./600/R-10/003 |
i10 | www.epa.go
United States
Environmental Protection
Agency
t of Wet-Weather Peak Flo
lending on Disinfection and Treatme
A Case Study at Three Wastewater
Treatment Plants
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EPA/600/R-10/003
April 2010
Impact of Wet-Weather Peak Flow Blending on
Disinfection and Treatment:
A Case Study at
Three Wastewater Treatment Plants
By
R. Boris Rukovets and Brian J. Mitchell
Interstate Environmental Commission
311 West 43rd St., Suite 201
New York, NY 1003 6
Contract Number: EP06C000010
Project Officers
Richard Field and Mary K. Stinson
National Risk Management Research Laboratory
Water Supply and Water Resources Division
U.S. Environmental Protection Agency
Edison, New Jersey 08837
National Risk Management Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Cincinnati, Ohio 45268
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Notice
The U.S. Environmental Protection Agency (EPA) through its Office of Water, Office of
Policy, Economics and Innovation, and Office of Research and Development has
financially supported and collaborated in the research described herein. It has been
subjected to the Agency's peer and administrative review and has been approved for
publication as an EPA document. Any mention of a trade name or commercial product
does not constitute endorsement or recommendation by the EPA for use. The views
expressed in this report are those of the individual authors and do not necessarily reflect
the views and policies of the EPA.
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Foreword
The U.S. Environmental Protection Agency (EPA) is charged by Congress with
protecting the Nation's land, air, and water resources. Under a mandate of national
environmental laws, the Agency strives to formulate and implement actions leading to a
compatible balance between human activities and the ability of natural systems to support
and nurture life. To meet this mandate, EPA's research program is providing data and
technical support for solving environmental problems today and building a science
knowledge base necessary to manage our ecological resources wisely, understand how
pollutants affect our health, and prevent or reduce environmental risks in the future.
The National Risk Management Research Laboratory (NRMRL) is the Agency's center
for investigation of technological and management approaches for preventing and
reducing risks from pollution that threaten human health and the environment. The focus
of the laboratory's research program is on methods and their cost-effectiveness for
prevention and control of pollution to air, land water and subsurface resources; protection
of water quality in public water systems; remediation of contaminated sites, sediments
and ground water; prevention and control of indoor air pollution; and restoration of
ecosystems. NRMRL collaborates with both public and private sector partners to foster
technologies that reduce the cost of compliance and to anticipate emerging problems.
NRMRL's research solutions to environmental problems by: developing and promoting
technologies that protect and improve the environment; advancing scientific and
engineering information to support regulatory and policy decisions; and providing the
technological support and information transfer to insure implementation of environmental
regulations and strategies at the national, state, and community levels.
This publication has been produced as part of the Laboratory's strategic long-term
research plan. It is published and made available by EPA's Office of Research and
Development to assist the user community and to link researchers with their clients.
Sally Gutierrez, Director
National Risk Management Research Laboratory
in
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Abstract
This research project was administered by the EPA Office of Research and Development
and funded by Office of Water; Office of Policy, Economics and Innovation; and Office
of Research and Development.
Blending is the practice of diverting a part of peak wet-weather flows at wastewater
treatment plants (WWTPs), after primary treatment, around biological treatment units and
combining effluent from all processes prior to disinfection and subsequent discharge
from a permitted outfall. For combined sewer systems, EPA's 1994 Combined Sewer
Overflow (CSO) Policy encourages delivery of maximum flows to WWTPs, while
ensuring that bypasses do not result in National Pollution Discharge Elimination System
(NPDES) permit exceedences. Consistent with that principle, blending of flows at
WWTPs serving combined sewer systems presents one of the more technically
practicable and economically feasible alternatives. In addition, in December 2005, the
EPA proposed, for public comment, a new policy for addressing peak flow events at
municipal WWTPs served by separate sewer systems, also through flow maximization.
This project's intent was to determine the microbiological impact of blending primary
effluent flows that are in excess of secondary treatment capacity with the secondary
effluent prior to disinfection at large municipal WWTPs. This approach is typically used
by a number of municipal WWTPs within the Interstate Environmental Commission's
(TEC) jurisdiction during wet weather to maximize the flow to the WWTP and reduce
CSO events. The primary objective of the study was to evaluate the effect of wet-weather
blending on the concentration of fecal coliform and Enterococcus indicator bacteria, total
residual chlorine, protozoa and viruses in the WWTP final effluent. Three New York City
WWTPs were monitored for this project. The project was important for better predicting
and understanding the impact of blending on CSO pollution control and receiving water
quality.
The results showed that during blending, the sampled WWTPs remove, on average,
between 97% and 99% of coliphage and enteric viruses; approximately 71% of
Cryptosporidium; and between 40% and 88% ofGiardia. The geometric mean for fecal
coliform effluent concentrations during blending at the three WWTPs ranged from 520 to
19,000 MPN/100 ml and the corresponding geometric mean for Enterococcus effluent
concentrations ranged from 870 to 17,000 MPN/100 ml. During blending, effluent BOD
and TSS concentrations remained below 30 mg/1 (a monthly average permit limit for both
parameters) at two out of three WWTPs; the third WWTP, that had results above 30 mg/1
for both parameters, was undergoing a partial construction at the time of sampling.
A sample maceration procedure was conducted to determine if bacteria occluded by
particulate matter could be enumerated. Maceration was accomplished using a
commercial Waring blender, which breaks apart particulate matter exposing bacteria
within the particle interstices. After a statistical evaluation, it was shown that the
maceration of effluent samples resulted in an increase in both fecal coliform and
Enterococcus concentrations when compared to unmacerated samples.
IV
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The measurement of flow rates was made for WWTP influent flows at all three WWTPs
during both dry-weather, non-blending events and wet-weather blending events. During
wet-weather blending events, the exact measurement of the flow through secondary
treatment systems was made only at one WWTP (i.e., WWTP 1). Based on knowledge
of the blending process and associated flow rates of primary flow treated versus
secondary flow treated, flows through the secondary system at the two other WWTPs
(WWTP 2 and WWTP 3) were estimated.
The strength of this study is that it gathered information at three full-scale WWTPs
functioning as usual during actual dry-weather non-blending and wet-weather blending
operation. Also, this study represents a first detailed effort to analyze the impact of
blending during wet weather.
The limitation of the study is that it represents only one geographical location for the
three plants studied and the wet-weather blending ratios or flow rates were measured in
only one of the three plants. Thus, the geographical closeness and the limited number of
facilities evaluated during the study suggest that these results should be viewed as plant -
specific.
Additional studies are recommended at a variety of WWTPs to provide reinforcement of
the data obtained in this study.
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Contents
Notice ii
Foreword iii
Abstract iv
Contents vi
Figures vii
Tables vii
Glossary of Terms and Acronyms viii
Acknowledgements ix
Chapter 1. Introduction 1
1.1 Proj ect Background 1
1.2 Treatment Processes at New York City Wastewater Treatment WWTPs 2
1.3 Key Research Questions 4
Chapter 2. Project Summary 7
Chapter 3. Project Design 9
3.1 Bacteria Sampling 9
3.2 Protozoa and Virus Sampling
10
3.3 Maceration 11
Charter 4. Discussion of Project Results 13
4.1 Analyses of Historical WWTP Performance 13
4.2 BOD5 and TSS Results 15
4.3 Bacteria Sampling Results 20
4.4 Blending Flow Ratio 23
4.5 Total Residual Chlorine (TRC) Results 24
4.6 Analysis of Existing Monitoring Data - Wet-Weather Non-Blending Events 26
4.7 Protozoa Results 27
4.8 Virus Results 30
4.9 Coliphage Results 35
4.10 Maceration Results 37
Chapter 5. Conclusions and Recommendations 39
5.1 Conclusions and Observations 39
5.2 Future Research 42
References 43
Bibliography 45
Appendix A. Detailed Sampling Results 46
Appendix B. Maceration Results 51
Appendix C. Flow Rate and Estimated Chlorine Contact Time Data 53
Appendix D. Maceration Optimization Analyses 57
Appendix E. Analytical Methods Used for Infectious Cryptosporidium and Virus 66
Analyses
vi
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Figures
Figure 1. Schematic of the Treatment Process at WWTP 3
Figure 2. WWTP Wet-Weather Blended and Dry-Weather Non-blended Sampling 9
Figure 3. BOD5 and TSS Results 16
Figure 4. Fecal Coliform and Enterococcus Concentrations 21
Figure 5. Residual Chlorine at Effluent 25
Figure 6. Historical IEC Wet-Weather Results - Percent of Design Flow vs. Fecal
Coliform 26
Figure 7. Giardia and Cryptosporidium Concentrations 28
Figure 8. Virus Concentrations by Cell Lines 33
Figure 9. Coliphage Concentrations Famp and C3000 36
Figure 10. Macerated vs. Unmacerated Concentrations 38
Tables
Table 1. CBOD5, BOD5 and TSS Effluent Limitations for NYC DEP WWTPs 6
Table 2. Sampling Events: Completed / Planned 7
Table 3. Dry-Weather Effluent Samples: Collected / Planned 7
Table 4. Wet-Weather Effluent Samples: Collected / Planned 7
Table 5. Sampling Summary 10
Table 6. Number of Analyses for Maceration Optimization 12
Table 7. Average Monthly Effluent TSS and % Removal 14
Table 8. Average Monthly Effluent CBOD5 and % Removal 14
Table 9. 30-Day Geometric Mean Monthly Fecal Coliform Values (per 100 ml) 15
Table 10. Comparison of Standard Deviation for Effluent BODs and TSS 15
Table 11. BOD5 and TSS Total Percent Removal 19
Table 12. BOD5 and TSS Percent Removal for Primary and Secondary Treatment 19
Table 13. Fecal Coliform and Enterococcus Concentrations 21
Table 14. Chlorine Contact Time, WWTP 1 26
Table 15. Historical IEC Wet-Weather Results (Non-Blending and Blending)
(coliform per 100 ml) 27
Table 16. Range of Final Effluent Concentrations for Protozoa 28
Table 17. Giardia and Cryptosporidium Average Percent Removal 30
Table 18. Range of Final Effluent Results for Viruses 31
Table 19. Detect!on by Cell Lines 31
Table 20. Detected Viruses 32
Table 21. Average Percent Removal of Viruses during Wet Weather 35
Table 22. Range of Final Effluent Concentrations for Coliphage 35
Table 23. Coliphage Average Percent Removal during Wet Weather 37
vn
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Glossary of Terms and Acronyms
AdV
BGM
BCS
BOD5
CaCo-2
Cell line
CBOD5
DESA
EPA
EV
h
HAV
IEC
MAI 04
mg/1
MOD
min
MPN
ND
NPDES
NYC
NYC DEP
NYS DEC
ORD
PLC/PRF/5
REO
rpm
RV
s
SP
TRC
TSS
WWTP
Adenovirus
Buffalo Green Monkey cell line
Biological Consulting Services
Five-Day Biochemical Oxygen Demand
Human intestinal cell line
Cells of a human or animal that are grown in a laboratory and used for
detection of the presence of a particular organism. In this study, four
cell lines, i.e., BGM, MA104, PLC/PRF/5 and CaCo-2, were used for
detection of the enteric viruses.
Five-Day Carbonaceous Biochemical Oxygen Demand
Division of Environmental Science and Assessment
Environmental Protection Agency
Enterovirus
Hours
Hepatitis A Virus
Interstate Environmental Commission
Cell line derived from Rhesus monkey kidney
Milligram per Liter
Million Gallon per Day
Minutes
Most Probable Number
Non-detect
National Pollutant Discharge Elimination System
New York City
New York City Department of Environmental Protection
New York State Department of Environmental Conservation
Office of Research and Development
Human hepatoma cell line
Reovirus
Revolutions Per Minute
Rotavirus
Seconds
Sampling point
Total Residual Chlorine
Total Suspended Solids
Wastewater Treatment Plant
Vlll
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Acknowledgments
This is to acknowledge the significant contributions to this document made by the
following fellow professionals:
Mohammed Billah, Donald Brady and Kevin Weiss, U.S. EPA-Office of Wastewater
Management
Jennifer Cashdollar, Christopher Impellitteri, Daniel Murray, PE, Mark Rodgers, Mano
Sivaganesan (Statistician), U.S EPA-Office of Research and Development
Stephen Schaub, Ph.D., U.S. EPA-Office of Science and Technology
Deborah Szaro, Ruth Sykes and Irwin Katz, U.S. EPA- Region 2 Laboratory (Edison, NJ)
Sarah Garman, U.S. EPA-Office of Policy, Economics and Innovation
James Olander, U.S. EPA- Region 2
Troy Scott, Ph.D. and George Lukasik, Ph.D., Biological Consulting Services
Claudio Ternieden, Water Environment Research Foundation
Special thanks to the staff of the New York City Department of Environmental Protection
for valuable assistance with the study design and during the on-site sampling.
Last but not least, we thank Richard Field, PE, Project Officer, and Mary Stinson,
Associate Project Officer, both from the U.S. EPA Office of Research and Development,
for providing the invaluable contributions to this report and important guidance
throughout the entire project.
IX
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Chapter 1. Introduction
1.1 Project Background
Blending is the practice of diverting a part of peak wet-weather flows at wastewater treatment
plants (WWTPs) after primary treatment around biological treatment units and combining
effluent from all processes prior to disinfection and subsequent discharge from a permitted
outfall. The U.S. Environmental Protection Agency's (EPA) 1994 CSO Policy provides
guidance for anticipated bypasses for WWTPs served by combined sewers. The aforementioned
CSO Policy encouraged delivery of maximum flows to the WWTPs, while ensuring that
bypasses do not result in effluent water quality violations. Consistent with that principle,
blending of flows at WWTPs serving combined sewer systems, in many instances, presents one
of the more technically practicable and economically reasonable approaches. To demonstrate the
viability of this approach, the impact of blending during peak wet weather on the microbiological
quality of the effluent was the subject of this study.
The project was conducted by the Interstate Environmental Commission (TEC) under the
direction of EPA. IEC is a tri-state (NY, NJ, CT) quasi-governmental regulatory pollution
control agency.
The major purpose of the project was to analyze the efficacy of microbiological treatment and
disinfection of blending primary effluent flows that are in excess of secondary treatment
capacity, with the secondary effluent prior to disinfection at large municipal WWTPs. This
approach is typically used by the New York City Department of Environmental Protection (NYC
DEP), and a number of other municipal WWTP operators, during wet-weather events to
maximize the flow to the treatment WWTP and reduce the number and flow volume of CSOs.
Analyses of the effluent concentrations of Total Residual Chlorine (TRC), fecal coliform,
Enterococcus, protozoa and viruses during wet-weather blending are methods used to determine
the impact of blended flows on the disinfection process and final effluent quality. The results of
the project are important for predicting and understanding the impact of blending on CSO water
pollution control and on water quality improvement.
While the latest Peak Wet-Weather Policy1 proposed by EPA in December 2005 addresses flow
maximization only for the separate sewer system, flow maximization for the combined sewer
system is no less challenging. While both system types may require flow maximization to
decrease the amount of flow that is discharged untreated into waterways, the need to maximize
the flow to the WWTPs for separate sewer systems during wet-weather events is primarily driven
by infiltration and inflow to sanitary lines, which can frequently be reduced through operation
and maintenance, rehabilitation and other capital investments. Given the differences in design of
the existing infrastructure and resulting peak volumes that occur during wet weather in combined
sewer system, the need for the flow maximization and, consequently, bypass of the secondary
treatment units during wet-weather events at WWTPs generally require greater capital
1 National Pollutant Discharge Elimination System (NPDES) Permit Requirement for Peak Wet-Weather Discharges
from Publicly Owned Treatment Works Treatment WWTPs Serving Separate Sanitary Sewer Collection Systems.
Federal Register, Vol. 70, No. 245, December 22, 2005.
1
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investments to reduce blending. Research on blending in combined sewer systems can
potentially lead to results that would apply to both combined sewer systems and separate sewer
systems as flow rates and sanitary wastewater loadings will tend to have similarities during wet
weather events.
In the project area, 12 out of 14 New York City (NYC) WWTPs receive influent predominantly
from a combined sewer system; most of these WWTPs use a flow maximization approach
similar to the one described in this report. The two remaining WWTPs receive influent primarily
from a separate sewer system and have sufficient hydraulic capacity to handle wet-weather
events. Since blending is typically not used at these two WWTPs, they were not chosen for this
study. Hence, the three WWTPs selected for this project were WWTPs with combined sewer
systems.
Since this study and its results represent only one geographic location, they cannot be used for
drawing definitive conclusions of overall impact of blending on a national scale. Also,
conclusions drawn from the results are dependent on the analytical protocol used. Classical
microbiological methods for enumerating viable bacteria rely on collection of a representative
sample. For consistent enumeration, microbes must be homogeneously distributed within such
samples (APHA, 2005). However, work conducted by several researchers has shown that
microbes can adsorb and/or adhere to particles within water samples (Wellings, et. al., 1976;
Hoff, 1978; Hoff and Akin, 1986). Interestingly, some recent work conducted by Perdek and
Borst (2000) suggests that for combined sewer overflow samples, recovery of indicator
organisms can be improved by macerating for 2 minutes in a blender at 22,000 rpm with a
mixture of additives described by Camper, et al. 1985. This mixture included a buffer, a
chelating agent, and a surfactant which was found to be effective for maximizing the recovery of
culturable heterotrophic bacteria from granular activated carbon. Work conducted on blended
effluents by Camper, et al. suggested that macerating samples may enhance recovery of
culturable bacteria consistent with the findings of Perdek and Borst. However, the effectiveness
of maceration, and/or surfactants for enhanced recovery of viruses, bacteriophage and protozoans
needs to be evaluated to determine if such sample handling techniques improves the recovery,
and therefore the accuracy and precision, of enumeration techniques for pathogens.
1.2 Treatment Processes at New York City WWTPs
As stated above, the three WWTPs evaluated during this project, receive most of their flow from
combined sewer systems. Figure 1 depicts the process schematic at WWTP 3. The process is
typical of NYC DEP WWTPs and includes coarse screening and degritting, primary treatment,
secondary treatment, disinfection, and sludge treatment.
Preliminary treatment begins by the wastewater flowing through bar screens located 1 to 3 inches
apart, which remove large pieces of trash including sticks, rags, bottles, plastic cups and other
items. This part of the treatment process protects the main pumps that deliver the wastewater to
the WWTP.
The wastewater then flows through a primary settling tanks, where the flow of wastewater is
slowed, allowing heavier solids to settle to the bottom and the lighter material to float. The
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lighter material that floats is skimmed from the top of the tank water surface. The heavier solids
(primary sludge) are pumped through cyclone degritters that use centrifugal force to separate out
sand, grit, and gravel; which are removed and disposed of by landfilling. The degritted sludge is
then sent to the sludge treatment facility. The primary setting tank effluent flows to the
secondary treatment system.
Secondary treatment at all three WWTPs consists of two sections: aeration tanks and final
settling tanks. Biological treatment by the activated sludge takes place in aeration tanks, where
air and settled activated sludge from a second set of settling tanks (final settling tanks) is mixed.
The air mixes the wastewater and activated sludge, which in turn stimulates the growth of
oxygen-using (aerobic) bacteria in the wastewater. These microorganisms consume most of the
remaining organic pollutants, leaving a residual of heavier particles that settle later in the final
settling tanks.
Bypass duihg vut aaodiM
CMtCttMnbcfffI
Jar Set
I "4V I
PLANT3
SIMPLIFIED PROCESS SCHEMATIC
Figure 1. Schematic of the Treatment Process at WWTP 3
Source: NYC DEP
The flow from the aeration tanks then goes into the final settling tanks. In these tanks, similar to
the process in primary settling tanks, the heavier particles settle to the bottom and are then
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removed as secondary sludge. The majority of the secondary settled sludge is returned to the
aeration tanks where it is used as the previously described seed sludge; a smaller portion of the
secondary settled sludge is sent to the sludge treatment facility. The treated water then proceeds
to the chlorine contact tanks for disinfection.
While primary and secondary treatment removes most of the solids and reduces the
microorganism content of wastewater, microorganisms that could cause disease remain in the
secondary effluent. Concentrations of these microorganisms must be reduced before the
wastewater is released to the waterways and has the potential to come into contact with humans.
The disinfection process used at all NYC WWTPs is chlorination by sodium hypochlorite.
Hypochlorite, dissolved in the treated water, is held for 15-30 minutes within contact tanks to
inactivate pathogens. The treated effluent is then released to local waterways.
A separate phase of treatment is sludge treatment. Sludge is removed from primary and
secondary treatment systems. This sludge is 99% water and must be concentrated before further
treatment. First, the sludge is sent to the sludge thickening tanks where it settles. The
supernatant is sent back to the head of the WWTP, while the thickened sludge is sent to the
digesters. The digesters are oxygen free tanks that are heated to 95ฐ F and hold the sludge for
two to three weeks. Methane, which is used as an energy source at some WWTPs, is one of the
byproducts of the digestion process. The digested sludge is then pumped to a dewatering facility
that dries the liquid sludge to a total solids concentration of about 26%.
During dry-weather flow conditions, the above-mentioned procedure is the wastewater flow
process through the WWTP. During wet-weather flow, the process will remain the same as that
for dry-weather flow, up to the point when the high flow through the WWTP reaches the
threshold of 1.5 times the design flow. As wet-weather flowrates increase (typically, up to two
times design flow), all flows entering the WWTP will still continue through preliminary and
primary treatment, but only the portion of the flow equal to 1.5 times design flow (according to
NYC DEP's Wet Weather Operation Manual) will be allowed to reach the secondary treatment.
All other primary effluent flow is diverted around secondary treatment and recombines or
"blends" with the secondary effluent for disinfection. This process is called "blending."
Additional wet-weather flows that are beyond the capacity of the WWTP are discharged from
overflow points in the collection system with no or partial treatment.
1.3 Key Research Questions
This study's objective was to answer to following questions:
Question #1: During wet-weather blending events at the three WWTPs studied what were BODs
and TSS levels in the blended effluent?
Question #2: During wet-weather blending events at the three WWTPs studied, what were the
fecal coliform and Enterococcus levels in the blended effluent?
Question #3: For the three WWTPs studied, was there evidence for the removal of protozoa
(Cryptosporidium, infectious Cryptosporidium and Giardia) during wet-weather blending?
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Question #4: For the three WWTPs studied, was there evidence for the removal of viruses
(Adenovirus, Astrovirus, Enterovirus, Rotavirus, Reovirus, Norovirus, Hepatitis A and male-
specific and somatic coliphages as an indicator for viruses) during wet-weather blending?
Question #5: For the three WWTPs studied, to what extent did maceration of disinfected
effluent samples change the levels of fecal coliform and Enter ococcusl
Question #6: For the three WWTPs studied, what were pollutant levels in dry-weather effluent?
In conjunction with Question #1, the study also evaluated the effect of wet-weather blending on
percent removal at the three WWTPs studied. However, it is important to point out that the
discharge permits for NYC DEP WWTPs require compliance with the 85% removal requirement
for both CBOD5 and TSS WWTPs based on a 30-day arithmetic mean, which does not include
the wet-weather data points. The NPDES permits for NYC WWTPs specifically state that
"During periods of wet- weather which causes the plant to exceed plant flows over the permitted
flow for a calendar day, the CBOD$ and TSS influent and effluent results for that day shall not
be used to calculate 30-day arithmetic mean percent removal limitations. However, all
concentrations shall be used in the calculation of the arithmetic mean value concentration
limitations."
The exclusion of wet-weather results applies solely to the calculation of 30-day percent removal
and not to any of the calculations of the 30-day arithmetic mean for CBOD5, BOD5; TSS or fecal
coliform effluent concentrations. Hence, all historical NYC DEP data presented in this report,
except for the average monthly percent removal portions of Table 6 and Table 7, include data
from periods of wet-weather flow. Additionally, all IEC results presented in this report include
data from periods of wet-weather flow, without any exceptions. The summary of effluent
limitations for NYC DEP WWTPs is given in Table 1.
There was high variation in many of the operational parameters among the three WWTPs in this
study. Therefore, the key research questions were addressed separately for each WWTP. Due to
the limited number of samples collected, especially for dry weather periods, the results should be
interpreted and applied to other operations with caution. It should also be noted that while
influent flow data were recorded for all three WWTPs, it was only at one plant (WWTP 1) that
wet-weather secondary flow was recorded during the study. Because of the project team's
knowledge of the blending process, they were able to estimate an approximate flow throughout
the secondary system at the remaining two plants.
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Table 1 - CBOD5, BOD5, and TSS Effluent Limitations for NYC DEP WWTPs
Parameter
CBOD5
CBOD5
BOD5
BOD5
BOD5
TSS
TSS
TSS
TSS
Type
Monthly Average
7-day arithmetic average
Monthly/3 0-day Average
7-day arithmetic average
6 consecutive hour
average
Monthly/3 0-day Average
7-day arithmetic average
Daily Maximum**
6 consecutive hour
average
Limitation
(mg/1)
25
40
30
45
50
30
45
50
50
Required by
NYS DEC
NYS DEC
IEC*
IEC*
IEC
NYS DEC/IEC
NYS DEC and IEC
NYS DEC
IEC
**
Not directly listed in the permit, but is incorporated by reference in the permit.
According to the permit, during periods of wet weather, which results in an instantaneous WWTP
influent flow that exceeds twice the permitted flow, the TSS Daily Maximum limit of 50 mg/1 shall
neither apply for the day of measured flow nor for the succeeding day.
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Chapter 2. Project Summary
The summary of all completed sampling events is presented in Table 2.
Table 2 - Sampling Events: Completed / Planned
WWTP
1
2
3
Total:
Permit Flow
120 MOD
60 MOD
275 MOD
Dry-Weather
Events
1/1
1/1
2/1
4/3
Wet-Weather
Blending Events
4/4
4/4
4/4
12/12
The breakdown of the number of collected effluent samples as compared to the planned number
of samples is shown in Table 3 and Table 4.
Table 3 - Dry-Weather Effluent Samples: Collected / Planned
WWTP
1
2
O
Total:
Bacteria
3/3
3/3
6/3
12/9
Macerated
Effluent
Samples
3/2
2/2
3/2
8/6
Giardia
3/3
3/3
___
6/6
Crypto
3/3
3/3
6/6
Infectious
Crypto
3/3
3/3
6/6
Vims
3/3
3/3
___
6/6
Table 4 - Wet-Weather Effluent Samples: Collected / Planned
WWTP
1
2
3
Total:
Bacteria
15/12
10/12
12/12
37/36
Macerated
Effluent
Samples
9/8
8/8
8/8
25/24
Giardia
12/9
7/9
___
19/18
Crypto
12/9
7/9
19/18
Infectious
Crypto
12/9
7/9
19/18
Virus
9/9
7/9
___
16/18
2 Permit Flow is a 12-month rolling average (average of the current month with the eleven previous months) flow
rate limit for the WWTP. The 12-month rolling average is calculated using total influent flow. During wet-weather,
the NYC DEP WWTPs can typically handle 2 x Permit Flow. For NYC DEP WWTPs, permit flow typically equals
the design flow rate.
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The difference between the collected and planned number of samples presented in Tables 2 and 3
is due to the fact that there were two additional WWTP visits (an extra dry-weather run at
WWTP 3 and an extra wet-weather blending run at WWTP 1) to make up for the portion of the
samples lost during the preceding sampling events. There were also two occasions when the
lEC's field staff had to interrupt sampling and, therefore, missed the last of the three wet-weather
time-variable sample collections at WWTP 2 because blending stopped (first occasion) and due
to a hazardous flooding condition (second occasion).
More detailed description of the number and type of samples that were targeted for collection
throughout the entire WWTP, not just the effluent portion of it, is presented in Chapter 3.
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Chapter 3. Project Design
3.1 Bacteria Sampling
During each sampling event, IEC field staff collected three grab influent (SP1, prior to any
treatment), three grab primary effluent (SP2), three grab pre-chlorinated effluent (SP3, prior to
chlorine contact tank) and three grab effluent (SP4, post chlorination) samples at 45-minute
intervals. (See Figure 2 for sampling locations). The samples were analyzed at the IEC
laboratory for fecal coliform (SM, 20th Edition: Method 9221 A, B, C & D) and Enterococcus
(SM, 20th Edition: 9230 A & B) using the most probable number (MPN) method. There were a
total of five sampling events per WWTP with at least one dry-weather (non-blending) event and
four wet-weather (blending) events. The dry-weather event was used for comparison purposes.
The dry-weather event, by definition, took place on a day when there was no precipitation and no
precipitation during the preceding 48 hours. During wet-weather events, all samples were
collected at peak flows, after WWTPs started bypassing secondary treatment.
IEC had also considered sampling a non-blending wet-weather event, for comparison purposes.
This option was not added to the scope of work because of financial constraints. However, LEG
analyzed available historical effluent data to derive additional comparative information about the
impact of non-blending wet-weather events on the fecal coliform effluent concentration (Section
4.6 of the report).
1.5 x Permit Flow Rate
During wet weather
SP 1
9 t
w
Bar Grit Primary
Screens Chambers Tanks
t
W
~>
SP2
0
i
t
w
r
Aeratic
Tanks
MI Secondary
Tanks
A A
\/'
c
Co
SP3
ฎ t
\
Chlorine
ntact Tanks
SP4
_ฎ_^
Bypass Around Secondary Treatment (up to 0.5 x Permit Flow Rate)
Notes:
1) Permit FlowRate = 12 Month Rolling Average Flow
2) SP1, SP2, SP3, SP4 - IEC Sampling Location
Figure 2. WWTP Wet-Weather Blended and Dry-Weather Non-blended
Sampling Locations
-------
At each of the WWTPs, sampling for the wet-weather events occurred during precipitation of at
least 0.25 inches of rain or higher that was heavy enough to cause a portion of the flow to bypass
the secondary treatment (for New York City WWTPs, this typically happens after the influent
flow exceeds one and a half times the permit flow limit for that WWTP). The sampling
summary is in Table 5 below.
Table 5 - Sampling Summary
Event
Wetl
Wet 2
Wet3
Wet 4
Wet5
Wet 6
WWTP 1
Bacteria
X
X
X
X
Dry 1
Dry 2
X
WWTP
Macer-d
Effluent
Samples
x + o
X
X
X
Protozoa/
Vims
X
X
X
WWTP 2
Bacteria
X
X
X
X
x + o
X
X
WWTP
Macer-d
Effluent
Samples
X
X
X
X
Protozoa/
Virus
X
X
X
WWTPS
Bacteria
X
X
X
X
X
X
X
Macer-d
Effluent
Samples
X
X
X
X
Protozoa/
Virus
X
Notes: X - Sampling event
O -Maceration Optimization Procedure (see Section 3.3)
3.2 Protozoa and Virus Sampling
In addition to the bacteria sampling at the WWTPs, IEC performed four sampling events at two
WWTPs (three during wet-weather blending and one during dry weather) for protozoa (Giardia
and Cryptosporidium), virus (adenovirus, astrovirus, enterovirus, reovirus, rotavirus, norovirus
and Hepatitis A) and male-specific coliphage. Due to budget constraints, only two of the three
New York City WWTPs - WWTP 1 and WWTP 2 - that were used for the bacteria portion of
the study were selected for the protozoa, virus and male-specific coliphage sampling.
Each sampling event at one WWTP was comprised of ten grab samples for protozoa analyses
and ten grab samples for viral analyses. The protozoan sampling consisted of three grab influent
(SP1, prior to any treatment), one primary effluent (SP2), three grab pre-chlorinated effluent
(SP3, prior to chlorine contact tank) and three grab effluent (SP4, post chlorination) samples
collected at 45-minute intervals.3 Viral sampling during the same event included a total of ten
samples - three grab influent (SP1, prior to any treatment), one primary effluent (SP2), three grab
pre-chlorinated effluent (SP3, prior to chlorine contact tank) and three grab effluent (SP4, post
chlorination) samples collected at 45-minute intervals.
! One additional influent sample was also collected to be used as a matrix spike for QA/QC purposes.
10
-------
After the completion of each sampling run, IEC delivered the protozoa samples to the EPA
Region 2 Division of Environmental Science and Assessment (DESA) Laboratory located in
Edison, NJ, where analyses for Giardia and Cryptosporidium were performed. On one occasion
when the EPA DESA Laboratory had other work commitments, a contractual laboratory,
Biological Consulting Services (BCS), was used for protozoan analyses.
For the protozoan portion of the study, the EPA DESA Laboratory detected and enumerated
Giardia and Cryptosporidium using EPA Method 1623. Since this method provides for
quantification of Giardia and Cryptosporidium., but does not allow for viability or infectivity
determination, the laboratory split the sample after processing.
Ten split samples per WWTP were sent out to BCS Laboratories to perform infectivity analyses
for Cryptosporidium using a published method with some modification (Slifko et al., 1999;
Rochelle et al., 2002). Following infectivity determination, molecular confirmation of the
genotype was ascertained by PCR analysis for all samples, except for the positive control
(Quintero-Betancourt et al., 2003).
For the virus portion of the study, ten virus samples per WWTP were also shipped to BCS for
further analyses. BCS performed quantitative viral analyses on all of the aforementioned
samples using EPA ICR Methodology (EPA/600/R-95/178).
In addition, BCS performed analyses for the detection and quantification of male-specific and
somatic coliphage on all samples using a soft agar overlay procedure (Snustad and Dean, 1971).
3.3 Maceration
Maceration breaks apart particles, thereby exposing the particle-associated, occluded, and
aggregated bacteria to the water column. The study consisted of two parts: 1) Maceration
optimization, described below, and 2) Maceration of final effluent samples (SP4) to determine if
maceration had any impact on the results described in Section 4.10.
Maceration Optimization
The optimization procedure was used for the disinfected final effluent samples (SP4) prior to
analyses for fecal coliform and Enterococcus.
The maceration optimization procedure was conducted during one wet-weather blending event
and one dry-weather event at WWTP 1 to determine the optimum speed (revolutions per minute
[rpm]) and time (seconds [s]) of the multi-speed (3,500-22,000 rpm) laboratory blender4 that was
used for maceration of effluent samples during the subsequent wet- and dry-weather runs. Based
on the assumptions and results of the previous studies conducted by the EPA, the optimum speed
and time corresponds to the largest increase in the concentration of bacteria (Enterococcus and
fecal coliform) of the macerated sample compared to the corresponding unmacerated sample.
1TBD Model No. 7012S/7012G, Waring Products, New Hartford, Connecticut
11
-------
Procedure Description: During the dry-period and wet-weather blending event, one final effluent
sample collected from the SP4 location and the eleven replicates of this sample - a total of 12
100 ml samples - were macerated at four different speeds (3500 rpm, 7000 rpm, 14,500 rpm,
and 22,000 rpm) and at three different time intervals (30s, 60s, and 90s) in an autoclaved Waring
blender (see Table 6, below).
Since none of the three WWTPs involved in the study dechlorinate their effluent, SP4 samples
were dechlorinated by IEC field staff (using sodium thiosulfate) immediately upon collection.
The maceration was conducted in the IEC laboratory before inoculation and within a 6-hour
holding time after a sample was collected.
This optimization procedure was subsequently repeated for two additional final effluent samples
taken at 45-minute intervals, to ensure replicability.
Table 6 - Number of Analyses for Maceration Optimization
Time/Speed
30s
60s
90s
3,500 rpm
3
O
3
Total Macerated Analyses:
7,000 rpm
3
3
3
14,500 rpm
3
3
3
22,000 rpm
3
O
3
36
In summary, the project team selected 36 dry-weather and 36 wet-weather macerated analyses to
be performed for fecal coliform and the same number of analyses (36 dry- and 36 wet-weather
analyses) to be performed for Enterococcus. Each of the three final effluent samples involved in
the experiment was analyzed as a regular unmacerated sample for comparison purposes.
Following the completion of the analyses, the optimum speed and time for wet-weather blended
and dry-weather samples was selected based on the largest increase in the bacterial concentration
of the macerated sample compared to the corresponding unmacerated sample. This selection was
done based on analysis of optimization results for each of these three individual effluent samples
and their geometric means. Selected optimization parametersspeed of 22,000 rpm and time of
60 swere then used for fecal coliform and Enterococcus analyses of macerated samples during
subsequent dry- and wet-weather blended events.
12
-------
Chapter 4. Discussion of Project Results
4.1 Analyses of Historical WWTP Performance
NYC DEP's monitoring reports were examined for all three WWTPs for the 12-month period
from May 2006 to April 2007 (Tables 7, 8 and 9). Over that period of time, all three WWTPs
showed very good operational performance with monthly average effluent values consistently
below 20 mg/1 and frequently in single digits for both CBOD5 and TSS parameters. Except for
one instance at WWTP 3, percent removal5 was consistently above 85% for both CBOD5 and
TSS parameters at all three WWTPs. Monthly geometric mean values for fecal coliform were in
double digits for WWTP 2 and WWTP 3 and ranged from double digits to low triple digits for
WWTP 1, consistent with dry-weather results obtained in this study.
The project team also looked at the results of lEC's compliance monitoring inspections
conducted at all three WWTPs over the last two years. During that period of time, IEC carried
out four unannounced inspections at each of the three WWTPs, i.e., a total of 12 inspections.
Most of these inspections took place during dry weather, at which time both WWTP 1 and
WWTP 2 were in compliance with their respective permit; only one out of six hourly samples6
for fecal coliform at WWTP 3 (also collected during dry weather) was in violation during one of
the inspections. However, when IEC inspected WWTP 1 on August 18, 2006, the WWTP began
blending and five out of six hourly samples collected by IEC on the same day were above the
permit limit,7 (i.e., >16,000; 3,000; 5,000; >16,000; 5,000) with geometric average of >5,300
MPN/100 ml, consistent with wet-weather results of this study.
5 As mentioned in Section 1.3, 30-day percent removal for CBOD5 and TSS are the only permit parameters that are
calculated without including wet-weather data.
6 All six hourly samples were collected on the same day.
7 The permit contains, among other parameters, lEC's fecal coliform limits of instantaneous maximum of 2,400
No/100 ml and 6-hour geometric mean of 800 No/100 ml.
13
-------
Table 7. Average Monthly Effluent TSS and % Removal
Month/
Year
May 2006
Jun 2006
Jul 2006
Aug 2006
Sep 2006
Oct 2006
Nov2006
Dec 2006
Jan 2007
Feb 2007
Mar 2007
Apr 2007
AVERAGE
WWTP1
TSS (mg/l)
14
16
14
11
18
16
17
13
10
9
9
15
14
Removal
(%)
94
95
94
96
93
93
92
94
94
95
95
92
94
WWTP2
TSS (mg/l)
6
5
4
4
4
4
6
4
4
5
7
6
5
Removal
(%)
96
97
97
97
98
97
96
97
97
97
96
97
97
WWTP3
TSS (mg/l)
8
8
7
6
9
7
10
11
13
18
14
16
11
Removal
(%)
94
95
94
94
94
94
93
90
88
83
86
89
91
Table 8. Average Monthly Effluent CBOD5 and % Removal
Month/
Year
May 2006
Jun 2006
Jul 2006
Aug 2006
Sep 2006
Oct 2006
Nov2006
Dec 2006
Jan 2007
Feb 2007
Mar 2007
Apr 2007
AVERAGE
WWTP1
CBOD5
(mg/l)
9
8
12
9
14
13
15
12
8
7
8
12
11
Removal
(%)
95
96
93
96
93
94
92
94
96
96
95
<93
94
WWTP2
CBOD5
(mg/l)
5
5
5
6
5
15
5
5
5
5
6
5
6
Removal
(%)
96
96
96
96
96
89
95
95
95
95
<95
<96
95
WWTP3
CBOD5
(mg/l)
5
6
5
5
5
5
6
7
8
11
7
9
7
Removal
(%)
96
95
95
95
96
96
96
93
92
89
92
92
94
14
-------
Table 9. 30-Day Geometric Mean Monthly Effluent Fecal Coliform Values 8
(MPN/per 100 ml)
Month/Year
May 2006
Jun 2006
Jul2006
Aug 2006
Sep 2006
Oct 2006
Nov2006
Dec 2006
Jan 2007
Feb 2007
Mar 2007
Apr 2007
WWTP1
Geom.
Mean
25
52
89
52
133
112
42
30
27
53
83
80
Highest
Daily Value
(during
monthly
period)
246
224
480
544
1200
4000
800
240
355
324
415
4000
WWTP2
Geom.
Mean
4
6
4
4
4
6
63
11
20
14
13
23
Highest Daily
Value (30-Day
Period)
540
800
4000
1000
400
400
4000
4000
4000
52
4000
4000
WWTP3
Geom.
Mean
27
21
27
6
9
19
27
85
85
45
67
74
Highest Daily
Value (30-Day
Period)
640
440
4000
600
300
260
278
680
4000
600
4000
2640
4.2 BOD5 and TSS Results
Analyses of BOD5 and TSS were performed in the lEC's Laboratory using the Standard Methods
SM 5210 B and SM 2540 D, respectively. The study results indicate that during blending,
effluent BOD5 9 and TSS concentrations at WWTP 1 and WWTP 2 were, on average, below 30
mg/1, and effluent BOD5 and TSS concentrations at WWTP 3 were, on average, above 30 mg/1;
the arithmetic averages for both parameters (See Figure 3 and Table 10) were calculated based
on five composite samples (one per sampling event) at WWTP 1, and four composite samples at
both WWTP 2 and WWTP 3. The comparison of standard deviations from historical data vs.
project wet-weather results (Table 7 & 8) shown in Table 10 indicates that these standard
deviations are comparable, with the standard deviation being higher for the project wet-weather
results vs. the historical ones (historical results included a combination of both dry- and wet-
weather data).
Table 10. Comparison of Standard Deviations for Effluent BOD5 and TSS
WWTP
1
2
3
Standard Deviation BOD5 (mg/1)
Historical
2.7
2.9
1.9
Project Wet-Weather
12.0
9.6
7.1
Standard Deviation TSS (mg/1)
Historical
3.1
1.1
3.9
Project Wet- Weather
4.7
5.9
8.6
8 Permits for NYC DEP WWTPs include effluent limit for fecal coliform of 30-day geometric mean of 200 No/lOOml; 7-day
geometric mean of 400 No/100 ml. They also include IEC limitations of 6-hour geometric mean of 800 No/100 ml; and
instantaneous maximum of 2,400 No/100 ml.
9 BOD5 is an effluent criteria used by IEC, as opposed to CBOD5, a criteria by the New York State Department of
Environmental Conservation, a state regulatory agency that issues the permits for NYS WWTPs - See Table 1.
15
-------
,200
WWTP 1 - BOD5 (Arithmetic Mean)
Project Results & Historical Data
(Error Bars Show Standard Deviation)
SP1
SP2
SP4
Wet
Dry
Historical
S 200
ctf
S 150
O
% ป
(L>
e
)
Q
O
PQ
100
50
WWTP 2- BOD5 (Arithmetic Mean)
Project Results & Historical Data
(Error Bars Show Standard Deviation)
SP1
SP2
SP4
Wet
Dry
Historical
Figure 3. BOD5 and TSS Results with Error Bars
10
10Error bars were calculated using standard deviation. No error bars shown for dry-weather results, since there were
only one or two dry-weather runs consisting of composite samples during the study.
16
-------
250
WWTP 3 - BOD5 (Arithmetic Mean)
Project Results & Historical Data
(Error Bars Show Standard Deviation)
SP1
SP2
SP4
oo
ctf
O
dr
&o
H
WWTP 1 - TSS (Arithmetic Mean)
Project Results & Historical Data
(Error Bars Show Standard Deviation)
Wet
Dry
Historical
SP1
SP2
SP4
Figure 3. BOD5 and TSS Results (cont.)
17
-------
WWTP 2 - TSS (Arithmetic Mean)
Project Results & Historical Data
(Error Bars Show Standard Deviation)
SP1
SP2
SP4
WWTP 3 - TSS (Arithmetic Mean)
Project Results & Historical Data
(Error Bars Show Standard Deviation)
SP2
SP4
Figure 3. BOD5 and TSS Results (cont.)
BOD5 and TSS removal during blending remained, on average, above 80% at WWTP 2, above
70% at WWTP 1 and showed a greater decline at WWTP 3 where it was 45% for BOD5 and
17% for TSS (Table 11).
Both BODs and TSS effluent concentrations, and percent removal for WWTP 3, were of lower
quality than those of WWTP 1 and WWTP 2 during the wet-weather events. IEC staff looked
into the potential reasons for this, and discovered that during the time of the sampling, a major
upgrade was being performed at WWTP 3.
Specifically at WWTP 3, at various times during the project, as much as 3 out of 13 aeration
tanks and 8 out of 39 final tanks were out of service for the upgrade. This reduction of capacity
at the WWTP could have had an adverse impact on the treatment quality, especially during
18
-------
blending at peak wet-weather flows. Therefore, the results of sampling at WWTP 3 should be
interpreted in this context.
Additional breakdown of percent removal for primary and secondary treatment for
WWTP 2 during both dry-weather and wet-weather sampling is shown in Table
demonstrates why during wet-weather blending total percent removal values for
were slightly below the expected average of 85% (except for TSS at WWTP 2).
limiting factor was the percent removal in the primary treatment portion of the
primary treatment during wet-weather conditions, the percent removal values
WWTP 2 and TSS at WWTP 1 were slightly below the typical range of removals
BOD5 and of 50-60% for TSS during standard primary treatment operations. u
WWTP 1 and
12. Table 12
both WWTPs
The possible
WWTPs. For
for BOD5 at
of 25-40% for
Table 11. BOD5 and TSS Total Percent Removal
12
WWTP
1
2
O
BOD5 -Dry
Weather (%)
92
88
93
BOD5 - Wet
Blending (%)
77
81
45
TSS -Dry
Weather (%)
89
99
93
TSS -Wet
Blending (%)
71
89
17
Table 12. BOD5 and TSS Percent Removal for Primary and Secondary Treatment
WWTP
1
Parameter
BOD5
TSS
Operating
Mode
Dry Weather
Wet Weather
Dry Weather
Wet Weather
Primary
Treatment
(%)
52
28
31
31
Secondary
Treatment
(%)
83
68
83
57
Total
WWTP (%)
92
77
89
71
2
BOD5
TSS
Dry Weather
Wet Weather
Dry Weather
Wet Weather
59
23
71
49
72
75
95
78
88
81
99
89
The percent removals for Table 12 are calculated by the equations below for both BOD5 and TSS.
For the wet-weather events, SP4 concentrations include the secondary influent that also already
received the blended primary effluent.
11
Tchobanoglous et al, 1991 and Peavy et al., 1985
12 Table 11 shows percent removal for the samples collected by IEC for this project, as opposed to Table 7 and
Table 8 that include the data collected by NYC DEP as part of its permit monitoring requirements.
19
-------
% Removal for Primary Treatment = (SP1-SP2) (100) / SP1
% Removal for Secondary Treatment = (SP2-SP4) (100)/ SP2
% Removal for Total WWTP = (SP 1-SP4) (1OO)/ SP 1
4.3 Bacteria Sampling Results
For both fecal coliform and Enterococcus at WWTP 3 and for fecal coliform at WWTP 1, the
difference between wet-weather blending and dry-weather effluent concentrations was between a
half and one order of magnitude. Effluent fecal coliform and Enter ococcus levels were three
orders of magnitude higher during wet-weather blending vs. dry-weather for both parameters at
WWTP 2 and for Enter ococcus at WWTP 1.
It is worth noting that wet-weather blending effluent concentrations were higher than the
corresponding dry-weather effluent concentrations for both fecal coliform and Enterococcus at
all three WWTPs. In addition, the order of magnitude reduction between influent and effluent
(the "kill") was at least two orders of magnitude stronger in most (five out of six) cases at all
three WWTPs during dry weather as compared to wet-weather blending (Table 13). Both
phenomena can be explained, in part by an increase in hydraulic load, partial treatment, and
reduction in chlorine contact time at subject WWTPs during wet-weather blending.
All results of quality control samples analyzed for both fecal coliform and Enterococcus, during
the timeframe of the blending project, fell within the manufacturer-determined acceptance
ranges. The average percent recoveries of the quality control samples run during the timeframe
of the blending project were calculated; the fecal coliform quality control samples averaged 83%
and the Enterococcus quality control samples averaged 139%. 13
13 These acceptance ranges are determined from interlaboratory studies. Though 139% is greater than 100%, but in
the world of bacteriology (especially for MPN results) it is still considered within the acceptance limits.
20
-------
Table 13. Fecal Coliform and Enterococcus Concentrations
WWTP
1
2
3
Average
Flow
(MGD)
239
122
125
31
469
238.5
Operating
Mode
Wet
Blending
Dry
Wet
Blending
Dry
Wet
Blending
Dry
Fecal Coliform -Geometric Mean
(MPN/lOOml)
Influent
4,200,000
19,000,000
1,100,000
5,000,000
1,600,000
5,600,000
Effluent
4,900
890
19,000
16
520
31
Order of
Magnitude
Reduction
103
104
102
105
103
105
Enterococcus -Geometric Mean
(MPN/lOOml)
Influent
890,000
470,000
260,000
220,000
280,000
1,700,000
Effluent
17,000
20
14,000
3
870
120
Order of
Magnitude
Reduction
102
104
10
105
103
104
e
o
o
WWTP 1 - Fecal Coliform Effluent Concentrations
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
1
O
"3
o
CL>
PH
Wet
Dry
SP1
SP2
SP3
SP4
Figure 4. Fecal Coliform and Enterococcus Effluent Concentrations
21
-------
WWTP 2 - Fecal Coliform Effluent Concentrations
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
O
O
o
u
BO
O
SP1
SP2
SP3
SP4
o
o
Q.
M
O
WWTP 3 - Fecal Coliform Effluent Concentrations
Arithmetic Mean of Log
(Error Bars Show Standard Deviation
SP1
SP2
SP3
SP4
WWTP 1 - Enterococcas Effluent Concentrations
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
7.00
SP1
SP2
SP3
SP4
Figure 4. Fecal Coliform and Enterococcus Effluent Concentrations (cont.)
22
-------
o
o
I
2
^
I
00
o
h-l
WWTP 2 - Enterococcus Effluent Concentrations
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
SP1
SP2
SP3
SP4
WWTP 3 - Enterococcus Effluent Concentrations
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
I
to
h-l
8
SP1
SP2
SP3
SP4
Figure 4. Fecal Coliform and Enterococcus Effluent Concentrations (cont.)
4.4 Blending Flow Ratio
The project team collected data for the WWTP influent flow rates at all three WWTPs during
both dry- and wet-weather blending sampling events. At WWTP 1, during wet-weather, the flow
rate through the secondary treatment system was recorded. While the exact flow rate through the
secondary treatment system was not recorded for WWTP 2 or WWTP 3 because they did not
have the necessary flowmeters, both of these WWTPs started blending at approximately 1.5
Permit Flow, i.e. at 90 MOD and 412.5 MOD, respectively.
-------
A summary of the flow rate data is provided in Appendix C.
This information allowed the project team to estimate the blending ratio, i.e., the ratio of a flow
bypassing secondary treatment to influent flow for all three WWTPs. At WWTP 1, this ratio
ranged from 9% to 29%, with an average value of 22%. This was in line with the usual 25%
ratio for blending at the NYC DEP WWTPs, i.e.:
Blending Ratio= Flow Bypassing Secondary Treatment / Target WWTP Wet-Weather Influent
Flow
For a NYC DEP WWTP accepting a maximum of 2 x Permit Flow, the ratio is:
Blending Ratio = 0.5 x Permit Flow / 2 x Permit Flow = 25% (see Figure 2, page 9)
Using the estimated 1.5 x Permit Flow values as the threshold for the beginning of the bypass of
secondary treatment for both WWTP 2 and WWTP 3, the project team approximated 29% as the
average blending ratio for WWTP 2 and 11% as the average blending ratio for WWTP 3. This is
important, since the higher blending ratio results in higher flow bypassing secondary treatment,
and could potentially lead to lower effluent quality. These results could also partially explain
why fecal coliform and Enterococcus results for WWTP 3, which had the lowest average
blending ratio (11%), were less affected during wet-weather blending (see Section 4.3).
4.5 Total Residual Chlorine (TRC) Results
There was no correlation between TRC vs. fecal coliform and/or plant flow (using both multiple
and two-variable regressions).
Chlorine residual concentrations were, on average, lower during wet-weather blending vs. dry
weather at WWTP 2 and higher at WWTP 1 and WWTP 3 (Figure 5). While not measured by
the project team, the contact times were shorter during blending events due to higher flow rates.
24
-------
Total Residual Chlorine (TRC) at Effluent
(Arithmetic Mean) Error Bars Show Standard Deviation
Figure 5. Total Residual Chlorine at Effluent
As background information, all three WWTPs have chlorine contact tanks and do not utilize a
dechlorination process following chlorination.
For TRC measurement, the project field staff used lEC's standard operating procedure based on
Hach Method 8167 and SM 18-20 4500-C1 G, which is a colorimetric version of the N, N-
diethyl-p-phenylenediamine (DPD) method. The method is based on the reaction of DPD with
chlorine to produce red color. The intensity of the color produced is proportional to the
concentration of total chlorine in the sample. The Hach Pocket Colorimeter instrument was
calibrated according to manufacturer's instructions to measure the total chlorine content in
aqueous samples from 0.1 mg/1 to 2.00 mg/1; samples in excess of the higher detection limit are
diluted as appropriate.
The chlorine contact time was not directly measured during sampling. However, for WWTP 1,
the chlorine contact time was later estimated using the WWTP flow rate values collected during
sampling, as follows:
Contact Time (min) = Total Volume of Chlorine Contact Tanks / Flow Rate
The average contact time values are summarized in Table 14; individual contact time values are
shown in Appendix C.
25
-------
Table 14. Chlorine Contact Time, WWTP 1
Operating Mode
Dry weather
Wet weather
Estimated Average Chlorine
Contact Time (min)
29.4
15.1
Range (min)
25.8-32.1
14.3-20.8
4.6 Analysis of Existing Monitoring Data - Wet-Weather Non-Blending Events
Though contracted to this research project, lEC's principal function was to conduct regular 6-
hour inspections at NYC DEP treatment WWTPs to check compliance with both the NPDES
permit requirements and lEC's Water Quality Regulations.
Examination of IEC monitoring data for the period 2001-2007 for the three WWTPs revealed
two mixed wet-weather events (each including both blending and non-blending samples) and a
partial wet-weather non-blending event with very low ("trace", i.e., less than 0.01 in.)
precipitation at WWTP 1. Linear regression analysis of the fecal coliform vs. flow rate data for
these three events (a total of 18 data points; 6 data points per event), showed a trend of moderate
magnitude with R2= 0.46 (Figure 6 and Table 15). This demonstrates that with increase in flow
rate, the values of effluent results for fecal coliform also show an upward trend.
Wet Weather
% of Design Flow vs. Fecal Coliform
18000 -i
16000
- 14000
= 12000
o 10000
^ 3000
Q.
2000
0
Wet-weather
Non-Blending
Wet-weather
Blending
-ป ซ-
v=139.3x-12039i
R2 = 0 461
50 100
% of Design Flow
150
200
Figure 6. Historical IEC Wet-Weather Results - Percent of Design Flow vs. Fecal
Coliform Count
26
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Table 15. Historical IEC Wet-Weather Results (Non-Blending and Blending)
(fecal coliform, MPNY per 100 ml)
WWTP
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Date
2/5/2001
2/5/2001
2/5/2001
2/5/2001
2/5/2001
2/5/2001
5/18/2004
5/18/2004
5/18/2004
5/18/2004
5/18/2004
5/18/2004
8/28/2006
8/28/2006
8/28/2006
8/28/2006
8/28/2006
8/28/2006
Flow 14
102
104
144
146
211
208
135
137
138
114
109
101
201
189
168
154
155
157
% of Design
Flow
85
87
120
122
176
173
113
115
115
95
91
84
167
158
140
128
129
131
Fecal
Coliform
170
340
800
500
16,000
16,000
5,000
3,000
450
2,200
2,300
800
1,100
16,000
3,000
5,000
16,000
5,000
TRC
(mg/l)
0.9
0.7
0.5
0.7
0.7
0.7
0.8
0.8
0.9
0.8
0.8
0.7
0.7
0.7
0.8
0.8
0.8
0.7
Daily Precipitation
(inV5
0.5
Trace
0.35
4.7 Protozoa Results
Effluent concentrations of Cryptosporidium were higher during wet-weather blending at one
WWTP (WWTP 1) when compared to dry weather. The Cryptosporidium effluent results during
wet weather were mostly in single or low double digits, with an average percent removal of 71%
at WWTP 1. Average percent removal for WWTP 2 could not be estimated, since less than three
detectable results were reported (Figure 7 and Table 16).
Infectious Cryptosporidium values at both WWTPs were mostly low or non-detectable. Only
two out of nineteen infectious Cryptosporidium effluent samples showed a detectable value; only
one of these two samples showed the presence of C. Parvum Genotype II.
Effluent values of Giardia spp. were one order of magnitude higher during wet-weather blending
vs. dry weather at both WWTP 1 and WWTP 2. The geometric mean of Giardia effluent results
during wet weather were in the low triple digits, with 88% removal, at WWTP 1 and with 40%
removal, at WWTP 2. While no estimation of infectivity of Giardia was performed for this
study, it is logical to assume that, similar to Cryptosporidium, a portion of remaining Giardia
should be non-infectious.16
Blending samples with WWTP flow exceeding 150% of the design flow are shown in bold (blending typically
occurs when WWTP flow exceeds 150%)
15 Central Park, NY
16 Studies showed that Giardia infectivity is generally more sensitive to hypochlorite than Cryptosporidium, which
already demonstrated low infectivity in effluent concentrations obtained in this study.
27
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Table 16. Range of Final Effluent Concentrations for Protozoa
WWTP
1
2
Operating
Mode
Dry
Wet Blending
Dry
Wet Blending
Giardia cysts/ 1
(enumerated values)
Range
6-21
40 - 720
2-4
7-720
Geometric
Mean
12
148
o
J
105
Cryptosporidium oocysts/ 1
(enumerated values)
Range
1-8
<0.2 - 52
2-4
<0.2 - 2
Geometric
Mean
2
8
2
NA
Infectious
Cryptosporidium
MPN/1
Range
0.2
<0.3 - <9.2
<0.2
0.5-
<2.4
Geometric
Mean
NA
NA
NA
NA
Note: NA =Less than three detectable results were reported, hence geometric mean could not be calculated
WWTP 1 - Giardia
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
Wet
Dry
SP1
SP2
SP3
SP4
Figure 7. WWTPs 1 & 2 Giardia17 & Cryptosporidium Effluent Concentrations
18
with Error Bars
19
Less than three detectable Giardia results were reported for both SP1 and SP2 locations at WWTP 1 and SP2
location at WWTP 2 during dry weather, hence the geometric mean could not be calculated.
18 Dry-weather results for SP1 and SP2 locations at WWTP 1 were affected by clogged filters and, therefore
prevented the full detection of Giardia and Cryptosporidium, therefore, dry-weather SP1 and SP2 results for WWTP
1 should not be used for deriving conclusions for this study.
19 For these charts, the Arithmetic mean of the log of results were calculated. The error bars were then calculated by
taking the standard deviation.
28
-------
WWTP 2 - Giardia
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
SPl
SP2
SP3
SP4
en
+j
>,
ctf
O
I
WWTP 1 - Cryptosporidium
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
Wet
Dry
20
Figure 7. WWTPs 1 & 2 Giardia and Cryptosporidium Effluent Concentrations (cont.)
20 Less than three detectable Cryptosporidium results were reported for the SPland SP2 locations at WWTP 1 during
dry weather, hence geometric mean could not be calculated. At WWTP 2, all of the sampling points, except SP3
and SP4 for dry-weather had less than three detectable Cryptosporidium results hence geometric mean for these
results could not be calculated.
29
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og Arithmetic Mean
sts/1)
> i-1
3 8
^ ฃ
s
:ง
c
o
g, 0.00
S
ง:
L)
-0.50
WWTP 2 - Cryptosporidium
Arithmetic Mean of Log
Error Bars show Standard Deviation
I
'
SP1 SP2 SP3 SP4
Dry|
Figure 7. WWTPs 1 & 2 Giardia and Cryptosporidium21 Effluent Concentrations with
Error Bars (cont.)
Table 17. Giardia and Cryptosporidium Average Percent Removal
WWTP
1
2
1
2
Weather
Condition
Wet
Wet
Dry
Dry
Removal of
Giardia (%)
88
40
NA
99
Removal of
Cryptosporidium (%)
71
NA
NA
NA
Note: NA =Less than three detectable values were reported at the influent and/or effluent of the WWTP, hence
average percent removal could not be calculated.
4.8 Virus Results
With relatively high WWTP influent results during wet-weather blending, the effluent results for
enteric viruses were, on average, in single digit or low double-digit infectious units/1 in final
effluents, with average removal between 98% and 99% for WWTP 1 and 99% for WWTP 2
Less than three detectable Cryptosporidium results were reported for the SPland SP2 locations at WWTP 1 during
dry weather, hence geometric mean could not be calculated. At WWTP 2, all of the sampling points, except SP3
and SP4 for dry-weather had less than three detectable Cryptosporidium results hence geometric mean for these
results could not be calculated.
30
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(Table 21). The results were generally consistent, with some variability, across all four cell
lines22 (BGM, MA104, PLC/PRF/5 and CaCo-2), as demonstrated in Table 18 and Figure 8.
Table 18. Range of Final Effluent Results for Viruses
WWTP
1
2
Operating
Mode
Dry
Wet
Dry
Wet
BGM Infectious
Units/1
Range
1-3
3-143
3-6
-------
Table 20. Detected Viruses
a) Dry weather
WWTP
1
2
Sampling
Location
SP1
SP2
SP3
SP4
SP1
SP2
SP3
SP4
BGM
EV
EV
EV
EV
REO, EV
EV
EV
MA-104
EV,REO,RV
EV,REO,RV
EV,REO
REO
EV, REO
EV,REO
REO
REO
PLC/PRF/5
EV, AdV
EV
EV, AdV
EV, AdV
EV, AdV
CaCo-2
EV
EV
EV
EV
b) Wet weather
WWTP
1
2
Sampling
Location
SP1
SP2
SP3
SP4
SP1
SP2
SP3
SP4
Event
#
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
BGM
EV
EV, REO
EV, REO
EV, REO
EV
EV, REO
EV
EV
EV
EV, REO
EV
EV, REO
EV, REO
EV, REO
EV
EV, REO
EV, REO
EV
EV, REO
EV
EV
EV
MA-104
EV,RV
EV,RV
EV, REO, RV
EV,RV
EV, REO
EV,REO
REO
EV, REO
REO
REO
REO
EV, RV, REO
EV, RV, REO
EV, RV, REO
EV, RV
EV, RV
EV, RV, REO
RV, REO
RV
REO
RV, REO
REO
PLC/PRF/5
EV, AdV
EV, AdV
EV, AdV
EV, AdV
EV, AdV
AdV
AdV
AdV
AdV
AdV
AdV
AdV
EV, AdV
EV, AdV
EV, AdV
EV, AdV
EV, AdV
EV, AdV
AdV
AdV
EV, AdV
AdV
CaCo-2
EV
EV
EV
EV
EV
EV
EV
EV
EV
EV
EV
EV
EV
EV
EV
EV
Note: AdV = Adenovirus
EV = Enterovirus
RV = Rotavirus REO = Reovirus
32
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Buffalo Green Monkey
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
o o
co c
H _
!C CD
3 01
ISTP 1 Dry
STP 1 Wet
STP 2 Dry
STP 2 Wet
SP1
SP2
SP3
SP4
MA -104
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
SP1
SP2
SP3
SP4
23
Figure 8. Virus Concentrations by Cell Lines
23 Less than three detectable vims concentrations were reported for the SP2 location for both WWTP 1 and WWTP
2 for all of the four cell lines during dry weather, hence geometric mean values could not be calculated
33
-------
PLC/PRF/5
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
STP 1 Dry
STP 1 Wet
STP 2 Dry
STP 2 Wet
SP1
SP2
SP3
SP4
c o
S3
z >
u .ti
'43 c
Ol 3
I s
ฃ o
oi 3
.
o
CaCo-2
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
SP1
SP2
SP3
SP4
24
Figure 8. Virus Concentrations by Cell Lines (cont.)
24 Less than three detectable vims concentrations were reported for the SP2 location for both WWTP 1 and WWTP
2 for all of the four cell lines during dry weather and for SP4 location for the CaCo-2 cell line during dry weather,
hence geometric mean values could not be calculated
34
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Table 21. Average Percent Removal of Viruses during Wet-Weather
WWTP
1
2
BGM Removal
(%)
98
99
MA- 104
Removal (%)
98
99
PLC/PRF/5
Removal (%)
98
99
CaCo-2 cells
Removal (%)
99
99
4.9 Coliphage Results
Analysis of the concentrations for the two WWTPs, at which the coliphage25 samples were
collected, shows that male-specific coliphage was generally lower during wet-weather blending
vs. dry-weather conditions throughout WWTP 1. At both SP3 and SP4 for WWTP 2, there were
no major differences in the geometric means between wet-weather blending and dry-weather
conditions.
Effluent concentrations for both coliphage parameters - Famp and C3000 (a plaque assay on E.
coif) - during wet weather were mostly in single digits, with average percent removal of 99% for
both C3000 and Famp at WWTP 1, and 97% removal for Famp at WWTP 2. (Table 23). The
average percent removal of C3000 for WWTP 2 could not be calculated, since less than three
detectable results were reported for that parameter.
Table 22. Range of Final Effluent Concentrations for Coliphage
WWTP
1
2
Operating
Mode
Dty
Wet
Dty
Wet
Famp bacteriophage / ml
Range
53-62
1-5
3-6
2-12
Geometric
Mean
57
2
4
4
C3000 bacteriophage / ml
Range
32-56
2-7
3-8
1-3
Geometric
Mean
43
3
5
NA
Note: NA =Less than three detectable results were reported, hence geometric mean could not be calculated
Here and thereafter, Famp represents F+ (male-specific) phage and C3000 represents both male-
specific and somatic phage.
25 Coliphages are bacteriophages that infect Escherichia coli (E. coli). They are frequently viewed as alternate
bacterial indicators, representing enteric virus contamination.
35
-------
M
o
.y E
O)
on
a O
ฃ 'C
ns oj
~
M
Bacteriophage-Famp
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
SP1
SP2
SP3
SP4
O
c
af .2
o -z
u
Bacteriophage-CSOOO
Arithmetic Mean of Log
(Error Bars Show Standard Deviation)
SP1
SP2
SP3
SP4
Figure 9. Coliphage Concentrations - Famp and C3000
26
26 Less than 3 detectable C3000 results were reported for the SP2 location at WWTP 1 during wet-weather and for
all of the four locations at WWTP 2 during wet-weather, hence geometric mean values could not be calculated.
36
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Table 23. Coliphage Average Percent Removal during Wet Weather
WWTP
1
2
Famp Removal (%)
99
97
C3000 Removal (%)
99
NA
TVofe: Aฃ4 =Less than 3 detectable values for C3000 were reported at the each of the four locations at WWTP 2
during wet weather throughout the WWTP, hence percent removal values could not be calculated.
4.10 Maceration Results
The project team investigated the impact of maceration on the detection and enumeration of fecal
indicator levels in chlorinated effluents. Previous research (Perdek and Borst, 2000) suggests that
conventional MPN/MF methods fail to adequately measure bacteria within clusters of bacteria or
particles. In an effort to account for such cluster and particle occlusion/association, two effluent
samples per WWTP were collected from the post-chlorinated final effluent (SP4) during the first
three wet-weather events and one dry-weather event. These samples were macerated at a pre-
determined proper contact time and speed to investigate the effect of penetration of the
disinfectant into the mix of blended primary and secondary effluent followed by disinfection.
After the maceration, these samples were further analyzed for Enterococcus and fecal coliform
and the results were compared to regular (unmacerated) effluent samples.
Since none of the three WWTPs involved in the study dechlorinate their effluent, SP4 samples
were dechlorinated by IEC field staff using 0.025 N sodium thiosulfate immediately upon
collection. The maceration was conducted in the IEC laboratory within a 6-hour holding time
after sample was collected.
During the dry-weather run on July 17, 2006, at the WWTP 1, IEC collected 34 additional
samples and 6 duplicates at SP4 to perform maceration optimization for fecal coliform and
Enterococcus. The maceration optimization analyses indicated that for this round of sampling
the optimum combination of blending speed and time was 22,000 rpm and 60 s, respectively, in
order to obtain the highest fecal coliform and Enterococcus count.
The first wet-weather event took place on September 14, 2006, at the WWTP 1. Similar to the
dry-weather run, 36 additional samples and 6 duplicates were collected from the SP4 location to
perform maceration optimization for bacteria. The maceration optimization analyses indicated
that for this round of sampling, there were two combinations that were potentially the optimum.
These combinations were 3,500 rpm at 90 s and 22,000 rpm at 60 s. On October 20, 2006,
during a wet-weather run at the WWTP 1, a second mini-optimization was performed with these
combinations of speed and time repeated. This second run showed that 22,000 rpm at 60 s is the
optimum setting for maceration for wet-weather events.
Since this portion of the study is purely a comparison of macerated and unmacerated results,
which is independent of location and weather conditions, and to give it a greater data pool, all of
the results comprising of 64 data points were combined. To get a more statistically precise
37
-------
number all results with greater than (< 3) or less than (> 24,000) value and one outlier were
removed. This still left 21 data points for fecal coliform and 24 for Enterococcus.
It was expected that maceration would result in higher fecal coliform and Enterococcus
concentrations, because maceration exposes bacteria occluded in larger particles. A statistical
evaluation of the data points performed for the macerated and unmacerated dry and blended
disinfected effluent laboratory analyses revealed that the increase in macerated concentrations
for fecal coliform and for Enterococcus was statistically significant. The statistical method used
was analysis of variance (ANOVA). A three-way ANOVA was used to compare two weather
types (Wet, Dry), three treatment plants (WWTP 1,WWTP 2, WWTP 3) and two treatments
(macerated and unmacerated).
an
o
5.00
o -4.50
c E
re o
o 4-.00
Macerated vs. Unmacerated
Arithmetic Mean of Log
Error Bars Show Standard Deviation
Macerated
Unmacerated
Feca Coliform
Enterococcus
Figure 10. Macerated vs. Unmacerated Concentrations
Detailed maceration optimization charts are included in Appendix E.
38
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Chapter 5. Conclusions and Recommendations
5.1 Conclusions and Observations
Samples of effluent from the three WWTPs that blended wet-weather flows were analyzed for
key pathogens, pathogen indicators, TSS and BOD. During the sampling period, a major upgrade
was being performed at WWTP 3, with several aeration and final tanks being out of service.
These temporary modifications to the treatment facility likely had an adverse impact on the
treatment quality, especially during blending at peak wet-weather flows. Based on this, the
results of sampling for WWTP 3, should be interpreted in this context.
Effluent from the three WWTPs operating under dry-weather conditions with all flows receiving
secondary treatment and disinfection was sampled for pathogens, pathogen indicators,TSS and
BOD.
In combined sewer systems, microorganism removal during wet-weather blending events may
vary from WWTP to WWTP depending on a number of different factors including design,
operation, maintenance, and rainfall, resulting in a variable flow into the plant.
The limitation of the study is that it represents only one geographical location for the three plants
studied and the wet-weather blending ratios or flow rates were measured in only one of the three
plants. Thus, the geographical closeness and the limited number of facilities evaluated during
the study suggest that these results should be viewed as plant-specific. Additional studies are
recommended at a variety of WWTPs to provide reinforcement of the data obtained in this study.
1) Question #1: During wet-weather blending events at the WWTPs studied what were BOD
and TSS levels in the blended effluent?
The average of BODs wet-weather blending effluent concentrations were 24 mg/1 at WWTP 1
(values ranged from 9.5 to 37 mg/1), and 22 mg/1 at WWTP 2 (values ranged from 9 to 30 mg/1).
The average of TSS wet-weather blending effluent concentrations were 29 mg/1 at WWTP 1
(values ranged from 22 to 33 mg/1) and 20 mg/1 at WWTP 2 (values ranged from 13 to 26 mg/1).
All of these average effluent values were below the IEC effluent value of 30 mg/1 for a 30 day
average.27
The average removal values for wet-weather blending samples collected during the study at
WWTP 1 were 77% for BOD5 and 71% for TSS; and at WWTP 2 were 81% for BOD5 and 89%
for TSS.
Since the total percent removal during blending at both WWTPs was slightly below the expected
average of 85%, further analyses of percent removal data during blending showed that the
possible limiting factor was the percent removal in the primary treatment portion of the WWTPs.
The average percent removal values for primary treatment during wet-weather blending events at
27 Since this study is a research project, the comparison with effluent limitations is used here only as a convenient
benchmarking tool
39
-------
WWTP 1 were 28% for BODS and 31% for TSS and at WWTP 2 were 23% for BODS and 49%
for TSS. The aforementioned results for BODS at WWTP 2 and for TSS at WWTP 1 were
slightly below the preferred range of removals of 25 to 40% for BODS and of 50 to 60% for TSS
during standard primary treatment operations. Another reason for the lower removals is that a
portion of the flow did not receive secondary treatment.
During the time of the sampling, a major upgrade was being performed at WWTP 3, with several
aeration and final tanks being out of service, this likely had an adverse impact on the treatment
quality, especially during blending at peak wet-weather flows. Based on this, the results of
sampling for WWTP 3, should be used with caution. At WWTP 3, average effluent
concentrations for both BOD5 and TSS (average of 37 mg/1 and 56 mg/1, respectively) were
higher than the other two WWTPs, and the percent removal was notably lower than the other two
WWTPs.
2) Question #2: During wet-weather blending events at the WWTPs studied, what were the
fecal coliform and Enterococcus levels in the blended effluent?
The fecal colifom effluent concentrations had a geometric mean of 4,900 MPN/100 ml at WWTP
1 during wet weather, 19,000 MPN/100 ml at WWTP 2 during wet weather and 520 MPN/100
ml at WWTP 3 during wet weather.
The Enterococcus effluent concentrations had a geometric mean of 17,000 MPN/100 ml at
WWTP 1 during wet weather, 14,000 MPN/100 ml at WWTP 2 during wet weather and 870
MPN/100 ml at WWTP 3 during wet weather.
3) Question #3: For the WWTPs studied, was there evidence for removal of protozoa
(Cryptosporidium, infectious Cryptosporidium and Giardid) during wet-weather blending?
The total Cryptosporidium enumerated (non-infectious) effluent results during wet weather were
mostly in single or low double digits, with removal of 71% for WWTP 1. Average percent
removal for WWTP 2 could not be estimated, since less than three detectable results were
reported.
During wet-weather blending, infectious Cryptosporidium showed a detectable value in only two
of nineteen effluent samples (both results were in single digit and at WWTP 1). Only one of
these nineteen effluent samples showed the presence of C. parvum Genotype II.28
The geometric mean of Giardia effluent results during wet weather were in the low triple digits,
with 88% removal, at WWTP 1 and with 40% removal, at WWTP 2. No estimation of
infectivity of Giardia was performed for this study.
4) Question #4: For the WWTPs studied, was there evidence for removal of viruses
(Adenovirus, Astrovirus, Enterovirus, Rotavirus, Reovirus, Norovirus, Hepatitis A and male-
specific and somatic coliphages as an indicator for viruses) during wet-weather blending?
1 C. Parvum Genotype II can infect both human and non-human hosts.
40
-------
Effluent results for enteric viruses during wet weather were mostly in single digits, with average
removal between 98% and 99% for WWTP 1 and 99% for WWTP 2. The presence of Reovirus,
Norovirus and Hepatitis A in the effluent was not detected at all.
During wet-weather blending, effluent results for both coliphage parametersas measured by E.
coli plaque analysis using Famp (male-specific) and C3000 (represents both male-specific and
somatic)were mostly in single digits, with average percent removal of 99% for both C3000
and Famp at WWTP 1 and 97% removal for Famp at WWTP 2. The average percent removal of
C3000 for WWTP 2 could not be calculated, since less than three detectable results were
reported for that parameter.
5) Question #5: For the WWTPs studied, to what extent did maceration of disinfected effluent
samples change the enumerated levels of fecal coliform and Enterococcusl
After a statistical evaluation, the results showed that the maceration of effluent samples resulted
in an increase in both fecal coliform and Enterococcus concentrations.
6) Question #6: For the WWTPs studied, what were the pollutant levels in dry-weather
effluent?
The dry-weather effluent concentrations for BOD5 were 15 mg/1 at WWTP 1,13 mg/1 at WWTP
2 and 9 mg/1 at WWTP 3. The dry-weather effluent concentrations for TSS were 12 mg/1 at
WWTP 1, 2 mg/1 at WWTP 2 and 8 mg/1 at WWTP 3.
The average percent removal for dry-weather samples collected during the study was 92% for
BOD5 and 89% for TSS at WWTP 1, 88% for BOD5 and 99% for TSS at WWTP 2 and 93% for
BOD5 and 93% for TSS at WWTP 3. All of these dry-weather results exceeded the expected
85% removal.
Additional Observations
There was no correlation between total residual chlorine (TRC) vs. fecal coliform and/or WWTP
flow (using multiple and two-variable regressions).
Enteric virus results were generally consistent, with some variability, across all four cell lines
(BGM, MAI04, PLC/PRF/5 and Caco-2).
Based on these findings, one of the additional implications of the study is that a pathogen
removal for wet-weather blending is WWTP specific. Although not analyzed in this study, it is
also clear that the design and operational characteristics of the individual WWTPs are factors
affecting the ability of individual WWTPs to adequately handle peak flow.
It is important to emphasize that the findings from this research study, conducted in a single
geographic area with a limited number of data points, are not meant to draw conclusions on a
national scale to directly support any future nor existing EPA policy guidelines or regulations.
Additional data collection is recommended at the WWTPs studied in this project, WWTPs with
41
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separate sewer systems and WWTPs located in other locations to improve our understanding on
impacts of wet weather flows on combined sewer and sanitary sewer system WWTP operations.
5.2 Future Research
A. Increase the understanding of the fate and transport of pathogens and related indicators
being discharged from WWTPs during blending by:
a. evaluating sampling protocols and test methods (including maceration, sonication,
and tissue homogenization) for determining more accurate concentrations of
specific microorganisms in WWTP effluents during normal dry weather
conditions and blending,
b. determining the major factors impacting fate and transport of pathogens in
blended effluents, including die-off and after-growth potential of specific
microorganisms in waters receiving effluents from WWTPs during blending, and
c. assessing the effects of the discharge of effluents from WWTPs during blending,
on risks to human health, especially in receiving waters used for recreation.
B. Characterize the effectiveness of treatment plant optimization and the application of
additional treatment technologies for managing increased wet-weather flows by:
a. obtaining information on municipal wastewater treatment plants regarding:
i. WWTPs that experience increased wet-weather flows and the frequency of
blending;
ii. WWTPs that have conducted "stress tests" to determine the peak, wet-
weather flow treatment capacity of their plant;
iii. WWTPs that have tested or acquired commercial treatment technology,
retrofitted existing technology, or otherwise treat side stream flows; and
iv. WWTPs that have formal institutionalized monitoring protocols and
decision-making processes for peak, wet-weather flow situations
b. developing and validating treatment plant stress-testing protocols for determining
peak, wet-weather flow capacities of WWTPs;
c. characterizing the ability of retrofit, side-stream and other technology and process
modifications to meet secondary treatment regulatory standards and, when
coupled with appropriate disinfection, to remove key pathogens, including;
i. physical-chemical processes, such as, chemical addition and ballasted
flocculation, tube and plate settlers, fine-mesh screening and filtration, and
dissolved-air floatation;
ii. enhanced biological treatment with high-rate parallel facilities, such as,
deep-bed, honey-comb plastic media trickling filtration; and series
treatment by switching from conventional activated sludge to contact
stabilization;
iii. high-rate disinfection and related process modifications, such as, increased
mixing intensity, increased disinfectant concentrations, more rapid and
effective disinfectants (oxidants and ultraviolet light), and multi-stage
dosing; and
iv. innovative and advanced technologies, such as, activated carbon, high-
gradient magnetic separation, and fluidized-bed biological treatment.
42
-------
C. Provide technical guidance on the use of "stress tests," commercially available parallel-
treatment units and other monitoring and treatment strategies by WWTPs to determine
and augment the peak, wet-weather flow capacity of current treatment plants.
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Quintero-Betancourt, W., A. L. Gennaccaro, T. M. Scott, and J. B. Rose. (2003). Assessment of
Methods for Detection of Infectious Cryptosporidium Oocysts and Giardia Cysts in
Reclaimed Effluents. Applied and Environmental Microbiology 69(9): 5380-5388.
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Perdek, J.M. and M. Borst (2000). Particle Association Effects on Microbial Indicator
Concentrations for CSO Disinfection. ASCE's Joint Conference on Water Resources
Engineering and Water Resources Planning & Management, July - August 2000,
Minneapolis, MN.
Reynolds, K.A. (2004). Integrated cell culture/PCR for detection of enteric viruses in
environmental samples. Methods in Molecular Biology. 268: 69-78.
Rochelle, P.A., M.M. Marshall, J.R. Mead, A.M. Johnson, D.G. Korich, J.S. Rosen, and R.D.
Leom. (2002). Comparison of In Vitro Cell Culture and a Mouse Assay for Measuring
Infectivity of Cryptosporidium parvum. Applied and Environmental Microbiology
68(8):3809-3817
Sedmak, G., D. Bina, J. MacDonald, and L. Couillard. (2004). Nine-Year Study of the
Occurrence of Culturable Viruses in Source Water for Two Drinking Water
Treatment WWTPs and Influent and Effluent of a Wastewater Treatment WWTP in
Milwaukee, Wisconsin (August 1994 through July 2003). Applied and Environmental
Microbiology. 71:1042-1050
Slifko, T.R., D.E. Friedman, and J.B. Rose. (1999). A most-probable-number assay for the
enumeration of infectious Cryptosporidium parvum oocysts. Applied and Environmental
Microbiology 65 (9): 3 93 6-3 941.
Slifko T.R., D.E. Friedman D, J.B. Rose JB, and W. Jakubowski. (1997). An in vitro
method for detecting infectious Cryptosporidium oocysts with cell culture.
Applied and Environmental Microbiology 63 (9):3669-75.
Snustad, S.A., andD.S. Dean. (1971). Genetic Experiments with Bacterial Viruses, W.H.
Freeman & Co. San Francisco; 1971.
Spinner, M.L. and G.D. DiGiovanni. (2001). Detection and identification of mammalian
reoviruses in surface water by combined cell culture and reverse transcription-PCR.
Applied and Environmental Microbiology 67: 3016-3020.
Tchobanoglous, G. andF.L. Burton (1991), Wastewater Engineering: Treatment,
Disposal, and Reuse, Metcalf & Eddy, Inc., McGraw-Hill, New York, 1991.
van Heerden J., M.M. Ehlers, A. Heim, and W.O. Grabow. (2005). Prevalence, quantification
and typing of adenoviruses detected in river and treated drinking water in South Africa.
Applied and Environmental Microbiology 99: 234-242
Wellings, F.M., Lewis, A.L. and Mountain, C.W. 1976. Demonstration of solids-associated
viruses in wastewater and sludge. Applied and Environmental Microbiology, 31:354-358.
Xiao, L., I. Sulaiman, R. Payer, and A.A. Lai (1998). Species and Strain-specific Typing
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Bibliography
1. U.S. Environmental Protection Agency, 2001. EPA Requirements for Quality Assurance
Project Plans (QA/R-5), U.S. EPA Office of Environmental Information.
2. U.S. Environmental Protection Agency, 2001. Guidance on Environmental Data
Verification and Data Validation (QA/G-8), U.S. EPA Office of Environmental
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4. AMERICAN PUBLIC HEALTH ASSOCIATION. 1992, Standard Methods for the
Examination of Dairy Products, 18th ed., American Public Health Association,
Washington. D.C.
5. AMERICAN PUBLIC HEALTH ASSOCIATION. 1970. Recommended procedures for
the examination of Sea Water and Shellfish, 4th ed. American Public Health Association,
New York.
6. AMERICAN PUBLIC HEALTH ASSOCIATION. American Water Works Association,
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7. Interstate Environmental Commission, January 2004. Standard Operating Procedures
Manual of the Interstate Environmental Commission for Sampling, Sample Preservation,
Analyses, and Quality Control, New York, N. Y.
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Procedures for Microbiological Testing and Analysis, New York, N.Y.
45
-------
Appendix A
Detailed Sampling Results
46
-------
Plant
Operating
Mode
Dry
Plant
Plant 1
Plant 2
Plant 3
Location
Influent
PE
SE (pre-chlor)
Final Effluent
Influent
PE
SE (pre-chlor)
Final Effluent
Influent
PE
SE (pre-chlor)
Final Effluent
Date
7/17/06
8/14/06
7/17/06
8/14/06
7/17/06
8/14/06
7/17/06
8/14/06
8/14/06
8/14/06
8/14/06
8/14/06
8/23/06
4/24/07
4/24/07
8/23/06
4/24/07
8/23/06
4/24/07
Fecal Conform
mpn/100ml
>24,000,000
>24,000,000
11,000,000
1 ,500,000
>24,000,000
>24,000,000
2,300
15,000
150,000
390
1,200
1,500
2,400,000
4,600,000
11,000,000
11,000,000
11,000,000
2,400,000
460,000
1,100,000
150,000
<3
93
15
2,400,000
2,400,000
4,600,000
>24,000,000
11,000,000
4,600,000
2,400,000
11,000,000
430,000
93,000
23,000
23,000
<3000
4,000
23,000
4
15
15
230
150
30
Entero
mpn/100ml
130,000
540,000
1 ,500,000
2,400,000
600,000
430,000
2,300
9,300
15,000
4
93
23
430,000
27,000
930,000
280,000
430,000
930,000
230,000
230,000
430,000
<3
<3
<3
750,000
750,000
930,000
>24,000,000
930,000
2,400,000
930,000
2,100,000
2,400,000
15,000
4,300
2,300
<3000
9,000
93,000
<3
<3
<3
4,300
2,100
9,300
Giardia
cysts/ L
<0.4
27.2
1.6
<0.33
24.9
3
9.1
20.7
12
6.4
356
618
276
536
446
5.7
6.2
2.3
2.8
2.3
3.5
Crypto
oocysts/ L
<0.4
1.4
<0.4
<0.33
5.4
<0.09
3.8
7.5
1.4
1.1
<1.0
4
<1.0
4
<1.0
0.7
1.1
0.7
2.0
1.9
3.6
MPN/L
Infectious
Crypto
<1.0
<0.9
<1.0
<0.9
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
<2.4
<2.4
<2.4
<2.4
<2.4
<0.2
<0.2
<0.2
<0.2
<0.2
<0.2
BQM
Infectious
Units/L
1,156
786
582
356
7
7
4
1
1
3
477
334
667
211
11
6
6
3
6
6
Virus
Detected
EV
EV
EV
EV
REO, EV
EV
EV
MA-104
Infectious
Units/L
713
233
970
356
11
6
6
5
1
1
478
771
578
564
14
8
5
8
14
5
Virus
Detected
EV,REO,RV
EV.REO.RV
EV,REO
REO
EV, REO
EV,REO
REO
REO
PLC/PRF/5
Infectious
Units/L
788
154
484
418
13
7
4
5
3
2
412
671
823
679
7
4
7
4
4
5
Virus
Detected
EV, AdV
EV
EV, AdV
EV, AdV
EV, AdV
CaCo-2 cells
Infectious
Units/L
7,880
2,412
13,920
2,200
3
3
1
<1
1
1
197
145
912
1,970
39
24
39
<3
<3
8
Virus
Detected
EV
EV
-
EV
EV
-
Famp
bacteriophage
/ml
832
600
712
425
52
61
47.2
52.8
62.4
56.8
400
480
680
360
42
26.4
22.8
3.2
4.8
5.6
C3000
bacteriophage /
ml
936
1344
888
800
95.2
72.8
89.6
56
32.4
52.8
680
720
840
560
108.8
105.6
113.6
2.8
8
6.4
No Protozoa, V rus and Coliphage samples were collected at Plant 3 as per scope of work requirements
BOD
(composite)
mg/l
185.9
90
15.1
111.8
45.9
13.2
123.6
141.4
70.4
2
15.6
TSS
(composite)
mg/l
105.4
72.3
11.85
150
42.5
1.9
110.5
108
58.7
1.02
14.4
Residual
Chlorine
mg/l
0.55
0.45
0.26
0.32
0.46
0.46
0.74
0.8
0.52
1.81
0.38
0.28
0.59
0.64
0.53
PE - Primary effluent
EV = Enterovirus
SE (pre-chlor) - Secondary effluent prior to chlorination
AdV = Adenovirus RV = Rotovirus
Av = Astrovirus
REO = Reovirus
47
-------
Plant
Operating
Mode
Wet
Plant
Plant 1
Location
Influent
PE
SE (pre-chlor)
Effluent
Date
9/14/06
10/20/06
11/8/06
3/2/07
4/27/07
9/14/06
10/20/06
11/8/06
3/2/07
4/27/07
9/14/06
10/20/06
11/8/06
3/2/07
4/27/07
9/14/06
10/20/06
11/8/06
3/2/07
4/27/07
Fecal Coliform
mpn/100 ml
4,600,000
4,600,000
4,600,000
4,600,000
2,400,000
11,000,000
>24,000,000
>24, 000,000
11,000,000
4,600,000
1,200,000
930,000
1,500,000
930,000
4,600,000
11,000,000
11,000,000
>24,000,000
1,500,000
930,000
230,000
4,600,000
4,600,000
2,400,000
430,000
930,000
430,000
2,400,000
2,400,000
930,000
1,100,000
>2,400,000
>2,400,000
930,000
390,000
930,000
2,400,000
930,000
2,400,000
930,000
150,000
230,000
2,400,000
2,400,000
2,400,000
930
>24,000
>24,000
1,500
4,300
930
>240,000
930
930
930
1,500
24,000
9,300
15,000
7,500
Entero
mpn/100 ml
390,000
11,000,000
4,600,000
430,000
430,000
4,600,000
2,100,000
640,000
2,400,000
93,000
150,000
2,400,000
230,000
430,000
930,000
2,400,000
2,400,000
930,000
230,000
230,000
150,000
230,000
930,000
930,000
390,000
210,000
230,000
430,000
2,400,000
2,400,000
150,000
240,000
240,000
23,000
43,000
43,000
43,000
93,000
230,000
93,000
930,000
430,000
430,000
430,000
11,000
>24,000
>24,000
9,300
>240,000
2,000
>240,000
46,000
24,000
230
24,000
9,300
5,500
24,000
46,000
6/airf/a
cysts/ L
820
1,200
880
790
1,100
4,300
1600
760
398
2,200
320
100
30
61
70
80
220
170
250
64
56
58
320
270
220
41
40
60
690
720
590
Crypto
oocysts/ L
280
20
24
1,000
100
<1.0
<1.0
12
462
30
14
30
22
63
66
78
<0.2
<0.2
<0.2
36
42
34
8
2
8
43
46
52
<0.2
2
<0.2
MPN/L
Infectious
Crypto
<9.2
<9.2
9.2(1.3-68)
18.4(2.5-136)
<2.4
<2.4
<2.4
<9.2
<9.2
<2.4
<9.2
<9.2
9.2(1.3-68)
<1.8
1.8(0.3-13.6)
<1.8
<0.48
<0.48
<0.48
0.3(0.04-2.1)
<0.3
<0.3
<9.2
<9.2
<9.2
<1.8
<1.8
1.8(0.3-13.6)
<0.48
<0.48
<0.48
BQM
Infectious
Units/L
2,111
1,279
2,111
572
914
914
92
738
222
2,111
775
143
59
68
115
40
35
57
2
4
<1.9
76
143
55
6
5
18
4
5
3
Virus
Detected
EV
EV, REO
EV, REO
EV, REO
EV
EV, REO
EV
EV
EV
EV, REO
EV
MA-104
Infectious
Units/L
1,741
1,279
792
914
5,425
1,520
143
54
4,069
759
412
429
48
151
216
236
44
205
2
102
2
58
393
18
19
20
40
2
<1.8
3
Virus
Detected
EV, RV
EV, RV
EV, REO,RV
EV, RV
EV, REO
EV, REO
REO
EV, REO
REO
REO
REO
-
PLC/PRF/5
Infectious
Units/L
1,213
435
870
1,677
6,606
1,677
110
114
686
257
1,677
1,424
12
8
23
66
22
57
23
51
98
15
9
20
19
20
32
25
23
10
Virus
Detected
EV, AdV
EV, AdV
EV, AdV
EV, AdV
EV, AdV
AdV
AdV
AdV
AdV
AdV
AdV
AdV
CaCo-2 cells
Infectious
Units/L
603
985
1,741
254
254
108
297
1,424
54
2,870
108
186
8
3
5
72
127
36
19
24
6
2
1
1
19
21
34
2
2
1
Virus
Detected
EV
EV
EV
EV
EV
EV
EV
-
EV
-
-
Famp
bacteriophage
/ml
500
340
180
320
500
220
160
110
130
400
360
130
6.5
5.7
6.7
10.4
11.4
12.5
5.8
5.4
1.7
1.6
2.8
1
1.8
2.5
3.9
3.6
2.7
4.8
C3000
bacteriophage /
ml
620
420
220
600
760
500
ND*
ND*
ND*
580
560
ND*
0.4
0.6
0.91
15
16.1
14.71
ND*
ND*
ND*
2.2
4.2
1.5
2.5
3.1
7
ND*
ND*
ND*
BOD
(composite)
mg/l
159.4
186
68
35.4
72.4
138.2
76
72
33.9
55
-
-
-
37
19
17
9.5
35.1
TSS
(composite)
mg/l
159.6
137
65
57.2
74
89.6
73.7
43
58.4
74.6
-
-
-
33.3
21.8
30
25.9
31.8
Residual
Chlorine
mg/l
0.03
0.03
0.04
0.26
0.16
0.13
0.49
0.64
0.61
1.18
1.43
1.33
0.3
0.94
1.05
0.5
0.7
0.57
PE - Primary effluent SE (pre-chlor) - Secondary effluent prior to chlorination
EV = Enterovirus AdV = Adenovirus RV = Rotovirus
*ND - Not done due to the high background concentration of indigenous bacteria
REO = Reovirus
48
-------
Plant
Operating
Mode
Wet
Plant
Plant 2
Location
Influent
PE
SE (pre-chlor)
Effluent
Date
1 1/8/06
1/8/07
4/12/07
7/18/07
1 1/8/06
1/8/07
4/12/07
7/18/07
11/8/06
1/8/07
4/12/07
7/18/07
1 1/8/06
1/8/07
4/12/07
7/18/07
Fecal Conform
mpn/100 ml
430,000
430,000
2,400,000
2,400,000
4,600,000
2,400,000
1 ,500,000
430,000
1,500,000
230,000
2,400,000
930,000
430,000
930,000
2,400,000
2,400,000
11,000,000
2,100,000
930,000
430,000
430,000
430,000
430,000
750,000
930,000
930,000
430,000
430,000
230,000
>240,000
>240,000
>240,000
2,300
90
46,000
4,300
1,500
>240,000
24,000
Entero
mpn/100 ml
120,000
230,000
210,000
930,000
430,000
230,000
430,000
430,000
93,000
150,000
430,000
430,000
230,000
750,000
1 ,200,000
4,600,000
930,000
430,000
210,000
430,000
75,000
430,000
43,000
93,000
43,000
23,000
43,000
93,000
93,000
46,000
24,000
24,000
4,300
930
15,000
>240,000
930
9,300
110,000
Giardia
cysts/ L
30
150
140
2,200
890
60
70
90
<1.0
20
3
3
52
<0.2
42
16
40
8
7
210
580
710
720
40
Crypto
oocysts/ L
<1.0
<1.0
<1.0
40
<1.0
<1.0
<1.0
<1.0
10
<1.0
3
1
<0.2
<0.2
<0.2
<0.2
<0.2
2
1
<0.2
<0.2
<0.2
<0.2
<0.2
MPN/L
Infectious
Crypto
<2.4
<2.4
<2.4
<2.4
<2.4
<2.4
<2.4
<2.4
<2.4
<2.4
<2.4
<2.4
<0.5
<0.5
<0.5
<0.5
<0.5
<2.4
<2.4
<0.5
<0.5
<0.5
<0.5
<0.5
BQM
Infectious
Units/L
297
914
4,068
54
429
1,520
5,420
190
686
914
48
52
7
3
<2
43
10
25
6
2
<2
<1
14
13
Virus
Detected
EV, REO
EV, REO
EV, REO
EV
EV, REO
EV, REO
EV
EV, REO
EV
EV
EV
MA-104
Infectious
Units/L
190
914
4,068
110
222
1,520
5,420
190
2,847
914
48
32
7
6
3
17
5
5
6
<2
<2
<1
12
4
Virus
Detected
EV,RV,
REO
EV, RV,
REO
EV, RV,
REO
EV, RV
EV, RV
EV, RV,
REO
RV, REO
RV
REO
RV, REO
....
REO
PLC/PRF/5
Infectious
Units/L
72
914
6,576
581
7,398
914
1,898
225
1,140
3,800
15
32
21
17
54
69
44
16
8
6
6
<1
104
41
Virus
Detected
EV, AdV
EV, AdV
'
AdV
'
CaCo-2 cells
Infectious
Units/L
216
229
1,140
309
1,101
360
220
190
2,847
810
29
27
26
4
7
14
9
21
4
<2
<2
<1
9
9
Virus
Detected
EV
EV
EV
EV
EV
EV
EV
EV
Famp
bacteriophage
/ml
200
370
100
120
90
244
188
220
130
258
11.1
3.4
5.7
5.7
7.4
16.5
32.4
6.9
1.7
4.7
6.4
2.2
9.6
12.2
C3000
bacteriophage /
ml
400
580
ND*
ND*
230
ND*
15.9
5.1
ND*
ND*
1.4
3.4
ND*
ND*
BOD
(composite)
mg/l
58
53
152.8
201
60
44
86
165
....
9
21
28.4
30
TSS
(composite)
mg/l
136
67
368.3
132.8
61
50
140
105.1
....
23
13
26.25
17.2
Residual
Chlorine
mg/l
0.19
0.26
0.46
0.48
0.87
0.3
0.52
0.65
0.52
0.71
PE - Primary effluent SE (pre-chlor) - Secondary effluent prior to chlorination
EV = Enterovirus AdV = Adenovirus RV = Rotovirus
*ND - Not done due to the high background concentration of indigenous bacteria
Av = Astrovirus
REO = Reovirus
49
-------
Plant
Operating
Mode
Wet
WWPT
3
Location
Influent
PE
SE (pre-chlor)
Effluent
Date
11/8/06
1/8/07
3/2/07
4/4/07
11/8/06
1/8/07
3/2/07
4/4/07
11/8/06
1/8/07
3/2/07
4/4/07
11/8/06
1/8/07
3/2/07
4/4/07
Fecal Coliform
mpn/100 ml
430.000
2.100.000
>24,000,000
4.600.000
2.400.000
2,400,000
430.000
43.000
>24,000,000
2.400.000
930.000
430,000
>24.000.000
2.500.000
2,400,000
23.000
4.600.000
1 1 ,000,000
2.400.000
430.000
930,000
1 .500.000
2.400.000
930,000
7.000
19.000
4,000
23.000
9.000
<3000
<3000
<3000
58,000
23.000
930.000
23,000
930
2.300
4,300
<30
90
40
230
930
4,300
210
210
9,300
Entero
mpn/100 ml
1 .200.000
230.000
230,000
230.000
930.000
930,000
430.000
93.000
93,000
430.000
150.000
93,000
230.000
230.000
2,400,000
23.000
750.000
4,600,000
93.000
93.000
430,000
230.000
930.000
230,000
<3000
<3000
<3000
150.000
<3000
<3000
<3000
<3000
<3000
210.000
93.000
230,000
2.300
430
210
230
90
430
340
930
340
46,000
430
46,000
BOD
(composite
)mg/l
76
40
65
92.4
225
137.6
99.7
141.2
....
....
....
40
32
46
31.1
TSS
(composite)
mg/l
83
41.6
76.2
69.6
212
138.9
212.2
26.1
-
-
-
59
52.7
66.1
45.9
Residual
Chlorine mg/l
0.5
0.62
1
0.75
1.2
0.85
1.39
1.19
1.3
1.08
1.12
1.22
PE - Primary effluent
SE (pre-chlor) - Secondary effluent prior to chlorination
50
-------
Appendix B
Maceration Results
51
-------
Location
Final Effluent
Plant
Operating
Mode
Dry
Wet
Flint
Plant 1
Plant 2
Plants
Plant 1
Plant 2
Plant 3
Data
7/17/06
8/14/06
8/23/06
4/23/07
9/14/06
11/8/06
3/2/07
4/27/07
11/8/06
1/8/07
4/12/07
7/18/07
11/8/06
1/8/07
3/2/07
4/4/07
Fecal Coliform
Macerated
mpn 100 ml
2,400
4,600
1 1 ,000
15
93
4
90
230
1 1 ,000
>24,000
>24,000
4,300
7,500
9,300
9,300
24,000
4,300
>240,000
24,000
40
110,000
9,300
>240,000
>240,000
24,000
9,300
430
430
230
2,300
2,800
930
Uninacerated
mpn 100 ml
390
1,200
1,500
<3
15
4
230
150
930
>24,000
>24,000
>240,000
930
930
1 ,500
9,300
1 ,500
>240,000
>240,000
90
4,300
1,500
>240,000
24,000
2,300
4,300
90
40
230
930
210
210
ErrteracQccus
Macerated
mpn 100 ml
230
430
430
<3
9
<3
4,300
9,300
>24,000
>24,000
>24,000
24,000
24,000
9,300
2,500
110,000
46,000
110,000
9,300
430
24,000
4,300
15,000
5,000
750
230
2,300
430
12,000
1 ,500
46,000
230
Unmacerated
mpn 100 ml
4
93
23
<3
<3
<3
4,300
2,100
1 1 ,000
>24,000
>24,000
>240,000
46,000
230
24,000
5,500
24,000
24,000
24,000
930
>240,000
930
9,300
110,000
430
210
90
430
340
930
46,000
430
52
-------
Appendix C
Flow and
Estimated Chlorine Contact Time Data
53
-------
FLOW RATE DATA
Wet-Weather Blending Runs
Date
9/14/2006
10/20/2006
11/8/2006
3/2/2007
4/27/2007
11/8/2006
1/8/2007
4/12/2007
7/1 8/07
WWTP
1
1
1
1
1
2
2
2
2
LOCATION
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
TIME
8:05
8:50
9:35
9:30
10:15
11:00
10:15
11:03
11:48
7:55
8:40
9:25
8:00
8:45
9:32
10:15
11:00
11:45
8:55
9:40
ND
7:55
8:40
9:25
7:50
8:35
WWTP INFLUENT
(MGD)
199
248
249
248
242
171
247
245
245
249
248
248
248
248
249
123
127.2
127.8
124
90
ND
137.4
136
137
124
121
SECONDARY INFLUENT
181
181
182
183
182
172
200
200
200
191
188
188
194
189
178
.
.
.
BYPASSED FLOW
18
67
67
65
60
47
45
45
58
60
60
54
59
71
.
.
.
BYPASSED
(%)
9
27
27
26
25
19
18
18
23
24
24
22
24
29
.
.
.
Estimated Chlorine
Contact
Time (min)
17.9
14.4
14.3
14.4
14.7
20.8
14.4
14.5
14.5
14.3
14.4
14.4
14.4
14.4
14.3
.
.
.
54
-------
FLOW RATE DATA Cont'd
Wet-Weather Blending Runs
Date
11/8/2006
1/8/2007
3/2/2007
4/4/2007
WWTP
3
3
3
3
LOCATION
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
TIME
11:25
12:05
12:50
9:10
9:50
10:35
7:45
8:30
9:15
13:50
14:34
15:20
WWTP INFLUENT (MGD)
566
574
580
459
400
401
406
419
500
439
436
445
SECONDARY INFLUENT
.
.
.
.
.
BYPASSED FLOW
.
.
.
.
.
BYPASSED
(%)
Estimated
Chlorine
Contact
Time (min)
.
.
.
.
.
55
-------
Dry-Weather Blending Runs
Date
7/17/2006
8/14/06
8/14/2006
8/23/2006
4/24/2007
WWTP
1
1
2
3
3
LOCATION
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
SP1-1
SP1-2
SP1-3
TIME
9:30
10:15
11:00
8:30
9:15
10:00
8:30
9:15
10:00
9:08
9:55
10:40
9:15
10:00
10:45
WWTP INFLUENT (MGD)
138
128
130
111
112
113
29.9
30.9
33.1
216-
236
234
262
250
233
SECONDARY
INFLUENT
.
.
BYPASSED FLOW
.
.
BYPASSED(%)
.
.
Estimated Chlorine
Contact
Time (min)
25.8
27.8
27.4
32.1
31.8
31.5
-
-
-
-
-
-
-
-
-
56
-------
Appendix D
Maceration Optimization Analyses
57
-------
Charts for Maceration Optimization Analyses
WWTP 1 - Dry Run - July 17, 2006
Fecal Coliform at 0 minutes
ฐ nnn
o,uuu
2 Cnn
,OUU
E *~^ nnn
o
Hi C ^^
o_ 1 nnn
ฃ I ,UUU
n;nn
z
/
,
^^^ ^^^*^^
^^^ ^\,
* 1 1 1
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
* 30 second
60 second
90 sec
Fecal Coliform at 45 minutes
>A nnn
oU,UUU
oc nnn
zo,uuu
Eon nnn
zu,uuu
o
o -< c nnn -
ID.UUU
a -in nnn
1 U,UUU
c nnn -
v?,UUU
A
/
ITZ \
^>-
I i 1
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
30 sec
--60 sec
90 sec
58
-------
WWTP 1 - Dry Run - July 17, 2006
Fecal Coliform at 90 minutes
i o nnn
I Z.UUU
1 n nnn -
I U,UUU
E O AAA
o.uuu
o
o c nnn
T D,UUU
g
a A nnn
ฃ '
A /"
/ \ Z
/ \ /
/ . X
3,500 7,000 14,500 22,000
Speed of Blender {rpm)
* 30 sec
60 sec
90 sec
Enterococcus at 0 minutes
-ปCA
iOU
->nn
=iUU
_. 1 en
O I DU
0
T"
"a i nn
I I.M.I
0.
ฃ 50
ou
-
/
/
/
/
ป*
3.500 7,000 14.500 22,000
Speed of Blender (rpm)
* 30 sec
60 sec
90 sec
59
-------
WWTP 1 - Dry Run - July 17, 2006
Enterococcus at 45 minutes
500
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
Enterococcus at 90 minutes
3000
2500
I 2000
o
? 1500
11000
500
0
30 sec
60 sec
90 sec
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
60
-------
WWTP 1 - Geometric Means for Dry Run on July 17, 2006
6nnn
,uuu
5nnn
,uuu
P A nnn
= 4,UUU
o
* ^ f\f\f\
^ u,UUU
o. 9 nnn
~ z,uuu
1 nnn
I ,UUU
Fecal Coliform - Geometric Mean
~"
jT
/
,
'^~'~~~f~ ~^~~ ~^~^~
4- """" / ~* ' - ^
m- ^^"
i i i
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
* 30 sec
60 sec
yu sec
^nn
j\j\j
AC\(\
*+uu
,_ onn
O oUU
o
T-
"c onn
^ zuu
Q.
c
"" "i nn
IUU
EnTerococcus - Geometric Mean
y*
/
- -"* ^
m^^^,
v ^
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
* 30 sec
-60 sec
90 sec
61
-------
WWTP 1 - Wet Run - September 14, 2006
Fecal Coliform atO minutes
in nnn
oU,UUU
oc nnn
Z.D.UUU
E"?r\ nnn
j^U,UUU
o
o A c nnn
,- ID,UUU
CL 1 n nnn
S- I U,UUU
c nnn
o,uuu
A
/ \
/ \.
/ _^\
. -r^"*"""" *- * "
J^-^^ mr-^
i i i
3.500 7,000 14.500 22.000
Speed of Blender (rpm)
30 sec
--60 sec
90 sec
E
e
*c
I
Fecal Coliform at 45 minutes
TI nnn
ou.uuu
oc nnn
zo.uuu
on nnn
jiU.UUU
-i c nnn
lo,Uuu
H n nnn
1 U.UUU
5 nnn
,uuu
r " " M
i i i
3.500 7,000 14,500 22.000
Speed of Blender {rpm)
* 30 sec
60 sec
90 sec
62
-------
WWTP 1 - Wet Run - September 14, 2006
Fecal Coliform at 90 minutes
ฐn nnn
ou.uuu
25 000
E~~ on nnn
zu,uuu
0
o -\ r nnn
T I D.UUU
a-i n nnn
1 U.UUU
5 nnn
,uuu
0,
n
\ / /
\ / /
A /
\ / \ /
^v
i i i
3,500 7,000 14.500 22,000
Speed of Blender (rpm)
30 sec
60 sec
90 sec
Entemcoccus at 0 minutes
ฐn nnn
ou,uuu
oc nnn -
ZvJ.vvU
Eon nnn
zu,uuu
o
| 15,000 -
a-\ n nnn
I U,UUU
5 nnn
,uuu
i
r.
\
\
\ ^^
\ ~-^*
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
30 sec
60 sec
90 sec
63
-------
WWTP 1 - Wet Run - September 14, 2006
Enterococcus at 45 minutes
^n nrifi -i
ou.uuu
25.000 -
ฃ~~ on nnn
Z\J,\J\J\J
o
One nnn
^- 1 D.UUU
o 1 n nnn
O. IU,vUU
5 nnn
,uuu
T
\ n /
\ /
\ /
\ /
V
I I I
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
* 30 sec
60 sec
90 sec
Enterococcus at 90 minutes
on nnn -,
OU.UUU
<-)c nnn
ZD.UUU ~
I 20,000 -
0
o -f c nnn
, ID.UUU
Q.1 0,000 -
5 nnn -
,uuu
^
r n r n
3,500 7,000 14,500 22.000
Speed of Blender {rpm)
30 sec
-60 sec
90 sec
64
-------
WWTP 1 - Geometric Means for Wet Run on September 14, 2006
on nnn
ou,uuu
oc nnn
ZD.UUU
Eon nnn
zu.uuu
o
o -\ c nnn
r- ID,UUU
a-i r\ nnn
I U.UUU
ฃ
5 nnn -
,uuu
Fecal Coliform - Geometric Mean
yv
/ \.
/ x^
m / /' ^
""^^"^T1^-^ ^
m^ ^^^^^f
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
30 sec
t>u sec
90 sec
Enterococcus - Geometric Mean
on nnn -,
ou,uuu
on nnn
ZO,UUU
Eon nnn
i-U.UUU
o -i c nnn
-^ 1 3, UwU
5 m nnn
" 1 U,UUU
^ nnn
3,VJUU
M ปT
\
\ /*
x. Z
^^v^
3,500 7,000 14,500 22,000
Speed of Blender (rpm)
ซ 30 sec
60 sec
90 sec
65
-------
Appendix E
Analytical Methods Used for
Infectious Cryptosporidium and Virus
Analyses
66
-------
Summary of Methods used by Biological Consulting Services Laboratories
for
Infectious Cryptosporidium and Virus Analyses
Cryptosporidium viability assay.
Concentrates from the IMS procedure were delivered to BCS Laboratories in Miami, Florida,
following sample collection and analysis of samples by EPA Method 1623 by the EPA contract
laboratory. Concentrates were analyzed for infectious Cryptosporidium as described by Slifko et
al. (1997, 1999). Briefly, IMS concentrates (50 jil) were pretreated (8 min at room temperature)
with a 10.5% (vol/vol) sodium hypochlorite (Sigma-Aldrich, St. Louis, Mo.) solution in
Phosphate Buffered Saline (pH 7.2) to enhance excystation. The samples were washed once by
centrifugation and were suspended in 1 ml cell culture medium supplemented with 10% fetal
bovine serum and other additives (2% 1 M HEPES and 2 mM L-glutamine). Aliquots of this
suspension were inoculated onto human ileocecal adenocarcinoma cell (HCT-8) monolayers
cultivated in eight-well chamber slides (LabTech II; Nalgene Nunc, Naperville, 111.). Slides
were incubated in a 5% CO2 atmosphere at 37ฐC for 72 h. After incubation, slides were fixed
with 100% methanol for 8 min and labeled by direct immunofluorescence with rat anti-C.parvum
sporozoite-FITC (Waterborne Inc.) Slides were examined under epifluorescence and DIG
microscopy, and each well was scored as positive or negative for infection. The results were
entered into a most probable number (MPN) program and results were expressed as the number
of infectious oocysts per 100 liters on the basis of the equivalent volume examined.
Cryptosporidium genotyping.
Positive slides were marked with a permanent marker, and DNA was extracted directly from the
slides following microscopic analysis. Cover slips were removed with a razor blade and cell
monolayers were scraped with a sterile scalpel and resuspended in 50 jil of molecular-grade
water. DNA was purified using a Qiagen DNA extraction kit (Qiagen, Inc.). Molecular
characterization of Cryptosporidium species and genotypes were determined using a nested
PCR-restriction fragment length polymorphism assay of the 18S small-subunit rRNA gene
fragment (Xiao et al., 1999, 2000). For restriction fragment analysis, 20 jil of the secondary PCR
product was digested in a 25 -jil (total volume) reaction mixture containing 20 U of Sspl (New
England BioLabs, Beverly, Mass.) for species diagnosis or 20 U of Vspl (MBI Fermentas Inc.,
Hanover, Md.) for genotyping of C. parvum. Digested products were fractioned on a 2.0%
agarose gel and visualized by ethidium bromide staining. The patterns of DNA bands were used
to differentiate the species and genotypes of Cryptosporidium parasites according to
methodology described by Xiao et al. (1998, 1999).
Enteric virus assay.
1MDS virus filters were shipped to BCS Laboratories, Inc. in Gainesville, Florida, and were
processed immediately upon receipt. Filters were eluted with 1 L of 3% BBL V beef
extract/Glycine (pH 9.2, 25ฐC), concentrated by organic flocculation, and assayed for viable
enteric viruses by the observation of cytopathic effects (CPE) on recently passed (<4 days)
Buffalo Green Monkey (BGM), Rhabdosarcoma (RD), and MA-104 cells. Positive controls
were performed in a designated area using Poliovirus I. The most probable number (MPN)
67
-------
determinations were calculated using EPA software. To increase sensitivity, samples were split
for assay by cytopathology and ICC/PCR. Cell extracts were then pooled for PCR analysis.
Integrated Cell Culture PCR (ICC-PCR).
An integrated cell culture RTPCR method was used to detect viruses that do not cause cytopathic
effects (CPE) in cell culture. Non-CPE viruses (e.g Noroviruses) can be present in treated waters
and many viral pathogens can infect cell cultures without causing CPE. These viruses can
subsequently be detected by PCR or RT-PCR. RT-PCR was performed on all viruses with the
exception of Adenoviruses (DNA genome) for which standard PCR analysis were performed
(Grimm et al., 2004; Oberste et al., 2006; Reynolds, 2004; Spinner and DiGiovanni, 2001; van
Heerden et al., 2005).
Coliphage analyses.
Somatic and male-specific coliphages were analyzed by two methods: a modified version of the
agar overlay method (EPA Method 1602) using E. coli (host strain F+amp for male-specific and
host strain C3000 ATCC 15597 for both male-specific and somatic) and a version of the large
volume (1L) presence/absence assay of (EPA Method 1601) for treated effluent.
Bacteriophages were enumerated as plaque forming units (PFU) per 100 mL or by MPN using
the presence/absence assay.
68
------- |