EPA-600/2-77-0643
September 1977
Environmental Protection Technology Series
NATIONWIDE EVALUATION OF
COMBINED SEWER OVERFLOWS AND
URBAN STORMWATER DISCHARGES
Volume I:
Executive Summary
Municipal Environmental Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, Ohio 45268
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EPA-600/2-77-064a
September 1977
NATIONWIDE EVALUATION OF
COMBINED SEWER OVERFLOWS AND URBAN STORMWATER DISCHARGES
Volume I: Executive Summary
by
Richard H. Sullivan
Martin J. Manning
American Public Works Association
Chicago, Illinois 60637
James P. Heaney
Wayne C. Huber
M. A. Medina, Jr.
M. P- Murphy
S. J. Nix
S. M. Hasan
University of Florida
Gainesville, Florida 32611
Contract No. 68-03-0283
Project Officer
Richard Field
Storm and Combined Sewer Section
Wastewater Research Division
Municipal Environmental Research Laboratory (Cincinnati)
Edison, New Jersey 08817
MUNICIPAL ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
'CINCINNATI, OHIO 45268
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DISCLAIMER
This report has been reviewed by the Municipal Environmental Research
Laboratory, U.S. Environmental Protection Agency, and approved for publica-
tion. Approval does not signify that the contents necessarily reflect the
views and policies of the U.S. Environmental Protection Agency, nor does
mention of trade names or commercial products constitute endorsement or
recommendation for use.
11
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FOREWORD
The Environmental Protection Agency was created because of increasing
public and government concern about the dangers of pollution to the health
and welfare of the American people. Noxious air, foul water, and spoiled
land are tragic testimony to the deterioration of our natural environment.
The complexity of that environment and the interplay between its components
require a concentrated and integrated attack on the problem.
Research and development is that necessary first step in problem
solution and it involves defining the problem, measuring its impact, and
searching for solutions. The Municipal Environmental Research Laboratory
develops new and improved technology and systems for the prevention, treat-
ment, and management of wastewater and solid and hazardous waste pollutant
discharges from municipal and community sources, for the preservation and
treatment o^ public drinking water supplies and to minimize the adverse
economic, social, health, and aesthetic effects of pollution. This publi-
cation is one of the products of that research; a most vital communications
link between the researcher and the user community.
This Executive Summary describes the contents of a two volume study
which considered the cost of abating pollution resulting from urban storm-
water runoff and characterized the quality of urban stormwater runoff and
combined sewer overflows in terms of their pollutional strengths.
Francis T. Mayo
Director
Municipal Environmental Research
Laboratory
111
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ABSTRACT
A study was conducted by the American Public Works Association and the
University of Florida to determine: the cost of abating pollution from
combined sewer overflows and urban stormwater, the impact of such
pollutional discharges on receiving waters, and the pollution po-
tential of such discharges. The study was based upon the availability of
existing data and prediction models.
Continuous simulation runs using one year of hourly data were made to
determine the attainable level of pollution control with a specified availa-
bility of storage volume and treatment rate in five cities: Atlanta,
Denver, Minneapolis, San Francisco, and Washington, D.C. This procedure
was used to derive generalized equations relating pollution control to
storage and treatment. These results were combined into a simple opti-
mization model which determined the optimal mix of storage and treatment
for any feasible level of control for any city. Then the nationwide assess-
ment is presented. The results indicate annual costs ranging from $297
million for 25 percent pollution control to $5,029 million for 85 percent
pollution control. The corresponding initial capital investment ranges
from $2,476 million for 25 percent control to $41,900 million for 85 percent
control. These costs can be reduced significantly if stormwater pollution
control is integrated with best management practices and integrated into a
multi-purpose program.
The balance of the study analyzed existing published and unpublished
information to characterize the pollution potential of urban runoff and to
estimate the impact of such runoff on receiving waters. It was found that
there appears to be direct connections between many parameters such as BOD
and suspended solids with the amount of street refuse. However, some
parameters appear to be related to more site specific factors. As a practi-
cal matter it was found necessary to relate pollution abatement to BOD and
suspended solids, even though there are many other pollutants in large
concentrations such as heavy metals and phosphorus.
The entire results from this project are contained in the three volumes
listed below:
1. American Public Works Association and University of Florida,
Nationwide Evaluation of Combined Sewer Overflows and Urban
Stormwater Discharges: Volume I, Executive Summary, USEPA Report
EPA-600/2-77-064a, 1977.
2. Heaney, J;P., W.C. Huber, M.A. Medina, Jr., M.P. Murphy, S.J. Nix,
and S.M. .Hasan, Nationwide Evaluation of Combined Sewer Overflows
IV
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and Urban Stormwater Discharges: Volume II, Cost Assessment and
Impacts, USEPA Report EPA-600/2-77-064[b], 1977.
3. Sullivan, R.H., M.J. Manning, and T.M. Kipp, Nationwide Evaluation
of Combined Sewer Overflows and Urban Stormwater Discharges:
Volume III, Characterization of Discharges, USEPA Report
EPA-600/2-77-064c, 1977.
This report has been submitted in fulfillment of Contract No. 68-03-
0283 between the American Public Works Association, and the Office of
Research and Development, Environmental Protection Agency. Work was
completed in October 1976.
v
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CONTENTS
Foreword
Abstract iv
Figures viil
Tables i^
Acknowledgements xl
SECTION I Conclusions 1
A. Cost Assessment 1
B. Relative Impact of Wet- and Dry-Weather
Flows On Receiving Water 3
C. Characterization of Combined Sewer Over-
flows and Urban Stormwater Discharges 4
Recommendations 6
A. Cost Assessment Methodology 6
B. Impact Of Urban Water Pollution Control On
Receiving Water Quality 6
C. Characterization of Combined Sewer Over-
flows and Urban Stormwater Discharges 7
Overview 11
SECTION II Cost Assessment 12
Demographic Characteristics of the Urbanized
Areas 12
Runoff Analysis 13
Stormwater Flow Prediction 13
Dry-Weather Flow Prediction 23
Quality Analysis 23
Stormwater Quality Prediction 23
Nationwide Quality Assessment 29
Cost Assessment Methodology 29
Control Technology and Associated Costs 29
Cost of Treatment and Storage 34
Relationship Between Storage/Treatment and
Percent Pollution Control 34
STORM Input Data for Detailed Study of
Five Test Cities 36
Results 37
References 56
SECTION III Receiving Water Impact - A Case Study 60
General Description 60
Data and Modeling 66
Results 66
Tradeoff in Alternatives 72
References 76
vi
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SECTION IV Urban Stormwater Pollutant Loadings 77
Alternative Approaches to Quality Characterization
of Runoff Discharge 79
Potential Pollution Sources ,79
References 94
vii
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FIGURES
Number Page
1 Storage/treatment isoquants for percent BOD5 removal with
first flush - Region III - Minneapolis 41
2 Mean annual precipitation in the United States, in inches,
and regional boundaries 42
3 Single purpose and multiple purpose stormwater pollution
control costs for U.S 53
4 Overall percent precipitation control vs. rainfall intensity -
Atlanta, Georgia (1948-1972) 55
5 Map of Des Moines area 61
6 Location map: river sampling points 55
7 Application to Des Moines, Iowa 57
8 Minimum DO frequency curves for existing conditions in
the Des Moines River 68
9 Minimum DO Frequency Curves for Varied Treatment Alternatives . . 69
10 Dry-weather minimum DO frequency curves for varied DWF
treatment alternatives 79
11 Annual minimum DO frequency curves 71
12 Geometric means and 95 percent confidence levels for dustfall
measurements, by land use and months 83
13 Sediment yield versus contributory basin area 85
viii
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TABLES
Number \
1 Demographic Characteristics of the Urban Areas .......... 14
2 Land Use Distribution for the Urban Areas in the U.S ........ 15
3 Land Use by Type of Sewerage System ............... 17
4 Population by Type of Sewerage System .............. 19
5 Population Density by Type of Sewerage System .......... 21
6 Annual Wet-Weather Runoff Flow for Combined Sewer, Storm,
and Unsewered Areas ....................... .24
7 Annual Dry-Weather Flow for Combined Sewer, Storm, and
Unsewered Areas ......................... .26
8 Pollutant Loading Factors for Nationwide Assessment ........ 28
9 Dry-Weather BOD Loadings ..................... 30
10 Wet-Weather BOD Loadings ..................... 32
11 Cost Functions for Wet-Weather Control Devices .......... 35
12 Values of Parameters for Isoquant Equations for Developed
Portion of the Test Cities ................... 39
13 Annual Control Costs - Combined Areas .............. 43
14 Annual Control Costs - Storm Sewered Areas ........... 44
15 Annual Control Costs - Unsewered Areas .............. 45
16 Optimal Percent Control for Specified Overall Control ....... 46
17 Optimal Annual Cost Per Acre for Specified Overall Percent
Control ............................. 48
IQ Optimal Annual and Capital Control Costs ............. 50
19 Pollutant Annual Loads for Drainage Area Above Des Moines,
Iowa .............................. 60
xx
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Number Page
20 Summary of Present Annual Metro Area Discharges 62
21 DWF Tertiary Treatment vs. WWF Control 73
22 Control Costs vs. Violations of the DO Standard 74
23 Accumulation Rates of Traffic Influenced Roadway Materials .... 80
24 Pollutants and Pollutant Levels Found in Snow Deposits 81
25 Concentration of Contaminants Found in Rainfall 82
26 Comparison of Suspended Solids Concentrations Computed From
Dustfall and Measured Values 84
27 Geometric Means for Cadmium and Zinc for 77 Midwestern Cities . . 84
28 Comparative Summary of Reported Values for Street Surface
Loadings by Land Use 87
29 Sampling Method for Measuring Street Surface Accumulations ... 88
30 Average Daily Dust and Dirt Accumulations and Related Pollutant
Concentrations for Select Field Observations 89
31 Percentage of Pollutants Found in Dust and Dirt and Flush
Samples Attributable to the Flush Fraction 92
x
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ACKNOWLEDGMENTS
This volume is one part of a joint effort between the American Public
Works Association of Chicago and the University of Florida. The cooperation
of Martin Manning, former project director for APWA, and William F. Henson of
APWA was very helpful. Richard H. Sullivan of APWA provided overall project
coordination and management. The advice and guidance of our advisory com-
mittees on this United States assessment and the Canadian assessment were
very useful.
Richard Field of USEPA provided invaluable overall guidance and
detailed critical review of findings throughout the study.
Numerous persons at the University of Florida contributed to this
effort under the able direction of James P. Heaney and Wayne C. Huber.
XI
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SECTION I
CONCLUSIONS, RECOMMENDATIONS AND OVERVIEW
CONCLUSIONS
A. Cost Assessment »
1. A total of almost 150 million people live in urbanized areas in the
United States at an overall average population density of 5.1 persons
per acre (12.6 persons per ha). Urbanized areas, as defined, are about
46.2 percent undeveloped. The distribution of the developed land uses
is approximately as follows:
Residential 58,4
Industrial 14.8
Commercial 8.6
Other 18.2
Total 100.0
About 14.4 percent of the urban area is served by combined sewers,
38.3 percent by storm sewers, and the balance of the developed area
contains unsewered storm drainage. About 25.2 percent of the urban
population is served by combined sewer systems, 52.1 percent by storm
sewer systems, and the remaining 22.7 percent is unsewered. Average
population densities, are 16.73 (41.30), 13.00 (32.09), and 4.59 (11.83)
persons per acre (persons per ha) in combined, storm and unsewered areas
and the overal average developed population density is 9.56 persons per
acre (23.6 persons per ha).
Annual wet-weather runoff was generated using a runoff coefficient that
is a function of imperviousness which in turn is a function of popu-
lation density. The results indicate an average runoff of 16.5 in.(41.9
cm) per year, 14.8 in. (37.6 cm) per year, and 10.8 in. (27.4 cm) per
year from an average precipitation of 33.4 in. (84.8 cm) per year in
combined, storm and unsewered urban areas, respectively. Dry-weather
flow is a function of population density on the basis of 100 gallons
per person-day (379 liters per person-day). The quantities of dry-
weather flow in combined, storm, and unsewered areas average 22.5 in.
(57.2 cm), 17.5 in. (44.5 cm) and 6.2 in. (15.7 cm) respectively.
Average annual dry-weather flow (DWF) is significantly greater than
average wet-weather flow (WWF) only in the arid areas. However, in most
parts of the country, dry-weather flows represent 30-50 percent of the
total (wet plus dry) runoff from urban areas.
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3. On the basis of the available data, pollutant loading estimates were
developed for wet -weather for BOD5, suspended solids, volatile solids,
total phosphate (PC^) and total nitrogen (N), and derived as functions
of precipitation, land use and population density, the latter only for
residential land use. Other land uses are commercial, industrial and
open. These estimates indicate that, for the same population density,
loads from combined sewered areas are approximately four times higher
than those from separate sewered areas. Furthermore, higher population
densities in combined sewered areas will increase the ratio even more
because loadings are assumed to be an increasing function of population
density.
Annual BOD5 loads were calculated for the 248 urbanized areas for
both wet and dry-weather conditions, the latter under the assumption
of 0.17 pounds per person-day (0.08 kg per person-day). Annual loads
for other parameters may be easily calculated for any urbanized area.
The national summary indicates that loading rates for untreated dry-
weather flow are higher than for wet-weather flow. However, if 85
percent secondary treatment is assumed for dry-weather BOD generation,
wet-weather loads are found to be one third of the total residual load-
ings in urban areas. Moreover, BOD loadings from combined sewered
areas are comparable to loads due to secondary effluents.
4. An evaluation was made of the relative desirability of using a mix of
storage with either primary treatment or secondary treatment. The basic
trade-off to be evaluated is whether primary treatment is sufficiently
less expensive than secondary treatment to offset its lower removal ef-
ficiency which necessitates treating a much larger amount of flow to
effect an equivalent BOD removal. The results indicate that a primary
type of facility is preferable up to BOD removals of about ten percent.
A secondary facility is preferable for higher levels of control.
5. The annual average percent runoff control and the annual number of over-
flow events were correlated to permit the reader to use either criterion
as an effectiveness metric. A precipitation event was assumed to termi-
nate following 12 hours of no precipitation.
6. The final assessment results indicate that, for the entire U.S., total
annual costs for 25, 50, 75 and 85 percent BOD control are $297, $886,
$2,725, and $5,029 millions of dollars per year. Similarly, the initial
capital investment for 25, 50, 75 and 85 percent BOD control is $2,476,
$7,391, $22,744, and $41,968 millions of dollars based on 85 percent of
the present worth of the total annual cost at an assumed interest rate
of 8 percent over 20 years. Note that the incremental costs for wet-
weather control increase significantly. This is due to the dispropor-
tionately larger control units needed to capture the less frequent,
larger storms.
7. An analysis was made of the possibility of cost allocation among wet-
weather quality control and dry-weather quality control (with flow
equalization) and wet-weather quantity control (with storage required
to reduce runoff rates and volumes). The results suggest that
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significant savings from 70 percent at low control levels to 30 percent
at high levels might be realized.
8. IP addition to using storage-treatment devices to control wet-weather
pollution, other management practices are available. A related study
suggests that significant savings in control costs could be realized if
these other management practices are used in conjunction with storage-
treatment. The savings range from about 50 percent at low levels of
control to about 38 percent at higher control levels. Further savings
could be realized by allocating some of the cost to other purposes, e.g.,
street sweeping for aesthetics.
9. The relationship between tertiary treatment and wet-weather control was
examined by finding the percent wet-weather control to initiate prior to
using tertiary treatment. Results indicate that about 4 percent of the
wet-weather flow problem should be controlled before initiating tertiary
treatment control. BOD removal was used as the effectiveness metric.
Different results would be obtained using nutrient control as the cri-
terion.
10. The results of this assessment indicate significantly lower control costs
than reported in earlier studies, i.e., the USEPA Needs Survey (initial
capital cost = $266.1 x 109) , and the National Commission on Water
Quality (NCWQ) study (initial capital cost of $288.6 x 109). The NCWQ
study was the only other one which explains its methodology and
assumptions. Thus, a comparison with that study has been made. Major
differences in results are attributable to the following:
a. Collection System Costs - The NCWQ estimate includes
$84.0 x 109 for constructing storm sewers. This study
does not view storm sewers as chargeable to pollution
control.
b. Choice of a Design Storm - The NCWQ studies used control
of the two year, one-hour storm as the basis for their mean
estimate of control costs. The concept of a design storm
was not used in this study because it was felt that a
continuous characterization in terms of percent of the
runoff which could be treated was more appropriate since
no accepted design event condition exists which also
specifies a design antecedent dry-weather period. Analysis
indicated that control of the one hour, one month storm
would permit capture of 90 percent of the precipitation
volume. Sizing for the two year, one hour storm yields
relatively little incremental control and requires a much
higher control volume.
B. Relative Impact of Wet- and Dry-Weather Flows On Receiving Water
1. The relative importance of separate stormwater , combined and dry-weather
flow runoff as waste sources generated by the urban environment may be
assessed more effectively through the use of models that simulate continu-
ously in time.
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2. Based on an annual simulation of waste inputs to the Des Moines River
from the Des Moines metropolitan area, various treatment alternatives
were investigated. Minimum dissolved oxygen (DO) cumulative frequency
curves indicate that:
a. During periods of wet-weather, the urban runoff contribution
of BOD is the most significant among all of the urban BOD
sources.
b. For existing treatment facilities in Des Moines, Iowa, 42
percent of the wet-weather events were predicted by the
mathematical models to violate a 4.0 mg/1 minimum DO standard.
During these periods of wet weather, the sewage treatment
facility provided secondary treatment to municipal wastewater.
c. During periods of dry weather, effluent from the secondary
treatment facilities violated the same stream DO standard two
percent of all the dry-weather days in 1968.
d. Combining the effects of wet weather and dry weather, the
models predicted that DO standard violations would occur 33
total days out of the year.
e. An evaluation of costs incurred indicates that 25 percent
BOD control of wet-weather flow, while providing secondary
treatment of dry-weather sanitary flow, is an effective treat-
ment strategy. Violations are reduced to 26 days out of the
year at an incremental annual cost of approximately $800,000
per year.
f. The benefits received from a reduction of shock loads from
urban runoff are not readily quantifiable but should be
considered when compared to strategies that involve high
levels of municipal wastewater control.
C. Characterization of Combined Sewer Overflows and Urban Stormwater
Discharge
1. Urban stormflow can be broadly characterized as: having solids con-
centrations equal to or greater than raw sewage; BOD concentrations
approximately equal to secondary treated wastewater treatment effluent;
and bacterial contamination of two to four orders less than untreated
domestic wastewater. Combined sewer overflows average less than half
the strength of raw domestic sewage, although the volume may produce
100 times the flow of domestic sewage.
2. Runoff quantity and quality are major factors in predicting the need for
treatment and type of treatment facilities. Runoff quantity estimating
methods have been well developed. The accuracy of physical and hydro-
logic data are major difficulties. Few areas have sufficient rainfall
gauging and other hydrologic monitoring networks.
3. Estimation procedures for runoff quality are not well defined. Two
major approaches have been used: characterization of discharge pol-
lution and receiving water monitoring; and identification and evalu-
ation of potential pollutant sources that may contribute to the
deterioration of runoff quality. Characterization of discharge pol-
lution suggests construction of treatment facilities whereas source
characterization suggests methods of preventing stormflow pollution.
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An integrated approach should provide the most cost-effective solution.
4. Only 16 cities were identified where surface runoff quality data in some
form were available. Of these, only six related the quality data to
physical basin characteristics.
5. Sampling methods and sampling site selection procedures were found to
vary widely. Separate storm sewer sampling performed at points in the
system where open earthen channels are used appear to add a large
solid component due to erosion.
6. Sampling results have been generally expressed in the form of mean pol-
lutant concentrations without regard to rainfall-runoff relationships
or variations in time. Thus, the data is not ideally suitable for
determining treatment requirements.
7. Soil erosion sediments are perhaps the largest single source of water
pollution. Sediments represent pollutional contributions in the form
of solids, organic loadings and related oxygen demands, nutrients,
soil salts, trace metals, and various other chemicals such as herbi-
cides and pesticides.
8. Sources and temporary storage locations of potential pollutants of
urban stormflow are often considered as being the same. Rather,
streets, rooftops, and catch basins while acting as a temporary point
of accumulation should be more accurately considered as an extension
of the stormflow collection system.
9. Dust and dirt, generally the fraction of street solids accumulation
which will pass a 0.125 in. (0.32 cm) screen, has been used for
analysis of the pollutional potential of street surface accumulations.
Some investigators have, in addition to sweeping, flushed the street
surface and/or vacuumed the surface to obtain a better representation
of the solids and soluble material which may be present.
10. A high level of replicability was found for sampling dust and dirt
taken at the same site at known time intervals. Thus, it appears that
intensive but not necessarily long sampling periods are needed to
characterize pollutional potential of given sites.
11. About 25 percent of the dust and dirt on streets may be associated with
wear of the pavement surface. Accumulation loadings on asphaltic
surfaced streets have been found to be about 80 percent greater than
on concrete surfaces.
12. Public works programs, practices and equipment may be used to affect
the quality of urban stormflow. More effective street cleaning programs
employing efficient equipment at a relative high frequency of cleaning
can remove a major portion of the potential stormflow pollutants.
Catch basin cleaning and snow and ice control practices may be
additional critical control activities.
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13. A direct relationship could not be found between all pollutants found
in receiving waters and potential pollutants found in dust and dirt.
Thus, dust and dirt cannot be considered as the sole indicator of
receiving water pollution from urban stormflow.
RECOMMENDATIONS
A. Cost Assessment Methodology
1. The methodology developed for this study should be extended to a wider
range of situations. The general methodology appears to work well and
thus, further use is desirable.
2. Cost and performance data on storage and treatment units should be
further refined.
3. The methodology should be extended to account for the interrelationship
between storage and treatment especially at higher levels of control
where detention times in storage are significant. Associated with
this effort could be a study of the impact of different reservoir
operating policies. A constant release rate is assumed at present.
4. The isoquant equations should be refined to account for snowmelt.
An updated relationship between annual overflow events and percent
runoff control should be included.
5. Further sensitivity analysis of the cost allocation formulation needs
to be made to derive generalized curves for various combinations of
influent treatment plant flow equalization and storage capacities.
6. The tradeoff with tertiary treatment should be evaluated using other
pollutants such as nutrients as the effectiveness criterion.
B. Impact Of Urban Water Pollution Control On Receiving Water Quality
1. In order to have basic information on the behavior of receiving waters
when subjected to pollutant stresses beyond their natural assimilative
capacity, continuous hydrologic models coupled with pollutant transport
routines must be applied. It was found throughout this study that
large amounts of data were available; however, these data were some-
what less than adequate for modeling purposes. In the area of data
requirements some specific recommendations are:
a. The water quality indicators that will be used for
planning purposes should be clearly identified before
actual data collection.
b. The data collection system should be designed to be
representative of the receiving water being investigated.
Flow velocities, diffusion and dispersion coefficients,
tidal cycles, etc., affect the frequency of sampling.
c. Sampling of receiving waters should be conducted before,
during, and after periods of urban runoff.
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d. The laboratory procedures utilized should be clearly described.
For example, whether natural or artificial (deionized) dilution
water was used in performing the standard 8005 test and the
particle size and settling velocity definition of suspended
solids.
e- Kinetic reactions of biochemical tests (i.e., deoxygenation
rates of BOD) should be reported and compared with other locally
obtained values.
f• Additional data on photosynthesis, algal respiration, and
benthic demand of water bodies are needed.
§• Measurements of the nitrogenous oxygen demand of waste inputs
and the receiving water are needed. The impact of such demands
are becoming more significant since greater numbers of second-
ary treatment plants are operational.
h. Both mass loadings and concentrations of pollutants should be
estimated and reported.
2. In the realm of modeling efforts, further work is required to characterize:
The response of receiving waters to urban runoff and dry-
weather flow inputs should be characterized when storage
of waste streams is considered in combination with treatment.
C. Characterization of Combined Sewer Overflows and Urban Stormwater
Discharges
1. Research is warranted in the estimation of the contamination of receiving
waters through discharges in melt water of the contaminants entrapped in
snow and ice deposits directly from source contamination or through
snow and ice control methods. Much of the interest exhibited to date
in this area has been in terms of chloride contributions as they are
liberated from snow and ice control materials. More recently, investi-
gations have provided general characterization data not only for these
pollutional contributions, but for source contaminants,entrapped within
snow and ice deposits as well.
2. Further study and evaluation of the water quality impairing characteris-
tics of atmospheric particulates is warranted. Atmospheric intermedia
effects as such are little understood, and the contributions of con-
taminants to surface runoff pollution from these sources may be signi-
ficant within urban areas. A clearer understanding of these water
quality effects would serve to indicate some of the impacts of air
pollution heretofore undefined and further pinpoint the necessity for
both air pollution and water pollution control. An evaluation of air
pollutional contributions to runoff in terms of sanitary engineering
water quality parameters alone would prove to be enlightening.
3. An evaluation of the pollutional contributions from the weathering or
wear products of street surface and other impervious surface materials
should proceed. Indications exist that these materials may represent
heretofore undefined sources of runoff contamination. Determination of
the magnitude of pollution involved would prove helpful in establish-
ing effective control strategies for these sources.
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4. Urban sediments and erosion products should be evaluated as to their
water quality characteristics. The study of erosion products has
generally been related to non-urban conditions. Their water quality
characteristics are not clearly.defined, but should be if the true
water quality impacts are to be established.
5. The pollution contributions attributable to tree and leaf litter should
be evaluated in sanitary engineering water quality terms. Vegetative
contributions, as such, may represent a significant source of urban
runoff water quality impairment during those periods of the year when
leaf fall occur. A clearer understanding of these contributions would
be helpful in the assessment of their relative impacts.
6. A further evaluation and assessment of the pollutional potentials of
accumulations on other non-street impervious surfaces is warranted.
Little real data exists for the assessment of p-ollutional potentials
from these sources.
7. Direct and indirect runoff discharge pollution data is reported on the
basis of mean concentration values for the purposes of gross character-
ization. The time-related effects such as first flush contributions
or variations of concentration with flow in time, are not reflected in
these average values. In only a few instances, have sufficient dis-
charge information been collected to provide a more, complete character-
ization reflecting these variations.
8. A detailed study of .runoff discharges from a completely developed
urban drainage basin should be performed. Runoff, as collected by a
storm drainage collection system, should be metered and sampled to re-
flect the time-related responses of the system as to flow and concentra-
tion for a variety of rainfall and runoff events. Discreet samples of
runoff should be collected and analyzed to provide quality information
on these urban runoff flows. The analysis should seek to provide some
indications of runoff characterization over time.
9. Standardized data collection and analytical methods should be estab-
lished for the evaluation of street and non-street impervious sur-
face accumulations and their pollutional potentials for runoff.
10. Sample handling and processing techniques for a subsequent analytical
evaluation of the potential physical, chemical and biological water
quality characteristics of dry samples should be investigated and
standardized. Current practices in the handling of dry samples are
varied and often unrelated to the mechanisms by which these potential
contaminants become runoff pollution. Thus, further study in this
area is warranted.
11- Standard methods and procedures for the metering of runoff flows and
for, the collection and analysis of urban runoff samples should be
developed. Significant efforts in developing standard methods for
sampling discharges has been performed to compare alternative sampling
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techniques and find desirable standard methods.* Proceeding from this
work, further methodological development applicable to the specifics
or urban runoff pollution samples should be established.
12. Standard procedures should be established for the collection of verifi-
cation data to be employed in the evaluation of existing analytical
methodologies. These procedures should include methods appropriate for
the accumulation of precipitation data, receiving water quantity meter-
ing, sample collection, sample processing preparation and sample
preservation techniques.
13. A field demonstration effort should be instituted on one or more select
small-scale urban drainage sub-basins to achieve a number of significant
objectives. Among these would be:
a. Identification of the pollutional contributions associated with
urban sources and repositories of contaminants for various
measures of oxygen depletion, nutrients, pesticides, metals
and other contaminants.
b. Comparison of sampling and analytical results for both identified
potential pollutional contributions — street surface, rooftops,
erosion products, rainfall, etc. — and for the actual equivalent
discharges related to these potential pollutional contributions.
c. Evaluation of the effectiveness of local control methods applica-
ble to the prevention of runoff contamination.
d. Comparison of both potential and actual pollutional contributions
among existing types of development in various land uses.
e. Assessment of the impacts of the first flush phenomenon, in-
cluding the contributions of catch basins and sewer system
accumulations.
14. The accumulation and removal mechanisms applicable to the deposition
of pollutants on street surfaces and other impervious surfaces should
be evaluated. These would include: airborne, water-borne, vehicular-
produced, and miscellaneous depositions, as well as wind erosion, run-
off, transportation-related and intentional removals. These accumula-
tion and removal mechanisms should be evaluated in terms of various
street configurations, paving types, curb and other barrier heights,
land use and other variables.
15. The removal of street surface contaminants by runoff flows should be
further investigated to establish the physical processes involved.
Such evaluation should consider the hydraulic modeling of rainfall
and runoff on representative street sections if necessary.
*Wullschleger, Richard E., et al., "Recommended Methodology for the Study
of Urban Storm Generated Pollution and Control," USEPA Report No. EPA-600/
2-76-145, Envirex, Inc., August, 1976.
-------
16. The evaluation of the effectiveness of street cleaning equipment in-
cluding new cleaning technologies in reducing the levels of potential
pollution on street surfaces should be conducted. Such studies should
relate air and water pollution.
17. The quantitative contributions of urban erosion sediments should be
further investigated in relationship with the major variables involved—
soil characteristics, cover management practices, rainfall and other
hydrologic conditions, physical configurations and other measurable
parameters. Although annual estimating methods exist for agricultural
sediment production, shorter-term single rainfall erosion responses
remain to be determined or the applicability of existing estimating
methods to urban areas and individual rainfall occurences should be
validated.
18. Sources of potential pollution for urban runoff should be evaluated to
provide a basis of prediction in connection with existing analytical
methodologies or new expanded methodologies should be developed.
Little real information in this regard is available.
19. Further study and evaluation of recalibration techniques employing
verification data for the calibration of existing models and their
use for the prediction of pollutional contributions due to subsequent
runoff events should be undertaken. Recalibration techniques employing
discharge information have been shown to be promising approaches for
fine tuning models to assure higher levels of accuracy in prediction.
These procedures should be further evaluated and more highly developed
for existing models where they may apply.
20. Further research into urban development characteristics should be
instituted, and recommended procedures for the collection of this data
should be established.
21. Various urban development parameters should be studied and analyzed as
to their applicability as meaningful parameters for the estimation of
urban runoff pollution. This analysis should proceed on the basis
of real runoff quality discharge information. The relative importance
of various urban development parameters with respect to runoff dis-
charge pollutional characteristics should be established.
22. Further research to establish on a nationwide basis, the comparison of
the pollutional contributions in receiving waters is appropriate. These
may be proposed on generalized per acre annual emission for various
types of land use.
23. The effects of benthal deposits and other sources of pollutional
impacts on receiving water should be further studied and evaluated.
The impact of these sources on water quality is generally significant
and of considerable interest. The fate of heavy metals is of parti-
cular concern.
10
-------
OVERVIEW
The American Public Works Association (APWA) and the University of
Florida (UF) conducted a study to characterize urban stormflow and combined
sewer overflows and to determine the cost of control or abatement of receiving
water pollution from such sources. The study encompassed a number of ob-
jectives which included: the generalization of the quantity and quality
characteristics of urban stormflow and combined sewer overflows; an assess-
ment of the pollutional significance of these wastewater flows on a national
basis as to their impacts, applicable prevention, abatement and control
methods and control costs; and a critical evaluation of the data which was
available.
The study was designed to utilize existing published and unpublished
sources of information and data.
Some broad inconsistencies exist within the body of information un-
covered as to the handling and reporting of various aspects of the complex
physical processes involved, sampling methods and equipment, the pollutants
measured, and the results identified. While the diversity and variation
encountered is representative of the current state of the art, it also
reflects the evolutionary character of this area of study over the past
ten years or so. Nevertheless, the information uncovered is representa-
tive of the best available for the purposes of this project.
Highlights of the two volumes of the study report are included in
this third volume, Executive Summary. Section II describes the overall
cost assessment results and methodology used. Section III evaluates the
impact of urban stormflow and combined sewer overflows on receiving
water quality. Section IV describes the essential features of the
characterization portion of the study.
11
-------
SECTION II
COST ASSESSMENT
During the past decade, much effort has been expended in identifying
and analyzing the wet-weather pollution control problem. The initial concern
with combined sewer overflows expanded to consideration of stormwater runoff
in general. This study assesses the costs of controlling wet-weather pollu-
tion to varying degrees. A key question is what is the relative importance
of various sources of wet-weather pollution and how does wet-weather pollu-
tion control compare to dry-weather pollution control? Also, what is its
impact on receiving water?
Control of wet-weather pollution is distinctly different than the tra-
ditional dry-weather problem. In wet-weather pollution control, one would
normally use a mix of storage and treatment, not treatment alone. Thus new
techniques are needed to determine optimal mixes of storage and treatment.
Numerous effectiveness criteria for wet-weather control have been used, e.g.,
number of overflows, percent runoff control, percent BOD control. For wet-
weather control, the most critical impact on the receiving water does not
necessarily occur under low flow conditions. How should the critical con-
ditions be defined? Basic questions of this nature arose throughout the
study because it is such a relatively new area of concern. Thus the final
estimate could vary widely if some of these assumptions are changed. However,
the approach is a fairly general one and assumptions are stated explicitly.
Thus, the interested reader can refine the estimates as better information
becomes available. The remainder of this section summarizes the cost
assessment.
DEMOGRAPHIC CHARACTERISTICS OF THE URBANIZED AREAS
Urban areas in this study have been taken as the 248 urbanized areas
defined by the Bureau of the Census of the US Department of Commerce in the
1970 census, and other urban areas. The 248 urbanized areas defined in 1970
are generally characterized as having; (1)
• a central city or urban core of 50,000 or
more inhabitants:
» closely inhabited surroundings, consisting of
incorporated places of 100 housing units or
more; and small unincorporated parcels with
population densities of 1,000 inhabitants per
sq mi (386 per sq km) or more: and
12
-------
• other small unincorporated areas that may
eliminate enclaves, square up the geometry
of the urbanized area or provide a linkage
to other enumeration districts fulfilling
the overall criteria within 1.5 mi (2.5 km)
of the main body of the urbanized area.
All 248 urbanized areas in the United States were analyzed in varying
levels of detail. Population density distribution functions were developed
for 50 urbanized areas. These results were extrapolated to the other 198
urbanized areas. Land use information was derived based on a statistical
analysis of 106 cities. (2) The results for all USEPA regions and the entire
U.S. are shown in Table 1. A total of almost 150 million people live in
urbanized areas in the United States at an overall average population
density of 5.1 persons per acre (12.6 persons per ha). Urbanized areas, as
defined, are about 46.2 percent undeveloped as estimated in Table 2. The
distribution of the developed land uses is approxmately as follows:
Residential 58.4
Industrial 14.8
Commercial 8.6
Other 18.2
Total 100.0
Information was obtained on population and area served by combined
sewerage systems. The population and area served by storm sewers and in the
unsewered area were estimated as residuals. All areas with a developed
population density of less than 5 persons per acre (12 persons per ha) were
assumed to be unsewered. The results, shown in Table 3, indicate that about
14.4 percent of the urban area is served by combined sewers, 38.3 percent by
storm sewers, and the balance of the developed area is unsewered. Table 4
indicates that 25.2 percent of urban population is served by combined sewer
systems, 52.1 percent by storm sewer systems, and the remaining 22.7 percent
is unsewered. Table 5 indicates nationwide average developed population
densities of 16.73 (41.30), 13.00 (32.09), and 4.59 (11.33) persons per acre
(persons per ha) in combined, storm and unsewered areas and an overall
average developed population density of 9.56 persons per acre (23.6 persons
per ha).
RUNOFF ANALYSIS
Stormwater Flow Prediction
Techniques for prediction of runoff quantities vary from very simple
methods of the Rational Method type to sophisticated models of the nature
of SWMM. The Storage, Treatment, Overflow and Runoff Model (STORM) was de-
veloped by Water Resources Engineers, Inc.(WRE) for the Hydrologic Engineer-
ing Center (HEC) of the Corps of Engineers. (3) The model was designed for
planning purposes, i.e., for long-term simulation of many storm events using
an hourly time step. Techniques used in STORM are relatively simple, relying
on weighted average runoff coefficients and a simple loss function to predict
13
-------
TABLE 1. DEMOGRAPHIC CHARACTERISTICS OF THE URBAN AREAS
S?f,
1
1
\
1
1
1
Tl
2
2
Tl
3
3
3
^
3
3
Tl
a
a
a
a
a
«
u
a
Tl
s
s
s
5
5
Tl f
S T A T f
(-T
MA
RT
?FG 1
Si T
MY
>FG 2
HE
nc
MO
P *
VA
Al
Fl
r, A
K V
s>S
"T
PC
TM
TL
T M
^T
MM
PM
u T
'FT, 5
IC£F°S
5^9.
?35.
966.
1?5.
162.
35.
?0«2.
1479.
830.
ao3.
13*0.
?598.
1275.
607.
30U.
276.
6*1.
719.
1 1P9.
778.
1 0^2.
171 a.
6P8.
61*7.
1970 P°P
23ua.
*07.
017.
P?6.
ia3.
9050.
637?.
1561 1 .
?19fl3.
395.
757.
3005.
B«31.
2933.
r> 8 o .
1 6 ? 0 3 .
201 1 .
5^6=;.
276P.
1687.
987.
2287.
1?33.
2307.
3371 .
25 ?7
291 1 .
32MO.
|
PPP 1
A v F P r> 1
a. 10
a . oa i
3.3J
5.00
a. 1 a
u.s*
",3<
Ifl.S?
9.5?
5.27
1 9.?.S
7.46
6 . ? .'i
5.1*
«.?1
6.?'J
^ p o
3,^7
3.57
3.51
3.59
3.79
7.7-
6.01
3 63
5.30
PFT,
6
6
6
6
Tl. f
7
7
7
7
Tl. f
P
fl
6
R
8
TL (
9
9
9
9
9
Tl F
10
10
10
Tl F
Tl I
3.20
7.34
4.07
2.91
3.51
3?74
4.53
4.61
4.96
4.15
5?1P
4.53
5.5.1
4.3/1
3.60
4.00
2.90
3.67
6.41
6.0.1
3.33
5.95
4.5*
4.60
14
-------
TABLE 2. LAND USE DISTRIBUTION FOR THE URBAN AREAS IN THE U.S.
EPA
RFG
1
t
J
1
1
1
1
AV
?
2
AV
3
3
3
3
3
3
AV
4
4
4
"
4
4
4
4
AV
5
5
5
5
5
5
AV
1 1
1 STATF 1
I TH 1
! CT 1
1 MAI
! NW I
1 PT 1
! VT 1
»EG 1 1
1 M J 1
! MY I
REH, 21
1 HE 1
I nC l
l MH i
1 P& 1
1 VA !
1 WV 1
1 A L 1
! FL !
! KY 1
1 Mr !
! SC !
1 TM i
! IL I
1 TM 1
i MI i
l . MM !
1 PH !
I» 1
Uj I 1
RFC 5!
1 .,,
1 . A K' D
IjMDVI
50.
69.
44.
56.
4?.
49.
49.
4ft.
23.
39.
40.
•?.
2ft.
36.
46.
47.
37.
61 .
50.
50.
30.
54.
55.
54.
5°.
53.
2ft.
47.
37.
54.
45.
40.
4?.
0 I
91
?!
o |
1 I
5 I
3!
=; i
8 I
6 I
ft I
8 I
4 I
3 I
o I
5|
7 I
3 I
0 I
5 I
7!
•? \
3 I
4 I
6|
7 I
1 I
^ I
1 !
3 I
7!
4 I
•- I
USE
RES
29.2
17.6
32.'6
25.'2
33.8
29.5
29.6
30.1
44.5
35.3
34.6
56.2
41 .8
37.?
31.0
30.V
36.4
22.6
29.?
28.9
35^5
26.4
26.2
26.7
23>
27.1
41 .6
30.9
36.6
26.8
32.0
29.4
33.6
A 9 '/-
1 CPMM
I «
1 ?
.3
.6
I /'.fl
1 3
1 5
I (i
1 tl
1 4
! 6
1 5
1 8
1 6
1 5
! 4
1 4
! 5
! 3
! n
1 3
1 3
I 3
1 3
I 4
1 6
1 4
1 3
! 4
1 4
. 0
.3
.4
.4
.6
.1
.3
.?
.5
.6
.5
.4
.3
.3
_ o
.9
.9
.0
. 1
.6
.«
^ p
.7
.3
.0
OF T
TNOL
7.4
4.5
*.*3
6.4
8.6
7.5
7.5
7.6
11. 13
8 .'9
8.8
14.2
10.6
9.4
7,9
7>
Q.2
5.7
7.4
7.7,
Q.O
6.7
6.6
6.8
6.0
6?
-------
TABLE 2 (cont'd)
1 1 1 AMD
EPAISTATE! 1
RFG! in IUMDVI
6
6
, 6
6
6
AV
7
7
7
7
AV
3
8
8
• 8
8
"fl
AV
q
q
q
9
9
AV
1 0
1 "
1 0
AV
AV
I AP
I I A
I MM
I TX
3Ff, 6
I IA
' KS
I M1"1
) NF
PFR 7
1 CO
J. MT
1 SD
! IJT
! WY
RFH 8
1 AK
1 A7
1 CA
! HI
1 MV
! OR
I WA
REP 10
U.S.
158
130
150
161
I56
I55
I a6
I50
ia6
I39
U7
I53
U6
(60
I53
I36
I38
! as
* ^ 1
.1 1
.1 I
.1 I
.01
.31
.71
.0 1
.4 1
. I
.21
.81
.71
if! 1
.51
.1 1
.71
.0 1
.1 1
.61
,0|
. " 1
.31
.1 1
USE
1
RES 1
35
29
22
25
26
23
31
31
33
28
33
31
35
30
27
29
31
23
27
37
37
25
35
31
31
31
31
31
.11
.21
"*7 |
.11
.'31
.1 1
.31
.91
M
.'5!
.1 1
.2!
.21
'3|
.01
.71
.ai
.0!
.61
.51
.a i
AS «
CPMM
3.5
5.2
/i. 3
3.3
3.8
3.F
'1.6
a. 6
fl.O
<1.3
fl.6
5.?
a.s
a.o
a. 3
0.6
3. «
a.o
5.6
3.7
5.*
fl.7
a. 7
a. 6
'1.6
«.6
nF
IN
6
9
7
5
6
6
5
7
7
8
7
8
7
9
7
6
7
7
5
6
9
9
6
q
fl
fl
7
8
TH
1
r>L l
.1 l
.0!
.PI
.5!
.6!
.9!
.9!
.ai
.3!
.6!
.9!
.01
.71
.91
.at
.91
.9 !
.6!
.5!
.31
.1 1
.0 1
.01
.9!
.0 !
nTH
7.
11 .
9.
7.
P.
P.
7.
".
9.
in.
9.
1 0.
p.
1 ,1 .
°.
p.
°.
o.
7.
B ^
1 -1 .
1 1 .
7.
1 1 .
9.
9.
9.
9.
/
5
1
1
1
0
1,
3
fl
7
/J
0
6
7
1
5
a
1
7
3
a
P
6
fl
?
A
q
8
8
fl
.0 I
°-
fl
*REA
TOTAL
100.0
100.0
1 00.0
100.0
100.0
100.0
loo.o
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
100.0
1 fi 0 . 0
100.0
100.0
1 0 0 . C
1 0 0 . 0
100.0
1 00.0
100.0
100.0
100.0
100.0
1 0(1.0
100.0
16
-------
TABLE 3. LAND USE BY TYPE OF SEWERAGE SYSTEM
1
IFPA
RFG
1.
1
1
1
1
1
Tl
2
2
TL
3
3
3
3
3
. 3
Tl
4
4
4
a
a
a
a
a
Tl. i-
5
c
5
5
5
5
STATE
TD
CT
MF
MA
MM
P!
VT
'Fn i
K!,T
MY
9FC 2
DF
nc
MH
PA
V4
wv
3FC 3
AL
FL
RA
KY
MS
MC
sc
JM
F.H 4
IL
TM
M?
MM
nw
WT
Tl PFn 5
APF^
1 1 N n v
279.4
1 64. a
426.9
71 .1
6«.3
17.1
1027. 1
717.6
197.1.
014.8
30.6
1 .5
1 1 a . 5
4PQ.5
268.8
76.7
970.8
418.8
837.4
352.1
1 19.4
151.2
359.1
1 8fc.7
427.0
2651 .8
341 .9
366.3
/i 0 6 . 8
376.6
775.7
341.9
2609.2
* SFRVFf
•i
C^MB
51,4
aa.4
101.8
31,7
21 .8
7.9
2^.1
26.5
245.6
272,1
6.8
12.7
0.. 0
89.3
28,0
^7.6
1 oa.,5
0.0
0.4
60.2
9.6
0.0
0,0
o.o
25.7
95.9
306.9
167,9
2^3.8
«7.9
21 1 .2
31,8
999^5
•) RY TYP
)00 ACPf
STflRw
82.7
n . n
160.5
O.n
23.o
o.o
267. n
301.^
241 .1
542.6
17.2
25.1
19(1.5
432.0
1. 5 4 . 3
3.5
822.6
10^.1
311.8
1 0?.7
38.1
51 .«;
i 13.7
62.1
9P-.P
933.6
218.5
57.3
15*. P
98.1
237.8
1 4 L\ . a
01 P.O
T rip SYSTEM
?«
",' IJNSFW i TOTAL
145J/I
""26?5
. 276?8
?2.t
48.2
9.6
528?5
433?4
145.9
579?2
"?;?3
0.0
97.9
, 339.5
120.0
, 23.7
. 6'M.4
159. 1
325.3
ifl'i.'n
87.4
73.5
178.1
94.8
. 1*7.5
1267.4
, 321.9
1*6?6
2Q5.4
172.Q
489.0
. 170.0
1635.8
17
558.8
235.3
966.0
124.9
16?.?
34.6
2 0 8 1. . 8
l'J79.n
829.7
2308.7
7^.0
39.3
402.8
1350.4
560,?
1. 6 1 . 6
2598.?
683.0
1274.7
696.9
304. a
276.?
650,9
343.6
71°. 9
a9as.6
H.80.1,
778.1
1092.0
69=;,*
171^.6
680.2
6156.6
-------
TABLE 3 (cont'd)
1
EPA 1 STATE
RFGI in
6 1 AR
61 1 *
61 MM
6 1 OK
61 TV
TI PF.C 6
i
7| TA
i
7 ! KS
71 nn
7 1 MF
Tl PF:r: 7
i
?! CO
i
8 1 MT
B 1 NH
PI Sn
61 I.IT
81 w Y
Tl °FS 8
9 ! AK
9 1 A7
91 C*
I
9! HT
9 1 M V
TI PEG 9
1 '"' 1 T 0
1 •'» 1 OP
101 W A
Tl PF.n 1Q
. I m
Tl U.S.
... | .....
ARE
i iNinV
177.0
12«.P
87.4
365.8
1426.8
218^.2
323.8
151.0
^31 .6
70.1
B86.4
140.5
3". 2
19.^
3P.7
124.1
2 a. 6
379.5
29.6
P 0 6 . P
100?.()
3«. 3
68.3
1 34«.4
3«.8
1 39. R
P5P.6
431 .2
13409. |
|
A SERVED RY TV
1000 * C P
COMR ! STHRM
11.61 30.1
0.0! 130.0
0.01 3>*.3
0 . 0 1 87.6
t
5.1 I "80. T;
I
16.71 77^.3
1
R.9I 76.=;
?1. 31 66.8
163.61 2°."
1 m
P9»6> 19. U
2P.3.3! IP?. ft
1.8! QP..1
0 , 0 I ? 4 . P
1.01 1 n . ^
0.7 I 15.0
0.01 46.3
0.01 11.3
3 . « 1 ? t 3 . 3
0.71 6.7
0,01 R 0 . 7
6 7 . 1 M 0 5 0 . 4
0.0 1 36.9
2.81 17.3
70.6 I 1 101 .9
0.0! 21.9
32.. 71 45.7
79.. 9! 6 P. 8
112.61 ?3^.F
(„..„.,,
2248.1 5987T
Pr OF SVSTE'M
F"
I.JS'Srwi TnTA!
. 82.41 301.0
69.5! 327.7
, U B . P | 1 7 U , 7
145.31 59*. 8
6?4.« 12546.0
970.9 I394«.P
126.7! 53c.o
87.6! 327,5
3 85. 4! 7 in. /l
. S 5 . P i 1 8 T . 9
4^5.51 1757.7
. 04.51 33/J.o
19. P | RP.P
JC.fi! 40.7
P 0 . 1 1 6 « . 4
60. 81 231.2
13.^1! 40. T;
219.31 p 1 5 . 6
, 12.11 4«.?
. Q7.'li 3P«.0
. 708.7!2«28.1
31.1! 106,?
31.11 119.6
, 880.1I3487.0
23.81 8/J.5
86.'7! 305.0
144. '31 54^.6
2r>4.. fel 035.1
739',! | 2Q037T 1
18
-------
TABLE 4. POPULATION BY TYPE OF SEWERAGE SYSTEM
FPA
RFG
1
1
, 1,
1
—
1
1
W M^ «
T!
m
. 2
2
Tl c
3
3
3
3
3
3
Tl
4
4
4
4
4
4
4
4
Tl c
5
5
5
1 5
1 5
! 5
1 Tl c
! ...
STATF
ID
CT
MF
MA
MH
PI
VT
?EP, 1
M,T
MY
'EH 2
OF
DC
MD
p A
VA
wv
?FG 3
AL
FL
GA
KY
MS
MC
sc
TM
>EH 4
IL
TM
MT
MM
nH
WT
?Fi~, 5
(
P.QMB
60?.
372.
1 155.
2*6.
346.
69.
2919.
405.
9603.
1H007.
83.
400.
0.
1 3^4.
298.
515.
2651.
0.
6.
590.
116.
0.
0.
0.
312.
1 024.
6109.
1 8 n 5 .
3293.
593.
2647.
679.
15166.
'HPIJLAT
( 1 0 0 ,} (
STHRM
979.
o.
2404.
0.
278.
u.
366*.
4473.
5369.
9842.
210.
357.
2545.
5802.
21 43.
42.
11100.
1238.
4075.
1156.
1 1 87.
596.
131=:.
697.
1249.
11512.
1582.
715.
1885.
1218.
3429.
1?72.
1010).
FHM SFP^
3 F P S O N <5
U N P F W
673.
135,
1 254.
131 .
202.
......
2^70.
1 405.
639.
21 34.
I'll.
o.
460.
1277.
492.
1?2.
2451.
773.
1385.
1 022.
384.
391 .
972.
5"^6.
746.
6209.
1530.
8M.
1 3«2.
71 6.
1Q44.
960.
7343.
,/rn
1
. TOTAL
. 2344?
507.
4e"3?
"""4T9?
826.
143.
9050.
, 637??
156"!?
219«3.
"""95?
•""759?
3005?
8433?
, 2933?
680.
16203.
•'Oil.
5465?
2768.
, 1 6 . V .
987.
22*7.
1233.
2307.
. 18745.
Q221 .
3371?
6559.
2527.
8021 .
29 11 .
32b1 0.
19
-------
TABLE 4 (cont'd)
1
EPA 1 STATE
RFGI TO
6 1 AP
6! LA
61 NM
,6! nK
1 „
61 TV
T! REG 6
71 !A
,71 KS
71 MO
71 NT
I «
TL. REG 7
8 1 CP
8 1 MT
.81 ND
.81. SO
8! IIT
81 WY'
TI. REP, s
.91 AK
91 AZ
9! CA
.91 HI
1
9 I MV
T! RFC,. 9
1 -i I T r>
I
10! HR
1 0 I W A
TI PEC; 10
ITI U.S?
— I.....I
COMB
80.
0.
0,
o.
101.
181.
252.
25a.
1635.
419.
?5S9.
36,
0.
10.
8.
0.
0.
55.
10.
0.
1663.
0.
«1.
ml!
0.
«?7.
903.
1330.
37606.
POPHLAT
ciooa
STORM
3as.
201?.
fl8R.
1150.
6031.
10023.
75&.
76R.
?sa.
?60.
2036.
1?60.
?5ft.
197.
1 83.
SflP.
126.
2610.
93.
989.
13U93.
a99.
317.
1539.1 .
33?.
tr^7a.
B71 .
1677.
77853.
TOM SER
PFRSnws
HNSEW
537.
. 3°A,
, ??6.
• •••»• m
590.
28()ir
^5^9^
609?
«63,
,1389.
23^.
?69?r
a«l.
116.
67;
. 106.
265?
75?
?070?
>.\t\.
«19.
2986.
139.
1?9.
3727?
"™?
flnl?
""nT?
12^8?
33906.
VfD
)
TOTAL
"" 962?
2406,
"""TT!
17^0?
. 893^?
1^753?
. uTs?
US5?
. 3d78?
.......
, 7291?
, 1737?
•""3*7??
""",17/1?
-"29??
85^.
, 201.
3735?
. 107.
. laofl?
iMfli?
638.
396.
20731?
"""187?
1«03?
2^75?
«265?
TJI9366?
20
-------
TABLE 5. POPULATION DENSITY BY TYPE OF SEWERAGE SYSTEM
1
EPA 1 STATE
RFGI 10
1 1 CT
1 1 MF
1 1 yA
1 1 MH
1 1 PT
1 ' VT
AV PFC i
2 1 NJ
?. 1 MY
A V P F "•• 2
3 1 OF
T 1 DC
3 1 MO
3 1 PA
3> V*
V W V
A v P F. R 3
U 1 A!
0 1 Fl
a 1 RA
a 1 KV
ii 1 -*S
oi '-ir
U I SC
a i TM
AV PFT. a
SI Tl
m !•>•
S 1 "T
51 M>J
5 1 nw
51 i>.< T
AV RFC 5
POP
(
rn"B
13.47
R.ife
M .3a
9.02
I^.OS
«.75
1 1 .?7
\*.?7
39.1 0
36. 7p
1?.?3
31 .ao
o . n
15.17
n.^3
B.<3U
1T.fr3
n.n
ia.?o
°.P!
1 ?. 03
0.1
o.o
o.o
12.16
10. f8
10.91
10.99
1U.08
15.37
12. S3
21 .3?
IS. 17
ULATIHM HFKipJTY
PFHROMS/ACPFI
RTOPM i iiK'RFi,; i AVER
1 i . PU i a. 63
0 . 0 1 «•. . 1 ?
lii.Qfli i.«;3
0 . ') I c . ° ?
11.6CM o . ? n
0 . n ) 7.73
13.711 4.67
1 a . P 3 i •*.'!«>
??.?7l -M - DFM«
IS/ACRF
1 " M S F W
6.52
^.6P
a. 62
ii.06
is .up,
a .66
a. «i
5.20
7.a9
a . 1 9
S.o?
a.66
C.p6
6.18
S.?fi
a. 37
c.6?
a.pp
3.6f>
ao
a.^?
a.?)
a .aft
a.a^
a.?3
^.52
fl .6a
'I.R6
a .9a
a. 59
UTY
•)
AVER
7.7fe
12.06
P. 15
7./17
7. OP
n.37
7.61
P.U5
B.65
P. 71
P. ^7
P. 93
P.C6
9.06
B.32
7. op
».16
P?^6
7.^0
7.92
o.Q3
° 0 3Q
7.7?
0.^8
«.U7
P.^0
•.as
P.afc
9.56
21
-------
hourly runoff volumes. Nonetheless, because of the nature of the continuous
simulation involved, it is at a considerably higher level, and therefore more
complex, than earlier, desktop techniques.
STORM computes a runoff coefficient, CR, weighted between pervious and
impervious areas by
CR = 0.15 (1 - 1/100) 4- 0.90 (1/100) (1)
= 0.15 + 0.75 (1/100)
where I is percent imperviousness and the coefficients 0.15 and 0.90 are the
default values used in STORM for runoff coefficients from pervious and imper-
vious areas, respectively. Note that in equation 1, the effect of demographic
factors (e.g., land use, population density) is incorporated into the percent
imperviousness, I.
A comparison of various estimating procedures indicates that the
New Jersey (5) equation provides a suitable predictive equation with the pop-
ulation density defined as developed population density. Thus, the equation
used to estimate imperviousness is
(0.573-0.0391 logl0PD,) (2)
I = 9.6 PDd. ±U d
where I = imperviousness, percent, and
population density in develo
urbanized area, persons/acre.
PD = population density in developed portion of the
The simplified equation for estimating annual runoff (AR) is
AR = (0.15 + 0.75 I/100)P (3)
where AR = annual runoff, inches/year,
I = imperviousness, percent, from equation 2, and
P = annual precipitation, inches/year.
Equation 3 can be refined by accounting for depression storage as is
done in STORM. For this simplified assessment methodology, the depression
storage is assumed to be as follows:
Land Use Depression Storage, in.(cm)
Impervious 0.0625 (0.159)
Pervious 0.25 (0.635)
For a given land use, the area weighted depression storage, DS, in inches,
is
DS = 0.25 - 0.1875 (1/100) 04 I< 100 (4)
22
-------
To approximate the effect of depression storage on estimated annual
runoff, one year of Minneapolis, Mn. data was simulated for varying levels
of depression storage. The results indicate that a factor for depression
storage can fie subtracted from the original runoff equation to yield the
final equation for estimating annual runoff, (6) i.e.,
AR = (0.15 + 0.75 I/100)P - 5.345(DS)0'5957 (5)
where AR = annual runoff, in./yr,
I = imperviousness, percent,
P = annual precipitation, in./yr, and
DS = depression storage, in. (0.005 < DS < 0.30)
The results, shown in Table 6, indicate average runoff of 16.5 in.
(41.9 cm) per year, 14.8 in. (37.6 cm) per year, and 10.8 in. (27.4 cm) per
year from an average precipitation of 33.4 in. (84.8 cm) per year in combined,
storm and unsewered urban areas, respectively.
Dry-Weather Flow Prediction
Dry-weather flow is predicted based on an average flow of 100 gals per
person-day (379 1 per person-day). Upon multiplication by population density
and conversion to appropriate units,
DWF =1.34 PDd (6)
where DWF = annual dry-weather flow, in./yr, and
PD, = developed population density, persons/acre.
Results of these calculations are shown in Table 7.
QUALITY ANALYSIS
Stormwater Quality Prediction
Quality analyses may be performed at several levels of detail, ranging
from an explicit formulation of runoff quality for small subcatchments within
a city to a broad representation of pollutant loads for an entire urbanized
area. It may be necessary to consider the entire spectrum during the course
of a study.
It is unfortunate that perhaps the only consistent remark about urban
runoff quality analysis in general is that data and results of previous
studies are so remarkably inconsistent. Few studies have been made of char-
acteristics of street litter, and they offer a wide range of values of con-
centrations of loads. Effluent data show a similar scatter. However, it is
necessary that a decision be made regarding actual values for use in the
analysis. Table 8 presents a predictive equation developed after a review of
available stormwater pollutant loading and effluent concentration data". T^he
equation permits one to estimate BOD5, SS, VS, PC>4 and N loads as a function
of land use, type of sewer system, precipitation, population density; and
23
-------
TABLE 6. ANNUAL WET-WEATHER RUNOFF FLOW FOR COMBINED
SEWER, STORM. AND JJNSEWERED AREAS
EPA
RFG
1
1
%
STATE
in
rr
ME;
1 y A
1
1
1
MM
RT
VT
AV PER 1
2 NJ
2
MV
AV RET. ?
3
3
T.
, 3
3
3
AV
a
4
OF
DC
MO
PA
V*
WV
PFT, 3
AL
FL
4 GA
/4
KV
4 MS
a NT
4
/J
sc
TM
AV PF_H 4
? 11
5 TM
5
5
5
MT
MM
HH
5 ^T
AV REH 5
... I .
TN/YR!
AMML. !
PPETPI
43.7!
43.51
43.61
41.0 !
40.01
35.01
41.1 1
42.81
38.11
40.51
45.0 !
41.01
42.01
41.01
42.91
41.01
42.1 1
55.8!
56.51
46.5!
42.3!
^4.5!
46.01
46.7 1
48.31
"9?6I
35.0 1
37.2!
31.0 1
26.01
37.21
29!7I
32.71
1-
WFT-XFATHFR F
CIMCWFS °ER VE
C0«t3 I STORM 1 UMSrW
lOi
16.01
17.61
15.41
18.5!
I3.4l!
17.21
19.1!
25. 8J
25 :?!
19.0 1
24.81
0.0 !
17.6!
16.91
15.4!
17.41
0.01
22.71
18. 1J
17.9!
0.0 1
0.0 I
0.01
19.41
._ _ _ _ i
18.51
16.61
14.71
13.61
10.51
14.61
14.51
14.fl|
18.1
o.o
19.6
0.0
1 6.5
0.0
.1 R.9
19.4
21.4
20.3
19.0
1 fl.2
18.5
18.2
18.7
-18.6
18.4
23.4
24.9
19.2
18.1
22.1
18.6
10.1
20.5
21.7
1 1 .6
15.1
12.9
10.6
.15.6
10. B
12.9
nT^
13.6
13.2
7Li
72!fl
12.. 6
13.2
.12.2
u.'o
11.9
74.2
0.0
13.1
11. >
13-. 2
n.'a
"iri
i7;7
17:1
15:3
.12:5
17,5
14.6
15.3
1 4*6
"7i?8
J 0.3
10.9
9.'5
7,4
10.2
9Ta
938
,OW
A^ER
16.1
15.2
16.4
14>
15. U
12.18
1.6.0
75!9
21.1
18.2
17.0
"20T7
"76?9
""5?9
16.6
15.2
16.3
20?3
27TI
.17?!
15.8
t9T6
16.4
17.0
1,7.3
"--i"
1.8.6
13?4
13.'3
tiN
9.1
12.9
10.5
12!3
24
-------
TABLE 6 (con
1
EPA 1 STATE
RFC! TH
6 I AP
61 1 A
6 ! NM
6 1 OK
fe! TX
AV RFC 6
71 TA
7 1 KS
7 1 MO
71 ME
AV PFC 7
8 1 cn
ft t MT
P ! MO
8 1 sn
1 «
S 1 III
ft I WY
AV OFR 8
9 1 AK
9 1 A?
9! f&
. 9 1 HT
9 ! MV
A V RFC 9
1 •> i in
I'.'l nR
1 n I w A
AV 'FT, 10
AV M.«S.
t'd)
IM/YR
PPETP
. 48.0
^6.0
9.0
^2.7
31 .0
33.0
36.8
?6.5
14.0
21 .0
?5.'0
15.0
15.0
17.4
30.0
9.0
17?2
?3?0
5.5
16.9
u.'o
•39.^3
30.3
26.9
33.4
W P T- 1*1 F A i
( i M r n F s c
COMBISTn^M
15^01 20.6
0.01 ?7.5
0.0 1 , 3.6
0.01 14.2
24.71 14.?
17.9) 16.?
18.0 1 12.1
14.11 13.?
14.2! 13.3
11.4! 11.5
14.0 1 1 ?.6
6.1 ! 5.8
0.01 5 . t\
8.3! 8.3
10.4 J 10-4
0.01 6.3
0.01 5.9
7.51 6.4
13.1 I 13.1
0.0 1 3.1
11.31 5.9
0.0 ! 9.9
2.9! 1.6
10.91 5.8
0.01 4.2
17.21 16.8
12.0' '5.5
13.51 .14.1
16.51 14.8
•HFR Ft
'E" YE'
1 1 M S F W
16.4
17.4
2.5
9.7
10.1
10.7
9.7
10.4
7.7
1.0 ,.8
4.0
6,9
7,9
4.7
4.7
8.6
4.6
6.9
1 .2
4.3
3.5
— m" "
». " »>
10.6
10.5
10.8
^PM
'AVER
17.4
3.1
11.7
"T2?3
1 3**4
11.1
i^rr
13.5
9?7
12.2
5.0
7?8
5.3
5.3
5.6
10.6
2.7
5?7
8.7
5.5
3 .'9
12.3
12.4
13.4
«• •«
25
-------
TABLE 7. ANNUAL DRY-WEATHER FLOW FOR COMBINED SEWER,
STORM, AND UNSEWERED AREAS
EPA
RFC
1
1
3
1
1
!.
AV
i.
2
AV
3
3
3
3
3
3
AV
a
u
a
t
u
>j
4
AV r
5
5
5
5
c
S
AV r
-.. i
STATF.
CT
MF
MA
NH
RI
VT
>FR 1
NJ
K'V
>FP ?
DF
DC
MD
PA
V*
wv
'FR 3
AL
FL
RA
KY
MS
MC
sc
TN
FR a
It
IN
MT
MM
OH
WT
En 5
AMNI_.
U3.5
03. 6
ai .0
"0.0
35.0
'Jt.J
38.1
fl 0 . 5
a 1 . o
0?;o
ttl.O
4l.o
«2.1
S5.8
56.5
46.5
42.3
'J6.0
iifi.3
«9.A
?5.0
37.2
31.0
26.0
37.2
32. '7 I
Of
r I'
18.1
31.2
15. £
11. fl
I5.'l
20.5
16.^
o.o
12.0
16.3
0.0
19.1
13.?
16.2
0.0
o;o
0.0
16.3
1«.4
26. a
14.8
16.6
.1 6 . f<
26.7
20. a
;.Y->;PA"
C H F ? f
STOP?-1
15.9
0.0
?n.i
0.0
1?.6
o.o
Jfi.^J
39.9
?a.a
16. a
19.1
JP.O
ie.c
1 * . 7
IP. 1
15. 8
17.6
1 R.6
15.5
15.1
17.0
16.6
9.7
16.8
16.2
16.7
!P. 4
J 1 .P
rHFR Fl
'EP YE/
! i M S F ^
6.9
6.1
8.0
5.6
10.1
6.3
a. 6
5.0
6.7
0.0
"~6?3
5.1
5.5
6.9
5.5
6.5
5,7
7,6
5.9
7.1
7.3
7.6
6.0
c.6
5.B
6.3
5.3
7,6
6.0
fR.3 . .
AVER
11.3
9.6
12.0
10.4
1 t . 8
11.0
11.2
33.2
12.0
?6.9
1 " . U
13.'2
13.0
10.8
13.5
10.2
1 1 .5
1 0.8
12.3
1 0.6
1 0.5
1 G.6
10.6
11.1'
1 A.6
1 1 .0
12.9
10.6
?I?5
11 .3
12. «
26
-------
TABLE 7 (cont'd)
EDA
RFC;
h
6
6
fc
6
A*'
7
7
7
7
A\'
8
A
6
?i
A
?5
A\'
O
•^
Q
vi
9
9
A\'
1 '.'
1 '.,'
1 "
AV
AV
STATF
ID"
AR
L*
MM
(IK
TX
Er, 6
I A
KS
MH
„
MF
Er, 7
cn
MT
wn
sn
IJT
UiY
?r r- 8
A*
A7
CA
HT
MV
'F;n 9
IP
no
! \>1 A
D t n 10
'.s.
I M / Y R
AM M| .
P F» F r p
afl.o
^6.0
f^.O
^2.7
"U .0
«:3
•51.3
^3.0
36. «
?6.5
31 .9
1^.5
1 a. o
?l.o
?5.0
^5.0
1 5 . 0
1 7. a
3 0 J 0
9.0
17.^2
?3.0
S.S
16.9
1 1 . 0
39.3
30.3
P6.9
33. u
I) P Y- 1-1 F A T H F R F 1
fIl-:CHFS PF'D VF^
CD'-'R 1 SThPM ! IIK'Sri^' !
Q.3! !^.«! 8.8
0.0' ? 0 . fl I 7.^
0.01 17.01 6.2
0>'! 1.7.Vl 5.5
c'6.6! l^.^i f.,0
1 a . 6 ' J 7 . /I 1 6.3
3H.1I 13.?l 6.5
1 6 . 0 | J y . S 1 7.1
1 3 . m 11 . /i i 1 o _ 5
19.0! 1 R . 0 i ^ , 6
1 5 . a I ' a . ? I 8.0
26. *8 1 17.-;; 6,3
0 . 0 i 1 « . ? ' 7.9
J « . 3 . 1 /J . 3 l P- , 3
1 6 . /4 1 ' 6 . U ! 7.1
0.01 i 7 . 1 ' S . 9
0.0' 'S.fi! 7.6
1 i
? 1 .' ^ ' 1 6 . 'J 1 6.6
1 8 . b ' 1 p- . S ' il . 9
I ( •
0 0 ! 16.^! S . 6
33.31 17.^1 S.7
0.01 1 8 . ? i 6.0
J9.'3' 16.P" 6.0
320bi 17.?! "3 .7
0 .' 0 i 1 « . ? ! « . 8
"?. "SI TL9I 6.S
15.\?1 I7.ni ^.5
1 ^ . ° i 1 6 . ri ! 6.6
1 ' "
??.SI .17.5' 6.3
flM
R^
AVER
1 0.4
16.2
1 1 . 0
1 0 . 0
10.I7
! 1.2
10>
1.1 . 4
"••••* •*•*
11.6
1 1. .7
1 1.2
1 ? . '.1
11. «
??.?
11.2
U)>
1 1. . 0
11 .'5
to.'i
10.6
1.3.4
1?.6
1 o . a
1 3 . 0
11. . '4
1 1 .a
«» «ai w t^ «•
i ! .
-------
TABLE 8. POLLUTANT LOADING FACTORS FOR NATIONWIDE ASSESSMENT
The following equations may be used Co predict annual average
loading races aa a function of land use, precipitation and population
density.
Separate Areas: Mg - a(l,J) • P • *2*P1V ' Y acre-yr
Ib
Combined Areas: M • 6(1,j) •
f2 20 d
<_ NB <_ 20 days
days
28
-------
street sweeping frequency. Loadings in combined sewer areas are assumed to
be 4.12 times as large as loadings in separate areas based on measured pol-
lutant loads from those areas. They are assumed to vary as a function of
developed population density. The intercept (0.142) was .determined based on
data for open space. The exponent (0.54) is based on the exponent of the
imperviousness equation at a population density of 8 persons per acre (20
persons per ha) such that pollutant concentration increases as a function of
population density. Lastly, the coefficient (0.218) is based on an average
of data points with a PD^ ranging from 5 to 15 persons per acre (12 to 37
persons per ha) to yield a value of f2(PDd) of 0.895 at 10 persons per. acre
(25 persons per ha). The street sweeping relationship was derived by mak-
ing numerous runs of STORM with varying street sweeping frequencies.
Nationwide Quality Assessment
Annual BOD5 loads were calculated for the 248 urbanized areas for both
wet and dry-weather conditions, the latter under the assumption of 0.17 Ib
per person-day (0.08 kg per person-day). The national summary is shown in
Tables 9 and 10. Loading rates for untreated dry-weather flow are higher
than for wet-weather flow. However, if 85 percent secondary treatment is
assumed for dry-weather BOD generation, wet-weather loads are seen to be one
third of the total residual loadings in urban areas. Moreover, BOD loadings
from combined sewered areas are comparable to loads due to secondary effluent.
COST ASSESSMENT METHODOLOGY
Control Technology and Associated Costs
A wide vareity of control alternatives are available for improving the
quality of wet-weather flows. (7,8,9) Rooftop and parking lot storage,
surface and underground tanks, in-line storage, and storage in treatment
units are used to control the flow. Wet-weather quality control alternatives
can be subdivided into two categories: primary devices and secondary devices.
Primary devices take advantage of physical processes such as screening, set-
tling and flotation. Secondary devices take advantage of biological pro-
cesses and physical-chemical processes. These control devices are suitable
for treating stormwater runoff as well as combined sewer overflows. At the
present time, there are several installations throughout the U.S. designed
to evaluate the effectiveness of various primary and secondary devices.
Based on these data, the representative performance of primary devices is
assumed to be 40 percent BOD5 removal efficiency and that of secondary
devices to be 85 percent BOD^ removal efficiency.
"Storage" devices will typically be used in conjunction with the above
"treatment" devices. The two purposes are interrelated. Wastewater detained
a sufficient time in a storage unit will undergo treatment. On the other hand,
treatment units also function as storage units in that they equalize fluctu-
ations in influent flow and concentration. The STORM model, which was used
in this assessment, assumes that no treatment occurs in storage and "treatment"
29
-------
TABLE 9. DRY-WEATHER BOD LOADINGS
I
F.PA
RFC
, 1
1
1
1
1
1
AV
2
2
AV
3
3
3
3
3
3
AV
o
o
a
^
a
4
a
&
AV >•
5
. 5
5
5
5
5
STATE
in
CT
ME
MA
NH
Rl
VT
'FP 1
Mj
NY
?ER 2
OF:
DC
MD
PA
VA
WV
?Er, 3
Al.
FL
GA
. KV
MS
MC
sc
JM
EG a
IL
IN
Ml
MM
PH
WT
AV PFG 5
IM/YRI DF
AN'NL.I CL
PPETPI COMB
43.71 836.
03.51 51".
43.61 70a.
01.01 560.
40.01 984.
35.0! 540.
41.11 700.
42.81 948.
38.1 I242R.
40.512284.
45.01 760.
41.011950.
0.
41.01 94?.
42.91 660.
41.01 555.
42.1! 846.
55.61 0-
^6.51 88?.
46.51 609.
42.31 747.
54.51 0.
46.01 0.
46.71 0.
46.31 755.
49.61 663.
35.011236.
37.21 683.
31.01 875.
26.01 76P.
37.21 77P.
29.711324.
32.71 94?.
.
30P.
n.
?°?.
?34.
?S4.
3?0.
?53.
30?.
?64.
340.
?73.
33(1.
33P.
351 .
277,
304.
?95.
?7().
?9n.
?57.
?47e
35.1 .
°?7»r
521.
000.
550.
48*1.
546.
509.
533.
520.
1533.
P7Q-
^53.
1?03.
647.
60p.
60?.
4PP.
6??.
473.
533.
490.
566.
490.
487.
468.
491 .
507.
676.
506.
594.
49?.
531 .
522.
•» m *e q> **
571.
30
-------
TABLE 9 (cont'd)
1
EPA ISTATE
RFGI ID
6! AR
61 LA
61 NM
61 OK
6 1 TX
AV PEP to
7! IA
71 KS
71 MO
7 1 NE
AV PFR 7
8! CO
8 1 MT
8 ! MD
8 ! SO
8! li T
8 1 WY
AV PFn 8
-9! AK
9] AZ
9 ! CA
9 I Hi
9 1 NJV
AW PER 9
1 0 1 I n
101 OP
L 1 0 1 /I A
AV PER 10
IN/YR
AM ML.
PPECP
as.o
56.0
9.0
32.7
31.0
35.3
31.-3
33.0
36.8
26.5
31-9
14.5
14.0
21.0
25.0
1.5.0
15.0
17.4
30.0
9.0
17.2
23.0
5.5
56.9
11.0
39.^3
3o;i
26.'9
AV/ U.S. 1 33. 4
.».( 1
OF
(I
COMB
430.
0.
0.
0.
122R.
675.
1763.
741.
621.
*•*•••«
880.
712.
123P.
I 0.
662.
759.
0.
0.
988.
1 854.
0.
1539.
0.
893.
1507.
0.
810.
703.
734.
1039.
JY-WFA1
BS/ACP
STORM
712.
961.
786.
815.
766.
803.
612.
714.
529.
833.
*57.
798.
657.
662.
759.
790.
693.
760.
854.
761 .
798.
8/41 .
777 .
797.
657.
780.
785.
763.
807.
.....
•HFR sno
JE-YTAR)
UMSFWr AVER
40«>T
352.
?87.
?5?.
278.
?9J .
299,
328.
46=;.
P60.
367.
?9p.
36iJ.
384.
328.
27J.
340.
303.
227.
268.
?6?.
277.
277.
263.
40S.
?88.
302.
307.
285.
48P.
749.
506.
464.
496.
520.
473.
52^.
537.
541.
520.
55^.
52^.
563.
516.
49S.
SP6.
532.
466.
49?.
617.
^83.
480.
601 .
•^26.
52P.
52S.
526.
S94 .
31
-------
TABL
EPA
RFG
1
1
. 1
1
. 1
1
AV E
?
2
AV
•j
-f
3
, 3
•^
3
AV
n
4
. 4
4
4
4
4
4
.AV P
5
, 5
5
5
5
5
E 10. Wl
STATE
ID
. CT
ME
MA
NH
PT
VT
F.R 1
NJ
NY
'FP 2
DE
nr
MD
PA
VA
iMV
?FR 3
At.
FL
, RA
KY
MS
NC
sc
. TN
FP 4
IL
IN
MI
MN
nw
WI
AV PEP. 5
1 Bl
ET-WEATHER BOD LOAC
JM/YRI K'FT-WFAI
A^M! . I (|_R?/ACF
PPECPI COMBISTHRM
43.7
43.5
43.6
41.0
40.0
35.0
41.1
42.8
38.1
40.5
45?0
4lT(J
u2?o
41.0
42.9
41.0
4?;i
55.8
56;5
46?5
a 2. '3
54.5
46.0
46.7
48.3
49.6
35.0
37.2
31.0
?6.0
37.2
P9.'7
32.7
158.61 37.8
144.31 0.0
152.91 39.7
137.81 0.0
152.91 34.6
117. 7J 0.0
IflOi 7R.7
160.11 39.2
190.81 41 .1
167. 8J 40.1
H62J2J 39.4
1187.41 37.1
1 0.01 3P.O
1147.01 37.4
!147.;6I 38.3
137^61 38.6
1147.51 37.8
1 0.01 48.7
1 9 C . 0 I 5 1 .' 0
159.71 40.4
153.2) 37.?
0.01 46.2
0.01 39.0
0.0 I 40.2
166.21 . 42.3
161.0). 44.9
133.61 ?6.3
128.61 31.5
114.51 27. t
90.51 22.3
125.3! 31-9
116.21 23.7
124."OI 27.4
HNGS
rHFR BC
?E-YTAf
UK'SFH
31.8
32.1
31.6
31.0
?P.8
?7.9
31.3
30.1
?6!i
29.1
33.3
oTo
3UO
?8.0
31.8
3?. 3
?9.6
41.6
40.6
35.3
30.0
40.5
34.0
35.3
34^7
J.7^2
24.6
?6.3
?2.7
'8.2
?4.6
21.5
ID
O
AVER.
56.9
1P2.4
56.9
94.0
59.1
6B.5
62.2
3P.2
95.9
M.u
~55?5
87.8
35.6
45.1
45.8
104.1
47.9
4& .4
45.9
58.6
39?8
42.9
36.0
37.2
46.8
45.5
64.6
68. 6
55."U
30.3
49.3
31 :i
23^5! 52?8
32
-------
TABLE 10 (cont'd)
EPA
RFC
ft
ft
ft
ft
ft
AV
7
7
7
7
AV
R
R
e
R
P
P
A v
P
0
o
9
o
AV
1 'i
1 <»
1 "
AV
AV '
STATE
in
AP
LA
MM
OK
TV
'FT, f,
TA
KS
wn
MF
11 Fr 7
cn
uj
MO
S^
III
U! Y
"FT, 8
AK
A7
TA
HT
KJV
-FT- 9
TH
nP
I*; A
•»(-n 10
I.*?.
IM/YR
A MM! .
pftrp
46.0
^6.0
9.n
32.7
31 .0
35.3
31 .3
•^3.0
^ft?e
?ft.5
^T?9
1ii.5
1 ^.0
21.0
£5.0
15.0
15.0
"7%
^o.o
o.O
17.2
?3.0
5.5
TftTo
1 1 .0
WF
rnt-M
l?.p.a
0.0
n.'o
0.0
200."T
1 ci 7 . 3
13h.l
1 ? 1 . 9
12"?.?
9ft. H
1Z1 .7
50.?
0,0
73.5
90.1
0.0
o.o
ft".?
111.0
0.0
Pn = 7
o.o
26.,-?
3ft. «
0.0
39.3 1/1 ft . 0
^0.3 103.9
?fr.9 ) 1 ft. 1
•?3.« 136.6
'T-WFA1
R ,c / A C I
S T P R M
^3.?
55.1
7.9
?9.0
?9.7
:< 3 . 'J
?ft.?
?7.Q
PP.?
?3.R
P7.0
1 ?.«
) ?.0
17.9
?1 .°
M.a
I P.°
13.7
?7.0
7.0
1?.5
? 0 . ft
c.o
1 ?.U
9.3
?CJ .9
')
AVER
/JR. 1
'IQ.9
7.2
P5.8
P7.5
7, 0 . ?.
?C.(I
37.5
70.3
in . B
^O.P
1 1 .ft
1 1 .3
1 9 . (i
?1 .3
1 ? . 0
1 P.U
1 "*.()
?^>.5
ft. 3
1 «.°
1 R.R
il.9
t " . 2
f^.°
53.8
^e.3
/I ft. 5
"3.6
33
-------
is assumed to be complete removal of all pollutants routed through treatment.
Thus, for the purposes of this assessment, no treatment is assumed to occur
in storage and control costs are assigned accordingly. This assumption tends
to underestimate the costs of storage since all provisions for solids handling
are included in treatment.
Cost of Treatment and Storage
Cost functions developed for various wet-weather quality control devices
are presented in Table 11. These costs include provisions for sludge handling,
engineering, contingencies and land costs. All treatment units exhibit eco-
nomies of scale, i.e., unit costs decrease as plant size increases. Thus,
there is an incentive to build larger units. The optimal size treatment unit
can be found by comparing the savings in treatment cost of going to a larger
unit with the increased piping costs.
For this analysis the number and flow rate of stormwater discharges in
urban areas were unknown. Thus, it is not possible to determine the optimal
mix of treatment plants and pipelines. Therefore, representative annual treat-
ment costs of $4,000 per mgd for primary devices and $15,000 per mgd (3,787m3)
for secondary devices were used. Review of data on the cost of storage indi-
cated wide variation. Thus, the relatively simple relationship shown in Table
11 was used. Annual storage costs are estimated as a function of gross popu-
lation density. The curve was derived using an unamortized capital cost of
$0.10 per gal ($0.026 per 1) for PD = 5 persons per acre (12.4 persons per
ha) and $0.50 per gal ($0.132 per 1) for PD = 15 persons per acre (37.1 per-
sons per ha).
Relationship Between Storage/Treatment and Percent Pollution Control
STORM(3,4) was used to evaluate various storage/treatment options for
controlling stormwater runoff pollution. This model assumes that the study
area can be characterized as a single catchment from which hourly runoff is
directed to storage and treatment.
STORM uses a simplified rainfall/runoff relationship, neglects the
transport of water through the city and assumes a very simple relationship
between storage and treatment. However, these simplifications are essential
if one hopes to do a continuous simulation. The continuous simulation approach
was used because no general concurrence exists regarding an appropriate single
event that one should analyze. The degree of control can be expressed in
terms of the percent of the runoff treated, the annual number of overflows,
or the amount of pollutants discharged to the receiving water.
As described in the User's Manual, STORM computes the runoff based on the
composite runoff coefficient and the effective precipitation. (3) The depres-
sion storage must be satisfied before the runoff coefficient is applied to the
precipitation. The amount of depression storage available in ditches,
depressions, and other surfaces is a function of the past precipitation and
the evaporation rates. Each hour that runoff occurs, the model compares it
34
-------
TABLE 11. COST FUNCTIONS FOR WET-WEATHER CONTROL DEVICES
Annual Cost: $/yr
Device
Primary
Control Alternative
Swirl Concentrator0^-6
Microstrainere'f
Dissolved Air Flotation6
Sedimentation6
Amortized Capital
CA = 1Tm
or1Sm
I m
1,971.0
7,343.8
8,161.4
32,634.7
Representative Primary Device — Total
Secondary
Storage
Contact Stabilization9
Physical-Chemical6
Representative Secondary
High Density (15/ac)
Low Density (5/ac)
Parking Loth
Rooftoph
19,585.7
32,634.7
Device Total
51,000.0
10,200.0
10,200.0
5,100.0
0.70
0.76
0.81
0.70
Annual
0.85
0.85
Annual
1.00
1.00
1.00
1.00
Operation and
Maintenance
OM = pTi
p q
493.0
1,836.0
2,036.7
8,157.8
0.70
0.76
0.84
0.70
Total
TC = wTz
or wSz
w z
2,464.0
9,179.8
10,198.1
40,792.5
0.70
0.76
0.84
0.70
Cost = $4,000 per mgd ($0.793/m3/day)
4,894.7
8,157.8
Cost =$15,000
0.85
0.85
24,480.4
40,792.5
0.85
0.85
per mgd ($3.93/m3/day)
51,000.0
10,200.0
10,200.0
5,100.0
1.00
1.00
1.00
1.00
Representative Annual Storage Cost' ($ perac-in) = $122 e°-16(PD)
Tk = Wet-Weather Treatment Rate in mgd; S1 = Storage Volume in mg
aEN R = 2,200. Includes land costs, chlorination, sludge handling, engineering and contingencies.
bSludge handling costs based on data from Battelle Northwest, 1974.
cField and Moffa, 1975. 1
dBenjes, et al., 1976.12
el_ager and Smith, 1974.8
fMaher, 1974.
9Agnew et al., 1975.14
hWiswall and Robbins, 1975. 15
'For T ^100 mgd. No economies of scale beyond 100 mgd (378,500 m /day).
'PD = giuss population density, persons/acre.
kOne mgd = 3,785 m3/day.
'One mg = 3,785 m3
35
-------
to the treatment rate. As long as the runoff rate is less than or equal to
the treatment rate all the runoff passes directly through the treatment plant
and storage is not utilized. When the runoff rate exceeds the treatment rate,
the excess runoff is sent to storage. If excess runoff occurs frequently
enough to exceed the storage capacity then overflow occurs. When runoff falls
below the treatment rate then storage is depleted at the excess treatment rate,
The hourly occurrence of treated runoff, stored runoff, and runoff that has
overflowed is tabulated for the entire record of rainfall. Included in the
output is the annual number of overflow events and the percentage of the run-
off that overflowed to the receiving waters. This type of analysis was car-
ried out for different storage capacities and treatment rates.
STORM Input Data for Detailed Study of Five Test Cities
STORM requires several input parameters that- characterize the urban area
under study. These include hourly precipitation, total area, land use types
and percentages, percent imperviousness and curb length per area for each land
use. Local data used to run STORM on the five study areas were collected by
onsite interviews. The percent imperviousness and length of street gutters
were found by their relationship to population density using Stankowski's
equation for imperviousness(5) and APWA's equation for curb length density,
i.e. ,
PT")
GT = 0.0782 - 0.0668(0.839) d (7)
Li
where G = curb length per area, miles/acre, and
Li
PD, = developed population density, persons/acre.
Daily evaporation rates for each month are from a report by Thornthwaite
and Mather.(16) The depression storage was assumed to be 0.01 in. (0.025 cm)
for all cities. Hourly precipitation data were acquired from the US Environ-
mental Data Service in Asheville, North Carolina. Twenty-five years (January,
1948, to December, 1972) of hourly data were obtained for the five test cities.
Two and one-half years (July, 1970, to December, 1972) of data were obtained
for all stations in the United States.
The frequency distribution of each of the twenty-five years of rainfall
was analyzed for each of the five cities. Little year-to-year variation in
distributions was noted, but there was considerable variation among cities.
In the early stages of the research it became apparent that multiple
runs of STORM would be required on each city to adequately determine the
effectiveness of different storage capacities and treatment rates. It was
also discovered that making STORM runs using the entire twenty-five years of
rainfall for each city was expensive and time consuming. Since the useful
information was in terms of the overall level of control of the runoff, it
appeared adequate to run STORM on a single year if the results were the same
as running STORM for the entire twenty-five year period.
36
-------
Results
Storage/Treatment Isoquants—
For each storage/treatment rate combination, there is a value for the
percent of the runoff and pollutants which are "treated". By making several
runs at different combinations of treatment and storage, points were generated
representing different levels of control. Then isoquants were drawn connect-
ing the points that represent combinations of storage capacities and treat-
ment rates which give equivalent percent runoff and/or pollutants "treated".
If the concentration of pollutants is constant and "treatment" efficiency is
1.0, then percent runoff control is synonymous with percent pollutant control.
Obviously, this is not the case. Thus, account needs to be taken of —
1. treatment efficiency, and
2. variable concentration due to first-flush effects.
Adjustment for Treatment Efficiency—
Let R denote the percent runoff control and 17 equal treatment plant
efficiency. If R^ denotes the percent pollutant control, then to realize R-^
one needs to process R^A? of the runoff. Note that R^ may be percent BOD
removal, percent SS removal, etc. The following representative treatment
efficiencies, in terms of BOD5 removal, were assumed for primary and secondary
devices.
Assumed Efficiency, rj
Treatment Device (BOD Removal)
Primary 0.40
Secondary 0.85
Thus, if one desires 25 percent BOD5 removal with a primary device, then
62.5 percent of the runoff volume must be processed whereas only 29.4 per-
cent of the runoff needs to be processed if a secondary device is selected.
Thus, to convert percent runoff control isoquants to percent pollutant
control isoquants, one uses —
Rl
R = , 0
-------
effectively because of the greater relative importance of capturing the
initial runoff. The first flush is accounted for by defining the output in
terms of pollutant control directly.
Mathematical Representation of Isoquants
The storage/treatment isoquants are of the form
T = T, + (T» - T1)e"K (9)
where T = wet-weather treatment rate, inches per hour,
T, = treatment rate at which isoquant becomes
asymptotic to the ordinate, inches per hour,
T9 = treatment rate at which isoquant intersects
the abscissa, inches per hour,
S = storage volume, inches, and
K = constant, inch
A relatively large storage reservoir is required to operate the treat-
ment unit continuously. Thus first flush effects would be dampened out and
the effluent concentration from the reservoir should be relatively uniform.
Thus, if stormwater entering the treatment plant has a relatively uniform
concentration, then T]_ can be found as follows for 8,7bO hours per year:
*- I O -T f f\ \1 f\f\ ) ȣ\.
where AR = annual runoff, in. per year,
a = coefficient defined by AR and conversion factors,
and
R = percent runoff control.
By relating the parameters Tj_, T2-T]_ and K to the level of control R,
one equation was developed for each of the five cities. The T2~T-i and K
terms versus R were found to be of the following general form:
T2 - T! = behR (11)
K = de"fR (12)
Based on this analysis the following general equation for the isoquants
is obtained:
T = aR + behR"(de )S (13)
The values of parameters a, b, h, d and f for various cities are presented in
Table 12. The correlation coefficients for each fit were all above 0.99.
38
-------
TABLE 12. VALUES OF PARAMETERS FOR ISOQUANT EQUATIONS
FOR DEVELOPED PORTION OF THE TEST CITIES
Percent BOD Control with First Flush, n = 1.0.
in
Test City
San Francisco
Denver
Minneapolis
Atlanta
Washington, DC
a
. hr-^% R)-1
(cm hr )
0,0000107
(0.0000271)
0.0000064
(0.0000162)
0.0000120
(0.0000304)
0.0000185
(0.0000469)
0.0000197
(0.0000500)
b
in. hr"1
(cm hr )
0.002165
(0.005500)
0.001363
(0.003462)
0.001366
(0.003469)
0.002586
(0.006569)
0.001896
(0.004816)
h d
(Z R)"1 in.'1
(cm )
0.03884 211.3
(536.6)
0.04398 185.0
(469.8)
0.04820 241.6
(613.7)
0.04682 190.2
(483.2)
0.04879 228.8
(581.3)
f
(% R)"1
0.03202
0.02792
0.03016
0.03125
0.03393
-------
The results for Minneapolis, presented in Figure 1, show the isoquants
calculated by the isoquant equation. Also shown are some actual data points
for a treatment rate of 0.01 in. (0.025 cm) per hour and varying amounts of
storage. The boundaries of the five regions are shown in Figure 2.
The optimal expansion path can be found using
CT
c = mSST (14)
where c = unit cost of storage,
o
c = unit cost of treatment, and
T
MRS = marginal rate of substitution of storage
for treatment.
A generalized method for evaluating the optimal mix of storage and
treatment for any desired level of pollutant control has been presented.
This method can be used for any city in the United States to obtain a first
approximation of control costs. Five cities (Atlanta, Denver, Minneapolis,
San Francisco, and Washington, DC) were used in the more detailed analysis.
The effects of treatment plant efficiency and first flush are included.
An evaluation was made of the relative desirability of using a mix of
storage with either primary treatment or secondary treatment. The basic
tradeoff to be evaluated is whether primary treatment is sufficiently less
expensive than secondary treatment to offset its lower removal efficiency
which necessitates treating a much larger amount of flow to effect an equi-
valent BOD removal. The results indicate that a primary type of facility
is preferable up to BOD removals of about ten percent. A secondary facility
is preferable for higher levels of control.
The annual average percent runoff control and the annual number of
overflow events were correlated to permit the reader to use either criterion
as an effectiveness metric. A precipitation event was assumed to terminate
following 12 hours .of no precipitation.
The final assessment results (annual costs per acre) are shown in
Tables 13, 14, and 15. In order to obtain an overall wet-weather pollutant
control of, say, 50 percent in a given urbanized area, the optimal strategy
is to use a blend of control in the combined, storm, and unsewerd por-
tions of the urbanized areas such that the marginal costs of control in
each of these three areas is equal. The results are shown in Table 16.
Knowing this result and the control cost equations for each type of sewer-
age system in each urbanized area, the optimal cost per acre can be deter-
mined as shown in Table 17. Lastly, the costs per acre are multiplied by
the acreage in the combined, storm, and unsewered categories to obtain
the final assessment results which are shown in Table 18. The results
indicate that, for the entire U.S., the total annual costs for 25
40
-------
.00
.90
-80-ffl
.70-4
.60 H
,50 -B
o:
o
.201
.10 1
.00
Tt cm/hr
.01 .02
.000
T, cm/hr
,004 .008 .012 .OI6
.000 .002 .004 .006
T, in/hr
ANNUAL RUNOFF = 10.50 in..
.000
-010
TREATMENT,!, in/hr
.020
.008
.00
rl.2
r-I.O
k80
h-60
CO
H.40
20
.00
.030
Figure 1. Storage/treatment isoquants for percent BODg removal with
first flush — Region III - Minneapolis
41
-------
Figure 2 Mean annual precipitation in the United States, in inches,
and regional boundaries
Source: Weather Bureau Climatic Atlas of the Unites States, 1968
-------
TABLE 13. ANNUAL CONTROL COSTS-COMBINED AREAS
1 1 1
ICPAISTATE
Rf M IP .
1 i CT
1 1 HT
t 1 MA
1 1 MH
1 I PT '
1 1 VT
A" RET, 1
? 1 MY
AV Pert ?
?l DC
31 nr
3 1 *n
31 PA
3 1 VA
3 1 wv
A** Qrr, 3
t 1 AL
t i FL
i! 1 KY
t i MS
Hi w r
tl sC
A v ® E ft ^
SI IL
b i IS
5 1 MT
51 -il
AV "EB 5
25T
33.
16.
?7.
16.
«-<.
13.
U)3.
97.
?".
11".
r.
u«.
?<*.
17.
3s.
I'.
53.
2s.
??.
0.
0 .
r. .
35.
3C.
76.
?7.
3U2.
799.
(116.
t |
S10. 1
187. 1
196. 1
A 1 1 . |
157. j
3SU. I
1068. 1
2797.1
3-5U/..I
0. 1
711. j
3U5.I
? n 6 . 1
O.I
MO. 1
310.1
T5C'. 1
U 1
0 1
0 . |
.
1'U.
0.
?5.
5u.
0.
0.
95.
107.
0.
2'I7.
0.
36.
237.
0.
12R.
eo.
90.
t ^ 1
'L CU3
C T )
0.
t'.
0.
992.
371.
1S4?.
193.
ins.
21".
2 ^ •
£30.
0.
"it.
u.
2B6.
2fl7.
0.
761.
0.
96.
732.
0.
3U3.
312.
25U.
Rn t
r
B5X
TflT.
0.
0.
o.
1665.
608.
2688.
3P7.
3?2.
349.
68fl.
0.
iau.
221.
0.
0.
aa5.
C26.
0.
1?01.
0.
112.
1150.
0.
509.
31«.
370.
ft 1 5
43
-------
TABLE 14. ANNUAL CONTROL COSTS-STORM SEWERED AREAS
BFC
1
1
J
1
1
1
AV
2
i
AV
3
3
3
J
3
j
AV
<•
<•
1
a
t
a
U
£
AV (
5
5
•;
$
5
c
'
in.
CT
MT
HA
MM •
Pi
V*
"EC. 1
Mj
wv
'FG <>
OF:
nc
vn
PA
A'V
-EG 3
AL
FL
KY
'•"*
•JC
•PI
F r u
ll
!»>•
JI
~"\'~
OH
*.'T
AV CEP. $
?5*
27.
n.
a?.
ii .
? 5.
M
36.
ai.
«6.
6 ' .
?«J.
35.
3?.
3".
35.
?*.
33.
ao.
5'1.
31.
32.
37.
32.
31.
0" .
'jn.
15.
32.
25.
" ?"7
£! fl
?5 .
'n(«/
fJCt
7".
0.
127.
f |
67.
0.
107.
12?.
3T5.
r' o.
««'.
t<;«;.
or ^
KM .
1 " 3 .
Pi .
1»0.
lie..
I7,".
Pu.
w,.
1 0 i) .
?(>.
P. 3.
11! .
1 1 (i .
'1 ' .
PP .
67.
.....
11?.
''M .
#,0.
M rjsr "
'7-j S 1 PbX "IflFG
? 5 *' .
r.
3«'.
I1.
|MC
').
31".
3 'j !' .
Mi3.
7S/-.
?'^.
3' i.
27'^.
•«'i5.
3 0 •> .
c1!^.
?<=.«.
roc.
^ c") .
??".
?p?.
p n .
2J3.
.3 1 X .
"$ ': 3 .
* t 'i .
2U3.
1 » 1 .
T^r
. .< 1 5 .
no.
1R9.
(l.tt 6
U. M 6
.£!!:!!..*
it 1 1 A V '
i. ej U 7
2271.11 7
n?3.'l 7
X74.IIAV «
('3D. II fi
i'73 . H E
'6d.ll 8
1 1 1 . M P
tu1;. ii A v t
S7U . M 9
iCU. M 9
/'TS. II •»
i 0 3 II 9
<^2 M A V t
'i S o 1 1 10
:<•••!. ii ie>
f*TATp
JP
AR
L*
IJM
riK
T*
'PC 6
T S
KS
•Fn 7
en
•-.T
•JO
s1?
llT
'FG 6
A«
A?
C*
MT
N V
>i-r. 9
TO
10
*A
,
\ <>.
13.
1".
22.
4 n
u.
16.
?•>.
6.
!'•.
13.
uu.
ai.
3(1.
3?.
'( */
CO*
CJ J
p /I o
.37.
Pi.
76.
50.
63.
no.
70.
56.
^ c *
7^.
5.
112.
170.
-------
TABLE 15. ANNUAL CONTROL COSTS-UNSEWERED AREAS
UT
RFGI in"
11 CT
..I!..:E.
1 1 PA
1 1 MM
1 1 RT
1 1 vT
AV BEG 1
21 K'J
21 VJY
AV ppr: j>
3i CE
31 nc
31 MO
31 PA
31 VA
3 1 sv
AV PFP 3
fll AL
a i FL
ai RA
a i *Y
flt V«5
a i \.
^3.
a1?.
««?.!! 61 AP
107. II 61 I A
93.11 61 'i*
113.11 61 OK
77.H 61 TV
13U. H AV PPR 6
«U.II 71 I»
72.11 71 Kf!
7«.ll 71 "0
72. '1 71 MT
1 01 . H 4V PFfi 7
o.ii fli r^
90. M 61 ^T
73.11 6' ^n
fiS.II 81 SO
] 01 . '! PI 'JT
?! . II f 1 «Y
tp7.iiAv PEG P
) 1 3. M 9| AX
121.11 91 A 7
rfU H e 1 C A
1 ~;3 II ° I t-I
f-ia-!i..!!..^.
121 . M AV PEC 9
no. n i6i in
j j «. ii le i no
7B.ll KM *4
79 |l A V P£H 10
70. II---I
7J.
77.
71.
"
2?r
15.
a.
7.
fi.
8.
0.
15.
6.
1 1 .
6.
7.
6.
7.
6.
7.
6.
P.
3.
1.
7.
2.
1.
6.
1?.
1 1 .
1).
fi _
eriNTRf
«-n*/'
30.
37.
q.
IP.
2^.
20.
22.
3P.
15.
27.
H.
19.
17.
17.
la.
IP.
1°.
7.
11.
IV.
a.
11.
16.
30.
27.
27.
22.
1L COS
CPE)
loo.
°5.
uM.
«A.
52.
50.
"7.
J no.
37.
7".
3«.
43.
'!?.
a3.
35.
a5.
37.
ne.
IF.
?7.
«?.
i:l.
27.
3P.
77.
68.
56.
r
ia/>.
13*.
30.
66.
1*.
32.
73.
PP.
1^7.
53.
1 0-3.
48.
62.
6?.
62.
50.
64.
53.
60.
25.
to.
61.
11.
™.
55.
112.
00.
tnu.
PI.
45
-------
TABLE 16. OPTIMAL PERCENT CONTROL FOR SPECIFIED OVERALL CONTROL
tPAISTATE
R€C 10
1 CT
i Mr
1 MA
1 1 NH
11 RI
1 VT
21 NJ
2 NY
3! DE
3" DC
3 HO
31 P*
31 VA
3 WV
1
a AL
01 FL
4 G*
4 KY
U 1 MS
41 WC
4! SC
41 TN
1
51 IL
51 IN
5' MT
5 1 MM
5 PH
51 wl
COMB
31.0
27."
34.6
28.3
26.5
3?.0
29.0
27.3
36.7
25.6
0.0
3?. 2
44.6
27.2
0.0
«0.9
37.8
44.0
0.0
0.0
0.0
39.0
22.0
28.4
28.2
34.4
30.6
IB. 6
25X
STORHIUNSEw
3. '
0.0
0.0
0.0
7.0
0.0
4.0
2.6
3.5
22.9
16.1
8.9
3.8°
0.0
10.4
9.9
0.9
6.6
12.1
11.7
13.1
1.2
2". 7
0.0
0.8
0.0
0.0
20.4
28.6
3.0
26.1
3.7
32.1
0.8
42.7
54.8
27.5
0.0
46.2
42."
36.5
6.5
36.3
43.0
21. U
37.3
35.3
34.7
33.9
31.9
uo.e
19.3
27.7
?9.5
28.3
35.8
COMB
S4.6
52.6
60.5
53.2
50.5
56.9
48.9
51.9
61.1
48.9
0.0
55.7
69.2
52.3
0.0
6407
62.3
68.4
o.o
0.0
0.0
63.3
«5.7
53.7
52.6
58.6
•56.3
39.7
OPTICAL. PERC
50t
3Tr>HMiuwsrn
29.1
0.0
in. a
o.u
32.1
0.0
2R.1
27.4
27.9
52.8
40.4
33.5
27.8
9.6
3/1. a
33.9
25.4
30.6
36.2
35.6
37.3
25.2
5'2.6
1/1.6
25.9
23.6
16.8
«6.7
>>6.1
?8.7
5«.4
?"».5
5<».a
?6.0
70.2
fll.O
54.0
0.0
73.0
70.3
<-3.5
33.1
62.1
69.2
47.4
*«.o
61.0
60.4
59.5
58.1
70.4
46.6
54.8
56.2
56.9
h3.5
:E^T CONTROL
75*
COXBI3TORMIUN3EW
78.1
77.7
78.1
75.1
el. 8
77. •»
78.5
S5.0
72.0
0.0
«3J3
flS.O
77.?
0.0
*5.0
85.0
«5.0
0.0
0.0
0.0
«5.0
71.9
78.3
77.0
83.1
80.7
63.7
54.2
42.2
0.0
57.8
0.0
63.0
5*1.3
52.7
82.6
TO. e
62. a
61.5
33.9
62.1
66.6
51.6
62.5
62.5
61,3
61 .6
50.9
83,5
39.1
51.0
47.8
40.9
76.6
«3;5
54.5
«1.2
55.3
85.0
51.2
85.0
"5.0
81.0
0.0
85.0
«5.0
85.0
59.3
«5.0
85.0
75,1
65.0
85.0
85.0
65.0
85.0
65.0
73.6
«2.0
82.7
64.0
65.0
COMR
85.0
P5.0
65.0
65.0
65.0
65.0
35.0
65.0
65.0
85.0
0.0
65.0
65.0
65.0
0.0
«5.0
65.0
65.0
0.0
0.0
0.0
85.0
85.0
*5.0
65.0
65.0
85.0
85.0
STORM lUNSE'w
65.0
0.0
95. 0
0.0
85.0
n.o
85.0
65.0
85.0
65.0
65.0
65.0
' 65.0
65.0
85.0
65.0
85.0
65.0
65.0
85.0
85.0
65.0
85.0
85.0
85.0
85.0
65.0
85.0
85.0
65.0
65.0
85.0
85.0
65.0
65.0
65.0
65.0
0.0
65.0
65.0
65.0
65.0
65.0
85.0
85.0
85.0
65.0
85.0
65.0
85.0
85.0
85.0
85.0
65.0
85.0
65.0
46
-------
TABLE 16 (cont'd)
1
IEPA
IRFC
6
e
6
6
6
7
7
7
7
8
*
8
e
e
8
9
9
9
9
STATE
10
AR
LA
NM
OK
TX
1*
KS
MO
CO
WT
NO
SO
UT
WY
AK
AZ
CA
HI
91 WV
10 10
25X 1
CnMQISTORMIUNSEW
55.0
0.0
0.0
0.0
25.7
38.2
31.4
27.7
24.6
0.0
51.4
44.6
0.0
0.0
36.1
0.0
19.7
0.0
30.2
0.0
101 OR 1 31.9
10 WA
32.2
1.4J 19.31
13.61 54. 31
7.41 41.6
5.81 39.5
10. ?l 39.1
1
15.71 36.5
4.21 27.1
0.01 4.2
0.01 28.7
1
9.61 44.7
16.71 36.7
15.51 32.4
9.51 35.5
6.91 41.9
13.01 36.5
1
0.31 39.0
8.61 41.6
13.41 47.6
10.61 46.0
2.51 35.6
1
16.41 33.7
0.01 27.7
0.01 23.8
80.1
25.51 44.6
0.0 37. 7j 81.6
0.0
o.o
44.9
30.9
62.6
56.3
52.5
05 4
0.0
76.1
68.9
0.0
0.0
60.2
0.0
41.7
o.o
54.1
o.o
57.0
57.8
31.51 67.5
29.41 65.5
3/1.31 65.3
1
41.41 63.9
28.71 siTs
24.11 ?9.B
20.3! -56.3
1
31. Ul 70.9
41.31 62.3
40.1! S8.3
33.61 61.4
30. 9j 67.8
37.41 62.1
2/1.41 64.9
32.81 67?4
38.61 74.4
35.01 71.9
27.01 61.7
1
41.01 59.1
22.61 54.1
ENT CnNTRDL
COMB ISTOftM IUNSEW
85.0
0.0
0.0
69.2
53.7
85.0
56.8
71.1
64.4
61.7
64.9
73.5
54.4
81. '1 1 49.2
76.8
73.8
0.0
85.0
85.0
0.0
0.0
85.0
0.0
69.9
o.4o
80.1
0.0
81.6
19.71 50. 7i 82.5
44.8
67.3
67.9
67.6
61.6
64.3
64.6
56.4
65.1
71.1
68,2
53.5
65.6
47.2
44.3
77.5
85.0
85.0
«5.0
85.0
85.0
80.8
55.4
P3.4
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
84.5
80.1
76.6
COMB
85.0
0.0
0.0
0.0
85.0
85. 0
85.0
85.0
85.0
85.0
0.0
?5.0
85.0
0.0
o.o
85.0
0.0
85.0
0.0
85.0
0.0
85.0
85.0
85X
STORM
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
S5.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
85.0
47
-------
TABLE 17. OPTIMAL ANNUAL COST PER ACRE FOR SPECIFIED
OVERALL PERCENT CONTROL
IC»A
BEG
1
1
1
1
1
1
2
2
3
3
3
3
3
3
a
4
4
4
4
U
4
4
5
5
5
5
5
5
STATE
CT
MC
MA
NH
RI
VT
NJ
NY
DC
DC
MD
PA
VA
wv
AL
FL
G*
KV
MS
KiC
sc
TN
IL
IN
Ml
MM
OH
Ml
25X
COMBI3TO&WlllNS€W
43.
16.
41.
19.
46.
18.
55.
116.
48.
125.
0.
62.
55.
19.
0.
101.
47.
61.
0.
0.
0.
61.
66.
31.
38.
30.
39.
50.
11.
0.
0.
0.
11.
0.
16.
25.
12.
32.
22.
17.
14.
0.
23.
27.
12.
15.
22.
19.
15.
15.
0.
9.
0.
0.
13.
10.
4.
5.
4.
10.
4.
14.
23.
11.
0.
20.
1".
13.
5.
21.
24.
11.
13.
21.
17.
18.
14.
15.
7.
B.
7.
9.
12.
n
COMB
127.
50.
124.
53.
133.
49.
157.
450.
135.
460.
0.
183.
156.
53.
0.
266.
125.
172.
0.
0.
0.
162.
198.
87.
105.
80.
113.
142.
'T5$$C
STOWM
32.
0.
31.
0.
32.
0.
-------
TABLE 17 (cont'd)
f
61
9TS5E
AR
6j LA
61
MM
6 0^
6
7
7
7
7
e
e
6
8
e
a
TX
IA
KS
HO
NC
cn
MT
NO
3D
UT
WY
9
9
9
9
9
AK
1 AZ
1 CA
HI
1 NV
1
IS ID
10
10
0*
1 WA
25*
05.1 13.
0.
53.
0.1 7.
0.
82.
10.
15.
49.
13.
04. 10.
28.
31.
45.
0.
0.
0.
13.
12.
37. 9.
44.1 11.
0. 12.
0.
12.
62. 15.
0.
6.
63. 10.
0. 17.
17. 3.
0. 9.
63.
0.
40. 0.
12.
00.
6.
12.
14.
12.
1".
7.
7.
1 1.
11.
9.
10.
11.
11.
13.
5.
10.
ia.
2.
9.
13.
10.
OPTIMAL ANNUAL
•sot
117.
0.
0.
u.
217.
134.
lie.
76.
85.
115.
0.
98.
116.
0.
o.
160.
0.
16".
0.
43.
0.
169.
108.
35.
1«8.
18.
37.
'U.
36.
27.
21.
33.
30.
24.
2*.
31 .
31.
3".
15.
27.
"4.
7.
23.
«0.
33.
31.
121.
16.
32.
36.
33.
25.
18.
18.
2".
27.
23.
26.
27.
28.
33.
14.
27.
38.
6.
22.
35.
28.
COST PER ACRE
75* 1 *5X
141.
0.
0.
0.
743.
072.
287.
202.
230.
012.
0.
140.
221.
0.
0.
426.
U.
607.
0.
118.
0.
445.
284.
121. lift.
.!2!:!_13?-
63.
136.
13".
3ft.
66.
75.
1
126.
75.
47.
57.
11".
81.
73.
70.
47.
50.
48.
62.
70. 62.
87. 62.
110. 5(1.
85. 64.
138. 6".
53.
25.
99. 40.
162. 61.
18.
14.
57. 54.
106.1 93.
68. 73.
141. 372.
0.
1096.
. °:! l??i
0.
1665.
307.
310.
2668.
287.
235.
322.
684.
0.
198.
254.
290.
236.
154.
140. 140.
221. 221.
0." 243.
0. 183.
I
426.1 426.
0. 112.
1201. 170.
0. 314.
142.
60.
0. 11".
509. 469.
310. 432.
136. j
30.
66.
75.
1
73.
82.
147.
53.
08.
62.
62.
62.
50.
64.
6".
25.
40.
61.
14.
55.
112.
9".
49
-------
TABLE 18. OPTIMAL ANNUAL AND CAPITAL CONTROL COSTS
1 1
IE** I3TATE
IRECl ID
11 CT
1 1 MT
1 1 Mi
1 1 NH
1 1 PI
1 1 VT
TL !?.<". 1
?l SM
21 '.Y
TI OPR .->
31 nE
31 oc
3' -I
31 Pi
3' vi
J ! % V
TI 7^ 3
U 1 il.
«l FL
4 1 r,i
U 1 KY
U 1 MS
Ul \C
ai sc
U | TN
TI PFr; 4
-.!!-.:!:.
SI TM
51 MM
51 UI
... I .....
TI. SET. 5
irjPTTMA
?MT
?5*
«.b
0.0
6.7
o.;
J.7
".;?
ia.o
12. b
3'."
•JiJ.'i
!?./
?.«l
'-.1
I7.'l
5.C1
1.^
3*.l
5.7
it. j
'•.I
1.0
2.?
S.^
2.9
•5.1
u7.a
p".?
6.6
1.7.9
i.6
1?./J
•5.5
6". 7
. AMNI'41
.1 ln^S
r)0t
U.'i
.•".->
35. -i
I.1
5.0
O.r>
« 9 . J
•4S.fi
ll'l.')
lflO.7
•>. 1
^.a
1 7.u
'.» 1 . ^
1 /;.o
3.4
-)«.;>
!'!..=>
•i 5 . i.
I'>.D
fl.S
0.1
13.*,
7.S
1-1.3
U'l.T
fl5.%
1 "J.'l
•4S..?
ft. a
U?.fi
15. ^
207.3
. C.IVTO-
V nni.C
7SK
39.5
7.0
75."
S.'J
ia.r-
i."
] 4.1.3
! I ^ . ?
')'» $. <
7 J « . 'J
'>.''
3^./<
•S*..'
J1"!".!
•4S.1
T.f>
3.(-
•5-?.l
9^.1
23. i
11^. a
au.«;
'S^s.';
11. COST
ius5
fl^t
^>fi..)
H.I
tr>7.1
3.7
u'4.2
•n.2
?7?,3
?L'9.fl
t?'"^.?
M7
U9JO
3o. n
19.9
3?.l
•»T;7
630.4
437.0
Bb.9
155. /I
•'I?.-'!
?i?«T7
79.1
t o^a.-i
nnTTM»L CAPITAL I
fBTUinNS np DOLL/
2«5X 1 SOt 1 75X
O.n39
'J.Ollfl
').()5'i
O.OU6
U . (' 1 "3
0.1)02
0.1 2a
0.1 OU
'1.316
o.a?c
') . I.I (' 6
0.fi2C
0 . (i 5 1
'1.116
D.oua
'l.dlO
0.?76
(!.f!«7
!).1 3'j
o.nSi
".-'25
M.'ll?
('.nail
'i.y?a
o.'ias
(i ,39a
0.?3«.
d.f'55
0.10*
').n22
0.105
0.?1U6
C.^73
0.1131 0.330
0.021' 0.05".
0.?T?I 0.608
0.0161 O.OaS
p.oasi 0.122
0.00
0.0281 O.OflO
O.B19I ?.5a9
0.1231 0.321-
0.3601 l.Cl«
0.1351 0.360
0.0711 n . 2 i 0
0.0581 n.152
0.1 iu 1 0.298
O.O'iSI 0.1%«
0.1191 0.316
1.0«3I ?.83fl
0.7101 2.200
0.1621 O.U35
0.29ai O.S02
0 . 0 7 « 1 0.195
0.3571 0.967
0.1301 0.371
1.7301 U.970
:OST
M»S1
«5T
0.573
0.093
1.311
0.073
0.202
O.OP1
2.273
1.91B
10.392
12.310
0.092
0.476
0.757
2.««7
0.7fr6
0.130
U.6f>9
0.5«:e
1.791
0.631
0.409
0.255
0.500
0.268
0.599
5.010
3.6U7
fl.7?5
1.297
0.354
1.875
0.652
P.539
50
-------
TABLE 18 (cont'd)
EPA I -STATE
PFGI 1*5
6 1 AP
61 L*
61 K'M
6 1 nK
61 TX
TL "ET, 6
71 1*
7 1 K3
7 1 Mfl
7 1 MC
Ti °er 7
e t cn
e ' MT
8 1 NO
e i sc
ft 1 llT
e t MY
TI "EC fl
Q 1 AK
91 AZ
91 C*
t 1 Hi
9 ! MV
TL PET, 9
101 ID
101 OB
101 W A
TL "cn to
TL U.S.
n"TWl
?5X 1
1 .9 1
9.9
0.6
J.O
16. SI
V.u
J.o
2.5
"5.9
1 .3
!?.»>
2.5
0.5
0. 5
0 . a
! .2
O...J
5.2
0.3
1,0
?1.9
1 .1
C.2
?U.5
O.'l
3. a
a. 6
fl.a
396. /
A'JN'JAI C"'JTTr
I IONS "F r>i'U! t
rjO* i 7<^r
i.oi 1 « . .<
P7.7I ««./
l.5i 3."
7.01 21 .S
a 3 . S I i 1 • . 1
85.rj| *a',./
S . 1 1 ? .? . I
6.51 I7. <
I6.?i a'f.?
a . o I i 'i . /
8! ..hl
1 . U 1 3.7
3.11 «.»
0.7; LA
»3.1-l 3S.O
0.31 ?.'
? . 6 1 (> . 7
^9.? t 17?. u
? . P i 7.9
O.a i i . j
f.5.fl ( J *?('. j
1 1 .0 1 ?."5
t 0 . a I ^.2
6A5."7 1 U>7PS./*
b,^"T
set
2."20l 0.0521 0.112
O.»0ll 0.0111 0.027
0 . i) 0 ? 1 0.0061 0.018
P.on'ij 0.0081 0.0?3
0. nl 01 0.0261 0.0t>8
0.01)21 0.0061 0,015
O.M13I 0.1091 0.2-)2
0 . '' U ? 1 0 . 0 n 6 1 0 . 0 1. 7
H.')D9I 0.021 I 0.056
0.1831 0.49^1 1.«39
O.dOPI 0.023I n.0fc6
o.ooi I o.oon n.009
<).?0al 0.5191 ] .587
O.D03I 0.0081 0.021
()."27I 0.0*571 0.230
0.0391 0.12H 0.327
0.0691 0.220' 0.578
2.U76I 7.391 122. 7a«
\m
"5X
0.2D7
1.270
0.057
0.331
1.727
3.595
0.103
0.252
0.596
0.151
1 .103
0.211
O.oai
0.028
0.039
0.119
0.021
0 .19U
0.031
0.096
2.100
0.113
0.016
2.658
0.033
0.399
0.577
1 .009
lT.968
51
-------
50, 75, and 85 percent BOD control are $297, $886, $2,725, and $5,029 millions
of dollars per year. Similarly, the initial capital investment for 25, 50,
75, and 85 percent BOD control is $2,476, $7,391, $22,744, and $41,968
millions of dollars based on 85 percent of the present worth of the total
annual cost at an assumed interest rate of 8 percent over 20 years. Note that
the incremental costs for wet-weather control increase significantly. This
is due to the disproportionately larger control units needed to capture the
less frequent, larger storms.
An analysis was made of the possibility of cost allocation among wet-
weather quality control and dry-weather quality control (with flow equaliza-
tion) and wet-weather quantity control (with storage required to reduce run-
off rates and volumes). The results suggest that significant savings might
be realized as shown in Figure 3, which indicates reductions ranging from 70
percent at low control levels to 30 percent at high levels.
In addition to using storage/treatment devices to control wet-weather
pollution, other management practices are available. A related study suggests
that significant savings in control costs could be realized if other manage-
ment practices are used in conjunction with storage/treatment. (17) The
estimated costs of control incorporating other management practices are shown
in Figure 3. The savings range from about 50 percent at low levels of
control to about 38 percent at higher control levels. Further savings could
be realized by allocating some of the cost to other purposes, e.g., street
sweeping for aesthetics.
The relationship between tertiary treatment and wet-weather control
was examined by finding the percent wet-weather control to initiate prior to
using tertiary treatment. Results indicate that about 4 percent of the wet-
weather flow problem should be controlled before initiating tertiary treat-
ment control. BOD removal was used as the effectiveness metric. Different
results would be obtained using nutrient control as the criterion.
The results of this assessment indicate significantly lower control
costs than reported in earlier studies, i.e., the USEPA Needs survey (initial
capital cost = $266.1 x 109), and the National Commission on Water Quality
(NCWQ) study (initial capital cost of $288.6 x 109). (18,19) The NCWQ study
was the only other one which explains its methodology and assumptions. Thus,
a comparison with that study has been made. Major differences in results are
attributable to the following:
1. Collection System Costs - The NCWQ estimate includes
$84.0 x 10y for constructing storm sewers. This study
does not view storm sewers as chargeable to pollution
control.
2. Choice of a Design Storm - The NCWQ studies used control
of the two year, one hour storm as a basis for their
mean estimate of control costs. The concept of a design
storm was not used in this study because it was felt
that a continuous characterization in terms of percent
52
-------
540CH
480O-
4200-
s
X O
t\J
-vt- »
0 »
-o o
c
O ii
- 30
CD
- w
< I-
^ w
o
V) O
25 u,
K 3
3
20 g
- 15
co a:
O o
o *
90
100
% BOD REMOVAL , R|
Figure 3. Single purpose and multiple purpose stormwater pollution
control costs for U.S.
53
-------
of the runoff which could be treated was more appro-
priate since no accepted design event condition
exists which also specifies a design antecedent dry-
weather period. Figure 4 shows that using a frequency
of one month would permit capture of 90 percent of the
precipitation volume. Sizing for the two year, one
hour storm yields relatively little incremental control
and requires a much higher control volume.
Only the future will tell which, if any, of the above cost estimating
procedures provides the most accurate estimate of national control costs.
Within the severe data gathering limitations imposed by a national estimate,
this study has attempted to make the results as site specific as possible.
Improved estimates can be obtained using local data. In particular, topo-
graphic information and knowledge of the numbers of outfalls permits
inclusion of pumping costs and analysis of the optimal combination of
control units and interceptor sewers.
54
-------
txO
6.0
FREQUENCY OF ONE HOUR INTENSITY STORMS
SYMBOL FREQUENCY
q TWO WEEK
b ONE MONTH
c SIX ••
d ONE YEAR
f
TWO
FIVE
0.3
0.6 0.9 1,2 1.5
RAINFALL INTENSITY, ia/hr
Figure 4. Overall percent precipitation control vs. rainfall intensity
(1948-1972)
1.8 2.1
Atlanta, Georgia
2.4
-------
REFERENCES
1. US Bureau of the Census, County and City Data Book, 1972, USGPO, 1972.
2. Manvel, A. D., Gustafson, R. H., and Welch, R. B., "Three Land Research
Studies", National Commission on Urban Problems, Researhh Report 12,
Washington, DC, 1968.
3. Hydrologic Engineering Center, Corps of Engineers, "Urban Storm Water
Runoff: STORM", Generalized Computer Program 723-58-L2520, May, 1975.
4. Roesner, L.A., et al., "A Model for Evaluating Runoff-Quality in
Metropolitan Master Planning", ASCE Urban Water Resources Research
Program, Technical Memo No. 23, ASCE, 345 E. 47th St., NY, NY 10017,
72 pp., April, 1974.
5. Stankowski, S. J., "Magnitude and Frequency of Floods in New Jersey
with Effects of Urbanization", Special Report 38, US Geological Survey,
Water Resources Division, Trenton, NJ, 1974.
6. Heaney, J. P., Huber, W. C., and Nix, S. J., "Stormwater Management
Model; Level I, Preliminary Screening Procedures," USEPA Report EPA-
600/2-76-275, 1976.
7. Field, R. I., and Struzeski, E. J., Jr., "Management and Control of
Combined Sewer Overflows", JWPCF, Vol. 44, No. 7, 1972, pp.1393-1415.
8. Lager, J. and Smith, W., "Urban Stormwater Management and Technology:
An Assessment", USEPA Report EPA-670/2-74-040, NTIS-PB 240 697, 1974.
9. Becker, B. C., et al., Approaches to Stormwater Management, Hittman
and Associates, USDI Contract 14-31-001-9025, 1973.
10. Battelle-Northwest, "Evaluation of Municipal Sewage Treatment
Alternatives," Council on Environmental Quality, NTIS-PB 233-
489, 1974.
11. Field, R. I., "Treatability Determinations for a Prototype Swirl
Combined Sewer Overflow Regulator/Solids-Separator," Proceedings
Urban Stormwater Management Seminars, Atlanta, GA, November 4-6,
1975, Denver, CO, December 2-4, 1975, USEPA Report WPD 03-76-04.
pp. II-98-II-111, January 1976.
12. Benjes, H. H., "Cost Estimating Manual—Combined Sewer Overflow
Storage Treatment," USEPA Report EPA-600/2-76-286, NTIS-PB 266 359,
December, 1976.
13. Maher, M. B., "Microstraining and Disinfection of Combined Sewer
Overflows - Phase III," USEPA Report EPA-670/2-74-049, NTIS-PB
235 771, August, 1974.
56
-------
14. Agnew, R. W., et al., "Biological Treatment of Combined Sewer
Overflow at Kenosha, Wisconsin," USEPA Report EPA-670/2-75-019,
NTIS-PB 242 120, April, 1975.
15. Wiswall, K. C. and Robbins, J. C., "Implications of On-Site
Detention in Urban Watersheds," ASCE Hyd. Div. Conf., Seattle, WA,
1975.
16. Thornthwaite, C. W., and Mather, J. R., "Instructions and Tables for
Computing Potential Evapotransporation and the Water Balance, Drexel
Institute of Technology, Publications in Climatology, Vol. 10, No. 3,
penterton, New Jersey, 1957.
17. Heaney, J. P., and Nix, S. J., "Stormwater Management Model:
Level I — Comparative Evaluation of Storage Treatment and
Other Management Practices," USEPA Report EPA-600/2-77-083, 1977.
18. US Environmental Protection Agency, "Cost Estimates for Construction
of Publicly Owned Wastewater Treatment Facilities", 1974 Needs
Survey, February 1975.
19. Black, Crow, and Eidsness, Inc., and Jordan, Jones, and Goulding, Inc.,
"Study and Assessment of the Capabilities and Cost of Technology for
Control of Pollutant Discharges from Urban Runoff", Binal Report to
National Commission on Water Quality, Washington, DC, October 1975
57
-------
LIST OF VARIABLES
a coefficient (inches per hour)
AR annual runoff (inches per year)
a coefficient
b coefficient (inches per hour)
/3 coefficient
GC unit cost of storage ( annual dollars per acre-inch)
Crp unit cost of treatment (annual dollars per inch per hour)
CR gross runoff coefficient
CR net runoff coefficient
d coefficient (inch ~ )
DS depression storage (inches)
DWF annual dry weather flow (inches per year)
ENR Engineering News Record Cost Index
17 treatment plant efficiency
f coefficient (percent R~l)
&L curb length (feet per acre)
7 street sweeping effectiveness factor
h coefficient
I percent imperviousness
K coefficient
1 coefficient
M annual pounds of pollutant (pounds per year)
MRSst marginal rate of substitution of storage for treatment (hours)
n annual pounds of pollutant (pounds per year)
Ns street sweeping interval
58
-------
P annual precipitation (inches)
PD gross population density
PD
-------
SECTION III
RECEIVING WATER IMPACT A CASE STUDY
GENERAL DESCRIPTION
The City of Des Moines, Iowa, is located near the confluence of the
Des Moines River and the Raccoon River as shown in Figure 5. It contains
approximately 200,000 people out of the total of 288,000 for the metropolitan
area.(1) The mean annual precipitation is 31.27 in. (79.5 cm), approximately
equal to the United States average. Annual pollutant unit loads upstream
from the city were determined (see Table 19).
TABLE 19. POLLUTANT UNIT LOADS FOR DRAINAGE AREA
(on annual basis) ABOVE DES MOINES, IOWA
(Davis and Borchardt, 1974)1
Drainage Area, acres (ha)
Unit Average Annual Runoff,
acre-ft/acre (ha-m/ha)
Unit BOD, Ibs/acre (kg/ha)
Unit N03, Ibs/acre (kg/ha)
Unit PO, , Ibs/acre (kg/ha)
Des Moines
River
3,738,000
(1,512,769)
0.42
(0.13)
13.40
(15.02)
3.75
(4.20)
0.54
(O.bl)
Raccoon River
2,202,000
(891,149)
0.40
(0.12)
6.93
(7.77)
3.74
(4.19)
0.42
(0.47)
Total
5,940,000
(2,403,918)
0.41
(0.12)
11.01
(12.34)
3.75
(4.20)
0,50
(0.56)
The estimated annual loading from the urban area's 45,000 acres (18,220
ha) of separate sewer and 4,000 acre (1,620 ha) combined sewer systems is shown
in Table 20.
Taking the total upstream drainage area for the Raccoon and Des Moines
Rivers, the annual pollutant contributions are: 65,225,000 Ibs of BOD
(29,586,000 kg); 22,222,000 Ibs of NO (10,080,000 kg); and 2,940,000 Ibs
of PO (1,334,000 kg).
60
-------
Soylarville
Reservoir
oes MOINIES
Figure 5. Map of Des Moines Area
(Davis and Borchardt, 1974)
61
-------
TABLE 20. SUMMARY OF PRESENT ANNUAL METRO AREA DISCHARGES
(Davis and Borchardt, 1974)
Wastewater Treatment Plant Effluent
Dry- Weather
b
"Wet" Dry- Weather
Subtotal
"Wet" Dry-Weather Overflow
d
Wet-Weather Combined Sewer Overflows
2.72 in. (69.1 mm) Rain
1.50 in. (38.1 mm) Rain
0.75 in, (19.1 mm) Rain
0.375 in. (9.5 mm). Rain
0.175 in. ( 4.4 mm) Rain
Subtotal
Days
257
108 6
365
108 S
1
5
12
18
20
56
BOD, Ibs
(kg)
4,060,600
(1,841,857)
2,246,400
(1,018,950)
6,307,000
(2,860,807)
2,235,600
(1,014,051)
40,500
(18,370)
101,500
(46,040)
32,500
(14,742)
0
0
174,600
(79,197)
N03, Ibs
400,900
(181,845)
237,600
(107,774)
638,500
(289,619)
9,700
(4,400)
240
(109)
680
(308)
220
(100)
0
0
1,140
(517)
O.PO Ibs
(kg)
1,737,300
(788,026)
1,036,800
(470,285)
2,774,100
(1,258,311)
263,500
(119,522)
6,350
(2,880)
12,200
(5,534)
3,250
(1,474)
0
0
21,800
(9,888)
-------
TABLE 20(cont'd)
Days BOD, Ibs
(kg)
Urban Storm Water Discharges
2.72 in. (69.1 mm) Rain 1 292,000
(132,449)
1.50 in. (38.1 mm) Rain. 5 765,000
(346,998)
0.75 in. (19.1 mm) Rain 12 966,000
(438,170)
0.375 in. ( 9.5 mm) Rain 18 495,200
(224,619)
0.175 in. ( 4.4 mm) Rain 20 149,800
(67,948)
Subtotal 56 2,688,000
(1,219,256)
TotaJ Annual Discharge 365 11,385,100
(5,164,194)
NO , Ibs
(kg)
6,800
(3,084)
15,300
(6,940)
19,300
(8,754)
9,900
(4,491)
3,000
(1,361)
54,300
(24,630)
703,640
(319,166)
O.PO Ibs
(kg)
3,900
(1,769)
9,200
(4,173)
12,000
(5,443)
6,200
(2,812)
1,900
(862)
33,200
(15,059)
3,092,600
(1,402,780)
"Based on sampling periods from October 1968 to October 1969.
B
-------
The urban area loadings (when added to upstream values) represent, respec-
and PO,
tively: 15 percent, 3 percent, and 51 percent of the total BOD, NOo:
mass load-ings to the Des Moines River below the metropolitan area. The Davis
and Borchardt report estimates made from river sampling data taken below Des
Moines indicate the following average annual river loadings:. 70,000,000 Ibs
of BOD (31,751,466 kg); 25,400,000 Ibs of N03 (11,521,250 kg); and 7,950,000 Ib
of P04 (3,606,059 kg). These figures reveal that: (1) 6,610,000 Ibs of BOD
(2,998,24b kg) are "lost" in transit through the urban section of the stream,
and (2) by contrast 2,474,360 Ibs of N03 (1,122,351 kg) and 1,917,400 Ibs of
P04 (8b9,817 kg) are gained in addition to the measured urban sources.
Davis and Borchardt offer some explanations:(1)
The "sometimes" decrease in organic load through the
metro area may be attributable to treatment realized
in the low head impoundments at Scott and Center
Streets on the Des Moines River and just below Fleur
Drive on the Raccoon. To some extent these impound-
ments may be serving as intermittent sedimentation
and stabilization units.
All BOD data, including that used from the two other
studies, were obtained from unfiltered samples. How-
ever, since the analytical technique was the same for
all samples, the relative magnitude of the data should
not be affected.
There has been some speculation that treated wastewater
effluents may exert an antagonistic or retardant effect
on the BOD exertion rate of the receiving stream. If
true, this may be due to surfactants or to the expected
lower exertion rate of the effluent. In this regard,
the decreased BODc; in 4 or 5 measurements between R-5
and R-6 is of interest. Increased loads between the
summation of R-4 and R-9 versus R-5 are likely due to
raw and combined sewage bypassing the intervening area.
Another, and probably tne most practical, possibility
for discrepancies is the fact that the data are bio-
logical and biochemical in nature and such data do not
always provide predictable comparative summations.
The sampling stations (numbers 4, 5, 6, 9) are shown in Figure 6. Inter-
vening creeks, such as Beaver Creek, which carries nutrient loads of
2,860,000 Ibs of N03 per year (1,297,274 kg per year) and 390,000 Ibs of P04
per year (176,900 kg per year), may be an answer to observed differences in
the nitrate loads. However, the phosphate totals are still unbalanced and
the cause unresolved.
64
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L. £. G E /V D
A Iowa Slaty Univtrnty
Engintaring, Research Institute
D Stolt Hygiinic Laboratory
& This Project
® USCS Streamflow Station
Figure 6. Location map: river sampling points
(Davis and Borchardt, 1974)1
65
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DATA AND MODELING
The data may be broken into categories describing needs for the runoff
simulation. All land use, population density, areas, curb lengths, etc,,
were obtained from data prepared by APWA for STORM simulations (Volume III).
Hourly rainfall values for the year 1968 were obtained from the National
Weather Records Center at Asheville, North Carolina. The area served by
combined sewers Ac = 4,000 ac, is given on p. 2 of the Davis and Borchardt
report. (1) Dry-weather flow values are taken from Table 5, p. 52. Receiving
water upstream flows, temperatures, BOD and DO levels are taken from.pp. 285-
308. Total urban runoff and its BOD concentration are obtained from the
STORM simulation on a hourly basis.
Stream DO's were simulated using a Streeter-Phelps formulation. More
sophisticated procedures were not warranted due to a lack of supplemental
data required for such models. Measured and computed values of DO at a
point 5.6 mi (9.0 km) downstream from the confluence of the Raccoon and
Des Moines Rivers are compared in Figure 7. Correlation between the cal-
culated and observed profiles is quite good. The point corresponds to
sampling location No. 6 as shown previously in Figure 6. Included in
Figure 7 are rainfall and average total river flow values for each wet-
weather event. Differences between measured and computed DO concentrations
may be attributed to such factors as: (1) the time of day during which the
sample was taken; (2) a lack of data on photosynthesis, algal respiration,
and benthic demand. The time scale in days represents the wet year beginning
on March 8 and ending December 30, 1968. Again, it should be reemphasized
that these DO values are not the minimum DO's resulting from maximum
deficits. The maximum deficits occur much further downstream (10-30 mi or
16-48 km) and water quality standards are violated much more frequently.
RESULTS
Based on NOAA records (Asheville, North Carolina), the total precipi-
tation that fell over Des Moines, Iowa, during 1968 was 27.59 in. (70.1 cm).
STORM computed a total runoff of 10.28 in. (26.1 cm) over a watershed area
of 49,000 acres (19,600 ha), for an overall urban area runoff coefficient of
0.37. There were 65 days in the year during which rainfall was recorded,
from which 58 wet-weather events were defined. The results are presented
in the form of minimum DO frequency curves for the wet-weather and dry-
weather periods through the calendar year.
Figure 8, illustrates all waste inflow combinations. The curves
indicate clearly that all combinations including a substantial amount of
wet-weather flow (WWF) result in a drastic decrease in river minimum DO
concentrations. For example, 42 percent of all the wet-weather events
throughout the year produced conditions in the receiving water that caused
minimum DO levels below 4.0 mg/1. Combined sewers contributed WWF from
only 8 percent of the total urban area modeled, yet the BOD5 concentration
was sufficiently high to inflict an appreciable reduction in DO levels when
compared to DWF sources during periods of runoff.
66
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(T
0.0-
0.5-
1.0-
1.5-
2.0-
o
ci
14-
12-
10-
8-
6-
4-
2-
0-
"FT
MEASURED FLOW
+ URBAN RUNOFF
V
MEASURED
I
50
MARCH
I I 1 I I I I I
100 150
DAYS
-0
- I
-2
-3
-4
-5
200
250
— 2000
— 4000
^-6000
^-8000
^- iopoo
— 12,000
1 I
300
DEC., 1968
|llll! IMIJIIII llf II
10 20 30 40
EVENTS
50
o
0>
O
o:
LU
cr.
o
r—0
— 100
— 200
— 300
o
in
to
Figure 7. Application to Des Moines, Iowa. Measured and computed
values of DO at 5.6 mi (9.0 km) downstream from
confluence of Raccoon and Des Moines Rivers
67
-------
100
V
PRECIPITATION YEAR OF RECORD ' 1968
DWF TREATMENT RATE' 85% (SECONDARY)
WWF TREATMENT RATE • 0% (NO TREATMENT)
RIVER FLOW = 100% (OF MEASURED FLOW)
COMBINED SEWER AREA ' 8.16% (OF TOTAL URBAN AREA)
INFLOW COMBINATION
RIVER FLOW + DWF
RIVER FLOW + DWF+ SEPARATE FLOW
V RIVER FLOW -t- DWF-I-COMBINED FLOW
,\ RIVER FLOW + SEPARATE FLOW 4- COMBINED FLOW
\\ RIVER FLOW+ DWF 4- SEPARATE FLOW + COMBINED FLOW
•\ INDICATES EVENTS EXCEEDING DESIRED D.O. LEVEL
2.0 4.0 6.0 8.0 10.0
DISSOLVED OXYGEN CONCENTRATION, mg/l
14.0
Figure 8. Minimum DO frequency curves for existing conditions in
the Des Moines River
The minimum DO frequency curves in Figure 9 compare four alternatives
to reduce water pollution during wet-weather periods, plus zero and primary
DWF treatment curves shown for comparison but not considered acceptable
alternatives. WWF treatment is seen to be considerably more effective in
reducing stream DO violations than is secondary or tertiary DWF treatment.
In fact, results indicate that a DO standard of 4.0 mg/l would be violated
only three percent of the time during wet weather if 75 percent WWF
treatment were instigated.
68
-------
It is now appropriate to examine the results of applying the model to
periods throughout the year during which no urban runoff was produced. Dry
weather was experienced for approximately 300 days throughout 1968. The
model was applied to these periods using a daily time step. This modifica-
tion is certainly justified since conditions are more truly steady-state
than during periods of precipitation and subsequent runoff. For example,
waste loadings (DWF treatment plant effluent) and river flow do not vary as
much during the day. For the dry-weather simulation period, upstream river
flow was on the average 94 percent of the total river flow, ranging from
82 percent ot 99.6 percent. The results are shown in Figure 10. A remarkable
97 percent of the dry-weather days exceed a minimum DO concentration of 4.0 mg/1.
100
PRECIPITATION YEAR OF RECORD < 1968
INFLOW COMBINATION'
RIVER FLOW* DWF + COMBINED FLOW * SEPARATE FLOW
COMBINED AREA1 8.16% {OF TOTAL URBAN AREA)
RIVER FLOW' 100% (OF MEASURED FLOW)
DWF TREATMENT RATE'
- 95 % (TERTIARY)
- 85 % (SECONDARY)
85 % (SECONDARY)
85 % (SECONDARY)
30% (PRIMARY)
0% (NO TREATMENT)
WWF TREATMENT RATE'
0 % (NO TREATMENT)
75 %
25 %
0 %(NO TREATMENT)
0 % (NO TREATMENT)
0%(NO TREATMENT)
INDICATES EVENTS EXCEEDING DESIRED D.O. LEVEL
2.0 4.0 60 8.0 10.0 120 14.0
DISSOLVED OXYGEN CONCENTRATION, mg/l
Figure 9. Minimum DO frequency curves for varied treatment alternatives
69
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Upgrading of DWF treatment becomes meaningful only if stream DO standards are
set higher than 4.0 mg/1. From Table 19 it is clear that the Des Moines
River in particular carries a high BOD5 load upstream of the Des Moines
urban area. -This explains why, even during dry-weather periods only, a
significant increase in the DWF treatment rate does not result in a cor-
responding increase in the critical DO levels, as shown in Figure 10.
100 -r
q 90
ci
UJ 80
I
SIMULATION PERIOD'
DRY WEATHER DAYS OF 1968
WASTE INPUT=
URBAN DWF + UPSTREAM SOURCES
RIVER FLOW = 100% OF MEASURED FLOW
DWF TREATMENT RATE :
95 % (TERTIARY)
85% (SECONDARY)
30% (PRIMARY)
0% (NO TREATMENT)
INDICATES, EVENTS EX
DESIRED D.O. LEVEL
\ \ \v INDICATES, EVENTS EXCEEDING
2.0 4.0 6.0 8.0 10.0
DISSOLVED OXYGEN CONCENTRATION, mg/l
1—" '"' '—T
12.0 14.0
Figure 10. Dry—weather minimum DO frequency curves for varied DWF
treatment alternatives
To maintain the proper perspective, it is desirable to view the effects
of urban runoff on an annual basis, not just during periods of wet-weather.
The frequency curves shown in Figures 9 and 10 are combined by weighting on
the basis of the number of rainfall days and dry-weather days in the year.
70
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The composite totals are presented in Figure 11. For example, a given
stream standard of 4.0 mg/1 is exceeded 90 percent of the time for existing
conditions in Des Moines, Iowa, throughout the year 1968. A significant
amount of treatment (75% BOD5 removal) of WWF in addition to secondary treat-
ment of DWF results in critical DO levels such that the same stream standard
is exceeded 97 percent of the days in the year. Annual DO duration curves
tend to mask the impact of shock loads of organic pollutants discharged
during periods of urban runoff. A few extended violations of stream DO
standards may cause anaerobic conditions resulting in fish kills and
proliferation of undesirable microorganisms.
100
SIMULATION PERIOD' 1968
WASTE INPUT- UPSTREAM SOURCES * DWF +
SEPARATE SEWER FLOW* COMBINED SEWER FLOW
RIVER FLOW = 100% OF MEASURED FLOW
COMBINED SEWER AREA '8.16% OF URBAN AREA
DWF TREATMENT RATE'
95 % (TERTIARY)
85 % (SECONDARY)
85 % (SECONDARY)
85 % (SECONDARY)
30 % (PRIMARY)
0 %(NO TREATMENT)
WWF TREATMENT RATE-
0 % (NO TREATMENT)
75 %
25 %
0 %(NO TREATMENT)
0%(NO TREATMENT)
0%(NO TREATMENT)
INDICATES EVENTS EXCEEDING DESIRED D.O. LEVEL
20 40 6.0 8.0 10.0 12.0
DISSOLVED OXYGEN CONCENTRATION, mg/l
14.0
Figure 11. Annual minimum DO frequency curves
71
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TRADEOFF IN ALTERNATIVES
To view the control strategies in the proper perspective, the status
quo conditions are included as a base for comparisons. Any alternative
plans that depart from this base must be justified on their cost-effective-
ness. Thus, the cost figures shown in Table 21 represent the additional
expense incurred in providing storage/treatment beyond that already
available with secondary treatment of DWF and no control of urban runoff.
Figures 9, 10 and 11 show the effects of various control strategies upon
the minimum DO concentrations of the Des Moines River.
The Des Moines River stretches for 200 mi. (322 km) from the City of
Des Moines to its junction with the Mississippi River and, in general,
the river is wide and swift with occasional deep holes and a broad flood
plain. According to the State Hygienic Laboratory, bottom material is
composed of silt deposits, sand, gravel and rubble providing numerous
habitats for fish and other aquatic life. Recreational activities such
as fishing and boating are quite heavy. The entire reach is classified
as warm water "B" stream by the Iowa Quality Standards (2) such that the
absolute minimum dissolved oxygen level specified is 4.0 mg/1. The Iowa
Standards also require a minimum of 5.0 mg/1 during at least 16 hours per
day. (3) Thus, taking 4.0 mg/1 as the standard or basis for water quality
comparisons, the different control options may be judged by the following
criteria:
1. total annual cost, and
2. violations of the minimum allowable dissolved
oxygen level.
Table 22, summarizes the cost-effectiveness of two advanced waste
treatment options, two wet-weather control options, and existing DWF
secondary treatment facilities. For comparative purposes, two additional
treatment conditions which are not presently acceptable by government
regulation are presented.
Examination of Figures 9, 10 and 11 and Table 22 reveals that:
1. Since both types of tertiary treatment remove essentially
the same amount of BOD5, option 1 is justified over option
2 only when nutrient removal is necessary;
2. option 4 is preferred over any form of advanced waste
treatment;
3. option 3 is attractive because it causes the least amount
of damage to the receiving stream, but it is the most
expensive alternative; and
4. any reduction in the degree of DWF treatment for existing
conditions, option 5, results in a substantial deterioration
to receiving water dissolved oxygen levels and must be
weighed against the savings incurred.
72
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TABLE 21. DWF TERTIARY TREATMENT vs. WWF CONTROL
Options
Amortized Annual
Capital Cost
$ (20 yrs, 8%)
Operation and
Maintenance Cost
($/yr)
Total Annual Cost
($/yr)
u>
1. DWF Complete "Tertiary
Treatment, No WWF
Treatment
2. DWF Activated Sludge-
Coagulation-Filtration,
No WWF Treatment-
3. WWF 75% BOD Removal,
DWF Secondary Treatment
4. WWF 25% BOD Removal,
DWF Secondary Treatment
2,158,000
4,132,000
6,290,000
1,664,000
9,293,000
816,000
SBased on 49,000 ad'4 (19,600 ha) of developed urban area. The total annual cost
includes amortized capital cost (20 yrs, 8%) and operation and maintenance costs.
-------
TABLE 22. CONTROL COSTS VS. VIOLATIONS OF THE DO STANDARD
Options
% Wet-Weather
Events0 Violating
Standard
% Dry Days in
Year Violating
Standard
Total Incremental
Annual Cost
($/yr)
Total N'o. of Days
During Year that
Standard is Violated
1. DWF Complete Tertiary
Treatment, No WWF
Treatment
2. DWF Activated Sludge
Coagulation-Filtration
Treatment, No WWF
Treatment
40
40
1.5
6,290,000
1-664,000
31
31
3.
4.
c
J .
6.
7.
DWF Secondary Treatment, 3
WWF 75% BOD Removal
DWF Secondary Treatment, 30
WWF 25% BODj-Reinoval
DWF Secondary Treatment, .42
;;q WOT Treatment
DWF Primary Treatment, 50
No WWF Treatment
No DWF Treatment, 53
No WWF Treatment
2.0 9,293,000 8
2.0 816,000 26
2.0 0 33
3.0 -l,438,000d 42
7.0 -1,843, 000d 55
In addition to control costs for existing conditions (5).
Based on a minimum allowable DO concentration of 4.0 mg/1.
CDefined by a minimum interevent time of 9 DWH.
aSavings incurred by reducing DWF treatment of trickling filter plant of 35.3 cigd (1.55 cu m/sec),
-------
Again, the issue of shock loads is important and favors high levels of WWF
control.
The reader should be cautioned that advanced tertiary treatment is
rarely imposed just to improve the BOD removal capabilities of existing
facilities. It is usually designed specifically for nitrogen and/or phospho-
rus removal. For the heavy precipitation in the months of June, July and
August, 1968, Davis and Borchardt (1) reported the following nutrient con-
centrations at a point approximately 5.5 mi (9.0 km) downstream from the
confluence of the Raccoon and Des Moines Rivers:
1. total organic nitrogen ranged from 1.6
to 3.7 mg/1,
2. nitrate nitrogen ranged from 0.2 to
7.8 mg/1, averaging 3 to 4 mg/1, and
3. orthophosphate (OPO.) ranged from 0.6
to 1.8 mg/1, averaging slightly over
1.0 mg/1.
Since most of the urban runoff would overflow untreated to the
receiving water, any program of advanced treatment given to all urban
DWF would be relatively ineffective. It would also be questionable
whether a level of WWF control consisting of secondary treatment (such
as that evaluated for 75 percent BOD removal) could reduce nutrient
levels in the Des Moines River and,Red Rock Reservoir to inhibit aquatic
plant growth. Davis and Borchardt observed high algal densities in
both the Des Moines and Raccoon Rivers, and they also state that nutrient
concentrations are almost always present at levels reported by Sawyer ^4)
to be sufficient for nuisance algal growths: 0.3 mg/1 for inorganic
nitrogen (NIL, N0?, N0_) and 0.015 mg/1 of inorganic phosphorus. Further-
more, since nitrates are abundant in groundwater and the surface and
subsurface hydrologic systems are not independent of each other, nutrient
control seems highly complex and improbable.(5)
The total annual precipitation for the year 1968 was 27.59 in. (70.1 cm).
The frequency and intensity of precipitation over an urban area has a
direct bearing on the magnitude of stormwater pollution and, consequently,
dissolved oxygen levels in the receiving water. In the selection of the
"best" control strategy, other factors may become important, such as:
1. recovery of receiving waters from shock loads during
runoff periods,
2. local and regional water quality goals,
3. public willingness to pay the costs associated with each
level of control, and
4. consideration of alternate use of WWF facilities as DWF
treatment facilities during periods of no urban runoff.
75
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In general, although selection of a storage/treatment configuration
involves many factors it is important to note that the impact of urban
stormwater runoff must be evaluated. Davis and Borchardt(l) compared
daily pollutant loadings (BOD, N03, PO^) from storms ranging in size from
0.175 in. (4.4 mm) to 6 in. (152.3 mm) in total depth to those from dry-
weather sources in the Des Mbines metropolitan area. In all cases, the
loads derived from urban runoff exceeded greatly the average daily loads
from dry-weather sources.
REFERENCES
1. Davis, P. L. and Borchardt, F., "Combined Sewer Overflow Abatement
Plan," USEPA Report EPA-R2-73-170, April 1974.
2. State Hygienic Laboratory, "Des Moines River - Limnology Study,"
Report submitted to the Department of Environmental Quality and the
Iowa Water Quality Commission, April 1974.
3. State Hygienic Laboratory, "Water Quality Survey of the Des Moines
River," Report submitted to the Iowa Pollution Control Commission,
October 1970.
4. Sawyer, C. N., "Basic Concepts of Eutrophication," JWCPF, Vol. 38,
No. 5, pp. 737-744, May 1966.
5. Sawyer, C. N., "The Need for Nutrient Control," JWPCF, Vol. 40,
No. 3, pp. 363-370, March 1968.
76
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SECTION IV
URBAN STORMWATER POLLUTANT LOADINGS
Federal interest, legislation and financial support through the
research and development programs of the U.S. Environmental Protection
Agency (USEPA), has stimulated extensive studies of the nature of urban
stormwater runoff and combined sewer overflow pollution over the past 11
years. Financial support by Federal, state, local and private entities
has resulted in better understanding the general areas of treatment; sewer
system monitoring, regulation and control; runoff and combined sewer over-
flow characterization; and mathematical modelling for estimating the quantity
and quality of runoff and combined sewer overflows. The resulting body of
knowledge has produced new technologies with which to estimate, evaluate and
analyze the pollutional contributions of urban runoff, as well as effective
methods for their abatement and control. The basis of and the major limi-
tations to this technological advancement dictate the methods by which
urban runoff quality and quantity are ascertained.
Runoff quantity estimating methods are well defined. Contemporary
techniques can produce fairly accurate results within reasonable objectives,
based on available data. The major concern is the accuracy of physical and
hydrologic data. Physical data may be gathered from existing sources, while
monitoring networks are seldom available. Historical hydrologic records,
therefore, are a significant data source.
Estimation of runoff quality is not well defined. Quality estimating
methods, on one hand, have been based on the characterization of discharge
pollution and receiving water monitoring. On the other hand, an alternative
approach has been to identify and evaluate potential pollutant sources that
may contribute to the deterioration of runoff quality. These varied ap-
proaches to the problem of analyzing the quality and pollutional contributions
of urban runoff demonstrate that no single best method now exists. Each
approach requires verification based on field sampling and laboratory
analysis. The diversity of these approaches, however, is desirable. In total
they implicitly suggest both structural and non-structural resoonses to the
problem of the prevention, control and abatement of the pollutional contri-
butions associated with urban runoff. Thus, with further research and
evaluation and with the reconciliation of the results attributable to each,
solutions to the problems of runoff pollution may be sought in cost-effective
alternatives other than wastewater treatment hardware. Some of these alter-
natives may take the form of solutions as mundane as: improved street cleaning
technologies; building code revisions, revised physical development standards;
new paving materials; and revised street construction standards.
77
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ALTERNATIVE APPROACHES TO QUALITY CHARACTERIZATION OF RUNOFF DISCHARGE
The quality characterization of runoff discharges has been attempted
through various sampling and measurement activities in drainage basins across
the country, These basins have often been urban or urbanizing, On occasion,
relationships between discharge quantity and quality data have been related
to physical basin characteristics and given rainfall events. Inconsistencies
exist within this body of information, however, due to variability in the
research objectives involved, the pollutants being evaluated, the sampling
techniques employed, and the measurements made.
A number of published references were reviewed to determine the extent
and adequacy of existing data sources. Approximately 16 cities were iden-
tified where surface runoff quality data in some form were available. Of
these, only six provided any definition of drainage basin characteristics as
to land use, population or development characteristics. Sampling activities
were found to vary considerably. Composite samples were collected most often
by automatic devices and grab techniques. Related flow measurements were
made in only a few instances. Similarly, flow-related discrete sample col-
lection occurred at only one location, although discrete grab samples were
used often in conjunction with automatically collected composite samples.
Sampling site location also plays an important role in defining sampling
results. As an example, it is likely that combined sewer sampling occurs
most often within or at the discharge of a sewer collection system. Simi-
larly, separate system sampling may occur at locations within the system or
at the point of discharge into receiving waters. Very often, separate
storm systems may take the form of open earthen channels, in whole or in part.
Sampling at these locations adds solids components and other pollutants
during a meaningful runoff event due to gully and channel erosion and other
conditions. This would not be experienced to the same degree in a combined
sewer system. Thus, most of the existing runoff discharge quality informa-
tion appears in the form of mean pollutant concentrations or averages of
sample results from one or more runoff events, most often without regard to
rainfall-runoff relationships and other variations in time.
Discharge quality and time and runoff flow data have been published in
only a few locales. Foremost among these is a published study from Durham,
North Carolina (9) that investigated a separate storm runoff collection system
in terms of the quality of surface runoff with respect to runoff quantity
during a number of rainfall events. An analysis of the collected data dis-
closed that the discharge rate and the time from the beginning of the storm
event were the most sigificant factors in defining variations in pollutant
concentrations during periods of runoff. These concentrations were generally
found to increase with increasing discharge and to diminish with increasing
time after the beginning of the storm event. Antecedent dry days -- days
from the time of the preceding rainfall-runoff event -- were not found to be
a significant factor in the quality of the runoff sampled. These findings
indicate the existence of a "first flush" or the removal of pollutant deposi-
tions within the collection system by the initial runoff flows. The "first
flush" is generally characterized as having high initial pollutant concen-
trations that diminish with time. It should be noted that the "first flush"
78
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reflected in the Durham study was one that occurred in a collection system
primarily composed of open earthen channels and not in a combined sewer system.
Currently available discharge data leave much to be desired. The
original objectives for the majority of the information available were to
produce order-of-magnitude estimates of the pollution represented by run-
off discharges. This type of information, once having fulfilled its basic
purposes, is no longer timely. Thus, further research in this area is
indicated.
POTENTIAL POLLUTION SOURCES
The evaluation of potential pollutant sources originated primarily
in the study of non-urban environments and non-point runoff discharges.
Generalizations from this body of knowledge are now being applied in urban
drainage areas to estimate pervious area pollutional contributions. The
use of the so-called Universal Soil Loss Equation (USLE) for the estimation
of sediment contributions is a good example of non-urban technology in use
in urban applications. Other, more specifically urban pollutional sources,
require further research and evaluation. It is apparent that the products
of combustion and other suspended materials in the air — particulates and
other emissions — may be scavenged from the atmosphere by falling rain.
Depositions of airborne materials on pervious and impervious surfaces may
be washed off by runoff. Other materials may also contaminate runoff.
Street paving and surfacing materials; debris from open areas, including
wind and water erosion products, organic, plant and animal wastes and a
variety of chemicals such as fertilizer, soil conditioners and pesticides;
transportation-related materials, including residual deposits of fuel,
lubricants, hydraulic fluids and coolants, tire, clutch and brake-wear
products, exhaust emission particulates, rust and dirt; street litter,
household and commercial wastes; and snow and ice control, antiskid and
corrosion inhibitor materials — all may contribute to runoff contamination.
In addition, the stored contributions of catch basin and collection system
solids depositions may be added to this list.
One of the major urban sources of potential pollution is related to
transportation activities. A recent study of the pollutants generated by
vehicular traffic was carried out in Washington, D.C. (1) This study
involved the collection.of street accumulation samples and of traffic
volumes during sampling periods. Analysis of the results of street measure-
ments compared with traffic volumes produced the accumulation rates shown
in Table 23. Although these values appear relatively low, they are of
considerable significance when applied to high traffic volumes.
Snow and ice control activities represent another prospective source of
potential pollution. On one hand, snow and ice deposits are a repository
of potential pollutants produced in urban areas. The concentrations of
various pollutants found in urban snow sampled in the Ottawa-Carleton area
of Ontario, Canada, are summarized in Table 24.
79
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TABLE 23. ACCUMULATION RATES OF TRAFFIC
INFLUENCED ROADWAY MATERIALS
(Washington, D.C. Metropolitan Area)
Parameter
Dry Weight
Volatile Solids
BOD
COD
Grease
Total Phosphate-P
Orthophosphate-P
Nitrate-N
Nitrite-N
Kjeldahl-N
Chloride
Petroleum
n Paraffins
Asbestos
Rubber
Lead
Chromium
Copper
Nickel
Zinc
Cadmium
Magnetic Fraction
Polychlorinated Biphenyls
Litter dry weight
Litter BOD
Rate
Ib/axle-mi gm/axle-m
2.38 x 10'3
1.21 x 10"4
5.43 x 10'6
1.28x 10'4
1.52x 10"5
1.44x 10~6
4.31 x 10"8
1.89x 10'7
2.26 x 10~8
3.72 x 10'7
2.20 x 10'6
8.52x 10"6
5.99 x 10'6
3.86 x 105 a
1.24x 1C'5
2.79 x 10'5
1.85 x 10'7
2.84 x 10'7
4.40 x 10'7
3.50x 10'6
3.11 x 10'8
1.26x10'4
1 x 10'4
1.69x 10'4
3.49 x 10'7
6.71 x 10'4
3:41 x 10'5
1.53x 10"6
3.61 x 10'5
4.28 x 10"6
4.06 x 10'7
1.21 x 10'8
5.33x 10'8
6.37x 10'9
1.05x 10'7
6.2 X 10"7
2.4 x 10'6
1.69x 10"6
2.39 x lO5"
3.49 x 1 0"6
7.86 x 10'6
5.21 x 10'8
8.00 x 10'8
1.24x 10'7
9.86 x 10"7
8.76 x 10~9
3.55 x 10"5
2.82 x 10"10
4.76 x 1Q"5
9.84x 10'8
a. In f Ibers/axle-km
Note: An axle-mile Is the length traversed for each axle of a vehicle.
Hence In traveling one mile, a two-axle vehicle will contribute
two axle-miles.
Source: Shaheen, D.G., "Contributions of Urban Roadway Usage to
Water Pollution," USEPA Report No. EPA-600/2-75-004
(NTIS No. PB 245 854), April, 1975.
80
-------
00
TABLE 24. POLLUTANTS AND POLLUTANT LEVELS FOUND IN SNOW DEPOSITS
Pollutant Concentrations, mg/l (or mg/kg snow)
Pollutant
Suspended Solids
BOD5
Chlorides
Oils
Greases
Phosphates
Lead
Cadmium
Barium
Zinc
Copper
Iron
Chromium
Arsenic
Location
_
Arterial street
Collectors
Local
Parking lot
-
Arterial street
Collectors
Local
Parking lot
-
All sites
All sites
_
Arterial streets
Collectors
Local
Residential
Industrial
Commercial
Highway
-
-
-
-
-
_
-
Windows
Undisturbed Adjacent to
Snow Street
_ _
3,570 mg/kg
1.920-4.020 mg/kg
1,215-?,530 mg/kg
1,620 mg/kg
- -
- 16.6 mg/kg
13. 2 my/kg
— 5.5 mg/kg
— 5.5 mg/kg
5 mg/kg 0-4.500 mg/kg
- 28.6 mg/kg (mean)
— 19.6 my/kg (mean)
_
0.032 mg/kg (mean)
0.087 mg/kg (mean)
— 0.065 mg/kg mean)
0.002-0.25 mg/kg
— 2 mg/kg (mean)
- 4.7 mg/kg (mean)
— 3.7 mg/kg (mean)
102.0 mg/kg
-
-
-
-
-
- —
-
Snow Dispotal
Disposal Site
Sites Runoff
96 mg/l
- -
- -
-
-
108 mg/l (mean) -
-
-
-
-
175-2.250 mg/kg
28.6 mg/kg (mean) -
19.6 mg/kg (mean) —
1.5 mg/kg (mean) —
_
-
-
0.9-9.5 mg/kg 0.048-0.173 mg/l
-
-
- -
-
<0.05 mg/kg
-------
On the other hand, procedures used for snow and ice control may also
create a source of potential runoff pollution. The most commonly used de-
icing agent now employed is common salt, applied by itself or in combination
with abrasive materials or other chemical additives. Salt application rates
of from 300 to 500 Ibs/lane-mi (85 to 140 kg/lane-km) have been recommended
for ice at 20°F (-3°C) where an adequate traffic load exists (2); however, ap-
plication rates have been reported as high as 700 Ibs/lane-mi (198 kg/lane-km)
in Toronto. This represents an annual salt loading of more than 160 tons/
street-mi (90,400 kg/street-km) (3).
Airborne materials constitute another potential source of contaminants.
These contaminants may originate naturally or through human activity, as
particulates and gases. Airborne particulates may be deposited within an'
urban area for subsequent pickup in runoff. Rain or snowfall may scavenge
these materials and gases, and carry them into a runoff flow. An indication
of the contaminants level found in rainfall in Cincinnati is shown in
Table 25.
TABLE 25. CONCENTRATION OF
CONTAMINANTS FOUND IN RAINFALL
Average Storm
Range During Concentration
Contaminant Storm (mg/l) (mg/l)
Suspended Solids 0.5-58 13.0
Volatile Suspended
Solids 0.5-12 3.8
Inorganic N 0.12-2.3 0.69
OrthoPO, 0 -0.9 0.24
Source: Wefbel, S.R., et al., "Urban Land Runoff as a
Factor in Stream Pollution," Journal of The Water
Pollution Control Federation, Vol. 36, No. 7,
July, 1964.
The magnitude of deposited particulates on a monthly basis can be
determined for data collected in 77 mid-western cities, as shown in Figure
12. The hypothetical effects of particulate depositions are shown in Table
26. This table shows projected suspended solids concentrations for runoffs
of 100 percent and 35 percent, in comparison to measured surface runoff
concentrations. Some of the heavy metal constituents reflected in dustfall
are tabulated in Table 27. Additional information on vehicular particulate
emissions is available through the publications of the USEPA Office of Air
and Water Programs at Research Triangle Park, as well as in reports of
recent work on some of the non-point emissions. Nutrient contributions may
also be attributed to airborne sources. Nitrogen compounds exist in the
atmosphere and are removed in bulk precipitation. (4) Similarly, phosphorous
precipitation, although typically small, can be cause for concern where
receiving waters may be subject to eutrophication. (5) Phosphorous preci-
pitation rates have been reported in the range of from 0.015 to 0.96 grams
82
-------
o
O)
o
CO
ID
O
00
U)
2.20
2.00
1.80
1.60
1.40
1.20
7.07
5A5
5.61
5.01
4.81
4.55
9.00
8.00
7.00
6.00
5.00
4.00
3.16
1.00
RES
L_
COMM
(NO
SEPT
_ZZ 3.00
OCT
NOV
DEC
AREA
MONTH
Figure 12. Geometric means and 95 percent confidence intervals for
dustfall measurements bv land use and month.
Source:
Hunt. W.F., et el., "A study of Trace Element Pollution of Air In 77 Midwestern Citlaa," Paper presented at the Fourth
Annual Conference on Trace Substances In Environmental Health, University of Missouri, June 1970.
-------
TABLE 26. COMPARISON OF SUSPENDED SOLIDS
CONCENTRATIONS COMPUTED FROM DUSTFALL
AND MEASURED VALUES
(Dustfalls are mean values from two
stations adjacent to study area.)
MONTH
MAY JUNE JULY AUG. SEPT. OCT. NOV,
Mean Dustfall
(ton/mi2 /mo)
(g/m2/mo)
Monthly Rainfall
(in)
(cm)
Calculated
Mean Solids
Concentration
(mg/l)
-100% runoff
- 35% runoff
Measured Mean
Surface Runoff
Suspended Solids
(mg/l)
- Quinpool Rd.
- Cambridge St.
7.1 4.9 4.0
2.5 1.72 1.40
4.3 3.8 3.6
T0.9 9.6 9.1
23 14 15
65 41 43
147
191
6.7 4.5
2.35 1.58
7.2 5.2
18.3 13.2
13 12
37 34
131
54
6.4 6.8
2.24 2.38
4.6 4.6
11.7 11.7
20 21
56 59
104
66
Source: Waller, D.H., "Pollution Attributable to Surface Runoff and Overflows from Combined
Sewerage Systems," Central Mortgage and Housing Corporation, Ottawa, Ontario, April,
1971.
per square meter per year. (6) These values may be found to be considerably
higher in urban areas due to industrialization and urbanization. (7)
TABLE 27. GEOMETRIC MEANS FOR CADMIUM AND ZINC
FOR 77 MIDWESTERN CITIES
kg/km2/mo (ton/mi2/mo)
Contaminant
Cadmium
Lead
Zinc
Residential
0.038 (0.00011)
5.212 (0.015)
5.560 (0.016)
LAND USE
Commercial
0.063 (0.00018)
12.509 (0.036)
9.382 (0.027)
Industrial
0.073 (0.00021)
9.730 (0.028)
12.510 (0.036)
Source: Hunt, W.F., et al., "A Study of Trace Element Pollution of Air in 77 Midwestern
Cities," Paper Presented at the Fourth Annual Conference on Trace Substances in
Environmental Health, University of Missouri, June 1970.
84
-------
Soil erosion contributions to the problems of water quality are well
documented. Sediment is perhaps the largest single source of water pollution.
Sediment production varies according to land use and physical site character-
istics. Some comparative indications of relative sediment yield are shown
in Figure 13. This figure shows findings for areas of differing sizes and
land uses in the Central Atlantic States. It also shows the high yields
found in conjunction with exposed or uncovered sites. Sediments represent
pollutional contributions in the form of solids, organic loadings and their
related oxygen demands, nutrients, soil salts, trace metals, and various other
chemicals such as pesticides and herbicides. Estimating functions for nutrient
losses by erosion processes have been proposed by Midwest Research Institute. (8)
IOOO OOO
AREA (km2)
.0026 .026
5
IOO OOO-:
o
LU
IO OOO-:
g. I
IOOO-r
5.:
IOO-;
6- :
O
UJ
CO
IO
.26
2.6
260
350.000
35,000
3,500
350
Oc
35
i I I j UJII I 1 '|""| ' ' '|""1 ' iTp ITT+-. i I lHlll[ I | l||ll|
Qooi oii o.i i 10 ido KX>O
AREA (mi2)
Figure 13. Sediment yield vs contributory basin area
Source:
Malcom, H.R., and C.A. Smallwood, "Urban Erosion as a Source of Pollution." Paper prepared for the Twentieth
Southern Water Resources and Pollution Control Conference, Chapel Hill, North Carolina, April, 1971.
85
-------
It is apparent that research and evaluation related to urban potential
sources are lacking, although important initiatives involving vehicular con-
tributions as well as those related to street surface accumulations have
been taken. Many of the analytical methods employed to estimate source
contributions are non-urban in their origins and their applicability for
urban areas remains to be verified. Other verifications are needed for
average annual estimating methods that are being applied to cover shorter
time intervals. A general deficiency of data exists in a number of the
prospective source areas previously discussed, indicating the need for
additional study.
The magnitude of pollutants that may be available for pickup in surface
runoff has been assessed. The basic assumption of the approach has been
that the developed urban street is a temporary depository for the accumula-
tion of pollutants — presumably coming from the sources previously dis-
cussed — that are representative waste products of an urban environment.
Another major assumption was that the urban street is a logical extension of
the urban drainage system. On the basis of these and other assumptions,
methods were devised for estimating the quantity of runoff pollution that
will be contributed from urban streets. An indication of the results of
field studies is shown in Table 28.
Land use was generally acknowledged as the means of classifying and
characterizing the results of field measurements, except in the case of the
Washington, D.C. study where vehicular traffic contributions were studied
in detail. In this case, the selection of sampling sites was based on the
assumption that land-use effects could be minimized. Even so, two sites in
commercial areas were acknowledged to be affected by strong land-use in-
fluences.
Some variations in field measurement techniques occurred in each major
study. A summary of sampling methods is shown in Table 29.
The largest and most susceptible component of the effects of runoff
was taken to be the dust and dirt fraction. This was defined in the three
studies as the fraction passing a 0.125 in. (0.3 cm) screen, a U.S. No. 6
sieve and, finally, the fraction less than 0.25 in. (0.6 cm) in size. Field
measurements were generally taken by sweeping, in some instances by a combi-
nation of sweeping and vacuuming and flushing with water. As may be expected,
each of these sample collection methods yielded different results.
In reviewing all existing data, measurements taken by sweeping and
vacuuming accounted for 90 percent of a total of 400 samples, while the
remainder included flush sampling components. Thus, flush samples were
not included in the general data set. Data taken at known time intervals
at the same sampling location were found to produce coefficients of varia-
tion of from 0.4 to 0.6 while the multi-city sampling of initial conditions
resulted in coefficients of from 1.6 to 1.8. Thus, it appears that a
higher level of replicability was found for samples taken at the same site
at know time intervals. In addition, the majority of the data in this set
86
-------
TABLE 28. COMPARATIVE SUMMARY OF REPORTED VALUES
FOR STREET SURFACE SOLID ACCUMULATION LOADINGS
BY LAND USE
(Dust and Dirt Fractions)
ReportedValues in kg/curb-km/day
(Values in Ib/curb-mi/day)
Land Use
Residential
Single Family
Multi-Family
Commercial
Industrial
Light
Heavy
Open Space
All Uses
APWA1
—
10
(37)
34
(121)
49
(174)
68
(243)
—
—
—
—
URS2
Research
Company
1972
166
(590)
—
—
51
(180)
395
(1,400)
—
—
—
—
Omaha4
District
Biospherics3 U.S. Corps
Inc. of Engineers
4-21
(13-/5)
— —
— —
49
(175)
— —
—
— —
— —
49
URS5
Research
Company
1974
42
(149)
—
—
21
(74)
—
110
(389)
57
(203)
3
(12)
44
(175)
(156)
Source: American Public Works Association, "Water Pollution Aspects of Urban Runoff,"
USEPA Report No. 11030DNS01/69 (NTIS No. PB 215 532), January, 1969.
Sartor, J.D., and G.B. Boyd, "Water Pollution Aspects of Street Surface
Contaminants," USEPA Report No. EPA-R2-72-081 (NTIS No. PB 214 408),
November, 1972.
Shaheen, D.G., "Contributions of Urban Roadway Usage to Water Pollution,"
USEPA Report No. EPA-600/2-75-004 (NTIS No. PB 245 854), April, 1975.
Telephone conversation; Omaha District Corps of Engineers, 1975.
Amy, G., "Water Quality ManageVnent Planning for Urban Runoff," USEPA
Report No. EPA-440/9-75-004 (NTIS No. PB 241 689), December, 1974.
87
-------
TABLE 29. SAMPLING METHODS FOR MEASURING
STREET SURFACE ACCUMULATIONS
Sampling
Programs
Sample
Area
Land Uses
APWA"
Length:
Full block frontage
from building line
parallel to curb
Width: Gutter
Residential
Commercial
Industrial
URSb
Research
Co.
Length: 12-15 m
(40-50 ft)
parallel to curb
Width: 7.6m (25 ft) I
to curb
74-93 m2 (800-1 ,000 ft2)
Residential
Commercial
Industrial
Biosphericsc
Inc.
Length: 18-31 m
(60- 100 ft) or more
parallel to curb
Width: Gutter,
1.2m (4ft)l
to curb
Isolated from
land use to the
degree possible to
reflect roadway
contribution
Some commercial
Omahad
District
U.S. Corps
of Engineers
Length: 1.5 m
(5 ft) parallel
to curb
Width: Gutter,
1.2m (4ft)lto
curb
Primarily
Residential
Sampling A. Hand Sweeping
Techniques B. Vacuum Sweeping
Sampling
Techniques
Most Often
Employed
Samples
Taken
Samples
Tested
Dry Samples
A. HandSweeping
B. Vacuum Sweeping
C. Flushing of hand
swept areas
D. Simulated rainfall
on unswept street
E. Simulated rainfall
on swept street
A on each site
C on occasion
Dry Samples
Liquid Samples
A. Hand Sweeping A. Hand Sweeping
B. Vacuum Sweeping
C. Flushing
A,B,Con
each site
Dry Samples
Liquid Samples
A on each
each site
Dry Samples
Dry Samples
passing the 0.3 cm
(0.18 in) mesh
pulverized with
subsequent screening
by U.S. No. 40 sieve
[0.00375cm (0.0015
Homogenized dry samples Dry litter samples Dry samples passing
and liquid samples
composited on the
basis of land use
in)]
retained on U.S.
No. 6 sieve
[0.03 cm
(0.012 in)]
Liquid samples
(flush fraction)
the U.S. No. 10
sieve
[0.02cm (0.008 in)]
Sources: "American Public Works Association, "Water Pollution Aspects of Urban Runoff," USEPA Report No.
11030DNS01/69 (NTIS No. PB 215 532), January, 1969.
Sart?r, J.D.and G.B. Boyd, "Water Pollution Aspects of Street Surface Contaminants," USEPA Report No.
EPA-R2-72-081 (NTIS No. PB 214 408), November, 1962.
Shaheen, D.B., "Contributions of Urban Roadway Usage to Water Pollution," USEPA Report No. EPA-6007
2-75-004 (NTIS No. PB 245 854), April, 1975.
Information on U.S. Corps of Engineers survey program was determined by telephone conversation with
Mr. Jack Rose, the project engineer for the Omaha District in March, 1975.
88
-------
was collected in the Great Lakes area while the greatest data deficiencies
existed in the Northwest and Southeast parts of the country. It was concluded
that regional comparisons of the data were warranted. A tabulation of the
means of all applicable data weighted by the number of samples taken, is
shown in Table 30.
TABLE 30. AVERAGE DAILY DUST AND DIRT ACCUMULATION AND RELATED
POLLUTANT CONCENTRATIONS FOR SELECT FIELD OBSERVATIONS
PoflutMIt
Land Use Categories
Dust and Dirt
Accumulation
lb/curt>-mi/daY
kg/curb-km/day
Chicago'1 '
Washington'2'
Multi-City'3'
All Data
BOD mg/kg
COD mg/kg
Total N-N
(mg/kg)
Kjeldahl N
(mg/kg)
N03-N
(mg/kg)
NO2-N
(mg/kg)
Total PO^
(mg/Vg)
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs.
Mean
Range
No. of Obs
Single Family
Residential
35(10)
19-96(5-27)
60
182(51)
3-950(1-268)
14
62(17)
3-950(1-268)
74
5,260
1.720-9,430
59
39,250
18,300-72,800
59
460
325-525
59
-
-
-
-
Multiple Family
Residential
109(31)
62-153(17-43)
93
_
-
157(44)
8-770(2-217)
8
113(32)
8-770(2-217)
101
3,370
2,030-6320
93
41,970
24,600-61,300
93
550
356-961
93
-
Commercial
181(51)
71-326(80-151)
126
134(381
35-365(10-103)
22
45(13)
3-260(1-73)
10
116(47)
3-365(1 -103)
158
7.190
1,280-14,540
102
61,730
24,800-498,410
102
420
323-480
80
640
230-1,790
22
24
10-35
21
0
0
15
170
90-340
21
Industrial
325(92)
284-536(80-151)
55
-
288(81)
4-1,500(1-423)
12
319(90)
4-1,500(1-423)
67
2,920
2,820-2,950
56
25,080
23,000-31,800
38
430
410-431
38
All Data
158(44)
19-536(5-15)
334
134(38)
35-365(10-103)
22
175(49)
3-1,500(1-423)
44
159(45)
3-1,500(1-423)
400
5,030
1,288-14,540
292
46,120
18,300-498,410
292
480
323-480
270
640
230-1,790
22
24
10-35
21
15
0
15
170
90-340
21
89
-------
TABLE 30 (cont'd)
Pollutant i
Land Ui* Categorin
P04-P
(mg/kg)
Chlorides
(mg/kg)
Asbestos
fibers/lb
(fibers/kg)
Ag
(mg/kg)
As
(mg/kg)
Ba
(mg/kg)
CD
(mg/kg)
Cr
(mg/kg)
Cu
(mg/kg)
Fe
(mg/kg)
Hg
(mg/kg)
Mn
(mg/kg)
Ni
(mg/kg)
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of CDS
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Single Family
Residential
49
20-109
59
-
-
Multiple Family
Residential Commercial
58
20-73
93
-
-
-
_
60
0-142
101
220
100-370
22
57.2x106(126x106)
Industrial
26
14-30
38
_
-
-
0-172.5x106(0-380x106)
-
--
_
-
3.3
0-3.8
14
200
111-325
14
91
33-150
14
21,280
11,000-48,000
14
450
250-700
14
38
0-120
14
-
-
-
-
_
-
-
2.7
0.3-6.0
8
180
75-325
8
73
34-170
8
18,500
11,000-25,000
8
_
-
-•
340
230-450
8
18
0-80
8
16
200
0-600
3
0
0
3
38
0-80
8
2.9
0-9.3
22
140
10-430
30
95
25-810
30
21,580
5,000-44,000
10
0.02
0-0.1
6
380
160-540
10
94
6-170
30
-
-
-
-
_
-
3.6
0.3-11.0
13
240
159-335
13
87
32-170
13
22,540
14,000-43,000
13
-
-
430
240-620
13
44
1-120
13
All Data
53
0-142
291
220
100-370
22
57.2x106(126x106)
0- 172.5x1 0s (0-380x1 06!
16
200
0-600
3
0
0
3,
38
0-80
8
3.1
0-11.0
57
180
10-430
65
90
25-810
65
21,220
5,000-48,000
45
0.02
0-0.1
6
410
160-700
45
62
1-170
65
90
-------
TABLE 30 (cont'd)
Pollutant
Land Use Categories
Pb
(mg/kg)
Sb
(mg/kg)
Se
(mg/kg)
Sn
(mg/kg)
Sr
(mg/kg)
Zn
(mg/kg)
Fecal Strep
NoVgram
Fecal Coli
No. /gram
Total Coli
NoVgram
Single Family
Residential
Mean 1,570
Range 220-5.700
No. of Obs 14
Mean
Range
No. of Obs
Mean
Range
No. of Obs
Mean
Range
No. of Ots
Mean 32
Range 5-110
No. of Obs 14
Mean 310
Range 110-810
No. of Obs 14
Geo. Mean
Range
No. of Obs
Geo. Mean 82.EOO
Range 26-130.000
No. of Obs 65
Geo. Mean 891.000
Range 25,000-3,000.000
No. of Obs 65
Multiple Family
Reiidential
1.980
470-3,700
8
-
-
_
-
-
_
-
-
18
12-24
8
280
210-490
8
_
38,800
1,500-1.000,000
96
1,900,000
Commercial
2.330
0-7,600
29
54
50-60
3
0
0
3
17
0-50
3
17
7-38
10
690
90-3,040
30
370
44-2,420
17
36,900
140-970.000
84
1,000,000
80.000-5,600,000 18,000-3,500,000
97
85
Industrial
1,590
260-3,500
13
-
-
--
13
0-24
13
280
140-450
13
-
30.700
67-530,000
42
419,000
All Data
1,970
0-7,600
64
54
50-60
3
0
0
3
17
0-50
3
21
0-110
-45
470
90-3.040
65
370
44-2,420
17
94,700
26-1,000,000
287
1,070,000
27,000-2,600,000 18,000-5,600.000
43
290
Source: 'American Public Works Association, "Water Pollution Aspects of Urban Runoff," USEPA Report No.
1 I030DNS01/69 (NTIS No. PB 215 532), January, 1969.
2Shaheen, D.G., "Contributions of Urban Roadway Usage to Water Pollution," USEPA Report No.
EPA-600/2-75-004 (NTIS No. PB 245 854), April, 1975.
3Sartor, J.D., and G. B. Boyd, "Water Pollution of Street Surface Contaminants," USEPA Report No.
EPA-R2-O81 (NTIS No. PB 214 408), November. 1972.
Amy, G., "Water Quality Management Planning for Urban Runoff," USEPA
Report No. EPA-440/9-75-004, (NTIS No. PB 241 689), December, 1974.
Note: Data for this table have had the flush fraction and some U RS Data edited out - these data represent
sweeping values only.
Although the foregoing table does not reflect flush samples, the
Information depicted in Table 31 gives an indication of its significance
as a method for capturing additional particulate and soluble materials
otherwise unremoved.
91
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TABLE 31. PERCENTAGE OF POLLUTANTS FOUNp IN
DUST AND DIRT AND FLUSH SAMPLES ATTRIBUTABLE
TO THE FLUSH FRACTION
Number Of Average Percentage Range Of Flush
Pollutant
Accumulation
(dry weight)
Volatile Solids
BOD
COD
Total PO4-P
P04-P
N03-N
N02-N
Kjeldahl N
Chlorides
Asbestos
Lead
Chromium
Copper
Nickel
Zinc
F. Strep
F. Coli
Observations
82
82
82
82
82
82
82
82
82
82
68
10
10
10
10
10
82
82
In Flush Fraction
7
20
36
16
15
43
69
97
33
43
13
4
17
5
5
2
44
76
Fraction Percentages *
5.2-8.8
17.1-22.9
31.1-40.9
13.3-18.7
11.7-18.3
33.7-52.3
63.7-74.3
95.4-98.6
27.9-38.1
35.7-50.3
5.4-20.6
2.5-5.5
5.7-28.3
2.0-8.0
3.5-6.5
1 .2-2.8
35.3-52.7
67.1-84.9
•Ranges inferred at 95% confidence interval
Source: Shaheen, D.G., "Contributions of Urban Roadway Usage to Water Pollution,'
USEPA Report No. EPA600/2-75-004 (NTIS No. PB 245 854), April, 1975.
As to deposition characteristics, the majority of street surface solids
has been found to accumulate within 6 in- (15 cm) of the curbface and vir-
tually all accumulations may be accounted for within 3.5 ft (1.2 m) of the
curb line. Street surface accumulations are not uniformly deposited longitu-
dinally along streets.
When classification of accumulations is based on the U.S. No. 6 sieve,
it seems likely that asphaltic concrete wear or weathering products would
probably contribute more to the litter fraction while concrete would produce
more dust and dirt sized materials. On this basis, about 25 percent or more
of the total accumulation on these pavement surfaces may be associated with
surfacing materials alone. Accumulation loadings on asphaltic surfaces have
been found to be about 80 percent heavier than on concrete streets.
92
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The effects of pavement types, variation in street pattern, curb height
and other physical factors can meaningfully influence results. The best
use of street accumulation data by itself would appear to be in completely
urbanized areas which have fully developed streets and wholly sewered col-
lection systems. In addition, use of this information by itself should be
most appropriate for low-intensity runoff events where pervious area
contributions are minimal.
STORM and SWMM modeling was applied to some of the street accumulation
values developed for five urbanized areas. Employing the reported pollutant
to solids relationships associated with these developed values, and measured
annual average pollutant concentrations reported for each, some level of model
calibration was possible through the adjustment of dust and dirt values. Dust
and dirt correction factors of 2.0 for Atlanta, 0.25 for Denver, 1.33 for Des
Moines, 0.1 for Minneapolis, and 0.5 for San Francisco, produced reasonable
estimates for single runoff events for the pollutant for which the adjustment
was made.
The foregoing discussions have attempted to outline techniques and tech-
nologies now available as a basis for estimating the magnitude and signifi-
cance of urban runoff pollution. In addition, they have attempted to highlight
some of the more apparent problems that exist in the use of this information.
It is apparent from the foregoing; that additional research and investigation
are warranted to resolve these problems. Further investigations are needed
to better determine temporal time and flow-related variations in discharge
pollutant concentrations for urban areas with wholly sewered collection
systems. In connection with this effort, street surface accumulation sampling
should be further pursued to clarify the relationships of potential and actual
pollutional contributions.
93
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REFERENCES
1. Shaheen, D.G., "Contributions of Urban Roadway Usage to Water Pollution,"
USEPA Report No. EPA-600/2-75-004 (NTIS No. 245 854), April, 1975.
2. "Use and Effects of Highway De-icing Salts," Legislative Research
Council Report, Commonwealth of Massachusetts, January, 1965.
3. J.L. Richards and Associates, Ltd., and Labrecque, Vezina and Associates,
"Snow Disposal Study for the National Capitol Area.: Technical Discus-
sion," Committee on Snow Disposal, Ottawa, Ontario, June, 1973.
4. Williford, J.W., and D.R. Cardon, "Possibility of Reducing Nitrogen in
Drainage Water by On-Farm Practices," USEPA Report No. 13030ELY05/72
(NTIS No. PB 221 482), June, 1972.
5. Bartsch, A.F., "Role of Phosphorus in Eutrophication," USEPA Report
No. EPA-R3-72-001 (NTIS No. PB 228 292), August, 1972.
6. Vollenweider, R.A., "Scientific Fundamentals of the Eutrophication of
Lakes and Flowing Waters, with Particular Reference to Nitrogen and
Phosphorus As Factors in Eutrophication," Organization for Economic
Cooperation and Development, Directorate for Scientific Affairs, Paris,
DAS/CSI/68-27, 1968.
7. Uttormark, P.O., et al., "Estimating Nutrient Loadings of Lakes from
Non-Point Sources," USEPA Report No. EPA-660/3-74-020 (NTIS No. PB
238 355), August, 1974.
8. McElroy, A.D., et al., "Loading Functions for Assessment of Water
Pollution From Non-Point Sources," USEPA Report No. 600/2-76-151,
May, 1976.
9. Colston, N. V., "Characterization and Treatment of Urban
Land Runoff,"" USEPA Report 670/2-74-096, December 1974.
94
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1..REPORT NO.
EPA-600/2-77-064a
3. RECIPIENT'S ACCESSION NO.
A. TJTL/E AND SUBTITLE
NATIONWIDE EVALUATION OF COMBINED SEWER OVERFLOWS AND
URBAN STORMWATER DISCHARGES
Volume I: Executive Summary
5. REPORT DATE
September 1977 [Issuing Date)
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S) Richard H Sullivan, Martin J. Manning (APWA)
James P. Heaney, Wayne C. Huber, M. A. Medina, Jr., M. P. Murphy,
S. J. Nix, S. M. Hasan (University of Florida)
«. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
American Public Works Association
1313 East 60th Street
Chicago, Illinois 60637
10. PROGRAM ELEMENT NO.
1BC611
68-03-0283
12. SPONSORING AGENCY NAME AND ADDRESS
Municipal Environmental Research Laboratory--Gin . , OH
Office of Research & Development1
U.S. Environmental Protection Agency
Cincinnati, Ohio 45268
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
EPA/600/14
is.SUPPLEMENTARY NOTES Project Officer: Richard Field, (201) 321-6674, FTS 340-6674.
This report is the executive summary for: EPA-600/2-77-064[b] , Volume II, "Cost Assessment and Impacts/-
and EPA-i600/2-77-064c, Volume III, "Characterization of'Discharges."
16. ABSTRACT
A study was conducted by the American Public Works Association and the University of Florida to determine: the cost of
abating pollution from combined sewer overflows and urban stormwater, the impact of such pollutional discharges on
receiving waters, and the pollution potential of such discharges., The study was based upon the availability of existing data
and prediction models.
Continuous simulation runs using one year of hourly data were made to determine the attainable level of pollution control
with a specified availability of storage volume and treatment rate in five cities: Atlanta, Denver, Minneapolis, San Francisco,
and Washington, D.C. This procedure was used to derive generalized equations relating pollution control to storage and
treatment. These results were combined into a simple optimization model which determined the optimal mix of storage and
treatment for any feasible level of control for any city. Then the nationwide assessment is presented. The results indicate
annual costs ranging from $297 million for 25 percent pollution control to $5,029 million for 85 percent pollution control.
The corresponding initial capital investment ranges from $2,476 million for 25 percent control to $41,900 million for 85
percent control. These costs can be reduced significantly if stormwater pollution control is integrated with best management
practices and integrated into a multi-purpose program.
The balance of the study analyzed existing published and unpublished information to characterize the pollution potential
of urban runoff and to estimate the impact of such runoff on receiving waters. It was found that there appears to be direct
connections between many parameters such as BOD and suspended solids with the amount of street refuse. However, some
parameters appear to be related to more site specific factors. As a practical matter it was found necessary to relate pollution
abatement to BOD and suspended solids, even though there are many other pollutants in large concentrations such as heavy
metals and phosphorus.
These reports have been submitted in fulfillment of Contract No. 68-03-0283 between the American Public Works
Association, and the Office of Research and Development, U.S. Environmental Protection Agency. Work was completed
in October, 1976.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDED TERMS C. COSATI Fields/GrOUp
Combined sewers
Water pollution
Cost analysis
Mathematical models
Surface water runoff
Fixed investment
Water pollution sources
Water pollution control
Water pollution treatment
Separated sewers
Capital investment
13B
18. DISTRIBUTION STATEMENT
Release to Public
INSECURITY CLASS (This Report)
Unclassified
21. NO. OF PAGES
107
20. SECURITY CLASS (This page)
Unclassified
EPA Form 2220-1 (9-73)
95
U.S. GOVERNMENT PRINTING OFFICE • 1977 0-241-037/73
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