Simultaneous Nutrient Removal: Quantification, Design, and Operation. Leon Downing, Ph.D., PE Donohue & Associates

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1 Simultaneous Nutrient Removal: Quantification, Design, and Operation Leon Downing, Ph.D., PE Donohue & Associates

2 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

3 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)

4 SND and You MUCT Process: Components for Denitrification A/O Process with SND: Denitrification

5 Mixed liquor Collection of floc SND Mechanisms 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.

6 SND Controlling Parameters Ideal DO: 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)

7 Is this unique? Yes, but not unprecedented Oxidation ditches, MBRs Alternating aeration Biofilm systems (IFAS) Key questions: How do we quantify SND? 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

CRWSers Currently planning for the future Biosolids/Energy

8 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

9 Nutrient Removal Study Process model development in Biowin Evaluate potential BNR configurations Recommend potential improvements

10 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

11 Model Development Nitrogen balance TKN= 32 mgn/l NO 3 =0 mgn/l NO 2 =0 mgn/l TN=4,600 lbs/d Influent Effluent N 2 (mg/l) (mg/l) TKN 32 N/A Ammonia-N Aeration Basin Nitrite-N < Nitrate-N < BOD rbcod 106 <1 Clarifier TKN= 0.5 mgn/l NO 3 =12 mgn/l NO 2 =0.0 mgn/l TN=1,500 lbs/d WAS solids=10,000 lbs/day TN=1,100 lbs/d Nitrogen Removed=4,600-1,500-1,100=1,900 lbs/day (14 mgn/l)

denitrification Incorporated sludge blanket thickness

12 Secondary Clarifiers Field Sampling Sludge blanket profiles RAS sampling Confirmed significant denitrification Incorporated sludge blanket thickness and biologically active blanket in Biowin Net RAS NO 3 - -N = 6 to 8 mgn/l

13 Aeration Basins TRA Central MLSS 4,500 mg/l Large, dense floc Relatively high f/m SND Aerobic denitrification Floc/biofilm denitrification

14 Aeration Basins Modeling in Biowin Floc size and diffusion not included How do we model this? Adjust aerobic half saturation constant for oxygen (K O2 ) for denitrifying bacteria

15 Calibrated Model Model calibrated to field sampling data Verified with 3 years of operational data

16 PS 13A Demonstration Testing Testing the robustness of relying on SND to achieve EBPR No Flow No Flow RAS Demonstration Basin

17 Case Study 2 - IFAS Integrated fixed film activated sludge (IFAS) Add carriers to aeration basins Increase biomass/volume increase treatment per volume

18 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

process modeling What is impacting the SND in the biofilm?

19 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 Case Study 2 IFAS Mixing regime Examined by varying liquid diffusion layer thickness

20 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

21 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

22 Process Control DO concentration is critical for SBNR Design for DO control and blower turndown

23 SVI improvements Process Control 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

24 Selector zones Baffle walls Mixers ORP measurement Swing zone flexibility Process Control Typical sizing 15 to 25% of total aeration basin volume 0.75 to 1.0 lbsbod/lbmlss

25 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)

26 Comparison Process Variability 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

27 Effluent Orthophosphate (mg/l) Process Variability Pearson-Tukey approach on both data sets A/O A/O with SBNR % 25% 50% 75% 100% Probability

28 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

29 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

30 Questions? Leon Downing, Ph.D., PE Donohue & Associates (920)

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