RESEARCH TRIANGLE INSTITUTE
RTI Project No. 41U-888-9
December, 1975
EXAMINATION OF THE RELATIONSHIPS BETWEEN ATMOSPHERIC OXIDANT
AND VARIOUS POLLUTANT AND METEOROLOGICAL VARIABLES
by
Tyler D. Hartwell
and
Harry L. Hamilton, Jr.
Research Triangle Institute
Research Triangle Park, North Carolina 27709
EPA Project Officer: William Hunt
Prepared for
Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Contract No. 68-021096
RESEARCH TRIANGLE PARK, NORTH CAROLINA 27709
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19796
ACKNOWLEDGEMENTS
The authors would like to acknowledge the valuable input provided by
Mr. William Hunt, Mr. Frank Noonan, Mr. Robert Faoro, Mr. William Cox and
Dr. Thomas Curran of the Monitoring and Data Analysis Division of the
Environmental Protection Agency in carrying out the research described in
this report.
In addition, we would like to thank Mrs. Brenda Gurley and Mrs. Janet
Price for their help in preparing the final report.
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6 . Conclusions
7 . Recommendations
Bibliography
Appendix A: Plots of Daily Maximum Oxidant (Ozone) Versus
Various Pollutant and Meteorological Variables
by Station
TABLE OF CONTENTS
Page
List of Tables .............................................. iii
List of Figures ............................................. iv
List of Appendix Figures .................................... vi
1 . Executive Summary ........................................... i
2 . Introduction ................................................ g
2 . 1 General Background ..................................... g
2.2 Study Objectives ....................................... 18
3 . Data Selection and Description .............................. 19
3 . 1 Data Selection ......................................... 19
3.2 Description of the Data and Data Editing Procedures ____ 21
4. Study Limitations ........................................... 30
5 . Data Analysis ............................................... 33
5 . 1 Introduction ........................................... 33
5.2 Yearly Summary Statistics for the Pollutant
Variables .............................................. 35
5.3 Frequency Distributions for the Pollutant
Variables .............................................. 39
5.4 One-At-A-Time Relationships Between MOX (MOZ)
and the Other Variables ................................ 42
5.4.1 Mean Plots of Several Variables
Versus MOX (MOZ) ................................ 42
5.4.2 Correlations .................................... 48
5.4.3 Scatter Plots ................................... 53
5.4.4 Means by Day of Week and Station ................ 55
5 . 5 Upper Percentile Analysis .............................. 53
5.6 Multiple Variable Relationships Between MOX (MOZ)
and the Other Variables ................................ 53
5.6.1 Stepwise Regression ............................. 59
5.6.2 Cluster Analysis .............. , ................. 73
5.6.3 Regressions ..................................... 33
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ii
Appendix B: Appendix J of the August 14, 1971 Federal
Register
Appendix C: Plots of the 75th and 50th Percentiles of
the MOX Distribution for Given Levels of THC
and NO2 by Station and Year
Appendix D: AID Results for DOLA, BETH, HYAT and SISP
Appendix E: Plots of Adjusted MOX (MOZ) Versus Adjusted
NO- and THC by Station (Adjusted for SRAD,
MTEMP, VIS)
Appendix F: Listing of Data
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ill
LIST OF TABLES
Page
1 Summary of the Times and Locations of Data Collection for
the Pollutant and Meteorological Data Received on Tape
from EPA's Data Bank 25
2 Frequency Distribution (in days) of Time of Maximum
Oxidant (Ozone) for Three Stations 27
3 Summary Statistics for Meteorological Data 27
4 Summary Statistics for Pollutant Variables by Year and
Station (units = ppm) 35
5 Daily Max. Oxidant, N02, NO and THC Frequency Distributions
and Summary Statistics for 1968 and 1972 (May through
October Data); for Stations AZU (Azusa) and DOLA
(Downtown) 40
6 Daily Max. Ozone, N02, NO, THC and NMHC Frequency Distri-
butions and Summary Statistics for 1973 (May through
October Data); for Stations BETH (Bethesda) and SUIT
(Suitland) 41
7 Correlations Between Daily Max. Ozone (Oxidant) Versus
Pollutant and Meteorological Variables (May through
October Data) by Station 51
j
8 Correlations Between Daily Max. Ozone (Oxidant) Versus
Pollutant and Meteorological Variables (May through October
Data) for Days When MOX (MOZ) > .08 ppm by Station 52
9 Results of Stepwise Regressions by Station with Daily Max.
Oxidant (Ozone) as the Dependent Variable (May through
October Data) 71
10 Results of Stepwise Regressions by Station with Daily Max.
Oxidant (Ozone) as the Dependent Variable (May through
October Data) 72
11 Categories Used in Running AID 75
12 Summary of Variables Used to Split MOX (MOZ) Groups in
AID Computer Runs (All Data Used was May through
October Data) 80
13 Means of Meteorological and Pollutant Variables for
Different Levels of Daily Max. Oxidant (Ozone), May
through October Data 82
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iv
LIST OF FIGURES
Page
1 Plot of 75th Percentile of the MOX (MOZ) Distribution for
Given Levels of THC by Station and Year 7
2 Maximum Daily Oxidant as a Function of Early Morning Total
Hydrocarbons, 1966-1968 for CAMP Stations; May through
October 1967 for Los Angeles 13
3 Maximum Daily Oxidant as a Function of Early Morning Total
Hydrocarbons, Denver, 1966-1968 14
4 Maximum Daily Oxidant as a Function of Early Morning Non-
methane Hydrocarbons, 1966-1968 for CAMP Stations; May
through October 1967 for Los Angeles 15
5 Maximum Daily 1-Hour Average Oxidant Concentrations as a
Function of 6 to 9 A.M. Averages of Total Nitrogen Oxides
in Washington, D.C., June through September, 1966
through 1968 16
6 Hydrocarbon-Oxidant Envelopes Superimposed on Maximum Daily
1-Hour Average Oxidant Concentrations as a Function of
6 to 9 A.M. Average of Total Nitrogen Oxides in Pasadena,
California, May through October 1967 17
7 Location of Air and Meteorological Stations in Los Angeles
Area 23
8 Location of Air and Meteorological Stations in Maryland
Area 24
9 Plot of Means of Daily Max. Oxidant (Ozone) and 6 A.M.
to 9 A.M. Daily Averages of NO, N02> THC and NMHC 37
10 Plots of the Means of Meteorological and Pollutant
Variables for Three Levels of Daily Max. Oxidant (Ozone)
(May through October Data) 44
11 Plot of MOX vs THC (6-9) at AZU 54
12 Plot of MOZ vs THC (6-9) at BETH 55
13 Plot of Means of Daily Maximum Oxidant by Day of Week
and Station 57
14 Plot of Means of Daily Maximum Ozone by Day of Week and
Station 58
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LIST OF FIGURES - Continued
Page
15 Plot of Means of THC (6-9) by Day of Week and Station 59
16 Plot of Means of THC (6-9 A.M.) by Day of Week and
Station 60
17 Plot of Means of N02 (6-9) by Day of Week and Station 61
18 Plot of Means of Daily Maximum Oxidant by Day of Week,
High and Low Solar Radiation (SRAD) and Station 62
19 Plot of 75th Percentile of the MOX (MOZ) Distribution for
Given Levels of THC by Station and Year 66
20 Plot of 75th Percentile of the MOX (MOZ) Distribution for
Given Levels of N02 by Station and Year 67
21 AID Results for AZU, May through October, 1972 Data 73
22 AID Results for SUIT, May through October, 1973 Data 79
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vi
LIST OF APPENDIX FIGURES
A-l Co A-24 Plots of Daily Maximum Oxidant (Ozone) Versus Various
Pollutant and Meteorological Variables by Station
B-l Appendix J of the August 14, 1971 Federal Register
C-l to C-10 Plots of the 75th and 50th Percentiles of the MOX (MOZ)
Distribution for Given Levels of THC and NO. by
Station and Year
D-l to D-4 AID Results for DOLA, BETH, HYAT and SISP
E-l to E-10 Plots of Adjusted MOX (MOZ) Versus Adjusted NO- and
THC by Station (Adjusted for SRAD, MTEMP, VIS)
F Listing of Data
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1. Executive Summary
While there is general agreement on the classes of reactants involved
in the production of oxidants in the atmosphere, thirty years of research
have provided limited scientifically or politically acceptable strategies
for the control of photochemical oxidants. An empirical relationship
between early morning concentrations of hydrocarbons and maximum (after-
noon) concentrations of oxidants on the same day was used as a basis for
a suggested control strategy in Appendix J to 40 CFR 50 (see Appendix B
of this report).
Since the issuance of Appendix J, little has been done to develop models
of the relationship between oxidant concentrations and concentrations of
precursors. Most attempts have been frustrated by the fact that regressions
between these variables have had small correlation coefficients. Smog
chamber studies, which provide controlled conditions for experimentation,
have yielded considerable knowledge concerning the classes of reactants
involved in the production of photochemical oxidants. Several of these
studies have shown positive relationships between oxidants and hydrocar-
bon concentrations. As this type of experimental study becomes more com-
plex, however, the new data developed require correspondingly more complex
models of the reactions involved. A complicating factor in attempting to
relate chamber experiment data to control strategy development is the fact
that the chamber studies, almost exclusively, have been concerned with the
reactions taking place with time among a particular set of initial reactants.
In real life new compounds are continually being injected into the air,
with marked influence on the reactions taking place. Further, most chamber
studies have been conducted using artificial light in lieu of actual sun-
light; seldom has the radiation intensity of the artificial light been as
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great as natural sunlight. While providing invaluable data contributing
to the understanding of the production of photochemical oxidants, chamber
studies have not yet furnished the guidance needed for the development of
control strategies. Aside from chamber experiments when both meteorologi-
cal variables and concentrations of precursor pollutants have been con-
sidered, the meteorological variables frequently have proven to be more
highly correlated with daily maximum hourly oxidant concentrations than
have precursor concentrations.
The present study, using meteorological and aerometric data from the
EPA data bank, examined relationships among pollutant concentrations and
meteorological variables and the daily maximum hourly oxidant concentra-
tions. Data sets from two areas, Los Angeles and Washington, having
different characteristics with regard to photochemical oxidant problems
were studied. Two stations of the Los Angeles County Air Pollution Control
District—Downtown Los Angeles and Azusa—provided ambient pollutant con-
centrations that were used along with surface meteorological measurements
from the U.S. Weather Service station at Los Angeles International Airport
to make up one data set containing data for 1965, 1968 and 1972. The
second data set containing data for 1973 only was comprised of ambient
pollutant data from four Maryland stations in the suburban area of Washington,
D. C., and records of the surface observations from the U.S. Weather Service
Station at Dulles International Airport. Within these two data sets, miss-
ing values for one or more pollutant variables on given days reduced the
useful sample size considerably particularly for the Washington, D. C.
area. The analyses were made using data collected from May through October—
the periods of highest ambient oxidant concentrations in both geographic
areas—and 6-9 A.M. concentrations of the precursor pollutant variables—
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since preliminary analysis did not indicate that other time periods gave
higher correlations with daily maximum oxidant.
Summary statistics for the two areas show that the May through October
frequency of occurrence of days with daily maximum hourly oxidant concentra-
tions greater than 160 ug/m (.08 ppm), the National Ambient Air Quality
Standard (NAAQS) not to be exceeded more than once per year, decreased at
Downtown Los Angeles and Azusa between 1968 and 1972 from 67.8 to 56.0
percent and from 85.1 to 75.6 percent, respectively. In the Washington,
D. C., area for the Bethesda and Suitland, Maryland, stations the 1973
May through October corresponding frequencies for oxidant concentrations
in excess of NAAQS were 37.5 and 28.8 percent, respectively. On a percentage
basis, the maximum oxidant concentration occurred more often between the
hours of 10:00 A.M. and 2:00 P.M. in Los Angeles than in Maryland. In
Maryland, several days (17.4 percent in Hyattsville) reported all zero
concentrations while in Los Angeles there were no days with all zero oxi-
dant concentrations.
On the average, nitric oxide (NO), nitrogen dioxide (N0_), total hydro-
carbons (THC), solar radiation (SRAD), daily maximum temperature (MTEMP),
and dewpoint temperature (DPT) values were found to be higher than average
when maximum hourly average oxidant concentrations were high. Visibility
(VIS), relative humidity (RH), wind speed at the time of the maximum oxi-
dant reading (WS), and average wind speed from 7:OOA.M. to 7:00 P.M. (AWS)
were found to be lower than average when maximum hourly average oxidant
concentrations were high.
Examination of the relationship between the 75th percentile values of
the distribution of daily maximum oxidant concentrations (MOX) for given
concentrations of THC and of N02 indicate that in Los Angeles the MOX con-
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Generations have decreased between 1968 and 1972 but THC and NO, concen-
trations have not. Similar analysis of MOX and THC data from three Maryland
stations combined into one data set shows the 75th percentile curve in
Maryland to have a shape similar to that of the Downtown Los Angeles station
/
within the range of THC concentrations measured. The range of THC concen-
i
trations for the Maryland data was about half of the range measured in
Los Angeles. The shapes of the MOX 75th percentile curves for Azusa for
both 1968 and 1972 data suggest a less rapid rate of increase with higher
THC (or NO.) concentrations; that is, the relationship is curvilinear. The
percentile curves for Downtown Los Angeles, however, appears to be reasonably
approximated by a linear relationship. (See Figure 1.)
Multiple variable analyses of the relationships between the several
pollutant and meteorological variables and the daily maximum hourly oxidant
concentrations indicate that in Los Angeles the most important pollutant
variables in predicting maximum oxidant concentration are, as would be ex-
pected, THC and NO.; none of the pollutant variables appear to be signifi-
cant predictors in Maryland. With regard to THC, this latter result is
possibly attributable to the small range of THC concentrations measured in
Maryland. Among the meteorological variables, MTEMP, SRAD, and VIS are
the most significant predictors. In Maryland, MTEMP and in Los Angeles,
SRAD were the most Important predictors. For the Los Angeles data, a posi-
tive linear relationship is still apparent between maximum oxidant and N0?
and THC after adjustment has been made for important meteorological variables.
The data sets used in this analysis were not ideal. Missing concen-
tration values for one or more of the pollutants or for oxidant limited the
number of data points considerably. In Maryland, for example, only about
half the days in the May through October period of 1973 had pollutant data
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for NO, NO., and THC; for 1965, no NO data and only a limited amount of
THC data were available for Los Angeles. Accordingly, for analysis pur-
poses the data set for Los Angeles only had pollutant data for 1968 and
1972 and meteorological data for 1972 while the data set for Maryland
only had pollutant and meteorological data for half the days of interest
in 1973. Meteorological data from stations up to 30 miles distant from
the pollutant monitoring stations were used. In Maryland, this distance
was thought to be unimportant. However, in the Los Angeles area the mari-
time influence on the coastal area, where meteorological data were avail-
able, probably caused conditions to differ greatly on occasion from the
conditions at the inland pollutant monitoring stations.
The present study indicates that the use of statistical analysis of
the many variable constituents and properties of the ambient air to develop
relationships that can be used as guidance in the development of control
strategies is a tenuous procedure. In the study of the oxidant precursor-
oxidant relationship and other relationships involving secondary pollutants
generated by reactions taking place in the atmosphere, the assumption is
made that the ambient air sampled for the morning concentration values of
precursors is representative of the air that reached the "downwind" station
at the time the oxidant concentration was measured. Such an assumption is
not warranted, a_ priori, since (1) the air from the site of the precursor
measurements may never have reached the site of the oxidant measurement
and (2) the air from the precursor site, although reaching the oxidant site,
may have been modified by the introduction of additional pollutants en route
so as to be unrecognizable.
Thus, while the large number of data points theoretically available
from existing ambient air monitoring stations is enticing, the requirement
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for pairs of data—precursors at one station, oxidant at the other—may
quickly reduce the useful data to a small sample population because of
missing data resulting from various causes.
In general, the statistical analysis of current archived oxidant
precursor and oxidant data appears to be an unfruitful method of attacking
the development of oxidant precursor-oxidant relationships useful in the
development of control strategies. There may be situations that are ex-
ceptions to this categorical statement, but each would have to be justi-
fied by "proof" that station data used are "representative" of the upwind
and downwind geographic areas and that the meteorological conditions are
sufficiently well documented to show on a day-to-day basis that the flow
was from the "upwind" to the "downwind" stations. In addition, any study
of this kind that is undertaken, should begin with several hundred days
of data to overcome the problems caused by missing data that will undoubt-
edly occur due to various causes such as unfavorable meteorological con-
ditions, instrument failure, etc.
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—Figure 1 —
-Plot of 75th Percentile of the MOX (MOZ) Distribution
for Given JLevels of THC by Station and Year.
--,50--
:IOX(MOZ)
•= AZU (1972)
_Q= AZU (1968)
_X= DOLA (1972)
0 = DOLA (1968)
__ •= BETH, HYAT
and SUIT
MARYLAND (COMBINED)
1 / ; i i ' i ' < i
1 * 3 V ^618
THC (f\ Q\
: : ! ' ppm • ' . .
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2. Introduction
2.1 General Background
Since the recognition, in the mid 1940s, of the importance of the role of
photochemical reactions in the production of oxidants in polluted atmospheres,
extensive research in the laboratory and in the use of measurements in the
atmosphere has failed to provide a scientifically or politically acceptable
strategy for the control of these oxidants. There is general agreement
on the classes of reactants involved in the production of oxidants, viz.:
hydrocarbons, nitric oxide, and nitrogen dioxide. Energy, in the form of
solar radiation, is essential to the reaction, and there is evidence that
ambient atmospheric temperature below a minimum value will restrain the
maximum hourly ozone concentration from increasing to the established
national ambient air quality standard of 160 ug/m (.08 ppm). Other
meteorological conditions, in addition to controlling the amount of solar
radiation available for the reaction of oxidant precursors, provide ever-
changing conditions under which the reaction occurs. Horizontal and vertical,
convective and turbulent dispersions non-unlformly affect reactant concentra-
tions, and horizontal transport by the wind over sources of pollutants
produces continual variation in the concentrations and concentration ratios
of the several reactants.
In summarizing a discussion of the relationship of atmospheric hydro-
carbons to photochemical air pollution levels, the authors of Air Quality
Criteria for Hydrocarbons [10] state: "the development of a model to relate
emission rates of hydrocarbons to ambient air quality and then to secondary
products of photochemical reactions has proved to be an elusive problem.
Because of this lack of an appropriate model, the relationship between
hydrocarbon emissions and subsequent maximum daily oxidant levels must be
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approached empirically." Such an approach was presented in this "criteria
document" in the form of envelope curves that enclosed the maximum oxidant
concentrations shown on a scatter diagram of maximum daily 1-hour oxidant
concentrations plotted against the 6:00 to 9:00 AM average hydrocarbon
(or nonmethane hydrocarbon) concentrations for the same day. Data for
several cities and for several years were combined in two of the three
plots presented in the document and reproduced here as Figures 2, 3, and
4. From the data sets used for Figure 2, Denver data were extracted
to prepare Figure 3. However, Figure 4 was prepared from different
data sets and, except in the case of the Los Angeles data shown, measured
methane concentrations were subtracted from measured total hydrocarbon
t
concentrations to arrive at the nonmethane hydrocarbon concentrations.
Los Angeles total hydrocarbon concentrations were reduced to nonmethane
hydrocarbon concentrations by the application of an empirical formula
derived from measurements of methane and nonmethane hydrocarbon concentra-
tions in downtown Los Angeles during the 6:00 to 9:00 AM period for 38 days.
The envelope drawn in Figure 4 provided:the relationship-for the develop-
ment of the curve presented as Appendix J to 40 CFR 50 (see Appendix B of
this report).
Scatter diagrams showing the relationship of maximum daily 1-hour
oxidant concentrations to 6:00 to 9:00 AM total nitrogen oxides concentra-
tion were presented in Air Quality Criteria for Nitrogen Oxides [7] for
several cities- Figure 5 is a copy of the scatter diagram for Washington, D.C.,
while Figure 6 shows, for Pasadena, California, the 6:00 to 9:00 AM nitro-
gen oxides concentration related to daily maximum 1-hour oxidant concentra-
tion with envelopes enclosing the associated (6:00 to 9:00 AM) calculated
nonmethane hydrocarbon concentrations. The nitrogen oxides criteria
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10
document presents several conclusions following the discussion of ambient
observations and laboratory data on the relationship of oxidant concentra-
tions to concentrations of nitrogen oxides and hydrocarbons. In particular,
three qualitative statements are of interest: (1) "The ambient levels of
6:00 to 9:00 AM precursors, HC and NO , are a reliable indicator of maximum
attainable 1-hour-average-oxidant concentration that occurs 2 to 4 hours
later, between 10:00 AM and 2:00 PM," (2) "The atmospheric conditions that
lead to maximum oxidant potential, i.e., low wlndspeeds, high temperature,
intense sunlight, and surface inversions occur on approximately 1 percent
of the days," and (3) "Laboratory studies do permit the independent evalua-
tion of the effects of varying either HC or N02- . . . The data base
suggests that reductions in HC should be the primary step for control
of oxidants. Coupled with HC control, NO must be controlled at a level
*W
that will hold ambient NO. values below the level of adverse health effect."
Subsequent to the publication of the criteria documents, which fur-
nished an excellent summary of the state of knowledge of the relationship
between photochemical oxidant and its precursors, numerous studies, including
laboratory work (smog chambers), field studies involving new measurement
station locations, and statistical manipulation of archived data, were made.
For example, Cleveland and his colleagues [2,3,4,5,6] have analyzed 1973
ozone concentration data from the New York City-New Jersey area using
statistical techniques. They conclude that: (1) correlations between
ozone concentrations at nearby stations are quite high (r > .80), (2) dally
1-hour maximum ozone concentrations occur between 1:00 and 3:00 PM,
Although this statement was included in the "Summary," no discussion of
necessary or sufficient meteorological conditions appeared in the maiin
body of the text.
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11
(3) Sunday ozone concentrations are slightly higher than workday concentra-
tions while corresponding Sunday concentrations of nitrogen oxide, nitrogen
dioxide, carbon monoxide, nonmethane hydrocarbons, and aerosols are markedly
lower than workday concentrations, (4) ozone concentrations are correlated
positively with solar radiation and temperature and negatively with wind
speed, and a multiplicative model relating these variables provides a
reasonable fit to observed data.
Jacobson and Salottolo [8] examined ozone concentration data from seven
locations in and around New York City for the period 1970 through 1972.
In general, their results only provide confirmation of work of other
researchers, i.e., the highest concentrations of oxidants occurred during
the months May through September; a diurnal pattern of oxidant concentra-
tions existed with daily maximum values usually occurring between 12:00 and
5:00 PM; and urban areas with heavy motor vehicle traffic generally reported
lower oxidant concentrations than sites in suburban areas. Relating
oxidant concentrations to meteorological conditions showed that high
concentrations occurred more frequently with winds from the southeast through
southwest sectors at speeds between 6 and 11 mph, total daily solar
radiation in excess of 400 Ly, temperatures greater than 75°F, and morning
mixing depths less than 1000 m.
The need for additional study of the relationships between photochemical
oxidant and its precursors is emphasized by Altshuler Cl] in a review of
CAMP station data for the period 1964-1973. He notes significant decreases
with time in the oxidant concentrations observed at central city monitoring
stations and suggests that hydrocarbon emission control strategies may
already be effective in spite of the fact that the full impact of control
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12
devices for tailpipe and evaporative emissions has not been obtained.
Altshuler indicates that the percentage decrease in the annual maximum
hourly oxidant concentrations in Philadelphia and Washington, D.C., for
example, between the 1964-1966 period and the 1971-1973 period amounted
to 50 percent and 14 percent, respectively. These decreases are equal
to or greater than the corresponding decreases of 33 percent and 14 percent,
respectively, in monthly average nonmethane hydrocarbon concentrations over
the same time interval.
Through this interval since the publication of the criteria, little
has been done to develop models of the relationship between oxidant concen-
tration and concentrations of precursors. One reason for this is the
fact that most attempts have been frustrated by the fact that regressions
between these variables have turned out to have small correlation coefficients.
In those studies where both precursor pollutant concentrations and meteoro-
logical variables have been considered, the meteorological variables have
proven to be more highly correlated with the daily maximum hourly oxidant
concentration than have the precursor concentrations.
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13
MAXIMUM DAILY 1-HOUR AVERAGE OXIDANT, ppm
b P ? ? ? P
3 «" o 5 fcj K fc
a DENVER .^ A
• CINCINNATI ^' A
A LOS ANGELES S* D
O PHILADELPHIA .S A
A WASHINGTON S & A
X D
.'*
S a a /VYN
— .'• A AA —
. o o &£ o
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/ OA O A A
y* A O a OAD O A AD A O A
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/ ©CAAOAO AD ©OAOOD ADO A ©oa ©o ^
/ DAAC1O OOA©OA ©ODA A ©DA
/ D O ^OAO©DOOOaAO®OAa AOAO AQ A
a a AA DAA ADAAOA© D©©A©Q A©A
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/ CO AACtiOA AADAOAA AOAOO© A OA O ©O Ad
/o n AQAAATAnAnA AA ©riAcaoAaoa ©OA A
326 DAYS OF DATA. COINCIDENT
POINTS NOT PLOTTED
1 1
0-1 2 3 ' 4 S
6-9 a.m. AVERAGE TOTAL HYDROCARBON
CONCENTRATION, ppm C
Figure 2. Maximum daily oxidant as a function of early morning
total hydrocarbons, 1966-1968 for CAMP stations;
May through October 1967 for Los Angeles
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0.30
0.2S
14
O.
z 0.20
Q
X
O
Ul
O
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ae
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o.os
Figure 3.
6-9 a.m. AVERAGE TOTAL HYDROCARBON
CONCENTRATION, ppm C
Maximum daily oxidant as a function of early morning
total hydrocarbons, Denver, 1966-1968.
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15
0.301
0.25-
i
Q.
z
Q
X
o
ui
O
QS
UJ
at
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O
0.20
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x
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0.10
O.OS
LOS ANGELES*
LOS ANGELES
DENVER
WASHINGTON
A • '
A LOS ANGELES
,*"A A PHILADELPHIA
LOS ANGELES
PHILADELPHIA* S
./*
PHILADELPHIA^'
WASHINGTON A' A
— WASHINGTON^A/p'H|LADELpH|A
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o.s
1.0
1.S
2.0
2.S
6-9 a.m. AVERAGE NONMETHANE HYDROCARBON
CONCENTRATION, ppm C
Figure 4. Maximum daily oxidant as a function of early morning
nonmethane hydrocarbons, 1966-1968 for CAMP Stations;
May through October 1967 for Los Angeles.
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16
0.25
0.20
0.15
0.10
0.05
APPROXIMATE UPPER-LIMIT OBSERVED OXIDANT
0.05 0.10 0.15
NOX
0.20 0.25 0.30
Figure 5. Maximum daily 1-hour-average oxidant concentrations as a
function of 6- to 9-a.m. averages of total nitrogen oxides in
Washington, D.C., June through September, 1966 through 1968.
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17
0.40
0.30
0.20
x
o
0.10
APPROXIMATE UPPER-LIMIT
OBSERVED OXIDANTS
HYDROCARBON ENVELOPES
• 1.5 ppm C
- — — 2.0 ppm C
—*—•'- 2.5 ppm C
0.10
NOX/ ppm
0.20
0.30
Figure 6. Hydrocarbon-oxidant envelopes superimposed on maximum
daily 1-hour-average oxidant concentrations as a function
of 6- to 9-a.ra. average of total nitrogen oxides in Pasadena,
California, May thorugh October 1967.
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18
2.2 Study Objectives
The main objective of the present study was to examine the relationships
between daily maximum oxidant (ozone) and the values of various pollutant
and meteorological variables using atmospheric data from EPA's data bank.
In particular, RTI was to examine atmospheric pollutant data supplied by EPA
on computer tape from two stations in Los Angeles and four stations in
Maryland. In addition, corresponding meteorological data from the U. S.
Weather Bureau from two stations, one in Maryland, and one in Virginia for
the Maryland pollutant data and one station in Los Angeles were merged
with the pollutant data for analysis. Besides examining the oxidant relation-
ships with the other variables being considered at each station, attention was
to be given to examining the potential differences of the relationships from
(i) station to station, and (ii) overtime (note, only the Los Angeles stations
had data for more than one year.) In order to perform its analysis, RTI was
to create a data base that could be used for the present study as well as
future studies dealing with additional objectives such as investigation of the
oxidant transport phenomena. In addition to the above objectives, EPA also
requested that RTI (1) examine upper percentile plots of daily maximum oxidant
(MOX) versus N02 and THC, and (2) contrast levels of the various variables
between weekend and weekday. It is important to note here that the objective
of the current study was not to determine a control strategy for oxidant but
only to examine relationships between MOX and various other variables.
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19
3. Data Selection and Description
3.1 Data Selection
In the selection of data for this study one objective was to obtain
sets from at least two geographic areas having different characteristics
with regard to photochemical oxldant problems. The Los Angeles area, with
its long history of photochemical smog problems and presumably a correspondingly
long period of record of required pollutant measurements, was an obvious
choice. The controversy that arose after this choice concerning
the techniques and procedures used for calibration of oxidant instruments
by the Los Angeles County Air Pollution Control District (LACAPCD) was
not considered a problem since only LACAPCD data were used and the data
set, therefore, was internally consistent.
Two aerometric stations were selected for analysis, the downtown
Los Angeles (DOLA) station at the LACAPCD headquarters, a metropolitan
location, and the Azusa (AZU) station located in a suburban industrial
area. Meteorological data required for the analysis were available only
from the Los Angeles International Airport. It was recognized that the
differences in weather conditions between the coastal location of the
airport and the inland locations of DOLA and AZU can be appreciable.
However, data availability was a deciding factor.
The east coast was selected as the source of the second data set. The
long period of record of oxidant, hydrocarbon, and nitrogen oxides concen-
trations from New Jersey appeared attractive. However, the fact that these
oxidant data were based on alkaline potassium-iodide determinations, known
to be subject to interferences, made their use impractical. Accordingly,
a compromise was made between quality of data and length of record and
four stations using gas-phase chemiluminescence detectors for ozone In the
-------
20
Maryland suburbs of Washington, D.C., were selected. These stations had
only nine months of data available. Meteorological data to merge into this
data set were available from both Dulles International Airport (Sterling,
Virginia) and Baltimore-Washington International Airport (Linthicum,
Maryland). Corresponding data were available from each of these airports
except that solar radiation measurements are not made at Baltimore-Washington
International.
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21
3.2 Description of the Data and Data Editing Procedures
RTI received two sets of data on computer tapes from EPA.. This data
was from EPA's data bank and contained, for various years
(i) pollutant data from six stations (four in Maryland and
two in Los Angeles) and
(ii) meteorological data from one station in Maryland, one station
in Virginia, and one station in Tos Angeles.
The site code, address, station and height of data collection for
each of the six monitoring stations are given below.
Station
Azusa,
Calif.
Downtown
Los Angeles
Bethesda,
Maryland
Hyattsville,
Maryland
Silver Spring,
Maryland
Suitland-
Silver Hill,
Maryland
Site Code
050500002 101
(AQCR 024)
054180001 101
(AQCR 024)
210200005 F01
(AQCR 047)
210980003 F01
(AQCR 047)
211480006 F01
(AQCR 047)
211560001 F01
(AQCR 047)
Address-Location
803 Loren Avenue
434 South Pedro St.
National Institute
of Health
Wisconsin Ave.
Trailer located in
open field
Trailer located in
northwest branch
park grounds 100
feet south of
Route 410
Argyle Comm. Bldg.,
Okinawa .Road
Located 50 feet North
of Interstate 95
Suitland Federal
Center,
Suitland Parkway
Station Type
Suburban-
Industrial
Center City-
Commercial
Suburban-
Residential
Suburban-
Mobile
Suburban-
Mobile
Suburban-
Mobile
Height
Ground
Level (sic)
100 ft.
Above
Ground
12 ft.
Above
Ground
12 ft.
Above
Ground
12 ft.
Above
Ground
10 ft.
Above
Ground
-------
22
In addition, the monitoring methods used in collecting the pollutant
data at the two cities under study were the following:
Total Nitric Oxide and Non-Methane
City Oxidant Hydrocarbons Nitrogen Dioxide Hydrocarbons
Los Angeles Neutral- Flame Colorimetric
Buffered KI lonization Saltzman
Maryland Gas-Phase Flame Colorimetric Flame
Chemiluminescent lonization Saltzman lonization
Figures 7 and 8 present maps showing both the air and meteorological
station locations.
Table 1 describes the times and locations of data collection for
data received by RTI. The table shows that data was obtained in Los
Angeles for various years on the pollutants nitric oxide (NO), nitrogen
dioxide (NO.), total hydrocarbons (THC), and oxidant (OX) while in Maryland
the pollutant data obtained was only for 1973 on the pollutants NO, N02, THC,
non-methane hydrocarbons (NMHC) and ozone (OZ). In addition, the table shows
that the meteorological data received was from the Los Angeles International
Airport for 1965 and 1972 and from Dulles and' Baltimore Airports for 1973
only.
v *
Before the raw data received by RTI could be analyzed, several preliminary
data editing steps had to be completed. These steps included the following:
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23
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fes^^^^KgflS^^^feit^I^
^FJ&X.: ^-^SM^ffrf^ptr^
p5^.'f; ^^^T-^^^x^v^^U^^^e^^
v-1.^H ;s_,.;'.=j—al ; .Lw^^r-^-ggigjA ••|>a-:;^-. -^r- Beach ::
S
-------
24
'• • .. .-,/ ^~\ff~ /Sdvace^-N-
•mi ILs^r/^^K^
It, r,.,,,maf / ' *J^ruiumat
•suille \j / \
•—
-------
25
TABLE 1
Summary of the Times and Locations of Data Collection for the
Pollutant and Meteorological Data Received on Tape from EPA's Data Bank
21
Station
NO
Pollutant Data (Hourly Readings)—'
Total Non-Methane
NO,
Hydrocarbons Hydrocarbons Oxidant Ozone
AZU
(Azusa)
DOLA
(Downtown)
BETH
(Bethesda)
HYAT
(Hyattsville)
SISP
(Silver
Spring)
SUIT
(Suitland)
1968-1973
1968-1973
1973
(Jan-Sept)
1973
1973
(Jan-Sept)
1973
(Jan- Sept)
1965-1973
1965-1973
1973
(Jan-Sept)
1973
1973
(Jan- Sept)
1973
(Jan- Sept)
1967-1973
1965-1973
1973
(Jan- Sept)
1973
1973
(Jan-Sept)
1973
(Jan- Sept)
1973
(Jan- Sept)
1973
1973
(Jan-Sept)
1973
(Jam-Sept)
1965-1973
1965-1973
1973
1973
1973
1973
Meteorological Dat,
I/
1. Ceiling Height
2. Sky Condition
3. Visability
4. Sea Level Pressure
5. Dew Point Temperature
6. Wind Direction
7. Wind Speed
8. Station Pressure
9. Weather
10. Dry Bulb Temperature
11. Wet Bulb Temperature
12. Relative Humidity
13. Cloud Cover
14. Solar Radiation
Present at LA International 1965, 1972;
Dulles and Baltimore 1973.
Present at LA International 1965, 1972;
Dulles 1973.
- Meteorological data was recorded once every three hours except for
Solar Radiation which was either hourly or daily total.
2/
- NOTE: Oxidant collected in Los Angeles, ozone collected in Maryland.
Also NMHC only collected in Maryland.
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26
A. Create a data file by station and year of summary
statistics for the pollutant data. This file in-
cluded the following statistics for each day of
the year:
(1) Date (Year, month, day)
(2) Daily max.— oxidant (ozone) between 8 A.M.
and 6 P.M. (denote by MOX or MOZ). (All
analysis on oxidant (ozone) in this report
was done on MOX or MOZ.)
(3) Second daily max. oxidant (ozone) between
8 A.M. and 6 P.M.
(4) Time of the first and second daily max.
oxidant (Table 2 gives the frequency dis-
tribution of the time of max. oxidant (ozone)
for three stations.)
(5) Number of oxidant readings between 8 A.M.
and 6 P.M.
(6) Three-hour averages and number of readings
present in the three-hour period for NO, N0_,
THC and NMHC. (All analysis on these pollu-
tants in this report was with three-hour
averages.) The three-hour averages computed
were: 5 A.M. to 8 A.M.
6 A.M. to 9 A.M.
7 A.M. to 10 A.M.
8 A.M. to 11 A.M.
9 A.M. to 12 A.M.
10 A.M. to 1 P.M.
- If max. occurred more than once then time of first max. was recorded,
-------
27
TABLE 2. Frequency Distribution (in days) of Time of Maximum Oxidant
(Ozone)— for Three Stations
Time of
Max. Oxidant
BETH (1973)
Freq. Percent
HYAT (1973)
Freq. Percent
DOLA (1972)
Freq. Percent
8-9 A.M.
9-10
10-11
11-12
12-1 P.M.
1-2
2-3
3-4
4-5
5-6
all zero
TOTAL
HBI^^^M^M
25
31
42
55
68
44
19
11
8
7
31
341
7.3
9.1
12.3
16.1
19.9
12.9
5.6
3.2
2.3
2.1
9.1
100
—•^^.A—
23
24
27
46
54
35
9
13
4
2
50
287
8.0
8.4
9.4
16.0
18.8
12.2
3.1
4.5
1.4
.7
17.4
100
A
27
36
63
82
75
40
15
16
6
1
362
7.5
9.9
17.4
22.7
21.0
11.0
4.1
4.4
1.7
.3
100
AT TIME
OF MAXIMUM
OXIDANT
(OZONE)
TABLE 3. Summary Statistics for Meteorological Data
The following meteorological variables were merged with the pollutant data.
Notation
1. Visibility (in miles) ~VIS
2. Sea Level Pressure (in millibars) SLP
3. Dew Point Temperature (in degrees, F) DPT
4. Wind Direction, North-South (in knots) XWD
5. Wind Direction, East-West (in knots) YWD
6. Wind Speed (in knots) WS
. 7. Relative Humidity (in percent) RH
8. Maximum Temperature (from 7 A.M. to 7 P.M. MTEMP
in degrees, F)
9. Solar Radiation (daily total in Langleys) SRAD
10. 24-Hour Change in Relative Humidity (in RHC24
percent)
11. Average Wind Speed (from 7 A.M. to 7 P.M.
in knots) AWS
12. Average Wind Direction, North-South (from XAWD
7 A.M. to 7 P.M. in knots)
13. Average Wind Direction, East-West (from YAWD
7 A.M. to 7 P.M. in knots)
- Max. between 8 A.M. and 6 P.M.
-------
28
If all three hours in a particular time period
were not present the average for the period
was still computed (note, at a later date an
editing rule was established to determine how
many readings in a three-hour period must be
present to consider the three-hour average
as not missing, see E. below).
Create a data file by station and year of summary statistics
for the meteorological data. These meteorological summary
statistics are given in Table 3.
Merge data files created in A. and B. to give one data file
by station and year of summary statistics for all pollutant
and meteorological data.
Generate cross-tabulations from files created in C. to
determine what data was available for analysis and to
establish data editing rules. For example, one of the
cross-tabulations generated was the following:
Body of Table » Number of_ Days Where Data Present
Oxidant Hours Present
Between 8 A.M. and 6 P.M.
N02
Three Hours Present 6 A.M. -9 A.M.
Two Out of Three Present 6 A.M. -9 A.M.
One Out of Three Present 6 A.M. -9 A.M.
Zero Out of Three Present 6 A.M. -9 A.M.
10
9
8
7
6 or less
E. Using the cross-tabulations generated in D. the follow-
ing data editing rules were established by RTI:
-------
29
(i) the max. daily oxidant (ozone) reading for a day
was considered present only if 9 or 10 hours
of data were present between 8 A.M. and 6 P.M.
(ii) a three-hour average for NO, N02> THC and NMHC
was considered present only if 2 or 3 hours of
data were present during the three-hour period.
F. In addition to the data editing referred to in E.,
RTI, after discussions with EPA personnel, also eliminated
a few days (approximately 1% of the total number of
days) of data which had questionable readings. (Note:
In this report not all of the data on the merged data
file was analyzed in detail. However, the file was
created so that in the future additional analysis
may be undertaken.)
Having merged and edited the atmospheric pollutant and meteorological
data received from EPA, RTI then examined the relationship between daily max.
oxidant (ozone) and the other variables available. Section 5 describes the
results of this examination.
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30
4. Study Limitations
The present study had several limitations due to the data and time that
were available for analysis. These limitations included the following:
(i) The meteorological data were collected at different sites
than the pollutant data. In Los Angeles the meteorologi-
cal data were collected at LA International while the
pollutant stations were Downtown LA and Azusa which are
approximately 12 and 30 miles respectively from LA
International. In Maryland the meteorological data were
collected at Dulles and Friendship Airports while the
pollutant data were from four sites around the Washington
area which varied from approximately 20 to 30 miles
from Dulles.
i
(ii) The meteorological data obtained in Los Angeles were only
for the two years 1965 and 1972.
(iii) The pollutant and meteorological data obtained for
Maryland were only for 1973.
(iv) All data obtained were surface data, i.e., there were no
upper atmospheric measurements.
(v) Time did not permit analysis of the transport phenomena,
i.e., all analysis was on a one station at-a-time basis.
(It should be mentioned here that the data base developed
by RTI during this study may be used at a later date by
EPA to investigate the transport phenomena).
-------
31
(vi) Some of the pollutant variables had a large number of
missing values (number of days where data was missing)
for some time periods. For example, in Los Angeles in 1965
no NO data and a limited amount of THC data were available
while for all four Maryland stations only about one-half
of the days (1973) had pollutant data for NO, N02> THC
and NMHC (see Tables 4 and 5 for sample sizes available).
The presence of this missing data, particularly in
Maryland, resulted in the loss of a great deal of informa-
tion when various statistical tools such as regression
and cluster analysis were employed. To illustrate the
sample size problem consider the Bethesda (BETH), Maryland
station. In BETH in 1973,after editing the data,there were
181 days with THC data, 149 days with N02 data, 161 days
with NO data and 157 days with NMHC data (see Table 4).
When analysis of this data was limited to the oxidant
season (taken to be May thru October in this report),
the corresponding sample sizes in BETH were THC=91 days,
N0.=73 days, N0=79 days and NMHC=89 days. Stepwise regression
analysis was then applied to this data which has the limita-
tion that if any day does not have information on all pollu-
tants then this day's data are considered missing. The
resultant sample size for the stepwise regression analysis in
BETH was only 56 days (see Table 9). (Table 9 shows that
all four Maryland stations had similar sample sizes for
the stepwise regression analysis.)
-------
32
(vii) The oxidant data collected in Los Angeles was not corrected
for SO. and NO interferences. However, for the analysis
£» X
presented in this report this was not considered to be a
serious problem.
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33
5. Data Analysis
5.1 Introduction
In this section the analysis of the merged and edited data described
in Section 3.2 is presented. Recall that the main objective of this
research was to examine the relationships between MOX and the various other
variables under study. Accordingly, in this section the data analysis is
presented as follows:
(i) First yearly summary statistics (e.g., means
and correlations) and frequency distributions
(for May through October data) are given for
the pollutant variables (Sections 5.2 and 5.3).
This analysis allows comparisons of (a) pollutant
levels between and within locations; (b) monthly
means and correlations and (c) the number of
days of missing data for each pollutant.
(ii) Next, relationships between MOX and each of
the pollutant and meteorological variables on
a one-at-a-time basis are examined (Section 5.4)
(that is, relationships between MOX and only
one other variable). This analysis ignores
the Joint effect of the various variables on
MOX but gives insight into how MOX is related
to each of the other variables one-at-a-time.
Included in this section are plots of the means
of several of the pollutant and meteorological
variables for different levels of MOX (MOZ)
-------
34
(Section 5.4.1), correlations between MOX (MOZ)
and the other variables under study (Section
5.4.2), scatter plots of MOX (MOZ) versus
several of the other variables (Section 5.4.3),
and maximum oxidant (ozone) versus day of the
week (Section 5.4.4).
(iii) A somewhat different look at the data using
upper percentile analyses is presented in
Section 5.5. This is done for two reasons:
(a) scatter plots between MOX and the other
variables are very hard to interpret because
of the relatively large variability in
atmospheric data and (b) the present control
strategy for oxidant is based on an upper
envelope analyses.
(iv) Finally, in Section 5.6 multiple variable
relationships are considered. That is, the
relationships between MOX and a combination of
several other variables are examined. This analysis
attempts to study the joint effect of several
variables on MOX. Included in this section
are stepwise regression (Section 5.6.1),
cluster analysis (Section 5.6.2) and linear
regression analysis including regression of MOX
on N02 and THC after adjustment for selected
meteorological variables (Section 5.6.3).
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35
5.2 Yearly Summary Statistics for the Pollutant Variables
A preliminary analysis was conducted for the pollutant variables.
Table 4 presents summary statistics for the pollutant variables by year
and station. Note that in Table 4, 6-9 A.M. averages were used for
THC, NO , NO, and NMHC. In examining the table the reader is cautioned
that the sample sizes vary a great deal; thus, making comparisons between
pollutants difficult. In particular, the table shows that at the four
Maryland stations a great deal of data is missing for THC, NO,, NO and
NMHC. Table 4 indicates that in Los Angeles the mean daily maximum oxi-
dant has decreased since 1965 at the two stations examined (Altshuller [1]
also noted a downward trend in oxidant levels over time). In addition,
the table shows that the MOX readings in Los Angeles are substantially
higher than the MOZ readings in Maryland and that AZU has higher MOX means
than DOLA. (Altshuller [1] states in Los Angeles that sites near the ocean
measure lower oxidant levels than sites well inland.) As would be expected,
the THC, NO. and NO levels are higher at DOLA than at AZU. For the four
Maryland stations SISF has the lowest MOZ levels and the highest levels
of NO and NMHC. (This is undoubtedly due to the fact that SISP is located
very near a major freeway.) In addition, to the means and standard devia-
tions given in Table 4, RTI also calculated means and correlations (bet-
ween MOX and the other pollutant variables) by month. For example,
Figure 9 presents a plot of the means by month for MOX, NO, NO., THC and
NMHC for AZU and DOLA (1972) and for SISP and SUIT (1973). (Plots of the
means by month for BETH and HYAT were similar to those for SUIT.) The
estimated correlations are not given here because many of them were based
on relatively small sample sizes due to missing data. Examination of these
means and correlations indicated, as expected, that the summer months had
-------
36
TABLE 4. Summary Statistics for Pollutant Variables
by Year and Station (units = ppm)i/
Daily Maximum Oxidant (MOX) Station
A2U (Azusa)
1965 1968 1972
DOLA (Downtown)
1965 1968 1972
MOZ
BETH HYAT SISP SUIT
1973 1973 1973 1973
Mean
s.d.
Max.
No. Days
Present
% of Days
Where Max.
>.08 ppm
.158 .147 .121
.11 .094 .087
.54 .44 .49
334 340 347
62.6 68.2 55.3
.120 .100 .080
.088 .070 .052
.58 .46 .25
340 342 331
.053 .045 .033 .048
.045 .043 .027 .044
.41 .20 .13 .40
291 246 276 247
55.6 49.7 40.8 19.2 17.5 6.2 15.0
THC (6-9 A.M. Average)
Mean 3.05 2.92 3.68
s.d. 1.04 1.03 .96
No Days
Present
103 318 340
4.52 3.94 3.79 1.22 2.01 1.90 1.54
2.44 1.69 1.36 .65 .90 .85 .40
253 336 330 181 224 181 145
N02 (6-9 A.M. Average)
Mean .045 .044 .065
s.d. .033 .038 .041
.096 .077 .100 .046 .065 .048 .055
.063 .056 .054 .028 .039 .034 .041
No Days
Present
259 324 322
329 312 320
149 205 177 151
NO (6-9 A.M. Average)
Mean .033 .047
s.d. .027 .054
.154 .134 .026 .054 .081 .045
.137 .114 .059 .064 .113 .067
No Days
Present
286 313
320 316
161 188 180 150
NMHC (6-9 A.M. Average)
Mean
s.d.
No Days
Present
.241 .223 .385 .295
.30 .35 .53 .39
157 180 169 124
— Mote the number days where data present varies a great deal over years
and pollutants.
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37
Plot of Means of Daily Max. Oxidant (Ozone) and 6 A.M. to 9 A.M.
Daily Averages of NO, NO., THC and NMHC
V-5
3-5
2.ol
AZU (1972)
DOLA (1972)
FIGURE 9
TIME (Months)
TDIE (Months)
SISP (1973)
SUIT (1973)
(ppm)
'•51
/.o
.5
-. -L
*^»
. ;:,:.
TIME (Months)
TIME (Months)
-------
38
higher means for MOX (MOZ) and higher correlations between MOX (MOZ) and
the other pollutant variables. In addition, monthly correlations bet-
ween MOX (MOZ) and averages of the other pollutants for various time
periods (e.g., 5-8 A.M., 6-9 A.M., 7-10 A.M., etc.) did not indicate
that in general any one 3-hour period gave higher correlations. Accord-
ingly, for the remainder of the analysis described in this report RTI only
examined data for the months May through October (the oxidant season, see
[9]) and 3-hour averages between 6-9 A.M. for NO, N02> THC and NMHC (6-9
A.M. was chosen because this is the time interval used in much of the
literature, see [9]). Furthermore, because the 1965 Los Angeles NO and
THC data had so many missing values no additional analysis was done with
this 1965 data.
-------
39
5.3 Frequency Distributions for the Pollutant Variables (May through
October Data)
Frequency distributions and summary statistics were computed for the
several stations using only data from May through October and 6-9 A.M.
averages for NO, NO., THC and NMHC. Results of these calculations are
given in Tables 5 and 6. Table 5 shows for the May through October data
that:
(i) AZU has higher levels of MOX than DOLA,
(ii) MOX levels have decreased from 1968 to 1972 in
both Los Angeles stations,
(iii) THC levels are about the same at both stations,
(iv) NO and N0? levels are higher at DOLA than at AZU,
(v) THC and NO- levels have increased somewhat from
1968 to 1972 at both stations.
Table 6 (for BETH and SUIT) shows that (the summary statistics for HYAT
were similar to those for BETH and SUIT while those for SISP were distorted
as shown in Table 4 due to its location near a major freeway):
(i) the levels of MOZ, THC, NO- and NMHC are about
the same at BETH and SUIT,
(ii) the levels of MOZ are lower in Maryland than
levels of MOX in Los Angeles,
(iii) the sample sizes (number of days) for THC, N02>
NO and NMHC in Maryland are only about one-half
of the corresponding sample sizes in Los Angeles,
(iv) the levels of THC are much higher in Los Angeles
than in Maryland,
(v) NO levels are higher in Los Angeles than in
Maryland.
-------
TABLE 5.
40
Daily Max. Oxidant, N02, NO and THC Frequency Distributions
and Summary Statistics for 1968 and 1972 (May through
Ocotber Data); for Stations AZU (Azusa) and DOLA (Downtown)
Cum. Freq. Distribution
Cum. Freq. Distribution
MOX
Intervals
(ppm)
0 -.04
.04-. 08
.08-. 12
.12-. 16
.16-. 20
.20-. 24
.24-. 28
>.28
Mean
Std. dev.
N
% Days >!/
.08 (ppm)
N02 (6-9 AM)
Intervals
(ppm)
0 -.03
.03-. 06
.06-. 09
.09-. 12
.12-. 15
.15-. 18
>.18
Mean
Std. dev.
N
AZU
1968
%
2.8
14.9
26.5
40.3
54.1
69.1
82.3
100.0
.193
.095
181
85.1
Cum.
1972
%
5.1
24.4
38.6
56.8
72.2
83.0
92.0
100.0
.159
.091
176
75.6
Freq.
AZU
1968
%
39.3
61.9
81.6
90.5
97.0
98.8
100.0
.054
.044
168
1972
%
13.3
43.4
66.9
83.8
97.6
99.4
100.0
.074
.041
166
DOLA
1968
%
6.3
32.2
56.3
74.7
86.3
92.5
96.0
100.0
.126
.075
174
67.8
1972
%
8.6
44.0
75.5
85.2
94.9
98.9
100.0
.100
.054
175
56.0
THC (6-9 AM)
Intervals
(ppra)
0-1
1-2
2-3
3-4
4-5
5-6
>6
Mean
Std. dev.
N
Distribution
DOLA
1968
%
15.6
37.8
67.1
82.1
88.7
91.7
100.0
.084
.063
167
1972
%
2.9
25.3
51.1
70.5
82.3
89.4
100.0
.103
.060
170
NO (6-9 AM)
Intervals
(ppm)
0 -.03
.03-. 06
.06-. 09
.09-. 12
.12-. 15
.15-. 18
>.18
Mean
Std. dev.
N
AZU
1968
%
0.0
.6
43.9
79.0
94.2
98.3
100.0
3.04
1.07
171
Cum.
1972
%
0.0
0.0
4.6
54.0
90.2
99.4
100.0
3.73
.77
174
DOLA
1968
%
0.0
.6
26.4
63.2
85.6
96.5
100.0
3.57
1.33
174
1972
%
0.0
1.1
10.9
58.3
85.1
94.9
100.0
3.70
1.09
175
Freq. Distribution
AZU
1968
%
61.3
85.7
96.4
98.8
99.4
99.4
100.0
.031
.027
168
1972
%
48.8
84.0
97.6
99.5
100.0
.035
.023
162
DOLA
1968
%
14.9
37.5
59.5
72.6
81.5
85.6
100.0
.104
.097
168
1972
%
16.3
36.8
59.7
74.2
85.0
91.0
100.0
.090
.066
166
— .08 ppm is the current yearly standard for MOX, N
number of days.
-------
41
TABLE 6. Daily Max. Ozone, N02, NO, THC and NMHC Frequency Distributions
and Summary Statistics for 1973 (May through October Data);
for Stations BETH (Bethesda) and SUIT (Suitland)
Cum. Freq.
Distribution
Cum. Freq.
Distribution
Cum. Freq.
Distribution
MOZ
Intervals
(ppm)
0 -.03
.03-. 06
. 06- . 09
.09-. 12
. 12- . 15
>.15
Mean
Std. Dev.
N
% Days >
.08 (ppm)-'
BETH
%
8.3
32.6
69.5
88.9
96.5
100.0
.076
.039
144
37.5
SUIT
%
6.8
33.9
78.8
92.4
99.2
100.0
.070
.033
118
28.8
THC (6-9 AM)
Intervals
(ppm)
0-1
1-2
>2
Mean
Std. Dev.
N
Cum. Freq.
Distribution
NO (6-9 AM)
Intervals
(ppm)
0 -.03
.03-. 06
.06-. 09
>.09
Mean
Std. Dev.
N
BETH
%
91.1
98.7
100.0
.008
.013
79
SUIT
%
75.0
89.1
95.4
100.0
.023
.034
64
NMHC (6-9 AM)
Intervals
(ppm)
0 -.01
.01-. 02
.02-. 03
.03-. 04
.04-. 05
.05-. 06
>.06
Mean
Std. Dev.
N
BETH
%
17.6
98.9
100.0
1.32
.30
91
N02 (6-9AM)
SUIT Intervals
% (ppm)
1.6 0 -.03
93.7 .03-. 06
100.0 .06-. 09
.09-. 12
>.12
1.53 Mean
.26 Std. Dev.
63 N-
BETH SUIT
% %
24.7 35.2
72.6 65.3
90.4 85.0
97.2 92.0
100.0 100.0
.048 .052
0.29 0.49
73 71
Cum. Freq.
Distribution
BETH
%
40.4
71.9
83.1
88.7
95.4
98.8
100.0
.152
.163
39
SUIT
%
47.9
77.1
85.4
89.6
89.6
93.8
100.0
.162
.230
48
— .08 ppm is the current yearly standard for MOZ, N = number of days.
-------
42
5.4 One-At-A-Time Relationships Between MOX (MOZ) and the other Variables
5.4.1 Mean Plots of Several Variables Versus MOX (MOZ)
In examining the relationships between daily maximum oxidant
(ozone) and the various pollutant and meteorological variables under
study, RTI calculated and plotted the means of several of the pollutant
and meteorological variables for three different levels of MOX (MOZ).
Figure 10 presents these plots for AZU and DOLA (1972) and BETH and
HYAT (1973) where the three levels of MOX in LA are:
(i) MOX * .08 ppm,
(ii) .08 < MOX $ .20 ppm, and
(iii) MOX > .20 ppm.
and the three levels of MOZ in Maryland are:
(i) MOZ S .04 ppm,
(ii) .04 < MOZ < .08 ppm, and
(iii) MOZ > .08 ppm.
In addition, the plots give the overall means of the various variables.
Before plotting the means in Figure 10, confidence limits for the means
from the four stations were computed and as expected these limits were
quite narrow except when sample sizes were small. In particular, in
DOLA the sample size for the M3 means for all variables was only 9
leading to relatively wide confidence limits. For this reason the M3
means for DOLA were not plotted. The sample sizes for all of the means
plotted were greater than 15; and therefore, confidence limits on these
means are relatively narrow.
The plotted means in Figure 10 show fairly consistent patterns within
location. The only exception to this is the quadratic pattern of NO- in
HYAT. However, the reader should note the range of the three NO. means
-------
43
plotted is only from .061 to .077 ppm which is a relatively small range.
Between locations, the plots show somewhat different patterns for VIS,
WS, and RH. (Note Table 13 in Section 5.6.2 gives some of the means plotted
in Figure 10.) Means for stations SISP and SUIT were not
plotted here because they give essentially the same patterns as BETH
and HYAT. The only exception to this were the means of SISP for NO
and THC which tended to decrease with increasing MOZ level. However,
the results for this station are suspect because SISP is located near
a major freeway.
-------
FIGURE 10. Plots of the Means of Meteorological and Pollutant Variables for Three Levels
of Daily Max. Oxidant (Ozone) (May through October Data).
44
5
AZU
(1972)
'
VIS
(miles)
/0-
\
- \
\
\
v oy/v-._ ,vt-/^*0
t
DOLA \
(1972) ... \
\
\
\
c;s T
» (miles) \
• \ ! - \
i ' i
*: ; // - />< 1
BETH
(1973)
12 •
'15 fo
(miles)
A
' / •
/ < 0/£^Au^ ft] E ft k{& tr'J
'
\
J rn; 7~. ,v3
AZU
rr
OPT
(degrees, F)
r-'-J
.,
.^^
f
1
1
1
1
;
*
J 7 . ' ' '
lt\ Ml M3
ffi; #2. ,« 3
HYAT
...
" / \ UP:
(miles) \
Ml *i -V;
/ZT
.
DOLA . /
So <• /
1 ... r> ff-
/
OPT ; /
(degrees, F)
~£ •^•
til .".12. ft 3
; /
a\ /
BETH /
/
/,' -i / ntf
i-'T
(degrees, F)J? _
[
/
HYAT /
/ n;>,
61 - /
(degrees, F^ /
r- t 1 ^
£3 ' T 1 » -' 'MI . '- if --
r. • ,.- .1^ IK f fl <** /''^
In AZU and DOLA, Ml = Mean when max. oxidant £ .08, M2 = Mean when max. oxidant .08 to .20 and
M3 = Mean when max. oxidant > .20 ppm.
In BETH and HYAT, Ml =» Mean when max. ozone £ .04, M2 - Mean when max. ozone .04 to .08 and M3 -
Mean when max. ozone > .08 ppm. Note in DOLA only 9 readings were present for max. oxidant
group M3; therefore, these means were not plotted. Sample sizes for all plotted means are £ 15.
-------
FIGURE 10. Plots of the Means of Meteorological and Pollutant Variables for Three Levels
continued ot~ Daily Max. Oxidant (Ozone) (May through October Data). ,
V knots'* ?
(.knots'*
DOLA
(knots)
HYAT
(knots)
>yfl
DOLA
(%)
-'•J T
HYAT
fi h'
• erf
i AIV ar.c DOLA, MI = Mean when aax. oxidaat < .08, M2 = Mean when aax. oxidant .08 to .20 and
Y.2 - Mean when r.ax. oxidant > .20 ppm.
-. 3ZTH ar.c -TVAI, Ml = Mean when riax. ozone £ .04, M2 = Mean when max. ozone . 0^ to .08 and M3 =
Mean when -ax. osone > .08 ppc. Note in DOLA only 9 readings were present for aax. oxidant
jrrur M2; therefore, these neans were r.ot plotted. Sample sizes for all plotted means are > 15.
-------
FIGURE 10.
continued
Plots of the Means of Meteorological and Pollutant Variables for Three Levels
of Daily Max. Oxidant (Ozone) (May through October Data).
46
AZU
(degrees)
—~c.fr.
r 7
DOLA
(degrees)
Off
BETH
(degrees) ;
HYAT
(degrees)
?}
•Off]
AZU
(Langleys)
•erf:
-I >
Hi.
BETH
- CA"
= *' * !!„.{.
(Langleys) \
•o/v
100
DOLA
(Langleys)
HYAT
(Langleys)
(eel.
/
-ic-C-
•orr.
1 ) '-
f'l />' ^ '/ 7
5,4
In AZU and DOLA, Ml = Mean when max. oxidant <. .08, M2 = Mean when max. oxidant .08 to .20 and M3
Mean when max. oxidant > .20 ppm.
In BETH and HYAT, Ml = Mean when max. ozone <> .04, M2 = Mean when max. ozone .04 to .08 and MJ =
Mean when max. ozone > .08 ppm. Note in DOLA only 9 readings were present for max. oxidant
group M3; therefore, these means were not plotted. Sample sizes for all plotted means are > 15.
-------
FIGURE 10. Plots of the Means of Meteorological and Pollutant Variables for Three Levels
continued of Daily Max. Oxidant (Ozone) (May through October Data).
AZU
(ppm)
DOLA
i'_ ;
(ppm)
— r ft
-\—
HYAT
/»; #; .:'5
'Cf'
CX
•
9
/
47
.'•II
BETH
(ppm)
-Olft
HYAT
(ppm)
/«'
/>! 2-
In AZU and DOLA, Ml = Mean when max. oxidant Z .08, M2 = Mean when max. oxidant .08 to .20 and M3
Mean when max. oxidant > .20 ppm.
In BETH and HYAT, Ml = Mean when max. ozone 2 .04, M2 = Mean when max. ozone .04 to .08 and M3 =
Mean when max. ozone > .08 ppm. Note in DOLA only 9 readings were present for max. oxidant
group M3; therefore, these means were not plotted. Sample sizes for all plotted means are > 15.
Note in HYAT for N02 the plot shows a quadratic pattern. However, the reader should note the
range of the means is only from .061 to .077 ppm.
-------
48
5.A.2 Correlations
Table 7 presents the correlations between MOX (MOZ) versus
the other variables for the six stations. (Note that the two sets of
correlations given for Maryland are for meteorological data at Dulles
and at Baltimore and that the correlations for Los Angeles are for
1972. In addition the numbers in [ ] for AZU and DOLA are correla-
tions for 1968). The plots in Section 5.4.1 and the correlations in
Table 7 show that:
(i) MTEMP and SRAD usually have a relatively high
positive correlation with max. oxidant (ozone),
(ii) in Los Angeles THC and NO- have a relatively
high positive correlation with MOX,
(iii) DPT usually has a relatively high positive
correlation with MOX (MOZ) while RH in Maryland
usually has a relatively high negative correla-
tion with MOZ,
(iv) VIS has a negative correlation with MOX (MOZ),
(v) NO, N02, THC and NMHC in Maryland have relatively
small correlations with MOZ,
(vi) WS and AWS have negative correlations with MOZ
in Maryland,
(vii) the corresponding correlations for Dulles and
Baltimore meteorological data are quite similar
and they were both given here only for the sake
of completeness (because of this fact only Dulles
meteorological data was used in subsequent analysis)
-------
49
(viii) the corresponding correlations in AZU and DOLA
for the pollutant variables in 1968 and 1972
are similar.
It should be pointed out here that in order to exhibit high
correlations between two variables, it is necessary to have a wide range
of values for both variables. That is, if neither variable has a wide
range of values the correlation between them cannot be demonstrated
even if it exists. This is one explanation of why the correlations
between MOZ and THC in Maryland are relatively low. Figure 19 in
Section 5.5 demonstrates this clearly. The figure shows that the
approximate ranges of THC in LA are from 1 to 8 ppm while in Maryland
these ranges are only from .5 to 3.5 ppm.
On the other hand, the relatively low correlations between
NCL and MOZ in Maryland cannot be explained by the above range argument
since both LA and Maryland have similar ranges for N0_. The lack of
correlation between N02 and MOZ in Maryland is readily apparent in
Appendix Figure A-ll.
In addition to the correlations in Table 7, Table 8 also
presents the correlations between MOX (MOZ) versus the other variables
for days when MOX (MOZ) > .08 ppm (the standard for oxidant) by
station. The correlations for SISP are not given because the number of
days when MOZ > .08 ppm was less than 15 days for this station. Table 8
shows that
(i) In AZU and DOLA the correlations when MOX > .08
tend to be smaller than the corresponding corre-
lations for all data. For example, the correlations
between MOX and SRAD for all data were .64 and
-------
50
.53 for AZU and DOLA while these same correlations
were .42 and .40 respectively on days when
MOX > .08.
(ii) In Maryland the correlations which were relatively
high for all data also tend to be smaller when
MOZ > .08. For example, the correlations between
MOZ and MTEMP for all data were .75, .76 and .66
for the three stations while for MOZ > .08 these
correlations were reduced to .31, .31 and .35,
respectively.
Thus, in general, deleting the lower range of MOX (MOZ) did not
increase its correlations with the other variables under study.
-------
TABLE 7
Met.
Poll.
= >
Correlations Between Daily Max. Ozone (Oxidant) Versus Pollutant
and Meteorological Variables (May through October Data) by Station
Variable*
VIS
SLP
DPT
XWD
YWD
WS
Rll
MTEMP
SRAD
RHC24
AWS
XAWD
YAWD
NO (6-9)
NO (6-9)
£
THC (6-9)
NM11C (6-9)
Ave. Sample
Size Met.
(Days)
Avu . Sample
Size Poll.
(Days)
BETH
Dulles**
-.26
.15
.52'
-.14
-.05
-.20
-.23
.75'
.58'
-.01
-.18
-.14
-.09
.09
.05
.24
.24
145
84
HYAT
Dulles
-.12
31X
.47'
-.18
-.20
-.30/
/
-.37'
.76'
.55'
.00
-.25
-.30'
-.11
.01
.12
.20
.13
115
89
SISP
Dulles
.03
.05
.31/
.15
-.21
-.11
/
-.49
64 '
v
-.22
-.33'
.22
-.34/
-.13
-.13
-.10
.04
143
97
SUIT
Dulles
-.07
.11
.36'
-.09
-.07
-.12
/
-.38
.66/
.6l'
-.10
-.13
-.16
-.08
.01
-.07
.36'
-.10
118
63
AZU
1972
j
-.34/
-.13
.33'
-.07
-.32'
.17
.13
.19
.64'
.12
.26
-.05
-.34'
31 '[
'M'l
.51':
173
167
DOLA
1972
j
-.42/
-.20
.36'
-.07
-.23
.07
-.05
44X
V
.06
-.00
-.06
-.08
BETH
Bait.
J
-.36'
.15
.52/
-.11
-.07
-.10
-.24
67/
;5i'
-.05
-.20
-.22
-.06
.30] .15 [.58]
.53] .63/C.50]
.63] .53/C.71]
172
170
144
HYAT
Bait.
-.23
.32'
.49'
-.27
-.09
-.27
j
- 40
;«'
.53'
-.04
-.28
-.41'
-.10
113
SISP
Bait.
-.08
.02
.35'
.11
-.23
-.07
/
-.48'
.66/
.59'
-.19
-.25
.17
-.32'
142
SUIT
Bait.
-.19
.09
.38'
-.10
-.06
-.11
j
- .41
.66/
.59'
-.17
-.15
-.21
-.09
118
30| * Definitions of the various variables are given in Table 3.
** Dulles = meteorological data from Dulles, etc. for Baltimore,
I J = Correlations for LA in 1968.
-------
52
Table 8
Correlations Between Daily Max. Ozone (Oxidant) Versus
Pollutant and Meteorological Variables (May through October
Data) for Days When MOX (MOZ) > .08 ppm by Station
Variable
VIS
SLP
DPT
XWD
YWD
WS
RH
MTEMP
SRAD
RHC24
AWS
XAWD
YAWD
NO (6-9)
N02(6-9)
THC(6-9)
NMHC(6-9)
Ave. Sample
Size Met.
(Days)
Ave. Sample
Size Poll.
(Days)
BETH
DULLES
-.34/
.25
.34/
-.05
-.02
-.19
.16
.31/
-.08
.11
-.15
.08
-.09
.15
.07
.09
-.06
54
35
HYAT
DULLES
-.08
.26
.17
.08
.02
-.17
-.16
.31/
-.15
.10
-.18
.16
.04
.03
.22
.19
.22
44
36
SUIT
SISP DULLES
-.36/
-.04
.32/
.04
-.19
-.22
-.03
.35/
.13
.11
-.13
-.01
-.15
.39/
.19
.28
.00
Sample 34
Size <15
Sample 24
Size <15
AZU
1972
-.27
-.01
.14
.13
-.10
.02
.13
-.04
.42/
.18
.26
.15
-.29
.33/
.56/
.52/
—
130
127
DOLA
1972
_|.30| SISP correlations not given because the number of days when
MOZ > .08 ppm was less than 15 days.
-------
53
5.4.3 Scatter Plots
Scatter plots of MOX (MOZ) versus several of the variables
were also plotted for the various stations. Figures 11 and 12,
respectively, present plots of (i) MOX versus THC in AZU (1972) and
(ii) MOZ versus THC in BETH. Several additional scatter plots are given
in Appendix A.
The most striking feature of all the plots is the large
variability in the data being examined. That is, for a given level of a
pollutant or meteorological variable the range of MOX (MOZ) values
observed is quite often very large. The effect of this variability was
previously observed in the correlations given in Table 7.
-------
FIGURE 11
= AZU. . .
PLOT OP MQX vs(THC (6-9))
OT50000300
May through October, 1972
Overall Corr. = .51
j.'uoooooco
~0."20QG0009
0.10000000
0^00000000
.
_ .- ..
A.
B
A
C . .
B
B
A
a
. c
c
_ A . B
B
A C
C
E
A " " " B
A A 0
A B
a
_ .
2.20000000 ( 1.00000000
--
--
A
.A
A
A
A
f)
A
"A
0
B
B
A
B
A
. fift\ ^i*>
A
A
A ._.-__-
A
.A A A
B B
. . _ ^
A B
A A A
A A A A ....
B A . A _ .. . . .-
A A A ....
C A A
A a A
H A
A B A .
A A . . C ... . . A
A A A. . . _ . .
B
0
B B ...
V C A A .. „
A A
_A _ 0 .
A
A a _
A B A •
A
A A _
B
A B
A B
A
1.80000000 4.60000000 5,40000000 6.>3000*.J3
THC(6-9)
Ui
-is
-------
LEGENOl A s \ OB3 i 8 s 2 OBS , ETC,
FIGURE 12
STATION = 3 = BETH
Plot of MOZ vs 1HC (6-9)
May throiiRh October, 1973
Over.-iU Corr. = .24
-0,20000000
0,16000000
! 0,12000000
0,09000000
. 0.01000000
0,00000000
* A
. ... A ..
ABA
A A A
A A A t< A
A A
A _____ A
A_
A
_A
A ____ _.
B A
A. . . _A. ._ A .A A _ A d A A
A B B A
A A
A A A A
A A A A A
BAA
__ _._.
._ _.
A _ A..
- - _ . .A
'.56
.88
L20 THC(6-9\.52
1.84
2.16
-------
56
5.4.4 Means by Day of Week and Station
RTI also computed and plotted the means of several of the
variables under study by day of week and station. Figures 13 and 14
present plots of MOX (MOZ) by day and station. Figure 13 shows that AZU
has higher levels of MOX than DOLA and that AZU has its lowest MOX levels
on the average on the weekends. Figure 14 shows that SISF has lower
levels of MOZ than the other three Maryland stations and that BETH,
HYAT, and SUIT have their lowest levels of MOZ on the average on Sundays.
(Cleveland in looking at New York and New Jersey data found somewhat
higher ozone levels on Sundays [4] while Altshuller [1] found oxidant levels
to be about the same on Sundays for several CAMP Stations.) Figures 15
and 16 give plots of means of THC and SRAD by day and location. Figure
15 shows that both AZU and DOLA have their lowest THC levels on the
weekends while LA International gave the highest levels of SRAD on
Mondays. Figure 16 indicates that the levels of THC were lower at BETH
than at the three other Maryland stations and that HYAT and SUIT had
their lowest THC levels on Sunday. Figure 17 presents a plot of NO
and NO. for AZU and DOLA by day of week. The figure shows that NO and
NO- levels are higher at DOLA (recall that MOX levels were higher at
AZU) and that the lowest levels of both NO and NO- are on the week-
ends. (Cleveland [4] found lower NO, NO. and NMHC levels on Sundays).
Finally, Figure 18 presents a plot of MOX for two levels of SRAD for
AZU and DOLA by day of week. As expected when SRAD is high, MOX is
higher at both stations but unfortunately no other patterns by day are
obvious. (This may be due to the small sample sizes (= 12 observa-
tions) that each mean is based upon.)
-------
FIGURE 13
Plot of Means of Daily Maximum Oxidant by Day of Week- and Station
ilOX
(ppm)
///'//-5.
DAY OF WEEK
h
Ffil
- Data for 1972 May through October.
Each mean based on approximately 25 observations.
AZU
DOLA
•:ut/
-------
MOZ
(ppm)
58
FIGURE 14
Plot of Means of Daily Maximum Ozone by Day of Week— and Station
BETH = Bethesda
HYAT = Hyattsville
SISP = Silver Spring
SUIT = Suitland
SISP
-fl
DAY OF WEEK
— Data for 1973, May through October.
Each mean based on approximately 20 observations.
-------
3.? r
THC (6-
(ppm)
FIGURE 15
I/
Plot of Means of THC (6-9) by Day of Week and Station*
59
AZU
2-2. t-
DOLA
W_L
SRAD
(Lang)
flicf/
DAY OF WEEK
Plot of Means of SRAD (Daily Total) by Day of Week
LA International
I/ v
TUBS
F; i
HAY OF WEEK
May through October, 1972; each mean based on 20 to 27 observations.
-------
FIGURE 16
I/
Plot of Means of THC (6-9 A.M.) by Day of Week and Station—'
60
THC (6-9)
(ppm)
rIYAT
SISP /
3ETH
I/
Plot of Means of SRAD (Daily Total) by Day of Week.—'
• y.>
SSAD
(LANG) '/J" -
Dulles
I/
May through October, 1973; SRAD means based on approximately 16 to 20 observations,
THC means based on approximately 10 to 14 observations.
-------
FIGURE 17
I/
Plot of Means of NO, (6-9) and NO (6-9) by Day of Week and Station—'
61
•12. ~
(ppm)
3. (AZU)
\
\i,
\
\ I/O (DOLA
X-
'•^/.'- (AZU)
rt,ct/
DAY OF
- May through October, 1972; Each mean based on approximately 25 observations.
-------
LGURE 18
62
Plot of Means of Daily Maximum Oxidant by Day of Week— ,
High and Low Solar Radiation (SRAD) and Station
MOX
(ppm)
fast;
DAY OF WEEK
I/
- Data for 1972, May through October; Each mean based on approximately 12 observations.
-------
63
5.5 Upper Percentile Analysis
The scatter plots presented in Section 5.4.3 and Appendix A indicate
large variability in the atmosphere data being examined in this report.
For this reason it is very hard to interpret these plots. Accordingly,
in the present section plots of the 75th and 50th percentiles of the MOX
(MOZ) distribution for given levels of THC and NO. are examined. These
plots give an indication of how the percentiles of the MOX distribution are
changing as levels of THC and NO. increase.
Another reason for looking at percentlle^plots for MOX (MOZ) versus
THC is that the current control strategy for controlling atmospheric oxi-
dant pollution is based upon reducing hydrocarbon emissions by a certain
percentage (see Appendix J of the August 14, 1971 Federal Register). The
Appendix J curve was derived from an upper envelope curve of a scatter
plot of MOX versus NMHC for several CAMP stations (see Section 2.1). RTI
felt (especially with the sample sizes available for this report) that
more could be gained by looking at upper percentile plots than upper
envelope curves because an envelope curve is only dependent on the ex-
treme value of the MOX distribution (which could be an outlier) while
percentile plots take into account the shape of the MOX distribution and
are not dependent on just one value of this distribution.
Appendix Figures C-l through C-10 give for stations (i) AZU, (ii) DOLA,
and (iii) BETH, HYAT and SUIT data combined 75th and 50th percentile plots
of MOX (MOZ) versus THC and NO.. A description of how these plots were
obtained is given in Appendix C. SISP was not combined with the other
three Maryland stations because it is located near a major freeway which
leads to relatively low MOZ levels. Also, the reader is cautioned here
to note that some of the intervals where the MOX percentiles were estimated
-------
64
have relatively few data points. Figures 19 and 20 summarize the MOX (MOZ)
versus THC and N0_ 75th percentile plots for all stations and years.
Figure 19 shows that:
(i) Both the AZU and DOLA 75th percentiles have shifted
downward from 1968 to 1972. That is, for the same
value of THC the 75th percentile points have decreased
at both sites.
(ii) The AZU percentiles are higher than the DOLA percentiles.
(iii) The Maryland THC range is much smaller than that of
both the LA stations (this was discussed in Section
5.4.2).
(iv) The Maryland 75th percentiles are similar to those
for DOLA (1972) for the corresponding values of THC
(it would be interesting to investigate this for
several other years.) The fact that the Maryland
75th percentile curve is relatively flat indicates
for the data examined here that there is not a strong
relationship between MOZ and THC (Table 7 also indi-
cates this result). Thus in Maryland for the range
of THC examined here, reducing THC levels appears to
have relatively little effect on MOZ levels.
(v) It appears a linear relationship would be a reason-
able approximation to the 75th percentile line for
DOLA (1968 and 1972) and Maryland combined while the
AZU (1968 and 1972) 75th percentile lines appear
to have some curvilinearity as THC increases. Thus,
one could argue that for locations with MOX values
-------
65
less Chan or equal to DOLA that the 75th percentile
line for MOX versus THC can be approximated by a
linear relationship while for locations with levels
as high as AZU a curvilinear relationship may be
required (again the reader is cautioned that the
sample sizes used to estimate the MOX (MOZ) 75th
percentiles were quite small for some of the THC
intervals, see Appendix C).
Figure 20 shows that:
(i) Both the AZU and DOLA 75th percentile lines have
shifted downward from 1968 to 1972.
(ii) The AZU percentiles are higher than the DOLA percen-
tiles.
(iii) The Maryland NO. range is approximately the same as
that of the LA stations (this was discussed in
Section 5.4.2).
(iv) The Maryland 75th percentile curve is relatively
flat indicating that there is very little relation-
ship between NO. and MOZ in Maryland for the data
examined in this report (the correlations given in
Table 7 also indicate this result).
(v) As with THC, it appears that a linear relationship
would be a reasonable approximation to the NO. 75th
percentile lines for DOLA (1968 and 1972) while the
AZU 75th percentile lines appear to have some
curvilinearity as NO. increases.
-------
Figure 19
Plot of 75th Percentlle of the MOX (MOZ) Distribution
for Given Levels of THC by Station and Year.
.1'}
MOX(MOZ)
(ppm)
• = AZU (1972)
0= AZU (1968)
X= DOLA (1972)
0 = DOLA (1968)
• = BETH, HYAl-
and SUIT
r—£)
AZU (1968)
- X
DOLA (1972)
o
DOLA (1968)
MARYLAND (COMBINED)
rlt'j
-I
2
I
7
THC (6-9)
ppm
-------
Figure 20 Plot of the 75th Percentile of the MOX (MOZ) Distribution
for Given Levels of NO by Station and Year.
• = AZU (1972)
O = AZU (1968)
X = DOLA (1972)
o = DOLA (1968)
• = BETH, HYAT and SUIT
MOX (MOZ)
ppm
AZU (1968)
(6-9)
ppm
DOLA (1968)
o
DOLA (1972)
-------
68
5.6 Multiple Variable Relationships Between MOX (MOZ) and the Other Variables
The analysis presented Co this point has compared MOX (MOZ) with various
other variables on a one-at-a-time basis (e.g., correlations scatter plots,
percentile plots). In this section the results of using two statistical
procedures (stepwise regression and cluster analysis) are discussed which
consider the relative strengths of the various variables in predicting max.
oxidant after taking into account the effects of the other variables. Note
that in the one variable at-a-time approach, the effect on MOX of one other
variable was studied with no attempt to adjust for the effects of other
variables. The main emphasis of the analysis is to determine which of the
variables under study appear to be the best predictors of MOX (MOZ) in LA
and Maryland not to actually obtain prediction equations; although, prediction
equations will also be discussed.
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69
5.6.1 Stepwise Regression
In this section the results of using stepwise regression
are discussed. This procedure is commonly used by researchers to
indicate which variables out of a large group of variables appear to be
the most important in predicting a given variable (e.g., MOX). The
procedure assumes that a linear relationship exists between the
dependent variable (MOX) and the independent variables (e.g., MTEMP).
For example,
MOXj^ = a + l^CTHCj) + B^MTEMP^ + B^SRAD^ + e±
where a, B-, B2> and B_ are unknown parameters and e. is a random error
term.
The stepwise regressions discussed here were run for each
station (using 1972 LA and 1973 Maryland data) with MOX (MOZ) as the
dependent variable and the various meteorological and pollutant variables
as independent variables.
In brief, the stepwise regression procedure used consists of
the following approach: The stepwise computer program finds the single-
variable model (i.e., max. oxidant on only one variable) which produces
2 2
the largest R statistic (where R is the square of the multiple corre-
2
lation coefficient). After entering the variable with the largest R ,
the program uses the partial correlation coefficients to select the next
variable to enter the regression. That is, the program enters the
variable with the highest partial correlation coefficient with max.
2
oxidant (given that the variable with the largest R is already in the
model). An F test is performed to determine if the variable to be
entered has a probability greater than the specified "significance level
for entry." After a variable is added, the program looks at all the
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70
variables already included in the model and computes a partial F-statistic
to determine if these variables should remain the model. Any variable
not producing a partial F significant at the specified "significance
level for inclusion" is then deleted from the model. The process then
continues by determining if any other variables should be added to the
regression. The process terminates when no variable meets the conditions
for inclusion or when the next variable to be added to the model is one
just previously deleted from it. For the present analysis all variables
in the final regression model were deemed significant at the .10 level
of significance.
Tables 9 and 10 present the results of running stepwise re-
gressions by station for two sets of independent variables. The inde-
pendent variables considered in Table 10 are a subset of those used in
Table 9 (i.e., in Table 10 SLP, XWD, YWD, XAWD and YAWD were not con-
sidered)— . The tables show that:
(i) in Los Angeles VIS, MTEMP, SRAD and NO. appear to
be the most important variables in predicting MOX,
(ii) in Maryland it is difficult to reach any general
conclusions except that MTEMP appears to be the
most important predictor. (Recall SISP is near a major
freeway; therefore, its data is suspect).
It should be noted here that in Maryland the effective sample sizes for
the stepwise regressions are relatively small and that the pollutant
variables do not appear in general to be important predictors of MOZ.
— Sea level pressure was dropped because its coefficient of variation
(c.v. = std. deviation/mean) was so small. For example, in AZU the c.v.
for SLP was only .26. Wind direction was dropped because of the fact that
the meteorological data was collected at different locations than the
pollutant data. For example, in Los Angeles, the meteorological data was
collected at LA International while one of the pollutant stations under
study was at Azusa.
-------
71
TABLE 9
Results of Stepwise Regressions^ by Station-7 with Daily Max. Oxidant (Ozone)
as the Dependent Variable (May through October Data)
Met.
Poll,
Independent
Variables
Considered
" VIS
SLP
DPT
XWD
YWD
WS
RH
MTEMP
SRAD
RHC24
AWS
XAWD
YAWD
" NO (6-9)
N02 (6-9)
THC (6-9)
. NMHC (6-9)
No. Days Used
in regg.
R2 = (Corr)2
R = Corr
AZU
MOX
4
3
5
2
1
—
125
.70
.84
1972
* DOLA
MOX
1
6
3
2
5
8
4
9
7
—
130
.71
.84
3/ 1973
BETH-' HYAT
MOZ MOZ
2 3
2
4
5
1 1
56 54
.38 .75
.62 .87
SISP
MOZ
2
1
4
3
70
.57
.75
SUIT
MOZ
2
1
4
3
35
.63
.79 1
* AZU column indicates that MOX - linear function (NO., SRAD, WS, VIS MTEMP)
The correlation coefficient for this regression is 784.
- Table gives most sig. variable in final equation as 1, second most si*, as 2,
G uC •
2/
- Stepwise procedure set up so that all variables in final equation are sig
at .10 level.
3/
- Maryland = Dulles Met. Data
-------
72
I/ 21
TABLE 10. Results of Stepwise Regressions— by Station— with Daily Max.
Oxidant (Ozone) as the Dependent Variable (May through October
Data)
Met.
Variables
Poll.
Variables
independent
Variables
Considered
"vis
DPT
WS
RH
MTEMP
SRAD
_AWS
"NO (6-9)
N02 (6-9)
THC (6-9)
NMHC (6-9)
No. Days Used
in Regg.
R2 = (Corr.)2
R = Corr.
AZU
MOX
3
4
5
2
1
125
.70
.84
DOLA
MOX
1
6
3
2
4
7
5
130
.67
.82
BETH^ HYAT
MOZ MOZ
3
1 1
4
2
56 54
.29 .69
.54 .83
SISP SUIT
MOZ MOZ
2
1
1
3
2
70 36
.60 ' .53
.78 .73
— Table gives most sig. variable in final equation as 1, second most sig.
as 2, etc.
2/
— Stepwise procedure set up so that all variables in final equation are
sig. at .10 level.
— Maryland = Dulles Met. Data.
-------
73
5.6.2 Cluster Analysis
In this section the results of using the Automatic Interaction Detector
computer program (AID) are discussed. The AID program developed at the University
of Michigan performs a type of cluster analysis which is useful in studying
the interrelationships among a set of variables. Regarding MOX (MOZ) as a
dependent variable, the program employs a nonsymmetrical branching process
based on variance analysis techniques to subdivide the sample into a series
of subgroups which maximize one's ability to predict values of the dependent
i
variable. Thus, AID is something like a stepwise regression program where
the independent variables (predictors) need not be quantitative. Unlike stepwise
regression, AID does not assume a linear relationship between the dependent
and independent variables.
The reasons for using the AID program for the present study were the
following:
(i) Ideally, in the present case the results of the AID program
give the combination of variables that lead to high (or low)
MOX days. Thus, RTI felt that this type of analysis, if
successful, could have results which would be very useful
in interpreting the air pollution data being studied in
this report. Accordingly, it was of interest to investigate
the potential usefulness of a cluster analysis approach
applied to air pollution data.
(ii) To compare the results of AID with those obtained by step-
wise regression in Section 5.6.1.
In particular, the AID program operates by first finding that dichotomy
-------
74
based on any predictor (e.g., MTEMP) which gives the largest between-group
sum of squared deviations for the dependent variate, MOX. That is, choose
a division so as to maximize
where N is the sample size for group 1, MOX is the mean of MOX for group 1,
etc. for group 2. Essentially this is the dichotomization which accounts
for more of the variance of MOX than any other dichotomization based on
grouping the categories of a single predictor into two groups. Having made
this first dichotomy, the program then takes the eligible group with the
largest within group sum of squared deviations for MOX and splits it in a
similar manner. A. group is eligible for splitting if it has a within group
sum of squared deviations at least as great as a specified proportion (PI)
of the original sum of squared deviations (in the present case PI was set
= .01). In addition, for a group to be split both resultant groups must
have NMIN observations (NMIN was set = 10). Splits are made only if the
within group sum of squared deviations (WSS) is reduced by some minimum
proportion (P2) of the total sum of squares (P2 was set = .01). The process
of dichotomizing groups continues until there are no eligible groups which
can be split or until some specified maximum allowable number of groups (MAXGP)
has been created at any point in the process which are eligible for split
attempts (MAXGP was set = 20). In the present case the AID program was run
for each of the six monitoring stations being considered using the same variables
as were used for the stepwise regressions in Table 10. Before the program
could be run it was necessary to categorize the independent variables. The
categories used are given in Table 11.
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75
I/
TABLE 11 Categories Used in Running AID -
Categories for Maryland
M«* *• «V*B^* *• *
Independent
Variable
1 NO
2 N0_
2
3 THC
4 VIS
5 DPT
6 WS
7 RH
8 MTEMP
9 SRAD
10 AWS
Category
0
1
2
3
0
1
2
3
0
1
2
0
1
2
0
1
2
0
1
2
0
1
2
0
1
2
0
1
2
0
1
2
Less than
.001 to
.031 to
.061 or
Less than
.001 to
.051 to
.102 or
Less than
1 to
4 or
Less than
10 to
15 or
Less than
56 to
60 or
Less than
8 to
11 or
Less than
62 to
67 or
Less than
71 to
76 or
Less than
1 to
580 or
Less than
6 to
8 or
Independent
Variable
.001 1 NO
.030
.060
over
.001 2 NO.
.050
.101
over
1 3 THC
3
over
10 4 NMHC
14
over
56 5 VIS
59
over
8 6 DPT
10
over
62 7 WS
66
over
1 71 8 RH
75
over
1 9 MTEMP
579
over
6 10 SRAD
7
over
11 AWS
Category
0
1
2
0
1
2
0
1
0
1
2
0
1
2
0
1
2
0
1
2
0
1
2
0
1
2
0
1
2
0
1
2
Less than .001
.001 to .009
.010 or over
Less than .001
.001 to .040
.041 or over
Less than 1
1 or over
Less than .001
.001 to .149
.150 or over
Less than 10
10 to 14
15 or over
Less than 56
56 to 62
63 or over
Less than 6
6 to 8
9 or over
Less than 57
57 to 66
67 or over
Less than 71
71 to 77
78 or over
Less than 260
260 to 499
500 or over
Less than 4
4 to 5
6 or over
— Definitions of the various variables are given in Table 3.
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76
The results of running the AID program are given in Figures 21 and 22,
Appendix Figures D-l through D-4 and Table 12— . For example, in Figure 21
the AID program splits on NO. and SRAD to obtain a group of 37 days where
the average daily max. oxidant was .251 ppm while splits on NO. (twice), WS
and DPT gave a group of 21 days where the average MOX was .049 ppm. The figures
and table indicate that the most frequent variables leading to high daily
max. oxidant (ozone) were NO., SRAD, MTEMP and VIS while the most frequent
variables leading to low daily max. oxidant (ozone) were NO., SRAD and MTEMP.
To further illustrate in which direction (increase or decrease) the means
of the various variables go when MOX (MOZ) increases, Table 13 gives the means
for the pollutant and meteorological variables for different levels of MOX
(recall these means were plotted in Figure 10). Tables 12 and 13 indicate
that usually NO, NO., THC, SRAD, MTEMP and DPT are higher than average when
MOX (MOZ) is high while VIS, RH, WS and AWS are lower than average when MOX
(MOZ) is high.
It is important to note here two major difficulties in running AID with
the present data set:
(i) The data for each station could only be split by AID
into a relatively few groups because the sample sizes were
less than 180 days per station.
— Before examining the figures the reader should note the following limita-
tion of the AID analysis. When AID splits the data on some variable (say N02),
it may perform the split such that only one category of the variable is left
in one of the split groups (call it SI). When this happens, AID can never
split on this variable again in SI since only one category of the variable is
left in SI. To illustrate this point consider Figure 21. AID first splits
on N02 such that days with N02 > .102 define one group (SI) and days with
N02 < .102 define the other group (S2). Now in Table 11 it can be seen that
N02 has four categories and that N02 ^ .102 contains only one of these cate-
gories. Therefore in SI, N02 can never again be used to split the data while
in S2, N02 can again be used as a dichotomizing variable.
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77
(ii) Since the program requires that the independent variable
be categorized (see Table 11), the available sample sizes
meant that the various categories for a particular vari-
able did not contain very many days of data for each
station. This also meant that only a few categories could
be defined for each variable; thus, causing the problem noted
in the footnote on the previous page. Because of these
difficulties, the AID results presented here are of marginal
value.
To summarize,
(i) the AID program gave results that were similar to those
obtained by stepwise regression;
(ii) the AID analysis was severely limited because of the
relatively small sample sizes of the present data and due
to this fact AID did not contribute significantly to the
present analysis;
(iii) the AID program may have some potential use as an
analytic tool in analyzing air pollution data but only
for data sets with a relatively large number (several
hundred) of data points (e.g., data over several years or
several monitoring stations).
(Text continued on page 83)
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78
FIGURE 21. AID Results for AZU, May through October, 1972 Data
(1) = Initial group before any splitting.
M = Group sample size.
Group mean for daily max. oxidant (units = ppra).
NOTE: Grou£S with high 0- are at the top of the figure and groups with
low 0, are at the Bottom of the figure.
-------
FIGURE 22, AID Results for SUIT, May through October, 1973 Data
79
(1) = Initial group before any splitting.
If = Group sample size.
0. = Group mean for daily max. ozone (units = ppm).
NOTE:
Groups with high O.j are at the top of the figure and groups with low 0.
are at the bottom of the figure.
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80
TABLE 12. Summary of Variables Used to Split MOX (MOZ)
Computer Runs (All Data Used was May through
AID Results
Groups in AID
October Data)
Variables-^ Variables^ Variables Selected
Whose Split Whose Split All Variables by Stepwise
Lead to High Lead to Low Used to Split Regression
Location
AZUU972)
DOLAU972)
BETH(1973)
HYAT(1973)
SISP(1973)
SUITU973)
0^ Means 0.. Means Groups (See Table 10)
1.
2.
3.
4.
1.
2.
3.
1.
2.
3.
4.
1.
2.
3.
4.
1.
2.
3.
4.
1.
2.
3.
4.
N02 + N02
SRAD + N02
WS
DPT
N02 + N02
THC + VIS
MTEMP + SRAD
MTEMP + MTEMP
VIS - MTEMP
SRAD +
AWS
MTEMP + MTEMP
N02 -1- SRAD
RH
VIS
SRAD + SRAD
RH - MTEMP
VIS - SRAD
N02
MTEMP + MTEMP
SRAD + MTEMP
N02 +
NO +
N02, SRAD, AWS, 1.
WS.DPT 2.
3.
4.
5.
N02, THC, MTEMP 1.
+ AWS, NO, VIS, 2.
SRAD 3.
4.
i
5.
6.
7.
MTEMP, VIS, 1.
SRAD, AWS, RH
MTEMP, N02,RH, 1.
VIS, SRAD 2.
3.
4.
SRAD, RH, VIS, 1.
N02, MTEMP, AWS 2.
3.
MTEMP, SRAD, 1.
N02,NO,VIS 2.
N02
SRAD
VIS
WS
MTEMP
VIS
SRAD
MTEMP
NO
THC
RH
N02
MTEMP
MTEMP
N02
WS
NO
RH
DPT
AWS
MTEIIP
THC
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81
TABLE 12 - CONTINUED
Variable
Summary Over Six Stations
Frequency of Occurrence of the Variable
Over the Six Stations
High
Low 0.
Overall
Stepwise
NO
N0_
2
THC
SRAD
MTEMP
VIS
DPT
ws
RH
AWS
1
5
1
4
4
3
0
0
2
1
0
2
0
3
4
1
1
1
0
0
2
5
1
6
5
5
1
1
3
4
2
3
2
2
5
2
1
2
2
1
— 1. means first split on this variable, 2. means second split, etc.
See Figures 21 and 22 and Appendix Figures D-l through D-4.
21
— The + sign indicates that high NO. (etc.) gave high 0_, etc. for the
- sign.
— Here the + sign indicates that high N0_ (etc.) gave low 0_, etc.
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82
TABLE 13.
Location
AZU
(1972)
DOLA
(1972)
BETH
(1973)
HYAT
(1973)
SISP
(1973)
SUIT
(1973)
No. times
increased
Means of Meteorological and Pollutant Variables for Different Levels
of Daily Max. Oxidant (Ozone) , May through October Data—
MOX(MOZ)
Levels
MOX< . 08
MOX> . 20
All
Levels
MOX<.08
MOX> . 20
All
Levels
MOX<.04
MOX>.08
All
Levels
MOXS.04
MOX> . 08
All
Levels
MOX<.04
MOX> . 08
All
Levels
MOX<.04
MOX> . 08
All
Levels
Pollutant Variables
NO
.029
.046
.035
.080
.121
.090
__«
.008
.008
.025
.030
.031
.090
.052
.067
— _
.020
.023
variable
from Low
N02
.040
.111
.074
.072
.190
.103
«_
.049
.048
.077
.083
.074
.063
.048
.052
.065
.046
.052
Summary
THC
3.4
4.3
3.7
3.19
4.85
3.70
1.26
1.39
1.32
1.76
1.96
1.83
1.87
1.79
1.76
1.46
1.63
1.54
Over
SRAD
345
616
492
441
633
504
232
535
425
266
541
440
356
550
424
223
550
412
Meteorological Variables
MTEMP
70.6
73.5
73.1
71.1
78.7
73.0
67.3
86.2
78.7
69.1
87.4
80.5
75.2
87.5
78.8
66.5
84.4
77.2
VIS
15.7
8.3
11.2
13.8
6.7
10.0
10.4
8.3
10.6
9.6
7.9
9.8
10.1
8.0
10.9
10.0
10.4
11.4
DPT
54.0
60.7
58.8
56.6
62.1
59.0
53.0
66.6
60.9
55.7
67.7
62.8
59.2
67.0
61.0
54.2
63.1
59.4
RH
62.3
66.1
64.2
65.6
60.0
65.6
70.5
57.8
61.9
73.3
58.5
62.8
69.8
57.5
64.3
74.6
54.1
62.2
WS
9.0
10.3
9.9
8.2
8.2
8.3
8.0
6.6
7.4
8.1
6.4
7.4
7.3
6.2
7.1
7.7
7.0
7.5
AWS
6.7
8.0
7.3
7.2
6.6
7.3
5.3
4.2
4.9
5.9
4.4
5.1
5.6
3.4
5.0
5.3
4.6
5.2
Six Stations
to High level of
MOX
No. times
decreased
3
variable
from Low
3
5
6
6
1
6
1
1
1
to High level of
MOX
1
2
1
0
0
5
0
5
4
5
- Units = ppm for pollutant variables, Meteorological units given in Table 3.
-------
83
5.6.3 Regressions
The results of running the AID program and the stepwise regressions
indicated that of the variables examined the most important meteorological
variables in predicting high MOX (MOZ) were SRAD, MTEMP and VIS while the
most important pollutant variables were N0_ and THC. To further illustrate
the relationship between MOX (MOZ) and these variables linear regressions
were fit by least squares to the May through October data for all stations
except SISP (as discussed previously, the data from SISP was of questionable
value) and the results are given below. These regressions equations are
given here only Ji£ illustrate relationships for the limited data available
for this analysis and should not be used as general prediction equations
for MOX or as evidence of causation. (This is rather obvious for a variable
such as VIS which may be caused by pollution rather than vice versa.) In
addition, the equations are not given as proof of linear relationships between
MOX (MOZ) and the other variables. (For example, Cleveland [2] fits a
multiplicative model to the relationship between MOX and SRAD, MTEMP and WS.)
Finally, the reader should be aware of the fact that for uncontrolled data such
as analyzed in this report the usual statistical assumptions underlying
regression analysis are totally violated; and therefore, the estimated
regressions do not have the nice statistical properties of estimates obtained
in a controlled experiment. With these caveats in mind, the least squares
estimates of the linear regressions are as follows (note in Maryland, NO,
was not included in the regression equation because of its low correlation
with MOZ):
AZU (1972)
MOX = -.2214 + .0026(MTEMP) -»- .00024(SRAD) - .0020(VIS) + .5932(N02) -I- .0105(THC)
-------
The correlation coefficient (R) for this regression was .83 and the sample
size (N) used to estimate the regression was 128. A test of the partial
regression coefficients showed that only the partial coefficient of THC
was not significant at the .10 level of significance.
DOLA (1972)
MOX = -.1652 + .0023(MTEMP) + .00013(SRAD) - .0024(VIS) + . 1876(NO ) + .0090(THC)
R " .82 N = 131
A test of the partial regression coefficients showed all coefficients signi-
ficant at the .10 level.
BETH (1973)
MOZ - -.1183 + .0021(MTEMP) + .000082(SRAD) - .0021(VIS) + .0144(THC)
R = .79 N = 90
The test of the partial regression coefficients showed that only the coefficient
of THC was not significant at the .10 level.
HYAT (1973)
MOZ = -.1717 + .0027(MTEMP) + .000065(SRAD) - .0012(VIS) + .0086(THC)
R = .79 N = 105
The test of the partial regression coefficients showed all coefficients
significant at the .10 level.
SUIT (1973)
MOZ = -.0884 + .OOll(MTEMP) + .OOOIOO(SRAD) - .OOIO(VIS) + .0284(THC)
R » .83 N - 62
The test of the partial regression coefficients showed all coefficients
significant at the .10 level.
The above estimated regression equations have reasonably high correlation
-------
85
coefficients (.79 to .83) and are consistent with regard to the signs of
the regression coefficients; i.e., MTEMP, SRAD, NO, and THC always have
positive coefficients while VIS always has a negative coefficient.
Because of the fact that meteorological variables cannot be controlled,
RTI also performed the following regression analysis for the five stations:
(i) the readings of MOX (MOZ), N02 and THC were adjusted for the effects
of the three important meteorological variables and then (ii) the relation-
ships between adjusted MOX and adjusted N02 and THC were examined. The reader
is cautioned here that adjusting for SRAD, MTEMP and VIS does not eliminate
meteorological effects entirely from MOX (i.e., there are other meteorologi-
cal variables which could have been included) but is done here only to reduce
the effects of meteorological conditions so that the residual effects between
MOX, N02 and THC may then be examined. In particular, RTI ran linear regressions
of the following form for MOX, N0_ and THC:
MOX.^ = a + B1(SRADi) +- B^MTEMP^ + B^VIS^ + e^^ i=l, .... n days (1)
where a, B^ B2> B3 are regression parameters and e. is a random error term.
The residuals from Equation (1) gave MOX. adjusted for SRAD, MTEMP and VIS
(similarly the residuals from (1) with MOX..^ replaced with N0» or THC gave
N02 and THC adjusted for the three meteorological variables).
The table below gives the percent of the total variation in MOX (MOZ)
accounted for by the regression of MOX (MOZ) on SRAD, MTEMP and VIS by station
(e.g., the table gives the square of the correlation coefficient = R2) .
AZU(1972) DOLA(1972) BETH(1973) HYAT(1973) SUIT(1973)
(Percent of Variation) R2 .58 .57 .48 .59 .64
(Correlation Coefficient) R .76 .75 .69 .77 .30
-------
86
Appendix Figures E-l through E-10 present plots for the five stations of
adjusted MOX (MOZ) versus adjusted NO and THC. In addition, the plots give
the correlations between the adjusted variables and the sample sizes involved.
The plots and correlations are given to indicate if a relationship still exists
between MOX and THC, N0« after adjustment for the meteorological variables.
A summary of the correlations between MOX, NO. and THC before and after adjustment
are given below:
Correlations Between MOX, N02 and THC Before and After
Before Adjustment
Corr(MOX, N02)
Corr(MOX, THC)
After Adjustment
Corr(MOX, N02)
CorrCMOX, THC)
N
Adjustment,
AZU(1972)
.67
.51
.48
.39
128
By Station
DOLA(1972)
.63
.53
.46
.44
131
BETHU973)
.05
.24
.07
.19
56
HYATU973)
.12
.20
.13
.18
82
SUIT(1973)
-.07
.36
.08
.37
50
The above correlations indicate that in Los Angeles there is still evidence
of a positive linear relationship between MOX and the two pollutant variables
NO 2 and THC after adjustment. In Maryland, the correlations before and after
adjustment are about the same order of magnitude with only the correlation
between MOX and THC at MD4 being greater than .30. Thus, the data analyzed
in this report indicates that the linear relationship between MOX and N09
and THC is stronger in Los Angeles than in Maryland both before and after
adjustment for three important meteorological variables SRAD, MTEMP and VIS.
Of course, as indicated earlier this fact may be explained by the significantly
higher MOX levels in Los Angeles.
-------
87
Another interesting result to come out of the regression analysis was
to note how adjusting MOX (MOZ) for SRAD, MTEMP and VIS affected the first
order autocorrelations of MOX (i.e., correlations of MOX readings one day
apart). That is, since meteorological conditions may last for several days
this results in autocorrelation in the MOX values. For example, for the present
data the first order autocorrelation for MOX in DOLA was .59. Accordingly, the
table below summarizes the first order autocorrelations for MOX (MOZ) for
three stations before and after adjustment.
_____ _ DOLA(1972) _ HYATQ.973) _ SUIT(1973)
Before Adjustment
Corr (MOX^, MOXi+_) .59 .46 .38
After Adjustment
Corr(MOX_f MOXi+_) .26 -.02 .08
The table shows that the first order autocorrelation in the two Maryland
stations was reduced to essentially zero after adjustment while in DOLA this
correlation was reduced by more than one-half. Thus, adjusting for SRAD,
MTEMP and VIS appears to eliminate a large portion of the day to day correla-
tion for MOX (MOZ). (Cleveland [2] also found this to be true in his analysis.)
-------
88
6. Conclusions
Before discussing the results of the present study it is important to
take note of the following caveats. The study described in this report was
carried out on a relatively small and limited data base (i.e., six monitor-
ing stations, three meteorological stations, one year of data in Maryland
and two years of data in Los Angeles); and therefore, it should be realized
that broad generalizations of the results of this study (or similar studies)
cannot and should not be drawn. As is well known, the processes that affect
the formation of atmospheric oxidant are quite complex and for this reason
several studies using atmospheric and laboratory data will have to be com-
bined to determine an effective control strategy for oxidant. In addition,
the results that can be obtained from the type of analysis and data examined
in this report are limited. Recall that the data analyzed here had pollutant
data at one station and meteorological data at another station (up to 30 miles
away). Thus, the observed relationships between daily maximum hourly oxidant
concentrations (MOX) and meteorological variables such as wind direction and
wind speed are suspect. In addition, because of the transport phenomena of
oxidant, it may be unrealistic, as was done in this report, to determine
relationships between MOX (which usually occurs in late morning or early
afternoon) and pollutant variables which are measured at the same station in
the early morning. Ideally, the type of analysis and data that should be
examined would be pollutant and meteorological readings (such as wind direction)
at one station and maximum oxidant and meteorological readings (such as SRAD)
at a second station which is downwind of the first station. (As mentioned pre-
viously the data base developed by RTI for its analysis may allow this type
of analysis in the future depending on the meteorology of the various stations
examined.)
-------
89
With Che above caveats in mind, the data examined in this report did allow
a great deal of analysis including the following: (a) The comparison of pollu-
tant levels between the within locations and for Los Angeles the comparison
of these levels over time, (b) The examination of the relationships between
MOX readings and pollutant variable readings at the same monitoring station
and meteorological variable readings at nearby stations (10 to 30 miles distant),
These relationships included correlations, scatter plots, percentile analysis,
and regression analysis.
For the data examined in this report, correlation analysis between MOX
(MOZ) and averages of the other pollutants for various time periods (e.g.,
5-8 A.M., 6-9 A.M., 7-10 A.M., etc.) did not indicate that in general any one
3-hour period gave higher correlations. A comparison of the pollutant
levels between stations indicated that MOX levels in Los Angeles are sub-
stantially higher than MOZ levels in Maryland and AZU has higher MOX levels
than OOLA. In addition, MOX levels have decreased from 1968 to 1972 in Los
Angeles. (Several studies including Altshuller [1] have also shown similar
results.)
Summary statistics for the two areas examined showed that the May through
October frequency of occurrence of days with daily maximum hourly oxidant
concentrations greater than 160 ug/m (.08 ppm), the National Ambient Air
Quality Standard (NAAQS) not to be exceeded more than once per year, decreased
at Downtown Los Angeles and Azusa between 1968 and 1972 from 67.8 to 56.0
percent and from 85.1 to 75.6 percent, respectively. In the Washington, D.C.,
area for the Bethesda and Suitland, Maryland, stations the 1973 May through
October corresponding frequencies for oxidant concentrations in excess of NAAQS
were 37.5 and 28.8 percent, respectively. On a percentage basis, the maxi-
mum oxidant concentration occurred more often between the hours of 10:00 A.M.
-------
90
and 2:00 P.M. in Los Angeles than in Maryland. In Maryland, several days
(17.4 percent in Hyattsville) reported all zero ozone concentrations while
in Los Angeles there were no days with all zero oxidant concentrations.
Means by day of week gave inconclusive results for weekday versus weekend
levels of daily maximum oxidant for the two areas studied.
On the average, nitric oxide (NO), nitrogen dioxide (N0_), total hydro-
carbons (THC), solar radiation (SRAD), daily maximum temperature (MTEMP), and
dewpoint temperature (DPT) values were found to be higher than average when
maximum hourly average oxidant concentrations were high. Visibility (VIS),
relative humidity (RH), wind speed at the time of the maximum oxidant reading
(WS), and average wind speed form 7:00 A.M. to 7:00 P.M. (AWS) were found to
be lower than average when maximum hourly average oxidant concentrations were
high.
Percentile plots were found to be a convenient way to graphically examine
relationships between MOX and other variables because they are much easier
to interpret than scatter plots. Examination of the relationship between the
75th percentile values of the distribution of daily maximum oxidant concen-
trations for given concentrations of THC and of N09 indicated that in
Los Angeles the MOX concentrations have decreased between 1968 and 1972 but
THC and N02 concentrations have not. Similar analysis of MOX and THC data
from three Maryland stations combined into one data set shows the 75th percentile
curve in Maryland to have a shape similar to that of the Downtown Los Angeles
station within the range of THC concentrations measured. The range of THC
concentrations for the Maryland data was about half of the range measured in
Los Angeles. The shapes of the MOX 75th percentile curves for Azusa for both
1968 and 1972 data suggest a less rapid rate of increase with higher THC (or
N02) concentrations; that is, the relationship is curvilinear. The percentile
-------
91
curves for Downtown Los Angeles, however, appears to be reasonably approxi-
mated by a linear relationship.
Multiple variable analyses of the relationships between the several pollu-
tant and meteorological variables and the daily maximum hourly oxidant con-
centrations indicated that in Los Angeles the most important pollutant vari-
ables in predicting maximum oxidant concentration are, as would be expected,
THC and N02; none of the pollutant variables appear to be significant pre-
dictors in Maryland. With regard to THC, this latter result is possibly
attributable to the small range of THC concentrations measured in Maryland.
Among the meteorological variables, MTEMP, SRAD, and VIS are the most signifi-
cant predictors. In Maryland, MTEMP and in Los Angeles, SRAD were the most
important predictors. For the Los Angeles data, a positive linear relationship
is still apparent between maximum oxidant and N0_ and THC after adjustment
has been made for important meteorological variables.
Finally, the multiple variable analyses indicated that cluster analysis
may have some potential use as an analytic tool in analyzing air pollution
data but probably should only be used for data sets with a relatively large
number of data points (several hundred). In addition, the presence of a large
amount of missing data in any variable can severely limit the use of any
multiple variable technique (e.g., stepwise regression) because of the fact
that these techniques for a particular time period (e.g., day) must have data
on all variables or consider the day's data as missing.
-------
92
7. Recommendations
The use of statistical analysis of the many variable constituents
and properties of the ambient air to develop relationships that can be
used as guidance in the development of control strategies is a tenuous
procedure. The history of attempts at strategy development and the
analyses undertaken in this study suggest a need for additional research
and the development of an adequate data base for future analyses.
Detailed knowledge of the reactants involved in the photochemical
production of oxidants is necessary. The significance of concentrations
and concentration ratios of all of the species of reactants, the effect
of serially injecting fresh reactants into an on-going process, and the
response of the reactions to one or more daylight-dark-daylight cycles
are some of the questions that must be answered. The Los Angeles Reactive
Pollutant (LARP) project may have acquired data useful for examining some
of these questions, but these data are not yet available. To obtain
definitive data concerning the reactants and reactions involved, appro-
priately designed and controlled chamber studies should be undertaken.
If ambient pollutant data are to be investigated in greater depth
than was possible in this study, the monitoring network should be designed
to provide a maximum opportunity for investigation of downwind transport
of reactants and subsequent oxidant concentrations. This implies that
meteorological conditions are sufficiently well documented to show on a
day-to-day basis whether or not the flow of reactants was from the "up-
wind" to the "downwind" stations. A program to provide a data base
should emphasize quality assurance, maintenance, and calibration activi-
ties to ensure that complete sets of usable data are obtained. In addition,
-------
93
any study of this kind that is undertaken should begin with several hun-
dred days of data to (1) overcome the problems caused by missing data
that will undoubtedly occur due to various causes such as the require-
ment of pairs of data - precursors at the "unwind" station, oxidant at
the "downwind" station and (2) account for the relatively large varia-
bility in atmospheric data. One method that can be used to increase
atmospheric sample sizes is to combine data over several years. It is
also important to note in analyzing ambient pollutant data that consider-
able effort and time must be expended in the organization of the data.
If this is not done then meaningful analysis is impossible.
Useful information on downwind transport of oxidant or oxidant
precursors might be obtained from ambient monitoring networks such as that
in the Maryland suburbs of Washington, D. C., except for the fact that on
only a few occasions of high oxidant concentrations will the stations be
oriented so that an upwind-downwind relationship exists. If the Maryland
suburban data could be supplemented by data from stations in Washington,
D. C., or adjacent Virginia, a larger number of applicable data points
might be obtained. It should be pointed out, however, that the relatively
small range of, and low values of, concentrations of hydrocarbons measured
in the suburban Maryland area may make it impossible to establish statis-
tically significant relationships with oxidant concentrations—which also
have a relatively small range in Maryland.
-------
94
BIBLIOGRAPHY
[1] Altshuller, A. P., Evaluation of Qxidant Results at CAMP Sites in the
United States. Journal of the Air Pollution Control Association,
Vol. 25, No. 1, (January 1975), pp. 19-24.
[2] Bruntz, S. M., W. S. Cleveland, B. Kleiner, and J. L. Warner, The
Dependence of Ambient Ozone on Solar Radiation, Wind, Temperature.
and Mixing Height; Report, Bell Labs Technical Memorandum.
[3] Cleveland, W. S., B. Kleiner, and J. L. Warner, Using Robust Statistical
Ilethods in Analyzing Air Pollution Data with Applications to New York-
New Jersey Photochemistry. Paper presented at the Annual Meeting of
the Air Pollution Control Association, Denver, Colorado, June 9-13,
1974. APCA No. 74-76.
[4] Cleveland, W. S., T. E. Graedel, B. Kleiner, and J. L. Warner, Sunday
and Workday Behavior of Photochemical Air Pollutants in New Jersey
and New York. Bell Labs Technical Memorandum.
[5] Cleveland, W. S., T. E. Graedel, B. Kleiner, and J. L. Warner, Ozone
Concentration in New Jersey and New York; Statistical Association
with Related Variables. Bell Labs Technical Memorandum (April 1974).
[6] Cleveland, W. S., T. E. Graedel, B. Kleiner, and J. L. Warner, Statisti-
cal Analysis and Phenomenological Interpretation of the Atmosphere
in the New York-New Jersey Metropolitan Region. Bell Labs Technical
Memorandum.
[7] Environmental Protection Agency Publication No. AP-84, Air Quality
Criteria for Nitrogen Oxides. Air Pollution Control Office, Washington,
D.C., (January 1971).
[8] Jacobson, J. S. and G. D. Salottolo, Photochemical Oxidants in the
New York-New Jersey Metropolitan Area. Atmos. Env., Vol. 9, (1975).
[9] National Air Pollution Control Administration Publication No. AP-63,
Air Quality Criteria for Photochemical Oxidants. U.S. Department of
Health, Education, and Welfare, Washington, D. C., (March 1970).
[10] National Air Pollution Control Administration Publication No. AP-64,
Air Quality Criteria for Hydrocarbons. U.S. Department of Health, Educa-
tion, and Welfare, Washington, D. C., (March 1970).
[11] Schuck, E. A., A. P. Altshuller, D. S. Barth, and G. B. Morgan,
Relationship of Hydrocarbons to Oxidants in Ambient Atmospheres.
Journal of the Air Pollution Control Association, Vol. 20, No. 5,
(May 1970), pp. 297-302.
-------
APPENDIX A
Plots of Daily Maximum Oxidant (Ozone) Versus Various
Pollutant and Meteorological Variables by Station
-------
J.'SOOJOOOO *
- . . . I
FIGUKL A-l
STATION " 1 = AZU
PLOT OF MOX VS NO (6_9)
May through October, 1972
Overall Corr. = .67
Corr (MOX > .08) = .56
H3X
0.20000030
o.
OS
A A
A A
A
A A
- - . - A _. A
A A A
A 0
A A A
A A .. A .
AD A
AAA
A
" B "A A
A
- - - ft A
* * A A A " A
A A B A A A A A
— A _ . A A AAA A
A " A - " " A " '
. AA A A A A
* A AA A A
A A A AA A -A
A A A A B A A
* A A . C A
A A A A
A A A A
* AA AAA
-A A~A A~ — — - A A —
AAA
A 9 A . AA A A
A A A A
AB DA A A A
-A A A3
A A
O.'OoOOOOOO 0.04000000
LESENPI A = I 033 , 0 : £ 03S , ETCl
O.flBOOOOOO O.'UOOOOOO
N02(6-9)
0,16000000
0(<:COOOVOO
-------
o.'sooooooo »
j;-;joooooo
K3X
'j.'20000«00
J.'lOOOOBOO
OS
J.'OOOOOOOO
FIGURE A-2
STATION*! = AZU
PLOT or HOX va SRAD
May through October, 1972
Overall Corr. = .64
Corr (MOX > .08) = .42
B A A
A
A A
A
. . A .... **
AA AA
A A
.A A . _ A ....
A" B A 8 »
A A A A
A
" " • A AA B ' A
AA AA AAA A
A A AA
•-- ' - A ' A A A
A A A A A A
A A A AA A .
A A A A A AA A
A A A A A A
A A A AB A . A
A A A A
A * *
AAA A AA
A AA
A A B A A A .A
A A A A A A
AA AAA A
A A
"A A
•no.'oooooooo 120.00000000
LEGENDi A = I 003 i' B = 2 OBs t ETC.'
ZBO.'OOOOOOOO 410.00000000
SRAD
600,00000000 76U,00000?00
-------
FIGURE A-3
._. STATION"I = AZU
PLUT or HOX v3 NTCMP
May through October, 1972
Overall Corr. = .19
O.'SOOBOOOO
aNooooooo
jTJooooooo
H3X
0.'20900000
~
0*10000900
1/1 -I
O."030.000»0
\
A
A A
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- . C
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A
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_ A.
A
A A
A A
B A
C
A
A
A A A
A A
A A
A A A
A A A
... .... * .A Q
A
A _ Corr. (MOX > .08) = -.04
A
A
A
A -
A .._...
A A
A A
A
A A A
A ft _
0 . . . . -
A A A A
A A A
a A A B
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1) A
A A U A
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A A A A A A
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A A A A A
B A . A. A ._ _ _
ABA A A
A A A A A A
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0 A
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A U ..__... * *
A A
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A A
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79,'SOOOOOOO
as.sooooooo
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-------
FIGURE A-4
.8TAM .08) = -.27
- - -- - -
A
a
A
A
- _ A
A
A
U
A
A A . . _ _ . . . ....
A A
A '_
A . U
C A
A A
. . C . A . _ .. A
A A A
A A
A . A .......... A ...
n ' - n ~ "~ " '" n ~ ' " " p " " . ._ — . . ...
A A A
U A A A
A A A A
C U A
A . . .A
A
17.50000000 '27.50000900 " """17.50000000 " «I7,50000I)00
via
-------
FIGURE A-5
STATION = 2 = DOLA
PLOT OF MOX VS THC (6-9)
A A
May through October, 1972
Overall Corr. = .53
.. . Corr (MOX > .08) = .40
0.'20JOOOOO
_
. 0.*IS999990
MOX
t.'iooocooo
-
o:)^009CO
m
. oToosooooo
__A •___
A
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B
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_ _ . _ .A .
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. _ C A 4 . A A A .
A AHA
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C A
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. — . . . . - -
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A A
A. 9 . . -
A A A B A
"A "
A A - -. . . -
A A A
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Q .A A . - - ...._... - . - -
A
C
A .. ._ A A A__ .. _...._ . . ...
DA A
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~8 A A
0 A
A A . ...
A
D
Q . .A .... _
A
-
0.60000000 " 2.20000000 "" " 1,80000000 THC(6~9^.40000000 "" 7.00000000
LEGENDl A » 1 033 , B e 2 DBS , ETC!
a,60oco9oo
-------
FIGURE A-6
STATION = 2 = DOLA
PLOT OF MOX VS N02 (6-9)
O.'JSOOWO
May through October, 1972
Overall Corr. = .63
Corr (MOX > .08) = .51
A
o.'zooooooo
M3X
0.*10030Q09
•C?
J.'OiJGOGOO
6,'cooooooo
lA
A A
.A
A A
A A
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A A
A A
AA A A
A A A
A .... A . A . A
A A
A
A A
A
... * A AA
A BB AA BAA AA
AAB A AA B8A A " A UA A *A A
A . A AA B A AA AA B
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A ABA AA A. .A
A AA AD B B A A
AA BOB A Q A
A. A * A AAA A A
A AAA A
A
O.'OlSOOOOO 0.07SOOOOO
LECENOl A = 1 083 , 0 s 2 063 , ETC.'
O.'llSOOOOO
0.25500000 O.Jt500900
(6-9)
-------
J.iSOOOOOO »
FIGURE A-7
STATION = 2 = DOLA
PLOT OF MOX VS SRAD
OT20JOOOOO
MOX
O.'lOOOOOOO
olOSOOOOOO
O.'OOQOQOOO
May through October, 1972
Overall Corr. = .53
_Corr (MOX > .08) = .40
A "" A ~
A .. A. ._ ._ . ..
A
A A AA
__ _. . .. . ... ._! A .... . A
A A A
. . „... A . . B A _A . .
A A
AA "A
. ... .._ A .... A.. . ... ft .._
A ABA A A 8 A A
A A A A " A C " B A AA A A A"
A A .. A _. A AAAA .AAA A
A *—A A—B It-K A
AAAA OAA" "A"" o A
AAAA .A A A A A
AA A A A A A AA
A ... A
A A
A AA A A AA AA
AA A . A A A A
A A
A
• 40,'OOOQOOOO 120.00000008
LECENPi A o I OB 3 , 8 • 2 UBS , ETC.
».b«k. i^t n - • »*ww f - — fc T*w- | »- I fc j
280,'flOOOOOOO ItO.'OOOOOOOO
§P*P
600,00000000 760.00000«>00
-------
FIGURE A-8
STATION = 2 = DOLA
PLOT OF MOX VS MTEMP
May through October, 1972
Overall Corr. = .44
Corr (MOX > .08) = .27
0*25009000
.99-
o.'osoooooo
0*00000000
...A A .. _
A -A
A A
A
A . A
A
»" A" A
»
B c A
( A a
C
A
A D
A A A
A
.A ..
A
A A 0
A C D
P * .
A A
A A A
C A A
a
A
A A
_, p , ft _
—-—— - —"^—^ O ——•-——
A
A A *
— B - -A—A- 0 - A -A
AD C D A U A
A B
A
A A
B
0
A
A a
A A
A
A A B
CAB
I) C
A A A
61.50000000 67.50000000
LtQtNOi A « I OBJ ,' E» « 2 OB3 i ETC!
71.'5»000000 79.50000000
HTCNP
es.50000000
9I.SOOOO&00
-------
3125900000 t
OI2G400000
i.'lSOOOOOO
H3X
oMooooooo
O.'OSOC'IOOO
O.'OOOJOOOO
FIGURE A-9
STATION = 2 = DOLA
PLOT OF MOX VS VIS
May through October, 1972
. — Overall Corr. = -.42
Corr (MOX > .08) = -.13
A A
A. .... _
A A
A A
A A A
A A
B_ _A .
A DO
YA"
C A ..
A A A
DA '.'
A A B A
ABCAAA8 B
ADCADOB B
A B C A C
— 0---D A C A
A C
A .A A
A
A A A
A
B .
0 A-
B 0 0
A A A
C A AC
A A
A
C
A
A
A
B
•2.50000000
\-tCtMi, t. * I OO»
7.50000000
,op» . ETC:
17.50000000
27.50000000
17,50000000
47,SOOOO?00
-------
0,20000000 t
O.lbOOOOCO
0.12000000
MOZ
0,08000000
0,30000000
0,00000000
FIGURE A-10
STATIONS=BETH, HYAT and SUIT
Combined
PLOT OF MOZ VS THC (6-9)
A
AA
A A
May through October, 1973
A A
U A AAAA
B C A A A
A AB U A AA
A B BUG BdAAAAA A
A A
A A A A
A A A
A AA AAAA A CAB A b A
A A AA A UC B A AB A
A A A AAOdCCCAAA A A B
A A bA AC BAFA ABB B
A A ABCCEULA CAAA A
A BA A B LBB C
AA BA AAA 0 AA A AA A
AA B A BA A
A A B AAA A AA A
A AA BA A A A
0,10000000 O.VOOOOOOO
LtGENOt A s | UBS , b = 2 UBS , ITC.
1.70000000 l.bOOOOOOO
THC (6-9)
3,30000000
-------
0,23000000
0,16000000
o.izoooooo
MUZ
o.ouoooooo
o.nnoooooo
0,00000000
FIGURE A-ll
STATIONS=BETH, HYAT & SUIT Combined
PLOT OF MOZ VS NO (6-9)
May through October, 1973
A A B
A B A A A
A C A A A|» AA
Att A A AA A A
A A bl)b L«A AAA A b A
A AA A B CA A AA B AA
H bbd A n UAAA A
BAA bUAAA A tAbAdA AA A
AA b ACbllUB BAA AAA A
b CFAUUC RA A AACA . H
BUS B BAAAA AAA A - - - AA
b A
A AAA A
A A b AA A
A A A A
AAA
A AA A
A A A
— A . _
-0,02000000
O.ObOOOOUO
0,|<4000000
U,
-------
FIGURE A-12
STATION = 3 = BETH
PLOT OF MOZ VS NO (6-9)
May through October, 1973
Corr. = .05
„ — o.aooooooo *-
0,16000000
o.jaoooooo
MO*
0,08000000
0,011000000
0,00000000
.A
A A A
A A A A A
A A
A
A A A
A A A tt
— A-A.A . A_...
-_.A A. A A A . A _ . A A
A B A A b A
A A A A
A
A A
A A A
N02 (6-9)
O.o^inonuo o.n'i9nnoon n.on/nonon n.i
-------
FIGURE A-13
STATION = 3 = BETH
PLOT OF MOZ VS SRAD
May through October, 1973
Corr. = .58
•- - 0,20000000
•
t
;-.--.-_ . -
i
• 0,J6000000
i- -
<\
,]
0,12000000
u
„
*
MOZ
i
•
- . . . _
- - _fl, 08000000.
*!
J
... 0(04000000
Ch
0,00000000
* — — _ .. . _
„ „_ _. _ _ ^ _^_ _ »
- — - - - — ...
..
— .. _. . ,. . _ __ ___, „ _______„_
A
_. . . A A
*
4_
4 A »ft »
A A a
A A AB A AA
.
* A A AA A A A
. . . A A . __ A 4 .. A, AA. A AAA A A
A A A A
AA ** A A
ABA A
A A
A 6A Q A.
A AA AA A A A
A A . A A A AA _ .. ..~M~
A A AA AA A A
A A_A4 A A A
BA A A AA A
0 A A b A
»-"—gg£5—-•»•-»- •
60 .'OnonotOn ??0.'00000000 360.00000nOO SQO.OOOOnOftO 7np onnnnnon
. nn
-------
FIGURE A-14
STATION = 3 = BETH
PLOT OF MOZ VS MTEMP
May through October, 1973
Corr.=.75
),20000000-
.„ .0,16000000
0,12000000
1,00000000.
— --0,01(000000
0,00000000
A .
A A A — A_ A A. A
AAAAAB AA
U B AS A A A
A d A
fl A- A-
A U A A
_A A
A.-H B.tt It U A.
A A U BO
A .. C _ A _ fl.B . A b A.A A — A
A C ABAAP A A
A-BA-AA — - B - A A C _
A A A A
-_ A A A
A..
-A -A — .. A .. A A .-
47,'Snononno S7.*nononon
MTEMP
77.5nonoono
-------
FIGURE A-15
8TAt|ON-a - HYAT
PLOT OF HQi VS THC (6-9)
May through October, 1973
Overall Corr. = .20
9:29999999
j_ •;|MM'"
; ^
j p. 12(99909
. HQZ.
•
0104900999
. - ---
—j.-.,,,,,,^
». ... ... A A !
1 - - - "~ " Corr (MOZ > .08) = T1Q
. j
A
ft
11
A "i J
* AAA A !-'
• L_ ..... A d
I A HI A^ AA A A " ' [.
AAAAAAAAA ''!
1 1
A. .. AAAA._JA B...A . ~" " '" "~ ~ '..
ABA A -- -' \
i
t ^ BA-AA • A A ..A B - I*
: A ABA A B A ' " " ' " ' " -^
1 flAAAABA.fl A _ A A A ''I
A_AA .a _."_!"." •• .",
1 - - - ]
• • — — •'
B A A AA A A '.'i
A... B ... A. . ._.A. ... ... ;!
... .... .. 1(
A A A A A ,";
AA ^_A. A A H
— LP
t.lSOOOOOO 1.7SOOOA6A 2'lSanaaAA I'acnnnnn^ i-Ef ,.....-. -.-- -. f
LEGEND | A a | QDJ ; B . 2 QB3
j;*5o«o«oo
THC (6-9)
4,j50oe9oo'
-------
FIGURE A-16
STAUONsSsi HYAL
PLOT OP NOZ vs SRAD
o<*2ooooooo
oTibOooooo
0:12000000
M3Z
O.'OBOOOOOO
0?0«000900
May through October, 1973
Overall Corr = .55
Corr (MOZ > .08) = -.15
A
A A A A A
A . A.
A A
_~44.-. AA& A 4,
A A A 9 OAA
A A A 4 "A A " A " A "~ A
AA A"
A—A A.—A -ft._..AA-i •__.._•._ 1--—-.-I.--T
Al_. *A A AC L.A ' ' A
--1 4. *84._&.._ g AA.__A__AA _..
A " 4 .. A AA
A A
A ""A 8
-*A._._A__Jk
A A
A A A A A A
~"A " V" T ""
^0700000000 " 220700000000
LCCENDi A a I DBS , B » 2 Q83 , ETC,'
S40.'00000909 '700,00000000 "' 860.00000900
9R40
-------
FIGURE A-17
PLOT OF HOZ V4 HTEHP
May through October, 1973
Overall Corr. = .76
Corr (MOZ > .08) =- .31
O.'l6000009
oToiooojoo
. JIO.OQ.04QQO.
A 9
B.-A.A A A A...
A » a A A a a
AA AA A B A A
-a—a-
ASA
•••"—• A/
A B
B A
»
A
.A .A
A
B
"A
A A
A A
A A A
.- ..._A.. A. A _ .... A
sa.'oooooooo ~' 66.60000669
LEOENDi A s 1 003 , B s J 003 , ETC,'
74,'eoooooop az.'oooooooo
MTEHP
'90,00000000
98,00000?00
-------
FIGURE A-18
STATION - 5 - SISP
(Silver Springs)
PLOT OF MOZ VS THC (6-9)
May through October, 1973
Overall Corr. = -.10
* A* *
A *A .AA . AAA.
A AAA A A A
4.A AA_ OA .".B*A. M_A!_*
A A A
AAA
A3A AA
AAA A A AA AAA
..A A_A.. A 4 AA. A._A ... A,...
A A
A A . . A
-0.05000000 " V.'ssb'oooo'o
B- a- 1 QM.
~I,'|500COOO.
THC (6-9) '
-------
FIGURE A-19
STATION - 5 - SISP
PLOT OF MOZ VS SRAD
May through October, 1973
Overall Corr. = .59
g.'iiOOOOOO »
L
O.V500000
._ 9.*97900999.
"a.'otsooooo
O."02*99099
?6.'99599999
._ AA
AO AA A AA
A
. "AA AA _ AA . A". AA~A~_ - . — A —.
AAAAA A 8 0 A AA
Ai A C8 A. i A»4 .__.*!> 1-A_ AA_
AA A *. A A* * .4. 9 A
AA A A AA A A AA 0 A
A ..ABAB. A A AA A_A_ _AA. _A_
B AA A A
A. A A
' *6,'99090000 220.'00000000"
LECENDi A a I QB9 , B • 2 OBS , ETCj
380,00000000 " ' 5<»9,'90009009~
3RAO
'799,00900000 * 860,00000?00
-------
6MZOOOOOO »
I
_ 1
' FIGURE A-20
STATION - 5 - SISP
PLOT OF MOZ VS MTEMP
May through October, 1973
Overall Corr. = .64
o.*o«sooooo
HOZ
0.*04SOOOOO
uTozoooooo
.4 A a_ .it *
V" -.7" C A A B A I . - - ** -
A AABAiAAB AAA
B A
V* Q A~
"A *" A
OAAB AAA AUA AA
B A
A...
i._.C...l.»-_A.A B __*._... 4.B .A.A .
AAA
47.'5bOOOOOO " 57.50000000
LECENPl A * I 003 i B s Z OBS i ETC!
67,'59000000 " " 77,'500«000«
MTEKP
87,50000000 9r,50000?00
-------
A • | DBS i 8 a Z "063 , tTC,
______ FIGURE
8T*TigN=6
May through October, 1973
Corr. = .36
SUIT
RLOI OF noz vs THC (6-9)
•0,20000000-4-
0,16000000
0,13000009
WOZ
0,08000000-
0,04000000
0,00000000 t
— A
— A A- .- A..
— A A_. . . . » B A_
A A A
A_ A_ ..B A
.§ t
A A A A
.* _.B_
A A A A
-A. 4_.*.
. A
•
0,'Mnnnino
i.i9ooonoo
i, 77oooooo
i.osonoooo
z.siooonon
-------
LEGEND I A • J UBS , B • 2 DBS , ETC,"
.Q,20DOQJQO t.
FIGURE A-22
Sf'.TKl" = ». = SUIT
-*ui vs NO (6-9)
May through October, 1973
. Corr. = -.07
- .0,16000000
0,14000000
MUZ
_. 0,08000000-
0,0(1000000
0,00000000
A-.
A A _A -A _ „
A A A
A - ABA.
A A A
-A AAA A
A-AA A A
AbA
A. AAC B A
AAA
..... A AA __
AA
• A - A
_A a—jk_l"
..A A-
'4,00500000 0.0550000Q 0,11*00000
N02(6-9)
O.I7SOOQOO-
o.aiboooon
0.?9Sftnonn
-------
LECENOi * • | 063 i B • 2 DBS , tTC,'
FIGURE A-23
STATION = 6 = SUIT
PLOT OF MOZ VS SRAD
May through October, 1973
O.ZOOOOOOO »
-- Corr. = .61
0,16000000
0,12000000
MUZ
-0,08000000
•
.. . 0,04000000
o oooooooo
A A B . A .
• A
A A
A A AA
* A A
A _A A. JC
A A A _ _ A _ *. A. * *
A AAAAAA AA ABA
AA
._ A A A A A
A A A A
A A AB A A A A . B
_._ _ ... -^___ _.
A. .* ..A --
____ ___A - _. B ..... ______ B
— - • __ ^ - ^^ -• '
A * A
A . . _ A ..
onononno ??o.'onononOO SBO. onnoOOOO SRAD bMO.'OOOOOOOO 700,00000000 860,00000000
-------
LECENOI A a | OHS , b R 2 OB9 i ETC,
FIGURE A-24
STATION = 6 = SUIT
PLOT OF MOZ VS MTEMP
- May through October, 1973
' Corr. - .66
_0,20000000.
0,16000000.
i ,
0,12000000
10Z
.0,06000000-
0,04000000
0,00000000
A A A A ..A..
A A A
A A B B A.
A A A A
A a A i B_
A A A * A A
A A
AB ABAAAA
A A B A_ U B A A~B B.A —B.-A A—
A "A c (F
B
A A
. A-A-
. A_A A -A A A A A_ A _
A A_
-A A A
riH,onoooonn
1 h6.0ftoooorn' MTEMP 70.00000000 BZ.oooooooo 90.00000000
-------
APPENDIX B
Appendix J of the August 14, 1971 Federal Register
-------
APPENDIX J
•MIWMHWSfREC I-teaP"CT: CHEMICAL MKMiT CCS'.i1 ":i
WJ «•»
en
i»
T
Figure 1. Required hydrocarbon emission cent-of as a function cf :-c'.::!-?~'C3! C" •:;-.{ ".r.«ix»
traifon. (R?r=--ence: Air Quality Criteria (or N.'.rosen Oxidss, A.= -i-, i.-i/;•:.-.-.:.":-! rrc..».J-»i
Agency, V/ashmjtcn, D.C., January 1971.)
KOCRAL lECISTEIt, VOL J6. NO. 158—SATUaOAT. Aw I jIT 1< 1
-------
APPENDIX C
Plots of the 75C and 50th Percentiles of the MOX (MOZ) Distribution
for Given Levels of THC and N0_ by Station and Year
-------
APPENDIX C: Plots of the 75th and 50th Percentiles of the MOX (MOZ)
Distribution for Given Levels of THC and N02 by Station
and Year
Appendix Figures C-l through C-10 give for stations AZU and DOLA and
years 1972 and 1968 plots of MOX versus THC and MOX versus N02. Figures
C-9 and C-10 give for BETH, HYAT and SUIT data combined plots of MOZ
versus THC and MOZ versus NO,. In addition for each of the ten plots,
the THC or N0_ axis have been divided into intervals. (The intervals are
different for each plot and were chosen so that the number of MOX readings
in an interval were of a 'reasonable' size, i.e., not too many or too few
observations in an interval.) For each interval, the 75 and 50 per-
centiles of the MOX distribution within the interval were located (75%
of the MOX observations in the interval are below the 75 percentile).
Lines were then drawn between the 75C percentiles and 50 percentiles
for each interval to give the 75% and 50% lines shown on the ten plots.
-------
FIGURE C-l
PLOT or HOX vs (THC (6-9))
May through October, 1972
Overall Corr. «• .51
- ^Corr-— (MOX->—K
75% line = for a particular interval 75% of observations are below this line, etc. for 507, line.
The number at the bottom of each interval indicates the number of observations in the interval.
-------
PL
9. $0400404 » •
STATlUN-l = A£U
OT OF MOX VS NO (6-9)
A
-- .._-.—
O."40030300
•
0^50000300 '""
M3X
oTJooaoooo _
A
A
'""... .. . A
A 0-cT
O.'JOOCOJOO
A
. . •«* D '* —
. ... A
A
A
A A
„_ A A
$.'30000300 " " " '" [f
--
A . _
A
V
A
— &A~
A
9.
A A
A3
'11
....
A
A A
A
A
A-£bf
A
A.
DA A
A
17
--
A
A
y&
A
AA
A
A
AQ
A
tt
4^00040000 0.01000004
. LECEHPl A « J 033 i' 9. a 2 033 • Etc:
A
A
J?
:tf
_. .*. ...
A
A
V
. A . >
A "
/*
A
.' . I
A
AA
A
ip
. A '..
1
^::/
rV
A";A A
A
A
A
A A
/
"ll
' •
A
A
A A
/ *
A A,
A ^^
A /^
A/ A . .
/ A A
A A
A
A .
..... .....
**
A
\*
AgJ-r,
A A
V
A
A
ir
Overall Corr. - .67
>" Corr (MOX > .08) = .56
A
A
n '
^i^KJf^-. .
'-—£" — ^
A- ^> ^cfye fii^t
. /
~Q A
A
A
A
A
A
. \
' " ' - - --_-..- -. .... |
— y: :::.:::nr : ' . • '~:.: \
4.49000040 4,'U000444 0,16000000 0, 24444004
N00(6-9)
75% line = for a particular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval indicates the number of observations in the interval.
-------
FIGURE C-3
STATION = 2 •= DOLA
VS THC 16-
May through October, 1972
Overall Corr. = .53
Corr (MOX > .08) = .40
o.*ooooooo j.aooooooo
LESENDi A a 1 03S , 8 e J DBS .ETC.'
3,80000000 5,40000009
THC (6-9)
7.00000000
75% line = for a particular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval indicates the number of observations in the interval.
-------
FIGURE C-4
STATION = 2 = DOLA
PLOT OF MOX VS NO,
May through October, 1972
Overall Corr. = .63
Corr (MOX > .08) = .51
O.'OlSOOOOO 0.07500000
LECEsJt A = 1 QBS i 0 = 2 Q8J , ETC."
.'JJSOOOOO
O.'l^OOOOO
0.31500^00
(6-9)
75;i, line = for a particular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval indicates the number of observations in the interval.
-------
FIGURE C-5
STATION = 1 = AZU
PLOT OF MOX VS THC (6-9)
May through October, 1968
7,00000000
8.-60000000
t'Tf"
* = i ruts . n r. •> tw
75% line = tor a particular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval indicates the number of observations in the interval.
-------
0,50000000
FIGURE C-6
STATION = 1 = A2U
PLOT OF MOX VS NO (6-9)
May through October, 1968
). 00000000
-0,02250000 0,02750000
lEGENDi A a J OD3 , D x Z OB 3 , tTC,
0,'o7750000
NC>2(6-?)
0,12/5.0000
0,17750000
0,227509.00
75% line = for a particular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval indicates the number of observations in the interval.
-------
FIGURE C-7
STATION =• 2 = DOLA
PLOT OF MOX VS THC (6-9)
May through October, 1968
1.60090000
3,20000000
isc{6;2i_ _ . ._„ _ „__
4,80000000 6,^0000000 6,00000000 9.60000^00
LCl'ENDl A * 1 1)03 / U a a UBS , ETC,
75% line = for a particular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval Indicates the number of observations in the interval.
-------
FIGURE C-8
STATION = 2 = DOLA
PLOT OF MOX VS NO (6-9)
May through October, 1968
0,"000»0000 "
^: » s i OUT , n = ? cmr, ,
O.lfrOOOOOO NQ2^6~9^ OV24000000
0,33000000
"0710000000
75% line = for a particular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval indicates the number of observations in the interval.
-------
FIGURE C-9
May through October, 1973^
••••;• •
SI
0 2 Q 00000 0 *
NATIONS .= BE1
.PLOT. 01
A
0,16000000
I" . "
... ..
. . ' ' . . . . „
i 0,12000000
MOZ '1o ~h A A
'*
- . 0,08000000 A
CL A A UA
^v A
0,04000000
•
0 ,00000000 • IS
j
... ...
AA
Afi '"i
**<
A
\ A
A.
•'®
A A
A
A B
AflAA
AC
/
A B
AAA
U B
B
A
3*
0,10000000 0,90000000
t
B
A
BE
^
l:
Dd
J*
1A
C
)
!
A
|
CH
F!
/
1
4
SI
:c
•0
(U
^ A
)A
t A
'A
y^
> "
wz
A
A/
A
A
A
a
i$A
A
6
AB
C
UA
£AT
VS
AAA
A-
AAAA
A
A
and SUIT Combined
TUG (6-9)
.. .
4 A
.... ... A .
^^
v AB A
i
'A A
AA A
A A
Zf
1,70000000
A
A
'
A.-- -
f) S YO **•*"*-
/'
A A -£}
-^>^
» A A ^^^
~^
£-^^LTzrIt :;': : •'-"-- -
-^^-i — • "
-- - ' -•
A . , .___..
A A A
A
A
A
..... . .-.._
A 1O
£,bOOOOOOO 3,30000000 4,10000000
J.EUENOI A • t UBS / B R a OB3 , tTC, TliC (6-9)
75% line = lor a particular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval indicates the number of observations in the interval.
-------
FIGURE C-10
STATIONS = btTH. HYAT and SUIT Combined
PLOT UF HUZ v3 Non (6-9)
0(20000000 t
0, UOOOOOO
• .'. . • I .(•«!* •
A
A A
n 1:11:5
A
' ' \
B
- . _ B
o.ouoooooo A
A
- 0,00000000 .
'£
-
Bfl
A
/
^
BB
A
A
*}
H C
AA
ifcd
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B
AA
}
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A
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: B
BAA
A A
AA
1
K A
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i
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A
A
A
Ab
/^
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H
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QA
A A
AA
A
i
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-27
A
A
A AB
A
^®6.
A AA
UAAA
. i ,XJ(|1 .
A ujffufi
A AAA
AAC
AAA
A
A
y'o
B
A
A A
1 till A
A^^A — A-
A U A
A<
AA A
A
A -
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A
A
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A . . _...,......____._
••--•-- - •
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r\-^t PJ , i
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j. — £)
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•
^\
^-,
A^S^ ^v^"c °ia JhrtZ
u
-A*-
A A
A
^
.LL
T T
0,10000000
-U,02000000 0.06000000 0,14000000 0,12000000
|rc,F'ir>; t. : i ri"l , t! s <> (ni> , fir . N0_ ''(6—9)
75% line = for a ^articular interval 75% of observations are below this line, etc. for 50% line.
The number at the bottom of each interval indicates the number of observations in the interval.
0,40000000
-------
APPENDIX D
AID Results for DOLA, BETH, HYAT and SISP
-------
FIGURE D-l. AID Results tor UOLA, May through October, 1972 Data
9)
(1) = Initial group before any splitting.
_N ^ Group sample size.
0, = Group mean for daily max. oxidant (units = ppm).
NOTE: Groups with high 0^ are at the top of the figure and groups with low 15
are at the bottom of the figure.
-------
FIGURE D-2. AID Results for BETH, May through October, 1973 Data
cv;
flO
fr)
0*3 =.
- .03(7
(1) = Initial group before any splitting.
I* = Group sample size.
O.j = Group mean for daily max. ozone (units = ppm).
NOTE: Groups with high 03 are at the top of the figure and groups with low C).
are at the bottom of the figure.
-------
FIGURE D-3. AID Results for HYAT, May through October, 1973 Data
(1) = Initial group before any splitting.
IJ = Group sample size.
0- = Group mean for daily max. ozone (units = ppm).
NOTE: Groups with high 0. are at the top of the figure and groups with low 0.
are at the bottom of the figure.
-------
FIGURE D-4. AID Results for SISP, May through October, 1973 Data
(1) = Initial group before any splitting.
]4 = Group sample size.
0- = Group mean for daily max. ozone (units = ppm).
NOTE: Groups with high ^3 are at the top of the figure and groups with low 0,
are at the bottom of the figure.
-------
APPENDIX E
Plots of Adjusted MOX (MOZ) Versus Adjusted
NO. and THC by Station
(Adjusted for SRAD, MTEMP, VIS)
-------
FIGURE r-J
AZU
PLOT OF MOX VS THC
Mav through Octo'if>r, 1972
Corr. = .39
N = 128
0,10000090
_ . . -
- -
Gt 12000000
'
MOX
-I"-- (Adj.)'.
-
-QtVooftOOQo
----- - - - -
' "-O.UOOOOOO
(Adj. for SRAD, MTEMP, VIS)
A
A
-
A :
1
' "" " - ' A A " A A - -.-.-._
A A A
AAA A
AAA ' I
'A - - - - A A • * A - - _- i
- • - A A A - '
U A A " ---.-.
A
A A AA A A !
AAA A 'A A
"""A A A" " " A A "' "A "
A AAA - "
A « A A ' ' ',
AAA A A '
A A A A A A
A A A A AAA A ......._.
-—- A A * A A A ' ' '
- - - A A A A A
A AA A " " ' A A •
AA 0 A
AA AAA A A A
D A A A " " -.__..._
•~ A' ' AD • A A -
AAA. A A "
n A
A :
.... A A .... A I
A A A
• A' • • ' - - ' - -• - - ---I
A ' '
A ' '
i
i
•'".'soooooo -
LEGENDI A a | 003 r B > Z OUS , tTC.
0.05000000 0.'b500000Q
THC (6-9) (Adj.)
I.Z5000000 _ ._ 1.8SOOOOOO__
-------
0,"18000900 »
FIGURE E-2
A?U
PLOT OF MOX VS N02
(Adj. for SRAD, MTEMP, VIS)
I-
May through October, 1972
Corr. = .48
N = 128
'I
0"
I).12030000
- MOX
(Adj.)
0,00000090
"11,120.001)00
A A
A A
A A A
A A _ A_
A A A
A A "
A"A "-A A A" " ~- — A~
A A A A A
A A _A
A " ' AA A A
'A " ~ A A "A A
A AA A —A- 'A —
A A AA A A A A
A A A A A
__ _
A A - .1 A A
"A " A " D A
""A AAA A" A ' " A" ~
A A A A
A A A
A ~A
NO., (Adj.)
*• o.'
o,o7onocoo
-------
_o.,j«jo_.2?op
-07990(^900
^04000000
MOX
JCAdJ,-
•}.01000000
FIGURE E-3
DOLA
PLOT OF MOX VS TUG (6-9)
(Adj. for SRAD, MTEMP, VIS)
, May through October, 1972
-; Corr. = .44
N = 131
...A".
A " _ _ _ A A _ A
~_I HI A Jl _|~_1_A " A I A _ ~_~_ "" A" _1 A
A - - - A~ ~~
_A AAA
AA _
A
A _A . _. A
AUA A A OA A A A_
A A~»~AB»"
AAA HA A AA A A
A A AA A A
AA
A. A A. AAA. A .. . A .AA
A A A A A A
' A »'J 1 _ _ A. " _J
A "A A" -- ~
A A U A A
A A A A A A A
A A
2,'900UUOOO
-------
9,14000000 ~\
i
J.OIOVOOOU
MOX -
"9','OtOOOOOO
"y.HQOOQOO
FIGURE E-4
DOLA
PLOT OF MOX VS NO, (6-9)
(Adj. for SRAD, MTEMP, VIS)
May through October, 1972
Corr. - .46
N = 131
' A '_
A A
~A—"A -
A A
-- A ' A~~ "" A ' A A A A
A A~ ~A A AA " " A ~~
A A A A (I
A AA MA A A A 0
A ~"k "' UA" ~ "U A "A
AA A II A 11 A
' ' - ~ • ~ A ' AAAA A
ft "A '~ "AAAA ""A A A "
A A A (I A A A
A A AA
A n — '
------ u AA A - A
AA ' ' ' A A A * _ A _
"A" 'f\ ~~ ' - ~ - -
A
A
A
AA
-I. l',S.in,'i'0
O.PlSOOOf
NO (Adj.),
i-O •* fl.f-
7500'inf,
o.'nsnoooc
O.I9SOOOOO
-------
-0755009000'
MOZ
-- (Adj .
'3101909000
FIGURE E-i
BETH
PLOT OF MOZ VS THC (6-9)
(Adj. for SRAD, MTEMP, VIS)
May through October, 1973
--. Corr. = .19
N - 56
-A"
UA A
A _A A A U_ AD
"A" "D " A A
A A A
_~ A A ' A A
A A
A A
"A A" A
"A A
A-
A A
A
A A A
A
A A AA
A A A
AA A
0.110090000.69000900
A - I DOS , il B 2 L'b3 , tTC, THC (6-9) (Adj.)
-------
i,0*000900
o;o2oo?ooo
MO/ -
(Adj.)
•OiOlOOOOOO
•Ot070000«0
FIGURE E-6
BKTH
PLOT OF MOZ VS N02 (6-9)
(Adj. for SKAD, MTEMP, VIS)
May through October, 1973
Corr. = .07
_ j N = 56
' - A ~ 'A
A
A " A
AAA A
AA A
A A~
A
A A
A A A
"~ A '" A •
A A A
A A
" ~~ A ""'A
A A A A A A
A A A A A
_ _ _.. ..^
A => i DOS ,' U a 2 UUS , EJC,
0,'0??0?00? 0,05700008 9,06500000
N02 (Adj.)
-------
0.10000000 »
FIGURE E-7
HYAT
. PLOT OF MOZ VS THC (6-9)
(Adj. for SRAD, MTEMP, VIS)
May through October, 1973
Corr. = .18
N = 82
-JT0790700T
A A~
A A
A
MOZ
.)
___________ A A ______ ..... A___ ..... A _____ AA ____________
-A- "A'"~ A" ......
... — - -
0.01900000
... A — A - - A
A A
A _ A__A_ __ A
._* A A _A_0____A .
A AA
A 0 A A
A A
AA A A
AA
A A
•970*999000
A A ADA A
AA
A
_— ..__
________ A._ A AA ......... ___________ ._..._ __ ..... __ .
. A -"—— - .....
AO
"59195909990.
lEGCNOl A s | 003 , U s 2 OUS , tTC,
. THC (6-9) (Adj.)
-------
FIGURE E-8
HYAT
PLOT OF MOZ VS N02 (6-9)
(Adj for SRAD> MTEMP> VIS)
May through October, 1973
Corr. = .13
N = 82
A A
MOZ
- (Adj.'X
A AA
T7~A~r"A A"
A "" A "
0,0>000000
A
AA A
U
" **_"!" "_"J"
A A~" " "
T" "A A "A
ABA A
C * A
7 u~"
T -AT
A
._.*__. A _. A A _
A _ A
A" A'
A A "*~"
A
A
6^12009909
0,g9009000
0.28000900
LECENOl A » I 003 , U 3 2 DBS , ETC,
(Adj.)
-------
-0,00000000-*—
0,05000000
0|OZOOOOOO
— MOZ —
•(Adj.)
••0,01000000-
.90,04000000
»0,07000000
FIGURE E-9
SUIT
PLOT OF MOZ VS THC (6-9)
(Adj. for SRAD, MTEMP, VIS)
May through October, 1973
Corr. = .37
N = 50
A A
-A
A
AA A
A . A
A A
A --
AA A AA
4 A
-A A A
-- 4 A A
... . . . A A. . . _
A A A A_.
A A
A A B A
AA A
.A .A
A ._ . . A .
A A
• 0,'17000000 »0,'19000000
0,09000000
lEGENDl A e I (JB3 , B » 2 OB3 i tTC,
0,J7000QOO
THC (Adj.)
0,65000000
0,93000000
-------
&,08000000-*-
_ ..0,05000000
0,02000000
-- MOZ
*otoioooooo
• 0,011000000
•0,0/000000
FIGURE E-10
SUIT
PLOT OF MOZ VS N02 (6-9)
(Adj. for SRAD, MTEMP, VIS)
May through October, 1973
Corr. = .08
N = 50
A - A
-A A
A A
A- A - - - A --
A A A A A A
-A—A * *
A U A AA A
A
AA
AA A A .
_. . -A - -A
A A A A
C A A
. . _ . .A
A
A A
A- —A --
•O.OSbOOOOO
0.00SQOOOO
0,ObbOOOOO
UEOENDl A s 1 UBS » B = 2 DBS i tit,
0000.0_
N02 (Adj.)
0,18^00000
0,21^00000
-------
Appendix F
Listing of Data
-------
Appendix F: Listing of Data
A listing of a majority of the data analyzed in this report is given
on the following pages. The data listing gives (a) May thru October data
for AZU (Station = 1) and DOLA (Station = 2) for the two years 1972 and 1968;
(b) May thru October data for BETH (Station = 3), HYAT (Station =» 4), SISP
(Station = 5) and SUIT (Station = 6) for the year 1973. The definitions of
the various variables for which data is listed are given in Tables 3 and 4
of this report. Missing data values are indicated by blanks.
-------
Da,.ta Listing .(Hay thru October, 1972)
083
.2
3
4
b
7
9
10
11
__ _ 1 2
14
Ib
i/
|0.
1 9
21
?2
23
214-
_ . 26
I'D
29
40-
- 31
._. .32
S3
34
-- 3b
- 3d
39
'10
44 .
Mb
46
(17
U M
__ 49 .
SO -
51
b2
S3 -
YR/MO/DAY"
DATE— STATION-- NCU
^. .. ^ —
7203 > \<-
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- 720b06
7 1*\ S l /
720b»lO ..
720b|| _ .
- /2ob»2
--72Gb |3
72031 '1
/20JI3
720310
720b|7
720510
/2.V.U-I — .
- 720520
720i21
720322
7_ob23 __
72Qb2b.
- 723b26 ._
720S27
7 1* o 3 '^
7 ^ 0 -i i2 ¥ ___
„ 7*0601
720*>0«!
720603
.._ 720604
7206Q5 -. -
720606
...-7206J7
720610 _. .
- .. /2f,61l ..._. _ . .
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72C013 _
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— 720u| >
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— - ,070 . -
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- -- U 1 U -
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69
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.. _6/3.-
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.... 14*
—
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6,1 6b
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6,5 60
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— 7,1 ..66 . . b..-.
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bu n
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65
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if Q\ (6—9)
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— — q .
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... ,OS3
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,153
- ,12/ . _.
.. ,063 .- - -
,010
. - ,090 _.
;J!3
._.. ,1,43 ......
.. ,U2/ ._.
. .OuO . . .
,037
,100
.100
.007
. 103
,050
,0'W
,007
. ,123
" |074
!oio
,033
. -.113. . .
!l"3
,123
._ ..020
(6-9
1^94
,323
.123
,204
.254
.250
,124
,050
,09/
,!»'
,097
,137
,095
,1/3
|o50
.out
,077
!ll4
,064
,044
,123
,290
,170
,060
,073
,06/
!l'3
.217
!o93
!o77
,077
,104
|ot>o
,080
,0'>4
,040
.054
,120
STATIONS*
THC
) (6-9)
5,000
- - 6.667
8,434
5|434
6,33i
5,334
4.66/
4.000
3,000
-------
-
UHS -OAlt
1J8 - 720SI7-
|49 720918
140 720919
141 7209?|
144 720924
1 /ij I J f QJil
14b 72.1926
14/ 72092/
\uti /20920
149 -..lln'^c^
liO 7209JO
1*1 721001
1*2 741002
1*4 721J04
1*0 / e \ o o 4
IS* /2JOOJ
156 - --721.100
1S7 721010
1*0 721011
15* 721014
|6b 721014
i ** «* - 7 P 1 .1 1 b
164 7210I/
IM 721020
16* /2102I
Ibo 721022
J6/ 721024
166 72U24
169 72102*
170 721026
171 72102/
172 72(028
174.- /2102V
(7« - - 721030
}7* . 721041
Q T A T 1 r\tj
y
... 2
2
2
2
. 2
3
2
2
. 2
2
2
2
J
.... 2
2
2
.... 2
_ .. 2
. . 2
2
2
2
. j
a
2
2
2
- - - 2
2
. . g
- .. HOX
- ,09
!l/
- ,'od
ftb
- --,1)3
- ,08
,10
,C8
.06
1 0
, 1 V
.15
- ,04
,02
,03
,06
— ,11
— ,09
,04
,07
,07
- ,C2
- ,07
.0.4
,02
,11
- !lO
- ,11
)o4
,02
,'Ob
.04
-- ,01
- ,04
-•
NO .
" ' / £ O \
1 D^ «r I
.... ,010 —
— — • 0 ii
1 1 0
;ie4
- ,070 - -
0 I 3
,090 .
,130
,0*7
,140
203
- — , c H J - -
.... ,197
,014
)«°
' ,160
- ,107
— ,400 - -
~ ",187"
,194
,054
-.014 --
... 164- --
- - - , » ov-
.,1*V
,134
~" I274 "V"
,1*4
,210
,134
... ,J64 _. .
- - ,02/ -
,200 -
M/\
WU*»
. (6-9
• ,05*
,070
',180
... ,U4
—.,040
,09/
,150
!o9/
- ,1«0
-.204
)o/4
.064
— 1204
- .08J
, If 4
)o7/
,06U
||04
,097
,107
.O*/
— , u J •
- ,04/
,054
STATION82
THC
) 7 (6-?)
— - 3,000
. 4,000
4.i\i
4,000
6.000
. 4,434
4 000
.. 4,334
4,o6/
4,000
4.434
-- 6^000
- 4.000
'i.OQU
- - 4J434
6.444
... . 4,000
4.000
-- 4,§434
... .4)000
4.00J
4, you
- - 4)000
... 3.433
4,000
4.000
l'b6?
1,000
- -2,434
-- -
. MTEhP
70
. .72
86
76
74
-- - /2
. . . 7il
73
72
74
7*
72
71
72
- 85
.. ^
/3
75
. 74
7 j
71
.- 70
bb
/O
.... 69
- - 70
. . 69
0«
b*
69
'IS
/O
. ._. ../O
- — -
3KAU
*40 "~
524.
.. . one
2*0
. _ 066 . .
429
418
406
... 012 - -
443
26*
41*-—
. 420- -
416
023
.. __ 420
2*5 .
._ .
-6.0 —
10.2 .
9,4
fc,4
5,9. .
- 3,9 ._
3 »
. 7.4 .
6.0
..*!* ..
P.0
-8.1. .
._9.5 .
4.6
5,0
8,1
3.8
.. 8.0
*'.2
5,5
U. 4
164 _ .. 4,*
1/4 6.2
464 *,9
444 *.0 -
2/2 4,9
301 <»- *
... 3/3 ...
106
3(>H
4do
349
"0)2"'"
0,8
/.O
-11,5 .
7.9
_3,3._
RH
73 .-
61._.
75
40
74 ..
66 . .
6N
*8
71
70 ._.
79
76 ..
68. _
*7
68
66 _
26 ._
64 ..
54 ,
7* .
66 ....
66
63
/O
bb
/6 _
73-._
73
44. .
75
84
70 __
87 .
lb
16_.
..V13 I
5
1 2
12
.. . 5
'.."l4 .. .,
..10 .. _
8
5
_. 10
0
4
... 1* .. .
20
2*
8
8
30
. .15 .
13
12
.. 30
. .00
_.10 ..
. . / „.
10
10
. . 2 ._ .
4
. .. .7 . _
4
2
4
40
_Ji
_.
iff «S
*tt .5 .
*6 _JJ
57 3
51 7
04 1 1
60 .7
59 7
*6 1 1
60 11
60 3
fau 4
66 ._. 7 _ _...
6i B_.. . .
*5 12
*8 10
59 9 . . .
*7 10
"*7.T.1. 5 -."..77 "77.7
bO U
*5 6
54 .._. * _.
.59 13
ib i _
*5 4- _ ..
*6 11
*« 11
*9 5
61 10 „
00 . 2.
49 6
57 3
*5 6
*<> 6
*>? 5
11 10
.17 U_. . .
-------
'Data Listing (May thru October, 1968)
-•--•----•
-
-/,J
I I
--JI
DBS
1
»
c
3
4
5
6
7
a
9
10
11
I *•
13
\t
15
16
17
|8
19
20
21
22
23
24
2*
26
27
20
29
30
31
32
33
34
3*
36
37
38
39
«0
41
42
43
44
4*
40
47
40
fj Q
M T
bO
51
52
S3
YR/MO/DAY
DATE STATION MOX
4 I- .• |L • J
6oQ*Oc
600*03
600*04
600*0*
6HQS06
60 0 * 0 /
brt o * 0 "
660*0**
60o*10
600*1 1
JK A A Q 1 -*
DOQj 1 C
6HOSJ3
66oSl«
6do*iS
600*18
600*|9
660*20
600*21
600*22
6*0*23
6bQ*2<4
60Q*2*
60o*2b
600*27
680*20
6riQ*2V
6dO*30
600*31
660601
6BQ002
600603
60Q604
66000*
60QOQ6
60Q60/
600608
68060?
66*0010
6000)1
68ob|2
680613
6006)4
60Q6I*
680010
86061 /
600610
Jh j4 A J* f O
66061'
600o20
660621
66Q623
,i«
, 1 2
,07
,16
,06
,12
, | 6
,09
,10
,12
,06
,04
,03
,07
.16
I2*
,30
,10
,06
,06
, 09
ill
,22
,28
, 19
,21
,12
,20
,52
,30
,24
,07
,05
,04
,02
,03
,13
J25
,18
,29
,21
,21
,28
,2-4
.29
,34
,36
,44
,27
,12
NO
(6-9)
,027
,020
,027
,040
,010
,020
,040
,0?3
,033
,010
,020
A * A
,010
,024 .
,010
,030
,093
,080
,097
,063
,023
,0?7
,013
,023
,053
,033
103
IO/3
,057
,067
,013
,067
,030
,020
,010
,030
,060
,090
,05'
,060
,093
,067
,060
,08/
,080
,0*7
,037
,01?
,043
,QlO
"~N02
(6-9)
/.. ,010 "
,010
,010
,010
,010
,010
,023
,010
,010
. ,010
,010
,010
,010
,010
,013
,017
,010
,017
,020
,027
,017
,010
,010
,010
,010
,023
,027
,017
,010
,010
,017
,010
,010
,010
,010
,010
,040
,010
,010
,020
,027
,017
,030
,020
,013
!uo
,115
,040
otation=i=A^u
THC
(6-9) - MT
},oo«" "
2,333
3JOOO
2,000
2,000
2,333
2.3J3
2,333
2.000
2,000
2,000
2,000
2,000
2,000
3,333
4,000
4.000
3,000 '
" 2,000
2,000
2,000
2,000
3,000
3,000
3,66/
3,333
2,333
2,000
2,000
3,000
3^67
3,000
3,000
2,000
2,000
2,333
2,000
2,000
2,333
3,067
3,000
3,333
•
4 , SoO
5,000 " "
4,000
4,333
2,000
—
fnp
69
66
65
66
63
67
68
66
66
66
68
64
63
65
68
70
75
73
72
70
69
67
69
73
80
82
78
72
69
71
70
70
72
66
69
70
68
69
70
73
71
74
72
74
77
73
68
71
71
70
72
71
71
• - »•«•*
. SRAO
""" 477
385
A62
572
364
678
53(1
" 390
707
563
442
658
61b
774
762
714
732
677
722
~ 682
750
728
767
762
769
736
650
6*7
663
632
545
'
'
715
746
728
711
556
676
734
' '774
752
524
" ' 6,50
ni«*»*«»
/. A"?
g,2
4,6
9,6
M
/ 90
4,6
76
ajs
6,1
1 ™
8,9
10,7
"9 »
10,1
7,4
7,1
6,4
" " ~ ta ^
~~lo!6
" f
6*1
69
67
" 7|o
5,7
3,6
6J4
6,6
0,0
• w
" ' b\t
5,6
4,5
8,9
^ 1
6,1
— 1 "
6,7
5,9
9
10,3
s •
9,1
6,5
SO
6,3
6,6
6,2
6,1
79
66
7,Q
8,1
6,'9
,..„„,.,„.
RM vis.
J
5
6
7
_1 _/./ *
«j
^
12
10
- -- 0
~ 12
- •- go
7
i
- 5
.. ^
8
12
6
5
— -- - - a
• 6
*
4
'• -I
."//_._ 3
1
4
7
20
a
--• • 10
8
6
4
' 4
.2
3
4
2
2
4 "
2
1
••••«••**•«
//OPT.;
5a— •-
55 ~ "
54
52
53 ~"~
" Si
52 "
"S3
52
52
46
44 "
~~ 46
47
56
57 "
59 "
59
_- 55 ...
54
S3
53
"52 "
" ~ 5* "
55 ' "
56
55
56
._.. 57
- 58 —
59
58
S3 I
* '
48 '
53 "
' ' 51 ~"
*J
55
57
5T
57
• 59 — •
*9
58
56
56
55-
-_. S8
59
61
- s, -
• v
"•» ~~"~. ~ ~~
7
6
6
8
5 ~'~~~ ~'_ '.
5 "~
3
4
3
6
8 ~
4 "~ "
S
5 " /"" ' "
3 " '" " " ' ~
a
6
a
r
4
14
7 -----
9
6
4
5
o ; ; _/ "_
3
6
- ...
2 - - - -
5 - • -
9
3
4
6
s ;__'•; •;
4
g
4
s ' •
3
4
5
J ~
-------
OB 3
54
SS
56
57
5b
59
60
61
62
6)
64
65
66
67
60
69
70
71
72
71
74
75
76
77
76
79
80
61
82
83
6U
85
86
87
80
89
90
91
92
VJ
9(1
95
96
97
98
99
100
101
104
103
too
105
106
DATE STATION HOX
680624- 1 ,15
680025
68Q626
6006?0
680629
68Q630
600701
680702
680703
680704
660/05
680700
60070/
680700
68Q7Q9
680710
6007)1
680712
600713
600/14
600715 .
68Q716
680717
600710
68071V
68Q720
600721
600722
680723
60Q724
600725
68o72o
600727
68Q720
680729
680730
6BQ731
600001
'60Q802
0800Q3
68QOQ4
66Q005
60Q80b
600807
60Q8QO
680809
680&10
680011
680812
600813
680814
6808J5
600810
,13
,22
• 13
,09
il«
: i2«
,29
,26
• ?'J
,?9
,20
,25
.»'
,21
• 21
. .30
• 37
,1«
,09
.13
.17
.21
,34'
,35
,20
,36
.34
,20
,17
.25
,26
,23
,28
• 22
,20
,17
,25
,30
,33
,2/
|25
,33
.37
.25
,26
,23
,22
|20
• 11
,15
,19
,10
NO
(6-9)
,010
,010
,010
,010
,010
,010
,010
,010
,010
,010
,040
,020
,010
,0|0
,010
,013
,020
,010
,0(0
,013
,0|0
,010
,017
,017
.»!*
,020
,027
,040
,010
,047
,020
,050
,613
,057
,040
,010
,«M>
,017
,050
,053
,010
,017
,083
,010
,010
,010
,010
MO
_J^2 THC -
(6-9) (6-9)
,020
,040
,043
,03*
,010
,030
,073
,060
,043
,123
,003
,090
,087
,050
,047
,04/
,063
,090
,037
,030
,027
,040
,067
,077
,063
,040
,067
,077
. .. .090
,053
.123
,117
,240
,087
,140
,070
,047
fQ6b
,064
,087
,010
.,050
,090
,023
,023
,020
.023
2,533
2,067
3,000
2,66/
2.000
2,000
3,000
3,000
3,333
4,000
3,000
4,000
4,000
2,000
3,333
3,000
3,333
2,000
tf.OOO
' 2,000
2,000
4,000
3,667
3,667
3,000
3,n6/
3,067
3,000
2,66/
3,333
3,000
5,000
4,000
5,333
3,667
3,000
3,000
3,000
3,000
3.000
3,000
4,000
4,000
4,000
3,000
3,000
3,000
2,000
2.000
2,000
2,333
HTEHP
70
69
67
67
69
72
67
68
72
67
68
68
73
73
75
80
78
75
71
72
73
71
71
68
71
76
72
72
76
77
72
74
72
72
00
74
74
77
73
72
72
71
72
73
71
74
74
74
71
70
73
'/3
70
3RAD
' 342
304
2/0
245
613
631
708
700
660
195
426
443
719
756
761
737
722
703 '
552
606
710
696
673
652
677
602
603
658
703
690
539
2V3
542
655
647
636
501
63|
612
612
626
652
700
685
589
640
446
514
589
566
323
A US
4,4 *
4,0
9,5
6,1
6,9
3,9
10,5
6,5
6,5
9,3
8,5
6,6
7,1
6,3
9,0
6,7
9,0
9,0
2,6
3,7
4,0
8,0
6,0
9,1
7,3
7,5
9,2
7,9
8,1
6,5
8,7
7,6
8,3
8,9
6,4
9,7
7,6
8,1
5,2
6,2
10,3
8.4
9,1
10,4
10,0
6,9
8,2
0,1
6,9
9,9
5,7
6,6
7,3
NH VI3
7
3
3
3
a
8
3
3
3
4
t
3
2
3
3
3
6
7
5
7
10
2
1
2
5
2
3'
4
6
2
3
10
5
7
10
7
4
4
2
2
2
3
/
10
7
2
5
5
7
6
4
9
OPT
57
59
56
S/
57
55
55
55
56
59
54
59
60
61
62
59
62
61
59
57
56
56
59
60
60
61
62
61
61
61
60
60
60
62
63
62
60
60
60
60
59
59
60
61
61
62
6|
60
59
59
57
59
S9
MS
11
"7
7
4
a
J
2
4
2
6
6
8
9
3
4
4
5
4
5
5
3
5
3
5
3
6
2
6
4
5
5
3
2
3
S
7
7
3
5
6
3
4
6
6
3
-------
DBS
107
job
109
110
111
112
113
114
115
11<>
It?
lie
ii9
120
l?l
122
123
12«
125
126
12'
12B
129
130
111
I"
134
134
135
136
137
Hb
139
l«o
111
1«2
l«3
144
145
106
147
lib
l«v
ISO
151
152
153
154
155
156
15/
iSb
159
DATE STATIQI
6B001V
600bltt
680019
600820
660621
680622
600023
6bO«;><4
6bOfl«>5
660626
6bOb2/
6bOb?8
6BQ62V
(.BobSO
660641
660VOI
600VQ2
66090J
600'<04
660905
6H0906
6U09Q/
660^06
66Q9Q9
6B09U
6BQ912
660'Mi
6bQ9l<(
66o9i;>
660<>io
66091 /
6bQ9l0
660V19
600920
6U0921
6B0922
6bO'>24
66o'»24
eBO'125
660421;
6«>09?/
Cbo928
680<»,»9
66!>
NQ
(6-9)
,010
,010
013
.020
,05/
,010
,010
,020
,«13
,023
,017
,060
,040
,040
,010
,010
037
,023
,017
,037
,010
,063
.037
,013
,010
,010
,010
,010
,010
,0(0
,010
,010
,010
,037
,010
,03/
,040
,060
,010
,010
,010
,033
,040
,027
.013
,020
,OlO
,010
,020
,047
NO
2
(6-9)
. ,010
,0«0
,047
,05/
,093
,063
|027
,070
,103
tO<>3
,207
,090
,107
,143
,063
,030
,103
,100
,074
,1"
,OBO
,113
,107
,070
,037
,017
,050
,070
,037
,013
,0t3
,017
,020
,057
,030
,064
,160
137
,OB7'
,010
,027
,04/
,057
,057
,023
,050
,040
,027
,044
|09J
iTATION*)
. THC
(6-9)
2,000
2,000
2,667
2.000
3,000
2,000
2,000
3,434
3,667
3,000
4,000
4,433
5.667
3,000
3,433
4,444
2,000
2,000
tf.OOO
4,333
4.667
3,000
4,000
2,434
4,444
4.000
3,667
2,000
1.000
2,667
3,000
3,000
2,000
2,333
2,333
3.000
6., 000
4,333
4,000
2,000
2,000
3,000
2,66/
3,000
3,000
3,000
" 2,667
2,»6f
2,66/
3,667
•HP
73 "
72
72
73
70
72
90
77
75
77
78
77
77
72
69
72
74
71
72
72
79
/7
76
60
73
72
73
71
69
78
60
60
62
62
62
60
61
60
60
57
58
60
59
59
57
55
51
55
38
32
40
60
60
57
56
56
57
56
58
59
56
58
56
57
58
5
5
3
6
7
7
"5
4
6
5
5
5
6
3
5
5
4
4
6
4
4
3
2
4
" 3
It
3
5
" 6
6
3
5
7
4
7
0
5
' 4
3
S
3
3
6
8
4
4
6
3
' 4
4
4
6
3
.1
l'
M
:?l
.1
i
i',
-------
»«^«
OB3
160
'161
162
163
164
165
166
167
166
169
170
171
172
173
174
175
176
177
176
179
180
083
1
2
3
Cj
6
7
6
9
10
11
12
13
14
15
16
17
IB
20
21
22
23
24
25
26
.T, ..,..*,. ..„,.,,*,
OAit " "STATIC
60)010
60)UI1
601014
60)0)3
6010)4
66)015
601016
601017
60]OlO
601019 . _
6«lo20 .
60102)
601024
661023
601024
60(025
60102<> j
60)Q2/
60)U20
601029
60)030
. 601031
DATE STATIO
600501
600504
600503 '_ _
60Q50'!
600505
60Q506
600500
600509
600510
600511
6005)2
600513
60Q514
" 60051S
60Q510
6005)7
6005)0
6805)1
6BQ520
6805<»l
600522
600523
600524
600525
600520
60Q527
•v.rrp**»*«
1* * MOX
,16
. ,13
,03
,09
,10
,09
.11
,21
',25
!so
.".. 120 .
,33
!l5
,04
,04
M hUX
2 ,06
2 ,07
2 ,06
2 ,09
I ,05
2 ,07
2 ,07
2 ,04
2 ,02
2 ,02
2 ,01
2 ,01
2 ,02
2 ,09
2 ,11
2 ,24
2 lie
4 ,10
2 ,10
2 ,05
2 . ,09 .I
2 ,07
2 ,10
2 ,15
2 ,20 .
2 ,26
NO
(6-9)
.013
,023
,010
,010
,0)0
,010
.017
,U20
,043
,050
,040
,040
!l30
,010
,087
,*017 . .
,190
,030
,030
,0)0
. . .... "c;
NO
(6-9)
.040
,043
,060
,020
,0)0
,040
,100
037
,060
,010
,010
.030
,050
,073
,067
!l5»3
,033
,037
,063
I053 .
,907 ... .
,060
,057
,047
,067
,087
-Nfl" '
MU2
(6-9)
,050
,077
,013
,Q63
Jo27
,037
,03/
,070
,093
!l03
,)40
,130
,047
,100
'133
',!"
,127
,033
,013
f- af *f n
CaL 1U
N02
(6-9)
,067
,075
!o37
,040
,073
,083
,090
,070
,016
,010
,043
,070
,090
,097
,403
,067
,103
,060
,060
!o53
,130
,120
ITATlONsl <
THC
(6-9)''
"2,667
3,000
2,000
2,000
2,000
2,000
2 SoO
4,667
2.333
4.000
4.000
" 5,333
4,333
5.000
2,333
4,667
6,333
5,333
7,667
4,333
2,000
2,000
THC
(6-9)
2.000
2.000
2,000
4.000
4,000
3,000
3,000
3,000
3,000
2,000
2,000
2 ,6b7
4,333
3,66?
4,000
"" 5,667
4,000
3.06/
3,067
3,000
3,000
2,667
3.000
3,667
5.000
4,667
!»•»»»»••
MTEHP
69
69
69
69
66
75
78
63
77
69
67
68
67
73
90
72
69
"67
66
65
68
67
MTEMH
69
66
"65
68
63
67
66
66
66
66
64
63
65
66
70
70
75
73
72
70
69
67
69
73
60
62
SRAP
284
227
377
367
144
403
451
457
370
3H3
309
374
405
3V4
410
308
349
366
312
312
379
206
3RAO
477
305
462
572
364
670
390
707
563
442
656
615
7/4
762
740
714
732
677
722
602
750
720
767
762
709
76J
AH3
_ —
5,0
J'j
i'l
2!*
4,1
?;!•
4)0
s *
V
»,J
ANS
2,2
4,6
9,5
9,6
7,8
9,0
7,6
8,5
6,1
6,9
10,7
9,3
10,1
7,4
.. 5,2
M
5,3
6,4
7,5
)0,6
',1
0,1
6,9
6,7
7,0
5,7
RH VIS
2
4
1
1
IS
15
2 '
." .". * '.. '
8
i
4
7
7
RH VI3
3
S
6
7
9
4
12
10
7
10
12
20
7
6
3
4
5
4
0
. . ... ^ .
6
5
e
6
OPT
57 ~
57
54
55
59
39
39
36
50
56
S3
55
56
4B
57
56
57
57
54
50
54
OPT
' 54
55
54
52
S3
M
53
52
Si
52
46
44
46
47
S3
56
57
59
59
55
54
53
53
52
55
55
NS
5
S
4
11
a '
s
3
6
3
6
6
3
5
3
6
4
9
6
MS
7
6
8
0
5
5
6
3
a
3
6
6
4
5
7
6
5
3
6
8
6
6
7
4
4
7
-------
(JOS
27
26
29
JO
31
32
33
34
15
36
3/
36
39
40
41
42
4J
UU
45
UO
47
40
«9
50
51
52
53
54
55
56
57
50
59
60
61
62
63
64
65
66
6?
66
69
70
71
72
73
in
75
76
77
76
79
OATt
60052H
660529
68Q530
6t>ObM
600001
600602
600603
640*104
60Q605
6 6 0 6 0 o
60QOQ7
bdQoQO
6dQoQ9
6OQ6 ( 0
600611
6006(2
6006m
b0Q6|5
6000(0
66Qo( /
6006(0
6006(9
6rtQo20
600621
600622
600623
60Q624
6»)0o26
600027
6006?0
60Q02')
60Q030
600/02
600/01
*>60704
600/05
600706
600/07
660700
660709
600/11
6007(2
600713
600/14
6007(5
600/10
66o/|7
60 07 1 &
600/19
600720
600721
600/22
600723
STATION
2
2
2
2
2
2
2
2
2
?
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
HQX
• 14
,12
,06
.10
1 12
,16
.16
!o4
,0*1
,04
.04
,00
.14
,11
,00
!l3
Its
,06
.!/
. 19
,14
,23
,06
,06
,06
.12
,07
,04
,06
,09
,11
.16
,13
,16
,07
,09
,25
,26
129
,11
,05
,10
,17
,16
,21
,15
,10
,15
,18
NO
(6-9)
,067
,045
,010
,073
,047
.01*
,030
013
,073
,113
,020
,010
,073
.140
,043
.137
,043
,040
.053
,077
,100
,093
,090
,043
,010
,030
,040
,U63
,OS7
,020
,010
,093
,110
,037
077
!l30
,060
.140
,090
,123
,173
,050
.013
,070
,070
,120
,065
,097
,113
1037
,117
107
— 2
(6-9)
,073
,085
,017
.077
• 120
,023
,103
,043
,060
,080
,040
,040
,140
. 3?3
,(03
Jo93
,09}
.153
,107
,237
,300
|4lS
,093
,040
,020
,070
,074
,067
,010
|017
!l20
,0o7
,090
,067
,047
,0/0
,153
',150
,020
,010
,017
,063
,»o
!»'?
Job/
1 23
,110
THC
(6-9)
3,333
3,000
2,000
3,333
4,000
4,000
3,000
3,000
2,000
2,667
3,000
2,000
2,000
3,333
5,667
3,000
4,66/
3,000
3,000
3,313
3,000
4,000
5,000
7,000
4,667
2,333
2,66/
3,000
3,000
3,000
2,000
2,000
3,000
4,667
3,667
4,000
4,000
4,000
3,333
3,667
4,66/
5,667
2,000
2,000
2,000
3,000
4,667
5,333
4.667
4,667
3,667
4,000
5,000
MTEMP
78
72
69
71
70
70
72
66
69
70
66
69
70
73
71
74
74
77
73
68
71
71
70
72
71
71
70
67
66
67
69
72
60
72
67
60
66
73
73
75
78
75
71
72
73
71
71
68
71
76
72
72
76
SRAO
736
650
293
657
663
"" 632
545
746
728
711
556
678
734
774
752
•52ft
650
342
2/8
215
245
613
631
708
700
660
195
426
443
719
761
737
722
703
552
606
' 710
696
673
652
677
662
66}
AHS
,6
.4
,6
.0
,9
"-- 5«6.
8,9
6,1
6,7
'.lo!3
9.1
6,5
5,0
6,6
6,2
8,1
7,9
8,6
7,0
6,1
5j7
9,9
9,5
6,4
81
8,9
3.9
8,5
6,5
6J5
7*,!
8,3
9,0
9,0
9,0
2,6
3,7
4,0
8,0
8,0
7,3
7,5
92
79
81
BH VIS
' 5 "
. ^ . __
7
6
)
.". """_ *
~
7
20
a
to '
a
6
s
4
2
3
- k
' ' A
2
2
4
2
1
4
1
3
2
3
"4
8
3
3
a
i
3
2
3
3
6
7
5
7
10
2
I
2
"
~ "5 "" "
2
3
• A -
DPT
59
56
55
56
57
SB
59
SB
S3
48
S3
51
S3
55
57
57
59
59
SB
56
56
55
5B
59
61
59
57
SB
57
57
57
55
55
58
S9
59
59
60
61
62
62
61
59
57
56
SB
59
60
66
61
62
61
61
»-»B»0
. *»
9
e
a
5
0
n
J
6
11
•
2
5
9
3
a
6
6
4
a
0 "
5
3
5
4
5
3
II
7
3
6
4
7 ~
3
5
8
a
H' " '
a
3
2
2
6
4
4
9
s
' a
a
5 "
a
5
5
3 '
I
1
- I
-r
-------
OB 3
60
61
62
65
84
85
86
67
86
89
90
91
92
93
94
9S
96
97
96
99
too
lot
102
104
105
106
107
108
109
UO
11 1
112
113
114
115
116
117
11»
119
120
121
122
123
124
125
126
127
120
129
130
HI
OAT£
66Q724
600725
600726
6HQ/2/
60Q720
600749
600730
600/51
660(101
68QU02
6000Q5
660004
600005
60Q007
60Q00U
680009
60QU10
6000U
60001 ^
600015
66n6l't
60Q<>15
600016
660017
600010
60Q020
600021
6«002«J
600025
600024
60Q025
6
6000 2 7
600020
600*2''
6dOh30
6&0031
600901
6009Q4
60Q905
60Q9Q4
6009Q5
6009Q6
600907
6009Q8
60Q4QV
600910
6609(1
6HQ912
660913
6809)4
600915
600'Ho
'STATION
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
i
2
2
2
2
2
2
2
"2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2.
2
2
2
2
Z
2
2
HOX
,09
,11
,20
,09
»09
!lO
,06
,15
,19
,16
J4
,14
,10
,09
, 1 1
,09
,05
,10
,15
,06
,06
,10
,04
,05
,09
tl7
,21
, 12
1 22
, 1 t
l 32
1 "
" ,09
,08
,15
.11
,06
,11
,22
,25
,31
,20
,40
, 17
1 16
, I4
• 15
,06
,05
, 14
NO
(6-9)
,050
,070
,067
,077
, 103
,140
,067
,090
,067
,030
,020
,110
,105
,107
,167
,04'
,020
,077
,025
,105
,050
"• ,010
,087
,050
• 17 1
103
,097
,090
,127
,223
, 31 3
.153
,125
,053
,053
,020
,050
,140
.2/5
,3 1U
,049
,473
,267
,407
Io7U
. ,01U
,C»10
, 157
N02
(6-9)
,027
, )47
,110
,080
,073
, (57
,055
,123
,075
,070
,050
,087
,12V
.103
.185
,053
,020
,055
,0^0
,QNU
. ,060
,025
,OJ/
,010
,045
,065
' , 1 2 0
,063
,065
,055
,095
,060
,050
,035
,o«o"
,020
,045
,063
, 1**0
,065
,020
, 09f
,060
,053
,000
.027
,01*
,020
,040
5TATION?2 •»«••*»
(6-9)
5,000
5,66f
4,000
3,535
4,000
4,66/
5,535
2,667
3,000
5,000
5,000
3,000
5,000
5,667
5.000
3,000
2,000
5,667
2,533
2,3i3
t • •» t
2,667
2,000
2.533
2,000
2,000
3,00(1
2,667
4,667
4.335
4,000
4,00V
5,000
4,667
4,000
2.667
2,6t>/
2,000
2,000
3,000
4,000
0,000
5,667
5,000
8,000
5,667
3,667
4,335
3.000
2,000
J.335
3,000
EMP I
77
72
74
72
72
60
74
74
77
73
72
72
71
73
71
74
74
74
70
73
73
70
73
72
73
70
72
90
77
75
77
78
77
77
72
69 '
72
74
71
72
72
/5
77
78
80
77
73
72
73
71
69
74
5RAD
656
703
69Q
559
293
542
655
647
656
501
631
612
612
654
700
605
589
640
446
514
589
5o6
323
545
91B
646
702
669
663
625
652
5>>2
651
596
571
5/4
305
496
456
551
394
562
564
503
583
597
591
606
555
440
349
242
sto
AHS
" 6,5
6,7
7,6
8,3
8,9
6,4
97
?|6
0,1
6)2
10,5
8,4
10,4
10,8
8,9
6, 1
6,9
' 9,9
5,7
6,6
7,3
8,5
6,1
9,8
11,7
7,2
b|«
eja
6,5
5,9
6j3
" 7,7
5,5
2,7
b>*
9l7
7,1
7,2
6,7
6,7
7,3
8,5
7,2
6,5
4,5
5,9
5,0
RH VIS
6
2
5
10
s
r
... (ft
7
4
4
^
i
i,
i
10
7
3
S
S
7
6
4
S
10
6
0
is
10
25
1
-------
OBS
)33
1 14
135
130
137
13*
139
140
141
112
143
129
6b09iU
hhtOOl
6H1UQ2
601003
6U1 00*4
60} QOb
6810Q6
681UO/
6blOQ8
68 100')
6610JU
6^1011
601012
68| 01 3
60101 <4
6'i| 0|5
601 did
61IJUIO
60(01*'
601020
601021
601022
601 02 >
601024
68102:*
6*»102*»
60|027
6d|02b
601029
681030
681031
STATION
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
•e
2
2
2
2
2
2
2
2
2
2
2
2
2
HOX
,04
,05
• 1 2
,1'
,11
,22
',30
,19
,07
,03
,04
,03
,06
,o/
c 08
,18
ill
fou
,09
,09
• 1 *
,15
!o2
,03
,13
,10
,15
, 1 2
,22
,20
|22
,24
, 2 /
, 16
,17
• 11
,03
,03
NO
H W
(6-9)
,020
,083
,137
,073
503
,255
,253
,430
,140
,017
,010
,040
,220
, 103
,193
,133
,010
,030
, 123
,110
1 1 70
,240
,027
,073
,0«0
,057
,3SO
\M
,120
|207
,553
,363
,46/
,280
',197
,127
,073
,063
2 THr
(6-9)
,040
,047
,037
,037
,077
,050
,063
, j33
,030
,010
,020
,040
,027
,023
,037
!o33
,063
, 0&7
,063
,057
,080
,067
,033
,030
,097
,047
, 170
,113
, 1°3
,J5'/
,253
!io7
,280
• HO
Il07
,013
,017
(6-9)
2,333
3,000
2,067
4,000
5,000
4,000
4,6b7
9,3i3
5,667
3,000
2,000
3,000
3,000
4,000
3,333
3,667
4,000
3,000
2,333
3,333
3,000
4,000
4,313
3.000
3,333
2,333
2,000
4,333
4,000
5,333
4.333
8,000
5,000
4,500
3,000
5,333
0,000
5,000
5,667
3,000
3.000
4,333
MEMP
" 68
"" 70
71
76
85
91
87
70
70
70
70
68
68
68
70
69
69
67
70
69
o9
69
69
69
69
66
75
78
77
69
67
68
67
73
90
72
69
67
66
65
68
67
5RAQ
j9j
501
532
55J
561
562
543
496
43)
337
174
|99
134
260
404
243
370
110
38J
430
313
2d4
227
377
367
142
40j
451
3/0
383
389
374
405
394
418
308
329
366
312
312
379
206
AW3
"75
*!°
48
*!<
1 "
4,9
7 ',6
3*°
0,1
7,0
s|o
1
7,1
b|a
• '
' 8,'S
3,7
3 0
O
43
4,9
0(2
4 5
2,6
6 3
4,9
6,2
7»2
42
40
5,6
8,6
£1*
VI
' • 4
4,? ..
RH VIS
"~ 5
b
6
9
12
20
" J , 7
1
2
10
io
8
4
a
2
2
1
" 4
6
3
4
2
' 4
t
" 1
25
IS
|5
2
1
a
i
4
7
7
OPT
~ 57
~ 55
51
55
38
32
40
60
60
57
56
56
57
56
58
59
56
58
56
- 57
58
57
57
54
55
' 59
41
39
36
58
56
53
55
56
48
57
56
57
57
54
58
54
MS
7
- 4
7
0
S
4
J
S
3
S
6
- fi
' 9
' 4
6
3
4
a
4
" 6
3
S
5
- 4
S
It
15
4
3
S
2
6
3
6
6
3
S
3
6
4
9
&
-- - --i!
-------
Data Listing (May thru October, 1973)
OU3
I
2
3
4
5
6
7
6
9
10
II
12
13
14
15
16
17
jB
19
20
21
22
21
24
25
26
27
28
29
10
11
12
11
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
SO
51
b2
S3 "
DATE
730501
730502
730508
730509
730510
730S1I
730512
73051)
730S|4
730515
710516
710517
730518
730519
710520
730522
7)0521
730524
71052S
730526
73U52/
7)0528
730529
710530
730511
730602
730001
730604
730605
730606
710609
730610
730612
7)0622
730623
7)0624
7)0625
730626
/30629
7)0630
730701
730702
730704
7)0705
710709
730710
730711
710713
7307)4
730715
730716
730717
730718
STATION
3
3
3
3
" 3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
'3
3
3
3
- 3
3
3
3
3
3
3
3
3
3
3
. -3
3
" " 3
3
3
3
" ' ' 3
3
3
" 3
3
3
3
3
3
3
3
3
3
HOZ
,09
,07
,'os
,05
Job
,U5
,04
,07
|04
,09
,04
,08
. ,01
,04
,01
,02
,02
,04
,06
Jo6
,11
,10
',07
,07
,10
,09
,08
Il2
,17
,07
',09
J06
!oe
,12
>
Jio
,06
,10
,09
,12
" NO "
(6-9) ,
,003
,000
,010
,000
,000
,000
,007
,005
,000
2
(6-9)
THC
m- -
,047 0,933
1.200
,043 0,Bo7
,093
1,100
,030 ' 0,931
NMHG
(6-9)
,200
,031
,100
,067
,267
,131
,040 0,900 ,131
,013 0,800
,100
,125
1,433
1,133
,053 _ .0,900
1,100
0.967
1,767
1,067
0,900
,000
,000
,000
,000
,000
,000
,003
,000
,000
,000
,000
,000
,010
,010
"
,000
,000
,000
,003
,010
,000
,000
,003
,000
,007
,000
,000
,007
"
1,667
1,300
1,113
1,033
0,967
,047
,023
1,000
1 ,467
1,150
,027 0;900
,027
,043
1,433
1,033
,040 0,900
0.800
,030
,077
,100
,045 ~ '
,033
,027
,047
,080
,010
,030
,067
,043
,047
,030
,020
,040
,000
,033
.233
,500
,867
,633
,331
,311
,767
,700
,400
,111
,733
,567
,433
,431
,467
,000
,167
,067
,000
,000
,000
,167
,000
,000
,433
,000
,000
,000
,000
,000
,100
,000
,000
,067
,090
,000
,000
,000
,133
,500
1933
,531
,131
, 1 -*3
,100
J400
,1*7
,167
,400
,231
,413
,000
,033
MTtMP
7»
61
60
76
61
77
71
66
66
66
60
62
63
74
65
77
65
60
Sb
56
50
62
81
" 80
73
62
61
89
86
85
90
' ' 89
86
60
- 83
' ~ 84
85
84
62
85
* 64
76
69
85
91
90
83
90
91
80
84
60
65
3RAO
" 379
500
116
459
58V
656
512
514
342
394
731
" " 256
51 7
b63
142
638
122
56
86
93
59
28b
508
556
" 461"
711
439
561
b/9
" 489
629
60?
592
337
410
611
552
408
884
686
487
300
60/
567
588
505
501
656
599
571
403
AWS
— ~ «.9
1IJ9
9,2
5,2
9,6
11.8
- 5,6
3.6
4,1
8,2
5J5
6,2
6,0
2.7
5,9
0,7
5,0
a, 2
76
7,5
13,6
2,6
' 7j4
0,9
1,8
3,8
55
7,6
7,7
3,3
7,9
3,1
25
37
2.5
8,0
3.4
3,5
4,9
4,4
5.9
3,4
3,4
6,9
|0,3
3,5
2,7
6,5
3,1
1 •
5,3
RH
- -5,
66
66
71
39
65
41 •
45
44
39
36
60
39
16
70
19
90
93
96
96
96
69
69
SO
SO
43
56
54
59
71
65
57
72
56
74
55
61
63
53
41
69
79
61
53
50
54
74
42
57
85
49
56
65
VIS
10
10
lo
13
IS
20
20
20
20
15
eo
10
20
20
6
12
2
1
3
3
2
12
20
12
IS
15
7
10
10
10
20
10
12
12
'5
5
4
5
12
12
*6
4
12
10
'3
1
S
20
12
5
12
10
7
DPT
" 51
59
57
62
54
51
• 46
46
4b'
40
37
48
33
4S
57
50
60
56
SJ
51
b4
71
66
59
53
57
60
74
70
66
71
69
71
61
69
64
66
67
62
56
68
71
68
66
70
71
69
64
70
U
63
63
66
HS
5
12
12
6
12
6
14
6
5
13
»J
li
8
6
(0
s
7
" 9
S
6
10
10
4
ll
7
3
to
1
10
10
s
6
6
*
5
6
7
7
5
4
4
7
8
7
7
6
IS
S
6
r
0
6
-------
033
54
Sb
57
56
59
60
61
62
63
6b
66
6/
69
69
70
71
72
73
74
75
76
77
78
79
80
82
83
94
Bb
Bb
87
88
69
90
91
92
93
94
95
96
9 7
~ i
96
99
100
101
102
103
104
105
106
DATE STATION
730719
9 I A I a A
1 iO 1 cO
730721
730722
730/23
730724
730/25
730/26
730727
730728
730729
730730
730731
730801
730602
7306QJ
730804
730805
7 .10806
730807
730808
730U09
730810
7308]|
730612
730813
730814
730815
73Q6ib
7308)7
7306(6
7306|9
730820
730822
730823
730824
730825
730626
730629
730630
730641
730901
7309Q2
7309Qb
730906
730907
7309Q8
730909
730910
730912
7309J3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
1
3
\
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
not
12
1 1 e
,10
,*06
,09
,13
,06
fl°I
Io7
,H
,'06
Jo5
,08
,0o
, 12
1 09
,H
,10
111
,11
,04
,08
,12
,08
,06
.13
1 •
,11
,09
,12
,19
,16
111
,06
,07
,09
,06
,06
,08
,08
,07
NO , N02
(6-9) ' (6-9)
.
,007
.000
,000
,000
,000
,000
,020
,030
,000
,000
,003
,003
,000
,013
,050
,020
,027
.017
,000
,003
,003
.003
,000
,0|0
,013
,013
,010
,000
,003
,030
,013
,027
,037
,000
,000 .'
,040
- .
,013
,030
,070
,100
,040
,047
,040
,040
. ,01? .
,063
' ,'"77
,027
,027
,093
,080
,073
,060
,033
,020
,010
,023
,000
,033
,077
,053
,033
,033
,057
,073
' ,047
,057
,000
• • ,000
,073
7/pQV rif1^ MUrlp
_
l.bOO
1,333
1,53}
1,300
1,633
2,233
i, too
1,600
1,533
1,433
1,400
1,467
1,400
1,333
1,167
1,467
1,367"
1,433
l,bOO
1,467
1,400"
1,233
1,233
»,767
1,467
1,633
1,600
1,367
1,467
1,600
i, "7
1,467
I, bOO
1,400
1,433
I,b33
1,600
1,833
" ,167
,033
,167
." " .°o? _.~
-. t*»*
,467 "-
I"* '
,200
,133
IOOQ
_. . ,U3
,067
,167
,200
,167
,100
,000
,167
,0b7
,167
,133
,000
;o33 -••
,000
!lb7
" ,100
,200 "
,200
,300
" ,500 ' ^
06
88
82
73
64
76
87
90
66
64
66
66
85
60
86
87
66
69
90
65
80
62
60
BO
62
/fl
77
83
81
95
92
92
92
91
68
68
64
85
60
78
77
83
79
78 '
8RA0
" ~ 66 1
"" 426 ""
263
101
506
573" "
367
526
579
593
572
615
510"
202
409
320
' b83
b6<|
SOS
516
474
" 529
- 528 -"
344 """
266
336
510
301
311
" 398
468
579
523
385
523
b66
521
547
367
482
68Q
273
561
466
313 ~
" 562
506
AHS
8,2 "
5,2
1,5
5'5
2!*
6,9
6.3
5,9
5,5
7,0
1,0
3,1
5,6
s!2
3,9
3,0
3,7 -
6,6
2!2
3,0
6|3 "-•
2,'3 ~
3,2
2,1
sjs
2,9
3,9
2,8
)0,2
3,3
3,0
6,0
6,5
2,2
2,0
5,2
3'6 ....
ijo
4!?
5,2
2,8
5,3
ill
ll*
1,1
42
6S
90
87
82
49
64
77
48
46
56
43
69
77
70
60
61
35
61
67
69
65
54
52
45"
79
74
53
71
69
65
55
58
45
53
67
61
46
52
54
68
56
63-
74
77
47
45
55
40
52
47
52
"'"»"_'"
IS" "*~
7
3
2
2
. i". 10 in"
_ ... . 8 . ..
is
10
12
_.. u
4 ""
-- - (, -••-
10
'6
6
20
-_-_; i ~.
5
5
~" 6 — '
8
5
12
'8
5
- e -
t ~"
s
14
20
7
_".." 4__L
12
'7
8
S
6
~ fl
2
4
15
IS
20 ""
40
15
20
" is -"
•••»•
M"~
"71
73
69
70
6l
"6$
72
68
frS
61
71
72
63
67
bb
67
69
69
71
72
69
66
67
72
71
65
68
68
67
64
61
52
64
69
75
69
72
72
74
73
71
b?
56
57
49
56
55
58
"i*
' " n
6
6
'.'.'. *
It
- - a
8
5
6
5
4
- 9
3
7
" -5
8
S
4
12
9 '
•- - 6
4
S
8
6
9
7
8
14
6
B
12
6
5
B
S
b
fl _
6
8
'•9
6
' 5 -
"7
7
6
-------
OBS
107
106
109
110
111
112
113
114
116
117
118
119
120
122
123
125
126
127
126
12*
130
131
132
133
134
136
137
130
139
140
141
| £1 3
142
143
|44
145
DATE
730*14
730*15
730*16
730*17
730*20
730*21
730922
730923
730925
730*26
730*27
730*28
730*2*
730*30
731001
731002
731003
731004
731009
731010
7310U
731012
731013
731014
731015
731016
731017
731019
73|02Q
73J021
731022
731023
73(024
731025
73|026
1 I i n a t
731027
73l02d
731030
731031
" "STATION
" • 3
3
3
J
3
3
3
3
3
3
3
3
3
3
3
3
3
3
"" 3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
"~ 3
' 3
"3
3
3
Kl/t ^^*/»
(6-9) - (6-9) _"(6-9) -
,*07 .010 " ,033" " ,*333
,07 ,000 ,020 ,467
,02 . ,433
,06 ,0}0 ,040
,01 ,600
,06 ,020 ,057 ,533
,04 ,013 ,047 ,400
,04
,08 . . .1,367
.06
,02 ,035 ,150
,03 ,063 ,073
.05 ,027 ,053
,04
.02
,06
,06 ' _"•._•. -
Jo5
,03
,05
,06
,04 • --..
,05
,03
,02
.. ,03
,03
,04 "
.05 - •"
,06
.07
,04 _._
•u; - " "."...••••
,04
" ,03
,01
,01
NMIJC MT
(6-9)
,300*
,067
,06/
,233
,267
,100
,100
,067
. - - .
. . .
"" ~ ""
EMP
73
79
71
75
61
79
63
69
73
03
02
63
72
71
71
62
66
74
64
72
73
73
n
67
57
59
M
62
65
69
72
72
/s
69
65
46
63
SRAP
75
333
323
450
139
326
337
126
245
216
204
422
276
62
343
379
06
276
144
379
361
" 415
392
430
413
. 371
326
310
316
359
326
347
62
UO
254
AH3
3,6
2,3
3,'7
4,2
3,*8
7.1
1 , •
3.9
6,5
2,6
4,4
I
7,0
3,6
0,8
• 1
S, 1
.. 3,5
3,'o
4,3
7.0
1 | V
6,0
10,9
9!7
9,2
1,8
• 1
3,9
2,3
1.0
2.7
4,6
5,1
4,4
f
io!o
3,3
6,6
RH
87
60
56
61
61
n
67
76
79
71
61
100
67
59
57
97
60
67
87
71
73
55
32
46
43
51
62
44
54
54
100
55
67
43
63
76
96
63
•?»-»-»
VIS
2
6
10
F "
15
i2
io
"5
12
5
7
14
"7
12
20
20
2
15
10
io
'7
6
10
I V
io
20
40
20
20
'20
15
15
1°
6
4
9
10
'9
12
i5
.•,«..,..
DPT
66
6] •
56
54
54
52
67
66
60
67
60
55
53
67
66
66
62
63
54
57
J f
56
41
46
3S
40
50
43
45
47
S3
49
46
49
54
02
«7
....
NS
7
4
9
15
10
is
s
5
4
9
6
7
a
S
6
4
1 0
» v
o
13
14
ll
12
7
6
4
3
7
6
10
9 *
9
14
6
-------
NO
OH3 DATE
1 7JOSOI
2 730502
3 7JOM4
4 730515
S 710516
6 730517
7 730518
6 /3V519
9 710520
10 7105*2
11 710523
12 7105*4
ll 7105*5
)« 7)0546
15 730"5*7
|6 710528
17 7105*9
16 71i)S10
19 /3051J
20 710602
21 710601
22 710604
23 710605
24 710606
25 7106U9
26 710MO
n 710611
*8 714612
29 710611
30 710614
11 71061S
32 7306)6
33 730o|/
14 710M8
15 710619
36 730620
37 /10*2l
38 730622
39 730704
40 710705
4| 710709
42 730710
43 7307)1
44 710712
45 710713
46 73071U
47 710715
48 /10716
49 . 730717
50 730718
SI M0719
52 710720
S3 710721
STATION
~4
4 "
4
4
4
4
4
• n '•
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
U
It
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
U
4
tt
4
MUZ
07
,07
,04
,04
,06
,06
Joa
,02
,06
,00
I00
,02
,01
,'07
, 1 j
,04
.10
,11
,10
.10
ill
,06
,11
|09
|06
f 12
,06
.05
!oi
,10
,09
,06
,10
,06
|io
,06
,03
.12
.U
,04
,08
,07
!io
Jos
NO
t»**
(6-9)
,09fl
,030
,012
,023
,020
,030
,003
,003
,003
,020
,037
,007
,003
,005
,003
,000
,000
,000
,000
,000
,000
,000
,007
,000
,000
,001
,000
,010
,007
,007
,000
,000
.007
,350
,000
,000
,000
,000
,000
,000
,003
,000
,000
,000
— 2 - TRC
(6-90 . (6-90
,160" "
• H3
,137
,070
,090
f 050
,060
.027
,030
,020
,041
,011
,091
,070
,110
,091
,040
,023
,021
,061
,053
,017
,010
,093
,030
,02J
,047
,040
,077
,053
,057
,053
,047
,107
,077
,050
,057
.020
,040
,060
,0/7
,121 2
,0/3
,047
,040
,700
,voo
,713
,367
,467 "
331 . .
!'3S
,667
,400
,213
,950
,533
,467
367
,3J3
,700
,700
,400
,000
,800
,100
,900
,433
,313
|'/ 00
,500
467
1767
,500
,600
,611
,400
,733
,600
,500
,700
,150
,767
,413
,213
,'lll
,400
,467
,400
V .
,600 "
,667
,400
,333
NMHC
*T**»***
(S-9)
~~~ —
0,400
0,233
0,167
0,000
o.ooo
0,000
0, 1 JJ
0,011
0,067
0,513
0,450
0,131
o,oll
0,000
0,000
0,207
0,|00
0,233
0,267
0,100
0,067
0,167
0,200
0,100
0,033
0,200
0,000
0,133
0,06? -
1,467
0,267
0,000
0,000
0,000
0,000
0,033
0,867
0,133
0,033
O.'OOO "
MTtMP
" 76
61
66
66
66
- 62
63
7<|
65
77
6*
60
' si
" 56
56
82
81
80
73
82
61
69
66
8b
90
89
90
68
85
82
81
62
73
69
75
65
66
" 60
6V
65
91
90
63
76
90
91
80
84
60
' 65
66
86
62
SHAD
379
500
342
394
731
256
" 5|7
563
142
6ia
122
56
66
""" 93
59
265
556
461
71 1
439
561
579
469
629
" 607
596
592
609
759
706
' 329
161
127
2 6 to
516
334
"• 337
607
567
588
505
501
732
656
599
571
* 403
" " 562
66)
428
264
AH3
~~" "4,9
"j j f 9
4, 1
62
. 7,«
X2
6,0
27
«jt9
0,7
"" e,'2
~ 7,6
1 3,**
2,6
7 4
" 0,9
1,6
b,b
7,6
7,7
3,3
7)9
7)6
• g t>
6 S
b(Q
7.4
7,2
3, 1
4,4
',
3,4
3,4
6 9
7 ,7
10,3
3,5
2.7
... 5!»
a§2
b 2
1,5
."". *M
59
-" 66
46
54
39
60
35
"~ 36
93
39
93
67
" 96
90
96
62
69
SO
93
50
56
54
72
87
' 6*
57
59
72
6J
' 3S
34
" 72
61
90
64
76
77
56
61
S3
63
61
56
44
43
48
65
51
82
- 65
62
5b
90
via
10
— - Jo
15
10
" 20
""" 10
'" 40
20
5
12
1
i
~ 1
™ 7
2
15
20
12
..'.. 20
6
10
6
10
20
— 10
'5
12
7
" "40
" 20
5
4
3
5
3
5
"12
12
10
'3
5
5
~ 20
20
10
'5
15
- y
10
7
3
". ". ?'T
51
59
44
49
J&
<|6
IS
• " ft!
S4
SO
" ' 59
5S
~" 51
" 53
54
75
" 66
5V
" 56
• 57
64
70
' 7d
~" 67
" 7t
"• 69
7i
73
67
Si
50
' 71
61
62
62
bb
" 72
63
66
66
73
74
65
46
61
66
72
63
~ " 69
" bb
bb
1*
~ Mj - ---
5
""II
S
9
•"" 8
g
0
g • ~~ :
9
tb
" 5 "
8
~" 6 "" "
4
l9
10 '
4 ^
6 " ~ '
5
10
10
g ""
15 "
$ -
7
- g
6
~" 10"" '~ "
u
s
9
& '
$
. -
7
6
s
5
10 '
12 -•-
11
9
6
B
7
6 "
7 '
6
" &
-------
r***«
DBS
54
55
56
57
58
59
60
61
62
63
bi
62
63
da
05
6b
67
68
69
90
91
92
93
9(1
95
96
97
96
99
100
101
102
103
too
105
106
DATE
"730722
730723
730724
730725
730726
730727
730728
730729
730730
73073)
73060)
730603
730804
730«05
730606
730807
730606
730609
7306)0
730811
730612
730813
730814
730815
730816
730817
7308)8
7306)9
730620
730621
730622
730823
730824
730625
730826
730929
730630
730831
7309Q)
7309Q2
/10903
730904
730905
730906
730906
7309)2
7309)3
7309)4
7309)5
7309)6
73)002
7310U3
731004
"STATION
4
" " 4
4
4
4
4
4
"' 4
4
4
4
4
4
4
4
4
4
4
"4
73
,123
,075
,050
,0"3
,053
,375
,137 .
,140
(IS)--" (25>- MTtMP 3K4D
,500
1633
,667
,533
,400
467
,667
,533
,700
,367
,600
,650
,700
,500
2,767
2,467
2,067
1,733
1,767
1,500
1,967
2,033
1,433
1,733
1,633
1,567
1,733
1,600
2,400
1,600
1,533
1,400
1.967
2,167
1,600
2,533
3,400
2,4o/
1,567
1,467
3,100
2,733
1,500
2,033
1,600
1,433
1,400
2,000
2,300
2,633
4,300
,033
II"
,100
|0&7
,100
" ~ ,033 '
,000
,033
,400
|0?3 I._ .
,200
,000
,000
,000 _
. - |J9P .
,000
,033
,100
,033
,367 ~
,833
,400
,000
,000
,500
,033
,1"
,033
,033
,000
,100
,067
,067
,700
73
64
64
7tt
67
90
66
64
66
80
ei
60 *
86
6/
66
8?
89
91
"91"
90
90
65
80
85
85
82
60
80
82
70
76
77
83
61
95
93
92
92
92
9)
91
86
66 "
64
60
79
78
73
7V
81
71
81 .
62
101
506
573
367
526
579
593
572
615
510
202
320
583
651
564
505
562
516
474
529
520
344
286
338
510
301
311
390
(166
92
512
579
523
365
523
566
52 1
547
519
367
471
462
660
273
468
506
305
75
333
465
62
343
379
AMS
• 5,6
2,9
2,5
«,9
»,3
5,9
5,5
7,0
1,0
5,1
5,6
3,2
3,9
3,0
3,7
6,6
5,4
2,2
1,0
0,3
3,3
2,3
3,2
. 2,1
«,5
3,5
2,9
3,9
. 2,8
tt,2
10,2
3,3
3,0
6,0
0,5
2,2
2.0
5.2
3,6
*,3
»,9
. 3,0
5,4
",5
2,«
1,5
1,1
3,6
2,3
1,7
0,6
. 5,1
3,5
RH
87
51
49
69
77
63
" 48
49
(16
69
79
60
61
35
51
67
69
47
70
44
50
53
79
74
53
63
69
65
55
93
" 66
45
53
67
56
46
52
54
54
56
54
77
74
77
45
47
52
87
60
44
97
93
58
VIS PPT
._ . 2 _..
8
10
15
6
10
10 "
io
12
4
6
6
6
20
7
4
5
4
a "
10
12
12
5
._ 12 .
6
6
8
6
5
4
15
20
7
4
4
12
'7
8
5
6
4
5
2
4
15
?0
is
2
6
12
2
8
12
67
64
63
6)
7*
72
66
63
62
71
73
6i
6?
55
66
64
69
68
74
65
66
66
73
71
65
67
68
6/
64
67
61
52
64
69
74
69
72
72
73
73
72
72
73
71
56
55
59
68
63
57
67
67
66
MS
7
8
7
11
a
8
5
9
4
4
s
7
5
8
5
8
5
4
" 5
10
4
5
7
S
a
5
9
7
a
10"
10
7
6
8
9
»
3
6
6
6
6
5
6
a
6
6
7
7
4
5
4
b
6
-------
303
107
106
109
110
111
112
1)3
114
OdS
1
2
3
4
5
b
7
8
9
10
11
12
13
14
15
16
17
I*
19
20
21
22
23
24
25
26
27
26
29
30
31
12
33
14
35
36
37
38
39
DATE STATION
731009 4
731010 4
731011 4
731012 4
731013 4
731014 4
731015 4
V31016 4
731017 4
DATE STATION
730SOI b
730-J02 b
730508
730509
730511
730512
730513
730S14
730blS
730516
730517
710518
730b|9
7305^0
7 3 'J 5 t. S
73057
7105^8
7J05
430
413
SRAl)
379
bOO
136
454
656
512
514
342
394
731
256
517
563
142
636
j24
56
" 86
93
59
265
508
55b
461
711
439
561
469
629
CO/
596
592
609
• 754
706
329
181
127
AN3
". 2.8
*iO
«,3
7,0
8,0
JO, 9
9,7
9,7
9,2
AWS
il1!
9,*2
5,2
U|B
*!*
4.1
76
5,5
b,2
6,0
2, 7
5,9
0,7
5.0
7J6
7|s
l3,6
2,6
5,9
7,4
0,9
3 B
is
7,6
7,7
*|4
7)2
7,"
45
8,6
6,9
5,0
RH
87 "~ "
71 '
73
bl
Sb
32
" 03
43
51
RH
59
66
90
71
51 '
34
52
44
39
39
60 ~
39 '
36
75
39
87
96
96 " ~
96
96
69
54
So
53
43
56
65
72
71
65 • "
57
59
72
S3
35
"34 '"
67
90
BU
vts
»••:-
B
10
10
20
40
20
20
OPT
62
63
54
57
Sb
41
52
41
35
M3
b
q
a
9
13
12
11
VIS DPT HS
10 51 5
10 59 12
io
is
15
20 ~
20
20
15
20
10 '
20 '
20
7
12
'2
1
3
3
2
12
20
15
IS
15
7
a
8
10
20
10
5
12
'5
40 " .
20 ""
B
I
5
54
62
52
41
46
Ub
40
36
48
33
43
5?
50
bi
55
Si
53
54
71
63
bO
53
57
60
b*
70
66
71
b9
71
73
66
si
50
70
70
63
7
6
' 10
9
6
5
13
b
' 9
li
a
4
10
4
a
B
s
6
10
12
B
14
a
3
i
Id
10
10
7
6
8
B
9
13
12
5
-------
089
40
41
42
43
44
45
U6
47
48
49
bO
bl
52
53
54
55
56
57
bB
59
60
bl
62
63
64
65
66
67-
66
69
70
71
73
74
75
76
77
78
79
60
61
62
63
84
65
66
87
88
89
90
91
92
PATE
730619
730620
730621
730622
/30623
730624
730625
730626
730619
730630
730701
730702
730704
730705
730709
7307(0
/307M
730712
730714
730715
730716
/30717
730718
730719
730720
730721
730723
730725
730726
730727
730728
730729
730730
730731
730801
730602
730603
730804
730805
730606
730807
730612
730813
730814
730»15
730816
730817
730616
7308|9
730620
730821
730622
730623
STATION
5
5
5
5
b
5
S
S
5
b
b
5
S
b
5
5
s
- 5
5
5
b
b
b
5
5
5
b
5
5
b
b
b
b
"" " 5
"b
5
b
5
S
5
5
b
S
5
b
b
5
b
5
b
._ b
b
HUZ "
|04
,04
,04
0 3
0 i
|06
,06
,02
,01 .
,10
,06
,09
,07 .
"" I0"
,07
109
,06
,'03
,04
,04
,01
,01
. ,04
. ,04
,05
,06
,09
,04
,04
,06
,04
,06
1 04
,04
,07
,07
,08
,05
,09
loo
,05 .
,03
,01
,08
,05
NO
(6-9)
"",007
,04Q
,047
,03Q
,040
,037
,067
,0b3
,017
,000
,047
,060
,000
,003
. ,000
,000
" ,000
,010
,003
,017
,020
,023 •
,027
,020
,010
,030
|010
,313
,000
,043
,505
,303
,027
.010
,ObO
,327
,117
,017
,200
,173
,017
,193 ."
,OOQ
,023
,003
,007
(6-9) -
,013 "
,060
,060
,037
,063
,090
,090
,067
,047
,017
,100
,073
,010
,020
,0b7
,060
,017
,083 " '
,090
,063
,070
,103
,073
,063 "
,053
,107
,053
|067
,087
,003
,027
,115
,040
,027
,023
,120
,10?
,067
,023
,063
,040
,020
,033
,007
,037
,023
,017
•• STAT
THC
(6-9)
l.bbo
2,133
2,300
2,300
2,333
2,600
2,333
2,200
1,633
2,600
2,100
1,600
1,767
1,567
1,433
1,633
1,767
1,700
1,967
2,967
2,100
1,933
1,833
2,000
2,067
1,650
2,167
1,533
1,567
2,933
2,333
1,767
2,033
1,633
0,000
1,250
1,500
0,050
0,367
0,767
0,533
0,467
0,567
0,000
0,533
. . . P.433
0,1*7
0,000
0,000
" 0,|33
0,133
0,ObO
0,267
0,967
0,500
0,467
0,333
0,4<>7
0,533
0,350
0,367
0,000
0,000
0,933
0,533
i 0,067
0,433-
0,200
0,000
' 7b "
65
86
80
el
84
85
84
62
8b
64
76
64
6b
91
90
63
76
91
80
84
80
65
61) '
" 68
82
84
78
67
90
88 '
64
86
66
61
85
80
80
67
66
67
90
85
60
8b
85
62
60
80
70
76
77
SRAD
266"
516
334
33/
418
61 1
bb2 "
406
684
686
467 .
300
607
b67
566
50b'
bOl
732
S99 '
b71
403
b62
661
426 ~
263
bOb
367
b26
b79
b93 "
b72
61b
510
202
409
320
5B3
651
564
bOS
b28
344
286
338
blO
301
311 ..
396
486
92
512
AK3
" 7,4-
-iil
III
3,'4
3,5
4,9
2,9
4,4
7,*7
3,5
2,7
3jl
5,4
6,2
" 5.2
1,5
2,9
$!'
5,5
7,0
1,0
5',6
3I2
3,9
3,0
3,7
6,6
3,3
2,3
3,2
2,1
3|5
2,9
3,9
2,8
to|2
3,3
RH
76"
76
77
69
71
69
' bi -
74
Sb
52
69 '
79
61
53
b2
63
74
44
" 57 ~~
77
51
56
53
62
65 '
77
62
64
77
48
61
54
46
55
79
70
60
61
35
61
67
SO
S3
7*
Sb
S3
71
93
79
67
90
56
4b
VIS
b
3
S
6
4
(1
12
12
b
4
12
10
3
2
5
20
12
12
15
10
"9
10
'7
4
2
20
8
15
'9
12
12
4
b
10
b
6
20
7
4
12
12
b
15
6
5
2
b
4
14
20
OPT
63
66
72
bb
b8
b/
bB
68
64
60
68
71
" " 68
66
71
72
69
46
•~ 70
72
63
63
64
66
71
74
70
bS
72
66
70
63
62
70
73
72
65
67
Sb
67
b9
66
66
73
67
65
66
69
67
bb
bb
61
S>2
-
MS
B ~~
• s
B
9
4
S
b *
7
8
7
ft ' ' '
4
7
6
to
8
12 '
S " '
b
B
a
7
7
7 ~ "
6
3
id
B
6 ; ;
to
ft
b
5
3
5
S
6
3
8
4 ' '
S
7 '
b
6
.
4
7
3
B
-------
033
93
94
95
96
97
96
99
too
101
102
105
104
105
106
107
108
109
110
111
112
1 1 5
1 1 *
115
116
117
110
119
120
121
122
125
124
125
126
127
123
129
130
131
132
133
134
135
136
137
130
1 39
140
141
)42
145
DATE
750024
750026
750029
7500)0
750031
730901
730902
730903
750904
7509QO
7509Q7
7309QO
730909
750910
750^12
750913
750914
730915
750*16
7509J7
750920
7501*?!
730922
730''25
750<«24
7509,Jb
730927
750920
750929
750930
751001
75(002
75IU05
75|004
751010
73(011
751U12
731013
751014
751015
731016
731017
751020
751021
/5lO?2
731025
73JO?6
751027
73(028
'731030
751031
STATION
5
5
5
S
5
5
b
5 '
5
S
5
5
5
b
S
5
b
5
b
5
5
b
b
5
5
5
5
5
b
5
5
S
b
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
b
5
HCU
,09
,09
,08
,*04
,11
,06
,10
,10
,05
,06
,06
,05
,05
,00
,02
,05
,04
,07
,01
,0"
,01
,05
,04
,0b
,01
,05
.02
,05
,02
,00
,02
,03
,06
,03
,01
,01
,03
,05
,02
,02
,01
!o3
,01
,04
,06
,04
,01
,00
,00
NO
(6-9)
,010
|017
J467
,000
,027
,017
|395
,257
,04/
,000
,037
,260
1*27
,030
,000
,045
,075
,000
,000
,000
,100
,033
,055
2
(6-9)
,045
.045
,127
,130
,017
,013
,000
,013
,02/
,070
)017
,000
,020
,005
,000
,000
,000
,033
,045
,007
THC
(6-9)
1,800
2,600
5,000
2,000
1,000
1,533
2,600
2,167
1,935
2,000
1,667
1,667
2,250
2,155
1,600
1,600
1,567
1,333
1,753
2,500
1,567
1,450
1,66?
1./33
1,600
"
NMHC
(6-9)
0,950
1,167
0,200
0,000
0,600
0,067
0,/67
0,«00
0,535
1
0,467
0,033
0,000
0,033
0,000
0,000
0,5i3
0,000
0,000
0,06?
V
0,135
0,000
"
HTErtP
~" '- 03
95
V3
92
92
' 92
'1
08
04
65
00
78
/7
79
/6
73
79
61
/I
75
61
79
05
04
69
03
02
63
72
71
71
02
74
64
72
73
73
77
67
57
73
62
65
72
73
69
65
46 *
63
3HAD
~ 523
523
566
521
547
519
367
471
462
273
561
466
313
562
506
505
75
333
485
525
450
139
526
557
4/9
126
425
2|0
204
422
276
62
345
379
2/6
144
3/9
381
415
592
430
413
371
328
359
326
347
82
" 120 "
2S4
AHS
3,0
6,5
2)0
5,2
". 3!6
1,9
3,0
4,5
5,2
5,3
2,9
111
• • •
3,6
2,3
j,7
3,7
4,2
6,1
9,6
3,0
7| 1
6,5
2,6
?Jo
0,6
3J5
3,0
4,3
f
7,0
8,0
10,9
9 7
9,2
2,' 3
1,0
5,1
4,4
2, a
* 10,0
3,3
6,6
RH
" " 53~
61 "
46
52
' 63
54
56 ' -
93 "~
77
77
41
45
55
40
47
55
67
69
' 44
61
72
01
76
51 "•
93 -
59
67
67
51
too
97
93
67
71
73
73
55
49
46
75
51
44
54
93
100
72
47
76
-- - 96" —
iOO
VJ3. .
7"
3
12
7
5 "
5 ~
6
2 "
S
4
£0 '
20
20
40
20
15
12
12
15
12
10
4
12
12 '
3
15
12
12
20
12
'2
8
10
7
8
10
10
20
40
20
20
IS
15
5
12
"9
15 •"
15
OPT
64
75
69
72
73
73
73
70
72
71
58
57
57
49
55
55
69
63
54
50
52
62
66
64 *
63
67
66
71
55
56
67
67
66
65
54
57
56
50
48
4d
3!»
50
43
47
37
49
4?
54
35
tti>
NS
6
12
b
S
6
' 6
6
3
S
8
6
6
5
7
b
6
7
5
S
9
10
10
a
s
6
7
7
7
8
$
S
4
6
S
4
S
10
9
is
14
S
12
7
ft
4
S
4
9
jO
"5
J
-------
OB3
1
2
3
4
S
6
7
6
9
10
11
12
13
14
15
|6
17
16
J9
20
21
22
23
24
25
26
27
26
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
46
4V
50
51
52
53
DATE STATION hoz
730501 ,11
730502 ' " ,09
7305Q8 ,05
730509 _. ... ,05
730510 ,07
730511 ,06
730512 " " 6 ,06
730514 ' 6 ,05
730515 6 ,04
7305J7 ,07
730516 ~~~ ,04
730519 " ,09
730520 ,04
730522 ,08
730523 ,03
730524 ,03
730525 ,02
730526 ,03
730527 ~ " " ,02
730528 ,03
7J0529 .,06
730543 ,13
73053J " " ,05
730602 " ,12
730603 ,1!
730004 ,13
730605 ,09
730606 ,14
730609 ,08
7306M ,23
730612 ,07
7306J3 ,07
730614 .07
730615 ,10
730616 ,06
730617 .05
730618 " ,02
730619 ' ' Jo3
730620 ,00
73062] ,06
730622 " ,07
730623 ,08
730624 "" " ,0b
730625 ,11
730626 ,06
730629 • ,14
730630 . .. ,11
730704 ,10
730709 ,14
730710 ,13
730711 ,07
730712 ,05
730713 ,09
NO - -
(6-9)
,040
,000
,007
,000
,010
,000
,017
,010
,003
,007
,010
,003
,000
,000
,010
,020
,007
,007
,003
,010
,010
,007
,007
,000
,010
,003
,010
,000
,oop
,000
,010
NO
Station
" 2 THC
(6-9) -(6-9) -
,110 ""
,075 ' " 1,933
,133
,070
,163
"" 0,933 '"
,140 1,333
,310
,160
,110
,000
,000
,067
,090
,043
,027
,017
,003
,023
,093
,047
,070
,027
,033
,030
,010
,010
,057 "
,007
,040
,027
,057
,023
,023
,040
,027
,040
,020
,043
,000
,000
,000
,033. .
2
,250
,200
,200 "
,550
,533
,400
,300
,400
,300
,?00
,267
,067
,544
,133
,600
,600
,600
,443
,400
,700
,400
,407
,444
,600
,400
,600
,534
,500
,567
,467
,843
,467
,343
.343
,400
,643
,600
,667
,343
,633
,4o7
,450
=6=SUIT
NMHC -
(6-9)
...
0,600
0,000
0,000
0,000
0,500
0,500
1,1*3
0,200
0,100
0,000
0,000
0,000
0,334
0,233
0,131
0.100
0,000
0,043
0,067
0,000
0,200
0,150
0,167
0,000
0,033
0,167
0,033
0,233
0,067
0,000
0,067
0,367
o,l oo
0,000
0,033 .
0,067 .
0,200
HTtMH
78
81
60
76
61
77
~ "71
60
66
6
-------
093 D»H 3IATIO
54 7307|4
5b 730T15
56 730716
57 7307(7
56 730/10
59 730/2U
60 730721
61 730722
62 730723
63 73o72<4
64 73072s
65 73o'26
66 730727
67 730/28
68 730729
69 730/10
70 730/3)
71 7ioaoj
72 730611
73 /3fl9ob
74 730906
75 730907
76 710*00
77 730909
78 7309)0
79 7309H
BO 7309|2
8l 730913
82 73Q9t<4
83 730915
B4 730916
85 730VU
Bo 730920
87 730921
6« 730923
89 730*24
90 730^29
91 730)26
92 730927
93 73f)920b
,0o
,06
,07
,07
il*
,05
,00
.04
,06
,09
,11
,00
,06
,03
,07
,06
,100
"
"
,633
9 V*"'*
NMHC
(6-9)-
,067 "
,167
,06?
,100
,100
,767
,100
,167
,067
,167
,100
,?67
1
— ^••5^^?'^
MTEMP
91
~" 80
64
00
Ob
Ob
02
73
04
ttU
7«
07
90
bfl
04
66
08
t»l
92
oa
04
OS
00 "
/8
77
63
79
78
73
79
7| "
61
P4
69 ~"
7} "•
03
82
63
72
71
71
01
02
66
74
64
72
73
73
77 ""
SRAD
"599
571
403
562
428
263
101
506
5/3
367
526
579
593
572
61b
510
£02
547
BttO
•273
561
468
jjj
562
531
S06
305
75
113
405
323
450
139
337
479
126
245
425
218
204
422
276
62
343
379
oa
276
144
179
361
m
A " w
™ 9
2,7
6,5
3,1
5,3
US
5,8
2^
8,9
8,3
5,9
" 5,5
7,0
3,1
5,6
." 5,2
4 ,b
5,2
2,6
5,1
V 2 «
1,3
1,5
s!6
2,3
Il7
4,2
6,1
1 1'
7,1
6)s
2,6
T!O
o,'a
5,1
3,5
. *!°
4,3
7,0
8,0
10,9
9|7
RH \
48 '
' 77 " "
49
58
53
bS
90
87 ' •
51
t|9
64
77
63
48
49
46
55
77
54
74 '
77
"1
45
'55 '
40
_ J7- - -
50
52
87
60
44 " '
61
61
63
61
51
79
. 7| - —
61
63
67
si
57
" 97
60
so
78
71
73
6 i
ai
32
43 " '
IS . .. 0"
10 " " " 68
12 72
12 63
to 64
'9 64
f" ' 71
1 ' 73
2 69
8 64
10 63
20 6S
8 72
10 72
10 '~ 66
10 63
12 62
4 70
4 73
4" ' 73
2 71
4 7i
20 56
ib 56
20 57
40 ' 49
20 " 54
9 55
IS 68
2 68
a 63
12 57
IS • 54
12 b4
15 40
12 6fl
12 ' 64
6 ' 62
7 ' " 60
14 67
10 66
12 71
20 53
20 53
2 67
IS 66
12 66
10 6l
7 63
a " 'si
10 ~ " 57
5 56
20 41
40 "~ " 52
_ " "_" 1.
^
i
7
d
1
7
6
j.
6
1
10
"8 ' '
8 " "
5
0
4
•6
9
i
6
6
6
6
- - j. - -
" 7 "._""_"
^
5
7
7
' U '
' S
~ 9
10
4
S
b
' 10 '
... . .
9
$
a '
s
7
"" n
b
6
- s
4
S ""
• ' a
s
U
• 12 '
-------
oaa
107
lo V
109
110
111
1 12
113
114
1 15
116
117
lie
119
DATE 3TATIO'
731016 " ' ' "•"
731017
731019
731020
731021 . ...
731022
73J023
731024
731026
731027
7)1028
731Q30
731031
4 MOZ
" .04
,03
,02
,05
,05
,05
,06
,07
,05
,04
,06 _
,01
,02
NO
NO- 2-. THC - ,NMHC MTEMP
(6-9) . (6=9) _. (6^9) .. (6^9.)
67
b7
59
73
t>d
_ . 65
69
72
73
69
65
63
SRAO
430
013
371
328
310
316
326
3*47
02
120
254
AHS
- , 7
9j2
1,8
2J3
1,0
2,7
4,6
2)0
10,0
~ •
3|3
6,6
RM
43
SI
62
44
54
54
too
55
43
47
66
96
83
VJ3
20
20
20
15
15
10
T
6
9
|2
10
12
15
DPT
41
3S
40
50
43
ttS
47 *
53
48
47
50
42
47
H3
1}
12
7
4
1
10
9
10
6
------- |