oEPA
United States
Environmental Protection
Agency
Great Lakes National
Program Office
536 South Clark Street
Chicago, Illinois 60605
EPA-905/4-79-029-H
Volume o
. /
The IJC Menomonee
River Watershed Study
Atmospheric Chemistry
Of Lead And Phosphorus
Menomonee River
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FOREWORD
The Environmental Protection Agency was established to coordinate adminis-
tration of the major Federal programs designed to protect the quality of our
environment.
An important part of the Agency's effort involves the search for information
about environmental problems, management techniques, and new technologies
through which optimum use of the nation's land and water resources can be
assured and the threat pollution poses to the welfare of the American people
can be minimized.
The Great Lakes National Program Office (GLNPO) of the U.S. EPA, was
established in Region V, Chicago to provide a specific focus on the water
quality concerns of the Great Lakes. GLNPO also provides funding and
personnel support to the International Joint Commission activities under
the U.S.- Canada Great Lakes Water Quality Agreement.
Several land use water quality studies have been funded to support the
pollution from Land Use Activities Reference Group (PLUARG) under the
Agreement to address specific objectives related to land use pollution to
the Great Lakes. This report describes some of the work supported by this
Office to carry out PLUARG study objectives.
We hope that the information and data contained herein will help planners
and managers of pollution control agencies make better decisions for
carrying forward their pollution control responsibilities.
Madonna F. McGrath
Director
Great Lakes National Program Office
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EPA-905/4-79-029-H
December 1979
Atmospheric Deposition of Lead and
Phosphorus on the Menomonee River Watershed
Volume 8
by
A.W. Andren
T.R. Stolzenburg
Water Resources Center and
Water Chemistry Program
for
U.S. Environmental Protection Agency
Chicago, Illinois
Grant Number R005142
Grants Officer
Ralph G. Christensen
Great Lakes National Program Office
This study, funded by a Great Lakes Program grant from the U.S.EPA, was
conducted as part of the TASK C-Pilot Watershed Program for the International
Joint Commission's' Reference Group on Pollution from Land Use Activities
GREAT LAKES NATIONAL PROGRAM OFFICE
ENVIRONMENTAL PROTECTION AGENCY, REGION V
536 SOUTH CLARK STREET, ROOM 932
CHICAGO, ILLINOIS 60605
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DISCLAIMER
This report has been reviewed by the Great Lakes National Program
Office of the U.S. Environmental Protection Agency, Region V Chicago,
and approved for publication. Mention of trade names or commercial
products does not constitute endorsement or recotmnendation for use.
ii
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PREFACE
The importance of air pollution to the direct and indirect loadings
of lead and phosphorus to Lake Michigan is evaluated utilizing dry and
wet deposition information obtained in the Menomonee River Watershed.
U.S. frwiro&mentat Protection Agency
Rtgion 5, Library (PL-12J)
77 West Jacfcson Boulevard, 12th floor
Chicago.il 60604-3590
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CONTENTS
Title Page i
Disclaimer ii
Preface iii
Contents iv
Acknowledgement v
*Part I - Atmospheric Monitoring Program I-i
*Part II - Lead Deposition to the Watershed Il-i
*Part III - Lead Deposition to Lake Michigan Ill-i
*Part IV - Total Phosphorus Loadings to the Watershed I V-i
*Part V - Atmospheric Chemistry of Lead and Phosphorus V-i
*Detailed contents are presented at the beginning of each part.
U fJ ! %1'HI YHkil/U «fc P'.««*.*S-B -£_y
sllilllf .»»-./v<^t^? !K,/.jUl:^fc: It
Oi^-M53'3^ J ,o|
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ACKNOWLEDGMENT
We wish to thank L. Anderson, G. Wanek and J. Schwarz of the
University of Wisconsin-Madison Biotron facilities for assistance in the
design, construction and support of the chamber. Financial support is
also acknowledged from the U.W. Sea Grant and the U.S. Environmental
Protection Agency (Grant No. R00514201).
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PART I
ATMOSPHERIC MONITORING PROGRAM
by
T, R, STOLZENBURG
A, W, ANDREN
J, W, STRAND*
*Currently in the Department of Chemistry, University of Indiana
at Bloomington, Indiana.
I-i
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ABSTRACT
Air monitoring stations were located in five different land use types of
the Menomonee River Watershed. Total suspended particulate concentrations
were highest in the industrial valley, decreasing to the residential,
transition-urban, mixed rural and rural. Even the rural station experienced
effects from local urban emission sources. All stations exhibited similar
temporal trends of suspended load.
The concentration of lead in rain was consistently at about 30 yg/L.
There were no obvious differences corresponding to land use type.
A method for accurately establishing the weight of air particulate matter
collected on filters has been developed by constructing a clean glove box.
The system is capable of maintaining a constant relative humidity and temper-
ature. A description of this system is presented.
I-ii
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CONTENTS - PART I
Title Page I-i
Abstract I-ii
Contents I-iii
Figures I-iv
Tables I-v
1-1. Introduction 1-1
1-2. Conclusions 1-3
1-3. Methods and Procedures 1-4
Total Suspended Particulates 1-4
Rain 1-4
Equipment 1-4
Field procedures 1-5
Analysis 1-5
Clean laboratory procedure 1-5
1-4. Results and Discussion 1-7
Total Suspended Particulates 1-7
Rain « 1-7
References 1-13
Appendix
I-A. A Constant Relative Humidity-Temperature Chamber for the
Accurate Weight Determination of Air Particulate Matter
Collected on Filters 1-14
I-iii
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FIGURES
Number Page
1-1 Location of air and rain monitoring stations ......... 1-2
1-2 Total suspended particulate concentrations for sites at
70th Street, Appleton Avenue and Donges Bay Road ....... 1-9
1-3 Total suspended particulate concentrations for sites at
Falk Corporation and River Lane ............... 1-10
1-4 Concentration of lead in rain as related to the amount of
rain ............................. 1-12
I-A-1 Diagram of the constant relative humidity-temperature
chamber ........................... 1-15
I-iv
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TABLES
Number Page
1-1 Arithmetic means for 21 sampling periods for total suspended
particulate concentrations 1-8
1-2 Arithmetic mean concentrations of several constituents in
rain 1-11
I-v
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1-1. INTRODUCTION
The Menomonee River Watershed is characterized by five major land use
types: heavy industrial, residential, transition-urban, mixed rural, and
rural. Samplers designed to collect rain and atmospheric particulate matter
were located in each of these areas for the purpose of investigating local
effects on air pollutant levels. Figure 1-1 indicates the air monitoring
stations in the watershed. The sampling locations, corresponding to land use
types, are: Falk Corporation, 70th St., Appleton Ave., River Lane and Donges
Bay Road,respectively. The duration of the investigation was from 9/76-9/77.
1-1
-------
Appleton Avenue
A
km
Fig. 1-1. Location of air and rain
monitoring stations.
1-2
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1-2. CONCLUSIONS
Average total suspended particulate (TSP) concentrations found in air for
the period 9/76-9/77 at each station is a function of land use types. The
highest average concentrations were measured at the heavy industrial site,
with a progressive decrease from residential, transition-urban, mixed-rural,
to rural sites. The total suspended load in air decreases by an average of
50% from the heavy industrial site at the Falk Corporation to the rural
station at Donges Bay Road, a distance of approximately 24 km. Nevertheless,
it is apparent that concentrations measured at Donges Bay Road are influenced
by the proximity of local urban emission sources during certain wind condi-
tions and the average background level of suspended particulate matter for
this area is in the range of 35 to 40 yg/m3.
The observed region-wide trends for TSP are thought to be the result of
two phenomena: a. Meteorological conditions affect the dispersion of
locally-emitted pollutants. The concentration of suspended particulate matter
is increased by low wind speeds and mixing height even though local emission
rates remain constant: b. Of secondary importance are the influences of
large air masses with characteristically higher pollutant loads compared to
average background levels. It is expected that air masses originating from
large urban centers such as Chicago or St. Louis carry higher pollutant loads
into the Watershed than winds from the northwest.
The spatial and temporal concentrations of lead in rain did not exhibit
marked trends or variations. The measured level was consistently around
30 yg/L with a range of 10 to 130 yg/L. The measured concentration of any
trace constituent in rain seems to be a function of many parameters and it is
difficult to quantify the effect of land use type or meteorological factors.
1-3
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1-3. METHODS AND PROCEDURES
Total Suspended Partlculates
Total suspended particulate (TSP) samples were collected with high volume
air samplers. Operationally, 30 ft3/min (1 m3/min) of air is drawn through a
9x7 inch (23 x 18 cm) surface of Whatman 41 cellulose filter for approxi-
mately 48 hr during the summer and 72 hr during the winter. The flow is
maintained at a constant rate with a mass flow controller.
Filters are transported and stored in plastic zip-lock bags; handling is
carried out with plastic gloves or plastic coated tweezers. Hygroscopicitycan
be a major problem in gravimetric analysis. In Appendix I-A proper handling
methods are discussed which overcame ambient humidity fluctuations.
Rain Sampling
Equipment
The Wang rain sampler was chosen after careful consideration of monitor-
ing and analysis needs. The desired system must meet three criteria, namely,
a. be non-contaminating for lead, b. collects only rain and excludes fugitive
dust and c. minimizes evaporative losses.
The Wang sampler, features an aluminum sliding cover triggered to open
by a moisture-sensing head. A heating coil within the head drives off
residual moisture following an event, which allows the cover to close during
dry periods.
The original collection apparatus was modified to meet the guidelines
stated above. Rain was collected in a linear polyethylene (LPE) funnel. A
small glass funnel is heat-embedded in the neck of the plastic funnel.
Attached to the neck of the glass funnel is 1/8" (0.32 cm) i.d. Tygon tubing
leading to a 2-L LPE collection bottle. A vent, of the same diameter as the
tube, protrudes from the cap, allowing air to escape while filling, and acting
as an overflow valve for large events.
A gap existed between the sliding cover and the sampler body in the
original equipment. With this configuration, wind-blown fugitive dust
conceivably could contaminate the rain samples. To prevent the problem, foam
covered by plastic was taped to the body, forming a virtual seal with the
1-4
-------
closed lid. This minimized evaporation losses, as did the small bore tubing
which limited the exposed surface area.
It was anticipated that the samplers would operate reliably since an
earlier investigation by Galloway and Likens (1) had ranked the Wang sampler
first among the wet-only samplers tested for functional reliability. In fact,
there were few electronic problems and the mechanical difficulties encounter-
ed resulted from the modifications.
Field procedures
Sample collection flasks were changed weekly unless insufficient volume
(< 75 ml) was collected. Samples are therefore composites of all events that
occurred during the period. It is evident that collection flasks from each
station must be changed at the same time in order to make loading comparisons.
Freezing conditions precluded operations from 12/1/76 to 4/12/77. Even
during the warmer months, a frozen lid due to extreme heat is probably the
single greatest factor contributing to sampling error. Several very large
events occurred in 1977 which caused the collection flasks to overflow but
this was the exception rather than the rule.
Some loss of quality control occurred in late 1977 when other investiga-
tors removed aliquots from the collection flasks on an erratic basis for other
analyses. Additionally, some rain was stored in plastic bottles with card-
board liners in the caps. These bottles may have adsorbed Pb++ or contaminat-
ed samples to an unknown extent.
The rain samples were usually acidified directly in the collection flask
to a pH of 1 with HNOs, transferred to other LPE containers and weighed to
ascertain volume. Samples were stored at 4 C prior to analysis.
Analysis
Lead was measured by injecting rain directly into a graphite furnace
atomizer of an atomic absorption spectrometer. Background absorption was
negligible for all samples and wavelengths checked. Standard additions of
lead yield very similar values to measurements obtained using a standard
curve. Both results verify that the total ion matrix in rain is dilute.
Clean laboratory procedure
All sample containers were made of linear polyethylene and were cleaned
by soaking for at least 24 hr in 10% HNOs before use. After soaking, water
distilled three times was used to rinse them. Finally the containers were
air-dried upside down.
All water used for standards and rinsing was triple distilled. Primary
1-5
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distilled water was passed through a glass still. This distillate was further
purified in a sub-boiling quartz still. The hazard of contamination is most
severe for cadmium and sodium at the levels found in rainwater.
1-6
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1-4. RESULTS AND DISCUSSION
Total Suspended Partlculates
Table 1-1 lists the arithmetic mean values of the total suspended
particulate concentrations from 21 sampling periods. Ranked by land use type
from high to low, the heavy industrial site at Falk Corporation consistently
is highest followed by residential, transition-urban, mixed rural and rural.
The frequency of sampling periods for which this order was exactly followed
was 43% of the time.
All stations exhibit a similar trend in the suspended load from one
sampling interval to the next. Figure 1-2 shows the results from three
stations. The same trends are observed even for the two most distant stations
(Fig. 1-3). Evidently regional conditions are primarily responsible for the
episodes of increased pollutant levels in air. Figure 1-3 also illustrates
the consistently higher TSP levels in the industrial valley in contrast to
the mixed-rural site.
Rain
Mean concentrations of lead together with several other constituents in
rain collected in the Menomonee River Watershed are listed in Table 1-2.
Lead concentrations exhibit only a few extreme values and consistently
approximate 30
One might expect that the average concentration of lead in rain would
show a marked difference for different land use areas. This concept is very
difficult to demonstrate since concentrations observed in rain are a function
of many variables, including local sources and rainfall intensity. Conse-
quently, it is difficult to show a relationship between rainfall amount and
concentration of pollutants. For one particular sampling interval (9/1 to
9/15/76), lead concentration seemed to be a function of rainfall amount
(Fig. 1-4) but this was an unusual case.
In general, the concentrations of trace metals, particularly lead, were
fairly consistent temporally and spatially. Hence, seasonal trends or
variations due to land use type were not obvious during the time period of
the investigation. Overall mean concentrations seem to be representative of
levels encountered at any place or time in the Watershed.
1-7
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Table 1-1. Arithmetic means of 21 sampling
periods for total suspended
particulate concentrations
Total suspended
Station particulates, yg/m3
Falk Corporation 87
70th Street 61
Appleton Avenue 55
River Lane 51
Donges Bay Road 43
1-8
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140 -i
130 -
120 -
110 -
100-
90-
80 -
•H 70
u
at
•g 50
0)
en
50 -
40-
30-
20 -
70th St.
Appleton Ave.
Donges Bay Rd.
A
9/1/76
Date
3/31
8/31/77
Fig. 1-2. Total suspended particulate concentrations at 70th Street, Appleton Avenue and
Donges Bay Road sites.
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140
H
M
O
9/1/76
Fig T 3 T Date'3'31 ' ! ''' ^"^ rr~i ^
iotal suspended particular. 8/31
^ane sites. t±CUlate Concentrations at the Falk r
3lk CorPoration and River
8/31/77
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Table 1-2. Arithmetic mean concentrations
of several constituents in rain
Parameter Concentration, yg/L
Pb 3.2
Cd 3.7
Ca 800
Mg 280
Na 120
1-11
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1/3rt «
o
CM
-------
REFERENCES - I
1. Galloway, J. N. and G. E. Likens. Calibration of Collection Procedures
for the Determination of Precipitation Chemistry. Water, Air and Soil
Pollution 6:241-258, 1976.
1-13
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APPENDIX I-A. A CONSTANT RELATIVE HUMIDITY-TEMPERATURE
CHAMBER FOR THE ACCURATE WEIGHT DETERMINATION OF AIR
PARTICULATE MATTER COLLECTED ON FILTERS
Investigators involved with measuring particulate matter in air by high
volume samplers must select filters characterized by high collection
efficiency, high flow rate, low elemental blank values, and ease of handling.
Glass fiber filters are adequate for measurement of many of the above physical
criteria and are used widely for total particulate and organic matter although
the lower particle cut-off size, with sampling time, is not well known. The
high inorganic blank values of glass fiber filters, preclude their use for
measuring concentrations of many elements in air. Other filters that have
been used include Whatman 41 ashless cellulose, Nucleopore, Millipore, Misco
and Delbag microsorban filters. The choice of a particular filter must be
guided by the particular sampling program and the analytical objectives.
Because of their high pressure drops, Nucleopore and Millipore membrane
filters cannot be used when high flow rates are required. Particle bounce-off
also occurs with these filters especially when used in cascade impactorsa.
It was found that Whatman 41 filters are quite acceptable for high volume air
filtration and as substrates for cascade impactors. Their hygroscopic nature
can lead to unacceptable weighing errors unless strict precautions are taken^3.
Sampling periods of 24 hr usually yield from 20 to 500 mg air particulate
matter in the areas sampled while 20 x 25 cm cellulose filters weigh around
4250 mg. Thus, small weighing errors of filters result in large discrepancies.
It has been shown that a change of a few percent in relative humidity from
tare to gross weighing conditions may introduce weighing errors in collected
material ranging from 20 to 200%. It is imperative that constant temperature
and humidity conditions be maintained during tare and gross weighing. To
overcome this problem a glove box has been constructed which is capable of
maintaining a clean environment and constant relative humidity and temperature
for weighing operations.
The clean box, 120 x 90 x 90 cm is made from sheet metal, angle iron, and
plexiglass plastic. Figure I-A-1 illustrates the essential components of the
system. Beginning at the rear of the chamber, conditioned air is circulated
through glass fiber filters into the front work space. The analytical balance
and work space are accessible through the plexiglass window by two glove ports
and a removable door. The chamber air is drawn by fans over heating, cooling
^Ttemynck, M. Determination of Irreversible Adsorption of Water by
Cellulose Filters. Atmospheric Environment 9:523-528, 1975.
Dzubay, T. G., L. E. Hines and R. K. Stevens. Particle Bounce Errors in
Cascade Impactors. Atmospheric Environment 10:229-234, 1976.
1-14
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Thermostat
t Deminerolized
Water
H
M
Ln
I
#2
Humidify
Air Temperature
We',
Fig. I-A-1. Diagram of the constant relative humidity-temperature chamber.
-------
and humidifier sensors. These sensors consist of two sets of precision
thermistors (YSI 44004). One set (three in each set) is dedicated to sensing
temperature and humidity and the other serves as the chamber operating
sensors through feedback loops. The individual thermistors thus function
as air temperature, dry bulb and wet bulb indicators.
The temperature sensor is linked to a bridge circuit differential
operational amplifier. On one side of the bridge the amplifier actuates a
heating element to warm the air and on the other side a cold brine solution
to cool it. The wet and dry bulb sensors are linked to another bridge
circuit differential operational amplifier. On one side of the bridge the
amplifier controls dehumidification of the air, using the same cold brine
that cools the air temperature. On the other side of the bridge circuit
the air is humidified. The analytical sensors are connected to strip chart
recorders and the output voltage is converted to resistance. The resistance,
in turn, can be related to temperature or relative humidity. Although the
long term precision of the chamber is 50 + 3% for relative humidity and
25+0.5 C for temperature, the daily variation is better than +_ 1% for the
former. In addition, appropriate corrections can be made easily by knowing
the rate of change of filter weight with relative humidity.
Before tare weighing, all filters, including two blanks, are equilibrat-
ed inside the chamber for 24 hr. The two blanks are weighed first followed
by the sample filters. The two blank filters are reweighed. The average
change between the first and second weighings of the two filter blanks is
applied incrementally to the sample filters. After sampling, the gross weight
determinations are made again after 24 hr equilibration in the chamber. The
blank filters are reweighed first, followed by the sample filters and a fur-
ther reweighing of the two blanks; the same corrections as above are applied.
Also, the average difference between the tare blank weight and the gross blank
weight is noted. All samples subsequently are normalized to tare conditions
when it is possible to directly subtract tare from gross sample weights.
Repeated measurements have shown that air particulate matter can be weighed
with greater precision than 1% (+ 0.1 mg) for glass fiber filters and 7% for
Whatman 41 cellulose filters.
1-16
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PART II
LEAD DEPOSITION TO THE WATERSHED
by
T, R, STOLZENBURG
A, W, ANDREN
ll-i
-------
ABSTRACT
The wet deposition of lead to the Watershed is calculated directly from
measurements in rain. Dry deposition from long range sources is distin-
guished from lead originating within the Watershed. Most atmospherically-
derived lead deposited in the Watershed does not reach Lake Michigan.
Il-ii
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CONTENTS - PART II
Title Page Il-i
Abstract Il-ii
Contents Il-iii
II-l. Introduction II-l
II-2. Conclusions II-2
II-3. Calculation and Discussion II-3
Deposition II-3
Delivery H-4
References II-5
Il-iii
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II-l. INTRODUCTION
Suspended dust concentrations in themselves are important for human
health reasons. However, deposition calcualtions must be made in order to
assess the impact of airborne pollutants on water quality. Atmopsheric lead
is removed from the atmosphere to the Watershed through wet and dry processes.
Both modes of transport to the surface must be accounted for when calculating
total flux.
Deposition by wet processes can be measured directly using wet only
samplers. Deposition by dry processes is difficult to measure directly owing
to the wide variety of natural impaction surfaces in the environment, i.e.,
water, grass, concrete, etc. Several investigators have made reasonable
estimates of lead flux to the surface (1,2) for Lake Michigan and rural
Illinois, respectively. In both studies, it is evident that most of the lead
originated from distant sources even though automotive exhaust represents a
large source of lead deposited in the watershed.
II-l
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II-2. CONCLUSIONS
Atmospheric lead is deposited on the Menomonee River Watershed by wet and
dry processes from distant sources at the rate of 1.4 x 10 kg/yr or 400 g/ha-
yr. Of this amount, less than half reaches Lake Michigan.
Automotive exhaust from vehicular traffic in the Watershed contributes an
additional 7.9 x 10"* kg/yr of lead to the Watershed. The delivery ratio of
lead to the river is probably quite high because the natural removal processes
(filtration, coagulation, adsorption and biological uptake) are bypassed.
II-2
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II-3. CALCULATION AND DISCUSSION
Deposition
Of the metals and nutrients studied only lead and phosphorus have
significant atmospheric inputs relative to weathering and point sources at
the land surface. Phosphorus deposition is dealt with later.
The rain sampling program undertaken permits measurement of lead concen-
trations and hence direct calculation of input of lead by precipitation.
Based on a mean concentration of 30 yg/L and an annual precipitation total of
76.2 cm, lead loading to the Watershed by precipitation is 230 g/ha-yr.
Dry deposition is a function of the suspended concentration and the
deposition velocity of particles containing lead. Based on current investi-
gations and those of Hudson et al (2) and Andren et al (1), the dry deposi-
tion rate for lead is approximately 180 g/ha-yr. Overall, lead enters the
Watershed through the atmosphere at a rate of approximately 400 g/ha-yr or
1.4 x 10* kg/yr.
However, the dry deposition estimates represent only lead from long range
transport (i.e. based on deposition calculations for Lake Michigan). Much of
the measured lead in precipitation falls into this same category. Hence the
lead input figure of 1.4 x 10"* kg/yr (400 g/ha-yr) includes only that lead
originating from outside the Watershed.
Clearly there exists a large near-ground source of lead from vehicular
traffic in the Watershed. The investigations of Habibi (3,4) demonstrate
that most of the lead from automobile exhausts is deposited within a few
meters of the highway. Therefore, the additional pertinent calculations are
the amount of lead emitted and remaining within the Watershed. The methodology
described by Huntzicker et al (5) was used for these calculations and the
reader is referred to this work for more details.
SEWRPC has estimated that approximately 490 x 106 L/yr of gasoline is
consumed in the Menomonee River Watershed. A telephone poll of service
stations by members of the Water Chemistry Program indicates that the ratio of
leaded to non-leaded gasoline sold in 1978 is approximately 40:60. Huntzicker
et al (5) indicate that leaded gasolines contain an average of 0.56 g/L lead
and that the non-leaded amount is 0.01 g/L. This yields an average consumption
rate of 110 Tonnes/yr in the Menomonee River Watershed.
The model of Huntzicker et al (5) indicates that the fate of this lead
is as follows: a. 27.5 Tonnes/yr remains in the cars (in the oil, oil filter
II-3
-------
and exhaust system), b. 82.5 Tonnes/yr is exhausted to the atmosphere, c. of
this 82.5 Tonnes/yr, 47 Tonnes/yr is deposited as large particulate matter
within a few meters of the vehicles (near deposition), d. the remaining lead
(35 Tonnes/yr) is available for long distance transport.
If one assumes a mass mean emission height of 1 to 5 m and an average
windspeed of 7.5 km/hr 50%, i.e., 17.5 Tonnes Pb/yr would deposit within 1
to 8 km of the vehicles indicating that < 17.5 Tonnes/yr (21%) of the 82.5
Tonnes/yr emitted could leave the near vicinity of the Watershed.
Finally, a total lead deposition to the Watershed, i.e. lead produced
outside added to that produced inside the Watershed can be calculated. From
the previous sections it follows that 14 + _> 65 Tonnes/yr or _> 79 Tonnes Pb/yr
deposit on the Watershed.
Delivery
From the investigations of Benninger et al (6) it is evident that lead
is sequestered by soil and particulate matter in the river. Hence, significant
dissolved concentrations do not occur in river water. Atmospherically-derived
lead would not be expected to reach the river unless it was deposited on an
impervious surface. Approximately 20% of the Watershed is impervious (roads,
roofs, etc.). During the winter months, when the ground is snow covered and
frozen, the extent of surface imperviousness is taken to be 100%. Using these
assumptions it can be shown that 40% of the deposited lead from distant sources
reaches the river. This is probably an overestimation since many impervious
surfaces are not connected to channels. Further, since most of the lead will
associate with particulate matter in the river, a very small fraction of the
atmospheric lead reaches Lake Michigan.
However, locally high concentrations of lead probably occur. Most of the
lead emitted in the Watershed is deposited on or near impervious surfaces so
that lead concentrations in street runoff can be extremely high.
II-4
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REFERENCES - II
1. Andren, A. W., S. Eisenreich, F. Elder, T. Murphy, M. Sanderson and R. J.
Vet. Atmospheric Loading to Great Lakes. Special Report to International
Joint Commission, Windsor, Ontario, Canada, 1978. 17 pp.
2. Hudson, J. L., J. J. Stukel and R. L. Solomon. Measurement of the Ambient
Lead Concentration in the Vicinity of Urbana-Champaign, Illinois.
Atmospheric Environment 9:1000-1006, 1975.
3. Habibi, K. Characterization of Particulate Lead in Vehicle Exhaust—
Experimental Techniques. Environ. Sci. Technol. 4(3):239-248, 1970.
4. Habibi, K. Characterization of Particulate Material in Vehicle Exhaust.
Environ. Sci. Technol. 7(3):223-234, 1973.
5. Huntzicker, J. J., S. K. Friedlander and C. I. Davidson. Material
Balance for Automobile-Emitted Lead in Los Angeles Basin. Environ. Sci.
Technol. 9(5):448-457, 1975.
6. Benninger, L. K., D. M. Lewis and K. K. Turekian. The Use of Natural
Pb-210 as a Heavy Metal Tracer in the River-Estuarine System. In: Marine
Chemistry in the Coastal Environment, T. M. Church, ed. Am. Chem. Soc.,
Washington, B.C., Am. Chem. Soc. Symp. Ser. 18, 1975, pp. 201-210.
II-5
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PART III
LEAD DEPOSITION TO LAKE MICHIGAN
by
T, R, STOLZENBURG
A, W, ANDREN
Ill-i
-------
ABSTRACT
A model is used to determine lead flux to Lake Michigan by dry processes
given certain average meteorological conditions and a suspended lead concen-
tration of 0.5 yg/m3.
Ill-ii
-------
CONTENTS - PART III
Title Page Ill-i
Abstract Ill-ii
Contents III-iii
Table Ill-iv
III-l. Introduction III-l
III-2. Conclusions III-2
III-3. Calculations and Discussion III-3
References III-7
III-iii
-------
TABLE
Number Page
III-l Dry deposition of atmospheric lead to Lake Michigan from
Milwaukee, Wisconsin, November 1, 1976 to April 28, 1977 . . . m_5
Ill-iv
-------
III-l. INTRODUCTION
Although only a small portion of the lead deposited on the Watershed from
the atmosphere reaches Lake Michigan, particulate lead from automotive exhausts
can enter the lake directly from the atmosphere. It is possible to treat
metropolitan Milwaukee as an area source for lead and use a model such as the
one presented by Gatz (1) to determine lead inputs to the lake given certain
average meteorological conditions. These calculations were made in an effort
to estimate the lead contribution from air over Milwaukee to that of total
lake loading.
III-l
-------
III-2. CONCLUSIONS
Model calculations suggest that, during the cold months (November to
April), approximately 40 Tonnes of lead are deposited on Lake Michigan from
Milwaukee by dry processes. Based on other estimates in the literature, this
value represents 3% of the total atmospheric lead entering the lake each year.
III-2
-------
III-3. CALCULATIONS AND DISCUSSION
The Menomonee River Watershed acts as a source of atmospheric lead since
it has a relatively higher traffic density than the surrounding countryside.
Prevailing westerly-winds carry lead aerosols over Lake Michigan. Lead
aerosols have been shown to have a mass mean diameter of 0.4 ym (2). Data
from Cawse (3) as compiled by Gatz (1) , indicate that particles of this size
have an average deposition velocity of 0.003 m/sec.
Thus, it is possible to estimate the amount of lead deposited by impaction
in the lake from the area source designated as metropolitan Milwaukee. Gatz
(1) introduced a mathematical model which can be used to calculate the pollutant
contribution from the urbanized south shore of Lake Michigan. A modified ver-
sion of this method has been developed here and a discussion of the input
parameters to the model follows:
Deposition rate for a given particle is given by the general equation:
D - C • V , Eq. (1)
d
where D is deposition rate in g/m2-sec
C is concentration of element near surface
in g/m3 and
V, is deposition velocity in m/sec
The value to be determined is deposition rate. In this case, C is a
variable which decreases with downwind distance from the area source (Milwaukee) ,
as turbulence disperses the aerosol laterally. The average deposition velocity
for lead will be taken as 0.003 m/sec in this calculation, although it undoubt-
edly varies as a function of wind speed.
The lake surface was divided arbitrarily into 5 pie-shaped sectors radiating
out from Milwaukee. For each sector, the change in Cfl with downwind distance
from the city (xfi) is described by the equation:
2TT(xfi + 2TT)
_S_ -
where Q is source strength in g/sec,
L is mixing height in m,
u_ is wind speed for sector 9 in m/sec,
III-3
-------
y is diameter of area source in m and
XQ is downwind distance to far shore for sector 0 in m.
o
The area source diameter is taken to be 20,000 m and the mixing height as
850 m (4). From a mid-city station the averages of the inverse hourly wind
speeds for each sector have been calculated. Downwind distance is a simple
measurement and source strength, Q, is obtained from:
Q - CQuLy Eq. (3)
where C is mean concentration in air passing through
a vertical plane at the downwind boundary of the
source in g/m3 and
u is the mean wind speed m/sec.
An appropriate value for C is 0.5 x 10~6 g/m3 (5). The mean wind speed
for all wind directions was calculated to be 7.5 km/hr from the same mid-city
station.
To determine deposition for a particular sector, Q is calculated, followed
by substitution of Eq. (2) into Eq. (1). An integration across the 5° arc and
along XQ produces a simplified formula:
o
Q v, x0
Finally, deposition for the whole lake consists of a summation of all 33
sectors multiplied by the frequency of wind in each sector (fQ). Thus,
H
33
£ DQf0 = total lake deposition. Eq. (5)
1 DO
The calculation has been performed for the winter months from November 1976
to April 1977 (Table III-l) . This season is defined by the condition that air
over the lake surface is warmer than air over the land. The reverse condition
resists aerosol deposition since little vertical mixing can occur over the
lake surface. Gatz (1) suggests that summertime deposition is minimal. Hence,
wind and mixing height values used in these calculations are averages for the
cold months.
As the aerosol is transported to the far shore, continuous deposition
depletes the suspended load. Therefore CA varies accordingly but is not
accounted for by this model. A simple calculation shows that, in most cases,
only a small fraction of the suspended load is lost (^ 8%). However, when wind
speed is low and a long fetch is present, depletion can be significant. The
hourly wind data suggests that such episodes occurred and deposition was over-
estimated. However, the low average depletion indicates that such cases were
rare.
It is interesting to compare values in Table III-l with other deposition
III-4
-------
Table III-l. Dry deposition of atmospheric lead
to Lake Michigan from Milwaukee,
Wisconsin, November 1, 1976 to
April 28, 1977
Portion of Lake Pb, Tonnes
Nor them-two-thirds 54
Southern-one-third 69
Total 123
II I-5
-------
figures published in the literature. Andren et al (6) estimate that 1300
Tonnes of lead annually enter Lake Michigan through the atmospheric route.
The calculation here (excluding wet deposition) suggests that about 9% of that
total originates from the urban area around Milwaukee. The total contribution
by Milwaukee may easily double if rain and snow were considered. Hence the
total contribution from Milwaukee may be as high as 18%.
Gatz (1) estimated that 200 Tonnes of lead enters the lake annually from
Chicago and northwest Indiana by wet and dry processes. At first glance this
result appears inconsistent since the southern shore represents a much larger
source strength than Milwaukee. However, the larger pollutant load is balanc-
ed by a lower frequency of offshore winds. Overall, Chicago and northwest
Indiana represent a source strength almost five times as large as metropolitan
Milwaukee, and yet the south shore contributes slightly less to Lake Michigan
via the atmosphere.
III-6
-------
REFERENCES - III
1. Gatz, D. F. Pollutant Aerosol Deposition into Southern Lake Michigan.
Water, Air and Soil Pollution 5:239-251, 1975,
2. Rahn, K. The Chemical Composition of the Atmospheric Aerosol. Tech.
Report, University of Rhode Island, Kingson, 1976.
3. Cawse, P. A. Report AERE-7769 Environmental and Medical Sciences Division,
United Kingdom Atomic Energy Authority, Harwell, Oxfordshire. 1974.
4. Sievering, H. Dry Deposition Loading of Lake Michigan by Air-borne
Particulate Matter. Water, Air and Soil Pollution 5:309-318, 1976
5. Schmidt, J. A. Selected Metals in Air Particulates Over Lake Michigan.
University of Wisconsin-Madison, M.S. Thesis, 1977.
6. Andren, A. W., S. Eisenreich, F. Elder, T. Murphy, M. Sanderson and R. J.
Vet. Atmospheric Loading to Great Lakes. Special Report to International
Joint Commission, Windsor, Ontario, Canada, 1978. 17 pp.
III-7
-------
PART IV
TOTAL PHOSPHORUS LOADING TO THE WATERSHED
by
T, R, STOLZENBURG
A, W, ANDREN
IV-i
-------
ABSTRACT
Wet deposition of phosphorus to the Watershed was calculated directly from
measurements of phosphorus in rain. Dry deposition is calculated from an
average suspended P concentration of 55 yg/m3 and a deposition velocity in the
literature. Suspended P concentrations show marked seasonal trends at all
stations.
IV-ii
-------
CONTENTS - IV
Title Page IV-i
Abstract IV-ii
Contents IV-iii
Figures IV-iv
IV-1. Introduction IV-1
IV-2. Conclusions IV-2
IV-3. Methods and Procedures IV-3
IV-4. Results and Discussion IV-4
Rain Samples IV-4
Wet Deposition IV-4
Total Suspended Particulate Phosphorus IV-5
Dry Deposition IV-17
References IV-18
IV-iii
-------
FIGURES - IV
Number Page
IV-1 Total suspended particulate phosphorus (TSSP) concentration
at Falk Corporation site IV-7
IV-2 Total suspended particulate phosphorus (TSSP) concentration
at 70th Street site IV-8
IV-3 Total suspended particulate phosphorus (TSSP) concentration
at Appleton Avenue site IV-9
IV-4 Total suspended particulate phosphorus (TSSP) concentration
at River Lane site IV-10
IV-5 Total suspended particulate phosphorus (TSSP) concentration
at Donges Bay Road site IV-11
IV-6 Mass concentration of phosphorus at Falk Corporation site . . IV-12
IV-7 Mass concentration of phosphorus at 70th Street site IV-13
IV-8 Mass concentration of phosphorus at Appleton Avenue site . . . IV-14
IV-9 Mass concentration of phosphorus at River Lane site IV-15
IV-10 Mass concentration of phosphorus at Donges Bay Road site . . . IV-16
IV-iv
-------
IV-1. INTRODUCTION
One of the key loading parameters designated for intensive study by the
International Joint Commission was nutrients. Murphy and Doskey (1) concluded
that 18% of the total phosphorus budget to Lake Michigan enters through pre-
cipitation directly on the lake surface. In a Lake Huron study, Delumyea and
Petel (2) determined that dry deposition of phosphorus was probably of equal
magnitude when compared to rain. A more recent study using bulk precipitation
collectors showed that—in 1976 (a dry year)—16% of the total phosphorus
entered Lake Michigan through the atmosphere (3). It is evident that as
sewage treatment facilities implement nutrient removal techniques, atmospheric
input of phosphorus to Lake Michigan will become the major source of this
nutrient. Both Murphy and Doskey (1) and Delumyea and Petel (2) indicated
that 40 to 50% of the incoming phosphorus is potentially available to the
biota.
Having identified phosphorus as a critical parameter in terms of atmos-
pheric transport, measurements were made on rain and suspended particulate
air samples in the Menomonee River Watershed to determine the magnitude of
deposition relative to loadings at the surface.
IV-1
-------
IV-2. CONCLUSIONS
Phosphorus concentrations in rain vary widely, from undetectable levels
to well over 100 Ug/L. A median value is in the range of 10 to 20 yg/L.
Annual input of phosphorus to the Watershed by all forms of precipitation is
at least 75 g/ha-yr.
Particulate phosphorus accounts for an average of 0.1% of the total
suspended mass. The fraction is lowest in winter and highest in late summer.
It is concluded that much of the phosphorus in air originates from continental
dust.
Dry deposition of phosphorus is calculated to be 108 g/ha-yr. The sum of
dry and wet deposition is somewhat lower than previous estimates.
IV-2
-------
IV-3. METHODS AND PROCEDURES
Rain and air sample collection and storage has been described previously.
Immediate acidification of rain samples for trace metal analysis precluded
measurement of available phosphorus. Only total phosphorus was analyzed on
all samples.
Approximately 10% of the filter pad from air samples was digested in a
1:5 (v:v) mixture of HaSOit and HNOs by the procedure described in American
Public Health Assoc. (4). Rain samples were digested in an autoclave by a
persulfate-sulfuric acid method (5). Color development for both types of
samples involved the molybdate complex reduced to a blue color by ascorbic
acid (5).
IV-3
-------
IV-4. RESULTS AND DISCUSSION
Rain
Phosphorus levels in rain varied widely. The range of concentration was
from undetectable levels (< 5 yg/L) to over 100 yg/L. A few extreme values
tend to exaggerate the calculated means. Because of this it was thought that
a median was a more appropriate expression of the average value. An overall
median for all samples and stations is 10 yg/L.
The question of which station exhibits the highest (or lowest) average
phosphorus concentration does not have a clear-cut answer. For comparison
purposes it is imperative to include only those events for which values exist
for all stations, since P concentrations varied widely for different events.
However, quite frequently one or more stations was inoperative for a particu-
lar event. This leaves very few events from which overall averages can be
compared. Hence, the median concentrations from pairs of stations were com-
pared in order to rank land use areas. The heavy industrial site (Falk
Corporation) exhibited the lowest average phosphorus concentration. Appleton
Avenue, representing a transition rural-urban station, had the highest median
concentration relative to other land use areas. The rural, mixed rural, and
residential areas were somewhere in between. One must immediately temper this
conclusion by noting that phosphorus concentrations are probably a function of
rainfall amount. The overall relationship also may show a seasonal dependence.
Wet Deposition
Loading calculations show that the minimum phosphorus loading does not
occur at the Falk Corporation site since rain amounts tend to be heavier in
the industrial valley. In addition, the maximum loading of phosphorus does
not occur at Appleton Avenue since less rain was collected here than at most
of the other stations for the events sampled. It appears that heavier rains
have slightly lower phosphorus concentrations. Furthermore, it has been
found that the concentrations of many trace constituents decrease during a
rain event (6). Hence, loadings do not vary directly with amount of preci-
pitation.
It is inappropriate to report phosphorus loadings by precipitation for
single events since rainfall amounts vary dramatically across the Watershed.
The sampler density was 1 per 5700 hectares, not nearly adequate enought to
accurately measure event loading. However, yearly averages can be determined
IV-4
-------
with more confidence. For an average phosphorus concentration of 10 yg/L
and 51 cm rain, the annual input by rain would be 1738 kg or 51 g/ha.
Phosphorus content of snow was not measured, but is thought to contain
as high a concentration of phosphorus, in terms of equivalent water volume,
as rain (7). Since an average of 25 more centimeters equivalent water falls
as snow, one would expect this to add at least 25 g/ha-yr phosphorus to the
Watershed.
Another method for calculating total phosphorus deposition by rain is to
sum the products of phosphorus concentrations and rain volumes for individual
events through an entire year. Unfortunately, at no station is there a
complete record. At the Falk Corporation site, where most events were
collected and measured from 4/26/77 to 10/26/77, total phosphorus deposition
was determined to be 46 g/ha. This is for a collected rain amount of 43 cm.
At 70th St. (up to 10/20/77) the individual loadings added up to 43 g/ha-yr
for a rain amount of 28 cm. Even though 70th St. received 32% less rain over
the whole interval, the phosphorus loading dropped by only 7%. For comparative
purposes, Murphy (8), measured phosphorus input at 250 g/ha-yr for a total
rainfall of 71 cm in Chicago. Average total P concentrations in rain were
2.5 to 3 times higher than in this study.
The above measurements indicate that an average of 10 yg/L phosphorus
in rain may be a little low for calculating yearly input. If a precipitation
weighted average concentration is used (1), the values are 11 yg/L at the
Falk site and 15 yg/L at 70th St. These numbers represent the phosphorus
concentrations if all rain samples were combined. These values compare
favorably with the precipitation weighted concentration of 20 yg/L reported
for Illinois Beach State Park, 43 miles south of Milwaukee (1). Rain samples
in the Murphy and Doskey (1) study were contaminated to a small degree by dry
fallout.
For an average phosphorus in rain of 15 yg/L, and with rainfall amounts
measured at 70th St., the phosphorus input is estimated for the spring seasons
of 1975, 1976 and 1977. Rainfall totaled 18.5, 40.1 and 14.5 cm, respectively,
for the spring seasons at this station. Hence, phosphorus deposition by rain
was approximately 28 g/ha, 60 g/ha and 22 g/ha for these spring seasons.
Total Suspended Particulate Phosphorus
Measurements of total suspended particulate phosphorus (TSPP) were made
with a greater degree of confidence because final sample solutions contained
higher amounts of this material. The geometric mean concentration for all
samples was 55 yg/m3. The geometric mean was 1.1 mg/g, i.e., 0.1% of the
total aerosol mass was phosphorus.
The ranking of land use areas by suspended phosphorus concentrations is
much more clear-cut than by concentrations in rain. The heavy industrial
site at Falk Corporation exhibited the highest suspended phosphorus load with
an 86% frequency when the sampler was in operation. This trend is not
unexpected, since for 93% of the time, the Falk Corporation site shows the
IV-5
-------
highest total suspended mass concentration. The linear correlation coef-
ficent between total suspended mass and total suspended phosphorus being
0.878.
Ranking by phosphorus concentrations occurs in the following order 29%
of the time during the sampling periods when all five stations were operat-
ing: Falk Corporation > 70th Street > Appleton Avenue > River Lane >
Donges Bay Rd. This ranking is also the one most frequently observed for
total suspended particulates. A major deviation from the above trend is
the occurrence of relatively lower values at 70th Street compared to either
Appleton Avenue or River Lane. The frequency of this observation is 43% of
the samples.
Figures IV-1 to IV-5 exhibit the same chronological trend of TSPP for
each station. Invariably, each plot indicates a relatively low concentra-
tion of suspended phosphorus during the period of early December, 1976
through mid-February, 1977. This strongly suggests that a major fraction
of the suspended particulate phosphorus arises from continental dust, an
aerosol source which is snow covered and frozen during this period.
Figure IV-6 to IV-10 show the mass concentration of phosphorus over
time for each station; early February, 1977 undoubtedly marks a minimum.
The trend appears to be upward through mid-August, and is especially
evident in Figs. 1V-9 and IV-10. Phosphorus accounts for an increasing
percentage of the TSP as the year wears on, although at most, this value is
0.25%.
What is not immediately evident from the graphs, is the relationship
between stations. The heavy industrial site generally exhibits a higher
phosphorus fraction than either the mixed-rural or rural sites. This trend
is reversed from mid-July through mid-August, when heavy rains occurred dur-
ing or just preceding sampling periods. It is proposed therefore that
suspendable street dust has a relatively high phosphorus content. This
potential aerosol is either washed into the sewers or prevented from being
suspended by heavy rains.
Sartor et al (9) found that street dust in the fraction < 43 ym
particle size contained 7.5 mg/g P. This amount is 7.5 times greater than
the average phosphorus concentration in aerosols over the Menomonee River
Watershed. In general, the phosphorus fraction in bulk soil also possesses
a lower concentration than street dust. Buckman and Brady (10) report a
range of 0.1 to 2 mg/g and Murphy (8) estimates the soil concentration at
0.42 mg/g. However, one expects to find higher concentrations for fertiliz-
ed, agricultural soils and in certain industrial emmissions, e.g., from
iron and steel manufacturing (8). The suspended solids in the Menomonee
River, which include urban and agricultural runoff, contain about 1.7 mg/g
P (11). This value is calculated from the total loadings to Lake Michigan
for 1975 and 1976 from both suspended solids and particulate phosphorus.
IV-6
-------
140
130
120-
_S 110-
80
c
to 100
M
o
90-|
CO
O-i
T3
0)
•a
13
a)
a.
o
E-i
80-
70-
60-
50-
40-
30-
20-
9/1/76
T
T
T
TTT
12/1/76
Fig. IV-l.
Ml1
3/31/77
Date
Total phosphorus concentration at Falk Corporation site.
rrr
i—r~p—r
8/31/77
-------
oo
9/1/76 10/1/76
Fig. IV-2.
3/31/77
Date
Total phosphorus concentration
8/31/77
at 70£h
-------
140
vo
17-3. Total Phosphorus
8/31/77
concentration at Appleton AvemM
-------
OT-AI
Total Suspended Particulate Phosphorus, ng/m3
-------
60
c
H
id
P-i
73
01
•a
S
P.
o
H
100-
90-
80-
70-
60-
50-
40-
30-
I I I
I I I I I—r
9/1/76
2/1/77
6/1/77
8/31/77
Date
Fig. IV-5. Total phosphorus concentration at Donges Bay Road site.
-------
f
!-•
to
in
o
fi
CX
O
4-1
ea
rH
O
•H
n)
PH
S
O,
to
3.0
2.0 -
1.0
0.9
0.8
0.7
0.6 -
0.5 -
0.4
9/1/76
12/1/76
I I
3/31/77
Date
Ml 'Ml ' I ' I ' Ml
8/31/77
Fig. IV-6. Mass concentration of phosphorus at Falk Corporation site.
-------
f
(->
10
to
1-1
o
.a
a,
CO
PH
0)
4J
id
rH
3
O
•H
4-1
M
id
p-l
13
o
H
3.0 -
2.0 -
1.0
0.9
0.8
0.7
0.6
0.5 -
0.4 -
0.3
9/1/76
i r
10/1/76
3/31/77
Date
I'M
8/31/77
Fig. IV-7. Mass concentration of phosphorus at 70th Street site.
-------
3.0 -1
CO
2
I
CO
o
0)
4J
t8
r-l
O
•H
4-)
tfl
P-l
T3
CU
fi
0)
fX
CO
3
o
H
2.0 -
1.0
0.9
0.8
0.7 -
0.6 -
0.5
0.4 -
0.3
9/1/76
T I
10/28/76
II I
3/31/77
Date
8/31/77
Fig. IV-8. Mass concentration of phosphorus at Appleton Avenue site.
-------
Ln
00
60
6
to
lH
O
o.
CO
O
3
•H
4J
t-l
(It
13
CU
T3
a
-------
3.0 -1
2
CTi
2.0
to
3
O
0.
IB
o
P-.
£ 1.0
0.9
0.8
-------
Dry Deposition
Atmospheric loadings by dry deposition can be estimated from a know-
ledge of the suspended particulate phosphorus concentration and the size
range with which most of the phosphorus mass is associated. The mass-
particle size function of phosphorus is bimodal, corresponding to the two
major emission sources, soil dust and combustion processes (2,8).
Delumyea and Petel (2) made detailed size distribution measurements
around Lake Huron. The mass mean diameter for phosphorus containing
particles was determined to be 1 ym. The calculated deposition velocity
from the compiled data of Gatz (12) would approximate 0.5 cm/sec. The field
data from the Lake Huron study indicated a deposition velocity of 0.6 cm/sec.
The average phosphorus concentration over the Menomonee River Watershed was
estimated at 55 yg/m3. Thus, deposition for the area can be calculated
using the expression described in Part III.
D - Vd • C Eq. (1)
Dry deposition rate to the Menomonee River Watershed is thus 108 g/ha-yr or
3.46 x 103 kg/yr for the entire area. Phosphorus concentrations and
deposition rate vary seasonally. It is thus evident that the above values
should only be considered approximate.
Bulk precipitation samplers in Milwaukee indicated an average loading
rate of phosphorus at 372 g/ha-yr (3). This value is somewhat greater than
the sum of loading estimates made in this study for rain, snow and dry
deposition, i.e. 50 + 25 + 108 g/ha-yr. Using 15 yg/L as the best estimate
of the average phosphorus concentration in precipitation, the total loading
estimate for the Menomonee River Watershed would be increased to 220 g/ha-yr.
Intuitively, one might speculate that the virtual deposition surface
formed by the open end of a cylindrical bulk collector is an understimate of
the actual surface area available for deposition by impaction. Hence, further
investigations may reveal that bulk collectors overestimate the dry deposition
rate.
IV-17
-------
REFERENCES - IV
1. Murphy, T. J. and P. B. Doskey. Inputs of Phosphorus from Precipitation
to Lake Michigan. U.S. Environmental Protection Agency Report No. EPA-
600/3-75-005, Grosse He, Michigan. 1975.
2. Delumyea, R. G. and R. L. Petel. Atmospheric Inputs of Phosphorus to
Southern Lake Huron. U.S. Environmental Protection Agency Report No. EPA-
600/3-75-038, Ann Arbor, Michigan. 1977.
3. Eisenreich, S. J., P. J. Emmling andA. M. Beeton. Atmospheric Loading of
Phosphorus and Other Chemicals to Lake Michigan. J. Great Lakes Res.
3(3-4):291-304, 1977.
4. American Public Health Assoc. Standard Methods for Examination of Water
and Wastewater, 13th ed. APHA, Washington, D.C. 1971.
5. U.S. Environmental Protection Agency. Methods for Chemical Analysis of
Water and Wastes. U.S. Environmental Protection Agency Report No. EPA-
625/6-74-003, Environmental Research Center, Cincinnati. Ohio. 1976
(Revised).
6. Ronneau, C., J. Cara, J. L. Navarre and P. Priest. An Automatic Sequen-
tial Rain Sampler. Water, Air and Soil Pollution 9:171-176, 1978.
7. Shiomi, M. T. and K. W. Kuntz. Great Lakes Precipitation Chemistry:
Part 1, Lake Ontario Basin. Proc. 16th Conf. on Great Lakes Research,
International Assoc. of Great Lakes Research, pp. 581-602. 1973.
8. Murphy, T. J.. Sources of Phosphorus Inputs from the Atmosphere and
Their Significance to Oligotrophic Lakes. Water Resources Center,
University of Illinois, Urbana, Research Report No. 92. 1974.
9. Sartor, J. D., G. B. Boyd and F. J. Agardi. Water Pollution Aspects of
Street Surface Contaminants. J. Water Pollution Control Fed. 46:458-467,
1974.
10. Buckman, H. 0. and N. C. Brady. The Nature and Properties of Soils.
Collier-Macmillan Ltd., London, 1971.
11. Sonzogni, W. C., T. J. Monteith, W. N. Back and V. G. Hughes. United
States Great Lakes Tributary Loadings. PLUARG Technical Report to Task
D, Ann Arbor, Michigan. 1978.
12. Gatz, D. T. Pollutant Aerosol Deposition into Southern Lake Michigan.
Water, Air and Soil Pollution 5:239-251, 1975.
IV-18
-------
PART V
EVALUATION OF SOURCES
by
T, R, STOLZENBURG
A, W, ANDREN
V-i
-------
ABSTRACT
A model utilizing multivariate regression analysis is used to predict
major emission sources contributing to the suspended dust in the
Menomonee River airshed. This source reconcilation model is sensitive to
changes in ambient aerosol composition caused by inputs of various
emission sources.
V-ii
-------
CONTENTS-PART V
Title Page V-i
Abstract V-ii
Contents » .......... V-iii
Tables V-iv
V-l. Introduction V-l
V-2. Conclusions V-2
V-3. Evaluation of Sources V-3
References • • «• V-l 8
Appendix
V-A. Soil Analyses V-l9
V-iii
-------
TABLES
Number Page
II .. —I Ml CJ
V-l Source profiles V-7
V-2 Fit heavy industrial ambient aerosol with 8 emission
sources V-9
V-3 Fit heavy industrial ambient aerosol with 8 modified
emission sources V-10
V-4 Fit heavy industrial ambient aerosol with 7 modified
emission sources V-l2
V-5 Fit heavy industrial ambient aerosol with 6 emission
sources V-l 3
V-6 Fit rural ambient aerosol with 7 emission sources V-14
V-7 Fit rural ambient aerosol with 7 emission sources weight
Cu by 1/10 V-15
V-8 Fit rural, winter ambient aerosol with 7 emission sources... V-17
V-A-1 Metal analyses of agricultural soil samples from the
Menomonee River Watershed V-19
V-A-2 lletal analyses of construction site soil samples from the
Menomonee River Watershed V-20
V-iv
-------
V-l. INTRODUCTION
Government regulatory agencies are coming under increasing pressure to
provide evidence that those industries being regulated can be held responsible
for the levels of ambient aerosols measured. For this reason, the development
of accurate and convenient source reconciliation methods is imperative.
The method presented here employs routine bulk analysis of ambient
aerosols by atomic absorption spectrometry. Given the elemental composition
of emission sources and ambient aerosols, successful source reconciliation is
achievable by multivariate regression analysis.
V-l
-------
V-2. CONCLUSIONS
The source reconciliation model presented here is generally applicable
at any atmospheric monitoring site. Accurate ambient elemental measurements
needed for input parameters to the computer program are routinely attainable
by high volume air sampling and atomic absorption analysis.
Results of this study indicate the model is sensitive to changes in
ambient aerosol composition caused by the relative inputs of various
emission sources. The composition of ambient aerosol in a heavy industrial
land use clearly reflects contributions of local emission sources. The
relative contribution of these anthropogenic emission sources decreases
dramatically over a distance of 15 km in a direction generally perpendicular
to the prevailing wind.
V-2
-------
V-3. EVALUATION OF SOURCES
Multivariate regression analysis was used to determine the
major emission sources contributing to the observed suspended dust in
the Menomonee River airshed. The method of Mayrsohn and Crabtree (1)
is presented below. A slight modification was introduced to improve
the fitting qualities of the model.
Ideally, one would like to know the actual fraction of measured
aerosol contributed by each source. This fraction is known as a
source coefficient. The mathematical expression of the source
coefficient is given in Eq. (1).
n
mx = Z c (a )(p ) Eq. (1)
• j AJ AJ
where
c-s is source coefficient; fraction of aerosol contributed by source j
px-j is fraction of source j that is element x
m is fraction of aerosol that is element x
OL..S is coefficient of fractionation
XJ
For a given element, both particle size distribution and distance
travelled influence a . . It is impossible to assign a value to ctxj , so
it is set equal to 1. An objection to this would be legitimate, but
at present no mathematical method has been developed to describe
the fractionation process. The fraction, mx, of the aerosol that is
element x is a measured value. One must either measure pxj or take a
value from the literature. The value to be calculated is c-.
A simple case occurs when the number of elements equals the number
of sources. Three equations are solved simultaneously for three
unknowns. For instance:
Example 1. Elements - x,y,z Sources - j,k,l
C-(PXJ) + ck(pxk) +
ck(pyk) + ci(pyl) = my
ck(pzk) + £l(Pzl) = mz
Normally the elements considered are not present in significant
quantities in all the sources. To obtain a source coefficient for
a source, a tracer element is assigned. This element would have no
other major sources (e.g., lead in automobile exhaust). Assuming
that all lead in aerosol samples originates from leaded gasoline,
the source coefficient calculation is simplified. A single equation
is needed for the determination in the following example.
V-3
-------
Example 2. pPb,ls. ' PPb,l ' PPb,o ' '" are ne§1:Lgible
therefore, ^ = PPb,auto (cauto)
Using typical values: p__ = 0.40
Pb,auto
mpb = 0.003
°auto mPb ' PPb,auto
= 0.003 T 0.40 = 0.0075
With slight modifications the calculations can still be handled
readily. For instance, lead may have two sources, one of which is
fuel oil combustion, the other auto exhaust. However, if a suitable
tracer can be found for the fuel oil source, both source coefficients
can be determined.
Example 3.
Step A. Vanadium is known to be a good tracer for fuel oil.
Cfuel oil = "V ^ PV,fuel oil
For typical values: pTT - , ., = 2.5
V,fuel oil
"V
c,. , ., = 0.04 v 2.5 = 0.016
fuel oil
= 0.04
Step B. With the source coefficient for fuel oil, one can
determine the amount of lead in the measured aerosol
contributed by fuel oil combustion:
mPb,fuel oil = PPb,fuel oil (cfuel oil5
= 0.04 (0.016)
m_,, ,. n . = 0.00064
Pb,fuel oil
Step C. By subtracting lead contributed by fuel oil from the
total lead measured, one obtains that amount contributed
by auto exhaust:
"Vb.auto = mPb ~ "Fb.fuel oil
0.003 - 0.00064 = 0.00236
Step D. The source coefficient for auto exhaust is calculated
knowing that p^., = 0.40
& Pb,auto
c = m ^ p
auto Pb,auto Pb,auto
0.00236 v 0.40 = 0.0059
V-4
-------
Still more complications prevent utilization of these simplified
formulae. Some sources do not have tracer elements which can readily
be identified. Most of the time, the number of elements analyzed is
greater than the number of sources considered. In essence, there
exists more data than necessary to solve the equations directly.
However, there is some error in-all elemental concentration measurements.
It would thus be useful to have as much of the data as possible to
obtain an average calculation of the source coefficients.
The method of multivariate regression analysis for source
reconciliation embodies this concept. In simple terms, the set of
source coefficients is computed which will yield an aerosol composition
that most closely resembles the measured profile. A computer program
is used so that many sources and elements can be accomodated.
When using many elements and sources, the elemental composition
of each source, the measured aerosol profile and the set of source
coefficients can be treated as matrices. Henceforth, the composition
of a source shall be named source profile, and capital letters will
denote matrices.
P is the source profile
M is the measured aerosol profile
C is the set of source coefficients
e is the number of elements
n is the number of sources
Equation (1) can be rewritten in matrix form:
M = P • C
where the a factors have been deleted.
Rewriting Example 1.:
PXJ
pyj
P .
p
p
p
xk
yk
zk
P
P
P
xl
yi
zl
•
m
m
m
P C = M
In the case of multivariate analysis of real data, P and M are
measured and an approximation of C is computed.
Since analytical errors are inherent in both P and M, and the
number of elements is greater than the number of sources, an exact
solution, C, for the equation P'C = M does not exist. However, for
any approximation of C, we can compute a source profile, E, where
E = P-C. The best approximation of C is found by minimizing D = E - M,
the difference between the computed and measured profiles.
The calculation is written in more complete form below. If
individual elements of matrices are denoted by small case letters, then:
V-5
-------
d —
y
J-i
. .
j yj
- m
Eq. (2)
The elements of D are now squared and summed to yield a lengthy
function not shown here:
y-i
Eq. (3)
A judicious selection of source coefficients will bring the
calculated aerosol profile more or less close to the measured aerosol
profile. An expression of this proximity is found in Eq. (4).
(dy)z * (e-l)
y-i
1/2
Eq. (4)
This value will be termed the standard error of estimate, and is an
index of fit.
The expression in Eq. (3) can be minimized by taking the partial
derivative with respect to each c. and setting it equal to zero. A
solution of n simultaneous equations will yield a set of source
coefficients which gives the closest approximation to the measured
aerosol profile.
The first step in applying this model is to consider all major
emission sources which may contribute significant fractions to the
total aerosol in the watershed. In a previous source reconciliation
study of Chicago aerosols, Gatz (2) accounted for contributions from
6 sources. For this study, 8 sources will initially be considered.
Source profiles for automotive exhaust, fuel oil fly ash and
cement manufacturing were taken from Friedlander (3). The composition
of municipal incineration emissions are reported in Greenberg et al. (4)
Iron and steel manufacturing data is listed by Gatz (2). Coal burning
emissions were taken from Klein et al. (5) and Andren and Lindberg (6).
Surface soil samples were collected from the watershed at a
construction site and a tilled field. Windblown dust from bulk soil
fractionates elements according to their preference for particle
size. The fractionation factors, found by Miller et al. (7), were
multiplied by the average elemental values measured in Menomonee
Watershed soil to obtain the composition of soil dust. Appendix V-A
lists individual and mean soil concentrations measured in soil samples.
The source profiles used for the regression analysis are compiled
in Table V-l.
The modification mentioned in the beginning of this section
concerns weighting the ultimate fit to individual element differences.
The regression analysis of Mayrsohn and Crabtree (1) minimizes
the sum of the squares of the absolute differences between measured
and computed aerosol profiles. Evidently, for this study, the
V-6
-------
Table V-l. Source profiles
<
Element
Al
Ca
Cu
Fe
K
Mg
Mn
Na
Pb
Zn
Coal
fly
ash
(COAL)
8.11
2.7
0.054
10.5
2.43
13.5
0.054
1.08
0.054
0.54
Fuel
Automotive oil
emissions ash
(AUTO) (FOASH)
0.8
1.3
0.2
0.4 6.0
0.2
0.06
0.06
5.0
40.0 0.07
0.14 0.02
Cement
manufacture
(CEMENT)
2.4
46.0
—
1.09
0.53
0.48
—
0.4
—
Iron and
steel
manufacture
(IR&ST)
2.4
5.4
1.6
38.7
—
1.6
2.4
—
—
1.8
Agricultural
soil dust
(ASOLID)
6.3
2.4
0.014
4.8
0.90
2.2
0.16
0.80
0.003
0.012
Construction
soil dust
(CSOILD)
5.2
16.5
0.01
4.2
1.0
12.8
0.13
0.47
0.003
0.0077
Incineration
emissions
(INCIN)
1.4
—
0.17
0.65
—
1.3
0.073
8.2
8.1
12.0
-------
calculation would be most sensitive to aluminum, calcium and iron,
whose concentrations are the highest in the aerosol profile. A
proportional error in the computed zinc concentration would have a
minimal influence on the overall fit. Therefore, correct determination
of source coefficients is highly dependent on the accuracy and
completeness of the major element data.
Although absolute concentrations are orders of magnitude lower,
the measurement of the trace constituents (e.g. Mn and Zn) is as
accurate as the major elements. It is contradictory to include
many more elements in a source coefficient calculation in hopes of
improving the approximation, and yet weighting the fit to only a few.
Hence, the computer program in this study weights each element equally
by dividing by the measured ambient concentration. In addition, more
versatility was added by including an option to weight individual
elements to any desired level. The following discussion illustrates
the utility of multivariate regression analysis.
An ambient aerosol sample from the heavy industrial site in
August was chosen for source reconciliation. Table V-2 shows the
calculated fit with the 8 considered emission sources. The measured
aerosol profile, expressed in percentage units, is the first of 4
columns. Both unweighted and weighted values will be shown in each
case. The standard error is an expression of overall fit, a low
number indicating similarity between computed and measured profiles.
Negative source coefficients indicate that some of the data is
incomplete or inaccurate. The final column shows that potassium
contributes most to the difference between measured and computed
profiles. In fact, the aerosol contains much more potassium than is
accounted for by the sources considered.
In reevaluating the emission source profiles, it was noted that
Gatz (2) reports no potassium or sodium emissions from iron and steel
manufacturing. However, Murphy (8) lists a sodium percentage from
this source as 1.03%. It is likely that potassium is also emitted,
but simply was not reported. There is no firm basis for calculating
a potassium percentage, but a tentative value can be assigned by
noting the sodium to potassium ratios in coal and cement. Potassium
contents are generally higher in these sources, and hence a value of
1.5% potassium was chosen for iron and steel.
Utilizing the modified source profile for iron and steel, the
regression analysis was run a second time (Table V-3). The sodium
and potassium changes improved the overall fit, but the troublesome
negative source coefficients still persisted. It is probable that
some of the sources considered contribute very little mass to the total
measured aerosol. The agricultural soil dust source exhibits the
most negative source coefficient and was deleted on that basis.
There is no mathematical justification for deleting an emission source
with the most negative value. However, if the overall fit improves,
there can be little argument in favor of retaining the source in
question.
V-8
-------
f
Table V~2. Fit heavy industrial ambient aerosol with 8 emission sources
SOURCE COEFFICIENTS
COAL AUTO FOASH CEMENT IR&ST ASOILD CSOILD INC IN SUM
.3816 .0310 .1027 .1371 .1097 -.2112 -.1025 -.0061 .4422
UW-MEA: UNWEIGHTED MEASURED AEROSOL PROFILE
UW-COM: UNWEIGHTED COMPUTED AEROSOL PROFILE
UW-RES: UNWEIGHTED RESIDUAL
W-RES: WEIGHTED RESIDUAL
ELEMENT
UW-MEA
UW-COM
UW-RES
STANDARD ERROR OF ESTIMATE
.3741428
— INDEX OF FIT
W-RES
AL
CA
CU
FE
K
MG
MN
NA
PB
ZN
1.820000
5.820000
.230000
5.730000
1.100000
3.570000
.314000
.733000
1.220000
.330000
1.896698
5.863515
.211577
7.580120
.727853
3.614123
.242374
.713198
1.219011
.333143
-.076698
-.043515
.018423
-1.850120
.372147
-.044123
.071626
.019802
.000989
-.003143
-.042142
-.007477
.080101
-.322883
.338315
-.012359
.228107
.027015
.000811
-.009523
-------
Table V-3. Fit heavy industrial ambient aerosol with 8 modified emission sources
SOURCE COEFFICIENTS
COAL AUTO FOASH CEMEMT IR&ST ASOILD CSOILD INCIN SUM
.3029 .0307 .0799 .1127 .1157 -.1674 -.0282 -.0035 .4426
UW-MEA: UNWEIGHTED MEASURED AEROSOL PROFILE
UW-COM: UNWEIGHTED COMPUTED AEROSOL PROFILE
UW-RES: UNWEIGHTED RESIDUAL
W-RES: WEIGHTED RESIDUAL
I
I—'
o
ELEMENT
UW-MEA
UW-COM
UW-RES
STANDARD ERROR OF ESTIMATE
.2986664
— INDEX OF FIT
W-RES
AL
CA
CU
FE
K
MG
MN
NA
PB
ZN
1.820000
5.820000
.230000
5.730000
1.100000
3.570000
.314000
.733000
1.220000
.330000
1.862011
5.862090
.214203
7.347329
.806329
3.598701
.268086
.714546
1.219129
.332890
-.042011
-.042090
.015797
-1.617329
.293671
-.028701
.045914
.018454
.000871
-.002890
-.023083
-.007232
.068684
-.282256
.266974
-.008040
.146223
.025177
.000714
-.008757
-------
Table V-4 shows another improvement in fit by removing the
agricultural soil dust source. In addition, all source coefficients
are positive. The process could be ended here. However, the regression
analysis allows us to remove any element(s) as long as the remaining
number of elements exceeds the number of sources. Since iron and
potassium contribute most to the overall error, they were deleted in
Table V-5.
The questionable tactic of assigning a potassium concentration
was thereby rendered inconsequential. Incineration emissions are
clearly negligible (< 0.5%). This source was deleted.
Table V-5 is the final reconciliation of emission sources for the
heavy industrial site. The considered sources account for 53% of
the total measured aerosol mass. Coal combustion, iron and steel
manufacturing and soil dust from a construction site, together account
for 36% of the total mass.
In a study by Draftz et al. (9) 90% of the particulate matter
collected at most suburban Chicago sites was said to be concrete
dust and automotive emissions. In this source reconciliation, the
cement emission profile would represent concrete dust. Automotive
emissions are also taken into account. Table V-5 shows that, at
most, 8.5% of the total dust is due to vehicular activity, assuming
that all cement emissions are actually via concrete ablation.
The reconciliation was then performed on the rural site aerosol
from the same sampling period (Table V-6). The agricultural soil
dust source appears to contribute to the rural aerosol. The major
error is from copper. Copper cannot be deleted since the number of
elements would then equal the number of sources. At this point,
the versatility of weighting becomes evident. The dependence of the
overall fit on copper can be reduced by a factor of 10.
Table V-7 is the final reconciliation of the rural aerosol
after desensitizing the analysis to copper. The standard error of
estimate is very low. Source coefficient calculations show a decrease
in contribution from iron and steel by 10 times in the 15 km between
Falk and Donges Bay. Auto emission contributions are decreased by
more than a factor of 2, while coal combustion contributions went
down 40%.
The results were expected. Anthropogenic emissions contribute
a major fraction of the total measured dust in the industrial valley.
The effect is, however, extremely localized in a north-south direction.
The accuracy of the computer program can be checked by two simple
tests. In the past, automotive emissions have been successfully
reconciled using a tracer element calculation (i.e. Pb). To confirm
the computer calculated source coefficient of 0.0303 in Table V-5,
the tracer determination was carried out in Eq. (5).
™Pb ' pPb,auto
= 1.22 T 40 = 0.0305
V-ll
-------
Table V-4. Fit heavy industrial ambient aerosol with 7 modified emission sources
SOURCE COEFFICIENTS
COAL AOTO FOASH CEMEMT IR&ST CSOILD INC IN SUM
.1496 .0295 .0693 .0712 .1152 .0835 .0031 .5213
UW-MEA: UNWEIGHTED MEASURED AEROSOL PROFILE
UW-COM: UNWEIGHTED COMPUTED AEROSOL PROFILE
UW-RES: UNWEIGHTED RESIDUAL
W-RES: WEIGHTED RESIDUAL
i—•
N3
ELEMENT
UW-MEA
UW-COM
UW-RES
W-RES
AL
CA
CU
FE
K
MG
MN
NA
PB
ZN
1.820000
5.820000
.230000
5.730000
1.100000
3.570000
.314000
.733000
1.220000
.330000
2.153997
5.766276
.207540
6.884598
.671228
3.314306
.299680
.719662
1.219411
.331376
-.333997
.053724
.022460
-1.154598
.428772
.255694
.014320
.013338
.000589
-.001376
-.183515
.009231
.097652
-.201500
.389792
.071623
.045605
.018196
.000483
-.004169
STANDARD ERROR OF ESTIMATE
.2848378
— INDEX OF FIT
-------
Table V-5. Fit heavy industrial ambient aerosol with 6 emission sources
SOURCE COEFFICIENTS
COAL AUTO FOASH CEMEMT IR&ST CSOILD SUM
.1041 .0303 .0802 .0549 .1287 .1284 .5266
UW-MEA: UNWEIGHTED MEASURED AEROSOL PROFILE
UW-COM: UNWEIGHTED COMPUTED AEROSOL PROFILE
UW-RES: UNWEIGHTED RESIDUAL
W-RES: WEIGHTED RESIDUAL
f
i—»
OJ
ELEMENT
AL
CA
CU
MG
MN
NA
PB
ZN
UW-MEA
..820000
>.820000
.230000
5.570000
.314000
.733000
L. 220000
.330000
UW-COM
2.016889
5.725492
.228854
3.286137
.335995
.728139
1.221688
.294706
UW-RES
-.196889
.094508
.001146
.283863
-.021995
.004861
-.001688
.035294
W-RES
-.108181
.016239
.004984
.079514
-.070048
.006632
-.001384
.106950
STANDARD ERROR OF ESTIMATE
.1317290
— INDEX OF FIT
-------
Table V-6. Fit rural ambient aerosol with 7 emission sources
SOURCE COEFFICIENTS
COAL AUTO FOASH CEMEMT IR&ST ASOILD CSOILD SUM
.0538 .0128 .0574 .0487 .0165 .0246 .1262 .3399
UW-MEA: UNWEIGHTED MEASURED AEROSOL PROFILE
UW-COM: UNWEIGHTED COMPUTED AEROSOL PROFILE
UW-RES: UNWEIGHTED RESIDUAL
W-RES: WEIGHTED RESIDUAL
f
ELEMENT
AL
CA
CU
MG
MN
NA
PB
ZN
UW-MEA
L.690000
1.630000
.065400
I. 450000
.057400
.426000
.522000
.059000
UW-COM
1.449144
4.688904
.042437
2.447883
.066348
.460555
.520907
.062991
UW-RES
.240856
-.058904
.022963
.002117
-.008948
-.034555
.001093
-.003991
W-RES
.142518
-.012722
.351112
.000864
-.155895
-.081114
.002095
-.067641
STANDARD ERROR OF ESTIMATE — INDEX OF FIT
.4233396
-------
Table V-7. Fit rural ambient aerosol with 7 emission sources weight Cu by 1/10
SOURCE COEFFICIENTS
COAL AUTO FOASH CEMEMT IR&ST ASOILD CSOILD SUM
.0642 .0129 .0443 .0519 .0112 .0656 .1089 .3588
UW-MEA: UNWEIGHTED MEASURED AEROSOL PROFILE
UW-COM: UNWEIGHTED COMPUTED AEROSOL PROFILE
UW-RES: UNWEIGHTED RESIDUAL
W-RES: WEIGHTED RESIDUAL
h-1
Ut
ELEMENT
UW-MEA
UW-COM
UW-RES
W-RES
AL
CA
CU
MG
MN
NA
PB
ZN
1.690000
4.630000
.065400
2.450000
.057400
.426000
.522000
.059000
1.686514
4.630852
.032169
2.449969
.057529
.426500
.521984
.059058
.003486
-.000852
.033231
.000031
-.000129
-.000500
.000016
-.000058
.002063
-.000184
.050812
.000013
-.002256
-.001174
. 000030
-.000979
STANDARD ERROR OF ESTIMATE — INDEX OF FIT
.0509271
-------
The calculated lead source coefficient in Table V-7 was similarly
confirmed.
Furthermore, it should be noted that high sodium levels in
ambient aerosols exist due to road salt application. A road salt
emission profile was not considered here. Therefore, a source
reconciliation for a typical winter sample should exhibit measured
sodium concentrations that exceed computed values. The overall fit
should also be disturbed by the incomplete data. Table V-8 shows
both these phenomena for a rural aerosol from late January.
More widespread use of the reconciliation model used here is
envisioned. Recent controversies between alleged emitters and
government regulatory agencies over the extent of industrial con-
tributions accentuates the need for more sophisticated interpretation
techniques than are now employed. The primary requirement at this
stage is accurate ambient and emission profiles to incorporate into
models which will generate undisputed source reconciliation.
V-16
-------
I
I—"
VJ
Table V-8. Fit rural, winter ambient aerosol with 7 emission sources
SOURCE COEFFICIENTS
COAL AUTO FOASH CEMEMT IR&ST ASOILD CSOILD SUM
.0951 .0055 .2073 .0412 -.0047 .2454 -.0807 .5091
UW-MEA: UNWEIGHTED MEASURED AEROSOL PROFILE
UW-COM: UNWEIGHTED COMPUTED AEROSOL PROFILE
UW-RES: UNWEIGHTED RESIDUAL
W-RES: WEIGHTED RESIDUAL
ELEMENT
UW-MEA
UW-COM
UW-RES
W-RES
AL
CA
CU
MG
MN
NA
PB
ZN
1.860000
1.660000
.035100
.815000
.039200
2.430000
.241000
.053400
2.150829
1.652452
.041693
.815234
.035040
1.309200
.241232
.050141
-.290829
.007548
-.006593
-.000234
.004160
1.120800
-.000232
.003259
-.156360
.004547
-.187847
-.000287
.106129
.461235
-.000964
.061028
STANDARD ERROR OF ESTIMATE — .INDEX OF FIT
.5361732
-------
REFERENCES - V
1. Mayrsohn, H. and J. H. Crabtree. Source Reconciliation of
Atmospheric Hydrocarbons. Atmos. Env., 10:137-143, 1976.
2. Gatz, D. F. Relative Contributions of Different Sources of Urban
Aerosols: Application of a New Estimation Method to Multiple
Sites in Chicago. Atmos. Env., 9:1-18, 1975.
3. Friedlander, S. K. Chemical Elemental Balances and Identification
of Air Pollution Sources. Environ. Sci. Technol., 7:235-240, 1973.
4. Greenberg, R. R., G. E. Gordon and W. H. Zoller. Composition of
Particles Emitted from the Nicosia Municipal Incinerator.
Environ. Sci. Technol., 12:1329-1331, 1978.
5. Klein, D. H., A. W. Andren, J. A. Carter, J. F. Emery, C. Feldman,
W. Fulkerson, W. S. Lyon, J. C. Ogle, Y. Talmi, R. I. Van Hook and
N. Bolton. Pathways of Thirty-seven Trace Elements through
Coal-fired Power Plant. Environ. Sci. Technol., 9:973-979, 1975.
6. Andren, A. W. and S. E. Lindberg. Atmospheric Input and Origin of
Selected Elements in Walker Branch Watershed, Oak Ridge, Tennessee.
Water, Air and Soil Pollution, 8:199-215, 1977.
7. Miller, M. S., S. K. Friedlander and G. M. Hidy. A Chemical Element
Balance for the Pasadena Aerosol. J. Colloid and Interface Sci.,
39:165-176, 1972.
8. Murphy, T. J. Sources of Phosphorus Inputs from the Atmosphere
and their Significance to Oligotrophic Lakes. Water Resources
Center, University of Illinois, Urbana. Research Report No. 92,
1974.
9. Draftz, R. G. Types and Sources of Suspended Particles in Chicago.
Report No. IITRI-C9914-C01, Dept. of Environ. Control, Chicago,
1975.
V-18
-------
APPENDIX V-A. SOIL ANALYSES
Table V-A-1. Metal analyses (%) of agricultural soil samples from the
Menomonee River Watershed
Subsample
Element
Al
Ca
Cu
Fe
K
Mg
Mn
Na
Pb
Zn
Al
Ca
Cu
Fe
K
Mg
Mn
Na
Pb
Zn
1
Tilled
6.67
1.43
0.00318
3.10
1.85
1.19
0.0898
0.834
-0.001
0.0117
Organic
5.82
1.65
0.00498
3.11
1.60
0.891
0.0530
0.774
-0.001
0.0148
2
Mean
Agricultural
6.51
1.51
0.00206
3.28
1.95
1.26
0.0936
0.769
0.001
0.0120
6.6
1.5
0.0026
3.2
1.9
1.2
0.092
0.80
0.001
0.012
Agricultural
6.12
1.70
0.00427
2.99
1.66
0.901
0.0519
0.750
•0.001
0.0137
6.0
1.7
0.0046
3.1
1.6
0.90
0.053
0.76
0.001
0.014
1
Subsample
2
Mean
Untilled Agricultural
6.30
1.33
0.00267
3.30
1.95
1.09
0.0962
0.881
-0.001
0.0110
Mean
6.28
1.73
0.00292
3.38
1.87
1.19
0.106
0.797
-0.001
0.0108
Agricultural
6.3
1.5
0.0028
3.3
1.9
1.1
0.10
0.84
0.001
0.011
6.3
1.6
0.0034
3.2
1.8
1.1
0.082
0.080
0.001
0.012
V-19
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Table V-A-2.
Metal analyses (%) of construction site
soil samples from the Menomonee River
Watershed
Element
Al
Ca
Cu
Fe
K
Mg
Ifa
Na
Pb
Zn
1
5.14
11.5
0.00266
2.83
2.00
6.53
0.0658
0.466
-0.001
0.00725
Subsample
2
5.29
9.89
0.00258
2.85
2.07
6.19
0.0624
0.475
-0.001
0.00809
Mean
5.2
10.7
0.0026
2.8
2.0
6.4
0.064
0.47
0.001
0.0077
V-20
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TECHNICAL REPORT DATA .
(Please read Instructions on the reverse before completing)
REPORT NO.
EPA-905/4-79-029-H
2.
TITLE AND SUBTITLE
Atmospheric Depostion of Lead and Phosphorus on the
Menomonee River Watershed-Volume 8
6. PERFORMING ORGANIZATION CODE
I. RECIPIENT'S ACCESSIOI»NO.
i. REPORT DATE
December 1979
AUTHOR(S)
A. W. Andren and T. R. Stolzenburg
8. PEF
PERFORMING ORGANIZATION NAME AND ADDRESS
Wisconsin Water Resources Center
University of Wisconsin
1975 Willow Drive
Madison, Wisconsin 53706
10. PROGR
AZ2B2A
±m tjD£.±i .
11. CONTRACT/GRANT NO.
R005142
2. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Great Lakes National Program Office
536 South Clark Street, Room 932
Chicago, Illinois 60605
13. TYPE OF REPORT AND PERIOD C<
Final Report 1974-1979
14. SPONSORING AGENCY CODE
U.S. EPA-GLNPO
5. SUPPLEMENTARY NOTES
Water Chemistry Program, University of Wisconsin-Madison assisted.
6. ABSTRACT
Air monitoring stations were located in five different land use types of the
Menomonee River Watershed. Total suspended particulate concentrations were
highest in the industrial valley, decreasing to the residential, transition-
urban, mixed rural and rural. Even the rural station experienced effects from
local urban emission sources. All stations exhibited similar temporal trends
of suspended load.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Air particulate
Evaporation
Suspended particulate
Pollutant
Parameters
Air masses
18. DISTRIBUTION STATEMENT
Document is available to the public through
the National Technical Information Service,
Springfield, VA. 22161
19. SECURITY CLASS (ThisReport)
21. NO. OF PAGES
98
20. SECURITY CLASS (Thispage)
22. PRICE
EPA Form 2220-1 (9-73)
V- 0. S. Government Printing Office- 1981 750-807
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