Blending and Wet Weather Operations: An Engineering ...€¦ · 19.06.2014 · Recent case studies of wet weather flow management ... Blending and Wet Weather Operations: An Engineering

Experts Forum on Public Health Impacts of Wet Weather Blending

Fairfax, Virginia | June 19-20, 2014

Blending and Wet Weather Operations: An Engineering Perspective

Engineering Experts Panel Julian Sandino Dave Wagner Jim Fitzpatrick

Don Gray Kati Bell

Blending and Wet Weather Operations: An Engineering Perspective

• Executive summary • The challenge of managing wet weather flows in POTWs • Wet weather flow management options • Recent case studies of wet weather flow management • Recent guidance documents • Summary points

Aspects of Public Health…… June 19, 2014

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Blending and Wet Weather Operations: An Engineering Perspective |

Public Health

Water

Quality

Dry Weather

Base-flow

Wet Weather

Run-off Overflow

Quantity

Drought Flood

Transportation Electricity

Bypass Blending

X Y Z

* You are here………

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Executive Summary

• Wet weather events have a short duration and are infrequent. Risks tend to be acute, not chronic.

• Site specific variables result in site specific impacts and thus require site specific solutions.

• POTWs blended discharges may have a lesser impact than non-point source contributions.

• Reducing peak flows to POTWs to a level that allows for effective treatment by traditional biological processes alone may not always be practical.

• If needed, wet weather flows could be treated effectively by physical and/or chemical methods to address acute water quality concerns.

June 19, 2014 Blending and Wet Weather Operations: An Engineering Perspective |

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Wet-weather flows pose significantly different challenges to POTWs than normal

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Inflow

Infiltration

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We have good answers for some of the challenges…but still working on others!

The challenge of managing wet weather flows in POTWs

To make sure we share the same language… June 19, 2014

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Background diagram from: U.S. EPA, Sanitary Sewer Overflows and Peak Flows Listening Session, 2010

Publicly Owned Treatment Works (POTW)

“Secondary Treatment” can be these or any other combination of methods that meet standards in 40 CFR 133.

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“Secondary Treatment” ≠ 100% biological treatment and doesn’t have a precise scientific definition, especially for episodic wet-weather flows. Let’s use scientific terms in this forum.


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Blending ≠ overflows or bypasses

Background diagram from: U.S. EPA, Sanitary Sewer Overflows and Peak Flows Listening Session, 2010

CSO or

SSO

Bypasses

This forum is focused on wet-weather flows received at the WRRF and blended with effluent from biological treatment processes. Not pictured here.

Compared to normal dry-weather challenges, wet-weather flows pose:

• Receiving waters - significantly different set of drivers and risks • Receiving stream flows >>7Q10 low-flow criteria • Focus of water quality concerns shift:

• From chronic toxicity to acute toxicity • From chronic public health to acute public health

• Point sources are a much smaller contributor than non-point sources in most watersheds. In many cases point sources may be negligible compared to stream background.

• Influent characteristics - significantly different than normal design ranges

• More variability from POTW to POTW, no one-size-fits-all solutions


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The challenge of defining design influent flow rates…that change all the time!

• In dry weather, flows and loads are predictable and somewhat “static”

• Wet weather flows and loads: unpredictable and “dynamic”

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Example wet-weather hydrograph

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Wet weather flow rates peak much higher than conventional POTW design standards

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Lawrence, Kansas WWTP Wet-Weather Influent Flows

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LAWRENCE, KANSASWWTP WET-WEATHER INFLUENT FLOWS

• QPK > 5QAA not unusual…

• …even with sustainable programs for inflow and infiltration reduction

Much higher than 2 to 3QAA in conventional POTW design standards (Ten States, WEF MOP 8, etc.)


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TOLEDO, OHIOBAY VIEW WWTP WET-WEATHER INFLUENT FLOWS

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Wet weather flows tend to be intermittent and short duration events SPRINGFIELD, OHIO WWTPINFLUENT FLOW PROBABILITY CURVE

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Hourly Average Data (1/1/07 - 9/30/09)Daily Average Data (1/1/06 - 10/20/09)Historical Average (1/1/06 - 10/20/09)Average Design CapacityPeak Daily Average Design Capacity

• QPK ~ 5% of thetime or less

Peak wet-weather flows often considered “outliers” by POTW standards that optimize for continuous discharge

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Blending and Wet Weather Operations: An Engineering Perspective | U

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The challenge of defining design influent pollutant characteristics…also highly variable and unpredictable • Concentrations and loadings change during a storm…as

well as between storms!

• First flush: How big? When does it occur? For how long?

• Highly dependent upon antecedent weather and soil conditions, design and operational details of collection system, condition of collection system, etc.

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Example wet-weather pollutograph

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Wet weather flow influent concentrations tend to decrease rapidly after “first flush”

Lawrence, KS Wet Weather Influent TSSLAWRENCE, KANSASWET WEATHER EXCESS FLOW INFLUENT TSS • C << CAA after first flush

• Similar for both combinedand separate sewers

First-flush dynamics are much different than conventional POTW diurnal design and operation standards


CINCINNATI, OHIO CSO CHARACTERIZATION STUDY

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24-Nov-201029-Nov-201011-Dec-201030-Dec-201031-Dec-201018-Jan-20113-Aug-20114-Sep-2011Best FitTypical WWTP Design Standard

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Challenges defining treatment objectives

• Historically - Primary clarification equivalent + disinfection

• How best to define treatment objectives? • Indicator concentrations in effluent? • Which indicator? • Water quality-based or technology-based effluent

limits?

• On what time basis? • Event average? • Weekly average? • Monthly average?

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A simple static number is not likely to be reasonable or defensible.

Challenge of rate-payer investments that are sustainable

• Life-cycle costs, benefits, and risks

• Asset management principles

• Appropriate levels of service • Uncertain nature of wet-weather lends itself to

probabilistic and risk-based planning and management

• Triple bottom line • Sustainable return on investment

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Knowing the true risks and benefits is the first step toward making sustainable investments

Historically, conventional POTW design and operating standards

• Generally optimized for continuous collection, treatment and discharge

• Separate planning, standards and regulations have evolved for: • POTW collection system • POTW treatment facilities • Separate stormwater systems

Optimal wet-weather solutions require: •More holistic and integrated approach than dry-weather •More POTW-specific considerations. One size doesn’t fit all.


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Wet weather flow management options

Sustainable solutions require holistic and long-term approaches

• Goals • Reduce risks from overflows • Protect water quality

• Ongoing programs vs. “one & done” projects • I/I reduction • Condition assessments • Operations & maintenance • Renewal & rehabilitation • Performance monitoring

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Sustainable Wet-Weather Flow

Management

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Integrated planning to evaluate and prioritize these + non-point source control measures on a watershed basis.

Reducing peak flows through I/I reduction • Are your long-term I/I reduction

goals realistic? • Old sewers leak…new sewers will leak

when they get old • Private property and jurisdiction issues

• Mains and manholes (public) • Satellite systems (multijurisdictional) • Service laterals (private) • Building I/I sources (private)

Different answers for each watershed. Pilot programs help determine cost and effectiveness of different I/I reduction measures.

Inflow

Infiltration

Example wet-weather hydrograph

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Reducing peak flows through additional storage


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• Huge volumes required to eliminate overflows. Back-to-back storms and bigger storms than “design storm”.

• May still need additional treatment capacity to handle storage dewatering rates.

• Too much storage may be more detrimental to environment. • Stored wastes more difficult to treat than fresh wastes.

Septicity and hydrolysis during storage. • Longer duration of wet-weather discharges when receiving

stream flows have dropped and recreational use more likely. • Longer duration of dilute influent risks upset or inefficient

biological treatment. Especially for biological nutrient removal.

Dynamic modeling and comprehensive analysis required to optimize storage and treatment sizing. Toledo case study.

Maximizing use of existing treatment facilities


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Background diagram from: U.S. EPA, Sanitary Sewer Overflows and Peak Flows Listening Session, June 30, 2010

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Biological processes can handle some wet-weather flows, but have inherent risks and limitations

• Cold influent challenges - snowmelt, road salt

• More biological equipment and infrastructure won’t necessarily increase biological treatment…biomass quantity and quality affect capacity.

• First-flush and dilution beyond range of conventional POTW design standards

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• Protect your biomass

• Critical dry-weather treatment component

• Full recovery can take weeks

• Slow-growing nitrifiers, PAOs and higher life organisms for stable AS and BNR processes are particularly sensitive to wet-weather upsets U

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Don’t Upset Your Good Bugs!

Some WRRFs may be able to temporarily reconfigure activated sludge trains to “weather the storm” • Wet-weather step-feed or biomass

transfer.

• Reconfigures AS to contact stabilization mode (a.k.a. “biocontact”)

• Temporarily reduces clarifier solids loading rate

• Helps reduce washout potential

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Offline Biomass Storage

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Does not increase biological degradation of wet-weather influent

Temporary contact stabilization mode relies on physicochemical mechanisms

AerationTank

Contact Tank

Clarifier

WASRAS

INF EFF

• Flocculation, adsorption and clarification mechanisms predominantactivated sludge process under peak wet-weather flows.

• Minimal benefit from heterotrophic degradation, nitrification,denitrification, biological phosphorus removal during peak flows.Significant risk of biomass washout and upsets to these processes.

• Biological degradation of solids occurs after the peak flow passes.

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Good solids/liquid separation is still the key

Wet-weather flow blending June 19, 2014

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Effluent disinfection process and design depends upon water quality standards and other site-specifics U

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Providing auxiliary treatment capacity June 19, 2014

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Auxiliary

Auxiliary treatment process and design depends upon disinfection requirements and other site-specifics U

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Effluent disinfection alternatives

• Disinfection ≠ sterilization

• High-rate disinfection was one of five, high-priority technology categories to be verified under the EPA/NSF ETV Wet Weather Flow Technologies Pilot. • Radiation - includes UV light, pulsed light, and other

emerging electromagnetic processes. Currently, only UV technologies are viable.

• Chemical - include high-rate chemical disinfection by the use of chemical oxidants (e.g., chlorine, bromine, chlorine dioxide, ozone, peracetic acid, peroxide, etc.)

• Mixing - which is relevant to high-rate chemical disinfection includes inductive mixers and diffusers.

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Efficacy of ANY disinfection system depends on effluent quality • UV disinfection

• TSS concentration • Particle size distribution • UV transmittance

• Chemical oxidants • Overcoming competing oxidant demands (COD – not BOD) • Process control (e.g., chloramination versus free chlorination) • Residual oxidant management challenges including TRC/TRO

limits and dechlorination/quenching, disinfection by-products, whole effluent toxicity (WET)

• Design of disinfection system requires knowledge of: target organism, inactivation rate (N/N0) and WQ

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Many studies focus on disinfection of indicator organisms in wet weather flows

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Disinfectant doses required to meet 2002 U.S. EPA criteria for illness rate of 14 illnesses per 1,000 people in CSOs (Moffa et al., 2005)

Indicator Organism

5-min Chlorination

5-min Chlorine Dioxide

3-min Ozonation

5-sec UV

Fecal coliform 18 mg/L 6.3 mg/L 25 mg/L 110 mJ/cm2

E. coli 18 mg/L 6.6 mg/L 23 mg/L 100 mJ/cm2

Enterococcus spp. 22 mg/L 8.6 mg/L 20 mg/L 140 mJ/cm2

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• A few studies have focused on pathogen removal performance of wet-weather flows

• A few studies have used site-specific pathogen data for development of human health risk assessments

We are designing disinfection systems and are complying with indicator organisms…


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Engineering challenges of disinfection are NOT inactivating indicator organisms…

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Chlorine CT values (mg*min/L) for pathogens at 20C Inactivation Rate Free Chorine at pH 7.5 Chloramines at pH 8

Giardia cysts (EPA Disinfection Profiling and Benchmarking Guidance Manual, 1999)

2-log 33 735 3-log 37 1100

Viruses (Keegan, et al., 2012; Black, 2009 and Sirikanchana, 2008)

2-log 10 2318 3-log 13 3141 4-log 16 3965

E. coli (Taylor et al., 2000)

3-log 0.09 73

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CDC report (2009 – 10) indicates about half of the outbreaks were associated with cyanobacteria toxins

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296 of 1326 cases were untreated venues

Pathogen and risk characterization of wet weather flows

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• “Dry and wet weather risk assessment of human health impacts of disinfection versus no disinfection in the CAWS” (Geosyntec, 2008)

• Risks < 8 - 14 illnesses/1000 exposures (EPA guidelines in RWQC)

• Pathogens in waterway are attributed to non-WRP sources

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Pathogen characterization of wet weather flows - impact of blending

• “Impact of Wet-Weather Peak Flow Blending on Disinfection and Treatment: A Case Study at Three WWTPs” (Rukovets and Mitchell, 2010) • Pathogen removal is site specific; depends on operations • TSS and some pathogen/indicator concentrations are higher

during blending, compared to dry weather events • Microorganisms (indicators) are associated with TSS • No risk assessment conducted in this study

• “Characterizing the quality of effluent and other contributory sources during wet weather events” (Gray et al., 2009) • The study also addresses risk assessment

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Microbial characterization of wet weather flows - impact of auxiliary treatment

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• Disinfection efficacy depends on effluent WQ and providing auxiliary treatment demonstrates substantial benefits with respect to disinfection of indicators/pathogens • Lawrence, KS study; HRT performance is indistinguishable from

main process (bacteria) • Akron, OH study; EHRT provides removal of pathogens, and

disinfection on EHRT effluent is more efficient for bacteria • City of Toledo, OH study; high rate treatment provided better

microbial removal than AS, no difference after disinfection • Many others… • Auxiliary treatment and disinfection provides microbial

quality indistinguishable from main treatment process

Auxiliary treatment with equivalent of primary clarification

• Conventional standard = primary clarification + effluent disinfection

• Standard technology assumption for

blending • Decades of full-scale operations

• Long understood by water quality

profession to support CWA and codified secondary treatment requirements, when operated in parallel with biological treatment

• Presumption Approach of USEPA 1994 CSO Control Policy

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Clarification alternatives June 19, 2014

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Sedimentation Filtration Flotation 1. Conventional Clarifier 1. Shallow Granular Media

(Sand, Anthracite, etc.) 1. Dissolved Air

Flotation (DAF) 2. Vortex Separators (Swirl

Concentrators) 2. Deep Granular Media

(Sand, Anthracite, etc.)

3. Lamella Settlers 3. Microscreens

4. Chemically Enhanced Sedimentation 4. Floating Media

a. Conventional Clarifier 5. Cloth Media

b. Lamella Settler 6. Compressible Media -Fuzzy Filter™, FlexFilter™

c. Solids Contact / Sludge Recirculation

- DensaDeg®, CONTRAFAST® d. Microsand Ballasted

Flocculation - ACTIFLO®, RapiSand™

e. Magnetite Ballasted Flocculation

-CoMag™

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Understanding disinfection requirements and influent solids are keys to successful treatment of wet-weather flows

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Total Solids (TS)

Total Suspended Solids (TSS)

Non-settleable TSS (TSSnon)

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EHRT alternatives focus on removing TSSnon

Summary of clarification technologies June 19, 2014

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Typical Range for Conventional Primary Clarifiers

m/h0 2 4 6 8 10 gpm/ft2

Typical Range for High-RateTreatment (HRT) is up to146 m/h (60 gpm/ft2)

Enhanced HRT (EHRT)

Figure 14.1 from Wet Weather Design and Operation in Water Resource Recovery Facilities, pending 2014 publication by WEF

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Starting to see some stormwater treatment with HRT and EHRT • Stormwater applications include:

• Vortex separators and screens for settleables and floatables • Chitosan enhanced sand filters treating stormwater runoff

from North Boeing Field, Seattle, WA • CMF + UV stormwater BMP treating Weracoba Creek in

Columbus, GA since 2007

• Can or should auxiliary treatment facilities also be used for stormwater treatment to provide higher level of pollutant removal than no stormwater treatment?

• Can or should controlled discharges of stormwater be allowed to help maintain sewers? Solids flushing, decreased odors and corrosion.

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Innovative use of existing infrastructure. Maximize use of WRRF capacity.

Recent case studies of wet weather flow management

We only have time now for a few, but data on blending also includes:

• Blending practiced in the U.S. ever since biological treatment became standard for dry-weather flows. DMRs record effluent monitoring results for indicator bacteria.

• What about blending practiced by WWTPs outside the U.S.? Europe, New Zealand, Australia, others?

• Draft Summary of Blending Practices and the Discharge of Pollutants for Different Blending Scenarios (USEPA/Tetra Tech, 2014)


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Data on receiving water quality and non-point source contributions during wet-weather discharges is more scarce.

Gray et al. (2009)

WATER ENVIRONMENT RESEARCH FOUNDATION

Wet Weather Effluent Blending Project

WERF Project No. 03-CTS-12PP

EBMUD Main Wastewater Treatment Plant

Blending at the EBMUD Main WWTP

EBMUD Main WWTP Blending at Peak Flow = 415 MGD

IPS

Wet WeatherStorage Basin

GritRemoval

PrimaryTreatment

SecondaryTreatment

FinalEffluent

Primary Effluent Diversion Channel

Influent

168 MGD

152 MGD

320 MGD415 MGD

95 MGD

320 MGD

Primary Clarifiers

Biological Treatment

Primary Effluent Channel

Project Approach

• Conduct field sampling compare final effluent and receiving water quality during blending to baseline conditions through field sampling — dry weather and wet weather non-blending (i.e., peak biological treatment)

• Use computer model to estimate pathogen and indicator organism concentrations in SF Bay under wet weather non-blending and blending scenarios

• Estimate incremental risk to public health, if any, attributable to blending practices

• Evaluate alternatives to blending practices and estimate incremental benefits to public health

• Prepare a guidance manual to assist other interested parties in conducting similar evaluations in their own area

Field Sampling Locations and Analysis

• Primary effluent, Final effluent – single grabs – Giardia, Cryptosporidium

– Adenovirus, Enterovirus

– Fecal coliform, E. coli, enterococcus, male specific coliphage

– cBOD5, TSS, VOCs, metals

• San Francisco Bay (3 locations) – Fecal coliform, E. coli, enterococcus, male specific

coliphage

– Limited Giardia and Cryptosporidium testing

In-plant Field Sampling Locations and Analysis at EBMUD MWWTP

Grab samples

Effluent PumpStation

TransitionStructure

Final Effluentfecal coliform/E. colienterococcusmale specific coliphageadenovirus, enterovirusnorovirus, rotavirusGiardia (enum., char.)Crypto (enum., infectiv.)cBOD5, TSSparticle size distribution

cBOD5, TSSVOCs, metals

Primary Effluent (prior to disinf.)fecal coliform/E. colienterococcusmale specific coliphageadenovirus, enterovirusGiardia (enum., characteriz.)Crypto (enum., infectivity)cBOD5/TSSVOCs, metalsparticle size distribution

Primary Effluent Diversion Channel

Primary Effluent Channel

Sec.Eff.

Disinfection

Disinfection

Sec.Inf.

SF Bay

Dechlorination

cBOD5, TSSVOCs, metals

Secondary Effluent (prior to disinfection)fecal coliform/E. colienterococcusmale specific coliphageadenovirus, enterovirusGiardia (enumeration, characteriz.)Crypto (enumeration, infectivity)cBOD5, TSSparticle size distribution

PlantInfluent

Plant Influentfecal coliform/E. colienterococcusmale specific coliphageadenovirus, enterovirusGiardia (enum., char.)Crypto (enum., infectiv.)cBOD5, TSS

Downstream of Blend Point(during blending only)fecal coliform/E. colienterococcusmale specific coliphageadenovirus, enterovirusGiardia (enum., characterization)Crypto (enum., infectivity)cBOD5, TSS

Disinfected Primary Effluent Channel

Bio. Bio.

Biological Effluent

-Blue highlights were added from Year 2 Field Sampling (EPA Phase II Funding) -VOCs (Volatile Organic Compounds) -TSS (Total Suspended Solids) -cBOD5 (5-day Carbonaceous Biochemical Oxygen Demand) -SF Bay (San Francisco Bay)

Field Sampling Events

• Completed 3 years field sampling, data allowed direct comparison ofblending to baseline conditions — dry weather and wet weather non-blending

Facility (Field

Test Site) CollectionSystem

Field Sampling Events Completed

Total

Dry Weather Wet Weather Non-blending Blending

Year 1

Year 2

Year 3

Total Year 1

Year 2

Year 3

Total Year 1

Year 2

Year 3

Total

EBMUD MWWTP

SSS 1 1 -- 2 2 2 3 7 4 1 2* 7 16

CCSF SEWPCP

CSS 1 -- -- 1 1 -- -- 1 5 -- -- 5 7

MMSD JIWWTP

CSS -- -- -- -- -- 0 1 1 -- 0 1 1 2

E/S WPCF

SSS -- -- -- -- -- 1 1 2 -- 0 0 0 2

Total 2 1 -- 3 3 3 5 11 9 1 3 13 27

Receiving Water Sampling at San Francisco Bay for EBMUD MWWTP

• Three Sampling Locations

– Outfall (midpoint of diffuser section)

– One nautical mile “Up-current”

– 1/2 nautical mile “Down-current”

• Up-current and down-current locations are dependent on tide direction

• Grab samples at each location during each sampling event

EBMUD MWWTP

Oakland

Alameda

San Francisco

Treasure Island

San Francisco

Bay Outfall

Up-current

Down-current

Receiving Water Sampling at San Francisco Bay @ Outfall, Upcurrent and Downcurrent

• fecal coliform • E. Coli • enterococcus • male specific coliphage • adenovirus • Giardia (enum., characterization) • Crypto(enum., infectivity) • In-situ measurements

(conductivity; temperature; depth at 0.5 ft interval)

EBMUD Field Sampling Event Details

Plant Flow Rates (MGD)

Year Event Type Date Influent Secondary1 1 DW No. 1 9/21/05 65 0 65 -- 0

2 WW Non-blend No. 1 1/14/06 135 0 135 -- 03 WW Non-blend No. 2 2/27/06 135 0 135 -- 04 Blend No. 1 3/6/06 210 42 168 0.25 20%5 Blend No. 2 3/25/06 215 65 150 0.43 30%6 Blend No. 3 3/29/06 180 30 150 0.20 17%7 Blend No. 4 4/3/06 200 40 160 0.25 20%

2 8 DW No. 2 12/4/06 65 0 65 -- 09 Blend No. 5 12/12/06 235 67 168 0.40 29%10 WW Non-blend No. 3 2/9/07 150 0 150 -- 011 WW Non-blend No. 4 2/10/07 168 0 168 -- 0

3 12 WW Non-blend No. 5 12/20/07 170 0 170 -- 0%13 Blend No. 6 (in-plant) 1/4/08 302 132 170 0.78 44%14 Blend No. 7 (in-plant) 1/25/08 286 118 168 0.70 41%15 WW Non-blend No. 6 1/26/08 164 0 164 -- 0%16 WW Non-blend No. 7 2/1/08 144 0 144 -- 0%

Diverted PE

Event No. Blend Ratio*

%Primary Effluent

Primary Effluent

Biological Effluent

DW = dry weather WW = wet weather * Blend Ratio = Ratio of Primary Effluent Flow (MGD) to Biological Effluent Flow (MGD)

Field Sampling Results at EBMUD MWWTP

Results similar between blending and non-blending events for Final Effluent

• Crypto and Crypto Infective • Enterovirus, Rotavirus • Fecal Coliform, E. Coli,

Enterococcus, Male Specific Coliphage

• Volatile organic compounds • Metals (calculated conc. for

blending events all below NPDES permit requirement)

Results higher during blending compared to non-blending events for Final Effluent

• Giardia Enumeration by ~ One Order of Magnitude

• Adenovirus (difference is not statistically significant)

• Norovirus GI and GII (non-quantitative, inconclusive)

• cBOD5 (33, 38 and 43 mg/L) and TSS (60, 62, and 89 mg/L) during blending events vs. less than 20 mg/L for non-blending events

Modeling Scenario

Modeling Period: Dec 1, 2005 to Jan 4, 2006, a 35–day period San Francisco Bay Modeling: Simulate relative water quality impacts of MWWTP blending practices on receiving water quality at the San Francisco Bay

Modeling Scenario

Modeling Flow

Input Pathogen Concentration for Bay Modeling (based on 3-yr field

sampling)

Pathogen Exponential Die-off Rate for Bay Modeling(1)

Bay Model Output

Non-blending Blending

Worst Case

Actual MWWTP final effluent flow rate (in 15-min interval)

Average conc. of non-blending events

2nd highest conc. measured for blending events

Lowest die-off rate based on literature review for seawater within the temperature range of 8 -18 0C(2)

Giardia: K = 0.45 day-1

Adenovirus: K = 0.054 day-1 (T99 = 85 days)

Simulated pathogen concentration for that 35-day period in 15-min interval at any location in San Francisco Bay

Geometric Mean Case

Same as above

Geometric mean conc. of non-blending events

Geometric mean conc. of blending events

Same as above Same as above

Note: (1). Die-off rate was discussed with PSC in an initial conference call; a subsequent conference call with PSC members who expressed interest; and it was reviewed by Charles Gerba. Ct = C0 * e (- K t)

(2). The temperature range was based on USGS data for San Francisco Bay during wet season from December to April.

Example: SF Bay Modeling Input and Output (Giardia, worst case)

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 2 4Dec2005 Jan2006

Trea

tmen

t Pla

nt F

low,

MG

D

0

50

100

150

200

250

300

350

COMPUTEDPlant Final Effluent Flow

NO BLENDINGWITH BLENDING

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 2 4Dec2005

Giar

dia

(Enu

m),

#/L

0

200

400

600

800

1,000

1,200

1,400

1,600

1,800

Giardia Concentration assumed for the Final Effluent Flow

NO BLENDINGWITH BLENDING

1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 2 4Dec2005

Giar

dia (E

num)

, #/L

5

10

15

20

25

30

35

40

45

Simulated Giardia Concentration at EBMUD Outfall

SF Bay Modeling Contour Results (worst case, Giardia,

at time of peak concentration, Dec 31, 2005)

Note the different concentration scales With Blending

No Blending

5000 ft

5000 ft

With Blending

No Blending

10,000 ft

10,000 ft

Crown Beach

Treasure Island

MWWTP Outfall

Aquatic Park

SF Bay Modeling Contour Results (worst case,

adenovirus, at time of peak concentration, Dec 31, 2005)

With Blending

No Blending

5000 ft

5000 ft

With Blending

No Blending

25,000 ft

25,000 ft

Results of Microbial Risk Assessment (Giardia, blending vs. non blending)

USEPA (1986) acceptable risk

level of 19 illnesses/1,000 swimmers at marine water

beaches

Worst Case Normal Case (one order of

magnitude higher)

(less than one order of magnitude higher)

Results of Microbial Risk Assessment (Giardia PI-negative)



beaches


magnitude higher)

(less than one order of magnitude higher)

Results of Microbial Risk Assessment (adenovirus)



beaches


magnitude higher) (less than one order of magnitude higher)

Lawrence, Kansas

Background and milestones

• 1974 – Wet-weather storage basin included with upgrades at WWTP.

• 1998 – Proactive sewer maintenance program

• 2003 – WWTP expansion and upgrade, including auxiliary wet-weather flow treatment facilities.

• Ongoing commitments and investments include: • Design for new 2.5-mgd WWTP with BNR and

additional 5-MG peak flow storage. • Additional I/I reduction initiatives • Adoption of Integrated Plan under MOU with KDHE

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Kaw River WWTP

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• 9-mgd dry weather

• 11-mgd annual average

• 16-mgd maximum monthly

• 65-mgd peak hourly

Kaw River WWTP Process Flow Diagram

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Summary of treatment from 2004 to 2014 • 36,432 MG treated through biological trains (98.2%

of total)

• 670 MG treated through HRC trains

• HRC discharged a total of 52 days in 10 years (1.4% of the time)

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Hydrographs from back-to-back auxiliary HRC runs during 7-day period in April/May 2009

CONSISTENTLY COMPLIANT EFFLUENT DISINFECTION

1

10

100

1,000

10,000

100,000Fe

cal C

olifo

rms

or E

. col

i(#/

100

mL)

Final Effluent (Grab)Ballasted Flocculation CCT Effluent (Grab)Activated Sludge CCT Effluent (Grab)NPDES Limit for Final Effluent (Monthly Geometric Mean)

E. coliFecal Coliforms

Fewer wet-weather excursions from HRC than from activated sludge train. 67 U

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Effluent coliform concentrations during auxiliary treatment < normal dry weather < upstream background

Suggests that public health risks from wet weather discharges are even lower than during normal dry weather operations. 68 U

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Collection system maintenance and WWTP capacity upgrades have resulted in elimination of vast majority of SSO

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One measure of success USE

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Toledo, Ohio

Auxiliary treatment is part of the solution


71

Auxiliary Treatment

Storage

Water Quality Model

SCADA

Sewer Separation

Hydraulic Model

Pumping

Main Plant Upgrades

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Background and milestones

• 1993 – Completed 20-MG in CSO storage tunnels

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• 2002 – Start of Toledo Waterways Initiative. 18-yr wet weather program to invest $521 million on three major areas:

1. Auxiliary wet weather storage and treatment to eliminate WWTP bypasses • 2007 – completed construction • 2009 – completed 2-yr performance study • 2011 – began pathogen study (ongoing)

2. Relief sewers and storage to eliminate SSO • Completed in 2013

3. Implement LTCP to reduce CSO • Complete by 2020

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Plus ongoing operation and maintenance of existing infrastructure

Comprehensive evaluation with dynamic modeling helped optimize storage and auxiliary treatment sizing

• Objectives • Biological treatment of 99.5% of influent volume in typical year • Auxiliary HRC to increase treatment capacity to 400 mgd • Meet existing permit limits

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• Results • Reduce WRF storage from 60

to 25 MG • First-flush capture • Lower duration of stress on

activated sludge train • Defer secondary clarifier

expansion

Dynamic modeling predicted compliance with all permit limits for 15 different maximum 7-day wet-weather scenarios. (Lyon, 2005)

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Dynamic model demonstrated better and more reliable effluent quality with smaller storage basin

Wet weather storage and auxiliary treatment at Bay View WRF

195-mgd Activated

Sludge Facilities

232-mgd HRC

232-mgd Grit Removal

Reaeration Chlorination

Dechlorination

25-MG Storage

Basin

• 45 mgd dry weather • 70 mgd annual average

Blending and Wet Weather Operations: An Engineering Perspective | June 19, 2014

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• 130 mgd maximum monthly • 400 mgd peak hourly

Preliminary results – pathogenic bacteria

75

0.1

1

10

100

Influent(A)

Pre-Chlorination(B)

Post-Dechlorination(C)

Cam

pylo

bact

er(M

PN/1

00 m

L)

Activated Sludge - Event 1 Geometric MeanActivated Sludge - Event 2 Geometric MeanHigh-Rate Clarification - Event 1 Geometric MeanHigh-Rate Clarification - Event 2 Geometric Mean

Event 1 HRC influent not shown because 2 of 3 grab sample results exceeded assay detection range.

1

10

100

Influent(A)

Pre-Chlorination(B)


Salm

onel

la (M

PN/1

00 m

L)

Activated Sludge - Event 1 CompositeActivated Sludge - Event 2 CompositeHigh-Rate Clarification - Event 1 CompositeHigh-Rate Clarification - Event 2 Composite

Measurements were below assay

detection limit of 1


Qualitatively similar reductions through activated sludge and HRC trains. Statistical analysis planned after 3rd event.

Preliminary results – pathogenic viruses

76

0.01

0.1

1

10

100

Influent(A)

Pre-Chlorination(B)


Tota

l Cul

tivab

le V

irus (

CPE

MPN

/L)

Activated Sludge - Event 2 Composite

High-Rate Clarification - Event 2 Composite

TCV not analyzed from Event 1.

Analyte not detected in disinfected effluent samples

from either train. Assay detection limit shown.

0.01

0.1

1

10

100

Influent(A)

Pre-Chlorination(B)


Aden

oviru

s(CP

E MPN

/L)


Analyte not detected in Event 1 influent samples for either train. Assay detection

limits shown.

Analyte not detected in Event 1 disinfected activated sludge

effluent sample. Assay detection limit shown.

Analyte not detected in disinfected effluent samples

from either train. Assay detection limit shown.


Similar reductions through activated sludge and HRC trains.

Preliminary results – pathogenic protozoa

77

0.1

1

10

Influent(A)

Pre-Chlorination(B)


Cryp

tosp

orid

ium

(ooc

ysts

/L)


Measurement was below assay detection

limit of 0.11

10

100

1000

Influent(A)

Pre-Chlorination(B)


Giar

dia

(cys

ts/L

)



Perhaps slightly greater reduction through HRC.

Preliminary results – turbidity & TSS

78

0

20

40

60

80

100

120

140

160

Influent(A)

Pre-Chlorination(B)


Turb

idity

(NTU

)

Activated Sludge - Event 1 Arithmetic MeanActivated Sludge - Event 2 Arithmetic MeanHigh-Rate Clarification - Event 1 Arithmetic MeanHigh-Rate Clarification - Event 2 Arithmetic Mean

0

20

40

60

80

100

120

140

160

180

200

220

240

260

Influent(A)

Pre-Chlorination(B)


Tota

l Sus

pend

ed So

lids (

mg/

L)

Activated Sludge - Event 1 Arithmetic MeanActivated Sludge - Event 2 Arithmetic MeanHigh-Rate Clarification - Event 1 Arithmetic MeanHigh-Rate Clarification - Event 2 Arithmetic MeanOutfall 001 NPDES Weekly Average Limit


Slightly greater reduction through HRC.

Milwaukee MSD

Background and milestones • 1990s – Added Inline Storage System (ISS). 19-mile network of

deep tunnels and pump station. • 1990s – Began implementing green infrastructure strategies. • 2006 – EHRT piloting of CEC and UV disinfection technologies. • 2007 – Completed 2020 Facilities Plan • 2011 to 2013 – EHRT piloting extended to CES, biocontact and

CMF technologies. • 2014 – Begin developing 2050 Facilities Plan


80 Source: MMSD Regional Green Infrastructure Plan (June 2013)

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Milwaukee MSD - Chemically Enhanced Clarification Demonstration Testing

• Location: MMSD’s South Shore WRF

• Piloted: ACTIFLO, DensaDeg, UV

• Treated primary influent • 240–300 gpm/HRT unit

• 12 Weeks (April – June, 2005) • Dry weather testing and wet

weather testing (2 events)

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HRC + Disinfection Compared to Existing Activated Sludge + Disinfection

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Treatment Processes E. coli Reduction

Fecal Coliform Reduction

F+ Coliphage Reduction

CEC + UV Pilot Test 3 to 4 log 3 to 5 log 3.5 to 4 log

Activated Sludge + Chlorine Disinfection at

South Shore WRF 3 to 4 log 3 to 5 log 3 to 3.5 log

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• CEC/UV reduction for E. coli, fecal coliform, and F+ coliphage similar to existing 1° & 2° treatment with chloramination

• Reduction of adenoviruses and enteroviruses by UV disinfection at 40 mJ/cm2 similar to chloramination

Recent guidance documents

Wet-weather challenges require site-specific plans, designs and management

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To be published in October 2014:

Wet Weather Design

and Operation in Water Resource

Recovery Facilities

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Recent POTW guidance for holistic and sustainable wet-weather solutions.

Summary points • Wet weather events have a short duration and are infrequent. Risks tend to be

acute, not chronic. • Reducing peak flows to POTWs to a level that allows for effective treatment by

traditional biological processes alone may not always be practical. • If needed, wet weather flows could be treated effectively by physical and/or

chemical methods to address acute water quality concerns. • POTWs blended discharges may have a lesser impact than non-point source

contributions. • Site specific variables result in site specific impacts and thus require site specific

solutions. • POTW planning, design and operations guidance have been updated to develop

and select optimum site-specific alternatives for wet-weather management. • The known risks to public health from well-designed and operated blending

facilities appears to be relatively low. Many of the recent regulatory drivers and concerns from the public appear to be caused by misinterpretations or misunderstandings about the practice and treatment processes. We hope our discussions today and tomorrow help shed much needed light on this topic.

Documents

Blending and Wet Weather Operations: An Engineering ...€¦ · 19.06.2014 · Recent case studies of wet weather flow management ... Blending and Wet Weather Operations: An Engineering