&EPA
United States
Environmental Protection
Agency
Municipal Environmental Research EPA-600/2-79-031b
Laboratory July 1979
Cincinnati OH 45268
Research and Development
Combined Sewer
Overflow
Abatement
Program
Rochester, NY
Volume II.
Pilot Plant
Evaluations
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate further development and application of en-
vironmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7. . Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the ENVIRONMENTAL PROTECTION TECH-
NOLOGY series. This series describes research performed to develop and dem-
onstrate instrumentation, equipment, and methodology to repair or prevent en-
vironmental degradation from point and non-point sources of pollution. This work
provides the new or improved technology required for the control and treatment
of pollution sources to meet environmental quality standards.
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/2-79-0315
July 1979
COMBINED SEWER OVERFLOW ABATEMENT PROGRAM, ROCHESTER, N.Y,
Volume II. Pilot Plant Evaluations
by
Frank J, Drehwing
Cornelius B, Murphy, Jr.
Steven-R. Garver
Donald F. Geisser
Dilip Bhargava
O'Brien & Gere Engineers, Inc.
Syracuse, New York 13221
Grant No, Y005141
Project Officers
Richard Field/Anthony Tafuri
Storm and Combined Sewer Section
Wastewater Research Division
Municipal Environmental Research
Laboratory (Cincinnati)
Edison, New Jersey 08817
Lawrence Mori arty
Region II
Rochester, New York 10007
Grant Officer
Ralph 6, Christensen
Great Lakes Demonstration Program
Great Lakes National Program Office
Region V, Chicago, Illinois 40604
MUNICIPAL ENVIRONMENTAL RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
CINCINNATI, OHIO 45268
and
GREAT LAKES NATIONAL PROGRAM OFFICE
U.S. ENVIRONMENTAL PROTECTION AGENCY
CHICAGO, ILLINOIS 60604
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DISCLAIMER
This report has been reviewed by the Municipal Environmental Research
Laboratory and the Great Lakes National Program Office, U.S. Environmental
Protection Agency, and approved for publication. Approval does not signify
that the contents necessarily reflect the views and policies of the U.S.
Environmental Protection Agency, nor does mention of trade names or com-
mercial products constitute endorsement or recommendation for use.
ii
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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,
treatment and management of wastewater and solid and hazardous waste
pollutant discharges from municipal and community sources, for the pre-
servation and treatment of public drinking water supplies and to minimize
the adverse economic, social, health, and aesthetic effects of pollution.
This publication is one of the products of that research; a most vital
communications link between the researcher and the user community.
The Great Lakes National Program Office, through Section 108(a) of
PL 92-500, enters into grants for the demonstration of new methods and
techniques and for the development of preliminary plans for the prevention,
reduction or elimination of pollution within all or any part of the water-
sheds of the Great Lakes. The Great Lakes National Program Office has
joined with the Municipal Environmental Research Laboratory in carrying
out this research and demonstration project to assist the Rochester Pure
Waters District to eliminate an urban drainage pollution problem to
Lake Ontario.
The deleterious effects of storm sewer discharges and combined sewer
overflows upon the nation's waterways have become of increasing concern
in recent times. Efforts to alleviate the problem depend upon characteri-
zation of these flows both as to quantity and quality. This report
describes the results of pilot plant studies of a number of treatment
technologies for controlling the quality of combined sewer overflow dis-
charges.
Francis T. Mayo Dr. Edith J. Tebo
Director Director
Municipal Environmental Research Great Lakes National
Laboratory Program Office
i i i
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ABSTRACT
The Rochester Pilot plant treatability studies were designed to
interact with combined sewer overflow (CSO) monitoring and system modeling
efforts for the Monroe County Pure Waters District with the ultimate
objective of evaluating CSO abatement alternatives, as presented in
Volume I of this Report.
The studies covered treatment by the following unit processes:
flocculation/sedimentation (F/S), swirl degritter and swirl primary
separator, microscreening with sonic cleaning, dual-media high-rate
filtration, activated carbon adsorption, sludge dewatering and high-rate
disinfection. Applied flowrates to the system ranged between 0.3 and
11.2 1/s (5 and 177 gpm).
Pilot operations covered nineteen overflow events during the period
of September 1975 through June 1976. The studies evaluated the effects
of design loadings and influent quality on system performance. Data
were evaluated through application of statistical techniques and develop-
ment of mathematical performance models. These models were used to
develop optimum cost/benefit comparisons of systems. Results were also
compared to published literature for similar installations at other
locations.
The flocculation/sedimentation system was evaluated employing
surface overflow rates from 33 to 82 m3/day m2 (800 to 2000 gpd/ft2).
Mathematical performance models were developed for the three chemical
treatment cases. These models related SS removal rates to overflow rate
and influent SS concentrations.
The swirl separators were pilot tested at flowrates ranging from
0.9 to 4.4 1/s (15 to 70 gpm). Mathematical performance models were
developed for each system relating SS removal rates to influent flowrate
and influent SS concentration. Chemical treatments were tested on the
swirl primary system, but the in-line flocculation technique did not
provide sufficient energy to permit effective flpc development. The
performance equations were compared to previously developed design
curves for swirl concentrators.
Testing of the microscreen system was limited due to equipment mal-
function. Headless development across the screen was shown to be related
to both hydraulic loading and screen rotational speed. The maximum
hydraulic loading attainable for most of the dry and wet-weather testing
was on the order of 550 1/min m2 (13.5 gpm/ft2) of screen surface when
using a 70 micron screen.
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Dual-media high-rate filters (DMHRF) were evaluated at hydraulic
loading rates between 407 to 1018 1/nrin m2 (10 to 25 gpm/ft*). Re-
sults are compared for filtration with no chemical addition and
with polyelectrolyte alone and alum plus polyelectrolyte. The per-
formance curves show the effects of the chemical addition and the
impact of the upstream (swirl primary separator) treatment on per-
formance of the DMHRF.
Operation of the carbon adsorption system was limited to three
storms. Detention times of 13.5 to 45 minutes were evaluated. Optimum
BOD5 removals (80-95 percent) were attained at detention times of 20
to 30 minutes.
Multiple regression modeling of the chlorine (Clp) and chlorine
dioxide (0102) disinfection data yielded statistically significant
equations for the high-rate disinfection systems. The models indicated
that disinfection by Clg is more sensitive to mixing intensity and
detention time than disinfection..by C102- System cost optimization
procedures indicated that C102 permitted use of lower detention time
facilities. The use of Cl2 permitted lower overall cost systems relative
to C102 for all trial cases of required kill and wastewater quality.
A review of literature is presented on solids handling consider-
ations involved with treatment of CSO.
Cost/benefit comparisons of the F/S and swirl primary separator
systems are presented. Cost/benefits of chemical treatment programs are
also presented. Cost/benefits of regional configuration alternatives
(central versus local treatment) and storage versus treatment sizing are
presented in Volume I of this Report.
This report was submitted in fulfillment of Grant No. Y005141 by
O'Brien & Gere Engineers, Inc. under the partial sponsorship of the U.S.
Environmental Protection Agency. This report covers the period from May
4, 1974 to November 1976, and work was completed as of September 1977.
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CONTENTS
Foreword i i i
Abstract : iv
Figures ix
Tab! es xi i i
Abbreviations and Symbols xv
Acknowl edgment xvi i
1. Introduction 1
2. Conclusions 4
3. Recommendations 7
4. Pilot Plant Facilities 9
General 9
Pumping Station 10
Flocculation/Sedimentation System 14
Swi rl Concentrators 15
Microscreening System 18
Storage Tanks 18
Dual Media Filters 18
Carbon Adsorpti on 20
Disinfection System 22
5. Project Plan 24
Program Development and Application of Results 24
Scope of Work 24
6. Flocculation/Sedimentation 27
Background 27
Outline of Experiments 28
Chemi cal Treatment Requ i rements 30
Suspended Sol i ds Removal 31
Scaleup "Considerations .' 35
Removal of Other Constituents 37
7. Swirl Concentrators 43
Background 43
Outl ine of Experiments 46
Swi rl Degri tter 50
Swirl Primary Separator 56
Removal of Other Consti tuents 60
8. Microscreening 68
General 68
Outl ine of Experiments 69
Results and Performance 69
9. Dual-Media, High-Rate Filtration 75
Background 75
Outline of Experiments 76
Operating Procedures 79
vi i
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CONTENTS (continued)
Results 80
10. Activated Carbon Adsorption 91
Background 91
Outline of Experiments 91
Resul ts 92
11. High-Rate Disinfection 95
Background 95
Test Program 96
Single Stage Treatment:Chlorine vs. Chlorine Dioxide... 98
Chlorine/Chlorine Dioxide Combinations 109
12. Solids Handling Considerations 122
Sludge Thickening 122
Sludge Dewaterability 123
Discussion 123
13. Capital and Operating Cost Estimates 136
Basis of Cost Estimates 136
Capital Costs 136
14. Comparison of Alternatives 141
Cost/Benefit Comparison of Swirl Primary Separator
versus Flocculation/Sedimentation 141
Secondary Level Treatment Alternatives 142
Mi seel 1 aneous Costs 143
Discussion 143
References 146
Appendices
A. SS vs time plots-flocculation/sedimentation and swirl
concentrators 152
B. Statistical analysis of influent and effluent data-
flocculation/sedimentation and swirl concentrators 162
C. Statistical analysis of influent and effluent data-
mi croscreen system -. 179
D. Statistical analysis of effluent data-DMHRF system 182
E. Cl2 and C102 analytical data '. 190
viii
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FIGURES
Number Page
1 Pilot Plant and Pumping Station Locations ...• 9
2 Rochester Pilot Plant Facilities 11
3 Rochester Pilot Plant Facilities. -. 12
4 Flocculation/Sedimentatioh Tank (Pilot Unit) 15
5 Swirl Degritter (Pilot Unit) 16
6 Swirl Primary Separator (Pilot Unit) 17
7 The FMC Sonic Cleaner Microscreen (Pilot Unit) 19
8 Storage Tank 20
9 Dual-Media High-Rate Filter (Pilot Unit) 21
/
10 Activated Carbon Column (Pilot Unit) 21
11 Pilot Disinfection Tank and Mixing Concepts 22
12 Comparison of Polyel ectrolyte Types 30
13 Selection 'of Polyel ectrolyte Dosage 31
14 Variation in Alum Demand 32
15 Performance of Flocculation/Sedimentation System @ 800 gpd/ft2... 35
16 Performance of Flocculation/Sedimentation System @ 1500 gpd/ft2.. 36
17 Performance of Flocculation/Sedimentation System @ 2000 gpd/ft2.. 36
18 Loading-Performance Relationships: Flocculation/Sedimentation
System 37
19 Swirl Regulator/Concentrator 44
20 Swirl Degritter 44
21 Swirl Primary Separator 44
ix
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FIGURES (continued)
ft
Number Page
22 Combined Sewer Overflows: Particle Size Distribution 49
23 Swirl Degritter: Model and Prototype Particle Size Distributions. 51
24 Performance of Swirl Degritter (6 ft dia. unit) 55
25 Swirl Primary Separator: Regression Model and Performance Data... 58
26 Swirl Primary Separator: Loading-Performance Relationship 58
27 Swirl Primary Separator: Model and Prototype Particle Size
Distributions 60
28 Mi croscreen System Performance 70
29 Microscreen System Performance 70
30 Microscreen System Performance 72
31 Microscreen System Performance 72
32 Mi croscreen System Performance 73
33 Microscreen System Performance 73
34 Typical Filter (DMHRF) Performance Curves 81
35 DMHRF Run Lengths.'. 82
36 DMHRF Run Lengths 82
37 DMHRF Run Lengths 83
38 DMHRF Specific Capture 84
39 DMHRF Specific Capture , 84
40 DMHRF Performance 86
41 DMHRF Performance 87
42 BOD5 Removal With Carbon Adsorption 93
43 BODs Removal With Carbon Adsorpti on .93
44 BOD5 Removal With Carbon Adsorption 94
45 Comparison of Regression Model With Literature Results 103
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FIGURES (continued)
Number Page
46 Effect of Cl2 Dose in Regression Models 104
47 Effect of C102 Dose in Regression Models 105
48 Effect of BOD5 in Regression Models 105
49 Effect of TKN in Regression Models 106
50 Predicted vs. Observed Bacterial Reductions for Chlorine 107
51 Predicted vs. Observed Bacterial Reductions for Chlorine
Dioxide 108
52 Optimization Trends 110
53 Two Stage Disinfection Iso-kill Curves 113
54 Two Stage Disinfection Iso-kill Curves 113
55 Two Stage Disinfection Iso-kill Curves 114
56 Two Stage Disinfection Iso-kill Curves 114
57 Two Stage Disinfection Iso-kill Curves 116
58 Two Stage Disinfection Iso-kill Curves 116
59 Comparison of Order of Addition: C12-C102 Combinations 117
60 Comparison of Order of Addition: C12-C102 Combinations 118
61 Comparison of Order of Addition: C12-C102 Combinations 119
62 Comparison of Order of Addition: C12-C102 Combinations 120
63 Comparison of Order of Addition: C12-C102 Combinations 121
64 CSO Primary Treatment Sludge Settling Curves 122
65 Sludge Dewaterability Tests 124
66 Sludge Dewaterability Tests 124
67 SI udge Dewaterabi 1 i ty Tests 125
68 Sludge Dewaterability Tests 125
69 Sludge Aging Studies ; 126
xi
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FIGURES (continued)
Number Page
70 Sludge Aging Studies 126
71 Sludge Aging Studies 127
72 Cost-Performance Comparisons , '.......144
73 Cost-Performance Comparisons 144
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TABLES
Number Page
1 Pilot Plant Design Parameters 13
2 Storm Characteri stics 26
3 Flocculation/Sedimentation System Test Matrix 29
4 Multiple Regression Analysis of Flocculation/Sedimentation Data:
No Chemical Treatment 33
5 Multiple Regression Analysis of Flocculation/Sedimentation Data:
Treatment with Anionic Polymer 34
6 Multiple Regression Analysis of Flocculation/Sedimentation Data:
Treatment with Alum and Anionic Polymer 34
7 Flocculation/Sedimentation System-Median Removals 39
8 Percent VSS of SS - Flocculation/Sedimentation System 42
9 Swirl Degritter and Primary Separator Test Matrix 46
10 Swirl Degritter and Primary Separator: Model and Prototype Flow
Rates 47
11 Particle Settling Distributions 48
1-2 Grit Solids Distribution 51
13 Swirl Degritter-Model to Prototype Scaling of Particle Sizes 53
14 Regression Analysis of Pilot Plant Swirl Degritter Data 54
15 Regression Analysis of Pilot Plant Swirl Primary Separator Data.. 57
16 Swirl Primary Separator-Model to Prototype Scaling of Particle
Sizes 59
17 Swirl Degritter System-Median Removals 61
18 Swirl Primary Separator System-Median Removals 64
19 Swirl Degritter - Percent VSS of SS 67
xi i i
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TABLES (continued)
Number Page
20 Swirl Primary Separator - Percent VSS of SS 67
21 Microscreening Analytical Data 74
22 DMHRF Operating Conditions 77
23 Sieve Analysis of Filter Media 79
24 Medi an Performance of DMHRF 88
25 Activated Carbon Operating Conditions *.. 91
26 Summary of Wet-Weather Disinfection Operating Conditions 97
27 Summary of Dry-Weather Disinfection Operating Conditions „ 98
28 Multiple Regression Analysis Results for Disinfection by Cl2 101
29 Multiple Regression Analysis Results for Disinfection by C102 101
30 Cost Optimization. CSO-Primary Effluent Ill
31 Cost Optimization. CSO-Filtered Effluent .111
32 Cost Optimization. CSO-Activated Carbon Effluent HI
33 Estimated Loadings for 100 Percent CSO Treatment 123
34 Rochester Pilot Plant Volatile Solids Fractions 129
35 Pilot Plant CSO Heavy Metals Data 129
36 Heavy Metal Characteristics of CSO Sludges 130
37 Sludge Processing Facilities 134
xiv
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LIST OF ABBREVIATIONS AND SYMBOLS
ABBREVIATIONS
ALPPH — alum feed rate
APWA -- American Public Works Association
ASCE — American Society of Civil Engineers
BODs — 5 day biochemical oxygen demand at 20C
cal -- calories
cc -- chemical cost
ce — effluent suspended solids concentration
cm — centimeters
CQ — influent suspended solids concentration
COD -- chemical oxygen demand
CSO -- combined sewer overflow
D.T. -- detention time
D2/D1 -- chamber diameter/inlet diameter
dia -- diameter
DMHRF -- dual-media high-rate filter
DOSE -- chemical dosage
e.s. — effective size
FBV — flocculation basin volume
ft — feet
ft2 -- square feet
ft3 — cubic feet
fpm -- feet per minute
F/S — flocculation/sedimentation
6 -- velocity gradient (sector rnin"1, as specified)
6T — effective mixing intensity
gal -- gallons
g -- grams
gc — effluent grit concentration
go — Influent grit concentration
gpd -- gallons per day
gpm -- gallons per minute
6/S -- swirl degritter
hr — hour
ha -- hactares
Hi/D2 — 'weir height/swirl chamber diameter
hp — horsepower
in -- inches
kg — kilograms
1 -- liters
LC -- labor cost
1/s -- liters/second
m -- meters
xv
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ABBREVIATIONS (continued)
m2 -- square meters
m3 — cubic meters
mg -- mill grams
mil gal — million gallons
mgd — million gallons per day
MGTPY — million gallons treated per year
ml — milliliter
mm -- millimeter
min -- minute
mg/1 __ milligrams/liter
M/S -- microscreen
N -- Newtons
NOF — number of overflow events per year
NUMUNITS -- number of swirl units
Np -- Froude number
O&G -- oil and grease
OR -- overflow rate
PC — power cost
PCB -- polychlorinated biphenyl
POLPPH — polymer feed rate
P/S -- swirl primary separator
PVC -- polyvinyl chloride
R-M — rapid mix
rpm — revolutions per minute
SA — surface area
S.G. — specific gravity
SETTS — settleable solids
scfm -- standard cubic feet per minute
SS — suspended solids
SWMM -- stormwater management model
T — contact time
TIP- — total inorganic phosphorus
TKN — total Kjeldahl nitrogen
TOC -- total organic carbon
TS -- total solids
USEPA -- United States Environmental Protection Agency
v — velocity
V — basin volume
VSS -- volatile suspended solids
WOR — weir overflow rate
SYMBOLS
Al -- aluminum
Cl2 — chlorine
C102 -- chlorine dioxide
P — phosphorus
Q -- flowrate, units as specified
/ ' — per (to indicate rates)
$ mil -- million dollars
xvn
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ACKNOWLEDGMENTS
O'Brien & Gere Engineers, Inc., gratefully acknowledges the
cooperation of the Monroe County Division of Pure Waters. Appreciation
is expressed to Dr. Gerald McDonald, Director, Thomas Quinn, Chief of
Technical Operations, Robert Hallenbeck, former Chief of Technical
Operations, and James Stewart of the Monroe County Division of Pure
Waters for their cooperation and assistance.
The support of this effort by the Storm and Combined Sewer Section,
Eidson, New Jersey of the USEPA Municipal Environmental Research Laboratory,
Cincinnati, Ohio and of the Office of the Great Lakes Coordinator, Region
V, USEPA, Chicago, Illinois and especially of Richard Field, Chief, Anthony
Tafuri, Project Officer, Storm and Combined Sewer Section, Ralph Christensen,
Chief, Section 108a Great Lakes Demonstration Program, and Larry Moriarty,
Project Officer, USEPA, Region II for their guidance, suggestions and
contributions is acknowledged with gratitude.
This report has been prepared by O'Brien & Gere Engineers, Inc.,
Syracuse, New York under the direction of Frank J. Drehwing, Vice President,
and Cornelius B. Murphy, Managing Engineer.
xvi i
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SECTION 1
INTRODUCTION
BACKGROUND
The significance of pollution caused by storm-generated discharges has
been well documented. A large portion of this pollution is associated with
overflows or relief points in combined sewer systems. A nationwide survey
by the APWA (1) indicated that combined sewers are used in more than 1300
municipalities serving a population of 54 million. The magnitude of the
overflow problem was exemplified by a 2-year study conducted on a 92.7 ha
(229 acre) combined sewer watershed in Northampton, England. This study
showed that the cumulative yearly five-day biochemical oxygen demand (BODs)
load in the combined sewer overflows nearly equaled the BODs load contained
in the effluent of the local secondary treatment plant. Suspended solids
within the overflows were three times the load contributed by the treat-
ment work effluent (1).
Another aspect of the problem was illustrated in a report on the
combined sewers in Buffalo, N.Y. (2). In Buffalo, 20 to 30 percent of the
annual collection of domestic sewage solids settle in the sewers during
dry periods and are eventually discharged during storms. This results in
shock loadings which are detrimental to aquatic life in the receiving water.
The most obvious solution to abatement of combined sewer overflows
(CSO) is construction of separate storm sewer networks. In terms of dollars
per acre served, this is a very costly alternative and is technically
difficult in heavily populated and developed urban areas. Moreover, it is
possible that quality control of storm sewer discharges may be necessary
in the future.
CSO abatement alternatives have been classified into three groupings:
(a) nonstructural alternatives, (b) minimal-structural alternatives and
(c) capital intensive alternatives. These have been described in detail
in Volume I of this Report (3).
Many CSO abatement techniques such as regulator adjustments, elimi-
nation of interceptor constraints and in-system storage, while reducing
overflow volumes, result in containment of large volumes of wastewater which
require treatment. Ideally, the flow-attenuating techniques would allow
treatment of the additional contained wastewaters in existing dry-weather
treatment facilities during nonstorm periods. However, it appears that
existing dry-weather treatment facilities in many communities do not have
either the hydraulic or solids-handling capabilities to adequately treat
even attenuated storm flows. These stormwater contributions could cause
very serious hydraulic and toxic upset conditions in biological treatment
1
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systems not specifically designed for this impact.
Therefore, an integral part of most CSO abatement programs is con-
sideration of the treatment technologies to be applied to the intercepted
wet-weather flows. Since the characteristics of combined sewage are quite
different from those of dry-weather domestic sewage, different treatment
concepts may be applied to wet-weather flows. For example, wet-weather
suspended solids generally exhibit a fairly coarse size distribution and
may readily be removed in primary facilities operated at relatively high
hydraulic loading rates.
PURPOSE OF STUDY
The pilot plant treatability studies were undertaken to delineate the
treatment alternatives available for control of CSO quality in the Rochester
Pure Waters District of Monroe County, New York.
The direction of the pilot plant study was based partly on requirements
outlined by the USEPA (73). These requirements stated that all CSO shall
have a minimum of primary treatment, phosphate removal,and chlorination
with absolutely no bypassing.
A major emphasis of the study was the development of cost/benefit com-
parisons of processes that would allow primary-level treatment efficiencies.
These processes were compared relative to their response to treating
variable-quality influent wastewater. Treatment of the highly concentrated
first-flush overflow was of particular importance. Most of the comparisons
centered around the flocculation/sedimentation and swirl separator
systems. Evaluations of chemical treatments were instrumental for the
determination of optimum conditions.
Previous studies of the District's combined system (74, 75) cited
deficiencies of the existing sewerage system and the effects of wastewater
discharges on the area receiving waters. Those studies recognized that
measures were necessary for collection, transmission, control and treatment
of combined wastewaters originating within the City of Rochester. Sub-
sequent studies (76) have reinforced the earlier studies and documented
the impact of CSO on the Genesee River and the Rochester Embayment of Lake
Ontario. The objective of this study was to outline a plan of best
management practices through a program of CSO monitoring, system modeling
and treatability studies. The treatability studies reported herein were
designed specifically to interact with the modeling efforts and evaluations
of abatement alternatives. The treatability studies and cost estimates were
particularly instrumental to evaluation of satellite overflow treatment
versus centralized treatment and determination of storage versus treatment
capacity optimizations.
The treatment processes included in this study represent those systems
that are currently receiving prime nationwide consideration for treatment
of CSO. Combinations of the piloted processes could result in process
trains capable of providing treatment efficiencies from grit removal through
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tertiary treatment quality and disinfection. A secondary objective of the
pilot program was to provide additional expansion of the nationwide data
base for evaluating CSO treatability. Every effort was made to compare
results of this study to results reported for similar installations at
other locations. '
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SECTION 2
CONCLUSIONS
1. Most CSO abatement techniques result in containment of large volumes
of wastewater which require treatment.
2. High-rate physical and/or chemical treatment processes are well
suited to the abatement of pollution from CSO.
3. Multiple regression modelling of the F/S data indicated the following
general relationships: % ^ pf
Influent OR (gpd/sq ft)
SS (mq/1) 800 1500 2000
No Chemical Treatment
200 15.9 12.0 10.1
500 60.9 59.1 58.2
With Polymer Treatment
200 53.1 47.6 44.9
500 77.6 75.0 73.7
With Alum plus Polymer
200 78.2 75.4 74.0
500 89.3 87.9 87.2
Performance of the flocculation/sedimentation (F/S) pilot system was
significantly enhanced by incorporation of chemical treatment. Per-
centage removal of suspended solids (SS) in the F/S system was highly
dependent on influent SS concentration as well as overflow rate (OR).
Increasing OR from 33 to 82 m3/day nr (800 to 2000 gpd/ft2) in the F/S
system resulted in only marginal loss of performance.
4. Performance of the pilot swirl degritter generally supported the
data presented for the pilot swirl degritter evaluated at Denver.
Multiple regression analysis of the data from the 0.91-m (3-ft) dia
swirl degritter developed the following general trends
% Grit Removal
Influent Flowrate (gprn)
SS (mg/1) 15 40 Zp_
100
300
400
69.0
100.0
100.0
59.8
91.0
99.1
54.6
85.7
93.8
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% SS Removal
Flowrate (gpm)
15
56.5
66.6
70.4
40
32.5
48.1
54.1
70
13.3
33.3
41.0
5. After scaling of hydraulic flows and particle settling velocities to
prototype scale, the performance data obtained from the pilot swirl
primary separator unit generally supported the previously developed
design curves developed by APWA.
Multiple regression analysis of data from the 1.8-m (6-ft) dia swirl
primary separator indicated the following:
Influent
SS (mg/1)
100
300
500
6. The hydraulic loading to the FMC pilot microscreening system with
ultrasonic cleaning appeared to be limited to about 550 1/min m2
(13.5 gpm/ft2) when using 70 micron screens. However, the data
suggested that higher loadings might be attainable if screen rotation
was increased above 136 rpm. SS removals averaged within the range
of 1.5-43.5 percent when treating CSO.
7. Increasing hydraulic loading to the pilot dual -media high-rate
filters (DMHRF) above 407 1/min m2 (10 gpm/ft2) tended to improve
specific captures by dispersion of trapped solids deeper into the
bed. However, without chemical treatment, SS removals fell rapidly
at the higher loadings. When chemicals were employed on or upstream
of the filters, performance loss at the higher influx was not as
great.
Flux . Average % SS Removal Spec. Capture
(gpd/sq ft) Range Mean (Ibs/sq ft)
No chemical 10-15 56-83 67 1.34
Treatment 20-25 40-71 50 1.57
With chemical 10-15 66-92 78 1.31
Treatment 20-25 45-95 64 1.59
8. The application of carbon adsorption indicated optimum BODs removal
at detention times of 20 to 30 minutes.
Influent BODs Detention Time Flux BOD5 Removal
(mg/1 ) (min) (gpm/sg ft) (%)
30 13.5 0.42 69
30 19.3 0.61 76
30 30.0 0.94 83
30 45.0 1.41 79
70 13.5 0.42 92
70 19.3 0.61 91
70 30.0 0.94 96
70 45.0 1.41 88
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9. Multiple regression modeling of Cl2 and C102 disinfection data
yielded statistically significant performance equations for high-
rate disinfection.
10. High-rate disinfection employing relatively short detention time
and high-intensity mixing appeared to be a more cost effective
method than conventional disinfection for the treatment of CSO. These
procedures tend to increase operating costs while decreasing capital
costs. CSO treatment facilities remain idle for much of the year;
thus, operating cost is a smaller fraction of the overall cost for
wet-weather facilities than for dry-weather plant.
11. Disinfection by Cl2 was preferred to disinfection by C102 on a cost
performance basis when treating CSO with site factors specific to
Rochester, NY.
12. Cost/benefit comparisons of the F/S and swirl primary separator
systems indicated that the choice of treatment methodology for
CSO was dependent on the influent quality and the degree of treatment
required. In general, the swirl separator was cost competitive
with F/S. However, chemical treatments incorporated into a F/S
system permitted significantly enhanced removal efficiencies with
fairly minor increases in operating costs.
13. Review of the literature indicates that, in general, sludges from CSO
treatment should not be bled back to dry-weather treatment plants.
"Physical/chemical sludges at local overflow sites should be treated
at separate on-site facilities. After considering site-specific
factors at Rochester, the recommended sludge treatment included
lime stabilization, thickening, vacuum filtration and land disposal.
-------
SECTION 3
RECOMMENDATIONS
1. Future studies of flocculation/sedimentation of CSO should include
evaluations of 'OR's above 82 nr/day m2 (2000 gpd/ft2), especially when
alum and.polyelectrolyte are employed.
2. Pilot and prototype scale swirl units should be tested side-by-side to
verify and establish the scaleup procedures for the pilot scale units.
3. Prototype verification testing should be conducted for the swirl
degritter and swirl primary separator units.
4. Chemical treatment should be further evaluated in the swirl primary
separator unit to study the enhancement in performance.
5. Because of operating difficulties encountered with the FMC Microscreen
system, limited.data were collected. CSO treatment data from other
microscreen systems are available from references cited in the text.
Future testing should evaluate loadings above 550 1/min m2 (13.5
gpm/ft2) and other screen mesh sizes.
6. This study suggested that treatment efficiency of units upstream of
DMHRF had an impact on performance of the DMHRF. This impact should
be evaluated further along with additional studies with chemical treat-
ment.
7. It has been demonstrated that carbon adsorption provides significant
removals of dissolved organics from CSO. Because of the high costs
associated with carbon adsorption, its application should be limited
to locations where receiving water loadings of dissolved organics and
toxicants are critical.
8. The need for dechlorination of disinfected effluents resulting from
high-rate disinfection systems using high Cl£ dosages should be
evaluated.
9. The formation of chlorinated organics and other refractory residuals
in high-rate disinfection systems using high Cl£ and C102 dosages should
be evaluated.
10. It is recommended that sludges resulting from the treatment of CSO
generated from the Rochester system employ lime stabilization,
-------
thickening, vacuum filtration, and either incineration or land disposal.
11. A more cost effective process should be developed for on-site generation
of ClOz-
12. The utility of employing the swirl separator concept for sludge
concentration should be evaluated.
13. Additional process evaluations should be conducted to study the removal
of toxicants known to be constituents of CSO.
8
-------
GENERAL
SECTION 4
PILOT PLANT FACILITIES
The pilot plant facilities were installed at the Joseph-Ward
Chlorination Station (Figure 1), a facility which had been abandoned as a
chlorination station. It is located near the Central Avenue overflow site
(designated as overflow No. 25 for the Characterization and Monitoring
Program). The drainage area associated with this overflow comprises an area
of 171.3 ha (423 acres), 137 ha (340 acres) of which could be characterized
as commercial usage. The remainder of the area is associated mainly with
residential use.
Inner Loop Trunk
Oft Diameter)
Joseph
PUMPING
STATION
FIGURE 1. Pilot Plant and Pumping Station Locations
-------
Three types of treatment processes were investigated at the Rochester
pilot plant: (1) primary solids separation; (2) chemical precipitation
to achieve a greater degree of fine solids removal along with phosphorus
reduction below the 1 mg/1 level; and (3) final polishing and high-rate
disinfection to achieve a secondary quality effluent with respect to
BOD5 and bacterial contamination. The primary solids removal processes
tested and evaluated included high-rate sedimentation, microscreening,
high-rate filtration, and swirl concentrators. The phosphorus removal
processes tested and evaluated included chemical addition and flocculation
prior to the high-rate sedimentation process and chemical addition prior
to application on high-rate, dual-media filter beds. Polishing and high-
rate disinfection included carbon filters to study the effect of providing
the equivalent of secondary treatment to wet-weather discharges. The
disinfection process was directed towards applying conclusions of earlier
studies of chlorine and chlorine dioxide (42) and testing several mixing
concepts to evaluate methods for achieving bacterial reductions within
very short detention periods (five minutes or less).
Physical dimensions and design parameters of the pilot plant facilities
are listed in Table 1. Figures 2 and 3 show photographs of the pilot
plant facilities.
PUMPING STATION
The pumping station which provided the influent to the pilot plant
was located upstream of the Central Avenue overflow in a section of the
3.66 m (12 ft) tunnel. The pumping station location, although not at
the actual overflow site, collected runoff as part of the combined
sewage from more than 95 percent of the drainage area. Pumping of flow
to the pilot plant was accomplished through the use of two 10.2 cm (4
in) submersible high-head pumps. Each pump was capable of delivering
25.2 1/s (400 gpm) under a total head of 26 m (85 ft).
Immediately downstream of the pumps a 0.6 m (2 ft) weir was constructed
in order to maintain a minimum level of flow around the pumps. This
made it possible to operate the pumps under both dry and wet-weather
conditions. A removable gate was installed in the weir which permitted
the areas behind the weir and around the pumps to be cleaned periodically.
The pumps were controlled from the pilot plant by two alternative
modes of operation. The pumps could be started manually and independent
of flow conditions in the tunnel, or the pumps could be started inside
the tunnel. An ultrasonic head probe and continuous recorder were used to
monitor and record the amount of overflow produced with each storm
occurrence.
Conveyance of flow to the pilot plant was provided through the use
of a 15 cm (6 in) diameter pipe, approximately 457 m (1500 ft) long. A
bypass valve controlled the flow of CSO into the pilot plant. Gate
valves were used to control the flow into each of the treatment units.
Flow measurements were made.with magnetic flowmeters with direct reading
indicators installed in the vicinity of the gate valves to monitor
incoming flows.
10
-------
and C102 High Rate
Disinfection Tanks
Swirl Primary Separator (foreground)
and Swirl Degritter (background)
From left: Swirl Degritter, Swirl
Primary Separator and Microscreen
Unit
Storage Tanks (on ground)
FIGURE 2. Rochester Pilot Plant Facilities
11
-------
Influent and Effluent Pumps Associated with Dual Media Filter Columns
Flocculati on—Sedimentati on Basi n
Dual Media Filter Columns for High
Rate Filtration
Activated Carbon Columns
FIGURE 3. Rochester Pilot Plant Facilities
12
-------
TABLE 1. PILOT PLANT DESIGN PARAMETERS
A. Flocculation Basin
1.
2.
3.
4.
5.
6.
7.
dimensions
surface area
volume
flow rates
detention times
velocity gradient
mixing intensity (GT) 42000-104000
211 m x 0.9 m x 1,98 m deep (7 ft x 3 ft x 6.5 ft)
1.95 m2 (21.0 ft2)
3864 1 (1021 gal)
4.5-11.2 1/s (71-177 gpm)
5.1-10.1 min
120/sec
B. Sedimentation Basin
1. dimensions
2. surface area
3. volume
4. flow rates
5. overflow rates
6. detention times
C. Microscreen
1. dimensi ons
2. tank volume '
3. screen surface area
4. flux
5. flow rates
6. detention time
7. maximum rotation
8. screen aperture
D. Swirl Degritter
1. dimensions (overall)
2. D2/Di ratio
3. H1/D2 ratio
4. chamber volume
5. grit cone volume
6. surface area
7. tested flow range
8. operating Np
9. detention time
6.1 m x 2.1 m x 1.98 m deep (20 ft x 7 f t x 6,5 ft)
11.8 m2 (127.3 ft2)
21900 1 (5790 gal)
4.5-11.2 1/s (71-177 gpm)
32.6-81.6 m3/day m2 (800-2000 gpd/ft2)
33-81 min
1.5 m dia. x 2.3 m (5 ft dia. x 7.5 ft)
3452 1 (912 gal)
0.56 m2 (6.0 ft2)
610-1221 1/min m2 (15-30 gpm/ft2) at full screen
6-11 1/s (90-180 gpm) submergence
5.1 - 10.1 min
136 rpm
10 or 70 microns
0.9 m dia. * 1.2 m (3 ft dia. x 4 ft)
6.0
0.40
214 1 (56.5 gal)
61 1 (16.0 gal)
0.64 m2 (6.87 ft2)
0.95-4.4 1/s (15 - 70 gpm)
0,0018 - 0.0392
1.04 - 4.83 min
E. Swirl Primary Separator
1. dimensions (overall)
2. D2/Di ratio
3. Hi/02 ratio
4. chamber volume
5. sludge cone volume
1.8 m dia x 1.8 m (6 ft dia. x 6 ft)
18.0
0.27
1173 1 (310 gal)
1181 1 (312 gal)
13
continued)
-------
TABLE 1.(continued)
6.
7.
8.
9.
10.
1.
2.
3.
4.
5.
1.
2.
3.
4.
5.
6.
1.
2.
3.
4.
5.
6.
surface area
tested flow range
operating Np
detention time
equivalent OR
2.6 m2 (28 ft2)
0.95 - 4.4 1/s (15 - 70 gpm)
0.0137 - 0.298
8.9 - 4.5 min
31.6 - 146.2 m3/day m2 (771-3600 gpd/ft2)
Dual-Media High-Rate Filters
15 mm dia. x 5.5 m (0.5 ft x 18 ft)
0.02 m2 (0.196 ft2)
407 - 1018 1/min m2 (10-25 gpm/ft2)
7.6-18.9 1/min (2-5 gpm)
1.5 m (5 ft) of No. 2 anthracite
0.9 m ( 3 ft) of No. 1220 sand
dimensions
surface area
design flux
flow rates
media
Carbon Columns
dimensions 0.9 m dia. x 2.9 m (3 ft x 9.5 ft)
surface area 0.66 m2 (7.07 ft2)
operating flow range 0.19-0.63 1/s (3 - 10 gpm)
detention time 13.5-45 min
flux " 17.3 - 57.3 1/min m2 (0.42-141 gpm/ft2)
media 2.1 m (6.8 ft) of Filtrasorb 400
Disinfection Tanks
dimensions 0.61 m x 0.61 m (2 ft x 2 ft)
operating depths 15-37 mm (0.5 - 1.2 ft)
volume 57 - 136 1 (15 - 36 gal)
operating flow rates 0.13 - 0.63 1/s (2 - 10 gpm)
detention time 3.4 - 8.4 min
mixing intensities
.(GT) 41400 - 179000
FLOCCULATION/SEDIMENTATION SYSTEM
The dimensions of the pilot flocculation/sedimentation system,
shown in Figure 4, are listed in Table 1. The elevation of the overflow
weir was adjustable so that both overflow rate and flow-through velocity
could be varied. Overflow from the flocculation basin was directed by a
baffle to the bottom of the sedimentation basin.
Chemicals were added to the flocculation basin using positive dis-
placement pumps equipped with either 25 mm (1 in) or 12.7 mm (0.5 in) Viton
pump heads. Alum was introduced as far back in the influent line as possible
to ensure adequate mixing with the influent before coming into contact with
the polymer. The polymer was fed at the point of influent discharge to the
flocculation basin. Additional mixing in the flocculation basin was accom-
plished using a 2.67 kg-Cal/min (0.25 hp) mixer equipped with two 13 mm
14
-------
(5.2 in) and one 20 mm (7.7 in) propellers on a 1.52 m (5 ft) shaft.
EFFLUENT
/////////////////////////////S////////S//SSS////S/////////////
BAFFLE
DRAIN
SKIMMER
SEDIMENTATION
BA3N
--,
12
Jl-
vo^/y/iov'>wv5w'
EFFLUENT
CHAMBER
— /
F-IGURE 4. Flocculation/ Sedimentation Tank (Pilot Unit)
The major portion ot the flocculation/sedimentation effluent was
returned to the main sewer system. A portion of this effluent was
capable of being directed into the carbon columns, the dual-media filters
and disinfection bays. Grab samples were taken from 12.7 mm (0.5 in)
taps located on the influent and effluent lines.
SWIRL CONCENTRATORS
The pilot facilities included a swirl degritter and a swirl primary
separator connected in series. Dimensions of the swirl degritter, shown
on Figure 5, are listed in Table 1. During normal operations the overflow
from the swirl degritter (Figure 5) became the influent for the swirl
primary separator (Figure 6). Provisions were also made, however, to
allow the plant influent to bypass the swirl degritter and go directly
into the swirl primary separator.
Both the inlet and outlet pipe diameters associated with the swirl
degritter were 15.2 cm (6 in); each was fitted with 12.7 mm (0.5 in)
sample taps. Installation of a 10.2 cm (4 in) gate valve on the swirl
degritter solids drawoff line permitted the intermittent discharge of
any solids which accumulated in the unit.
The dimensions of the swirl primary separator, shown in Figure 6,
are listed in*Table 1. The inlet pipe diameter, DI, was 10.2 cm (4 in)
and the outlet diameter was 7.6 cm (3 in). Sample taps were located on
15
-------
poilers
1/4"
WEIR
RING
* INLET
-2'-6"
ELEVATION
FIGURE 5. Swirl Degritter (Pilot Unit)
both the influent and effluent lines.
Two methods of sludge drawoff were provided for the swirl primary
separator unit: intermittent and continuous. Installation of a 12.7 mm
(0.5 in) ball valve on the solids drain line permitted accumulated
sludge to be withdrawn intermittently. Continuous drawoff was achieved
through a 2.54 cm (1 in) line using the head differential between the swirl
unit and the outlet.
Chemical treatments to the swirl primary unit were added using positive
displacement pumps. Alum was introduced to the swirl degritter effluent
immediately as it exited the overflow weir. Anionic polymer was introduced
approximately 1.8 m (6 ft) downstream from the point of alum addition and
2.4 m (8 ft) upstream of the swirl primary unit. A second mode of chemical
addition was tested during Storm No. 19. It was attempted to gain enhanced
mixing and contact time by adding alum upstream of the swirl degritter—
16
-------
r-io 1/2"
4-41/2
BOTTOM
OFOUTER
TROUGH
PLATE
ELEVATION ;
FIGURE 6. Swirl Primary Separator (Pilot Unit)
D2=6'-0"
PLAN
TROUGH
WITH
- WEIR
PLATES
-------
converting the degritter to a flocculation basin by installing a mixer.
MICROSCREENING SYSTEM
The microscreening system* used at the pilot plant employed a sonic
cleaning mechanism. Figure 7 shows an elevation view of the microscreen
and the sonic cleaner. Used in conjunction with the rotating strainer drum,
the sonic cleaner provided continuous cleaning of the screen area of 1.83
m2 (6 ft2) with a peak hydraulic loading rate of 1221 1/min m2 (30 gpm/ft2).
This represented a maximum flow rate of approximately 11.4 1/s (180 gpm).
Determination of the headloss across the screens was accomplished
through the use of two manometers attached to the outside of the unit.
Both influent and effluent lines were 10.2 cm (4 in) in diameter.
Effluent from the unit could be directed back into the main sewer system or
into any of the four storage tanks. To prevent the accumulation of solids
in the unit during operation, a 25 mm (1 in) flexible hose and ball valve
were connected to the solids concentrate drain line. This permitted the
drawoff of solids on an intermittent basis in lieu of continuous drawoff.
STORAGE TANKS
The effluents from both the microscreen system and .the swirl
separators were capable of being stored in quantities of 37.9 m3 (10,000
gal ) each. Four steel tanks, each having a capacity of 18.95 m3 (5000
gal), were used to provide this storage. This storage permitted, the
operation of the secondary treatment units for four to five days follow-
ing the wet-weather event. Figure 8 shows dimensions of the storage
tanks used at the plant facilities.
Mixing of the stored CSO in each tank was provided with a 10.68 kg-
cal/min (1 hp) mixer to keep the solids in suspension and maintain the
D.O. levels above 2 mg/1.
DUAL-MEDIA HIGH-RATE FILTERS
Pilot filter studies were conducted using one PVC and two plexiglass
columns. These filter columns were operated in parallel. Each column
was 15 cm (6 in) in diameter and 5.5 m (18 ft) in depth. Filter media
consisted of 1.5 m (5 ft) of No. 2 anthracite over 0.9 m (3 ft) of No.
1220 sand. Influent to the filter was from the storage tanks containing
the effluent from either the microscreen or the swirl separator systems
and was delivered through 25 mm (1 in) diameter pipes using 16.02 kg-
cal/min (1.5 hp) centrifugal pumps. Similar pumps were employed in
transferring the filter effluent to subsequent pilot operations. Flow
measurements for both the influent and effluent were obtained using 19
mm (0.75 in) rotameters having a range of 0.13 to 0.63 1/s (2 to 10
gpm). Installation of a float-valve mechanism on the filter discharge
facilitated the operation of the filter units. Figure 9 shows dimensions
of the filter columns.
* supplied by FMC Corporation
18
-------
EFFLUENT
(TREATED)
~T (SOLIDS
' CONCENTRATE)
FIGURE 7. The FMC Sonic Cleaner Microscreen (Pilot Unit)
19
-------
"ill Mixer
2'-0"
PLAN
Inlet - 4" Dia.
Outlet - 2" Dia.
1 Overflow - 4" Dia
1
I Manway
4=
i
Jo
Drain -4" Dia.
=\
]
7
_,
10'-0"
7<-5"
ELEVATION
FIGURE 8. Storage Tank
Samples were taken at the influent and effluent ends of the filters
and at depths of 0.6 and 1.5 m (2 and 5 ft) below the surface of the
filter beds. Headless measurements across the filters were obtained at
depths of 0, 0.6, 1.5, and 2.4m (0, 2, 5, and 8 ft) below the surface
of the filter beds. Upflow backwash of the filters was accomplished by
feeding tap water to the bottom of each column. Air scouring was also
provided.
Chemical addition to the filter influent was accomplished by utilizing
positive displacement pumps. Alum was introduced upstream of the filter
feed pumps. Polymer was introduced immediately downstream of the feed pumps.
CARBON ADSORPTION
Three carbon columns were installed at the pilot plant site'. Figure
10 shows dimensions of these facilities. The units were sized to accept a
portion of the effluent from the flocculation/sedimentation system or the
total flow from the dual media filters. The three columns could be
arranged in either parallel or series to allow flexibility in testing.
Piping following the columns was arranged to allow the effluent to be
directed into any of the disinfection bays.
The units were filled with 2.1 m (6.8 ft) of Calgon Filtrasorb 400
granular carbon. This media has an effective size of 0.55 - 0.65 mm, a
uniformity coefficient of 1.9 or less, and a bulk density of 400 kg/m3
C25 lb/ft3). Backwash facilities were provided by connecting a water line
.to the bottom of each of the columns.
20
-------
"1
u
BA
r~jT
BACKWASH
3'
^=f] r, M INFLUENT
-»•
c=
"2
ANTHRACITE
CKWASH {
1^
L
6in.
Wi>^'
|QQ\/0&<»
\ PRESSURE GAUGES
/(typical)
-O
x !
y SAMPLE TAPS
9 4 -
)
SAND -
-r-x^^X
^g n ^
— fcfi
> FLOAT VALVE
9'
i
<
t
i
Eight -1 l/'
Holes on
(outlet)
-6"
r '
12"
.6"
/^
R
-
~^
3-*— 2" Connection for Intet & 'Backwash
-O
Ir-e"
(typical)
p, -
-ou^- Pressure Gage (typical)
-O
-. > — 2" Connection -for Carbon
jf Removal
• • — 'Steel Plate
J-l
^ — 2" Connection -for Outlet 8' Backwash
/ rf 'Q^^n\ " Four - 1 1/4" Holes on
/ / -Qf&cC 4"R
^ ^ X>-° / 1 Note: Each 1 1/4" Hole Equipped
V V_ o' / With a 304 S.S.
\^^ _^^ Microwedge- Strainer
PLAN
VIEW
STEEL PLATE
FIGURE 9. Dual-Media High-Rate Filter
(Pilot Unit)
FIGURE 10. Activated Carbon Column
(Pilot Unit)
-------
DISINFECTION SYSTEM
Three parallel, high-rate pilot tanks were provided to study dis-
infection optimization by mixing methods. The mixing techniques included
parallel corrugated baffling, sequential flash mixing and single flash
mixing at the point of application. These are outlined along with the
tank dimensions in Figure 11. Provisions were made to allow each mixing
technique to be evaluated in each of the three bays. Flash mixing was
furnished by 2.53 kg-cal/min (0.05 hp) mixers equipped with 0.46 m (18
in) shafts and 5 cm (2 in) diameter props. Each mixer delivered a water
hp of approximately 0.02. G values were calculated for three components:
walls, baffles, and mixers (58). The system 6 value was defined as
SGT/ET using the zone of influence for each component. A number of
different weir heights were made available for the purpose of evaluating
different detention times.
EFFLUENT
44.5"
INFLUENTf Tr.
I 1 l\*l-
FIGURE 11. Pilot Disinfection Tank and Mixing Concepts Plan View
The disinfectants used were chlorine and chlorine dioxide. Chlorine
was supplied in cylinders and chlorinators were used to disperse the
chlorine in water prior to dosing. The portion of the chlorine solution
applied to the bays was measured manually and samples were withdrawn
hourly for determination of solution strength by lodometric back titration
methods (77).
Chlorine dioxide was initially prepared through two chlorine dioxide
generators (supplied by Chemical Generators, Inc.). Laboratory testing
22
-------
of chlorine dioxide revealed that low concentrations of the solution
would remain relatively stable for a period of 3-4 days if kept in a
closed container. This made it possible to manually prepare sufficient
quantities of the solution in advance of any disinfection testing. The
chlorine dioxide was fed into the bays using pumps having a capacity of
17 ml/min (0.004 gpm). Application rates were measured volumetrically.
Strength of the chlorine dioxide solution was determined using Starch-
Iodide (77) or DPD titration techniques (50).
23
-------
SECTION 5
PROJECT PLAN
PROGRAM DEVELOPMENT AND APPLICATION OF RESULTS
The Rochester CSO study program included overflow sampling and monitor-
ing, sewer network modeling, and pilot plant testing of the CSO treatment
alternatives. The pilot plant studies were designed to interface with the
mathematical modeling for evaluation of abatement alternatives.
The system modeling generally employed the EPA-developed Stormwater
Management Model (SWMM). One of the components of this model is a Storage-
Treatment block which provides estimates of treatment efficiency for time-
variable storm flows for specified process train selections and design
conditions.
The test programs and development of performance equations were
directed toward evaluating the effects of varying hydraulic loadings and
influent quality on the performance of the treatment systems. The effects
of chemical treatments are also included, where applicable. The performance
models, coupled with cost developments were used to compile cost/benefit
comparisons and design optimizations of some of the alternatives. Oppor-
tunities for such optimizations generally arise because of the relative
infrequent use of the wet-weather treatment facilities. These optimizations
may indicate the possibilities of achieving greater economies by employing
procedures that may increase the operating cost (e.g. high chemical doses
or high energy mixing) by permitting great reductions in sizing of facili-
ties and the capital costs. The operating costs for wet-weather facilities
represent a much lower fraction of total yearly costs than the cost for
dry-weather plants. These optimizations are highly dependent on site-
specific factors such as number of overflows and the total quantity of
overflows to be treated per year.
The cost and performance relationships were also used to evaluate a
number of area-wide alternatives. These alternatives are presented in Volume
I of this report (3). The alternatives included: a) optimizations of
storage versus treatment sizing, b) use of local satellite treatment
plants versus centralized treatment, c) alternative locations of centralized
treatment, and d) use of satellite treatment for first-flush overflows
only,with collection of remaining flows.
SCOPE OF WORK
Pilot operations covered nineteen overflow events during the period
of September 1975 through June 1976. Storm characteristics associated
24
-------
with these storms are listed in Table 2. The piloted processes included
flocculation/sedimentation, swirl degritter and swirl primary separator
microscreening', dual-media high-rate filtration, activated carbon adsorp-
tion and high-rate disinfection. Hhile these include some of the major
processes generally considered for CSO treatment, there are other alterna-
tives that were not piloted. For example, dissolved air flotation,
biological lagoons, and rotating biological discs have been studied by
others for application to CSO treatment. It was also not intended to
comprehensively evaluate all design parameters associated with each
system. The sampling and operation schedules were established to permit
evaluations of variable influent quality and the effects of the selected
operating conditions. Analyses included evaluations of BODs, SS, VSS,
total solids, volatile solids, setteable solids, COD, TOC, total inorganic
phosphorus, TKN, oil and grease, temperature, metals, and fecal coliforms.
All analyses were conducted in accordance with Standard Methods (77)
and/or Methods for Chemical Analysis of Hater and Hastes (78).
In addition to the pilot plant process operations, a number of support
studies were included throughout the program. These included dry weather
testing of the unit processes, determination of reaction rates in the C102
generator, determinations of alum and polyelectrolyte dosage requirements,
sludge thickening and dewaterability testing, particle size distributions
and specific gravities, and analyses of heavy metals content of influents,
treated effluents,and sludges.
25
-------
TABLE 2. STORM CHARACTERISTICS
Storm
Ho.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
Rainfall
Start
Date Time
09/25/75
10/09/75
10/17/75
11/10/75
11/21/75
12/06/75
12/09/75
12/09/75
01/26/76
02/18/76
02/18/76
02/21/76
03/03/76
03/12/76
03/19/76
03/31/76
04/21/76
05/11/76
05/19/76
06/21/76
1600
1345
1815
0630
1255
0400
0715
1130
2100
0400
0200
2030
1230
0315
1400
1140
1620
1130
1145
1830
Rainfall Total
Duration Rainfall
(hrs.) (inches)
6.0
6.6
7.2
4.0 0.22
0.7 0.30
5.8 0.50
2.5 0.60
2.3 0.25
9.0
8.5
7.0
2.25 0.15
4.5
6.25 0.45
2.25 0.30
3.2 0.60
2.6 0.50
4.5 0.25
13.5 1.51
2.0
Pilot
Plant
Startup
Time
1840
1810
2100
0830
1310
0815
0830
1255
2255
0930
0730
2115
1315
0530
1500
0920
1215
1615
1335
1250
1900
Overflow
Duration
(hrs.)
5.25
2.7
6.75
3.0
1.6
3.7
2.25
1.1
7.5
14.0
5.0
2.4
2.0
11.75
2.0
7.7
3.9
2.7
3.5
14.5
1.8
Peak
Overflow
Rate
(MGD)
7.0
12.1
7.0
10.6
5.7
6.8
30.0
30.0
30.0
10.0
10.0
50.0
50.0'
12.0
30.0
26
-------
SECTION 6
FLOCCULATION/SEDIMENTATION
BACKGROUND
Primary sedimentation of raw municipal wastewater has been applied
conventionally at overflow rates (OR) of 24 to 41 m3/day m2 (600 to 1000
gpd/ft^). Typically, suspended solids removal rates of 30 to bO percent
are attained in this process.
The OR is the single most important design criteria for sizing of
sedimentation basins (6, 7, 8). Theoretically, depth and detention time
have minor influence on determining removal efficiencies for discrete
particles. However, for flocculent particles, detention time plays a
more important role since settling velocity increases with time of
particle agglomeration. In practice, minimum depths and detention times
are employed based on experience.
OR is an expression of the upflow hydraulic velocity created in the
basin. Particles with settling velocities greater than the upflow
velocity will be removed. In combined sewer overflows the particle size
distribution is considerably coarser than in typical dry weather flow,
since the high scour velocities created in the sewer suspend larger
particles. It would be expected, then, thatOR's applicable to treatment
of CSO might be considerably higher than those applied to dry-weather flow.
The effects of OR on SS removals from municipal wastewater have been
evaluated by several investigators. The ASCE Manual of Engineering
Practice Number 36 (71) includes a design curve for selecting OR for a
desired removal efficiency. This is shown on Figure 18. Smith (72)
presented a similar evaluation from analysis of field data and developed
the performance function:
SS Removal Efficiency (%) = 82 e"(OR/2780)
This equation shown on Figure 18 closely approximates the ASCE curve. Both
relationships above were basically •developed for municipal dry-weather flows.
An analysis of operating data for primary facilities at Los Angeles
(9) evaluated OR's as high as 163 m3/day m? (4000 gpd/ft2). These results
indicated that major losses in performance were not experienced until OR
was increased beyond about 82 rip/day m2 (2000 gpd/ft2) (see Figure 18). One
of the major reasons why such high OR's were attainable might have been
the relatively high influent SS concentration (average 500 to 600 mg/1) in
the raw wastewater. This might indicate a relatively coarse solids size
27
-------
distribution. This study also indicated that performance was not in-
fluenced by flow-through velocities, v, less than 1.2 m/min (4 fpm), but
sludge resuspension became significant at levels above 1.2 m/min (4 fpm).
Camp (7) has stated that velocities up to 5.5 m/min (18 fpm) may not cause
resuspension, however, designs should incorporate velocities substantially
under 5.5 m/min (18 fpm). Other tests at Los Angeles (10) showed that
velocities above 1.8 m/min (6 fpm) did not hinder removals when alum and
polyelectrolyte were employed. The selected velocity influences the con-
figuration of the basin, high velocities being associated with shallow and
narrow basins. Below the scour velocity, high velocities tend to enhance
velocity gradient flocculation (11).
Data from full-scale primary facilities treating sanitary and wet-
weather combined sewage at Toronto, Canada,- has also been published (12).
These data, covering a range of influent SS from 287 to 627 mg/1, show
significant removals at OR's up to 82 m3/day m2 (2000 gpd/ft2). Removals
are shown to be related to influent SS concentration, indicating the
impact of the coarser particle size distribution associated with the
higher SS levels.
OUTLINE OF EXPERIMENTS
A high-rate sedimentation system has been designed for treatment of
wet-weather flows from the Rochester Pure Waters District (13). The
facility is proposed to consist of four units with a total capacity
of 1041 m3/day (275 mgd). Dimensions of each unit are 117 m (384 ft)
x 32.5 m (106.5 ft) x 4.7 m (15.5 ft) deep. Design parameters included
maximum OR of 81.6 m3/day m2 (2000 gpd/ft2), detention time of 75 min
and flow-through velocity of 1.22 m/min (4.0 ft/min).
The primary sedimentation basin at the pilot plant was intended to
evaluate the chemicals necessary to achieve phosphorous removal through
the flocculation/sedimentation process. However, due to the detergent
ban in New York State, the levels of phosphorous observed in Rochester
CSO have generally been less than 1 mg/1 as P even under peak conditions.
These low levels of phosphorous preclude the need for phosphorous removal
as applied to the Rochester CSO.
Alum treatment is incapable of producing phosphorous levels
significantly below those observed. Therefore, chemical treatment (alum
and/or polymers) was evaluated mainly from the standpoint of enhancement
of suspended solids removal. However, a limited amount of testing was
included whereby the influent was spiked with phosphate and the alum
dosage adjusted for phosphorous removal.
The matrix of tests employed in the program is outlined in Table 3.
The pilot plant tests included evaluations of the effect of OR under
four chemical treatment programs. The chemical treatments included: no
chemical addition, polyelectrolyte only, alum + polyelectrolyte, and
phosphorous spiking accompanied by higher alum and polyeletrolyte doses.
Selection of the chemical treatments is discussed in subsequent pages.
28
-------
TABLE 3. FLOCCULATION/SEDIMENTATION SYSTEM TEST MATRIX
Storm No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
Pilot
Flowrate
(gpm)
71
71
133
124
165
165
177
162
71
133
177
71
133
177
177
71
133
177
71
177
OR d.t.
(gpd/ft2) (min.)
800
800
1500
1407
1870
1870
2000
1830
800
1500
2000
800
1500
2000
2000
800
1500
2000
800
2000
38.8
38.8
15.7
16.7
15.2
15.2
14.2
15.6
78.0
42.0
31.0
78.0
42.0
31.0
31.0
78.0
42.0
31.0
78.0
31.0
v P-Spike
(fpm) (mg/1)
0.
0.
2.
2.
2.
2.
2.
2.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
8
8
3
3
2
2
2
0
24
45
59
24
45
59
59
24
45
59
24 2.13
59 0.85
Alum Polymer
(mg/1) (mg/1)
1
1
1
40 1
40 1
40 1
105 1
105 1
.0
.0
.0
.0
.0
.0
.0
.0
The matrix of tests also included evaluations of OR's of 33, 61 and
82 m3/day m2 (800, 1500 and 2000 gpd/ft2). OR was held constant throughout
the duration of each storm to study the system efficiency under variable
influent solids concentrations. It was considered necessary to evaluate
the performance relative to CSO quality, since some of the area-wide
abatement alternatives considered the use of facilities for treatment of
the first-flush storm component only.
Sludge withdrawal was not employed with any of the tests. Calculations
indicated that sludge accumulation for an average storm of 4 hours duration
would result in an accumulation of less than two inches of sludge. The
sludge layer was sampled at the termination of each test.
Weir overflow rates (WOR) of 84, 63 and 33 m3/day m? (6800, 5100 and
2700 gpd/ft) of weir were employed at OR's of 33, 61 and 82 m3/day m2
(800, 1500 and 200 gpd/ft2) respectively, which were low enough to prevent
exit losses of suspended particles.
The 2.67 kg-cal/min (0.25 hp) agitator employed in the flocculation
basin imparted a velocity gradient (6) of approximately 120 sec'1. This
resulted in mixing intensities (GT) of 42,000 to 104,000, values typically
associated with flocculation systems.
29
-------
CHEMICAL TREATMENT REQUIREMENTS
In order to select the types and dosages of chemicals to be employed
in the pilot tests, a number of laboratory jar tests were conducted using
Rochester CSO. A range of polyelectrolyte types were tested in conjunction
with an alum dosage of 50 mg/1. Figure 12 indicates the comparison of the
performance of several polyacrylamides based on the charged functional
groups. These data indicate increasing performance with increasing anionic
content of the polyelectrolyte. A highly anionic polyacrylamide (Nalcolyte
676) was selected for use in all testing at the pilot facilities.
^
_J
tio.
H 8 -
Q
m
o: 6 .
D
t 4
^J
D
5 2 -
UJ
o:
J
0/'1
rAlum alone - no polymer
\AII tests w/50 mg/l alum
+ 1 mg/l polymer
•x
•—^^
1 1
LOW
LOW MODERATE
HIGH
CAT IONIC
ANIONIC
FIGURE 12. Comparison of Polyelectrolyte Types
The same trend was verified when the data of Mebolsine, et al. (14)
were evaluated. That report presented the results of filtration of CSO
when employing a variety of polyelectrolytes from many suppliers. When
compared on the basis of charged functional groups it was again noted
that flocculation of CSO responded best to highly anionic polyelectrolytes.
The effect of polyelectrolyte dosage is indicated on Figure 13. A
typical dosage of 1.0 mg/l was anticipated to provide optional flocculation,
and was verified by this test.
30
-------
t 8 .
Q
m
CK 6 J
§2
UJ
ct;
Alum alone - no polymer
All tests w/50 mg/l alum
0.05
—r—
O.I
LO
ANIONIC POLYMER DOSE (mg/l)
FIGURE 13. Selection of Polyelectrolyte Dosage
Alum dosage requirements were established by testing samples of CSO
taken during several intervals throughout a storm. Figure 14 shows test
results when several alum doses were tested on each CSO sample. It is
noted that for all portions of the storm, optimal results were attained
with an alum dosage of approximately-40 mg/l.
SUSPENDED SOLIDS REMOVAL
Appendix B presents the results of the SS analysis of influent and
effluent data for the flocculation/sedimentation basin. These plots
indicate results as the samples were taken, and are not adjusted for
the detention time in the unit. From these curves, influent data were
lagged by the theoretical detention time in the treatment unit and SS
removal rates were calculated for each 20 minute increment. Multiple
regression analysis was then conducted between the SS removal rates,
surface overflow rate,and the concentration of influent suspended solids
for three chemical treatment conditions. A statistical fit to the pilot
plant data was obtained in the form of the following equation:
Log (ce/c0) = KI + K2 log Q + K3 log c0
31
-------
where
= fraction of SS remaining
Q = flow through the flocculation/sedimentation basin (gpm)
c0 = influent suspended solids concentration in the unit (mg/1)
K1»K2'K3 = regression coefficients representing different chemical
treatments
0 pH 6.75
3OJ
20-
>-
t
o
ID
§10.
<
g
in
UJ
o:
O O 0/F - 0830
a n 0/F -0900
A 0/F - 0930
Raw Suspended Solids = 148 mg./1.
" " " =!28mg./l.
" =!20mg./l.
" " " = 44mg./l.
All tests w/ I mg/1 anlonic polymer (Magnlfloc 835A)
pH6.7
pH 6.7
10 20 30 40 50 60 70
ALUM DOSAGE (mg/1)
80
9O
100
FIGURE 14. Variation in Alum Demand
Results of the regression analyses are indicated in Tables 4, 5, and
6. In all three cases the regression coefficients indicated the following
trends: (a) percent removal of SS decreases as the hydraulic loading to the
system increases and (b) percent removal of SS increases as the influent
SS concentration increases. The magnitude of the regression coefficients
associated with hydraulic loadings in all cases indicate a fairly minor
effect of applied flowrate within the test range on SS removals; 'T' values
(measure of the statistical significance of the regression coefficients)
associated with the flowrate data indicate degrees of confidence of > -99,
75 and 55 percent, respectively, for treatments of no chemicals, polymer
only and alum plus polymer. The influent concentration of SS has a major
effect on the percentage removal of SS; 'T1 values associated with the
influent SS data in all cases represent degrees of confidence greater than
99 percent.
The performance equations were derived from the regression analysis by
providing the conversion OR = Q x 11.3.
32
-------
For no chemical treatment:
log (ce/c0) =1.71 + 0.072 log Q - 0.836 log c0
ce/c0 - 43.4 (OR)0'072 (cor°-836
For treatment with anionic polymer:
log (ce/c0) = 1.20 + 0.175 log Q - 0.806 log c0
,. ir. in o ,ADN0.175 ir- \-0.806
ce/c0 = 10.3 (OR) (c0)
For treatment with alum plus anionic polymer:
log (CG/CQ) = 0.765 + 0.193 log Q - 0.775 log c0
O CQ fnD\°-193 Ir. \~0.775
= 3.63 (OR) (c0)
where ce = effluent SS concentration (mg/1), c0 = influent SS concentration
(mg/l)» Q = applied pilot plant flowrate (gpm) and OR = overflow rate
(gpd/ft2).
TABLE 4. MULTIPLE REGRESSION ANALYSIS OF FLOCCULATION/SEDIMENTATION DATA:
NO CHEMICAL TREATMENT
Standard Correlation -Regression Std. Error Computed
Variable Mean Deviation X vs Y Coefficient of Reg. Coef. j Value
Log Q 1.07 1.054 -0.131 0.072
Logcn 2.45 0.225 -0.855 -0.836
Dependent
Log (ce/c0) -0.260 0.173
0.010 7.08
0.048 -17.4
Intercept 1.71
Multiple Correlation 0.934
Std. Error of Estimate 0.063
Analysis of Variance for the Regression
Analysis of Variance for the Regression
Source of Variation
Attributable to Regression
Deviation from Regression
Total
Degrees
of Freedom
2
45
47
Sum of
Squares
1.23
0.179
1.41
Mean
Squares
0.618
0.0039
F Value
154.8
33
-------
TABLE 5. MULTIPLE REGRESSION ANALYSIS OF FLOCCULATION/SEDIMENTATION DATA:
TREATMENT WITH ANIONIC POLYMER
Standard Correlation
Variable Mean Deviation X vs Y
Log Q 2.16 0.118 0.496
Log co 2.42 0.220 -0.908
Regression Std. Error Computed
Coefficient of Reg. Coef. T Value
0.175 0.146
-0.908 0.078
1.19
-10.2
Dependent
Log (ce/co) -0.373 0.206
Intercept 1.20
Multiple Correlation 0.912
Std. Error of Estimate 0.086
Analysis of Variance for the Regression
Degrees
Source of Variation of Freedom
Attributable to Regression 3
Deviation from Regression 30
Total 32
Sum of Mean
Squares Squares
1.13 0.566
0.226 0.0075
1.36
F Value
74.9
TABLE • 6. MULTIPLE REGRESSION ANALYSIS OF FLOCCULATION/SEDIMENTATION DATA:
TREATMENT WITH ALUM AND ANIONIC POLYMER
Variable Mean
Standard Correlation Regression Std. Error Computed
Deviation X vs Y Coefficient of Reg. Coef. T Value
Log Q 2.00
Log co 2.443
Dependent
Log (ce/c0) -0.741
0.172
0.253
0.298
0.197
-0.675
0.193
-0.775
0.244
0.166
0.792
-4.667
Intercept 0.765
Multiple Correlation 0.684
Std. Error of Estimate 0.225
Analysis of Variance for the Regression
Source of Variation
Attributable to Regression
Deviation from Regression
Total
Degrees
of Freedom
2
27
29
Sum of
Squares
1.20
1.37
2.57
Mean
Squares
0.603
0.050
F Value
11.8
34
-------
, The regression equations are plotted on Figures 15, 16 and 17. Also
plotted on these Figures are the experimental results for the test series
at hydraulic loadings of 33, 61 and 82 m^/day m2 (800, 1500 and 2000
gpd/ft2). It is noted that the chemical treatments result in significantly
enhanced SS removals at all influent SS concentrations. It is also noted
that only minor performance losses are incurred by raising the overflow
rates from 33 to 82 m3/day m2 (800 to 2000 gpd/ft2). This indicates that
overflow rates greater than 82 m3/day m2 (2000 gpd/ft2) should be evaluated,
especially with the chemical treatments. It should be emphasized that
the performance equations apply to only OR's up to 82 m3/day m2 (2000
gpd/ft2) and influent SS concentration up to 800 mg/1. Results outside
of these ranges should not be extrapolated.
100 •
90 •
80
70 •
_ 60
I 5O •
Or
« 40
3«
30-•
ZO-
10
A Data - No Chemical Treatment
• Data-Alum & Anionic Polymer
Regression Model -no chemical treatment
Regression Model-anionic polymer
Regression Model-alum ft anionic polymer
100
200
300 400
Influent SS ( mg/l)
500
600
FIGURE 15. Performance of Flocculation-Sedimentation System @ 800 gpd/ft2
SCALEUP CONSIDERATIONS
Camp (7, 47) has presented a comprehensive consideration of factors
involved in scaleup of the design of sedimentation systems. While overflow
rate is the most important design parameter, a number of other design
factors affect performance, particularly when dealing with flocculent
suspensions. For example, flocculation is affected by detention time,
differences in particle settling velocities,and velocity gradients in
the liquid. Turbulence due to density currents or high velocities can
retard settling or result in scour from the bottom. Entrance and exit
designs also affect performance. Camp (7) has demonstrated that the de-
gree of short-circuiting in a basin is a function of the Froude'number
of the horizontal flow. Thus there may be some rationale for the appli-
cation of Froude Law scaling relationships. However, neither scaleup by
35
-------
IOO
90
80-
70
o 60-
'r~~~
/• A /^^
/ • .s'
• ^ >x^
/ A. S
' /
/ / A Dato - No Chemical Treatment
/ / • Dato -Anionic Polymer
' / • Data -Alum and Anionic Polymer
/ / Regression Model - no chemical treatment
/ / Regression Model -anionic polymer
•/ • / Regression Model -olum 6 anianic polymer
/ /
t /
1 '
||| | J
100 ?00 300 400 500 600
Influent SS (mg/l)
FIGURE 16. Performance of Flocculation/Sedimentation System @ 1500 gpd/ft2
I00-|
90
80
7O
60
1
1 50-
(/>
c/>
- 40-
>*
30
2O
10
_-^
-^— " — *
«. ^- * •
• --"^ * • --- —
• / ,^"'
/' • -""
•/ . ••,'''• ^^A
/ • X' " ^?L
/ /*
*/
/ ^r
t •• A / AA
• L. "" x ^^
_ /• / A Data - No Chemical Treatment
/ A / • Data -Anianic Polymer
f/ A / • Data -Alum ond Anionic Polymer
/ / Regression Model -no chemical treatment
/ / Regression Model -anionic polymer
/ / Regression Model -olum & anionic polymer
/ /
° KX> 200 300 400 500 600
Influent SS (mg/l)
FIGURE 17. Performance of Flocculation/Sedimentation System @ 2000 gpd/ft2
36
-------
overflow rate nor Froude Law take into account the effect of detention time
on flocculation.
Figure 18 presents a comparison of loading-performance relationships
derived from several sources. Some commonly accepted relationships for
domestic sewage are illustrated for comparison. Results of treatment of
CSO at the Humber plant in Toronto (12) are shown (six primary tanks 34 ft
x 327 ft x 10 ft deep). Results were presented for several OR's and for
different storm intervals. The influent SS concentrations covered a range
from 287 to 627 mg/1. Removals predicted by regression analysis of the
Rochester data are presented for the same range of influent SS concentra-
tion. All data apply to treatment without chemicals. At the higher
loading rates, performance results in Toronto and Rochester were similar,
while treatment at the lower loading rates were slightly better for
Toronto CSO.
Also indicated on Figure 18 are removals predicted from Rochester CSO
particle size analyses (see Section 6). Actual SS removals are in agree-
ment with the removals expected from the calculated particle settling
velocities.
too
80-.
60
o
0>
o:
40--
20--
Rochester CSO Regression fco=287-627 mo/I)
I
Toronto CSO (co= 287-627mo/l)
NOTE! Performance functions of ref.
9,67,71 S 72 are for domestic
Hyperion (ref.9) sewage.
Imhoff a Fair (ref.67)
Predicted from
Particle Size Distribution.
Rochester CSO fc = 334 ma/I)
ASCE(ref.7l)\
Smith (ref.72) \
\
\
\
1000 2000 3000 4000
Overflow Rate (gpd/ft2)
5000
FIGURE 18. Loading-Performance Relationships: Flocculation/Sedimentation
System
37
-------
REMOVAL OF OTHER CONSTITUENTS
Removals of other parameters were evaluated on a storm-average basis.
Listings of minimum, maximum, arithmetic means, geometric means and
standard deviations of influent and effluent data are included in Appendix
B. Table 7 represents the geometric mean or median data for each storm
and parameter tested in Rochester, M.Y.
VSS removals were generally higher than the corresponding SS removals.
Average VSS removals were 37 percent without chemical treatment, 47 percent
with the addition of polymers and 79 percent with alum and polymers. Set-
tleable solids removals were 52, 58 and 94 percent for no chemical treatment,
polymer addition, and alum + polymer treatment, respectively.
removals also showed an increase with chemical addition. Median
removals were 21 percent for no chemical treatment, 37 percent with polymer
addition, and 61 percent for alum + polymer treatment. Average TOC removals
were 11 , 29 and 47 percent for the above three chemical treatments respec-
tively. Oil and grease removals were 27 percent without chemicals and 35
percent with the addition of alum plus polymer. The effluent pH values
ranged from 5.9 to 7.8 without alum, and 5.4 to 7.5 when alum was used.
No appreciable TKN removals were observed in the F/S system under each
of the three treatment conditions. TIP removals average 8 percent with no
chemical treatment, 11 percent with polymer addition, 71 percent with
alum (40 mg/1) and polymer, and 71 percent when phosphorous was spiked
(1-2 mg/1 as P) and an alum dose of 105 mg/1 was used in conjunction with
polymer.
Table 8 shows the percent VSS of SS for influent and effluent samples
from the F/S system. Mean percentage of VSS in the CSO for all storms was
48.6 and 38.6 percent for effluent samples; 84 percent of the storms showed
a decrease in percent VSS for the effluent samples.
38
-------
TABLE 7. FLOCCULATION/SEDIMENTATION SYSTEM: MEDIAN REMOVALS,
CO
-' —
SS Data
(mg/1)
Storm Median Median
No. Infl. Effl.
1
2
3
4
5
6
7A
7B
8
9
10
n
12
13
14
15
16
17
18
19
132.29 236.16
137.72 122.49
164.65 194.13
71.13 93.98
87.75 123.36
262.38 223.14
74.42 50.33
189.12 197.30
302.58 180.10
190.48 229.44
,171.35 120.88
266.01 112.06
195.49 119.97
330.72 199.71
449.56 34.67
445.37 74.50
162.52 50.98
151.82 55.60
183.59 59.21
VSS Data
(mg/1)
%
Removal
-78.52
11.06
-17.90
-32.12
-40.58
14.96
32.37
- 4.33
40.48
-20.45
29.45
57.87
38.63
39.61
92.29
83.27
68.63
63.38
67.75
Median
Infl.
24.98
58.98
92.09
31.44
49.84
158'. 19
46.44
105.67
158.54
83.65
85.84
146.04
132.12
133.59
162.15
155.25
79.20
74.12
41.05
Median
Effl.
32.00
48.43
75.11
82.41
46.34
87.59
15.89
57.51
80.53
86.46
57.99
54.40
70.08
67.89
6.65
26.64
17.60
13.40
17.55
%
Removal
- 28.10
17.89
18.44
-162.12
5.02 '
44.63
65.78
45.58
49.21
- 3.36
32.44
62.75
46.96
49.18
95.90
82.84
77.78
81.92
57.25
SETTS Data
(mg/1)
Median Median
Infl . Effl .
2.64
1.83
5.36
.41
2.13
1.71
1.24
1.55
2.52
4.00
6.73
7.10
1.40
8.45
5.88
2.24
94
1.61
2.81
.24
1.04
.15
.54
.92
.81
1.41
1.76
.13
.26
.19
.10
.10
%
Removal
64.39
12.02
47.57
41.46
51.17
91.23
56.45
40.65
67.86
64.75
73.85
98.17
81.43
97.75
98.30
95.54
BODc Data
(mg/1)
Median
Infl.
7.82
29.63
340.97
20.58
82.47
21.74
71.46
30.18
51.32
37.27
77.82
102.25
135.12
121.37
48.71
126.26
71.43
35.58
Median
Effl.
35.68
500.07
13.86
78.63
19.96
88.58
23.38
42.25
25.86
32.52
79.97
83.92
30.40
27.73
64.76
19.74
11.24
Removal
- 20.42
- 46.66
32.65
4.66
8.19
- 23.96
22.53
17.67
30.61
58.21
21.79
37.89
74.95
43.07
48.71
72.36
68.41
% •
(continued)
-------
TABLE 7. (continued)
COD Data
(mg/1)
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
Median
Infl.
7.93
28.23
97.00
25.41
54.04
25.42
86.49
11.04
15.69
Median
Effl.
10.23
32.74
37.65
27.95
55.53
24.77
155.79
12.99
24.35
%
Removal
- 29.00
- 15.98
- 10.00
- 2.76
2.56
- 80.12
- 17.66
- 55.19
TOC Data
(mg/1)
Median
Infl.
16.87
48.22
20.45
109.67
30.55
61.66
14.15
48.31
31.39
44.01
26.27
30.59
60.46
114.47
55.94
47.71
67.29
44.90
19.16
Median
Effl.
20.07
42.93
19.99
94.53
29.12
60.91
14.25
48.36
28.55
39.75
16.72
21.44
48.66
72.70
30.88
26.87
28.75
26.56
11.70
Removal
- 18.97
10.97
2.25
13.81
4.68
1.22
- .71
- .10
9.05
9.68
36.35
29.91
19.52
36.49
44.80
43.68
57.27
40.85
38.94
O&G Data
(mg/1)
Median
Infl.
9.34
28.92
24.19
20.36
1.27
64.17
46.67
41.55
27.41
38.48
50.87
54.39
Median
Effl.
21.00
9.90
24.04
6.86
1.33
63.96
33.33
8.64
14.07
76.39
51.54
51.94
%
Removal
-124.84
65.77
.62
66.31
- 4.72
.33
28.58
79.21
48.67
- 98.52
- 1.32
4.50
pH Data
Median Median
Infl. Effl.
6.18
5.72
5.90
6.21
6.80
7.07
7.02
6.51
7.17
7.16
8.09
6.68
7.00
7.63
7.20
7.12
6.86
6.97
7.61
6.04
5.90
6.02
6.63
6.19
7.26
7.13
6.44
7.40
7.04
7.85
6.76
7.00
7.78
7.50
6.99
7.09
5.41
6.82
(continued)
-------
TABLE 7. (continued)
TKN Data
(mq/1)
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
Median Median
Infl. Effl.
.29
2.63
1.10
6.20
2.50
4.57
1.22
3.05
.77
.81
2.45
3.39
5.42
4.12
4.17
2.25
3.47
2.70
1.33
.63
3.18
1.44
5.98
2.29
5.16
1.36
3.85
1.21
1.16
2.67
3.06
5.59
4.56
3.98
2.99
4.87
3.71
1.20
Removal
-117.
- 20.
- 30.
3.
8.
- 12.
- 11.
- 26.
- 57.
- 43.
- 8.
9.
- 3.
- 10.
4.
- 32.
- 40.
- 37.
9.
24
91
91
55
40
91
48
23
14
21
98
73
14
68
56
89
35
41
77
TIP Data
(mq/1)
Median Median
Infl. Effl.
.10 .
.24
.26
1.49
.55
.63
.18
.42
.22
.26
.29
1.16
.62
.82
.86
.31
.56
2.63
1.05
.12
.33
.24
1.29
.55
.71
.23
.84
.21
.33
.31
1.03
.64
.79
.19
.35
.21
.81
.29
%
Removal
- 20
- 37
7
13
- 12
- 27
-100
4
- 26
- 6
11
- 3
3
77
- 12
62
69
72
.00
.50
.69
.42
.00
.70
.78
.00
.55
.92
.90
.21
.23
.66
.91
.90
.50
.20
.38
Aluminum Data
(mq/1)
Median
Infl.
1.67
2.28
.60
.50
1.09
5.67
4.76
.61
.75
.05
3.06
1.26
2.94
1.12
1.77
6.96
Median
Effl.
2.16
2.11
1.45
.46
1.27
4.23
4.47
.33
1.62
1.33
2.57
2.93
14.10
9.85
Of
7o
Removal
- 29.34
7.46
-141.67
8.00
- 16.51
25.40
6.09
56.00
47.06
- 5.56
12.59
-161.61
-696.61
- 41.52
-------
TABLE 8. PERCENT VSS OF SS-FLOCCULATION/SEDIMENTATION SYSTEM
Storm No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
Inf. SS
132.29
137.72
164.65
71.13
87.75
262.38
74.42
189.12
302.58
190.48
171.45
266.01
195.49
330.72
449.56
445.37
162.52
151.82
183.59
Inf. VSS
24.98
58.98
92.09
31.44
49.84
158.19
46.44
105.67
158.54
83.65
85.84
146.04
132.12
133.59
162.15
155.25
79.20
74.12
41.05
Inf. % Vol.
18.88
42.83
55.93
44.20
56.80
60.29
62.40
55.87
52.40
43.92
50.10
54.90
67.58
40.39
36.07
34.86
48.73
48.82
22.36
Eff. SS
236.16
122.49
194.13
93.98
123.36
223.14
50.33
197.30
180.10
229.44
120.88
112.06
119.97
199.71
34.67
74.50
50.98
55.60
59.21
EFF. VSS
32.00
48.43
75.11
82.41
47.34
87.59
15.89
57.51
80.53
86.46
57.99
54.40
70.08
67.89
6.65
26.64
17.60
13.40
17.55
Eff. % Vol.
13.55
39.54
38.69
87.69
38.38
39.25
31.57
29.15
44.71
37.68
47.97
48.55
58.41
33.99
19.18
35.76
34.52
24.10
29.64
42
-------
SECTION 7
SWIRL CONCENTRATORS
BACKGROUND
The swirl concentrator has been developed following demonstration of
a vortex regulator by Smisson (15) who noted that the device permitted
solids separation in addition to functioning as an overflow regulator.
Swirl concentrators achieve removals of suspended solids by rotationally
induced forces causing inertia! separation in addition to vertical gravity
sedimentation during relatively short detention times. Originally developed
as a CSO regulator (16, 17) the concept has been refined and extended to
selective grit removal (18) and attainment of primary removal efficiencies
(12).
Mathematical and hydraulic modeling have been conducted in the studies
cited above. These models were developed using synthetic materials
simulating the particle size distributions and specific gravities of grit
and organics found in domestic sewage and CSO. The models are also being
verified by testing in prototype and pilot facilities using actual sanitary
wastewater and CSO at Lancaster, PA, (U.S. EPA Grant No. S-802219), Denver,
CO. (64), Toronto, Ont. (12), and Syracuse, NY (22). Original development
work (12, 16, 17, 18) has presented a series of design curves relating
anticipated performance to design capacity and other design parameters.
Structurally, swirl regulators/concentrators, swirl degritters, and
swirl primary separators incorporate distinctly different features. Some
of these differences are illustrated on Figures 19, 20 and 21. The selected
configuration for each application is a result of consideration of hydraulic
principles and testing on a variety of physical models. Distinct differ-
ences are noted in weir configurations, baffling and floor layouts. The
units also differ in design features such as inlet velocities, D2/Di (unit
diameter/inlet dimension) ratios, and H-J/DI (weir height/inlet dimension)
ratios. The swirl regulator and degritter studies have presented results
for units with D2/Di ratios of 6, 7.2, 9 and 12. The swirl primary
separator study employed a unit, with D2/D-] ratio of approximately 15.
Performance results in each of the above studies were scaled from
model results to predicted prototype results by using Froude Law scaling
relationships. Model to prototype conversion used the Froude number
for scaling of unit dimensions, where Np = Froude number, v = velocity,
43
-------
a. n
b Flow DflNvcror
c. Floor Gulttrj
4 Scum Balllt
t. Owttow WiH
n DewfMMll
1. Floatobln Collider
J Foul Snrtf Outltl
A ln!=t
B Deiiector
C Weir and Weir N
0 Spoiiir
E Floor
F Conleri Hopp»
FIGURE 19.
Swirl Regulator/
Concentrator
FIGURE 20. Swirl Degritter
A - Inltt
B - Dtfltctor
C - Skirt
D - Effluent Gutttn
E - Cltor Effbtnt Oultet
F-eofii<
G • Sludge Diechoroe
Sludge Diectacge
FIGURE 21. Swirl Primary -Separator
44
-------
g = acceleration due to gravity and s = reference length.
Since v = Q/A and area, A, is a function of the square of the inlet
diameter DI
therefore, Np _ r
L
Froude number scaling thus employs the relationship:
Q model =[ Dl mode1 ]5/2
Q prototype D-j prototype
for scaling of hydraulic flows. Geometric similarity must be maintained
between model and prototype. In addition, foul fraction (percent of flow
which is wasted) must be the same in prototype as in the model.
In a similar manner, particle settling velocities were also scaled
in the above studies using Froude Law relationships. Since
NF.f C-4-)
scaling of settling velocities employs the relationship
2
v prototype Dg prototype
2 - - A
v model ^2 model
where A = scale factor.
Since settling velocity is dependent on particle diameter and specific
gravity, the above studies employed synthetic materials to represent
settling velocities in the model studies. These represented scaled-down
settling velocities from prototype scale for expected particle size
distributions and specific gravities. The regulator studies used gilsonite
and polythene, the degritter studies used sand, gilsonite and pumice, and
the primary separator studies used petrothene and IRA-93 anion exchange
resin to simulate, respectively, solids in CSO, grit in domestic sewage,
and organics in domestic sewage.
The swirl regulator and the degritter studies reported effects of
varying the H]/D] ratio. Although results showed some impact on the
performance within the range tested, the effect was minor in comparison
to other design parameters. Selection of other unit dimensions is in
conformity with maintaining geometric similarity between model and
prototype.
The early work of Smisson on regulators/concentrators employed foul
fractions of 30 percent using a vortex device. Later studies (12, 16,
17, 18) demonstrated removals using foul fractions in the range of 2 to 3
percent. The regulator study (16) presented results indicating that
removal efficiency improved as foul fraction was increased from 3 to 30
45
-------
percent. Foul fractions employed in the Rochester work are discussed in the
subsections below.
OUTLINE OF EXPERIMENTS
Testing of the swirl degritter and primary separator was directed
toward evaluating the effects of hydraulic loading and variable influent
quality on removal efficiencies when treating Rochester CSO.
A matrix of tests was established whereby the swirl degritter and
primary separator units were evaluated at five flowrates from 0.95 to 4.4
1/s (15 to 70 gpm) without chemical treatment. Flowrate was held constant
throughout the duration of each storm to observe the system efficiency
under variable influent solids concentrations.
Several of these tests were repeated in the program employing chemical
treatments (polymer alone and alum plus polymer with and without phosphorous
spiking). Selection of chemicals and dosages is described in Section 5.
Table 9 lists the matrix of tests conducted for the swirl degritter
and primary separator units. Also shown on this Table is the foul
percentage employed during each test. Grit withdrawal from the swirl
degritter was conducted intermittently at 20 minute intervals. Sludge
withdrawal for the swirl primary separator was carried out on both an
intermittent and continuous basis. For intermittent withdrawal, the sludge
was extracted at 20 minute intervals. Continuous sludge withdrawal was
conducted utilizing hydraulic pressure differentials which forced the sludge
through a '£..54 cm (1 in) line at rates ranging up to 0.3 1/s (5 gpm).
TABLE 9. SWIRL DEGRITTER AND PRIMARY SEPARATOR TEST MATRIX
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
H
15
Flowrate
(gpm)
30
30
40
50
30
30
30
50
30
50
50
40
50
30
50
40
Foul Percentage . P/S Chemical Addition
P Alum Polymer
Degritter P/S* (mg/1) (mg/1) (mg/1)
0.26
0.46
0.44
0.33
0.26
0.47
0.30
0.39
0.58
0.52
0.73
0.72
1.12
0.53
0.92
0.88
0.67
0.53
0.87
0.44
0.48
0.63 40
0.46 40
0.90 1.55 105
0.52
1.26 1.37 105
1.0
1.0
1.0
1.0
1.0
1.0
1.0
46
(continued)
-------
TABLE 9. (continued)
Storm Flowrate
No. (gpm)
Foul Percentage
Degritter P/S*
P/S Chemical Addition
P Alum Polymer
(mq/1) (mg/1) (mg/1)
16
17
18
19
50
70
15
50
0.22
0.34
0.43
2.4** 1.37
2.7**
9.6**
105
40
1.0
1.0
* P/S - Swirl primary separator ** - Sludge continuously drawn
Scaling of hydraulic flows from model to prototype uses Froude Law
relationships as discussed earlier. The inlet pipe diameters, (D-j), for the
degritter and primary separator swirl units were 15 and 10 cm. (6 and
4 in), respectively. The unit diameters, (02), were 0.91 and 1.83 m
(3 and 6 ft), respectively.. Thus the D2/Di ratios employed in these
designs were 6 and 18, respectively. Table 10 shows the flowrates tested
in the pilot plant and indicates the Froude number and flowrate for a 11 m
(36 ft) diameter prototype unit, corresponding to each model flowrate.
This Table also indicates the detention time in the model at each flowrate.
TABLE 10. SWIRL DEGRITTER AND PRIMARY SEPARATOR: MODEL AND PROTOTYPE FLOWRATES
Model
(gpm)
Swirl
3 ft
15
30
40
50
70
Swirl
6 ft
15
30
40
50
70
D.T. in
Flowrate Model
(mgd) (min)
Degritter
dia model
0.022
0.043
0.058
0.072
0.101
Primary Separator
dia model
0.022
0.043
0.058
0.072
0.101
Influent
Froude
Number
Prototype
Flowrate
(rngd )
D.T. in
Prototype
(mini
6 ft dia prototype
4.7
2.4
1.8
1.4
1.0
41.3
20.7
15.5
12.4
8.8
0.0018
0.0072
o:oi28
0.0200
0.0392
0.0137
0.0547
0.0972
0.1518
0.2977
0.12
0.24
0.33
0.41
0.57
36 ft dia
1.9
3.8
5.1
6.3
8.9
7.8
3.9
2.8
2.3
1.6
prototype
105.3
52.6
39.2
31.8
22.5
Particle size distributions for Rochester CSO were measured for
several samples following storms 14, 15 and 17. These samples included
composites of influent CSO for the first and second half of each storm and
full-storm composites of effluents from the swirl degritter and swirl
47
-------
primary systems.
Particle size distributions were determined by passing wet samples
across individual screens ranging in size from 74 to 1000 microns. SS
determinations were conducted before and after screening. A small sample
volume was applied per surface area of screen to prevent matte formation.
The sample was initially deflocculated by adding 10 mg/1 of detergent.
Results of the screen analysis are presented in Table 11. Results of the
influent CSO analyses are plotted on Figure 22 as a log-probability plot of
percent finer versus particle size. Figure 22
distributions presented in the APWA studies
Lancaster, PA, and San Francisco, CA. It is
also shows CSO particle size
(18,64)for samples from
noted the the Rochester samples
exhibited size distributions slightly finer than the other locations.
TABLE 11. PARTICLE SIZE DISTRIBUTIONS*
CSO
Size Range
(microns)
Storm
No.
1st Half
2nd Half
Swirl
Degritter
Effl.
Compos.
Swirl Primary
Separator
Effl.
Compos.
>1000
841-1000
595-841
420-595
180-420
149-180
74-149
<74
>1000
841-1000
595-841
420-595
180-420
149-180
74-149
<74
14
15
0
27
1
6
6
0
74
280
394
0
30
20
50
10
30
60
480
680
54
0
0
8
10
8
18
192
290
10
10
10
0
5
5
70
150
260
16
2
2
54
208
282
0
20
16
40
254
330
0
0
22
8
148
178
20
0
0
68_
96
>1000
841-1000
595-841
420-595
180-420
149-180
74-149
<74
17 36
10
20
10
30
0
20
170
2%
0
2
5
0
14
2
15
48
41 0
14 4
0 8
5 4
135 80
86 195 96
* Results as SS (mg/1)
48
-------
98"
95-.
90-.
80-
70"
GO-
or
UJ
| 50"
S« 40-
30—
20"
10- •
5 L
---Lane.
•*•
^.San Francisco
14-2
Identification:/l3v®*-Represents First 1/2 of Storm
\{5^EH-Represents Second 1/2 of Storm
Storm 3P *
I
50
100
' I I
500
I'M
1000
I I
5OOO
FftRTICLE SIZE (MICRONS)
FIGURE 22. Combined Sewer Overflow Particle Size Distributions.
-------
Specific gravity of dried sludge solids was determined following
Storm No. H for a composite of swirl degritter and swirl primary
separator sludges. The specific gravity of the combined grit and
organic solids was determined as 1.70.
SWIRL DEGRITTER
Denver (64) and LaSalle (18) swirl degritter performance studies
were conducted on a 1.83m (6 ft) diameter prototype unit and a 0.9m (3 ft)
diameter pilot scale unit, respectively. Both studies concluded that the
swirl degritter could be effectively used to remove grit solids from all
v;astewater flows at application rates higher than those employed in con-
ventional aerated grit chambers.
The LaSalle study (18) was conducted to determine a design procedure
for the removal of grit solids using the swirl concentrator concept. -The
pilot scale model consisted of a 0.9m (36 in) diameter separation chamber
with a height of 1.02m (40 in). The influent pipe diameter was varied
to test the model at different operating conditions. Simulated materials
such as Gilsonite, pumice and fine sand were used to simulate grit material
found in combined sewage. The model was scaled up to a prototype unit by
using Froude Law relationships for both mass flow and particle settling
velocity.
The Denver (64) study was essentially an extension of the LaSalle
study (18), but conducted on a prototype scale using real .sewage. The per-
formance of this unit was also compared to the efficiency of a conventional
aerated grit chamber (AGC). The swirl degritter unit consisted of a 1.83m
(6 ft) diameter separation chamber with a 30.4 cm (1 ft) diameter influent
pipe. The grit was defined as that component having a diameter greater
than 0.20 mm and a specific gravity greater than 2.65. Chasick samplers
were installed at the influent and effluent ends of the swirl degritter
to measure grit greater than 0.2 mm in size.
The LaSalle report (18) calculated the grit removal efficiencies of
various grit chamber diameters at different scaled-up flowrates. This report
also presented a design curve for 80 to'95 percent range of grit removal
efficiencies of the swirl degritter.
In the Denver (64) study, two series of tests were conducted. In the
first series, only real sewage was applied to the swirl degritter, whereas
in the second series of tests, dry blasting sand, size 0.25 mm, was added
to the sewage after it was pumped from the influent channel. Grit removal
was measured as the weight of dry grit recovered and the weight of grit
ash recovered. The percentage removal of grit ash in the swirl degritter
ranged from 68. to 84 percent during the first series of tests. The grit
removals in the second series of tests were higher and uniform for the lower
applied flows. However, the removals at the higher flow rates (2.0 and
3.0 mgd) were erratic and at times indicated negative removals.
50
-------
Grit Definition
Grit is generally defined as particles greater than or equal to 0.2 mm
with a specific gravity of 2.65, thus possessing a settling velocity of
2.6 cm/sec (0.085 ft/sec) or greater. The specific gravity of CSO solids
measured for Storm No. 14 was 1.70. Therefore, particles of 0.3-mm size or
above would have a settling velocity of 2.6 cm/sec (0.085 ft/sec) or greater.
For the particle size distributions measured during Storm numbers 14, 15 and
17, the percentage of solids with particle size greater than 0.3 mm was
calculated. These are shown in Table 12.
TABLE 12. GRIT SOLIDS DISTRIBUTION
Storm Duration Wt. % of Particles > 0.3 mm
14
• 14
15
15
17
17
1st half
2nd half
1st half
2nd half
1st half
2nd half
8.6
22.0
14.7
11.5
25.7
8.1
The percentage of particles greater than 0.3 mm has been defined here
as the percentage of grit in the influervt CSO. It was attempted to
correlate percentage, of grit with the influent SS level, but no strong
correlation was observed. Therefore, the arithmetic mean value of grit in
the influent CSO has been used as a measure of the concentration of grit in
untreated CSO.
Prototype Swirl Degritter Performance
The particle size distributions tested in the model translate to a
different size distribution when scaled to prototype. Figure 23 shows the
mean particle size distribution of the influent to the swirl degritter for
three overflow events.
Particle settling velocities are scaled from model to prototype by
multiplying by the square root of the scale- factor A. A new particle size
distribution is thus obtained for the prototype by entering a chart of
settling velocity versus particle size and specific gravity such as those
found in the APWA reports (18, 64). The results of these calculations are
presented on Table 13 for the particle size distributions measured in the
Rochester work. The 1.8 m (6 ft) diameter prototype size distributions are
shown on Figure 23. It is noted that the particle size distribution for the
prototype swirl degritter does not differ greatly from that of the pilot
scale model. Therefore, the prototype swirl degritter performance
equations have been developed by assuming the same particle siz.e
distribution as was observed in the pilot scale unit.
51
-------
tn
ro
98-^
95-
90-
8O-
7O-
Z 6O-
UJ
ec 40.
ui
Q.
3O.
20.
10 -
Actual CSO Swirl Degritter
Oft dia.model)
Swirl Degritter
(36ft dia prototype)
Swirl Degritter
(6 ft dia. prototype)
• Actual CSO model data
* Scaled up prototype, 6 ft dia.
a Scaled up prototype, 36 ft dia.
I i T . I I T r -, | TT-T-r^
50 IOO 50O IOOO
PARTICLE SIZE (microns)
I
50OO
FIGURE 23. Swirl Degritter Model and Prototype Particle Size Distributions
-------
TABLE 13. SWIRL DEGRITTER MODEL TO PROTOTYPE SCALING OF PARTICLE SIZES;
S.G. = 1.70
Model
Size Range
(microns)
Assumed
Model Size
(mm)
Ave. Infl.
Distrib.
(X)
Settling Velocity
(cm/sec)
Model Proto.
Prototype
Size
(mm)
Model dia. = 3 ft, Prototype dia. = 6 ft, \ = 2
>1000
841-1000
595-841
420-595
180-420
149-180
' 74-149
<74
1.4
0.92
0.71
0.50
0.27
0.16
0.10
0.04
5.0
3.9
2.8
3.7
3.7
2.2
12.8
65.8
9.0
7.0
5.8
4.2
2.0
0.8
0.4
0.07
12.7
9.9
8.2
5.9
2.8
1.1
0.6
0.1
2.8
1.7
1.1
0.75
0.31
0.18
0.13
0.04
Results and Performance
In the Rochester CSO analysis, it has been assumed that changes in
particle settling velocity distributions are reflected in the influent grit
solids concentration. That is, conditions such as high sewer velocities
which tend to scour heavier particles also result in higher influent grit
solids concentrations. Performance of the degritting unit was thus related
to influent grit 'solids concentration levels and the flow through the swirl
degritter. Influent and effluent SS results across the swirl degritter
are plotted in Appendix A. The pilot scale model was scaled from a
0.91 m (3 ft) diameter unit to a 1.83 m (6 ft) diameter unit to compare
performance with the data obtained from the LaSalle and Denver studies.
Multiple regression analysis was conducted to statistically fit an
equation to the pilot plant data. The following equation was obtained
from the analysis:
9e/9o = kl + K2 Log Q + K3 Log c0
where ge/go = Fraction of grit remaining
Q = Flow through the swirl degritter (gpm)
GO = Influent suspended solids concentration in the unit (mg/1)
K-],K2,I<3= Regression coefficients
It was assumed that grit loading to the unit varied with the measured
influent SS concentration and that grit solids represented approximately
15 percent of the influent SS concentration (Table 12).
The developed regression coefficients of flow and influent SS in-
dicated that the performance decreases with increase in flow through
the swirl degritter and increases with increasing concentration of SS.
The results obtained from the above regression analysis are shown in
Table 14. The T Values associated with the flow and influent SS
53
-------
represent degrees of confidence above 70 percent and 99 percent, respective-
ly. The 'F1 value gives an indication of the statistical significance of
the regression expression. In the above analysis, the 'F1 value represents
a degree of confidence greater than 99 percent. The final regression
equation obtained for the 3 ft diameter pilot system is as follows:
9e/9o = 1-36 + 0.217 log Q - 0.653 log c0
Results of the regression analysis are indicated on Figure 24 after
scaling flowrates to a 1.8 m (6 ft) diameter prototype. Figure 24 indicates
that performance is affected not only by hydraulic loading but also by
influent grit concentrations. The dotted line on Figure 24 indicates
anticipated grit removals for the median concentration of solids in CSO
at the Rochester pilot plant location.
TABLE 14. REGRESSION ANALYSIS OF PILOT PLANT SNIRL DEGRITTER DATA
Standard Correlation Regression Std. Error Computed
Variable Mean Deviation X vs Y Coefficient of Reg. Coef. T Value
Log Q
Log CD
1.57
2.28
.161
.261
.142
-.400
.217
-.653
.198
.122
1.09
-5.32
Dependent
ge/9o .215 .440
Intercept 1.36
Multiple Correlation .408
Std. Error of Estimate .404
Analysis of Variance for the Regression
Source of Variation
Degrees Sum of Mean
of Freedom Squares Squares F Value
Attributable to Regression
Deviation from Regression
2
161
5.26
26.3
2.63
.163
16.1
Total
163
31.5
Study Comparisons
Figure 24.indicates results of the swirl degritter studies at LaSalle
and Denver, both for a 1.8 m (6 ft) diameter unit. The LaSalle design
curve is based on hydraulic modeling using sand, gilsonite and pumice. The
Denver results express removals for grit in domestic sewage arid also include
some tests with sand added to domestic sewage. It is noted that the Denver
data indicate grit removals significantly lower than removals predicted by
the LaSalle modeling. The Rochester CSO data illustrate a trend
54
-------
o
W)
1
UJ
o
tt
tu
ioa.
90..
80-.
70..
i
60--
so-.
40-.
30..
20--
IO-.
Median cone, in
Roch. CSO
r~-g0 -75 mg/l
^* A
Regression analysis of Rochester data
A La Salle data
o Denver data
Median GS concentrations Rochester data
g 0 ? Grit Solids
g 0 - 15 % of influent SS
-H 1 1 h-
O.2 O.3 0.4 O.5
\—
I.O
>
FLOW (CFS)
La Salle data
•Denver data
O.I
2.0
3.
4.0 5.0
FIGURE 24. Performance of Swirl Degritter ( 6 ft dia. unit)
-------
more consistent with the Denver data than that indicated by the LaSalle
model.
SWIRL PRIMARY SEPARATOR
Primary treatment of CSO and municipal wastewater by the swirl primary
separator principle was developed in a series of hydraulic (using synthetic
sewage) and mathematical model studies (12). The developed design con-
figuration was then tested on a pilot installation in Toronto, Canada. The
purpose of the Toronto study was to verify the design when treating munici-
pal wastewater.
The hydraulic and mathematical model studies developed a series of
design curves for different size units. This study was conducted on a 0.9m
(3 ft) diameter unit and was scaled to prototype sizes using Froude Law
relationships. The Toronto pilot study was conducted on a 3.7 m (12 ft)
diameter unit.. The Toronto tests were carried out at flow rates of 1,137
m3/day (0.3 mgd) and 1,700 m^/day (0.45 mgd). Figure 26 shows a comparison
of the predicted performance by the LaSalle design curves and the arithmetic
mean of the SS removal results obtained at Toronto.
Pilot Plant Results
Data from operation of the 1.8 m (6 ft) diameter swirl primary
separator at Rochester are indicated in Appendix A. These curves represent
analyses corresponding to actual sampling times. Removal rates were
calculated after lagging the effluent analyses by the theoretical detention
time in the unit. Hydraulic loading to the unit was held constant for
each storm. For each storm it was noted that SS removal rates fluctuated
as a function of the influent SS concentration (c0). It was furthermore
noted that an approximately straight line relationship was developed for
each storm when'log (ce/c0) was plotted versus log c0. Since the sus-
pended solids concentration in CSO fluctuates in response to scouring
velocities in the sewer line, c0 was viewed as a gross indicator of the
particle settling velocity distribution. Thus, wastewaters during the
first-flush, when c0 is highest, tend to have a greater proportion of solids
of larger size and specific gravity.
The SS removal rate is also a function of hydraulic loading to the
unit. In order to account for both influences, the pilot plant data were
statistically fit using a multiple regression analysis to an equation of
the form:
log (ce/c0) = KI + K2 log Q + K3 log c0
where Q = hydraulic flow applied to the unit and K-j, Kg and l<3 are
regression coefficients.
Results of the regression analysis are shown on Table 15. The signs
associated with the regression coefficients indicate that SS removals
generally increased with an increase in c0 and a decrease in Q. 'T1 values
associated with Q and c0 indicated degrees of confidence of >99 percent
for the overall expression.
56
-------
TABLE 15. REGRESSION ANALYSIS OF PILOT PLANT SWIRL PRIMARY SEPARATOR DATA
Variable
Log Q
Log c0
Mean
1.52
2.17
Standard
Deviation
.236
.279
Correlation
X vs Y
.351
-.215
Regression
Coefficient
.447
-.239
Std. Error
of Reg. Coef.
.129
.109
Computed
T Value
3.46
-2.18
Dependent
Log ce/c0-2.46 .297
Intercept -.409
Multiple Correlation .416
Std. Error of Estimate .273
Analysis of Variance for the
Regression
Degrees Sum of
Souce of Variation of Freedom Squares
Attributable to
Deviation from
Total
Regression
Regression
2
78
80
1.22
5.83
7.06
Mean
Squares F Value
.613 8.20
.074
The final regression equation was thus obtained as
r. I,* - n QQO n -447 „ -0.239
CQ/CO - 0.389 Q C0
The trends indicated by the regression equation are shown on Figure
25. Using this model it is possible to predict the performance of the
swirl primary separator for simultaneously varying flows and influent
quality such as that which occurs during an overflow event. It should be
emphasized that the above equation was developed for a 0.9 m (3 ft) diameter
model tested up to the flowrate of 4.4 1/s (70 gpm) and influent SS con-
centrations range of 100 to 800 mg/1.
On Figure 26 the Rochester regression model is compared to performance
predicted by the LaSalle design curves. It is noted that for a range of
c0 between 100 to 500 mg/1, the Rochester data generally support the LaSalle
curve, except at the lower flowrates. It is recognized, however, that
the LaSalle curves were developed for a material synthesizing the settling
velocity distribution of municipal sewage while the Rochester work used
actual CSO. Figure 26 also shows a comparison of results of the Toronto
study (12) with the design predictions from the LaSalle study (12).
All of the analyses above used only the data from runs in which no
chemical treatment was employed. In general, it was observed that chemical
treatments (anionic polymer alone or alum plus anionic polymer) produced
no significant improvement beyond that observed without chemicals. It is
speculated that the mode of chemical addition was responsible for the
lack of improvement. Because of inadequate velocity gradients and/or
contact time, in-line mixing of chemicals may not have provided efficient
floe development. It cannot be stated that the swirl primary separator is
ineffective for separation of chemical floe.
57
-------
100-T-
I p—I—I—I—I
8 9 K>
20 3O 4O SO 60 7O SO 90 IOO
APPLIED FLOWRATE (gpm)
FIGURE 25. Swirl Primary Separator Regression Model and Performance Data
LaSolle Design Curves
C0= SOOmg/lj Rochester
C0=IOOmg./r (6f».Dia.)
mg/l* 16 ft. Dia.)
Toronto CSO (12'Dio)
-t 1 1—I I I I I |
1 1—I I I I
H 1 1 1 I I I I
OOI
FIGURE
ai
1.0
10
FLOWRATE (MGD)
26. Swirl Primary Separator Loading-Performance Relationship
58
-------
Scale-Up Considerations
Figure 26 illustrates the trend attained by scaling of flows and parti-
cle settling velocities as proposed by the LaSalle work. It is noted that
scaling of particle settling velocities results in lower removal efficiencies
for larger size prototypes at equivalent scaled hydraulic loads.
It is noted that scale-up by Froude Law results in a prototype size
significantly different from that which would be obtained by traditional
scale-up using OR. A rationale for the use of Froude Law scaling may
perhaps be seen in data presented by Camp (7, 47) for narrow and wide
rectangular sedimentation basins and circular, radial-flow basins. In
evaluating the results of dye tracer studies, Camp showed that the degree
of short-circuitng in the basin was related to the Froude number of the
horizontal flow through the basin. Thus, by scaling based on Froude
Law relationships it would be expected that the model and prototype would
both display the same degree of short-circuiting.
When dealing with primary separators in which flocculent particles are
removed, it may not be entirely appropriate to apply Froude Law scaling to
particle settling velocities. It was noted on Table 10 that Froude Law
scaling of hydraulic flows results in greater detention times in the
prototype than in the model. While separation of discrete particles
is theoretically independent of detention time, there are aspects of
flocculent agglomeration that are affected by detention time. As flocculent
particles collide, the combined, particle size is increased and the settling
velocity increases. .This flocculation process is affected by detention
time, differences in particle settling velocities,and velocity gradients
in the liquid. Thus, it is possible that the loss in removal efficiency
predicted by particle scaling is partially offset by increased flocculation
in the larger prototype units.
Figure 27 shows the mean particle size distribution of the influent
SS to the swirl primary separator for three overflow events. For scale up
from model .to prototype, particle settling velocities have been scaled by
multiplying by the square root of the scale factor A. Table 16 presents
the prototype particle size distributions for the data obtained in Rochester.
TABLE 16. SWIRL PRIMARY SEPARATOR-MODEL TO PROTOTYPE SCALING OF
PARTICLE SIZES, S.G. = 1.70
Model
Size Range
(microns)
Assumed
Model Size
(mm)
Ave. Infl.
Distrib.
( SO-
Settling Velocity
(cm/sec)
Model Proto.
Prototype
Size
(mm)
Model dia. = 6 ft, prototype dia. = 36 ft; A = 6
1000
180-420
149-180
74-149
<74
0.60
0.27
0.16
0.10
0.04
7.1
4.5
2.2
12.3
73.9
5.1
2.0
0.8
0.4
0.07
12.5
4.9
2.0
1.0
0.17
2.5
0.55
0.26
0.17
0.065
59
-------
Figure 27 shows the particle size distributions for the 1.83 m (6 ft)
diameter pilot scale model and the 11.0 m (36 ft) diameter prototype unit.
If Froude Law scaling of particle settling velocities is to be employed, it
may be necessary to adjust removal rates to account for the coarser size
distribution represented in the prototype. However, as discussed above,
this may be offset by the longer detention times in the prototype.
REMOVALS OF OTHER CONSTITUENTS
Removals of pollutants other than SS were evaluated on a storm-average
basis. Listings of minimum, maximum, arithmetic means, geometric means,
and standard deviations of influent and effluent data are included in
Appendix C. For each of the parameters the geometric mean or median data
were compiled for each storm and median removal rates were determined (see
Tables 17 and 18).
Tables 19 and 20 show the -percent VSS of SS for the influent and
effluent samples for the swirl degritter and the swirl primary separator
systems. Mean percent VSS of SS in the raw CSO for all storms was 48.6
oercent.
98y
95-
90-
80-
70-
60-
* 40^
30
20-
10-
5
Particles -=3-5 mm
P/S (36' Dio. Prototype)
IRA-93 used In
LaSolte study
seated to 6' Dia.
and s.g.= l.70
Actual IRA-93 (s.g.= 1.04)
/used in LaSalle study
f Actual Petrothene
/used in LaSalle study
LEGEND;
• 6' DIA, MODEL
O 36'DIA. PROTOTYPE
P/S- SWIRL PRIMARY SEPARATOR
100 500
Particle Size (Microns)
1000
5000
FIGURE 27. Swirl Primary Separator Model and Prototype Particle Size
Distributions (specific gravity = 1.70).
60
-------
TABLE 17. SWIRL DEGRITTER SYSTEM
en
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
SS Data
(mg/1)
Median Median
Infl. Effl.
132.29 134.58
137.72 112.27
164.65 124.05
71.13 124.84
87.75 139.23
262.38 245.31
74.42 41.38
189.12 249.75
302.58 184.56
190.48 259.85
171.35 149.35
266.01 164.06
195.49 249.69
330.72 336.95
449.56 302.16
445.37 239.85
162.52 148.09
151.82 109.29
182.59
VSS Data
(mg/1)
%
Removal
- 1.73
18.48
24.66
- 75.51
- 58.67
6.51
44.40
- 32.06
39.00
- 36.42
12.84
38.33
- 27.73
- 1.88
32.79
46.15
8.88
28.01
Median
Infl.
24.98
58.98
92.09
31.44
49.84
158.19
46.44
105.67
158.54
83.65
85.84
146.04
132.12
133.59
162.15
155.25
79.20
74.12
41.05
Median
Effl.
24.39
50.14
64i 08
112.96
74.20
120.32
14.38
75.14
84.74
102.34
76.99
42.56
116.44
143.41
97.07
62.60
101.54
46.76
V
h
Removal
2.36
14.99
30.42
-259.29
- 48.88
23.94
69.04
28.89
46.55
- 22.34
10.31
70.86
11.87
- 7.35
40.14
59.68
- 28.21
36.91
SETTS Data
(mg/1)
Median
Infl.
2.64
1.83
5.36
.41
2.13
1.71
1.24
1.55
2.52
4.00
6.73
7.10
1.40
8.45
5.88
2.24
Medi an
Effl.
1.94
1.54
5.66
0.36
2.72
1.23
0.88
1.37
2.09
3.69
6.22
11.00
6.60
7.40
2.66
-------
01
ro
TABLE 17. (continued)
COD Data
(mg/1)
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
Median
Infl.
7.93
28.23
97.00
25.41
54.04
25.42
86.49
11.04
15.69
Median %
Ef f 1 . Removal
5.
21.
41.
26.
51.
21.
18.
15.
48 30.90
13 21.61
00
18 - 3.03
01 5.61
34 16.05
15 - 64.40
48 1.34
TOC Data
(mcf/1)
Median Median %
Infl. Effl. Removal
16.87
48.22
20.45
109.67
30.65
61.66
14.15
48.31
31.39
44.01
26.27
30.59
60.46
114.47
55.94
47.71
67.29
44.90
19.16
18.62 -
44.98
17.90
82.21
34.04 -
52.44
13.38
51.74 -
31.89 -
30.33
26.28 -
31.34 -
63.52 -
99.44
87.45 -
40.36
67.07
33.49
10.37
6.72
12.47
25.04
11.42
14.95
5.44
7.10
1.59
31.08
.04
2.45
5.06
13.13
56.33
15.41
.33
25.41
U&G Data '"
(mg/1)
Median
Infl.
9.34
28.92
24.19
20.36
1.27
64.17
46.67
41.55
27.41
38.48
50.87
54.39
Median
Effl .
12.50
29.06
24.82
31.00
7.00
28.00
20'. 00
42.00
24.00
18.50
88.00
32.00
56.00
18.00
100.00
66.00
%
Removal
- 33.83
- .48
- 2.60
- 37.18
31.43
- 34.78
34.33
-159.88
- 29.74
pH Data
Median Median
Infl. Effl.
6.18
5.72
5.90
6.21
6.80
7.07
7.02
6.51
7.17
7.16
8.09
6.68
7.00
7.63
7.20
7.12
6.86
6.97
7.61
6.03
5.78
5.92
7.81
7.33
7.65
•
(continued)
-------
TABLE 17. (continued)
en
CO
TKN Data
(mg/1)
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
Median Median %
Infl. Effl. Removal
.29
2.63
1.10
6.20
2.50
4.57
1.22
3.05
.77
.81
2.45
3.39
5.42
4.12
4.17
2.25
3.47
2.70
1.33
.27
2.19
.87
4.96
2.33
4.84 -
.81
.18
1.34 -
1.21 -
2.24
2.34
6.62 -
4.59 -
2.49
2.05
4.42 -
2.51
6.90
16.73
20.91
20.00
6.80
5.91
33.61
94.10
74.03
49.38
8.57
30.97
22.14
11.41
40.29
8.89
27.38
7.04
TIP Data
(mg/1)
Median Median
Infl . Effl .
.10
.24
.26
1.49
.55
.63
.18
.42
.22
.26
.29
1.16
.62
.82
.86
.31
.50
.50
.20
.08
.25
.20
1.15
.52
.60
.18
.94
.31
.17
.26
.09
.71
.61
.41
Removal
20.00
- 4.17
23.08
22.82
5.45
4.76
.00
-123.81
- 40.91
34.62
10.34
92.24
13.41
- 8.93
18.00
-------
TABLE 18. SWIRL PRIMARY SEPARATOR SYSTEM
01
Storm Median
No. Infl.
1
2
3
4
5
6
7A
7B
8
9
10
n
12
13
14
15
16
17.
18
19
134.58
112.27
124.05
124.84
139.23
245.31
41.38
249.75
184.56
259.85
149.35
164.06
249.69
336.95
302.16
239.85
148.09
109.29
183.59
SS Data
(ma/1)
Medi an %
Effl . Removal
122.88
80.67
56.56
135.25 -
35.55
300.72 -
55.69 -
198.70
209.35 -
175.81
113.48
121.79
153.71
260.12
109.85
135.90
121.58
88.32
91.77
8.69
28.15
54.41
8.34
74.47
22.59
34.58
20.44
13.43
32.34
24.02
25.76
38.44
22.80
63.65
43.34
17.90
19.19
50.01
VSS Data
(mg/1)
SETTS Data
(mg/1)
Median Median %
Infl . Effl . Removal
Median Median
Infl. Effl.
°/
h
Removal
24.39 53.86 -120.83
50.14 27.93
64.08 12.19
112.96 120.86 -
74.20 20.31
120.32 147.87 -
14.38 23.24 -
75.14 63.19
84.74 87.09 -
102.34 63.54
76.99 47.11
42.56 58.39 -
116.44 59.84
143.41 104.00
97.07 32.10
62.60 41.81
101.54 79.65
46.76 37.15
41.05 24.99
44.30
80.98
6.99
72.63
22.90
61.61
15.90
2.77
33.03
38.81
37.19
48.61
27.48
66.93
33.21
21.56
20.55
39.12
1.94
1.54
5.66
.36
2.72
1.23
.88
1.37
2.09
3.69
6.22
11.00
6.60
7.40
2.66
2.24
.76
1.41
4.67
.33
1.55
1.07
1.13
2.61
1.56
.22
2.62
1.75
3.77
4.49
.32
1.18
60.82
8.44
17.49
8.33
43.01
13.01
- 28.41
- 90.51
25.36
94.04
57.88
84.09
42.88
39.32
87.97
47.32
BODs Data
(mg/1)
Median
Infl.
10.35
32.75
1302.00
13.16
75.09
15.79
72.02
20.74
32.98
36.05
45.72
54.54
97.08
60.95
25.68
113.28
56.46
35.58
Median
Effl.
24.63
1739.00
14.67
89.58
18.31
64.02
22.87
24.86
24.35
29.61
39.63
79.07
31.76
18.19
110.44
51.21
24.63
i
h
Removal
24.79
-33.56
- 11.47
- 19.30
- 15.96
11.11
- 10.27
24.62
32.45
35.24
27.40
18.55
47.89
29.17
2.51
9.30
30.78
(continued)
-------
TABLE 18. (continued)
cr>
en
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
n
12
13
14
15
16
17
18
19
Medi
Infl
5.
22.
41.
26.
51.
21.
18.
15.
COD Data
(ma/1)
TOC Data
(mg/1)
an Median %
. Ef f 1 . Removal
48
13
00
18
01
34
15
48
10.65 -
22.25 -
39.72
29.03 -
61.24 -
22.02 -
83.91
11.31
16.57 -
94.34
.54
3.12
10.89
20.05
3.19
37.69
7.04
Median Median
Infl. Effl.
18.62
44.98
17.90
82.21
34.04
52.44
13.38
51.74
31.89
30.33
26.28
31.34
63.52
99.44
87.45
40.36
67.07
33.49
19.16
18.08
42.92
16.63
73.19
33.57
96.45
14.95
50.08
21.22
20.96
25.74
26.06
42.34
68.20
33.02
31.80
33.91
32.92
18.01
V
h
Removal
2.90
4.58
7.09
10.97
1.38
- 83.92
- 11.73
3.21
33.46
30.89
2.05
16.85
33.34
31.42
62.24
21.21
49.44
1.70
6.00
O&G Data
(mg/1)
Median
Infl.
12.50
29.06
24.82
31.00
7.00
28.00
20.00
42.00
24.00
18.50
88.00
32.00
56.00
18.00
100.00
66.00
54.39
Median
Effl.
10.38
33.45
11.22
24.00
14.00
15.00
24.00
38.00
16.00
15.00
76.00
30.00
17.00
15.00
88.00
67.00
49.00
%
Removal
16.96
- 15.11
54.79
22.58
-100.00
46.43
- 20.00
9.52
33.33
18.92
13.64
6.25
69.64 '
16.67
12.00
- 1.52
9.91
pH Data
Median Median
Infl. Effl.
6.03 5.90
5.78 5.86
5.92 5.89
7.81 7.56
7.33 7.47
7.65 7.85
7.61
(continued)
-------
TABLE 18. (continued)
TKN Data
(mg/1)
Storm
No.
Median Median
Infl. Effl.
%
Removal
TIP Data Aluminum Data
(mg/1) (mg/1)
Median Median
Infl. Effl.
% Median Median %
Removal Infl . Effl . Removal
1
2
3
4
5
6
7A
7B
8
9
10
n
12
13
14
15
16
17
18
19
.27
2.19
.87
4.96
2.33
4.84
.81
.18
1.34
1.21
2.24
2.34
6.62
4.59
2.49
2.05
4.42
2.51
1.33
.39
2.90
1.26
4.29
2.30
5.91
.94
2.86
1.31
1.49
1.58
2.18
7.40
5.11
2.30
2.40
4.74
2.84
1.57
- 44.44
- 32.42
- 44.83
13.51
1.29
- 22.11
- 16.05
-1488.89
2.24
- 23.14
29.46
6.84
- 11.78
- 11.33
7.63
- 17.07
- 7.24
- 13.15
- 18.05
.08
.25
.20
1.15
.52
.60
.18
.94
.31
.17
.26
.09
1.55
.71
1.37
1.37
.61
.41
.20
.09
.33
.31
1.10
.51
.61
.20
.41
.10
.20
.02
.10
2.04
.65
1.50
.68
.46
.47
.20
- 12.50
- 32.00
- 55.00
4.35
1.92
- 1.67
- 11.11
56.38
67.74
- 17.65 1.92
92.31
- 11.11
- 31.61
8.45
- 9.49 134.00
50.36
24.59
- 14.63
.00 6.96
-------
TABLE 19. SWIRL DEGRITTER - PERCENT VSS OF SS
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
mg/1
Inf.
SS
132.29
137.72
164.65
164.65
71.13
87.75
262.38
74.42
189.12
302.58
190.48
171.35
266.01
195.49
330.72
449.56
445.37
162.52
151.82
mg/1
Inf.
VSS
24.98
58.98
92.09
92.09
31.44
49.84
158.19
46.44
105.67
158.54
83.65
85.84
146.04
132.12
133.59
162.15
155.25
79.20
74.12
Inf.
Vol. %
18.88
42.83
55.93
55.93
44.20
56.80
60.29
62.40
55.87
52.40
43.92
50.10
54.90
67.58
40.39
36.07
34.86
48.73
48.82
Eff.
SS
134.58
112.27
124.05
124.05
124.84
139.23
245.31
41.38
249.75
184.56
259.85
149.35
164.06
249.69
336.95
302.16
239.85
148.09
109.29
Eff.
VSS
24.39
50.14
64.08
64.08
112.96
74.20
120.32
14.38
75.14
84.74
102.34
76.99
42.56
116.44
143.41
97.07
62.60
101.54
46.76
Eff.
Vol. %
18.12
44.66
51.66
51.66
90.48
53.29
49.05
34.75
30.09
.45.91
39.38
51.55
25.94
46.63
42.56
32.13
26.10
68.57
42.79
TABLE 20. SWIRL PRIMARY.
SYSTEM -
PERCENT VSS
OF SS
Storm
No.
1
2
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
mg/1
Inf.
SS
134.58
112.27
124.05
124.84
139.23
245.31
41.38
249.75
184.56
259.85
149.35
164.06
249.69
336.95
302.16
239.85
148.09
109.29
183.59
_ _ _
Inf.
VSS
24.39
50.14
64.08
112.96
74.20
120.32
14.38
75.14
84.74
102.34
76.99
42.56
116.44
143.41
97.07
62.60
101.54
46.76
41.05
Inf.
Vol. %
118.12
44.66
51.66
90.48
53.29
49.05
34.75
30.09
45.91
39.38
51.55
25.94
46.63
42.56
32.13
26.10
68.57
42.79
22.36
mg/1
Eff.
SS
122.88
80.67
56.56
135.25
35.55
300.72
55.69
198.70
209.35
175.81
113.48
121.79
153.71
260.12
109.85
135.90
121.58
88.32
91.77
_ _ _
Eff.
VSS
53.86
27.93
12.19
120.86
20.31
147.87
23.24
63.19
87.09
68.54
47.11
58.39
59.84
104.00
32.10
41.81
79.65
37.15
24.99
Eff.
Vol. %
43.83
34.62
21.55
89.36
57.13
49.17
41.73
31.80
41.60
38.99
41.51
47.94
38.93
39.98
- 29.22
• 30.77
65.51
42.06
27.23
67
-------
SECTION 8
MICROSCREENING
GENERAL
The microscreen is a liquid straining device that utilizes a micro
fabric mesh to remove suspended materials from liquid-solid suspension.
Although the use of the microscreen in the waste treatment field is not
new, application of the units for the treatment of CSO has been very
limited. Microscreen studies conducted by the Hydrotechnic Corporation
(14) demonstrated suspended solids removals ranging from 17 to 40 percent
and 6005 removals of 4 to 22 percent. The screens employed during these
investigations had aperture sizes of 420 and 841 microns. NeKetin and Dennis
(25), utilizing screens with a 105 micron aperture size, found suspended
solids and COD removals equal to 26.6 and 15.5 percent, respectively.
Microscreen experiments conducted by Glover and Herbert (26) exhibited
suspended solids removals of 20 to 93 percent. The screen aperture size
utilized during their investigations was 23 microns. Also, organic matter,
as measured by COD and TOC, was found to be reduced by 25 to 40 percent.
Glover and Herbert (26) also suggested that conventional'microscreens
employed in CSO treatment be operated at high headless differentials of
approximately 61 cm (24 in). They proposed that this differential would
permit loading rates of 142 to 1831 1/min m^ (35 to 45 gpm/ft^) of screen
area and produce an effluent quality of 40 mg/1 suspended solids.
The microscreen used at the Rochester pilot plant was comprised of a
vertically aligned cylindrical drum, the lower portion of which was covered
with a woven micromesh filter fabric (See Figure 6). When in operation,
the drum rotated about its vertical axis at peripheral speeds of 91 to
213 m/min (300 to 700 fpm) which corresponds to a rotational speed of
58 to 136 rpm. A sonic transducer was rigidly mounted on a stationary
support inside the strainer drum and as the fabric-covered portion of the
drum passed over the transducer, it was cleaned by the gas cavitation that
was developed in the liquid at the surface of the drum as a result of the
high-energy sound waves produced by the sonic transducer. Because the
sonic transducer must be covered with liquid to effectively clean the
fabric, the liquid (filtrate) inside the drum must be maintained at a level
sufficient to keep the transducer submerged. The liquid outside the drum
was maintained at a level greater than that of the filtrate so that a
differential head was established, forcing the unfiltered liquid outside
the drum through the filter fabric.
The microscreening process at the pilot plant was evaluated in
comparison to swirl concentrators to establish primary solids removal prior
to filtration. The purpose of this comparison was to investigate the type
68
-------
of pretreatment efficiency necessary (90 percent SS removal for microstrain-
ing or 50 to 70 percent SS removal for swirls) to optimize the performance
of dual-media high-rate filtration.
OUTLINE OF EXPERIMENTS
Two of the more important variables that are relative to the micro-
screening process are hydraulic loading rates and screen aperture size.
Since there areno historical data on the overall performance and efficiency
of sonically-cleaned microscreens in treating combined sewer overflows,
it was necessary to concentrate on hydraulic leading rates during the
initial testing stages. The emphasis of operation during the initial
investigations was concerned with establishing screen performance at
hydraulic rates of 1000 to 1200 1/min m2 (25 to 30 gpm/ft2).
The microscreen was originally equipped with screens having an aperture
size of 10 microns based on manufacturer's recommendation. Hydraulic load-
ing rates greater than 400 1/min m2 (10 gpm/ft2) were unattainable without
creating an overflow condition in the unit when using the 10 micron screens.
This condition could have been due to the screen aperture size and/or to
the ineffectiveness of the sonic cleaning mechanism. In an attempt to
attain higher hydraulic loadings, the 10 micron screens were replaced with
screens having an aperture size of 70 microns. However, subsequent testing
of the microscreen, utilizing the larger aperture screens, failed to yield
any improvement in performance.
Examination- of the microscreen unit disclosed a faulty transducer in
the sonic cleaning mechanism. The mechanism was returned to service only
prior to Storm No. 13. Because of time limitations in the pilot plant
program, subsequent testing of the microscreen unit was restricted to
maximizing the hydraulic loading rate.
RESULTS AND PERFORMANCE
Evaluations of the microscreening process were fairly limited due to
the problems encountered with the sonic cleaning mechanism. Results of
the first dry weather test (Storm No. 67) conducted in the microscreen
are presented in Figure 28. Suspended-solids removals averaged 33 percent
at a loading of 895 1/min m2 (22 gpm/ft2). Operating at a drum speed of
136 rpm, headless in the unit stabilized at 30 cm (12 in).
During the next wet weather test, the microscreen unit reached a
loading rate of approximately 407 1/min m2, operating under a head
differential of 25 cm (10 in). Drum speed during this investigation
was maintained at 136 rpm. Figure 29 shows the suspended sol ids.removal
efficiency for this test. Mass balance calculations indicated that a very
small fraction of the solids removed were present in the solids blowdown.
The majority of solids accumulated upstream of the strainer.
Following the above tests, the screens were steam cleaned and a series
of dry weather tests were conducted. Higher headlosses generally prevented
operation beyond a hydraulic loading of 407 1/min m2 (10~apm/ft2). The
69
-------
DRUM SPEED (rpm)
E4O 1420
TIME (hr»)
FIGURE 28. Microscreen System Performance
Storm No. 67 (2/25/76)
(dry-weather flow)
DRUM SPEED (rpm)
TIME (hrs)
FIGURE 29.
Microscreen System Performance
Storm No. 12 (3/2/76)
(wet-weather flow)
-------
hydraulic loading and the drum speed were gradually increased to 407
1/min m2 (10 gpm/ft2) and 136 rpm, respectively. Headlosses associated
with the higher loading rates were much smaller than the headlosses in-
curred by the sudden increase in loading rates as was done in the above
tests. Figures 30 and 31 present suspended solids removal results for
the two dry weather tests conducted under the above operating conditions.
Figure 32 presents the SS removal efficiency of the unit at a maximum
hydraulic loading of 598 1/min m2 (14.7 gpm/ft2) and a rotational speed
of 136 rpm. The headless incurred in this test was 44 cms (17.5 in). A
final wet-weather analysis was conducted by increasing the rotational
speed of the drum to 136 rpm at a hydraulic loading of 273 1/min m2 (6.7
gpm/flr). Figure 33 presents the system performance results during the
final wet-weather analysis.
From the above analysis, it appears that the rotational speed is a
very important parameter in the operation of the unit. Results indicated
that the microscreen performance improved considerably when the microscreen
drum was rotated at the maximum speed. With the exception of one storm
the maximum hydraulic loading attainable without producing overflow was
549 1/min m2 (13.5 gpm/ft2). This appeared to be the operating limit of
the microscreen for both wet- and dry-weather flows at the"Rochester
pilot plant site. During wet-weather flows, operation of the unit was
considerably more erratic and hydraulic loadings attainable were lower
than those experienced during dry-weather investigations. This could
have been due to the varying level of suspended solids present in the
influent. Influent suspended solids averaged 240 to 317 mg/1 during the
wet-weather investigations and 40 to 60 ;mg/l during the dry-weather
operations. However, the higher influent SS during wet-weather testing
did not always result in higher SS removals as seen in Table 21.
A list of removal percentages for all the parameters analyzed during
the microscreen investigations is presented in Table 21. A statistical
analysis of this data for storm operations is presented in Appendix C.
71
-------
DRUM SPEED (rpm)
ro
DRUM SPEED (rpm)
122O MOO
TIME (hrs)
FIGURE 30. Microscreen System Performance
Storm No. 13 (3/12/76)
(wet-weather flow)
FIGURE 31. Microscreen System Performance
Storm No. 71 (5/3/76)
(dry-weather flow)
-------
s
DRUM SPEED (rpm)
CO
1220 1100
TIME (hrs)
u>
1 DRUM SPEED (rpm)
2|
3 o.
3 & 8.
900
85O
800
730'
« TOO
f"* 650-
6OO-
~* 550'
Zi 4so.
OT *X>
O
i»
" 'l»
o ro eocgigo o
• | i 1
I
1
1
1
i
I
/
c
A
/\ 1- INFLUENT
/ \ E- EFFLUENT
/ \ C- CONCENTRATE
/ \
/ Q f-
F
74
• i »
BOO (44O 1620 I8OO
TIME (hre)
FIGURE 32. Microscreen System Performance
Storm No. 72 (5/4/76)
(dry-weather flow)
FIGURE 33. Microscreen System Performance
Storm No. 17 (5/11/76)
(wet-weather flow)
-------
TABLE 21. MICROSOREENING ANALYTICAL DATA*
PARAMETER
Storm No.
Infl. SS (mg/1)
Effl. SS (mg/1)
% SS Removal
Infl. BODr (mg/1)
Effl. BOD§ (mg/1)
% BOD5 Removal
Infl. VSS (mg/1)
Effl. VSS (mg/1)
% VSS Removal
Infl. SETTS (mg/1)
Effl. SETTS (mg/1)
% SETTS Removal
Infl. TIP (mg/1)
Effl. TIP (mg/1)
% TIP Removal
Infl. TKN (mg/1)
Effl. TKN (mg/1)
% TKN Removal
Infl. TOC (mg/1)
Effl. TOC (mg/1)
% TOC Removal
Infl. 0 & 6 (mg/1)
Effl. 0 & G (mg/1) •
% 0 & G Removal
WET WEATHER ANALYSIS
12
261.2
147.6
43.5
82.6
42.6
48.4
128.3
62.3
51.4
2.48
0.87
64.9
7.27
0.41
94.4
3.56
3.42
3.9
29.6
43.2
13
236.9
212.1
10.5
107.9
109.0
154.5
114.0
26.2
9.41
3.62
61.5
0.63
0.99
4.88
6.49
62.9
85.2
86.0
76.0
11.6
17
317.3
314.5
1.5
209.6
201.4
3.9
200.6
188.4
6.1
13.50
7.14
47.1
1.01
1.23
3.32
6.74
107.4
97.7
9.0
59.0
52.1
11.7
DRY WEATHER ANALYSIS
67 71 72
40.5 54.6 59.5
27.3 36.7 45.6
32.6 32.8 23.4
35.3
22.8
35.4
Results are geometric means of the values obtained
74
-------
SECTION 9
DUAL-MEDIA HIGH-RATE FILTRATION
BACKGROUND
Studies of wastewater filtration have focused primarily on polishing
of secondary effluents. In this application deep bed filters have been
employed at hydraulic loading rates of 81 to 407 1/min m2 (2 to 10 gpm/ft2).
Dual or multi-media filters are generally preferred in wastewater appli-
cations, as they allow more efflicient use of the filter depth.
In addition to removal efficiencies, the performance of filter units
is characterized by the run lengths attainable as determined by the rate of
headloss. Since run length is also affected by the hydraulic loading rate,
a more appropriate measure of production is specific capture or the total
kilograms of SS accumulated per m2 of surface area per run.
When treating secondary effluent, Baumann and Huang (31) have indicated
results showing up 'to 85 percent removal of SS when employing 30 cm (12 in)
of 1.84 mm anthracite over 30 cm (12 in) of 0.55 mm sand. Specific captures
of 3 to 3.6 kg/m2 (0.62 to 0.73 lb/ft2) per run were demonstrated when
employing terminal headlosses of 3 m (10 ft) of water. Their work indicated
that specific capture was basically unaffected by hydraulic loading and
applied solids concentration, but was related mainly to filter media size.
Tchobanoglous and Eliassen (32) developed a mathematical model for deter-
mining specific capture based on data for activated sludge effluent from
Palo Alto. Cal . They indicated specific captures ranging from 1.95 to
12.7 kg/m2 (0.4 to 2.6 lb/ft2) per run as media size was increased from
0.4 to 1.5 mm diameter.
The filter performance equations employed in the EPA SWMM II model
(34) are based partly on secondary effluent filtration studies at Chicago
reported by Lynam et al. (33). These studies demonstrated SS removals of
65 to 78 percent for 0.58 mm sand with hydraulic loading (flux) rates of
102 to 244 1/min m2 (2.5 to 6 gpm/ft2). The filter results obtained at
Washington, D.C. (35) using a'synthetic storm overflow were also incor-
porated .in the SWMM model. This report presented results for three
filters. The first filter consisted of fiberglass media which demonstrated
SS removals of 87 to 95 percent and BODs removals of 60 to 75 percent for
flux rates of 610 to 2035 1/min m2 (15 to 50 gpm/ft2). The second filter was
comprised of 91 cms ( 36 in) of coarse garnet. Two-hour run lengths were
attained at 407 1/min m2 (10 gpm/ft2) with SS removals of 80 to 95 percent
and BOD5 removals of 50 to 80 percent. The higher removals were attained
with chemical treatment (150 mg/1 alum + 4 mg/1 flocculant aid). Flux
75
-------
rates of 814 1/min m2 (20 gpm/ft2) resulted in one-half hour runs. The
third filter consisted of 1.2 m (48 in) of medium garnet and 23 cm (9 in)
coarse garnet operated in an upflow mode. This filter maintained flux
rates of 204 to 610 1/min m2 (5 to 15 gpm/ft2) with SS removals of 60
percent and BODs removals of 45 percent. Efficiency dropped sharply for
flux rates above 610 1/min m2 (15 gpm/ft2).
Filtration of CSO was studied at Cleveland, Ohio by Nebolsine et al.
(14), where the filtration was preceeded by fine mesh screening (40 mesh).
After testing anthracite sizes of Numbers 2, 3, and 4, a filter media con-
figuration of 1.5 m (5 ft) of No. 3 anthracite (4.0 mm e.s.)over 0.9 m (3 ft)
of No. 612 sand (2.0 mm e.s.) was chosen. Results without chemical treat-
ment indicated average SS removals of 65 percent. The performance of the
system decreased as the flux increased from 407 to 1628 1/min m2 (10 to 40
gpm/ft2). SS removal efficiencies of 90 and 95 percent were attained for
respective flux rates of 1017 and 326 1/min m2 (8 and 25 gpm/ft2) with the
addition of 1 mg/1 of polyelectrolyte. Typical filter influent SS ranged
from 114 to 301 mg/1. 8005 removals ranged from 23 to 62 percent without
chemical and 54 to 72 percent with the addition of polyelectrolyte. Phos-
phorus removals averaged 26 to 52 percent with influent P concentration of
0.71 to 0.76 mg/1. Oil and grease removals ranged from 32 to 50 percent.
Results were also presented for treatment with alum and polyelectrolyte.
Typical run lengths were 6 to 10 hours at 977 1/min m2 (24 gpm/ft2) with no
chemicals and 3 to 6 hours with polyelectrolyte. The filtration tests with-
out chemical addition were terminated by headless development while the poly-
electrolyte runs generally resulted in termination due to solids breakthrough.
Filtration studies of CSO at Syracuse (36) used filtration through
No. 3 anthracite, -16 +50 mesh clinoptilolite, and 3.2 mm (0.125 in) plastic
pellets (37). When employing alum and polymer treatment, SS removal rates
of 90 to 100 percent were achieved at application rates of 407 to 529 1/min
m2 (10 to 13 gpm/ft2). Phosphorus removal increased from 30 to 98 percent
as the A1:P molar ratio was increased from 0.5 to 3.5.
Backwash water requirement is a function of the filter media used.,
The Cleveland study (14) showed backwash requirements of 1.9 to 8.6 percent
of filtered flow with a median value of approximately 4 percent. Backwash
rates of 1261 to 3663 1/min m2 (31 to 90 gpm/ft2) were used with durations
of 4 to 25 minutes. It is generally agreed that filters designed for waste-
water treatment should incorporate both air scour and surface wash facili-
ties. The Syracuse studies using No. 3 anthracite recommended 5 minutes of
air scour at 1.2 m3/min m2 (4 scfm/ft2], 3 minutes of scour-backwash at 1.2
m3/min m2 (4 scfm/ft2) and 814 1/min m2 (20 gpm/ft2), respectively, followed
by 12 minutes of backwashing at 814 1/min m2 (20 gpm/ft2).
OUTLINE OF EXPERIMENTS
The dual-media high-rate filter (DMHRF) experiments included evalu-
ations of the effects of hydraulic loading and chemical treatment on per-
formance. Flux rates of 407, 610, 814 and 1017 1/min m2 (10, 15, 20 and 25
gpm/ft2) were employed. Chemical treatments included: no chemicals, poly-
electrolyte only (1 mg/1 - Nalcolyte 676) and alum (30 mg/1) plus poly-
electrolyte (1 mg/1).
76
-------
The swirl separator effluent was used as influent to the DMHRF, Since
several chemical treatments were employed on the swirl separator system,
DMHRF performance is related to the upstream..swirl treatment as well as
the chemicals applied to the filter influent. Table 22 is a summary of
the flux rates and chemical treatments associated with each filter run,
TABLE 22. DMHRF OPERATING CONDITIONS
Run No.
5-1
"
11
6-1
11
6-2
"
n
7-1
"
"
7-2
"
11
7-3
n
"
7-4
n
it
8-1
"
"
8-2
"
"
8-3
11
n
9-1
n
n
9-2
n
"
9-3
n
n
9-4
n
n
Filter No.
1
2
3
1
2
?
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
9 Chemicals On Chemicals On
Flux (gpm/ft^) Swirl Separator* DMHRF*
25 None None
10
20
25
10
20 ' || ||
15
10
25
10
20
20
15
10
10
25 " "
15
15
15
15
25 Polymer "
10
20
20
15
10
10
25
15
25
20
10 " " i
10
15
25
20
10
15
25 " Polymer
20
10 " »
77
-------
TABLE 22. (continued)
Run No.
9-5
"
"
11-1
"
"
12-1
n
"
12-2
"
13-1
11
II
13-2
II
II
13-3
"
"
15-1
n
11
15-2
"
11
16-1
n
n
16-2
n
"
17-2
11
n
17-3
11
11
17-4
"
M
*Chemical
Filter No.
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
dosages: alum,
Flux (gpm/ft2)
25
20
10
15
15
15
15
15
25
15
15
15
25
25
o r*
25
20
20
20
15
15
15
25
25
25
15
15
15
25
25
25
25
25
25
15
15
15
15
15
15
15
15
15
30 mg/1 ; polymer,
Chemicals Chemicals On
Swirl Separator* DMHRF*
Polymer Alum + Polymer
n n
n n
Alum + Polymer "
n n
n n
" None
" Polymer
n ii
11 Alum + Polymer
" None
Phos. + Alum Alum + Polymer
+ Polymer
11 Polymer
" None
11 Alum + Polymer
" Polymer
" None
" Alum + Polymer
„ Polymer
„ None
„ Polymer
„ "
None
Phos. + Alum Polymer
+ Polymer
n M
" None
n ii
n n
n ii
" Polymer
n n
n n
None "
n "
n n
ii ii
n n
n ii
" None
n ii
n ii
1 mg/1
78
-------
The filter media consisted of 0.9 m (3 ft) of Mo. 2 anthracite over
1.5 m (5 ft) of No. 1220 sand. Following storm No. 8, the filters were
regraded by hydraulically scalping the fines from the surface in an attempt
to attain longer run lengths. Sieve analyses indicated size distributions
of No. 2 anthracite (effective sizes and uniformity coefficients) for
samples taken from the top of the filters as shown on Table 23.
TABLE 23. SIEVE ANALYSIS OF FILTER MEDIA
Filter No. Effective * Uniformity
Size (mm) Coefficient
No. 2 Anthracite 2.7 1.30
a. before regrading
1 1.7 1.69
2 1.4 1.61
3 1.3 1.52
b. after regrading
1 2.1 1.48
2 1.8 1.39
3 1.7 1.35
*Since the samples were taken from the top of the hydraulically classified
bed, the effective size would be expected to be slightly finer than the
unclassified media.
Filter runs were terminated upon headless development of approximately
0.145 N/mm2 (21 psi), 14.8 m of water (48.5 ft water). Headlosses were
determined from pressure gauge readings taken at the top of the bed, and
at the locations of 61, 152, and 244 cm (24, 60 and 96 in) below the
top of the bed. Headlosses were corrected for static pressures at each
location.
OPERATING PROCEDURES
The filter units were prepared for service by backwashing at 80 to 90
percent bed expansion. Backwash was preceeded by air scour at 0.6-1.5
m3/min m2 (2-5 ft3/min ft2) plus'backwash at 2279 1/min m2 (56 gpm/ft2)
for five minutes followed by an additional 10 minute backwash at 2890 1/min
m2 (71 gpm/ft2).
Three parallel filters were operated with each run set. The units
initially contained clean water to prevent channel formation on start-up.
Flowrate was controlled by regulating a pump drawing wastewater from an
effluent sump. A float valve on the column effluent thus regulated flow
through the filter equal to the rate of sump withdrawal. Applied flowrate
was constant throughout each entire run.
79
-------
Pressure readings at each of four locations were taken every 15
minutes. Grab samples of influent, effluent and intermediate locations were
taken at 15 to 30 minute intervals. Intermediate samples were taken at
depths of 24 and 60 inches from the top of the media.
RESULTS
Figure 34 is a typical performance plot of data from the DMHRF system.
Headless and SS data are shown versus time. It is noted that the majority
of the headless occurred within the top 61 cm (24 in) of media. It is also
noted that a gradual deterioration of effluent quality was obtained toward
the end of this run. This is typical of the trend reported in the Cleveland
study (14) for treatment with polyelectrolyte.
Run Lengths
Figures 35 through 37 show run lengths versus applied flux for
several chemical treatment cases. In general, the results indicate the
classical trend of reduced run lengths at higher flux rates. It is noted,
however, that the upstream treatment (swirl separator) had a definite
impact on the run lengths attained. Use of polymer and alum + polymer
on the swirl separator unit tended to result in longer run lengths on the
DMHRF. There may be two reasons for the longer runs. First, longer runs
would be expected when lower SS concentrations are applied to the filters.
However, as noted in Section 6, the chemical treatments on the swirl unit
generally did not result in imporved performance across that unit. More
likely, the longer filter runs were associated with the effluent solids
from the swirl unit being chemically conditioned further ahead of the
filter units.
Specific Capture
Measurements of filter run lengths do not allow assessment of the
effects of changes in influent SS concentrations and the effects of attain-
ing greater removal efficiencies. For these reasons the use of specific
capture is a better indicator of performance.
Specific captures were determined by summing the incremental SS re-
movals across the DMHRF for the duration of'the filter runs. Results were
calculated as total kg (or Ib) of SS accumulated, per m^ (or ft^) of sur-
face area per run. Although the capture is expressed per unit of surface
area, this does not necessarily imply that solids are only captured at the
surface of the bed.
Figures 38 and 39 show specific captures versus flux rates. The most
significant point immediately evident from these figures is that specific
capture generally increases in most cases as flux rate is increased. It is
characteristic of deep-bed filters that higher flux rates promote deeper
penetration of solids into the interior of the bed and permit fuller
utilization of the filter volume. However, as demonstrated below, higher
flux rates also result in a greater rate of solids contamination of the
effluent, so that tradeoffs must be evaluated.
80
-------
40--
30"
~ 20--
o
2
PRETREATMENT!
Alum SAnionic Polymer
FILTER TREATMENT:
Alum 8 Anionic Polymer
x - af 24 Depth
• -at 60" Depth
•- at 96" Depth
8 9 10
x-Influent SS
•- Effluent SS
0 I
89 IO
TIME (MRS.)
FIGURE 34. TYPICAL FILTER (DMHRF) PERFORMANCE CURVES
Run No. 11-2-2. Flux = 15 gpm/ft2
81
-------
00
ro
6--
•4- -
£
*^
x
u
24-
Z
|" No Chem. on DMHRF
L- Polymer on DMHRF
No Ch«m. on OMHRF
V
10
A
1
FLUX (gpm/ft2)
-H
25
6--
4..
X
0
2+
Z
No Chem. on DMHRF
Polymer on DMHRF
No Chem. on
DMHRF
_J 1
10 15
FLUX (gpm/ft2)
20
-H
25
FIGURE 35. DMHRF Run Lengths. No chemical
treatment on Swirl Primary Separator
FIGURE 36. DMHRF Run Lengths. Alum + Polymer
Treatment on Swirl Primary Separator
-------
8-r
6--
4--
X .
t-
o
z
111
§2
OL
• ?No Ghent on DMHRF
A=-Polymer on DMHRF
ipAlumt Polymer on
DMHRF
Alum »Polymer
on DMHRF
10
15
20
FLUX (gpm/ft2)
25
FIGURE 37. DMHRF Run tenths. Polymer on Swi>l Primary
Separator
83
-------
5--
co .
J3 4
UJ
CE
QL
5
UJ
a.
CO
I o No Chemical Trtmt. on P/S
II • Polymer Trtmt. on P/S
III A Alum a Polymer on P/S
IV • Phos. a Alum a Polymer on P/S
1
•
20
25
30
FLUX (gpm/ft2)
FIGURE 38. DMHRF Specific Capture. No Chemical
Treatment on DMHRF.
CJ 5--
4--
UJ
CE
3
O.
3--
I A Polymer on DMHRF, Polymer on P/S
II D Alum a Polymer or DMHRF, Polymer on P/S
III A Polymer on DMHRF, Alum & Polymer on P/S
IV* Alum a Polymer on DMHRF, Alum 8 Polymer on P/S
V O Polymer on DMHRF, Phoa, Alum & Polymer on P/S
o
o
10 15 20
FLUX (gpm/ft2)
25
30
FIGURE 39. DMHRF Specific Capture.
Treatment on DMHRF.
Chemi cal
84
-------
Figures 38 and 39 demonstrate the impact of the chemical treatments
employed in the upstream swirl primary separator. Specific captures on
the order of 9.8 kg/m2 ( 2 lb/ft2) per run were attained when alum + polymer
were employed upstream. Comparison of Figure 38 to Figure 39 suggests that
upstream chemical treatment had more impact on DMHRF performance than the
chemicals applied directly ahead of the DMHRF. This points out the
importance of contact time for chemical conditioning of CSO solids.
SS Removal Rates
Figures 40 and 41 show the effect of flux rate on percent removals of
SS. In general, average percent SS removals decrease as the flux rate is
increased. Figure 40 represents results for DMHRF runs where no chemicals
were applied to the DMHRF. Figure 41 includes results for DMHRF runs employ-
ing chemical treatment. Again, the upstream chemical treatment on the swirl
unit shows more significant effect on DMHRF performance than the chemicals
applied to the DMHRF. SS removals generally ranged from 60 to 85 percent at
408 1/min m2 (10 gpm ft2) to 40 to 80 percent at 1018 1/min m2 (25 gpm/ft2).
Best removals were attained when alum plus polyelectrolyte were applied to
the swirl unit and/or the DMHRF.
Removal of Other Constituents
Statistical analyses of other parameters tested during the DMHRF runs
are included in Appendix D for influent and effluent samples. Results of
all tests of similar flux and chemical treatment (both swirl unit and DMHRF)
were grouped for'this analysis. Appendix D includes minimum, maximum,
average, geometric mean,and standard deviation for each data set. The
influent and effluent geometric mean (or median) data are compiled on Table
24 and median removals are listed for each set of flux and chemical treat-
ment employed.
VSS removals ranged from 30 to 61 percent without chemicals and 43 to
96 percent when chei.iicals were employed. 8005 removals ranged from 32 to 56
percent without chemicals and 20 to 92 percent with chemicals. TOC removals
were generally higher than COD removals. TOC removals ranged from 19 to 50
percent without chemicals and 23 to 68 percent with chemical treatment. COD
removals averaged 13 percent without chemicals and 42 percent with chemicals.
Oil and grease removals were less than 4 percent without chemicals
and ranged from 5 to 56 percent when chemical treatments were employed. TKN
removals ranged from 8 to 13 percent without chemicals and 1 to 49 percent
with chemicals. TIP removals of 7 to 34 percent were attained without
chemicals, while chemical treatments generally resulted in TIP removals of
20 to 89 percent. Effluent pH ranged from 6.8 to 7.2 when chemicals were
not employed and from 3.6 to 7.4 when chemicals were employed. Aluminum
reductions were 10 to 93 percent without chemicals and 12 to 94 percent
with chemical addition.
85
-------
8O-i-
60-
2 4O-
UJ
CE
CO
g
O •
co
UI20-
cn
co
O
Polymer Trtmt.
on P/S
= 0.37
No Chem.
on P/S
O.IO
= 0.16
Alum 8 Polymer
Trtmt.
O
O
o
A Phos.jAlum 8 Polymer on P/S
o No Chem. Trtmt. on P/S
• Polymer Trtmt. on P/S
• Alum 8 Polymer Trtmt. on P/S
10 15 20
FLUX (gpm/ft2)-
25
30
FIGURE 40. DMHRF Performance. No Chemical Treatment.
86
-------
o
o
8O_
60..
i
o
s
Ul
CC
40..
o
en
o
tu
Q
z
UJ
Q.
-------
TABLE 24. MEDIAN PERFORMANCE OF DMHRF
CO
CO
Treatment*
On
P/S DMHRF
NC
NC
NC
NC
NC
PO
PO
PO
PO
PO
PO
PO
PO
PO
PO
AP
AP
AP
AP
AP
AP
AP
AP
AP
NC
NC
NC
NC
PO
NC
NC
NC
NC
PO
PO
PO
AP
AP
AP
NC
NC
NC
PO
PO
PO
AP
AP
AP
Flux
gprn/ff1
10
15
20
25
15
10
15
20
25
10
20
25
15
20
25
15
20
25
15
20
25
15
20
25
Inf.
mg/1
58.8
56.1
70.5
53.6
142.7
203.4
187.4
240.3
196.5
229.2
217.4
217.4
185.6
185.6
185.6
104.6
192.6
87.9
98.4
192.6
161.1
152.6
192.6
205.7
SS
Eff.
mg/1
25.3
24.5
38.9
31.3
28.2
45.8
31.9
85.5
57.8
78.7
117.1
119.5
39.8
66.1
80.1
40.1
114.1
52.4
7.7
47.7
8.1
42.9
62.5
82.3
Rem.
56
56
45
42
80
77
83
64
71
66
46
45
79
64
57
62
41
40
92
75
95
72
68
60
Inf.
mq/1
26.6
26.6
30.9
25.1
82.4
61.9
54.6
80.5
57.9
71.4
70.1
70.1
35.9
35.9
35.9
40.2
79.8
31.3
38.4
79.8
54.0
54.4
79.8
85.6
VSS
Eff.
JUS/ "I
10.5
13.2
16.9
17.5
18.4
14.3
11.1
30.1
17.6
21.3
39.9
34.0
6.8
9.1
18.9
15.5
42.9
14.3
2.3
17.0
2.3
15.6
23.5
35.8
Rem.
61
50
45
30
78
77
80
63
70
69
43
51
81
75
47
61
46
54
94
79
96
71
71
58
Inf.
mq/1
15.3
16.0
17.7
12.5
76.5
26.7
24.9
24.0
28.9
12.6
12.2
11.5
11.5
11.5
27.6
21.4
27.9
27.6
27.6
21.4
29.5
23.1
21.4
34.7
BOD5
Eff.
mq/1
6.67
10.90
10.00
7.50
6.00
7.70
5.80
19.10
6.80
17.40
19.50
17.10
24.30
17.20
TOC
%
Rem.
56
32
44
40
92
71
77
20
76
37
30
Inf.
mg/1
18.8
17.8
20.7
19.5
35.7
32.5
29.8
42.4
30.4
37.2
37.4
37.4
33.1
33.1
33.1
34.1
53.0
26.8
31.4
53.0
39.7
46.2
53.0
43.0
Eff.
mq/1
13.4
12.6
10.3
15.7
18.0
11.3
9.4
17.2
11.9
17.1
22.3
24.1
15.1
20.3
19.4
24.8
39.6
20.2
12.3
29.1
14.0
19.0
31.2
33.0
%
Rem.
29
29
50
19
50
65
68
59
61
54
40
36
54
39
41
27
25
25
61
45
65
59
41
23
*NC - no chemical treatment
PO - polymer treatment only
AP - alum + polymer treatment
(continued)
-------
TABLE 24. (continued^
Treatment*
COD
0 & G
TKN
TIP
00
ID
P/S
NC
NC
NC
NC
NC
PO
PO
PO
PO
PO
PO
PO
PO
PO
PO
AP
AP
AP
AP
AP
AP
AP
AP
AP
On
DMHRF
NC
NC
NC
NC
PO
NC
NC
NC
NC
PO
PO
PO
AP
AP
AP
NC"
NC
NC
PO
PO
PO
AP
AP
AP
Flux
gpm/ft2
10
15
20
25
15
10
15
20
25
10
20
25
15
20
25
15
20
25
15
20
25
15
20
25
Inf.
mg/1
18.7
17.3
20.7
18.5
20.4
15.2
53.5
20.4
Eff. %
mg/1 Rem.
17.5 5
13.4 23
18.2 12
18.8
17.0 17
13.7 10
30.9 42
22.4
-
Inf.
mg/1
58.0
55.6
27.6
40.8
31.6
27.6
40.8
30.8
37.4
40.8
86.0
Eff.
mg/1
55.8
53.4
24.4
26.8
18.0
12.1
20.0
15.6
24.0
40.8
%
Rem.
4
5
12
34
43
56
51
50
41
53
Inf.
mg/1
0.95
0.91
1.19
1.03
4.10
2.80
2.80
2.20
2.80
2.03
1.83
1.83
2.23
2.23
2.23
3.94
8.91
2.90
4.03
8.91
2.76
4.82
8.9
8.2
Eff.
mg/1
1.10
2.10
1.03
1.38
3.40
1.80
1.42
1.80
1.68
1.72
1.69
1.82
1.81
1.78
1.75
3.50
7.82
2.06
3.36
7.90
2.40
2.80
8.30
8.05
%
Rem.
13
17
35
49
18
40
15
8
1
19
20
22
11
12
29
17
12
13
42
7
2
Inf.
mg/1
0.14
0.12
0.16
0.15
0.29
0.56
0.61
0.67
0.51
1.34
1.34
1.34
1.49
1.49
1.49
0.45
2.27
0.20
0.42
2.27
0.85
0.89
2.27
1.60
Eff.
mg/1
0.13
0.17
0.10
0.15
0.23
0.33
0.22
0.30
0.20
0.37
0.22
0.75
0.58
0.19
0.23
0.32
1.50
0.27
0.09
0.67
0.23
0.10
0.99
1.28
of
/o
Rem.
7
34
22
41
64
55
60
72
84
44
61
87
85
29
34
79
70
73
89
56
20
*NC - no chemical treatment
PO - polymer treatment only
AP - alum + polymer treatment
(continued)
-------
TABLE 24. (continued)
10
o
Treatment*
On
P/S DMHRF
NC
NC
NC
NC
NC
PO
PO
PO
PO
PO
PO
PO
PO
PO
PO
AP
AP
AP
AP
AP
AP
AP
AP
AP
NC
NC
NC
NC
PO
NC
NC
NC
NC
PO
PO
PO
AP
AP
AP
NC
NC
NC
PO
PO
PO
AP
AP
AP
Flux
gpm/ft2
10
15
20
25
15
10
15
20
25
10
20
25
15
20
25
15
20
25
15
20
25
15
20
25
Inf.
7.01
7.16
6.89
6.94
6.92
7.16
7.20
7.16
7.10
7.35
7.30
7.30
7.19
7.19
7.19
6.23
4.07
6.53
6.08
4.07
6.18
5.51
4.07
3.40
PH
Eff.
7.03
7.20
7.08
6.80
7.00
7.25
7.14
7.28
6.95
7.40
7.42
7.28
7.11
7.37
7.41
6.38
4.15
6.51
6.57
4.15
6.42
6.64
4.10
3.60
Al
Inf. Eff.
mq/1 mq/1
0.70 0.52
0.45 0.03
0.86 0.51
0.72 0.65
0.60 0.05
2.53 0.71
3.10 1.90
1.52 0.82
2.60 0.16
2.53 0.85
2.70 1.55
2.70 1.56
1.83 0.77
1.83 1.83
1.83 2.23
16.55 12.10
96.00 80.50
10.82 6.97
12.17 4.63
96.00 67.10
12.88 7.56
33.63 3.97
96.00 76.20
98.90 87.00
Rem
26
93
41
10
92
72
39
49
94
66
43
42
58
27
16
38
76
30
41
88
21
12
*NC - no chemical treatment
PO - polymer treatment only
AP - alum + polymer treatment
-------
SECTION 10
ACTIVATED CARBON ADSORPTION
BACKGROUND
The polishing of the effluent from the flocculation/sedimentation (F/S)
and dual-media high-rate filtration (DMHRF) processes may be desirable and
necessary to provide a secondary quality overflow effluent with respect
to BOD5 during wet-weather periods. Polishing of dry-weather flows at the
VanLare plant may also be a direct benefit of having facilities designed
to serve a dual purpose. The carbon facilities would be available to pro-
vide additional BODs removal capability for dry-weather flows. During wet-
weather conditions the carbon facilities could be switched over to provide
treatment of the effluent directly related to either the CSO treatment
tanks (flocculation/sedimentation basins) or, in the event of future plant
expansion, the high-rate filtration process.
OUTLINE OF EXPERIMENTS
Evaluations of the carbon adsorption system were very limited. An
outline of the experiments is presented in Table 25.
TABLE 25. ACTIVATED CARBON OPERATING'CONDITIONS
Storm No. Influent Origin Detention Time (min)
13
16
17
DMHRF
F/S
F/S
45.0
13.5, 19.3, 30.0
13.5, 19.3, 30.0
Investigations conducted during Storm No. 13 were performed on filter
effluent applied to the carbon columns at a rate of 0.19 1/s (3 gpm), which
provided a detention time of 45 min at a surface flux of 57.4 1/min m2
(1.41 gpm/ft2). BODs removal rates-.were evaluated for Storm No. 16 over a
lower range of detention times (13.5, ,19.3 and 30.0 min) with surface flux
at 17.1-38.3 1/min m2 (0.42-0.94 gpm/ft2). These investigations were per-
formed on the effluent from the F/S basin operating at 61.2 m3/day m2
(1500 gpd/ft2) and chemically treated with alum and polymer.
BOD removal rates for Storm No. 17 were also evaluated over the same
range of detention times and surface flux for Storm No. 16 and,at a hydrau-
lic loading rate of 8-1.6 m3/day m2 (2000 gpd/ft2) on the F/S basin.
91
-------
RESULTS
The major goal of pilot testing of the carbon adsorption system was
to compare BOD5 removal rates with detention time. 8005 removal results
associated with Storm Nos. 16 and 17 are presented in Figures 42 and 43,
respectively. Figure 42 showed a significant improvement in the removal of
BOD5 when the detention time was increased from 13.5 to 19.3 minutes. No
improvement, however, was experienced when the detention time was further
increased to 30 minutes.
The results depicted in Figure 43 suggest that for Storm No. 17,
within the range of detention times investigated, variation in the
detention time had minimal effect on the BODs removal efficiency of the
carbon facilities. The disparity between these results and those attained
for Storm No. 16 may be attributed to the different influent BODs levels
experienced in each storm. Influent BODs in Storm No. 16 ranged from 16
to 46 mg/1 while those associated with Storm No. 17 ranged from 52 to
79 mg/1.
BOD5 removal results for Storm No. 13 are shown in Figure 44.
Influent BODs experienced during this investigation were similar to those
experienced in Storm No. 16. A comparison of the results from these two
storms indicates that there was no enhancement in the BODs removal
efficiency when the detention time was increased beyond 30 minutes. This
shows that for an influent BODs range of approximately 15 to 50 mg/1, there
appears to be an optimum detention time for 6005 removal between 13.5 and
30.0 minutes.
92
-------
100-
I70
UJ
£C
n
o
o
m
Storm No. 16
Influent-Flocculotlon/Stdfmtntatlon
D.T. _FLUX
I • 13.5 mln. 0.42 gpm/ft2
II • 19.3 mln. 0.61 gpm/ft2
IDA 30.0 mln. 0.9 4 gpm/ft2
10
zo
SO
40
INFLUENT BODc
90
(mg/l)
60
•o
FIGURE 42. BOD5 Removal with
Influent BOD5 concentration
Carbon Adsorption. Low
too • <
I
UI
X.
90 ..
O
o
ffi
II
Storm No. 17
Influent -Flocculotion/Sedimentotion
D.T. FLUX
I • 13.5 min. O.42 gpm/ft2
II • 193 mln. O.6 I gpm/ft2
III A 3C.O min. O.94 gpm/ft2
so
60
INFLUENT BOD5
(mg/l)
TO
•o
FIGURE 43. BODs Removal with Carbon Adsorption. Higher
Influent 8005 concentration
93
-------
9O . .
80 . .
1
Z
111
e
00
*
so ..
Storm No. 13
Influent DMHRF
Detention Time 45.0 mln.
Flux = 1.41 gpm/ft2
10 20
3O «O
SO SO
INFLUENT BOD5 (mg/l)
•o
FIGURE 44. BOD5 Removal With Carbon Adsorption
94
-------
SECTION 11
HIGH-RATE DISINFECTION
BACKGROUND
Studies on disinfection of simulated combined sewer overflow (SCSO)
in Syracuse, N.Y. (42) indicated that bacterial reductions occur
rapidly in the presence of free chlorine (Cl?). As the level of chlo-
rine demanding substances in wastewater increases, the amount of
free C12 available as a bactericide significantly reduces. Ridenaur
and Ingols (43) have hypothesized that chlorine dioxide (C102) has an
advantage over C12 as a bactericide since it is less reactive with
reduced substances present in wastewater.
The Syracuse studies (42) stated that the time of existence of
free C12 in the SCSO was very limited. They also reported that follow-
•ing the initial steep bacterial reduction brought about by the free
Cl2 » there followed a gradual decrease in the bacterial population
over an extended period of time. This second and lower rate of dis-
infection has been attributed to the combined form of Clo , which is
considerably less powerful as a disinfection agent than free C12- The
work involving ClOg revealed that rapid bacterial kills were obtained
within the first 30 seconds with little kill attained upon additional
contact. It was concluded that C102 itself is the disinfection species
and its decomposition product C102~has very little disinfecting capabil-
ity. It was also concluded that on a weight basis, C102 is approx-
mately twice as effective as Cl2 in reducing bacterial populations
to target levels. The Syracuse study (42) also observed an enhance-
ment in the disinfection process with a two-stage (sequential) addition
involving the application of C12 followed by C102 after an initial con-
tact time of 15 to 30 seconds. It was hypothesized that this may be
due to the regeneration of C10£ through the interaction of chlorite
ion (C102~) and C12.
Mixing has been shown to be a significant parameter in aTl dis-
infecting practices. In his report on a survey of a number of treat-
ment plants in the San Francisco Bay area, White (44) found that all of
the plants exhibiting good disinfection had good mixing.
The influence of mixing intensity on bacterial kills with C12 has
been demonstrated by Coll in (45) and Kruse (46). The use of the
velocity gradient (G) as a measure of the mixing intensity was first
95
-------
proposed by Camp and Stein (47) in 1943. More recently, the non-
dimensional expression, GT, has been associated with the effective
mixing intensity. In this expression, G represents the velocity grad-
ient and T is the nominal contact time in the disinfection chamber. Glover
(26,49) reported that disinfection performance can be considered a
function of the GT-parameter and suggested that as the value of GT
increases, disinfection is enhanced. Glover (49) also proposed the
use of initial flash mixing and corrugated baffles in the disinfection
chamber as an inexpensive means of increasing the GT value.
TEST PROGRAM
The intent of the disinfection program was to evaluate the
performances of C12 and ClOg in a high-rate disinfection application.
Since CSO treatment involves capital facilities that are not operated
full-time, it may be desirable to reduce the capital cost of the
facilities at the expense of operating and chemical costs. If C102
reacts faster and more effectively than Cl2, as has been experienced
in previously mentioned studies, the higher applied chemical cost
associated with C102 may be offset by lower capital costs.
As a result of the bench-scale studies on high-rate disinfection
conducted in Syracuse, N.Y. (42), two-stage disinfection with Cl2 and
C102 was evaluated in the Rochester pilot plant. It was considered
possible that a more cost-effective alternative to single-stage dis-
infection could be developed if there were an improvement in the level
of disinfection realized by two-stage application using Cl2 and 0102-
The disinfection program also sought tp define the type and ,level
of mixing which is necessary to optimize the disinfection process^ It
was anticipated that if an optimum level of mixing could be established,
it might prove advantageous to reduce capital costs by lowering process
contact times.
The equipment involved in performing the disinfection studies is
presented in Section 4. Testing was conducted in three parts. During
storm events, the three disinfection systems were operated at three
different dosage rates with all other conditions being identical. This
allowed for the evaluation of the effect of the changes in chemical de-
mand during the storm which could be attributed to organic and nitro-
genous substances. This type of evaluation was conducted for both
single-stage and two-stage disinfection. The latter part of the test
program included the evaluation of different mixing conditions.
Following each storm, the disinfection systems were run using swirl
primary separator and/or microscreen effluents collected prior to and
following filtration. This allowed for further evaluations of the effects
of solids levels on disinfection. In addition, the post-storm dis-
infection allowed for the evaluation of a larger array of dosages, deten-
tion times, and mixing conditions. During the holding period the quality
of the stored wastewater remained relatively stable.
96
-------
Part three of the disinfection studies included a number of tests
utilizing dry-weather flow. These permitted the supplementary evaluation
of the effect of chemical demand and solids loadings on the disinfection
process.
Operating conditions for the wet- and dry-weather tests are outlined
in Tables 26 and 27. The variables controlled in these tests were dosage,
detention time,and mixing intensity.
TABLE 26. SUMMARY OF WET-WEATHER DISINFECTION OPERATING CONDITIONS
Storm No. <
1-5
6
7
8
9
10
11
12
13
15
16
17
Influent
Origin
F/S*
F/S
DMHRF
F/S
DMHRF
F/S
DMHRF
F/S
DMHRF
F/S
F/S
F/S
DMHRF
F/S
DMHRF
F/S
DMHRF
DMHRF
CC §
DMHRF
CC
DMHRF
J.4.J-
D.T.tl1
(min )
1.8-5.6
1.8-5.6
1.1-8.4
1.8-5.6
1.1-8.4
1.8-5.6
1.1-8.4
1.8-5.6
1.1-8.4
1.8-5.6
1.8-5.6
1.8-5.6
1.1-5.6
1.8-5.6
1.8-5.6
1.8-5.6
1.1-5.6
1.8-5.6
1.3-3.8
1.1-3.4
1.3-3.8
1.8-5.6
Mixing
CORR**
CORR
CORR
CORR
CORR
CORR
CORR
CORR
CORR
CORR
CORR
CORR
CORR
t+ §§
FMT ,SFM ,
FM SFM ,
CORR
CORR
FM,SFM,CORR
CORR
FM,SFM,CORR
FM
FM -
Cl2 Dose
(mg/1)
0
0
0
0
0
0
0
2-19
6-19
4-
4-14
6-15
6-15
CORR 4
CORR 4
2
2
2
0
0
4,6,8
4,6,8
0-12
ClOp Dose
(mg/1)
2-12
3-10
3-10
2-9
2-9
2-8
0
0
0
0
0
0
0
0
1,2,3
1,2,3(C12
First)
2
2,4,6
0
4,6,8
0
0-6(C12
First)
(continued)
97
-------
TABLE 26
. (continued)
Influent
Storm No. Origin
18 F/S
p/5***
19 F/S
P/S
D.T.
(min)
1.8-5.6
1.8-5.6
1.8-5.6
1.8-5.6
C12 Dose
Mixing (mg/1)
FM,SFM5CORR 0
FM,SFM,CORR 0
2,4,6
FM,SFM,CORR 1,2,3
FM,SFM,CORR 1,2,3
C102 Dose
(mg/1)
5
4,6,8
0
1,2,3 (Cl2 First)
1,2,3 (C102 First)
*F/S - Flocculation/Sedimentation tttD.T. - Detention Time
tDMHRF - Dual-Media High-Rate Filter
§CC - Activated Carbon Columns
**CORR - Corrugated Baffles
tt-FM- Single Flash Mix
§§SFM - Sequential Flash Mix
***P/S - Swirl Primary Separator
TABLE 27. SUMMARY OF DRY-HEATHER DISINFECTION OPERATING CONDITIONS
Storm
No.
65
66
69
70
76
Influent
Origin
F/S
F/S
P/S
P/S
P/S
D.T.
(min )
1.8-5.6
1.8-5.6
1.8-5.6
1.8-5.6
1.8-5.6
Mixing
CORR
CORR
CORR
FM,SFM,CORR
FM,SFM,CORR
FM
C19 Dose
(mg/1 )
4,6,8
4,6,8
4,6,8
1-4
1,2,3
0
6^
C109 Dose
(mg71)
0
2,4,6
0
1-4 (C12 First)
1,2,3 (C102First)
4,6
n
SINGLE STAGE TREATMENT: CHLORINE VERSUS CHLORINE DIOXIDE
Multiple Regression Analysis
In order to evaluate the effects of the operating conditions and
variable wastewater quality it was considered desirable to develop a
mathematical model from the disinfection data. Multiple regression analysis
was thus conducted to statistically fit an equation to the pilot plant data
and to develop an optimal design configuration for treating CSO.
98
-------
The final equation selected for the multiple regression analysis was:
log kill = K1 (C) K2 (G) K3 (DT) K4 (10) K5 TKN + K6BOD
where log kill = log Influent F. Coli-log Effluent F. Coli
C = concentration of disinfectant, mg/1
G = velocity gradient, min
D.T. = detention time, min
TKN'= concentration of TKN, mg/1
BOD = concentration of 8005, mg/1
K] through KS = constants
The relation between D.T. and log kill was based on the'.first-order
relationship normally referred to as Chick's law (51), i.e.:
dN _ (2)
dt
where dN/dt = time rate of kill
k = rate constant
N = number of living microorganisms
Equation 2 may be rearranged (11) to yield:
t _
-------
C = concentration of disinfectant
n = coefficient of dilution
k" = constant,
I/
Equation 4 suggested the use of the factor C in the regression model
(equation 1).
Use of the term, G, in equation 1 was based on a review of Glover's
(49) work with high-rate disinfection of CSO. Examination of Figure 2
presented in reference 49 indicated a straight line relationship
between the log (log kill) and the log GT:
log (log kill) = m log GT (5)
where m = slope
GT = measure of mixing intensity, unitless.
Equation 5 can be further reduced to:
log kill = (GT)m = GT
where G = velocity gradient, t~
T = contact time
Most relationships developed in the literature between disinfectant
dosage and kill are presented in terms of disinfectant residual. Dis-
infectant residual is a function of dosage as well as contact time and
concentrations of reduced substances present in the wastewater (53).
Iiiorder to develop a mathematical relationship between kill and dosage
it was therefore necessary to include BODs and TKN data, as these para-
meters affect the ability to maintain a disinfectant residual.
In addition to the variables presented in Equation 1, a number of
other possible variables were tested in the multiple regression analysis.
Changes .in pH, temperature, suspended solids concentrations, and volatile
solids concentrations did not show statistically significant effects with
the disinfection system performance data.
Tables 28 and 29 present the results obtained from the regression
analysis conducted on the Rochester pilot plant data. The regression
coefficient values correspond to the exponential K values in equation 1.
The value of K-, in equation 1 is equal to 101 where i is equal to tne
intercept value. The magnitude of the regression coefficient gives an
indication of the relative importance of this term in the regression
expression. In the case of disinfection by £~\2> positive regression co-
efficients associated with the dosage, detention time, and velocity
gradient signify that as these values increase, the value of the log' kill
100
-------
also increases. The negative signs associated with the TKN and BOD indicate
that as these values increase the value of the log kill decreases.
TABLE 28. MULTIPLE REGRESSION ANALYSIS RESULTS FOR DISINFECTION BY
Standard Correlation Regression Std. Error Computed
Variable Mean Deviation X vs Y Coefficient of Reg. Coef. T Value
Log Ci 0.820
Log T 0.511
C2 3.80
Cs 36. 'I
Log (G) 4.43
0.193
0.202
2.56
25.0
0.193
0.605
0.110
-0.205
-0.503
-0.137
0.662
0.456
-0.00431
-0.00456
0.280
0.059
0.119
0.00433
0.00052
0.125
11.21
3.82
-0.996
-8.83
2.24
Dependent
Log (Log N]_) 0.466
N2
0.265
Intercept -1.37
Multiple Correlation 0.727
Std. Error of Estimate 0.183
Analysis of Variance for the Regression
Source of Variation
Attributable to Regression
Deviation from Regression
Degrees
of Freedom .
5
284
Sum of
Squares
10.74
9.57
Mean
Squares
2.14
0.0337
F Value
63.7
Total
289
20.3
TABLE 29. MULTIPLE REGRESSION ANALYSIS RESULTS FOR DISINFECTION BY C102
Standard Correlation Regression Std. Error Computed
Variable Mean Deviation X vs Y Coefficient of Reg. Coef. T Value
Log C-] 0.525
Log T 0.500
Ce 3.17
Cs 25.1
Log (g) 4.42
0.216
0.210
1.16
13.6
0.201
0.548
0.031
0.157
-0.00719
-0.0241
0.628
0.0781
0.00314
-0.00719
0.0502
0.0797
0.139
0.0139
0.00156
0.146
7.88
0.560
0.224
-4.v61
0.343
Dependent
Log(Log NI)0.399
N2
0.204
Intercept -0.0212
Multiple Correlation 0.698
Std. Error of Estimate, 0.150
(continued )
101
-------
TABLE 29. (continued)
Source of Variation
Attributable to Regression
Deviation from Regression
Degrees
of Freedom
5
88
Sum of
Squares
1.88
1.98
Mean
Squares
0.377
0.0225
F Value
16.7
Total 93 3.87
Multiple regression analysis with the CIO;? data also produced positive
regression coefficients for the dosage, detention time, and velocity
gradient and a negative regression coefficient for BOD5- The magnitude of
the standard error of the regression coefficient and the T value associated
with the TKN indicate that the effect of this parameter is fairly in-
significant.
The 'T1 value designates the degrees of confidence with which the
corresponding regression coefficients may be assumed to be statistically
significant. In the case of Cl2 disinfection, the 'T1 values for the
dosage, detention time, and BODs correspond to a degree of confidence
greater than 99.5 percent. The 'T1 value associated with the velocity
gradient, G, represents a degree of confidence greater than 95 percent,
while that associated with the TKN indicates less than a 70 percent degree
of confidence. The 'T1 values associated with BOD5 and the C102 dosage
indicate degrees of confidence greater than 95 percent each.
The 'T1 values for C102 disinfection associated with detention
time, velocity gradient, and TKN represent degrees of confidence lower
than 50 percent, 30 percent, 20 percent, respectively. These low values
indicate that variations of these parameters did not account for variations
in performance. The 'F1 value in the multiple regression analysis gives
an indication of the statistical significance of the entire regression
expression. 'F1 values associated with both the Cl2 and C102 regression
analysis represent degrees of confidence greater than 99 percent.
The final regression equations obtained from the Rochester pilot
plant data are as follows:
log kill = .0422(C)'662(G)-280(DT)-456(10)-0043™-00456BOD(6)
for Cl25 and
log kill = .952(C)-628(G)-0502(DT)-0781(10)-0031™-00719BOD (7)
for C102.
Lists of the multiple regression analysis input data and the regression
residuals for both Cl2 and C102 are presented in Appendix E.
102
-------
Illustrative Trends of the"Regression Model
Subsequent to their development, the regression models were used to
investigate the separate effects of the independent variables on the dis-
infection unit performance. Variation in unit performance was first
evaluated with respect to mixing intensity and detention time. Plots of
performance versus GT were developed using detention times of 1, 4, and 30
minutes. These detention times were selected in an effort to compare the
model results with the results Glover (49) obtained using a Cl2 residual
of 5 mg/1. A Cl2 dosage of 8 mg/1 in the Cl2 regression model roughly
corresponds to the Cl2 residual of 5 mg/1 used by Glover (49). The 4 mg/1
C102 dosage in the C102 regression model is roughly comparable to an 8 mg/1
Cl2 dose. Values for TKN and BOD5 used in this model analysis were the
average values-experienced in the Rochester studies.
Plots of Glover's (49) results along with the results obtained using
the regression models are presented in Figure 45. A comparison of the
curves for Cl2 shows similar trends. The slope of these curves indicates
that disinfection with Cl2 is greatly enhanced with an increase in mixing
intensity. The slope associated with the C102 curve implies that additional
mixing does not produce-a very significant change in bacterial reductions
when C102 is used as the disinfectant. Figure 45 also suggests that at very
low mixing intensities and short contact times, C102 is more effective than
in reducing bacterial populations.
Z
o
»-
o
Q
Ul
cr
o
o
tu
5T --
4--
3--
2--
•= BEAKER TESTS ( REE46) D.T. • I min.
•« CORRUGATED BAFFLES (REF.49)D.T..4min.
A- CONVENTIONAL ( REF. 49) .. . D.T-30min.
CI2 RESIDUAL-Sm^l
— REGRESSION MODEL
-------
Figure 46 is a plot of performance versus 6T for different dosages
of Cl2 using the average TKN and BOD5 values from the Rochester data.
Apparent in Figure 46 is the influence of mixing intensity on Cl2 disinfection
effectiveness. This figure also suggests that there is a more pronounced
effect on the performance when the Cl2 dosage is varied at the higher mixing
intensities.
A plot of performance versus 6T for various C102 dosages is presented
in Figure 47 for average TKN and BOD5 values. The slope of the curves
indicates that mixing intensity has only a slight effect on the effective-
ness of disinfection experienced with C102. The distance between the curves
suggests that increasing the C102 dosage produces similar increases in
bacterial kill, regardless of the mixing intensity. Comparison of Figures
46 and 47 shows C102 to be a better disinfectant than Cl2 at lower mixing
intensities.
The effect of changing BODs was the next area evaluated using the
regression models. Figure 48 presents plots of performance versus dosage
for both Cl2 and C102« BODs values used in the analysis corresponded'to
half the average, the average, and twice the average of the BODs values
encountered in Rochester. Comparing the plots shows that lower dosages of
C102 are employed relative to those required when using Cl2- The plots also
indicate that variations in the BOD5 level of the applied wastewater produce
significant changes in the disinfection effectiveness of Cl2 and C102, the
greatest sensitivity observed for C102-
O
F
o
D
LJ
o:
o
o
o:
o
5T
4--
3 -
2--
D.T - 40 minutes
TKN «3.6 mg/l
BOD » 31.5 mg/I
i 10 100 1000 IO.OOO lOOpOO 1,000,000
GT
FIGURE 46. Effect of Cl2 Dose in Regression Models
104
-------
z
o
I
Q
UJ
o:
_
o
o
u:
o
5T
4--
3 -
2 -
I --
D.T =4.0 minutes
TKN.= 3.6 mg/l ,
BOD = 3l.5mg/l
8mg/l-CI02
6mg/l -CI02
4mg/!-Cl02
2mg/!-C!02
10
100
iooo lo.ooo loo.ooo ipoopoo
_GT
FIGURE 47. Effect of C102 Dose in Regression Models
5-r
D.T » 2.0 minutes
GT = 15,000
TKN- 3.6 mg/l
D.T. » 2.0 minutes
GT = I5,000
TKN =3.6 mg/l
%J
1 4
O
o
UJ ,
oc 3
o
0 -
u:
J 1
0
BOD- 16 mg/l
BOD* 31.5 mg/l
. BOD= 63 mg/l
/-"^
./^ --''""'
XX^,^''^
------- -i - i i i i
2 46 8 lb
BOD=l6mg/l /
BOD=3l.5mg/l/
. BOD=63mg/j/
/
/ / ^
/ /*
/ /'
s
. /
i i i
2 k 6
/
^
s
^.^
8
CI2 (mg/l)
FIGURE 48. Effect of BOD5 in Regression Models
CI02 (mg/l)
105
-------
A similar sensitivity analysis was conducted using the TKN information.
Results of this analysis are presented in Figure 49. The set of curves for
both Cl;? and C102 indicates that variation in the TKN levels produces a
fairly insignificant effect on the bacterial reductions experienced with
either of these two disinfectants.
DT. «
GT-
BOD
2.O minutes
15,000
31.5 mg/l
z
o
o
D
O
UJ
4--
3-
_l
O 2
O *
Q I"
TKN -1.8 mg/l
TKN = 3.6 mg/l
TKN = 7.2 mg/l
Cl
6
(mg/l)
8
10
D.T.- 2.O minutes
GT- 15.000
BOD =31.5 mg/l
-TKN =1.8 mg/l
•TKN' 3.6 mg/l
•TKN= 7.2 mg/l
4-
468
CI02 (mg/l)
FIGURE 49. Effect of TKN in Regression Models
Figures 50 and 51 indicate the correlation between actual data and
performance predicted by the regression equations.
Cost/Benefit Analysis
Design factors such as G, D.T., and dose affect both capital and opera-
tion/maintenance costs as well as the performance of the disinfection treat-
ment facilities. It was the objective of the cost/benefit analysis to
determine the combination of design factors necessary to develop the most
cost-effective facility for the disinfection of combined sewer overflows.
Disinfection cost equations have been developed from the cost curves
presented in reference (54). Capital costs for the disinfection facilities
are presented as a function of the size of contact chamber and the amount of
106
-------
mixing provided.
index of 2480.
All costs have been adjusted to the ENR construction cost
6 T
5 -.
o
Q 3 4-
o
QL O •-
UJ * r
tf>
m
o
• •
• '. •
v.V
01234
PREDICTED LOG KILL
FIGURE 50. Predicted vs. Observed Bacterial Reductions for Chlorine
CAPITAL COST ($) = 10.229 (G)'566? (V)'65
where G = velocity gradient, sec" 3
V = volume of contact chamber, ft
(8)
When the capital costs are amortized over 20 years at an interest rate of
6 percent, the following yearly cost is attained:
CAPITAL COST ($/yr) = 0.89176 (G)*5668 (V)'65
(9)
Using the cost curve relating manpower requirements to the size of a rapid
mix basin, the following equation is developed:
MAN-HOURS = 0.04867 (OF)'78031(V)'633
where OF = number of overflow events per year
(10)
107
-------
6T
5 -
o
Q
UJ
en
03 2
o
•V y-
0 I 23456
PREDICTED LOG KILL
FIGURE 51. Predicted vs. Observed Bacterial Reductions for Chlorine Dioxide
For the purposes of the cost/benefit analysis, all overflows in the
Rochester area under the application of the two-year design storm were
considered eliminated and all wet-weather flow was assumed treated at
central facilities. It was also assumed that a rainfall of 2.5 mm (0.10
in) would produce enough runoff to warrant the operation of these facili-
ties. Averaging the number of days per year in which the rainfall in
Rochester exceeded 2.5 mm (0.10 in) (1961-1975). Equation 10 yields:
MAN-HRS/yr= 1.4431 (V) *633 (11)
Assuming a manpower cost of $15/hr, the final operation and maintenance
cost equation becomes:
0 & M COST ($/yr) = 21.646 (V)'633 (12)
Transformation of the material and supply cost curves produced the following:
M & S COST ($/yr) = 1.0768 (V)'6404 (13)
The expression relating costs to power requirements, assuming a charge of
$.025/KWH, was found to be:
PWR COST($/yr) =
257,875
(14)
108
-------
o
Chemical costs were based on a total yearly treatment of 17,600 m (4651
mil gal), which corresponds to the average yearly quantity of wet-weather
flow experienced in Rochester over the past ten years (1965-1975). Using
a cost for Cl2 of $0.10/lb, the chemical cost expression for Cl2 becomes:
C12 COST ($/yr) = 3878.9 (DOSE) (15)
where DOSE = disinfectant dosage, mg/1
Assuming a cost of $0.50/lb for C102 the cost equation becomes:
C102 COST ($/yr) = 19394.5 (DOSE) (16)
The cost equations were used to optimize facilities costs for a
selected set of operating conditions. These operating conditions included
the treatment rate, values of TKN and BOD5, and the desired bacterial kill.
Facilities costs were calculated for different detention times and
disinfectant dosages and the minimum cost was determined along with optimum
GT, dose, G, and D.T. values. In all of the optimization analyses, the
treatment rate was fixed at 1041 m3/day (275 mgd), which is the design rate
of proposed wet-weather facilities for Rochester. An evaluation of
facilities costs for three different quality conditions was performed using
the cost optimization program. This was done for both Cl2 and C102-
Minimum-cost facilities were developed for 3, 4, 5, and 6 log reductions
of F. Coliforms. Comparisons were conducted employing wastewater quality
representative of settled CSO, filtered CSO, and carbon adsorption effluent.
Comparisons of the minimum total costs for the optimum C12 and C102 systems
under these conditions are presented in Tables 30, 31, and 32. In most
instances, the C102 optimum systems exhibited lower detention times and GT
values than the C12 systems. However, because of the higher chemical costs
associated with C102» all of the Cl2 optimum systems exhibited much lower
total system costs than the C102 systems. This apparently indicates
that even in a high-rate application, utilization of C12 instead or C102 as
the disinfectant will produce a more cost-effective disinfection facility.
Examples of two cost optimizations are shown in Figure 52 illustrating
the trends obtained during the iteration procedure for determining the
optimum cost system.
It is noted that attainment of high-rate disinfection employs chlorine
dosages slightly higher than those normally encountered in conventional
disinfection. It is recognized that such effluents may require de-
chlorination to protect receiving water aquatic life. The cost of these
facilities has not been included in this analysis.
CHLORINE/CHLORINE DIOXIDE COMBINATIONS
Several tests were conducted during the Rochester studies to investigate
two-stage disinfection with both C12 and C102- It has been suggested (42)
that Cl2 added 15 to 30 seconds prior to the addition of C102, enhances
disinfection. It was hypothesized that after the C102 has been oxidized
109
-------
to C102~, any free Cl2 also present might oxidizu C102" back to C102- It
was further suggested (42) that this process may prolong the existence of
the more pp.tent disinfectant, ClC^j and thus enhance disinfection beyond
that expected by the sum of the respective concentrations of Cl2 and C102-
lO--
* ,
o
~ 5
5--
-GT Associated With Optimized
Cost
5mg/l
10 mg/.l
Log Reduction = 3.0
Treatment Rate =275 MGD
BODs = 59.5mg/l
TKN = 2.7 mg/l
FIGURE 52.
10 15 20 25 30
Detention Time (minutes)
Optimization Trends
35
Storm No. 69 involved a series of tests on dry-weather flow comparing
the disinfection performance of chlorine, chlorine dioxide, and various
combinations of the two. These tests were conducted with Cl2 added before
C102 and employed corrugated baffles. The results of the above tests are
presented in Figures 53, 54, and 55. Figure 53 shows bacterial kill as a
function of Cl2 and C102 doses for a 5.6 minute contact time. Iso-kill lines
are interpolated between the observed data. This presentation indicates that
C102 causes the same bacterial kill as chlorine at roughly half the dosage.
The fact that the iso-kill lines are nearly linear indicates that combination
treatment does not exhibit a synergistic effect; combination treatment simply
results in replacing a portion of one disinfectant with another.
Figures 54 and 55 represent the same test conditions but at contact
times of 3.8 and 1.9 minutes. Again, the iso-kill lines are nearly linear.
The slopes of the iso-kill lines presented in Figures 54 and 55 are
greater, demonstrating that the contact time is less critical with C102
than with C-
110
-------
TABLE 30. COST OPTIMIZATION. CSO-PRIMARY EFFLUENT*
3.0
Required Log Kill
4.0 5.0
6.0
Treatment With Chlorine
Minimum Cost ($/yr)
Optimum GT
Optimum Dose (mg/1)
Optimum D.T. (min)
OjDtimum G (sec'1)
Treatment With Chlorine
Minimum Cost ($/yr)
Optimum GT
Optimum Dose .(mg/1)
Optimum D.T. (min)
Optimum G (sec'1)
Dioxide
481,000
26,400
12.0
4.0
110
232,000
47,500
10.0
8.0
99
673,000
48,800
17.8
7.0
102
279,000
62,000
12.4
11.0
94
875,000
63,400
24.1
11.0
96
322,000
75,600
15.3
14.0
90
1,- 086, 000
86,400
31.0
15.0
96
362,000
89,800
17.8
17.0
88
At BOD,- = 59.5 mg/1
TKN = 2.7 mg/1
Treatment Rate = 275 mgd
TABLE 31. COST OPTIMIZATION. CSO-FILTERED EFFLUENT*
3.0
Required
4.0
Log Kill
5.0
6.0
Treatment with Chlorine Dioxide
Minimum Cost ($/yr)
Optimum GT
Optimum Dose (mg/1)
Optimum D.T. (min)
Optimum G (sec~l)
201 ,000
8,500
4.1
1.0
141
278,000
12,200
6.1
2.0
102
357,000
16,300
8.5
2.0
136
440,000
24,500
10.8
3.0
136
Treatment With Chlorine
Minimum Cost ($/yr)
Optimum GT
Optimum Dose (mg/1)
Optimum D.T. (min)
Optimum G (seer1)
169,000
30,900
6.4
5.0
103
203,000
39,900
8.1
7.0
95
234,000
48,500
10.1
8.0
101
263,000
57,000
11.7
10.0
95
* At BODs =12.6 mg/1
TKN =2.0 mg/1
Treatment Rate = 275 mgd
TABLE 32. COST OPTIMIZATION.
CSO-ACTIVATED CARBON EFFLUENT*
3.0
Required
4.0
Treatment With Chlorine Dioxide
Minimum Cost ($/yr)
Optimum GT
Optimum Dose (mg/1)
Optimum D.T. (min)
Optimum G (sec-1)
168,000
6,800
3.2
1.0
113
230,000
10,000
4.9
1.0
167
Log Kill
5.0
295,000
13,900
6.6
2.0
116
6.0
363,000
16,400
8.7
2.0
137
-,.,, (continued)
-------
TABLE 32. (continued)
3.0
Required Log Kill
4.0 5.0
6.0
Treatment With Chlorine
Minimum Cost ($/yr) 159,000
Optimum GT 28,300
Optimum Dose (mg/1) 6.0
Optimum D.T. (min) 4.0
Optimum G ( ec-1) 118
190,000
36,000
7.5
6.0
100
219,000
43,700
9.3
7.0
104
245,000
52,400
10.6
9.0
97
* At
=2.5 mg/1
TKN =2.0 mg/1
Treatment Rate = 275 mgd
112
-------
8
Flash Mixing Plus
Corrugated Baffles Mixing
Cl2 First,CI02 added 15-30 sec.
Note: Encircled Noa later
Represent "Log Kill"
Flash Mixing Plus
Corrugated Baffles Mixing
CI2 First,CIO added
15- 30 sec. later
Note: Encircled Nos,
Represent "Log Kill"
CI02 (mg/l)
FIGURE 53. Two Stage Disinfection Iso-Kill
Curves. Storm No. 69. Swirl Separator Effluent,
D.T. In Disinfection Basin - 5.6 minutes
C102(mg/l)
FIGURE 54. Two Stage Disinfection Iso-Kill
Curves. Storm No. 69. Swirl Separator Effluent,
D.T. In Disinfection Basin = 3.8 minutes
-------
8
2-
I-
Flash Mixing Plus
Corrugated Baffles Mixing
Cl2 First,CIO~ added 15-30
2 sec. later
Note; Encircled Nos,
Represent "Log Kill"
Flash Mixing Plus
Corrugated Baffles Mixing
Cl2 First,CJ02 added 15-30 sec.
Note: Encircled Nos.
Represent"Log Kill"
6
CI02 (mg/l)
FIGURE 55. Two Stage Disinfection Iso-Kill Curves.
Storm No. 69. Swirl Separator Effluent. D.T. in
Disinfection Basin = 1.9 minutes.
2 4
CI02 (mg/l)
FIGURE 56. Two Stage Disinfection Iso-
Kill Curves. Storm No. 17. DMHRF Effluent.
D.T. in Disinfection Basin = 5.6 minutes.
-------
Disinfection tests similar to those conducted during storm No. 69
were also performed for Storm No. 17. The results of these investigations
are presented in Figures 56, 57 and 58. Again, a series of iso-kill lines
were interpolated between the observed data. A comparison of these results
with those obtained for Storm No. 69 reveals that similar trends were
exhibited in both cases. The linear relations again illustrate no
apparent synergistic effect on the combination treatment. Similar bacterial
kills were again experienced with approximately half as much C102 as Cl2-
The effects of mixing and order of addition on two-stage disinfection
were examined during Storms No. 19, 69 and 70. Figures ^9 and 60 show
the results obtained when these investigations were conducted on dry-weather
flow (Storms No. 69 and 70). Wet-weather (Storm No. 17) results are
presented in Figures 61, 62 and 63. Both series of tests implied that
slightly higher bacterial kills are obtained when C102 is introduced prior
to the addition of Cl2- Examination of the results also disclosed that
in the majority of the tests, sequential flash mixing was more effective
in reducing bacterial populations than were the other two mixing conditions
(corrugated baffles and single flash).
A comparison of Figures 59, 60, '62 and 63 revealed that, at similar
dosage combinations, greater bacterial reductions were achieved during
the wet-weather investigations.
115
-------
8-
5.5 Log
CTi
Flash Mixing Plus
Corrugated Baffles Mixing
Cl2 First, Chadded 15-30
S6C«IOt6r
Note: Encircled Nos.
.Represent "Log Kill"
4
CI02 (mg/l)
FIGURE 57. Two Stage Disinfection Iso-Kill
Curves. Storm No. 17. DMHRF Effluent. D.T.
In Disinfection Basin = 3.8 minutes
Flash Mixing Plus
Corrugated Baffles Mixing
C\2 First, Chadded 15-30
' 2 sec. later
Note; Encircled Nos
Represent "Log Kill"
CI02 (mg/l)
6
FIGURE 58. Two Stage Disinfection Iso-Kill
Curves. Storm No. 17. DMHRF Effluent. D.T.
In Disinfection Basin = 1.9 minutes
-------
STORM No.70 CI02 First
Sequential Flash Mixing
Corrugated Baffles Mixing
Single Flash Mixing
O
h-
o
a
UJ
a:
o
o
2-.
23456
DETENTION TIME (Minutes)
STORM No.69 CI2 First
Sequential Flash Mixing
Corrugated Baffles Mixing
- Single Flash Mixing
§ 4 +
§
S
o:
13 34-
O
o
I 23456
DETENTION TIME (Minutes)
FIGURE 59. Comparisons of Order of Addition C12 - C102 Combinations. C102 = 2 mg/1; Cl2 = 2 mg/1
-------
STORM No. 70 CIO First
Sequential Flash Mixing
STORM No.69 Cle First
~~~~~—•"•—"• Sequential Flash Mixing
Corrugated Baffles Mixing
— Single Flash Mixing
Corrugated Baffles Mixing
Single Flash Mixing
z
o
o
4- •
o
o
2--
00
4+
b
o
£
o
o
(D
O
2--
I"
234
DETENTION TIME
-f
4-
4-
FIGURE 60.
56
(Minutes)
Comparison of Order of Addition Cl2-
1—
234
DETENTION TIME
+
—f-
5 6
(Minutes)
- C102 Combinations. C102 = 3 mg/1; Cl2 = 3 tng/1
-------
o
o
o
o
4--
2--
STORM No. 19 CI02 First
Sequential Flash Mixing
Corrugated Baffles Mixing
_ Single Flash Mixing
0
234
DETENTION TIME
5 6
(MinutesT
STORM No. 19 Cl£ First
- Sequential Flash Mixing
Ul
CL
_J
o
o
Corrugated Baffles Mixing
Single Flash Mixing
4..
4-
234
DETENTION TIME
5 6
(Minutes)
FIGURE 61. Comparison of Order of Addition C12 - C102 Combinations. C102 = 1 mg/1; Cl2 = 1 mg/1
-------
ro
a
g
o
o
o
Li:
§
STORM No.!9C!0'2 First
Sequential Flash Mixing
_•__•—Corrugated Baffles Mixing
, _ Single Flash Mixing
4
+
+
FIGURE 62.
23456
DETENTION TIME (MinutesT
Comparison of Order of Addition
STORM No. 19 CJ2 First
Sequential Flash Mixing
Corrugated Baffles Mixing
Single Flash Mixing
o
UJ
en
o
o
Lu
O
O
0'
234
DETENTION TIME
5 6
(Minutes)
C102 Combinations. C10-2 = 2 mg/1; Cl2 - 2 mg/1
-------
O
O
Q
O
O
4--
2--
STORM No. 19 C1O2 First
Sequenital Flash Mixing
Corrugated Baffles Mixing
-. . — Single Flash Mixing
—j 1 j—
234
DETENTION TIME
5 6
(MinutesT
5--
4..
a
UJ
o
o
3"
o
3 2+
STORM No. 19 CI2 First-
Sequential Flash Mixing
Corrugated Baffles Mixing
Single Flash Mixing
0'
4-
-J-
4-
234
DETENTION TIME
5 6
(Minutes)
FIGURE 63. Comparison of Order of Addition C1 -
C102 Combinations.
= 3 mg/1 ; Clg = 3 mg/1
-------
SECTION 12
SOLIDS HANDLING CONSIDERATIONS
SLUDGE THICKENING
The scope of the pilot plant investigations did not permit extensive
studies of optimization of sludge withdrawal rates from the primary systems.
The philosophy of operation of the swirl devices was to withdraw sludges
at a rate sufficiently high to prevent solids contamination of the
effluent. Sludge withdrawal techniques associated with the swirl devices
have been described earlier in Section 7. Rough approximations of the
effect of reduced draw-off rates may be gained by analysis of sludge
settleability curves, assuming that compaction would be attained in the
hopper of the swirl separator. Figure 64 shows sludge settleability
curves for the three primary treatment systems composite sludges acquired
during Storm No. 13. These tests, represent measurements of the compacting
sludge layer fn a. 1QOQ jnl graduated cylinder with quiescent settling.
F/S Sludge Initial Total Solldi (TS) • I.I %
Primary Swirl Separator Sludg* Initial TS-0.61%
• —
Swirl Degrltter Sludge Initial TS-0.32%
. TIME (mln)
FIGURE 64. CSO Primary Treatment Sludge Settling Curves (Storm No. 13)
122
-------
SLUDGE DEWATERABILITY
Dewaterability of CSO treatment residuals was also evaluated utilizing
sludge derived from the pilot plant primary treatment systems. Figures 65
and 66 show results of Buchner filtration tests of flocculation/sedimentation
(F/S) sludge for Storm Nos. 13 and 14, respectively. These sludges were
gravity thickened to 3.28 percent total solids (TS) (Storm No. 13) and 9.32
percent TS (Storm No. 14) prior to testing. A cationic polymer (Hercules
812) was used for flocculation. These Figures also show specific resistance
(a measure of dewaterability, sec2/g) as a function of polymer dosage.
Comparison of Figures 65 and 66 indicates that sludges derived from sedimen-
tation basins employing polymer treatment exhibit a lower specific resistance
than sludges originating from untreated sedimentation systems. These Figures
also indicate that polymer treated sedimentation sludge is more conducive to
dewatering than untreated sedimentation sludge.
Figures 67 and 68 illustrate Buchner filtration test results for com-
bined swirl degritter and swirl primary separator sludge from Storms No. 13
and 14, respectively. Examination of the results indicates that polymer treat-
ed swirl sludge dewaters much more easily than untreated swirl sludge.
The chemical requirement for dewaterability of the sludge may be affect-
ed by its septicity. Figures 69, 70 and 71 show the changes in pH and alka-
linity of pilot plant sludges upon storage at room temperature.
DISCUSSION
Sludge Volume and Characteristics
Table 33 gives a preliminary estimate of the quantity of sludge solids
produced in Rochester, N.Y. during 1975 (assuming the average CSO discharge
per storm).
This analysis assumes 100 percent treatment of the CSO and includes
grit, sludge and scum loadings. It should be noted that utilization of
biological treatment methods and/or the employment of chemical addition
in the selected treatment process would also add solids to the final
sludge volume.
TABLE 33. ESTIMATED LOADINGS FOR 100% CSO TREATMENT
No. Description . Quantity
I Average CSO per storm 3.2 x 105 m3 (85 mil gal)
II Average SS concentration of CSO 244 mg/1
III Average O&G concentration of CSO 47 mg/1
IV Estimated volume of screenings in CSO
(wet basis) >15m1/mJ (>2 ft3/mil gal)
cont. on pg»128
-------
ro
FIGURE 65.
Note'- Polymer Treat. w/Hercules 812
(Nalco 676 Added in F/S)
3.28% Initial TS
2.2 I % Initial VS
POLYMER DOSE (Ibs/dryton)
Sludge Dewaterability Tests: Storm
No. 13 F/S Sludge
0.5
Note: Polymer Treat. w/Hercules 812
(No Chemical Treat, in F/S)
2.70% TS
0.24% VS
LO
1.5
2.0
05 1.0 1.5
POLYMER DOSE (Ibs./dry ton)
FIGURE 66. Sludge Dewaterability Tests: Storm
No. 14 Swirl Degritter and Separator
Sludges
20
-------
9
10+
OJ
u
UJ
O
1
to
V)
tu
(E
a.
CO
ro
tn
Note: Polymer Treat. w/Hercutes 812
(Phosphorus, Alum 8 Nalco 676
added to P/S)
2.37% TS
1.64 % VS
tu
cr
a.
(O
1.0
zo
^30t
§
O
V) 20-r
V)
a
-4-
-+-
FIGURE 67.
LO 20
POLYMER DOSE (Ibs./dry ton)
Sludge Dewaterability Tests;
No. 14 Swirl Degritter and
Separator Sludges
Polymer Treat. w/Hercules 812
(No Chemical Treat, in F/S)
9.32 % TS
5.37 % VS
10
0.8
1.0-
c 20--
4-
-+-
Storm
0 0.2 0.4 0.6 0.8
POLYMER DOSE (Ibs./dry ton)
FIGURE 68. Sludge Dewaterability Tests:
Storm No. 13 F/S Sludge
LO
-------
x
Q.
§
o
o
ITSOr
1500--
1250-
1000-•
750--
500--
250-•
I 23456
CLOSED STORAGE AT 20°C
7-
6
5.
G/S Sludge
^ R/ifsiudge
i 1
. F/S Sludge
1 1 1
o
1200-•
1000 CLOSED STORAGE AT 20°C
800
600
400f
-fVS Sludge
1 1 1 1 1— 1
0 I 23456
TIME (days)
FIGURE 69. Sludge Aging Studies: Storm No. 14 F/S
Sludge
200" G/S Sludge
JVS Sludge
0 I 2345
TIME (days)
FIGURE 70. Sludge Aging Studies: Storm No. 13
Swirl Degritter and Separator Sludges
-------
8--
7
P/S Sludge
• i *H
F/S Sludge
4000r
3500-•
3000--
2500-•
to
o
o
-------
TABLE 33. (continued)
No. Description Quantity
V Estimated quantity of grit expressed as % of SS 9%-15.5%
VI Average No. of overflows anticipated per year 43
VII Estimated quantity of sludge anticipated from
an average storm (dry solids basis) 42,600-
48,000 kg
(94,000 -
106,000 Ib)
VIII Estimated quantity of O&G anticipated from an
average storm (dry solids basis) 3,800 kg
(8,400 Ib)
IX Estimated quantity of screenings anticipated 3
from an average storm 4.76 m ~
(>170 ft")
X Estimated quantity of grit anticipated from an
average storm (dry solids basis) 6,985 -
12,250 kg
(15,400 -
27,000 Ib)
XI Estimated current VanLare operation
(A) Sludge processed per day (dry solids basis) 38,900 kg
(85,700 Ib)
(B) Grit processed per day (dry solids basis) 7,500 kg
(16,600 Ib)
(C) Screenings processed per day (wet solids basis) 4,600 kg
(10.200 Ib)
The volatile percentage of solids found in the flocculation/sedimen-
tation system, swirl degritter and swirl primary separator sludges and the
pilot plant influent are listed in Table 34. The pilot plant sludges
averaged between 20 and 60 percent volatile solids. Envirex (55) reported
sludges exhibiting volatile fractions ranging from 25 to 63 percent; bio-
logical treatment showed the highest volatile fraction (about 60 percent),
while the physical and physical/chemical treatment processes exhibited
sludges with a 25 to 48 percent volatile fraction. The volatile percentages
of solids found in the pilot plant sludges were similar to the volatile
percentage of SS in Rochester CSO (Table 8).
128
-------
TABLE 34. ROCHESTER PILOT PLANT VOLATILE SOLIDS FRACTIONS
Storm No.
1
3
4
5
6
7A
7B
8
9
10
11
12
13
14
15
16
17
18
19
Influent
% Vol .
18.9
42.8
55.9
44.2
56.8
60.3
62.4
55.9
52.4
43.9
50.1
54.9
67.6
40.4
36.1
34.9
48.7
48.8
22.4
Swirl
F/S* Sludge
% Vol .
70.6
31.8
72.4
69.9
46.6
42.2
40.8
41.1
67.0
52.7
26.6
65.2
Degritter
Sludge
% Vol.
49.4
61.5
50.4
48.0
31.8
37.8
44.2
52.5
39.8
31.8
61.8
48.4
53.8
39.5
70.8
63.8
31.0
P/S** Sludge
% Vol.
63.5
83.0
13.0
8.2
16.6
28.8
32.0
24.8
10.3
49.3
40.8
46.2
32.2
50.6
42.2
32.0
F/S - Flocculation/Sedimentation
** P/S - Swirl Primary Separator
Possible toxic substances .in CSO sludges .include heavy metals (zinc,
lead, copper, nickel, chromium, and mercury), PCB and pesticides (pp1 ODD,
pp1 DDT, and dieldrin).- A list of the heavy metals encountered in the
pilot plant influent and the process effluents, which could contribute to
the heavy metal content in the process sludges, is presented in Table 35.
Another heavy metals analysis was performed on both the swirl degritter
and swirl primary separator sludges for Storm No. 17. The results of this
analysis are presented in Table 36. Also shown in Table 36 are the ranges
of heavy metals reported in the Envirex (55) study for sludges associated
with physical and physical/chemical treatment systems.
TABLE 35. PILOT PLANT CSO HEAVY METALS DATA*
Storm No. 8
Influent
Cd
mg/1
Cr
mg/1
0.03
Cu
mg/1
0.05
Hg
ug/l
Ni
mg/1
Pb
mg/1
Zn
mg/1
0.07
Storm No. 9
6/S Effluent 0.02
P/S Effluent <.01
P/S Effluent <.01
DMHRF Effluent <.01
<.01
<.01
<.01
<.01
0.04
0.06
0.04
0.04
0.59
<.01
<.02
0.03
<.02
0.03
<.02
0.00
<.02
<.02
0.17
0.11
(.continued)
-------
TABLE 35. (continued)
Cd Cr Cu
mg/1 mg/1 mg/1
Storm No. 10
Influent <.01 <.01 0.04
F/S Effluent <.01 <.01 0.04
G/S Effluent <.01 <.01 0.04
P/S Effluent <.01 <.01 0.02
Storm No. 11
Influent <.01 <.01 <.01
P/S Effluent <.01 <.01 <.01
DMF Effluent <.01 <.01 <.01
Storm No. 17
First Half
Influent <.01 <.01 <.01
Second Half
Influent <.01 <.01 <.02
F/S Effluent <.01 <.01 0.06
G/S Effluent <.01 <.01 0.08
P/S Effluent <.01 <.01 0.06
M/S Effluent <.01 <.01 0.06
Hg
ug/l
1.48
0.79
0.39
24.2
28.0
20.2
28.9
23.1
20.7
Ni
mg/1
<.02
<.02
<.02
<.02
<.02
<.02
<.02
<.02
<.02
<.02
0.03
<.02
<.02
Pb
mg/1
<.02
' 0-<.02
<.02
<.02
<.02
<.02
<.02
<.02
<.02
<.02
<.02
<.02
<.02
Zn
mg/1
0.07
0.11
0.15
0.12
0.13
0.10
* G/S - Swirl Degritter
P/S - Swirl Primary Separator
F/S - Flocculation Sedimentation
M/S - Micro Screen
DMHRF - Dual -Media High-Rate Filter
TABLE 36. HEAVY METAL CHARACTERISTICS
OF CSO
SLUDGES*
Description Cd Cr Cu
Hg
Ni
Pb
Zn
Storm No. 17
Swirl Degritter
Sludge 23.4 249.6 1235 0.78 147.4 1241 2345
Storm No. 17
Swirl Primary
Separator Sludge 15.8 386.1 4554 0.28 85.6 1658 1980
Physical Treat-t
ment Processes 50- 250 200-800 0.01-3.0 125-300 1200-2500 800-1200
Physical/Chemi-§
cal Processes 150-1700 250-500 2.0 -4.0 50-225 150-1600 700-1700
(continued)
130
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* Results reported as mg/kg of Dry Solids
t Taken from Envirex Report (55); processes included storage-sedimentation
and microscreening
§ Taken from Envirex Report (55); processes included screening/dissolved-
air flotation and dissolved-air flotation.
Summary of Envirex Study
CSO sludge characteristics vary as the influent solids concentrations
vary. It was thus necessary to assess alternatives which may prove useful
in the handling of storm generated discharge residuals. These alternatives
included (1) bleed-back of the residuals to the dry-weather treatment
facilities, (2) separate on-site residuals treatment and (3) land disposal
of treated or untreated CSO residuals.
The following presents a summary of conclusions developed in the
Envirex study (55). These conclusions are general and are not universally
applicable. Site factors specific to Rochester are discussed later.
I. Effect of Handling CSO Treatment Residuals by Bleed-Back to the Munici-
pal Dry-Weather Plant —
Investigations have indicated that bleed-back of raw CSO treatment
sludges to the municipal dry-weather plant is not practical.
The Envirex report generally indicated that bleed-back of CSO treatment
sludges to the dry-weather treatment plant over a 24-hour period would
grossly overload the plant hydraulically, solids-wise and/or organically,
resulting in appreciably decreased treatment efficiency and deterioration
of the plant effluent quality.
Extending the bleed-back period does not appear to be a viable
alternative. Even under favorable conditions(minimum design dry-weather
plant operating conditions, no diurnal dry-weather flow flucuations, etc),
a bleed-back period of up to one to two weeks or more would be required.
For less than favorable conditions (plant operating conditions between
minimum and maximum design operating conditions, significant dry-weather
flow fluctuations, etc), a bleed-back period greater than that indicated
under favorable conditions would be required. If the dry-weather plant
were operating at maximum design operating conditions, no bleed-back would
be allowable. Disadvantages of prolonged bleed-back periods include:
(1) the longer the bleed-back period is extended, the more unfavorable the
alternative becomes, (2) the capability of handling succeeding CSO treatment
residual events is materially reduced and (3) because of the anticipated
extended bleed-back period, provision would have to be made during sludge
storage to minimize-organic solids decomposition and prevent nuisance
conditions from occurring.
Bleed-back, of CSO treatment sludges directly to the dry-weather sludge
handling facilities over a 24 hour period would hydraulically overload the
131
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facilities, both solids-wise and organically. These overloads would be
expected to detrimentally affect the dewatering and stabilization performance
and treatment efficiency of the dry-weather sludge handling facilities.
The downgrading in treatment efficiency would be manifested in poorly
stabilized sludge for disposal and grossly deteriorated thickener effluents,
filtrates, supernatants, etc. for recirculation back to the dry-weather
treatment plant.
Since handling of CSO treatment sludges in the dry-weather sludge
handling facilities does not appear to be feasible, it becomes apparent
that CSO sludge must be separately treated. Two alternatives for separate
treatment are (1) on-site facilities and/or (2) additional parallel
facilities at the dry-weather plant.
Biological CSO treatment facilities should be located at sewage
treatment facilities to provide a continuous active biomass. Therefore,
CSO sludges originating from biological treatment should be separately
handled in separate parallel facilities at the dry-weather treatment plant.
Physical and physical-chemical CSO treatment facilities lend them-
selves more easily to remote satellite locations. However, because of the
problems involved in transporting the sludges from the remote CSO treatment
site to the dry-weather plant, CSO sludges derived from these systems
should be separately treated at on-site facilities.
II. Effect of Handling CSO Treatment Residuals by Separate On-Site Treat-
ment—
A. Generally, the process elements comprising a CSO sludge handling
system would include grit and low volatile solids removal, sludge dewater-
ing, stabilization and ultimate disposal. The specific sludge treatment
train utilized will be dependent upon the characteristics of the CSO con-
veyance system and the treatment method employed.
Grit and Low Volatile Solids Removal— Physical and physical-chemical
CSO treatment methods treat raw CSO with little or no preliminary treatment
for inert solids removal. It is therefore expected that CSO sludges from
physical and physical-chemical treatment will require provision for grit
and low volatile solids removal.
Biological CSO treatment methods are usually preceded by treatment
steps which remove the major portion of the grit and inert solids in the
raw CSO. Therefore, it is anticipated that CSO sludges from biological
treatment will not generally require provision for grit and low volatile
solids removal.
Stabilization— It is necessary to stabilize sludges before ultimate
disposal in order to minimize health hazards and nuisance conditions.and
further reduce mass. Stabilization processes and equipment include
anaerobic and aerobic digestion, heat treatment, composting and chemical
treatment (chlorine oxidation and lime treatment). Preliminary examina-
tion of these alternatives indicates that anaerobic disgestion and lime
132
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stabilization are more applicable to handling CSO sludges. Evaluation
and comparison of these two processes from an operating, cost, and land
requirement standpoint indicate the advisibility of employing lime stabili-
zation.
Dewatering and Volume Reduction -- Evaluation and comparison of gravity
thickening, vacuum filtration, centrifugation and incineration for appli-
cability in handling CSO sludge indicates that thickening and vacuum
filtration are the dewatering methods preferred for handling CSO sludges.
Ultimate Sludge Disposal -- Evaluation and comparison of ocean dumping,
drying and land disposal (by landfill, land spreading and/or land
reclamation) indicates that land disposal is the most applicable to
handling CSO sludges.
B.1 Estimation of costs for handling and disposal of CSO sludge using
landspreading and landfill as the ultimate disposal alternatives indicates
that although landspreading has a significantly lower initial investment,
landfills have significantly lower operating costs and appreciably lower
land requirements.
C. The logistics of operating and maintaining multiple CSO solids handling
plants at different locations throughout a city are formidable but not in-
surmountable. Similar logistics would be required for multiple CSO treat-
ment facilities from which the sludges to be handled are derived.
III. Considerations for Land Disposal Alternatives
The criteria that must be considered for any waste disposal operation
are:
1) land application method to be used,
2) required preapplication treatment,
3) collection and transportation of the waste to the site,
4) suitability of the area in terms of present and future land
uses in and around the site, proximity to surface waters, and
sensitive environmental areas,
5) amount of land required
6) effects of climate on the disposal operation,
7) site topography, geology, and existing vegetation,
8) surface runoff control,
9) necessary storage facilities,
10) waste distribution techniques,
11) treatment efficiency and pollutional loading constraints,
especially in regard to nitrogen and heavy metals,
12) possible growth of crops,
13) protection of public health, and
14) a site monitoring program.
Specific recommendations regarding some of the preceding criteria
ore outlined in the Envirex Report (55).
133
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Facilities .and Cost Estimates
Using the estimated sludge quantities given in Table 33 it is seen that
treatment of an average storm in Rochester over a 24-hr period would produce
a solids loading of 110-124 percent of the current solids loadings at the
VanLare plant. Preliminary estimates were compiled to assess the order
of magnitude of sludge handling facilities required for the Rochester
area. These estimates are presented on Table 37. This analysis assumed
that the CSO solids would be treated in a manner similar to that used
for treatment of dry-weather solids at the existing VanLare plant, i.e.,
sludge thickening,'storage, vacuum filtration, and incineration (Option
A). The cost of facilities to handle these solids was found to be in
the range of $4.5 million.
Implementation of the treatment train recommended by Envirex (55),'
which consists of gravity thickening, lime stabilization, vacuum filtration
and landfill (Option B), would substantially reduce these costs by
replacing the high costs associated with the incineration process with
much lower landfill costs. Based -on figures derived from the Envirex Re-
port (55), it is estimated that capital costs for lime stabilization and
land-filling are $96,000 and $533,000, respectively. Thus, sludge handling
facilities costs would be reduced to the range of $3.3 million.
While it appears that landfill ing of sludges is the least costly
alternative, there are several factors which might reduce requirements
for incineration. It is possible that existing incinerators at VanLare
might be capable of handling wet-weather sludges if some modifications
are incorporated. Detention of wet-weather sludges may permit attenuation
of vacuum filter and incinerator loadings. Lime stabilization should be
applied prior to detention. Inclusion of wet-weather sludges also
results in a sludge mixture that contains a higher ratio of primary/secondary
components. The improved dewaterability of this type of sludge may
enhance operation of the existing incinerators.
The cost estimates presented here assume centralized treatment of CSO
and CSO sludges. Volume I of this Report concluded that receiving water
constraints preclude the use of satellite CSO treatment; therefore, costs
of satellite sludge handling facilities have not been developed.
TABLE 37. SLUDGE PROCESSING FACILITIES
Project Cost Estimate (Mid-1976)§}tt
Incinerator Landfill
No. Treatment Operation (Option A) (Option B)
I. Lime Stabilization: 9,463 m3/day $96,000
(2.5 mgd) loading (1% sludge)
II. Thickeners*
Design Loading: 962,200 kg
(212,000 Ib) dry sol ids/day $1,570,000 96,000
III.
Sludge Storage
Design Loading:
(318,000 gal) -
1,204 m3
8% sludge
540,000
540,000
(continued)
134
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TABLE 37. (continued)
Project Cost Estimate (Mid-1976)
Incinerator Landfill
No. Treatment Operation (Option A) (Option B)
IV. Vacuum Filters**
Design Loading: l-in-20 yr max.
7,260 kg (16,000 Ib) dry solids/
day 590,000 590,000
V. Landfill: (5 yr: land purchase,
preparation) 533,000
VI. Sludge Incinerator
Design Loading: l-in-20 yr max.
7,260 kg (16,000 Ib) dry solids/
day
1.880.000
TOTAL PROJECT COST ESTIMATED$4.580,OOP $3.329.0.00
§ No special site conditions have been factored into estimate.
tt Equipment cost estimates are based upon references (54) and (56).
* Thickener costs include structure, mechanism, associated pumps and
piping.
** Vacuum Filter costs include all mechanical equipment, pumps, piping,
etc. These costs also include sludge conditioning tanks and an
allowance for a structure to house filter and controls.
t Sludge incinerator costs include incinerator, controls, and necessary
appurtenances including air pollution controls and ash handling equip-
ment. An allowance has also been included for a suitable structure to
house the facilities.
§§ Project costs include engineering, legal and miscellaneous fees plus
contingency allowance and estimated interest during construction.
135
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SECTION 13
CAPITAL AND OPERATING COST ESTIMATES
BASIS OF COST ESTIMATES
The cost'equations presented in. this section have been employed
to estimate capital, operating and maintenance costs for full-scale
flocculation/sedimentation-and swirl concentrator unit processes.
These equations were developed from cost curves presented by Benjes
(57), and are based on the application of the unit process to CSO.
Capital costs include structural, mechanical, piping, housing, labor,
contingency, electrical and instrumentation expenses. The capital costs
do not include the fees associated with land and site work, engineering,
legal and administrative services, fiscal concerns, and interest during
construction. Operating and maintenance costs include labor, power,
chemicals, miscellaneous supplies, administration costs, laboratory and
sampling, and yard maintenance. All .cost equations are adjusted to
November, 1976 according to the ENR Construction Cost Index of 2480.
CAPITAL COSTS
The following equation for estimating sedimentation basin capital
cost has been developed from reference 57,
SED CAP COST ($) = 238 (SA)0'817 . (1)
where SA = surface area, ft2.
The equation for estimating flocculation basin capital costs was
derived from the cost curve relating construction cost to basin volume and
is presented below:
FLOC CAP COST ($) = 1.27 (106) x (.438 + (2.29)(10~6)(FBV)) (2)
3
where FBV = flocculation basin volume, ft .
Employment of chemical treatment in the flocculation/sedimentation
process would require additional capital cost due to the installation of
chemical feed systems. Cost equations were therefore developed for both
alum and polymer feed systems since these chemicals were employed during
the Rochester studies. The respective capital cost equations for alum
treatment and polymer treatment were as follows:
ALUM CAP COST ($) = 1.127 (103) (28.8 + 0.0655 (ALPPH)1'09) (3)
136
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where ALPPH = alum feed rate, Ib/hr
and,
o
POLY CAP COST ($) = 1.12 (106) (.0081 + .0183 (POLPPH)'898) (4)
where POLPPH = polymer feed rate, Ib/hr
The cost equation for estimating swirl primary separator capital cost
has also been developed from reference 57 and modified by cost data from
LaSalle (12). The finalized form of the swirl primary separator capital
cost equation was:
SWIRL CAP COST ($) = 1620 (SA)0'779 (5)
where SA = surface area, ft2
OPERATION AND MAINTENANCE COSTS
A number of operation and maintenance costs are associated with the
flocculation/sedimentation and swirl concentrator processes. The equations
developed for estimating these costs are presented below.
Flocculation/Sedimentati on
Operating and maintenance requirements were developed for a
flocculation/sedimentation system consisting of a rapid mix basin, a
flocculation basin and a sedimentation basin. Estimates of operation and
maintenance labor costs associated with the rapid mix basin were derived
from the following equation:
R-M LABOR ($/yr) = .0156 (LC) (NOF) (V)'681 (6)
where LC = labor cost, $/hr
NOF = number of overflow events per year
V = basin volume, ft3
R-M = rapid mix
Rapid mix materials costs were assessed using the equation:
R-M MATERIALS ($/yr) = .844 (V)'688 (7)
and power costs were estimated from:
R-M POWER ($/yr) = .104 (PC) (NOF) (V) (8)
where PC = power cost, $/kwh
The above equation was developed assuming two days of operation per
overflow event.
Flocculation basin operating and maintenance labor costs were obtained
from the following equation:
137
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FLOC LABOR ($/yr) = ..000375 (LC) (NOF) (V) (9)
Material and supply costs for the flocculation basin were Calculated
using:
FLOC MATERIALS ($/yr) = 1.99 (V)'588 (10)
Operating and maintenance costs associated with the sedimentation
basin were derived from:
SED LABOR ($/yr) = 0.0211 (LC) (NOF) (SA)'875 (11)
where SA = surface area of basin, ft^
and materials costs were computed from:
SED MATERIALS ($/yr) = 8114 (SA/112500)0'7 (12)
Sedimentation basin power requirements were estimated from:
SED POWER ($/yr) = .0042 (PC) (NOF) (SA)'926 (13)
Employing chemical treatment in the flocculation/sedimentation process would
also contribute to its operating and maintenance costs. Listed below are
the equations which were developed for estimating these costs for both the
alum and polymer feed systems.
1) Manpower Requirements
ALUM FEED LABOR ($/yr) = .0452 (LC)(NOF)(ALPPH)>715 (14)
POLY FEED LABOR ($/yr) = 2.94 (LC)(NOF)(POLPPH)>167 (15)
2) Materials and Supplies:
ALUM FEED MATERIALS ($/yr) = 1.12 (47.5 + .914 (ALPPH)) (16)
POLY FEED MATERIALS ($/yr) = 1.12 (69.6 + 69.5 (POLPPH)) (17)
3) Requirements (assumes two days of operation per overflow event):
ALUM FEED POWER ($/yr) = (NOF) (PC) (12.2 + .00676(ALPPH)) (18)
POLY FEED POWER ($/yr) = (NOF) (PC)(7.52 + 4.05 (POLPPH)) (19)
4) Chemicals:
ALUM FEED CHEMICALS ($/yr) = 8.34 (MGTPY)(DOSE)(CC) (20)
POLY FEED CHEMICALS ($/yr) =8.34 (MGTPY)(DOSE)(CC) (21)
138
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where MGTPY = million gallons treated per year
DOSE = chemical dose, mg/1
CC = chemical cost, $/lb
Swirl Concentrator
The cost equation developed for estimating swirl concentrator labor
costs was:
SWIRL LABOR ($/yr) = (LC)(NOF)(12.f + .0082 (SA)) (22)
Estimates of materials and supply costs for the swirl concentrator
were computed from the following equation: '
SWIRL MATERIALS ($/yr) = 2028 (NUMUNITS)0'7 (23)
where NUMUNITS = number of swirl units
Miscellaneous Costs
Presented below is a list of equations which were developed to
estimate additional operating and maintenance costs which would generally
accompany any type of combined sewer overflow treatment facility.
1) Administration and general manpower:
A & G LABOR ($/yr) = 20 (LC)(Q)'460 (24)
where Q = treated flow, mgd
2) Administration and general materials and supplies:
A & G MATERIALS ($/yr) = 84.5 (Q)'470 (25)
3) Laboratory manpower (assumes 2 days of lab. work per overflow
event):
LAB LABOR ($/yr) = 17.4 (LC) (NOF) '(26)
4) Laboratory materials and supplies (assumes 2 days of lab.
work per overflow event and 4 samples/day):
LAB MATERIALS ($/yr) = 51.8 (NOF) (27)
5) Yardwork manpower (assumes yardwork area equal to 2.5 times
the equipment surface area):
YARD LABOR (.$/yr) =26.7 (LCl CSA/4QQ).'795 [27)
6) Yardwork materials and supplies:
YARD MATERIALS ($/yr.) = 15.4 (SA/400)'862 (28)
139
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Several other costs associated with CSO handling and treatment are
discussed in Section 14. These include overflow storage and transmission
facilities and sludge disposal costs.
140
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SECTION 14
COMPARISON OF ALTERNATIVES
COST/BENEFIT COMPARISON OF SWIRL PRIMARY SEPARATOR VERSUS FLOCCULATION/
SEDIMENTATION
Cost/benefit comparisons of four alternative primary systems for
treating CSO are presented below. These include: 1) flocculation/
sedimentation with no chemical treatment, 2) flocculation/sedimentation
with polyelectrolyte treatment, 3) flocculation/sedimentation with alum
and polyelectrolyte treatment, and 4) swirl primary separator with no
chemical treatment. All costs were adjusted to November, 1976 based on
the ENR Construction Cost Index of 2480. Comparisons of satellite versus
centralized treatment, and storage versus treatment optimizations are
presented in Volume I of this Report (3).
Performance equations defined percent SS removal at various hydraulic
loadings and influent SS concentration. However, the designs associated
with each hydraulic loading result in facilities with different capital
costs. The operation and maintenance costs associated with each system
are also different. For example, treatment with chemicals in the floc-
culation/sedimentation system results in improved performance but also
results in higher operating and maintenance costs. It was the intent of
the cost/benefit analysis to compare the cost and performance tradeoffs
resulting from variations in-system design and operating conditions.
Several design configurations were selected for each primary system and
capital costs and predicted performance were developed for each design
condition.
Operation and maintenance costs associated with each design were then
calculated from the operation and maintenance equations outlined in Section
13. The following assumptions were made to develop the performance and
cost data for an example facility: a) collection and attenuation of over-
flows with treatment at a central facility (VanLare STP in Rochester, N.Y.)
and a treatment rate of 275 mgd, b) 77 overflow events per year and c) a
total treated CSO volume of 4651 mil gal per year. The assumed treatment
rate was based on the design rate of the proposed wet-weather facilities
at VanLare. The number of overflow events and total CSO volume were based
on the available Rochester data for recent years.
The costs outlined in this Section include comparison of the primary
unit processes only. These costs do not include real estate nor facilities
for collection, transmission and storage of CSO, pumping, flow measurement,
preliminary screening, disinfection, sludge handling, treatment and disposal.
It was assumed that these items and associated costs would be common to each
of the primary alternatives. Disinfection and sludge handling costs have
been discussed in Sections 11 and 12. Costs associated with the collection,
transmission and storage of CSO and raw wastewater pumping are outlined in
141
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Volume I of this Report (3). That Volume also presents additional
treatment alternatives and cost optimizations of various CSO abatement
alternatives.
Capital, operating and maintenance costs, and predicted performance
results for various design conditions at two different influent SS levels
were developed.
Amortization is for a period of 20 years at an interest rate of 6
percent per annum. Total yearly treatment facility costs for two influent
SS conditions are plotted in Figures 72 and 73. These figures indicate the
estimated cost to achieve stated performance levels using alternative
systems. For example, Figure 73 indicates that for flows encountered dur-
ing first-flush overflows (c0 ^ 500 mg/1), three of the four alternatives
would be expected to provide 50 percent removal of SS at approximately the
same annual cost. For influent SS concentrations more representative of
average CSO conditions (c0 % 300 mg/1), Figure 72 indicates that swirl
primary separators are cost-competitive with flocculation/sedimentation
incorporating chemical treatment. For SS removals greater than 60 percent,
the only system capable of providing this treatment appears to be a
flocculation/sedimentation system employing alum and polyelectrolyte
treatment.
Examination of Figures 72 and 73 also indicates that in all cases,
the highest SS removals are attained utilizing a flocculation/sedimentation
system employing alum and polyelectrolyte treatment. These Figures
illustrate that large improvements in performance of the flocculation/
sedimentation system are attained by chemical treatment for a relatively
small increase in yearly cost.
SECONDARY LEVEL TREATMENT ALTERNATIVES
The addition of high-rate filters to the primary systems would result
in overall SS removals of 72 to 84 percent when filters are operated with-
out chemical treatment. Addition of high-rate filters that employ chemical
treatment following the primary systems would result in overall SS removals
of 86 to 92 percent. The capital cost associated with a high-rate
filtration system employing polyelectrolyte treatment is estimated to be
$6,300,000. This cost is based on a design flow of 1 x 106 m3/day
(275 MDG) and a surface, flux of 651 1/min m2 (16 gpm/ft2). The capital
cost has been developed from reference 57 and includes structural,
mechanical, piping, housing, labor, contingency, and electrical and
instrumentation expenses.
The addition of a carbon adsorption system to the primary treatment
processes would result in overall BODs removals of 92 to 98 percent.
Capital costs were developed for a carbon adsorption system consisting of
a carbon contactor and complete regeneration facilities (41). Carbon
contactor costs include carbon, miscellaneous tanks, piping, valves,
building costs,and instrumentation. Regeneration costs include a feeding
and conveying system, scrubber, afterburner, instrumentation storage,
dewatering, defining tanks,and building costs. The capital cost associated
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with the carbon contactor was based on a design flow of 1 x 106 m3/day
(275 mgd) and a contact time of 30 minutes. Regeneration costs were
developed for a furnace loading rate of 195 kg/m2 yr (40 lb/ft2 yr), a
carbon exhaustion rate of 60 gm/m3 (500 Ib/mil gal), 77 overflow events per
year and a total treated CSO volume of 17.6 x 106 m3 (4651 mil gal) per year.
Total capital cost of the carbon adsorption system was estimated".to be
$45,000,000.
MISCELLANEOUS COSTS
The capital costs associated with flow measurement and primary sludge
pumping were derived from cost curves presented in reference 57. These
costs include structural, mechanical, piping, housing, labor, contingency,
and electrical and instrumentation costs. The flow measurement cost was
based on a design flow of 1 x 106 m3/day (275 mgd) and was estimated to be
$64,000. Assuming a SS concentration of 209 mg/1 (average SS value of
Rochester pilot plant influent), a SS removal rate of 70 percent and a
sludge solids concentration of 2.5 percent, the sludge pumping cost was
estimated at $327,000.
Cost curves developed by Smith (59) were utilized to derive the
preliminary screening capital cost. The capital cost was estimated to be
$1,200,000. This cost includes a screen chamber, grit chamber (or swirl
degritter), overflow, and bypass chamber.
DISCUSSION
The above anlaysis applies only to the stated case of central treat-
ment at the the VanLare facility. Other areawide alternatives are dis-
cussed in Volume I of this Report (3). That Volume considers several
alternatives including: (1) storage and treatment of the first-
flush from all of the river overflow sites at wet-weather facilities
located at the VanLare plant and treatment of all post first-flush flows
with primary swirl devices; (2) storage and treatment of the total over-
flow at a treatment plant located on the Genesee River in the vicinity
of the lower falls; (3) storage and treatment of the total overflow at
a treatment plant located at the VanLare facility; (4) storage and
treatment similar to that expressed in Alternative 1, with the exception
that the post first-flush is not treated but directly discharged to the
river; (5) treatment of the entire overflow volume at each of the river
overflow locations using primary swirl concentrators; and (6) conveyance
of the river overflows to the Cross-Irondequoit Tunnel for storage and
treatment at the VanLare facility.
Optimization of storage versus treatment rates were also discussed
in Volume I of this Report. That Volume concluded that since organic load-
ings to the Genesee River are critical, the only alternative that could
be considered was collection and storage of the combined sewer overflow
with treatment by facilities at the VanLare location. A storage volume
of 0.2 x 10b m3 (60 mil gal) was recommended with a treatment rate of 1 x
10o m3/day (275 mgd) at the wet-weather facilities. In order to meet the
requirement of the EPA for primary treatment with disinfection, it appears
143
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IOOT
i
80-
60-
40-
20-
A« FLOCOJLATION-SEDIMENTATION: NO CHEM. TREATMENT
B'FLOCCULATION-SEDIMENTATION' POLYMER ONLY
C» FLOCCU-ATON-SEDIMENTATION: ALUM ' POLYMER
D« SWIRL PRIMARY SEPARATOR : NO CHEM. TREATMENT
X /
1.0 2.0
TOTAL YEARLY COST ($MM)
3.0
FIGURE 72. Cost-Performance Comparisons. Inf. SS=300 mg/1
oor
80
60
o
UJ
a:
40
20-
A' FLOCCULATION-SEDIMENTATION NO CHEM TREATMENT
6' FLOCCULATtON-SEDIMENTATION' POLYMER ONLY
C" FLOCCULATION-SEDIMENTATION; ALUM ' POLYMER
,1 D-SWIRL PRIMARY SEPARATOR : NO CHEM. TREATMENT
10 20
TOTAL YEARLY COST ($MM)
SO
FIGURE 73. Cost-Performance Comparisons. Inf. SS=500 mg/1
144
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that the most appropriate system would be flocculation/sedimentation
operated at 82 m^/day m2 (2000 gpd/ft2) with alum and polyelectrolyte
treatment followed by a high-rate disinfection process employing a 5
minute detention time and a mixing intensity (GT) of 35,000. Recommended
sludge handling would include thickening, lime stabilization, vacuum
filtration, and landfill disposal.
The alternatives evaluated in this Section were specifically limited
to swirl separators and flocculation/sedimentation with and without
chemical treatment. Based on receiving water quality objectives, as
discussed in Volume I of this report, the objective was to develop re-
commendations for primary treatment of CSO at Rochester using centralized
facilities. Other alternatives, such as dissolved air flotation, micro-
screening, dual-media high-rate filtration, or carbon adsorption, may be
viable processes for other locations, depending on effluent objectives.
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REFERENCES
1. Field, R. and A.N. Tafuri. Stormflow Pollution Control in the U.S.
Combined Sewer Overflow Seminar Papers. USEPA Report No. EPA-670/2-
73-077, NTIS No. PB 231 836, November 1973.
2. Field, R. Combined Sewer Overflows. Civil Engineering ASCE, 43, 2
February 1973.
* 3. Drehwing, F.J., C.B. Murphy, D.J. Carleo, and T.A. Jordan. Combined
Sewer Overflow Abatement Program, Rochester, N.Y.: Volume I, Abatement
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4. O'Brien & Gere Engineers, Inc. Combined Sewer Overflow Abatement
Program, Rochester, New York. Detailed Project Plan, USEPA Grant
No Y005141. October 1974.
5. O'Brien & Gere Engineers, Inc. Combined Sewer Overflow Abatement
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USEPA Grant No. Y005141. January 1976.
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7. Camp, T.R. Studies of Sedimentation Basin Design. Sewage and
Industrial Wastes, 25, 1, January 1953.
8. Dick, R.I. Folklore in Design of Final Settling Tanks. Presented
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3, 1973.
9. Theroux, R.J., and J.M. Betz. Sedimentation and Preaeration Experi-
ments at Los Angeles. Sewage and Industrial Wastes, 31, 1259,
November 1959.
10. Betz, J.M. The Valley Settling Basin Facilities, Los Angeles,
California. Sewage and Industrial Wastes, 29, 667, June 1957.
11. Kalbskopf, K.H. European Practice in Sedimentation, Water Quality
Improvement by Physical and Chemical Processes. University of
Texas Press, Austin, Texas, 1970.
12. Sullivan, R.H., et al. The Swirl Primary Separator: Development
and Pilot Demonstration. USEPA Report No. EPA-600/2-78-122, NTIS
No. Pending, December 1976.
146
-------
REFERENCES (continued)
13. O'Brien & Gere Engineers, Inc. Preliminary Design Additional
Treatment, Frank E. VanLare Wastewater Treatment Plant. December 1973.
14. Mebolsine, R., P.J. Harvey, and C-Y Fan. High Rate Filtration of
Combined Sewer Overflows. USEPA Report No. 11023 EYI 04/72, NTIS
No. PB 211 144, April 1972.
15. Smisson, B. Design, Construction and Performances of Vortex Overflows.
Proc., Symp. on Storm Sewage Overflows. Inst. Civil Eng., 6.B. 1967.
16. Sullivan, R.H., et al. The Swirl Concentrator as a Combined Sewer
Overflow Regulator Facility. USEPA Report No. EPA-R2-72-008, NTIS No.
PB 214 687, September 1972.
17. Sullivan, R.H., et al. Relationship Between Diameter and Height for
the Design of a Swirl Concentrator as a Combined Sewer Overflow
Regulator. USEPA Report No. EPA-670/2-74-039, NTIS No. PB 234 646,
June 1974.
18. Sullivan, R.H., et al. The Swirl Concentrator as a Grit Separator
Device. USEPA Report No. EPA-670/2-74-026, NTIS No. PB 233 964,
June 1974.
19. White, R.A. A. Small Scale Swirl Concentrator for Storm Flow. Ph.D.
Thesis, University of Wisconsin, Milwaukee.
20. Smisson, B. Swirl Concentrators in Combination Using Multiple Tanks
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21. Field, R. Design of a Combined Sewer Overflow Regulator/Concentrator.
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22. Field, R., et al. Treatability Determinations for a Prototype Swirl
Combined Sewer Overflow Regulator/Solids-Separator. Proceedings of
the Urban Stormwater Management Seminars, Atlanta, Georgia, November
4-6, 1975, and Denver, Colorado, December 2-4, 1975, USEPA Report No.
WPD 03-76-04, NTIS No. PB 260 889, January 1976.
23. Field, R. The Dual Functioning Swirl Combined Sewer Overflow
Regulator/Concentrator. Water Research, Vol. 9, Pergamon Press, 1975.
24. Sullivan, R.H., et al. The Helical Bend Combined Sewer Overflow
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PB 250 619, December 1975.
25. Neketin, T.H., and H.K. Dennis. Demonstration of Rotary Screening for
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No. PB 206 814, July 1971.
147
-------
REFERENCES (continued)
26. Glover, G.E., and G.R. Herbert. Microscreening and Disinfection of
Combined Sewer Overflows - Phase II. USEPA Report No. EPA-R2-73-124,
NTIS No. PB 219 879, January 1973.
27. FMC Corporation, Correspondence, June 24, 1976.
28. Maher, M.B. Microstraining and Disinfection of Combined Sewer
Overflows - Phase III. USEPA Report No. EPA-670/2-74-049, NTIS No.
PB 235 771, August 1974.
29. Phillips, T.G., and A.D. Bubp. The Effects of Prescreening Storm
Water and Combined Sewer Overflows. Presented at the Ohio WPCF
Conference, June 1975.
30. Keilbaugh, W.A., et al., Microstraininq - with Ozonation or
Chlorination - of Combined Sewer Overflows. Combined Sewer Overflow
Seminar Papers, USEPA Report No. 11020—03/70, NTIS No. PB 199 61,
November 1969.
31. Baumann, E.R., and J.Y.C. Huang. Granular Filters for Tertiary Waste-
water Treatment. JWPCF, 46, 1958, August 1974.
32. Tchobanoglous, G., and R. Eliassen. Filtration of Treated Sewage
Effluent. ASCE Journal SED, 96, 261, April 1970.
33. Lynam, B.T., et al. Tertiary Treatment at Metro Chicago by Means of
Rapid Sand Filters and Microstrainers. JWPCF, 41, 247, February 1969.
34. Storm Water Management Model, Volume 1 - Final Report. USEPA Report
No. 11024DOC07/71, NTIS No. PB 203289, July 1971.
35. DeFilippi, John A. Assessment of Alternative Methods for Control/
Treatment of Combined Sewer Overflows. Combined Sewer Overflow
Seminar Papers, USEPA Report No. 11020—03/70, NTIS No. PB 199 61
November 1969.
36. O'Brien & Gere Engineers, Inc. Nutrient Removal Using Existing
Combined Sewer Overflow Treatment Facilities. Draft Report. USEPA
Demonstration Grant No. S-802400, September 1976.
37. O'Brien & Gere Engineers, Inc. Nutrient Removal Using Existing Combined
Sewer Overflow Treatment Facilities. Bench Scale Study for Onondaga
County Department of Public Works, February 1975.
38. Cleasby, J.L., et al. Developments in Backwashing of Granular Filters.
ASCE Journal EED, 101, 713, October 1975.
39. Process Design Manual for Suspended Solids Removal. USEPA Report No.
EPA 625/1-75-003a, January 1975.
148
-------
REFERENCES (continued)
40. Process Design Manual for Carbon Adsorption, USEPA Report No. EPA
625/1-71-002a, October 1971.
41. Fornwalt, H.J. and R.A. Hutchins. Purifying Liquids with Activated
Carbon. Chemical Engineering, 73, 179, April 11, 1966.
42. Moffa, P.E., et al. Bench-Scale High-Rate Disinfection of Combined
Sewer Overflows with Chlorine and Chlorine Dioxide. USEPA Report No.
EPA-670/2-75-021, NTIS No. PB 242 296, April 1975.
43. Ridenour, G.M., and R.S. Ingols. Chemical Properties of C102 in Water
Treatment. J. Amer. Waterworks Ass., 40, 1207, 1958.
44. White, G.C. Disinfection Practices in the San Francisco Bay Area.
JWPCF, 46, 89, January 1974.
45. Collins, H.G., et al. Problems in Obtaining Adequate Sewage Disin-
fection. ASCE, Journal SED, 97, 549, October 1971.
46. Kruse, C.W., et al. The Enhancement of Viral Inactivation by
Halogens. Water and Sewage Works, 118, 187, June 1971.
47. Camp, T.R., and P.C. Stein. Velocity Gradient and Internal Work in
Fluid Motion. Journal of the Boston Society of Civil Engineers, 30,
219, 1943.
48. Process Design Manual for Upgrading Existing Wastewater Treatment
Plants. USEPA Technology Transfer, October 1974.
49. Glover, G.E. High-Rate Disinfection of Combined Sewer Overflow.
Combined Sewer Overflow Seminar Papers. USEPA Report No. EPA-670/2-
73-077, November 1973.
50. Pal in, A.T. Determining Chlorine Dioxide and Chlorite. J. Amer. Water
Works Ass., 62, 483, August 1969.
51. Chick, H. An Investigation of the Laws of Disinfection. Journal of
Hygiene, Cambridge, England, 8, 92, 1908.
52. Rich, L.G. Unit Processes of Sanitary Engineering. John Wiley and
Sons, Inc., New York, 1963.
53. Sykes, G. Disinfection and Sterilization. D. VanNostrand Co., Inc.,
New York. 1958.
54. Gulp, Wesner, Gulp. Estimating the Costs of Wastewater Treatment
Facilities. Draft Report for Commonwealth of Virginia, March 1974.
149
-------
REFERENCES (continued)
55. Huibregtse, K.R., et al. Handling and Disposal of Sludges Arising from
Combined Sewer Overflow Treatment, Phase II - Impact Assessment.
USEPA Report No. EPA-600/2-77-0536, NTIS No. PB 280 309, December 1977.
56. Van Note, R.H., et al. A Guide to the Selection of Cost Effective
Wastewater Treatment Systems. USEPA Report No. EPA-430/9-75-002,
July 1975.
57. Benjes, H.H., Jr. Cost Estimating Manual - Combined Sewer Overflow
Storage and Treatment. USEPA Report No. EPA-600/2-76-286, NTIS No.
PB 266 359, December 1976.
58. Water Treatment Plant Design, American Water Works Assoc., Inc.,
New York, N.Y. 1969.
59. Smith, R. Cost of Conventional and Advanced Treatment of Wastewater.
JWPCF, 40, 1546, September 1968.
60. Burns and Roe, Inc. Process Design Manual for Suspended Solids
Removal. Technology Transfer, USEPA Report No. EPA 625/1-75-003a,
January 1975.
61. Parker, H.W. Wastewater Systems Engineering. Prentice-Hall, Inc.,
New Jersey 1975.
62. Havens and Emerson, Ltd. Survey Scope Study for Wastewater Management
Program. Cleveland, Ohio, October 1972.
63. Huber, W.C., et al. Storm Water Management Model User's Manual -
Version II. USEPA Report No. EPA-670/2-75-017, March 1975.
64. Sullivan, R.H. et al. Field Prototype Demonstration of the Swirl
Degritter. USEPA Report No. EPA-600-2-77-185, NTIS No. PB 272 668,
September 1977.
65. Gupta, M.K. and R.W. Agnew, Screening/Dissolved-air Flotation
Treatment of Combined Sewer Overflows. Combined Sewer Overflow
Seminar Papers. USEPA Report No. EPA-670/2-73-077, NTIS No. PB 231
836, November 1973.
66. Parker, D.S., et al. Processing of Combined Physical-Chemical-
Biological Sludge. Presented at the 46th WPCF Conference, Cleveland,
Ohio, October 1973.
67. Imhoff, K. and G.M. Fair, Sewage Treatment, John Wiley and Sons, Inc.,
New York, 1941.
68. Keefer, G.E., Sewage Treatment Works, McGraw-Hill, New York, 1940.
150
-------
REFERENCES (continued)
69. Federation of Sewage and Industrial Wastes Assns. Sewage Treatment
Plant Design - Manual of Practice No. 8. 1959.
70. Great Lakes - Upper Mississippi Board of State Sanitary Engineers,
Recommended Standards for Sewage Works, 1968.
71. American Society of Civil Engineers. Sewage Treatment Plant Design -
Manual of Practice No. 8. 36. 1960,
72. Smith, R. Preliminary Design of Simulation of Conventional Waste-
water Renovation Systems Using the Digital Computer, US EPA Report,
1968.
73. Letter of D.A. Louma, US EPA Region II, to I, Brodell, Monroe County
Division of Pure Waters, dated November 3, 1972.
74. Black & Veatch Consulting Engineers,, Report on Comprehensive Sewerage
Study for the City of Rochester, NY, 1969,
\i
75. Teetor-Doban Consulting Engineers, Engineering Report, Irondequoit,
Bay Pure Waters District, Monroe Co., NY, December, 1968.
76. Lozier Engineers, Inc., Seelye Stevenson Value and Knecht and Erdman
Anthony Associates. Wastewater Facilities Plan, Volume IV subreports,
Combined Sewer Overflow Abatement Program. Rochester Pure Waters
District, Monroe Co., NY, December, 1975.
77. American Public Works Association, Standard Methods for the Analysis
of Water and Wastewater, Fourteenth Edition, 1975,
78. NERC, Manual of Methods for Chemical Analysis of Water and Wastes,
US EPA Report No. EPA-526/6-74-003, 1974,
151
-------
APPENDIX A
SS vs. Time PIots-Flocculation/Sedimentation
and Swirl Concentrators
Legend
I = Influent
F = Flocculation/sedimentation system effluent
G = Swirl degritter effluent
P - Swirl primary separator effluent
152
-------
ECO.
2SO
H
ISO.
3 100.
x
(2 50
0
STORM 1*01 - F/S,G/S,AP/S SYSTEMS
STORM «03 - F/S.G/S.AP/S SYSTEMS
153
-------
500 _
.•450
0300
250.
ISO
so
STORM «04 - F/S.G/S.dP/S SYSTEMS
3CO-
340.
260
".220
120.
100 .
i
i GO .
«0.
20
in
STORM w05 - F/S.G/S.&P/S SYSTEH5
154
-------
340
320
£300
lu
10 280
£260
fe2"0
£220
"-200
fclBO
<5
£]60
U_
J HO
£
7 120
1DO
BO
« 60
m <0
15 '
20
p
goo
650
ulBOO
In"750
\
ufeso
> 450
3
S
STORM w06 - F/S.G/S.4P/S SYSTEMS
STORM «07 - F/S,G/S,«P/S SYSTEMS
155
-------
5EO,
s
STORM «08 - F/S,C/S,&P/S SYSTEMS
700,.
STORM «09 - F/S,G/S,&P/S SYSTEMS
156
-------
STORM wlO - F/S.t/S.-SP/S SYSTEMS
STORM Ml - F/S.G/S.4P/S SYSTEMS
157
-------
700.
Si 050.
| MO
t 550
Uj
J4K>.
U.
in 400
u.
^350
-t
r-4
250.
3200
40
£|50
iy>
*"" |00
STORM
-------
HO
STORM #14 - F/S.C/S.&P/S SYSTEMS
1100
STORM «|5 - F/S,G/S,AP/5 SYSTEMS
159
-------
I! 00
, 1000
\tl
u.
IU
«> 300
o,
a~
J 800
is 700
it
o
it GOO
Ul
".- 500
u.
.J
u.
II
300..
200
100
STORM »16 - F/5,C/5,&P/5 SYSTEMS
STORM «17 - F/S,G/S,&P/5 SYSTEMS
160
-------
•JOO.
JO
£260
i 200
u_
t 180
£ 160
u.
i 140
100.
5 80..
20
STORM »18 -
SYSTEMS
1300,
1MO
"3 noo
i 1000.
tu 900
£ 700^
"V 600
U.
fe 500.
tt
400
„ 300
£ 200
m
tn
•• 100
STORM «19 - F/S,C/S,4P/S SYSTEMS
161
-------
APPENDIX. B
Statistical Analysis of Influent and Effluent Data
Flocculation/Sedimentation and Swirl Concentrators
Note: The tables in Appendices B, C and D were
developed by a generalized computer routine.
The number of significant digits displayed
does not reflect the accuracy of the
analyses.
Concentrations of all parameters except pH,
SETTS and F.Coli are expressed as mg/1. SETTS
concentrations are expressed as ml/1. F.Coli
concentrations are expressed as colonies/100 ml
162
-------
O'BRIEN t GERE ENGINEER), INC, LABORATORY DATA 9Y3IEH AUO la, 1976 10106
ROCHESTER CSO PP — PERFORMANCE OA1A •-• INFLUENT CSO (STOHM • 01)
PARAMETER POINTS MINIMUM MAXIMUM AVERAGE CEO, MEAN BID DEVIATION 9KEKNE33 KURI03IS
T3)
V33
13
VS
SETT3
BOOS
CUD
TUC
010
PH
TUN
IIP
AL
rcoLi
PARAMETER
193
V3S
T3
V9
SETTS
UUOS
COO
TOC
010
PH
TKN
IIP
AL
rcoii
PARAMETER
133
V3S
13
VS
SETT3
BODS
COO
TOC
DID
PH
TKN
TIP
AL
FCOL1
PARAMETER
TSS
V33
13
VS
SEIT3
8005
COO
TOC
0(0
PH
TKII
TIP
AL
FCULI
PARAMETER
133
V83
IS
VS
8EU8
BUDS
COO
TOC
CIO
PH
TKN
I If
AL
FCCLI
6
6
0
0
0
6
15
19
6
IS
IS
IS
0
0
POINTS
0
0
0
0
0
0
t
t
5
S
8
e
0
0
POINTS
17
17
17
17
17
16
1
17
9
9
17
17
0
0
POINTS
12
12
0
0
0
0
0
0
0
0
0
0
0
0"
POINTS
7
7
9
9
0
9
0
9
5
9
9
9
9
0
16,0000
t, 70000
1,60000
.000000
1,00000
4.00000
5,80000
,2oOOOO
,6oOOOOt«
MINIMUM
11,0000
21,0000
19,0000
5,60000
1,20000
,100000
MINIMUM
55.0000
10,0000
90,0000
6,00000
.300000
5.00000
97,0000
5.00000
8,00000
5.60000
,3ooooo
,000000
MINIMUM
Si, 0000
32,0000
MINIMUM
JO. 0000
12,0000
296,000
101.000
30,0000
56.0000
J. 60000
5,80000
1.70000
.610000
.000000
359.000
07,0000
sa.oooo
16.0000
07.0000
32.0000
6.50000
.aooooo
01 ,200000
ROCHESTER C30 PP
MAXIMUM
19,0000
99,0000
36.0000
5.60000
6,10000
.650000
ROCHESTER CSD PP
MAXIMUM
070.000
270.000
615.000
376,000
25,0000
290,000
97,0000
61.0000
01.0000
6.30000
o.ooooo
,730000
ROCHESTER CSO PP
MAXIMUM
079,000
220.000
ROCHESTER CSO ft
MAXIMUM
109.000
•(,0000
969.000
585.000
9300.00
530.000
101.600
6,80000
17.6000
4,58000
5.00000
1*9.000
28.1167
11.9500
T, 93333
22.0667
13.3333
6.19666
.30666*
,110666
... PERFORMANCE
AVERAGE
30.3750
55.0000
29,6000
5.71999
2,90000
,277500
... PERFORMANCE
AVERAGE
187.176
91.1706
235.607
102.000
a. 82901
50.1875
97.0000
25,5290
27,0000
5,39999
1.11765
,2611117
». PERFORMANCE
AVERAGE
196, 7bO
106,250
-.- PERFORMANCE
AVERAGE
80,57111
11,11129
447.555
198.000
815,555
143.889
3d. 2000
6.22222
6.94404
1. 99111
1,66667
132.219
21,7798
7.82081
.000000
16.87)9
9,)4405
6,18319
.291119
.103316
98,0881
11,8209
12,2161
4.26S62
14.8120
1I.279J
.193620
,227615
.421847E.OI
I. 10919
.7007J1E-01
1.162-37
, 314614
.190864
.715010
,«38|80
1.10517
,704785
3.201109
2.33477
,
3.95041
2.61159
1.47190
1.70109
2.48991
2.6U61
2.23575
DATA ». INFLUENT cso (JIOHH * 02)
GEO, MEAN
28,2318
18.21)2
28.9208
5.719(5
2,6)1)0
.237370
DATA ."
GEO, MEAN
137.722
58,97)8
185,661
56.8140
2,60043
29.6J16
96,9997
20.1597
21,1915
S, 89700
1.103)0
.000000
DA1A •-•
GEO. MEAN
161,648
92.0VI6
DAIA —.
910 DEVIATION
9.66873
22.7596
5.88557
,979795E«01
1.36290
.165057
8KENNESS
.915758
.615867
.827791
,408015
1,35130
1.21356
KuitrosiJ
.17616
.61472
.416)8
,16050
.12*91
.49612
INFLUENT CSO (9TOHH • Olj
3TD DEVIATION
136,919
77.7199
157,150
103.284
5.00871)
68.6125
,000000
15.1962
10.9949
,188562
1,02912
.211543
SKEMNE3S
.812010
,984705
,887958
1,35502
2.35894
2.23237
.000000
,601954
,264326
.497272
1. 39811
.6079(5
KUHJD3I9
2.55301
2.99768
2.88692
3.82696
8.45173
7.52120
,000000
2,54550
1.72232
3.12896
0. 69467
1,9102*
INFLUtNT C3U (3TONM « 04)
STO DEVIATION
124. 60S
57.6V62
SKEHNESS
1.2323!)
1.01155
KUHfosia
3.32)41
3,08488
INFLUENT C3U (ITOKM • 05)
CEO, MEAN 910 DEVIATION
71.1303
31,1398
414.878
J6«,2Bb
300. 9*7
109,667
20,14)0
6,21)18
6,19702
1,189)1
.000000
41,4611
26,8510
203, 450
108.901
1006.71
110,510
34,7130
.332572
1,99611
1.17287
1.19071
9KENNE33
.707700E-01
.137900
1.78187
1.88093
1,58021
2,22747
1,2768)
.258358
1,97960
.620061
.483871
KUHI09II
1, 03589
1.87U31
0.9UU
5,16022
4,30594
6,17758
2,76791
I.836S1
5,70077
1.70696
I. 21000
163
-------
O'BRIEN I GCDt ENGINEERS, INC. LAUUKATURV DATA SYSTEM AUB 24, IV76
ROCHESTER C30 PP — PERFORMANCE DATA — JHFLUtNI C3U (910HH • Ok)
PARAMETER POINTS MINIMUM
MAXIMUM
GEO, MEAN 810 DEVIATION SKEHNtSS
ISS
V33
19
V3
sens
60D5
COD
IOC
010
PH
TKN
IIP
AL
PCOll
PARAMETER
tiS
vss
IS
VS
SEITS
BU05
CUD
IOC
UK.
PH
IKN
lie
AL
FCULI
PARAMETER
I3S
V3S
IS
VS
SHIS
81)1)5
COD *
IUC
Oil.
VH
1KN
I IP
AL
FCUL1
PARAMETER
193
V33
U
V3
JEITS
6005
COD
IOC
Oil)
PH
IKN
IIP
il
FCULI
PARAMETER
138
V3a
13
V»
SEIIS
BOOS
CUD
IOC
010
PH
1KN
1 IP
AL
fcou
12
li
11
1)
0
11
1J
13
6
15
11
IJ
1)
0
PU1NI5
4
4
4
4
4
0
4
4
0
II
4
4
000
MINIMUM
220.000
128.000
1131,00
1)3.000
4,1,0000
13,0000
45,0000
50.0000
t, 80000
11,00000
,590000
,000000
MINIMUM
26,0000
11,3000
760.000
1,00000
.looooo
6.00000
22.001)0
1.00000
6.60000
.800000
.1)0000
,000000
MINIMUM
100,000
52.0000
1110.00
91.0000
.looooo
38.0000
31.0000
20.0000
6,15000
1,90000
.170000
.000000
MINIMUM
15«.ooo
7S.OOOO
413,000
30.0000
.900000
tl.oooo
t.00000
23,0000
6, 80000
,110000
ilaoooo
1.46000
2411,000
ue.ooo
490,000
239.000
5,00000
60,0000
32,0000
79,0000
6.40000
7,00000
4,10000
,710000
4,50000
ROCHESTER CSD PP
MAXIMUM
340,000
209,000
2014,00
150.000
6.00000
95.0000
78.0000
73,0000
7,30000
5,70000
,660000
1,20000
ROCHESTER CSO PP
MAXIMUM
252.000
172,000
1642,00
127,000
5,40000
66,0000
47,0000
49,0000
7,40000
11,5000
,;5oooo
1,20000
ROCHESTER C80 PP
MAXIMUM
512.000
229,000
3017,00
271(000
9,00000
(01,000
205,000
94.0000
6,85000
4,10000
l;24000
t.60000
HOCHtlTM CIO PP
MAXIMUM
496.000
192.000
601.000
150,000
1,40000
9«iOOOO
17.0000
at, oooo
7.10000
», 29000 •
-jjseooo
It. 9100
107.111
60.6667
m,6i5
112.231
2.25000
25,0000
25.6154
11.1077
1.26667
6.79999
Z.5769J
.557692
2.4230>
-•• PERFORMANCE
AVERAGE
266,000
161,000
1559,75
14), 000
b. 40000
93.0000
55.5000
62.5000
7,07499
4,62500
.632500
,600000
... )>EKFO>4MANCt
AVEKAGt
95,4166 •
62,1900
993,500
49.333S
1,25000
27,1667
26,1667
18. OBJ!
7.02500
1,90000
.184166
,500000
... PERFORMANCE
AVERAGE
201.900
Ill.ltO
1984,16
169,840
9,90400
76,6<00
101,200
51.3200
6.51199
1.19000
.451400
1,09900
-» PERFORMANCE
AVCRAGC
lal.125
196,975
526,750
96,7500
1,88750
30.8750
11.5714
12,2837
7,174»9
1. Ol«i9
.1*1429
7.19000
87.7545
49.8191
124,100
147,714
1.9)142
20.5792
25.4100
10.5151
,000000
6,79549
2,49574
,545705
2,27726
DAIA ".
71,0765
16,5067
91,6545
16,7637
1,600711
16,1436
3,34062
13.8530
2. 3)714
.241796
.664053
,110451
.•51392
.929501
,697721
,662211
,006621
1,09702
,951652
,811620
J, 68069
1,69998
1,79576
.945496
.295611
,801502
2.21113
J. 11760
2.49U96
1,0742V
2,29447
2.56t79
2.46V50
9,96198
J.9J642
5,59957
2.80V07
J. 37133
],6628b
INFLUINT CJU [STOHM f 7A)
GEO, MIAN SID DEVIATION
262,1711
156,169
1523,16
142,962
5.36923
82,4714
54,0414
61.6S69
7. 07131
K,i7Ml
,631»05
,000000
DATA -••
45.475)
30.7734
334.923
6.204B4
.616441
9.354(4
13,5000
10,16|2
,227761
,7013)6
,294746t>01
,600000
SKEHN199
,771733
,505961
,V00938E'01
.679147
.153671
,624692E>01
,921911
.857842E-01
.713316E-OI
.550)1)
,)62402
,000000
KURIOStS
2,04139
1.70477
1,54101
2.09411$
1.20<21
1,2758V
2.1U03
1.1227V
1.09464
1.69627
1.46767
1,00000
INFLUENT C3U (SI OKU > TB)
GEU, MEAN 311) DEVIATION
74,4156
46,4397
970,649
15.7059
,40918(1
2I.7U49
25.4212
!4,!U!>4
7,02031
I.;i790
.161031
.000000
DAIA *-'
CED, MEAN
199.121
105,668
1908,36
162,560
2,1311)9
71.4592
86.1)106
49,1107
6.51111
1,04836
,416947
,000000
DATA —
OCO. MEAN
102,5(1
158,540
521,117
74,«roo
1, 71011
10. mv
11.51147
11.1869
7.17115
,7657*2
ill»771
5,67217
67.9)51
46,9102
236,367
35,1267
1,66508
17,9026
7,17440
12.419i
.255359
2.9090>
.29568It'01
,26B67!>
INFIUCNT CBU (SIOHH
91D DEVIATION
8|,»197
16,671)
553,469
49,889]
2,13269
12.1798
55. lilt
17,7915
,188955
,974472
.201401
,571517
INFLUENT CSO (STORM
ITO DtvlAIION
170.064
109.016
5»,7987
44,0961
.956501
t. 11141
1,11197
7.«14|6
.156125
.1733J5
.112260
7,409«
3KCHHESS
.962)57
1,00401
1.7469S
,60)563
1,16090
,72))95
2,05785
1,08006
.309610
2.96614
,460941
.'14527
* 06)
9KEHNC9S
2.06970
1.19)19
,327196
,400910
1.21579
2.1449*
.477886
.620669
.839988E-01
1,20696
2|I46«5
.991077
1 Of)
9K(HNCS8
,669842
.•10092
;7}9652
.769677E-01
.702465
,-349199
,6}6}69C'01
,512421
1,55190
,117796
1(61075
2.2J621
KURIU3U
2. 65486
J.0353B
5.11024
2.67312
3.6S<69
2.4S640
6,09702
3.58235
1.70008
9.90630
>. 256)0
J. 63120
KU"I0318
9,61099
5.01639
1.73193
2.00192
1.91044
9i09765
1,70903
2.75610
2.29604
•.59229
9.76«2l
4,50f97
KURI031S
2,92463
2,21069
2,13141
1.11996
2. 0*07*
1.90627
2,22625
1.8)770
4.12117
2.12181
«. 11119 •
6.06991
164
-------
O'oRItft I CERE t'flGlllbEKS, INC. LAUORAIORV DATA SYSTEM AUB 21, 1V76 IOIU6
ROCHESTtR CSO PP --- PtHFORMANCb DATA --" INFLUtMT CSO (IIOHH • 10)
PiRAMEUR POlNtS MIHIMOM MAXIMUM AVERAGE GEO. MIAN ill) DEVIATION 3KEHNES3 KOH10813
ISS
VS3
IS
V3
SEITS
BUU5
COO
IOC
CIO
PH
TKN
UP
AL
rcuLi
PARAMETER
TSS
VSi
IS
vs
SEITS
BUDS
coo
IOC
oii;
PH
TXfl
lie
4L
fUlll [
pAHAHt lt»
113
VS5
IS
VS
stits
BOOS
COO
IOC
CIS
PH
IKN
IIP
AU
FCllLI
P»R4"EICH
ISS
vss
IS
vs
SEtlS
BUU5
cou
tuc
OSG
PH
TX'I
IIP
4L
KOLI
P4R4HE1ER
ISS
V3S
IS
VS
JEMS
BUU5
COD
IOC
use
PH
IKN
IIP
«L
FCULI
4
0
POINlS
10
10
10
lu
10
10
0
10
0
10
10
10
V
0
POINTS
to
2)
22
22
21
21
0
21
u
24
21
21
tl
0
POINIJ
15
IS
IS
15
IS
IS
0
IS
6
IS
IS
IS
IS
0
P01NI3
13
12
12
13
II
12
0
6
6
6
fr
6
6
1
61.0000
26.0000
166.000
70,0000
.100000
11,0000
11,0000
20,0000
6,90000
.6ljOOOO
.150000
J. 36000
MINIMUM
S7.0000
32,0000
142.000
76,0000
.300000
IB. 0000
12,0000
7,60000
l.uOOOO
,220000
.OoOOoO
HIMHOH
102.000
12,0000
B29.000
147.000
1,00000
'22.0000
15,0000
0.40000
2,00000
.700000E
,000000
MINIMUM
12,0000
6?. 0000
607.000
ill. ooo
,3(10000
55.0000
37.0000
31,2000
6.50000
1,31000
,i;oooo
,000000
MINIMUM
ise,ooo
62,0000
B»8.000
IOa.000
6,00000
7S,oono
61,0000
31.6000
7.30000
3,qOOOO
,450000
l,?0000
20.0000
631.000
320.000
1120,00
553.000
7.50000
110.000
27,001)0
123.000
7.40000
.960000
.570000
7,69000
HOCHlSltK CSO PP
MAXIMUM
61*. 000
11S.OOO
9S02.00
9011. OU
IO.SOOO
12^.000
96,0000
B.bOOOO
6.90000
.410000
i.roooo
RUCHESttR C30 PP
MAXIMUM
706.000
Sal.OUO
2961.00
Ic^.OOO
6,10000
261.000
70.0000
7,00000
6.10000
•oi li.tooo
2,40000
KUCHESHR C30 Pp
HtllMUM
361.000
309,000
I0">.00
371.000
IS.SOOO
166.000
109,000
93.6000
7.10000
6.B6000
1,11000
,800000
ROCHE3UH CSO PP
MAXIMUM
Q92.000
344,000
17«6.00
306,000
7,50000
210.000
270.000
60.6000
7.90000
5.50000
1.21000
S. 60000
30.0000
288, t)i
120.667
624.000
142.667
2.48111
S6.6667
16,7500
57.2500
7.16666
.S22SOO
.J77SOO
5,0001)0
-.- PEHFOKMAKCt
AVEHACE
261, iOO
126.600
1478.70
I02S.60
2.91000
IS, 7000
32,7000
B, 00999
2.6BOOO
.241000
.611111
-•- PtHFUHHlNCl
AVtHACt
32I.17S
191,71V
1111.41
286, 045
2,77083
95.6522
31,1111
6.67V16
3.52063
1.02416
.749996
— PtHFOHHINCt
AVERAGE
211.33!
107,600
74", 667
175. 73J
S, 74(66
I0». 7J1
63,6667
66.6000
7.00666
5,af,«66
,642666
.51533JE-OI
-•- PEHFDRMJNCt
IVtRAGE
349,417
146,167
IJM.33
232,333
6.75000
141,83)
12'. 167
46.I331
7.6335J
U, 16666
,869999
3,40000
20.0000
190.479
81.6491
S91.630
120.744
I,217S<(
51,3165
IS. 6890
41,0098
7.16161
,810049
,261431
4.7S726
DAIA --•
OEO, HtAN
171.151
89,8427
751,006
181,401
l,SS14a
37.2665
i6.26bS
U.OB570
2,45204
,266002
,000000
DAU —
CEU, HbAK
266.009
146,040
1350.67
21S.634
2,5)731
77.8176
10.5911
6,67600
J.186S9
I.ISH7I
,000000
UAlA -->
272, 78U
101,741
22S.8JB
97,3i8d
J.SSUi
14,01116
6.119)6
41,12110
,169967
,1411)4
,t042t!>E-OI
1.65304
INFLUtNf CSO (5IOKH
3ID DEVIATION
246,468
124. )32
2679,76
2671.01
3,20170
32,1668
21,618)
.262M8B
I.1SUO
.71302U-OI
,779521
1,15178
, 993206
1,65713
1,55124
1,07222
t. 14429
,765041
,71556)
.2S654J
.118559
,511144
,791010
• 11)
SKENNbSS
1,24)29
1.59118
2,64729
2.66221
1.27782
1.38715
1,60255
.222860
2.10434
.690024
.6)8661
2.62104
2.49717
1,9)826
1,71516
2,68071
). 1)777
1,95666
1,89644
I.81V4V
1.H55?
2, 02290
2.00000
.KUHI0313
3,35005
4,47)01
B.04b84
8.09702
1.41U11
3.81V06
4.SIVIS
2.225V9
6,14t))2
2,0)0)0
I.17VS5
INFLUINT CSO (SIOHH » 12)
STO DEVIATION
191,19!.
140.163
515. 317
77.4651
1, 21147
62.467:1
D.V602
,2040Ba!
1.01602
b, 62119
.5J3U73
JXFLUtNI CSO CSTOKH
CEO. )lt»N 310 DEVIATION
195.485
132, lib
736,373
181. 2111
a.oona
102,299
60,4591
64.1704
7,00160
5,12210
.6J9V36
.000000
OAIA —
'1.0i20
69.S478
136, S21
H2.7400
4.S624!
40.1062
18.0402
17,8314
.764491
.692751
.183065
.199555
6KEnNtss
.SD1623
1.01126
1.27040
1.67666
,946742
I.1511B
.V96110
,4065!>9t-01
1.17227
1.91611)
.7S7S29
• 13)
SKEH.'JESS
.456169
,650938
1.066)3
1,08056
1,J1?H
.204063
.796376
.229162
.082727
,541144
1.1)599
3.47440
KOKIObl^
1,96101
), 09)04
1.11UI7
S. 16019
3.17i2!>
1.U9721
1.10b91
l.OObSO
).866)!l
S. 14114
I.JoiH
Kuninsis
1.64874
2,49118
3, 30J38
1. 85130
0,03/31
1.414)6
), 22641
2.02469
3.2)129
2.4BI04
3, 59723
D.OM4
INFLOtNl CSO CSTONM • 10)
CEO, MEAN STO DEVIATION
330.723
1)3. see
1326,58
21), 014
6,72675
135,133
110.471
46.6670
7.6)119
4,12110
,81971)
3,05761
20,0000
106.551
S7.5642
298,656
60,044V
.5590U
41.6870'
68.60)r
11.3151
.179506
.6446)6
,2Bl)6b
1,40000
.000000
SKEHNE5S
.299219
.640735E-02
.197665
.116680
.000000
.833302E-01
1, 18969
,438568
,505739
1.17687
.185195
.610948E-05
.000000
KURI03I9
1,861)1
1,72400
1.65238
2.18868
1,69000
3,04484
3,18)80
1.49630
2.80016
3,31015
1,4)481
2.IIV53
.000000
165
-------
O'URIEN t GERE tNUlSEEKS, Inc.
LABORATORY DATA 3T3!tH
AUG SS, 1976
PARAMETER
133
VSS
IS
13
SEII3
DUDS
CUU
IOC
IUG
PH
IKn
I1J>
AL
FCOL1
PARAMETER
ISS
VSS
IS
VS
3EM3
BUDS
COD
IOC
OlG
PH
TUN
IIP
AL
FCOLI
PARAMETER
T33
VSS
T9
VS
sens
BUDS
COD
IUC
OlG
PH
Jf.ll
IIP
AL
FCULI
HARAHEttR
T43
VSS
IS
V3
SETTS
HOUS
CUD
IOC
QIC
PH
IKN
IIP
AL
FCULI
PARAHEItR
Ibs
VSS
IS
V3
StITS
BODS
COD
IOC
UlO
Pil
IKN
IIP
AL
FCULI
poiHia
13
11
11
12
S
IJ
0
5
!
5
5
S
S
0
POINTS
10
10
10
10
1
10
0
10
S
10
to
10
10
0
POINIS
lu
10
10
10
i
lu
.0
10
S
10
10
10
10
0
POlHlS
12
12
12
12
1
11
0
12
6
12
12
12
12
0
POINI3
0
6
6
b
2
6
0
0
MINIMUM
ISd.OOO
JJ.oooO
559.000
ltd. 000
2,jOono
12,0000
9. ooooo
16,8000
6.611000
1.80000
.210000
.81)0000
MINIMUM
Jit, 000
$6.0000
371.000
116.000
.600000
23,0000
28,0000
11,2000
7.1)0000
1.10000
.laoooo
1.00000
MINIMUM
tie. oooo
10,0000
'H6.000
11?, 000
1.50000
71,0000
22,0000
25.1000
6.60000
2,10000
,170000
.onoooo
MINIMUM
4S.UOOO
20.0000
246.000
10,0000
2.50000
11,0000
21,0000
20.4000
6,60000
1.10000
.260000
,000000
MINIMUM
74.0000
28.0000
275.000
52.0000
2.QOOOO
25,0000
6.00000
SI, 2000
7.10000
,9oOOoO
.100000
1.10000
ROCHESTER CSO
MAXIMUM
isrs.oo
1010,00
2056,00
1202,00
17,0000
S10.000
270.000
168,000
r.uuooo
4,80000
2,00000
2,00000
ROCHESTER C30
HAllHUM
1812.00
620.000
|)S5.000
158,000
1.00000
111,000
92,0000
SO. 6000
7.10000
5,80000
2,16000
8.00000
ROCHE31ER CSO
MAXIHUH
195,000
260.000
960.000
400.000
18,0000
316.000
115,000
60.0000
7.20000
7,60000
l.blOOO
2.SKOOO
ROCntSItH CiJ
MAXIMUM
112,000
228.000
771.000
112,000
10.SOOO
190,000
I11.00U
111.000
7,10000
8.4000U
i.iaooo
1,20000
HOCHtaUH CSO
MAXIMUM
1226.00
89.0000
417.000
7JI.OOOO
2,50000
il.OOOO
29,0000
S5.6000
g. ooooo
2.10000
.110000
14,0000
PP — PERFORHANCt
AVERAGE
611.692
281,077
837.615
126.581
9,90000
170.921
92.8000
SS.1711
7,14999
5,21000
1.I9BOO
1.12000
PP ••- PERFORMANCE
AVERAGE
566,100
208.200
iSO.200
181,100
1.75000
S6.2000
SO. 9000
11.7600
7.12000
2,71000
,496999
1.68000
PP -« PERFORMANCE
AVERAGE
196,700
111.800
646,700
211,700
10.2SOD
111,600
79,1000
41.1600
6.65999
1.61000
,711000
1,12000
PP -•- PtHfOHK.iNCL
AVbRACt
161.111
93,4167
121,667
167,917
D.b2bOO
32,6667
51,2500
60.1111
0. 94666
J.iiejj
.555000
1,76666
PP — PEWFDRMANCt
AVLHAGt
•124.667
44,61)3
146,1111
60,6667
2.2SOOO
16,8}}}
' 20,6667
SI. 1000
7,61666
1,10000
,206666
7.60000
DAIA —
INFLUENT csu OIOHH * is)
C[0. MEAN 310 DEVIATION
4U9.S61
162. 105
742.809
111,579
7,09802
121.170
55.9J61
4I,5S|4
7,19686
4,16691
,655157
1,26191
DATA — -
GEO. HEAD
105,170
155. 2115
SSI. Oil
170,296
1.1996S
18,7062
17,7090
21,1060
7,11916
2,20791
,106025
2.911S1
DAIA ---
HO, MIAN
162,519
19,2006
621,511
201,922
6.1S192
I2D.260
67.2111
16.1760
6,85776
1,46719
.$64611
,000000
DAIA —
CtU. MtAN
151.819
71.1219
194,161.
155.260
b,B7871
71.0131
14,9017
SO, 8664
6,96578
2,69510
,499471
.000000
DAIA --•
GEO. MtAN
161.592
01.0491
310,916
59,9105
2,21606
15.S806
14,1621
54.3667
7.61199
1.11101
.19716*
6.V5057
500.741
291.651
562.001
161.926
6.01922
118.741
91.2166
16,4611
.209762
1.26717
.751718
.391918
INFLUENT ciu CJIOHM
5TO DEVIATION
175.619
176.156
181.441
76.2011
1.10671
29.6657
16.6062
16,6788
,107703
1,71683
,644492
2.41901
INFLUENT C90 (3TOHH
310 DEVIATION
124,271
69.6095
166.410
116,217
S, 79311
77.9761
19,5261
15,1661
,174156
1,76490
.501190
.6471U
IXFLUtlll lau lilOKH
ilU bLVlMION
6«.ObbO
62,1196
151,407
70. 11JS
2.61670
46,6946
i6,b77i
16.7b7i
.110554
2,11281
,271150
1,19161
INFLUtNT CSU (STOnH
3TU OEVIAT10X
111,060
21,0900
6). I860
V. 62057
,250000
4,95665
6.62116
1.20000
,267187
,461860
.A61997E-OI
J.JB68U
SKEtlNESS
1,29702
1,16140
1,11083
1,11619
.220111
1,01021
1,27911
1.61020
1,17007
,274616
.152122
,567722
> 16)
SKEHNE3J
1,60189
1,10612
.696807
1.11796
1,11411
.S6I622
.617597
,327290
,7690266-01
.602544
J. 29105
.051115
• 1M
3KEHNE33
.665049
.6191/r
,659118
,561956
.148505
1,06047
.659620E-OI
.212182
.112161
.988667
.711417
.147986
• 16)
intnNtSS
1.20876
.954755
.761991
1,09299
.110912
.476131
,669144
1,06161
,121705
.921020
,811722
.267812
• 14)
ShEnNESS
1,66112
1.35062
.2146291-01
.129297
.000000
,613575
,676011
,000000
,240614
,941618
1,07410
,862810
KURT0319
3. 71411
3,72589
J.00d9i
1, 41026
I.21S61
1.11V10
3,00148
4,26020
2,63014
1.1S11J
1.22111
2.13620
KURI03II
4,91556
1.56501
2.33606
1,11169
2.30242
1.97260
2.67192
1,12482
1,518014
1.7015J
6,61iJ5
1,86011
KURI03U
,67102
.61606
.80V66
.64S19
,35851
,69162
,46096
.21152
2.52287
2.60961
Z. 10480
1.55671
KuklOMSi
J.1SV70
2.90B66
2.1.7694
1,60476
1,96041
2,00^26
1,10060
2.95346
1,81462
2,17429
J.uUiU
1 ,72646
KUHT031U
1,417)1
1.11776
1.07140
1.19431
l.OOUOO
1.96b26
2.142651
1.00000
1.19149
2.69678
2.95161
2.78005
166
-------
O'ORIEN I GERE ENGINEERS, IHC,
LAUOKAlORr OA1A SYSTEM
AUG 21, |V76
III12
PARAMETER POINTS
ROCHESTER CSO PP
MINIMUM MAXIMUM
PERFORMANCE DATA — FLUC-SED EFFLUENT (J10RH I 01)
AVERAGE CEO. MEAN 3ID DEVIATION SKEtlNESS
KUH10SI3
133
VS3
TS
VS
stns
BUDS
COD
TOC
Olli
PH
TKN
TIP
AL
FCOLI
6
6
0
0
0
0
15
15
t
15
15
15
0
0
168,000
.000000
1.00000
9,00000
.000000
5.75000
.300000
.600000E-01
166.000
86.0000
11.0000
51.0000
44,0000
6.15000
1,80000
,260000
ROCHESTER CSO PP --•
PARAMETER
TS3
V33
TS
VS
9EII3
BOOS
COO
TOC
015
PH
TKH
TIP
AL
FCOLI
POINTS
0
0
0
0
0
0
9
9
5
5
9
9
0
8
MINIMUM
12.0000
10,0000
2.00000
5,70000
1,90000
.190000
2000,00
MAXIMUM
94,0000
60.0000
24.0000
6,20000
7,10000
.710000
2000.00
ROCHESTER CSO ff »-«
PARAMETER
TSS
vss
TS
VS
SEITS
801)5
COD
TOC
ota
PH
1KN
HP
AL
FCULI
POINTS
17
17
17
17
17
17
0
1 7
U.
B
17
U
0
17
MINIMUM
IS, 0000
12.0000
75,0000
29,0000
,100000
6.10000-
5.00000
1.00000
5.70000
.700000
.lOOOOOE'Ol
200000.
MAXIMUM
164,000
179,000
511.000
199,000
1.50000
160.000
64,0000
41.0000
6.10000
6,10000
,940000
.7IOOOOE 07
ROCHESTER CSO PP ---
PARAMETER
TSS
VSS
IS
VS
sins
BOOS
COD
IDC
DIG
PH
TKH
IIP
AL
FCULI
POINTS
s
5
0
0
0
0
0
0
0
0
0
0
0
MINIMUM
100.000
20,9000
.I02000E 07
MAXIMUM
296,000
115,000
.900000E 07
ROCHESTER CSO PP — ••
PARAMETER
T33
VSS
IS
vs
9EH3
BOOS
COD
IOC
UtG
PH
IKN
HP
AL
FCOLI
POINI3
5
4
0
0
0
9
4
8
4
8
8
g
7
0
M:«IMUM
61,0000
52.0000
lOo.ooo
11.0000
59.0000
.800000
6,20000
1.90000
.650000
1.00000
MAXIMUM
161.000
132.000
1510,00
47.0000
161.000
37.6000
7,00000
10,6000
1.52000
3.00000
241,667
12.0000
11.6000
22.9000
21,0000
6,01999
,766666
,112000
PERFORMANCE
AVERAGE
17,0000
40.113!
11.2000
5,90000
1,76666
,186666
2000,00
PERFOHMANCE
IVEHAGE
147,290
62.6470
221,294
92,9412
1.47059
50,1059
24,8215
28,0000
t. 02500
1,70000
.158125
216,165
.000000
10i22;8
20,066!
.000000
6.01737
.627717
.119512
""J'uof
11.2115
5.88556
11.7114
15.9894
.1772011
.517251
,600222t*01
,810126
,517432
,808095
,925075
.S37710E-01
,201157
1,11029
,877626
2.77739
1.6SJ06
2.52121
1.10145
1.55464
1. 82522
2.76855
2.SI097
DATA -•.- FLOO3ED EFfLUtNT (SIOHM 1 OZ)
GEO. MEAN
12.7179
12.9123
9,89676
S. 89711
1,179(1
.111016
1999,99
DATA '«' FLOC*
CEO, MEAN
122,417
18,1260
195,091
70,6112
.911665
IS, 6801
19,9866
24,0175
6.02107
1.41755
,241610
.I61765E 07 988591,
PERFORMANCE
AVERAGE
212.400
89.6000
STD DEVIATION
15,9164
10,7600
7.BB1I6
,176885
2.09971
,215716
,000000
SKEHNE33
,116951
.228625
.144759E-OI
.628901
.186711
.510504
.000000
HUB 1 03 IS
1 .48^19
1,60)61
1.64669
1.95116
1.54152
I. 46141
"
.000000
JED IfFLUlHT (ITORH • 01)
3ID DEVIATION
85,0181
45.2482
116. 15B
19,5645
1.13902
41.116!
16.2054
10,1715
,216506
1.27510
.271117
.170I72E 07
SKEHNES8
,800154
Iil49l8
1,10115
1,06808
,191911
1,11174
,970088
1,14194
.249164
2.70722
,605140
2,06659
KURIOSIS
1,25011
1,54010
4,27716
2.99511
1.86084
4,01/72
1,03590
4,21/06
1.01171
10.0810
2.24011
7.50214
DATA ... FLOC-3ED EFFLUtNl (9JOHH • 00)
CEO. MEAN
194,126
75.1095
.177II1E 07 .228517E 07
PERFORMANCE
AVERAGE
101.400
89.0000
630.000
31.0000
100.500
19.6000
6.61750
6.25000
1.50750
2.28571
»!0 OIVIA1IOH
91.8621
40,1514
.169758E 07
BKEtiNESS
.298411
.419176
.704067
KURIOSIS
1.11447
2.14647
l.toooo
DATA ... FLOC-JED EFFLUENT tSIOHH • 05)
GEO. MEAN
91.9015
82,1110
500.079
17.651)
94.5158
6.8S570
6.61170
5,97617
1,29171
2.15522
BID DEVIATION
40.0779
13.867*
480.46V
5. 11854
16.6741
14.7486
.221257
1.96021
.898411
,699854
SKEHNESS
.496151
.107038
1.11814
,966162
.770414
.451108
.140080
1.02081
1,22660
,459279
KURIOII3
1.59571
1.19138
Z.1II7I
2.22IH
2.02179
1.60162
2.80055
1,41012
1.41789
2.104J t
167
-------
O'URIEN 1 GENE EN6INLERS, INC,
UDOMAIOHV OAT* SYSTEM
AU5 24, 1976
11112
PARAMETER POINTJ
ROCHESTER CSO PP
MINIMUM MAXIMUM
PLHFOHHANCE DATA —- FLUC'SLO IFFLUtNT (SjOHH < Ob)
AVErtAGt CEO, MtAN 3TO DEVIATION BKENWtSS
XUKI06I9
139
V33
13
V3
StllS
BOOS
COO
IUC
010
PH
TKN
TIP
AL
FCULI
11
11
0
0
4
11
11
11
6
11
11
11
11
12
62.0000
24,0000
1,00000
5,00000
24,0000
16,0000
,000000
5,90000
I.SOOOO
.110000
.OoOOOO
270000,
200.000
92.0000
3.00000
11,0000
17,0000
97,0000
9,00000
6,70000
1,20000
,760000
1,00000
, 1220001
ROCHESTER CSO HP
PARAMETER
13$
VSS
IS
VS
StllS
aUDS
CUD
IOC
OlG
PH
T^iN
UP
AL
FCULI
POlNlS
1
}
0
0
)
1
1
1
0
1
1
1
1
1
MJNIMUM
200,000
60.0000
2,50000
76.0000
ID. 0000
52.0000
7.00000
5.00000
,590000
1,20000
.IOOOOOE 07
MAXIMUM
246,000
100,000
1.10000
82,0000
71,0000
62.0000
7,40000
5,50000
,920000
1,60000
, IOOOOOE
ROCHESTER cso HP
Hll/MEHH
liS
via
IS
vl
StlTS
BJUS
COD
IOC
DIG
HH
TKII
HP
AL
FCULI
HOINll
11
11
1
1
11
11
11
11
0
11
11
11
Id
6
MINIMUM
25.0000
4.00000
93i, 000
46.0000
,100000
10,9000
20.0000
6,00000
6.60000
,600000
.uoooo
,400000
595000.
MAXIMUM
140.000
62.0000
932.000
46,0000
1,70000
55.0000
42.0000
12.0000
7.4000U
2,10000
,400000
1.20000
,1420001
ROCHJ9TER CIO PP
PARAMETER
T35
VS1
19
V9
1EI18
HOD)
coo
TOC
010
PH
IKJI
IIP
AL
FCOLI
POINTS
12
12
0
0
12
U
9
U
0
11
12
12
12
12
MINIMUM
168.000
52.0000
.600000
7«,0000
127.000
IS, 0000
6,15000
1.10000
,640000
,900000
760000.
MAXIMUM
220.000
71.0000
1.60000
105.000
197,000
61.0000
6.70000
4,40000
1119000
2.00000
.160100S
ROCHI9TM CIO PP
PARAMETER
198
V3J
13
VS
9EITS
BODS
CUD
IOC
cue
PH
IKK
TIP
AL
FCOLI
POINI9
MINIMUM
160.000
71.0000
.looooo
• 15,0000
10,0000
22,0000
6,60000
.790000
,170000
4,11000
S'OOOO.
MAXIMUM
114.000
92.0000
.100000
•5,0000
16,0000
10,0000
9,00000
1.60000
.260000
•.21000
•05000.
128.519
51.0769
1.75000
It. 0000
21.1518
10.6154
1.1111!
6.20000
2.16154
.561519
2.11511
07 57U50.
"• PERFORMANCE
AVEHAGl
224,000
66.0000
2,61)1)
78.6667
56,6667
62,1111
7 ,26666
5,16667
.721111
1,46667
121.164
47.1JJ7
1.61185
11.6556
27.9501
J».IUl
.000000
6.19460
2.29490
.547174
,000000
H15U7,
15,5649
20,4051
.750000
9.11697
1,50486
iO.lDlt
2.99142
,260177
,55820V
,124644
,719227
,246000
.777218
,889069
,666982
liOllO)
1|07106
1,79981
.576501
,141606
.I6941le>01
1,20102
1.1S711
2, 84450
I.l26i6
2.16519
2.46179
1.592S2
•,20009
2,08165
2.04023
4.42*74
2,95109
DATA — • fLOC-SEO EFFLUENT CSIOHH i 7A)
C.EU, MEAN
221,119
67,5901
2,6|)6t>
76,6271
55,5327
60,9111
7,26416
5,16140
.710221
1.45)70
07 .1000001 07 999987,
>-> PtRtOHHAIlCE
AVIKAGt
59,9091
21.7271
9)2,000
46,0000
,500000
21.1616
25,16)6
15,4545
7.11616
1,4)636
,218162
.500000
07 9281)1.
... PERFORMANCE
AVEKAse
197,917
37.7500
1,1081)
99,0000
157.222
49.2106
6.44611
1.67499
.855853
1,10000
07 .1I54I7E 07
--. PERFORMANCE
AVERAGE
191,000
10,9111
.166667
24,0000
11,1667
29,6667
7.41666
1,24000
•-,206)1!
4,21000
157100,
3TO DEVIATION
19.5959
6,69098
,119914
2,49444
11,7294
11,9124
.168562
.215702
.141970
. 166b62
.000000
SKErtNESS
.000000
.595170
526004
Il616l4
.611949
.704168
,707046
,707115
,560168
.707106
.000000
KUK1U21U
1.50UOO
1.50UOO
I.50UOO
1.50U01
1,501100
1.50UOO
1,49194
1.50U01
1.50001
1.50000
.0001100
DATA ..- FLUC-SED EFFLUENT (SIUHM • 7b)
(.El), MEAN
50.3)16
15,64)4
931,997
45,9999
,24011?
19.96)7
24,7749
14,25)7
7 13)16
l!lS769
,226105
,460415
869V61,
310 DEVIAI10N.
17.4225
17.2789
,000000
,000000
,569290
13,74)9
6,10919
6.74689
.205/04
,451C|7
.7216S1E-01
.238047
140694.
SXtHHESS
1,01541
1,09426
,000000
,000000
1,06660
1.15747
1.620)4
1,27670
,368661
,101140
,653149
2.22)96
,494090
KUHIIJilS.
2.71446
1.12566
.000000
.000000
2.49V20
1.09/22
5.21004
). 75/20
1.90006
1.56196
2.84267
6,46/13
I.460D7
DATA -•- FIOC-1EO (FFIUEM (9JOHM f 06)
CEO, MEAN
197,297
57.1099
1.01926
111. 716
46.3620
6.44471
1,99469
,817109
.II1412E 07
DATA ... PLOC-
OEO, MEAN
190,095
90.1114
.U1I09
21,1791
12.9901
26,9411
7,40112
.106116
4,21999
9TD DEVIATION
11.1119
1.41795
.179601
9,61200
11,1906
9,10710
.119109
.199711
.192001
211706.
9KEHNES3
,599)67
1,02962
.641420E-OI
il|9770
,545654E-Ol
.100S11E-OI
.269766
.411260
.426001
.9|«S)0
.226291
KURI0318
2.05091
1,47486
l.olull
K11951 •
I.61J71
1.15112
2.20991
2.12522
U99779
l'.B6600
9ED EFFLUENT (IIOHM 1 09)
STO DEVIATION
11,1646
6,96220
,745>S5E-01
It, 501)
2.11476
9.2676S
.477552
.266270
,10»)06E-OI
,296t02C'0!
17189,7
9XCKNE93
,195769
.100971
,626100
,671251
,219299
1,61)94
.969060E*01
,271118
.412927
1,00000
.i9192«
KURI09U
2.19195
1.94181
2,04000
Ii5104)
1.65677
1,95246
1.11795
2.11667
>, 02646
1.00000
t,i9311
168
-------
O'UHIE'N 1 GERE tNGlNEEriS, INC, LAdORAIOHY DATA SrSIEH
BOCHE31EH C60 PP —• PERFORMANCE DATA — FLUC'
AUG 24, 1976 11112
SEO EFFLUENI (SIUKM I 10)
PAHAMETEH
|U5
VSS
13
V9
StITS
BOOS
COO
TOC
015
PM
IKN
UP
At
FCULI
poiHia
5
5
0
0
5
5
5
5
0
5
5
S
Si
5
MINIMUM
140.000
54.0000
,200000
27.0000
22,0000
17.0000
6.60000
1.05000
.310000
3,46000
650000.
MAXIMUM
390.000
125.000
1.50000
61.0000
27,0000
61.0000
7.20000
1.12000
.160000
9,77000
.102000E
ROChtSun C30 PP
PARAHEIEK
lib
VS3
14
Vi
SUTS
UUD5
CUI)
IUC
OI.U
PH
IKN
IIP
AU
FCULI
POINTS
4
4
0
0
4
4
0
4
0
4
4
4
4
4
MINIMUM
104.000
46,0000
.700000
22.0000
• 11,0001)
7.70000
J.POOOO
.300000
.000000
255000,
MAXIMUM
196,000
77,0000
1.30000
34.0000
22.0000
8. 10000
1.20000
.3300011
.000000
615000.
ROCPIESIEH CSO PP
PAflAHETEK
IdS
VSS
IS
vb
SEITS
UOD5
CUD
IOC
GiG
Pri
IKN
IIP
AL
FCULI
PUINIS
22
22
0
0
22
21
0
22
0
17
22
22
'it
22
MINIMUM
76,0000
34,0000
,bOOOOO
17,0000
15,0000
6,60000
2,20000
,350000
,000000
lioooo.
MAXIMUM
144.000
66.0000
1,20000
136.000
39,0000
7,00000
4,00000
23.3000
,600000
.IBOOOOE
nnciiE3i>R cso PP
PARAMEIER
133 "•
VSS
IS
vs
stns
SUU5
CUD
IOC
OIK
PH
IKN
IIP
AL
FC.ULI
points
14
14
0
0
14
14
0
13
7
13
13
13
11
7
MINIMUM
89.0000
5] ,0000
,700000
64,0000
31 ,0000
a6.4ono
6.F.OOOO
.',(,0000
.270000
,000000
2ISOOO.
MAXIMUM
191.000
tofl.ooo
4,10000
1(9,000
76.0000
112,000
7,30000
7.05000
1,10000
.000000
,|JS500E
ROCHESTER cso PP
PARAHEIEK
ISS
VS3
IS
vs
SEITS
BUDS
CUD
IUC
uis
PH
IKN
UP
AL
FCULI
PU1NI3
10
10
0
0
4
10
0
5
5
5
5
5
5
0
MINIMUM
157.000
56 , oono
HOOOO
63.0000
60,0000
21,6000
7,70000
0,10000
."80000
l,?0000
MAXIMUM
240,000
no, oooo
2,20000
16,0000
67.0000
36.6000
7,90000
0,70000
1.56000
2,40000
AVERAGE '
246.000
90.8000
,700000
44.6000
24,4000
43,4000
7.04000
1,16000
.1)2000
4.54000
07 614000,
- rtHFUHHANCE
AVERAGE
122,000
59,0000
,950000
26.2500
17,2500
7,84999
2,70000
.310000
.000000
436750,
-• - PERFORMANCE
AVERAGE
114,000
56,0909
.618161
36,1429
22,3636
6.75862
3.09545
3.82272
.127272
07 694545,
--• PERFORMANCE
AVERAGE
IJ3.857
M.8S71
1,52143
81.2143
50.5365
66,3999
7,00000
5,66922
,690769
,000000
OF 615000,
--- PERFORMANCE
AVERAGE
201,200
66.5000
1.80000
BO, 4000
73,4000
33,5200
7,77999
4.56000
,974000
1.68000
GEO, MEAN
229,4)6
86^4577
,537627
42,2499
24,1411
39,7494
7,03639
1,1564)
.111560
4.46544
6J1I02,
31U DEVIATION
91.1717
27.62U
,465798
14.0656
1,62481
II. 460V
.149666
,9])0)9E-01
.172046E-01
.821189
I45114.
SKEHNESS
.195807
,662994E>0|
.596608
.420175E-01
,179052
.627631
,141553
,65)096
.395695
,111721
.5077791-01
KUHIOSI3
1,7)499
1,40347
I.B220U
I.47J6D
2.26860
2.10190
1.64691
2.24742
1.99454
I.7227Z
UAI* -•- rlOC-SEP EFFkUtNT (Slunn « n)
GEU, MEAN
120.879
57,9912
,923704
25 ,6612
16.7207
7.6U657
2,6btJ25
,309764
,000000
414916,
3IU DEVIATION
16.7162
11,2916
.229126
4,71036
4,02117
,150000
.412311
,I22474E-OI
,000000
140061,
SKEXNES3
,128393
.692864
.496765
.847697
,505253
,688987
.1I9563E-06
,616497
.000000
.523966E-01
KUHI03I3
1.49678
1.902S6
1.76191
2.05436
I, 950U J
2,16110
1.22145
2,00000
,000000
1.42640
DATA — • FLOC-StO EFF'LUENl (5IOHM t 12)
GEO. MEAN
112.063
54.1964
,606196
32.5220
21,4403
6.75777
3,06157
1,01451
.000000
606066.
3TU DEVIATION
20,1269
13.7964
, 1434^
23.6173
6.759IJ
,119106
, 440514
6,46505
,331278
195247.
SKEnNESS
.499681
,266983
.660355
3.68021
.829662
,626048
.316470E-01
1.70448
.350710
,477.106
KUKIOS13
2.15602
1.99905
-
3,66614
2.65610
2.67699
2.42016
4,64*04
1.52721
2.354UO
DATA --- FLUC-3EP EFFUUENI (3IORH t 1))
CEO, MEAN
119,967
'0.0760
1.40541
79,9711
46,6621
63,9633
6.99655
5,56512
,643218
,000000
541608.
3ID DEVIATION
32.6449
16,5523
. 755151!
15, 3212
13.9814
19.9657
.218366
.937824
.239822
.000000
311528,
3tiE»HES3
.833817
2,713"!
U51055
,407937
1,48897
.04J076
.387971
.102066
,000000
.906678
KURI0313
2.42
-------
U'URUN I CEHt tNCINltWS, INC, LAUOHAIORY Dili SrlTtH AUG Ji, |976
ROCHtbltR CSO PP --> PtfiUJHHANCt DAT* --- FLOC-SED tfHUtuI lilOKH «
PAHAMEttK POIIllS H[NINUH
MAXIMUM
UtO. MIAN SID DEVIATION SnbnNtSS
1SS
VS3
73
VS
SHIS
UOUS
COD
JOC
CJUt
PH
1KH
11)"
»L
FCOLI
;
7
0
0
•3
7
0
1
1
1
}
)
}
14
20.0000
4.00000
,100000
18,0000
25,0000
5,60000
7.50000
2,80000
,110900
1.20000
21SOOO,
20,0000
1(1,0000
.200000
IS, 0000
16,0000
12,1000
J.SOOOO
1,00000
.250000
1,10000
.i6«oooE or
HOCHtSUR CSO PP —
PARAMETER
I3S
VSS
IS
VS
itHS
BODS
COD
IOC
blO
CM
IKN
UP
AL
KUU
POIHIS
a
u
0
0
I
8
0
a
u
0
«
8
11
a
MINIMUM
63,0000
17.0000
,200000
16,0000
li.oooo
11,6000
b. 90000
1.80000
.210000
1,70000
IdOOO.O
MAXIMUM
102,000
140,0000
,500000
46.0000
36,0000
17,60011
7,20000
4.90000
.580000
3,30000
265000,
ROCMS3TEB C!>0 PP -—
PAHAMtTtH
liS
VS3
ti
• tS
StltS
BUUS
COO
IOC
ULG
PM
inn
llf
AL
FC.ULI
points
000,
PtnronHAUCE
AVERAGE
57.2500
1J.B750
,100000
20.8750
26.7500
73,1)13
5,46250
3,98750
,876250
15,1750
1D200.0
PERFORMANCE
AVEKAGE
63,8000
11,6000
,100000
11.3200
12,8000
52,0000
6,8199?
1,20006
,332000
10.3400
34.6687
6.6U722
,125992
10, 4042
30,bU12
0.63324
7,119998
1.98JS8
,l»26iO
1,329(11
Sl76i9,
I. 53766
3.49927
.imuobt-oi
4.28021
*.3U«6
2.50S91
,000000
.9201 Hi
,S09902b-01
.412808E-OI
S69197,
,6318311
,600940
,707108
,99811431-01
.43U710E-OI
.J63590E-OS
,000000
,700848
.52800)
.707107
.785860
2.50/16
2.21160
1.50000
1.6U21
1,50000
1,706 an
,000000
1,50000
1,50000
1,50000
1. 97102
Dili — - H.OC-3fcU tfrUJtNI (3IOHH I 16)
C£0, MEAN
74,5012
26,6355
,262071
27. 7.151
26,8744
14,0707
k.lUbta
i.fauos
,146152
2.56629
I01SIV.
DAT* — FLUC
uEO, MEAN
50,9790
17,5942
.191291
64.7571*
28,7465
76,)908
7,08771
4,a;i8i
• 2I1U1
t,-uim
371116,
3TD DEVIATION
13.3972
b.S0643
,471404t-01
11.6^12
7,56617
2.56710
.92702*E-01
1.20461
.1)1476
.528559
93298,9
iKtntltSS
.665539
.543459
,707104
,265072
.197180
.13)002
1.19157
,2d)446
.402167
,51)067
,809479
KUHI03J3
2.26695
2.20571
1.50UOO
l.uSeU
1,66415
1,1^780
3.74V21
1,48^82
1.6U15
1.86^24
2,11049
-3tO tFFLUCNI ISIOHH I )7)
3TD OtVlAIIOli
60,)1>4
i5.»»21
.2820113
16.1390
17,510^>
7.11727
.128620
1.15513
,886U42t-01
,5566511
418715,
9Kt«lltS3
2,01856
1,99)44
.707107
,752098
,727x72
,491914
.1056119
.108797
.181544
.399769
.519916
MJKIOS13
5.72ifli
5.646)7
1.50UOO
2.26UI9
2,55744
2,11355
1.989)0
1.5JbU9
2.44191
2.02923
1.50UOO
UA?A -.- HOC-SID EfFLUtHI ISIOIIM • m
CEU. MEAN
55,6001
11,4089
,100000
19,7369
24.5590
51,5409
5.40777
3.M4I2
.610)25
14,0969
.000000
310 DEVIATION
1J, 1.199
1,62069
.000000
7,00781
3.23071
60,8406
,788887
1.53821
.315196
5.07671
8812,06
3KEKNCSS
.21)488
.322195
.000000
,3909«o
.358646
.664958
•.190261
.558274
.313567
.9H7I20E-OI
.186708
KUH10313
1.38VJ9
, 1.84191
.000000
1, 56(05
1.60139
1,50000
1.34U37
1,611)9
1. 48515
1,40107
1,94106
DAT* -'- FLOC-JEO CFFLULNt (SIOBM • |
CEU, HltH
59.21ID
17,54611
,100000
11,24411
11,69^1
51,9)81
6.81750
1.19924
.291292
9,854811
3TU DEVIAMON
24,4491
6.621)4
.000000
1.29368
n.ktalt,
2.57682
,183301
.1095115
,169199
3.11554
3KEXN[$3
.295571
.750582
,000000
.152695
,S23480
1.06044
,655745
.912888
.739774
.127963
KUDI03I3
1.28U56
2.0X99
,000000
1.3616;
2,00018
2.25^50
2.22V52
2.50002
1.92101
1.3115)
170
-------
O'URIEN ( GERE ENGINEERS, INC.
LABORATORY DAT* SYSTEM
AUB 24, 1976
11115
PARAMETER POINIS
ROCHESTER cso PC
MINIMUM MAXIMUM
PERFORMANCE DATA -•- CR1I-3HIKL EFFL. (9JOHH I 01)
AVERAGE GEO, MEAN 311) DEVIATION 3KEHNtS3
KURI0319
TSS
V33
TS
VS
9ETT3
eoos
COD
IOC
Oil!
PH
TKN
IIP
II
FCULI
6
t
0
0
0
)
IS
IS
6
IS
15
15
0
g
60.0000
IS. 0000
6,60000
o.ooooo
6.00000
,000000
5,85000
,000000
.joooooe-oi
271,000
112,0000
ID, 0000
12,0000
58,0000
21,0000
6,20000
.$00000
,190000
ROCHESTER CSO Vt —.
PARAMETER
136
V3S
T3
V3
SETT3
BOPS
coo
foe
QIC
PH
TKN
HP
It
KOLI
POINIS
0
0
0
0
0
0
9
9
s
5
9
9
0
0
MINIMUM
7,00000
il.0000
20,0000
5.70000
1,20000
,170000
MAXIMUM
18,0000
80,0000
JO, 0000
6.00000
5,10000
.620000
ROCHESTER CSO Vf —•
PARAMETER
T33
V8S
U
VJ
JUTS
6005
COD
we
OIC
PH
IKN
IIP
AL
FCoiI
POINTS
IS
IS
IS
IS
IS
IB
0
18
9
9
IS
18
0
0
MINIMUM
28.0000
8,00000
89.0000
1.00000
.200000'
li.OOOO
6,00000
7,00000
S, 60000
,200000
.700000E-0!
MAXIMUM
090,000
350.000
691,000
JJ1.000
2S.SOOO
210,000
123,000
51,0000
6,20000
0,10000
,810000
ROCHtSTER CSO PP •-•
PARAMETER
us
VS3
13
VI
sens
BOOS
COD
IOC
DIG
PH
TKN
IIP
At.
FCOL1
POINTS
S
S
0
0
0
0
0
0
0
0
0
0
o-
0
MINIMUM
Si. 0000
J2.0000
MAXIMUM
3J6.000
112,000
ROCHESTER CSO PP -—
PARAMETER
TSS
VSS
IS
V3
SETTS
BUD;
COD
TOO
QIC
PH
TKN
TIP
AL
rcou
POINIS
a
a
0
0
0
6
s
6
0
0
s
a
0
0
MINIMUM
71.0000
68.0000
60.0000
It. 0000
4). 0000
J. 20000
,680000
MAXIMUM
359,000
30*, 000
tt«SOO,0
57,0000
182.000
S. 00000
3.78000
108.000
25.63JJ
10,8667
S.S6667
22,4000
12,5000
6. 031))
,266666
131,575
24.3931
10.3502
5.US90S
IS, 6221
,000000
6,0)2112
.000000
.87JJJ2E-01 ,7i52f2E-OI
PERFORMANCE
mRAGE
25,1335
48,SS89
29,6000
5.78000
a.qaw
,27t«ai
PERFOUMANCt
AVERAGE
151. an
79,5000
227. )89
7J.555S
1.00000
06,5889
2(1,3333
29,6869
5.92222
1,38889
.257222
PERFORMANCE
AVERAGE
1H4.500
68,0750
PERFORMANCE
AVERAGE
1*1,875
126,500
7178,75
11.8750
88.6250
5.15000
1. 40500
ta.UTi
8,9333V
),12b52
2,)6OI
,813700
,657480
.496229
1,37250
1,05809
,16)503
.25733?
.119921
.576661
J. 06047
2,241158
1,50000
1.8SV25
3,6ii)«
I.JOJ65
2,36)01
2.5813B
2.72746
DATA -•• gRIT-SKIRU EFFU. (ITORM 1 02)
GEO, MEAN
22,1)15
44,9788
29,0575
5,77811
2,1866)
,250655
SID DEVIATION
11,2250
20.07«b
5.Z7636
, 11661V
1,23658
,1)6)09
SKCHNES3
.292501
,607129
,959381
1,15001
1. 18381
1,72150
KVRIOSI8
l.6031
4,72<50
DATA — • GRIT-SHIRL CFFL, (SIOKM t OJ)
GEO, MEAN
112,269
so.iiJo
192,2)7
36,2410
1,91674
32,7540
I7.S997
24. m?
S.9192J
.870570
,201748
STD DEVIATION
IIS. 064
«1.J)5S
148,597
81,1111
5,«»18i
48,2211
25.7638
11,650)
,187248
1,23328
,194)02
SKEnNESS
,)274«
,02920
,72028
,83902
,57086
,27084
). 05052
.150807
.222242
.949068
l,)7659
KUBIOSI3
4.J8330
7,10)01
•71*36
,2«496
,>«!>4I
,71696
2,0116
,99/tt
.9)694
2,8140)
4,16010
DATA -" OSII-SrllKL CFFL, (3IOKH < 04)
CEO. MEAft
124.045
61.0717
STD DEVIATION
83.5112
15,1865
SKEilNESS
1. 21562
,2)2924
KURIOS1S
1.791)0
1.91*11
DATA ••• OBIT-SKIRL EFFL, (SIOHM • OS)
GEO. MEAN
124.84)
Hi. 955
1)02.1*
40,9991
92,216)
4.9562)
I.U4«I
STD DEVIATION
96.0558
71,0194
16092,4
8.69536
IB. 0514
1,45945
I.C08S6
SKEhNESI
1,87544
1,80506
2.2561*
.192011
1,59691
.676)85
l,46f)l
KURTOSIS
5,16204
4,988*1
6.11)18
1.77(2$
1.60663
2.«5080
).»?»«*
171
-------
O'UHHN I CERE ENB1NEEH6, INC. LABORATORY OA)A 3Y3ItH AU5 24, 1111, 11115
ROCHESTER C90 ft ••' PtHKJRHANCe OAtA -•- GHII-8
1,5400)
11.1619
26,1800
14.0158
2.114U
.$14514
66,«117
21.177)
,}44862
9,64915
1,14062
17,1861
,767151
,115150
OATA .-- GRIT-3HIHL tffLUENI
(.60, MEAN
245,109
120,114
5,65065
75,0924
51,0125
52,4185
4,64028
,545776
DATA >-' Grill-
CEC, MEAN
41,1829
14.1751
.159246
15.7421
21,1410
11.1760
,ttUS01!>
,1)5117
50, 1495
OATA •-- CRI7
CCO, MEAN
244,743
73.1175
2.7)807
71,0187
51,701*
7,91178
,000000
.943797
3TU DEVIATION
25 1664
u!ll07
1.10252
5.40666
5,74272
4.42161
.49oobtl
.7257 lot -01
SHIRL IHLUENT
SID DEVIATION
50.1060
20.1597
1.06406
11.1190
4.61244
9.79U5
.4b9b5b
,388281t-01
11.5000
1,21119
I.246S2
,652024
1", 15JJO
.MT629
,561252
.96«69)
.1S1I44
(STURM • 7A)
aKEHNESS
,502066
,674556
,U5113Jt.01
,691934
.111064
.209706
.1U1794
,544141
(5IURH • 7!»
SKEHI.ES5
1.41154
1.85518
1.21151
.467767
.868245
1,10797
. 17bb01
.455884
.000000
4,14160
1,71761
2.09645
1.16067
1.4S921
2.7)41)4
2,19478
1,61)61
KURIOSJ3
1,50000
1.50000
I.50UOO
1,50000
1.50000
1.50000
1.50000
1.50001
KURIObU
1.71107
S.17V98
2.81002
2.56V69
1.1005)
1,68416
2.40/10
1,68657
1.00000
•SHIRL EFFl. (STORM 1 o«)
STO DEVIATION
116,130
44.2257
2,29830
5I.540*
13.5051
, 22*494
, 190257
»748)17
SKEXNtJS
.)614||
.703437
.762467
i»7070I
.404)17
.463176
2.B8SB2
2«7l»lt
Kuniosts
1,76107
1.66932
),21*5 1
9, 47457
11.7)17
10. tilt -
' PERFORMANCE OATA •-- ORIT-IKIRL IPFL. (ItODM • 09)
AVERAGE
188,750
85.7300
1,11250
M.)7JO
19.1730
11,8750
7.11750
1.17875
;)3»130
OEO, MEAN
I81.5M
94,7414
1,12328
20.7MO
18,1525
11.888*
7,11)30
l(19)0<
ildiiol
STO DEVIATION
18.1328
U.J471
,«8S84«
7,19646
2,64436
ll.44sr
,i)9<«3
,664111
IKCKNESS
.111364
.596657
.460001
114986
.185616
|i8979)
lll»»«
KUR10SI9
1.76551
2,85447
1,85867
1,04442
2,77169
1,61050
2,14650
I.8JJ62
•SiT670«
172
-------
U'bHIEN ( SERE ENOlNtEHS, INC. LAbuKAJOKY DAI* SYSTEM »uc i«, 1976 11115
ROCHESTER CSO PP --. PERFORMANCE DAT* -.- SHir-S*IRL EMU. ISTOHH I to)
PARAMETER POINTS MtHlHUH MAXIMUM AVERAGE CEO, MEAN STU OEVIAIION SKEKNES3 XUKIU3I3
TSS
VSS
TS
VS
SETTS
BOOS
COO
TOC
016
PH
TUN
TIP
AL
FCUII
PARAMETER
I iS
VSS
VS
SETTS
BOOS
COD
IOC
DIG
PH
IKN
AL
KUL1
PARAMETER
ISS
VSS
IS
vs
btllS
uoos
cou
IOC.
usi;
Hn
IKN
UP
A.L
FCULI
PJRAMMER
ISS
VSS
IS
VS
StITS
B005
cuu
IOC
OSU
PH
I«N
IIP
AL
FCULI
PSHAMEUR
ISS
VSS
IS
VS
SETTS
BUDS
CUD
IOC
osr.
PH
IKN
IIP
AL
FCOLI
4
4
0
0
6
6
2
0
points
9
9
0
0
9
9
0
8
0
0
9
4
0
0
POINIS
24
24
0
0
24
24
0
24
U
0
24
24
0
0
POINIS
14
14
0
0
1 4
14
0
14
U
0
I"
14
0
0
POINIS
12
12
0
0
4
12
0
12
0
0
12
0
0
116.000
37.0000
. looooo
16,0000
1 1.0000
14,0000
7,60000
1,10000
,110000
1.92000
ROCHESTER
MINIMUM
64,0000
40,0000
,400000
28,0000
10.0000
1.30000
,190000
ROCHESTER
MINIMUM
85,0000
40,0000
,800000
30,0000
3,00000
1 ,50000
.Ooouno
ROCHESUB
MINIM.,
204,000
80,00110
i.ooooo
2?, 0000
48.0000
i,7eooo
,610000
ROCHESTER
MINIMUM
190,000
83.0000
o.soooo
50.0000
60.0000
3.90000
,300000
710,000
275,000
7,50000
120,000
27,0000
68,0000
7,70000
1.60000
,260000
1,92000
CSO PP
MAXIMUM
480,000
176,000
4.10000
62.0000
55,0000
6.00000
,310000
CSO PP «-
HUIHUM
526,000
197,000
6,00000
137,000
74.0000
3.60000
,2bouOO
C90 PP —
MiMMUH
3(6.000
204.DOO
17.0000
142.000
111.000
8. 47000
J. 42000
CSO PP
MAXIMUM
494.000
214.000
7,90000
mo. ooo
153.000
5,50000
4.61000
329,790
112.290
2,26667
41.8313
16.1667
38.83)3
7.65000
1. 21667
,160000
1,99000
PERFORMANCE
AVERAGE
193.778
89.0000
1,81111
17,4444
30.3750
2,47777
.265555
PERFORMANCE
AVERAGE
166.000
65.5000
2,40066
50.7500
36.6750
2.40000
259, 8S2
102, 3JB
,882b36
12.9761
15,4644
10.3294
7.64V8I
1.21422
.171106
1.9JOOO
211.8))
90.22SS
2.62086
15.9231
5.17741
27.1293
.S00002E-OI
,184270
.091J&bl-Ol
,000000
DATA --- GHII-bHIKL EFFLUENT
GEO, MEAN
149,347
76,9890
1.37440
16,0514
26.2803
e,23o74
.262321
DATA — Ghll-
CEO, MEAN
164.061
76,9050
2,06/14
45,72)1
31,3430
2.34244
.866065E-01 .000000
PERFORMANCE
AVERAGE
253,286
120.714
5.04286
58.7143
65.7857
6.73428
1.93071
PERFORMANCE
AVERAGE
349.000
148.917
6,55000
101,250
10i,250
4.61666
1,00583
STU DEVIATION
141,676
48,9675
1.2S117
10.94S4
15,810V
1.1247V
.197523E-01
SKIRL EFFLUENT
Sill DEVIATION
)05.794
42,5590
1,46280
26,8410
17,0717
.533054
.832990E-OI
DAIA •— GHI1-3XIHL EFFLUENT
i;eo. MEAN
249,691
116,436
3,69350
54.5923
63.5167
6,62326
1.55251
310 DEVIATION
45,1306
35,0)31
4,52086
26,2690
J9.2990
). 20744
1.00121
DATA •— GHII-SHIHL EFFLUENT
CEO, MEAN
336,953
143,412
6,2)649
97,0849
99,4111
4,59202
.706B32
STU DEVIATION
87.6594
38.83)8
1,25200
27,1757
27.866)
,479291
1.1520)
,830190
.618715
1.11644
1,50616
1.30967
,796456
.000000
1,22796
,181266
,000000
(SIUHM < U)
SKE'KNESS
.907803
,731376
,55715V
1,05135
.493827
1.93290
.657220
(SIUHH • 12)
SKEnHcSS
1 ,63644
1.14/76
,959507
1,70974
.200416
.504458
,937003
tSIURM • 13)
SKEHNE39
1.21793
1.31092
1,64046
2.16503
1.523?6
.JJ9309E-OI
.972830
(SIUHH > 14)
SKENNESS
,)72962
,145436
.430696
.417152
.230667
, 465018
2,50972
9.04302
1, 91214
2.83470
3.64576
1.189D
I. 96025
1,00000
2,93889
I.V3261
,000000
KuRlOSIS
2.42418
2.00917
1,91541
3,07069
1.60V86
5.6700V
2.08167
RUHI03I3
5.23*43
3.18292
2, 65o23
5.27086
2.62/13
2.53371
2.49489
KUKIObla
3.58100
3.75836
4.48
-------
O'OHIEII 1 Ubflt tNUlr.tEHi, IHC, LAOOKAIORY Dili SYMtM
flOCHtSTER CSO PP — PEKFOHHAMCt DM* • -- CHII-
PARAMETER POINTS MINIMUM MAXIMUM AVERAGE GEu, MEAN
AUC, 23, I tic, 0
» IB)
3IU DEVIATION
25.3118
?0.0560
1,91099
23.0308
18.5130
2.0118)
,110900
3KEHNL9S
1,29261
.4161151
.160565
.571570
,2851|»
1.21332
.520 (27
1
2
)
1
1
J
1
KURI03I3
.24104
.24062
,092 1^
,60662
.67175
* 02USU
,72002
PAIA — GRIT-SWIRL EFFLUENT CSTORM » It)
GEO, MEAN
310 DEVIATION
SKEHUE5J
KURIOS13
'10 DAIA EXISTS FOX THIS REOUEJt
174
-------
O'flHltN t CERE ENtlNttHS, IHC,
LAaOKATORY OATA SYSUM
AUB ill,
line
ROCHESTER C30 ff — PERFORMANCE OATA — PH1M-S«||HL 1>FL, (S10KM I 01)
PARAMETER PUINTS
MIX]HUH
AVERAGE
CEO, MEAN alD DEVIATION SKtKNtSS
T63
VSS
IS
VS
sens
8005
CUD
TOC
Oil.
PH
IKN
IIP
AL
tern r
6
6
0
0
0
0
IS
IS
6
IS
IS
IS
0
A
91.0000
19,0000
5,00000
8,00000
4,00000
5,55000
,100000
,S»OOOOE«OI
220.000
164.000
21,0000
42,0000
17,0000
6.10000
1.20000
.220000
ROCHEITCf) C90 PP
PARAMETER
TSS
VSS
T4
vi
311IS
BOUS
coo
IOC
OlLli
PH
I HI
TIP
AL
FCOLI
POINTS
0
0
0
0
0
0
9
9
5
5
9
9
0
0
MINIMUM
12,0000
30.0000
23,0000
5.70000
1,40000
,190000
MAXIMUM
15.0000
51,0000
47,0000
6.10000
6.00000
.790000
ROCHESTER CSO PP
PARAHtTEK
US
VSS
IS
VS
3EITS
80 US
too
IOC
ota
PM
IKN
TIP
AL
FCOLI
POINTS
IB
IB
18
17
la
18
0
18
9
9
18
18
4
I)
MINIMUM
16,0000
12,0000
80,0000
11,0000
,100000
9,70000
5,00000
1,00000
5.60000
, iooooo
,'OOOOOE-OI
MAXIMUM
195,000
IIS.OOU
166,000
140,000
2,10000
107,000
11.0000
50,0000
6.20000
6,00000
,970000
HOMESTER C30 re
P»RAH£IER
T33
VSS
TS
VS
SETTS
BOOS
CUO
me
Dili
PM
TKH
TIP
Al
FCOLI
POINTS
10
t
0
0
0
0
0
0
0
0
0
0
0
0
MINIMUM
14,0000
2.00000
MAXIMUM
155.000
56.0000
ROCHESTER CSO ft
PARAMETER
153
VSS
TS
VS
sttis
eoos
coo
TUC
01 G
PH
TKN
TIP
Al
FCOLI
POINTS
7
7
0
0
0
7
7
7
0
0
7
7
0
0
MINIMUM
104.000
96,0000
Ho. ooo
11,0000
55,0000
1.50000
.710000
MAXIMUM
184.000
172,000
31600.0
46.0000
100,000
5,10000
2.95000
111,131
71,1667
11,0000
20.8000
tl.SOOO
5,90111
,*11111
,9.66665E»0
-— PERFORMANCE
AVERAGE
21.6667
41.5555
14.4000
5.65999
1.14444
,162222
--• PERFORMANCE
AVERAGE
91.2222
IS. 7222
198,276
56.7059
.905555
12.0811
16.2222
14.6667
5.86886
1.45000
.IT9444
... PERFORMANCE
AVERAGE
76,5000
|9,4atiq
». PERFORMANCE
AVERAGE
137.7(0
121.429
5991,43
40.0000
74,5714
a,]42«>
1.23714
122.611
51,8560
10,6486
16,0809
10,3836
5.69977
,19)695
1 .67117SE-OI
DATA — PRIM-
CEO, MEAN
22.2491
42.9209
11.4514
5.85S44
2,69686
.312)19
DATA ... PRIM'
CEO. MEAN
80,6711
27,9315
181.145
46.07(7
,756645
it, 6306
16,6320
1I.2UO
5,66616
1,26479
,111601
49,5771
49,4045
5,67651
10,4810
4,46261
,203668
.351504
,5?6962E'
8H1HL (FFL.
'01
,721829
.732215
.589150
.176512
.186146
,126108
,486775
1,15837
2.08956
2.48347
1.94954
1.94121
1.94928
2.59257
2,42651
3.06171
CtlOHM I 02)
STO DEVIATION
7.61577
7,16645
6,01498
.115646
,21175)
SHIHL EFFL,
SKtnHtSS
,265919
,454109
.166546
,750156
,476752
.625277
KUHjOSIS
1,95710
2,09127
2,06637
2.36401
1.54599
2.10551
(6IOHM 1 01)
IIP DEVIATION t)KEHNt66 MJRlOSla
47,5202
30,60ik
81,1217
11,44611
.470761
26.5U05
7,45769
12,9672
{,66069
DAIA -." PRIM-SKIRL EFfL,
GEO, MEAN
56,5579
12,1862
1.00174
1,77648
.569726
1.01760
.552936
1,60434
.519764
2.11627
.167052
1.14)0)
1,09656
2,77097
4, 45021
3.09201
4,06641
1.21815
2.5946*
6,180)1
2.14260
1,54813
1,10615
(J10HH 1 00)
SID DEVIATION
50,0764
16,1986
DATA -.- PRIM-8NIBL EFFL.
CEO, MEAN
115.352
120, «»7
1719,15
39.7215
4,29303
1,09892
3KEHNESS
.205468'
.944367
KUP10M8
1.60361
J, 10013
(6IOKM f 05)
SID DEVIATION
2t,2609
25.9607
11295,9
4,65986
14,7924
.665168
.721916
SKEHNE6S
.315482
.631018
2,02258
,144007
,734004
,12341V
1.76511
KUHIOSII
2.00999
2.17606
5.12560
1. 46944
2.74?59
1.46807
«.606|9
175
-------
O'BRItN I CERE ENSlNbERS, INC, LABORATORY DATA 3T31EH AUG 24, 1176 11116
ROCHEJTER C30 PP ••• PERFORMANCE DATA — PRIH-aHIRL EFFL. «RA.- PH1H-SH1RL IFI-LUENT
GCCJ, MEAN
100,721
147, 661
0,66890
89,5771
61,2171
96,4517
5.91117
,605856
S|D DEVIATION
262.591
184.689
19.84BU
111.047
17,1548
178.861
,6617110
.124700
OAIA •-. PHIH-snlRL EFFLUENT
GEt), MEAN
55.6967
21.2411
,126201
18,5055
22.0216
14,9460
.917628
.20449]
DATA -— PRIM
CEO, MEAN
196.70)
61.194)
1,55258
64.02)4
61,906*
50,0791
7,65626
2,661)6
,4U7i?
OATA -'• PRIM
CEO, MEAN
209. )50
67,0900
1,07262
22,6677
11.3014
21,22)7
7.4745)
t.lllU
.000000
SID DEVIATION
10,2805
15.0216
,8b9026
I4.111U
5,45171
ll.liOb
.580229
,69(042
.944869
,000000
.519462
.meioE-oi
,59667)
,16182*
,209805
UTUKH I 7A)
3KEHHE33
1,14617
1,14958
1.15416
1,10872
.961050E-OI
1.15568
,950274
.661)81
(8TUHH » 78)
8KIHME3S
.717779
1.27976
1,20159
1,12607
1,42921
1,19680
.470965
,902875
2,6567)
t,B2!>92
1,00000
S.OUU71
2,05701
2.51765
1,94167
1.70167
lURIDSta
2,)2612
2.12V15
3,)1t6
1.91792
5,55)25
2.62606
3,64)5i
•»ri:«L till, (I10RM 1 09)
ITO DEVIATION
29.J999
14,2996
• ,244949
4,6460?
i.iom
T, 84219
.6Z9IS5E-01
,144665
.6)05671-0!
8KINNE66
.22442)
,7)2669
,15)096
,7)6296E-0!
.511)10
.622601
.49)559
,24)660-
.522999E-01
KURT09II
>,)5t66
2,170(1
-I.6HOO-
1,41462
2.1868?
2,1)449
1.62621
-i.esVos
176
-------
O'BRJEN 1 GERE tNlil(ttER3, INC, LAUOHAIOHY DATA SYSTEM AUG 20, 1976 11118
ROCHESTER CSO PP --- PERFORMANCE DATA ••• PRlH-SnlHl. EFFL, CSIORH 4 10)
PARAMETER POINIS MINIMUM MAXIMUM WRACl CEO. MIAN SIP OEVIAT10N SKIHNIS8 KUR10SI3
I3S
V33
TS
V3
6ETT3
SOUS
COO
TOC
DIG
PH
TKN
IIP
AL
FCOLI
6
6
0
0
6
6
6
6
0
2
6
6
0
0
79.0000
36,0000
,$00000
IT. 0000
11,0000
11,0000
7,60000
1,11)000
,150000
340. OHO
IIS. 001)
i. 00000
42,0000
26,0000
17,0000
7.40000
2,10000
,350000
(JOCHESIEB C30 PP —
PARAMETER
ISS
vsa
IS
V3
sins
BOU5
coo
IOC
UIG
PH
1KN
UP
AL
fCOLI
PARAMETER
IS3
VSS
IS
VS
stns
UOUS
cou
IOC
0(0
Pn
IKN
IIP
AL
I-COLI
PARAMETER
iss
vss
13
V3
SEII3
BOU5
COU
IOC
OKi
PH
IKN
HP
AL
FCOLI
POINTS
1
1
0
0
1
1
0
6
0
0
9
<>
0
0
POINTS
la
2U
0
0
19
20
0
in
0
0
20
21
0
0
POINTS
l«
11
0
0
14
11
0
11
0
0
It
10
0
0
MINIMUM
71.0000
10,0000
1,^0000
16,0000
19,0000
1,00000
,000000
HOCHtSUR
MINIMUM
62,0000
12,0000
. oooono
1,1.0000
r.ooooo
, VOODOO
,000000
pocxtsitn
HI»IMUH
IJT.OOO
08,0000
•looooo
22.0000
3J.OOOO
3,66000
1.11000
MAXIMUM
170,000
69,0000
3,60000
40,0000
16,0000
2,t>0000
.600000E-0!
CSO PP —
MAXIMUM
23.000
65.0000
1.70000
61,0000
31,0000
3,70000
.210000
MAXIMUM
350.000
100,000
5.10000
92.0000
98.0000
6.60000
2.69000
201.000
;s.iooo
1,2633}
26.63)3
17,1667
22,5000
7.BSOOO
I.SJ667
,106666
PEHFOBHANCt
AVtKAGE
lib. 776
50.2222
2,70000
25.SSS5
27.1250
l.tbiSS
175,809
te.SJSI
1.13161
24,6570
16.5661
20,9621
J,Ht1ii
1, 08642
,1474811
100,157
Jo.euat.
.542780
10,1)645
4.HI02V
b, 4406V
.500004E-01
.40704.V
.687180E-01
DATA --- PrIIH-SHIHU EFFLUtNT
GEO. HtAN
113,175
07.1066
2.60U10
20,3439
25,735^
l.S7i(>S
.I55555E-0! . 000000
PERFORMANCE
AVtHAGt
129.792
66.6667
1.66750
31.9S8J
2B.9167
2.30000
,103750
PERFORMANCE
AVtHACE
150,071
60,1029
.265710
01.9206
03.0000
7,09928
2,15603
PERFORMANCE
AVE1IGE
265.633
107.167
2,90000 .
79,5000
71,8333
5.19166
,821666
OAIA — HHIH.
(.EO, MtAN
121.766
58,3695
1.56171
29.6075
26.0604
2,17«aS
,000000
S10 DEVIATION
35,5063
19.1298
,666066
6.42102
9,11090
.527160
.163249E-OI
,215461
,I>0090«E-01
,J55643E-0|
,620«a«
. 644857
,459015
,000000
.569955
1,34953
(b)UHH » 11)
SKEnNESS
.242119
.V9S666
,364092
1,01401
1,08200
,501066
1,42602
1.00571
1.3878J
1.3UB35
1,48722
2.18198
1.91447
1.00000
1.51529
3,27<403
KURIOS19
1.59476
2.62^16
I.an><55
2,94326
2,50074
2,0502V
4,06366
anIRL EFI-LUtNI ISIORH « 12)
SIO DEVIATION
51.0016
36.682V
,5«e
-------
O'UHIEN 1 UERt itlUNtEBS, INC. LABORATORY Dili SYSTEM
ROCHESTER CSO PP •— PENFOKMAhCt DAIA •-- PN1M-
PARAMETER POINTS MINIMUM MAXIMUM AvtKA&t eta, HLAN
AUG 2b, IV76 08159
SnlKL IK-LUINI (SIOKH • 15)
311) DEVIATION SKEMNb&S NUB 10313
153
V83
IS
VS
SE1TS
BUDS
COD
IOC
Olb
PH
IKN
TIP
AL
fCOLI
PARAHUEH
ISS
V4S
13
VS
SEIT3
(iOOS
COD
IOC
OiG
PH
IKN
UP
AL
fCOLI
PARAMETER
T33
V3S
IS
VS
SEITS
8005
COD
TOC
DIG
PH
IKII
11H
AL
FCOLI
PARAHflER
1S3
V33
13
VS
3E1T3
BOD?
COD
TUC
DIG
PH
IKN
IIP
AL
rcoLi
PARAMETER
133
VSS
13
VS
SETT3
BOOS
COD
IOC
Otli
PH
IKN
UP
AL
FCOLI
12
12
0
0
11
12
0
12
0
0
u
12
2
0
POIN1S
9
3
0
0
1
9
0
4
0
0
4
4
0
o
POINTS
10
10
0
0
u
10
0
10
0
0
10
10
0
ft
points
11
11
0
0
4
11
0
11
0
0
11
u
0
0
POINTS
6
6
0
0
2
6
0
6
0
0
6
6
0
0
bl 0000 157.000
17,0000 70.0000
.100000 1.20000
16,0000 90.0000
IS. 0000 50.0000
,7oOOOO 8.70000
,6jOOOO 2,26000
95,0000 169,000
ROCHESTER CSO PP —
MtNIMUH MAXIMUM
60.0000 185.000
30.0000 58.0000
2.70000 4.00000
11,7000 36,0000
24.0000 42.0000
1.60000 4.SOOOO
.050000 .400000
ROCHESTER CSO PP —
MINIMUM MAXIMUM
i7,0000 294,000
40,0000 20U.OOO
2.SOOOO 13.0000
67.0000 221,000
11.0000 108,000
2,90000 8, 4000(1
.170000 ,970000
ROC'lESlER CSO PP —
MINIMUM MAXIMUM
76,0000 96.0000
21.0000 fj.0000
.100000 ,100000
11.0000 ni, oooo
20,0000 105,000
1,50000 7,00000
.2*0000 ,6?0000
ROCHES1ER CSO PP —
HjNluuM MAXIMUM
59,0000 HO.OOO
12,0000 48,0000
1.00000 1,40000
11,0000 13.0000
IS. 0000 27.0000
.tooono 2,soooo
.160000 .260000
114.417
10,4167
2,07!>00
17,1667
1OOOO
1.2SOOO
1,61583
102,000
PEHFORHANCE
AVERAGE
140.111
41.1250
1.86667
SO. 1689
32.7!>00
J. 65000
.707500
PERFORMANCE
AVlWCt
lie. 400
94.SOOO
S.SbOOO
121.400
4), 1000
4.9(1999
,524999
PERFORMANCE
AVERAGE
38.545°
IS. 5454
.125000
51.8182
17.0000
1.12727
.4B818I
PERFORMANCE
AVERAGE
99,0000
27.6667
i, 20000
26,1111
18,6667
1,666(7
.205000
109. B49 10.667B .251999
ij.1014 11.4916 1,20996
l,7!>49j ,967421 .4bl744
31,7640 22.7009 1,1S!>96
%
ll.OIStl 9.54176 .16e;flOE-»l
2,1022) 2.60114 1.04018
I,i03tt .544478 .457302
ll>,996 47,0000 .000000
DAIA •"- PHlH-SnlRL tK-LUEIIT (3TURH I 161
CEO. MEAN SID DEVIATION 3KEHNESS
I1S.902 12.260V .502842
41.8032 10.6215 ,12869!,
1,7658$ ,811999 .619104
16,1938 9,46777 .612285
11.7961 7,85414 .29992IE-01
2,40415 1.19269 .594111
.680021 ,190181 .219871
DATA ••• PHlH-SnlHL mtUENl (3TUHH II 17)
CEO. MEAN 31U DEV1M10II SKEtlNtSS
121.580 71.0911 ,0t005b
79.652S 58.0969 .877614
4.48604 1.85110 .V4B142
110,441 54.7196 .711184
11.9121 28.0741 1.11818
4.71995 l.694lf 1,02751
,Ub|844 ,249289 ,111829
DAIA ... PtUM-ONIHL CFFLUENT (DTURH • U)
GtO, MEAN SID DEVIAIIUN 3Kt«»E!5
88,1187 6.2S7S5 .162112
17,1522 10.2102 .13BI8IE-01
.122172 .411011E-01 1.15471
51.2I1S 17.097) ,411116
12,9154 22,6756 2,15985
2.34014 1,91220 ,717211
.1167922 .115411 .114149
DAIA .'• PRIM.3HIRL tf'LUENI (SIOKM 1 19)
GtO. MEAN 310 DEVIATION 3KEHNES9
91.7661 18.9487 .S62916
24,9856 12.1511 ,509091
1.18122 .200000 .000000
24.6256 9.06764 .68101BE-01
18.0071 5.249)4 .742009
1,5716) .5617111 .244816
,201789 .1S919BE-0! .142016E-04
I.91UOO
4.44801
1.82631
1. 07412
i. 67.166
2.46U45
1.62043
l.OOUOO
KURTOJI3
2.06121
1,40479
1.50UOO
1.61922
1.10270
1.74801
1.29M5
KUHIOSU
2.11950
2.12194
2. 14(117
2.01601
1,4)541
2.8JU10
1.9UU97
KURIOJIS
2.14620
1.301)17
2,13115
1.56 036
7.01668
I,9jb64
1.69S24
KUBI09IU
2,05024
I.IIS466
i.ootioo
1, 53^60
2,0)54)
1,69149
1,77251
178
-------
APPENDIX C
Statistical Analysis of Influent and Effluent Data
Microscreen System
Note: Concentrations of all parameters except pH
and SETTS are expressed as mg/1. SETTS
concentrations are expressed as ml/1.
'STORM *~\2 --03/03/75
«£>
PARAMETER
AL
BUDS
CL-M
PH
SETTS
TC
TOS
TIC
TIP
TKN
TOC
T.S
TSS
VDS
Vi
VSS
PARAMETER
BOD'S
SETTS
TC
TIC
IIP
TKN
TOC
TSS
VSS
POINTS
20
19
20
20
20
20
20
20
20
£0
20
20
20
in
20
19
POINTS
20
20
20
20
20
20
20
20
20
MINIMUM
.000000
22.0000
300.000
6,yOOOO
1.00000
32.00-00
369.000
15,0000
,/OOOOOE-01
2.20000
13.0000
829.000
10?. 000
4,00000
147.000
42.0000
MINIMUM
26,0000
.500000
34,0000
13.0000
.290000
2.60000
12.0000
98.0000
40.0000
INFLUENT --
MAXIMUM
2.10000
26a.ooo
1404.00
7.00000
5.00000
tO<*,000
2400,00
28.0000
13.9000
6.10000
76.0000
2963.00
706.000
229.000
469,000
543.000
EFFLUENT - -
MAXIMUM
66.0000
2.10000
89,0000
25.0000
,600000
4,bOOOO
71.0000
317,000
123.000
ROCHESTER CSO
AVERAGE
,780000
102,308
599.500
6.64499
2,67500
53.1000
1064,85
20.6000
3,31450
3,07999
32.5000
1381,50
31-6,650
102.000
232.250
194,789
ROCHESTER CSO
AVERAGE
44.1500
,959999
64,6000
19,1500
,421500
3.45499
45,4500
157,650
65.9000
PILOT PLANT -•
REO, MEAN
,000000
62,5904
543.568
6.64130
2,48365
51.1577
972,249
20.2507
1.14402
3,55761
29,6438
1306,05
261,195
72,2852
221,637
145.834
PILOT PLANT «
GEO, MEAN
42,6341
,872660
63,3941
18,7040
,413622
3.4168B
43,240o
147.630
62.3036
FMC DATA
STD DEVIATION
.572363
60.4483
269.865
.206095
1,03090
15.4722
463,507
3.83927
5.59021
1.02742
14.4482
512.281
193.387
56.9962
78,5658
146,474
FMC DATA
STD DEVIATION
It, 5986
,466261
11,8085
3,69154
,810723E-01
.524657
12,1593
65.6569
23,7800
SKEWNESS
,599790
.950541
1,38269
.311332
,724954
1.5U40
1.0o084
,4l2o54
2,08677
1,25404
1,21554
1,62301
.675189
.101331
1,58162
1,02810
SKEWNESS
.292574
1,30471
,356076
.235666E-01
.166041
.690495
.423056
1.41295
1,15870
KURTOSIS
4.14353
2, 91556
4,30510
1,98125
3,00761
6.37626
4,20748
2,24096'
5,84£08
3.53427
4,78067
5,49087
2.07204
3,08018
5.00Z03
2.99167
KUR10SI3
1.92597
3,33796
3.80773
1,79271
2.32153
3.17363
4,51938
3,76480
3.23386
-------
STORM "13- 03/12/76
PARAMETER
AL
BOOS
CL-M
OS.G
PH
sens
TC
TD3
TIC
TIP
TKN
TOC
TS
TSS
Vl>3
vs
VSS
PARAMETER
BOD 5
04G
SETTS
TC
TIC
TIP
TKN
TOC
TSS
VSS
POINTS
3
3
3
1
3
3
3
3
3
3
3
3
3
3
3
3
3
POINTS
3
2
3
3
3
3
3
3
3
3
MINIMUM
,000000
70,0000
151 ,000
86.0000
6.50000
a. 50000
75.0000
45«,000
as. oooo
.560000
4.31000
46.0000
613.000
13fl.OOO
7.QOOOO
I3a.ooo
90.0000
MINIMUM
107.000
75.2000
2,jOOOO
114.000
32.0000
.SflOOOO
5,92000
72,0000
200.000
103.000
INFLUENT
MAXIMUM
,000000
168.000
196.000
86.0000
7.00000
18.5000
1*16,000
746.000
33.0000
.6&OOUO
5 . 4
-------
STORM"-|7 - 05/11/76
PARAMETER-
AU
8005
CL-M
OiG
PH
SfcTTS
TC
70S
TIC
TIP
TKN
TOC
TS
TSS
VOS
VS
VS3
PARAMETER
BOOS
0*6
SETTS
TC
TIC
TIP
TKN
TOC
TSS
vss
POINTS
9
9
9
a
9
3
9
9
9
9
9
9
9
9
9
9
9
POINTS
6
3
2
6>
6
6
6
6
6
6
MINIMUM '
.000000
73.0000
58.0000
25.2000
6.60000
3.S0000
45.0000
330.000
24,0000
.170000
2.10000
22.0000
443.000
83.0000
53.0000
11?. 000
14.0000
MINIMUM
187.000
45.6000
6.00000
106.000
29,0000
1.0^000
6.00000
73,0000
240.000
136.000
INFLUENT --
MAXIMUM
2.50000
313.000
104.000
59.2000
7.20000
13.5000
164.000
574.000
36.0000
1. 53000
5.30000
128.000
94S.OOO
39S.OOO
213.000
406,000
230.000
EFFLUENT --
MAXIMUM
240.000
56,8000
8.50000
162,000
49.0000
1.44000
7,70000
127.000
400,000
250.000
ROCHESTER CSO
AVERAGE
1.01111
134.222-
76.1111
36,7000
6,84444
7,66667
100.889
432.889
28,0000
.632222
3.38389
72,8889
611.889
179.0.00
113,333
213.111
99.7778
ROCHESTER CSO
AVERAGE
202,333
52.2000
7. 250 0^
135,333
36.3333
1.24167
6.66666
99,0000
318.000
191,333
PILOT PLANT —
GEO, MEAN
.000000
118.235
74,9831
34,4311
6.84215
6,5o926
92.4494
425.752
27,6763
.50)528
3,177o6
62,2822
592.223
148.959
102.983
190.298
70, 021V
PILOT PLANT —
GEO, MEAN
201.449
51,9720
7,14142
134.192
35,8569
1.23342
6,63794
97,6800
314,476
188,406
FMC DATA
STD DEVIATION
.623672
76.6605
13.4614
13.7996
,177082
4,24918
40.4102
80.1865
4,47214
.421631
1.29910
36.7467
165.301
118.433
50.4777
107,502
83,6404
FMC DATA
STD DEVIATION
19,8634
4,78609
1.25000
17,2691
6.18241
,142410
,626276
16.0831
47,0213
33,1344
SKEWNESS
.632110
1,46067
.702531
,805846
,391899
,52SOOt>
.152109
.519388
1,07331
.954016
1.00261
.295042E-01
.9690S3
1,06074
,663657
.925324
.977973
SKEWNESS
1,65323
,553840
.000000
.231051
1.12598
.329673E-01
.459746
.173070
,121561
.147959
KURTOSI8
1,93242
3,90465
2,73584
1.99«J08
2,b8d46
1,50000
1,53688
2,10b95
2.42333
2.67506
2.48b9S
1 ,46784
2.50044
2. 36938
2.17751
2,30678
2.34238
KURTOSIS
3,96982
1,49999
1,00000
2,37340
3.28150
1.61U12
1,70033
2,67654
2,80541
2,93444
-------
APPENDIX D
Statistic Analysis of Effluent Data Dual Media Filters
Note: Concentrations of all parameters except pH are expressed as mg/1.
Dull Media Miter Influent Dill
0'HMt>i * Glut b'
|hC,
POINTS h|NIMJM
(.ABDItATURY UA1A IY9IEH OCT 26, |»76
fiOCHESUH CSU P.P. ... SWlNC DHFINC 10 IPM/^dfT
MAXIMUM AVERAGE OtO, MEAN 310 DEVIATION
ShtKIIESS
T3S
VSS
BOOS
IOC
coo
me
IK'I
IIP
PH
AL
PtkAMEIIH
TSi
VSS
601)5
IOC
CflO
QIC
7 KM
IIP
Prt
AL
PARADE lit*
T3S
VSS
BUrti
70C
CUD
Dili
IKH
UP
Prt
AL
PARAKEIEK
133
V33
POOS
IOC
con
O»G
TK'I
IIP
PH
Al
PAHAHE1EK
I3S
V3S
BOOS
IOC
con
015
TKN
HP
PH
AL
PAKAMETEK
T33
VSS
BODS
IOC
COD
DIG
TUN
TIP
PH
Al
59
59
SI
41
41
0
4S
4'l
42
22
PU1NIS
49
49
47
11
£7
1
11
10
10
POINlS
44
44
38
28
28
0
28
26
28
17
PUINI3
JS
31
27
13
I)
0
13
11
J2
23
POINTS
13
1)
5
13
0
1
1!
13
It
11
POINI3
116
43
47
47
17
0
90
48
45
JS
It, 0600
4,00000
1,00000
s, ooooo
11,0000
,200000
.SOOOOOE-Ol
6,10000
.tooooo
MINIMUM
16,0000
4,00000
1,00000
8,00000
11,0000
SB, 0000
,1100000
.HOOOOOE.Ol
6,90000
.000000
MINIMUM
16.0000
t, ooooo
9,20000
5, OOOOO
|U,OOUO
.200000
.5(100001.01
6.10000
.nooono
M|N|MIJM
l*,oooo
4. noooo
3,00000
*», ooooo
13,0000
,200000
,500000E-OI
6,10000
,400000
MINIMUM
126.000
28,0000
70.0000
19.0000
50,0000
1,00000
,200000
6,60000
,000000
M|NJHUH
52.0000
4.00000
6,00000
2.00000
11,0000
,000000
,100000
6,60000
.000000
4012.00
68.0000
14,0000
42,0000
71,0000
J.OOOuO
,66(1000
7,50000
1.40000
KOCHltlEB
HixlHUH
118,000
82,0000
65,0000
42.0000
71.0000
5U.OOOO
5,10000
.120000
1.40000
1,10000
HOCHtSTEK
MAXIMUM
4012.00
.66,0000
14,0000
41,0000
71,0000
t.ouooo
.660000
7.50000
2.4001)0
BOCMfSltO
MAXJMIIM
4012,00
68.0000
10,0000
42,0000
?7 ,0000
5,00000
,660000
7,00000
r, 40000
ROCHfSHfl
MAXIMUM
18", 000
l?4.!)00
lo.or.oo
If. 0000
60,8000
4.90000
,450000
7,40000
l.loooo
ROCMISH*
MAXIMUM
114.000
| 40.000
141,000
154.000
56.0000
4,70000
21.2000
7,90000
26,5000
IJI.S08
11,1220
17.1170
20.6511
i.mi?
. j 6U048
7,01664
,»Jb561
CiU H.P, ...
AVtHAGt
6U.S10*
10,'77S5
19,2468
19,19)5
10,7017
50,0000
1,201)2
.111871
,110000
CSC P.p. ...
AVERAGE
164.250
11,9316
f.^717
22.7657
22.1071
l.fiOOO
.242692
6.14999
1. 01176
C»0 P.P. .-.
AVERAGE
171,60*
JO. 1515
ll.4?22
21 ,6364
1 8,8485
1,47879
.221611
6,94994
,869564
C9U P.p. ...
AVERAGE
I4J.SI8
8*1, 2308
76.8000
39,2308
56,6667
4, 15J84
,104f.|5
6.92307
,59999*
C.10 P.P. ...
AVENGE
216,022
71,0222
JJ.7407
J7.70JI
2", 2941
2. 79386
1,014)6
7.I7J10
P.tJI4?
58,7505
26,6247
I5,2<)94
18,8004
|8,7XJ4
,949696
,1)6816
7.0J069
,698192
8M IMC OHF
CEO, MEAN
56,0755
at. 4440
16,0197
17,81)0
17,1134
56,0000
!l2!l!0
7.15806
,000000
510.788
11,86)8
8.08291
8.66664
«, 18354
1.1H85
,182010
,285287
.124441
INC 15 (.CM/SUM
31D DEVIATION
4I.I896
I|6
,000000
SHIPD DHf
ctn, MEAN
201. m
t6|70|4
12. 4917
?0.4J»2
.000000
,56)745
7.16519
.000000
3TD DEVIATION
U.2462
21,1774
7.02967
I7.0'i26
0.7590B
,579940
.7 Y3490F*OI
,»il78!
IHC 10 GPM/9QFI
STD DEVIATION
64,0082
29,6674
24,1)668
22, 09)5
H.5I??
2.0SJS1
S.61S1 6
, J80?9?
4~,?49|4
3KEHMES3
1.51216
1,10957
1.07797
.540471
.64761!
.919106
,120081
,619551
,5302901.0)
8KEHNF.3S
.425020
.281536
1. 81761
1,04727
1,22250
.590M5
,8716)21-0)
5,08917
KURTOSI3
4.71IJ7
2J7I21?
1.50000
?.579ie
2,36692
2,86684
>, 01177
KURIU3I3
3.6)688
?., 76618
7,91813
16,6J?P
2.5S9I7
?,Q65*jO
^,08982
1,75629
28,9488
. 182
-------
O'SHItX t CtHE ENGINEERS, !'-C.
PAHAfiEIEH POINTS MINIMUM
Dud) H..-Jia Filter Influent Uau
LABUHAIOBV mTA SVSIEM OCl 26, 1976
KOCHkSTtB C90 P.P. .» 3W|PO OHFlNC 15 UPM/10F1
MAXJHUH AVERAGE CEO, MEAN 3111 DEVIATION
16I«0
tss
vss
BODb
TOC
COD
OiC
TKN
IIP
PH
AL
PA«AMEt[K
TSS
VSS
BOO*
TOC
COO
DIG
TKN
HP
PM
AL
F.WFtllH
IS3
VSS
BOOS
rue
COD
otc
IK ii
UP
Ph
AL
PARAMETE"
T9S
VSS
B005
TOC
COD
010
TxN
TIP
PH
AL
PARAMOUR
TSS
VSS
BOD5
TOC
COD
otn
TKW
TIP
PH
AL
PARAMETJR
139
VSS
•005
toe
COD
DIG
TKN
TIP
»H
AL
15
14
16
16
II
0
11
17
14
25
POINTS
19
19
20
20
4
0
20
SO
19
19
POINTS
16
35
16
16
17
0
SI
17
15
27
POINTS
8
a
a
a
0
0
8
a
a
a
POINTS
IT
17
9
16
0
5
16
16
14
16
POIflS
Ji
25
1
25
0
2
25
25
25
25
52,0000
4,00000
7,00000
2,00000
11,0000
,000000
,120000
6,60000.
,000000
MINIMUM
192.000
44.0000
6,00000
26,0000
SI, 0000
1 ,55000
,100000
6,60f>GO
,000000
MINIMUM
52.0000
4,00000
6.00000
2.00000
11,0000
,000100
,100000
4,60000
,000000
MINIfUH
;o4,ooo
tl.OOOO
1 1,0000
21,0000
1,64000
,noooo
6,80000
7,00000
MINIMUM .
Ito'.OOO'
26.0000
17.0000
H.nooo
16.41)00
t.ioooo
.280000
1.10000
7,70000
, MINTMUM.
96.0000
50.0000
20.0000
Ji.oooo
1 fc.Aono
3. 41)000
'. 150000
4 .00900
000000
164.000
121,000
61,0000
154,000
21.0000
6,60000
21.2000
7,90000
26,5000
KocHiittn
MAXIMUM
296,000
122,000
141,000
IS4.000
56,0000
5.90000
11.0000
7,90000
1,20000
HOChtm*
MAXIMUM
194.000
112.000
141.000
10.0000
56.oooo
6.60000
11,2000
7,90000
16.5000
ROCM1 B TCR
MAX )MUM
276,000
80.0000
14,0000
ai.oooo
1.7SOOO
J2.0000
9.00000
1,20000
ROCHESTER
MAXIMUM
264.000
101.009
04 ,0000
210.000
86.0000
8'.11000
14,7000
6.SOOOO
lol.ooo
RPCMJSTER
MAXIMUM
126.000
111.000
28.0000
62.0000
IK, 01) 01)
8,10000
2,14000
6.90000
97.0000
"200. ill ""
45.1176
29,9444
13,1055
)S,1077
2,79545
3,11051
7.IIU70
1.14000
ceo P.P. ...
AVERAGE
242. ISB
92,7695
31,0000
47,0500
51.5000
2,11900
1.14599
7.16941
1.62771
C>u P.P. ...
AVtRACE
211.061
69,0000
16.11)1
n.llll
24.2941
2,90090
J.iuodo
7.1057)
1.17017
CSU P.P. ...
AVERAGE
210,175
7 1 ,6250
12.6250
18,5000
2,11175
6.74120
7.16210
2,55000
can P.P. ...
AVERAGE
165.765
59,7059
It. 111!
17,0400
3.UB74
1.66500
20.8871
can P.P. ...
AVERAGE ,
160, 3<0
58,1600
21.3113
46,6800
17,4000
5.09599
1.06959
5.88799
1J.6119
197,418
54,6115
24,6949
29, «li|
15.1991
.000000
.6100)2
7,20511
,000000
8H.PO DMF
C(0, M|AN
240.277
9Q.4762
24.0064
"2,I9|6
5J, 4694
2.19900
.671614
7.15691
.000000
65,2154
21.8706
11,2146
21.1021
1.91697
2 20U|1
5.69940
.170319
4.9S94C
NC 20 CPM/JOM
SID UEV[AJ10N
2«,4I22
19,1959
31.0122
27,16)7
1 .80279
1.11441
5.196)1
.40&297
l,0|0«4
*4222«E.O|
|24SIO«
,6406S4
1,54814
|,784«2
,461919
I.9I092
.220250E.01
4,ltO«74
3KEKNES3
.476989
.124465
2.12921
2.96S20
.000000
1,69160
I.4UI9
.2999591.02
,295109
J.T6289
2,19252
l.7149tl
19,9622
6,00503
1,60521
5,14091
1,97065
21.1791
KUKT091S
2,04010
2.1)5404
T. 57445
11,4X6
1.95207
5.19791
1,55962
1. 49611
l.7«"72
atiipo OHMNC 25 CPH/IU^I
CEO, MEAN
196.501
S7.8872
23.9694
10,1479
20.43U2
,000000
.SIOSJ8
7,09679
,000000
SID IHV|ATICJN
67.94»7
29.5142
25.8076
1S,740!>
16,11 22
2.09527
5.91596
,156921
4'. 9) 4 72
3HENNE3S
.104177
,51)629
I.H6290
.297954
l.2?2>0
,4410)1
t ,91960
.152SI06
4.45466
KiiHioais
3,10069
2.27777
3.00754
2.546)9
2.559)7
).»0941
5. 22046
9.06«7S
P2.2459
SMIPO DMFIPO to CPM/3SfT
CEn. MEAII
229.211
71.3507
12.59)2
17,25»0
2.02747
i.ioeji
7,35<15
2.52716
3TO DEV1AIION
23,3215
6,2617)
.956957
9,0829^
.684615
8.56301
,187096
,192783
9KENNC33
.599957
.562205E.OI
,191042
,5h8996
1,60122
.687796
,155901
,391060
KURT03I3
2.12991
U57079
2.51172
2.30107
4,20073
1.71211
1.87509
2.HJ74
3H|AP DMFtPO »< CPM/S«FI
.ctn', MEAN
IM'.Oll
54,0226
*9,06»»
J9.67JI
10.9220
2.751«8
,8509«5
IP.,«818
»Hi»p fpuf
ceo'. »E>N
1")2'.S80
54.3648
51.99J9
46.1719
J7.J9H
,8855(1
5.51019
.000000
S10. DEVIATION
40.255"
25.0711
9.585ES
4K.OJI5
25.15811
1^97448
1,19115
1.11255
IP 11 DPM/StFT
STD.OEVJATIpN
54.572!
22.9548
6^9569!
,600006
1.71001
.668206
l'.3«362
40',8595
SHEH'HJS
.594331
.599921E.01
.271106
3.27678
I. 19790
1.96951
>. 5S51I
2.27096
2. 26944
SKEHNtSS
1.13940
1.49143
.525009
,149543
,000000
.432672
,589402
.402697
. 901959
KURTnSIS
2.63777
1.56445
H2979
12',5732
2.95174
5.42000
11.6520
6.1(965
6.18954
Ki;RTn»IS
.42584
.47674
.50000
.28650
.00000
.176J2
.4)772
.17(46
.24256
183
-------
Dual Media Filter Influent Data
o'BHil'i t ctRE ENGINEERS, tuc.
LABORATORY DATA 3Y3IEM DCI 26. 1976
ROCHESTER can P.P. ... 3wjAp n' 20 CPM/JDPT
MAXIMIJU AVERAGE .GEO', HE»N JTD.OfVIATlON
>K(WNfSS
135
V33
BOOS
IOC
COO
DIG
TK'I
TIP
PH
'<•
pjHWir"
TS3
VS3
nons
IOC
CUD
OIG
IKN
TIP
PH
AL
PARAhFlFl-
IS3
V33
BOOi
TOC
COO
DIG
TUN
TIP
PH
*L
P»Ra"Flf R
133
V3S
noos
TOC
COD
OlS
TK'I
TIP
PH
«L
PAR»Hf Ifk
133
VSS
RU05
TOC
COO
OIG
IKH
TIP
PH
AL
PARAMF.1ER
133
VSS
B005
IOC
COO
OIC
7K'l
TIP
PH
AL
4
4
2
4
0
t
1
4
4
4
POINTS
3
3
3
2
0
1
2
2
2
2
PUINlS
5
5
5
5
0
0
5
5
5
5
POINIS
5
5
5
5
0
0
5
5
5
5
Points
T
7
7
7
0
0
6
6
6
7
POINTS
7
7
7
7
0
0
6
6
6
7
172.000
71.0000
20.0000
42.0000
40.8000
n, 20000
2.19000
4.00000
91.0000
MINIMUM
1«2'.noo
78.0000
24.0000
42.0HOO
86.0000
8.05000
1.25000
3.10000
95.000.1
BINIHIIH
204,0(10
61,00110
11.0000
30,0000
1.64000
.210000
6,60000
2.UOOOO
M,,,1W,,
201, onn
6),0ono
ll.aono
30,0flnn
t , f 4 0 (i 0
.2100KO
6, 80000
2,400110
Kill! HUM
140,000
20.0000
11,0000
21,0000
I.600UO
,250000
6,70000
,000000
MINIMUM
140,000
20.0POO
11.0000
21.0000
1,60000
.250000
6,70000
,0000110
212.000
89.0000
23.0000
66.0000
40,8000
9^70000
2,40000
4.10000
97,0000
BO.CH13TER
MAX i HUH
260.000
lol'.ooo
44.0000
44.0000
86.0000
8p33000
2P04000
3.70000
103.000
KOCH131ER
MAXIMUM
506,000
80.0000
13,4000
45,0000
2.5dooo
22,0000
7,60000
3.20000
MAXIMUM
248.000
Bo.ooon
13,0000
45.0000
2.50000
tj.opoo
7,80000
3,20000
HOCHtSIER
MAXIMUM
jjn.nno
76.0000
13.0000
56.0000
£.48000
2I,?000
7,70000
t, 80000
HOCHESIER
MAXIMUM
228.000
76.0000
13.0000
56,0000
t. 96000
21.2000
7.70000
2,60000
191.250
80,0000
21,1000
53,7500
40,6000
6.93333
2.26750
4.07500
96,4000
C30 P,P. •••
AVERAGE
208,667
66.5311
19.3313
41.0000
66.0000
8.18999
I.64SOO
3,40000
99,0000
C30 P.P. ...
AVtRAGE
218,000
70,4000
12,2000
37,«000
1.85600
7.«»I99
7.299V9
2,72000
'VtPAGE
?16,000
70,4000
12.2000
U.ROOO
1.85600
7.48399
7,29991
7,72000
C3U P.P. ...
AVtRABE
180.714
39,4?8t
11,5714
35,0000
2,27500
5,57499
7,19999
1.82857
CSU P.p. ,-.
AVERAGE
188,714
39,4286
11,5714
15.0000
2.27500
5.C499
7.19999
t.BAns?
192.617
79.61)4
21.4476
51. OU1
40.7999
•',91233
2.26610
4.07476
95.9837 (
3Mi«l> DMF
GEO*. HF AN
20S'.725
65.5736
34.7J92
42.9862
85.9999
ft. 1 88T9
1.59617
3.18674
98.91B6
11.4171
llS2?68
I 50000
8.84237
,000000
.612626
,8042S8E.«|
.033010E.01
- t'.71205
UP 2» GPH/SQFT
SID DEVIATION
36,3073
IJ.785I
6.59966
1.00000
.000000
.139999
,394999
,100000
u'.ooooo
.167701
,1101464.
,000000
, 714621E.O J
,000000
,8molE-OI
,64141)
1. 11451
1 .11470
3KEHHC33
,705498
.707107
.294802
,000000
,000000
.9I7U4E.04
,000000
.000000
,000000
1.10147
2,00000
1.00000
1.71304
.000000
1.50000
2.06743
2.13305
2.31333
KURT os i s
1.50000
1.50100
1.50000
1.00000
.000000
1.00000
1.00000
1 .00000
1 ,00000
3H|pfl DHFIPO.JO GPH/30FT
CEO. HilH
217. 4JS
70,0695
12,1766
37.44(19
1.82521
1.3407A
7.29119
3TO CEVIAIIDM
16.1986
6.6)131
,748131
5.11468
. K.60JU
9,16749
.157771
*,70!6? .299112
3KEHNE33
I.009S6
,265243
.143620
,135240
1.42254
.595080
,7656991.01
,343625
GtO. MIAN 3TO HFVIATIOH BKErtNESS
217.425
70.0695
12.1766
37.4449
1 ,82521
1.14018
7,291 J9
2.70J8I
3«|PO OMFt
CEO, MEAN
185,591
15,87»J
11.5492
35.IB71
2.23268
1.49395
7,19026
,000000
SHiPB OMFI
GEO. MIAN
185.591
•35.6753
11.5492
31.1271
2,23268
1.49393
7.190J6
,000000
16.1968
6.65131
.748331
5.11466
,166038
9.16749
.357771
.f.99312
«P 10 CPH/BOFT
SID nevi>itoN
34,1673
17,9412
.7e84 11
11,6005
,435612
7,76066
,174)66
,877045
AP 70 CPU/SOFT
8TD DEVIATION
34.1873
17.9412
, 7?8U3t
11,6005
.435612
7,76066
.374166
,877845
1,00056
, 265?43
.343670
,135740
1,42?54
,595984
, 7P56&9F.01
,503625
SKfHNFSS
,527jeoE.01
,948614
,659895
,«S6S07
.133124
1,?OB35
.439972E-04
1,06909
3KCHIIE3S
,5273606-01
.948614
.859B95
,436'i07
,131124
1,20615
,4399721-04
1,06909
KURTOSI3
.57676
.44669
,64694
.91576
.13423
.56796
.64550
,64694
KURTOSI3
2.57676
1 .44669
1.F4694
1. 91576
S, 13423
1,56796
1.64550
1,64694
KURIOSIS
1.33637
J.J9767
2,36391
2.06605
8,17590
2.870J7
1,50000
2.99303
KURID3IS
1.33637
2.79767
7.36391
2.06605
Z. 17590
t, 87027
1.50090
Z, 99503
184
-------
O'UKUN 1 CtfiE ENBINEtHS, IllC,
PABAMEIEH POlNtS MINIMUM
Dual Media Filter Influent I)3U
LAHOIUTaRV UAIA 3VSIEM UCT 26, |976
ROLHESIEN C3U P.P. ... aniPtl DMflAP 25 GI'M/SUfl
MAXIMUM AVERAGE CEO. MEAN 3TU D(V)A|ION
SKEKHES3
KUHT03IS
133
V33
SOOb
IOC
COD
OIC
IKH
IIP
PH
AL
PAhAhEIEK
US
VSS
BODS
IOC
COO
DIC
TKN
IIP
PH
AL
PWETEH
TS3
V33
BOOi
IOC
COO
OIC
IKH
IIP
PH
AL
PARAMETER
133
VSS
BODS
IOC
COO
DIG
IKH
TIP
PH
Al
PARAMETER
T33
V3S
8005
IOC
COO
DIG
TKN
TIP
PH
Al
PARAMETER
T33
V33
SODS
IOC
COO
CIC
IKN
TIP
PH
11
7
7
7
7
0
0
6
6
6
7
POINTS
56
56
26
So
0
5
57
58
56
58
POINTS
4
4
2
4
0
1
1
4
4
4
POINTS
4|
01
31
37
0
6
01
92
02
12
POINTS
03
01
28
39
0
5
«2
03
41
"
POINT3
4
4
2
4
0
1
3
4
4
4
100,000
20,0000
11,0000
21,0000
1,60000
,150000
6,70000
,000000
MINIMUM
51,0000
10,01100
20,0000
9.00000
19,1000
2.50000
,4000001-01
4.00000
.000000
MINIMUM
172.000
75.0000
20.0000
42,0000
40.8000
6,20000
.2,19000
4,000(10
41,0000
MINIMUM
Jl. OOOP
10,0000
10,0000
9,00000
21 , 6000
1,60000
.600000E »01
3,10000
,000000
MINIMUM
31,0000
10.0000
20,0000
9,00000
19,0000
2,90000
,*OOI)OOE101
4,00000
,000000
MINIMUM
172,000
13,0000
20,0000
42,0000
00, (000
e,?oooo
2.KOOO
4,00000
91,0000
226,000
76,0000
11,0000
56,0000
2.90000
21.2000
7.100UO
2,60000
HOCHUTEfl
MAXIMUM
126,000
1)4.0(10
14.0000
(6,0000
16,0000
6.10000
20,7000
9.10000
97,0000
KOCIH5TEH
MAXIMUM
212,000
69.0000
tl.OOOO
66,0000
00.6000
4.70000
2,40000
4.10000
97,0000
"OCHEMER
MAXIMUM
260.000
101,008
44,0000
210.000
86,0000
8.13000
10,7000
9.10000
103.000
ROCHESTER
MAXIMUM
126,000
1)0,000
30,0000
66,0000
5«,0000
9.30000
20,7000
9.10000
97,0000
NOCHI9IER
MAXIMUM
212,000
(9,0000
13,0000
86,0000
OO.BOOO
9,70000
?.«onoo
0,10000
97,0000
106.710
1 1 ,571 0
15,0000
2,27500
5, (7094
7.19999
1,826(7
C3U P,P, ...
AVERAGE
126.291
27.76(7
16,1296
20.6400
4.16642
1,4174?
6,17916
I6.J5I7
C3U P.P. ...
AVERAGE
191.250
6U.OOOO
21.5000
53.7500
110,0000
6,911)1
2,26750
0.07500
46, 0006
C30 P.P. ...
AVERAGE
104,1(7
29,61 29
!),62I6
36,9000
3,0946]
,645900
6. 19760
10.8190
C30 P.P. ...
AVERAGE
128,149
30.17S1
27,7657
36, 3590
26,6000
0,3333)
1 ,715)4
6.F125I
2».l»7«
C90 P.P. ...
•VERA6E
1'3,230
80,0000
21,1000
51.7500
40,9000
8,911))
2, »6730
0,07500
96,0000
I8S.S91
15.C7S1
Il!l2ll
2.21269
1, 09141
7.19026
,000090
30.187)
IF, '012
11.6005
.415612
7.T6066
,170166
,»T76«5
.527I60C-01
,94I6|4
.6S969S
,016107
,111110
1.206IS
,0)9972E'04
1.06909
1.1)817
2,79787
2.16191
2,06605
2.17S90
2,67027
1,50000
(,9910)
IK HP DKflHC II tPM/80fl
GEO. HEIN
104.6119
00,1640
27,6009
14,1440
27,6116
1. 44224
.444771
6,2f(«9
,000000
6ID DEVIATION
69,5101
26,6666
1.05101
11.5849
7.58136
1,51041
J, 46041
1.12277
10,7801
8KtHNE3a
,156697
,01)440
,995661
,601086E«02
.763696E.01
1,29698
4,11220
1 .292(1
1.7U75
KURI03I6
2.34192
2,02*10
4.12166
3.16667
1.02607
1.2(797
21.5104
1.99276
4.12120
3«liP DMriNC It GPH/60M
CEO. H(AN
142.627
74.1114
21.4476
51.0161
40.7999
(.9)211
2.26610
4.07476
95.9817
IHllP DMf
CEO, MEAN
67 6670
3li250a
27,4106
26, 6] 42
31,6291
2,66196
,201910
6,52402
,000000
310 DEVIATION
13.0171
5.52268
1. 50000
6.1142)7
.000000
.612626
,I04?BU( .01
,4)10|OE»01
1.71205
IHC 23 CPM/SDM
910 DEVIATION
61.0636
26, 4892
6,1)649
H.OS69
?2,768)
1, 456)1
2,23014
,121576
20,6676
9KEWNE3S
.167701
.601464
,000000
,7146211. 0|
,000000
,ei4301C>0|
.«02
-------
981
19fl*OE
olfto'z ;
06IO'|I
?Z9St *S
tono'sl
ttiti't
01(163*9
'
OOOOt'f
OOOO'ii
OOOO'lt
0000*01
OOOO'IB
ooo'tot
OOOOOO*
OOOOt'9
OOOOOli'
OOOO'Bl
00000'9
oooo'ot
OOOOO'I
00000*6
Bt
Ot
Ot
0
Ot
01
9f
9f
N'J
nto
no]
301
ss»
BMO'tl
to?«;;'t
00008*1
ftdlf'l
OtHB'f
. JtMSP
to-lnlitott1
'nan
009000'
os»tii!
zeiotM
09I9D't
tt(.50'f
«000(*t
BJft'W
NOIlilAlii nil
Hlit/H^-l «j
/tBOif
OOOOOO'
OOOO'lt
«ti*ti
BZll'ft
OOOOOB1
OOOOf'l
oooo f,?'
OOOB'Bf
0000'9t
OOOO'lt
OOO?*BI
OOOO'lf
oooo'(«
UnHTNtH
000000*
00001*9
to-ioooooi*
ooooot1
oooi't;
OOOO'lt
ooooo*s
00009*1
OOOOOO'
OOOOO'B
tt
u
f
«i
H1I3NDHVH
UH
H/l
tint
j»0
OD3
onl
sooo
BBl
cummin
WtO'B
t6t*i*l
OBliS*'*
B90J1M
ts/»o'»
BtJOO'f
oono^'l
Jllufi
ocoooo'
U«60't
t'9i tt
049t'tt
OOOOOO'
CtlS'Ot
<«9llO'/
llttlf
to/eft
9090'pt
l»B»*Bt
NHHIXVH
oooot't
OOOOl't
ooooot*
ooooo't
OOOO'tt
oooo'tt
0000*02
OOOO'ff
0000'6»
HOHINTW
OOOOOO1
OOOOB'9
lo-tooooot1
OOODOt1
00000*4
ooooo's
OOOOOO'
00000*4
OOOOO'I
!!
«r
?f
tt
f
6f
1»
.Hi
Htl
t>n
31)1
R«A
CSl
ctsninnii
NouvtAid olfi NV3H 'risS
UnE/MHrt oi SNJJHO ON I MB
9l*t '9? 130
HdHtirvH
miSiHSOH
HnwtNtM BJNtOH
Tivn
J31HJ
-------
Dull Media Filter Effluent Data
O'KHltN I
INC,
P4fUME|(H PQINT.* HINJMUM
LMOK1IOK1 UATA «y»|tM UCT 26, |y?6
ROCHHUS C3I> P.P. «. *N|PQ DHFINC 19 CPH/IUFt
MAXIMUM *VlRig( OJO, MEAN (TO pEyjAtlON
•KEhNEJS
KUBI05I?
III
vis
BOOS
IOC
CQD
DIG
TKN
UP
PH
PABAMftfH
tss
VB*
BOOS
IOC
CUD
010
IKN
UP
PH
At
PAK»MEIEK
148
V«>
BODS
IOC
COD
CIS
IKN
IIP
PH
AL
PARlWClEfl
T8S
VSS
BODJ
TOC
COD
010
IKN
IIP
PH
At
PARAMETER.
T89
VSS
8005
TOC
COD
OIS
TKN
TIP
PH
At
PABA«m*.
19S
VSS
(005
TOC
COD
DIG
TKN
TIP
PH
It
24
ft
11
II
4
16
JO
17
16
point?
17
(7
6
17
2
4
17
17
17
IT
PPINIJ
If
1$
9
14
tl
4
It
It
It
If
POINTS
g
8
4
8
4
C
S
*
•
POINTS
25
21
)
2)
4
8
24
24
2)
24
POINTS
16
16
2
15
4
4
• 19
15
15
IS
16,4444
4,44444
1,14440
2,00040
It, 0444
,600440
•444400CvOl
5,40040
,444444
MINIMUM
46.4444
16.4404
11,0040
(.00444
19.4444
,144444
,?44444E.01
6,10000
,040044
HINJHUH
21,4404
7.44000
1.70000
1.40004
11,4004
1.00000'
.tOOOOOtrO.1
6,14444
.044444
MINIMUM
16,4440
,000444
11,4440
1,17000
,i44009t«OI
6,70009
,044044
^MINIMUM
T.84494
'.•ooood
IP. 1000
9,04044
l'50444
'.044009
3.50000
',040004
MINIMUM
10,0004
1.14444
11.1449
3.00000
2 $4446
'.*44040t*0t
l.JOOOO
.040004
(4,4000
11,4944
(,04044
11,0044
16,0444
4, 14404
1,41000
1.44440
22,7044
HOCHIIH*
MAXIMUM
172.444
*4.9444
14.0000
29.0400
11.0000
4,44444
1.7)494
7,60000
1,44044
BOCHUTH
MAXIMUM
114,440
49.0940
1,60000
10.4044
fq.4944
1.44400
1,40000
7.74400
,400404
ROCHI8TEN
MAXIMUM
1)4,444
34.4444
24.4444
2,58444
12,4044
(,44400
1,24004
BOCHMTES
. MAXIMUM
118.440
9J.0444
42,4004
41.4404
ti. 2444
8,1)000
1,48044
*,*4044
*1,4464
•OCHtltl*
.MIXIHUM
144.400
02,4444
21.9444
14.0449
V. 40000
'.1*4004
7.14444
ft, 00114
"l»*4400**"" '
u!*ioo
5.1749*
10,1151
11,7271
1.44400
.iioooo
U10094
"l"((l»""*
J.7WT2
11.671*
1 .416*9
,il 7)1*
}, mil
•994044
U.D66
1^46066
1,79(21
1 ,212$(
1,0(076
,4755.20
,*(0
11.6*42
C|U P.P. ... |M|PO ONFfNC 24 GPH/IOFT
AyWAff
92,2941
)*.70S»
20, >m
l»,)«»
11.49.44
1.1442)
,429991
7,'IKJH
,«l)»jt
C(0 P.P, ...
iVffllQt
64.4667
24. Hi?
li.4714
26.9991
1,17511
,|49})I
6.16666
.164044
C90 P.P, ...
AVEPACI
(4,9444
21,7500
|7,5044
1,162)4
r',4i"o
,(94900
CIO P.P.* ...
•ve«ef,,.
21,2604
9.10404
2°.))))
]9,(649
|*JJ*»J
,t)248)
6,M9**
7.962SO
eso P;P; ...
•«••«?,.
50.73U
21.4544
17,74,00
Pl.)fi)
J.85^99
.131)11
6.*7»4»
3.1733)
CEO, HE>N
(9,5214
14,t«l2
n'.lajo
)».')»«
1 7912S
.102612 .
7.277(2
"40040
110 DEVIATION
17,2961
11,1765
1.1)770
j|oooop
,77(1*2
,864917
,612419
IXEHN.EH
,766(72
.602042
.67I790C.01
,000000
1 .(2551
2.46429
,S26*fi)
,11192)
KUH10SI1
,26454
,16476
!l7ilt
,04440
.)009)
,2(22)
,((>SO
,169)9
J»|PO OHFINC 21 CPH/««F7
CEO. «((N
57,7517
I7,6i«l
6, (17**
II.8M9
|jJJ°*{
6,95)64
,440044
SH|PO CMFtl
CEO, H|>N
78,6711
.044044
17, 4«I2
,$69774
T.tom
,444044
(HllP OHP)
.0?o;.«E«N..
!,08M«
{•• liJj
|3(9907
is.tsio
*.i941f
,440094
6*,4i )*8
.000««4
8Hl«* DMFl
,OEO',.m«N. ,
(2.86*9
15,5174
IT.l*(4
19.44)4
2* 7*11*
.9898 488*01
6'.6«)7
.000940
ITO PCyiMION
27 9496 -
u!«i«
l,)241)
(.44701
U.D1I
,*096(7
.421164
,4217(9
.19599*
0 14 CPM/IOFT
ITD DEVIATION
26,9815
11,0199
). 79819
,176511
), 87023
?466)69
•0 »» OPM/»«^t
«T6.0EVt»fI?N
X.03TO
l)io»07
7.455Q6
ij',644"2
1.7)841
.428786
,(900)9
ti.*(12
IP l< OPM/IDFt
• Tp.OEViMIpN
H'.4I54
4,24444
7.6949?
41
,753114
2,21585
,5448)9
,717146
._8H|HNe88.F
I.70889-
1,62984
«'05594
2,04449
!:?!!»
r.09?9)
2,»)6>2
1.01442
•KEHHESS.
.176096
.7094I8E.9I
.990400
.6978**
(.6*141
J.JIT53
3.21144
J.4T401
KURIOII*
1 *(129
1 if 455.fi
4, 99679
2,9(464
1,75009
1.6646)
10. till
2,7446$
1,16667
KUR109II
1,84451
f ,(891 7
2,69154
3,971)2
6,44198
), 44(77
liT9429
_KU(ITOSI8
4.10177
I.1276D
1.50000
6. (5541
5.J4556
H.J9267
9.18228
».)1II)
1 O'jl (68
./VK'P'I'
J.11079
1.91781
1.94444
3.479*6
9.19964
t.1216?
11,06??
11.4528
187
-------
Dual Media Filter Effluent Data
O'BRIEN t GERE INOIIECBI, INO'.
P*R»MtlER POINT) . MINIMUM..
TSS
VSS
8005
toe
COO
010
T>IS
SQ.OlTl
Jfl.Hll
1* 8P|iT
t'""'
f277il
I.S*»11
It' 4709
S, 11Q! t
•'. 1?290
,«IBit9
,171771
,l!9|ltl.0l
,100000
PO tl OPM/ltFI
8TO.OEV|MION
)i,S«lt
4 '.10 105
,41SSI4
10'.I7I9
,191907
, 1*7771
,101111
.411141
.totitl
,4B)M6
|irt>t9i.os
IKEHNEII
,llt|Sl
,441719
.750*10
.2A014S
1 ,49i44
.171114
.ultoor.oi
I ,91S|I
I.T99I7
1.10431
;!tzto9
KIIRTOSIJ
J.176JI
?' 232tl
!.|9lao
1 . 40lQt
l.tsooo
POINIS MINIMUM...
BOCHEIIEll CIO P.p.
HtKIMUM AVEPtGC
IHtPO DHFltP II OPM/IOFT
CEO', *riN JTO,otvi*tlpn
IKfMNIII
KURTpSM.
TS8
VIS
Born
toe
COD
otc
TIP
PH
it
TSS
VSS
BOOS
IOC
COD
04G
TXN
TIP
PH
IKEHNESS
,tni*i)
1.31011
,214048
,114941
,1511451.01
|«577»0
«!lUt»B
1,71808
1.41104
«.«7tt9
1.74111
KyRTpSJS.
t. 10002
I.IT3S*
_
1 .fcolSI
t'.TIlll
t.T«S05
2.II2IS
J.UT99
188
-------
Dual Media Filter Effluent Data
O'BRIEN I CERE ENGINEEH3. INC'.
PARAMETER POINTI M|N(HUH..
LABORATORY DATA SYSttM OCt 26. 1976
RocHEsm C9o P.P. ... 9»iiPo DMMAP 25 GPH/IOPT
M»X|MUM . AVERSE . CEO', MEIN JTO.DEVOTION
16124
8KENNES.S
XURTOSI3
T99
VS3
BOOS
TOC
coo
OIG
IM
IIP
PH
AL
PARAMETER
TS5
V9S
6005
TOC
COD
DIG
tKN
TIP
PH
AL
PARAMETER
T99
V9S
nons
TOC
COO
OIG
TKN
TIP
PH
AL
PARAMETER
T93
VS3
BOOS
TOC
COO
nic
TKIJ
TIP
PM
AL
PARAMETER
139
V39
BOOS
TOC
COO
OIG
TKN
TIP
PH
AL
PARAMETER
TSJ
V99
BOOS
TOC
COO
OIG
TKN
TIP
PH
AL
7
7
0
7
0
0
7
7
7
7
POINT3
72
72
95
68
0
4
71
71
71
7J
POINT!
4
4
0
4
0
1
4
4
4
a
POINTS
51
51
27
06
0
8
44
49
49
49
P01NT3
15
15
25
10
0
4
14
15
14
15
P01N73
1
4
0
4
0
1
t
4
4
4
20.0000
4.00000
7 '.00 000
I'.IJDOO
'.100000E.OI
7'.00900
'.100000
.MINIMUM
7,00400
2.00000
6.40000
'.000000
11.4000
2.40000
'.4000.00E.OI
4.00000
.004000
.MINIMUM.
74.0900
21.0000
27.0000
26.8000
7.50000
'.940000
4.10000
60.0000
MINIMUM
7.00000
1.00000
ll.oooo
5,00000
'.oooooo
1. 10000
'.oooooo
1.70000
.ononoo
MINIMUM .
7.00000
'.700000
4.00000
1.00000
9 ',60 000
2.00DOO
'.ioOOOOE.01
1.80000
'.oooooo
MINIMUM
22.5000
8. 11)000
20.0000
20.QOOO
7.40000
'.JIOOOO
4.10000
40.1000
144,000
00.0000
14,0000
J^JOOOO
1,21000
7,80000
1.20000
SOCMIMEK
MAXIMUM
178.000
74.0000
26.0000
51.0000
11.6000
7,10000
1,4)000
7.10000
84,0000
ROCHESTER
MAXIMUM.
116.000
40,0000
48.0000
26.8000
•lloooo
1,77000
4110000
84.0000
ROCHCITElt
.MAXIMUM
2oo'.ooo
95.0000
11 .0000
'05.0000
25.2000
8152000
1,67000
7.00000
81.0000
ROCHESTER
MAXIMUM
110,000
41.0000
26.1000
42.0000
15,2000
7150000
1,42000
7.40000
81,0000
ROCMEITEH
MAXIMUM
104'. 000
18.0000
40.0000
20.0000
8' 20000
1,42000
4.10000
84.0000
41,7141
21.4714
21.4286
1.76428
7,41428
2,40000
CIO P.P. ...
AVIRAGf .
46.8469
21.0444
18.0280
24.9215
25.2000
5,69416
.097017
6.48105
12.1888
C30 P.P. ...
AVERAGE
117.250
44.9500
40.5000
24.8000
7.89500
t , $0.240
4,11000
81.7500:
CIO P.p. ...
AVERAGE
44.5841
24.0000
20.2000
22.4565
19.0000
2.25959
.245418
4.52841
6.47144
C90 P.P. ...
, AVERAGE
11.0771
4.42857
18.4770
14.7667
12'. 1000
1.48215
.140284
6.64411
4.4142*
CIO P.P. ...
AVERAGE
41,0000
21.6400
10.2400
70.0000
7.81111
.8J4944
4.14000
64.8240
"eolioto""'
is^ija
14.4047
l'.744»7
'.127819
7,408(4
2.21171
4 j', 1426
10.8146
8'.24171
• J55726
.115707
,289968
.709124
.484808
.526195
.2S4111
.111162
.475055
,152960
1.11444
2.00611
1.84408
2.21067
2.S7197
2.188J!
1.77158
1.46280
Ih'lAP OMFINC II CPH/HH
CEO', MEAN
40.1028
15.5505
17,1779
.000000
r
24.1719
!'.504I9
'.}t 7044
4,18129
,000000
8!D.r>EV|»7IgN
4|,1I47
10.9159
4,40558
II.S9JS
6140624
1. 54174
,104244
I.OHIO
27.1697
. 8K(HNES9 .
,475544
l,064!0
,442448
.41747!
,5817021-02
1.77164
1.70.428
1.44417
2.09204
. ..KUHT09I9
2.18749
f.$40|!
1. 16441
7.03861
1.00778
4.65774
4.70107
5.01940
5.41140
IKlAP OMMNC 21 CPM/IOPT
. GtV, MEAN
I14'.049
4S.8800
14,4618
26.7449
7,814|)
I,49S«6
4,I44|0
80,64(1
810. DEVIATION
24' 8110
10^2561
e'.0777S
.000000
,194741
,141465
,1660241*01
ll'.S574
8KEHN&33
1,04418
,672180
.922071
,000000
,692004
1.12740
1,11476
1.11470
KURT09I9
2.21679
1.86128
2.16052
',000000
2.06195
2.11072
2.11141
?,mtt
9HlAP DMFINC 24 GPM/tgfT
CEO*. MEAN
42.4174
I4I2740
I4.44»
20.2»f4
.000000
2'. 064 17
.000000
8.50717
.000000
310. DEVIATION
42" 1558
14^4685
5.6274!
4.11264
7114846
1,19581
.J60647
,454007
11.5915
9KE NE99
.421018
1.21144
.SIH77
.171719
1.64605
1,11071
2,96644
4,91969
5,71144
KIIRT09I3
1.18901
4.48005
2.05782
1.20697
4.66229
16' 0188
16.4969
10,8540
17.7771
9H|AP OMPlPO II GPM/IIFT
,GEO'. MEAN
7'.712JS
2.26657
17.1081
I2.26t4
I2.09>5
1115515
4.57220
.000010
87D.pEV|AMgN
22.8819
4,101711
6,15114
8155(115
2^21585
1.11526
1 .11878!
,852147
I4.JU6
. 3KEWNE5S
1.70910
1.70474
t. 42126
t. 61065
.9I0726E-01
3. 49679
2.92909
t.54!4l
1. 81449
. KURT03I3
14,1586
l$,2689
1.68644
6.41124
1.16667
4.J0751
10".720.2
8.17568
15'.6042
8«|A» OMPIPO 28 GPH/SOfT
.GEO'. MEAN.
47,6816
17,0102
29,1245
20.0000
7182611
.6680(4
4.144)0
67.0861
alO.DEVIATIpU
18'.I65B
11.5182
e'.07!88
.000000
.124981
.401221
,866024E»0|
17'.5851
9KEMNE39
.24I791E.01
.726I21E.01
.496469E-01
",000000
.294746
.110926
1.14476
.956927
..KURT08I3
1.01444
1.04709
1.29005
'.OOOOOO
1.49998
1. 21999
2.1HU2
2.16622
189
-------
APPENDIX E
Chlorine and Chlorine Dioxide Analytical Data
Note: Concentrations of F.Coli are expressed as colonies/100 ml,
CL0 DATA
ID
O
SAHP NO.
«37P7
13727
43727
«3731
03731
09246
«9c9fl
19290
"9561
49SM
49561
19561
19561
09561
09561
19561
09563
09563
1956)
09563
49S63
19563
PHEOICTtD
LOG KILL
2.47966
2.31601
2.30654
3.50014
3.74711
3,50631
3.960S8
0.25362
2.77611
3.13845
3.13469
3.54031
2.03719
2.30113
2.46350
1.6*340
1.91252
1.35839
2.098H6
3. 24696
2.157SB
?. 43710
2.oC907
2.>)067u
2.266J6
2. .12628
i.i37M
3.76960
4.1)3559
5.03172
5,18281
2.1 0527
2,37769
2.34546
3.50167
3,95477
4.23383
2. 58931
3.13130
2.709SO
3,Ofc04S
3,27643
3.31757
0.11955
4,41022
5.31892
3.74626
4.01274
3.70101
4.27320
0.57472
OBSERVED
LOG KILL
3.6B649
3.30670
4,?B4u3
6.57403
3.61979
3,0641)6
3.5»7n?
3.6639J
5.92912
3.45230
4.34242
4,J42<|?
3.?0202
3.UM03
3.39581
3.92942
3.72984
3,55760
3.17944
3.90982
3. 73373
3,55764
5.7715?
3.57'JOS
4.03119
".4191 5
3,04201
3.01707
3.94201
4.41913
4,72016
3.J25P5
«.?5527
3,77815
3.65J21
3.55630
4.07918
5.68425
3,79339
3.59710
3.93558
3.61730
O.puOSS
2.97575
4.116240
3.60639
3,41326
4.0043?
3.3»53S
3,11245'J
3.74905
RESIDUAL
-I.UC6S3
-.99029
-1.37SM
•3.07369
.12752
-.45865
.39356
.56909
-1.15131
-,313?4
-1.20773
-.80211
-1.164^3
-.99990
-.°32i2
-2.23602
- .817J3
- .69925
- .06056
- .66267
- .57545
- .1ZC54
- .16245
- .56733
- .754o3
- .9:9
-.O47'i7
.(19358
.61259
.96265
-1.22058
-1,87758
-1.232b9
-.15154
.39847
• .ISIoS
-1.09444
-.66209
-.88725
-.92479
-.340S7
-. 59298
1.14332
-.05217
-. 28756
.3J501
,008«2
,473?6
.84867
.S25SV
oost
CHG/L)
3.1
3.1
3,9
9.1
9.1
£1.9
6.9
0.9
6.2
6.2
5,2
5.2
5,5
5.5
5.5
4.2
4.2
3.3
3.3
3.3
4.2
a, 2
o. a
3.6
3.6
3.6
7.8
7.8
7.8
14,4
14.4
3.6
3.6
3.6
7.8
7.8
7.8
7.8
7.8
8.3
3.3
6.3
13.0
13.0
13.0
7.8
7.1)
7,8
9.5
9.5
9.5
D.T.
(KIN)
5.6
3.6
5.6
3.8
5.6
1.5
3.0
4.5
1.1
2.2
1.9
3.8
1.9
3.8
5.6
1.9
3.3
1.9
3.8
5,6
1.9
3.3
5.6
1.9
3.8
5.6
1.9
3.6
5.6
1.9
3.3
1.9
•3.8
5.6
!.•»
3.6
5.6
1.9
5.6
1.9
3.8
5.6
1.9
3.3
5,6
1.9
3.6
S.6
1.9
3.3
5.6
GT
69601.
89527,
89604.
895P7.
896C4.
67211.
67302.
67394.
53795.
53893.
69451,
B9527.
69451.
69527.
b9o04.
89451,
89527.
69451.
69527.
69604,
69451.
89527,
69604.
89451,
69527.
69604.
69451.
69527.
89000.
69051.
69527.
69451,
69527.
69o04,
894S1,
89527.
69604,
89451.
89604.
89051,
89527,
P9604,
89451.
69527,
64604,
69527.
69604,
B9451,
69527.
89604.
TEMP
C C)
7,0
7.0
7.0
7,0
7.0
9,0
6.0
8,0
5,0
5.0
5,0
5,0
9,0
9,0
9.0
9.0
9.0
9.0
9.0
9,0
9,0
9,0
9,0
8,0
8,0
Sl.O
8,0
8.0
a.o
8,0
8,0
6.0
8,0
8.0
8.0
6,0
8.0
7.0
7,0
7.0
7,0
7,0
7.0
7,0
7.0
7.0
7.0
7.0
7.0
7.0
Pri 7KN
CMG/L)
8.0 !.4
8.0
6.0
6.6
6.6
7.3
7.3
7.3
7.2
7.2
7.0
7.0
6.8
t.6
6.3
6.6
6,8
7,2
7.2
7.2
7.2
7.2
7.2
,4
.0
.4
.0
.1
.1
B j
.1
.1
.1
.1
.2
,2
.2
.2
.2
,1
.1
,1
.1
.1
.1
7.8 3,0
7.8 3,0
7.8 3.0
7,8 3,0
7.8 3.0
7.8 3.0
7.8 3.0
7.8 3,0
3.1 2.4
6.1 2.4
8.1 2.0
8.1 2.4
8.1 2,4
6.1 2.4
6.8 2.2
6.8 2.2
6,6 2.2
6.6 2.2
6.8 2,2
6.8 2.2
6.6 2.2
6.8 2.2
6.7 2.6
6.7 2.6
6.7 2.6
6.7 2.6
6.7 2.6
BOD
(Mli/U)
lb.0
15.0
lb.0
45.0
45.0
19.0
1^.0
1^.0
o.O
b.O
b.O
8,0
Si.O
5i.O
Si.O
53.0
Si.O
30.0
30,0
50. 0
30,0
30,0
30,0
26,0
2b.O
Hf.,0
26. G
2o,0
26,0
2t.O
2fc.O
a<;.o
22.0
2i.O
22,0
22.0
2
ni "Z.
O t>
5) r
m •<
—\
^
— o
O "b
z r
> o
z 5
r 3
5
^ c
_,
r~
N
m
Q
z
2
C
q
-Q
r-
m
-------
SAMP NO,
49563
89565
49563
495o5
49565
19565
49So5
19565
49565
19565
49565
4956S
49St>7
49567
19567
49567
49567
19S67
09567
19567
19567
19569
19569
II9S69
19569
49<,69
19569
19569
19569
89569
119571
49571
19571
19SH
19571
49571
49571
49571
49571
53356
50256
50256
50256
50256
50256
502S6
50256
50257
S02S7
50257
50257
PREDICTED
LOG KILL
4^95754
5.5990!)
5,99411
3.37532
3.!ll26!r
4,08166
3.98468
4.S0029
4.»1783
5.27917
5.96227
«>.3829ii
3.23469
3.65324
3.91102
3.61010
4.07723
4.J6492
5.'12931
5.79302
6.20178
3,12510
3.52956
3.77801
3.31416
3.74100
4.IIOM1
4.975??
5.61962
6,01614
2.82650
3,19224
3,117!'9
2. 78312
3.14318
3,16526
4.40534
1.97539
5.32046
2,92459
3.30527
J, 53850
2.72392
3,07636
3.293'JS
1.31133
4.36920
J.032o2
3.12503
3.nt>o70
2.7293J
OBSERVED
LOS KILL
1.52720
3.77387
4.70329
3.19149
3.5l'3l6
4.4X430
2.53006
"l.?41j6
3. (,5499
3.S3109
3,68842
4.3873"
S.6954S
4.4«I36
1.-S1527
J.64o26
3.P8930
4.24832
3,8»9?0
1.09342
4.|39]3
3.J7712
3.77815
2.96759
3.59581
3,8S>4(,o
4.139S8
4,?3o79
4.PJSS5
4.66275
3,S"040
3.62472
3.02575
3.41067
1,16679
1.37291
4.59476
4.40982
S.071B8
3.50543
3,30452
3,795f<8
3.89279
3. (-1979
4,09691
1.1 9jfl2
4.79588
•3.25123
3,Q?020
3. 55226
3.31336
RESIDUAL
.43034
1.82516
1, 29081
.18433
.29:1 '13
",40263
1. 45463
.25903
1.162M4
1,44803
2.27380
1.99559
-.460'9
-.838) 1
-.4042S
-.03616
.187."3
.11660
1.24001
1.69960
2.06260
-.3S11"!
-.24359
.79102
-, 2816-5
-,1'Jlh.)
-,132'7
.7399-'
.78077
1.35V39
-.71390
-,4J2'f3
-,5032i
-.63533
-1.02531
-1.00763
-,189'40
.50557
.25453
-.63383
,00076
-.25738
-1.15337
-.sum
-.B0345
.11751
,07332
-.21301
-.52517
.11*44
-,58!iu5
DOSE
(HG/L)
14.2
14,2
14.2
7.8
7.8
7.8
10,0
10.0
10,0
15.3
15.3
15.3
7.1
7,1
7.1
6.4
8.1
3,1
14.2
14.2
lli.2
6.7
6.7
6.7
7.3
7.3
7.3
13.5
13.5
13.5
6.5
6.5
6.5
. 6.4 ,
6.4
6.4
12,8
12.8
12.8
7.1
7.1
7.1
6.4
6,4
6.4
12,8
12.8
7.5
7.5
7,5
6,4
O.T.
(KIN)
1,9
3.8
5,6
1.9
3.8
5.6
1,9
3.8
5.6
1.9
3.8
5.6
1.9
3,3
5.6
1.9
3.8
5.6
J.9
3.8
S.6
1.9
3.3
5.6
1.9
3.3
5.6
1.9
3,8
5.6
1.9
3.3
5.6
1.9
3.8
5,6
1.9
J.3
5.6
J.9
3,8
5.6
1.9
3.8
5.6
1.9
3,8
1.9
3.8
5.6
1.9
GT
89451.
89527,
89604,
89151,
89527,
89604,
89451,
8952?.
89604.
89451.
89527.
89604,
69451.
89527.
89604.
89451.
89527.
89604,
89451,
89527,
89604.
89451.
89527.
89601.
691S1.
89527.
69604,
fc^l'Jl,
89527,
89604,
89451,
89527.
89604,
89451,
89527.
89604,
89451,
89527.
89604,
89451.
89527,
89004.
89451,
89527.
89604.
89451.
89527.
89451.
89527,
89604,
89451.
TEMP
( C)
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7,0
7.0
7.0
7.0
7.0
7.0
7.0
7,0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7,0
7.0
7,0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7,0
7.0
7.0
PH
6.7
6,7
6.7
6.7
6.7
6.7
6,7
fc.7
6.7
6.7
6.7
6.7
6. a
6.8
6.8
6.8
6.8
6,8
6.6
6.8
6.8
7,0
7.0
7.0
7,0
7.0
7.0
7.0
7,0
7.0
6,9
6,9
6,9
6.9
6.9
6.9
6.9
6.9
6/9
6,6
6.6
6.6
6.6
6,6
6.6
6,6
6.6
6,7
6.7
6,7
6.7
TKN
(MG/L)
2,6
2.6
2.6
3.0
3.0
3.0
3,0
'3.0
3.0
'3.0
3.0
3.0
3.4
3.4
3.4
3.4
3.4
3.4
3.1
3.4
3.4
2.9
2.9
2.9
2.9
2.9
2.9
2,9
2.9
2.9
4.0
4.0
4.0
4,0
4,0
4.0
4.0
4.0
1.0
3,0
3,0
3.0
3.0
3.0
3,0
3.0
3.0
2. a
2.8
2,8
2.8
BOO
(Mli/L)
27.0
27.0
27,0
25.0
25.0
2b,0
25,0
25,0
25. 0
25.0
25.0
2b,0
23.0
23,0
23.0
23,0
23.0
23,0
23.0
23.0
23.0
23.0
23,0
23,0
23.0
23. 0
23.0
23.0
23.0
23. 0
30.0
30.0
30.0
30,0
30,0
30,0
30,0
30.0
3U.O
33,0
33,0
33,0
3i.C
33,0
33.0
33,0
33.0
33.0
33.0
33.0
33.0
TSS
(Me/L)
128.0
128,0
128.0
138.0
138.0
138,0
138.0
138.0
i3t>r6"
138.0
138.0
118,0
12fc.O
126.0
126.0
126,0
126.0
126.0
120.0
126,0
126.0
120.0
120,0
leO.O
120,0
120.0
120.0
120,0
120.0
120,0
126,0
126,0
126.0
126,0
126.0
126,0
126,0
126,0
126,0
36,0
38,0
38.0
88.0
83.0
58,0
98,0
38.0
38.0
38.0
88. 0
38.0
vss
(Mb/L)
64.0
61.0
64.0
64,0
64,0
64,0
64.0
64.0
64.0
64,0
64.0
64.0
70.0
70,0
70.0
70.0
70.0
70,0
70,0
70.0
70.0
60.0
60.0
60.0
60.0
60.0
60.0
60.0
60.0
60.0
66.0
66,0
66.0
66.0
66.0
66.0
66.0
66.0
66.0
46.0
46,0
46.0
46.0
46.0
46.0
46.0
46.0
42.0
42.0
42.0
42.0
INFLUENT
f. COL I
toioooo.
loioooo.
1010000.
1220000,
1220000,
1220000,
1220000,
1220000.
1220000.
1220000.
1220000.
1220000,
1240000.
1240UOO.
1240000.
1240000.
1240000.
1240000.
1240000,
1240000.
1240000.
1380000.
1380000.
1380000,
1380000.
1380000,
1360000.
1380000.
1380000.
1380000.
1180000.
1180000.
1180000.
1180000.
1180000.
1180000.
1180000.
1180000.
1160000,
625000,
625000,
623000.
625000.
025000.
625000.
625000.
625000.
535000.
515000.
535000.
535000.
EFFLUENT
t, COLI
30,
170,
20,
785,
370,
40,
3600,
.79«
270,
180,
250,
50,
250.
40,
60,
280,
160,
70,
160,
100.
90.
460,
230.
1420,
350,
180,
100.
80.
20.
30,
340,
280.
140,
450,
80.
50,
30,
40,
10,
170,
310,
100.
80,
150.
50,
40,
10.
300,
60,
ISO,
260,
-------
_j *4 -* -*-
u. »
u. >*.•
*Z _i ooooooooooooooooooo oooooooooooooooooooooooooooo-oooo
3 ,^J OOOOOOOOOOOO33OOOOO^OOOOOOOOOOO3OO3OOOOOO33OOOOOO3O
_i inininininoo^ooooo-oooooooo^o3oo^oooo3inj^'^iAin^1^jn-.i^a*ia3'3'**^inlAj-.
j. • itK>itKiKir'ir'iKiKiKi'O'OKiito>o>CTotO' ^o~o*O'J^i"i'>'j'iirtin/*j^uioo^^oooc>o»*»H»*»-t—*inj*iin/%ji
2ik \f*^\J\\fr-J\^^^f^rf\'f*'fiFf\tstt*~r--t*~r~.r*~f-.t~-t~-t~-:3^;y^:3:3^!& ^ -G-Q-G-Q-G-O •&-*>-& -^ -* ^ rvinjrvinj
J OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO^OOOO
_j OOOOO-OOOOOOOOOOOOOOOO-^OOOOOOOOOOOOOOOOOOOOOOOO^I OCOO-
SIiJ ajaDtoaj®ajt05»cca^*ia>*ia>^inj*urJnj*u'Jnj-u»^ »^=r^a ^a=T-3-^=T3^33=r^-HOooc»3Ci>»a>
_
J^i r\jf\lOiA|f\l»orOrnfOf^rn^H1^rnw»»Oto»OW^^>^H1Hli^i^i^MKlKl^rn^»n^»nHli^f^»n^^
^, OOOOOOOOCOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO
— » I » • I t —
KO
0. -l
K»»nro^Hi^iAu^^
^
192
-------
10
CO
SAMP NO.
50070
50070
50070
50070
50070
50072
50072
50072
50072
50972
50072
50072
50071
5007fi
50070
50070
50070
50074
59076
50076
50076
50076
50076
5C076
50076
50076
50078
50078
50078
50078
50078
50376
50078
50076
50080
50080
50080
50080
50080
50030
50060
500SO
53105
52105
52105
52131
52131
52131
52107
52107
52107
PHEQlCTtO
LOG KILL
.99225
1.06227
1,05550
1.19J61
1. 27513
1.7B515
2,62111
,93119
1,05123
1.12847
l,t>1087
1.«1894
2.111)31
2.S31M
.92BJ1
1,01835
1,71028
1,96506
1.A8832
2.773J6
1.00685
1,13713
1.21737
1.701=2
1.92157
2.05995
1.66610
2,11679
,579i6
,6bl6/
,70o8o
1.50372
1,69795
1.817)8
2,«3}i>S
2,i 32399
,68106
,76919
.82317
1,81622
2.US032
2,19508
I, 92610
2,17199
2.33532
2.05111
2.31616
2.18639
2,72118
3,07278
3,2992=1
UUstRVtO
LOG KILL
.51886
,68367
1.65118
1.95251
2,67853
.905PO
1,i28(,7
1.09082
.21560
.12867
2.51786
2,52601
1.0'J139
1.3»212
,?52S1
.00998
1.K2S90
2,06367
1.02119
1.32222
.P'691
.73116
.11613
1.81510
2.11810
3,22531
1.t34J1
".I 5131
1.09291
1.20192
.13537
1.93921
2.51887
1.25927
1.33J11
1.031H
1.08711
1. 10199
1.15635
2.65120
3.1*6}1
1.03141
2.11111
2.2V6S2
2.P6SH
2.070S8
2.14721
2.52268
1.97517
2.?1972
2.71856
RE5IDUM.
.07339
.37860
-.59618
-.76090
-1.60310
, 87955
•1,30753
-.55713
.83868
.70000
-.9369*
-,S07«7
-1.601u8
•1.51071
,67572
I.OJ537
-.08363
-.09660
-2.13237
-1.51886
.70991
.10598
1.07121
-.11068
-, 19552
•1.16535
•2.16793
-1.68755
-, 51J28
-.5SC>i5
.26519
-.1fl!!
-------
UD
SAMP NO.
S2tO<>
5210V
52109
521U
52111
5?111
52113
55113
52113
53115
52115
52115
52117
52117
52117
5213]
52133
S213]
52J96
52596
52396
52400
52iiou
52000
52101
52101
52101
52106
52406
52108
52112
52*112
521U2
52146
52116
52681
52681
526B1
52681
526811
526B1
52681
52681
52681
52691
52691
52691
52691
52690
52o91
52b91
PHEOlCTtO
LOG KILU
2.71693
5.10I8S
3.33016
1.39738
1.96551
5,33150
3.63159
1.10121
(1. 4278V
3.62353
1.0V172
1.11111
3.81135
1.3071*
1.61680
5.69262
1.16973
a, 09853
1,17520
«. 71150
5.01613
1.19513
1.73731
5.U7058
3.S2615
3.98196
1.26265
3.05JS7
3,69965
1.17397
2.05552
2.32102
2.46128
2.81702
3.0172B
1,71590
2.17109
2.51931
1.66932
1.3B58B
2.01895
1.66917
1.66S11
2.01772
2.23596
2.62920
3.283!)7
2.20296
2.16802
2. 60358
2.03119
OBSERVED
L06 KILL
2,19629
1.83727
2.98069
6.01139
6.011J9
6.01139
6.25527
6.?bS27
6.?5S2?
1.00132
6,00132
6,00132
1.1 I3Q1
6.) U9U
6,11391
3, 815(0
5.81509
5.R1509
1,ri3111
1.03IU1
1,33211
1.32222
O.J2222
0,32222
2.70602
3.S71PO
1.61571
2.33288
2.13933
3.Q9S{.3
2,?0426
2.3B53S
1.05136
2.32736
3.39791
1.87335
1,?597«
1.55971
,uo2S3
.83663
1.50171
.7JJ71
1.10380
1.32565
1. 60971
1.71303
2.U7712
1.37560
1.25072
2.505U5
.("5274
RESIOU'L
,55061
1.26158
.31977
-1.61101
-1.07SM
-.70968
-2.62068
-2.15106
-1.82738
-.38079
-1.91260
-1, 58991
-.29559
-1 .80675
-1.16706
-.15218
-1.67S36
-1.31652
.11579
.68509
.71369
-,12o79
-1. 58167
-1.25161
, 81811
.11016
-.12369
1.12069
1.16032
,17333
-.15371
-.06133
-1.57007
.51«66
-.35066
-.15755
.61136
,95058
1.20699
1.01925
,sr/2i
,95oVl
.78131
.69207
,62&<;2
1,08625
.803«5
.82730
1.23730
.15tll2
l,|7b«l
OOSf
(HG/L)
6.2
6,2
6,2
11.9
11.9
11.9
8.1
6.1
8.1
8.1
8.1
8.1
8.6
S.6
8,6
8,6
8.6
8.6
8.1
1.1
4.1
8.1
8.1
8.1
6.2
6.2
6.2
6,2
6,2
6,2
1.0
1.0
1.0
1.0
1.0
1.2
1.2
1.2
1.0
1,0
1,0
4.0
1.0
1.0
1.9
1.9
1.9
1.6
1.6
i.e
1.2
D.T.
(KIN)
1.3
2.6
3.9
1.3
2.6
3.9
1.2
2.1
J.7
1.2
2.1
3.7
1.2
2.1
3.7
1.2
2.1
3,7
1.9
3.B
5.6
1.9
1.8
5.6
1.9
1.8
5.6
1.9
3.8
5.6
1.9
3,8
5.6
3,8
5.6
1,9
3.8
5.6
1.9
3.3
5.6
1.9
3,8
5.6
1.9
3.8
5.6
1.9
3.5
5.6
1.9
CT
191(50.
19162.
19«71.
19150.
19162.
1917".
59776.
59791,
59805.
59776.
59791,
59BOS.
59776.
59791.
59SOS.
59776.
59791,
S9805.
89386,
89397,
89109.
69386,
69397,
B9109.
6938t>.
89397.
89109.
£9366,
89397.
89109,
69386,
69397.
69109.
69397,
69109.
69366,
IjlOEI.
178783.
69151.
89527.
69601,
69386.
69397.
£9109,
89366.
131061,
176763.
69.451.
69527.
fc9o01.
69356.,
iEMP
( 0)
16,0
16,0
16,0
16.0
16,0
16.0
16, C
16,0
16.0
16. C
16.0
16.0
16.0
16.0
16,0
16,0
16.0
16, C
13.0
13.0
13.0
13,0
13.0
13,0
13.0
13.0
n,o
:z.o
13.0
13.0
11.0
11.0
11.0
11.0
11,0
16.0
16.0
16. C
16.0
16.0
16.1)
16,0
16.0
16.0
16.0
16.0
16.0
16.0
16,0
lo.O
16.0
PH TKN
CHG/L)
7,0 6.7
7.0 6.7
7.0 6,7
7,0 3.5
7.0 3,5
7.0 3.5
7.0 1,7
7,0 1.7
7.0 1,7
7.0 6,7
7.0 6.7
7.0 6.7
7,0 3.5
7.0 3.5
7.0 3.5
7.0 3.7
7.0- 3.7
7,0 3.7
7,2 2.1
7.2 2,1
7.2 2,1
7,1 3,5
7.1 3,S
7.1 3,5
6,6 3.3
6.8 3,3
6.8 3,3
7,1 3.5
7.1 3,5
7,1 3.5
7.1 21,7
7.1 21,7
7.1 21,7
7.1 3.8
7.1 3.8
7,0 2,6
7,0 2.6
7,0 2,6
7,0 2,
7,0 2,
7.0 2.
7,0 i..
7,0 2.
7.0 2.
7.2 3.0
7.2 3.0
7.2 3,0
7.2 3.0
7.2 3,0
7.2 3.0
7,2 1.0
BOD
CMfc/L)
1.1
1.1
1.1
1.0
1.0
1.0
3.2
3.2
3.2
1.6
1.6
1,6
.7
.7
,7
3.6
3.6
3.6
10.6
10.6
10,6
9.1
9.1
9.1
6,4
0,1
0.1
6.2
6.2
6,2
10,3
10.3
10.3
10.6
10.6
51.0
51.0
Sl.O
51,0
51.0
51.0
31.0
51,0
51,0
35,0
35.0
Jb.O
35.0
35.0
35.0
35,0
iSS
(H6/U)
7,0
7,0
7,0
7.5
7.5
7,5
39.0
39.0
39,0
6,3
6,3
6.3
3.0
3.0
3.0
1,3
1.3
1.3
18.0
18.0
• 16.0
25,0
25.0
25,0
29.0
29.0
-------
vo
en
SAMP NO.
53690
53494
53700
53700
53700
53701
53700
53700
52700
53700
b3703
,«6'<«1
.88531
'.05381
.05271
.61633
-, 037*7
.71125
.831M
,30o61
.55378
1.P3139
.867/9
1.06oUO
. .13017
.58009
.78758
.83366
.09651
-.13700
-.10376
.73008
-.08530
-.l?7il
,61|S6
-.00033
1.16735
1.30130
1.56351
. 51519
-.OloM
-.15325
.93507
.58357
DOSE
(MG/L)
0.3
1.3
6,5
6.5
6,5
4.'
6,3
6.3
6,5
6.5
6.5
6.3
6.3
6,3
6.5
. 6,5
6.5
6.5
6.5
6.5
8.3
6.3
8,0
8.0
8,1
8.3
8.3
8,1
8,0
8.1
8.3
8.3
8.3
8,1
8.1
D.T.
(KIN)
3.8
5.6
1.9
3.8
5.6
1.9
3.6
5.6
1.9
3.8
5.6
1.9
3.8
5.6
1.9
3.8
5.6
1.9
3.8
5.6
1.9
3.8
1.9
3.8
5.6
1.9
3.3
1.9
3.8
5.6
1.9
3.8
5.6
1.9
3.8
GT
89397.
89009.
89386.
130060.
178783.
89051.
89537.
896CO.
6938o.
69397.
89009.
89386.
130080,
170783.
891151.
B9537,
69600.
89386.
F-9397.
69109,
89386.
131081.
89151.
B9537.
»9601,
b9386.
89397.
69386,
131081,
178783.
S9051.
S*537.
89601,
89386.
89397.
IEMP
t C)
16.0
16. d
16.0
16.0
16.0
16.0
16.0
16.0
16,0
16,0
16.0
16.0
16.0
16.0
16.0
16,0
16.0
16.0
16,0
16,0
16,0
16,0
Iti.O
16.0
16,0
16.0
16.0
16.0
16,0
16,0
16.0
16.0
16.0
16,0
16.0
PH
7.3
7.3
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7.0
7,0
7,0
7.0
7.0
7.0
7,0
7.0
7.0
7.0
7.0
7,0
7.0
7.0
7,0
7.0
7.0
7.0
<7.0
7.0
7.0
7.0
7.0
7.0
7.0
TKN
(MG/L)
3.0
3.-0
3.9
2.V
3.9
3.9
3."
3.9
3.9
3.9
3.9
3.9
3.9
3.9
3.9
3,9
3.9
3.9
. 2.'
3.V
5.5
5.5
5.5
5.5
5.5
5.5
5.S
3.9
3.9
3.9
3.9
3.9
3.9
3.9
3.9 '
HUD
CMU/L)
35.0
35.0
35,0
35.0
35,0
35.0
35.0
35,0
35,0
35.0
35.0
3o.O
3t,0
36.0
3o,0
3o.O
3t.,0
3o.O
36,0
36.0
31.0
31.0
31,0
31.0
31.0
31.0
31.0
32.0
32.0
33,0
32.0
32,0
32.0
32.0
32.0
155
IMLVL)
80,0
80.0
153.0
152.0
152.0
153,0
153,0
153,0
152,0
153.0
153.0
80.0
80.0
80,0
80.0
80,0
80.0
80.0
80,0
80,0
82,0
83.0
82,0
82.0
82,0
83.0
82.0
81.0
81,0
80,0
81,0
ao.o
81,0
81,0
81,0
VSS
(Mb/LJ
33.0
33.0
95.0
95.0
95,0
95,0
95.0
95,0
95.0
95.0
95.0
30.0
30.0
30.0
30.0
30.0
30.0
30.0
3u.O
30.0
32.0
33.0
33.0
32.0
33.0
33.0
33.0
36,0
36.0
36.0
36.0
' 36.0
3h.O
36.0
3o.O
INFLUENT
' F, COLI
385000,
3850.00.
205000,
205000.
305UOO,
205000.
305000,
20'JOOO.
205000,
305000.
305000.
175UOO,
175000.
175000,
175000,
175000,
175000.
r/sooo.
175000,
175000.
315000.
305000,
305UOO.
305000.
315000.
315000.
3C-.VOOf
315000,
205000,
205000.
305000.
315000.
315000.
205000,
305000,
tFFLUENT
t, COLI
16000,
3800,
1155.
580.
300,
1300,
860,
120,
2200,
1300,
190,
1600,
980,
200.
0200,
490,
380,
2300.
1130,
130.
150.
20.
1035,
60,
30,
880,
70,
1730,
310,
130.
150,
20.
10.
1210.
310,
-------
OOOOOOOOO.Q-*
UlO OOOOOOOOOOOOOOOOOOOOOOOOOOC>OOOi>OOO*OO AOOOQOOOOOOOOO
_| OOOOOOOOOOKIrnr\JfUt\IOOOOU^lT»t/*OOOOOOOOOOOOOOOOOOOOOOOOOOOOO
gj ^X »•»»•••••.•» . * • • • • » -.^B • • ••.»••••«»» » . •*••.«•».»•••....
a. f^ ooooooooooc»oooooo.ooooooooooooooooooooo-ooooooooooooo
a 2T -^rvjf^-«tn-^nj-^airo-*f^-*n
-^^
o o o a* « to * o -o -o «o -
196
-------
SAMP HO.
52634
52634
52634
52534
52631
52634
52631
52644
52644
52644
52!>44
S2644
52641
52644
52644
52614
52654
52654
52654
52654
52654
52654
52654
52651
52554
52664
52661
52664
52644
52664
52561
52661
52664
52661
52474
52671
52674
52574
52671
S2674
52674
52674
52671
PHEOICTtO
LOG KILL
1.66915
1.56062
1.59432
1.61224
1.56415
1.59470
1.412U6
2.34804
2,44313
2,50565
2,31612
' 2.39407
2,42022
2.3180'i
2.39390
2.41996
2.25410
2.3«539
2.10541
2.27796
2.32254
2.31791
2.25410
2.29312
2.3231"
3,02496
3.14716
3,22902
3.02507
3.06427
3. 1179s
3.024V,
3.06435
3.117ol
3.22012
3.35054
3.13627
3,22024
3.26326
3.31911
3.22012
3.26302
3.31875
OBSERVED
LOc KILL
1.55023
1.Q496?
,?1443
.13628
.12426
.26695
,15229
3.91645
4,?1718
3.74036
2,6*600
2.96221
3.01336
2.50991
2.53624
2.M542
3.27684
3.4b293
3.B7S90
2.77624
2.fr9S?7
2.06166
2.51093
2,ftb466
3.Q3360
2.83266
3.J567?
3,30777
2.99123
3,o"o7U
3.4?60
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/2-79-031b
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
Combined Sewer Overflow Abatement Program,
Rochester, NY - Volume II: Pilot Plant Evaluations
5. REPORT DATE
July 1979 (Issuing Date)
6. PERFORMING ORGANIZATION CODh
7. AUTHOR(S)
Frank J. Drehwing, Cornelius B. Murphy, Jr.,
Steven R. Garver, Donald F. Geisser, Dilip Bhargava
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
O'Brien & Gere Engineers, Inc.
1304 Buckley Road
Syracuse, New York 13221
10. PROGRAM ELEMENT NO.
1BC822, SOS 1, Task 31
11.
GRANT NO.
Y005141
12. SPONSORING AGENCY NAME AND ADDRESS
Municipal Environmental Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, Ohio 45268
13. TYPE OF REPORT AND PERIOD COVERED
Final May 1974 to Sept. 1977
14. SPONSORING AGENCY CODF.
EPA/600/14
15. SUPPLEMENTARY NOTEsj0int Sponsorship with: Great Lakes National Program Office,
U.S. Environmental Protection Agency, Chicago, Illinois 60604. Project Officers:
Richard Field & Anthony N. Tafuri, FTS 340-6674. (201) 321-6674
161 ABSTRACT - The pilot plant treatability studies were designed to interact with com-
bined sewer overflow (CSO) monitoring and system model inn efforts for the Rochester
Pure Water District with the ultimate objective of evaluating CSO abatement alter-
natives (see Volume I of this Report).
The studies covered treatment by the following unit processes: flocculation/
sedimentation, swirl degritting and swirl primary separation, microscreening with
sonic cleaning, dual-media filtration, activated carbon adsorption, sludge dewatering
and high-rate disinfection. Applied flowrates to the system ranged between 5 and
177 gpm.
Pilot operations covered 19 overflow events during the period of September
1975 through June 1976. the studies evaluated the effects of design loadings and
influent quality on system performance. Data were evaluated through application
models. These models were used to develop optimum cost/benefit comparisons of systems.
Results were also compared to published literature for similar installations at other
locations.
Cost estimates related to facility sizing of all treatment processes were com-
piled and documented from literature sources. Cost equations were developed and
applied for comparison of a number of alternatives in conjunction with the performance
models. Cost/benefit relationships of the individual primary and chemical/physical
systems are also presented in this report.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
Combined sewers, *Overflows~sewers, Water
pollution, *Waste treatment, Sewage, Con-
taminants, Sewage treatment, *Pilot Plants,
Cost analysis, *Cost effectiveness, *Floc-
culating, *Sedimentation, *Swirling, Grav-
ity concentrators. Grit removal, Strainers,
•Filtration, *Activated carbon treatment,
•Disinfection, Bactericides, *Mathematical
models,' Sludge, Mixing, Polyelectrolytes.
b.lDENTIFIERS/OPEN ENDED TERMS
Physical-chemical treatment, *Combined sewer
overflows, Pollution abatement. Water pollu-
tion control, Rochester, N.Y., Suspended
solids removal, *Flocculation/sedimentation,
*Swirl degritter, *Swirl primary separator,
*Microscreening, *Wastewater treatment,
*High-rate dual-media filtration, *Carbon
adsorption, *High-rate disinfection, Chlo-
rine dioxide, Alum, Mixing intensity, Storm
runoff.
COSATl Field/Group
13B
13. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
19. SECURITY CLASS /ThisReport)
UNCLASSIFIED
21. NO. OF PAGES
216
20. SECURITY CLASS (Thispage)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
198
i U S. GOVERNMENT PRINTINC OFFICE, 1979 -657-060/5437
------- |