CA State Water Board Grant on Water Reuse: Introduction Thursday, - - PDF document

11/7/2019 1

CA State Water Board Grant

• n Water Reuse: Introduction

1

Thursday, November 7, 2019 1:00 – 2:30 pm ET

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Today’s Speakers

Julie Minton The Water Research Foundation Adam Olivieri, Ph.D. EOA, Inc. Jim Crook, Ph.D., PE Environmental Engineering Consultant Shane Trussell, Ph.D., P.E., BCEE Trussell Technologies Brian Pecson, Ph.D., PE Trussell Technologies Jean Debroux, Ph.D. Kennedy Jenks

Agenda

• Welcome and Introduction
• Background of CA State Board and WRF Grant Investigations

Julie Minton and Dr. Adam Olivieri

• Pathogen Monitoring in Raw Wastewater
• Dr. Brian Pecson
• Plant Reliability and Quantitative Microbial Risk Assessment
• Dr. Brian Pecson
• Identification and Control of Chemical Peaks
• Dr. Jean Debroux and Dr. Shane Trussell
• Q&A

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A Brief History of WRF Potable Reuse Research

WateReuse Research Foundation: DPR Research Initiative (2012‐2016)

• In response to CA legislation to

determine “Feasibility of developing criteria for DPR”

• $6 million raised – Leveraged to

$24 million

• 34 projects funded that informed

DPR Expert Panel

Outcomes

• DPR Expert Panel report
• SWB Report to legislature  Yes,

it is feasible to develop regulations for DPR

Recycled Water Grants from State Water Board

Grant 1: $1.4M

• 5 projects recommended by the

SWB DPR Expert Panel for developing DPR regulations in California

• Agreement executed February

28, 2018

• Research being conducted Q4

2018 – Q4 2020 Grant 2: $3.1M

• 20 reuse research projects

recommended by the WRF’s Water Reuse Advisory Committee and SWB.

• Agreement executed March 30,

2018

• Research being conducted Q1 2019

‐ 2023

California Legislation – AB 574 (2017): Established deadline for DPR legislation of 2023 5 6

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SWB Grant 1: 5 DPR Research Projects

7

Research addressing Pathogens

• DPR‐1. Quantitative Microbial Risk Assessment*
• DPR‐2. Measure Pathogens in Wastewater*
• DPR‐3. Collecting Pathogens in Wastewater During

Outbreaks

Research addressing Chemicals

• DPR‐4. Treatment for Averaging Potential Chemical

Peaks

• DPR‐5. Low Molecular Weight Unknown

Compounds Research implementation late 2018 – late 2020

Public Health Protection

*Co‐funded by Metropolitan Water District

Coordinating Committee

Oversees the program and each project

• Adam Olivieri (EOA)
• James Crook (Environmental Engineering

Consultant)

• Bob Brownwood, DDW
• Claire Waggoner, DWQ

Research Team

• Scientific engineers, experts, etc.

conducting the work WRF Project Manager and Project Advisory Committee DDW Technical Liaison Jing‐Tying Chao

WRF

Julie Minton, Project Director

CA SWB DDW

Technical Advisor Bob Brownwood

Technical Working Group (TWG)

• Scientific experts overseeing the research
• Develop Request for Proposals (if needed)
• Select Research Teams
• Conduct the work when no RFP

8

SWB Grant 1: Research Oversight & Communication

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Background of CA State Board and WRF Grant Investigations

9

• Dr. Adam Olivieri

Is it feasible to do potable reuse without an environmental buffer (DPR)?

Division of Drinking Water

QUES QUESTION: TION:

California’s Big Question

State of California Expert Panel on DPR

Can we do DPR safely?

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Expert Panel Findings on Direct Potable Reuse

• CA State Expert Panel assessed DPR

feasibility

• Concluded it is feasible to create

uniform regulations for DPR

• Expert Panel recommended 6 topics

for further research DPR DPR

E X P E R T P A N E L F I N A L R E P O R T

Evaluation of the Feasibility

• f Developing Uniform

Water Recycling Criteria for Direct Potable Reuse

California State Water Resources Control Board

State Water Board Conclusions on DPR

• DDW concurred on feasibility of DPR
• More information on research topics needed

before regulations could be written

• AB 574 requires DPR regulations by 2023

DPR DPR

INVESTIGATION ON THE FEASIBILITY OF DEVELOPING UNIFORM WATER RECYCLING CRITERIA

FOR DIRECT POTABLE REUSE STATE WATER RESOURCES CONTROL BOARD Report to the Legislature December 2016 In Compliance with Water Code Section 13563

STATE OF CALIFORNIA Edmund G. Brown Jr., Governor CALIFORNIA ENVIRONMENTAL PROTECTION AGENCY Matthew Rodriquez, Secretary STATE WATER RESOURCES CONTROL BOARD P.O. Box 100 Sacramento, CA 95812 Homepage: http://www.waterboards.ca.gov

INVESTIGATION ON THE FEASIBILITY OF DEVELOPING UNIFORM WATER RECYCLING CRITERIA

FOR DIRECT POTABLE REUSE STATE WATER RESOURCES CONTROL BOARD Report to the Legislature December 2016 In Compliance with Water Code Section 13563

STATE OF CALIFORNIA Edmund G. Brown Jr., Governor CALIFORNIA ENVIRONMENTAL PROTECTION AGENCY Matthew Rodriquez, Secretary STATE WATER RESOURCES CONTROL BOARD P.O. Box 100 Sacramento, CA 95812 Homepage: http://www.waterboards.ca.gov

“The use of recycled water for DPR has great potential but it presents very real scientific and technical challenges that must be addressed to ensure the public’s health is reliably protected at all times.” – SWRCB 2016 11 12

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13

Potable Reuse In California

Pathogens

Giardia

Chemicals

Research Related to Public Health Protection

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Source Control Outbreak Monitoring Quantitative Microbial Risk Assessment Pathogen Monitoring Control of Chemical Peaks Non‐Targeted Analysis and Low Molecular Weight Compounds

Pathogens Chemicals

Research Related to Public Health Protection

SWB DPR Research Projects (1 – 5 are WRF Grant projects)

16

• 1. Develop Probabilistic Analysis Tools for DDW to Assess Treatment Performance

and Quantitative Microbial Risk

• 2. Collect Pathogen Data in Untreated Wastewater
• 3. Investigate Feasibility of Collecting Pathogens in Wastewater During Outbreaks
• 4. Evaluate Options to Reduce Potential Chemical Peaks
• 5. Investigate Feasibility of Analytical Methods for Non‐Targeted Analysis of

Recycled Water with focus on Low Molecular Weight Compounds

• 6. Establish an enhanced source control program

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DPR‐1 Plant Reliability and Quantitative Microbial Risk Assessment & DPR‐2 Pathogen Monitoring in Raw Wastewater

17

• Dr. Brian Pecson

DPR Pathogen Risk and Treatment

Drinking water

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DPR Pathogen Risk and Treatment

Drinking water 10-4 infections per person per year

Risk Thres Risk Threshold

High Very Low

Pathogen Concentration

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water 10-4 infections per person per year

Risk Thres Risk Threshold 19 20

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High Very Low

Pathogen Concentration

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water 10-4 infections per person per year

Risk Thres Risk Threshold

Risk Risk

High Very Low

Pathogen Concentration

Raw wastewater

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water

Risk Risk

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High Very Low

Pathogen Concentration

Raw wastewater

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water

Treatment eatment Requirements irements

10-log

Risk Risk

High Very Low

Pathogen Concentration

Raw wastewater

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water

Treatment eatment Requirements irements

10-log

Risk Risk Pathogen Pathogen Concentrations Concentrations

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High Very Low

Pathogen Concentration

Raw wastewater

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water

Treatment eatment Requirements irements

10-log

Risk Risk

11-log

Pathogen Pathogen Concentrations Concentrations

High Very Low

Pathogen Concentration

Raw wastewater

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water

Treatment eatment Requirements irements

10-log

Risk Risk

11-log 12-log

Pathogen Pathogen Concentrations Concentrations

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High Very Low

Pathogen Concentration

Raw wastewater

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water

Treatment eatment Requirements irements

10-log

Risk Risk

11-log 12-log

Pathogen Pathogen Concentrations Concentrations DPR-1: Implementation

• f Probabilistic

Treatment Train Performance and QMRA

High Very Low

Pathogen Concentration

Raw wastewater

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water

Treatment eatment Requirements irements

10-log

Risk Risk

11-log 12-log

Pathogen Pathogen Concentrations Concentrations DPR-1: Implementation

• f Probabilistic

Treatment Train Performance and QMRA DPR-2: Pathogen Monitoring

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DPR‐1 TWG and Research Team

Charl Charles Haas s Haas

Drexel University

Nick As Ashbolt hbolt

University of Alberta

There Theresa Slifk Slifko

Metropolitan Water District

Brian P ian Pecson (

• n (chair)

hair)

Trussell Technologies

Techn chnical W cal Workin rking Gr Group

• up

Re Research T Team

Dan Gerrit Dan Gerrity

UNLV

Edmun Edmund Se Seto

University of Washington

TWG is not developing DPR treatment criteria…

• Development of guidelines for evaluating DPR

facility treatment performance (Goal #1)

• Use of QMRA to assess the level of treatment

needed to achieve risk‐based targets (Goal #2)

• TWG and Research Team are developing tools
• The tools provide DDW with a consistent approach

vetted by a team of experts

”So what’s this? I asked for a hammer! A hammer! This is a crescent wrench! … Well, maybe it’s a hammer.… Damn these stone tools.”

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1.

• 1. E

Expo posur sure Asses Assessment nt

Steps in QMRA

Raw wastewater Treatment Drinking water levels Drinking water consumption Exposure

1.

• 1. E

Expo posur sure Asses Assessment nt 2.

• 2. Dose-R

Dose-Res espon ponse

Steps in QMRA

Raw wastewater Treatment Drinking water levels Drinking water consumption Exposure Dose-response

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1.

• 1. E

Expo posur sure Asses Assessment nt 2.

• 2. Dose-R

Dose-Res espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Steps in QMRA

Raw wastewater Treatment Drinking water levels Drinking water consumption Exposure Dose-response Risk

1.

• 1. E

Expo posur sure Asses Assessment nt 2.

• 2. Dose-R

Dose-Res espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Steps in QMRA

Raw wastewater Treatment Drinking water levels Drinking water consumption Exposure Dose-response Risk

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1.

• 1. E

Expo posur sure Asses Assessment nt

• 2. Dose-R
• 2. Dose-Res

espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Multiple Decision Points in the Process

Ra Raw w wa wastewater er

Treatment Drinking water levels Drinking water consumption Exposure Dose-response Risk What pathogens?

What enumera What enumeration me methods thods?

What data sets should we use? Do we need new data? How do we use non-culture-based data? Culture Microscopy Molecular

1.

• 1. E

Expo posur sure Asses Assessment nt

• 2. Dose-R
• 2. Dose-Res

espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Multiple Decision Points in the Process

Raw wastewater

Tr Treatment

Drinking water levels Drinking water consumption Exposure Dose-response Risk How d do w we q quantify p performance? Use surrogates or direct pathogen measurements? What data should we use? Should w

• uld we us

use s site-spe

• specif

cific p c perfor

• rman

mance d e distributio butions? s? Rang nges f es from t the l e liter erat ature? e? What frequency of data collection?

35 36

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1.

• 1. E

Expo posur sure Asses Assessment nt

• 2. Dose-R
• 2. Dose-Res

espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Multiple Decision Points in the Process

Raw wastewater Treatment

Drink Drinking wa water l leve vels ls

Drinking water consumption Exposure Dose-response Risk

LRV

Influent Concentration Effluent Concentration

1.

• 1. E

Expo posur sure Asses Assessment nt

• 2. Dose-R
• 2. Dose-Res

espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Multiple Decision Points in the Process

Raw wastewater Treatment Drinking water levels

Drink Drinking w water r consu consumption

Exposure Dose-response Risk Ho How muc much water do peo do people dri drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Does i es it matt tter er? H ? How m w much does i es it matt tter er?

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1.

• 1. E

Expo posur sure Asses Assessment nt

• 2. Dose-R
• 2. Dose-Res

espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Multiple Decision Points in the Process

Raw wastewater Treatment Drinking water levels

Exposu Exposure re

Dose-response Risk Drinking water consumption

1.

• 1. E

Expo posur sure Asses Assessment nt

• 2. Dose-R
• 2. Dose-Res

espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Multiple Decision Points in the Process

Raw wastewater Treatment Drinking water levels Drinking water consumption Exposure

Dose Dose-respo ponse

Risk Whi Which D-R D-R func functions t to use? use? What about molecular data?

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1.

• 1. E

Expo posur sure Asses Assessment nt 2.

• 2. Dose-R

Dose-Res espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

Multiple Decision Points in the Process

Raw wastewater Treatment Drinking water levels Drinking water consumption Exposure Dose-response

Risk Risk

Annual risk? Daily risk? What risk framework? Wha What le level of

• f risk

risk? 1 10-4

• 4? 1

? 10-6

• 6?

1.

• 1. E

Expo posur sure Asses Assessment nt 2.

• 2. Dose-R

Dose-Res espon ponse

• 3. Risk
• 3. Risk

Charact aracterization rization

There are a lot of decisions….

Raw wastewater Treatment Drinking water levels Drinking water consumption Exposure Dose-response

Risk Risk

What pathogens? What enumeration methods? What data sets should we use? Do we need new data? How do we use non-culture-based data? What pathogens? What enumeration methods? What data sets should we use? Do we need new data? How do we use non-culture-based data? What pathogens? What enumeration methods? What data sets should we use? Do we need new data? How do we use non-culture-based data? What pathogens? What enumeration methods? What data sets should we use? Do we need new data? How do we use non-culture-based data? How do we quantify performance? Use surrogates or direct pathogen measurements? What data should we use? Should we use site-specific performance distributions? Ranges from the literature? How do we quantify performance? Use surrogates or direct pathogen measurements? What data should we use? Should we use site-specific performance distributions? Ranges from the literature? How do we quantify performance? Use surrogates or direct pathogen measurements? What data should we use? Should we use site-specific performance distributions? Ranges from the literature? How do we quantify performance? Use surrogates or direct pathogen measurements? What data should we use? Should we use site-specific performance distributions? Ranges from the literature? How do we quantify performance? Use surrogates or direct pathogen measurements? What data should we use? Should we use site-specific performance distributions? Ranges from the literature? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Does it matter? How much does it matter? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Does it matter? How much does it matter? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Does it matter? How much does it matter? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Does it matter? How much does it matter? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Does it matter? How much does it matter? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data? What pathogens? What enumeration methods? What data sets should we use? Do we need new data? How do we quantify performance? What data should we use? How do we quantify performance? What data should we use? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data? What pathogens? What enumeration methods? Should we use site-specific performance distributions? Ranges from the literature? How do we quantify performance? Use surrogates or direct pathogen measurements? What data should we use? What data should we use? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data? What pathogens? What enumeration methods? Should we use site-specific performance distributions? Ranges from the literature? How do we quantify performance? Use surrogates or direct pathogen measurements? What data should we use? What data should we use? How much water do people drink? Estimate with a distribution? Which one? Use a point estimate? Which one? Which D-R functions to use? What about molecular data? Which D-R functions to use? What about molecular data?

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Task 1: Literature Review – Major Sections

• Raw wastewater pathogen concentrations
• Treatment Train Performance
• QMRA
• Linking Performance and QMRA
• General approach:
• Provide discussion on the topic
• Give TWG recommendation on how to proceed

Task 1: Literature Review – Major Sections

• Raw wastewater pathogen concentrations

Which pathogens? Which enumeration methods?

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Evaluating Treatment Train Performance

LRV Credits for Cryptosporidium

45

Evaluating Treatment Train Performance

46

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Evaluating Treatment Train Performance

This is a Probabilistic Assessment of Treatment Train Performance Peppermint Patty

• r

Patty, P .

47

Task 1: Literature Review – Major Sections

• QMRA

Drinking water consumption

1 L? 2.5 L? Published distributions?

Dose-response

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Tools can be used together to develop DPR criteria

12 / 10 / 10 12 / 10 / 10

Treatment Requirements

Crypto

Performance Evaluation

0.1 1 5 10 20 30 50 70 80 90 95 99 99.9 1E-15 1E-14 1E-13 1E-12 1E-11 1E-10 1E-09 1E-08 1E-07 1E-06 1E-05 1E-04 1E-03 1E-02 Annual risk of Cryptosporidium infection Percent less than or equal to .9 Baseline risk - no failures

QMRA

Tools can be used together to develop DPR criteria

Crypto

0.1 1 5 10 20 30 50 70 80 90 95 99 99.9 1E-15 1E-14 1E-13 1E-12 1E-11 1E-10 1E-09 1E-08 1E-07 1E-06 1E-05 1E-04 1E-03 1E-02 Annual risk of Cryptosporidium infection Percent less than or equal to .9 Baseline risk - no failures

Performance Evaluation QMRA

If we shift the treatment requirements…. …what is the impact on public health?

12 / 10 / 10 12 / 10 / 10 13 / 11 / 11 13 / 11 / 11 14 / 12 / 12 14 / 12 / 12

Treatment Requirements 49 50

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Task 1: Specifications and Scope of Work

July 2019 August 2019

Remaining Project Schedule

• Task 2: Develop Performance and QMRA Tools
• Draft PATTP and QMRA tools

April 2020

• Final PATTP and QMRA tools

June 2020

• Training workshop with State Board

June 2020

• Task 3: Final Report

Fall 2020

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Approach used to calculate treatment requirements

V / G / C V / G / C 4 / 3 / 2 4 / 3 / 2

Surface Water Treatment Rule Indirect Potable Reuse Regulations

12 / 12 / 10 / / 10

Approach used to calculate treatment requirements

V / G / C V / G / C 4 / 3 / 2 4 / 3 / 2

Surface Water Treatment Rule Indirect Potable Reuse Regulations

12 / 12 / 10 / / 10

Raw Water Augmentation Treated Water Augmentation

? / ? / ? ? / ? / ? ? / ? / ? ? / ? / ?

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Importance of Research for DPR

• We set risk‐based goals for drinking water
• DPR should provide the same level of protection
• Tools allow DDW to quantify public health protection provided by

different treatment requirements

• Informs DPR regulations by providing insight into treatment criteria

High Very Low

Pathogen Concentration

Raw wastewater

DPR Pathogen Risk and Treatment

105 10-5 1 Drinking water

Treatment eatment Requirements irements

10-log

Risk Risk

11-log 12-log

Pathogen Pathogen Concentrations Concentrations DPR-2: Pathogen Monitoring

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Study Background: CA DDW Expert Panel Report

“The State Water Board will work…to include monitoring requirements for pathogens in the raw wastewater feeding potable reuse systems, using improved methods that allow for better characterization and improved precision of concentrations of pathogens, to provide more complete information on concentrations and their variability” (DDW, 2016)

E X P E R T P A N E L F I N A L R E P O R T

Evaluation of the Feasibility

• f Developing Uniform

Water Recycling Criteria for Direct Potable Reuse

California State Water Resources Control Board

INVESTIGATION ON THE FEASIBILITY OF DEVELOPING UNIFORM WATER RECYCLING CRITERIA

F O R D I R E C T P O T A B L E R E U S E S T A T E W A T E R R E S O U R C E S C O N T R O L B O A R D R e p

• r

t t

• t

h e L e g i s l a t u r e D e c e m b e r 2 1 6 I n C

• m

p l i a n c e w i t h W a t e r C

• d

e S e c t i

• n

1 3 5 6 3

Pathogen Monitoring TWG and Project Goals

There eresa S a Slifk ifko (ch (chair) ir)

Metropolitan Water District

Brian Brian P Pecs cson

• n

Trussell Technologies

Kar Kara Nel Nelson

• n

UC, Berkeley

Chann Channah R Rock ck

University of Arizona

Menu Leddy Menu Leddy

Techn chnical W cal Workin rking Gr Group

• up
• Goals:
• Develop recommendations for the collection and analysis of pathogen data

in raw wastewater

• Conduct pathogen monitoring of raw wastewater as inputs to DPR‐1

George DiG George DiGiovan anni

Metropolitan Water District

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Review of DPR‐2 Scope

• Scope
• Task 1: Literature and methods review
• Task 2: Develop monitoring plan and RFQ
• Task 3: Conduct pathogen monitoring campaign
• Task 4: Data analysis and preparation of guidance

Task 1 – Literature and Methods Review

TWG R G Recommend commendations f ations for Pa r Pathog thogens a ens and E Enumeration Met umeration Methods

• ds

Virus Virus Enterovirus (culture and molecular) Adenovirus (culture and molecular) Norovirus (molecular) Bacteriophage (culture and molecular) Protozoa

• zoa

Giardia (microscopy) Cryptosporidium (microscopy)

• Includes historical drinking water and IPR pathogens
• Includes additional viral pathogens and indicators
• Uses both traditional (non‐molecular) and molecular enumeration methods

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Task 1 – Literature and Methods Review

• Completed literature review to support sampling plan and RFP
• Industry needs more pathogen data
• Current “standard”: Rose et al. 2004
• Six facilities with 5‐6 samples
• Mostly small utilities outside CA

0.01 0.1 1 5 10 20 30 50 70 80 90 95 99 99.9 99.99

0.01 0.1 1 10 100 1000 10000 100000

Giardia cysts (#/L)

Percent of Values Less Than or Equal to Indicated Value

Rose 2004 Raw Rose 2004 Secondary

Task 1 – Literature and Methods Review

• Completed literature review to support sampling plan and RFP
• Industry needs more pathogen data
• Current “standard”: Rose et al. 2004
• Six facilities with 5‐6 samples
• Mostly small utilities outside CA
• IPR’s 12/10/10 based on highest

concentrations in the literature

0.01 0.1 1 5 10 20 30 50 70 80 90 95 99 99.9 99.99

0.01 0.1 1 10 100 1000 10000 100000

Giardia cysts (#/L)

Percent of Values Less Than or Equal to Indicated Value

Rose 2004 Raw Rose 2004 Secondary

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Industry needs high quality pathogen data

Method 1623: Cryptosporidium and Giardia in Water by Filtration/IMS/FA December 2005

• Drinking water methods pose challenges for wastewater matrices

Industry needs high quality pathogen data

• Previous studies have not reported recoveries
• QA/QC is important for high‐quality data

Giardia counted: 2 Colorseed counted: 1 Colorseed added: 10 Recovery percentage: 10% Ac Actual al Giardia in sample: 2 x 10 = 20

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Task 2 –Methods Pre‐Testing: Cryptosporidium

Filtration Centrifugation

100 mL 500 mL 1000 mL

Concentration Step Sample Volume

Task 2 –Methods Pre‐Testing: Cryptosporidium

Filtration Centrifugation

100 mL 500 mL 1000 mL

1 mL 2 mL 4 mL

Concentration Step Sample Volume Pellet Volume

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Task 2 –Methods Pre‐Testing: Cryptosporidium

Filtration Centrifugation

100 mL 500 mL 1000 mL

1 mL 2 mL 4 mL

ND ND (<10-12) ND ND (<3-6) 5-9 5-9

Concentration Step Sample Volume Pellet Volume Concentration (oocysts/L)

Task 2 –Methods Pre‐Testing: Cryptosporidium

Filtration Centrifugation

100 mL 500 mL 1000 mL

1 mL 2 mL 4 mL

ND ND (<10-12) ND ND (<3-6) 5-9 5-9 26% 26% 6-1 6-18

Concentration Step Sample Volume Pellet Volume Concentration (oocysts/L) Average Recovery Corrected Conc. (oocysts/L)

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Task 2 –Methods Pre‐Testing: Cryptosporidium

Filtration Centrifugation

100 mL 500 mL 1000 mL

1 mL 2 mL 4 mL

ND ND (<10-12) ND ND (<3-6) 5-9 5-9 26% 26% 18 18-32

• 32

30% 30% 6-1 6-18 40- 40-55 55

Concentration Step Sample Volume Pellet Volume Concentration (oocysts/L) Average Recovery Corrected Conc. (oocysts/L)

Sit Site 1 1 Sit Site 2 2

Task 2 –Methods Pre‐Testing: Cryptosporidium

Filtration Centrifugation

100 mL 500 mL 1000 mL

1 mL 2 mL 4 mL

ND ND (<10-12) ND ND (<3-6) 5-9 5-9 26% 26% 18 18-32

• 32

30% 30% 6-1 6-18 40- 40-55 55

Concentration Step Sample Volume Pellet Volume Concentration (oocysts/L) Average Recovery Corrected Conc. (oocysts/L) Also suitable for Giardia cysts

Sit Site 1 1 Sit Site 2 2 69 70

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Task 2 –Methods Pre‐Testing: Cryptosporidium

Filtration Cent Centrifuga gation

• n

100 mL 500 mL 1000 mL 000 mL

1 mL 2 mL 4 mL 4 mL

Concentration Step Sample Volume Pellet Volume

Task 2 –RFQ and Selection of Laboratories

July 2019

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Task 2 –RFQ and Selection of Laboratories

Lead lab Methods Development Lab

Task 2 –Full‐Scale Campaign

Five facilities 24 samples 120-point datasets for:

• 3 pathogenic viruses
• 2 pathogenic protozoa
• 1 viral indicator

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Next Steps

• Task 3: Conduct pathogen monitoring campaign
• Methods optimization for 5 wastewaters
• Demonstration of capability
• Full‐scale campaign until January 2021 including two winters
• Task 4: Analyze data and develop recommendations

Wa Walt J Jaku kubowski

QA/QC

Importance of Research for DPR

• Raw wastewater pathogen concentrations a key input for evaluations of DPR

in California

• Industry does not have sufficient high‐quality pathogen data for regulatory

development

• New SOPs will address the limitations of previous monitoring efforts
• Provides industry with the largest dataset of raw pathogen concentrations
• Data from DPR‐2 will feed into evaluation in DPR‐1 (Treatment and QMRA)

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DPR‐4 Identification and Control of Chemical Peaks

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• Drs. Jean Debroux and Shane

Trussell

DPR‐4: Treatment for Averaging Potential Chemical Peaks

• Full advanced

treatment (MF/RO/UV‐ AOP) is a highly effective treatment train employed today for groundwater recharge

• Water quality

excursions have been

• bserved

Acetone

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Project Scope

• Task 1 – Literature Review
• Task 2 – Case Study Report
• Task 3 – Experimentation to Address Knowledge Gaps

Project Schedule

Project Initiation December 1, 2018 Task 1 – Literature Review May 31, 2019 Task 2 – Case Study Report July 31, 2019 Task 3 – Experimentation January 31, 2020 Final Report March 31, 2020

What is a chemical peak?

• Diurnal and process‐related TOC baseline variations
• Outliers

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Defining a chemical peak

• Peak height – must exceed baseline

threshold

• Due to outliers, non‐normal distribution
• All data used
• Baseline Threshold = Q3 + 1.5 * IQR, where

IQR = Q3‐ Q1

• Peak width – Due to non‐plug flow

processes and recycle flows in WWTP, an instantaneous illicit discharge results in a peak width of hours to days

• On‐line data every 15 minutes

Baseline threshold Peak width

Example excursions from baseline

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What chemicals can pass through FAT?

Chemical Family Sub‐group Good (>90%) Intermediate (50‐90%) Poor (<50%) VOCs Solvents and Industrial Compounds Ethers Halobenzenes; 1,1,2‐TCE Nitriles; Haloalkenes Haloalkanes CCl4; Ethanes with 3‐4 Cl atoms; Most C4+ haloalkanes Some C1‐C3 haloalkanes C1‐C2 haloalkanes with 1‐2 halogen atoms Alkylbenzenes C10+ C6‐C9 Pesticides/ Herbicides 1,2,3‐TCP MITC LMW Oxygenated Compounds Alcohols Branched C4+ alcohols Isopropyl alcohol; Most unbranched alcohols Methanol; Ethanol; Aldehydes, Ketones Methyl isobutyl ketone (MIBK) Acetone; Most Ketones Formaldehyde; Most Aldehydes PPCPs Flame Retardants Chlorophosphates; PFAS Pharmaceuticals Steroids; β‐blockers; NSAIDs; X‐ray Contrast Media DBPs Nitrosamines C4+ nitrosamines; NMOR NDMA; NDEA Halogenated DBPs HAAs HANs THMs

Summary of RO rejection of organic compounds and chemical families

References: Howe 2019, Zeng 2016, Rodriguez 2011, Snyder 2007, Kiso 2011, Tackaert 2019, Fujioka 2012; Doederer 2014

Predicted removal of organic compounds via AOP

Notes: 1. High removal in UV/AOP systems References: Drewes 2008, Howe 2019, Ahmed 2017, Drewes 2006, Buxton 1988, Swancutt 2010

Organic compounds poorly removed by FAT

Family Compounds poorly removed by FAT VOCs LMW haloalkanes LMW alcohols, aldehydes, ketones Acetonitrile MITC DBPs THMs Family Greater than 1,4‐dioxane Less than 1,4‐dioxane VOCs Haloalkenes Halobenzenes Alkylbenzenes C4+ Alcohols C4+ Aldehydes C6+ Ketones Acrylonitrile C1‐C3 Haloalkanes C1‐C3 Alcohols C1‐C3 Aldehydes C3‐C5 Ketones Acetonitrile MITC PPCPs Most pharmaceuticals Flame Retardants DBPs Nitrosamines1 THMs

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Potential Treatment/Blending Technologies

Ozone/BAC Pre‐treatment Air Stripping Activated Carbon Additional RO/AOP Treatment Blending

Case Studies

• Compare elements of source control measures,

experiences, monitoring and detection of chemical peaks

• Orange County Water District Ground Water Replenishment

System

• Singapore Public Utilities Board
• City of San Diego North City Pure Water Demonstration

Facility

• Compare strategies for averaging Chemical Peaks

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TOC and Acetone grab sample results during 2013 GWRS Acetone event

Sample Date Sample Location EPA 524.2 Acetone Theoretical TOC from Acetone1 EPA 415.3 TOC Baseline TOC2 Acetone Contribution to Elevated TOC3 2/18/2013 6:00AM RO Feed 1,940 µg/L 1.2 mg/L 9.39 mg/L ~ 8.0 mg/L ~ 86% RO Permeate 1,410 µg/L 0.9 mg/L 1.18 mg/L ~ 0.025 mg/L ~ 78%

1 – acetone carbon contribution is approximately 62% 2 – from online TOC data preceding the acetone event 3 – Baseline TOC subtracted from EPA 415.3 TOC used to calculate % acetone that contributed to elevated TOC (e.g., for RO feed → 1.2 mg/L / (9.39 mg/L – 8.0 mg/L) = 86%

OCWD TOC monitoring October 24, 2018 acetone event

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Singapore PUB Singapore PUB

List of Prohibited Organic Compounds (PUB)

1,2,4‐Trimethylbenzene Furan Octane 1,1,1‐Trichloroethane Heptane Polybrominated diphenyl ether 1,1,2‐Trichloroethane Hexane Styrene Benzene Isobutanol Tetra‐chloromethane Decane Isopropyl ether Tetra‐chloroethylene Diethyl ether Methyl ethyl ketone THF (Tetrahydrofuran) Dimethyl sulphide Methyl isobutyl ketone Toluene Dimethyl sulphoxide Methyl tert‐butyl‐ether Trichloroethylene DMF (N,N‐Dimethylformamide) Methylene chloride Turpentine Ethylbenzene Nonane Xylene (o,m,p) 89 90

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Singapore PUB VOC Monitoring in the Sewershed San Diego Pure Water Demonstration Facility Chemical Challenge Testing

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Discharge Volume Impact of Sewershed Size

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Chemical Discharge Duration

Treatment Robustness for Averaging Chemical Peaks

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Engineered Buffer with Residence up to 24 Hours Engineered Buffer with Residence up to 60 Days

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How will online TOC analyzers be used?

• Advanced oxidation reactions to mineralize organic

carbon in sample (UV/persulfate and O3/hydroxide)

• Expert panel expressed concern that highly volatile
• rganics might not be captured with online TOC

Experimental matrix

*OH rate constant (k*OH, L/Mol*s) Henry's Law Constant (Hyc)

HYC > 1.0 0.1 < HYC < 1.0 0.01 < HYC < 0.1

k*OH >1 x 109

Vinyl chloride Toluene MIBK 1x 108 < k*OH < 1x109 Acetone

1x 107 < k*OH < 1 x 108

Methylene chloride Principal Investigator Eric Dickenson, PhD, PE 99 100

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DPR‐4:Treatment for Averaging Potential Chemical Peaks

Thank you to: Research Team: Stephen Timko, PhD, Rodrigo Tackaert, PhD, Aleks Pisarenko, PhD TWG: Jim Crook, PhD and Adam Olivieri, Dr. PH PAC: Mehul Patel, PE Guidance: SWRCB, Water Research Foundation, California DDW

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Time for Questions: Facilitated by Dr. Jim Crook

Open and close your control panel Join audio:

• Choose Mic & Speakers to use VoIP
• Choose Telephone and dial using

the information provided Submit questions and comments via the Questions panel Note: Today’s presentation is being recorded and will be available shortly after today’s webcast

Your Participation

Thank You!

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