&EPA
United States Region II Office
Environmental Protection 26 Federal Plaza
Agency New York, N.Y. 10007
Air
Participate Source
Contributions in the
Niagara Frontier
-------
ERRATA
An error has been discovered in the calibration factor which was used
during the x-ray fluorescence analysis for bromine in the particulate air
filters. At the time that the xrf system was operated, an incorrect response
slope had been programmed into the computer software which lead to the high
values observed for bromine. Subsequent reanalysis of two bromide standards
has confirmed the error and has given rise to the correction factor 0.62. This
factor should be used to multiply all bromine concentrations as they appear in
appendices B and C. As a result of this action, bromine concentrations less
than 0.017 micrograms/cubic meter should be considered to lie below the
analytical detection limit within this project.
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA 902/4-79-006
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
PANICULATE. SOURCE CONTRIBUTIONS 'IN THE
NIAGARA FRONTIER
5. REPORT DATE of Preparation
December, 1979
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
Dr. Nicholas P. Kolak, James Hyde, Robert Forrester
9. PERFORMING ORGANIZATION NAME AND ADDRESS
New York State Department of Environmental Conservation
Division of Air
Bureau of Developmental Technology
50 Wolf Road, Albany, New York, 12233
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO".
68-02-2880
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Region II
Air Programs Branch
New York City, N. Y.
13. TYPE OF REPORT AND PERIOD COVERED
Final Jan. 1978-Jan. 1980
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
17. KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS
TSP
particulate matter
ion chroma to graphy
x-ray fluorescence analysis
chemical element balance
dichotomous sampler
hi-vol sampler
_partien1afp sizp elassi Fi eati on
18. DISTRIBUTION STATEMENT
b.lDENTIFIERS/OPEN ENDED TERMS
inhalable particulates
urban area particulates
elemental analysis
micro -inventory
New York State air qualit;
filter analysis
air pollution control
19. SECURITY CLASS {This Report)
20. SECURITY CLASS (This page)
c. COSATI Field/Group
21. NO. OF PAGES
22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION i s OBSOLETE
-------
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EPA Form 2220-1 (Rev. 4-77) (Reverse)
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PARTICULATE SOURCE CONTRIBUTIONS IN THE
NIAGARA FRONTIER
by
N. P. Kolak, J. Hyde, R. Forrester
Division of Air
Bureau of Developmental Technology
Albany, New York 12233
EPA Contract No. 68-02-2880
Deborah Brome
Project Officer
USEPA Region II
New York City, N.Y. 10007
New York State Department of Environmental Conservation
50 Wolf Road
Albany, N.Y. 12233
-------
DISCLAIMER
This report has been reviewed by the Region II, United States Environ-
mental Protection Agency, and approved for publication. Approval does not
signify that the contents necessarily reflect the views and policies of the
U.S. Environmental Protection Agency, nor does mention of trade names or
commercial products constitute endorsement or recommendation for use.
ii
-------
ABSTRACT
Several areas throughout the Niagara Frontier Air Quality Control Region
have consistently been faced with air particulate concentrations which exceed
the Federal primary AAQS. Within this region there is much heavy industry
associated with electric power production, coking, steelmaking, graphitizing,
and bulk material handling. An attempt to investigate the nature of the
particulate composition at six receptor sites was initiated for an eighteen-
month period beginning January, 1978. Dichotomous samplers employing teflon
filter membranes were utilized to provide two size fractions of air particulates
-- 0-4 and 4-15 micrometers particle diameter. At least two sampling runs were
conducted each week from summer through spring. Approximately 550 pairs of
air particulate filters were subjected to x-ray fluorescence analysis for
twelve metals lead, bromine, zinc, nickel, iron, manganese, chromium,
vanadium, calcium, sulfur, silicon, and aluminum. Extraction of these filters
and analysis by ion chromatography yielded data for fluoride, chloride,
nitrite, bromide, phosphate, nitrate, sulfate, ammonium, potassium, and sodium
ions.
A chemical element balance approach was used to model the chemical compo-
sition of various particulate source categories - iron and steel, soil, lime,
oil, refuse, and automobile. The chemical fingerprints of the particulates
derived for each of these categories were used to resolve the total particle
mass observed at each receptor site into the component categories.
iii
-------
Major differences were observed in site-to-site concentrations of various
metals, especially lead, iron, and zinc. Various patterns were observed for
trace metal levels with respect to wind direction. Sulfate loadings, when
expressed as a percent of TSP, exhibited only minor fluctuations throughout
the test area regardless of wind direction, and serve as a indicator of back-
ground particulate levels which are transported into New York State.
This report was submitted in fulfillment of Contract No. 68-02-2880 by
the New York State Department of Environmental Conservation under the sponsor-
ship of the U.S. Environmental Protection Agency. This report covers a period
from January 1978 to December 1979, and work was completed as of December 1979.
IV
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CONTENTS
Disclaimer
Abstract
Figures vi
Tables viii
Abbreviations ix
Acknowledgements x
1. Introduction 1-1
2. Conclusions and Recommendations 2-1
3. Site Description 3-1
4. Collection of Air Particulates 4-1
Hi-vol Samplers (Glass Fiber Filters) 4-1
Hi-vol Samplers (Whatman-41 Filters) 4-1
Dichotomous Samplers (Teflon Filters) 4-2
GCA Air Particulate Monitor (APM) 4-8
5. Laboratory Analyses 5-1
Suspended Particulate Weights 5-1
Whatman-41 Filters 5-1
Millipore Fluoropore Filters 5-1
X-Ray Fluorescence Analysis 5-2
Ion Chromatography 5-4
Scanning Electron Microscopy and Electron Microprobe
Analysis 5-5
6. Suspended Farticulate Data 6-1
Whatman-41 Hi-vol Data 6-1
Dichotomous Sampler Data 6-8
GCA Ambient Particulate Monitor (APM) Data 6-15
7. Particulate Sulfur and Sulfate 7-1
8. Chemical Components - General Observations 8-1
Introduction 8-1
Light Elements (Al, Si, S, Ca) 8-14
Aluminum 8-14
Silicon 8-15
Sulfur 8-17
Calcium 8-17
Transition Metals (V, Cr, Mn, Ni, Zn, Fe) 8-19
Vanadium 8-19
Chromium 8-19
Manganese 8-20
Nickel 8-20
Zinc 8-20
v-a
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Page
Iron 8-21
Q -OA
Lead and Bromine o-^t
Ion Chromatographic Data 8-25
Introduction 8-25
Sodium 8~25
Potassium 8-25
Ammonium 8-26
Halides (F, Cl, Br) 8-27
Nitrate and Nitrite 8-27
9. Scanning Electron Microscopy 9-1
10. Chemical Element Balance 10-1
Introduction 10-1
Source Category Coefficients 10-3
Six Source Resolution 10-7
Seven Source Resolution 10-17
Particulate Mass Balance 10-21
References R-l
Appendix A - Chemical Components-Project Averages For Each Site . . A-l
Appendix B - Project Data - Fine Particle Fraction B-l
Appendix C - Project Data - Coarse Particle Fraction C-l
Appendix D - Hi-Vol Suspended Particulate Data (Whatman-41) .... D-l
Appendix E - CEB Results - Six Source Category-Fine Fraction . . . E-l
Appendix F - CEB Results - Six Source Category*Coarse Fraction . . F-l
Appendix G - CEB Results - Seven Source Category-Fine Fraction . . G-l
Appendix H - CEB Results - Seven Source Category-Coarse Fraction . H-l
v-b
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Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
FIGURES
Bell Inlet System
Details of Dichotomous Sampler
Relationship of suspended particulate concentrations using . .
Site 3 ratios of particulate weights (Fine/Total)
Site 6 Ratios of particulate weights (Fine/Total)
Wind rose for APM suspended particulates at site 5
Dosage rose for APM suspended particulates at site 5
Comparison of APM SP to Hi-Vol SP
Total Sulfate - monthly averages per site (M-g/m3)
Dichotomous sampler suspended particulates - monthly
averages per site (i-Lg/nr*)
Sulfate as a percent of total sulfur - monthly averages
per site
Fine particulate sulfate as a percent of IP
Page
3-4
3-5
4-4
4-5
6-2
6-5
6-6
6-10
6-11
6-13
6-14
6-16
6-17
6-18
6-20
6-21
7-2
7-4
7-5
7-7
vi
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Number Page
Q Q
21 Site variations for silicon, sulfur, aluminum, and calcium . - °~°
22 Site variations for chromium, vanadium, and nickel °~"
23 Site variations for zinc and manganese 8-10
24 Site variations for iron, lead, and bromine 8-11
25 Site variations for sodium, potassium, nitrite, and halides . . 8-12
26 Site variations for sulfate, ammonium, and nitrate 8-13
27 Wind sector analyses for iron and silicon for sites 5 and 6 . . 8-16
28 Histogram of Predicted and Observed Suspended
Particulate Concentrations 10-23
vii
-------
TABLES
Number Page
1 Sampler Location 3-2
2 Site Identification Numbers 3-3
3 XRF Detection Limits 5-3
4 Statistical Characteristics of Hi-vol Measurements Using Whatman-41
and Glass Fiber Filter Media 6-1
5 Site Data Summary From Dichotomous Samplers 6-8
6 Total Sulfate From Dichotomous Samplers ((j,g/m3) 7-1
7 Average Values of Chemical Species for Total Dichotomous Suspended
Particulates 8-2
8 Chemical Species - Percentage of Fine Particulate Fraction 8-3
9 Enrichment Factors for Chemical Components 8-6
10 Chemical Species - Percentage Composition of Fine and Coarse Particle
Fractions 8-7
11 Wind Directions Observed for High Iron Concentrations 8-22
12 Normalized Elemental Concentrations for Each Source Category (Fine) . .10-4
13 Normalized Elemental Concentrations for Each Source Category (Coarse) .10-5
14 Six Source Category Distribution Summary (% FSP) 10-12
15 Six Source Category Distribution Summary (% CSP) 10-16
16 Seven Source Category Distribution Summary (% FSP) 10-18
17 Seven Source Category Distribution Summary (% CSP) 10-19
18 Mass Balance of Suspended Particulate Concentrations 10-22
viii
-------
LIST OF ABBREVIATIONS AND SYMBOLS
SIP State Implementation Plan
NFAQCR Niagara Frontier Air Quality Control Region
AAQS Ambient Air Quality Standard
TSP Total Suspended Particulates (Glass Fiber Data)
IP Inhalable Particulates (Dichotomous Sampler Data; IP = FSP + CSP)
FSP Fine Suspended Particulates (Dichotomous Sampler Data)
CSP Coarse Suspended Particulates (Dichotomous Sampler Data)
SP Suspended Particulate (Whatman-41 Data)
CEB Chemical Element Balance
Hi-Vol High-Volume Air Sampler
SEM -- Scanning Electron Microscopy
RH -- Relative Humidity
xrf -- X-Ray Fluorescence
BR-S -- Soluble Bromide as measured by Ion Chromatography
Kev -- Kilo Electron Volts
Kv Kilovolts
ma -- Milliamperes
sec -- Seconds
HR Hours
CFM -- Cubic feet per minute
urn -- Micrometer
LPM -- Liters per minute
ix
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ACKNOWLEDGMENTS
Project Officer Deborah Brome's dedicated assistance contributed to this
study and is gratefully acknowledged. The authors are grateful to many of the
staff members of the Division of Air for their support in this project. In
particular, the assistance of Gopal Sistla has been invaluable in the area of
computer programming and in the development of a chemical element balance
program. Special thanks are extended to our staff in Region 9, particularly
Henry Sandonato and Frank Price, for assisting us in establishing and maintain-
ing field operations throughout the course of this investigation. The sem
work performed by Mr. Roger Cheng at the Atmospheric Sciences Research Center
is gratefully acknowledged. The comments of Dr. Glenn Gordon and Mr. Scott
Rheingrover of the University of Maryland are greatly appreciated. The authors
would like to thank Mrs. Catherine Cassidy and Miss Nancy Gardner for typing
this report, and Mrs. Carol Clas and Mr. Gary Lanphear for drafting the
figures.
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SECTION 1
INTRODUCTION
Traditional source dispersion models have been used in the Buffalo-
Lackawanna region of New York State to estimate TSP concentrations from
emissions inventory and meteorological data. This approach balances its total
predicted TSP to 100% of actual observed concentrations, but suffers from an
inherent inability to describe in more detail the impact of various individual
contributors on any specific receptor site. In order to provide a more
accurate assessment of the individual influences of various emission source
categories on receptor sites in the NFAQCR, it is necessary to define the
chemical composition of the source categories and of the TS-P for each particu-
late filter sample. This approach has been attempted in the past by various
groups (1-5) with increasing success. Basically, a computer model is used to
resolve each air particulate sample among the various major source categories
which are located within the region. Resolution is accomplished by the use
of a set of simultaneous equations which represent a "chemical fingerprint"
for each of the major source categories. The chemical composition observed in
the TSP sample is reconstructed from these equations until a best fit is
obtained.
To provide detail in particle size, dichotomous samplers were employed
at each site to permit monitoring of the inhalable particulate fraction, 0-15
micron particle diameter. The field stations were equipped with hi-vol
samplers employing both Whatman-41 and glass fiber filter media to permit the
1-1
-------
intercorrelation of all participate measurements. All of the particulate
filters collected by the dichotomous samplers were analyzed by x-ray fluores-
cence for the following elements - lead, bromine, zinc, nickel, iron, manganese,
chromium, vanadium, calcium, sulfur, silicon, and aluminum. Subsequent ion
chromatographic analysis of the filter samples yielded concentrations for
fluoride, chloride, nitrite, bromide, phosphate, nitrate, sulfate, ammonium,
sodium, and potassium ions. Chemical fingerprints, descriptive of the major
particulate source categories, were derived in terms of the latter chemical
components and were used to resolve the particulate concentrations observed at
the receptor sites into the respective source category contributions.
1-2
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SECTION 2
CONCLUSIONS AND RECOMMENDATIONS
The conclusions and recommendations which arise from an interpretation
of the final results of the Niagara Frontier study are presented below. Since
many of the facts here are unrelated to each other, no attempt was made to
write this section in a continuous manner. The facts are simply stated in
list form with no order of importance.
1. From the final analysis of all project data, it is concluded
that the six field stations have provided a wealth of high quality
data for the characterization of sources which contribute to
the overall TSP observed in the Niagara Frontier. Because of
the predominant southwesterly winds and the intense industrial
emission sources within the urban area, it is recommended that
any future efforts attempt to set up at least two more stations.
One station should be located on the lake shore west of the area
defined by Sites 2, 3, 4, and 5. The second additional station
should be situated south of the Bethlehem Steel complex below
Site 5. The purpose here is to provide additional TSP measure-
ments which are close to the existing sites and which provide
upwind (background) data from areas which are adjacent to major
emission sources. Coke oven emissions do not appear to be
adequately described by the present data base and future investi-
2-1
-------
gations may wish to consider upwind-downwind sites that are closer
to this industrial operation. These additional sites will be difficult
to install and must consider the availability of power and the use
of private lands.
2. Data for suspended particulates which supercede that produced within
this project represents information based on the use of glass fiber
filter media. The use of dichotomous samplers in this study has
produced data which is size fractionated and previously unavailable
to us. From the final results of this study, it is concluded that
the fine and coarse particulate fraction and data are essential if
one is to resolve emission sources contributing to TSP. However,
»
dichotomous samplers represent a non-standard methodology and
results must be related to glass fiber data from current hi-vol
monitoring. As in the Niagara Frontier study, it is recommended
that stations be simultaneously equipped with instrumentation
which provides particle size classification as well as hi-vol glass
fiber data. Such a data base permits some comparisons to be made
between the two independent systems in regard to current air
quality standards. Without these comparisons, the results from
size classified data are almost impossible to relate to standard
hi-vol data. It is further recommended that dichotomous samplers
be used which are better designed and possess a coarse-fine
separation at 2.5 microns particle diameter. This separation
value would permit data to be correlated with that arising from
projects outside the state and would allow a comparison of
particulat'e data from regions throughout the nation.
2-2
-------
3. Because size classified data has been judged so important, a further
aspect to be considered in the collection of particulates is the
diurnal variation of particulate concentrations. The use of auto-
matic dichotomous samplers should be used which have the capacity
to collect samples on some multiple hour basis. Samples collected
in this manner would offer more source category information by
permitting a closer accounting of variations in wind direction.
4. One observes from the chemical analyses in this project that many
components of TSP were monitored - 12 metals and 10 ions. It is
concluded that these 22 variables represent the main core of para-
meters with which one should be concerned and that a reasonable
characterization of SP has been achieved. From knowledge of the
application and function of the GEB model, itfs expected that more
accurate source resolutions will be obtained as the number of
parameters in the chemical profiles is expanded. Therefore, it
is recommended that chemical analyses be expanded to include more
components and that detectable limits be pushed to levels consistent
with time and funding requirements.
5. It is concluded that sulfate comprises the single major species
(50-99%) of all possible forms of sulfur-containing particulates.
Sulfate and sulfur particles are primarily found in the fine
fraction (>95%) and are most likely representative of long range
transport of material arising from gas-to-particle conversion
processes. Site averages of sulfate throughout the course of this
project have shown that similar levels are observed at all six
stations. One concludes that major emissions of sulfur particulates
2-3
-------
from industrial processes are not readily discernible in project
data, and local emission sources may possibly be negligible despite
such activities as coking and the use of bulk sulfuric acid. After
consideration of wind direction data, it is concluded that greater
than 75% of all sulfate material enters New York State from west of
Buffalo. It is further observed that the overall project sulfate
concentrations form approximately 187° of IP concentrations. When
ammonium and nitrate concentrations are included with sulfates as
representing background particulate concentrations, this fraction
represents one of the largest single groups which contribute to
the overall observed IP levels.
9
6. The following list of chemical components was found to occur pre-
dominantly (>60%) in the fine particle fraction - lead, bromine,
zinc, vanadium, sulfur, sulfate, nitrate, nitrite, potassium, and
ammonium. On the other hand, calcium, silicon, aluminum, and iron
were found mainly in coarse particles. The segregation of particle
size and the different chemical compositions afford one the
opportunity to make distinctions in the contributing sources. The
remaining components were fairly equally dispersed between the fine
and coarse fractions - nickel, manganese, chromium, and sodium.
7. The effects of the steel industry are evident at all urban sites.
Project data permits the conclusion that Sites 4 and 5 in Lackawanna
experience heavy localized concentrations of IP that are rich in
iron, manganese, and calcium. These metals implicate the respective
raw materials used in the production of steel.
8. The elevated ammonium concentrations that are observed at Sites 1
2-4
-------
and 2 lead one to suspect that emissions from coking operations
are responsible for the observed increases. It is felt that project
results have not adequately addressed the contribution to IP of
emissions from coke production. Filter samples from Sites 1 and 2
were often quite black and suggestive of carbon from coal/coke.
However, no chemical data currently resulting from this project
appears to be useful in estimating the percentage contribution of
coke emissions to observed TSP- It is recommended that future
studies concerned with this aspect may make use of analysis for
polynuclear aromatic hydrocarbon components or other similar classes
of compounds which are peculiar to coke production, thereby serving
as a tracer.
9. The increased levels of calcium within Lackawanna implicate lime
and/or slag operations at Bethlehem Steel Corp. An initial data
analysis in Section 8 of this report suggests that Ga/Fe and Ga/Mn
ratios may help to distinguish between these two emission sources
in future work.
10. Major chemical components which are observed at the background
station are silicon, aluminum, ammonium, and sulfate. The conclusion
can be drawn at Site 6 that the bulk of the SP is composed of con-
tributions mainly from soil and the long range transport of parti-
culates.
11. Silicon data is found to increase in the direction of increasing
traffic density. Observed site variations are attributed to an
increase in re-entrainment and permit one to conclude that silicon
is mainly representative of soil particulates. To be sure, silicon
2-5
-------
is used in the steel industry. However, site data currently indicate
that silicon contributions from steel emissions are negligible.
Support for these statements is also drawn from the aluminum data.
Site data suggest that the bulk of all aluminum originates from soil
and that any industrial emissions of this metal within the study
area are also negligible. Because of the importance of these two
elements in distinguishing among all emission source categories, it
is recommended that future studies make use of improved analytical
sensitivities for both components so that any subtle variations in
concentrations may be followed more accurately.
12. The interpretation of zinc data is rather confusing at this time.
The high metal levels at Site 1 are expected to arise chiefly from
abraded rubber tire particles since this station is usually downwind
of the nearby New York State Thruway. However, zinc occurs at
similar high levels only at Sites 4 and 5 in Lackawanna. Although
major roadways exist upwind of these two sites, the realization that
galvanizing operations are located nearby results in confusion in
the distinction of the two source categories. It is recommended that
future investigations accurately define the importance of zinc from
automotive emissions and determine whether or not galvanizing
operations make any contributions at all.
13. An analysis of the SP data permits the conclusion that dichotomous
samplers collect approximately 607, of the particulate weight at all
urban sites which is similarly collected by conventional hi-vols
employing glass-fiber filter media. This fact must be well understood
by anyone wishing to interpret the dichotomous data and. to make
2-6
-------
extrapolations to standard hi-vol data. While one may multiply
IP data by 100/60 to estimate comparable glass fiber TSP, one may
introduce large errors by applying a similar procedure to individual
chemical components. For example, sulfates are essentially fine
3
particles and dichotomous sampler values in y,g/m should compare
directly to glass fiber data. Presumably there is little or no
sulfate in the 40% additional mass which is collected on glass fiber
filters. The application of the factor 100/60 to dichotomous-derived
sulfate in order to obtain hi-vol (glass fiber)-derived sulfate would
be incorrect. More generally, a component of a particular size
fraction of IP cannot be so simply "scaled up" to a value which is
expected for TSP since the factors are frequently different for each
particle size fraction.
14. The GEB model attempts to distribute observed chemical component
concentrations among pre-defined emission source categories, using
as a basis the chemical profiles which are characteristic of each
source category. A detailed knowledge of the coefficients which
comprise the chemical profiles used in this study lead one to
conclude that this aspect of the CEB model is deficient, both in
terms of accuracy and in the necessary detail. Despite these
deficiencies, the resulting distribution of IP among the potential
source categories appears highly reasonable for all sites. However,
improvements in the overall resolution can be expected from the
recommendation that chemical profiles should be used in the future
which are specific for the Buffalo region. This action would
necessitate the collection of bulk samples which adequately represent
2-7
-------
the bulk emissions for each source category. Such an approach is
expected to provide more accurate results in terms of emission
source resolution. It is impossible to determine at this time
whether the accuracy would be improved 10% or even 500%. The degree
of improvement involves the relationship of the data which is presently
used in the chemical profiles with any such changes found necessary
in profile data which is specifically determined for the Niagara
Frontier.
15. On the basis of the results of the CEB analyses of FSP which was
performed on project-average data for each site, one may state the
following conclusions for a six source category resolution. Soil
»
components average 45%.of the observed FSP at the three Buffalo sites.
This material becomes airborne from the action of lake breezes on
the shore and barren lands and is assisted inland by re-entrainment
from vehicular activities. Steel, oil, and liming emission source
categories account for a combined total of 10% of the observed FSP
in Buffalo. Automotive particulates represent approximately 40% of
the contributions to FSP throughout all the urban sites, decreasing
to 25% at the rural station. Emissions from the steel category do
rise within Lackawanna (Sites 4 and 5) and form an appreciable
portion (21%) of FSP. One further concludes that industrial steel-
making contributions to FSP are comparable to those which are
estimated from soil as well as auto categories.
16. On the basis of the results of the CEB analysis of GSP on project-
average data, the following statements can be concluded for the six-
source resolution. Soil components at the Buffalo sites comprise
2-8
-------
the single largest contribution (807.) to observed CSP. Contributions
from steel, oil, refuse, and auto exhibit only minor inputs to the
coarse particle fraction. The liming category reveals a significant
contribution (157.) to GSP within Buffalo. One should realize that,
while the steel category itself does not reveal much impact, any
possible contributions from slag operations would appear in the
liming category. A steel emission contribution is observed in
Lackawanna but barely reaches 57.. Again, slag particles would appear
in the liming category and the 107. rise noticed here, above the
Buffalo values, is believed to represent slag and/or limestone
operations which are associated with steel production.
17. The GEB analysis was extended to seven sources with the inclusion of
a category for particulates arising from the combustion of coal
during power generation. Interpretation of the CEB results becomes
more difficult. The seventh category, coal, permits a reasonable
distribution of particulates in the FSP fraction without significantly
changing the estimates derived from the six category resolution.
While designed specifically for coal-fired power plant emissions,
the coal profile results in observed increases at Sites 4 and 5 and
may reflect some contributions from the coal/coke processing
operations in that area. A similar attempt to analyze the CSP
fraction results in an overall poor fit so that the value of the
addition of a coal source category is questionable.
2-9
-------
SECTION 3
SITE DESCRIPTION
Six field sites were chosen in the NFAQCR for the installation of air
sampling equipment. The major consideration in the sitings was the knowledge
that there were only several "hot-spots" in the Buffalo-Lackawanna region
where excessive TSP levels were frequently observed. After reviewing several
additional factors such as the availability of electrical power, ease of
access by personnel, and the time schedule, field stations were eventually
located in close proximity to existing and approved New York State network
sites. The added benefit could then be realized of the direct comparison of
the TSP measurements to the State*s hi-vol system using standard fiberglass
filter media.
A description of each site is provided in Table 1, where the location,
height above ground, and other characteristics are presented. Table 2
presents New York State's site identification numbers which are renumbered 1-6
to aid in establishing the north-south relationship of sites. Site 1 is the
northernmost station while Site 6 is the southernmost and rural background
station.
3-1
-------
TABLE 1. Sampler Location
City
Buffalo
Buffalo
Buffalo
Lackawanna
Lackawanna
Angola-On-The-Lake
Site Identification
1401-13
1401-11
1401-02
1402-10
1402-01
1463-02
Location
Public School #28
1515 South Park Avenue
UTME 186915 UTMN 4752215
Public School #26
84 Harrison Street
UTME 187100 UTMN 4750700
Holy Family Church & School
920 Tift Street
UTME 185800 UTMN 4748600
Friendship House
264 Ridge Road
UTME 185800 UTMN 4748600
Lackawanna Sewage Treatment Plant
252-282 Lehigh Street
UTME 186100 UTMN 4747700
Big Sister Creek Waste Water
Treatment Plant
Old Lake Shore Road, near
Benett Road
UTME 170000 UTMN 4722300
10 m
15 m
5 ra
5 m
6 m
Land Use
Industrial
Comments
No obstructions.
Industrial-residential Although other
buildings are near-
by, PS #26 is
tallest.
Residential-commercial No obstructions.
Commercial
No obstructions.
Industrial-residential No obstructions.
Residential
No obstructions.
-------
TABLE 2. SITE IDENTIFICATION NUMBERS
State I.D. # Project I.D. #
1401-11
1401-13
1401-02
1402-10
1402-01
1463-02
1
2
3
4
5
6
Figures 1 and 2 reveal the spatial relationship among the five urban stations
and the single rural background station, respectively. The urban sites
follow an approximate north-south line about 7.2 kilometers in length. The
rural station, Site 6, is located approximately 24 kilometers south of Site 5,
well removed from the heavy industrial and populated urban centers. Each
site was installed according to EPA siting guidelines, with special attention
paid to height above ground, distance from walls and other obstructions, and
proximity to major emission sources.
3-3
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1402-01
TV V
J I < x.;
1401-11
1401-13
£1401-02
FIGURE 1. LOCATION OF URBAN SITES IN BUFFALO AND LACKAWANNA.
3-4
-------
1463
FIGURE 2. LOCATION OF RURAL (BACKGROUND) SITE IN ANGOLA.
3-5
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SECTION 4
COLLECTION OF AIR PARTICUIATES
HI-VOL SAMPLERS (GLASS FIBER FILTERS)
The locations of five project sites (Site 4 is excluded) were coincident
with stations in the Department's statewide particulate monitoring network.
The State's hi-vol samplers at the five locations used conventional glass
fiber filters. This equipment was calibrated and operated according to
procedures set forth by the Environmental Protection Agency. The glass
fiber filters collected 24-hour suspended particulate samples and the
resultant loadings were determined by the New York State Department of Health.
Access to this TSP data permitted comparisons to be made with the project's
Whatman-41 and dichotomous data, respectively.
HI-VOL SAMPLERS (WHATMAN-41 FILTERS)
Each of the project's six sites was equipped with a second hi-vol unit
which was operated using Whatman-41 cellulose filter media. All of these
(7)
samplers were essentially maintained and operated according to EPA procedures
mentioned in the preceding section. The project's hi-vol sampling schedule
was altered in August, 1978 so that one of the two weekly sampling runs would
always coincide with the State's once-every-six-day schedule.
Several differences in the operation of the equipment are presented here.
Instead of the standard Visi-float guages, each hi-vol was upgraded with the
more accurate manometer system for determining flow. The hi-vol orifice
4-1
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manometer adapters were calibrated by passing a known quantity of air (100
ft3) through the adapter and recording the elapsed time required for passage.
A Roots-Gonnersville positive, rotary dry gas meter was used to guage the
volume of air. A calibration curve was generated by operating the system and
varying the number of filters in place to simulate an increase in flow
resistance. The calibration curve for each hi-vol adapter was obtained by
plotting flow rate (CM) versus manometer readings on logarithmic paper. The
resultant curve is described by the equation y = ax , where y = air volume
(CFM), x = manometer reading, a = intercept, and b = slope. A total of five
calibration points were obtained by operating the hi-vol motor (110 volts)
with 0, 1, 2, 3, and 4 filters (Whatman-41) in place. All flow rates are then
corrected to standard conditions of temperature and pressure (STP).
The manometer-equipped hi-vols had the following advantages over their
rotameter counterparts:
(1) Worn brushes or armatures could be replaced in the
motors for preventive maintenance in the field with-
out the necessity of flow rate recalibration;
(2) A complete motor could be replaced without recali-
bration;
(3) The manometer-equipped adapters offer a more reliable
and accurate measurement of air flow through the
system.
DIGHOTOMOUS SAMPLERS (TEFLON FILTERS)
All six sites were equipped with a dichotomous sampler in order to
obtain size classification data on suspended particulates. Thus, each site
had two hi-vols (one with glass fiber and one with Whatman-41 filters) and
4-2
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one dichotomous sampler, all spaced approximately 2-8 meters from each other
to minimize inter-sampler effects from pump and motor exhausts. Site 4 was
not part of the State's hi-vol network system and was not equipped to produce
hi-vol glass fiber data.
These dichotomous samplers (manufactured by Environmental Research Corp.)
operate by removing particles larger than 3.5y, from the main airstream by
inertial separation. Figures 3 and 4 show the inlet system and the main
features of the air flow internal to the dichotomous sampler. The larger
particles are directed into a region of relatively stagnant, low-flow air
which is then drawn through a filter, giving rise to the coarse particulate
fraction. All remaining air containing the smaller particles is drawn
through a second filter to give rise to the fine particulate fraction. One
should realize that the air flow directed to the coarse particulate filter
represents approximately 5% of the total inlet air flow and therefore contains
5% of all fine particulates. A correction was made for the 5% fine parti-
culates deposited in the coarse particulate filter by use of the "uncontami-
nated" 95% fine particulate weight.
The total volumetric flow through the dichotomous sampler determines the
cut point for size separation as well as the portion of fine particles
deposited on the coarse filter. It was originally intended that the samplers
would operate at a total flow rate of 50 1pm which would have resulted in a
50% cut point at 3.5^,*. When calibration was attempted, however, it was
found that the samplers could not achieve a 50 1pm flow rate when using O.Sy,
*This result is based on calculations using unit density, aerodynamic particle
diameters as determined by the manufacturer.
4-3
-------
cm
Or
2-
4
6
8
10
FLOW
SHIELD
STILLING
CHAMBER
FLOW TO (NCHOTOMOUS SAMPLER
FIGURE 3. BELL INLET SYSTEM
4-4
-------
SAMPLE FLOW
FROM
AEROSOL INLET
INTAKE
FIRST STAGE
SEPARATION
COARSE
PARTICLE
FLOW
FINE
PARTICLE
FLOW
SECOND STAGE
SEPARATION
COARSE
PARTICLE
FILTER
FINE
PARTICLE
/FILTER
FIGURE 4. DETAILS OF DICHOTOMOUS SAMPLER
4-5
-------
teflon filters. The highest flow rate that could be maintained was 35 1pm
which resulted in a 507. cutpoint at about 4p, as determined from the manu-
facturer's performance data.
Each unit was equipped with rotometers for fine and coarse flow
adjustment and a vacuum gauge to measure the pressure at the fine flow
rotometer. The fine flow rotometer and its pressure gauge were used for
field measurement of flow and were calibrated using a wet test meter. The
inlet head was removed from the sampler and tubing attached to the inlet of
the virtual imp actor head. Air was drawn through the wet test meter and into
the instrument. It was not possible to measure the flow on the exhaust side
because of leaks in the carbon vane pump which was incorporated into the
system. The coarse flow rotometers were not calibrated but set at a constant
value equivalent to 5% of the nominal total flow. Because of the light
loading of the coarse filter and its low flow rate, it was assumed that
changes in the coarse flow would be small and would have a negligible effect
on the total flow.
Even though the dichotomous samplers reject particles with diameters
greater than ISy, and, therefore, collect fewer particles, they are more
susceptible to filter overloading. The teflon filters employed in this study
have a higher initial pressure drop and lower particulate loading capacity
than either glass fiber or Whatman-41 filters. Because frequent filter
plugging occurred at the onset of this investigation, the filters were
switched from O.Sp, pore diameter to l.Oy, pore diameter to increase the flow
through the filter and yet retain high capture efficiency. However, this
charge in porosity did not result in all subsequent samples having elapsed
times of 24 hours. Plugging of filters still occurred but with reduced
4-6
-------
frequency. The dichotomous samples as delivered had no mechanism to detect
a low air flow condition caused by excessive particulate loadings. The pump
and its timer would continue to operate even though the flow controllers
could no longer maintain the desired flow rate. This situation resulted in
an inability to calculate the final total air volume. The samplers were,
therefore, modified so that operation of the pump and timer would cease if
the flow rate through the fine particulate filters dropped below 90% of the
preset value. This modification was accomplished by monitoring the pressure drop
in the inlet above the filter with a pressure transducer set to terminate
power when the inlet pressure drop indicated a decreasing flow condition.
The preset value was obtained from calibration data for flow rate versus
»
pressure data and was selected to permit a maximum 10% decrease in the flow
rate. Thus, the data represented by a filter which was beginning to plug
could be saved by terminating any further operation. A valid air volume and
particulate concentration could then be computed. It is possible that all six
sites operated for 14 hours on a given date. The trace metal data contained
in such samples can be invaluable but would otherwise have been lost.
Because of the low temperatures encountered in the Buffalo area during
the winter months, problems were anticipated for operation of the dichotomous
sampler pumps. These pumps, unlike hi-vol motors, consist of high tolerance
carbon vanes which were not designed for such extreme temperature conditions.
It was expected that moisture and low temperatures could cause the vanes to
freeze solid. Upon start-up, it is conceivable that the pump motors could
then burn out from excessive power consumption or the pump could spin freely
with the vanes frozen in the retracted position. To circumvent this problem,
a 100 watt thermostated heating tape was attached around the pump head assembly.
4-7
-------
The tape supplied heat to the carbon vanes whenever the air temperature
dropped below 35°F. The wiring was performed in such a manner that electrical
power to the heating tape was interrupted whenever the sampler was operating
and was re-supplied when the sampler had ceased operation. This heating
scheme was judged a success since only one pump had failed during the entire
project.
GCA AIR PARTICULATE MONITOR (APM)
The APM was provided for our use on this study through the courtesy of
GGA Corporation for the automatic and continuous monitoring of the concentra- _
tion of ambient air particulates. Particulate matter is divided into fine
and total particle fractions by a cyclonic device and is collected on a tape
filter from a known volume of air. The resultant attenuation of low energy
beta radiation by the particulates is converted into suspended particulate
3
concentration units (y,g/m ). This entire system was pre-calibrated by the
manufacturer.
The APM was installed at Site 5 on June 28, 1978 for an approximate
6-week period. Since this equipment was somewhat cumbersome, Site 5 was
selected for the installation because of its relative ease of access and its
proximity to heavy industrial operations. The instrument parameters were
selected to provide hourly suspended particulate data on a 24-hour basis,
seven days per week. Data was only obtained at Site 5 over this 6-week period,
It was thought to be of less value to gather a little data at each of the
six sites since only one instrument was available. The objective here was
to monitor and establish the diurnal variations in suspended particulate
concentrations. Operations involving the APM ceased on September 7, 1978 and
the equipment was returned to the manufacturer at that time.
4-8
-------
SECTION 5
LABORATORY ANALYSES
SUSPENDED PARTICULATE WEIGHTS
Whatman-41 Filters
Whatman-41 cellulose filters were chosen for use in the high-volume air
samplers in order to facilitate x-ray fluorescence analysis. Although these
filters have been found to be satisfactory for use in hi-vols, their use
greatly complicates weight measurements. The cellulose fibers readily sorb/
desorb water with a consequent change in weight for which a correction must be
made. A previous study (6) found the filter weight to change linearly and
reproducibly with relative humidity in the 35-55% range. Comparable results
were obtained in this study when the RH was changed slowly in small stages.
The weight change was found to average 7.7 mg per 17, increment in RH. Further
studies indicated that the history of the filter affected any subsequent equil-
ibration attempts with water vapor. All filters in this study were equilibrated
for 24 hours in an enclosed chamber which was maintained at 21 + 1°C
(52-60% RH); weighings were conducted to the nearest 0.1 mg. Although the
corrective weight term only approximated a first-order attempt, project data
demonstrated sufficient accuracy in this approach for our purposes.
Millipore Fluoropore Filters
Fluoropore filters consist of teflon bonded to high density polyethylene
netting. The filter weights do not^change appreciably with R H and the filters
equilibrate rapidly. These filter media were stored before weighing at 21 + 1°C
5-1
-------
and 52-60% RH in order to achieve accurate weights and to minimize static
charge. During weighing, the filter samples were exposed to p-radiation from
a 10 me Kr85 source to eliminate any residual static charge. Weights of these
filters were measured on a microbalance to a accuracy of + 2 us and were not
corrected for relative humidity.
X-RAY FLUORESCENCE ANALYSIS
Energy dispersive x-ray fluorescence was used to analyze all of the fine
and coarse particulate filters of the dichotomous samplers. The xrf equipment
consisted of a Siemens Kristalloflex 4 x-ray generator and a Siemens VRS Vacuum
X-ray Spectrometer with a ten sample tray and automatic sample changer. A
lithium-drifted silicon detector (United Scientific Spectrace Model 105-42) was
used with a Nuclear Semiconductor Model 513 amplifier and the data was processed
on a Tracor Northern TN 2000 X-Ray Analyzer. All initial and final data were
stored on floppy disks.
The TN 2000 software included a package (Super ML) which allows for back-
ground correction and the deconvolution of overlapping x-ray spectra..This
system permits the simultaneous quantitative analysis of several elements, even
when their spectra overlap. Input into the program consists of element peak
shapes generated from pure samples, and calibration curve slopes and intercepts.
Each sample was analyzed twice, once for the transition metals (vanadium,
chromium, manganese, iron, nickel, and zinc) and again for the other elements
(calcium, silicon, sulfur, aluminum, lead, and bromine)- The transition metals
were analyzed with an aluminum filter inserted over the x-ray tube to reduce
spectral lines inherent from the geometry of the equipment and to enhance the
analytical sensitivity toward these metals. No filter was used in the analysis
for bromine, lead, and the lighter elements. Semiquantitative data were also
obtained and stored for titanium, cobalt, and copper; these metals were not
5-2
-------
of immediate concern and, therefore, calibration factors are not currently
available.
The majority of the quantitative xrf calibration standards were prepared
in this laboratory by aerosol generation. The procedure involved the deposition
of aerosols of the desired elements onto 142 mm filters. Several deposition
times were used to produce a graded series of loadings. Smaller samples were
cut from each large filter and analyzed setniquantitatively by xrf techniques.
One sample in each concentration range was analyzed by the New York State
Department of Health (typically by atomic absorption spectroscopy) to produce
a calibration curve for that metal. The calibration curves were generated from
the least-squares straight line of the data and forced through the zero intercept.
The remaining filters for that metal were then normalized to this resultant
curve.
Detection limits were calculated in Table 3 from the formula D.L. = 2m/CB>
where m is the slope (micrograms/sq. centimeter/pulse count) of the calibration
curve and Cg is the background pulse count.
TABLE 3. XRF DETECTION LIMITS
ELEMENT LINE
Mv «
^Qffl
Q -rr
L^fi
K^yQ
f^a V
^*fyfl
V Kg'
Cr K£
Mn Ka
Fe KQ,
Ni K^
Zn KQ,
Br KQ,
Pb Lo
DETECTION
pg/Cm2
1.40
1.50
0.09
0.02
0.02
0.01
0.01
0.01
0.02
0.03
0.33
0.15
LIMITS
ng/m3 *
600
650
40
10
10
5
5
5
10
15
145
65
^Approximate airborne concentration detection limits
when based on a 37 cubic meter average air volume.
5-3
-------
Energy calibration of the multichannel analyzer system was performed daily
using a titanium-zirconium standard. All xrf spectra of all filter samples
were accumulated for 200 sec under vacuum over the energy range 0 to 20 Kev.
The xrf tube (molybdenum) was operated at 35 Kv and 10 ma without an aluminum
xrf filter for the analysis of the non-transition elements. When the aluminum
filter was employed in the analysis of the transition metals, the current was
increased to 16 ma. A coarse collimator was used for all analyses.
ION CHROMATOGRAPHY
Ion chromatography was used to analyze aqueous extracts of both the dichot-
omous fine and coarse particulate filters after these filters had already been
analyzed by xrf spectroscopy. The apparatus consisted of a Dionex Model 10
Ion Chromatograph which was interfaced to a second similar unit that had been
constructed in this laboratory. Sample loops and a splitting valve allowed for
simultaneous sample injection into each of the two units. The Dionex unit was
equipped with analytical and suppressor columns for anion analysis while the
second unit was equipped for cation analysis. This system permitted the simul-
taneous analysis of anions (fluoride, chloride, bromide, nitrite, nitrate,
phosphate and sulfate) and cations (sodium, potassium and ammonium) in a single
sample.
Samples were extracted on a shaker table for 24 hrs. with 25 ml of distilled
deionized water. The extracts were loaded into a Technicon Sampler IV from
which they were drawn through the rotary injection valve by a small pump. Sample
injection was pneumatically activated by a pre-programmed integrator.
Output of the conductivity meter was recorded graphically and simultaneously
analyzed with an integrator (Columbia Scientific Industries Supergrator 3).
Quantitative data was obtained by comparison of sample peak heights to the peak
5-4
-------
heights of standards. Calibration standards were prepared gravimetrically from
analytical reagent grade chemicals and were processed after every 10 samples to
provide a system check.
The anion chromatography system consisted of a 3 x 150 mm precolumn, a
3 x 500 mm separator column and a 6 x 250 mm suppressor column. The eluent
was a aqueous NaC03 - NaHCOg buffer and the suppressor regenerent was dilute
I^SO^.. The cation chroma to graphic system consisted of a 3 x 150 mm precolumn,
a 6 x 250 mm separator column and a 9 x 250 mm suppressor column. The cation
eluent was dilute HN03 and the suppressor regenerent was dilute NaOH.
SCANNING ELECTRON MICROSCOPY AND ELECTRON MICROCROPROBE ANALYSIS
The xrf analysis of the dichotomous filters provides much information about
the total particulate composition but provides little direct information on the
composition of individual particles. Knowledge of the physical and chemical
characteristics of individual particles is more useful in defining source
categories than are the xrf properties. Therefore, individual particles were
analyzed by scanning electron microscopy and electron microprobe analysis.
Instrumentation consisted of a Coates and Welter field emission scanning electron
microscope interfaced with a Princeton Gammatech energy dispersive x-ray analyzer.
In order to obtain an extremely flat field and a sample of particulates
with good spacial separation, a special sample collection was conducted. The
samples were collected by dichotomous samplers using Nucleopore filters
(1 micron diameter pore size, 1 x 10 pores/cm^). The field run was conducted
for a period of six hours on January 25, 1979 from 9:00 a.m. to 3:00 p.m.
Portions of the fine and coarse particulate filters exposed at Sites 5 and 6
were coated with carbon and examined by sem and by electron microprobe analysis
using energy dispersive x-ray spectroscopy. About 25 particles on each filter
5-5
-------
were selected at random to represent various size and shape categories. For
each particle, the beam was placed on the area of interest and counts above
background for each of the elements of interest were recorded.
5-6
-------
SECTION 6
SUSPENDED PARTICULATE DATA
WHATMAN-41 HI-VOL DATA
With the exception of Site 4, each of the sampling sites which were used
in this study were also maintained by New York State as hi-vol air sampling
stations using glass fiber filters. A summary and comparison of this data
appears in Table 4 and are shown graphically in Figure 5.
Whatman-41 Glass Fiber Ratio
No. of Average SP Average TSP Ave. TSP/
Site Samples Q-ig/m3) (|ig/m3) Ave. SP
1
2
3
5
6
42
38
45
103
40
76.62
76.21
68.93
100.54
45.92
98.10
92.10
82.67
126.37
37.22
1.28
1.20
1.20
1.26
.81
TABLE 4
STATISTICAL CHARACTERISTICS OF HI-VOL MEASUREMENTS
USING WHATMAN-41 AND GLASS FIBER FILTER MEDIA
It is evident from the ratio data in Table 4 that the urban sites (1,2,3, and 5)
differ markedly from the rural background station (Site 6). Application of a
test for homogeneity of variance indicated that the urban site data could be
grouped for subsequent regression analysis but that the background site could
not be so grouped.
Linear regression analysis of the urban data yields the least squares line:
Y = 1.34 + 1.22X
where: Y = TSP concentration using glass fiber filters
X = SP concentration using Whatman-41 filters
6-1
-------
380
360
340
320
300
280
260
_ 240
(O
£
o» 220
oo 200
I
ct
ijj 180
CD
u.
oo 160
CO
140
120
100
80
60
40
20
*
*
^
to I line
Site 6 data is circled
° 2° 4° 60 80 ,00 120 140 160 ' ,80 20O 220 240 260 280 ' 30O
WHATMAN-41 SP(ug/m3)
Figure 5. RELATIONSHIP OF SUSPENDED PARTICIPATE CONCENTRATION
USING GLASS FIBER AND WHATMAN - 41 FILTER MEDIA
6-2
-------
The correlation coefficient of .91 and corresponding R.2 value of .83 are
indicative of a very good linear fit explaining some 83% of the variation
inherent in the data. Because the intercept value 1.34 is comparatively low,
forcing the regression line through the origin produces very little change in
the final results. The resulting equation is:
Y = 1.24X
where Y and X are as above. The correlation coefficient and R2 value did not
change significantly from the least squares result. This latter equation
indicates that on the average, glass fiber filter media at the urban sites
will lead to concentrations of TSP about 24% greater than that resulting from
the use of Whatman-41 filters.
Separate regression of the Site 6 data yielded the least squares line:
Y = .91X - 4.63
where X and Y are as above. The fit is also quite good as indicated by its
correlation coefficient of .91 and R2 value of .84. Forcing this line through
the origin results in the equation:
Y = .83X
with no significant reduction in the correlation coefficient or R2 value.
Site 6 data in Figure 5 is circled to show that most of it lies below the
1:1 line within a region bounded by 100 |j.g/m3. This observation contrasts
with the urban data within this graphical region as indicated by the ratio
data in Table 4. The regression equation for Site 6 indicates that hi-vols
equipped with Whatman-41 cellulose filters collect 17% more particulates at
the rural station than hi-vols employing glass fiber filters. These analytical
results are provided here so that one may relate the Whatman-41 data in the
project in terms of standard glass fiber data.
6-3
-------
Whatman-41 suspended particulate (SP) averages are shown in Figures 6 and
7. It should be noted that all averages in this report are arithmetic unless
otherwise stated. Figure 6 illustrates the means of the monthly SP averages
among the six sites, together with the maximum and minimum month averages.
Figure 7 compares the means of the average urban monthly SP values observed at
Sites 1-5 and similar monthly data from the rural station (Site 6).
In Figure 6 the urban averages fall into two categories: Sites 1,2, and
3 (Buffalo) and Sites 4 and 5 (Lackawanna). The SP data at the Lackawanna
sites is approximately 30% greater than the SP data at the Buffalo sites. These
large differences are certainly due to local effects since the urban sites are
located over an aerial distance of only 3.5 miles. In contrast to the urban
sites, the SP loadings observed at Site 6 are considerably lower. All sites
have maximum monthly averages which are 2-3 times the respective minimum
monthly averages. In Figure 7 the maximum monthly average for all sites
occurred in May. The'minimum for all sites occurred in September, except Site
3 where it occurs in January. The month-to-month variations (Figure 7) for a
composite of the urban sites (1-5) are compared against the rural site data.
The two traces follow each other fairly well with a deviation noted in December
when the urban SP remains high while the background value drops sharply. This
SP difference is not readily explainable at this time although it may somehow
be related to the "lake" effect.
The effects of Lake Erie on TSP measured in the Buffalo-Lackawanna area
have been studied. Anderson (8,9) developed a mathematical model for predicting
monthly TSP arithmetic averages at Site 5. The model included a term containing
the lake temperature minus the land temperature (AT), a parameter for steel
production (P), and a constant. His equation is:
TSP(ng/m3) = p(0-20 + 0.0123 A T) + 76
6-4
-------
150-
100-
ro
>^
o>
0,
0.
en
50-
< HIGHEST MONTH AVG.
TOTAL AVG.
«, LOWEST MONTH MQ.
12345 6
SITE NO.
FIGURE 6. WHATMAN-41 SP - MONTHLY AVERAGES AND EXTREMES
6-5
-------
100-
ro
e
\
en
3,
Q.
CD
50
MAR
URBAN SITES AVERAGES
RURAL SITES AVERAGES
JUN . SEP
1978
DEC MAR
1979
FIGURE 7. WHATMAN-41 SP - MONTHLY VARIATIONS
6-6
-------
According to the model, the relatively cold lake water chills the lower atmo-
sphere in the spring, stabilizes it, and thereby prevents good mixing of
emissions. The TSP therefore is expected to be elevated in March, April and
May. In the fall when the water is still warm, the lake heats and humidifies
the lower atmosphere and generates instability and turbulence. The resultant
mixing and dispersion of particulate emissions causes the decrease in TSP for
October, November, and December. This trend assumes that steel production does
not vary significantly. The model predicts that steel production will have a
much greater effect on the observed TSP during the warm months than during the
cold months. The model predicts that TSP will be independent of steel pro-
duction if A T = -16°F and that TSP will decrease with increased steel produc-
tion if A T < -16°F. Such predictions begin to show the limitations of the
model. However, such conditions for A T occur infrequently and are expected
to have a minor effect on the model's fit to the observed data. If the factor
for steel production in the model equation is set equal to zero, the resulting
TSP value is 76 (ig/m^ (arithmetic average or 68 ng/mP geometric average).
The data collected within this project has an overall annual pattern
which is consistent with the model although no quantitative checks were made.
While it is obvious that steel production should affect TSP and reasonable
that the lake have an effect, the background TSP concentration of 76 ng/ra"* is
more difficult to rationalize. This value must be looked upon as a "background"
which is not affected by atmospheric turbulence or steel production. The
value of 76 |ig/m^ appears too high when considering the TSP data in Figure 7
for the background site.
6-7
-------
DICHOTOMOUS SAMPLER DATA
The main reason for employing dichotomous samplers in this study was to
obtain chemical composition data for two size fractions of particulates.
Various emission sources, both natural and anthropogenic, have characteristic
particle size distributions and chemical compositions which can aid in deter-
mining their respective contributions to the overall particulate burden. This
section is concerned with the dichotomous sampler data from a gravimetric
standpoint only, while a later section will consider the composition of the
particulates which is distributed between the fractions.
Table 5 summarizes the dichotomous sampler data for each of the six sites.
Probably the most important aspect of this data is the ratio of the fine particle
weight to the total particle weight. This ratio is a function of:
(a) the fine to coarse particle cut point of the dichotomous sampler;
(b) the upper particle size exclusion limit of the dichotomous sampler; and
(c) the size distribution of the particulates in the air being sampled.
TABLE 5. SITE DATA SUMMARY FROM DICHOTOMOUS SAMPLERS
Site #
No. Samples 54 46 70 64 66 68
Fine Og/m3) 41 42 34 44 47 24
Coarse Gig/m3) 20 22 19 26 27 9
Total Gag/m3) 61 64 53 70 74 33
Fine/Total (%) 68 66 65 63 64 73
No. Samples 28 23 33 27 24 45
Total (Dichotomous)* .76 .67 .69 .74 .78 .67
Hi-Vol (Whatman-41)
*The data base which was used in this ratio was comprised of dichotomous
sampler runs which spanned 23-24 hour elapsed time to be consistent
with the hi-vol data.
6-8
-------
Assuming the effects of (a) and (b) to be relatively constant and equal for all
six samplers, changes in the weight ratio (fine/total, F/T) will indicate changes
in the particle size distribution of the measured air mass.
Plots of this ratio with respect to the time of year are shown in Figure 8
(Site 3) and Figure 9 (Site 6). The two plots are surprisingly similar even
though they represent urban and rural stations. The fine/total particle
percentage rises slowly and erratically until late February at both sites, after
which it drops sharply. The slopes of the least squares straight line through
each set of data (until mid-March) differ by less than 10% and the day-to-day
variations are fairly similar. Because these sites are located far from each
other (approximately 16 miles) and in vastly different environments (urban
versus rural), it becomes obvious that a major component of the fine/total
particle percentage affects both the urban and background sites with similar
intensity. The minima which occur in March appear to be associated with
decreases in sulfate and ammonium concentrations. This decrease in F/T in March
also coincides with the spring thaw. A decrease in the production of fine
particles resulting from less combustion of heating fuels may begin to be
realized at this time of year. This effect may begin to be coupled with higher
winds and an increased entrainment of larger particles to dramatically change
the F/T ratio. Site-to-site variations (Table 5) in F/T are small at the urban
sites; and the urban site values are significantly lower than background
(Site 6). Since the coarse particle components arising from vehicular reentrain-
ment and industrial activities are much lower at Site 6 relative to the urban
sites, the F/T ratio at Site 6 is larger.
The ratios of total dichotomous to Whatman-41 suspended particulates are
shown on the sixth line of Table 5. There are no distinct site-to-site
variations. The data do indicate, however, that one-quarter to one-third of
6-9
-------
1 0 -
I
I1
o
09 -
0.8 -
0.7 -
06 -
O5 -
0.4 -
SEP
OCT I NOV
DEC | JAN | FEB | MAR
FIGURE 8. SITE 3 RATIOS OF PARTICULATE WEIGHTS (FINE/TOTAL)
-------
1.0 -
0.9 -
0.8 -
O.7 -
0.6 -
0.5 -
0.4 -
SEP I OCT I NOV I DEC I JAN I FEB I MAR
FIGURE 9. SITE 6 RATIOS OF PARTICULATE WEIGHTS (FINE/TOTAL)
-------
the suspended particulates collected by the hi-vols is not collected by the
dichotomous samplers. The particulates which are not collected by dichotomous
samplers most likely represent that fraction of the coarse particulates with
particle diameters above the exclusion limit of the dichotomous sampler but
below that of the hi-vols. Thus, only 40-60% of the total coarse particulate
fraction is actually collected by the dichotomous samplers. Therefore, the
contribution of coarse particles to the hi-vol SP or TSP could be considerably
greater than is indicated by the dichotomous sampler data.
A high percentage of fine particles observed at all six sites appear to be
transported into the Erie County area, predominantly from the southwest from
across Lake Erie. The pollution roses for FSP concentrations at each site are
presented in Figure 10. The solid lines show the average FSP values together
with their standard deviations. The dotted lines represent dosage roses, which
are actually frequency plots of pollution rose data which was normalized to
100%. For all sites the fine particles predominantly arrive from the south-
west quadrant, accounting for approximately three-quarters (68-77%) of all the
observed FSP. This data was obtained from a wind sector analysis approach
which was extended to each measured chemical variable in this study.
Further interpretation of Site 6 data shows that a summation of the
project's average values of the sulfate, nitrate, and ammonium components from
Appendix A accounts for almost one-half (45%) of the observed average FSP. It
does not seem likely that much of these materials (sulfate, nitrate, and
ammonium) could arise from the beach proper, which is located approximately
one-quarter mile southwest of Site 6. Particulate material from the beach
would be expected to contribute to the coarse particle fraction, as opposed to
the fine particle fraction, and would not be expected to contain sulfate,
nitrate, and ammonium at the levels observed in the FSP samples. It is more
6-12
-------
SITE I
SITE 4
SITE 2
a*
SITE 3
WE w tTg*
SITE 6
Figure 10. POLLUTION AND DOSAGE ROSES FOR FSP
6-13
-------
reasonable to assume that the FSP component at Site 6 arrives from the west of
New York State. Since the average FSP at Site 6 in Table 5 is about one-half
that observed at the urban sites, then one could expect that 257=, of the
observed urban FSP is comprised of sulfates, ammonium, and nitrate components
necessarily produced outside of New York State.
With such an interpretation it must be remembered that the background or
incoming FSP, its absolute value and chemical composition, must be expected to
overlay that FSP which is produced locally in the Erie County area. However,
such an extrapolation to the CSP fraction (Figure 11) is not so readily made
since transport over short distances may not be as uniform as for fine
particles. In other words, the CSP fraction observed at Site 6 may bear
little relation to that observed at the urban sites in regard to the CSP
absolute value or its chemical composition.
GCA AMBIENT PARTICIPATE MONITOR (APM) DATA
The APM was programmed to measure suspended particulates in one hour
intervals to permit the measurement of diurnal variations. The data in
Figure 12 presents the wind rose for the APM data which was collected during
an eighteen day period during July-August, 1978. Such data was only available
from Site 5 since use of the instrument was limited.
The compass has been divided into 18 sectors of 20° each; the average
suspended particulate concentrations for those hours in which the wind was
from that sector is plotted radially. Although Figure 12 shows that the
southwest quadrant possesses the strongest input of particulates, it is the
dosage rose in Figure 13 which more effectively displays the vector strengths
when combined with frequency of occurrence. The dosage rose data is obtained
by multiplying the average suspended particulate concentration (pollution
6-14
-------
SITE <
flTC t
FIGURE 11. POLLUTION AND DOSAGE ROSES FOR CSP
6-15
-------
330
320
220
210
30
2OO 190 WO 170 16O
150
140
FIGURE 12. WIND ROSE FOR APM SUSPENDED PARTICULATES AT SITE 5
6-16
-------
N
320 330 340 350 0 10 20 30
310
230
220
40
140
210 200 190 180 170 160 150
FIGURE 13. DOSAGE ROSE FOR APM SUSPENDED PARTICULATES AT SITE 5
6-17
-------
3-
i/>
120-
110-
100
90
o 80
o
T3
O>
T3
Q_
<
70
60
50
40
30
20
t
6 12 18
Hour of Day
24
FIGURE 14. DIURNAL VARIATION OF SUSPENDED PARTICULATES
6-18
-------
rose data) for each wind sector by the number of occurrences of wind arising
from that sector and dividing this value by the sum of all values from all
the sectors.
The diurnal variation of suspended particulates is presented in Figure 14.
From 0500 hours to 1900 hours, the suspended particulate concentration rises
sharply and steadily and then drops precipitately until 2400 hours. A sub-
sequent rise occurs until the daily low is registered between 0400 and 0500
hours. This data would at first suggest an increase in local particulate
production throughout the day. However, in view of the data presented in
Figure 15, the previous fact would not be the major reason for the observed
diurnal variation. In fact, it appears that the "lake effect" strongly
influences the observed profile (Figure 15). Late at night and early in the
morning, land breezes tend to proceed toward the lake where warmer air is
rising. Throughout the day the land heats up and reaches a peak in the late
afternoon. The air rising above the land is now met by cooler breezes
approaching more from the west from Lake Erie. The hourly wind direction has
been observed to rotate clockwise through 360° and results in a more complex
picture for the interpretation of suspended particulate sources. The strong
resemblance of Figures 14 and 15 suggests that most of the diurnal variation
of suspended particulates can be explained by changes in wind direction and
the unique source-sampler geometry present at Site 5. Since most of this APM
data was obtained in July 1978, it is normal at this time of year for wind to
arrive predominantly from the southwest. Such patterns may shift during other
portions of the year.
Since the APM sampler is sufficiently different from hi-vol sampler
operation, the following information is intended to briefly describe the
6-19
-------
80
(VJ
70
(VJ
60
50
.£
o
r
o
20
10
6 12 18
Hour of Day
24
FIGURE 15. SOUTHWEST WINDS VS. TIME OF DAY
6-20
-------
150-
E
o>
T 100-
£
Ji
3
a>
a.
U)
en
50
Least Squares Straight Line
1M Ratio Line
50 100
Whatrnan-41 Hi-Vol SP
150
200
FIGURE 16. COMPARISON OF APM SP TO HI-VOL SP
6-21
-------
relationship of their resultant data. It would not be expected that each
instrument would measure the particulate air mass in precisely the same manner.
The data in Figure 16 permits a comparison to be made between hi-vol
(Whatman-41) and APM data. The APM hourly values of suspended particulate
concentrations are summed and plotted against the hi-vol SP value for the
same 24-hour period. In every case the APM values are lower than the hi-vol
values (dotted line represents one-to-one correspondence). The solid line is
the least-squares straight line fit to the data. Although the correlation
coefficient for fit (R^) is only 0.70, the intercept of the line is very good.
The low R2 value could be due to the small data set and the compounding of
errors in both measurements.
6-22
-------
SECTION 7
PARTICULATE SULFUR AND SULFATE
Early project data had indicated that sulfur-containing particulates form
a significant percentage of the total particulate aerosol in the Niagara Frontier
Air Quality Control Region. The following dichotomous sampler data is presented
to define these site-to-site concentrations and variations.
The data in Figure 17 was obtained from the analysis of approximately 720
air filter samples which were collected over an eight month period. Total
sulfate from the combination of fine and coarse particulate fractions is
expressed as monthly averages. Although annual data is lacking here, the sul-
fate pattern appears consistent with the general contention that sulfate con-
centrations are higher during the summer period and lowest during the winter
months. The data for total sulfate in Table 6 presents the maxima, minima, and
arithmetic averages which were found for each site throughout the course of this
investigation.
TABLE 6. TOTAL SULFATE FROM DICHOTOMOUS SAMPLERS 0-ig/m3)
August 1978 through March 1979
Site No.
Maximum
Minimum
Arith. Avg.
1
51.0
1.0
12.1
2
33.8
0.8
11.8
3
57.1*
0.8
10.2
4
71.4
0.8
12.2
5
68.5
1.0
12.1
6
44.3
1.1
7.9
*Represents Fine Particle Fraction Only.
7-1
-------
Siti
Sift 4
50-
40-
50-
20-
10-
0
ASONDJFM
ASONDJFM
Site 2
50-
40
o
i30
S20-
10-
SiteS
50-
i i i i i i i i
ASONOJFM
i
A
L I I I I '
S 0 N D J F M
Sitt3
50-
40-
10-
' I I I I I
A S 0 N D J
Site6
50-
F M
A S 0 N D J F
i
M
FIGURE 17. TOTAL SULFATE - MONTHLY AVERAGES PER SITE (ng/m3)
7-2
-------
The minimum sulfate concentrations at each site are fairly constant at 1
while the mean of the urban arithmetic averages is 11.7 iig/m^. However, the
o
mean sulfate concentration at Site 6 exhibits a slightly lower value of 7.9 ng/m .
The singular high sulfate values observed in Table 6 may be associated with
particular weather patterns and/or higher than normal particulate loadings and
are presented to simply illustrate the high concentrations which were obtained
under actual field conditions.
The monthly averages per site for suspended particulates are presented in
Figure 18. Trends are displayed for the fine, coarse, and inhalable particulate
(fine plus coarse) fractions. A comparison of the sulfate data in Figure 17
with the FSP data in Figure 18 exhibits very good correlation. Upon consider-
ation of the findings in Section 6, it is concluded that a significant percentage
of fine particulates arrives from the west from outside of New York State. It
is similarly concluded that most (> 75%) of the sulfate material which enters
New York State arises from the west beyond Lake Erie. Although the data in
Table 6 for Site 6 indicates an annual mean of 7.9 i-ig/m^ for sulfate, this value
is 3.8 (ig/m3 lower than the mean value observed for the urban sites. It is
possible that this enhancement of observed sulfate levels at the urban sites
may arise from local emission sources within the Buffalo-Lackawanna area. This
increase in sulfate represents almost 33% of the observed total sulfate concen-
trations. It is difficult to explain this sulfate increase with regard to the
industrial processes which are located between Lake Erie and the line of field
stations.
Additional data in Figure 19 supports the conclusion that much (50-99%) of
the sulfur in the particulate aerosol exists in the form of sulfate. In general,
all sites exhibit a decline in the sulfate/sulfur percentage during the colder
months. The decline in this ratio may be associated with the increased usage
7-3
-------
Sit*1
Srtt4
10
100-
80-
6 60
40
20
100
0«-r
10
120-
100-
80-
60-
40
20
0
ASONDJFM ASONDJ
Site 2 Sit* 5
120-1
~~l~l I T I I 1 I
ASONDJFM
~lIIIIT
A S 0 N 0 J
F M
Site3
Sit* 6
100-
80-
«°-
«0:
20
100
I I T~
ASONDJFM
A S 6 N
Ti
FIGURE 18. DICHOTOMOUS SAMPLER SUSPENDED PARTICULATES -
MONTHLY AVERAGES PER SITE (|ig/m3)
7-4
-------
Site 1
Site 4
100-
80-
o" 60-
V)
$ 40-
20-
0
100
OH-
ASONOJFM ASONDJFM
Site 2
SlteS
100-
80-
-------
of heating fuels and the increased generation of particulates which contain
forms of sulfur other than sulfate. The data which is presented in Figure 20
represents fine particulate sulfate which is expressed as a percentage of IP.
Fine particulate sulfate is considered here since less than 3% of the total
sulfate was ever found to reside in the coarse particulate fraction. The
general trends exhibited in Figure 20 show the sulfate percentages to be fairly
constant at all six sites throughout the specified eight months. The mean
overall sulfate percentage is approximately 1870. From this data it appears
that the sulfate component of IP (or TSP) is not significantly affected among
the urban sites by heavy industrial operations or heavy vehicular activities.
Even the background Site 6 curve is very similar to the urban site data. Such
behavior for the sulfate component is more consistent with the long range
transport of sulfates into New York State from the predominantly southwesterly
winds.
7-6
-------
Site 1
Site 4
100-
80-
0*" 60-
co
84 40-
20-
0
100-
80-
0 60-
w
^ 40-
20-
0
100-
80-
O 60-
w
84 40-
20-
0
100-
^- *-~ ~
ASONDJFM "ASONDJFM
Site 2
wo-
-
SiteS
ASONDJFM ASONDJFM
Site 3
WO-
Site 6
^-^
ASONDJFM "ASONDJFM
FIGURE 20. FINE PARTICLE SULFATE AS A PERCENT OF IP
7-7
-------
SECTION 8
CHEMICAL COMPONENTS - GENERAL OBSERVATIONS
INTRODUCTION
Data in this section will be presented for the various chemical components
which were found to occur in the particulate samples as determined by xrf and
ion chroma tographic methods. The discussion of all components~wi11 be limited
to overall observations and generalizations. However, more detailed information
concerning suspended particulates and sulfates can be found in Sections 6 and
7, respectively.
Average concentrations of the chemical components which were observed from
the overall project are shown in Table 7. These values represent the averages
for total dichotomous suspended particulates, where initially the individual
fine and coarse measurements for each component were summed. Additional infor-
mation contained in Table 8 represents for each component the percentages of
their mean total concentrations which are found in the fine particulate fraction.
For example, 81% of the lead at Site 1 was observed in the fine particle
fraction. In fact, at all six sites lead is found predominantly in the fine
fraction, urban and rural sites being similar. In contrast to lead, only 15-20%
of calcium is represented by fine particles at each of the six sites. The large
differences which are observed for the various chemical components in their
degree of distribution between the two size fractions (fine and coarse) permits
one to distinguish among the sources of such materials. The lead particles are
mainly fine material and are consistent with automotive-type particle emissions,
8-1
-------
TABLE 7. AVERAGE VALUES OF CHEMICAL SPECIES FOR
TOTAL DICHOTOMOUS SUSPENDED PARTICULATES
DICHOTOMOUS TOTAL (ng/m3)
Site No.
SPECIE
Pb
Br
Zn
Ni
Fe
Mn
Cr
V
Ca
S
Si
Al
F"
ci-
Br-
N02~
N03-
804=
1
844
1130
191
12
1848
57
3
19
2170
5794
7017
1566
46
287
58
276
2162
12968
2
821
988
67
11
2453
89
3
13
2521
5577
7307
1523
52
315
96
374
2273
11940
3
472
813
58
9
1815
49
2
11
2153
5013
6128
1274
61
295
52
213
1195
11240
4
860
829
138
11
4057
115
4
12
4032
5992
6515
1448
88
603
79
237
1732
12758
5
943
845
146
12
4824
104
3
15
4089
5653
6063
1505
123
745
58
320
1603
12126
6
235
272
22
7
446
15
1
7
466
3590
4601
1039
59
102
21
185
600
8306
Na+
K+
NH4+
474'
376
5315
323
403
5015
382
356
3637
712
915
3987
571
1315
3603
248
194
2759
3-2
-------
TABLE 8. CHEMICAL SPECIES - PERCENTAGE FOUND
IN FINE PARTICULATE FRACTION
ELEMENT
Pb
Br
Zn
Ni
Fe
Mn
Cr
V
Ca
S
Si
Al
F'
Cl"
Br~
N02"
N03"
804"
Na+
K+
NH4+
SITE NO.
1
81
82
90
58
37
53
38
82
14
88
26
36
72
26
88
92
78
90
41
82
95
2
83
81
88
45
40
51
47
62
14
89
26
37
73
48
69
94
75
92
51
83
97
3
75
78
86
56
35
47
50
64
14
89
23
35
64
18
88
92
54
92
52
88
97
4
86
77
89
55
45
61
44
58
19
88
24
40
49
46
57
75
68
90
56
93
98
5
87
76
85
58
39
51
47
67
15
87
21
36
37
59
86
87
63
90
63
93
99
6
82
69
86
57
36
60
62
57
16
92
27
36
71
39
62
81
38
93
54
87
98
8-3
-------
The lower value (Table 7) which is observed for lead at Site 6 as compared to the
urban sites may be reflective of the differences in vehicular traffic densities.
The fact that the Site 3 value is one-half that of all other urban sites is more
difficult to explain. The Site 3 station is the tallest (15m) above ground
level and sampler height would certainly be expected to have an effect on
particulate measurements. However, Sites 1 (10m) and 2 (12m) do not appear to
be sufficiently different in height in order to account for the large changes
in the observed measurements. The contention here is that height is not an
important factor in explaining the lower lead level at Site 3. Further support
for this conclusion can be obtained from Table 10 where the percentage of lead
in the fine fraction is found to be relatively equal at all urban sites. Certainly
industrial lead emissions are possible within this region. However, overall
site averages in the urban sector do not indicate a major impact from an
industrial point source.
The calcium component appears mainly as large particles (3-15 micrometers
diameter). This size classification allows one to conclude that the calcium
sources are most likely soil and/or slagging operations. The physical crushing
and grinding of slag material associated with steel production is a mechanical
process which cannot produce fine particles below 3 microns diameter. Thus, the
calcium-containing coarse particulates most likely represent a combination of
these two principal sources and it remains for the CEB method and refined
/
chemical profiles to distinguish the actual contributions from either source
category.
At all sites the predominant components are silicon, sulfur, calcium,
aluminum, and iron, while the corresponding major water soluble materials are
sulfate, nitrate, and ammonium ions. This statement is made aside from the
8-4
-------
fact that carbon, hydrogen, oxygen, and nitrogen were not determined but which
certainly form significant percentages of the suspended particulates.' Figures
21-26 show site-to-site variations for all measured chemical components as
represented by overall project averages of the combined fractions. This data
is presented in a different form in terms of "enrichment factors" in Table 9.
The site-to-site "enrichment factor" here is obtained as the ratio of the
average of the three Buffalo sites to the average for the rural site. Similar
treatment was afforded the data from the two Lackawanna stations. These
"enrichment factors" help to indicate which of the chemical components result
mainly from the urban/industrial environment and which components more likely
comprise the general background particulates.
Fluoride at Sites 1 and 2 (Table 7) was the only component which was not
enriched above background. The following components in Table 9 showed only
moderate enrichments (1.2 - 1.9)
vanadium nitrite
nickel sulfate
sulfur fluoride (in Lackawanna)
silicon sodium (in Buffalo)
a luminum aramon ium
On the other hand, the following components exhibited significant enrichments
(2.0 - 4.9) --
lead calcium (in Buffalo)
bromine chloride (in Buffalo)
zinc (in Buffalo) bromide
iron (in Buffalo) nitrate
manganese (in Buffalo) potassium (in Buffalo)
chromium
8-5
-------
TABLE 9. ENRICHMENT FACTORS FOR CHEMICAL COMPONENTS
SPECIES
Pb
Br
Zn
Ni
Fe
Mn
Cr
V
Ca
S
Si
Al
F"
Cl"
Br"
N02"
N03"
so4=
Na+
K+
NH4+
Buffalo
3.3
4.1
4.9
1.5
4.7
3.7
2.4
1.9
4.3
1.5
1.4
1.4
0.9
2.9
3.3
1.6
3.1
1.4
1.6
2.0
1.7
La cka wanna
4.1
3.4
6.5
1.6
11.6
6.9
2.8
1.8
9.2
1.5
1.2
L.5
1.8
6.6
3.3
1.5
2.8
1.5
2.6
5.7
1.4
8-6
-------
Pb
Br
Zn
Ni
Fe
Mn
Cr
V
Ca
S
Si
Al
Br~
N02"
N03'
TABLE 10.
FINE
CHEMICAL SPECIES - PERCENTAGE COMPOSITION
OF FINE AND COARSE PARTICLE FRACTIONS
Na"1"
K+
NH^
1
1.68
2.27
0.42
0.02
1.69
0.07
<0.01
0.03
0.76
12.60
4.51
1.38
0.08
0.18
0.13
0.62
4.15
28.83
0.47
0.76
12.51
2
1.63
1.92
0.14
0.01
2.34
0.11
<0.01
0.02
0.83
11.95
4.60
1.36
0.09
0.36
0.16
0.84
4.10
26.43
0.40
0.81
11.76
3
1.62
1.87
0.15
0.01
1.89
0.07
<0.01
0.02
0.86
13.10
4.15
1.32
0.11
0.16
0.13
0.58
1.90
30.28
0.59
0.91
10.36
4
1.69
1.47
0.28
0.01
4.21
0.16
<0.01
0.02
1.72
12.01
3.63
1.33
0.10
0.64
0.10
0.41
2.69
26.27
0.92
1.94
8.97
5
1.77
1.38
0.27
0.02
4.08
0.11
<0.01
0.02
1.32
10.58
2.73
1.15
0.10
0.95
0.11
0.59
2.17
23.35
0.77
2.62
7.62
6
0.81
0.79
0.08
0.02
0.69
0.04
<0.01
0.02
0.31
13.99
5.26
1.60
0.18
0.17
0.06
0.64
0.95
32.86
0.57
0.72
11.42
COARSE
1
0.81
1.04
0.10
0.02
5.79
0.13
0.01
0.02
9.26
3.43
25.83
5.01
0.06
1.06
0.03
0.11
2.40
6.43
1.40
0.34
1.23
2
0.64
0.86
0.04
0.03
6.61
0.20
0.01
0.02
9.72
2.72
24.10
4.28
0.06
0.74
0.13
0.11
2.55
4.33
0.71
0.30
0.60
3
0.63
0.94
0.04
0.02
6.20
0.14
0.01
0.02
9.85
2.88
24.95
4.37
0.12
1.28
0.03
0.08
2.90
4.85
0.96
0.23
0.55
4
0.45
0.70
0.06
0.02
8.40
0.17
0.01
0.02
12.42
2.82
18.67
3.28
0.17
1.22
0.13
0.23
2.11
4.84
1.18
0.26
0.26
5
0.45
0.75
0.08
0.02
10.94
0.19
0.01
0.02
13.01
2.71
17.95
3.62
0.29
1.13
0.03
0.16
2.21
4.67
0.79
0.34
0.19
6
0.46
0.90
0.03
0.03
3.02
0.06
<0.01
0.03
4.17
3.09
35.73
7.04
0.18
0.66
0.09
0.37
3.99
5/86
1.21
0.27
0.69
-------
8H
io
o»
I"
o:
LJ
o
UJ
o
UJ 3-1
Vs-
2345 «
SITE NUMBER
FIGURE 21. SITE VARIATIONS FOR SILICON,
SULFUR, ALUMINUM, AND CALCIUM.,
8-8
-------
0.020-
0.015-
ro
a.
O
\-
cc
UJ
o
<
o:
UJ
0.010
Ni
0.005-
V
3 4
SITE NUMBER
FIGURE 22. SITE VARIATIONS FOR CHROMIUM,
VANADIUM, AND NICKEL.
8-9
-------
.200T
to
E
v.
o>
3.
*
z
a:
i-
o
o
e>
UJ
IT
LU
.150-
.100-
.050
FIGURE 23.
345
SITE NO.
SITE VARIATIONS FOR ZINC
AND MANGANESE.
8-10
-------
4-
ro
O
ce.
LU
o
O
o
UJ
QC
UJ
4 5
SITE NO.
FIGURE 24. SITE VARIATIONS FOR IRON,
LEAD, AND BROMINE.
8-11
-------
1.5H
(2345
SITE NUMBER
FIGURE 25. SITE VARIATIONS FOR SODIUM,
POTASSIUM, NITRITE, AND HALIDES,
8-12
-------
15-
g io-
Z
UJ
UJ
o
IT
UJ
5-
FIGURE 26. SITE VARIATIONS FOR SULFATE,
AMMONIUM, AND NITRATE.
8-13
-------
Very high "enrichment factors" were observed in Lackawanna for iron (11.6),
calcium (9.2), manganese (6.9), chloride (6.6), zinc (6.5), and potassium (5.7).
It appears that all six of these components can be related to the production of
steel. In the interpretation of this data, one should be aware that high
"enrichment factors" are not necessarily indicative of high contributions to the
overall observed TSP from emissions from a single source. However, the chemical
species with the largest "enrichment factors" will serve as chemical indicators
of the source categories which contribute to the TSP levels observed at the
downwind sites.
Additional information is presented in Table 10 to show the percentage
contribution for each species to the suspended particulate concentration for
both fine and coarse fractions. It should be kept in .mind that most of the
chemical' components are not found in pure form but rather as compounds such as
oxides, sulfides, carbonates, etc. When such anions are considered with their
cation counterparts, the overall percentage contributions to observed TSP are
much greater than the data in Table 10. As an example, if silicon is present
as common sand (SiC>2), the values in Table 10 must be multiplied by 2.14. If
calcium were present as the simple oxide (CaO), the calcium values in Table 10
would be multiplied by 1.4.
LIGHT ELEMENTS (Al, Si, S, Ca)
These four elements constitute individually and collectively the major
proportion of the coarse particulate fraction; and individually (for sulfur and
silicon) and collectively they comprise the major proportion of fine particulates
Their distributions vary considerably between the fine and coarse fractions as
shown in Tables 8 and 10.
Aluminum
Aluminum varies little among all six sites (Figure 21). Although aluminum
8-14
-------
exhibits a lower concentration at Site 6 (Table 7), it constitutes a larger
percentage of the TSP (Table 10) than at the urban sites, especially evident in
the coarse fraction. The reasonably constant concentration of aluminum at the
urban sites and its low "enrichment factor" over background suggest that its
source is predominantly soil.
Silicon
Silicon is the only chemical component except bromine which is more abun-
dant at Sites I and 2 than at Sites 4 and 5 (Figure 21). This observed trend
is difficult to explain as anything more than an increased soil contribution
to the TSP since a projected source such as cement or slag would also have
elevated the calcium levels. The enrichment of silicon above background for
the urban sites is only 1.4, far lower than for most other components*.
By sorting the silicon data for Sites 5 and 6 into twelve wind sectors
(each 30° in width) and plotting each sector average concentration, one can
overlay the results for both sites as in Figure 27. The information gathered
throughout the entire project shows a striking similarity (Figure 27) between
actual silicon concentrations for the urban station (Site 5) receiving the
greatest TSP loading and the rural station (Site 6) receiving the least. The
asterisks in Figure 27 represent the project's average concentration for that
site. The silicon trends at Sites 5 and 6 overlap to such a degree that it is
difficult to visualize any significant contribution to silicon at Site 5 from
industrial operations. This data suggests that the single major source of
silicon is soil. This fact is extended to all sites since the average silicon
values found in Table 7 appear to increase in the direction of increasing
traffic density. It is possible that the increased levels of silicon as one
proceeds from Site 6 to Site 1 may result from reentrainment due to the increase
f
in vehicular activity. While it is certain that the steel industry contributes
8-15
-------
300O-
K)
E
o
<
or
2
UJ
O
o
o
UJ
_i
UJ
200OH
100CH
0
Site 5
. v * .-"
....
3
E
6
S
9
W
10 H
12
N
FINE PARTICLE FRACTION
- Site 5
...... Site 6
Site 6 Represents the average of all data used
in the wind sector analysis.
3
E
6
S
9
W
10
12
N
COMPASS WIND SeCTORS
-------
to silicon emissions, any major impact among the urban sites is not evident.
All of the proceeding analysis is in contrast with the iron data which is pre-
sented in similar fashion in Figure 27. The site average data (asterisks) for
Sites 5 and 6 differ by a factor of 12 for iron and a factor of unity for silicon.
The iron concentrations at Site 5 bear little resemblance to that for Site 6 and
are indicative of sources of iron other than soil.
Sulfur
Sulfur is by far the largest single contributor to the fine particle fraction
if one does not consider the light elements (carbon, hydrogen, oxygen, and
nitrogen). Approximately 88% of the total observed sulfur is found in the fine
fraction were it constitutes about 12% (Table 10) of the FSP fraction at the
urban sites and 14% at the rural station. In t"he coarse particle fraction,
sulfur comprises 3% of the CSP at all sites. Site-to-site variations (Figure 21)
for sulfur within the urban area are relatively minor and the enrichment factor
is only 1.5. These observations suggest that sulfur is not strongly associated
with a point source and that most of it is not generated locally.
Furthermore, most of the sulfur at all six sites is present as sulfate.
The percentage ranges from 71% at Site 4 to 77% at Site 6, with an urban average
of 73%. The lower urban percentage could be affected by non-sulfate sulfur
arising from coking or other sources.
Calcium
Calcium possesses the second highest enrichment factor after iron and
surpasses iron in its percentage contribution to the IP concentration. The
site-to-site calcium variations (Figure 21) are found to be very similar to that
for iron (Figure 24). Because of the high enrichment of calcium, especially at
Lackawanna (9.2), and its large mass contribution to the ,TSP, analysis was
extended to determine the nature of its source(s).
8-17
-------
Calcium is found to comprise approximately 857, of the CSP fraction. The
observed concentrations of calcium at the two Lackawanna sites are about nine
times greater than those at the rural site and twice those measured at the three
Buffalo sites. For Sites 4 and 5, a subset of the entire data base was produced
which included sixteen individual field runs containing the ten greatest calcium
concentrations in the CSP fraction. This data subset simultaneously included
80% of the ten highest concentrations which were observed at the three Buffalo
sites. While Sites 4 and 5 essentially had equal calcium levels (project average),
usually large differences were observed between the sites on a single day. The
correlation coefficient for calcium from this data was only 0.14 between the two
sites. This result was unexpected since the two sites are only about one kilo-
meter apart and possess similar overall levels for most of the chemical components,
This data suggests for calcium that (1) a single major source is so close
to the sites that small variations in wind direction have enormous effects on
observed downwind concentrations, or (2) there are several major sources nearby.
When the concentration of calcium at Site 4 is significantly higher 0200%) than
at Site 5 in this data subset, the observed ratios of Ca/Fe and Ca/Mn are greater
at Site 4 than at Site 5. When the reverse occurs where calcium at Site 5 is
about 200% greater than at Site 4, the observed Ca/Fe and Ca/Mn ratios become
larger at Site 5. In general, calcium was not found to correlate well with iron,
manganese, or silicon at Sites 4 and 5. However, subsets of the data can be
found which exhibit high calcium-iron and calcium-manganese correlations,
suggesting that such calcium may originate from slag. It appears that the
highest calcium concentrations which were observed at Sites 4 and 5 may include
emissions from the lime plant (steel production) which would account for the
selective enrichment of calcium.
A summary of this data suggests that there are at least two major calcium
8-18
-------
sources contributing to the TSP which are located in close proximity to the two
Lackawanna sites. The two most probable sources for coarse-particle calcium are
operations which involve the production of lime and the processing of slag.
Fine-particle calcium may arise from coking and furnace (steel) dust emissions.
TRANSITION METALS (V, Cr, Mn, Ni, Zn, Fe)
Of the measured transition metals, only iron is a significant contributor
to TSP. Manganese and zinc offer minor contributions while the remaining tran-
sition metal components are negligible in terms of absolute ambient concentrations.
However, each of these metals is regarded as important indicators of emission
source categories. Manganese, iron, and zinc were found to be substantially
enhanced at all urban sites while chromium, vanadium, and nickel exhibited only
slight increases in concentration.
Vanadium
Vanadium (Figure 22) appeared rather irregularly at all sites but seldom
at levels above 0.02 M-g/m^, except at Sites 1 and 5. Site averages from the
overall project lie in the range 0.01 - 0.02 i-ig/m^ with Site 6 being much lower.
Vanadium constitutes approximately 2.5% by weight of particulates arising from
the combustion of fuel oil. Thus, fuel oil is believed to be the single major
source for this metal based on the current understanding of industrial processes
and emissions in the Niagara Frontier. While very low in absolute concentration,
vanadium later serves as an excellent marker or "tracer" in the CEB resolution
of the major source categories.
Chromium
Concentrations of chromium (Figure 22) were usually less than 0.001
at all sites and there is little net contribution to TSP. While chromium would
appear to be associated with the production of steel, such data is currently
lacking. For the moment chromium appears to provide little usable information
8-19
-------
in distinguishing among contributing source categories.
Manganese
Manganese and iron display similar site-to-site variations (Figures 23 and
24) and a high linear correlation exists among the urban sites. Although
manganese peaks at Site 4, iron is found to peak at Site 5. The concentrations
for both metals at the Lackawanna sites are about double those observed at the
Buffalo sites. The high levels of both manganese and iron are presently
associated with the production of steel. Any contribution of automotive man-
ganese from gasoline additives would be expected to provide higher observed
levels in areas of higher traffic densities (Sites 1-3). Since this effect was
not evident, it is felt that automotive manganese offers a negligible contribution
to observed concentrations of the metal.
Nickel
Nickel is found at very low levels at all sites (Figure 22). Although the
urban site concentrations are 50% above background, the urban site levels do
not vary much among themselves. The source of most of the observed nickel is
believed to be particulates from the combustion of fuel oil.
Zinc
Zinc levels are unusual in that site-to-site variations (Figure 23) are
very similar to trends which are characteristic of iron, calcium, and manganese,
except that a second peak exists at Site 1. Zinc is the only metal*for which the
highest average value appears at Site 1. Ninety percent of the zinc observed
at Site 1 appears in the fine particle fraction and with elevated bromine, could
indicate that automotive exhaust is the main source. However, further examina-
tion of the data on a day-to-day basis indicates little correlation between bromine
-'-Non-metals such as bromine, sulfate, and ammonium also show
peak values at Site 1 (Figures 24 and 26).
8-20
-------
and zinc. Wind direction data also indicates that the source of zinc differs
from that for bromine. Combined wind direction data for Sites 1 and 2 suggest
that the zinc source lies in a region which is currently used for coke and
steel production in Buffalo.
Iron
Because steel production is the predominant industrial activity in the
study area, iron has become one of the most interesting elements in this inves-
tigation. Iron has been found to exhibit the largest site-to-site enrichment
factor of all chemical components. Both Lackawanna sites show an average
enrichment factor of 11.6 above background and total iron concentrations
(project average) of 4.4 ng/m^. The data in Figure 24 presents the average
"project concentrations which were observed for each site and clearly indicates
that strong local sources affect the urban sites, especially Sites 4 and 5.
The average enrichment factor observed at Sites 1, 2, and 3 in Buffalo, although
subdued when compared to Lackawanna, is still high at 4.7.
The effects of 24-hr resultant wind direction upon observed concentrations
of iron were studied to gain information on the geographic locations of poten-
tial source contributors. For the moment this analysis is confined to the
fine iron particulates since it is this fraction which most likely will be
transported throughout the study area. Information is presented in Figure 27
for Site 5 which shows average iron concentrations observed for each 30° wind
sector. Site 6 data is similarly displayed for reference. Such data is
summarized in Table 11 where the actual compass directions pointing to the
steel facilities are tabulated for each site to permit comparisons with the
observed data. The wind directions, which were observed during periods when
iron concentrations were high, are represented very well by those wind sectors
8-21
-------
TABLE 11. WIND DIRECTION OBSERVED FOR HIGH IRON CONCENTRATIONS
WIND DIRECTIONS FOR
IRON CONCENTRATIONS
COMPASS DIRECTION
TO STEEL FACILITIES
SITE NO.
1
2
3
4
5
>2ng/m3
208-234 (4)**
208-277 (7)
223-230 (2)
320 (1)
192-247 (16 )t
193-274 (25)t1>
10 highest
208-234
208-277***
217-230 (9)
320 (1)
192-235f
193-274
Bethlehem
180-210
185-225
190-235
170-290
180-310
Republic
205-230
265-300
305-320
355-10
355-5
* In degrees, north = 0°, east = 90°, etc.
** Values in ( ) indicate number of observations.
*** Also one reading at 18°.
t Also one reading at 37°.
tt Also one reading each at 37, 75° 103° 150°.
8-22
-------
that traverse the steel facilities with respect to each station. The data for
Sites 1, 2, and 3 are particularly interesting since there are two potential
iron sources which can impact within this area. For Site 1, the ten highest
iron concentrations all occurred within a narrow wind sector (208 - 234 ).
These observations appear to indicate emissions emanating from Republic Steel.
Only one or two of these readings possess a reasonable probability of involving
emissions which originate from Bethlehem Steel. Because of its location, Site 2
presents a more dramatic distinction in the emissions arising from the two steel
o
complexes. Two separate wind sectors are observed for high iron levels - 208-223
and 230°-277° which represent the general locations of Bethlehem Steel and
Republic Steel, respectively.
At Site 3, nine of the ten highest iron concentrations lay in the 217°-234°
sector where Bethlehem Steel is upwind. However, the tenth observation, repre-
senting the third highest concentration, possessed a wind direction of 320 and
arose from the general direction of Republic Steel.
When the analysis of iron concentrations is now limited to values greater
than 2 ng/m^, fifteen of sixteen observations (Table 11) for Site 4 fall into
the 192°-247 sector and point toward Bethlehem Steel. The sixteenth value
(37°) may involve emissions from Republic Steel, the nearby slag operation, or
from the rail yards. A similar analysis at Site 5 shows that 21 of 25 observa-
tions lay in the compass sector 193°-274° when iron exceeded 2 M-g/m3. Bethlehem
Steel is found upwind of this sector. Similarly, high readings (Table 11) were
obtained for directions represented by 37 , 75°, 103°, and 150°. These data
fall into the first five wind sectors displayed in Figure 27 and represent the
first three peaks, each with an easterly component. This data points to the
nearby rail yards and may involve the scrap iron plant which borders the
southern edge of Site 5. One should not totally rule out a reentrainment
8-23
-------
component of iron particulates arising from steel emissions which are constantly
transported into this area by the predominant southwesterly winds.
Further evidence in support of iron emissions which originate from the
steel industry is provided from a comparison of iron and manganese in the fine
particle fraction at Site 5. To avoid the uncertainties associated with low
levels of manganese, only those days in which iron concentrations exceeded
1 ng/rn^ (38 out of 66 total observations) are considered. The least squares
regression line for iron and manganese revealed a 0.81 correlation coefficient.
For iron levels below 3 ng/m^, the Mn/Fe ratio is consistently lower than when
iron exceeds 3 i-ig/m^. This information may describe the situation where a
portion of the iron that is contributed by non-steel emission sources is depleted
in manganese relative to the iron from steel. Iron is certainly prevalent in
soil and such a general source is expected to impact on the sites throughout
this region. Hopefully a more advanced analysis involving the CEB approach may
better utilize such subtle differences in the chemistry of particulates to
distinguish the relative contribution from major emission sources.
Lead and Bromine
Lead and bromine are two elements which are normally associated with auto-
motive emissions. Both of these elements are consistently present at all sites
(Figure 24) and found mainly in the fine particulate fraction (Pb, 82%; Br, 77%).
Site-to-site variations were generally small among the urban stations with
Site 3 having the lowest averages. Enrichment factors for both components
ranged three to four.
The ratios of bromine/lead were examined but found to be far too high when
compared to literature values (.15-.40) for automotive exhaust. It appears that
the bromine values, not lead, have been overestimated during sample analysis.
8-24
-------
This condition may have been caused by a deterioration of the bromine xrf
standards. While the absolute bromine values reported here may be incorrect,
the relative values are still indicative of meaningful trends. Fine particulate
bromine is enhanced a factor of 5 at Site 1 which is adjacent to the New York
State Thruway. Meteorological data help to show that both bromine and lead
concentrations are elevated when Site 1 is downwind from the New York State
Thruway.
Fine particulate lead peaks at Site 1. and is believed to originate mainly
from automotive traffic. However, lead similarly peaks at Site 5 while there
is no corresponding increase in bromine. A similar trend is witnessed for
Site 4. Sites 4 and 5 together could indicate lead emissions arising from the
steel industry where the metal is added at times to reduce brittleness.
ION CHROMATOGRAPHIC DATA
Introduction
Ion chromatographic data appears in Tables 7, 8, 9, and 10, and represent
only those portions of each component which are water soluble. The general
procedures involved in the measurement of the ten ionic components has been
previously described in Section 5.
Sodium
Sodium generally constitutes less than 1% of the total dichotomous suspend-
ed particulate weight (Table 10) with 53% residing in the fine particle fraction.
The enrichment factors are 1.6 for Buffalo and 2.6 for Lackawanna. Sodium
levels peak at Site 4 (Figure 25) and are essentially constant at the Buffalo
sites. For the moment sodium has no readily identifiable source other than as
a roadway deicing agent.
Potassium
Potassium displays a behavior which is quite different from that for sodium.
8-25
-------
The enrichment factor for potassium is 2.0 for Buffalo, reasonably similar to
the 1.6 observed for sodium. However, for Lackawanna the potassium enrichment
jumps to 5.7. Potassium exists primarily as small particulates at all sites
where 82-93% (Table 8) is found in the fine particle fraction. Levels of
potassium rise sharply at Sites 4 and 5 (Figure 25) where it represents approx-
imately 27» of the dichotomous IP- The Buffalo sites exhibit small variations
at much lower levels. Although limestone is known to contain small amounts of
potassium, the exact source for most of this metal is currently unknown. It
should be noted that variations in chloride concentrations (Table 7 and Figure
25) are similar to the trend observed for potassium. It is not known from this
data whether potassium and chloride exist as a single compound, potassium
chloride, but the individual components do possess similar enrichment factors
(Table 9) at identical sites. Potassium chloride can be used as a flux in some
high temperature operations but its possible use in steel production is unknown
at this time.
Ammonium
Ammonium ion comprises about 10% of the fine particulate weight at all sites
and is the second largest contributor to the measured water-soluble components.
Modest enrichment factors are observed for Buffalo (1.7) and Lackawanna (1.4).
Average ammonium concentrations display an increasing trend toward the more
northern sites (Figure 26). An analysis of ammonium concentrations versus wind
direction reveals that the greatest mass of ammonium arrives on southwesterly
winds. However, northern winds exhibit significant ammonium concentrations at
Site 3 and result in the highest observed concentrations at Sites 4 and 5. This
pattern may reflect ammonia emissions from coke ovens which are located north
of Sites 1 and 2. Obviously this source of ammonia would be superimposed on
material carried into the region from long range transport. Therefore, it is
8-26
-------
not unexpected that a regression analysis of 30 sampling dates at Site 5 showed
little correlation of ammonium ion to either sulfate or nitrate (other gas-to-
particle conversion products).
Halides (F. Cl, Br)
As a group the halides generally represent 1% of the dichotomous IP for
most sites, approximately 1.1% at Site 4 and 1.4% at Site 5. Chloride is by
far the predominant halide component and shows the greatest enrichment (6.6)
at Lackawanna. Potential sources of chloride are automotive exhaust, combustion,
road salt, and steel manufacturing. The bromide analyzed here is soluble (BrS)
and necessarily represents only a portion of total bromine as determined by
xrf procedures. All forms of bromide in this project are mainly attributed to
automotive exhaust. Fluoride is similarly found to occur at low levels but
does exhibit a maxima at Site 5. Although it is known that fluorspar (calcium
fluoride) is sometimes used in fluidizing slag during steel production, this
source has not yet been verified. If fluorspar is used continuously, then it
may help to serve as a marker element to distinguish between the various
emission sources arising within the steel industry.
Nitrate and Nitrite
Both ions are found to be enriched above background (Table 9). However,
nitrate appears to be the more interesting component and constitutes about
2-3.5% of the dichotomous IP. Nitrate at the urban sites is found mainly in
the fine particle fraction (54-78%) but drops to only 38% at the rural station
(Site 6). Sites 1 and 2-in Table 7 are considerably enriched in fine particle
nitrate as compared to the remaining sites. This trend may reflect the presence
of nearby coke ovens which are known to emit nitrogen oxides. Little correla-
tion was found in a comparison of nitrite or nitrate to either ammonium or
sulfate concentrations.
8-27
-------
SECTION 9
SCANNING ELECTRON MICROSCOPY
Analysis was conducted on special samples of suspended particulates
collected at two field stations in an effort to characterize the major types
of particles present. The objective of this effort was to provide source
category information for the CEB program from the classification of the
physical and chemical characteristics of the predominant types of particles.
Since this analysis was designed as a small effort, filter analysis was re-
stricted to Sites 5 and 6 which represent urban and rural background stations,
respectively. It was expected that major differences in types of particles
would be evident between these two sites.
From the observation of many particles from the fine and coarse particulate
filters of both sites, silicon appeared as the predominant element. Most
particles contained silicon but no reasonable correlation could be made between
silicon content and particle size or shape. The varying sizes and shapes of
particles containing silicon sometimes contained additional metals, making it
difficult to distinguish between sand, clay, or other sources.
Sulfur was found to be present in most of the fine and coarse particles
from Site 5 but only in the fine particles from Site 6. These facts support
other project data which indicate that the majority of sulfur in the particulate
samples exists as sulfate which is confined to the fine particle fraction
(< 4 M. diameter). However, at Site 5 some sulfur was evident in the coarse
particles in which calcium was simultaneously present. It is possible that
9-1
-------
such particles originate from blast furnace slag or limestone in the steeltnaking
process. However, much more SEM data would be required to substantiate any such
claim. In general, sulfur was most often associated with fine particles which
contained very low levels of other elements. Calcium was found at Site 6 to
exist mainly in the fine particles with levels significantly lower than at the
urban sites. The much higher calcium concentrations found at Site 5 were usually
associated with high silicon and/or sulfur and/or aluminum levels. Such
associated metals are suggestive of blast furnace slag particulates. In contrast
to Site 5, the lower concentrations of calcium observed in the particulates at
Site 6 were not associated with similar levels of silicon, sulfur, and aluminum.
This fact suggests that the calcium component at the rural site may be comprised
mainly of soil limestone and/or roadway deicing agents as opposed to the type
of calcium-containing material which is evident at the urban sites. Although
calcium chloride as the deicing agent is considered here, its actual impact
appears to be negligible at Sites 5 and 6 since the measured chloride in each
case accounts for a maximum of only 10% of the total observed calcium.
The highest iron concentrations were observed at Site 5 in particles which
were low in other elements. Such iron particles most probably exist as the
oxide, Fe£ 03, since a rouge color was often evident on filter particulate
samples. The single most important source for such a component would involve
the steelmaking furnaces, most probably the basic oxygen furnace since these
iron particles were fairly small (< 2 M- diameter). Such small particles are
more indicative of industrial process emissions associated with condensable
particle streams. Iron particles arising from soil and ores are either con-
siderably larger in size or, from combustion sources, are associated with other
metals. The iron particles observed at Site 6 usually contained silicon,
sulfur, and aluminum components. In addition, the presence at Site 5 of
9-2
-------
relatively high manganese concentrations appeared in particles which were
simultaneously rich in iron or zinc-nickel-chromium. Manganese in this region
is apparently related mainly with steel production processes rather than from
automotive or fuel combustion sources.
Aluminum, was the second most frequently appearing element, associated
usually in round particles with similar concentrations of silicon. The fact
that aluminum appeared mainly in round particles is again suggestive of con-
densable particle emission sources such as coal and/or oil combustion or
steelmaking/slagging operations. Aluminum from soil components would tend to
be associated with irregularly shaped particulates.
Lead and bromine at Site 5 appeared most frequently in the coarse partic-
ulate fraction as opposed to its presence mainly in the fine particles at
Site 6. While it was expected beforehand that lead and bromine would present
information regarding the impact of an automotive source throughout the study
region, the situation has become more complicated. Lead is occasionally used
in the production of steel where it is added directly to molten iron. This
procedure would most certainly give rise to lead-containing particulate
emissions. Therefore, difficulties will arise in distinguishing automotive
and industrial process contributions to the measured concentrations of lead.
It was further observed that overall zinc concentrations at all sites
were much lower than for many of the other analyzed metals. From SEM analysis,
some zinc-containing particles were unusually depleted in most other metals.
Such particles are believed to originate from the wear of rubber tires since
rubber usually contains zinc compounds for curing. However, other zinc par-
ticles were enriched in other heavy metals. Although galvanizing operations
are associated with steel production, the present information regarding such
particles is insufficient to establish possible source(s).
9-3
-------
Although the SEM analysis begins to show important differences in the
particle characteristics associated with Sites 5 and 6, a greater in-depth
particle analysis will be required in the future in order to obtain represen-
tative results which are applicable to studies of this type. This SEM data
which is summarized in this section represents the interpretation of samples
collected on only one day of the project and is necessarily limited.
9-4
-------
SECTION 10
CHEMICAL ELEMENT BALANCE
INTRODUCTION
The dispersion modeling of various pollutants has traditionally involved
the development of rather sophisticated computer programs. Such atmospheric
dispersion models attempt to simulate observed parameters which describe the
meteorological profile within the study area. By employing the emission factor
for a single source, the model then predicts the downwind TSP concentrations
which are contributed by that source. The treatment for multiple sources is
similar and the downwind concentrations are obtained from the principle of
superposition of each individual source. In this approach, some difficulties
arise from an attempt to accurately model complex meteorology, which at best
can only be approximated.
Before one can devise optimum control strategies for TSP, the source
strengths of various sources must be defined. Estimates of source strengths
from dispersion modeling are necessarily based upon emission factors which are
obtained from source emissions inventories where data is often inaccurate or
incomplete. Some of the errors in the subsequently predicted source strengths
are associated with the incorrect assumption that contributions to the TSP from
individual sources are directly proportional to the overall masses of material
which are emitted. However, the different residence times, dilution factors,
and transport properties of particles are based on their different size dis-
tributions and points of release. The various chemical species arising from
10-1
-------
a single point source and eventually observed" at a downwind site do not
necessarily possess the same proportionality to the composite emissions factor.
A different approach in determining the strengths of the various sources
within an area is the chemical element balance (CEB) method. The major emission
source categories for the region are defined. Subsequently, the respective
samples from the categories are analyzed for many chemical species in order to
establish a "chemical fingerprint" for each category. Samples of ambient
suspended particulates are then collected at the various field stations and
each is analyzed for the same components which are specified in the "chemical
fingerprint". The assumption is made, similar to that used in dispersion
modeling, that the concentration of trace elements found in the aerosol is a
linear combination of the emission from all types of sources in the area. The
CEB method then attempts to resolve the aerosol into its component sources.
From the CEB approach, the measured concentration of element i, C±, in a
particulate sample can be represented as :
(10-1) Ct = SnjXjj
where nij is the fractional mass contribution to suspended particulates from
source j, and Xjj is the concentration of the chemical component i in
the particulate matter from source j. Using iron as an example and three
source categories, one would have:
(10-2) C-r, = m-ix-j + moxo + nux?
*e L ^ 2 ^ ^ J
Fe
where Cpe is the concentration of iron as represented by the filter particulate
sample. Additional equations can be written for other chemical species which
have been measured in the investigation. If the matrix elements x . in
equation 10-1 are known for all the major source categories contributing to the
field sample, then equation 10-1 can be solved to obtain the source strength
10-2
-------
coefficients, mj. From this method, one should be able to indicate the con-
tribution of each type of source category to the TSP as well as the contribution
of each source category to the concentration of each chemical component.
SOURCE CATEGORY COEFFICIENTS
In order to apply the resolution of the source category components to the'
field data gathered in this study, it is first necessary to identify the major
source categories and to establish the "chemical fingerprint", K±j, for each.
Since the field data represents two size fractions of particulates, the power
of the CEB model is only fully realized if one provides a "chemical fingerprint"
for each of the particle size fractions.
No attempt was made within the course of this investigation to obtain
physical samples of materials representing the individual source categories.
Analysis of such materials would be useful in order to establish directly the
necessary coefficients. However, such an effort is beyond the scope of the
current project.
The CEB approach received major notice in 1973 in a publication by
Friedlander (2). Although the CEB concept has been advanced considerably since
that time, it is to be considered still in its infancy.
In order to operate the CEB model for the Niagara Frontier data, the only
source for the x^j coefficients is the literature. The data in Tables 12 and 13
represent the values which were used to perform the source resolution. All
values appear in standard scientific notation in double precision format, i.e.
25.D-2 is equal to 0.25; all values within a category are normalized with
respect to a "tracer" element. The seven source categories which were chosen
for this analysis are soil, steel, coal, oil, refuse, auto, and lime. Much of
the subsequent resolution of the Niagara Frontier data makes use of the CEB
10-3
-------
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model which was developed by Dr. Glen Gordon, et.al., (10, 11). With the
exception of steel, all of the "chemical fingerprints" for the source categories
were derived from the Washington, D.C. aerosol study. It is believed that
this data represents the most complete category profiles which were available
to us for application to the Niagara Frontier data. However, coefficients for
a steel category were obtained from the Chicago aerosol study (4). Where
possible, relative proportions of metals were updated from more current
information.
An abundance of information exists in the literature for use by those
employing the CEB approach. However, more often than not, the specific chemical
parameters which describe the particulate emissions from a source category
don't coincide with those parameters actually measured in a project. When this
event occurs, the "chemical fingerprints" are incomplete and a highly detailed
resolution of the data base cannot be achieved. This situation exists at the
moment when attempts are made to resolve the Niagara Frontier data.
The information in Tables 12 and 13 for source categories for soil and
lime do not represent two different size fractions, but rather the bulk overall
sample. Similarly the values for a steel component represent bulk particle
emissions and are not size classified. These three chemical profiles are
simply not available at this time in the detail required by such studies
employing dichotomous samplers. The available chemical profiles (Tables 12
and 13) were used under the constraints which are described. One should realize
that this situation will not permit full interpretation of the data. Certainly
such chemical profiles can be advanced in the future and the data can then be
reanalyzed to permit a greater understanding of the relationship of source
category contributions to TSP in the Buffalo-Lackawanna area.
10-6
-------
SIX SOURCE RESOLUTION
A six-source CEB analysis of fine particles is presented in Appendix E.
The source categories which are considered to account for approximately 95% of
the observed TSP in the Buffalo-Lackawanna area are soil, steel, oil, refuse,
auto, and liming. A marker element is designated within each source category
but does not necessarily have to represent the respective chemical constituent
with the highest concentration. The prime consideration here is whether or not
a marker element is peculiar to a single source category. When this situation
occurs, the distinguishing features of the chemical profile for that source
category are enhanced above the remaining choices. Although it is felt that
such marker elements aid in resolving the contributions from the various source
categories, one is not always permitted the opportunity to select marker
elements which occur in only a single source category.
In this study the soil category possesses a chemical profile which is
based upon a silicon marker. This profile will account for soil particles
observed in the TSP, regardless of the manner in which these particles become
airborne. However, silicon is also found to occur in the steel category,
particularly in slag material. On the other hand, the marker element for steel
was chosen to be iron, which similarly forms an appreciable percentage in soil.
Vanadium was selected as the marker for particulates originating from the com-
bustion of fuel oil. Within this study, vanadium is the marker which comes
closest to fulfilling the earlier requirement that a marker be found predomi-
nantly in the chemical profile for only one source category. Meanwhile, zinc
was the marker element chosen for refuse since literature reports find refuse
to be the chief source for this metal in the environment. However, the matter
is certainly complicated by the presence of zinc in the abraded particles from
10-7
-------
rubber tires of vehicles and in emissions from galvanizing operations. It is
felt that neither of the latter zinc sources has yet been adequately character-
ized for studies of this type. The marker selected for the auto (vehicular)
source is lead. Certainly the reduction of lead in gasoline in the future may
eventually force one to reconsider this choice. Although the use of unleaded
fuel is constantly on the rise, vehicular traffic is still considered to be the
major source of lead which is emitted into the environment. The sixth category,
liming (10), was found to be necessary to account for a source of calcium. In
this study, liming will represent a chemical profile of particulate emissions
which result chiefly from the abrasion of concrete surfaces and from slag
operations. Other sources of calcium, i.e., cement, would also be included in
this category.
From the data which is presented in Appendix E for Site 1, one observes
the predicted distribution of the chemical components among the six source
categories. The input, C ^, for Site 1 for the chemical components is labelled
"Observed" in Appendix E and does not represent the measurements made on
individual filter samples. The "Observed" data represents the respective
project average values for fine particles. Although the input to the CEB
program could have been the chemical component concentrations which are descrip-
tive of a single filter sample, the current number of source categories and/or
the present quality of each chemical profile occasionally results in the
prediction of large negative concentrations for entire source categories. The
project's average site values effectively remove large variations within a
given chemical measurement and results in a computer source resolution which
is considered here to be more meaningful in its interpretation. Certainly a
great deal of information is lost by not utilizing individual filter samples.
10-8
-------
However, it is judged more important for the moment to present the average
findings in view of the project's overall goals to broadly define the nature of
TSP in the Niagara Frontier region.
From Site 1 data in Appendix E, lead is distributed chiefly in auto, then
refuse, and.is negligible in all other remaining categories. The total predicted
concentration for lead is 711 |ig/m3 as compared to the average observed value of
682 tig/m3. The resulting ratio large/small (L/S) is 1.04 and reveals very good
agreement overall. The L/S ratio for bromine is 4.33 where the observed value
is considerably in excess of the predicted value. It is felt that the observed
bromine values are in error as discussed in Section 8. Despite a poor chemical
analysis for bromine, one observes a decrease in the bromine L/S ratio from 4.3
at Site 1 to 2.8 at Site 6. This decrease toward unity in the ratio suggests an
improving fit. However, the xrf data appears to overestimate the concentrations
of bromine by approximately a factor of 2.5.
Zinc is found to be distributed between the auto and refuse categories,
similar to lead but in the reverse order of predominance. Iron and manganese
are chiefly found in the steel category, where chromium, lead, nickel, and other
components are reported to be zero simply because the analyses for these metals
relative to iron in the chemical profile was not readily available to the project,
If chromium was present in steel emissions, presumably the CEB program would
predict a chromium component for steel. Thus, the L/S ratio of 1.34 may even-
tually move toward unity, indicating a better correlation between predicted and
observed values.
The bulk of calcium containing particulates is found in the liming category,
although appreciable quantities are also distributed in soil and steel emissions.
Much of the calcium may arise from the degradation of concrete and from slagging
operations, both sources of which are figured into the liming profile. Once
10-9
-------
sufficient confidence is achieved in the chemical profiles, it is possible that
slag contributions to TSP could be resolved directly by establishing a chemical
profile specifically for such a material.
The concentration of vanadium is distributed chiefly in the oil category.
Although there is a wide variety of heavy industries and chemical processes to
be considered in the Buffalo-Lackawanna area, present information suggests that
fuel oil combustion is the prime contributor to the observed levels of vanadium.
In contrast to the reasonable fit for vanadium, the resolution of sulfur appears,
at first, to be extremely poor with regard to resolution and distribution among
the specified source categories. The L/S factor exceeds 500. However, one
should realize that background particulates arising from some combination of
distant sources cannot be adequately characterized in a chemical profile as a
single source. The end result is that the CEB approach simply must ignore the
background aspect of TSP. The CEB method must ignore those components which
arise from gas-to-particle conversion processes and which enter the study region
through long range transport, i.e., sulfate, nitrate, ammonium, etc. The inability
of the CEB method to cope with this aspect of the TSP problem should not be
considered as a deficiency in the model. Data from Section 7 has presented a
detailed discussion of sulfur-containing particulates and has shown that much of
the sulfur exists as sulfate. Except for minor variations, the bulk of the
observed sulfate, nitrate, and ammonium particulates appears to be well dispersed
among the sites and to be largely independent of industrial activities throughout
the entire region. From a study of the chemical profiles of the source categories
presented in Table 12, one realizes that sulfur is an element which exists at
very low levels when normalized to the marker element. Thus, correspondingly
low levels of sulfur are predicted and distributed among the sources. One could
10-10
-------
argue that the sulfur data should not have been included in the resolution
analysis. In any case, the CEB results should be interpreted as simply reflect-
ing the absence of any major sulfur species in the source categories considered.
Upon examining the results for silicon, one finds that the CEB model has
predicted that approximately 80% of this element arises from a soil component.
An order of magnitude lower concentrations are received from refuse and liming
categories. Similar trends are observed for aluminum and potassium in the
discussion of data at Site 1. At this stage in the interpretation of the data,
one should recall that the liming category was included in an attempt to explain
additional sources of calcium. The liming chemical profile was modified in an
attempt to include a slag component based mainly on silicon and calcium. It is
probable that errors exist here since good data was not available. Therefore,
a future reanalysis is expected to decrease the predicted soil component in an
effort to account for slag particulates which are included in the liming category.
The high predicted distribution of chloride in the automotive category
appears reasonable since chlorinated scavengers are still in use in leaded
gasoline. Chloride is also expected to be produced from the incineration of
refuse containing appreciable amounts of chlorinated plastic films, i.e., PVC
(polyvinyl chloride), etc.
The CEB analysis of potassium does not account very well for its presence
among source categories as is evident in the L/S ratio of 3.02. The zero values
predicted for steel, oil, and refuse sources simply arise from the lack of
information for potassium in the respective chemical profiles. As discussed
in Section 8 of this report, potassium levels rise near the steel industry.
The verification of a potassium emission from steel production could be expected
to improve the resulting mass balance distribution and the subsequent L/S ratio
for this metal.
10-11
-------
Additional information may be found toward the bottom of page E-2 (Appendix'
E) which describes three variables. The "COEFF" variable is simply the m,
value resulting from the CEB analysis. The "TSP" variable is computed from
knowledge of the weight percent of the marker element in a sample from the
respective source category. The percentage weight values which were used in
this analysis appear under the heading "EST. % WEIGHT" found on page E-8. For
example, at Site 1 the predicted value of silicon is divided by .250 and results
in a predicted TSP value of 7189 ng/m3 arising from the soil. The "% TSP"
variable simply represents the predicted source category contribution to FSP
as a percentage of the sum of all the predicted contributions.
Similar information is presented for the remaining Sites 2-6 (pages E3-E7)
and one can now draw comparisons from the results on a site-to-site basis. For
'instance, the predicted soil contributions (% FSP) can be seen in Table 14 to
vary among the sites. A maximum soil component (72%) is observed at Site 6.
TABLE 14. SIX SOURCE CATEGORY DISTRIBUTION SUMMARY (7, FSP)
Site # Soil Steel Oil Refuse Auto Liming
1
2
3
4
5
6
42.8
47.5
44.3
31.2
25.5
72.0
5.8
8.8
7.5
20.6
22.6
-2.1
1.2
0.6
0.7
0.4
0.7
0.7
11.1
1.4
2.0
2.9
2.8
2.7
35.8
38.5
41.5
37.9
43.5
24.9
3.4
3.1
4.0
6.9
4.9
1.8
While this absolute value may be argued, the source-by-source distribution at
Site 6 seems entirely reasonable. The soil category percentage is lowest at
Sites 4 and 5 but this trend is in agreement with the observed facts. For
Sites 4 and 5 the overall TSP values, and therefore FSP, are the highest
10-12
-------
observed throughout the project. The chemistry of the particulates at Sites 4
and 5 differ considerably from the other sites and the CEB model predicts a much
larger percentage of steel emissions contributing to the observed TSP. Thus,
while one could conceive that the soil component could be relatively constant
among the sites from the discussions in Section 8, the soil percentage decreases
at Sites 4 and 5 due to the increased percentage of contributions from the
steel category. The CEB model predicts that percentages of particulates derived
from steel emissions in Lackawanna are 3-4 times greater than similar percentages
which are projected for the Buffalo sites. The negative value which is predicted
for steel emissions at Site 6 reflects the inability of the model to match the
chemical profile with the observed data. A refinement in the CEB parameters
and modeling routines should eventually lead to positive values. However, the
conclusion to be drawn here is that Site 6 does not receive any steel particu-
late emissions when project-average data is used. Certainly on a single day
basis, project information exists which strongly suggests that steel emissions
from Lackawanna can impact fifteen miles south at Site 6. This ocurrence is
infrequent because winds arriving from the north are infrequent. Hence the
project average distribution summarized in Table 14 does not reflect this
possibility.
The impact of percent FSP from oil particulates is relatively constant for
all sites. An exception is noted at Site 1 where the percentage is doubled.
The generally low overall values suggest that little attention need be devoted
to this category in the development of SIP control strategies. A similar trend
is observed for refuse contributions among the sites. Percentages for each site
are fairly constant. The overall low values are consistent with the knowledge
that major incineration facilities do not exist within the study area. Further-
more, any such facilities outside of the study area make little impact within
10-13
-------
this area. The five-fold increase which is observed for Site 1 is difficult
to explain. At the moment it is believed that the chemical profile for refuse
may not realistically represent the situation in NFAQCR. The refuse marker
element is zinc and Site 1 has been shown to exhibit high zinc levels. More
general knowledge suggests that zinc at Site 1 may originate from rubber tire
particles from nearby heavy traffic. If the latter fact proves true, then the
CEB results are in error simply because the authors have failed to include
rubber tire wear in the automotive chemical profile. An accounting of this
zinc source is easier said than -done since appropriate data does not exist.
In any event the refuse component using zinc at Site 1 may be overestimated.
Conversely the automotive component at Site 1 may be underestimated. While the
"auto" percentages at the urban sites are uniform, an interpretation of data
from individual days can indicate a much greater impact at Site 1 from an auto-
motive source than at Site 2. However, project-averaged data does not support
this theory under the present conditions of analysis. The last category
(liming) in Table 14 can best be described as helping the CEB model in achieving
a balance of distribution. Sources of calcium occur in the environment other
than from the categories represented by soil, steel, oil, refuse, auto, or
coal. Cement operations do exist in the study area and may represent a contri-
bution to observed TSP. More importantly, calcium particulates from the
abrasion of concrete roadways is expected to provide a larger contribution to
TSP than cement. Relatively small sources such as these are not easily repre-
sented by singular chemical profiles. In CEB modeling it is easier to combine
such non-related sources into one overall category. Although the liming
category in Table 14 ranges only 2-7%, important information is contained
within this source and represents some of the finer details of the overall TSP-
picture.
10-14
-------
While the data from all six sites have been individually analyzed (pp. E2-
E5), a composite average is provided by the CEB program and results appear on
page E-8. It is recognized that the particulate aerosol at the rural site is
much different from the urban sites, so that perhaps the average fit here is
somewhat confusing. We recognize now that more meaningful data would have
resulted from an average fit of all urban sites, which then could have been
compared directly to the Site 6 data on page E-7. Nevertheless, one finds that
the CEB model considers soil and automotive sources to represent 40% each, or
80% combined, of the total predicted TSP. The average steel contribution to
TSP at all sites is 12.5% but would increase slightly if the rural site was
deleted from this analysis. An additional data summary is presented on page
E-9 where data from the product of the source strength coefficients, mj , and
the marker element concentrations are tabulated in ng/m^. This data allows one
to readily compare the predicted concentrations within the respective source
categories for the marker elements only.
Now that results from the fine particulate fraction have been interpreted,
a similar analysis is extended to the coarse particulate fraction. The CEB
analysis of the coarse particle data is identical to the fine particle case
except that ideally all of the six source chemical profiles are replaced. In
actuality, chemical profiles were not available to us to describe the soil,
steel, and liming categories for the coarse fraction. In these instances, we
could only use the profiles which represent bulk samples.
The six-source CEB analysis is found in Appendix F and is summarized in
Table 15. The coarse particulates are mainly attributed to a soil component
which comprises approximately 80% of the overall predicted CSP concentration.
This percentage drops at Sites 4 and 5 because a steel component becomes evident
10-15
-------
TABLE 15. SIX SOURCE CATEGORY DISTRIBUTION SUMMARY (% CSP)
Steel Oil Refuse Auto Liming
1
2
3
4
5
6
79.5
79.0
79.5
67.3
66.6
96.4
-.7
.1
-.4
4.3
3.8
-6.0
.1
.1
.1
.1
.1
.2
.5
-.1
.0
-.7
-.3
1.2
6.0
5.0
4.9
4.4
4.3
2.7
14.7
16.0
15.9
24.6
25.5
5.5
and the liming category increases significantly. At Site 6 the soil component
reaches its maximum of 96.4%. It is to be expected that much of the coarse
particle fraction consists of soil particulates. The separation of large and
small particles was taken into account in the.design of the operation of the
dichotomous samplers. Because the conduct of this study is new to us and to
New York State and necessary literature data is still incomplete, the absolute
values of the numbers resulting from this investigation may not be entirely
correct. However * the type of distribution which is noted for Site 6 in
Table 15 seems reasonable when one considers the nature of the surroundings for
this rural station. The negative values associated with the predicted steel
and refuse components indicate that the CEB program and/or chemical profiles
need further refinement. The automotive contribution is found to increase
continuously as one proceeds northward from Site 6 to Site 1, consistent with
the direction of increasing traffic density. The liming category exhibits an
increase in 7, CSP at sites 4 and 5 which is above that observed for the Buffalo
urban sites. This increase in % CSP in Lackawanna is believed to represent
input from slag/limestone operations which are associated with emissions from
the steel industry. This increment in %CSP should probably be added to the
10-16
-------
4% figure which is evident in the steel category column (Table 15). In effect,
the actual total steel emissions have been split between the steel and liming
categories because of the manner in which data was available for the respective
chemical profiles. This problem is minor and may be rectified in future work
by the development of a chemical profile which is characteristic of the composite
plume representing all possible steel emissions.
The average data for all six sites which represents the coarse particulate
fraction can be found on page F-8. The "EST. % WEIGHT" factors are deficient
here since information regarding fine and coarse fractions of the respective
categories was not available. We had no recourse at this time but to use the
same factor for either size fraction. The resultant situation is obviously
incorrect since the marker elements are certainly not expected to be equally
dispersed by weight between the fine and coarse fractions for a given source
category. Aside from these shortcomings, coarse particulates are predicted to
be comprised mainly of soil and liming components to the combined extent of
94%. In comparison to the average results for the fine fraction (page E-8),
one finds that the soil component constitutes about twice its share in the
coarse fraction as it does in the fine fraction. Steel emissions (furnace-type
particulates) are predominantly found in the fine fraction as are automotive
particulates. Refuse does not appear to represent an impact on coarse partic-
ulates, and only a minor impact in the fine fraction. Calcium-containing
materials are chiefly found as larger particles in the coarse fraction.
SEVEN SOURCE RESOLUTION
In an effort to define the major source categories which ultimately con-
tribute to the total observed TSP, one should include those categories which
account for at least 90% of the resultant TSP. The previous sub-section
presents a CEB resolution which was conducted in this manner. One could argue
10-17
-------
that the list of the six source categories should have been altered to exchange
one or more items for other categories. However, such freedom does not really
exist.
We have attempted to include in our final analysis another category which
has been an important consideration in other studies of this type. The six
source categories are expanded here to seven to include particulates arising
from the combustion of coal. The % FSP and % CSP resulting from the resolution
of the data appear in Appendices G and H and are summarized in Tables 16 and
17. The values which are 'reported in Table 16 for the fine fraction for a
seven-source resolution are not really much different than the six-source data
in Table 14. As a result of the inclusion of a coal category, contributions
from soil have been reduced 2-4 percentage units at each site. Residual con-
tributions to the observed coal values in Table 16 have been redistributed by
the CEB program from the steel and auto categories. The oil and liming distri-
butions remain essentially unchanged for either 6 or 7 source analysis. However,
the soil component is affected at all sites and one should be aware of possible
category interactions. The chemical profiles of soil and coal are the most
similar of all other categories.
TABLE 16. SEVEN SOURCE CATEGORY DISTRIBUTION SUMMARY (% FSP)
Site #
1
2
3
4
5
6
Soil
40.9
45.6
41.9
29.1
23.4
68.1
Steel
5.3
8.7
7.0
19.0
20.4
-2.3
Coal
4.2
2.4
4.6
6.6
8.0
5.0
Oil
1.1
.6
.7
.4
.6
.7
Refuse
10.7
1.4
2.0
2.8
2.6
2.6
Auto
34.6
38.2
40.2
35.7
40.4
24.1
Limin!
-*
3.2
3.0
3.8
6.4
4.4
1.7
10-18
-------
TABLE 17. SEVEN SOURCE CATEGORY DISTRIBUTION SUMMARY (% CSP)
Site #
1
2
3
4
5
6
Soil
«M«_^M»
77.0
75.0
76.7
59.5
53.0
103.0
Steel
6.3
9.9
8.9
16.6
20.7
-.3
Coal
-8.4
-10.0
-10.9
-7.4
-3.2
-13.7
Oil
.2
.3
.2
.2
.2
.3
Refuse
-.9
-2.1
-1.8
-3.2
-3.8
.1
Auto
7.9
7.0
6.9
6.0
5.8
3.9
Liming
17.9
20.0
20.0
28.3
27.3
6.7
It should be realized that a resolution analysis which makes use of these
two categories results in a certain amount of internal competition for the same
chemical components during the distribution scheme. It becomes increasingly
difficult to interpret such results and to simultaneously comprehend the subtle
interrelationships in the source categories. For instance, data for coal in
Table 16 indicates an increase at Sites 4 and 5 and may represent the heavy use
of coal/coke from the nearby steel industry. On the other hand, when one attempts
to over-define the resolution analysis of a data system by employing too many
source categories, the CEB model simply proceeds in a mechanical fashion to
develop the best fit to the data. The additional source categories may create
an unnecessary readjustment of the distribution of the observed chemical compo-
nent concentrations. It is believed that at some point human judgment must be
used to maintain the data analysis as simple as possible without seriously
degrading the final results. Such results are aimed at eventual use in the
development of SIP control strategies, where an over-resolved analysis may not
be needed and may serve to unnecessarily complicate the problem of interpretation.
The preceding discussion may be reflected in a comparison of the coarse
fraction data found in Tables 15 and 17. During the fitting routine, the
10-19
-------
additional category (coal) in Table 17 has provided more constraints which now
result in both larger and more frequent negative values for both coal and refuse.
Such results may indicate an attempt to overload the resolution program. It may
also be argued that the chemical profiles for all categories are not entirely
correct. The fit to the observed data begins to deteriorate as evidenced in
the data for Site 6 (Table 17) where the soil component now emerges as 103% of
the CSP. In an effort to accommodate the coal category, coal and refuse results
are forced negative while steel is significantly increased in the positive
direction to maintain balance. Oil, auto, and liming results are hardly affected
at all. It is too early at this time to conclude that the chemical profiles
contain large errors. Certainly the profiles can always be improved. Similarly
one cannot claim that a seven-source resolution is solely responsible for the
deterioration in the results. The chemical profile for coal is representative
of particulaues derived from coal-fired power plants. Particulates arising from
large stockpiles of coal, coking operations, and other industrial processes
using coal in the Buffalo area may not result in a coarse particulate fraction
which is adequately addressed by the chemical profile used in this study.
In the application of the CEB model to air pollution data within the study
region, judgments must be made which consider the realistic emissions and
characteristics of the aerosol within the urban-rural community so as not to
unnecessarily complicate the number of source categories in the model. Some of
the interpretations from this type of analysis are highly subjective and are
strongly dependent upon the input parameters. It should be noted that many of
these parameters are not well established because of their site dependent nature.
It is hoped that the efforts of this study have defined the basic approach which
we have attempted to apply to the TSP aspects of air pollution in Erie County.
10-20
-------
While it is difficult to interpret how much of the observed TSP results from
fugitive dust, reentrainment, etc., we are confident that such an approach
will eventually lead to a greater understanding of this complex problem.
PARTICULATE MASS BALANCE
Despite all of the recognized shortcomings in this investigation and in
the interpretation of the data, the following information is presented for
review regarding a projected mass balance of suspended particulate (SP) concen-
trations. In order to compare the predicted SP resulting from the CEB model
with the observed SP data, one must recall that background particulates are not
currently treated in this model. Therefore, starting with the FSP fraction,
the predicted FSP value is added to the respective concentrations for sulfate,
ammonium, and nitrate ions to yield an estimated gross FSP concentration. It
is felt that the background FSP levels are adequately represented by the sum of
the concentrations of these three ionic particulates. The trace metal concen-
trations which are associated with these three ions as well as those which are
associated with the remainder of the observed FSP are all included in the CEB-
predicted FSP levels. This data is presented in Table 18 for each site and
includes similar calculations for the CSP fraction. The data from this analysis
is presented in Figure 28 for ease of interpretation.
It is surprising to find such good agreement overall between the predicted
and observed SP concentrations. In general, the CEB model has slightly under-
predicted the FSP contributions to the fine fraction at all sites, even after
attempts are made to include background components. The amount of underprediction
ranges 14-23%. This comparison is easily seen in Figure 28. In a reverse fashion,
it appears that the CEB model has overestimated the predicted CSP concentrations
which range 32-90% above the observed values. Upon summing FSP and CSP data to
10-21
-------
TABLE 18." MASS BALANCE OF SUSPENDED PARTICULATE CONCENTRATIONS
Site
No.
1
2
3
4
5
6
FSP
SO/^ NH/+ NOo" Predicted
f if O
11.7 5.0 1.7 16.8
11.0 4.88 1.7 17.9
10.3 3.53 .65 13.5
11.5 3.92 1.17 19.6
10.9 3.55 1.01 19.1
7.75 2.69 .23 7.6
Sumtt
35.2
35.48
27.98
36.19
34.56
18.3
Observed
41
42
34
44
47
24
CSP
S04= NH4+
1.3 .25
.97 .13
.92 .10
1.28 .07
1.25 .05
.55 .06
N03~ Predicted
.48 30.8
.57 33.7
.55 28.9
.56 33.5
.6 33.9
.37 16.1
Sum''"'' Observed
32.8 20
35.37 22
30.47 19
35.4 26
35.8 27
17.1 9
IP
Total
Pred.**
68
70.8
58.5
71.6
70.4
35.4
Total
Observed***
61
64
53
70
74
33
* All units are ng/m3
** Total Predicted IP = FSP-Sum + CSP-Sum
*** Total Observed IP = FSP-Observed + CSP-Observed
= Total of 804= + NH4+ + N03" + Predicted SP
-------
Projected Average Concentrations - SO4 * NH4 + NO 3
Predicted Suspended Particulates from CEB
Predicted IP from CEB (= Predicted FSP + Predicted CSP)
Observed IP (FSP or CSP or IP)
bu-
7O
60-
^ 50
Q.
I-H 40-
30-
20-
10
o
i
/ :
I
!-
MM
^
.
\
&
:£>:
V^^H
I
%
\
&
*ffi
*
r i
\
1
\
M
i
1
\
&
SvS
^M
I
!. <£
$. 3$
IP FSP CSP IP FSP CSP IP FSP CSP IP FSP CSP IP FSP CSP IP FSP CSP
1 2 3-4 5 6
SITE NUMBER
FIGURE 28. HISTOGRAM OF PREDICTED AND OBSERVED SUSPENDED PARTICIPATE CONCENTRATIONS
-------
obtain total concentrations, the resulting IP concentration data for observed
and predicted values are found to agree exceptionally well with each other
(worst case is 11%). This analysis implies that it may be possible to advance
the model to improve its resulting predictions with respect to CSP and FSP
observed data.
This comparison between predicted and observed data neglects two other
obvious constituents of suspended particulates - carbonaceous materials and
moisture. Carbon-containing particulates are visually identifiable on a
majority of the fine particulate filter samples. However, fine carbon possesses
a very large unit surface area. A small amount of this element can effectively
cover large areas and yet represent only a very small percentage of the entire
mass. Similarly, moisture is believed to represent only a small portion of the
total SP mass.
From the overall project, it is very encouraging to realize that reasonable
mass balances of suspended particulates may be within the grasp of investigators
in the future. A source category apportionment when combined with a particulate
mass balance offers considerably more information toward the development of
particulate control strategies than can otherwise be obtained from the traditional
approach of dispersion modeling.
The application of chemical element balance procedures to the study of
suspended particulates in New York State is new to us. The resulting data are
expected to be controversial and to have far-reaching implications in the design
of control methods. One can envision use of the CEB approach to serve as a more
effective monitor of air quality in an attempt to define net gains and losses
resulting from the field installation of various phases of a master particulate
control plan. The future monitoring of the chemistry of air particulates is
essential to the interpretation and enforcement of regulations. This fact is
10-24
-------
especially true now as major changes are implemented in our production of
energy; i.e., use of higher sulfur oil, coal, and synthetic fuels. Significant
changes in the percentage use of these raw materials for the generation of
energy will possibly change observed TSP concentrations but will certainly
change the chemical profile of air particulates. These chemical changes must
be defined and monitored in an effort to maintain an air quality which is
consistent with our health requirements and the protection of the environment.
10-25
-------
REFERENCES
1. Miller, M.S., Friedlander, S.K., and Hidy, G.M. A Chemical Element
Balance for the Pasadena Aerosol. J. Colloid and Interface Science,
39:165, 1972.
2. Friedlander, S.K. Chemical Element Balances and Identification of Air
Pollution Sources. Environ. Sci. Technol., 7:235, 1973.
3. Gladney, E.S., Zoller, W.H., Jones, A.G., and Gordon, G.E. Composition
and Size Distribution of Atmospheric Particulate Matter in Boston Area.
Environ. Sci. Technol., 8:551, 1974.
4. Gatz, D.F, Relative Contributions of Different Sources of Urban Aerosols:
Application of a New Estimation Method to Multiple Sites in Chicago.
Atmos. Environ., 9:1, 1975.
5. Dzubay, T.G. Chemical Element Balance Method Applied to Dichotomous
Sampler Data. Presented at the Conference of Aerosols: Anthropogenic
and Natural - Sources and Transport, New York Academy of Sciences, New
York City, New York, 1979.
6. Neustadter, M.E., et. al. The Use of Whatman-41 Filters For High Volume
Air Sampling. Atmos. Environ., 9:101-109, 1975.
7. Federal Environmental Protection Agency. Quality Assurance Handbook for
Air Pollution Measurement Systems, Vol. II, Ambient Air Specific Methods.
EPA-600/4-77-027a. May, 1977.
8. Anderson, J.F. Lake Erie and Particulate Air Pollution in Lackawanna and
South Buffalo, New York. Erie County Department of Health, Division of
Air Pollution Control, Buffalo, N.Y., 1973.
9. Anderson, J. F. Effects of Lake Erie on Suspended Particulate Air Pollution
in Lackawanna, N.Y. for 1974-1977. Erie County Department of Environment
and Planning, Air Resources Bureau, Buffalo, N.Y., March, 1978.
10. Kowalczyk, G.S., Choquette, C.E., and Gordon, G.E. Chemical Element
Balances and Identification of Air Pollution Sources in Washington, D.C.
Atmos. Environ., 12:1143, 1978.
11. Kowalczyk, G.S. Concentrations and Sources of Trace Elements on
Washington, D.C. Area Atmospheric Particles Thesis, U. Maryland, 1979.
-------
APPENDIX A
The following data is tabulated for the fine and coarse particulate
fractions resulting from the dichotomous samplers. The various chemical
species which were measured throughout the study are presented here as pro-
3
ject averages for each site in ng/m .
A-l
-------
FINE SUSPENDED PARTICULATES
Site #
FSP*
Pb
Br
Zn
Ni
Fe
Mn
Gr
V
Ca
S
Si
Al
F
Cl
NO 2
P°4
BrS
N03
so4
Na
NH4
K
# of
Samples
1
41
682
921
171
7
684
30
1
14
309
5110
1830
558
33
74
253
6
51
1680
11700
192
5070
308
54
2
42
678
796
59
5
972
45
1
8
343
4970
1910
564
38
150
350
7
66
1700
11000
164
4880
336
46
3 "
34
552
636
50
5
644
23
1
7
292
4470
1410
449
39
54
197
23
46
647
10300
200
3530
312
70
4
44
740
641
123
6
1840
70
2
7
753
5250
1590
581
43
280
177
11
45
1170
11500
401
3920
847
64
5
47
823
645
124
7
1900
53
1
10
613
4930
1270
538
45
443
277
7
50
1010
10900
361
3550
1220
66
6
24
192
187
19
4
162
9
1
4
74
3300
1240
377
42
40
150
9
13
225
7750
134
2690
169
fis
*The units for FSP are u8/m3.
A-2
-------
COARSE SUSPENDED PARTICULATES
1
20
161
209
20
5
1160
27
2
5
1860
689
5190
1010
13
213
23
24
7
482
1290
282
248
68
2
22
143
192
9
6
1480
44
2
5
2180
609
5400
959
14
165
24
9
30
571
970
159
134
67
Site
3
19
120
177
8
4
1170
26
1
4 .
1860
545
4710
825
22
241
16
0
5
548
916
182
104
44
#
4
26
120
184
15
5
2220
45
2
, 5
3280
745
4930
867
45
323
60
2
34
558
1280
311
68
68
5
27
120
200
22
« 5
2920
51
2
5
3470
724
4790
967
78
302
43
4
8
590
1250
210
52
92
6
9
43
85
3
3
284
6
0
3
392
290
3360
662
17
62
35
5
8
375
551
114
65
25
CSP*
Pb
Br
Zn
Ni
Fe
Mn
Cr
V
Ca
S
Si
Al
F
Cl
N02
P°4
BrS
N03
so4
Na
NH4
K
#of
Samples 54 46 68 64 66 68
3
*The units for CSP are
A-3
-------
APPENDIX B
The data base for the entire project is listed here and represents all of
the dichotomous particulate filters which were collected for the fine particle
fraction. Each filter is printed along with information describing the date
(month and day), elapsed time, sampled air volume (flow), meteorological data,
and concentrations of particulate weight and various chemical components. A
series-20000 filter reflects the use of 0.5|-i pore diameter filters while the
series-40000 reflects the change to 1.0|j. pore diameter filters. The series-
20000 filter data for fine particulates corresponds to the series-30000 filter
data for coarse particulates which is presented in Appendix C. Similarly, the
series-40000 filter data for fine particulates corresponds to the series-50000
data for coarse particulates in Appendix C.
FILTER SERIES DESIGNATION
PARTICULATES
FILTER PORE DIAMETER FINE COARSE
0.5n 20,000 30,000
1.0|i 40,000 50,000
B-l
-------
N 1
***** Sift tf 1
FILItH H
U
It t\
20001 41
20021 49
20028 bJ
20036 Dl
20011 60
20080 61
20109 62
200dl 04
200d/ Ob
2009b 66
20100 6/
200 /J 6d
4000J 69
4000 7 /O
20201 72
40016 73
40022 /4
400J4 70
40040 7 /
4002d /b
20094 /9
20214 82
40046 dJ
400b2 84
400bd da
40064 8/
40O/0 db
400/6 89
401 Jo lOb
4OI33 lOo
40139 IO/
40144 lOb
40149 109
40lbb NO
40163 112
M
O
N
6
7
1
7
d
d
b
8
9
9
9
9
9
9
9
9
9
10
10
10
10
10
10
10
10
1
1
1
U
A
Y
27
19
21
25
Id
22
24
30
1
7
1 1
1 J
17
19
23
26
29
b
/
1 1
1 3
23
2b
29
31
4
/
10
2
9
1 1
Ib
1 /
21
27
TiMH
HHS
b.d
7.3
6.6
7.b
1 /.7
1 7.7
7.1
I/./
18.0
18.0
17.2
23.6
23.6
23.6
23.9
23.7
23.6
23.7
23.8
23.8
23.6
23.6
23.6
23.7
23. b
6.9
23.0
23.7
23. /
23.8
14.8
23.8
10.9
23. d
23.9
FLom
M**3
12.2
ID./
Ib.l
Jb.2
41 .1
39.0
17.7
43. 1
4b.3
43.4
43.7
b6. 1
b3.2
b4.0
bO.O
bl .2
b 1 .6
b4.l
bb.2
b4.4
42. d
bd.6
70.3
70.6
6/.b
19.7
66.3
6b.b
70.1
08.6
42.9
68. /
31 .2
71 .6
/0.9
HIND
UIU SFU
LIEG MHli
212
193
20b
209
156
238
21 1
Id/
23b
284
204
4/
bl
32
92
20b
1 14
163
274
1 68
Ib
313
192
lob
219
209
254
1 16
2bd
221
190
243
244
336
23 /
b
6
b
b
3
4
/
3
1
3
1 1
9
3
4
2
3
2
d
10
3
2
6
10
b
6
b
3
2
/
12
1
14
6
4
6
A G A H A FRONT
FliMH PArtflCULATb
FSP
UGM/
M**3
73
122
1.16
b2
40
36
86
29
31
33
93
12
Ib
19
Ib
29
22
28
7
3d
26
19
57
17
bb
67
1 7
bl
20
bl
39
31
34
Id
42
«
577
I3d2
771
IOJ2
616
b6b
831
40d
I4ld
3d9
723
392
4/4
4o 1
1 153
12/4
I6o8
lOOb
293
II //
6/b
240
1 1 la
b4d
996
30bb
263
1631
320
721
/9I
b/2
713
330
306
BH
181
783
743
13/6
Ib26
1 186
40/
630
2393
3/6
29d
491
768
b89
2215
1948
3lb2
774
464
I90b
1037
292
8b9
670
963
5920
484
2658
464
1 99
1973
373
10.15
380
b09
I t H S f U U Y
DATA (PART - 1
ZN
1426
246
165
1622
60
28
368
19
73
54
507
22
2
20
2
13
21
43
2
20
54
94
431
1
399
21
45
Ibl
25
96
38
131
26
1 1
247
NI
1 1
8
9
9
3
3
31
3
9
3
3
2
2
2
2
5
5
2
2
17
3
7
3
1
16
14
4
8
9
22
16
16
8
9
9
) *****
Fli MM
NANOGHAMS/M**3
1551
3337
1 120
884
882
461
925
3.98
562
440
1750
330
10
1 79
108
327
249
705
45
568
598
144
3260
1 19
1872
484
408
7/2
165
3817
465
615
186
40
44
45
52
27
9
. 23
10
54
3
27
22
63
83
2
43
2
13
37
25
b
22
64
9
84
17
65
28
10
42
1 1
125
19
16
8
1
1
CM
1 1
0
0
0
6
7
7
6
6
3
3
2
0
0
5
0
0
0
0
0
3
0
3
3
0
0
0
6
0
2
0
0
0
0
0
\7
11
17
48
9
3
7
39
3
33
15
6
12
2
23
2
5
5
2
2
42
9
II
1
15
22
7
4
a
15
10
19
20
4
23
1 1
CA
1245
4435
422
656
272
195
313
017
308
216
288
I7b
28
223
127
292
4bO
168
62
45d
210
403
782
72
477
196
2
214
69
300
255
463
9J
30
124
S
5560
26863
20086
6820
2718
4879
.16830
2627
2983
3171
43038
372
833
1397
640
2335
904
3360
451
4535
1396
1756
6000
1621
6574
4853
499
5940
2707
7210
3314
5764
4894
1890
7160
-------
w
NIAUAHA HHONTIHR
S I T t it I FINE. HARTICULATE UATA
S T U 0 Y
(PAHT - I )
*****
FILThli
*
40164
40170
40176
40182
40187
40193
40.1 yy
40205
4021 1
402 1 7
40223
40228
40234
40240
4O246
40252
40258
4O264
40270
rt
U
13
14
15
16
17
18
19
120
121
122
123
124
I2b
126
127
128
129
130
131
M
0
N
1
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
0
A
Y
30
2
6
8
12
14
20
22
26
28
4
7
10
14
16
20
22
26
28
TIMH
HWS
23.8
24.0
11.6
23.9
22.0
12.0
6.7
14.1
23.8
9.5
23.8
20.6
23.9
23.9
23.8
1.9.3
23.8
23.9
23.8
FLOrt
M**3
71.8
69.7
35.1
69.3
63.7
34.7
19.4
41.7
67.9
28.1
52.9
46.4
52.7
54.2
53.8.
43.2
52.0
52.7
53.0
HIM
UIH SPU
UEU MPH
277
254
241
251
43
68
220
247
43
220
I/I
61
23a
243
232 .
24 /
28
253
177
9
10
3
13
3
4
6
6
11
4
15
4
13
15
12
1
2
13
7
FSH
UGM/
M**3
II
25
51
31
27
48
82
71
15
66
23
36
49
33
54
53
29
20
25
,
233
449
730
293
436
323
932
481
142
597
180
444
270
311
2/8
631
588
215
409
dK
366
586
620
517
719
555
113
670
32
538
285
426
307
398
525
1099
802
35 /
830
ZN
5
55
675
800
21
327
242
53
34
1 12
2
35
60
28
100
64
13
2
67
NI
9
9
3
25
2
3
7
3
2
4
2
2
IO
7
2
3
2
/
2
FE MN
NANOUKAMS/M**3
77
157
193
129
69
207
3097
139
93
1515
IO/
319
552
457
574
772
293
144
537
9
7
15
9
6
15
149
3
6
133
5
56
13
25
20
41
18
0
15
CR
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
V
13
13
31
45
2
39
7
39
12
4
5
14
18
45
12
3d
13
26
7
CA
48
222
395
327
102
918
484
311
79
488
81
190
212
235
198
689
309
186
472
S
1325
3770
8046
4900
1410
7134
J3600
8390
165.9
7739
4032
4662
6503
3578
5909
4091
1924
2907
2114
STATISTICS
A\/i£kAGt: 40.5 682.5 921.2 I/I. I
25.4 501.9 964.3 318.5
1.0 684.3 29.9
6.4 886.0 33.5
1.4 14.0 309.0 5105.1
2.5 II.2 283.9 4975.8
UtYJATKM
-------
*****
FILTbH H
J
rf N
20001 44
20021 49
20028 bO
20036 3l
20077 00
20080 6 1
20109 62
20081 64
2008 / 63
2009b 66
20100 o/
20073 68
40003 69
40007 70
20201 12
40016 73
40022 74
40O34 /6
40040 //
40028 7d
20094 79
20214 82
40046 83
40032 84
400b8 83
40064 87
400/0 88
400/6 89
40136 103
40J33 106
40139 IO/
40144 lOd
40149 109
40.1 b8 NO
40J63 112
M
O
N
6
7
7
7
d
8
8
0
9
9
9
9
9
9
9
9
9
10
IO
10
.10
10
10
10
10
1
1
1
J
U
A
Y
21
19
21
2b
18
22
24
30
1
7
1 1
13
17
19
23
26
29
b
7
N
13
23
2b
29
31
4
/
10
2
9
1 1
Ib
1 7
21
27
TIMB
rtKS
b.8
7.3
6.6
7.5
J 1.1
17.7
7.1
J/.7
18.0
18.0
1 1.2
23.6
23.6
23.6
23.9
23.7
23.6
23.7
23.8
23.8
23.6
23.6
23.6
23.7
23.5
6.9
23.0
23.7
23.7
23.8
14.8
23. d
10.9
23. d
23.9
FLOrt
M**3
12.2
15. /
Ib.J
.lb.2
41 .1
39.0
17.7
43.1
4b.3
43.4
43. /
b£.l
b3.2
b4.0
bO.O
bl .2
bl .6
b4.l
b3.2
b4.4
42. d
b8.6
/0.3
70.6
67. b
19. /
66.3
68. b
70.1
6d.6
42.9
6d.7
31 .2
/I .0
/0.9
N
b i f b #
rill
UIH
UHG
212
193
20 b
209
Ib6
23d
2 1 1
187
23b
284
204
4/
bl
32
92
203
1.14
163
2/4
168
Ib
313
192
I6b
219
209
2b4
1 16
288
221
190
243
244
336
23/
NlU
SHU
MHH
b
O
b
b
3
4
7
3
1
3
1 J
9
3
4
2
3
2
8
10
3
2
6
10
b
6
b
3
2
7
12
J
14
6
4
O
I A U A H A F ti 0 N I
1 FlNh HArtTICULATE
SI
b424
7933
3381
2407
Ib29
1399
5231
. |238
2252
2613
3117
3878
398
1046
704
1580
2071
1480
188
3141
33/1
1294
2600
854
2/95
1074
150
3867
1094
1 139
894
544
3169
144
296
AL
838
65)
679
0/4
249
2o2
530
238
135.7
692
888
4/9
192
84d
709
9/7
1 169
452
I8b
1090
lOld
1 74
74 /
I4b
492
2136
134
774
4/4
149
239
149
I28b
2d9
J/4
F
163
0
179
Ib7
72
51
169
46
66
69
45
0
0
3/
0
0
5d
0
0
55
70
0
0
0
29
50
30
0
14
29
0
43
96
0
0
I E H
DATA
INI03
4292
445
145
427
97
128
396
255
66
lib
183
53
2o3
185
JOO
254
0
0
36
36
1517
272
996
368
3168
4513
844
9/8
136-9
1327
2059
1092
480
1409
3284
S f U U Y
(PAHT - 2 )
CL
dl
19
159
1 1 1
24
/6
0
69
0
0
45
53
b6
b5
20
117
0
18
12
0
0
68
455
99
103
50
0
0
99
58
23
0
0
2/
0
S04
14390
12949
54446
10849
7297
11666
37960
5318
6d8b
6680
46977
784
2144
3bb5
1701
6331
2034
7996
797
10540
3618
5285
17805
3510
1 75b9
1 1 Ob4
2066
14905
5821
17558
6111
1 1649
85/8
4633
22839
N02
0
305
318
263
0
0
0
0
88
46
0
0
338
0
0
0
0
0
416
0
280
0
1095
608
533
405
678
0
684
787
0
0
0
2456
1099
*****
NA
588
1061
663
197
145
102
453
139
154
69
572
178
0
0
120
58
58
92
0
73
140
238
441
184
222
304
105
175
42
58
233
43
96
1 II
0
P04
0
0
0
0
0
0
0
0
66
69
0
0
0
0
0
0
0
0.
0
0
70
0
0
0
0
0
0
0
0
0
0
0
0
0
0
«,4
4946
19275
17241
3949
2529
4538
13533
1463
2383
2741
9594
71
940
1259
460
2051
290
2991
326
4102
1657
2796
4312
1642
7254
8164
754
392 /
4437
7714
6018
7936
5985
3433
13788
BK-S
0
0
0
J84
243
179
0
1 16
308
0
0
71
1 12
.92
280
0
426
0
90
257
0
0
0
0
0
0
0
379
0
0
0
0
0
0
0
K
858
2733
464
329
145
25
0
185
44
184
366
17
0
0
20
0
0
166
144
0
233
0
1323
0
222
0
120
291
71
131
209
72
.0
0
0
-------
N I A U A H A F H 0 iM T I t H STUDY
SITE # I FINE HAMriCULATE DATA (PAHT - 2 )
*****
FILTEH
40164
40170
40.1 76
- 40182
40187
40193
. 40 1 99
402 Ob
40211
4021 7
40223
40228
40234
40240
40246
402b2
40258
40204
402 /O
K
U
N
13
14
15
16
17
18
19
120
121
122
123
124
I2b
126
127
128
129
130
131
M
0
N
1
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
0
A
30
2
6
8
12
14
20
22
26
28
4
7
10
14
.16
20
22
26
28
TIME
riKS
23.8
24.0
11 .6
23.9
22.0
12.0
6.7
14.1
23.8
9.5
23.8
20.6
23.9
23.9
23.8
19.3
23.8
23.9
23.8
FLOH
M**3
71.8
69.7
35.1
69.3
03.7
34.7
19.4
41.7
6/.9
28.1
b2.9
46.4
52.7
54.2
53.8
43.2
52.0
52. /
53.0
till
UIK
UEG
211
254
241
251
43
68
220
247
43
220
171
61
235
243
232.
247
28
253
1 77
ID
MPri
9
10
3
13
3
4
6
O
11
4
15
4
13
15
12
1
2
13
7
SI
472
451
778
806
726
1757
4293
979
538
1574
395
2344
417
82o
15.76
2.183
1630
512
1260
AL
142
445
292
147
160
603
1673
245
350
365
193
220
194
447
556
997
197
194
905
F
0
0
0
14
47
0
51
0
0
35
0
21
18
0
18
0
38
18
0
N03
654
1205
4107
2581
1569
4066
411
3953
529
4882
113
3144
67/5
2362
10044
62DI
3328
1744
1262
CL
0
258
0
0
15
57
0
167
0
0
0
0
0
258
390
416
0
94
395
S04 riO2
NANOGHAMS/M**3
2395
9471
18311
10757
2699
13383
35116
24083
27o7
18674
67/2
10833
19 tid9
10391
15941
8288
3963
7224
5202
459
846
1340
0
0
0
0
0
0
0
0
0
0
350
0
0
0
0
282
NA
55
172
85
43.
204
317
565
167
117
64 J
227
0
0
221
130
0
0
0
301
F04
97
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Nri4 BR-S
2423
2683
15744
8161
2574
4182
1 6555
7117
1015
6450
2251
3833
6054
3525
6045
4144
2232
2806
1319
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
O
0
0
K
69
0
256
201
0
288
0
239
176
1888
378
581
835
461
911
717
519
189
584
AVHHAOt 1826.2 558.4 33.'l 1680.2 74.2 11675.0 253.3 191.8 5.65066.9 50.7 308.2
STATISTICS
STANDARD IS4/.2 429.6
UbVIAflON
4b.9 2077.2 114.3 11023.5 4S3.6 211.7 20.3 4581.0 106.2 493.8
-------
N I
***** s I T E # 2
FILTER
if
20002
20008
20022
20029
200/1
20066
201 10
200b2
200bb
201 12
20231
40002
40008
20202
40017
4002J
400 JJ
40041
400J3
20122
4004 /
40053
40059
4006b
40071
400/7
40143
40J6b
401/1
401 77
40183
401 bd
40194
40200
40200
rt
U
N
40
41
49
bl
60
61
62
64
63
61
68
69
70
/2
/3
74
16
11
78
dO
83
84
db
Bl
88
89
12
13
14
13
16
1 /
18
19
120
M
0
N
6
6
/
7
8
8
d
b
9
9
9
9
9
9
9
9
10
10
10
10
10
10
10
1 1
1 1
1 1
1
1
2
2
2
2
2
2
2
U
A
V
2b
27
19
23
Id
22
24
30
1
1 1
13
17
19
23
26
29
b
7
1 1
1 /
2b
29
31
4
7
10
21
30
2
6
d
12
14
20
22
TIME
6.1
0. I
8.8
13. b
18. 1
10.3
18. 1
Id. 1
lb.3
0.8
23.4
20.8
21 .8
24.0
24.0
24.0
24.0
24.0
12. b
23.7
24.0
24.1
24.1
13. 1
20.1
22.7
24.2
24.2
24.3
1.2.0
24.3
22. /
24.3
1 1 .4
13.2
FLO.rf
M**3
12. b
12. b
18.3
2/.I
43.8
20.4
38.0
3d. 8
32.2
14.6
30.3
4J.2
45. /
4/.J
bO.3
bO.3
b2.7
b3.l
26.0
48.7
52.8
b3.2
49.8
2d.O
42.2
bO.O
b3.0
b2.d
53.7
26. b
b2.d
bO.O
b3.4
26.2
2U.9
MlNU
UIH Sh>U
UEG MHH
226
212
193
209
Ib6
23d
21 1
187
235
204
47
bl
32
92
205
1 14
163
2/4
168
64
192
165
219
209
254
1 16
237
27/
254
241
2bl
43
68
220
24/
b
b
6
b
3
4
7
3
1
1 1
9
3
4
2
3
2
b
.10
3
1
10
4
6
b
3
2
6
9
10
3
13
3
4
6
o
A G A K A F H 0 N T
HSH
UGM/
M**3
29
82
109
b2
39
48
74
28
50
db
7
IB
23
14
22
15
23
25
50
23
41
20
48
84
22
59
2b
2b
30
b4
53
34
25
64
7d
,
805
1077
680
33 /
5o9
2/1
710
1 102
1 122
956
294
724
966
1004
/I3
J003
2/3
1388
1506
17/6
595
633
653
968
1 165
20/3
127
653
649
287
40 /
7/8
327
381
339
»
1247
177
120
331
1 101
108
965
1880
1458
151
415
1250
1202
1696
80J
1518
160
203
2034
3649
359
952
314
726
1569
3628
I2/
238
275
523
398
1 142
360
I9b
633
I E ti STUDY
DATA (HAHT -
ZN
1 1
144
392
61
41
6
65
J07
81
94
2
3
3
2
2
8
26
117
63
25
123
2
63
135
16
144
2
NO
41
02
65
38
44
137
14
Ml
1 1
1 1
7
5
3
6
3
3
4
9
2
6
3
b
2
2
2
7
b
2
10
13
8
9
3
22
5
2
2
5
2
2
2
3
4
| ) *****
FE MN
NANOGHAMS/M**3
342
2843
2085
755
1025
665
459
628
675
4206
30
19
109
102
517
104
522
3033
7/2
2/2
2626
179
1618
1248
157
928
88
I9b9
930
847
1285
676
184
682
503
1 1
144
60
25
34
13
21
21
34
142
0
3
9
2
19
1 1
18
80
42
34
68
Ib
50
02
9
1 10
5
65
23
52
52
108
15
63
19
CH
II
0
0
5
3
6
0
3
4
9
0
0
0
2
0
0
0
0
0
0
2
2
0
4
0
5
0
0
0
0
0
0
0
0
0
V
II
II
7
JO
6
6
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313
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1 1273
-------
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*****
N 1 A U A H A F H 0 N T J K H
S I T bi It 2 FINk: PAWTICULATt UATA
STUDY
(PAHT - I )
*****
FILThR
*
40212
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40224
40229
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0
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-------
w
NIAUAHA I-' H 1) M T I h H STUUY
S 1 T if it 2 HINb HAKfieULATE DATA (HAHT - 2 )
*****
FILTbH H
J
# N
40212 121
40218 122
40224 123
40229 124
4023b 12D
4024 J 126
40247 127
40253 128
4O259 129
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40271 131
M
()
N
2
2
3
3
3
3
3
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26
28
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20
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26
28
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24.3
16.3
24.3
24.2
24.2
24.2
24.3
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24.3
24.2
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M**3
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171
61
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243
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NANOUHAMS/M**3
3407
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1242
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1092
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289
199
703
199
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696
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200
199
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0
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214
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96
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2885
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Ak/£HAUh: 1908.1 b64.0 37.9 1702.0 149.6 J 0969.7 350.4 164.1
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STATISTICS
STANDAHU 1684.8
UB/IATION
491.9 bl.6 2520.I 309.b 8645.5 1261.2 157.9 28.34356.8 129.0 388.1
-------
FILTbH
20003
20009
20024
20032
20038
20033
200b3
20060
200b9
200/3.
20072
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20083
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20096
20098.
2021 1
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40009
20203
40018
40024
40031
40030
4003Q
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202 Ib
40049
400b4
40060
40066
40072
40078
40091
a
40
41
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30
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54
55
56
58
59
60
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62
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63
66
61
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89
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6
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9
9
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10
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1 1
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u
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25
27
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21
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22
24
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1
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1 1
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17
19
23
26.
29
5
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1 /
23
2b
29
31
4
7
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22
*****
TIME
HKS
b.6
5.9
12.5
17.7
18.2
16.4
17.2
10. B
13.5
18.2
18.2
18.1
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24.1
24.1
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23.6
23.7
23.6
23.8
23.7
23.7
23.6
23.5
23.7
23.7
23.7
16.6
22.5
23.7
23.6
t
FLOrt
M**3
1 1 .6
12.3
2b.8
36. b
3/.4
31 .0
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36.1
49.6
bo. 3
bO.2
43.2
49.4
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49.4
50.2
48.1
48.7
47.3
49.3
49.5
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31 .B
S I T
N I A G A H A F ti O N T
b tf 3 FINE HArtflCULATb
HINU
OIH SPU
UbJ MPri
226
212
193
203
209
I9/
330
219
181
150
156
238
2 1 1
187
235
284
204
47
51
32
92
205
1 14
163
274
168
64
313
192
165
219
209
254
1 16
281
b
5
6
5
5
6
2
13
4
4
3
4
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9
3
4
2
3
2
8
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1
6
10
5
6
5
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FSH
UUM/
M**3
38
67
Bd
92
38
48
35
69
50
57
26
42
93
21
39
2b
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6
14
16
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12
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32
19
19
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42
75
49
51
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629
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I b H S f U D Y
DATA (PAliT - 1
ZN
II
67
91
269
25
35
31
45
48
51
26
23
635
1 1
80
19
72
2
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2
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1 1
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2
125
2
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5
3
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17
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2
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2
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0
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2
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309
4620
1650
1570
614
599
244
1796
400
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476
587
4842
440
485
324
1504
1 1
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46
76
260
104
434
104
371
210
134
0
0
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10/5
135
596
61
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MN
1 1
112
26
26
14
13
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45
27
27
19
19
52
22
32
23
46
2
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5
9
14
16
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25
14
0
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45
43
II
39
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0
5
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0
0
6
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3
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7
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II
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5
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3
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46
19
3
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1 1
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4
3
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6
2
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5
8
2
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0
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3
1 1
2
2
CA
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1228
814
660
470
187
43
452
119
59
87
207
577
144
272
218
3/6
47
63
187
73
182
149
75
5/
198
224
84
0
114
603
687
129
173
155
S
2534
6107
15859
42670
6395
7528
4503
12459
6388
7437
2853
5181
11943
2115
3876
3191
46025
332
984
1613
725
1632
1 165
2087
1433
4226
654
1968
0
2377
5249
40891
1376
5959
1335
-------
FILTEK
*
40088
40099
4O097
40103
40107
401 10
401 14
401 18
40123
40122
40135
4O134
40013
40145
40150
40157
40162
40166
40 1 72
40l7d
40184
40189
40195
40201
4O2O7
40213
40219
40230
40236
40242
40248
40234
40260
40266
40272
H
U
ri
94
95
96
9/
va
99
101
102
103
104
105
106
107
108
109
10
12
13
14
15
16
17
18
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120
121
123
124
123
126
127
126
129
I3J
131
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N
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12
12
12
12
12
12
12
12
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
U
A
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28
30
4
6
10
12
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19
22
28
2
9
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15
17
21.
27
30
2
6
8
12
14
20
22
26
4
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10
14
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20
22
20
28
*****
TIME
HKS
23.7
23.6
23.7
23.7
23.6
23.7
23.7
23.6
23.7
23.7
23.7
23.7
15.8
23.7
20. 6
15.3
23.8
24.0
24.0
18. b
24.0
22.9
Ib.l
9.9
14.3
23.5
24.0
24.0
24.0
24. 0
24.0
19.2
24.0
24.0
24,0
N I
SITE » 3
FLOrt
M**J
52.5
46.7
47.6
40.1
47.4
47.8
48.1
49.3
49.6
50.3
50.5
4d.3
34.4
47.6
41 .d
31 .4
52.1
52.5
52.4
41.3
52.4
50.1
39.3
21 .6
31 .0
50.5
50.7
51.2
50.3
51.5
51 .0
40.5
49.7
50.1
50.9
MlNU
DIM SHU
DEO
9d
80
43
75
103
37
209
307
229
322
288
221
190
243
244
336
237
277
254
241
251
43
68
220
24 /
43
171
61
235
243
232
247
28
253
176
MHH
7
9
17
O
12
9
10
3
12
4
7
12
1
14
6
4
6
9
10
3
13
3
4
6
6
II
15
4
13
15
12
1
2
13
1
AUAHA FHONT
FINE HAKTI CULATE
UOM/
M**3
26
31
22
35
6
28
35
24
22
42
1.9
33
42
22
26
36
23
14
14
37
19
25
30
70
48
12
16
27
39
30
53
46
30
16
16
»
BH
I E K S T U 0 Y
DATA (t^AHT - 1
ZiM
NI
FE
) *****
MN
Ctt
V
CA
S
NANOGHAMS/M**3
226
204
346
460
87
269
354
359
296
1 112
186
450
547
332
397
312
III
3/
290
532
162
618
410
1020
290
150
I2d
461
429
276
559
603
51V
116
160
300
136
46
47d
46
46
363
457
3d5
1 145
216
292
1104
171
222
308
146
200
454
566
42
806
408
468
227
43
234
424
129
104
353
718
885
174
440
21
32
26
60
2
09
63
42
30
68
8
71
40
96
19
4
2
2
Jl
93
13
8
63
346
13
2
2
8
63
16
97
47
47
2
16
2
2
5
2
2
2
5
5
2
a
2
5
4
2
3
13
2
2
2
3
2
2
3
6
4
2
2
2
2
2
13
3
2
2
2
255
645
614
688
32
805
873
469
913
2465
304
1471
435
7o2
291
22
77
221
100
794
256
85
232
3112
133
49
32
227
1 163
10/8
1491
1015
498
2/6
201
13
23
26
25
5
28
20
25
33
60
13
40
20
20
9
0
7
10
7
26
.10
2
14
102
4
0
2
a
41
51
97
47
19
16
5
0
0
0
Q
0
0
2
0
2
2
0
0
0
2
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
3
2
0
0
10
II
8
3
2
14
2
14
2
13
JO
2
4
2
3
48
2
5
2
3
2
13
3
32
8
a
2
5
2
2
5
23
2
2
2
282
497
460
941
160
223
3/4
185
259
2/5
71
7/7
817
448
86
30
162
173
163
268
203
151
172
776
263
/9
68
218
294
258
366
8/2
473
218
179
2648
4209
3.980
3427
1882
5174
4105
3193
3109
4459
2705
4415
3537
2921
5268
2803
.3412
2105
826
5996
3402
1950
3274
12951
II 174
1886
3308
4898
6612
4342
6085
4818
2981
1868
1976
s r A r i
i i c
AYEHAUE 34.1 552.4 635.7 49.5
SfAHOAHU 22.O 408.3 681.6 90.4
UEVIAHON
5.1 643. / 22.8
1.3
6.4 781.8 22.7 2.3
7.0 291.8 4468.1
7.6 256.9 3593.5
-------
w
*****
NIAGARA F H 0 N I I E H
S I T E * 3 FINE PAHTICULATt: DATA
STUDY
(PART - 2 )
FILTEK
20003
20009
20024
20032
2003d
20O55
20053
20060
20039
20075
200/2
20064
20107
20083
200d9
20096
2009d
20211
40006
40009
20203
400 Id
40O24
40031
40030
40036
20127
20213
4O049
40034
40060
40066
40072
40078
40091
ti
J
N
40
41
49
50
51
54
55
56
38
59
60
61
62
64
63
66
67
68
O9
70
72
73
/4
76
77
/d
dO
d2
83
84
83
87
88
89
93
M
0
N
6
6
/
7
7
a
8
8
8
d
d
d
d
d
9
9
9
9
9
9
9
9
9
10
10
10
10
10
10
10
IO
1 1
II
1 1
1 1
U
A
Y
25
27
.19
21
25
2
6
8
12
15
18
22
24
30
1
/
1 1
13
17
19
23
2o
29
b
7
11
17
23
2b
29
31
4
7
10
22
TIME
HHS
b.6
5.9
12.5
17.7
18. 2
JO. 4
17.2
10. 8
13.5
18.2
18.2
18.1
12.5
18.1
16.7
18.2
17.6
24.1
24.1
24.1
23.6
23.7
23.6
23.8
23.7
23.7
23.6
23.5-
23.7
23.7
23 . 7
16.6
22.5
23.7
23.0
FLOrt
M**3
II .6
12.3
25.8
36.5
3/.4
31.0
3b.l
21.1
25.6
34.8
36.3
33.4
23. d
37.4
34.5
35.4
36.1
49.6
50.5
50.2
45.2
49.4
49.0
49.4
50.2
48.1
4d.7
47.3
49.3
49.5
49.1
34.6
47. O
49.5
51 .d
141:
OIH
226
212
193
205
209
197
330
219
Idl
150
156
23d
211
Jd/
235
284
204
47
51
32
92
205
J 14
163
274
168
64
313
192
163
219
209
254
1 10
281
UU
SHU
5
5
6
5
5
6
2
13
4
4
3
4
7
3
1
3
11
9
3
4
2
3
2
8
-10
3
1
6
10
5
6
5
3
2
4
SI
892
2625
5550
3008
2180
2177
1 /86
2603
1804
1741
667
1408
3118
1 154
2/77
1 126
3956
209
751
852
7d3
1099
692
335
206
2125
603
1506
0
1.264
3ld5
4/OJ
95 d
3534
575
AL
880
833
396
280
1080
330
914
4db
400
667
282
289
431
5/3
296
289
283
206
649
419
839
630
209
207
504
984
d/6
61 1
0
416
916
293
218
d50
737
F
d5
8
46
112
1.20
0
108
151
0
86
0
129
126
106
86
84
no
0
39
19
22
60
0
40
19
0
0
0
0
0
61
57
83
0
0
N03
515
2091
0
0
66
0
76
307
109
0
27
48
0
106
173
84
0
0
257
39
88
0
0
0
0
20
82
147
0
262
488
635
446
444
425
CL
0
699
116
57
16
0
113
-156
0
28
no
14
0
26
0
0
0
80
39
79
66
0
61
0
19
83
123
84
0
20
8.1
0
0
0
3 7
S04 ri02
MANOUHAMS/M**3
5283
14784
22.9 /d
53643
1 33/5
20351
1 1520
18584
15954
31 831
6031
19138
45034
4300
8229
6544
54281
806
23/5
3722
1724
3746
1735
3984
2328
9189
1644
4838
0
4463
13515
25230 .
2809
15945
200 /
0
0
0
265
56
148
0
189
160
28
0
203
168
106
173
84
0
0
0
0
0
60
0
O
0
436
0
0
0
1454
162
1270
0
0
0
NA
85
504
669
383
160
129
170
426
234
200
247
169
294
186
173
112
304
100
0
39
176
60
0
80
19
270
102
147
0
242
305
404
148
242
154
H04
0
0
0
0
0
0
0
0
86
0
0
0
0
160
0
0
0
0
0.
0
0
0
0
0.
0
0
0
0
0
0
0
O
0
0
0
-4
2886
4442
7052
8216
4329
5455
4897
6676
6259
6773
2451
6216
10774
1842
3245
2961
8866
0
1049
1393
205
1275
.489
1254
915
3929
143
2703
0
1939
6146
11258
659
4607
598
Bft-S
214
0-
0
0
0
0
99
85
39
28
165
0
0
106
202
56
27
0
138
79
265
141
0
0
19
124
472
0
0
60
0
0
191
262
251
K
343
2367
746
876
320
387
199
994
273
86
192
197
42
53
57
28
193
0
0
0
44
0
0
0
0
353
61
0
0
0
386
317
106
363
154
-------
N I A U A H A F H O N T I E H
SITE # 3 FINE h>AtfncULATE DATA
S T U U y
(HAHT - 2 )
*****
FILTEK
#
40088
4O099
40097
40103
40107
401 10
40114
40)18
40123
40122
4O.I35
40134
40013
4OI43
40130
40157
40162
40166
40172
40J78
40184
40.1 89
40.1 95
40201
4O2O7
40213
40219
40230
40230
40242
4O248
40254
40260
40266
4O2/2
s r
ti
U
ri
94
95
90
97
.98
99
101
102
103
104
103
106
107
lOd
109
10
12
13
14
13
16
17
Id
19
120
121
123
124
123
126
I2/
128
129
130
131
A
M
0
N
II
II
12
12
12
12
12
12
12
12
1
1
1
1
1
1
-1
1
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
T 1
L>
A
y
28
30
4
6
10
12
16
iy
22
28
2
y
1 1
15
1 /
21
27
30
2
6
8
12
14
20
22
2o
4
7
10
14
16
20
22
20
2d
S
TIME
rtHS
23.7
23.6
23.7
23.7
23.6
23.7
23.7
23.6
23.7
23.7
23.7
23.7
15.8
23.7
20.6
15.3
23.8
24.0
24.0
18.8
24.0
22. y
18. 1
y.y
14.3
23.5
24.0
24.0
24.0
24.0
24.0
19.2
24.0
24.0
24.0
f i
FLOrt
M**3
52.5
46.7
47.6
48.1
47.4
47.8
48.1
49.3
49.6
50.3
50.5
4d.3
34.4
47.6
41. d
3.1 .4
52.1
52.3
52.4
41 .3
52.4
50.1
39.3
21.6
3J .0
50.5
50.7
51 .2
50.3
51 .5
51 .U
40.5
49.7
50.1
50.9
c s
rtINU
UIH SHU
OEO MHrt
.98 7
80 9
43 17
/5 6
103 . 12
37 9
209 10
30 / 3
229 12
322 4
288 7
221 12
190 1
243 14
244 6
336 4
23 / . 6
277 - 9
254. 10
241 3
251 13
43 3
68 4
220 6
247 6
43 1 1
171 15
61 4
235 13
243 13
232 12
24 / 1
2d 2
253 13
1 /6 /
AVEKAUE
S f ANOAHb
SI
1432
847
218
648
558
. 1287
1287
1513
1246
206
1026
1419
302
1612
2065
330
467
1093
459
1166
1303
207
1390
1 /90
334
205
204
1057
1537
658
1559
3252
1 /62
945
845
1414.3
1106.3
AL
iy5
2W
215
4s7
4d5
75y
213
609
206
203
620
212
298
215
503
326
196
195
iy5
248
195
204
619
1334
330
202
202
563
203
446
201
895
206
204
744
449.0
2/8.4
F
0
42
42
41
168
41
0
0
40.
19
0
0
87
63
71
0
0
0
0
0
19
19
0
92
0
0
0
19
0
0.
58
49
80
19
0
39.0
43.1
N03
838
1240
252
2703
232
104
915
912
1291
1531
1148
2091
17/4
630
95
572
537
932
247
633
95
IO37
2592
741
32
39
39
97
774
1009
4U84
5160
2231
538
392
647.3
1 002 . 4
CL
0
171
42
103
21
20
0
0
40
357
0
0
116
0
0
0
0
114
3d
0
0
0
0
0
0
0
0
0
0
50
58
0
100
259
157
54.0
102.3
S04
UArtOGH
6419
78/1
649 /
5d22
2890
10150
7073
6124
5749
9864
5130
7971
5875
4832
9336
4487
6830
4414
419
10721
6222
3391
5007
27988
20993
2891
5/99
9701
15849
8910
14044
8518
5045
3712
4102
10323.5
1 100 1 .4
N02
A M^ f M W A
0
0
0
0
0
0
582
709
0
0
851
2132
1279
0
0
572
537
0
0
169
0
0
0
O
0
0
0
0
0
324
0
0
0
1437
19
196.8
421.2
NA
3
114
213
168
207
147
188
208
141
221
278
59
414
203
. 231
71
254
76
114
133
411
171
259
355
787
386
138
98
0
0
271
176
0
341
7.9
157
200.0
148.2
P04
0
0
0
145
42
0
0
0
0
0
0
0
58
0
0
0
0
0
0
0
0
0
177
0
0
0
276
IJ7
0
0
0
0
0
558
0
23.1
81 .1
NH4
2704
3358
2186
1954
1055
3265
4867
A061
2138
3739
4318
3768
1657
2122
5937
1750
5986
1655
324
7405
5077
2414
2211
10750
5256
930
1953
2791
38/2
3203
4433
3753
2010
658
981
3533.3
2663.4
BR-S
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
50
0
0
0
98
58
0
0
0
0
0
0
0
46.1
88.5
K
285
0
525
561
105
0
0
202
0
0
178
848
232
294
0
445
0
209
0
556
95
0
254
2363
419
0
138
566
714
582
1059
716
603
219
529
311.9
446.8
UEiMAflON
-------
*****
FILTtH
it
20004
20010
20025
20039
20056
20057
20061
20076
20044
20 II 7
20106
20084
20090
20097
20101
20223
40001
40010
20204
40019
40025
40032
40043
20124
40048
4005b
40061
40067
40073
400.79
4008 /
40090
40089
40092
4OIOO
rt
U
N
40
41
49
bl
54
55
t>8
b9
60
61
62
64
6D
66
67
68
69
70
72
73
74
76
11
8J
83
84
85
87
88
89
91
92
93
94
97
(J
tt
6
6
7
/
8
8
8
8
8
8
8
8
9
9
9
9
9
9
9
9
9
10
10
10
10
10
10
2
U
A
V
25
27
19
25
2
6
12
Ib
18
22
24
30
1
7
1 1
13
17
19
23
2o
29
b
7
17
2b
29
31
4
7
JO
16
20
22
28
6
TlMt
riKS
6.b
6.3
7.8
12.3
b.O
16.7
7.1
6.8
23.9
16.2
b.l
17.7
1 1.1
17.7
11 .1
24.2
24.1
24.1
24.0
23.9
23.9
24.0
23.9
16.2
23.9
24.0
17.3
14.7
22.3
23.3
24.1
24.1
24.2
24.0
13.9
FLUri
M**3
13.7
II .9
16.1
24.8
9.8
3b./
14.0
13.2
49.3
34.1
10.7
37.8
37.9
3b.8
24.9
50.9
bl .9
bl .9
bO.3
bl .b
bl .3
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590
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0
6632
12548
1193
6307
1363
3171
1053
3980
4590
-------
01
N I A J A H A F H 0 N T I E tt
S I T E tf 4 FINE HAHTICULATE UATA
S T U U y
(HAKT - I )
*****
FILTEH
#
40404
401 14
401 Ib
40.1 1 9
40124
4OI30
40141
40146
40151
40150
40161
4O467
40173
40179
40190
40196
40202
4020d
40214
40220
40225
40231
40237
40243
40249
40255
40201
4O267
40273
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U
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99
101
102
103
106
107
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121
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12
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17
21
27
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2
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12
14
20
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28
4
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10
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16
20
22
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28
TIME
riKS
24.0
24.0
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24.0
24.0
24.0
12.9
24.0
19.6
22.3
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53.2
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54.4
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103 .
37
209
307
229
221
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243
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336
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SPIJ
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4
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10
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FSP
UUM/
M**3
32
43
40
19
43
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44
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31
39
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51
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42
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253
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266
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1167
288
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1072
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145
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2
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131
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101
4
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50
10
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38
119
66
2
52
369
21
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2
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73
106
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19
127
28
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2
5
2
10
10
16
4
4
3
13
3
2
2
2
2
3
6
4
2
6
2
2
42
2
II
2
2
2
13
FE MN
NANOGHAMS/M**3
466
3277
1649
500
26a7
2621
522
1823
687
248
793
445
I4D2
1936
72
425
3688
1224
44
3717
354
296
32767
2064
3828
2084
482
4677
698
34
404
38
20
76
65
27
105
31
26
32
43
86
125
2
18
96
88
0
125
42
10
1178
105
118
135
21
206
15
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0
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0
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126
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266
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24d
230
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5430
5918
4127
2156
4899
4339
2731
5937
5916
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3271
2746
4875
6192
1880
3068
12148
43025
J972
5635
3699
4498
27869
3824
5105
4611
2710
4723
2960
STATISTICS
AVERAGE
SF AMDAHL)
DEVIATION
43.7 739.7 640. / 122.9
28.2 675.7 493.9 338.9
5.8 1840.4 69.9 1.9
6.2 4172.5 149.6 4.4
6.6 /53.0 5246.5
6.6 1214.6 4940.0
-------
*****
HILTHtf
tt
20004
20010
20025
20039
20056
20057
20061
2007o
20044
20 II 7
20106
20084
20090
20097
20101
20223
40001
40010
20204
40019
4002b
40032
40043
20124
40048
40Obb
40061
4006V
40073
40079
40087
40090
40089
40092
40IOO
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U
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40
41
49
bl
54
55
58
59
00
61
62
64
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66
61
68
69
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73
74
76
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80
83
84
85
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91
92
93
94
97
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0
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6
6
7
7
8
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10
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6.3
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24. 1
24.0
23.9
23.9
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54.0
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OIH SHU
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226
212
193
209
197
330
181
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156
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284
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114
163
274
64
192
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219
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110
69
210
281
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5
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5
6
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10
1
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5
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2
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6
I A 0 A H A H H O N T
4 FINtf HArfflCULATb
SI
2/78
2615
10376
2163
1058
955
1899
5073
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918
4349
2296
4327
3296
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92b
199
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704
699
1258
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1262
340
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750
864
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1841
207
300
3949
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187
301
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0
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315
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101
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327
57
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301
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438
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CL
0
801
154
120
0
0
150
75
20
58
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0
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0
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38
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0
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1 7074
2741 1
18647
17380
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44429
31570
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5764
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29281
785
2310
31 18
1788
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2163
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2410
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0
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27459
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2890
7067
2245
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0
0
0
0
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353
428
0
0
0
372
52
105
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120
0
0
38
0
58
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383
0
583
0
1824
1455
0
0
0
0
0
0
0
*****
MA
0
607
1 145
281
407
140
714
679
101
146
279
158
422
195
280
117
0
57
59
116
19
78
146
88
704
0
435
474
144
199
94
221
257
182
623
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0
0
0
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633
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0
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0
0
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3060
1559
10854
7487
6931
4121
135/1
1 1480
1176
5195
12208
951
301 1
2594
9065
0
1155
1270
397
1689
584
2888
803
dd
1409
0
4219
11483
642
4540
1020
2103
570
2739
820
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226
0
0
0
0
381
0
151
101
58
0
105
211
55
40
0
115
77
158
116
0
58
18
235
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0
0
0
0
258
245
0
239
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0
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380
2908
1021
281
1223
336
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528
385
0
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423
184
55
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310
58
0
146
0
1469
0
1742
664
165
358
151
1 162
147
365
1673
-------
w
N1AUAHA F H O N T I H R STUDY
S I f k£ » 4 FINE fAttTICULAT£ DATA (HAHT - 2 )
*****
FILTbH
tf
40J04
401 1 1
401 Ib
401 19
40124
40I3O
4OI4I
40146
40lbJ
4Olb6
40161
40167
40 1 73
40179
40iyo
40Jy6
40202
4020d
40214
40220
40225
40231
40237
40243
4O24y
4025D
40261
4O267
40273
a
a
N
yd
yy
101
102
103
106
107
108
toy
10
12
13
. 14
16
17
Id
19
120
121
122
123
124
I2D
126
127
128
i2y
130
131
M
O
N
12
12
12
12
12
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
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A
10
12
16
19
22
y
II
1 5
17
21
27
30
2
a
12
14
20
22
26
2d
4
7
10
14
10
20
22
26
28
TIME
HKS
24.0
24.0
20.8
24.0
24.0
24.0
12. y
24.0
19.6
22.3
17.0
24.1
24.1
24.0
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16.5
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14.6
24.0
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24.1
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5.0
24.0
23.5
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24.0
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M**3
52.0
53.2
46.3
53.2
54.1
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30.5
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38.2
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54.4
54.0
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32 .y
53.2
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52.7
13.0
52.7
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UIH
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103
37
2oy
307
22y
221
190
243
244
336
237
277
254
251
43
68
220
247
43
220
I/I
61
23b
243
232
247
28
253
177
no
SHU
MHH
12
y
10
3
12
12
1
14
6
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10
13
3
4
6
6
1 1
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4
13
Ib
12
1
2
13
1
SI
1335
1248
1652
1021
1530
joy?
340
1182
1650
200
1307
190
536
661
616
279
454
1 /2b
601
496
188
804
795
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886
30by
1503
1 1/4
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402
192
221
841
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410
777
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821
197
268
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487
66b
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311
192
489
185
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194
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197
441
807
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133
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0
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18
87
32
53
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0
0
0
0
0
0
0
87
0
0
0
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.76
0
0
38
79
0
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2610
267y
921
2920
2681
1969
1774
498
1158
1726
698
1028
1 29
1510
2664
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131
6542
90
284
5363
1801
4010
7381
2277
1203
415
CL
0
56
172
0
406
543
0
88
0
0
837
238
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0
0
1762
891
52yo
768
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132
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12283
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5021
11036
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3357
4818
26847
27347
2930
9933
7490
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63804
9140
10238
11380
4872
12571
6685
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0
0
950
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0
0
0
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0
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226
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)
228
37b
561
94
517
560
328
496
90
173
366
220
385
370
251
457
1180
577
169
1337
0
0
4214
398
1621
0
336
534
264
P04
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
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0
0
0
0
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NH4
3270
3981
3112
2595
3216
1770
2756
4985
9127
3109
8631
2517
3196
8665
881
2234
760d
7748
IOU2
4OII
2285
2750
12337
. 3451
3839
4306
1723
2598
1378
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0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
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0
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STATISTICS
1586.3 580.5 43.0 1173.7279.6 Il4d0.7 176.8 401.1 N.I. 3919.0 45.4 846.8
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-------
oo
*****
N 1 A 0 A H A K H O N f I E
SITE # 5 FINE HArtnOJLATE DATA
S f U U V
(HAKT - I )
*****
FILTEK
H
20005
2001 1
20026
20040
20050
20054
20002
20074
20078
201 Id
20105
200db
20091
20099
20102
20222
40004
4001 1
2020b
40020
40020
40029
40042
40038
20J2b
20234
40050
40056
40062
40068
40074
40080
40086
40101
40 1 Ob
H
U
N
40
41
49
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54
55
56
59
00
61
62
64
63
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67
08
69
70
72
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74
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80
82
83
84
83
87
88
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91
96
97
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6
6
7
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8
8
8
8
8
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8
9
9
9
9
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10
10
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10
10
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25
27
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6
8
15
18
22
24
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17
19
23
26
29
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17
23
25
29
31
4
7
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16
4
6
TIME
I1HS
6.5
6.3
10.0
9.3
6.3
17.9
10.2
5.0
16.0
13.7
10.1
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17.9
11.7
23.5
23.6
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24.0
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23.9
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13.4
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226
212
193
209
197
330
219
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64
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5
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6
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31
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207
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5088
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1 1441
1 144
5415
1283
4072
4272
-------
w
SITE
I A iJ A H A F H 0 N T I E K STUDY
b FINE HAHTICULATE DATA
- I )
*****
FILTEH
if
40108
40112
401 16
40120
40127
40132
40137
40142
40147
40152
4O155
40160
40.168
40174
40180
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40191
40197
40203
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99
101
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104
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TIMH
HRS
24.1
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334
1288
342
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661
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291
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283
819
342
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206
1689
311
475
400
561
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833
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269
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109
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763
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384
1069
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113
137
33
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76
48
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183
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93
119
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1 16
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13
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7
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FE MN
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2146
3041
1202
357
471
1127
997
465
1223
925
765
2678
536
2711
2381
2549
101
220
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4054
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146
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32
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2
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5
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4
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15
10
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3
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26
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256
480
744
259
180
195
237
269
670
216
153
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81
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107
529
606
62
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163
109
266
1019
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6325
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2118
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STANDARD
UtMi ATI ON
46.6 823.0 644.7 .123.9
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-------
dd
FILThK
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2000b
2001 1
20026
20040
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299
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53b7
-------
*****
H I A O A H A H ri O N T I b W S f U U Y
SITE tf b HI Mb HArtTICULATE UATA (PAHT - 2 )
FILTbrt
40108
401 12
4OI 16
40120
40127
40132
40137
40142
40147
40lb2
40lbb
40160
4O168
40174
40180
40185
40191
401 97
40203
40209
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40221
40226
40232
40238
40244
402bO
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40262
40268
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8
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24.1
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STATISTICS
STANUAKU 1251.5 4M.I 62.3 1460.11009.7 II/4/.I 771.1 273.3
Ut: VI AT I ON
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-------
N I A J A H A F H 0 iM f I t H
SITE # 6 FINE PAKTICLJLATE DATA
S T U 0 Y
(PAKT - I )
*****
FILTEH
tf
20O06
20027
2O04I
2004d
20051
20052
20063
20070
20079
201 19
20J08
20086
20092
201 II
20IO3
20212
40005
40012
20206
40021
40027
40015
4OO39
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20216
40051
4O057
40063
40069
400/3
40081
40082
40094
40O96
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49
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33
54
53
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61
62
64
65
66
67
68
69
70
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83
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91
92
93
94
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6 27
7 19
7 25
7 31
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8 8
8 12
8 Id
8 22
8 24
8 30
9 1
9 7
9 II
9 13
9 17
9 19
9 23
9 26
9 29
10 5
10 1 1
10 17
10 23
10 25
10 29
10 31
4
7
10
16
20
22
28
TIME
HHS
5.4
21.5
17.7
17.7
13.7
17.9
17.6
17.7
17.7
18.0
17.7
17.7
17.9
17.9
23.6
23.6
23. /
23.6
23.7
23.8
23.8
23.8
23.9
23.7
23.8
23.7
23.9
23.8
IS. 7
23.8
19.5
23.7
23.8
23.9
23.9
FLOW
M**3
10.5
44.1
34.4
36.4
26.5
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33. d
34.9
34.1
37.1
34.2
36.0
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36.6
49.3
48.6
49.5
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48.5
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53.4
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212
193
209
215
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330
219
181
156
238
211
187
23b
284
204
47
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32
92
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163
168
64
313
192
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219
209
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210
281
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3752
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10930
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6401
1793
2613
1690
2319
-------
Ni
***** SIT
FILTEH H
U
it
-------
NIAGARA F H 0 N f I h' R
S I I h It o FINH PARTICULAR DATA
(PART - 2 J
*****
F 1 L TbR
20006
20027
20041
20048
20O5I
200b2
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200/9
20 1 19
20IOd
200dO
20092
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40012
20200
40021
40027
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212
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197
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794
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280
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206
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204
506
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545
563
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194
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419
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76
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200
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16938
15581
6225
19253
12455
14586
7733
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1 1329
28045
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14919
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143
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174
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146
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3336
5145
5090
3133
6671
5038
4346
3777
2786
4612
6222
2192
1 149
3603
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2800
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14/7
13/6
22b4
3241
323
1812
2441
1736
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4851
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2052
1250
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27
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0
0
0
60
40
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0
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20
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382
186
203
137
263
268
1094
57
29
0
0
0
267
0
162
0
0
322
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438
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3J8
151
280
-------
w
N I A U A H A F H O N T I E H
S I T E u 6 FINE HAHTICULATH UATA
STUDY
<*>AUT - 2 )
*****
FILTEH
it
401 02
40098
40106
40IO9
4OII3
40117
40121
40126
40128
40138
40148
40lb3
40154
40159
40169
40173
40181
40 1 86
40192
40 1 yd
40204
40210
40216
40222
40227
40233
40239
4024b
402bl
4025.7
40263
40269
4027b
H
J
93
96
97
98
99
101
102
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104
107
108
109
10
12
13
14
15
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I«i0
121
22
123
124
123
126
127
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129
130
131
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1 1
12
12
12
12
12
12
12
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1
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2
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12
14
20
22
26
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4
7
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14
16
20
22
26
28
TIME
HRS
23. d
24.1
23.8
24.0
23.8
23.8
23.8
23. d
24.0
24.0
24.0
24.0
24.0
23. d
23. d
23.9
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16.6
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23.9
23.9
23.9
23.9
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23. d
23.9
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50.8
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44.8
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46.8
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bl .0
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DIK SHU
L)tG MHrl
80
43
7b
103 .
37
209
3O7
229
322
190
243
244
336
237
277
2b4
241
2bl
43
68
220
24 /
43
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171
61
233
243
232
247
2d
2b3
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9
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10
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12
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193
201
1202
204
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424
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1017
1240
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927
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911
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201
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2497
314
43d
1499
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I3bl
1437
1286
610
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AL
191
b49
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490
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191
946
513
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192
193
194
193
386
190
1 iJ9
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218
194
2/9
199
194
224
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198
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807
20 /
204
202
b03
F
1 II
38
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Ib/
0
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3/
36
18
76
b/
0
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b6
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NO3
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967
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467
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139
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217
0
S04 N02 MA
NANOOHAMS/M**3
3337
4277
4410
2933
6366
4676
2118
3798
3065
2313
3996
10272
51 05
4998
.2012 -
1000
88O9
4769
4849
4201
27/bO
268bb
4160
12291
7164
9602
8097
3769
5b96
5l5d
3135
3241
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0
0
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848
1 793
209
488
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509
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0
1159
0
0
0
0
0
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0
0
0
179
0
0
0
0
177
0
93
116
174
137
92
93
57
56
128-
75
114
76
56
94
74
92
200
. 75
341
285
108
272
189
0
154
0
238
136
0
0
279
79
196
P04
0
0
0
0
0
0
0
0
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0
0
0
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0
0
0
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0
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0
0
0
0
0
0
0.
NH4
1211
1819
1818
1023
5093
3928
1183
2632
1009
1166
2531
6106
4141
3394
447
166
5530
2884
1666
1482
2505
4372
1063
3177
1103
2936
2248
1340
2701
2488
1218
533
1803
8H-S
0
0
0
0
147
0
76
0
73
0
0
0
0
0
0
37
1 II
0
0
0
0
0
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0
38
0
0
0
0
0
0
o
0
K
242
0
464
0
0
0
0
94
0
0
0
0
0
0
93
0
200
0
149
228
81
446
0
153
290
618
397
485
427
485
499
217
3/2
AVEHAUh 1241.6 376.3 41.6 22b.O 40.4 7/34.8 149.8 .134.2
8.5 2694.1
13.3 169.I
STATISTICS
SfANUAKU IO/b.4 243.3 44.6 4/8.9
DEVIATION
bb.d 7437.9 350.1 IO/.0 35.4 1730.6 33.3 210.7
-------
APPENDIX C
The data base for the entire project is listed here and represents all of
the dichototnous particulate filters which were collected for the coarse particle
fraction. Each filter is printed along with information describing the date
(month and day), elapsed time, sampled air volume (flow), meteorological data,
and concentrations of particulate weight and "various chemical components. A
series-30000 filter reflects the use of 0.5M. pore diameter filters while the
series 50000 reflects the change to 1.0(i pore diameter filters. The series-
30000 filter data for coarse particulates corresponds to the series-20000
filter data for fine particulates which is presented in Appendix B. Similarly,
the series-50000 filter data for coarse particulates corresponds to the series-
40000 data for fine particulates in Appendix B.
FILTER SERIES DESIGNATION
PARTICULATES
FILTER PORE DIAMETER FINE COARSE
0.5(1 20,000 30,000
I.OM. 40,000 50,000
C-l
-------
n
*****
HILTbH H
U
ft ^
30001 41
J002I 49
30028 bO
30036 51
30073 6d
30077 00
300dO 61
3 008 1 04
30O8/ Ob
300y4 7y
30O9b oo
30100 6/
30IOy 02
30204 12
30214 82
bOOOJ 69
bOOOV /O
bOOJ6 /3
30022 /4
b002d 7d
bOO34 /6
b0040 11
b004o d3
bOOD2 d4
bOObd 83
bOOO4 8/
300/0 88
bOO/O 89
b0133 106
DO 136 103
3Ol3y io/
30144 lOd
t>oi4y ioy
bOlbd 1 IO
DO 4 O-) 112
M
o
N
6
7
7
/
y
d
d
d
y
10
y
y
d
y
10
y
y
y
y
10
10
10
10
10
10
i
i
i
L)
A
y
27
iy
21
2b
13
Id
22
JO
1
13
7
1 1
24
23
23
17
iy
2o
2y
1 1
b
/
2b
2y
31
4
/
10
y
2
1 1
Ib
1 /
2(
21
TlMt
HHi>
b.d
7.3
0.6
7.5
23.0
1 1.7
17.7
1 I.I
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23.6
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17.2
7.1
23.9
23.6
23.0
23.6
23.7
23.0
23.8
23.7
23. d
23.6
23.7
23. b
0.9
23.0
23.7
23.8
23.7
14. d
23. d
10. y
23.8
2J.y
S
hLlM
M**3
12.2
Ib./
Ib.l
lb.2
bo. 1
41 .1
3y .0
43. 1
4b.3
42. d
43 .4
43.7
1 /./
bO.O
bd.o
53.2
b4.0
bl .2
bl .0
54.4
b4.l
bb.2
70.3
70.0
67. b
iy.7
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od.o
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42. y
od./
31 .2
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1 T b
>il
UIK
UEU
212
1 9j
2 Ob
2oy
4/
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23d
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23b
Ib
284
204
21 1
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313
bl
32
203
1 14
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103
274
i y2
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243
244
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a i
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SHL)
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b
6
b
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3
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1
1 4
0
4
6
I A U A H A K H 0 N T
COAKSH
CSH
UUM/
M**3
31
/y
46
44
10
30
24
23
14
12
22
32
2b
II
6
b
12
20
16
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14
4
42
7
27
32
8
30
12
5
6
24
14
2
1 1
HAKriL
Hb
BR
I t H S f U
DATA
ZM
u y
(HAHT - 1
NI
Ht
) *****
M
CH
V
CA
S
NANl)iJHAMiJ/M**3
/y
24o
22y
20y
175
323
132
1 44
2Dy
200
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88
ioy
2/y
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d/
205
2d/
333
|yo
42
1 /b
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400
o
3/8
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222
161
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38
3d
181
810
146
1 45
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23b
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5/1
3o5
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50
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3/
41
30/
324
330
212
304
40
IOD
iy2
221
7 ob
0
byo
Ib3
IbO
2bb
y2
332
30
4 Ob
1 1
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209
2
3
3
3
15
3
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60
23
2
2
2
2
2
2
2
2
2
47
1
82
7
2
48
22
1
3
14
4
1
25
22
8
9
9
2
6
3
3
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3
3
3
23
8
2
2
2
2
10
2
2
5
5
3
2
21
2
2
8
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3
10
4
1
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2/y/
5564
1 6yy
2051
2oy
1431
976
1241
1299
6/8
804
24/3
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343
25 /
y3
3V4
8/6
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1156
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3968
319
2686
1004
3o 1
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288
438
16yd
385
03
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167
45
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14
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30
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1 39
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21
10
38
38
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40
a
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8
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9
4
10
7
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8
9
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4
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3
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2
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3
7
4
7
2
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3
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4
1
b
4733
6920
23/8
2780
565
2324
1654
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2/66
9b3
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2216
1466
10/5
31 1
3bl
1579
18/8
1 134
2700
1608
2od
5210
609
3149
2106
0
3348
1001
262
575
1887
543
131
byy
939
2165
1671
647
59
397
497
357
424
320
386
1519
1560
160
125
406
666
395
174
606
485
52
1001
198
1 119
449
0
742
848
383
37 /
951
372
218
3313
-------
S I T t
N I A 0 A H A F k 0 tt I I b H
I COAHSb HArfriCULATb UATA
STUDY
(HAHT - I )
*****
FILTHH
bO!64
501/0
3O176
bOld2
50487
30493
30199
bO203
U
N
13
14
Ib
lo
I/
18
19
20
30211 121
30217 122
3O223 123
G 30228 124
50234 I2b
b024O I2o
30240
b02b2 128
302t>8
<;y
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M
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3
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3
3
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30
2
6
a
12
14
20
22
20
28
4
7
10
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16
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22
20
2d
TIMH
23
24
II
23
22
12
6
14
23
y
23
20
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23
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M**3
71 .d
69. /
3b.l
69.3
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34.7
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41.7
67. y
28.1
b2.y
40.4
b2.7
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b3.8
43.2
b<2.0
b2./
b3.0
tllNU
UlH SHU
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277
2b4
241
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43
08
220
247
43
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171
61
23b
243
232 .
24 /
28
2b3
1 //
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3
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3
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6
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4
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4
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12
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1
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M**3
3
12
13
13
y
22
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n
4
12
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23
14
13
12
67
42
24
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,
13
61
110
33
93
163
348
63
14
dd
18
247
68
94
lay
2/3
2db
39
yo
titi
9o
8b
63
31
263
03
348
149
(32
340
183
187
42
2oy
403
lay
42
131
22 y
»
1
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86
83
2
3
7
3
2
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2
2
2
2
2
44
21
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3y
NI
1
1
3
1
2
3
7
3
2
4
2
2
2
2
2
3
2
2
2
Ft
77
316
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389
228
423
3183
295
328
2877
421
957
9b6
897
I28b
2988
1319
1008
1514
MN
0
7
7
b
4
II
49
6
40
34
7
1.7
13
10
10
109
37
23
52
OH
0
0
0
0
0
3
0
0
0
4
0
0
O
2
2
3
2
2
2
V
3
1
7
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4
3
7
9
4
4
2
b
5
2
2
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2
7
2
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.140
1148
I4//
Ib09
593
497 1
541
1520
3/9
612
4/4
2723
1235
9O4
685
76b4
4634
I6bl
4399
S
204
699
869
589
356
846
1196
902
369
730
351
757
1369
697
909
904
501
640
655
STATISTICS
AVEHAUt
STANUAHU
20.1 461.3 209.3
19.9
lb.4 120./ 1/1.8 36.3
4.8 1164.2 26.9 2.3
4.9 1108.6 32.7 3.2
5.0 1864.0 689.3
3.3 1705.9 b73.2
-------
S I T t
NIAGARA F H O N T I H H S T U U
i CUAHSH HAKficuLATK DATA
- 2 )
F1LTI-M
it
30001
30021
30028
30030
3OO/3
30077
3OOdO
300dl
300d7
300y4
30Oyb
301 00
30ioy
3O201
M2 1 4
b0003
DOOO/
DOOI6
50022
D002d
b0034
b0040
D0046
bOOb2
bOObd
b0064
bOO/0
bOO/o
bOI3J
bOl36
DO 139
DO 144
bOI4y
bOlbd
DO lOJ
U
N
41
4y
bO
bl
68
00
01
64
6D
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66
6/
62
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82
o9
70
/J
74
/d
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//
d3
d4
8b
d/
dd
89
106
lOb
107
108
109
1 10
1 \2
M
O
N
O
7
7
7
9
d
d
d
9
10
9
9
d
9
10
9
9
y
y
10
10
10
10
10
10
1
1
1
U
A
Y
21
iy
21
2b
13
Id
22
30
1
13
7
1 1
24
23
23
17
19
20
29- .
1 1
b
/
2b
29
31
4
/
10
y
2
1 1
ID
1 /
21
J /
TlMt
HHS
b.8
7.3
6.6
7.5
23.6
1 /./
17. /
17.7
18.0
23.6
18.0
1 1.2
7.1
23. y
23.6
23.6
23.6
23.7
23.0
23.8
23.7
23.8
23.6
23.7
23. b
0.9
23.0
23. /
23.8
23.7
14.8
23.8
10.9
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23.9
FLOM
M**3
12.2
ID. 7
Ib.l
lb.2
bo.l
41 .1
39.0
43. 1
4b.3
42.8
43.4
43.7
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bO.O
bd.O
b3.2
b4.0
bl .2
bl .0
54.4
b4.l
Db.2
70.3
70.0
6/.b
19. /
60.3
6d.b
6d.6
70. 1
42.9
6d./
31 .2
71 .6
7O.9
rt I NU
OIU SPO
UhG MPH
212
193
-------
N I A O A H A FRONTIER S T U U Y
S I T hi tf I COAHSt HArtf ICULATK DATA (^AHT - 2 )
*****
FILTt-H
DO 1 04
50)70
30170
50182
501 8 /
50193
5OI99
50203.
50211
502 1 7
f}
Ir, bO^iiJ
5022d
50234
50240
50240
50252
502bd
b02o4
D027O
U
U
N
13
14
ID
10
I/
Id
19
)20
121
122
123
124
123
126
J27
I2d
129
130
131
M
0
N
1
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
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A
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30
2
6
d
12
14
20
22
26
28
4
7
10
14
10
20
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26
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23.8
24.0
1) .6
23.9
22.0
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0.7
14. 1
23.8
9.5
23.8
20.6
23.9
23.9
23.8
19.3
23.8
23.9
23.8
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M**3
VI .8
09.7
35.1
69.3
03. /
34. y
19.4
41.7
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28.1
52.9
46.4
52. /
54.2
53.8
43.2
52.0
52.7
53.0
» I NU
OIH SfO
UHU MHli
27 /
254
241
251
43
08
220
24 /
43
220
17 1
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243
232.
24 /
28
253
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9
IO
3
13
3
4
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6
1 1
4
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4
13
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12
)
2
13
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SI
447
1168
Ib24
1597
2028
3447
5/82
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II 72
3/0
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2bOd
2062
250)
14356
1 IDIO
39b4
.7406
AL
142
147
292
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430
1022
I28d
24b
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365
193
2IJ3
194
189
190
3lol
1049
764
1469
F
0
0
0
0
0
0
0
0
0
0
0
0
75
0
0
0
0
0
0
NO
3
83
86
513
23O
109
374
719
263
0
748
56
366
455
221
930
6/1
827
151
207
CL
III
9/5
0
158
957
144
0
287
0
0
113
64
113
0
013
)342
481
4/4
1319
SO
4
30o
1392
1369
1052
486
1153
2827
1725
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-------
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-------
S I f h
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-------
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1 119
1220
1017
980
1336
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92
2/b
9d
29b
624
723
299
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bib
J068
2113
2263
1 9bl
486
1116
240
313
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90
69
83
33
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40
27
39
27
38
31
33
40
27
139
2b
9
0
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2
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20
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47
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2
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0
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b
7
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3
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o
N I A J A H A H H O N T I b H
S I f b if 3 COAHSb ^AKriCULAfb UATA
T U U Y
(J^AHT - I )
RLTbrt
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b0097
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bOlO3
bO 1 07
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bOl 14
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bOI22
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bOI34
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bOI4b
50 IbO
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bOI72
bOJ 78
b01d4
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12
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AVbKAJb
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Id.9 119.6 177.3 8.O
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2.4
4.0 1861.2 545.0
3.4 I6U.3 406.2
-------
*****
N I A 0 A
SITE # 3 OMHSH
A H H O N T I t H S f, U U Y
HAKTICULAfd DATA (fAHT - 2 )
*.****
F I LTtH
#
30003
30009
30024
30032
30038
300b3
300bb
300b9
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-------
SITE
-N I A U A H A H » O N T I t H STUDY
3 CDAHiit HAHTICJLATt UATA (PAHT - 2 )
HILTEH
ff
booyv
booyy
30403
30J 07
bOI 10
301 14
301 18
30122
30123
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2a
TIME
MS
23.7
23.6
23.7
23.6
23.7
23.7
23.6
23.7
23.7
23.7
23.7
23.7
20.6
15.3
23.8
24.0
24.0
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24.0
22.9
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103
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209
307
322
229
221
288
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244
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630
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3/62.8 002.8 04.2 642.9 662.8 650.1 83.5 233.7
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76.4
-------
N I A (J A K A H H 0 N T I h H
b I I t tt 4 COAKSH HArfTlCULATb UATA
STUDY
(HAI2T - I )
*****
FILTtH H
U
it i4
3OOO4 4O
30010 41
30023 49
30039 b 1
30044 OO
300b6 34
300b/ 33
30O6I 38
30070 by
30084 64
300yO 03
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30101 61
30106 o2
301 1 / 61
30124 80
30204 72
30223 08
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b002b /4
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30048 83
30033 84
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24.0
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20.8
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-------
b I 1' t
c^
N 1 A U A K A H H I) N T I H H S f U L) Y
4 COAHbH HArfllCULATh DATA (PAKT - 2 )
HILThH
J0004
JOOIO
3002D
joojy
J0044
JOObo
JOOb/
JOOOl
300/6
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30097
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JOI24
30204
30223
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DOOIO
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b002b
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1197
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442
330
194
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91
382
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221
109
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292
232
216
120
81
713
2b2
214
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79
264
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160
3/2
146
88
119
39
b/
0
0
11
39
36
241
19
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411
82
79
18
2lb3
313
b4
820
SO
4
6b8
2b2
2043
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405
2b48
1037
1000
2190
898
13/3
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3261
1232
205
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19
21 1
1251
427
253
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426
1579
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13/3
170
0
756
620
2264
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2
MS/M**3
0
0
1393
0
20
101
56
785
0
0
0
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681
372
0
0
178
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0
0
0
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0
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0
0
0
0
0
0
0
NA
219
337
191
161
81
I32b
308
214
226
79
132
I9b
120
186
88
b8
59
58
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58
0
39
54
120
19
136
63
103
79
56
2558
55
127
164
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4
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0
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41
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4
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40
186
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253
41
39
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92
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73
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40
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59
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60
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0
252
408
120
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168
142
226
105
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100
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126
20
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92
0
229
-------
n
*****
S I T t
NIAGARA F Hi) N I I b H STUDY
# 4 COAHSh ^ArtfieULATt DATA < ^AUT - 2 )
*****
FILTtiH
tf
50104
3OI 1 I
bOI Ib
boi iy
30124
bOI30
3O14I
bOI46
bOlbl
bOlb6
bOI6l
bO.I 67
30 1 73
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D02O2
30208
b02l4
30220
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b0243
3024V
b02bb
3O2oJ
3020 /
b02/3
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0
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yy
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102
103
100
IO/
108
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10
12
13
14
16
17
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121
122
123
124
123
126
127
128
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130
131
M
o
N
12
12
12
12
12
2
2
2
2
2
2
2
2
3
3
3
3
3
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10
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22
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17
21
21
30
2
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12
14
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22
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28
4
7
10
14
10
20
22
20
28
TIMt
HHS
24.0
24.0
20.8
24.0
24.0
24.0
12. y
24.0
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22.3
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24.1
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24.1
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24.1
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37
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307
22y
22.1
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243
244
336
237
277
2b4
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43
68
220
247
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220
171
61
233
243
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4
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1
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404b
2382
3600
2623
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1836
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2bb6
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86b
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3972
2b/2
1429
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4b4
3lb
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2474
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-------
*****
FILTER
a
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1197
1383
343
543
229
734
1394
-------
o
SITE
N I A U A U A F H O N T I fci K
it 5 COARSE HAHTICULATE DATA
S f U U
.*****
FILTEH
50108
501 12
50 No
50120
SOI27
50132
5OI37
50142
50147
50152
5OJ55
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50168
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50244
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50250
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101
102
104
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121
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129
130
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12
12
12
12
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15
17
21
27
30
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0
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12
14
20
22
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4
7
10
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16
20
22
20
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TIME
HHS
24.1
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24.1
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221
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243
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277
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241
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232
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2
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3
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4328
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2
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3
3
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2
6
2
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2002
2025
3030
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841
1283
1429
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3222
830
690
5531
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3505
761
870
3420
4009
194
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876
3848
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5566
6638
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688
897
853
365
370
710
720
342
1069
661
374
1699
141
612
862
1 163
437
493
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173
, 894
275
463
386
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1130
627
1507
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20.7 II9./ 200.4 22.0
20.2 /l.d 20/.d 29.0
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4.3 30d6.2 509.6
-------
*****
S I 1' t
N I A U A H A H H 0 rt f I h H S f U U Y
«f b COAHSt HAHTICULATH DATA (HART - 2 )
*****
HILTttf
JOOOb
JOOI 1
J0020
J0040
JOObO
J0054
J0062
J0074
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JOOdb
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30011
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500b6
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5O068
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56
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141
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243
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299
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299
76
281
224
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193
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121
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349
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102
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260
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108
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2136
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4 2
dANOUHAMS/M**3
823
1149
2745
504
1313
IO29
2114
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733
571
1571
1367
3716
4653
1065
181
235
71
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649
1349
488
202
333
1143
514
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424
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91
221
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127
40
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283
103
115
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54
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52
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37
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N I A U A K A F H O N T I b K
Sift H 6 COAHSb HAHTlCULATb DATA
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(HAHT - I )
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-------
W I A G A K A r H 0 H T I t H STUDY
S I T t if 6 COAHSb HArtTlCULATb DATA (PAHT - 2 )
*****
FILTtK
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0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
39
0
40
0
40
OO
59
24
38
0
0
0
mi)
3
0
1059
523
192
II 08
91 1
.IOU5
1202
557
138
I2d3
831
1022
19 1
6/4
141
104
61
181
80
463
1 /8
2/9
199
300
220
39
820
24/9
118
780
133
18
b6
132
CL
286
40
0
0
75
0
39
1 14
146
110
100
101
2y
218
80
60
0
20
20
40
20
0
0
59
20
120
0
80
2/2
|3B
/3
19
0
0
151
SO NO
4 2
NANOURAMS/M**3
764
1518
7b6
604
980
696
1241
744
3dl
332
b34
3001
2249
382
1025
161
144
20
221
202
2 195
J36
259
259
420
440
256
580
1209
336
4d/
133
261
301
341
764
574
232
2/4
0
0
0
0
264
0
0
O
1 16
0
0
0
0
82
0
0
0
0
0
0
0
0
0
0
0
0
0
5/
0
0
0
NA
669
0
58
82
150
80
147
143
176
83
106
101
58
109
53
40
41
41
40
20
120
98
59
19
20
80
0
20
60
19
24
38
149
169
416
4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
J
0
0
0
0
0
0
0
0
0
0
0
Nri
4
0
553
87
21
0
26
118
0
29
0
0
790
496
0
26
0
0
0
0
0
0
39
59
0
0
0
0
0
0
0
24
3d
0
0
0
dH-S
0
0
0
0
0
0
0
0
0
0
0
0
0
82
0
0
20
20
20
20
0
0
0
0
0
0
0
0
0
158
0
0
0
0
0
K.
286
90
58
54
37
26
59
57
58
55
53
40
87
136
53
40
0
0
20
0
0
0
0
0
0
20
0
0
0
0
0
0
0
0
0
-------
*****
N I A U A H A H H 0 N f I h H S T U U Y
S 1 T b # O COAKSb CAitflCULATb UATA (HAHT - I )
*****
FILTbH
f
5009d
bO 102
bOI06
boioy
bOI 13
30 1 1 7
30121
30126
bO12d
30138
bOI4d
bOlb3
bOlb4
30.1 by
bOI6V
301/3
bOldl
DO 106
3OI92
30l9d
b0204
30210
3O2 16
b0222
30227
30233
30239
3O243
30231
302b7
3O263
50269
b02/b
H
U
N
96
93
97
90
99
101
102
103
104
IO/
lOd
109
IO
12
13
14
Ib
16
17
Id
19
120
121
122
123
124
I2b
126
127
120
129
130
131
M
O
N
12
II
12
.12
12
12
12
12
12
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
0
A
Y
4
JO
o
10
12
16
19
22
20
II
Ib
17
21
21
30
2
6
d
12
14
20
22
26
28
4
/
10
14
16
20
22
26
20
TIMb
HHS
24.1
23. d
23. d
24.0
23. d
23. d
23. d
23. d
24.0
24.0
24.0
24.0
24.0
23. d
23. d
23.9
20.1
23.9
21.2
23. d
16.6
23.2
23.9
21.1
23. d
23.9
23.9
23.9
23.9
.23.b
23.8
23. 9
23.8
FLOrt
M**3
31.7
b3.6
bl 17
bO.8
b4.2
b3.b
b2.4
b3.2
34. b
b3.2
b2.b
32.6
32.9
b3.O
b3.7
D4.0
44.8
b3.0
46. d
b2.6
36.7
bl.b
32.6
4b.6
bl.O
bl.d
bO .3
bl.b
bl.b
49.4
bO.I
bO.6
bl .0
rtli
OIK
ubo
43
do
7b
103 ..
37
2oy
307
22V
322
190
243
244
336
23 /
211
2b4
241
2bl
43
od
220
247
43
22O
I/I
61
233
243
. 232
247
2d
2b3
1 //
ID
SHU
MHri
1 /
9
6
12
9
10
3
12
4
1
14
6
4
o
9
10
3
13
3
4
6
6
II
4
13
4
13
Ib
12
1
2
13
7
bl
load
1283
2641
2167
2136
194
6/87
2203
J449
34 /
2219
1678
196
I9b
193
1082
1161
* 19b
1 /36
639
1882
dbb
991
4018
201
bOOl
1490
1178
3278
7007
9089
2698
2/40
AL
438
643
447
201
803
191
b49
bOO
188
326
193
194
193
193
190
bOD
228
433
807
194
2/9
199
194
b46
198
319
421
33!
686
1208
1206
b!4
43 /
F
0
0
0
.19
36
Id
19
0
O
0
yb
0
o
o
0
0
o
0
1O6
0
dl
0
b6
0
0
0
o
0
bd
0
0
by
0
NO
3
iy
bb
306
0
2bd
37
8b8
202
3b
94
361
228
Yb
37
Id
37
446
94
213
28b
1007
Ibb
36
613
19
40b
/9
38
b44
44 b
b99
O
98
CL
0
0
0
0
0
0
24 d
0
Id
0
9b
0
37
bO
0
0
2o 7
b6
.234
37
O
0
0
Ib3
0
19
0
0
136
dO
139
0
117
SO NO
4 2
NANOUKAMS/M**3
231
290
3O9
7d
461
id
43d
33d
2/b
112
323
532
302
432
204
314
537
339
40b
323
I22b
1127
433
633
309
b9d
636
300
272
304
3b9
632
313
0
0
O
0
0
0
0
0
0
0
0
0
O
O
O
O
0
0
0
0
0
0
0
o
0
0
0
0
o
0
o
o
0
NA
232
V3
96
137
92
74
20V
112
2V3
22b
361
266
109
IbO
0
bb
22
433
149
19
0
136
0
IV7
0
lib
39
bd
97
80
279
0
7d
4
0
0
0
0
0
O
0
0
103
O
0
0
O
0
O
0
0
0
0
0
0
0
0
0
0
0
0
0
174
O
0
0
0
Hri
4
0
0
3d
39
36
0
0
0
0
75
3d
0
0
75
74
0
0
0
.1089
O
0
Ibb
0
ob
19
lib
0
3d
3d
40
b9
79
0
8H-S
0
0
0
0
0
0
0
0
36
0
0
0
0
O
0
0
0
0
0
0
0
19
0
0
0
0
0
0
Ibb
0
0
0
0
K
0
37
0
0
0
0
0
0
0
0
0
0
0
56
III
0
0
0
0
0
o
77
0
d7
19
0
0
58
3d
0
. 0
0
0
AVbHAUb 33by.2 661.D 17.2 3/*>.2 61.6 bbl.O 34.7 114.3
b.2 6b.l
3 f
r i c s
7.a 25.2
SfANUAHU 2728.1
Ub VI ATI 014
bbd.b 2d.l 437.2 77.d b2I.V 123.4 I Id.I 30.4 I8O./ 2d.6 45.6
-------
APPENDIX D
The following tabulated information represents the entire Whatman-41
hi-vol data base which was produced within the project. Revelant data is
presented here regarding the date, particulate mass, air volume sampled (flow),
and SP concentration.
D-l
-------
ITE
NO.
1
2
3
4
5
2
1
3
6
5
4
6
6
5
3
2
1
4
6
3
1
2
3
5
4
6
FILTER
NO .
10001
10002
10003
10004
10005
10009
10010
10011
10012
10013
10014
10006
10015
10016
10017
10018
10019
10020
10021
10022
10109
10110
10111
10112
10113
10114
DflTE
JJ
3-
.-,
Zf
3-
3-
3-
"!_
o
o~
"[
o
3-
3-
3-
o
3-
3-
3-
3-
*V
_<
J.
4-
14-
14-
14-
14-
14-
16-
X f"' ~
1 C1 ~"
16-
16-
16-
14-
21-
21-
21-
21-
21-
21-
Ll -'
'"' '"j
29-
29-
4-29-
4-
4-
4-
29
29-
29-
78
78
78
73
f' O
70
i O
I1' l~l
78
78
78
~? i"i
1 >.'
78
-n ,-.
r o
-ji-i
r u
78
73
i'1 y
~7 |-(
r C"
78
78
73
78
78
78
78
73
1
1
1
1
1
2
2
1
2
1
1
1
2
1
1
2
2
1
1
2
3
-'
3
TSP
62.
52.
35.
89.
37.
16.
16.
84.
95.
12.
65.
25.
22.
25.
95.
8 3 .
30 .
50.
04.
96.
55.
19.
05.
60.
403.
2
D2
1 8 .
6
jit
6
4
d
9
4
1
0
5
5
1
6
5
8
9
I-!
9
0
3
4
1
C'
3
4
0
FLOW
-------
;ITE
NO.
2
1
4
5
6
3
5
4
2
5
3
1
2
2
5
4
1
3
2
5
4
1
2
3
5
4
1
FILTER
NO.
10023
10024
10027
10028
10029
10030
10031
10033
10034
10036
10037
10038
10039
10040
10041
10042
10043
10044
10045
10046
10048
10049
10050
10051
10052
10053
10064
HfiTE
3-23-78-
3-23-73
3-23-78
3-23-78
3-28-78
3-30-78
3-23-78
3-30-78
3-28-78
3-30-78
4 -1-7S
3-30-78
3-30-78
4 -1-78
4 -1-78
4 -1-78
4 -4-78
4 -4-78
4 -4-73
4 -4-78
4 -4-78
4 -6-78
4 -6-78
4 -6-78
4 -6-78
4 -6-78
4 -1-78
TSP
CMC)
179. 1
297.6
271.5
279.5
130.3
226.0
370.0
349. 1
190.1
389.5
172. 1
222.4
196.2
218.6
249.1
242.5
283.1
231.8
243.0
276.5
304.1
233. 1
165. 7
156. 6
125.2
100.3
224.9
FLOW
CMS)
2284.0
2458.5
2559.1
2370.9
2448.3
2414.7
2343.2
2404.9
2396.5
2161.7
2212.2
2251.0
2255. 1
2005.5
2262.4
2174.4
2161.2
2012.6
1808.4
2162.9
2016.8
2189.7
2111.3
1853.2
2474.4
611.6
2338.7
CONC.
(UG/M3)
78
121
106
118
53
94
158
145
79
180
78
99
87
199
110
112
131
115
134
128
151
106
78
84
51
164
96
D3
-------
ITE
NO.
6
6
4
6
5
iL.
o
1
6
cr
2
-,
1
4
'*'
li'
3
.^i
5
5
6
6
4
4
1
1
FI
LTER
NO.
10035
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0047
0054
0055
0056
0057
0053
0059
0060
0061
0062
0063
0065
0066
0067
006S
0069
0070
0071
0072
0073
0074
0075
0076
0077
0078
DflTE.
4
4
4
4
4
4
4
4
4-
4-
4-
4-
4-
4-
4-
4-
4-
4-
4-
4.-
4-
4-
4-
4-
4-
4-
-6-
-4-
,-i
'..>
y
o
'I'
o __
-8-
11-
11-
11-
11-
11-
11-
13-
15-
13-
15-
13-
15-
13-
15-
13-
15-
13-
15-
78
78
78
78
78
78
73
78
78
78
f'-Q
73
78
78
78
7b'
78
78
78
7'8
78
78
78
78
78
78
TSP
(MG)
90.
198.
200.
97.
310.
237.
173.
145.
130.
279.
226 .
291.
265.
352.
248.
183.
307.
185.
380.
300.
150.
76.
314.
'': 9 ti .
221.
169.
6
6
3
9
1
4
4
0
-i
6
5
2
f
9
6
1
6
i
(
si1
8
r'
o
6
Q
0
g
FLOW
ai3>
2434.
2374.
2083.
2463.
2241.
2110.
2181.
2425.
2514.
2162.
2108.
2112.
1958.
2024.
2109.
2072.
2011.
2183.
2217.
2087.
2356.
1753.
1920.
1986.
O "' ~? '"'
i u_ I' O .
2389.
1
8
5
1
6
0
7
9
~i
£
o
"I"
9
1
8
6
5
5
t'
1
J
y
2'
9
4
9
^i
CONC.
(UG/M3)
1
1
1
1
1
1
1
1
1
1
1
1
1
37
84
96
40
38
13
79
60
52
29
07
o o
36
74
18
91
53
85
^~i
r iL.
44
64
44
64
97
97
71
D4
-------
ITE
NO.
1
2
3
5
4
6
4
6
5
3
2
1
4
1
6
2
3
2
1
2
3
6
5
4
1
2
FILTER
NO.
10979
10080
10081
10082
10083
10084
10085
10086
10087
10088
* 10089
10090
10091
10092
10093
10094
10095
10096
10097
10098
10099
10100
10101
10102
10103
10104
DfiTE
4-18-78
4-18-78
4-18-78
4-18-78
4-18-78
4-18-78
4-20-78
4-20-78
4-20-78
4-29-78
4-28-78
4-20-78
4-22-78
4-22-78
4-22-78
4-22-78
4-22-78
4-22-78
4-25-78
4-25-78
4-25-78
4-25-78
4-25-78
4-25-78
4-27-78
4-27-78
TSP
CMC)
298.4
190. 1
172.9
181.9
238.7
137.4
182.5
87.9
189.4
109.5
126.8
106.0
333.9
167.6
121.5
409.0
176.5
187.6
258.2
232.4
186.9
185.7
189.6
286.7
258.6
249.2
FLOW
2160.3
2108.8
2145.8
2374.9
2051.4
2353.0
2302.5
2604.9
2399.2
2314. 1
2072.0
2483.9
1987. 1
2273.3
2518.6
2050.7
2079.1
1863.0
2133.7
2075.1
2150.2
2137.5
2295.2
2177. 1
1930.2
1936.3
COHC.
(UG/M3)
138
90
81
77
116
58
79
34
79
47
61
43
168
74
48
199
85
101
121
112
87
87
83
95
134
129
D5
-------
SITE
HO.
1
2
3
5
4
4
3
2
1
4
5
1
2
3
6
3
2
1
6
5
4
3
2
1
6
5
FILTER
HO.
18115
10116
10117
10119
10120
10121
10122
10123
10124
10125
10126
10127
18128
10129
10139
10131
10132
10133
10134
10135
10136
10137
10138
10139
10140
10141
DflTE
5 -6-78
5 -6-78
5 -6-78
5 -6-78
5 -6-78
5 -9-78
5 -9-78
5 -9-78
5 -9-78
5 -4-78
5 -4-78
5 -4-78
5 -4-78
5 -4-78
5 -4-78
5-13-78
5-13-78
5-13-78
5-11-78
5-11-78
5-11-78
5-11-78
5-11-78
5-11-73
5 -9-78
5 -9-78
TSP
(MG>
343.2
205.9
261.6
604. 1
467.8
352.4
217.8
224.5
255. 1
196.3
239.4
319.3
219.7
171.9
230.4
155.0
144.2
172.1
105.7
188.9
234.7
226.9
235.9
236.7
65.2
202.3
D6
FLOW
2553.4
2379.9
2179.7
2429.0
2118.8
1998.1
2090.5
2157. 1
2137.0
2092.0
3539.0
2252. 1
2155.4
2032.6
2194.8
2295.0
2338. 1
2485.8
2359.S
2342.8
1972.7
2044.6
2066.0
2199.0
2372. 1
2316.5
CONC.
134
87
120
249
221
176
104
104
119
94
68
142
98
85
105
68
62
69
45
81
119
111
114
108
27
87
-------
;ITE
NO.
4
6
i
2
5
1
2
3
5
6
4
1.
2
3
5
6
4
1
2
3
6
5
1
2
3
FILTER
NO.
10146
18147
18148
19149
10150
10151
10152
10153
10154
10155
10156
10157
10158
10159
10160
10161
10162
10163
10164
10165
10166
10167
10169
10170
10171
10172
BfiTE
5-13-78
5-13-78
5-16-78
5-16-78
5-16-78
5-18-78
5-18-78
5-18-78
5-18-78
5-18-78
5-18-7-8
5-28-78
5-20-78
5-20-78
5-20-78
5-20-78
5-20-78
5-23-78
5-23-78
5-23-78
5-23-78
5-23-78
5-25-78
5-25-78
5-25-78
5-25-78
TSP
(MG)
152.6
113.6
147.8
152.9
136.6
450.2
275.6
312.6
653.2
116.4
407. 1
268.4
262.9
268.8
423.0
177.8
483.5
219.3
212.1
167.6
155.8
290.7
411.5
3 19.2
363.5
210.4
FLOW
-------
ITE
NO.
3
6
5
4
1
O
u.
~j
6
5
4
1
'~'
5
4
2
6
5
3
1
6
1
-i
-'
5
1
'd
FILTER
HO .
191
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
101
102
102
102
102
l'' f
-Jl-l
f >J
79
30
82
l-l '"I
Q'i
34
35
86
87
y y
89
90
91
92
93
94
96
97
98
99
00
01
14
15
5
DflTE
-30-
5-30-
5
5
6
6
6
6
6
6
6
b
6
b
6
b
6
6
6
-30-
-30-
-1-
-1-
-1-
-1-
1
-1-
-b-
.-i
u
"~* b
-6-
-10-
£, _
y
-8-
-8-
6-10-
6
6
6
6
6
-10-
-10-
-10-
-21-
-21-
73
78
78
"7O
i '-<
73
78
78
78
78
78
78
78
78
78
78
78
7y
73
73
78
78
T"n
i '_'
78
78
78
TSP
(MG)
.-, .-, .-,
fcl O -'
214.
393.
315.
193.
220.
190.
137.
316.
273.
179.
184.
276.
453.
217.
82.
321.
259.
189.
70.
112.
114.
157.
166.
144.
9
6
"7
f
5
6
6
9
5
1
6
5
5
4
9
7
y
6
9
7
3
kZ.
4
o
9
4
FLOW
2121.
2323.
2152.
1399.
2220.
2003.
2063.
2361.
2206.
1386.
2285.
2256.
o o o o
L_ ,_ i_l '-' .
4033.
1842.
2157.
2219.
2122.
2389.
2071.
2131.
~\ '-I |-j Ti
ii o y o .
o o o -
u. _' i_ L. .
2261.
2179.
Q
4
6
y
6
0
1
6
9
6
6
I*
4
-,
f
2
i'*
1
1
0
6
6
J
0
2
COHC.
(UG/M3)
1
10
92
183
1
1
1
1
1
1
1
1
1
66
89
10
93
58
43
45
79
82
21
14
18
38
45
'~'^'
79
34
53
50
63
74
66
D8
-------
ITE
NO.
6
6
6
3
3
2
2
4
5
3
2
1 '
3
e
5
4
5
6
3
2
1
5
6
3
2
1
FILTER
NO.
10292
10203
10204
10205
10206
10207
10208
10209
10210
10211
10212
10213
10216
10217
10218
10219
10220
10221
10222
10223
10224
10225
10226
10227
10228
10229
DflTE
6-25-78
6-27-78
6-29-78
6-27-78
6-29-78
6-27-78
6-29-78
6-25-78
6-25-78
6-25-78
6-25-78
6-25-78
6-21-78
6-21-78
6-21-78
6-21-78
6-19-78
6-19-78
6-19-78
6"- 19-78
6-19-78
6-15-78
6-15-78
6-15-78
6-15-78'
6-15-78
TSP
2150.6
2307.7
2304.0
2062.8
2107.3
2193.2
2267.4
2125.4
2166.7
2183.4
2114.7
2148.4
2179.7
2294.0
2178.9
2089.0
2180.8
2112.2
2046.3
2140.4
2299.9
2234.3
2024.4
2012.8
1974.4
2172.6
CONC.
(UG/M3)
76
74
68
154
138
162
127
124
115
87
92
97
85
47
133
121
98
36
74
69
57
68
17
56
62
44
D9
-------
ITE
NO.
3
6
2
1
1
1
5
5
5
4
4
4
1
2
3
6
5
4
1
2
3
6
5
4
1
2
FILTER
NO.
10235
10236
10237
10238
10239
10240
10241
10242
10243
10244
10245
10246
.10247
10248
10249
10250
10251
10252
10253
10254
10255
10256
10257
10259
10260
10261
DflTE
7 -1-78
7 -1-78
7 -1-78
6-27-78
6-29-78
7 -1-78
6-27-78
6-29-78
7 -1-78
6-27-78
6-29-7-8
7 -1-78
7 -7-78
7 -7-78
7 -7-78
7 -7-78
7 -7-78
7 -7-78
7-11-78
F-ll-78
7-11-78
7-11-78
7-11-78
7-13-78
7-13-78
7-13-78
TSP
115.6
112.6
119.5
302.8
272.5
130.7
453.2
399.9
140.3
505.1
389.1
161.4
262.4
338.9
264.0
212.3
369.1
344.1
176.9
207.3
184.3
130.8
245.7
333.9
265.8
202.6
D10
FLOW
2212.9
2241.5
2204. 1
2123.3
2231.5
2260.6
2081.4
2166.7
2262.3
2131.4
2029.7
2212.5
2197.8
2166.2
2222.6
2278.6
2163.7
2098.7
2332.7
2113.0
2138.1
2339 . 3
2402.5
2115.6
2193.5
2217.3
CONC
-------
ITE
NO.
2
3
5
6
4
6
5
2
4
3
1
3-
6
2
4
1
5
4
5
6
3
2
1
4
5
1
FILTER
NO.
10266
1Q267
10268
10269
10270
10271
10272
10273
10274
10275
10276
10277
10278
10279
10280
10281
10282
10283
10284
10285
10286
10287
10288
10289
10290
10294
DflTE
7-15-78
7-15-78
7-15-78
7-15-78
7-15-78
7-19-78
7-19-78
7-19-78
7-19-78
7-19-78
7-19-78
7-25-78
7-21-78
7-21-78
7-21-78
7-21-78
7-21-78
7 -4-78
7 -4-78
? -4-78
7 -4-78
7 -4-78
7 -4-78
6 -3-78
6 -3-78
6 -3-78
TSP
(MG>
249.9
236.2
314.5
187.3
344.6
196.6
297.4
241.2
335.8
230.8
247.2
181.9
296.3
369.7
409.8
323.3
362.4
96.4
88.6
81.3
124.7
113.4
115.8
150.7
203.8
150.5
Dll
FLOW
2086.1
2091.2
2093.7
2513.9
2113.6
2058.9
1990.5
2112.7
1965.7
2029.8
1947.9
2137.5
2261.9
2165.8
2085.9
2106.6
2122.0
2460.2
2521.3
2390. 1
2108.9
2339.3
2539.9
2013.3
2296.4
2357.3
CONC.
(UG/M3>
120
113
150
74
163
95
149
114
171
114
127
85
91
171
196
153
171
39
35
34
59
48
46
75
89
64
-------
;ITE
NO.
6
4
5
3
1
6
6
1
5
6
5
4
3
5
1
6
1
3
1
3
4
5
6
1
3
4
FILTER
NO.
18309
19302
10303
10304
10305
1030
1030
1030
1031
1031
1031
1031
1031
1031
1031
1031
1032
1032
1032
1032
1932
1032
1032
1032
1032
1032
£1
T1
r
o
0
2
-!
4
5
ti
7
g
0
1
O
3
4
5
b
r
y
q
r "~
-?
t
r ~~
^
i'
^<
i
r ~~
r' ~
r "~
r' ~
y
o
3
ft
o
G
8
o
3
1-1
o
8
S"
8-
,-,
i~t
'_>
o
p _
8-
DflTE
25-78
27-78
27-73
31-78
£ i1'
27-
31-
31-
31-
-2-
-2-
-2-
. O -.
-6-
~" u. ~"
6~
-6-
-6-
-8-
-8-
10-
-Fl-
i-i
o~
10-
10-
12-
31
78
"7 i"i
r o
78
78
78
\ d
r' o
78
78
78
i'' O
78
78
78
78
78
78
78
78
78
r' o
TSP
(MG>
119. 8
207.2
23 1.7
110.6
139.
96.
73.
130.
154.
169.
224.
235.
204.
2 1 3 .
239.
157.
165.
171.
290.
3 1 3 .
1 8 1 .
313.
156.
156.
146.
258.
2
4
9
4
4
-'
1
4
O
4
(''
C.
-)
5
y
8
-I
4
1
6
4
0
FLOW
2057.0
1706.7
2137.4
2270. 1
2224.
2187.
2262.
2290.
2337.
2316.
2233.
2072.
2471.'
2414.
2388.
2436.
2414.
2459.
O '"' ] '"'
2324.
2292.
2313.
2505.
2293.
2267.
2372.
5
g
-n
l'
6
2
p
Q
6
y
0
1
£
9
5
8
y
6
-I
0
0
i'
5
COHC.
(UG/N3)
53
121
132
49
1
1
1
1
1
1
1
85
44
33
57
66
73
00
14
83'
90
00
64
68
70
26
35
79
38
62
68
65
09
D12
-------
ITE
NO.
1.
5
6
3
4
5
6
3
1
4
5
6.
2
4
3
1
2
5
6
2
1
4
5
3
6
5
FILTER
HO.
10334
10335
19336
10337
10338
10339
10340
10341
10342
10343
10344
10345
10346
10347
10348
10349
10350
10351
10352
10353
10354
10355
10356
10357
10358
10359
DflTE
8-15-78
3-12-78
8-12-78
8-15-78
8-15-78
8-15-78
8-15-78
8-18-78
8-18-78
8-18-78
8-18-7-8
8-18-78
8-18-78
8-22-78
8-22-78
8~ _ "' '< _ "7 O
i_i- i O
8-22-78
8-22-78
8-22-78
8-24-78
8-24-78
8-24-78
8-24-78
8-24-78
8-24-78
8-26-78
TSP
CMC)
211.3
276.6
120.7
198.9
187.8
233.5
145.9
136.5
180.2
184.5
190.6
97. 1
161.8
214.2
153.0
172.9
163.7
215.1
128.3
400.6
320.6
447.4
310.0
307.8
162.8
95.9
FLOW
2226.3
2351.5
2451.5
2228.5
1412.5
4382.3
2447.2
2394.9
2344.5
2304.7
2304.9
2458.5
2325.2
2256.9
2432.2
2377.3
2362.5
2351.5
2417.7
2385.3
2367.7
2227.8
2427.9
2241. 1
1464.3
2501.0
COHC.
(UG/M3)
95
118
49
89
133
53
60
57
77
80
83
39
70
95
63
73
₯69
91
53
168
135
201
128
137
111
38
D13
-------
ITE
NO.
6
1
2
3
4
5
6
1
2
4
5
6
3
5
1
2
4
6
5
4
3
2
1
FILTER
NO.
18364
18365
18366
18367
18368
18369
18378
18371
18372
18374
18375
18376
18389
18391
18392
18393
18394
18395
18396
18397
10398
10399
10408
DRTE
,-, .-, .- -^ ,-,
C* ~ £ t1 ~" i' O
3-38-78
8-30-78
8-38-78
8-38-78
8-30-78
8-38-78
9 -1-78
9 -1-78
9 -1-78
9 -1-73
9 -1-78
9-17-78
9-17-78
9-17-78
9-17-78
9-17-78
9-19-78
9-19-78
9-19-78
9-19-78
9-19-78
9-19-73
TSP
58.8
73. 1
87.8
53.5
86. 4
87.2
2.8
187.2
93. 1
1 O !*' 0 O
146.0
42.4
10.5
56.3
17.2
46. 8
33. 8
75.8
54.6
34.2
26. 8
89.4
63.8
FLOW
-------
ITE
HO.
1
1
2
2
3
4
4
5
5
6
1 .
1
2
2
3
3
4
4
5
5
6
6
1
2
FILTER
HO.
10401
10402
10403
10404
10405
10407
10408
10409
10410
10411
10413
10414
10415
10416
10417
10418
10419
10420
10421
10422
10423
10424
10425
10426
DflTE
9-21-78
9-23-78
9-21-78
9-23-78
9-21-78
9-21-78
9-23-78
9-21-78
9-23-78
9-21-78
9-26-78
9-29-78
9-26-78
9-29-78
9-26-78
9-29-78
9-26-78
9-29-78
9.-26-7S
9-29-78
9-26-78
9-29-78
10 -3-78
10 -3-78
TSP
(MG)
204.5
0.9
194. 1
13.1
177.0
313.2
6. 9
245.0
6. 1
91.6
52.6
61.4
123.9
126. 1
87.0
110.0
122.8
139.3
120.7
112.0
59.5
94.4
154.3
140.0
FLOW
CM3>
2307.9
2400.6
2397.0
2535.1
2343.0
2100.8
2307.6
2383.4
2565. 1
2510.6
2179.3
2227.9
2313.4
2226.8
2200.1
2301.7
2036.9
2048.4
2322.9
2493.7
2367.1
2390. 1
2212.5
2314.6
CONC.
(UG/M3)
89
0
81
5
76
151
3
103
2
36
24
28
54
57
40
48
60
68
52
45
25
39
70
60
D15
-------
;ITE FILTER
NO.
2
2
3
3
3
4
4
c-
J
5
5
6
6
6
2
3
6
5
4
2
3
6
5
4
2
O
5
NO.
10455
10456
10453
10459
10460
10461
10462
10463
10464
10465
10466
10467
10463
10470
10471
10472
10473
10474
10476
10477
10473
10479
10480
10482
10433
10435
IiflTE
12-12-73
12-14-73
12-12-78
12-14-78
12-16-78
12-14-73
12-16-78
12-12-73
12-14-73
12-16-78
12-12-78
12-14-78
12-16-78
12-19-73
12-19-78
12-19-78
12-19-78
12-19-78
12-22-78
12-22-78
12-22-78
12-22-73
12-22-78
12-23-78
12-23-78
12-23-78
T3P
-------
ITE
NO.
5
4
3
2
1
6
3
4
5
6
2
1
3
4
5
6
6
1
2
4
3
5
1
2
3
5
FILTER
HO.
19489
10498
10491
16492
10493
10494
10495
10496
10497
10498
10499
10500
10427
10428
10429
10430
10431
10432
10433
10434
10435
10436
10437
10438
10439
10440
DRTE
10-17-78
10-17-78
10-17-78
10-17-78
10-17-78
10-17-78
9-11-78
9-11-78
9-11-78
9-11-78
9-11-78
9-11-78
10 -3-78
10 -3-78
10 -3-78
10 -3-78
10 -5-78
10 -5-78
10 -5-78
1& -5-78
10 -5-78
10 -5-78
10 -7-78
10 -7-78
10 -7-78
10 -7-78
TSP
(MG)
82.8
117. 1
118.7
118.1
121.7
55. 1
342.7
438.6
271.0
203.9
134.6
332.0
125. 1
146.2
133.5
107.2
82.9
153.9
138.1
145.5
118.4
727.2
61.0
137.0
67. 1
131.0
D17
FLOW
-------
ITE
NO.
3
5
4
6
1
2
3
5
6
.I1
4
5
6
1
2
-.,
6
5
4
1
1
4
£
6
3
5
FI
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
LTER
NO .
0445
0446
0447
0448
0449
0450
0451
0452
0453
0501
0502
0503
0 5 0 4
0601
0602
0603
0604
0605
10606
1
1
1
1
1
1
1
0607
0603
0609
0610
0611
0612
0613
DflTE
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0-1
0-1
0-1
0-1
0-1
0-1
0-1
0-1
0-1
1 -
1 -
1 -
1 -
0-1
0-1
0-1
0-1
0-1
0-1
a- 2
0-2
0-2
0-2
0-2
0-2
0-2
1
1
3
1
-'
o1
j
i
3
r
-?
i1
-7
('
r
Q
Q
9
9
Q
Q
cr1
tj
3
'~j
!j
-'
I'
r o
-78
-78
7y
-78
-78
-78
-78
-78
n,-,
t o
-78
-78
"~ i' Cp
-78
-78
-78
\ o
-78
~~ r o
-7y
-78
-78
(' d
-78
-73
-78
TSP
(MG)
145.
139.
124.
79.
117.
146.
US.
116.
69.
114.
123.
1 1 3 .
73.
186.
229.
139.
123.
253.
206.
266.
119.
198.
159.
30.
1'24.
190.
D18
2
9
7
1
4
5
5
r'
o
3
4
0
0
9
'i-
1
9
9
3
5
6
3
9
1
9
0
FLOW
(M3)
2169.
1975.
2087.
2123.
1958.
2173.
2270.
2183.
2396.
2284.
2100.
2191.
2421.
2393.
2187.
2502.
2575.
2243.
2135.
2412.
2479.
2268.
2406.
2583.
2603.
2283.
6
5
-i
hi
6
0
7
6
5
3
8
5
C'
1
2
5
6
2
9
9
8
4
1
6
6
2
2
CONC.
(UG/M3)
67
96
60
J7
60
67
52
53
29
50
59
54
30
f O
105
76
48
113
97
110
48
tt7
66
31
48
83
-------
ITE
NO.
1
2
3
4
5
6
1
3
4
5
6
6
1
2
3
5
4
1
3
6
4
5
1
3
6
FILTER
HO.
19585
10596
10507
10508
10509
10518
10511
10513
18514
18515
10516
10517
10518
10519
10520
10521
10522
10524
10525
10527
18528
10529
10538
18531
10532
10533
DflTE
11-18-78
11-10-78
11-18-78
11-10-78
11-10-78
11-10-78
11-14-78
11-14-78
11-14-78
11-14-78
11-14-7-3
11-16-78
11-16-78
11-38-78
11-16-78
11-16-78
11-16-78
11-22-78
11-22-78
11-28-78
11-30-78
11-30-78
11-22-78
11-28-78
11-28-78
11-28-78
TSP
CMG:>
198.4
193.6
155.6
288.7
155.9
137.6
244.0
147.3
254.6
212.6
75.9
85.7
144.9
162.8
107.7
94. 1
102.3
189.9
104.0
60.2
180.8
225.3
139.1
101. 1
95.9
58.6
D19
FLOW
2152.2
2012.3
2167.7
2874.5
2388.3
2111.9
2288.4
2434.3
2172.7
2272.2
2448. 1
2468.2
2311.9
2174.9
2476.6
2388.9
2316.7
2372.4
2302.3
2722.7
2135.6
2327.9
2315.8
2542.7
2409.5
2498.9
CONC.
(UG/M3)
92
96
72
97
65
65
107
60
117
94
31
35
63
75
43
39
44
80
45
22
84
97
60
40
48
24
-------
ITE
HO.
6
2
4
5
1
1
2
2
3
3
4
4
5
5
6
6
1
1
5
3
4
1
2
3
4
5
FILTER
NO .
10539
10540
10541
10542
10543
10544
10545
10546
10547
10548
10549
10550
10551
10552
10553
10554
10555
10556
10557
10553
10559
10560
10561
10562
10563
10564
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
i!
y
2
£
'd
2
2
2
O
2
2
2
w
2
2
1
*
1
1
1
1
1
1
DflTE
-4-78
-4-78
-6-78
-4-78
-6-78
-10-78
-6-78
-10-78
-6-78
-10-78
-10-78
-12-78
-6-78
-10-78
-6-78
-10-78
-12-78
-14-78
-2-79
- -2-79
-9-79
-9-79
-9-79
-9-79
-11-79
-9-79
TSP
67.5
178.
308.
188.
175.
127.
192.
273.
201.
141.
284.
202.
322.
283.
76.
71.
206.
227.
168.
95.
258.
191.
150.
148.
48.
134.
0
0
6
3
5
3
0
6
6
1
2
4
4
ci
7
7
5
5
5
8
8
6
8
2
2
FLOW
2292.9
2274.
2151.
2484.
2486.
2825.
2174.
2226.
2271.
2633.
2250.
2234.
2361.
2500.
2261.
2562.
2302.
2324.
2696.
2606.
2060.
2349.
2240.
2345.
2321.
2584.
8
6
4
3
4
6
1
0
6
4
6
5
1
3
0
0
8
2
6
O
0
1
5
7
5
COHC.
(UG/M3)
29
78
143
76
70
45
88
123
89
54
126
90
137
113
34
28
90
98
62
37
126
82
67
63
21
52
D20
-------
ITE
NO.
1
1
2
2
3
3
4
4
4
5
5
5'
6
6
6
1
1
2
2
2
3
3
3
4
4
5
FILTER
HO.
10567
10568
10570
10571
10573
10574
10575
10576
10577
10578
10579
10580
10581
10582
10583
10584
10586
10587
10588
18589
10590
10591
10592
10593
10594
10595
DflTE
1-15-79
1-17-79
1-15-79
1-17-79
1-15-79
1-17-79
1-15-79
1-17-79
1-21-79
1-11-79
1-15-79
1-17-79
1-- 15-79
1-17-79
1-21-79
1-21-79
1-30-79
1-21-79
1-25-79
1-27-79
1-21-79
1-25-79
1-27-79
1-25-79
1-27-79
1-21-79
TSP
CMC)
183. 4
157.7
213.2
174.0
131.2
108.4
1 96 . 6
174.4
132.9
127.4
178.8
210.2
72.1
93.0
71.2
93.6
78.3
98.7
112.2
119.6
103.6
114.4
122.1
157.4
180.3
157.8
D21
FLOW
2586.2
2543.6
2360.7
2419.4
2452.0
2531.5
2098.9
2256.9
2278.6
2259.6
2477.1
2463.2
2473.2
2542.2
2441.0
2714.0
2424.0
2566.1
2510.0
2786.1
2412.3
2302.5
2355.5
2172.9
2350.0
2501.3
COHC.
71
62
92
72
54
43
_94
77
58
56
72
85
29
37
29
34
32
38
45
43
43
50
52
72
77
63
-------
ITE
NO.
6
1
2
3
4
6
4
4
4
1
1
1
2
2
2
3
3
3
5
5
5
6
6
6
5
2
FILTER
NO.
10618
10619
18628
10621
10622
18624
10625
10626
10627
10628
10629
18638
18631
18632
18633
18634
18635
10636
10637
10638
18639
18648
18641
18642
18643
18644
DRTE
18-25-78
18-29-78
18-29-78
18-29-78
18-29-78
18-29-78
18-31-78
11 -2-78
11 -4-78
18-31-78
11 -2-78
11 -4-78
18-31-78
11 -2-78
11 -4-78
18-31-78
11 -2-78
11 -4-78
18-29-78
1&-31-78
11 -2-78
18-31-78
11 -2-78
11 -4-78
11 -4-78
11 -7-78
TSP
O1G>
9 1 . 3
104.6
121.1
187.3
189.9
68. 1
244.8
367.3
337.1
289.2
262.6
273.8
228.2
278.8
267.3
188.6
389.4
256.2
99.8
285.2
388.4
123.7
124.8
217.8
284.5
134.6
FLOW
(M3>
2369. 1
2399.1
2225.8
2327.7
2188.3
2419.6
2113.1
2188.5
1869.8
2213.1
2167.3
2181. 1
2841.8
2853.9
2288.8
2225.6
2213.1
1995.9
2285.9
2891.2
2893.4
2293.3
2398.4
2258.2
1945.6
2121.5
CONC.
OJG/MS)
39
44
54
46
58
28
116
175
188
95
121
138
108
136
121
81
140
128
43
136
147
54
52
97
146
63
D22
-------
ilTE
NO.
1
1
2
2
3
3
4
4
5
5
6
6
1
2
3
6
5
4
1
2
3
fa
5
4
1
1
FILTER
NO.
10663
1Q664
10665
10666
10667
10668
10669
10670
10671
10672
10673
10674
10675
10676
10677
10678
10679
10680
10681
10682
10683
10684
10685
10686
10687
13688
DflTE
3 -7-79
3-10-79
3 -7-79
3-10-79
3 -7-79
3-10-79
3 -7-79
3-16-79
3 -7-79
3-10-79
3 -7-79
3-10-79
3-14-79
3-14-79
3-14-79
3-14-79
3-14-79
3-14-79
3-16-79
5-16-79
3-16-79
3-16-79
3-16-79
3-16-79
3-20-79
3-22-79
TSP
222.9
128.3
239.8
175.8
183.3
173.2
187.0
294.5
151.0
261.8
137.2
83.8
145. 1
168.9
147.3
76.9
194.8
205.0
194.7
164.9
226.6
118.4
265.4
324.1
383.3
19,4.4
D23
FLOW
1885.3
1625.9
223S.-5
2359.4
2356.3
2464.9
2254.4
2255.9
2322.4
2147.8
2283.1
2419.4
2111.0
2577.2
2570.5
2438.3
2307.4
2220.5
2277.1
2468.0
2371.6
2379.5
2179.0
2195.7
1972.1
1971.9
COHC.
118
79
107
74
78
70
83
131
65
122
60
35
69
66
57
32
84
92
85
67
96
50
122
148
154
99
-------
ITE
NO.
4
5
5
6
6
1
1
2
2
3
3
4-
4
5
5
6
6
2
3
5
4
1
2
3
6
5
FILTER
NO.
10646
10647
10648
10649
10650
10651
10652
10653
10654
10655
10656
10657
10658
10659
10660
10661
10662
10701
10702
10703
10704
10705
10706
10707
10768
10709
DfiTE
2-26-79
2-22-79
2-26-79
2-22-79
2-26-79
2-28-79
3 -4-79
2-23-79
3 -4-79
2-28-79
3 -4-79
2-23-79
3 -4-79
2-28-79
3 -4-79
2-28-79
3 -4-79
1-30-79
1-30-79
lv 3 0-79
1-30-79
2 -2-79
2 -2-79
2 -2-79
2 -2-79
2 -2-79
TSP
aio
93.2
255.1
85.8
145.7
81.8
249.6
109.3
211.5
104.5
201.6
94.9
269.4
125.8
223.6
105.2
133.3
74.0
142.3
98.8
270.7
133.4
131.4
140.5
71.9
45.0
204.5
D24
FLOW
2412. 1
2260.9
2629.0
2270.9
2326.7
1995.9
2472.6
2081.7
2587.3
1949.2
2529.8
2029.4
2493. 1
2022.2
2579.7
2182.5
2479.9
2430.7
2242.7
2389.3
2019.1
2261.8
2521.4
2231.0
2803.2
2412.0
CONC.
(UG/M3)
39
113
33
64
35
125
44
102
40
103
37
133
50
111
41
61
30
59
44
113
66
58
56
32
16
85
-------
ilTE
NO.
4
4
5
5
6
6
1
1
4
£
2
3'
3
4
4
5
5
6
6
3
5
4
6
FILTER
NO.
10693
10694
10695
10696
10697
10698
10699
10700
10745
10746
10747
10748
10749
10750
10751
10752
10753
10754
10755
10105
10106
10107
10108
DflTE
3-20-79
3-22-79
3-20-79
3-22-79
3-20-79
3-22-79
3-26-79
3-28-79
2-22-79
3-26-79
3-28-79
3-26-79
3-28-79
3-26-79
3-28-79
3-26-79
3-28-79
3-26-79
3-28-79
4-27-78
4-27-78
4-27-78
4-27-78
TSP
305.3
214.9
i **~i £ *~i
._! .Ml D « fc»
198.1
135.9
126.0
172.4
237.3
221.3
208.5
177.8
144.4
148.3
280.7
180.7
319.5
173.8
82.6
99.7
243.4
258.5
367.3
214.4
FLOW
(M3>
2044.3
2057.2
2175.7
1927.3
2194.2
1964.1
2299.9
2219.4
2255.4
2360.3
2476.0
2517.0
2557.9
2109.5
2378.1
2093.6
2536.2
2420.8
2450.6
1982.9
2191.0
2017.4
2248.8
CONC
149
104
155
103
62
64
75
107
98
88
72
57
58
133
76
153
69
34
41
123
118
182
95
D25
-------
ITE
NO. '
4
5
6
1
i!
6
5
1
£
.-,
6
5
4
1
L.
4
5
6
1
2
3
6
5
4
1
1
FILTER
NO .
10714
10715
10716
10717
10718
10720
10721
10722
10723
10724
10725
10726
10727
10728
10729
10730
10731
10732
10733
10734
10735
10736
10737
10738
10739
10740
DflTE
2 -3-79
2 -6-79
2 -6-79
£ -8-79
£ -8-79
'I1 O ~ *"* O
L_ u i r
£ -8-79
2-12-79
2-12-79
£-14-79
2-12-79
2-12-79
2-12-79
£-14-79
£-14-79
£-14-79
£-14-79
£-14-79
£-£0-79
£.-20-79
£-£0-79
£-£0-79
£-£0-79
£-£0-79
£-£2-79
2-26-79
TSP
O'1G>
211.5
165.7
95.6
155.0
£ £ Z . '
63. £
£70. 7
134.5
122. 1
84. 1
107. 1
1 0 9 . 6
117. 1
146.3
102.9
110.5
105.7
74.2
321.7
£32.0
218.9
136.3
24£.6
£83.9
244.8
106.6
FLOW
2254.2
£596.7
£359. £
£373.4
££87.6
£491. 1
£349.9
£145.3
£303.4
2882. 8
£340. 1
£413.5
£195.0
££35.0
£503. 3
£ 1 £ 1 . 9
£474.5
£350. 9
£147.7
£340.0
£00£.0
££83.9
£206. 0
1962.0
£350.8
£538.7
COHC.
(UG/M3)
94
64
41
65
97
£5
115
63
53
40
46
45
53
65
41
5£
43
32
150
99
109
60
110
145
104
42
D26
-------
ITE
NO.
5
4
1
2
5
£
2
1
3
5
1 '
1
3
4
5
5
£
1
3
4
3
2
1
FILTER
NO.
10173
10174
10175
10176
10231
10232
10233
10234
10262
10263
10264
10265
10295
10297
10298
10299
10330
10331
10332
10333
10360
10361
10362
10363
DfiTE
5-25-78
5-25-78
5-30-78
5-30-78
6-13-78
6-13-78
6-13-78
6-13-78
7-13-78
7-13-78
7-13-78
7-15-78
7-25-78
7-27-78
7-25-78
7-25-78
8-10-78
8-10-78
8-12-78
S-12-78
8-26-78
8-26-78
8-26-78
8-26-78
TSP
O'1G>
514.4
428.9
277.5
246.8
129.4
27.9
100.5
61.8
257.9
351.7
186.3
224.4
158.4
141.7
174.4
205.0
176.9
91.5
204.6
187.1
102.1
80.9
104.9
72.1
FLOW
-------
ITE
HO.
1
4
5
2
6
1
4
6
2
1
2
3
4
5
1
1
3
3
6
2
1
6
6
i
2
3
FILTER
NO.
1Q377
10379
103 30
10381
10382
10383
10441
10442
18443
10444
10614
10615
1 06 1 6
10617
10534
10535
10536
10537
10486
10487
10488
10538
10565
10566
10569
10572
DfiTE
9 -7-78
9 -7-78
9 -7-78
Q _ ~? _ "7 O
7 I I u
9 -7-78
9-13-78
10 -7-78
10 -7-78
10-11-78
10-11-78
10-25-78
10-25-78
1Q-25-78
10-25-78
11-30-78
12 -4-78
11-30-78
12 -4-78
12-28-78
1 -2-79
1 -2-79
11-30-78
1-11-79
1-11-79
1-11-79
1-11-79
T3P
2449.8
2281.3
2298.3
2287.3
2466.7
2127.8
2257.3
2519.3
2000.0
1844.6
2262.9
2299.6
2101.6
2190.3
2484.6
2507.5
2256.7
2590.4
2388.5
2338.2
2363.3
2326.0
2402.5
2227.7
2109. 1
2063.8
CONC.
OJG/riS)
42
76
79
53
30
20
42
13
88
97
99
66
102
87
51
68
62
49
24
57
44
26
22
61
5?
60
D28
-------
HIE
NO.
5
5
6
6
6
1
2
2
3
3
4
1
2
3
2
2
3
3
FILTER
NO.
10596
18597
19598
10599
10600
10645
10689
10690
10691
10692
10710
10711
10712
10713
10741
10742
10743
10744
IlfiTE
1-25-79
1-27-79
1-25-79
1-27-79
1-30-79
11 -7-78
3-20-79
3-22-79
3-29-79
3-22-79
2 -2-79
2 -6-79
2 -6-79
2 -6-79
2-22-79
2-26-79
2-22-79
2-26-79
TSP
CMC)
128.6
235.4
60.5
65.9
35.4
122.2
332.0
230.0
288.6
280.6
157.6
214. 1
170.8
138.7
243.5
118.1
173.3
82.3
FLOW
2426.8
2637.3
2505.5
2548.2
2575.7
2243.5
2108.5
2054.3
2168.9
2124.0
2183.3
2073.9
2290.9
2097.8
2317.5
2275.3
2441.0
2670.1
COHC.
(UG/M3>
53
89
24
26
14
54
157
112
133
94
72
103
74
66
105
52
71
31
D29
-------
APPENDIX E
The following information represents the GEB computer results for the
fine particulates. The resolution in this appendix was performed for six
source categories and includes an analysis of the project's overall average
values for each chemical component for each site. Additionally, the GEB
program calculates a combined average fit for all sites and provides com-
posite data for predicted source strength coefficients when multiplied by
the respective marker element concentrations.
E-l
-------
fO Tilt: AJfi.UJar'ukitt: (;
Si'fctL
OIL HtrUbt! AUl'O Llrfirtu PKhUlCl'hiU OiJbtKtftU L/S
Ha . oaal .0000
LiiV . O3b7 .OOOO
Zrt .04/0 1 /.b/00
HI .2blO .0000
Ft: 2b / . 36 1 4 J 7 / . d3OO
M J . 3y4b 1 1 . / 1 J4
en ,44yj .0000
v . 3yji .0000
CA J / . /424 32. /IOI
M
i
N> 6 i . /y/j .oj/d
bl 1 /y /.23db J. //tib
AL 44y.JI40 l.duyj
CL 1.32/7 .0000
iJA 2a . 1 o 1 o . OOOO
1C dd.Oos/ .OOOO
COtFr .yd2l . b324
for1 /idy. y/6.
^ Tbt^ 42. d 3.b
.2 1 /2
.0000
.yoy4
o./doj
i .4yjo
.OJdO
.0421
IJ.b/20
2.0 Jay
. OOOO
.OOOO
d.2/yj
.0000
a.d222
.0000
.yoyo
iy4.
1 .2
I0y.440o
2.2dOd
loJ. J442
.2I2J
j.y2o^
.«O 04
.b004
.022y
4.yooj
.0000
/6.44bl
b . 1 6 /2
y.doo/
ya.ooob
.OOOO
.yb,2
IdbO.
H. i
oO 1 .obOJ
2IO.b//0
IJ.2JOJ
.JO/0
d.42Jl
1 .20JJ
.0000
.0000
d.42JI
.OOOO
.0000
.0000
4o.y2d/
.0000
I2.OJJO
,dd22
ooi /.
Jb.d
.0061
.OO4I
.01 J4
.01 J4
4.0303
4.0b03
.00/J
.Ol J4
202.b2bJ
6.0dHd
46.04yd
d. 1 1 JO
.1014
.26J/
i.do^r
.0364
boJ.
J.4
71 1.4022
2l2.y242
|yb. /20J
7.0JO/
i
1
OdJ.J042
21 .4061
1 . 003 1
14.2020
JOU.OJ/I
iy24. uiy
4/b.76J4
3d. Jbdb
1 J2.2340
loi .yojd
od2.000o
y2l .0000
1 71 .0000
7.0000
6d4 . OOOO
2y.yooo
I.JbOO
1 4 . OOOO
joy.oooo
3l 10. OOOO
id jo. oooo
bbd.OOOO
74.2000
iy2.oooo
jOd.OOOO
TOTAL ^Ktui<
1 .04
4.JJ
1 .14
i .oy*
1.00
1 .40*
1 .J4*
1 .01
1 .00
*****
1 .03
I.I/
1 .21*
\ .43
J.02*
*A\/U
Jft'U TbP
I .62
-------
> L 1"±= ^ Ai/O i-'i
TO
-J U>iO J
.d //o
.022J
.024/
/.y/db
.0000
.oooo
4.d6oy
.oooo
b. IdoO
.0000
.yjd/
1 14.
.0
I4.yjd4
.JI2I
22.2yol
.02yo
.SJD.
. loyj
.06*1
.OOJI
.oody
. oooo
I0.4J40
1 . 1 1 4d
1 .JJ /d
u.j/70
.0000
.Jd03
2bJ.
1.4
6dv.Jdyy
24 1 .2UOJ
1 b . 1 ooo
.42O3
y.6bi3
1 .J/dd
.0000
.0000
.oooo
.oooo
.oooo
3J.//24
.oooo
1 J. /u/d
1 .olod
6d*4.
Jd.3
.OOoO 7O4.366I
.0040 24l.66d3
.01 J2 6 7.^ol /
.OIJ2 4. /4Vo
4.00J4 yo7.d03j
4.00J4 2d.7b02
.00/2 .6323
.OIJ2 d.6y64
200.1 /24 J4I ,/yOJ
6.00b2 d.iy2J
46.0_>y6 2ldd.442o
d.OOoy b4d.b!22
.1001 3 /.Ol /2
.2602 4d.3d3/
i . /dis i iy . /Jbo
.bd,0
bb6.
J.I
6 /d . OOOO
7 y o.oooo
bd . oOOO
4.7600
y/2.oooo
4b.tOOO
1 .J/00
d.bOOO
J4J.OOOO
4y 7o. oooo
iy 10. oooo
364.0000
1 bO. OOOO
1 04 . OOOO
JJa. OOOO
i'OTAL ^HfcUi(
1.04
j.2y
1 .13
1 .00*
1 .00
l.b/*
2.1 /*
i .02
1 .00
*****
1 .Ib
1 .OJ
2.0J*
J.Jd
2.dl *
*A^GI 2.oj
JTtu TJH« r/yo4.
-------
1'n J
t'Lh'MfNf
hMt:LJl a
Si
AL
CL
ilA
Ix
Cuht-V
ibp
,i TSP
.0/Jl .OOUO
.0462 .0000
.jj>til Id.) odo
. 20d / . OUUO
2Jd.aaJd JyO. /22y
2.ydiy 12. 1 124
.J/2/ .0000
.4y20 .oouu
JI.JI02 a4.bObd
i.4v 10 .ojyi
I4yo.yolb j.yo/2
J72. /404 1 .ybJo
1 .20/J .OOOO
20.d/Ja .oooo
/J.Oa/l .0000
1 .Oa /4 .606 /
ay&4. 1010.
44 . j / . a
. 1 OOa
. ouoo
.44ol
J. J2dd
. /J2J
.oido
.O2O6
o.ob //
.yyd/
. oooo
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4.O6I2
.0000
4. J2/a
.0000
.y4a/
ya.
./
Ib.dbo/
. JJU
2J.006/
.OJOd
.a6do
. 1 1 00
.U/J4
.OUJj
. /I 00
.uuuo
1 1 .0/00
I . idjj
1 . 42 00
14.2000
.oooo
.4/dl
2oy.
2.0
bay. I ooJ .Ooay b/b
I ya. /ud2 .oojy |yo
I2.JUI / .OI2y ab
.J4II .OI2y J
/.d2dJ J.VI60 042
I . 1 loJ J.y 1 66 2U
.uooo .00/0
.ouuo .oi2y /
/.d2dj lyb.djia 2yi.
.0000 b.d7aO 7
.0000 4b.04U IbaO
.OUUO /.dJJJ Ml.
4J.oibO .oy/y 4o.
.0000 ,2b46 jy.
1 1 .IdJJ 1 . /42y db.
1.0 IJU .6/0/
bay2. b44.
41 .a 4.0
. 2Od4 ba2.0OOO
. Ody/ ojG.oooo
. IJ2/ 4y.aUOO
.y224 b.oyoo
.J220 044.0000
.2ojy 22. d 000
4/Jd 1.2/00
1 06U /.040O
Id4d 292.0000
40bO 44/0.0000
yaoo i4io.uooo
//Id 44y.OOOO
4002 D4.0000
6aba 200. OOOO
9dJJ J 12. OOOO
TOTAL pifkLUu
1 .04
J.24
1 . 1 1
1 . JO*
1.00
1 .IJ*
2.6d*
1 .02
1 .00
*****
1. 10
1 .16
1 .16*
b.04
3.0J*
*A »/U «
rbu i'sp«
I .yd
134/J.
-------
*» AV I-.' I- i .Jf-
1\) filt
(|M
-------
fc b AVvj-r iiJt:
JOiJi'tMuUl UM 1'U 1'llt AiViiJbi-'ilLri't ( rtu/i.i J J
bLtMtiJT
UiL Rl-.hUbh AUi'O LiMiNJ FrtcUiCi'hU Ud^fc'UVtU L/o
^J .Ubyd .uuuu
tiit . uj/y .uuuu
ZN .4jyo //.y|y|
ill .1 /uy . uuoo
t-t lyb.Jbyu io/D.obui
'I''' 2. -t42U b 1 .y40l
^ . JUD^ .uuuo
i !22U.yyJd lO.Vbob
AL JUj.24d4 d.J/b4
L'L 1 .UJ /d .UUUU
iJA I / . uyjy .uuuu
'^ by.d2d/ .UUUU
<~ohi-r . yoi-4 . bdi y
l'^ 4bd4. 4JJU.
^ 'i'iJr1 2D.b 22. 0
. 1 DDD
. UUUU
.ODI2
4.dby4
I .uoy i
.U2/2
.UJUI
y . / 1 db
1 .tb /d
.uuuu
.uouu
b.y2ti4
.uuuu
0. Jl /^
. uuuu
.y /jy
i jy.
. /
JI.4U/V dJJ.24jy .UIOI
.OboJ 2y| .oJb4 .UUO/
40.d//l ld.JJ!4 .0222
.U6Uy .bUdJ .U222
1 . I2bl ||. oob4 o. /jy2
. 22y / 1 . ooob 6. /jy2
. 1 4bJ .UUUU .U 121
.UUoo .UUUU .U222
1 .4U6J Il.00b4 JJO.yDyo
.UUUU .UUOO lU.IUdd
21 .yjdb .OUUU //.bUU/
2.J4jy .UUUO U.4/d4
2.dl20 04 .yyjO . loUb
2d. I20J .UUUU .4JbO
.uuuu I6.6o4y 2.yydy
. J/bU 1 .UI24 ,b4y/
3-i-i. bJJ2. yjo.
2.d 4J.D 4 .y
bo4.d//U b2J.UUUO
2y2.JJo2 04b.UUUU
I44.24UO 124. UUUU
b.o2ld /.JOUU
iby i .oj/y lyuo.uouu
oJ.UbU/ bJ.JUOO
4y2d i . J6uu
1 U. 1 bUD IU.UUUU
OlU.bd/J 6IJ.UUUU
1 1 .4y /j 4yju. oooo
uj/.idya 12/u.uuuu
JJb.J//D bJb.OOUU
oy.UI2U 44J.UUUU
bl.y/b4 J6I.OUUU
/y.4y2D 1220. uuuu
fUl'AL FHtUlU
1 .Ub
2.21
1 . lo
1 .JO*
1 .00
1 . id*
2 . /o*
1 .U2
1 .00
*****
1 .UD
1 .6U
6.42*
6.ya
Ib.Jb*
*A i/U «
ftU fbFJ
b.40
-------
Cl.MrrfllJlU'lUN fi)
UiL
Mcl-'Ubt
AUl'O
Ll.'.iiHL>
Otibfc-KVtu
L/S
r"J .00 /I .OOOO
drt .042D .OOOO
£A .4yJ2 -2.d/4y
i4l .lyid .0000
Ft 2iy.id04 -oi.d2oy
iM 2./jyd -i.yioo
Crf .J42b .UOOO
(/ .41)^1 .0000
CA 2d./O/4 -d.624d
J i.joyy -.OU62
SI iJoy.d//4 -.6ldJ
AL J42.40VJ -.JOyl
CL 1.1044 .OOOO
iM ly. 1 /dJ .0000
S. 0/.I240 .OUUO
vJOht-V I.I 047 -.Jdlo
l"o f D4JO. 1 6O .
/, TbH /2.0 -2.1
.06lb I2.iyld ldy.4l-->4
.OUOO .2b4d OO.2yi>4
.2b// Id. lyod 4.lo/l
1 .y2JJ .02J7 . 1 1 bu
.42JI ,4JO/ 2.Obld
.ojod .ouy2 .j/dd
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J.d40/ .002'-) .0000
,b//o .D4ay 2.0Did
. OOOO . OOOO . OOOO
. OOOO d . D 1 6 1 . OOOO
2.J40D .yoyd .0000
.0000 i .oyid i4. r/44
2.oooj lo.yiui .ouoo
.OOOU .UUOO J./dtiJ
.yo/2 .*«//
20/. Iby4.
./ 2./ 24. y
.00 ID
.0010
.OOJJ
.OOJJ
1 . 0042
1 . 0042
.00 Id
.OOJJ
D0.2IOJ
1 .b06J
1 1 .D4d4
2.00d4
.02bl
.06DJ
.446y
.0 lot
uy.
1 . J
201 ./J/4
06. by jo
20.24J2
2.2b7o
I ol .doy4
2.JOOI
.4126
4.J046
/4. 12 /o
2.b/00
i joy. J2J6
j4/.424y
1 /.ODD/
J2.O62U
/i . jDy2
iy2.oooo
i a / . oooo
iy.2ooo
4 . 440O
1 62 . OOOO
y.jDOO
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4.240O
/4.20OO
JJ 00. OOOO
1240.0000
J 7 /.OOOO
40.4000
1 J4 . OUOO
lov.oooo
i'Oi'AL HHtUi
I.OD
2.dl
I.OD
i .y/*
1 .00
4.OD*
2.0J*
1 .02
1 .00
*****
1.12
i .oy
2.J/*
4.10
2.J/*
*A>/Ui 2.D6
ol'h'U fSpi 761 b.
-------
Mi
!MlAuA. 1 . -_>dy / .O/oO
rt Si iaby.7Jd4 7.6OU
1
00 AL jy/.4J4o J.d006
CL I.JDU .oooo
MA 22.2DOJ .0000
iC //.dy/2 .0000
wiAJon fc'LEi.ibNr di FH
cSi". >i HtiJrir .230 .Jd/
TSH oj'jy. iyo4.
,i TUfAL Tbr' 40. J I2.b
.I2// J0.2by/ 002. //yO
.0000 . /!)// 2IO.y/2/
.3J40 34. 1 190 1 J.2ol 1
j.ydyd .0/04 .jo//
.d//d I .2ydy d.4Jby
.O22J .2ob2 1.2030
.024/ . Io7d .OOOJ
/.y/y/ .00/0 .oooo
i . iv /o i ,o2Jo d.4Jby
.OOOO .OOOO .OOOJ
.OOOO 23.J277 .OOOO
4.d6/o 2. /ObV .OOOO
.0000 J.247I 4/.OIod
D.ldod J2.4/I4 .oooo
.0000 .OOOO !2.Obbo
\/ Zn Pii
.0/0 .Obd .100
114. oil). OO2d.
. / J.y -id. 2
.00/4
.oo4y
.0102
.0102
4.yody
4.yody
.oodd
.0162
24b.44bl
V.J6J4
36.4b24
y.u) /d
.I22/
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2. Id43
CA
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4. J
ojy.2al /
211. Vd4b
I0j.b4y I
4.Ot)6/
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JJ. I4b4
.bydd
d.b2bl
jyo. 1266
y.o2yi
io/y.i iy/
4lb.o2oo
bl.7J/y
00.2JJO
y2.jj/2
TOTAL ^i
o 1 1 . 1 oo /
oj /.6o6/
yo.ddJj
j./JJj
IOJJ.006/
Jd.jyi /
1 .J46J
d.jybo
jy/.Joo/
4o7 1 .000 7
1341 .0007
3 1 1 . 1 00 /
I/J.OOOO
242.0000
DJ2.OOOO
JhUUTliO TSHi
1 .Ob
J.OI
1. 14
I.2J*
1 .00
1 .10*
2.2b*
1 .02
1.00
*****
I .oy
1 .22
J. J6*
4.02
3.77*
-* A Jt " I
*Avu 1
lD7o2.
2.7b
-------
SlTt I AVo-
bli'b 2 AVo-
Sift: 3 AVJ-
cilTti 4 AVU.-
SITt tj AVU- I22u.yy4
biTfc: O AVJ- IJoy.U//
COtfr-'l-'lClblJl') T( MAHh.l£l< l£l_ii..lh;iJ 1' CtJ.-JvJCb-iJTii Ai" 1 L
UIL iibFU6t AU"i\J
J//.U1JO
OI2.00J
jyu./2j
t>6'j. /2o
o'/'j.odo
-61 .d2/
1 J.b/J
/.y/y
6.6:>d
0. 104
y . / 1 y
J.U47
2J.oo/
OUt .030
ouy.jyo 2UJ.I/2
iya.dJ2
4do.o/2
4o.d// bJJ.244
vo
-------
APPENDIX F
The following information represents the GEB computer results for the
coarse particulates. The resolution in this appendix was performed for six
source categories and includes an analysis of the project's overall average
values for each chemical component for each site. Additionally, the GEB
program calculates a combined average fit for all sites and provides com-
posite data for predicted source strength coefficients when multiplied by
the respective marker element concentration.
F-l
-------
l"t I
t-Mtt Ji oi'liu
i'U 1Mb Al'iAOiiHlllzHt
LnJiL oi'thL
OiL Kht-UJl; AUl'J LiMliJJ
L/'J
I-J
bit
ZH
Hi
Ht
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Clt
*
CA
3
Si
AL
CL
NA
K.
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TbP
£ i'bP
.JOOI .OOOO
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2.204U -J.dOJy
. d3/4 .OOOO
y/y.yibo -di.dOJb
I2.24dy -2.3Jby
1 . _> J 1 1 . OOOO
2 .02 1 1 . OOOO
I2d.ol Jd -11.4110
O. 1 24b . 00d2
oi2-H.4ody . d I do
1 i)J 1 . 1 1 /2 -.40yO
b.20bd .OOOO
db./426 .0000
joo.oyyo .0000
1 . 1 dOI -.O/Ob
244yd. -211.
/y.b -./
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. OOOO
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1 .4JJb
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2. do/0
2 .40d2
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. / 1 0 /
.OOOO
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41 .
. 1
b.JIbl IUJ./4J4
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I2.6bbl y.Db4/
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b. I ddo o/.ydbl
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1 b. Id6l /b. JJ4d
. OOOO . OOOO
b.y22o .OOUO
1 1 . /oy2 .0000
2V. 1000 bb. 12 JO
I0.4bl0 .OOOO
.0000 j.o/4y
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144. IdJ/.
. b 0.0
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.10/4
J2.bbya
J2.bbyd
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. 10/4
1 O2 /.yddJ
4d.bJyo
J /4.4J/J
Ob . 1 1 yb
.b!40
2 . 1 1 04
1 4.4dy I
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K./
ijy
127
20
2
1004
4J
1
D
1 dJb
b4
Ob04
1007
yo
lOb
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. 4O4b
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.yjby
.b2oy
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4.
1 100.
20.
2.
3.
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ody.
-j iyo.
1010.
2IJ.
2b2.
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TOTAL
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yooo
dOOO
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yooo
JOOO
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oooo
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2000
Hktou
1
1
1
1
1
1
1
1
1
12
1
1
2
2
4
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. 10
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.00
.01
.b4
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.oy
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*AVU» 2.Jb
rspi joaji .
-------
OJ
t'LtMt'Hf
iiJlL iiftt'L
l\t f.lt: AI'Mi
OIL Itel-'Ubh
(iJu/»iJ>
AUl'O LirtiHJ
L/i
HJ . 32oO .OOOO
Utt .2063 .OOOO
/U 2.3y32 .4/03
NI .yjiD .0000
Kb- 1064. 3 Jod 10.1133
Mrt I3.300/ .JUb
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Si 66b3.j34d .1011
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j.dd/7 -.OJ/D .ouoo .0000 .0000
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2 . /2o9 -.OO03 .OOOO .12/9
2.2900 -.30d2 30./2d9 I9dd.dd44
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-------
APPENDIX G
The following information represents the CEB computer results for the
fine particulates. The resolution in this appendix was performed for seven
source categories and includes an analysis of the project's overall average
values for each chemical component for each site. Additionally, the GEB
program calculates a combined average fit for all sites and provides com-
posite data for predicted source strength coefficients when multiplied by
the respective marker element concentration.
G-l
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blfe I
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Sl'l-hL
COAL
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40.2
3.d.
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SlTti 6 AViJ- UJJ.'joO -t>y.Ob4 b2.Joy J.oytJ I6.2oo
-------
APPENDIX H
The following information represents the GEB computer results for the
coarse particulates. The resolution in this appendix was performed for
seven source categories and includes an analysis of the project's overall
average values for each chemical component for each site. Additionally, the
GEB program calculates a combined average fit for all sites and provides
composite data for predicted source strength coefficients when multiplied
by the respective marker element concentrations.
H-l
-------
tuiv,itu cJ.MiiililUli.M I'o Trib Al'MUbVilbrtd (HO//.U)
hLtMbiJT SOIL di'thL COAL OIL HtFUbh AUTu
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tit{ .1512 .0000 -.U4bl .UUUU -.J426 U/.//2O
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