6     .7     .6     .6    .5    .6-888.0
4142   3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4142   4      -.6   -.6   -.6   2.7     .9   1.6    .7    .8-888.0
4142   4  -866.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4142   5       .8   1.3    .9   1.2   1.5   1.7    1.0    1.5-888.0
4142   5  -888.0-888.0-888.0-888.0-888.0-888.O-888.0-888.0-888.0
4142   6  -999.0-999.0-999.0     .2     .2     .2    .2    .7-868.0
4142   6  -888.0-886.0-888.0-888.0-868.0-888.0-888.0-888.0-888.0
4J51     4.    1.88    6.7   6«40   9* 0  4595   687 2223  332
4151   1    21.0  28.0   J9.0  27.0  43.0  23.0   32.0  23.0-888.0
4J5I   1  -888.0-888.0-888.0-888.0-888.0-888.0-886.O-888.0-888.0
4151   2     2.3   2.4   2.3   2.4   2.9   2.3    1.6   2.3-888.0
415J   2  -888.0-888.0-888.0-888.O-888.0-888.0-888.0-888.0-888.0
4151   3       .6     .6     .6     .7     .7     .6     .5     .8-888.0
4151   3  -888.0-888.0-888.0-888.0-888.0-888.0-388.O-888.0-888.0
4151   4     -.6     .7   1.4   3.1   5.3   2.0     .9   1.4-888.0
4151   4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4151   5     1.1   1.3   1.4   1.2   2.0   1.0    1.7   1.1-688.0
4151   5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4151   6  -999.0-999.0-999.0     .2-999.0     .1     .1     .2-888.0
4J51   6  -886.0-888.0-888.0-888.0-888.0-888.0-868.0-888.0-888.0
                             143
-------
4152   236.   3.73   J3.5  U«50  14*20  2174  3252J78  32?
4152  I    26.0  44.0  45.0  41.0  49.0  48.0-888.0  34.0-688.0
4152  I  -883.0-888.0-888.O-888.0-888.0-888.0-888.0-888.0-888.0
4J52  2     4.5   3.6   5.5   4.9   4.7   4.8-888.0   4.6-888.0
4152  2  -888.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0
4152  3     1.3   1.6   J.5   1.6   1.3   l.4-88d.O   1.3-888.0
4152  3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4152  4     2.1   3.1   5.4   1.9     .7   -.6-886.O     .9-888.0
4152  4  -88d.O-888.0-888.O-888.0-888.0-888.0-888.0-888.0-888.0
4152  5     1.2   1.0   1.2   I.I  14.1    .5-888.0   1.4-888.0
4152  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
4152  6       .6-999.0   2.6    .6     .4    .9-888.0-999.0-888.0
4152  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4182   224.   3.41   J8.2  J3t 0   I5«30  2426  363 2822  422
4182   1    54.0  60.0  34.0  58.0  69.0  46.0  69.0  57.0-d88.0
4182   I  -88d.0-883.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0
4182  2    10.6  10.7   9.5   9.2  10.4-999.0   8.1   9.3-686.0
4162  2  -88d.0-888.0-888.0-888.0-888.0-88d.0-886.0-888.0-888.0
4182  3     3.2   3.0   3.0   3.3   3.0   2.8   2.4   2.8-868.0
4182  3  -888.0-886.0-888.0-888.0-688.0-888.0-888.0-888.0-688.0
4182  4     3.1   3.1   5.3   1.3   1.3   1.0    1.0    1.2-688.0
4162  4  -868.0-886.0-888.0-888.0-888.0-888.O-866.0-888.0-888.0
4182  5     1.0     .9     .8     .6     .3-999.0    1.0     .9-388.0
4182  b  -886.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4182  6       .5-999.0     .5     .2     .5-999.0    1.0-999.O-868.0
4182  6  -888.0-886.0-888.0-888.0-888.0-888.0-886.0-888.0-888.0
4191     34.    3.01    16.1    7t  0    9*30  4383  6t>5 2234  341
4191   1     33.0   26.0  12.0-888.0   41.0  3o.O  30.0  3I.O-888.0
4191   1  -888.0-888.0-888.0-888.0-888.0-88^.0-888.0-888.0-888.0
4191   2      5.2-999.0   5.5-888.0    4.9   5.6   3.9   5.O-888.0
4191   2  -888. 0-888.0-888.0-888. 0-888. 0-886.0-888. 0-888. 0-388.0
4191   3      1.9    1.8   1.7-888.0    1.6   1.6   1.3   1.5-888.0
4191   3  -883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4191   4       .7     .9   1.1-888.0    2.1   2.8   1.8   2.1-888.0
4191   4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-886.0-888.0
4191   5       .5-999.0    .5-888.0     .7    .8    .6    .5-888.0
4191   5  -883.0-888.0-888.0-888.0-886.0-883.0-888.0-888.0-388.0
4191   6  -999.0-999.0-999.0-888.0     .4-999.0    .3-999.0-388.0
4191   6  -888.0-888.0-888.0-888.0-888.0-886.O-888.0-888.0-888.0
                              144
-------
4192   156.   2.69   20.4  I I 120  13*30  2135  3)92013  3Ji
4192  J    23.0  46.0  38.0  30.0  18.0  29.0  32.0  32.0-38U.O
4192  1  -883.0-88d.O-888.0-888.0-888.0-888.0-888.0-88d.0-d88.0
4192  2     4.8   4.3   5.0   4.6   4.4   4.7   2.9   5.0-388.0
4192  2  -888.0-88d.0-888.0-888.O-883.0-888.0-888.0-888.0-d8d.O
4192  3     J.4   1.4    1.6   J.4   1.3   1.3   1.0   1.4-888.0
4192  3  -888.0-888.0-888.0-8bd.0-888.0-888.0-883.0-888.0-388.0
4192  4     1.7   1.1   2.4   1.8   1.0   -.6   -.6     .8-dd8.0
4192  4  -8dd.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0
4192  5      .6    .6    .7     .6     .4     .7     .6     .7-888.0
4192  5  -888. 0-888.0-888. 0-888.0-8b8. 0-888. 0-888.0-888.0-388.0
4192  6      .3-999.0    .8-999.0-999.0     .2     .2     .2-888.0
4192  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.D-888.0
4201    128.   1.95    11.9   7i 0   9i50  4247   635 2241
4201   1    22.0  32.0  39.0  30.0  21.0  2D.O   19.0   24.O-d88.0
4201   1  -888.0-8dd.0-888.0-888.0-888.0-888.0-888.0-888.J-d88.J
4201  2     2./   J.O   3.0   2.d   3.1    1.2     .7    2.4-ddd.O
4201  2  -8dd.0-8dd.0-d88.0-888.0-888.0-888.0-88d.0-888.0-ddd.O
4201  3       ./     .d     .9    ,d     .7     .7     .6     ,8-ddd.O
4201  3  -883.O-8d8.0-888.0-888.0-888.0-888.0-88d.0-888.0-d88.0
4201  4     1.6   2.b   4.0    1.7     .6    -.6   -.6     ,7-d8d.i)
4201  4  -88d.Q-8dd.0-888.0-888.0-d88.0-888.0-888.0-888.O-8d8.0
4201  5       .8     .6     .9    .8     .7     .7    1.0     ,t>-d88.0
4201  5  -888.0-88d. 0-888.0-888.0-888.0-888.0-888.0-888. 0-838.0
4201  6       .5     .6     .5    .4     .2     .5-999.0     .2-888.0
4201  6  -88d.0-888.0-d8
4201  6  -8dd.0-888.0-888.0-88d.O-888.O-888.0-888.0-888.0-888.0
4202    186.   2.51    lts.1   1H50   I4HO   2141   3202138  319
4202   1    25.0   33.0  27.0   J3.O   15.0   24.0   17.0   17.0-888.0
4202   I  -888.0-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
4202   2      1.7   2.7    2.7-999.0-999.0    3.6    1.6    2.3-d8d.O
4202   2  -88d.0-883.0-888.0-888.0-888.J-888.0-888.0-888.0-d88.0
4202   3      1.2   J.O    J.I    1.0    1.0    1.1     .8    1.1-888.0
4202   3  -888.0-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
4202   4      1.7   1.5    3.2   -.5   -.5    -.5    -.5    -.5-d88.0
4202   4  -88d.0-888.0-888.O-888.0-888.0-888.0-888.0-888.0-888.0
4202   5       .6     .8     .8-999.0-999.0     .7     .8     .7-88d.O
4202   5  -888.0-888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0
4202   6       .4     .8     .5-999.0-999.0     .6     .7     .6-888.0
4202   6  -88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-d8d.O
                              145
-------
421    283.    .99   20.2  10i2Q  12*50  2269  33V 1928  288
421   J     39.0  52.0  47.0  36.0  16.0  31.0  27.0  34.0-688.0
421   1   -883.0-888.0-888.0-888.0-888.0-888.O-888.0-888.0-888.0
421   2     6.0   6.4   6.6   6.0   5.9   6.5   5.7   5.6-338.0
421   2  -888.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-888.0
421   3     1.7   J.7   J.9   1.7   J.D   1.3   1.J   1.6-888.0
421   3  -888.0-888.0-388.0-688.0-888.0-886.0-866.0-888.O-388.0
421   4     2.2   2.6   4.4     .8   -.6   -.6   -.6   -.6-888.0
421   4  -886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-668.0
421   5     2.1     .7   1.2     .8   1.2   J.0     .8     .8-388.0
421   5  -888.0-888.J-888.0-888.0-888.0-688.0-888.0-888.0-888.0
421   6       .6   1.7     .6   J.I   1.0     .9   J.I   1.3-688.0
421   6  -888.0-888.0-688.0-888.0-888.0-808.0-888.0-888.0-888.0
4212   223.     .19    18.4   J4i20   I6«40  2/30  408  3855   576
4212   I    25.0   18.0  39.0   14.0   9.0  13.0  20.0  16.0-888.0
4212   I  -886.0-688.0-888.0-888.0-888.0-886.0-868.0-888.0-886.0
42J2   2      J.8   4.0   2.0    4.3-999.0   3.2    2.8   4.9-888.0
4212   2  -888.0-888.0-886.0-886.0-838.0-888.0-883.0-888.0-886.0
4212   3      J.J   1.0    1.1    I.I    1.1   1.1     .7   1.1-888.0
4212   3  -888.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4212   4      1.9   1.3   4.1    -.6     .8   -.6    -.6   -.6-886.0
4212   4  -888.0-886.0-888.0-886.0-888.0-688.0-888.0-888.0-888.0
4212   5       .7   1.0    1.0     .6-999.0     .7     .7    .7-888.0
4212   5  -888.0-886.0-888.0-888.0-888.0-888.0-888.0-886.0-888.0
4212   6       .6     .8-999.0     .8-999.0     .9     .7-999.0-888.0
4212   6  -888.0-888.0-888.0-888.0-888.0-888.0-886.0-888.0-668.0
4221    280.    J.I I    16.7   6*50   9*20  4484  670 2260  338
4221   I    57.0  80.0  70.0  57.0  61.0  59.O-888.0  55.0-888.0
4221   1  -888.0-888.0-888.0-886.0-888.0-888.0-886.0-888.0-888.0
4221   2   J8.7  16.4  15.9  18.2  18.8  18.2-886.0  16.4-688.0
4221   2 -888.0-888.0-888.0-888.0-888.0-888.0-868.O-886.0-888.0
4221   3     4.3   4.1    4.2   4.2   4.5   4.3-888.0   4.5-888.0
4221   3 -888.0-888.0-888.0-888.0-886.0-888.0-886.0-888.0-888.0
4221   4     3.7   3.2   5.9   1.7   1.2   1.5-888.0   1.4-888.0
4221   4 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4221   5     1.0   1.6   1.6   1.3   1.0   1.3-888.0    .9-888.0
4221   5 -888.0-888.O-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4221   6      .7   1.4    .7   1.0    .6    .8-888.0-999.0-888.0
4221   6 -888.0-888.0-888.0-888.0-888.0-888.0-886.0-888.0-888.0
                              146
-------
4222   280.   1.02   22.4  12* 0  I4i20  2166  324 2189  32/
4222  1     63.0  73.0  66.0  64.0  47.0  51.0-833.0  65.0-683.0
4222  I   -888.0-88d.0-886.0-888.0-888.0-86d.O-888.0-888.0-888.0
4222  2    J8.J  21.8  18.3  16.7  16.8  21.6-886.0  15. 9-888.0
4222  2  -868.0-888.0-688.0-888.0-888.0-886.0-886.0-888.0-686.0
4222  3     4.6   5.2   5.0   4.8   4.5   5.0-886.0   4.9-868.0
4222  3  -886.O-88d.0-888.0-888.0-868.0-688.0-888.O-888.0-888.0
4222  4     2.2   1.6   4.1   -.6   -.6   -.6-888.0   -.6-388.0
4222  4  -888.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-688.0
4222  5      .9    .6     .4     .6     .8    .7-686.0     .8-888.0
4222  5  -886.0-88d.0-888.0-888.0-888.0-888.0-886.0-888.0-688.0
4222  6      .4   l.b-999.0     .8     .4    .8-888.O-999.0-888.0
4222  6  -886.0-888.0-388.0-868.0-888.0-886.O-888.0-888.0-888.0
4251    12.   2.00    5.5   8«30   11« 0  3148  470 2012  3JI
4251  1     19.0  ld.0  23.0  54.0  30.0  39.0-888.0   77.0-688.0
4251  I   -86d.0-886.O-888.0-886.0-886.0-686.0-868.0-888.0-888.0
425)  2     4.4   4.3   5.4   6.9   4.5   5.4-886.0   6.1-888.0
4251  2  -868.0-888.0-888.0-888.0-888.0-886.0-866.0-888.0-866.0
4251  3     2.2   2.0   2.3   2.2   2.1   2.1-886.0   2.0-666.0
4251  3  -888.0-888.0-888.0-888.0-868.0-888.0-886.0-888.0-888.0
4251  4     -.6   -.6   -.6   3.5   2.1   2.4-888.0   1.6-886.0
4251  4  -888.0-886.0-888.0-886.0-688.0-888.0-888.0-888.0-866.0
4251  b       .D     .9    .7     .7     .8     .7-888.0     .6-888.0
4251  5  -888.0-886.0-888.0-888.0-868.0-886.0-886.0-888.O-888.0
4251  6  -999.0     .1-999.0-999.0-999.0-999.0-888.0     .5-888.0
4251  6  -886.0-888.0-888.0-886.0-888.0-888.0-868.0-888.0-688.0
4252   213.    1.49    10.0   I4UO   16MO  2/19  4063761   562
4252   1    42.0-886.0   72.0  31.0  24.0  32.0-888.0   31.0-888.0
4252   I  -868.0-888.0-888.0-888.0-888.0-888.O-886.0-888.0-888.0
4252  2     6.2-886.0   6.9    5.5   4.9   6.1-886.0   4.3-888.0
4252  2  -888.0-888.0-688.0-888.0-888.0-888.0-886.0-888.0-688.0
4252  3     2.1-888.0   2.2    2.1   2.1   2.1-888.0   2.1-888.0
4252  3  -888.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
4252  4     3.1-888.0   6.0    1.7   1.1   1.2-888.0     .7-886.0
4252  4  -888.0-888.0-888.0-888.0-888.0-686.0-888.0-888.0-688.0
4252  5      .5-888.0    .8     .9     .8     .d-888.0     .7-388.0
4252  5  -868.0-886.0-888.0-888.0-888.0-688.0-888.0-888.0-888.0
4252  6      .2-888.0-999.0     .2     .3-999.0-888.0-999.0-888.0
4252  6  -886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
                              147
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4261   192.    .94
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4261  4  -833.0-883
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4292   329.   4.34    8.5  I0»40   13*10  2lb3  326  1951  292
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4292  2     1.6-999.0-999.0   2.6   3.3   2.8-888.0-888.0-888.0
4292  2  -888.0-888.0-388.0-888.0-888.0-888.0-888.0-888.0-888.0
4292  3      .7    .7    .7    .8    .7    .8-888.0-888.O-388.0
4292  3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
4292  4     -.5   -.5   -.5   3.6   1.6   1.8-888.0-888.0-888.0
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4292  5      .9-999.0-999.0    .7    .5    .7-888.0-888.0-888.0
4292  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
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5021   2     6.1   2.4   5.9    4.0    5./    5.6-88d.O-88b.O-8d8.0
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502J   3     J.6   1.8   1.6    1.4    1.6    J.6-888.0-888.0-888.0
5021   3  -888.0-888.0-888.0-888.0-888.0-888.O-88d.Or888.0-888.0
5021   4     2.1   2.2   4.2    -.6    -.6    -.5-888.0-888.0-888.0
5021   4  -888.0-888.0-888.0-888.0-888.0-388.0-888.0-888.0-888.0
5021   5     1.2   1.2     .9     .8     .8     .5-888.0-888.0-888.0
5021   5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5021   6     1.2   1.5   1.0    1.0    1.0     .9-888.0-888.0-888.0
5021   6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5022    213.    2.40    14.4   12120  15*  0  2287  342 2432  363
5022   1    34.0  36.0  39.0  30.0  28.0  24.0-888.0-888.0-888.0
5022   I  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5022   2     7.4  5.5   6.5   6.2   6.5-999.0-888.0-888.0-888.0
5022   2 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5022   3     1.9   1.8   1.8   J .9   1.8   1.8-888.0-888.0-888.0
5022   3 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5022   4     4.1  3.4   5.0   1.3    .7    .7-888.0-888.0-888.0
5022   4 -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5022   5     1.3   1.0   1.1   1.0   I.1-999.O-888.0-888.0-888.0
5022   5  -888.0-888.0-888. 0-888.0-888.0-888.0-888.0-888.0-888.0
5022   6     1.9   J.2   1.5   -2.2   1.4-999.0-888.0-888.0-888.0
5022   6 -888.0-888.0-888.O-888. 0-888. J-888.0-888.0-888.0-888.0
                              150
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5031   359.   4.04   13.3   7i 0   9*40  4320  645 2264  33d
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5031  2     2.6   J.O   3.3   J.I   2.7   2.3-888.0-888.0-888.0
503J  2  -888.O-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5031  3      .7    .8    .8    .6    .7    .8-888.0-888.0-888.0
5031  3  -888.0-886.0-888.0-888.0-838.0-888.0-888.0-888.0-888.0
5031  4     -.6   -.6   -.6   2.6   J.I   2.1-888.0-888.0-888.0
5031  4  -888.0-886.0-888.0-888.0-888.0-888.0-886.0-888.0-888.0
5031  5      .8    .8    .4    .8    .7    .6-888.0-888.0-888.0
5031  5  -838.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5031  6      .J-999.0    .2-999.0    .2    .2-886.0-888.0-888.0
5031  6  -888.0-888.0-888.0-888.0-8«8.0-888.0-888.0-888.0-888.0
5032   337.   2.99    17.2   IU30   141 0  2140  3202082  311
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5032  1  -888.0-888.0-66t>.0-888.0-888.0-888.0-886.0-888.0-688.0
5032  2       .9   2.9   2.0   2.9   3.0   2.7-888.0-888.0-388.0
5032  2  -888.0-888.0-388.0-888.0-888.0-688.0-888.0-888.0-686.D
5032  3       .9   J.O    1.0   J.I   1.0   1.0-888.0-888.0-686.0
5032  3  -888.0-888.0-088.0-888.0-888.0-888.0-888.0-888.0-868.0
5032  4     -.6     .6   -.6   3.6   1.9   1.8-886.0-888.0-688.0
5032  4  -838.0-888.0-888.0-888.0-888.0-888.0-888.0-868.0-888.0
5032  5       .6     .3     .4     .5     .4     .5-888.0-888.0-688.0
D032  5  -886.0-888.0-888.0-886.0-888.0-888.0-888.0-888.0-888.0
5032  6  -999.0-999.0-999.0   2.2     .3- 999.0-886.0-888.0-888.0
5032  6  -888.0-888.0-888.0-888.0-838.0-888.0-868.0-868.0-888.0
5041    J49.    J.52    13.8    8»IO   J0i40   3432   5132107   315
5041   J    26.0  30.0  42.0   J8.0   18.0   11.0-886.0-888.0-688.0
5041   1  -886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-688.0
5041   2     2.J   3.5    2.4    J.I   3.2    J.6-868.0-888.O-388.0
5041   2  -868.0-888.0-888.0-888.0-888.0-888.0-888.0-868.0-668.0
5041   3       .7     .8     .8     .8     .7     .8-868.0-888.0-688.0
5041   3  -888.0-888.0-888.0-888.0-888.0-888.0-868.0-888.0-868.0
5041   4     J.6   2.3    4.J    2.4     .6    -.6-866.0-888.0-888.0
5041   4  -883.0-888.0-888.0-888.0-886.0-888.0-888.0-888.0-888.0
5041   5       .5     .6     .6     .5     .7     .4-888.0-888.0-888.0
5041   5  -886.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5041   6       .2-999.0-999.0-999.0     .3-999.0-888.0-888.0-888.0
5041   6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-868.0
                               151
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5042   195.   2.64   13.5  11120  I3i50  2137  3J92043  305
5042  I     24.0  31.0  45.0  24.0  22.0  20.0-888.0-886.0-886.0
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5042  2     3.1   4.3   4.8   3.4   3.4   2.7-688.0-888.0-888.0
5042  2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5042  3     J.O   I.I   1.1   1.1    .9   1.1-888.0-886.0-888.0
5U42  3  -883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-838.0
5042  4     1.8   2.3   4.4   -.5   -.5   -.6-888.0-888.0-888.0
5042  4  -888.0-888.0-888.0-888.0-888.0-803.0-888.0-888.0-888.0
5042  5      .5   1.2    .7    .6    .5     .4-888.0-888.0-388.0
5042  5  -883.0-883.0-883.0-888.0-888.0-888.0-888.0-888.0-388.0
5042  6  -999.0    .2    .2    .5-999.0     . I-883.O-888.0-888.0
5042  6  -888.0-883.0-388.0-888.0-888.0-888.0-888.0-888.0-388.0
511    348.   2.15   12.9   9*20   12*30  2535  379  1912  236
511    I    12.0   3.0-888.0  29.0-999.0  23.0-888.0-888.0-388.0
511    I  -883.0-888.0-888.0-888.0-888.0-386.0-883.0-888.0-388.0
511    2     2.6   1.2-888.0    1.3-999.0    I.5-888.0-888.0-388.0
511    2  -888.0-888.0-888.0-888.0-838.0-888.0-888.0-888.0-388.0
511    3       .5     .5-888.0     .6     .4     .3-888.0-885.0-388.0
51     3  -838.0-838.0-888.0-888.0-888.0-888.0-888.0-888.0-368.0
51     4     -.5   -.5-388.0    3.0   -.8    1.8-888.0-888.0-388.0
51     4  -838.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
51     5       .7     .5-888.0 '    .7   1.3     .8-838.0-888.0-888.0
51     5  -883.0-883.0-888.0-888.0-888.0-888.0-388.0-888.0-888.0
51     6  -999.0     .1-888.0     .3-999.0     .3-888.0-888.0-388.0
51     6  -886.0-888.0-888.0-888.0-838.0-888.0-886.0-888.0-888.0
5J2!   283.   2.34    16.9    7*10   9*30  4370   653  2293   343
5121   I     16.0  21.0  31.0   44.0  22.0  2«.0   27.0  3I.O-888.0
5121   I  -888.0-883.0-888.0-888.0-888.0-8^. .0-888.0-888.0-388.0
5121   2     2.7   2.6   4.2   3.4   2.3   3.5    1.4   2.8-388.0
5121   2  -888.0-888.0-388.0-888.0-888.O-888.0-888.0-888.0-888.0
5J21   3       .9     .9     .9    1.0     .9     .9     .8   J.0-888.0
5121   3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-688.0
5121   4       .6    1.1    1.8   4.7   2.5   2.5    2.2   2.2-888.0
5121   4  -838.0-883.0-388.0-888.0-888.0-888.0-888.0-888.0-388.0
5121   5       .4     .4     .5    1.2     .5    1.0     .9    .4-886.0
5121   5  -883.0-888.0-888.0-863.0-888.0-888.0-888.0-888.0-388.0
5121   6       .1     .3     .3     .2-999.0     .1     .3-999.0-338.0
5121   6  -888.0-888.O-888.0-888.O-888.0-888.O-888.0-88b.O-388.0
                              152
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5J3J   316.   4.88   13.3   7*20   9*50  4175  624 2254  33 /
5131  I    37.0-999.0 128.0   6.0  41.0  4b.O  39.0  48.O-888.0
5J3J  1  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5)31  2     9.2  11.9   9.2   9.2   9.6   9.5   6.9   8.4-388.0
5I3J  2  -888.0-883.0-888.0-888.0-888.0-888.0-888.O-888.0-880.0
5131  3     2.8   2.7   2.7   2.6   2.5   2.7   2.0   2.3-888.0
5131  3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5131  4     -.5   -.5   -.5   3.0     .9   1.7   -.5    1.4-888.0
5131  4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5131  5      .5    .5     .5     .0     .5     .6     .4     .5-888.0
5131  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5131  6  -999.J    .8     .3     .5     .2     .3-999.0     .3-888.0
5131  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.O-888.0
5161   268.    1.26    19.2   8120   J0i50   3299   493  2057   3J7
5161  1    3b.J  5/.0  55.0  46.0  32.0   41.0   41.0-999.O-888.0
D16J  1  -888.0-8dd.0-888.0-888.0-888.0-888.0-888.0-888.0-ddd.U
5I6J  2     3.7   4.3   3.8-999.0   2.4   2.8-999.0   4.4-888.0
13161  2  -88d.0-88d.0-888.0-888.0-888.O-88d.O-88d.0-888.0-8dd.O
5161  3     1.1   1.2   1.3    1.2   1.0    1.2     .9   1.2-ddd.O
5161  3  -888.0-8dd.O-«88.0-888.0-888.0-888.0-88d.O-888.0-888.0
5161  4     2.2   3.4   5.6    3.6   2.6   2.1    1.1   1.7-888.0
5161  4  -88d.0-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5161  5       .6     .9     .7-999.0     .9     .9     .7    .7-888.0
5161  5  -888.0-888.0-888.0-888.0-888.0-88d.0-888.0-888.0-888.0
5161  6       .4     .6     .2-999.0     .5     .5     .6    .5-8dd.O
5161  6  -888.0-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5162   302.   2.09   22.0   111 0   J3*30   2148   321  2006  300
5162   I    45.0  48.0  57.0   64.0   46.0   52.0   46.0  57.0-888.0
5162   1  -888.0-888.0-888.0-888.0-888.0-88d.0-888.O-888.0-888.0
5162  2     5.0   5.0   4.9   5.8    5.6    5.0    8.3   7.4-888.0
5162  2  -888.0-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5162  3     1.7   1.7   1.7   1.7    1.6    1.6    1.5   1.8-888.0
5162  3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5162  4       .9   1.9   2.2   4.1    2.3    2.8    1.4   2.3-888.0
5162  4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5162  5       .7     .8    .9   1.0     .7     .8    1.0   1.1-888.0
5162  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.O-88d.O
5162  6       .7   1.3    .8   1.0     .7    1.0     .7   1.1-388.0
5162  6  - 888.0-888.0-888.0-888.0-888.0-88d. 0-888.0-888.0-888.0
                               153
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5171   248.   1.47   19.2   7«IO   8«20  4928  736 2372  354
5J7I  I    75.0  95.0  90.0 186.0  58.0  64.0  54.0-999.0-388.0
5171  I  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
5171  2    N.I  12.1  14.5-999.0  10.3-999.0   8.0  24.7-ddd.O
5171  2  -888.O-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-d8b.O
5J7I  3     3.2   3.4   3.5   3.4   3.2   3.5   2.4   3.1-dd8.0
5171  3  -888.0-888.0-388.0-888.0-888.0-888.0-888.0-888.0-888.0
5171  4     3.7   4.4   6.2   2.0   2.0   1.5   1.3   2.7-888.0
5171  4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5171  5     1.3   1.2   1.4     .9   1.0   1.0   1.0   1.1-888.0
5171  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5171  6      .8   1.4    .7     .8    .7    ./    .9   1.4-888.0
5171  6  -888.0-888.0-888.O-888.0-888.0-888.0-888.0-888.0-888.0
5172   299.   1.78   24.5   8«DO   MHO  2987  446 1941  290
5172  1    67.0  63.0  60.0  61.0  56.0  81.0  /2.0  79.0-888.0
5172  1  -888.0-888.0-888.0-888.0-888.J-888.0-888.0-888.0-888.0
5172  2    11.8  12.4  11.4  14.3  11.2  U.l   8.0  13.9-888.0
5172  2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-880.0-888.0
5172  3     3.5   3.3   3.6   3.7   3.5   3.4   2.9   3.6-888.0
5172  3  -888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
5172  4     1.6   2.4   4.2   5.8   3.8   3.4   2.7   2.7-388.0
5172  4  -886.0-888.0-388.0-888.0-888.0-888.0-888.0-888.0-888.0
5172  5       .8     .8    .7     .8     .7     .8     .6     .7-888.0
5172  5  -888.0-888.0-388.0-888.0-888.0-883.0-888.0-888.0-888.0
5172  6       .5     .9    .3     .5     .3     .4     .6     .5-888.0
5172  6  -888.0-888.0-888.0-888.O-888.0-888.0-888.0-888.0-888.0
5181   306.   2.04   24.9    7*10   9«40  4304  643 2271  339
5181   I    73.0  90.0   77.0  103.0  79.0  106.0  97.0  M5.O-888.0
5181   1  -888.0-883.O-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5181   2    40.3  39.5   37.5   18.3  40.8  34.9  32.7  38.2-888.0
5J8J   2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5J8I   3     9.1   9.4   9.4   9.3    7.8   8.9    7.8    9.6-888.0
5J81   3  -888.0-888*0-388.0-888.0-888.0-888.0-888.0-888.0-888.0
5181   4       .7   1.0   2.3   5.1    2.0   2.9    3.0    2.8-888.0
5181   4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5J8J   5       .7     .7     .4     .7     .9     .7     .7     .6-888.0
5181   5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5181   6       .2     .4-999.O-9V9.0     .2     .3     .4     .6-888.0
5181   6  -888.0-888.0-388.0-888.0-888.0-888.0-888.0-888.0-888.0
                              154
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5191     56.   1.91   14.1   7i20   9*50  4)75  624 2254  337
5191   I     sl.O  50.0  56.O-888.0  5fa.O  52.U  91 .0  49.0-d8d.O
5191   1   -8dd.0-886.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5191   2    14.0  12.3  J2.1-888.0  12.5  13.0   9.7   7.8-dd8.0
519J   2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
PI91   3     3.3   3.2   3.3-888.0   3.4   3.3   2.9   2.2-388.0
5J91   3  -888.0-888.0-388.0-888.0-888.0-888.0-888.0-888.0-888.0
5191   4     1.1    1.8   I.8-888.0   3.3   3.4   2.1   1.9-388.0
5191   4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-88tt.O-888.0
5191   5      .7    .7    .6-888.0    .4    .6    .7    .6-888.0
5191   5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5191   6  -999.0    .4    .8-888.0    .3    .3    .7    .6-888.0
5191   6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5192    46.   3.74    lo.O  IOi3J   13»10  2208  330  1949  291
5192  1     48.0  46.0  33.0  51.0  38.0  40.0-888.0  53.0-d86.0
5192  1   -838.0-888.0-888.0-888.0-8dd.0-888.O-888.0-8d8.0-d8b.O
3192  2     8.5   8.6    .6-999.0   8.4   8.9-8dd.O   I0.3-d88.u
3192  2  -8dd.0-888.0-888.0-868.0-888.0-888.0-88d.0-888.0-ddd.O
5192  3     1.0   2.7    .3   2.5   2.4   2.5-888.0   2.6-888.0
5192  3  -883.0-888.0-d88.0-888.O-888.0-888.0-888.0-888.0-888.0
5192  4     -.6   -.6   -.6   4.9   2.0   l.6-8dd.O    1.4-888.0
5192  4  -883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-d88.0
5192  5       .8     .4    .8   1.0     .5     .5-883.0     .8-838.0
5192  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5192  6  -999.0-999.0-999.0-999.0-999.0     .2-888.0     ,3-88d.O
5192  6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
D201   238.    1.1 I    13.2   5i50   8«20  4751   710  1824   273
5201   1    58.0   86.0-888.0  73.0  69.0  bd.O   52.0  62.0-888.0
5201   1  -88d.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
D201   2    10.7   10.8-888.0   9.4    8.9    8.9-999.0   8.9-888.0
!p20J   2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5201   3     2.7   2.8-888.0   2.6    2.5    2.8   2.9   2.7-888.0
D20I   3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
520J   4     4.4   6.4-888.0   3.4    2.1    1.1    1.2   1.7-888.0
5201   4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5201   5     3.1   3.2-888.0   2.7    2.6    2.0    1.9   l.6-d8d.O
5201   5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5201   6     1.9   2.5-888.0   1.8    1.6    U6-999.0   1.6-888.0
5201   6  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
                              155
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5202   207.   J.96   20.0   9«50  !2<20  2411  360 1901  234
5202  I   -999.0  73.0-888.0  62.0  94.0  57.0  53.0  66.0-388.0
5202  I   -888.O-888.0-888.0-888.0-888.0-888.0-888.0-88d.0-dd8.0
5202  2    10.9  JJ.d-888.0  13.3  JO.9-999.0-999.0  I  I ./-B88.0
5202  2  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5202  3     3.0   3.0-888.0   3.3   3.2   3.0   2.2   3.J-888.0
5-202  3  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-ddd.O
5202  4     3.7   D. 1-888.0   3.0   2.4   1.9   1.5    1.7-888.0
5202  4  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-88d.0-888.0
5202  5     1.4   1.2-888.0   1.0   1.3-999.0-99>>.0    .9-888.0
5202  5  -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5202  6     J.I   1.1-888.0   J.I    .7-999.0-999.0    1.1-888.0
5202  6  -888.0-888.0-888.0-888.0-888.0-888.O-888.0-888.O-888.0
5232   212.   3.47   23.0  10*50   I3«IO  2163  323 1962  293
5232  J  -999.0  46.0-d88.0  37.0  31.0  47.0  41.0-999.0-8dd.0
5232  1  -883.0-8bd.0-dd8.0-888.0-88d.0-88b.0-88d.0-888.0-886.0
5232  2     4.6   4.2-888.0-999.0   4.5   3.0   3.8-999.O-ddd.O
5232  2  -888.0-88d.0-d8d.0-888.0-888.0-888.0-888.0-888.O-ddb.O
5232  3     1.3   1.4-888.0    1.3   1.2   1.4   1.1     .l-dd8.0
5232  3  -888.0-8dd.0-d88.0-888.0-88d.0-888.0-88d.O-88b.O-ddd.G
5232  4     2.5   4.9-888.0    -.6     .9   -.6   -.6    -.6-388.0
5232  4  -888.0-883.0-888.0-888.0-888.0-888.0-88d.O-88d.O-88U.O
5232  :>     1.3   J.1-388.0-999.0   1.3   1.2   I.d    l.4-d88.0
5232  5  -888.0-88d.0-d88.0-888.0-888.0-888.0-888.0-888.0-838.0
5232  6     1.1   1.0-888.0-999.0     .9   1.1   J.I     .9-888.0
5232  6  -883.0-88d.0-888.0-888.0-888.0-888.0-888.0-888.0-3dd.O
5242   222.   3.62    23.9   10«20   12*50  2269   339  1928   288
5242   1    61.0  69.O-888.0 81.0  45.0  5/.0  106.0 81.0-388.0
5242   I   -888. 0-888.0-888.O-888.0-8dd.O-t*38. 0-888. O-888. 0-888.0
5242   2    12.J  13.0-888.0  12.3   11.6  12.2    9.3  11.4-888.0
5242   2   -888.0-888.0-888.0-888.0-888.0-888.0-883.0-888.0-388.0
5242   3      3.5   4.O-888.0  3.7    3.4   3.7    2.9   3.4-888.0
5242   3   -888.0-883.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0
5242   4      2.3   D.2-888.0  -.6    -.6   -.6    -.6   -.6-888.0
5242   4   -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-388.0
5242   5       .5     .5-888.0    .5     .4     .5     .4    .5-888.0
5242   5   -888.0-888.0-888.0-888.O-888.0-888.0-888.0-888.0-888.0
5242   6      1.3   1.3-888.0   1.5    I.I    1.3    1.6   1.7-388.0
5242   6   -888.0-888.0-888.0-888.0-888.0-888.0-888.0-888.0-338.0
                              156
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-888.0-888.0 1.2 8.0 4.1 4.7 3.7 3./ 3.1
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-888.0-886.0 .3 .9 .5 .6 1.2 .6 .6
-886.O-886.0 1.1 .4 1.0 1.0-999.0 .6 1.1
-888.0-886.0-999.0 .5 .4 .5 .4 .8 .7
-886.0-888.0 .8-999.0 .9 .9-999.0 .6 1.5
231. 2.21 19.6 I4i 0 16*20 2690 402 3592 537
1
1
2
2
3
3
4
4
5
5
6
6
-888.0-886.0 81.0 71.0 50.0 59.0 51.0 41.0 56.0
-886.0-888.0 37.0 15.0 22.0 32.0-999.0 39.0 35.0
-888.0-886.0 20.9 25.0 22. O 24.0 22.8 23.0 18.9
-888.0-886.0 1.8 1.1 2.4-999.0 1.4 .2 1.6
-888.0-888.0 6.6 7.9 6.8 8.0 7.0 8.2 6.6
-888.0-888.0 .5 .2 .3 .5 .3 .5 .3
-888.0-888.0 7.7 2.0 1.0 1.3 -.7 1.1 1.4
-888.0-888.0 - 1.9 -.7 -.7 -.7 -.7 -.7 -.7
-888.0-888.0-999.0 1.5 .9 1.4 .9 1.0-999.0
-888.0-886.0 .9 1.1 .9 1.1 1.0 1.0 1.0
-888.0-886.0-999.0 .8 .3 .4-999.0 .1-999.0
-868.0-888.0 .7 .4 .7 .7 .7-999.0 .6
157
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                                   TECHNICAL REPORT DATA
                            (Please read Instructions on the reverse before completing)
1. REPORT NO.
   EPA-600/4-79-011
                             2.
                                                           3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
 DISPERSION OF  POLLUTANTS NEAR HIGHWAYS
 Data Analysis  and  Model  Evaluation
                                                           5. REPORT DATE
                                                          February 1979
                                                        6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
 S.  Trivikrama
 Perry Samson
            Rao,  Michael  Keenan, Gopal  Sistla, and
                                                           8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
 New York State  Department of
 Environmental Conservation
 Albany, New  York  12233
                                                         10. PROGRAM ELEMENT NO.

                                                         1AA601   CA-05 (FY-77)
                                                         11. CONTRACT/GRANT NO.
                                                          R-803881-01
                                                          R-804579-01
12. SPONSORING AGENCY NAME AND ADDRESS
 Environmental Sciences  Research Laboratory - RTF, NC
 Office of Research  and  Development
 U.S.  Environmental  Protection  Agency
 Research Triangle  Park, NC 27711	
                                                            13. TYPE OF REPORT AND PERIOD COVERED
                                                          Final  Q/75 - 7/78
                                                         14. SPONSORING AGENCY CODE

                                                          EPA/600/09
15. SUPPLEMENTARY NOTES
16. ABSTRACT
      The validity  of various assumptions  underlying mathematical  modeling  of
 pollutant dispersion near at-grade  highways was examined  and the simulation
 capability of various dispersion models  determined.  The  data base generated
 during the Long  Island Dispersion Experiment is utilized  to  study the micro-
 meteorological characteristics adjacent  to a highway and  to  evaluate four
 numerical and four Gaussian highway  dispersion models.
17.
                                KEY WORDS AND DOCUMENT ANALYSIS
                  DESCRIPTORS
                                              b.IDENTIFIERS/OPEN ENDED TERMS
                                                                      c.  cos AT I Field/Group
 * Air pollution
 * Atmospheric diffusion
 * Highways
 * Mathematical Models
 * Evaluation
 * Micrometeorology
        processing
Data
                                                                       138
                                                                       04A
                                                                       04B
                                                                       09B
                                                                       12A
18. DISTRIBUTION STATEMENT
  RELEASE TO PUBLIC
                                               19. SECURITY CLASS (This Report)
                                                   UNCLASSIFIED
                                                                       21. NO. OF PAGES
                                                                         170
                                           20. SECURITY CLASS (Thispage)
                                                UNCLASSIFIED
                                                                          22. PRICE
EPA Form 2220-1 (9-73)
                                             158
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