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
1
2
3
4
5
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