E-Andrew Sindt Creative Component S11.pdf

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month of May, 2005 so the flow data used in the simulation of the regular mode was taken from themonthly mechanical monitoring reports for May, 2005 (see Appendix III).In addition to these data sources, two 24-hour composite samples were taken on October 20, 2010 andanalyzed to determine the volatile fraction of the total suspended solids.Table 3.2- Wastewater characteristics (combinedinfluent and industrial wastewater a )CombinedConcentration (mg/L)IndustrialComposition Average b Average b Low High1644 ±Flowrate (m 3 /d)1108 91 ± 37 11 214pH 7.7 ± 0.2 8.6 ± 1.8 5.1 12.34260 ±COD 510 ± 9.11280 1440 11800sCOD 396 ± 8.0 NA NA NA2286 ±BOD 5 295 ± 10.91462 453 6500Oil and grease NA 382 ± 268 64 1213Total nitrogen 42.6 ± 2.0 NA NA NAAmmonia-N 22.9 ± 1.8 NA NA NANitrite-N 0.2 ± 0.1 NA NA NANitrate-N 0.1 ± 0.1 NA NA NAOrganic N 20.7 ± 2.6 NA NA NATotal Soluble P 11.4 ± 0.9 NA NA NASuspended Solids 75.4 ± 8.4 NA NA NANo. of Measurements 104 24a Based on records for 2004 and 2005; NA = not availableb Statistical 95% confidence intervalFrom Ersu et al., 2008Table 3.3- Wastewater treatment performance for different modes apH sCOD BOD5 TN NH 3 NO - 2 -N NO - 3 -N TP TSSRegular May 20˚CInfluent 7.5 430 175 41.9 21.2 0.2 0.4 10.8 -Effluent 6.8 26.7 11.3 19 1.5 3.4 10.5 6 15.1Removal (%) 93.4 93.2 54.7 93.2 - - 44.7 -BNR-S1 August 23.8Influent 7.2 608 342 39.6 24.1 0.1 0.3 9.5 -Effluent 6.9 29.3 14.2 6.6 1.4 1.3 2.6 1.5 7.9Removal (%) 95.5 95.6 84.3 94.5 - - 88.2 -BNR-S2 October 20.1Influent 7.4 738 433 34.4 20.9 - - 9 -32
Effluent 7.2 35 7.8 3.5 0.8 0.8 1.9 1.6 4.7Removal (%) 94.3 97.9 89.4 97.3 - - 86.9 -BNR-S2 (colder) Jan/Feb 15.7Influent 7.4 830 NA 33.7 27.7 - - 10.4 -Effluent NA 34.7 NA 7.7 0.6 1.7 5.4 2.1 4.1Removal (%) 95.4 NA 81 96.1 - - 70.4 -a Number of measurements for regular, BNR-S1, BNR-S2, and BNR-S2 (Jan) were 3, 8, 5, and 8, respectively. NA = not available. Mean valuesgiven as mg/L (condensed version from Ersu et al., 2008)Table 3.4 contains calculated values of total COD, influent flocculated and filtered COD (FF COD), cBOD,and filtered carbonaceous biochemical oxygen demand (fcBOD). Total COD for each mode wascalculated from the ratio of the long term (2 yr average) COD/sCOD times the sCOD for the given mode.This method was selected over the typical method of using BOD to predicted COD because of aninconsistency in the BOD data for regular mode. Projected estimates for values not given were made byusing ratios of longer term data (Table 3.2).Table 3.4- Influent specifier input values regular modeParameter Value Units Data SourceFlow 1911.6 m 3 Mechanical monthly monitoring reports/d(May, 2005)Influent total COD 554 mg/L Estimated using Table 3.2 and 3.3 dataTKN 41.3 mg/L Calculated from Table 3 dataTotal P 10.8 mg/L Table 3.3Nitrate 0.4 mg/L Table 3.3pH 7.5 - Table 3.3Alkalinity 300 mg CaCO 3/L DefaultCalcium 80 mg/L DefaultMagnesium 15 mg/L DefaultD.O. 0 mg/L DefaultEffluent filtered COD 26.7 mg/L Table 3.3Influent filtered COD 430 mg/L Table 3.3Influent FF COD 241 mg/LEstimated using Table 3 data and defaultvaluesAmmonia 21.2 mg/L Table 3.3Acetate 12 mg/L DefaultOrtho-phosphate 5 mg/L DefaultInfluent cBOD 5 277 mg/L Estimated using COD/cBOD = 2Influent filtered cBOD 5 215 mg/L Estimated using sCOD/fcBOD = 2Influent VSS 151 mg/L Estimated from sample taken 10/20/10Influent TSS 183 mg/LMechanical monthly monitoring reports(May, 2005)3.4 BioWin Simulator SetupBioWin wastewater simulator contains a prepackaged dynamic SBR module that can be implementedthrough the use of one simple icon (Figure 3.3). For this report, only constant value inputs were useddue to limited data availability. Steady state results were achieved by running the dynamic simulation33
Page 1 and 2: Prediction of nutrient removal with
Page 3 and 4: Table of ContentsList of Figures ..
Page 5 and 6: 3.9 Effect of COD Fractions .......
Page 7 and 8: List of FiguresFigure 2.1- Biomass
Page 9 and 10: Figure AI.14- D.O. set point itiner
Page 11 and 12: Table AI.1- Influent specifier inpu
Page 13 and 14: Chapter 1: Introduction1.1 Importan
Page 15 and 16: Chapter 2: Literature Review2.1 Nut
Page 17 and 18: has a very low cBOD concentration a
Page 19 and 20: dissolved oxygen (D.O.) at a suffic
Page 21 and 22: Denitrification using biomass decay
Page 23 and 24: Figure 2.7- Phoredox process (Rittm
Page 25 and 26: increased the mean volatile fatty a
Page 27 and 28: used model is the Activated Sludge
Page 29 and 30: conditions included a discrete fill
Page 31 and 32: 3.1 Wastewater Treatment Plant Desc
Page 33: BNR-S2 operated with 1.5 hours simu
Page 37 and 38: constant width of 12.6 m over this
Page 39: Table 3.5- Sensitivity Parameters f
Page 42 and 43: 3.6.2 Calibration of BNR-S1 ModeThe
Page 44 and 45: Chapter 4 Results and Discussion4.1
Page 46 and 47: include 24-hour composite samples t
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Page 50 and 51: Percent deviation (predicted-observ
Page 52 and 53: Percent deviaton in value (model-ob
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Page 58 and 59: Calibrated simulator parameters for
Page 60 and 61: Sum absolute value of percent devia
Page 62 and 63: Absolute value of percent deviation
Page 64 and 65: Table 4.10- BNR-S2 colder (15.7 o C
Page 66 and 67: Table 4.13- Width adjustment effect
Page 68 and 69: Percent removala linear trend from
Page 70 and 71: Chapter 5: Conclusion5.1 SummaryBio
Page 72 and 73: Chapter 6: ReferencesAlleman, J.E.,
Page 74 and 75: Libra, R. D., Wolter, C. F., and La
Page 76 and 77: Appendix IBioWin Simulation Setup74
Page 78 and 79: Figure AI.2 - Influent specifier fr
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Page 82 and 83: Figure AI.9 - SBR operation page fo
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Figure AI.13 - SBR operation page f
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Appendix IISelected BioWin Simulati
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Table AII.1- Percent deviation from
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Table AII.2- Percent deviation from
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Sum absolute value of percent devia
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AOB and NOB maximum specific growth
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Appendix IIIMonthly Monitoring Repo
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DAYIrrig.1000'sGPDInfluentNH3-Nmg/L
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