600382056
   METEOROLOGY AND AIR QUALITY PATTERNS IN
            ST. LOUIS RAPS PROGRAM
             Upper Level Analyses
                    by

                 Mark Vuono
               Fletcher Shives
                Elmer Robinson

        Air Pollution Research Section
       Chemical  Engineering Department
         Washington State University
          Pullman,  Washington  99164
         EPA Grant  No. 806176010
               Project Officer:

               George Holzworth
     Meteorology and Assessment Division
  Environmental  Sciences Research Laboratory
Research Triangle Park, North Carolina  27711
  ENVIRONMENTAL  SCIENCES RESEARCH LABORATORY
      OFFICE OF  RESEARCH AND DEVELOPMENT
     U.S.  ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE  PARK, NORTH CAROLINA  27711

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                                  DISCLAIMER
     This report  has been reviewed by the Environmental Sciences Research
Laboratory,  U.S.  Environmental  Protection Agency, and approved for publica-
tion.  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.

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                                    ABSTRACT
     A statistical map typing procedure developed by Lund to classify synoptic
weather patterns into similar groups was used to stratify regional  weather
patterns.  The investigation extended over a 800-km radius centered about the
greater St. Louis area and was intended for subsequent application  to air
pollution studies.  This typing analysis was applied to 850 mb height data and
to geostrophic wind patterns based on surface pressure gradients.   In the
analysis program, data for a specified number of weather stations  on a given
day are correlated with the same parameters measured on each of the other days
in the four year period 1973 through 1976.

     A total of 21 separate weather map types were identified for  the 850 mb
level synoptic patterns, and a total of 36 map types were identified to
classify the geostrophic wind flow across the St. Louis region based on
surface pressure differences.

     To show the relationships between the synoptic weather types  and air
quality, this report also contains a statistical comparison of the  map types
with air quality data.  The air quality analysis included ozone, carbon
monoxide, total suspended particles, sulfate, and nitrate concentrations
sampled in the St. Louis Regional Air Monitoring System of the EPA, for a
period of approximately two years during 1975-76.

     The results show that the synoptic map typing program, which  separates
synoptic weather patterns into identifiable map type classes, has  a definite
and useful correspondence with significantly different levels of air pollutant
concentrations.  The results also indicate that the correspondence  between map
types and average air quality concentrations is higher for the 850  mb typing
procedure than for the surface or geostrophic typing programs.  This is
attributed to the fact that the 850 mb typing scheme stratified the data into
fewer types than did the other two schemes.
                                      m

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                                 TABLE OF CONTENTS


Abstract	iii
Figures	vi
Tables	vii

     1.   Introduction	   1
               Study Objectives	   1
     2.   Research Techniques and Results 	   3
               850 mb Map Typing	   3
               Geostrophic Wind Map Typing  	   6
               Air Quality Data Selection	11
               Air Quality vs. 850 mb Map Types	15
               Air Quality vs. Geostrophic Wind Map Types	32
               Comparison of 850 mb, Geostrophic, and
                    Surface Map Typing Schemes  	  50
     3.   Summary and Conclusions	58

References	60
Appendices

     A.   Daily Map Type Assignments	61

     B.   Weather Type Base Maps

          1.  For 850 mb	66

          2.  For Geostrophic Wind	88

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                                 FIGURES
Number                                                                Page
   1.  Correl ation between network  sea  level pressures	     7
   2.  RAMS stations locations	    13
   3.  CO concentration and log concentration
         distributions  for map  type B(850F)	    15
   4.  Synoptic analysis for map type E(850S),
         June 6,  1976	    27
   5.  Synoptic analysis for map type E(850SP),
         April  28, 1976	    28
   6.  Synoptic analysis for map type A(850F),
         November 13, 1973	    29
   7.  Synoptic analysis for map type D(850F),
         November 28, 1973	    3,0
   8.  Synoptic analysis for map type F(850S),
         June 19, 1976	    31
   9.  Synoptic analysis for map type B(GeoS),
         July 3,  1974	    44
  10.  Synoptic analysis for map type C(GeoSP),
         May 12,  1975	    45
  11.  Synoptic analysis for map type I(GeoF),
         November 23, 1973	    46
  12.  Synoptic analysis for map type C(GeoW),
         January 29, 1973	    47
  13.  Synoptic analysis for map type D(GeoF),
         October 2, 1975	48
  14.  Synoptic analysis for map type F(GeoSP),
         April  7, 1974	    49
  15.  Frequency distribution for surface  and geostrophic
         map types relating to  map  types D(850S)  and E(850S)  ....     56
                                     vi

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                                    TABLES
Number                                                                   P^age

      1.  Stations for 850 mb level  used in this study	    4

      2.  Summary of seasonal synoptic map types for
            850 mb level, 1973-1976  	    8

      3.  Geostrophic station pairs  used in this study	    10

      4.  Summary of seasonal synoptic map types for
            geostrophic wind, 1973-1976 	    12

      5.  Seasonal 850 mb map types  ranked by ozone
            concentrations averaged  for stations 101,
            104, 105, 106, 107,  110	    16

      6.  Seasonal 850 mb map types  ranked by carbon
            monoxide concentrations  averaged for
            stations 101, 104, 105,  106, 107, 110	    18

      7.  Seasonal 850 mb map types  ranked by total
            suspended particle concentrations averaged
            for stations 103, 105,  106, 108	    20

      8.  Seasonal 850 mb map types  ranked by sulfate
            concentrations averaged  for stations
            103, 105, 106, 108	    22

      9.  Seasonal 850 mb map types  ranked by nitrate
            concentrations averaged  for stations
            103, 105, 106, 108	    24

     10.  Seasonal geostrophic map types ranked  by ozone
            concentrations averaged  for stations 101,
            104, 105, 106, 107,  110	    33

     11.  Seasonal geostrophic map  types ranked  by carbon
            monoxide concentrations  averaged for stations
            101, 104, 105, 106,  107,  110	    35

     12.  Seasonal geostrophic map types ranked  by total
            suspended particle concentrations averaged
            for stations 103, 105,  106, 108	    37

                                      vii

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Number                                                                  Page

     13.   Seasonal  geostrophic map types  ranked by
            sulfate concentrations averaged  for
            stations 103,  105, 106, 108	   39

     14.   Seasonal  geostrophic map types  ranked by
            nitrate concentrations averaged  for
            stations 103,  105, 106, 108	   4.1

     15.   Seasonal  surface map types  ranked  by ozone
            concentrations averaged for stations
            101,  104,  105, 106,  107,  110	   51

     16.   Comparison of seasonal  950  mb,  geostrophic, and
           surface map types  in  relation  to  maximum and minimum
            03,  CO, and TSP mean concentrations	   54

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                                    SECTION 1

                                   INTRODUCTION


     The relationship between air pollutant concentrations  and  the  prevailing
synoptic weather patterns has been of concern  to air quality analysts  for some
time.  The dispersion and transport of pollutants between a source  and a
receptor is controlled primarily by the wind field at the time  the  pollutant
is emitted into the atmosphere and while it remains airborne.   The  total  wind
field includes the direction, speed, and the turbulence or  mixing processes of
the flow.  For transport to occur on a mesoscale basis, with a  distance on the
order of 100 km and a time factor of one day,  the upper level winds (up to a
height of 1-2 km) as well as the surface flow  are of primary concern.
Recently, the influences of the upper level winds and their relation to air
pollution have been taken into consideration in the formulation of  pollutant
dispersion models.

Study Objective

     The primary goal of this study was to determine the synoptic weather
patterns on a regional scale around St. Louis  in terms of a limited number of
characteristic types and to relate these patterns to specific pollutant con-
centrations.  To achieve this, the surface weather map types determined using
the method of Lund (1963) and developed by Robinson and Boyle (1980) as well
as the upper level map types resulting from this study have been used  to
describe the synoptic weather patterns around  St. Louis. Once  the  synoptic
pattern types were determined, they were then  correlated with ozone (O^)?
carbon monoxide (CO), total suspended particles (TSP), sulfate  (S07),  and
nitrate (NOl) concentrations to obtain relationships between weather types and
air quality.  The Duncan new multiple range test (Steel and Torrie, 1960) was
used to test for statistical significance.  Forecasting techniques  were not an
objective of this study although the delineation of useful  weather  types  and
corresponding pollutant relationships could provide a first step toward an
objective forecasting procedure.

     The historical background and relevance of the Lund (1963, 1971)  map
typing methodology are fully described in an earlier report by  Robinson and
Boyle (1980).  In their study, the method developed by Lund (1963)  was used to
develop a series of weather types based upon surface sea level  pressures
observed at 21 National Weather Service stations over a region  of 500  miles
radius centered on St. Louis, Missouri.  Synoptic data for  a four year period,
1973-1976, were obtained for each station.  The synoptic data were  grouped
into seasons in the conventional manner as follows:  Winter: December, January,
February; Spring:  March, April, May, Summer:   June, July,  August;  Fall:
September, October, November.  The result of the study by Robinson  and Boyle

                                      1

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(1980) was the identification of a total  of 52 surface map types:   12 winter
map types, 13 spring map types, 14 fall  map types,  and 13 summer map types.
For each season, approximately 90 percent of the data was assigned to specific
types, which was comparable to 89 percent typed by  Lund (1963).   After the
seasonal map types were defined, they were related  to pollutant  data obtained
from the St. Louis Regional Air Measurement network.   Robinson and Boyle (1980),
correlated total suspended particles and carbon monoxide with map type.   Their
results are discussed and compared with  the results of this study in a
following section.

     In this study the emphasis has been placed on  large scale weather patterns,
i.e. those that could be assessed from regular synoptic maps. This was done
so that research results could be applied readily by other investigators to
tasks such as model verification.

     The present report considers weather types based on 850 mb  height obser-
vations as an approximation to the wind  field and weather patterns at the top
of the planetary boundary layer.  Although the 850  mb wind field is generally
considered to be geostrophic, the synoptic weather types based on 850 mb con-
tours will relate to more than just the  wind field.  This report also assessed
the application of weather map types that approximated the geostrophic wind
field directly from an assessment of the sea level  pressure gradient field
across the study area.  As will be shown the geostrophic wind field typing was
less successful than the 850 mb contour  typing, and thus it might be concluded
that the added synoptic pattern inferences in the contours were  useful
additions to the system.  In terms of general pollutant transport within the
planetary boundary layer Hoecker (1977)  has shown that wind trajectories
intermediate between the surface and geostrophic winds are probably the more
realistic approximation of the pollutant transport field across  the Midwest.

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                                    SECTION 2

                         RESEARCH TECHNIQUES AND RESULTS


     This research program was developed in two major phases:   first, the
development of 2 sets of seasonal weather types, one based on  850 mb contours
and the other on surface pressure gradients; and second, the assessment of
statistical relationships between air quality in St. Louis and synoptic
weather as represented by the predetermined weather types.  The synoptic
weather types were defined using observations across a major part of the
Midwest where the region of interest was defined by a circle of 800 km radius
centered on St. Louis.  Thus this research provides an extension to upper
boundary layer weather patterns of the previous study of relationships between
surface weather types and St. Louis air quality by Robinson and Boyle (1980).

     The use of 850 mb height data, as mentioned above, to define the synoptic
situations, including the general flow regime was a practical  choice because
of the general availability of this observation and the fact that it would
define conditions at about 1.5 km above sea level.  Although mid summer
maximum mixing depths might exceed this altitude the 850 mb patterns were
considered to be a satisfactory representation of the wind and general weather
patterns in the upper part of the planetary boundary layer.

     The other set of weather map types were developed based on sea level
pressure gradients between 17 pairs of National Weather Service stations in
the midwest region around St. Louis.  These pressure gradient  data provide a
set of patterns related to the sea level pressure pattern geostrophic wind.
As indicated above, this is usually a reasonable approximation of the upper
boundary layer (approximately 1 km) wind flow (Slade, 1968).  The surface
pressure patterns across this region had been determined by Robinson and Boyle
(1980) in their study of synoptic weather patterns around St.  Louis.  Thus the
weather situations affecting the St. Louis region could be identified on the
basis of three different types of patterns -- the 850 mb height contours, the
surface geostrophic winds, and the surface pressures.

850 mb Map Typing

     Lund's (1963) technique for map typing pressure patterns  was used on the
850 mb geopotential heights instead of the surface sea level pressures to
determine the upper level wind flow patterns.  Most of the stations used were
the same ones used by Robinson and Boyle (1980), with nearby substitute
stations for the ones that did not collect upper level radiosonde data.
Eighteen stations were used for the map typing procedure, covering an area of
approximately 800 km radius centered on St. Louis, Missouri.  Table 1
identifies the stations used in this study and also indicates  stations

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substituted  for the  original stations used by Robinson and Boyle (1980).

     The data used in this  analysis were the heights above sea level  of
the 850 nt> surface given  in geopotential meters for OOZ (6 pm CST)  covering
a four year  period,  1973-1976.  Both the time and the period were chosen  for
ease of comparison with Robinson and Boyle's (1980) surface map types for the
same time and period.  The  data were separated into .four seasons:  Winter:
December, January, February; Spring:  March, April, May; Summer: June,
July, August; Fall:  September, October, November.

     The technique developed by Lund (1963) is basically a simple linear
correlation  between  values  at  a given set of stations on one day and  values
at the same  stations on a second day.   It is then assumed that a good corre-
lation between these values for the two days indicates similar weather
patterns, i.e., the  same  weather map type, on the two selected days.
            Table 1.   Stations used in this study for 850 mb heights
        Call  Letters
                              Name of Station
AHN (ATL)
JAN (ME I)
BNA
LIT (MEM)
HTS
SAL (STL)
TOP (MKC)
MON (SGF)
DDC
PIA (ORD)
FNT (DET)
SSM (TVC)

OMA (DSM)
PIA (ALO)
DAY (IND)
HON (FSD)
STC (MSP)
OMA (GRI)
OKC
SHV*
LGV (SHV)**
Athens (Atlanta), Georgia
Jackson (Meridian), Mississippi
Nashville, Tennessee
Little Rock (Memphis), Arkansas
Hunti ngton, West Vi rgi ni a
Salem (St. Louis), Illinois
Topeka (Kansas City), Kansas
Monet (Springfield), Missouri
Dodge City, Kansas
Peoria (Chicago), Illinois
Flint (Detroit), Michigan
Sault Sainte Marie (Traverse City),
Michigan
Omaha (Des Moines), Nebraska
Peoria (Waterloo), Illinois
Dayton (Indianapolis), Ohio
Huron (Sioux Falls), South Dakota
St. Cloud (Minneapolis), Minnesota
Omaha (Grand Island), Nebraska
Oklahoma City, Oklahoma
Shreveport, Louisiana
Longview (Shreveport), Texas
Indicates stations used by Robinson and Boyle (1980)
 Shreveport  was  used  from January, 1973 to July, 1975.
  Longview was used from July, 1975 to December, 1976.
     **

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     A map type is  a group of weather maps with a pressure or other weather
pattern distinctive enough to be classified separately from other  groups of
weather maps.   The  simple linear correlation procedure of Lund (1963) used
sea level  pressures and was based on the statistical  interdependence between
the sea level  pressures at a given set of stations on one day and  the pres-
sures at the same stations on a second day.  For example, in the St. Louis
program as illustrated by Figure 1 if the X-axis (abscissa) is used to plot
station pressures for day 1 and the Y-axis (ordinate) the pressures for day 2,
the pressure data from 21 stations will define a corresponding set of 21
points in the X-Y field.  Standard statistical techniques can then be used to
determine the correlation between station pressures on day 1 versus those on
day 2.  It is assumed, then, that a "good" correlation between station pres-
sures on the two days is indicative of similar synoptic map patterns on the
two days.   In Figure 2, the correlation coefficient is 0.81 between June 1,
1973 and June 7, 1973 data.  Sea level pressures were used by Robinson and
Boyle (1980) while  the present study correlates 850 mb heights or  sea level
pressure gradients  over a fixed grid of station pairs.

     Previous statistical typing by Lund (1963) and by Robinson and Boyle
(1980) were based on weather types being identified by correlations of 0.70
or greater between  each map date within the type and an identified base map.
The choice of magnitude of the lowest acceptable correlation for determining
a type classification was examined in detail  by Lund (1963).   He determined
that the same key or base maps would be identified with the use of either 0.90
or 0.80 instead of  0.70.  The major impact of the choice of a value for the
lowest acceptable correlation was in number of cases falling into  each type
and the number of untyped maps.  The higher the limiting correlation the
fewer the number of maps in each case, but not much difference in  the identi-
fied types, and the larger the number of untyped maps.  After a careful con-
sideration of the limiting correlation value Lund (1963) chose 0.70 as his
lowest acceptable correlation.  With this correlation limit he was able to
type 89% of his map file.  Robinson and  Boyle (1980) also used 0.70 as a
lowest acceptable correlation and typed 90% of their map file.  In the present
study a value of 0.70 was used for the lowest acceptable correlation coeffici-
ent for type identification with the 850 nb height patterns but a  value of
0.65 was used with  the pressure gradients or geostrophic wind patterns.

     Following Lund's guidelines, the St. Louis regional synoptice- map types
were determined by  the following steps:

     1.  Correlate  the 0000 GMT weather parameter value for each day of the
         selected season with the corresponding parameter value on every day
         of the season over the four-year test period.

     2.  Identify the day which has the most other days related to it by a
         correlation coefficient of 0.70 or greater.   Designate this day as
         the base map for Type A and the maps correlated with it (r ^ 0.70)
         as belonging to the Type A classification.

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     3.   Remove all  Type A maps  from the  map  file  and  then  identify  the  date
         in the remaining maps which now  has  the most  maps  suitably  correlated
         (r >_ 0.70)  with it.  This  is the base  map for Type B  and  the  maps
         correlated   with it  make up the  Type B classification.

     4.   Remove all  Type A and Type B maps from the file  and proceed to  ident-
         ify the Type C base  map and the  maps in the Type C classification,
         as was done for B.

     5.   Repeat the  typing process  until  most (about 90%  or more)  of the maps
         have been typed.

     6.   Since a given map may be well  correlated  with more than one type,
         review all  calculated correlations relating each map  and  the  several
         base maps.   Determine that the map type assigned by the first cor-
         relation check was the  type that had the  highest correlation.  If
         the given map is not assigned to the base map type having the high-
         est correlation, move the  test map to  the map type which  is most
         highly correlated.

     7.   Continue the map typing process  until  each of the  four seasons  has
         been completed.

In this  study, the WSU AMDAHL 470V/6-II computer system was used for the
correlation analysis.

     This technique identified the  following  850 mb level types: 3 winter
map types, A(850W) through C(850W): 6 spring  map types, A(850SP) through
F(850SP); 6 summer map types, A(850S) through F(850S); and  6 fall  map  types,
A(850F)  through F(850F).  Thus a total  of 21  850 mb map types  were identified,
compared to 52 surface types  identified by Robinson and Boyle  (1980).   The
results  of the 850 mb map typing procedure are  shown in Table  2, with  the
date of  the base map (the map that  .had the most days correlated with it) and
the number of cases or days that correlated with the base map.  A  correlation
coefficient of 0.70 or greater was  used to define  an acceptable correlation
between  daily conditions.  The map  typing technique on 850  mb  data was very
successful with between 88 and 93 percent of the total number  of days  being
assigned types.  The 850 mb base map types are  reproduced in Appendix  B.
Appendix A lists the map type assigned to each  day of the 4-year typing period.


Geostrophic Wind Map Typing

     The geostrophic wind is defined as a flow  that results from the
balance  between the pressure gradient force and the coriolis force (e.g.
a basic  meteorological text such as:  Hess, 1959).  The geostrophic wind
is essentially the same as the  gradient wind, except that the  geostrophic
wind neglects the curvature of  the  flow while the  gradient  wind includes
curvature of the flow.  For this research we are  neglecting the effects of
curvature and are assuming that  the geostrophic wind is representative
of the flow  above the  planetary  boundary  layer.

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     In calculating the geostrophic wind, the pressure gradient, or change in
pressure with distance, is the main parameter of concern.   The equations used
to calculate the geostrophic flow are in the form of:


                         Vq = -1
                          3   pf

where p is the density of the air, f is the coriolis parameter which is equal
to 2n sin is the latitude,
and dP/dn is the local change in pressure with distance.

     For the purposes of this study, several assumptions  were made to simplify
the geostrophic wind calculations.  First, it was assumed that at any given
time the density of the air was the same at all  of the stations considered.
Second, it was assumed that the coriolis parameter, f, did not vary signifi-
cantly over the region.  With these two assumptions, the  geostrophic wind is
then proportional to the gradient of sea level pressure over an area, and
approximates the actual wind even though the geostrophic  wind represents
isobars without curvature.

     For the purposes of applying the map typing process  a data set based on sea
level pressure gradients between two selected stations instead of the surface
pressure gradient at a given station was used.  Since the pairs of weather sta-
tions were always the same and since the distance between two stations remains
constant, the component of the geostrophic wind normal to the line between the
two stations and directed such that low pressure is to the left of the flow.

     In this phase of the study, the potential station pairs (i.e., pressure
gradients) were selected from the stations used in the other portions of this
program, the 850 mb height analysis and the surface analysis of Robinson and
Boyle (1980).  The goal of the sector selection was to provide variously
oriented sectors around St. Louis so that the geostrophic wind components
identified by the individual pressure gradients would provide a reasonable
representation of the geostrophic flow regime across the  region.  In designing
the sector combinations it was assumed that especially long sectors should be
avoided because of the increasing probability of a nonuniform pressure gradient
along the sector.  It was practical to limit the sector lengths to less than
250 km.  In addition the sectors should wherever possible meet with a large
angle between adjacent sectors so that the resultant components of the geo-
strophic wind in the adjacent sectors would define more closely the geostro-
phic wind vector of that particular region.  With these several assumptions, a
number of different sector combinations were tested with  the final judgement
being based on the performance of the particular sector combination in the
weather typing procedure described above.  The preliminary tests were based on
a single season of data to limit computer costs.  This procedure resulted in a
data set consisting of pressure gradients across 17 sectors using the 17 pairs
of stations listed in Table 3.  It was necessary, however, to lower the corre-
lation coefficient used to identify a given weather type  from 50.70 to sO.65
for the geostrophic wind pattern study.  This change resulted in the assign-
ment of map types to between 72 and 80% of the days in the 4-year test period.

-------
     After the final combination of station pairs were decided upon,  the
pressure differences were calculated for the four year period for each pair
of stations,  and  the pressure differences were used to map-type the data.
When the map  typing procedure was carried out on these surface pressure
difference data,  the results were: 9 map types for winter, A(GeoW) through
I(GeoW); 9 spring map  types, A(GeoSP) through I(GeoSP); 9 summer map  types,
A(GeoS) through I(GeoS);  and 9  fall map types, A(GeoF) through I(GeoF).
   Table 3.   Station Pairs  Used  for Geostrophic Map Types.
Call Letters
BNA-MEM
DSM-MKC
DSM-ALO
IND-STL
IND-HTS
IND-BNA
JAN-SHV
MEM-JAN
MKC-SGF
MKC-STL
MSP-ALO
MSP-FSD
ORD-STL
ORD-IND
ORD-ALO
SGF-MEM
TVC-DET
Station Combinations
Nashville, TN - Memphis, TN
Des Moines, IA - Kansas City, MO
Des Moines, IA - Waterloo, IA
Indianapolis, IN - St. Louis, MO
Indianapolis, IN - Huntington, WV
Indianapolis, IN - Nashville, TN
Jackson, MS - Shreveport, LA
Memphis, TN - Jackson, MS
Kansas City, MO - Springfield, MO
Kansas City, MO - St. Louis, MO
Minneapolis, MN - Waterloo, IA
Minneapolis, MN - Sioux Falls, SD
Chicago, IL - St. Louis, MO
Chicago, IL - Indianapolis, IN
Chicago, IL - Waterloo, IA
Springfield, MO - Memphis, TN
Traverse City, MI - Detroit, MI
   All stations are hourly reporting National  Weather Service Stations.
                                       10

-------
Table 4 gives a summary  of the map typing  results, with the date of the
base map (the map that  had the most days correlated with it) and the number
of cases or days that correlated with each base map.  The surface weather maps
corresponding to the geostrophic base map types derived by this procedure are
reproduced in Appendix  B.  Appendix  A  lists types-for  the 4-year study period.

Air Quality Data Selection

     In order to complete  the objectives of this  study, pollutant data from
the St. Louis Regional Air Measurements  (RAMS) network were correlated with
the synoptic map types developed in this study, in an attempt to better
understand the local  and regional air pollution conditions.  From all  of the
pollutant data collected by  the RAMS  network, five pollutants were chosen
to accomplish this objective.  These five  pollutants were ozone (03),  carbon
monoxide (CO), total  suspended particles (TSP), sulfate (S0|) and nitrate
(N0§).

     In the RAPS program,  air quality data were collected from January 1975
through December 1976.   Sampling for 03  and CO was continuous and averaged
on an hourly basis at  all  of the 25 RAM  stations.  High volume sampling was
used for TSP, SO^, and  N0§ and 24-hour average samples were collected
every third day at selected  stations throughout the network.

     Stations representative of the air quality of St. Louis central urban
area were chosen from the  25 stations in the RAMS network depicted in Figure
2.  For 03 and CO, stations  101, 104, 105, 106, 107 and 110 were selected
and for TSP, SOj and NOo,  stations 103,  105, 106  and 108 were chosen.   These
stations were selected to  provide an indication of the average concentrations
of the  pollutants across the central part  of the St. Louis commercial  and
industrial  area.  It was expected that changes in synoptic conditions
would have the most influence and thus be detected most readily in this part
of the  city since the concentrations tend to be maximized there.

     Once the pollutant  data were collected, they were classified and
averaged by synoptic map types for each  season for both the 850 mb and
geostrophic map types.   The  ozone data were averaged by daily one hour maxi-
mum concentrations for the two year period 1975-1976.  The one hour maximum
concentration was chosen because there is  a strong diurnal  03 cycle, and it
was concluded that the maximum value would be the best indicator of synoptic
effects.  The CO data were analyzed by daily average concentrations for the
two year period.  The daily  average was used to minimize errors that^ could
occur if a one hour value  was used.  The data for TSP, S0| and N03 were
analyzed by 24 hr averages for every third day for the two year period.

     To determine if there was a significant relationship between map  types
within a season certain  statistical tests were applied to the stratified
pollutant data.  Since  it  was found that the pollutant data used in this
study usually followed  a log-normal distribution, and to ensure greater
sensitivity throughout the analysis, the logarithms of the pollutant values
as well as the basic pollutant data were used for the tests.  Figure 3 shows
the concentration and logarithmic concentration distributions for CO for
the B (850F) map type.   The  figure shows that while the data are skewed to
                                        11

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Figure 2.   St.  Louis Regional  Air Pollution  Study air monitoring network,
            1975-76.
                                13

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                          14

-------
the lower values, by taking the log of the data, a more normal  distribution
results.  Since most statistical tests handle normally distributed data better
than skewed data, the statistical tests were applied to both the arithmetic
and geometric means of the concentration data.

     The first test performed on the pollutant data which had been stratified
by map types for each season was an analysis of variance and a F test.   For
each pollutant, the mean concentration for one map type was compared to the
mean concentrations for each of the remaining map types within the same
season.  The presence of significant differences between the concentrations
for each type were determined by comparing the means for each map type.  The
results indicated that there were differences, and thus a more powerful
statistical procedure, the Duncan's New Multiple Range test, was employed
(Steel and Torrie, 1960).   First, this tests compared the means for pairs of
map types within a season, and determined if there were significant
differences between the map types.  Second, this test ranked the map types
from higher to lower concentration, and third, it indicated which ones  were
significantly different from each other and which were not.  Both the actual
concentration data and the logarithms of the concentration data were used in
this test.

Air Quality vs. 850 mb Map Types

     A tabular ranking of seasonal map types by high to low concentrations of
0.,, CO, TSP, SOT, and NOZ is given in Tables 5 through 9, which also shows the
map types, number of station pollutant observations, mean concentrations,
significant differences between map types, and remarks on the synoptic  flow
for each map type.  Since there is a tendency for certain map types to
identify with either higher or lower pollutant concentrations, some of  the
more important map types will be reviewed in the following discussion.

     A close examination of the results listed in Tables 5 through 9, shows
that the correlation with pollutant values mentioned above does exist for the
850 mb synoptic flow.  Specifically, the results indicate that higher
pollutant concentrations occur when there is a high pressure system present or
when the flow is from the SW quadrant, while lower concentrations are related
to low pressure systems or a northerly flow into St. Louis.  This is shown by
comparing the map types for each pollutant for each season and choosing the
ones which correspond to high or low concentrations on a consistent basis.

     For the winter season, map types A and C correlate with high pollutant
concentrations while map type B is significantly lower for all  of the
pollutants analyzed except 0,.  This situation occurs because 03 concentra-
tions are at a background level for the winter season, and, as Shown by
Table 5 there is no significant difference between map types.  However, map
type C has a SSW flow into the St. Louis area and map type A has a westerly
flow.  Thus, these two elevated 03 map types compare well with most of  the map
types for the spring, summer, and fall seasons which have the significantly
higher mean 0^ concentrations.  For example, map types D and E for the
spring season; D and E for the summer season, and A, C, and F for the
fall season all correspond to significantly higher pollutant concentrations


                                       15

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and all have flows from the SW quadrant or flows  indicative  of the  presence  of
a high pressure system.

     Figures 4, 5, and 6 show the 850  mb patterns for map  types E  (850S),
E (850SP), and A (850F), respectively.   Map type  E (850S), Figure 4,  corre-
lates with generally elevated pollutagt concentrations,  ranking first in  the
summer season for CL, CO, TSP, and SOT while ranking  only  fifth for N03>   The
weather pattern associated with this map type,  as indicated  by Figure 4,  is
dominated by a large high covering most of the  area east of  the Rocky
Mountains.  The high center is north of St. Louis over the Great Lakes.   Winds
into the St. Louis area are generally  from the  easterly  gradient with
relatively weak speeds of about kts.
                               4 /?

     Map type E (850SP), Figure 5, is  an elevated pollutant  type for  the
spring season.  It was ranked first for 03, COL,  and  N03,  and it was  not
significantly different in average concentration  from tne  highest  ranked  map
types for TSP and SO,.  The synoptic pattern near St. Louis  for this  map  is
influenced by a broad weak ridge between east coast and  west coast  low
centers.  The St. Louis area is generally in a  cold region with light and
variable winds.  Figure 6 shows the 850 mb flgw for map  type A (850F). This
fall map type was ranked first for TSP and SOT, and was  ranked second for 0^,
CO and NOZ.  The 850 mb flow is from the SW quadrant  with  moderate  30 to  40  kt
wind speeas.  A high pressure system is to the  SE and is still dominating the
synoptic pattern.  Note the trough west of St.  Louis, along  the Rockies.   The
contour interval is 60 m for this map  compared  to 30  m for Figures  4  and  5.

     As previously mentioned, the only exception  to the  occurrence  of higher
pollutant concentrations with the presence of a high  pressure system  or a SW
flow occurs during the winter season for 03 concentrations,  however this  is
not considered important since there is no significant difference  between any
of the winter map types when related to 0-.  This is  due to  the generally low
levels of 03 which result from the limitation of  photochemical processes
because of limited amounts of solar radiation during  this  season.

     The lower average concentrations  of pollutants occurred with  850 mb
patterns favoring flow from the north  or with the presence of a low pressure
system.  This is seen by comparing the map types  which correlated  with the
minimum mean concentration for each pollutant for each season.  For the winter
season, map type B with a northerly flow into St. Louis  had  a significantly
lower pollutant concentration.  Similarly, map types  C and F for spring;  map
types B and F for summer; and map types B and D for the  fall had significantly
lower mean concentrations with flows from the northerly  direction  or  the
presence of a low pressure system.  Figures 7 and 8 show the 850 mb flows
associated with lower pollutant concentrations  for map types D-fall and
F-summer, respectively.  From both figures, it is clear  that a low pressure
trough dominates the St. Louis region.  The wind  speeds  are generally in  the
25 to 30 kt range.  Since the presence of low pressure systems are usually
associated with unstable air, cloud cover, and possible  precipitation, the
type of synoptic patterns shown in Figures 7 and  8 are expected to correspond
with lower pollutant concentrations.  The only exception to lower pollutant
concentrations correlating with a north wind or a low pressure system occurs


                                       26

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with total  suspended  particles during the summer season; in this  case map type
D (850S) with a SW  flow  had the lowest mean TSP concentration.

     There is also  a  tendency for higher and lower average concentrations
to have a seasonal  cycle, but the cycle varies depending on the pollutant.
For 03, the higher  mean  concentrations occurred during the summer and the
lower mean concentrations occurred during the winter.  This is expected
since there is a decrease in photochemical processes during the winter
months.

     Both CO and NOj  had higher mean concentrations during the winter
than any other time of the year.  This is believed to be due to the
expected increase in  combustion and heating activity during the winter
and also to the presence of radiation inversions and stagnation which
are frequent during this time.  With regard to SO^, higher concentra-
tions occurred during the summer and lower concentrations throughout the
rest of the year.  This  is considered to be indicative of photochemical
reactions involving S02, and has been noted in other studies (Hidy, et  al.
1978).  The highest TSP  concentrations occurred during the summer and
the lowest during the fall.  This probably indicates the increased prob-
ability of local resuspension of dust during the summer months when
roads and other dust  sources are rrore likely to be dry.  Average summertime
winds are 20 to 30% lighter than winter surface winds so except  in summer
convective storms resuspension by wind is probably more related to surface
conditions.

Air Quality vs. Geostrophic_ Wi nd
Map Types

     A tabular ranking of seasonal map types by high to low concentrations  of
03, CO, TSP, SOj and  N0§ is illustrated in Tables 10 through 14.   These
tables show the map types, number of station pollutant observations, mean
concentrations, significant differences between map types, and  remarks con-
cerning the synoptic  flow for each map type.  Examination of the  results listed
in these tables shows that there is a tendency for pollutant concentrations to
be classified according  to certain geostrophic map types.  As with the other
analysis, the results indicate that higher pollutant concentrations occur when
there is a high pressure system present or when the flow is from the SW quad-
rant, while lower concentrations are related to low pressure systems in the
region around St. Louis. These results are similar to the ones  determined
from the 850 mb map type analysis.  However, the tendency for higher or lower
concentrations to stratify by map types is less clearly defined  for the geo-
strophic wind types than for the 850 mb flows.  This is attributed to the  fact
that the 850 mb patterns are divided into only six pressure distributions  for
each season, while  the pollutant correlations with the geostrophic wind are
divided among nine  map types.  As one example of how the flow becomes more
complex, a flow from  a single direction could be divided into two distinct  map
types for the geostrophic wind due to differences i n wi nd speed  while only
one 850 mb map type would probably be identified.  Another factor that  makes
the geostrophic pattern  less satisfactory is that each pair of stations defines
only a component of the  wind  normal to the line between the stations.   This
component may not be  a close approximation to the actual wind.
                                      32

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     Analysis of the  results  of the  statistical tests applied to the geostrophic
map types for pollutant  concentrations shows that higher pollutant concen-
trations repeatedly correlate with map types A, B, H and I for the winter
season; G for the spring season;  B and G for the summer season; and I and
G for the fall season.   Lower pollutant concentrations occur with map types
E and C for winter; E and F  for spring; H, F and D for summer; and B and D
for fall.  These results show that,  except for spring, two or more map types
were associated with  similar pollutant concentrations for a season.  For
the spring season map type G generally corresponded to higher pollutant
concentrations.

     Figures 9, 10, and  11 show the  surface flows related to the geostrophic
map types B(GeoS), G(GeoSP),  and  I(GeoF), respectively.  Map type B(GeoS)
shown in Figure 9 repeatedly  correlated with higher pollutant concentrations,
ranking first for 0-j, TSp and S0| while being insignificantly different
from the map type with the highest mean concentration for CO and Nog.
Figure 9 shows that the  flow into St. Louis from the SSW direction results
from a low pressure system to the west, and the large high centered off the
South Carolina coast. The pressure  gradient over the region is well developed
resulting in south southwesterly  flow and surface wind speeds of 5 to 15 kts.
Skies were generally  clear to scattered clouds.

     Figure 10 shows  the surface  weather pattern for May 12, 1975, the base
map for map type G(GeoSP).   This  map type was strongly correlated with
high concentrations for  all  of the pollutants except CO.  Although the iso-
baric pattern is complex, the characteristic feature of this pattern seems to
be the large area of high pressure to the northwest, north, and southwest of
St. Louis and the large  area of almost negligible pressure gradient west of
the city.  A weak frontal system  lies through the Great Lakes.  The very weak
pressure gradient around St.  Louis contributes to weak geostrophic flow and
the predominance of local effects.

     Map type I(GeoF), as shown by Figure 11, is similar to map type
G(GeoSP), with a high pressure system north of St. Louis along with a weak
frontal system.  However, i n Type I(GeoF) there is another well developed
high pressure system to  the  east  that is also influencing the flow.  The
resulting wind flow is from  the south at first, later changing to the north as
the high moves into the  area from the west.

     Average pollutant concentrations were generally lower when there was a
low pressure system affecting the area.  Lower concentrations also occurred
with the presence of a high  pressure system with strong winds.  This is
evident in Figures 12, 13 and 14  which show map types C(GeoW), D(GeoF) and
F(GeoSP), respectively.

     Map type C(GeoW] in Figure 12 corresponds to the lowest mean concen-
trations for TSP, SO^ and N0§ and to relatively low concentrations
for 03 and Co.  The wind flow is  from the north due to a low pressure system
to the east and a high to the west.  The lower concentrations are attributed
to the strong winds and  the  presence in the low pressure systems of pre-
cipitation and increased turbulent mixing.  Figure 13 shows the surface
                                       43

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weather pattern for map type D(GeoF).  The figure shows that a frontal  system
recently moved through the  region and a cold high is moving into the area.
The winds are light,  5 to 10 kts, from the north.  This type of pattern would
be expected to be replaced  by patterns with stronger anticyclonic influence
and generally higher  pollutant concentrations.  This was generally the  case
with the D(GeoF)  base map of October 2, 1975 which, as shown by Appendix A-2,
was followed by map types E(GeoF) and C(GeoF).  Tables 10-14 show that  these
had generally higher  coneenrtrations than D(GeoF).  Figure 14 shows the sur-
face flows associated with  map type F(GeoSP). JThis map type is associated
with the lowest concentrations for 0^, TSP, SO^ and NOo, but had the
highest concentration for CO.  The map pattern shows that the strong wind
flow from the south is caused by a high to the SE and a low pressure system  to
the west of St. Louis.  The steep pressure gradient between these systems
results i n wi nd speeds of 10 to 20 kts.  The lower pollutant concentrations
are attributed to the increasing wind speeds with the approach of the trough
to the west and the increasing instability expected with this system.

Comparison of 850 rob, Geostrophic,
and Surface Map Typing Schemes

     From this study  and the study by Robinson and Boyle (1980), a total of
three different sets  of map types was developed and compared with air quality
data—namely the surface level, the 850 mb level, and a component pattern re-
lated to the geostrophic wind.  The three sets of map types were examined on
the basis of their performance in stratifying pollutant data into useful con-
centration classes.   The following discussion compares the results of an air
quality analysis by map type using the three sets of map types.  The discussion
is limited to the pollutants 03, CO, and TSP, for which data are available for
all three map typing  procedures.  Robinson and Boyle (1980) analyzed the
surface map types using mean concentrations for CO and TSP, and their results
will be used in this  comparison.  Maximum daily ozone concentrations were
analyzed as a part of this  study using Robinson and Boyle's surface map types,
and the results are given in Table 15.  As before this table provides a
ranking of seasonal maps by high to low 03 concentrations, and includes the
number of station pollutant observations, mean concentration, significant
differences between map types, and remarks concerning the synoptic flow for
each map type.  The  results for the surface analysis are similar to the results
from the 850 mb and  geostrophic  analysis for 03, and show generally  a tendency
for 03  concentrations to stratify by map types.

     The data also show that the stratification of the surface map types by
higher to lower ozone concentrations is not as clear cut as it is for either
the 850 mb or the geostrophic map types.  This is seen by comparing the
results from the 850  mb  and geostrophic wind analysis, listed in Tables 5
and 10, respectively, to those illustrated in Table 15 for ozone concentrations
during the summer months.   The summer season is  a good test period because
ozone concentrations  are maximum during this season and the synoptic systems
have the greatest effect on the ozone concentrations during the summer.

     The 850 mb analysis,  (Table 5) indicates that map types E and A for the
summer season have significantly higher mean 03 concentrations of 88 and
82 ppb, respectively, and these  are statistically different from the other 4
                                        50

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summer map types.   Map  type  E(850S)  has  an easterly flow due to a high to the
NNE, and map type  A(850S)  has  a WSW  flow into St. Louis.  For the geostrophic
wind, (Table 10) summer map  types B, G,  C and A  have significantly higher 63
concentrations of 83, 82,  82,  and 81 ppb, respectively, when compared to the
other types.  The  flows for  these map types  are  from the south, except for map
type G, which has  light and  variable winds due to the presence of a high
pressure system centered over  the area.   Surface level map type L has the
highest statistically significant concentration  (122 ppb) for eight observa-
tions, but then there were no  significant differences for map types ranked two
through ten with 03 concentrations  ranging from 89 to 73 ppb.  Map type L
correlates with the highest  concentration but the small number of station
observations makes it of questionable usefulness.  Other than this one type,
L, there are more  map types  associated with  the moderate to high 03 concentra-
tions and fewer unique  synoptic pattern  characteristics for the surface level.

     The results from the  comparison of  the  three sets of map types for the
rest of the year for 03, CO, and TSP concentrations are similar to the results
during the summer.  Table  16 gives the map types associated with the maximum
and minimum 03, CO, and TSP  concentrations for the 850 mb, geostrophic, and
surface map types, the  number  of station observations, the mean concentration,
and the significance for each  season.  The number of map types associated with
either the maximum or minimum  mean pollutant concentration for the three sets
of map types are indicated by  the significance column.  For example, to deter-
mine the number of map  types associated  with maximum springtime 03 concentra-
tions for the 850  mb, geostrophic, and surface patterns, an analysis of the
significance must  be accomplished.  For  the  850 mb level, spring map type E
is associated with the  maximum 03 concentration, and it is significantly
different from the remaining five 850 mb  map types for the spring season.
Surface spring map type Mis also correlated with the highest 03 concentra-
tion; however, it  is significantly different only from map types 6-12 (the
surface level identified 12  to 14 map types  per  season), and it is statisti-
cally similar to the four  map  types 2-5.  Therefore, all of the first five map
types are associated with  higher pollutant concentrations.  Similarly, the
first two geostrophic map  types are associated with higher 03 concentrations.
Thus the 850 mb pattern seems  to provide a better classification of the high
03 days.

     An inspection of Table  16 shows that the 850 mb, geostrophic wind, and
the surface map types all  correlate with pollutant concentrations; however,
the 850 mb map types appear  to stratify  the  pollutants into a more limited
number of types than the other two procedures.  This is related primarily to
the fact that there were fewer map types identified for the 850 mb analysis
and thus larger pollutant  case populations could relate to each type.  The
greater number of  surface  and  geostrophic map types implies that two or more
of these map types are  represented by one 850 nb map type.  This is indicated
in Figure 15, which shows  the  frequency  distribution for the surface and geo-
strophic map types in relation to map types  E(850S) and D(850S).  The fre-
uency indicates the number of  days that  are  common to the surface or geo-
strophic map type  and to map types D and E for the 850 nb level.  Map types
D and E were chosen because  they repeatedly  identify with high pollutant
concentrations for the  summer.  The data in Figure 15 show that each of the
850 mb map types correspond  to several surface or geostrophic map types.
                                       53

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   10
                  I E (850S)


                     D (850S)
>   0
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   SURFACE  MAP  TYPES
                                 III
J  K  L  M  0

(SUMMER)
                     E(850S)

                     0 (850S)
 Figure 15,
 ABCDEFGHIO

GEOSTROPHIC  MAP TYPES  (SUMMER)


 *Type 0 indicates dates not typed


 Frequency distribution for surface and geostropliic map types
 relating to map types D(85QS) and LC850S).


               56

-------
The occurrences of the 850 mb map type E are divided among three different
surface and three geostrophic map types while cases of 850 mb map type D are
related to five surface and four geostrophic types.  Untyped maps, indicated
as 0 in Figure 15 are not counted.  These data also indicate that two surface
and three geostrophic map types contain days from both of the 850 mb map
types.  This is evident with surface map types B and M, and geostrophic map
types A, B and E.

     The greater number of map types for the surface and geostrophic classes
leads to a greater probability that overall  two or more of the weather
patterns have some similar features and lead to types that may not describe
significantly different flow patterns.  This dilutes the results of the air
quality application and makes stratifying pollutants into distinct pattern
types more difficult.  The increased number of surface pressure patterns is
due to the increased complexity of the surface regime of which the effects of
friction and terrain are probably most important.  The movement of air masses
and the presence of frontal systems also affect the wind flow at the surface
more than at the 850 mb level.  A reduction in the magnitude of these factors
leads to more generalized wind flows at the 850 mb level compared to that at
the surface.  For the geostrophic or pressure gradient types the poorer corre-
lations with pollutants is attributed to difficulties in typing the geostro-
phic wind by components.  As previously indicated, the geostrophic map types
are based on pressure difference between certain station combinations with the
assumption that the pressure gradient is uniform between the two stations, and
the single indicated component of the geostrophic wind is a good indicator of
the flow.  For the best results, the maximum number of station combinations
with a minimum distance between stations should be utilized along with sectors
meeting at a large angle or even intersecting.  Our choice of the number of
station pairs and their distribution over the area was a compromise between
the detail needed to describe the geostrophic system and the realities of the
typing computation problem.  Also, it is recognized that when the geostrophic
wind is less than about 5 knots the wind regime will probably be dominated by
the local wind systems rather by the apparent geostrophic pattern (Moses and
Hess, 1976).
                                      57

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                                    SECTION 3

                             SUMMARY AND CONCLUSIONS


     The statistical  map classification procedure developed by Lund (1963)
served as the basis for compiling comprehensive sets of primary seasonal
weather map types for the 850 mb level  and for components of the geostrophic
wind using surface pressure differences between paired stations for the four
year period 1973-1976, for the St. Louis, Missouri,  region.  These map types
were matched with mean concentrations of ozone, carbon monoxide, total sus-
pended particles, sulfate and nitrate data applicable to the St. Louis central
urban area, using observations from the St. Louis RAMS network for the period
1975 and 1976 within the larger St. Louis RAPS program.

     The average pollutant data, stratified by weather type, were assessed by
analysis of variance statistical techniques using the Duncan's multiple range
test (Steel and Toerie, 1960).  This was a basis for determining significant
differences between map types within each season of  the year.  The results
indicated that the regional synoptic scale patterns  for the 850 mb, surface,
and geostrophic wind components can be used to classify the pollutant con-
centrations for all of the pollutants considered.  Higher pollutant concentra-
tions repeatedly occurred with wind flows from the south and/or the presence
of a high pressure system in the area while lower concentrations occurred with
the presence of a low pressure system and/or strong  wind fields.  Maximum mean
pollutant concentrations were found to differ by season, depending on the type
of pollutant.  For example, higher ozone concentrations occur during the
summer months due to more favorable conditions for the photochemical reaction
processes.  Lower ozone concentrations occur during  the winter season.

     The 850 mb and the geostrophic map types were compared to the surface map
types developed by Robinson and Boyle (1980).  The 850 mb map types were
concluded to be the most effective in stratifying the pollutant data.  This
conclusion was a result of the lower number of seasonal map types and thus the
better resolution of major patterns by the 850 mb types than for the surface
or geostrophic map types.

     The results of this investigation comparing different weather pattern
types with air quality should provide a basis for future research relating air
quality to synoptic flow.  This study provides a basis for the use of 850 mb
flow level map types with diffusion models for the prediction of pollutant
concentrations at receptors located long distances from a major source.  The
results might also aid in the prediction of periods  of high or low pollutant
concentrations, in an effort to curtail harmful pollutant episodes.  For
                                      58

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research programs  where  it is useful to deal with similar synoptic situations
either at 850 nt> or at the surface the results of this study, as tabulated  in
Appendix A-l for 850 mb  types, or Table 3 in Robinson and Boyle (1980)  for
surface pattern types could be used to select similar synoptic patterns.  The
base maps for each identified type are given in the appendices of the final
report for each study.
                                       59

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                                   REFERENCES

Christensen, W.  I., Jr,  and R.  A.  Bryson,  1966:   An  investigation  of  the
potential  of component analysis for weather classification.  Monthly Weather
Review 94_, 697-709.

Hess, S.  L., 1959:   Introduction to Theoretical  Meteorology.   Holt, Rinehart,
and Winston, New York.

Hidy, G.  M., P.  K.  Mueller, and E.  Y.  long, 1978:   Spatial  and temporal
distributions of airborne sulfate in parts of  the United States.   Atmos.
Environ., ]2, 735-752.

Hoecker,  W. H. , 1977:  Accuracy of various techniques  for  estimating
boundary-layer trajectories.  J. Appl.  Meteor.,  16,  374-383.

Lund, I.  A., 1963:   Map-pattern classification by statistical  methods.
J. Appl.  Meteor., 2_, 56-65.

Lund, I.  A., 1971:   Correlations between area! precipitation and 850-millibar
geopotential heights.  Monthly Weather Review, £9, 691-697.

Moses, H., and P. E. Hess, 1976:  Comparison of  the Surface and Geostrophic
Winds.  Paper No. 76-23.4, presented at 69th Annual  Meeting, Air Pollution
Control Association, Portland, Oregon,  June, 1976.

Robinson, E., and R. J.  Boyle, 1980:  Synoptic Meteorology  and Air Quality
Patterns  in the St. Louis RAPS Program.  EPA-600/4-80-001,  U.S. Environ-
mental protection Agency, Research Triangle Park, NC,  January, 1980,  87  pp.

Slade, D. H. (ed),  1968:  Meteorology and Atomic Energy.  U.S. Atomic Energy
Commission, Washington, D.C.

Steel, R. G. D., and J.  H. Torrie, 1960:  Principles and Procedures of
Statistics.  McGraw-Hill Book Company,  Inc., New York.
                                          60

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                               APPENDIX A

                       DAILY MAP TYPE ASSIGNMENTS
     As a result  of this program map types were assigned to each day
for the 4-year period  1973-1976.  A tabulation of these daily map types
is given in Table A-l  for the 850 mb contour patterns and in Table A-2
for the geostrophic patterns.   In these 2 tables the identifications
is by letter code in each season.  The notation 0 indicates that the
map was not typed within one of the map categories, i.e. no correlation
met the typing qualification.   The notation X indicates that some data
were missing and  thus  no type was assigned to the daily pattern. These
tables can be compared with a similar tabulation of surface patterns
given by Robinson and  Boyle (1980) in their Table 3.
                                      61

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     APPENDIX B



      SECTION 1







BASE MAPS FOR 850 MB
        66

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          APPENDIX B



           SECTION 2







BASE MAPS FOR GEOSTROPHIC WIND

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                                   TECHNICAL REPORT DATA
                            (Please read Instructions on the reverse before completing)
 1. REPORT NO.
                              2.
                                                           3. RECIPIENT'S ACCESSION-NO.
 4. TITLE AND SUBTITLE
  METEOROLOGY AND  AIR QUALITY PATTERNS IN ST.  LOUIS
  RAPS PROGRAM
  Upper Level Analyses
             5. REPORT DATE
             6. PERFORMING ORGANIZATION CODE
 7. AUTHOR(S)
                                                           8. PERFORMING ORGANIZATION REPORT NO.
  Mark Vuono,  Fletcher Strives and Elmer  Robinson
 9. PERFORMING ORGANIZATION NAME AND ADDRESS

  Washington  State University
  Pullman, Washington 99164
              10. PROGRAM ELEMENT NO.

               CDTA1D/03-0335 (FY-82)
             11. CONTRACT/GRANT NO.

               806176010
 12. SPONSORING AGENCY NAME AND ADDRESS
  Environmental  Sciences Research Laboratory  -  RTP,  NC
  Office  of Research and Development
  U.S.  Environmental Protection Agency
  Research  Triangle Park, North Carolina  27711
              13. TYPE OF REPORT AND PERIOD COVERED
                Final   10/78-2/S2	
             14. SPONSORING AGENCY CODE
                EPA/600/09
 15. SUPPLEMENTARY NOTES
 16. ABSTRACT
        A  statistical  map-typing procedure was  used to stratify regional weather pat-
   terns over  a  800-km radius area centered  on  St.  Louis.   It was intended  for appli-
   cation  to air pollution studies.  Seasonal weather types were obtained for 850-mb
   height  patterns  and for geostrophic wind  patterns based on surface  pressure gra-
   dients  for  the four-year period 1973  through 1976.  A total of 21 separate weather
   map  types were identified for the 850-mb  level  synoptic flow, and a  total  of 36
   map  types were identified for the geostrophic wind flow.
        To  show  the relationships between the synoptic weather types and air  quality,
   statistical correlations were calculated  between the daily map types and observed
   air  quality data using Ov CO, total  suspended  particles, sulfate,  and nitrate
   concentrations from the T975-1976 St. Louis  RAPS program.  The results show that
   synoptic map  types  have a definite and useful correlation with significantly dif-
   ferent  levels of air pollutant concentrations.   The results also indicate  that the
   correlations  between map types and average air  quality concentrations is better
   for  the  850-mb weather pattern types  than for the surface or geostrophic types.
   This is  attributed  to the fact that the 850-mb  typing scheme stratified  the data
   into fewer  types than did the othe two schemes.
 7.
                               KEY WORDS AND DOCUMENT ANALYSIS
                  DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS  C. COSATI Field/Group
 8. DISTRIBUTION STATEMENT
                       RELEASE  TO  PUBLIC
                                              19. SECURITY CLASS (ThisReport}
                                                   UNCLASSIFIED
                                                                         21. NO. OF PAGES
                                 133
                                              20. SECURITY CLASS (Thispage)
                                                   UNCLASSIFIED
                                                                        22. PRICE
EPA Form 2220-1 (9-73)
                                            125

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