2. Bio301 Overview of Topics Intro Bioprocessing – Biotechnology: Make money from bioprocesses Inputs are of lower value than outputs (products)

3. Lecture overview L1-3 Lecture 1: Intro, study guide, what is a bioreactor, Lecture 2: Intro to CBLA use, oxygen solubility, show bioprosim, download material, use floppy disks, Henry’s law, temperature effect on oxygen solubility. Use of spreadsheets for data processing Lecture 3: What is diffusion, how can we predict the behaviour of a randomly moving molecule? moving dots, entropy, driving force, equilibrium, rate of diffusion, first order kinetics

4. Lecture 4: oxygen transfer rate, kLa value. Graphical method of determining the kLa. Mathematical (2 point) determination of kLA Calculation and prediction of oxygen transfer as function of DO. Oxygen transfer efficiency. Bacterial OUR, DO. steady state Lecture 5: In situ method of determining kLa sulfite method of determining kLa Lecture 6: Online OUR monitoring as a key bioprocess monitoring tool. Saturation behaviour of OUR. Critical DO. Respirometric testing of substrates and inhibitors. Numeric integration of rate data Lecture overview L 4-6

5. Molecular diffusion relies on random movement resulting in uniform distribution of molecules

6. Oxygen Transfer Rate (OTR) Overview Diffusion, how does it work, how can we predict it? Diffusion is random …. and yet predictable.

7. Oxygen Transfer Rate (OTR) (diffusion, convection) Low OTR High OTR Transfer by diffusion is extremely slow and depends on surface area Wind Oxygen transfer by convection (turbulences) is more efficient Air In Bioreactors combine maximum convection with maximum diffusion Course bubbles cause more convection, fine bubbles more diffusion How soluble is oxygen?

8. The net transfer of oxygen from gas phase to solution reaches a dynamic equilibrium O2 input = O2 output equilibrium results in defined saturation concentration (cs). Oxygen solubility (cS)

9. Oxygen is not very polar  poorly soluble. Oxygen Solubility is described by Henry’s Law p = k*C p = partial pressure of gas k = constant depending on gas type, solution and temperature c = concentration of gas dissolved in water Meaning: The amount of oxygen which dissolves in water is proportional to the amount of oxygen molecules present per volume of the gas phase. Partial pressure ~ number of O2 molecules per volume of gas increases with O2 concentration in gas increases with total gas pressure How to calculate partial pressure? (refer to CBLA) Oxygen solubility (cS)

10. Effect of temperature Oxygen solubility decreases with increasing temperature. Overall: oxygen is poorly soluble (8mg/: at room temp.) More important than solubility is oxygen supply rate (oxygen transfer rate OTR). c s = 468 (31.6 + T) Oxygen Saturation Concentration c s (mg/L) Temperature (°C) Oxygen solubility (cS)

11. Oxygen Transfer Rate (OTR) (gradient, driving force) Question: What is the driving force for oxygen dissolution? OTR At oxygen saturation concentration (c s ): dynamic equilibrium exists between oxygen transferred from the air to water and vice versa. Answer: The difference between oxygen partial pressure and oxygen in solution) is the driving force. OTR is proportional to the that difference. Thus: 1. OTR depends on dissolved oxygen concentration (c L ). 2. No oxygen transfer at saturation concentration. 3. Maximum oxygen transfer when dissolved oxygen is zero. How does an aeration curve look like?

12. First: steep step in oxygen (top layer saturated, next layer oxygen free) Then: buildup of a gradient of many layers. Each layer is only slightly different from the next  Transfer from layer to layer has little driving force.  Gradient build-up inhibits fast diffusion OTR –Significance of gradient

13. 1. Deoxygenation (N 2, sulfite + Co catalyst) 2. Aeration and monitoring dissolved oxygen concentration (D.O. or c L ) as function of time 3. OTR = slope of the aeration curve (mg/L.h or ppm/h) Significance of OTR: critical to know and to control for all aerobic bioreactors 0510 8 Air On cL (ppm) Time (min) OTR – depends on DO (cL)

14. OTR = k L a (c s - c L ) ppm/h h -1 ppm 4. Observation: Slope is not constant but depends on cL What is the real OTR? 5. The statement of OTR only makes sense when cL is specified 6. OTR is highest at cL = zero (Standard OTR) 7. OTR is zero at oxygen saturation concentrations (cs) 8. OTR is correlated to the saturation deficit (cs - cL), which is the driving force for oxygen transfer 9. The factor of correlation is the volumetric mass transfer coefficient kLa OTR – depends on DO (cL)

15. 10. OTR is not a useful parameter for the assessment of the aeration capacity of a bioreactor. This is because it is dependent on the oxygen concentration (c L ) 11. The k L a value is a suitable parameter as it divides OTR by saturation deficit: 12. k L a = the key parameter oxygen transfer capacity. How to determine it? OTR (c s - c L ) k L a =

16. Rate is proportional to concentration  First order kinetics Slope = k L a max OTR OTR (mg/L.h) Dissolved oxygen [mg/L] OTR = k L a (O 2 saturation (cS) – O 2 concentration (cL)) (first order kinetics) Aeration Curve Time Dissolved Oxygen Air on (c s ) OTR – from aeration curve to kLa summary

17. During aeration of oxygen free water, the dissolved oxygen increases in a characteristic way OTR – Aeration curve from CBLA

18. Can the relationship between rate and DO be expressed mathematically? Highest Rate at lowest dissolved oxygen concentration Rate of zero when DO reaches saturation concentration OTR – aeration curve from CBLA

19. OTR – How to determine kLA Example: determine OTR at 6 ppm OTR is the slope of the tangent for each oxygen concentration OTR = ∆ cL/ ∆ t = 5 mg/L/ 4.5 min = 1.1 mg/L/min = 66 mg/L/h 0510 8 Air On cL (mg/L) Time (min) 6 4.5 min 5 ppm

20. k L a = OTR = 66 ppm / h (c s -c L ) = 3.3 h -1 (8 ppm – 6 ppm) Q: Problem with this method? A: based on one single OTR slope measurement and unreliable to obtain from real data. OTR – quick estimate of kLA Time DO

21. 1. Monitor aeration curve 2. Determine graphically the OTR at various oxygen concentrations (c L ) 8 2 4 6 0 510 3. Tabulate OTR and corresponding c L values cL (ppm) 0.5 3.0 4.0 6.0 8.0 Time (min) 7.5 5.0 4.0 2.0 0.0 30 60 50 25 0 c L (mg/L)C s - c L (mg/L)OTR (mg/L/h) At 6 ppm: OTR = 25 mg/L/h At 4 ppm: OTR = 50 mg/L/h At 3 ppm: OTR = 60 mg/L/h At 0.5 ppm: OTR = 30 ppm/h OTR – Graphical determination of kLa

22. 0 50 100 02468 4. Plot OTR values as a function of c s - c L. OTR (mg/L/h) Standard OTR cscs c s - c L (mg/L) 5. A linear correlation exists between k L a and the saturation deficit (c s - c L ) which is the driving force of the reaction. 6. The slope of the plot OTR versus c s - c L is the k L a value. 7. The standard OTR (max OTR) can be read from the intercept with the c s line. (Standard OTR = 100 ppm/h) kLa = = 12 h-1 70 mg/L/h 6 mg/L OTR – Graphical determination of kLa

23. Mathematical Determination of k L a 1. OTR is a change of c L over time, thus = dc L /dt Integration gives 2. k L a = dc L /dt (c s - c L ) () c s - c o 3. k L a = ln c s - c i t i - t o () 8 - 3 ppm k L a = ln 8 - 6 ppm 10.5 - 6.1 min = 0.21 min -1 = 12.5 h -1 = ln 2.5 4.4 min Dissolved Oxygen Concentration (mg/L) c i = 6 c o = 3 toto titi Time (min) cscs

24. 4. This method should be carried out for 3 to 4 different intervals 5. Once the k L a is known it allows to calculate the OTR at any given oxygen concentration: OTR = k L a (c s - c L )

25. Factors Affecting the Oxygen Transfer Coefficient k L a k L a consists of: k L = resistance or thickness of boundary film a = surface area Bubble Bulk Liquid Cell [Oxygen] Distance Main boundary layer = steepest gradient → rate controlling, driving force

26. Effect of Fluid Composition on OTR The transfer across this boundary layer increases with: 1) ↓ thickness of the film, thus ↑ degree of shearing (turbulence) 2) ↑ surface area 3) ↓ surface tension 4) ↓ viscosity (best in pure water) 5) ↓ salinity 6) ↓ concentration of chemicals or particles 7) detergents? 8) ↑ emulsifiers, oils, “oxygen vectors”

27. Engineering Parameters Influencing OTR Increase depth vessel Decrease bubble size Increase air flow rate Increase stirring rate Deeper vessel  bubbles rise a long way  ↑ OTR, OTE but more pressure required  ↑ $$  Larger surface area  ↑ OTR, OTE smaller bubbles rise slower  more gas hold up  ↑ OTR, OTE  ↑ Number of bubbles  ↑ OTR but ↓ OTE  ↑ turbulence  ↓ thickness of boundary layer  ↑ OTR, OTE  ↓ Bubble size  ↑ OTR, OTE

28. Oxygen Transfer Efficiency (OTE) OTE = oxygen transferred oxygen supplied Significance of OTE: economical, evaporation Calculation of OTE (%): % OTE = oxygen transferred (mol/L.h) oxygen supplied (mol/L.h) X 100 Why do students find this type calculation difficult? Units are disregarded. Molecular weights are misused.

29. Oxygen Transfer Efficiency (OTE) A bioreactor ( 3 m 3 ) is aerated with 200 L/min airflow. If the OTR is constant (100 mg/L/h) determine the %OTE. 1. Convert the airflow into an oxygen flow in mmol/L/h 200 L air /min = 12000 L air/h = 2520 L O 2 /h = 102.9 mol O 2 /h = 34.3 mmol O 2 /L.h (x 21%) (÷ 24.5 L/mol) (÷ 3000 L) 2. OTR (x 60) 100 mg/L.h = 3.1 mmol O 2 /L.h (÷ 32 g/mol) % OTE = 3.1 (mmol/L.h) 34.3 (mol/L.h) X 100 = 9%

30. Oxygen Transfer Efficiency (OTE) OTE is dependent upon the cL in the same way than OTR OTE decreases with increasing airflow (more oxygen is wasted) % OTE 5 10 Airflow

31. Microbial oxygen Uptake Rate (OUR) Depends on: 1. Specific activity of cells (Q O 2 ) 2. The number of cells (X) OUR = Q O 2. X Q O 2 depends on: 1. Strain 2. Substrate 3. [Substrate] 4. Temperature 5. Growth conditions 6. [Oxygen] (cL)

32. OUR [Substrate] Time X In batch culture OUR changes strongly over time due to increase in biomass (X) depletion of substrate (S). However OUR can be considered constant: over short time intervals (min) in continuous culture OUR – Variation during batch culture

33. 1.Critical indicator of culture status (respiration rate). 2.Inidicator or growth (relationship X / OUR). 3.Indicator of health, inhibition etc ( if X= constant). 4.Essential for culture optimisation. 5.Should be ideally monitored online. OUR – Significance

34. 1. Aerate to maximum 2. Stop aeration 3. Monitor c L cLcL Time (sec) Conclusion: 1. OUR is linear over most c L values 2. A critical D.O. exists OUR – Determination

35. 1. Aerate to maximum 2. Stop aeration 3. Monitor c L cLcL Time (sec) Conclusion: 1. OUR is linear over most c L values 2. A critical D.O. exists OUR – Determination O2 dependent OUR OUR not dependent on DO

36. D.O. (mg/L) Time Maximum rate about half maximum rate OUR – Dependency on DO

37. D.O. (mg/L) Time (sec) Maximum rate about half maximum rate OUR – Dependency on DO

38. OUR (mg/L/h) D.O. (mg/L) The OUR is mostly independent of D.O. At very low D.O. the OU R is strongly dependent on D.O. OUR – Dependency on DO

39. OUR (mg/L/h) D.O. (mg/L) Key words: D.O. saturation D.O. limitation first order reaction zero order reaction Michaelis Menten kinetics OUR – Dependency on DO

40. 0.512 OUR (ppm/h) Critical DO DO (ppm) Dependence of OUR on DO (cL) Conclusions: 1. Typical Michaelis Menten relationship 2. k s at about 0.1 ppm (critical D.O.: 0.2 ppm)

41. D.O. (mg/L) Time Air off Effect of interruption of oxygen supply on the D.O. concentration in an active microbial culture Air on cS 8 - 4 - dc/dt = 0 dc/dt = OUR OUR – steady state

42. dcL/dt = 0 dcL/dt = OUR DO (ppm) Air Off Air On Time (sec) ABC A B C = - Q O 2.X dcL/dt = OTR - OUR = kLa (c s - cL) - Q O 2.X Steady state:1. OUR constant 2. OTR constant 3. DO constant 4. OUR = OTR When dc L /dt = 0→ OUR = OTR → OUR = k L a(c s – c L ) Conclusion: When k L a is known, steady state OUR can be calculated from the dissolved [oxygen] (D.O.) (c L ) OUR – Indirect online monitoring

43. D.O. (mg*L -1 ) Time (min) Feed off Feed off Feed on Feed on Effect of cyclic feed additions on D.O. profile in aerobic bioreactor OUR – Effect of feed availability

44. Feed On Feed On Feed Off Feed Off Feed Off DO (ppm) Time (min) The addition of feed to a starving culture of microbes results in an instantaneous increase of OUR, which Causes a drop in the D.O. OUR – Dependency on DO

45. OUR – calculation from in situ DO monitoring 1. Calculation of OUR from k L a and c L e.g. k L a = 20 h -1, cL = 2 ppm, cS= 8 ppm OUR = ? OUR = 20 h -1 x 6 ppm 2. Determination of k L a in situ (dynamic method) Since under steady state: OTR = OUR k L a = OUR (c s – c L ) = 120 ppm/h

46. 3. Calculation of new OUR from old OUR and c L Original OUR = 120 mg/L/h at cL of 4 mg/L After further growth DO lowered to 2 mg/L What is the new OUR? k L a = = = 30 h -1 OUR 120 mg/L/h (c S – c L ) 4 mg/L OUR = k L a * (c S – c L ) = 30 h -1 * (8 mg/L – 2 mg/L) = 180 mg/L OUR – applications of online DO monitoring

47. 1. Calculation of new kLa from old kLa and c L Original kLa = 30 h-1 at cL of 2 mg/L After increasing airflow the new cL was 5 mg/L What is the new kLa? new k L a = = = 60 h -1 OUR 180 mg/L/h (c S – c L ) 3 mg/L OUR = k L a * (c S – c L ) = 30 h -1 * (8 mg/L – 2 mg/L) = 180 mg/L OUR – applications of online DO monitoring

48. 1.Static Gassing Out Method (N 2 ) De-oxygenate solution, monitor DO increase over time. Determine kLa (a) graphically or (b) mathematically 2. Sulfite Method Titration of sulfite consumption during oxygenation trial - indirect measurement + no oxygen probe required + allows direct monitoring of standard OTR standard OTR = kLa. cs 3. Dynamic Method (in situ kLa) + measured real in situ value considering changes of medium such as viscosity, particles, surface tension... - depends upon known OUR + only slight process interuption necessary + only works when DO >> critical DO OUR- Comparison of Methods for kLa determination

49. 4. Oxygen Balance Method = Direct Monitoring OTR = specific air flow. ([O 2 ] in - [O 2 ] out ) mg/L.hL(g)/L(l).hmg/L(g) + integrates over the whole reactor volume + not affected by fine air bubbles + excludes lag of oxygen probe + no lag of large reactors - dependent on precise flow of air - longer response time to step changes OUR- Comparison of Methods for kLa determination

50. D.O. (mg/L) Time Effect of minute feed addition on D.O. profile of aerated starving microbial culture Add feed There is very useful information in the OUR response of microbial cultures to the addition of substrates or inhibitors OUR – indirect respiration activity monitoring

51. D.O. (mg/L) Time Effect of minute feed addition on D.O. profile of aerated starving microbial culture Add feed OTR D.O cS OUR D.OcS

52. D.O. (mg/L) Time Effect of minute feed addition on D.O. profile of aerated starving microbial culture Add feed OUR (mg/L/h) OUR – indirect respiration activity monitoring

53. Time (min) OUR response to feed spike by starving microbial culture. Numerical integration (counting squares) allows to determine the amount of oxygen used due to the feed spike addition. OUR (mg/L/h) 61224 20 40 20 mg/L/h * 0.1h = 2 mg/L

54. End of slides Beyond this point some spare slides

55. Feed Time (min) Feed Time (min) OUR (ppm/h) DO(cL) (ppm) Applications of Relationship OUR – D.O. 3. Degradability monitoring 4. Optimising aeration or growth conditions 5. Estimation of yield coefficient (Y)

56. Oxygen Solubility Oxygen Solubility is described by Henry’s Law p = k*C p = partial pressure of gas k = constant depending on gas and solution c = concentration of gas dissolved in water 1. Meaning: The amount of oxygen which dissolves in water is proportional to the amount of oxygen molecules present per volume of the gas phase. What is partial pressure? (refer to CBLA) Effect of temperature on oxygen solubility Oxygen solubility decreases with increasing temperature. 3. Overall: oxygen is poorly soluble (8mg/: at room temp.) c s = 468 (31.6 + T) Oxygen Saturation Concentration c s (mg/L) Temperature (°C)