Simultaneous Nutrient Removal: Quantification, Design, and

Operation

Leon Downing, Ph.D., PE Donohue & Associates

Simultaneous Nutrient Removal

Simultaneous nitrification, denitrification, and potentially phosphorus removal

– SND – simultaneous nitrification and denitrification

– SBNR – simultaneous biological nutrient removal (N and P)

Definition of SND

– Historically: nutrient removal is occurring where we didn’t expect (or design) it to occur

– Current and Future: nutrient removal is carried out in systems designed to produce multiple redox conditions in a single tank system

SND and You

Why would achieving SND be important in Illinois?

– Nitrate concentration in return activated sludge (RAS) impact enhanced biological phosphorus removal (EBPR) efficiency

– SND achieves denitrification in a system while potentially eliminating the need for additional selector zone volume or internal mixed liquor recycles (IMLR)

SND and You

Components for Denitrification

MUCT Process:

A/O Process with SND:

Denitrification

SND Mechanisms

Mixed liquor

– Collection of floc

– Not individual, free swimming bacteria

– Floc is analogous to a biofilm

Biofilm dynamics

– Diffusion, hydrodynamics, and “driving force” are major impacts on: ▪ Floc activity

▪ Microbial ecology

▪ Environmental conditions

SND Controlling Parameters

Ideal DO: 0.5-2.0 mg/L

High SRT

– Higher MLSS

– Larger Floc size/Biofilm Thickness

C/N of 10

F/M ratio of > 0.1 g BOD/g MLSS/day

Oxygen diffusion

– “Shallow” diffusion leads to more anoxic/anaerobic volume

Oxygen concentration variation

– For biological phosphorus removal, cells need to be exposed to both anaerobic and aerobic conditions

Pochana et al, WS&T (1999); Diagger and Littleton, WER (2000); Points and Downing, WEFTEC (2010); Jiminez et al, WEF Nutrient Removal (2011)

SND

Is this unique?

– Yes, but not unprecedented

– Oxidation ditches, MBRs

– Alternating aeration

– Biofilm systems (IFAS)

Key questions:

– How do we quantify SND?

– How do we design SND? (how robust is the process)

– How do we operate for SND?

Case Study 1 – Nitrifying Activated Sludge

TRA CRWS Treatment Plant

– Forward thinking clean water agency

– Home of the TRA CRWSers

– Currently planning for the future ▪ Biosolids/Energy

▪ Nutrients

Key question: How will we achieve future nutrient discharge permit?

Downing et al, WEF Nutreint Removal 2011; Downing et al, WWTMod 2010; Downing et al, Texas Water 2010

Nutrient Removal Study

Process model development in Biowin

Evaluate potential BNR configurations

Recommend potential improvements

Model Development

Kinetic parameter estimation

Calibration

– Based on a given set of data ▪ One month of data

▪ Special sampling period

Validation

– Verify accuracy of calibrated model over a range of conditions

Evaluation

Model Development

Nitrogen balance

Influent

(mg/L) Effluent

(mg/L)

TKN 32 N/A

Ammonia-N 22 0.18 Nitrite-N <1 0.14 Nitrate-N <1 12.2 BOD5 187 7.5 rbCOD 106 <1

Aeration Basin Clarifier TKN= 32 mgN/L

NO3=0 mgN/L

NO2=0 mgN/L

TN=4,600 lbs/d

WAS solids=10,000 lbs/day

TN=1,100 lbs/d

N2

Nitrogen Removed=4,600-1,500-1,100=1,900 lbs/day (14 mgN/L)

TKN= 0.5 mgN/L

NO3=12 mgN/L

NO2=0.0 mgN/L

TN=1,500 lbs/d

Secondary Clarifiers

Field Sampling

– Sludge blanket profiles

– RAS sampling

– Confirmed significant denitrification

– Incorporated sludge blanket thickness and biologically active blanket in Biowin

Net RAS NO3- -N = 6 to 8 mgN/L

Aeration Basins

TRA Central MLSS

– 4,500 mg/L

– Large, dense floc

– Relatively high f/m

SND

– Aerobic denitrification

– Floc/biofilm denitrification

Aeration Basins

Modeling in Biowin

Floc size and diffusion not included

How do we model this?

– Adjust aerobic half saturation constant for oxygen (KO2) for denitrifying bacteria

Calibrated Model

Model calibrated to field sampling data

Verified with 3 years of operational data

Demonstration Testing

Testing the robustness of relying on SND to achieve EBPR

PS

13

A

RAS

No Flow

No Flow

Demonstration Basin

Case Study 2 - IFAS

Integrated fixed film activated sludge (IFAS)

– Add carriers to aeration basins

– Increase biomass/volume – increase treatment per volume

Case Study 2 – IFAS

Original study

– Focused on full-scale nutrient removal (Downing et al, 2009)

– Significant denitrification observed in “aerobic” biofilm

Downing et al, WEFTEC 2009; Points et al, WEFTEC 2010

Further investigation

– Research effort with Southern Methodist University

– Combination of batch studies, bench scale testing, and process modeling

What is impacting the SND in the biofilm?

– DO concentration

– Mixing regime

▪ Examined by varying liquid diffusion layer thickness

Case Study 2 – IFAS

Aeration provides both mixing and oxygen – Lower DO concentration – increased denitrification

– Lower DO concentration achieved through decreased aeration

▪ Lower mixing intensity

▪ Larger diffusion thickness (LDL)

▪ Increased denitrification

Case Study 2 – IFAS

Design for SND

Inclusion of operational flexibility

– DO control

– Secondary clarifier solids loading rates

Evaluation of variability is a key to SND (and nutrient removal in general)

– Set reasonable expectations for performance

Process Control

DO concentration is critical for SBNR

Design for DO control and blower turndown

Process Control

SVI improvements

– SVI impacts the MLSS concentration carried in the aeration basins

– Low SVI produces a good settling sludge

Selector zones

– “select” for floc forming bacteria that settle well

– Provide anoxic/anaerobic conditions to increased nutrient removal

– Form larger flocs, higher potential for SBNR

Process Control

Selector zones

– Baffle walls

– Mixers

– ORP measurement

– Swing zone flexibility

– Typical sizing

▪ 15 to 25% of total aeration basin volume

▪ 0.75 to 1.0 lbsBOD/lbMLSS

Process Variability

Variability of influent has a significant impact on nutrient removal

Emerging field of study within the industry

– Monte Carlo simulations

– Pearson-Tukey three-point approximation ▪ Similar results as Monte Carlo, with significantly fewer simulation

runs (Martin et al 2010)

▪ Produces closer results to annually observed nutrient removal performance than traditional approach (Downing et al 2012)

Process Variability

Comparison

– A/O process prediction without SND

– A/O process prediction with SND

Traditional approach

– Evaluate minimum week, average day, and maximum week

– Both evaluations predicted effluent orthophosphate below 1 mg/L

Process Variability

Pearson-Tukey approach on both data sets

0

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3

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6

7

0% 25% 50% 75% 100%

Eff

lue

nt

Ort

ho

ph

osp

ha

te (

mg

/L)

Probability

A/O

A/O with SBNR

Operational Considerations

Aeration control

– How can DO be controlled throughout basins

– What DO profile works for nitrification requirements

MLSS levels

– How does the system respond to a higher concentration

– f/m gradient in aeration basin

Operational Considerations

MLVSS/MLSS

– EBPR results in PHB accumulation in cells (inert)

– EBPR plants can have a lower VSS/TSS value

Primary effluent sampling

Aeration basin profiling

– What is going on inside the basins

Questions?

Leon Downing, Ph.D., PE Donohue & Associates

(920) 803-7304 ldowning@donohue-associates.com