Impact of Wet-Weather Peak Flow

Blending on Disinfection and Treatment: 

A Case Study at Three Wastewater 

Treatment Plants

Office of Research and Development

National Risk Management Research Laboratory - Water Supply and Water Resources Division

EPA/600/R-10/003 | March 2010 | www.epa.gov /nrmrl
 

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 10036 

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 
 

 

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. 

ii 
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 

iii 
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 

(IEC) 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% of Giardia. 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/l (a monthly average permit limit for both 

parameters) at two out of three WWTPs; the third WWTP, that had results above 30 mg/l 

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 WaringTM 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 
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. 

v 
 

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 Project 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 
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 BOD5 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. Detection 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 

vii 
Glossary of Terms and Acronyms 

AdV Adenovirus 

BGM Buffalo Green Monkey cell line 

BCS Biological Consulting Services 

BOD5 Five-Day Biochemical Oxygen Demand 

CaCo-2 Human intestinal cell line 

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. 

CBOD5 Five-Day Carbonaceous Biochemical Oxygen Demand 

DESA Division of Environmental Science and Assessment 

EPA Environmental Protection Agency 

EV Enterovirus 

h Hours 

HAV Hepatitis A Virus 

IEC Interstate Environmental Commission 

MA104 Cell line derived from Rhesus monkey kidney 

mg/l Milligram per Liter 

MGD Million Gallon per Day 

min Minutes 

MPN Most Probable Number 

ND Non-detect 

NPDES National Pollutant Discharge Elimination System 

NYC New York City 

NYC DEP New York City Department of Environmental Protection 

NYS DEC New York State Department of Environmental Conservation 

ORD Office of Research and Development 

PLC/PRF/5 Human hepatoma cell line 

REO Reovirus 

rpm Revolutions Per Minute 

RV Rotavirus 

s Seconds 

SP Sampling point 

TRC Total Residual Chlorine 

TSS Total Suspended Solids 

WWTP Wastewater Treatment Plant 

viii 
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 
 

 

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 (IEC) 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 
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 

2
 
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. 

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 

3
 
 

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 95o 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 BOD5 

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? 

4
 
 

 

 

Question #4: For the three WWTPs studied, was there evidence for the removal of viruses 

(Adenovirus, Astrovirus, Enterovirus, Rotavirus, Reovirus, Norovirus, Hepatitis A and malespecific 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 Enterococcus? 

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 CBOD5 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. 

5
 
Table 1 - CBOD5, BOD5, and TSS Effluent Limitations for NYC DEP WWTPs 

Parameter Type Limitation 

(mg/l) 

Required by 

CBOD5 Monthly Average 25 NYS DEC 

CBOD5 7-day arithmetic average 40 NYS DEC 

BOD5 Monthly/30-day Average 30 IEC* 

BOD5 7-day arithmetic average 45 IEC* 

BOD5 6 consecutive hour 

average 

50 IEC 

TSS Monthly/30-day Average 30 NYS DEC/IEC 

TSS 7-day arithmetic average 45 NYS DEC and IEC 

TSS Daily Maximum** 50 NYS DEC 

TSS 6 consecutive hour 

average 

50 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/l shall 

neither apply for the day of measured flow nor for the succeeding day. 

6
 
 

 

 

Chapter 2. Project Summary 

The summary of all completed sampling events is presented in Table 2. 

Table 2 - Sampling Events: Completed / Planned 

WWTP Permit Flow 2 Dry-Weather 

Events 

Wet-Weather 

Blending Events 

1 120 MGD 1/1 4/4 

2 60 MGD 1/1 4/4 

3 275 MGD 2/1 4/4 

Total: 4/3 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 Bacteria Macerated 

Effluent 

Samples 

Giardia Crypto Infectious 

Crypto 

Virus 

1 3/3 3/2 3/3 3/3 3/3 3/3 

2 3/3 2/2 3/3 3/3 3/3 3/3 

3 6/3 3/2 --- --- --- ---

Total: 12/9 8/6 6/6 6/6 6/6 6/6 

Table 4 - Wet-Weather Effluent Samples: Collected / Planned 

WWTP Bacteria Macerated 

Effluent 

Samples 

Giardia Crypto Infectious 

Crypto 

Virus 

1 15/12 9/8 12/9 12/9 12/9 9/9 

2 10/12 8/8 7/9 7/9 7/9 7/9 

3 12/12 8/8 --- --- --- ---

Total: 37/36 25/24 19/18 19/18 19/18 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. 

7 
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 

IEC’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. 

8
 
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, IEC 

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 

1.5 x Permit Flow Rate 

Primary 

Tanks 

Aeration 

Tanks 

Secondary

Tanks 

Chlorine 

Contact Tanks 

SP 1 SP 3 SP 4

Bypass Around Secondary Treatment (up to 0.5 x Permit Flow Rate) 

During wet weather 

Grit 

Chambers 

Bar 

Screens SP 2 

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 

9
 
 

 

 

 

 

 

 

 

 

 

 

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 

WWTP 1 WWTP 2 WWTP 3 

Bacteria WWTP 

Macer-d 

Effluent 

Samples 

Protozoa/ 

Virus 

Bacteria WWTP 

Macer-d 

Effluent 

Samples 

Protozoa/ 

Virus 

Bacteria Macer-d 

Effluent 

Samples 

Protozoa/ 

Virus 

Wet 1 X X + O X --

Wet 2 X X X X X --

Wet 3 X X X X X X X --

Wet 4 X X X X X --

Wet 5 X X X X X --

Wet 6 X X X X X --

Dry 1 X X + O X --

Dry 2 X X X X 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. 

3

 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. 

4

 TBD 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 3,500 rpm 7,000 rpm 14,500 rpm 22,000 rpm 

30 s 3 3 3 3 

60 s 3 3 3 3 

90 s 3 3 3 3 

Total Macerated Analyses: 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 parameters—speed of 22,000 rpm and time of 

60 s—were 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/l 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 IEC'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, IEC’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 WWTP 1 WWTP 2 WWTP 3 

TSS (mg/l) 

Removal 

(%) TSS (mg/l) 

Removal 

(% ) TSS (mg/l) 

Removal 

(% ) 

May 2006 14 94 6 96 8 94 

Jun 2006 16 95 5 97 8 95 

Jul 2006 14 94 4 97 7 94 

Aug 2006 11 96 4 97 6 94 

Sep 2006 18 93 4 98 9 94 

Oct 2006 16 93 4 97 7 94 

Nov 2006 17 92 6 96 10 93 

Dec 2006 13 94 4 97 11 90 

Jan 2007 10 94 4 97 13 88 

Feb 2007 9 95 5 97 18 83 

Mar 2007 9 95 7 96 14 86 

Apr 2007 15 92 6 97 16 89 

AVERAGE 14 94 5 97 11 91 

Table 8. Average Monthly Effluent CBOD5 and % Removal 

Month/ 

Year WWTP 1 WWTP 2 WWTP 3 

CBOD5 

(mg/l) 

Removal 

(% ) 

CBOD5 

(mg/l) 

Removal 

(% ) 

CBOD5 

(mg/l) 

Removal 

(% ) 

May 2006 9 95 5 96 5 96 

Jun 2006 8 96 5 96 6 95 

Jul 2006 12 93 5 96 5 95 

Aug 2006 9 96 6 96 5 95 

Sep 2006 14 93 5 96 5 96 

Oct 2006 13 94 15 89 5 96 

Nov 2006 15 92 5 95 6 96 

Dec 2006 12 94 5 95 7 93 

Jan 2007 8 96 5 95 8 92 

Feb 2007 7 96 5 95 11 89 

Mar 2007 8 95 6 <95 7 92 

Apr 2007 12 <93 5 <96 9 92 

AVERAGE 11 94 6 95 7 94 

14
 
 

 

 

 

Table 9. 30-Day Geometric Mean Monthly Effluent Fecal Coliform Values 8

 (MPN/per 100 ml) 

Month/Year WWTP 1 WWTP 2 WWTP 3 

Geom. 

Mean 

Highest 

Daily Value 

(during 

monthly 

period) 

Geom. 

Mean 

Highest Daily 

Value (30-Day 

Period) 

Geom. 

Mean 

Highest Daily 

Value (30-Day 

Period) 

May 2006 25 246 4 540 27 640 

Jun 2006 52 224 6 800 21 440 

Jul 2006 89 480 4 4000 27 4000 

Aug 2006 52 544 4 1000 6 600 

Sep 2006 133 1200 4 400 9 300 

Oct 2006 112 4000 6 400 19 260 

Nov 2006 42 800 63 4000 27 278 

Dec 2006 30 240 11 4000 85 680 

Jan 2007 27 355 20 4000 85 4000 

Feb 2007 53 324 14 52 45 600 

Mar 2007 83 415 13 4000 67 4000 

Apr 2007 80 4000 23 4000 74 2640 

4.2 BOD5 and TSS Results 

Analyses of BOD5 and TSS were performed in the IEC’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/l, and effluent BOD5 and TSS concentrations at WWTP 3 were, on average, above 30 mg/l; 

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 wetweather data). 

Table 10. Comparison of Standard Deviations for Effluent BOD5 and TSS 

WWTP Standard Deviation BOD5 (mg/l) Standard Deviation TSS (mg/l) 

Historical Project Wet-Weather Historical Project Wet-Weather 

1 2.7 12.0 3.1 4.7 

2 2.9 9.6 1.1 5.9 

3 1.9 7.1 3.9 8.6 

8 Permits for NYC DEP WWTPs include effluent limit for fecal coliform of 30-day geometric mean of 200 No/100ml; 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 
 

 

   

       

         

   

       

         

104

75

24

186

90

15

179

11

0

50

100

150

200

SP 1 SP2 SP4

BOD5 ; Arithmetic Mean (mg/l) 

WWTP 1 ‐ BOD5 (Arithmetic Mean)

Project Results & Historical Data

(Error Bars Show Standard Deviation)

Wet

Dry

Historical

116

89

22

112

46

13

117

6

0

50

100

150

200

SP 1 SP2 SP4

mg/l

WWTP 2‐ BOD5 (Arithmetic Mean)

Project Results & Historical Data

(Error Bars Show Standard Deviation)

Wet

Dry

Historical

BOD5 ; Arithmetic Mean (mg/l) 

Figure 3. BOD5 and TSS Results with Error Bars10 

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 
   

       

         

       

       

         

68

151

37

133

70

9

100

7

0

50

100

150

200

250

SP 1 SP2 SP4

mg/l

WWTP 3 ‐ BOD5 (Arithmetic Mean)

Project Results & Historical Data

(Error Bars Show Standard Deviation)

Wet

Dry

Historical

BOD5 ; Arithmetic Mean (mg/l) 

WWTP 1 ‐ TSS (Arithmetic Mean)

Project Results & Historical Data

(Error Bars Show Standard Deviation)

250

200

150

mg/l 100

50

0

197

99 105

68 72.3

12 13

29

Wet

Dry

Historical

SP 1 SP2 SP4

TSS; Arithmetic Mean (mg/l) 

Figure 3. BOD5 and TSS Results (cont.) 

17
 
        

       

       

       

       

       

176

89

20

150

43

2

128

5

0

50

100

150

200

250

SP 1 SP2 SP4

mg/l

WWTP 2 ‐ TSS (Arithmetic Mean)

Project Results & Historical Data

(Error Bars Show Standard Deviation)

Wet

Dry

Historical

TSS; Arithmetic Mean (mg/l) 

68

147

56

109

59

8

106

9

0

50

100

150

200

250

SP 1 SP2 SP4

mg/l

WWTP 3 ‐ TSS (Arithmetic Mean)

Project Results & Historical Data

(Error Bars Show Standard Deviation)

Wet

Dry

Historical

TSS; Arithmetic Mean (mg/l) 

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 BOD5 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 1 and 

WWTP 2 during both dry-weather and wet-weather sampling is shown in Table 12. Table 12 

demonstrates why during wet-weather blending total percent removal values for both WWTPs 

were slightly below the expected average of 85% (except for TSS at WWTP 2). The possible 

limiting factor was the percent removal in the primary treatment portion of the WWTPs. For 

primary treatment during wet-weather conditions, the percent removal values for BOD5 at 

WWTP 2 and TSS at WWTP 1 were slightly below the typical range of removals of 25-40% for 

BOD5 and of 50-60% for TSS during standard primary treatment operations. 11 

Table 11. BOD5 and TSS Total Percent Removal 12 

WWTP BOD5 - Dry 

Weather (%) 

BOD5 - Wet 

Blending (%) 

TSS - Dry 

Weather (%) 

TSS - Wet 

Blending (%) 

1 92 77 89 71 

2 88 81 99 89 

3 93 45 93 17 

Table 12. BOD5 and TSS Percent Removal for Primary and Secondary Treatment 

WWTP Parameter Operating 

Mode 

Primary 

Treatment 

(%) 

Secondary 

Treatment 

(%) 

Total 

WWTP (%) 

1 BOD5 Dry Weather 52 83 92 

Wet Weather 28 68 77 

TSS Dry Weather 31 83 89 

Wet Weather 31 57 71 

2 BOD5 Dry Weather 59 72 88 

Wet Weather 23 75 81 

TSS Dry Weather 71 95 99 

Wet Weather 49 78 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 = (SP1-SP4) (100)/ SP1 

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 Enterococcus levels were three 

orders of magnitude higher during wet-weather blending vs. dry-weather for both parameters at 

WWTP 2 and for Enterococcus 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 

Average 

Flow 

Operating 

Mode 

Fecal Coliform –Geometric Mean 

(MPN/100ml) 

Enterococcus –Geometric Mean 

(MPN/100ml) 

(MGD) Influent Effluent Order of 

Magnitude 

Reduction 

Influent Effluent Order of 

Magnitude 

Reduction 

1 

239 

Wet 

Blending 4,200,000 4,900 103

 890,000 17,000 102 

122 Dry 19,000,000 890 104

 470,000 20 104 

2 

125 

Wet 

Blending 1,100,000 19,000 102

 260,000 14,000 10 

31 Dry 5,000,000 16 105

 220,000 3 105

3 

 469 

Wet 

Blending 1,600,000 520 103

 280,000 870 103 

238.5 Dry 5,600,000 31 105

 1,700,000 120 104 

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

9.00

SP1 SP2 SP3 SP4

WWTP 1 ‐ Fecal Coliform‐ Effluent Concentrations

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

Wet

Dry

Log Fecal Coliform (MPN/100ml) 

Figure 4. Fecal Coliform and Enterococcus Effluent Concentrations 

21
 
22

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

SP1 SP2 SP3 SP4

Log Fecal Coliform (MPN/ 100 ml)

WWTP 3 ‐ Fecal Coliform Effluent Concentrations

Arithmetic Mean of Log

(Error Bars Show Standard Deviation

Wet

Dry

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

SP1 SP2 SP3 SP4

Log Fecal Coliform

M PN/100ml)

WWTP 2 ‐ Fecal Coliform‐ Effluent Concentrations

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

Wet

Dry

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

SP1 SP2 SP3 SP4

WWTP 1 – Enterococcus‐ Effluent Concentrations

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

Wet

Dry

Log Enterococcus (MPN/100ml)

Figure 4. Fecal Coliform and Enterococcus Effluent Concentrations (cont.)
     

     

       

     

     

       

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

SP1 SP2 SP3 SP4

WWTP 2 – Enterococcus Effluent Concentrations

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

Wet

Dry

Log Enterococcus (MPN/100ml) 

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00

SP1 SP2 SP3 SP4

WWTP 3 – Enterococcus‐ Effluent Concentrations

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

Wet

Dry

Log Enterococcus (MPN/100ml) 

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 MGD and 412.5 MGD, respectively. 

23
 
 

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
 
           

           

WWTP 1 WWTP 2 WWTP 3

Wet Weather 0.7 0.5 1.0

Dry Weather 0.4 0.7 0.7

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Total Residual Chlorine (TRC) at Effluent

(Arithmetic Mean) Error Bars Show Standard Deviation

TRC; Arithmetic Mean (mg/l) 

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 IEC’s standard operating procedure based on 

Hach Method 8167 and SM 18-20 4500-Cl G, which is a colorimetric version of the N, Ndiethyl-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/l to 2.00 mg/l; 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 Estimated Average Chlorine 

Contact Time (min) 

Range (min) 

Dry weather 29.4 25.8 – 32.1 

Wet weather 15.1 14.3 – 20.8 

4.6 Analysis of Existing Monitoring Data – Wet-Weather Non-Blending Events 

Though contracted to this research project, IEC’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 IEC’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. 

Figure 6. Historical IEC Wet-Weather Results – Percent of Design Flow vs. Fecal 

Coliform Count 

26
 
 

 

Table 15. Historical IEC Wet-Weather Results (Non-Blending and Blending)

 (fecal coliform, MPN/ per 100 ml) 

WWTP Date Flow 14 

% of Design Fecal TRC 

(mg/l) 

Daily Precipitation 

Flow Coliform (in.) 15 

1 2/5/2001 102 85 170 0.9 

0.5 

1 2/5/2001 104 87 340 0.7 

1 2/5/2001 144 120 800 0.5 

1 2/5/2001 146 122 500 0.7 

1 2/5/2001 211 176 16,000 0.7 

1 2/5/2001 208 173 16,000 0.7 

1 5/18/2004 135 113 5,000 0.8 

Trace 

1 5/18/2004 137 115 3,000 0.8 

1 5/18/2004 138 115 450 0.9 

1 5/18/2004 114 95 2,200 0.8 

1 5/18/2004 109 91 2,300 0.8 

1 5/18/2004 101 84 800 0.7 

1 8/28/2006 201 167 1,100 0.7 

0.35 

1 8/28/2006 189 158 16,000 0.7 

1 8/28/2006 168 140 3,000 0.8 

1 8/28/2006 154 128 5,000 0.8 

1 8/28/2006 155 129 16,000 0.8 

1 8/28/2006 157 131 5,000 0.7 

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 

14 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
 
 

 

 

 

 

 

 

     

       

Table 16. Range of Final Effluent Concentrations for Protozoa 

WWTP 

Operating 

Mode 

Giardia cysts/ l 

(enumerated values) 

Cryptosporidium oocysts/ l 

(enumerated values) 

Infe

Crypto

M

ctious 

sporidium 

PN/l 

Range Geometric 

Mean 

Range Geometric 

Mean 

Range Geometric 

Mean 

1 Dry 6 – 21 12 1 – 8 2 <0.2 NA 

Wet Blending 40 – 720 148 <0.2 – 52 8 <0.3 - <9.2 NA 

2 Dry 2 – 4 3 2 – 4 2 <0.2 NA 

Wet Blending 7 – 720 105 <0.2 – 2 NA <0.5 – 

<2.4 NA 

Note: NA =Less than three detectable results were reported, hence geometric mean could not be calculated 

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

SP1 SP2 SP3 SP4

Giardia; Log Arithmetic Mean (cysts/l) 

WWTP 1 ‐ Giardia

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

Wet

Dry

Figure 7. WWTPs 1 & 2 Giardia17 & Cryptosporidium Effluent Concentrations18 

with Error Bars19 

17 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
 
 

 

 

     

       

     

       

Figure 7. WWTPs 1 & 2 Giardia and Cryptosporidium20 Effluent Concentrations (cont.) 

20 Less than three detectable Cryptosporidium results were reported for the SP1and 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. 

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

SP1 SP2 SP3 SP4

WWTP 2 ‐ Giardia

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

Wet

Dry

Giardia; Log Arithmetic Mean(cysts/l) 

‐0.50

0.00

0.50

1.00

1.50

2.00

2.50

3.00

SP1 SP2 SP3 SP4

WWTP 1 ‐ Cryptosporidium

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

Wet

Dry

Cryptosporidium; Arithmetic Mean (cysts/l) 

29
 
 

 

 

     

       

‐0.50

0.00

0.50

1.00

SP1 SP2 SP3 SP4

Cryptosporidium;Log Arithmetic Mean 

(cysts/l) 

WWTP 2 ‐ Cryptosporidium

Arithmetic Mean of Log

Error Bars show Standard Deviation

Dry

Figure 7. WWTPs 1 & 2 Giardia and Cryptosporidium21 Effluent Concentrations with 

Error Bars (cont.) 

Table 17. Giardia and Cryptosporidium Average Percent Removal 

WWTP Weather 

Condition 

Removal of 

Giardia (%) 

Removal of 

Cryptosporidium (%) 

1 Wet 88 71 

2 Wet 40 NA 

1 Dry NA NA 

2 Dry 99 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/l in final 

effluents, with average removal between 98% and 99% for WWTP 1 and 99% for WWTP 2 

21 Less than three detectable Cryptosporidium results were reported for the SP1and 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
 
 

 

(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 

Operating 

Mode 

BG

Un

M In

its/l 

fectious M

Infectio

A-104 

us Units/l 

PLC/

Infectiou

PRF/5 

s Units/l 

CaCo

Infectious

-2 

Units/l 

Range Geom. 

Mean 

Range Geometric 

Mean 

Range Geom. 

Mean 

Range Geom. 

Mean 

1 Dry 1 – 3 2 1 – 5 2 2 – 5 3 <1 – 1 NA 

Wet 3 – 143 14 <2 – 393 21 9 – 32 18 1 – 34 4 

2 Dry 3 – 6 5 5 – 14 8 4 - 5 5 <3 – 8 NA 

Wet <1– 25 6 <1 – 12 4 <1- 104 11 <1 – 21 5 

Note: NA =Less than three detectable results were reported, hence geometric mean could not be calculated 

Enterovirus, Reovirus and Adenovirus were the “Top Three” viruses detected in WWTP 

samples; on a few occasions, Rotavirus was also detected (Table 20). Only Enterovirus, 

Reovirus, and Adenovirus were detected in final effluent samples. The cell lines that were used 

for detection of the enteric viruses using ICC-PCR and/or PCR shown in Table 19. 

Table 19. Detection by Cell Lines 

Cell Line Viruses Targeted for PCR Detection 

BGM: Enterovirus, Reovirus 

MA104: Enterovirus, Rotavirus, Reovirus 

PLC/PRF/5 Adenovirus 

CaCo-2 Enterovirus, Astrovirus 

Norovirus and Hepatitis A were analyzed by the direct RT-PCR method and neither was detected 

in samples. 

In the cases when several viruses were detected in one sample, individual MPN concentrations 

for each virus group could not be generated due to the limitations of the EPA-ICR method. 

Overall, the relative recoveries for virus samples were approximately 50%. The majority of 

recoveries were consistently 50%. The matrix spikes were performed with poliovirus as per the 

method described in EPA 600/R-95/178. 

22 Cell line – Human or animal cells 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 (Buffalo Green Monkey cell line), MA104 (cell line 

derived from Rhesus monkey kidney), PLC/PRF/5 (human hepatoma cell line) and CaCo-2 (human intestinal cell 

line), were used for detection of the enteric viruses. 

31
 
 Table 20. Detected Viruses 

a) Dry weather 

WWTP 

Sampling 

Location BGM MA-104 PLC/PRF/5 CaCo-2 

1 SP1 EV EV,REO,RV EV, AdV EV 

SP2 EV EV,REO,RV EV EV 

SP3 EV EV,REO --- ---

SP4 EV REO --- --- 

2 SP1 REO, EV EV, REO EV, AdV EV 

SP2 EV EV,REO EV, AdV EV 

SP3 EV REO EV, AdV ---

SP4 --- REO --- --- 

b) Wet weather 

WWTP 

Sampling 

Location 

Event 

# BGM MA-104 PLC/PRF/5 CaCo-2 

1 SP1 

1 EV EV,RV EV, AdV EV 

2 EV, REO EV,RV EV, AdV EV 

3 EV, REO EV, REO, RV EV, AdV EV 

SP2 

1 EV, REO EV,RV EV, AdV EV 

2 EV EV, REO EV, AdV EV 

3 EV, REO EV,REO AdV EV 

SP3 

1 EV REO AdV EV 

2 EV EV, REO AdV ---

3 EV REO AdV EV 

SP4 

1 EV, REO REO AdV ---

2 EV REO AdV ---

3 --- --- AdV --- 

2 SP1 

1 EV, REO EV, RV, REO EV, AdV EV 

2 EV, REO EV, RV, REO EV, AdV EV 

3 EV, REO EV, RV, REO EV, AdV EV 

SP2 

1 EV EV, RV EV, AdV EV 

2 EV, REO EV, RV EV, AdV EV 

3 EV, REO EV, RV, REO EV, AdV EV 

SP3 

1 EV RV, REO AdV EV 

2 EV, REO RV AdV EV 

3 EV REO EV, AdV ---

SP4 

1 EV RV, REO --- --- 

2 --- --- --- --- 

3 EV REO AdV ---

Note: AdV = Adenovirus EV = Enterovirus RV = Rotavirus REO = Reovirus 

32 
 

 

   

     

       

   

   

   

   

     

       

   

   

   

   

0

1

2

3

4

5

6

SP1 SP2 SP3 SP4

Buffalo Green Monkey; Arithmetic

Mean of Log (infectious units/100 L)

Buffalo Green Monkey

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

STP 1 Dry

STP 1 Wet

STP 2 Dry

STP 2 Wet

0

1

2

3

4

5

6

SP1 SP2 SP3 SP4

‐MA‐104, Arithmetic Mean of Log

(infectious units /100 L)

MA ‐104

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

STP 1 Dry

STP 1 Wet

STP 2 Dry

STP 2 Wet

Figure 8. Virus Concentrations23 by Cell Lines 

23 Less than three detectable virus 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
 
34

0

1

2

3

4

5

6

7

SP1 SP2 SP3 SP4

CaCo‐2, Arithmetic Mean of log

(infectious units/100 L)

CaCo‐2

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

STP 1 Dry

STP 1 Wet

STP 2 Dry

STP 2 Wet

0

1

2

3

4

5

6

SP1 SP2 SP3 SP4

PLC/PRF/5, Arithmetic Mean of log

(infectious units/100 L)

PLC/PRF/5

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

STP 1 Dry

STP 1 Wet

STP 2 Dry

STP 2 Wet

Figure 8. Virus Concentrations24 by Cell Lines (cont.) 

 

24 Less than three detectable virus 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
 

 

Table 21. Average Percent Removal of Viruses during Wet-Weather 

WWTP BGM Removal 

(%) 

MA-104 

Removal (%) 

PLC/PRF/5 

Removal (%) 

CaCo-2 cells 

Removal (%) 

1 98 98 98 99 

2 99 99 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. 

coli) - 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 Operating 

Mode 

Famp bacteriophage / ml C3000 bacteriophage / ml 

Range Geometric 

Mean Range Geometric Mean 

1 

Dry 53 – 62 57 32 – 56 43 

Wet 

1 – 5 2 2 – 7 3 

2 

Dry 3 – 6 4 3 – 8 5 

Wet 

2 – 12 4 1 – 3 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 malespecific 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
 
36

0

1

2

3

4

SP1 SP2 SP3 SP4

Bacteriophage‐Famp, ArithmeticMean of log

Bacteriophage/ ml

Bacteriophage‐Famp

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

STP 1 Dry

STP 1 Wet

STP 2 Dry

STP 2 Wet

0

1

2

3

4

SP1 SP2 SP3 SP4

Bacteriophage‐C3000,Arithmetic Mean of log

Bacteriophage/ ml

Bacteriophage‐C3000

Arithmetic Mean of Log

(Error Bars Show Standard Deviation)

STP 1 Dry

STP 1 Wet

STP 2 Dry

Figure 9. Coliphage Concentrations - Famp and C300026 

 

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.
 

Table 23. Coliphage Average Percent Removal during Wet Weather 

WWTP Famp Removal (%) C3000 Removal (%) 

1 99 99 

2 97 NA 

Note: NA =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 predetermined 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). 

Figure 10. Macerated vs. Unmacerated Concentrations 

Detailed maceration optimization charts are included in Appendix E. 

38
 
 

 

 

 

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 BOD5 wet-weather blending effluent concentrations were 24 mg/l at WWTP 1 

(values ranged from 9.5 to 37 mg/l), and 22 mg/l at WWTP 2 (values ranged from 9 to 30 mg/l). 

The average of TSS wet-weather blending effluent concentrations were 29 mg/l at WWTP 1 

(values ranged from 22 to 33 mg/l) and 20 mg/l at WWTP 2 (values ranged from 13 to 26 mg/l). 

All of these average effluent values were below the IEC effluent value of 30 mg/l for a 30 day 

27 average. 

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 BOD5 and 31% for TSS and at WWTP 2 were 23% for BOD5 and 49% 

for TSS. The aforementioned results for BOD5 at WWTP 2 and for TSS at WWTP 1 were 

slightly below the preferred range of removals of 25 to 40% for BOD5 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/l and 56 mg/l, 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 Giardia) 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 malespecific and somatic coliphages as an indicator for viruses) during wet-weather blending? 

28 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 parameters—as 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 Enterococcus? 

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/l at WWTP 1, 13 mg/l at WWTP 

2 and 9 mg/l at WWTP 3. The dry-weather effluent concentrations for TSS were 12 mg/l at 

WWTP 1, 2 mg/l at WWTP 2 and 8 mg/l 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, MA104, 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
 
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, wetweather 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, highgradient magnetic separation, and fluidized-bed biological treatment. 

42
 
 

C. Provide technical guidance on the use of “stress tests,” commercially available paralleltreatment 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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Wastewater. 21st Edition, Washington, D.C. 

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procedures to desorb bacteria from granular activated carbon. Journal of Microbiological 

Methods. 3:187-198. 

Chauret, C., S. Springthorpe, and S. Sattar. (1999). Fate of Cryptosporidium oocysts, Giardia 

cysts, and microbial indicators during wastewater treatment and anaerobic sludge 

digestion. Canadian Journal of Microbiology. 45:257-262. 

Escalante, A.A., R. J. Montali, R. Fayer, and A.A. Lal (1999). Phylogenetic Analysis of 

Cryptosporidium Parasites Based on the Small-Subunit rRNA Gene Locus. Applied 

and Environmental Microbiology 65(4):1578–1583. 

Grimm, A.C., J.L. Cashdollar, F.P. Williams, and G.S. Fout. (2004). Development of an 

astrovirus RT-PCR detection assay for use with conventional, real-time, and 

integrated cell culture/RT-PCR. Canadian Journal of Microbiology. 50: 269-278. 

Hoff, J. C. The Relationship of Turbidity to Disinfection of Potable Water. In: Evaluation of the 

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00C, U.S. Environmental Protection Agency, Washington, DC, 1978, pp 103-117. 

Hoff, J. C. and Akin, E.W. 1986. Microbial resistance to disinfectants: mechanisms and 

significance. Environmental Health Perspectives. 69:7-13. 

Oberste, M.S., K. Maher, A.J. Williams, N. Dybdahl-Sissoko, B.A. Brown, M.S. Gookin, 

S. Penaranda, N. Mishrik, M. Uddin, and M.A. Pallansch. (2006). 

 Species-specific RT-PCR amplification of human enteroviruses: a tool for rapid 

 species identification of uncharacterized enteroviruses. Journal of General 

Virology 87:119-128. 

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. 

Peavy, H.S., D. R. Rowe and G. Tchobanoglous (1985), Environmental Engineering, 

Mc Graw-Hill, Inc., New York, NY, 1985. 

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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):3936-3941. 

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., and D.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. and F.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. Fayer, and A.A. Lal (1998). Species and Strain-specific Typing 

of Cryptosporidium Parasites in Clinical and Environmental Samples. Memórias 

do Instituto Oswaldo Cruz 93(5): 687-692. 

44
 
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 

Information. 

3. U.S. Environmental Protection Agency, 1994. Guidance for the Data Quality Objectives 

Process (QA/G-4), U.S. EPA Office of Environmental Information. 

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, 

and Water Environmental Federation, 1992. Standard Methods for the Examination of 

Water and Wastewater, 20th ed., Washington, D.C. 

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. 

8. Interstate Environmental Commission, January 2002. Quality Control Manual of the 

Interstate Environmental Commission, New York, N.Y. 

9. Interstate Environmental Commission, January 1983. Quality Assurance/Control 

Procedures for Microbiological Testing and Analysis, New York, N.Y. 

45
 
Appendix A 

Detailed Sampling Results 

46
 
Plant MPN/ L BGM MA-104 PLC/PRF/5 CaCo-2 cells Famp 

bacteriophage 

/ ml 

Operating 

Mode Plant Location Date 

Fecal Coliform 

mpn/100 ml 

Entero 

mpn/100 ml 

Giardia 

cysts/ L 

Crypto 

oocysts/ L 

Infectious 

Crypto 

 Infectious 

Units/L 

Virus 

Detected

 Infectious 

Units/L 

Virus 

Detected

 Infectious 

Units/L 

Virus 

Detected

 Infectious 

Units/L 

Virus 

Detected 

>24,000,000 130,000 <0.4 <0.4 <1.0 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

7/17/06 >24,000,000 540,000 27.2 1.4 <0.9 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

Influent 11,000,000 1,500,000 1.6 <0.4 <1.0 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

---- ---- ---- ---- ---- 1,156 713 788 7,880 832 

8/14/06 ---- ---- ---- ---- ---- 786 EV 233 EV,REO,RV 154 EV, AdV 2,412 EV 600 

---- ---- ---- ---- ---- 582 970 484 13,920 712 

1,500,000 2,400,000 <0.33 <0.33 <0.9 ---- ---- ---- ---- ---- ---- 

PE 7/17/06 >24,000,000 600,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

>24,000,000 430,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

8/14/06 ---- ---- ---- ---- ---- 356 EV 356 EV,REO,RV 418 EV 2,200 EV 425 

Plant 1 2,300 2,300 24.9 5.4 <0.2 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

7/17/06 15,000 9,300 3 <0.09 <0.2 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

150,000 15,000 9.1 3.8 <0.2 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

SE (pre-chlor) 

---- ---- ---- ---- ---- 7 11 13 3 52 

8/14/06 ---- ---- ---- ---- ---- 7 EV 6 EV,REO 7 --- 3 --- 61 

---- ---- ---- ---- ---- 4 6 4 1 47.2 

390 4 20.7 7.5 <0.2 ---- ---- ---- ---- ---- ---- 

7/17/06 1,200 93 12 1.4 <0.2 ---- ---- ---- ---- ---- ---- 

Final Effluent 1,500 23 6.4 1.1 <0.2 ---- ---- ---- ---- ---- ---- 

---- ---- ---- ---- ---- 1 5 5 <1 52.8 

8/14/06 ---- ---- ---- ---- ---- 1 EV 1 REO 3 --- 1 --- 62.4 

---- ---- ---- ---- ---- 3 1 2 1 56.8 

2,400,000 430,000 356 <1.0 <2.4 477 478 412 197 400 

Influent 8/14/06 4,600,000 27,000 618 4 <2.4 334 REO, EV 771 EV, REO 671 EV, AdV 145 EV 480 

11,000,000 930,000 276 <1.0 <2.4 667 578 823 912 680 11,000,000 280,000 536 4 <2.4 ---- ---- ---- ---- ---- 

PE 8/14/06 11,000,000 430,000 446 <1.0 <2.4 211 EV 564 EV,REO 679 EV, AdV 1,970 EV 360 

Dry Plant 2 2,400,000 930,000 ---- ---- ---- ---- ---- ---- ---- ---- 

SE (pre-chlor) 8/14/06 

460,000 230,000 5.7 0.7 <0.2 11 

EV 

14 

REO 

7 

EV, AdV 

39 

---

42 

1,100,000 230,000 6.2 1.1 <0.2 6 8 4 24 26.4 

150,000 430,000 2.3 0.7 <0.2 6 5 7 39 22.8 

Final Effluent 8/14/06 

<3 <3 2.8 2.0 <0.2 3 

---

8 

REO 

4 

---

<3 

---

3.2 

93 <3 2.3 1.9 <0.2 6 14 4 <3 4.8 

15 <3 3.5 3.6 <0.2 6 5 5 8 5.6 

Plant 3 

Influent 

8/23/06 4/24/07 

2,400,000 750,000 

No Protozoa, Virus and Coliphage samples were collected at Plant 3 as per scope of work requirements 

2,400,000 750,000 

4,600,000 930,000 

>24,000,000 >24,000,000 

11,000,000 930,000 

4,600,000 2,400,000 

PE 4/24/07 

2,400,000 930,000 

11,000,000 2,100,000 

430,000 2,400,000 

SE (pre-chlor) 

8/23/06 4/24/07 

93,000 15,000 

23,000 4,300 

23,000 2,300 

<3000 <3000 

4,000 9,000 

23,000 93,000 

Final Effluent 

8/23/06 

4 <3 

15 <3 15 <3 

4/24/07 

230 4,300 150 2,100 

30 9,300 

PE - Primary effluent SE (pre-chlor) - Secondary effluent prior to chlorination EV = Enterovirus AdV = Adenovirus RV = Rotovirus Av = Astrovirus REO = Reovirus 

47
Plant MPN/ L BGM MA-104 PLC/PRF/5 CaCo-2 cells Famp 

bacteriophage 

/ ml 

Operating 

Mode Plant Location Date 

Fecal Coliform 

mpn/100 ml 

Entero 

mpn/100 ml 

Giardia 

cysts/ L 

Crypto 

oocysts/ L 

Infectious 

Crypto 

 Infectious 

Units/L 

Virus 

Detected

 Infectious 

Units/L 

Virus 

Detected

 Infectious 

Units/L 

Virus 

Detected

 Infectious 

Units/L 

Virus 

Detected 

4,600,000 390,000 ---- ---- ---- 2,111 1,741 1,213 603 500 

9/14/06 4,600,000 11,000,000 ---- ---- ---- 1,279 EV 1,279 EV, RV 435 EV, AdV 985 EV 340 

4,600,000 4,600,000 ---- ---- ---- 2,111 792 870 1,741 180 

4,600,000 430,000 820 280 <9.2 572 914 1,677 254 320 

10/20/06 2,400,000 430,000 1,200 20 <9.2 914 EV, REO 5,425 EV, RV 6,606 EV, AdV 254 EV 500 

11,000,000 4,600,000 880 24 9.2 (1.3-68) 914 1,520 1,677 108 220 

>24,000,000 2,100,000 790 1,000 18.4 (2.5-136) ---- ---- ---- ---- ---- ---- ---- ---- ---- 

Influent 11/8/06 >24,000,000 640,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

11,000,000 2,400,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

4,600,000 93,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

3/2/07 1,200,000 150,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

930,000 2,400,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

1,500,000 230,000 1,100 100 <2.4 92 143 110 297 160 

4/27/07 930,000 430,000 4,300 <1.0 <2.4 738 EV, REO 54 EV, REO,RV 114 EV, AdV 1,424 EV 110 

4,600,000 930,000 1600 <1.0 <2.4 222 4,069 686 54 130 

11,000,000 2,400,000 ---- ---- ---- ---- ---- ---- ---- ---- 

9/14/06 11,000,000 2,400,000 ---- ---- ---- 2,111 EV, REO 759 EV, RV 257 EV, AdV 2,870 EV 400 

>24,000,000 930,000 ---- ---- ---- ---- ---- ---- ---- ---- 

1,500,000 230,000 760 12 <9.2 ---- ---- ---- ---- ---- 

10/20/06 930,000 230,000 ---- ---- ---- 775 EV 412 EV, REO 1,677 EV, AdV 108 EV 360 

230,000 150,000 ---- ---- ---- ---- ---- ---- ---- ---- 

4,600,000 230,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

PE 11/8/06 4,600,000 930,000 398 462 <9.2 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

2,400,000 930,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

430,000 390,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

3/2/07 930,000 210,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

430,000 230,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

2,400,000 430,000 ---- ---- ---- ---- ---- ---- ---- ---- 

4/27/07 2,400,000 2,400,000 2,200 30 <2.4 143 EV, REO 429 EV, REO 1,424 AdV 186 EV 130 

Wet Plant 1 930,000 2,400,000 ---- ---- ---- ---- ---- ---- ---- ---- 

SE (pre-chlor) 

9/14/06 

1,100,000 150,000 ---- ---- ---- 59 

EV 

48 

REO 

12 

AdV 

8 

EV 

6.5 

>2,400,000 240,000 ---- ---- ---- 68 151 8 3 5.7 

>2,400,000 240,000 ---- ---- ---- 115 216 23 5 6.7 

10/20/06 

930,000 ---- 320 14 <9.2 40 

EV 

236 

EV, REO 

66 

AdV 

72 

---

10.4 

390,000 23,000 100 30 <9.2 35 44 22 127 11.4 

930,000 43,000 30 22 9.2 (1.3-68) 57 205 57 36 12.5 

11/8/06 

2,400,000 43,000 61 63 <1.8 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

930,000 43,000 70 66 1.8 (0.3-13.6) ---- ---- ---- ---- ---- ---- ---- ---- ---- 

2,400,000 93,000 80 78 <1.8 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

3/2/07 

930,000 230,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

150,000 93,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

230,000 930,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

4/27/07 

2,400,000 430,000 220 <0.2 <0.48 2 

EV 

2 

REO 

23 

AdV 

19 

EV 

5.8 

2,400,000 430,000 170 <0.2 <0.48 4 102 51 24 5.4 

2,400,000 430,000 250 <0.2 <0.48 <1.9 2 98 6 1.7 

Effluent 

9/14/06 

930 11,000 64 36 0.3 (0.04-2.1) 76 

EV, REO 

58 

REO 

15 

AdV 

2 

---

1.6 

>24,000 >24,000 56 42 <0.3 143 393 9 1 2.8 

>24,000 >24,000 58 34 <0.3 55 18 20 1 1 

10/20/06 

1,500 9,300 320 8 <9.2 6 

EV 

19 

REO 

19 

AdV 

19 

---

1.8 

4,300 >240,000 270 2 <9.2 5 20 20 21 2.5 

930 2,000 220 8 <9.2 18 40 32 34 3.9 

11/8/06 

>240,000 >240,000 41 43 <1.8 ---- ---- ---- ---- ---- ---- ---- ---- ---- 

930 46,000 40 46 <1.8 ---- ---- ---- ---- ---- ---- ---- ---- ---- 930 24,000 60 52 1.8 (0.3-13.6) ---- ---- ---- ---- ---- ---- ---- ---- ---- 

3/2/07 

930 230 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

1,500 24,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

24,000 9,300 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

4/27/07 

9,300 5,500 690 <0.2 <0.48 4 

---

2 

---

25 

AdV 

2 

---

3.6 

15,000 24,000 720 2 <0.48 5 <1.8 23 2 2.7 

7,500 46,000 590 <0.2 <0.48 3 3 10 1 4.8 

PE - Primary effluent SE (pre-chlor) - Secondary effluent prior to chlorination EV = Enterovirus AdV = Adenovirus RV = Rotovirus Av = Astrovirus REO = Reovirus *ND - Not done due to the high background concentration of indigenous bacteria 

48
Plant MPN/ L BGM MA-104 PLC/PRF/5 CaCo-2 cells Famp 

bacteriopha

/ ml 

Operating 

Mode Plant Location Date 

Fecal Coliform 

mpn/100 ml 

Entero 

mpn/100 ml 

Giardia 

cysts/ L 

Crypto 

oocysts/ L 

Infectious 

Crypto 

 Infectious 

Units/L 

Virus 

Detected

 Infectious 

Units/L 

Virus 

Detected 

Infectious 

Units/L 

Virus 

Detected

 Infectious 

Units/L 

Virus 

Detected 

430,000 120,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

11/8/06 430,000 230,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

2,400,000 210,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

2,400,000 930,000 30 <1.0 <2.4 297 190 EV,RV, 72 216 EV 200 

Influent 

1/8/07 4,600,000 430,000 150 <1.0 <2.4 914 EV, REO 914 REO 914 EV, AdV 229 370 

2,400,000 230,000 140 <1.0 <2.4 4,068 4,068 6,576 1,140 100 

4/12/07 1,500,000 430,000 2,200 40 <2.4 54 EV, REO 110 REO EV, RV, 581 EV, AdV 309 EV 120 

430,000 430,000 890 <1.0 <2.4 429 222 7,398 1,101 90 

1,500,000 93,000 60 <1.0 <2.4 1,520 1,520 EV, RV, 914 360 EV 244 

7/18/07 230,000 150,000 70 <1.0 <2.4 5,420 EV, REO 5,420 REO 1,898 EV, AdV 220 188 

2,400,000 430,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

11/8/06 930,000 430,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

430,000 230,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

930,000 750,000 90 <1.0 <2.4 190 EV 190 EV, RV 225 EV, AdV 190 EV 220 

PE 

1/8/07 2,400,000 1,200,000 ---- ---- ---- ---- ---- ---- ---- ---- 

2,400,000 4,600,000 ---- ---- ---- ---- ---- ---- ---- ---- 

4/12/07 11,000,000 930,000 <1.0 10 <2.4 686 EV, REO 2,847 EV, RV 1,140 EV, AdV 2,847 EV 130 

>24,000000 >24,000000 ---- ---- ---- ---- ---- ---- ---- ---- 

2,100,000 430,000 ---- ---- ---- ---- ---- EV, RV, ---- ---- EV ---- 

Wet Plant 2 

7/18/07 930,000 210,000 20 <1.0 <2.4 914 EV, REO 914 REO 3,800 EV, AdV 810 258 

SE (pre-chlor) 

11/8/06 

430,000 430,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

430,000 75,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

430,000 430,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

1/8/07 430,000 43,000 3 3 <2.4 48 EV 48 RV, REO 15 AdV 29 EV 11.1 

750,000 93,000 3 1 <2.4 52 32 32 27 3.4 

4/12/07 

930,000 43,000 52 <0.2 <0.5 7 

EV, REO 

7 

RV 

21 

AdV 

26 

EV 

5.7 

930,000 23,000 <0.2 <0.2 <0.5 3 6 17 4 5.7 

430,000 43,000 42 <0.2 <0.5 <2 3 54 7 7.4 

7/18/07 430,000 93,000 16 <0.2 <0.5 43 EV 17 REO 69 EV, AdV 14 --- 16.5 

230,000 93,000 40 <0.2 <0.5 10 5 44 9 32.4 

Effluent 

11/8/06 

>240,000 46,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

>240,000 24,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

>240,000 24,000 ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- ---- 

1/8/07 2,300 4,300 8 2 <2.4 25 EV 5 RV, REO 16 ---- 21 ---- 6.9 

90 930 7 1 <2.4 6 6 8 4 1.7 

4/12/07 

46,000 15,000 210 <0.2 <0.5 2 

----

<2 

----

6 

----

<2 

----

4.7 

4,300 >240,000 580 <0.2 <0.5 <2 <2 6 <2 6.4 

1,500 930 710 <0.2 <0.5 <1 <1 <1 <1 2.2 

7/18/07 >240,000 9,300 720 <0.2 <0.5 14 EV 12 REO 104 AdV 9 ---- 9.6 

24,000 110,000 40 <0.2 <0.5 13 4 41 9 12.2 

PE - Primary effluent SE (pre-chlor) - Secondary effluent prior to chlorination EV = Enterovirus AdV = Adenovirus RV = Rotovirus Av = Astrovirus REO = Reovirus 

*ND - Not done due to the high background concentration of indigenous bacteria 

49
Plant BOD TSS 

Operating Fecal Coliform Entero (composite (composite) Residual 

Mode WWPT Location Date mpn/100 ml mpn/100 ml ) mg/l mg/l Chlorine mg/l 

430,000 1,200,000 ----

11/8/06 2,100,000 230,000 76 83 ----

>24,000,000 230,000 ----

4,600,000 230,000 ----

1/8/07 2,400,000 930,000 40 41.6 ----

Influent 2,400,000 930,000 ----

430,000 430,000 ----

3/2/07 43,000 93,000 65 76.2 ----

>24,000,000 93,000 ----

2,400,000 430,000 ----

4/4/07 930,000 150,000 92.4 69.6 ----

430,000 93,000 ----

>24,000,000 230,000 ----

11/8/06 2,500,000 230,000 225 212 ----

2,400,000 2,400,000 ----

23,000 23,000 ----

1/8/07 4,600,000 750,000 137.6 138.9 ----

PE 11,000,000 4,600,000 ----

2,400,000 93,000 ----

3/2/07 430,000 93,000 99.7 212.2 ----

930,000 430,000 ----

1,500,000 230,000 ----

4/4/07 2,400,000 930,000 141.2 26.1 ----

Wet 3 930,000 230,000 ----

SE (pre-chlor) 

11/8/06 

7,000 <3000 

---- ----

----

19,000 <3000 ----

4,000 <3000 ----

1/8/07 

23,000 150,000 

---- ----

----

9,000 <3000 ----

<3000 <3000 ----

3/2/07 

<3000 <3000 

---- ----

----

<3000 <3000 ----

58,000 <3000 ----

4/4/07 

23,000 210,000 

---- ----

----

930,000 93,000 ----

23,000 230,000 ----

Effluent 

11/8/06 

930 2,300 

40 59 

0.5 

2,300 430 0.62 

4,300 210 1 

1/8/07 

<30 230 

32 52.7 

0.75 

90 90 1.2 

40 430 0.85 

3/2/07 

230 340 

46 66.1 

1.39 

930 930 1.19 

4,300 340 1.3 

4/4/07 

210 46,000 

31.1 45.9 

1.08 

210 430 1.12 

9,300 46,000 1.22 

PE - Primary effluent SE (pre-chlor) - Secondary effluent prior to chlorination 

50 
Appendix B 

Maceration Results
 

51
 
52
 
 

Appendix C 

Flow and 

Estimated Chlorine Contact Time Data
 

53
 
FLOW RATE DATA 

Wet-Weather Blending Runs 

WWTP INFLUENT BYPASSE

Date WWTP LOCATION TIME (MGD) SECONDARY INFLUENT BYPASSED FLOW (%) 

9/14/2006 1 SP1-1 8:05 199 181 18 9 

SP1-2 8:50 248 181 67 27 

SP1-3 9:35 249 182 67 27 

10/20/2006 1 SP1-1 9:30 248 183 65 26 

SP1-2 10:15 242 182 60 25 

SP1-3 11:00 171 172 

11/8/2006 1 SP1-1 10:15 247 200 47 19 

SP1-2 11:03 245 200 45 18 

SP1-3 11:48 245 200 45 18 

3/2/2007 1 SP1-1 7:55 249 191 58 23 

SP1-2 8:40 248 188 60 24 

SP1-3 9:25 248 188 60 24 

4/27/2007 1 SP1-1 8:00 248 194 54 22 

SP1-2 8:45 248 189 59 24 

SP1-3 9:32 249 178 71 29 

11/8/2006 2 SP1-1 10:15 123 - - - 

SP1-2 11:00 127.2 - - - 

SP1-3 11:45 127.8 - - - 

1/8/2007 2 SP1-1 8:55 124 - - - 

SP1-2 9:40 90 - - - 

SP1-3 ND ND - - - 

4/12/2007 2 SP1-1 7:55 137.4 - - - 

SP1-2 8:40 136 - - - SP1-3 9:25 137 - - - 

7/18/07 2 SP1-1 7:50 124 - - - 

SP1-2 8:35 121 - - - 

54
 
FLOW RATE DATA Cont’d 

Wet-Weather Blending Runs 

BYP

Date WWTP LOCATION TIME WWTP INFLUENT (MGD) SECONDARY INFLUENT BYPASSED FLOW 

11/8/2006 3 SP1-1 11:25 566 - - 

SP1-2 12:05 574 - - SP1-3 12:50 580 - - 

1/8/2007 3 SP1-1 9:10 459 - - 

SP1-2 9:50 400 - - 

SP1-3 10:35 401 - - 

3/2/2007 3 SP1-1 7:45 406 - - 

SP1-2 8:30 419 - - 

SP1-3 9:15 500 - - 

4/4/2007 3 SP1-1 13:50 439 - - 

SP1-2 14:34 436 - - 

SP1-3 15:20 445 - - 

55
 
Dry-Weather Blending Runs 

SECONDARY 

Date WWTP LOCATION TIME WWTP INFLUENT (MGD) INFLUENT BYPASSED FLOW BYPASSE

7/17/2006 1 SP1-1 9:30 138 - - - 

SP1-2 10:15 128 

SP1-3 11:00 130 

8/14/06 1 SP1-1 8:30 111 - - - 

SP1-2 9:15 112 - - - SP1-3 10:00 113 - - - 

8/14/2006 2 SP1-1 8:30 29.9 - - - 

SP1-2 9:15 30.9 SP1-3 10:00 33.1 

8/23/2006 3 SP1-1 9:08 216- - - - 

SP1-2 9:55 236 

SP1-3 10:40 234 

4/24/2007 3 SP1-1 9:15 262 

SP1-2 10:00 250 SP1-3 10:45 233 

56
 
Appendix D 

Maceration Optimization Analyses
 

57
 
 

Charts for Maceration Optimization Analyses 

WWTP 1 – Dry Run - July 17, 2006 

58
 
WWTP 1 – Dry Run - July 17, 2006 

59
 
WWTP 1 – Dry Run - July 17, 2006 

60
 
WWTP 1 – Geometric Means for Dry Run on July 17, 2006 

61
 
WWTP 1 - Wet Run - September 14, 2006 

62
 
WWTP 1 - Wet Run - September 14, 2006 

63
 
WWTP 1 - Wet Run - September 14, 2006 

64
 
WWTP 1 – Geometric Means for Wet Run on September 14, 2006 

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 μl) 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, Ill.). Slides 

were incubated in a 5% CO2 atmosphere at 37°C 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 DIC 

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 μl 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 μl of the secondary PCR 

product was digested in a 25 -μl (total volume) reaction mixture containing 20 U of SspI (New 

England BioLabs, Beverly, Mass.) for species diagnosis or 20 U of VspI (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, 25°C), 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