Modeling Reactions Between Activated Sludge Fractions and Ozone to Optimize Biosolids Reduction Processes

Transcription

1 Engineering Conferences International ECI Digital Archives Wastewater and Biosolids Treatment and Reuse: Bridging Modeling and Experimental Studies Proceedings Spring Modeling Reactions Between Activated Sludge Fractions and Ozone to Optimize Biosolids Reduction Processes Dominic Frigon McGill University Follow this and additional works at: Part of the Environmental Engineering Commons Recommended Citation Dominic Frigon, "Modeling Reactions Between Activated Sludge Fractions and Ozone to Optimize Biosolids Reduction Processes" in "Wastewater and Biosolids Treatment and Reuse: Bridging Modeling and Experimental Studies", Dr. Domenico Santoro, Trojan Technologies and Western University Eds, ECI Symposium Series, (2014). This Conference Proceeding is brought to you for free and open access by the Proceedings at ECI Digital Archives. It has been accepted for inclusion in Wastewater and Biosolids Treatment and Reuse: Bridging Modeling and Experimental Studies by an authorized administrator of ECI Digital Archives. For more information, please contact

2 Modeling Reactions Between Activated Sludge Fractions and Ozone to Optimize BiosolidsReduction Processes Dominic Frigon Microbial Community Engineering Laboratory Department of Civil Engineering McGill University June 12,

3 Introduction Cost of biosolidsdisposal is rising in North America due to disposal options and environmental taxes. For our partner wastewater treatment facility, disposal cost more than doubled over the last 7 years. In some Canadian jurisdictions (e.g., Province of Quebec), landfilling of biosolids will be banned by Thus, facilities want to reduce biosolids production. Air Liquidetries to open the North American market, but imprecision in performance predictions remain an obstacle. New Canadian laws require proper nitrification even during winter (water temperature <<10 C ) Is nitrification affected by RAS-ozonation? 2

4 Schematics of RAS Ozonation Unit Aeration Basin Clarifier Return Activated Sludge WAS Ozone Contactor 3

5 Objectives Develop and validate a mathematical model to improve performance predictions. Perform a global sensitivity analysis to understand the impact of biological processes on biosolids reduction. Perform a scenario analysis on nitrification stability to identify threatening operation conditions. 4

6 Concept of Ozone Unit Performance Technical/economic performance Mass of O 3 per day Mass of Sludge Reduction per day True performance evaluation steps Mass of O 3 per day Reactions in O 3 Contactor Mass of Sludge Solubilized Re-degradation in Treatment Basin Mass of Sludge Reduction per day 5

7 O 3 Contactor Performance by COD Solubilization Note: total COD and total suspended solids (TSS) are related Solubilization: g-cod/l COD Solubilization (%) COD solubilization performance vary 1 to 3 Factors: SolubilizationPerformance: Soluble COD g-cod Bubble size solubilized /g-o 3 Ozone transfer rate Ozone dosage (g-o 3 /g-tss) Ozone dose: g-o 3 /L Folodari, Andreottola and Ziglio(2010) Sludge Reduction Technologies in Wastewater Treatment Plants 6

8 BiosolidsReduction with Increasing SolubilizationRate (COD Solubilized/Solids Inventory/day) OZONATED CONTROL Sludge Production Ratio Biosolids Production Ratio Sludge Prod. Ratio = b O3 Constant MLVSS SRT for constant MLVSS SRT = b O3 1221b O b O b O3 (day 1 ) Constant SRT Sludge Prod. Ratio = e 4.85b O3 Solubilization Rates (COD Solubilized/COD Solids Inventory/day) SRT for Constant MLVSS (day) SRT for Constant MLVSS (day)

9 Soluble Particulate Model of Activated Sludge + RAS-Ozonation Influent COD Model development: Description of Inactivation/transformation Determination COD Fractions Non- Degradable Substrate cbod 5 Substrate Biomass Non- Degradable (1-Y) O 2 Outlet COD (Effluent+Sludge) Effluent Non- Degradable Substrate < 5% Sludge Yield (Y) Heterotrophic Inactivation process Biomass Non- Degradable f soluble,non-deg. f soluble,degradable + f particulate,degrad. Biomass Debris O 3 f mineralized Transformation process NH 4 + (1-Y N ) O 2 Nitrifying Biomass O 3 Inactivation process 8

10 Pilot-Scale Parallel Reactors (1 m 3 Aeration Tank) Distribution Well (HRT 1min) Control Reactor Test Reactor O 3 Contactor Aeration Tank (HRT 12 hours) Waste from Aeration (SRT 7 days) Portion of RAS Clarifier 9

11 Modeling Development and Validation Description of inactivation kinetics and stoichiometry Model prediction of pilot-scale experiments data Same installation studied in 3 different years 10

12 Modeling Effects of Ozone on RAS Biomass Is biomass inactivated at low O 3 dose? Others reported dose threshold Others reported linear inactivation Lab-scale Respirometer Conclusion: contactor NO O 3 threshold Exponential inactivation Inactivationoccurs at low O 3 doses Does inactivation solubilize biomass? From literature: ozone solubilizes cellular content Conclusion: Little COD solubilizationupon inactivation SOUR/SOUR0 Lab-scale: Pilot-scale RAS Fresh RAS 1.0 Lab-scale: Fresh RAS Lab-scale: sonicated RAS 0.8 Pure culture: R. jostii Ozonator Scale/Solids source COD solubilization (mg-cod/mg-o 3 ) O 3 dose (mg/l) 11

13 3 Pilot-Scale Experiments (3-5 months each) Year 1 Year 2 Year 3 Phase 1 Phase 2 Phase 3 Aeration +OzonatedReactor Control Rule Aerobic +Constant MLVSS Aerobic +Constant SRT Anoxic/Aerobic Aerobic Aerobic +Constant MLVSS SRT (day) Ozone Dose g-o 3 kg-vss Inventory day Biosolids Reduction 6 0 to 0to % % (lowercod solubilization) 22% 19% 18% 12

14 Year 1 Calibration of Model Independent calibration of inactivation parameters Fitting of inventory with transformation parameters. Good fit of the observed state variable. Total Solids Inventory Ozonated reactor Effluent Soluble COD Control reactor 13

15 Improvements in State-Variables Predictions for Different Descriptions of Inactivation Inactivation Linear Exponential Exponential Fractions: Inactivation Same Same Independent vs. Transformation Predicted State-Variables Relative Squared Errors Conclusions Exponential inactivation works better Inactivation solubilizes <10% of cellular COD 14

16 Calibrated Parameters of Year 1 Satisfactorily Predicted Year 2 and Year 3 Observations Year 2 - Total Solids Inventory Ozonated reactor Year 2 Nitrification Activity Control reactor 15

17 Model Global Sensitivity Analysis Trends in biosolids reduction performance Generate implementation guideline 16

18 Sensitivity of BiosolidsReduction to Model and High Sensitivity Medium Sensitivity Low Sensitivity Operation Parameters Maximum hydrolysis rate Maximum storage rate Maximum growth rate Influent COD HRT Substrate half saturation Hydrolysis half saturation Decay rate True yield Ozone soluble inert fraction Ozone inactivation Temperature Influent substrate Ozone particulate substrate fraction SRT Absolute Standardized regression coefficient Sludge Production Ratio slope variation Constant MLVSS Sludge Production Ratio Daily Solubilized COD fraction (d -1 ) Biomass Parameters Operational Parameters Ozone Reaction Parameters BOD5/COD 17

19 Operation Parameters Most Influential of BiosolidsReduction Standardized regression coefficient High Sensitivity Medium Sensitivity Anoxic/Oxic vs. Aerobic Sludge Production Ratio Sludge Production Ratio slope variation Temperature Influent COD Degradability Constant MLVSS Daily Solubilized COD fraction (d -1 ) Sludge Production Ratio Sludge Production Ratio slope variation Constant MLVSS Daily Solubilized COD fraction (d -1 ) Initial SRT SRT 18

20 Nitrification Scenario Analysis Explaining inconsistent data on nitrification rates Identification of operation conditions threatening nitrification Developing strategies to protect nitrification Nitrifiers Ammonia Oxidizers/ Nitrite Oxidizers NH 3 (-III) NO 2- (+III) NO 3- (+V)

21 Change in Specific Nitrification Rates Anoxic/Oxic conditions less detrimental than fully aerobic Specific nitrifcationrates can increase in some cases: influent TKN/COD < 0.1 g-n/g-cod Specific Nitrification Rate (mg-n/(mg-vss day) Change in Specific Nitrification Rates (ln[ozonated/control]) Year 1 Aerobic Year 3 Aerobic Year 3 Anoxic/ Oxic Influent TKN/COD Ratio (g-n/g-cod) 20

22 Operation Conditions Threatening Nitrification Safety Factor (SF) = SRT operation /SRT min SRT min of nitrifiers =(μ ANO,max b ANO b ANO,O3 ) 1 3 simulation studies of 1,500 simulations: variable reductions, 40% and 60% reduction Lower sludge reduction shows higher risk 4 ln[sf O3 /SF control ] Ln (SF O3 /SF Ctrl ) Variable refrence line Constant-40% Constant-60% Biosolids Reduction (%) Sludge reduction(%) Reduction in predicted nitrification stability 21

23 Operation Conditions Threatening Nitrification (Constant 40% Biosolids Reduction) Temperature SRT ln[sf O3 /SF control ) Inactivation rate constant (day 1 ) Temperature ( C) Inactivation rate constant SRT (day) 32% Potential problem: Temperature < 15 C and SRT < 16 days and Inactivation rate constant > 0.09 day 1

24 How to minimize inactivation rate? Ozone Contactor Biosolidsproduction is function of overall daily solubilization Overall daily solubilization: Solubilization in contaction Proportion of inventory treated Same factors for overall inactivation Minimize proportion of inventory BiosolidsProduction vs. Overall Solubilization Solubilization in Contactor Inactivation in Contactor Sludge Production Ratio Sludge Production Ratio slope variation Constant MLVSS Daily Solubilized COD fraction (d -1 ) SOUR/SOUR O3 dose (mg/l) 1.0 Pilot-scale RAS Lab-scale: Fresh RAS O 3 dose (mg/l)

25 Conclusion Bioprocess conditions influence greatly performance of RAS-ozonation units for biosolids reduction. Developed a model capable of predicting performance based on inactivation and COD solubilization. Nitrification stability is generally enhanced. Nitrification can be negatively impacted at lower temperature, SRT and higher overall inactivation. Contactor operation can be adjusted to alleviate problems. 24

26 Students Acknowledgements Overall Operation Inactivation Sensitivity Lab-scale reactors Siavash Isazadeh PhD Pinar Ozcer PDF Min Feng MEng Luis Urbina Rivas MEng Theresa Luby MEng Shameem Jaffur MEng Funding Organizations Regie d Assainissement des Eaux du Bassin LaPrairie Air Liquide Canada Natural Science and Engineering Research Council of Canada 25