E-Andrew Sindt Creative Component S11.pdf

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Chapter 4 Results and Discussion4.1 COD Fractions4.1.1Regular Mode COD FractionsInfluent data for the regular mode (Table 3.4) were entered into the influent specifier (see Appendix Ifor complete data set) and COD fractions were calculated by the influent specifier (see Figure 4.1).Notable differences between default and calculated values include the readily biodegradable COD(RBCOD) fraction (F bs ) and the acetate fraction (F ac ) . The calculated RBCOD fraction was nearly 2.5times the default value while the calculated acetate fraction is only 37% of the default value. Also, thecalculated non-colloidal slowly biodegradable fraction (F xsp ) was only one third of the default value. Thecalculated fractions of unbiodegradable soluble COD (F us ), unbiodegradable particulate COD (F up ),ammonia (F na ) and phosphate (F po4 ) were slightly less than the default values.Figure 4.10- Influent specifier COD fractions page for regular mode (EnviroSim, 2010)4.1.2 BNR-S1 mode COD FractionsCOD influent data for the BNR-S1 mode (Appendix I, Table AI.2) were entered into the influent specifierand COD fractions were calculated by the influent specifier (see Figure 4.2). Values of the fractions weresimilar to the regular mode with the most notable deviations from default values being the highcalculated RBCOD (F bs ) and acetate (F ac ) values as compared with the default values. The calculated noncolloidalslowly biodegradable COD (F xsp ) was significantly less than the default value. The fractions ofunbiodegradable soluble COD (F us ), unbiodegradable particulate COD (F up ), and ammonia (F na ) wereslightly less than the default values while phosphate (F po4 ) was slightly greater than default values.42
Figure 4.2 - Influent specifier COD fractions page for BNR-S1 mode (EnviroSim, 2010)4.1.3 COD Fractions DiscussionAccording to Melcer et al. (2003) RBCOD and unbiodegradable COD are arguably the most significantmunicipal wastewater characteristics for BNR modeling. It is important to note the variations betweenthe calculated and default COD fractions for RBCOD and, to a lesser extent of variation, unbiodegradableparticulate COD. RBCOD is an important food source for PAOs in the anaerobic phase as they work tosequester electrons (Rittman and McCarty, 2001). The ratio of RBCOD concentration to phosphorusconcentration can determine the success of a nutrient removal system designed for excess phosphorusremoval. If the RBCOD concentration to P concentration is too low, insufficient energy will be availableto PAOs in the anaerobic phase. This could result in the PAOs failing to adequately establish themselvesin the process and EBPR will not be achieved. The BNR-S1 mode should not be limited by RBCOD inachieving EBPR because the RBCOD fraction is nearly 2.5 times the default and the influent TPconcentration is around the typical value of 6 mg/L.The unbiodegradable particulate COD fraction has important implications for sludge production andoxygen demand (Melcer et al., 2003). These particulate fractions occupy space in the bioreactor butprovide no benefit to the process. This accumulation of unbiodegradable particulate leads to anincrease in MLSS concentration at a given SRT. Excessive MLSS concentration leads to solids/liquidseparation issues in secondary clarifiers or in SBR settling operations. A mixed liquor that contains highconcentrations of unbiodegradable particulate COD will be less effective in treating wastewater thanone that has normal or low levels of unbiodegradable particulate COD on a per unit MLSS basis.Increasingly long sludge age can intensify this condition as the unbiodegradable particulate CODaccumulates in the system. Unbiodegradable particulate COD should not have a significant effect on thepredicted effluent total nitrogen or phosphorus concentration in the regular or BNR-S1 modes.According to Melcer et al. (2003), “…The quality of the data used to calibrate the simulator will have adirect impact on the reliability of the predictions made when using the calibrated simulator.” In order todefine the COD fractions as accurately as possible, data in addition to that typically monitored atwastewater treatment facilities will need to be collected. Recommended data gathering activities43
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
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Page 35 and 36: Effluent 7.2 35 7.8 3.5 0.8 0.8 1.9
Page 37 and 38: constant width of 12.6 m over this
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Page 42 and 43: 3.6.2 Calibration of BNR-S1 ModeThe
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Page 58 and 59: Calibrated simulator parameters for
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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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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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