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Print version Updated: 26 November 2019 CEE 370 Environmental Engineering Principles Lecture #32 Wastewater Treatment III: Process Modeling & Residuals Reading M&Z: Chapter 9 Reading: Davis & Cornwall, Chapt 6-1 to 6-8 Reading:


  1. Print version Updated: 26 November 2019 CEE 370 Environmental Engineering Principles Lecture #32 Wastewater Treatment III: Process Modeling & Residuals Reading M&Z: Chapter 9 Reading: Davis & Cornwall, Chapt 6-1 to 6-8 Reading: Davis & Masten, Chapter 11-11 to 11-12 David Reckhow CEE 370 L#32 1

  2. Microbial Biomass in a CMFR General Reactor n n dm ∑ ∑ − − A (C Q ) (C Q ) mass balance dt = r V Ai Aj A in out i j i=1 j=1 But with CMFRs we have a single outlet concentration (C A ) and usually a single inlet flow as well C A C A Q 0 C A0 Q 0 V 2 CEE 370 L#32 David Reckhow

  3. Batch Microbial Growth 0 0 General Reactor n n dM ∑ ∑ A − (C Q ) (C Q ) mass balance = - r V Ai Aj A i in j out dt i=1 j=1 Batch reactors are usually filled, allowed to react, then emptied for the next batch Because there isn’t any flow in a batch reactor: 1 dM C A A = - r A V dt For 1 st order V X kX biomass And: growth dC A dt = - r A 3 CEE 370 L#32 David Reckhow

  4. Batch Microbial Growth  Observed behavior Stationary Death Covered in lecture #17 Lag Exponential Growth Time 4 CEE 370 L#32 David Reckhow

  5. Exponential Growth model Covered in lecture #17   dX ≡ µ   X  dt  gr D&M Text where, N X = concentration of microorganisms at time t t t = time µ = proportionality constant or specific r growth rate, [time ─ 1 ] dN/dt dX/dt = microbial growth rate, [mass per volume-time] 5 CEE 370 L#32 David Reckhow

  6. Exp. Growth (cont.) Covered in lecture #17   dX   dX ≡ µ   X ≡ µ   dt or  dt   X  gr gr   X µ ln   = t   X o µ t X = X e o 6 CEE 370 L#32 David Reckhow

  7. Substrate-limited Growth  Also known as resource-limited growth  THE MONOD MODEL S   dX SX µ = µ ≡ µ = µ and   X max S + max K S +  dt  K S gr S where, µ max = maximum specific growth rate, [day -1 ] S = concentration of limiting substrate, [mg/L] K s = Monod or half-velocity constant, or half saturation coefficient, [mg/L] 7 CEE 370 L#32 David Reckhow

  8. Monod Kinetics Covered in lecture #17 0.5*µ m K S 8 CEE 370 L#32 David Reckhow

  9. Substrate Utilization & Yield  Related to growth by Y, the yield coefficient  Mass of cells produced H&H, Fig 11-38, pp.406 per mass of substrate utilized dX ∆ X dt ≡ = Y dS ∆ S dt  Just pertains to cell growth  dX  dS =   Y  dt  dt gr 9 CEE 370 L#32 David Reckhow

  10. Microbial Growth  dX  dS =   Y  dt  dt gr  Monod kinetics in a chemostat (batch reactor) Substitute for dS µ   dS XS dX SX = ≡ µ = µ   X max max S + +  dt  K S dt Y K S gr S & Divide by Y XS  Where = e r k su + K S  dS/dt = r su = actual substrate utilization rate S e  k = maximum substrate utilization rate = μ max /Y  S = concentration of substrate (S e in H&H)  K S = half-saturation constant  Y = cell yield = dX/dS 10 CEE 370 L#32 David Reckhow

  11. Death  Bacterial cells also die at a characteristic first order rate with a rate constant, k   dX = −   k X d  dt  d  This occurs at all times, and is independent of the substrate concentration 11 CEE 370 L#32 David Reckhow

  12. Overall model: chemostat  Combining growth and death, we have:       dX dX dX = +        dt   dt   dt  net gr d SX = µ − k X See: M&Z equ 9.3 max d + K S S  And in terms of substrate utilization   dX dS ≡ ÷ Y    dt  dt gr     dX dS = −   Y   k X d  dt   dt  net 12 CEE 370 L#32 David Reckhow

  13. Activated Sludge Flow Schematic  Conventional X o Q+ Q r Q X X e Effluent S o Aeration S S Basin Settling Influent Tank V,X Q r X r Return activated sludge 13 Q w X r S Waste activated sludge CEE 370 L#32 David Reckhow

  14. Efficiency & HRT  Efficiency of BOD removal ( ) − S S 100 % = E o S o  Hydraulic Retention Time, HRT (Aeration Time)  Same as retention time in DWT (t R ) V θ =  Actual HRT is a bit different Q  Isn’t used as much in design V θ = act + Q Q R 14 CEE 370 L#32 David Reckhow

  15. SRT – solids retention time & R  SRT: Primary operation and design parameter  How long does biomass stay in system XV XV θ = ≈ ( ) See: M&Z equ 9.10 c − + Q Q X Q X Q X w e w r w r  Typically equals 5-15 days Q  Recycle Ratio = r R Q  Values of 0.25-1.0 are typical 15 CEE 370 L#32 David Reckhow

  16. F:M Ratio and volumetric loading  Food-to-Microorganism Ratio (F/M) ∗ F Q BOD = ∗ M V X F QS = o M&Z equ 9.16 M XV  Typical values are 0.2-0.6 in complete mixed AS  BOD volumetric Loading QS = o Loading V  Typically 50-120 lb BOD/day/1000ft 3 tank volume 16 CEE 370 L#32 David Reckhow

  17. Act. Sludge: Biomass Model  dX   dX   dX  = +  Steady State mass balance on biomass       dt dt dt       net gr d   dX dX SX = 0 = − − + = µ − V QX Q X Q X V   k X max d + o e e w r K S dt  dt  S batch From chemostat model  Incorporating the chemostat model gets:   dX SX   = = − − + µ − V 0 QX Q X Q X V k X   o e e w r max d + dt K S   S  And simplifying   SX   − + + = µ − QX Q X Q X V k X   o e e w r max d + K S   S  Finally, we recognize that the amount of solids entering with the WW (i.e., X o ) and leaving in the treated effluent (i.e., X e ) is quite small and can be neglected 17 CEE 370 L#32 David Reckhow

  18. Biomass Model II  So it becomes   SX   = µ − Q X V k X   w r max d + K S   S  And rearranging Q X S 1 = µ − ≈ w r k θ max d + VX K S c S Earlier equation for SRT XV XV θ = ≈ ( ) c − + Q Q X Q X Q X w e w r w r 18 CEE 370 L#32 David Reckhow

  19. Act. Sludge: Substrate Model  Steady state mass balance on substrate µ dS XS = max S + dt Y K S   dS dS = 0 = − − + V QS Q S Q S V   o e w From chemostat model dt  dt  batch  Substituting and noting that Q e =Q-Q w   µ XS   = − + − QS QS Q S Q S V max   o w w + Y K S   S  And further simplifying   µ XS ( ) − =   Q S S V max   o + Y K S   S 19 CEE 370 L#32 David Reckhow

  20. Merging the biomass & substrate models If we divide the previous equation by V and X  ( ) − µ   µ Q S S S XS ( )   − = = Q S S V max o max   o + Y K S   + VX Y K S S S Multiply both sides by Y  ( ) − YQ S S S = µ o M&Z equ 9.8 max + VX K S S Now insert the LH term into the 1 Q X S  = = µ − w r k earlier equation based on biomass max d θ + VX K S c S ( ) − 1 Q X YQ S S = = − w r o k M&Z equ 9.9 d θ VX VX c 20 CEE 370 L#32 David Reckhow

  21. Combined model II  Now recognize that Q/V is the reciprocal of the HRT ( ) − 1 1 Y S S = θ − o k d θ X c 21 CEE 370 L#32 David Reckhow

  22. Question  All else being equal, as SRT goes up: Settleability goes down 1. F/M goes down 2. Waste sludge return ratio must go down 3. Endogenous respiration becomes less 4. important Sludge yield increases 5. 22 CEE 370 L#32 David Reckhow

  23. Aeration: Loadings  Food-to-Microorganism Where  Q=WW flow Ratio (F/M)  V=volume of aeration tank  X=MLVSS=mixed liquor ∗ F Q BOD  = volatile suspended solids ∗ M V X (biomass concentration) X e =VSS e = suspended solids in   Sludge Age or mean cell wastewater effluent residence time ( ɵ c ) X W =VSS w = suspended solids  in waste sludge Q w = flow of waste sludge VX  θ = SS is sometimes used instead ( ) ( )  c + X Q X Q of VSS e e W W VX ≈ X Q W W 23 CEE 370 L#32 David Reckhow

  24. Operating Criteria  Loading, biomass, retention time, etc H&H, Table11-4, pp.395 24 CEE 370 L#32 David Reckhow

  25. Activated Sludge  Mixed liquor  Return Activated sludge 1. Surface aerators 2. Bubble diffusers 25 CEE 370 L#32 David Reckhow

  26. Updated: 26 November 2019 CEE 370 Environmental Engineering Principles Lecture #32b Wastewater Treatment IIIb: Process Modeling & Residuals Reading: M&Z Chapter 9.11 Other Reading: Davis & Cornwall, Chapt 6-1 to 6-8 and Davis & Masten, Chapter 11-11 to 11-12 David Reckhow CEE 370 L#32 26

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