1. IF YOU HAVE A DISABILITY OR MEDICAL CONDITION, DON’T FEEL UNSURE!
CONTACT EQUITY AND SOCIAL INCLUSION ON

2. Industrial Bioprocessing and Bioremediation 2014 !
Welcome to
Industrial Bioprocessing and Bioremediation 2014 !
(Environmental Biotechnology)
Unit coordinator background:
This unit is different to your other biotechnology units as it focusses on the TECHNOLOGY part (engineering).
This requires being able to analyse processes, solve problems, predict outcomes, carry out mass balances, etc.

3. Industrial Bioprocessing and Bioremediation 2014 !
Welcome to
Industrial Bioprocessing and Bioremediation 2014 !
(Environmental Biotechnology)
Example processes: How to:
make renewable biogas from organic wastes.
remove polluting nutrients from wastewater
breed microalgae for food or energy production
make beer, yoghurt,
mine ores by using bacteria (bioleaching)
understand microbial processes in ocean, soil and bioreactors

4. Fundamentals taught Bioprocesses convert S to P How much S to P?
Mass balance
How much hydrogen gas can we make as fuel from fermenting sugars ?
How much oxygen is needed for respiration?
How much electricity can be formed from sugar ?

5. Lecture content over the next weeks
Day
Time
Venue
Topic
Lecturer 1
Mon
Jul 21
AMEN 2.023
Introduction, Diffusion, Bioreactor
RCR
LB 3.032
Tues
Jul 22
1.2 Oxygen solubility and transfer
Wed
Jul 23
1.3 Oxygen mass transfer coefficient kLa 2
Jul 28
2.1 Microbial oxygen uptake
Help with BioProSim1
Jul 29
2.2 Oxygen steady state calculations
Jul 30
2.3 Online OUR monitoring 3
Aug 4
3.1 Fundamentals of microbial growth
Aug 5
3.2 Microbial competition for substrate
Aug 6
3.3 Four growth constants determine growth

6. Lab schedule over the next weeks
Venue
Topic
Time 1
LB 3.032
Small Comp Lab
Virtual Lab 1- BioProSim1 pm 2
BS 2.050
Oxygen Transfer - RCR 3
Oxygen Uptake - RCR 4
Penicillin Production as a secondary metabolite demonstration – RCR 5
Algal Biotechnology- NM
6 Study Break 7
Chemostat Project (or week 9)
pm* 8
Chemostat Project (or week 10)
All Week * 9
Chemostat Project (or week 7) 10
Chemostat Project (or week 8)
All Week*
11 Study Break 12
Bioprocess Modelling 13
Off Campus
Visit of Industrial Bioprocessing Site
2.00pm offsite 14
TBA 15
Study Break

7. Assessed activities over the next weeks
Type
Topic
Marks
Due
Week
Due Day
CBLA1)
Oxygen solubility (OTR1) 1
Fri
Oxygen transfer (OTR2)
Oxygen uptake (OTR3) 2
Group
Instant Lab Report on oxygen transfer
Thurs
Instant Lab Report on oxygen uptake 3
Individ.
BioProSim 1 mass transfer simulation
Microbial growth principles (GRO1)
Mon
Microbial growth kinetics (GRO2)
Wed
Microbial cell cultivation (GRO3)
Lab Report on Algal Biotechnology 4 5
Penicillin a secondary metabolite? 7
Bio-reaction oxidation states (OXS)
BioProSim 2 chemostat simulation 8
Exam 2)
Mid-semester Exam 25
Chemostat Group Report 10
10 /12
End-semester Exam 40
Total
100

8. Type
Topic
Marks
Due
Week
Due Day
CBLA1)
Oxygen solubility (OTR1) 1
Fri
Oxygen transfer (OTR2)
Oxygen uptake (OTR3) 2
Group
Instant Lab Report on oxygen transfer
Thurs
Instant Lab Report on oxygen uptake 3
Individ.
BioProSim 1 mass transfer simulation
Microbial growth principles (GRO1)
Mon
Microbial growth kinetics (GRO2)
Wed
Microbial cell cultivation (GRO3)
Lab Report on Algal Biotechnology 4 5
Penicillin a secondary metabolite? 7
Bio-reaction oxidation states (OXS)
BioProSim 2 chemostat simulation 8
Exam 2)
Mid-semester Exam 25
Chemostat Group Report 10
10 /12
End-semester Exam 40
Total
100

9. Type
Topic
Marks
Due
Week
Due Day
Group
Instant Lab Report on oxygen transfer 1 2
Thurs
Instant Lab Report on oxygen uptake 3
Individ.
BioProSim 1 mass transfer simulation
Fri
Lab Report on Algal Biotechnology 4 5
Penicillin a secondary metabolite? 7
BioProSim 2 chemostat simulation 8
Mon
Exam 2)
Mid-semester Exam 25
Chemostat Group Report 10
10 /12
End-semester Exam 40
Total

10. Type
Topic
Marks
Due
Week
Due Day
Group
Instant Lab Report on oxygen transfer 1 2
Thurs
Instant Lab Report on oxygen uptake 3
Individ.
BioProSim 1 mass transfer simulation
Fri
Lab Report on Algal Biotechnology 4 5
Penicillin a secondary metabolite? 7
BioProSim 2 chemostat simulation 8
Mon
Exam 2)
Mid-semester Exam 25
Chemostat Group Report 10
10 /12
End-semester Exam 40
Total

11. Fundamentals taught Bioprocesses convert S to P
Sugar to energy (biogas, ethanol, hydrogen, electricity)
Pollutants to harmless substances (dechlorination, degradation, dirty water to clean water
Need to be able to predict (modelling)
Quantify (rates)
Understanding (driving force, equilibrium)

12. Fundamentals taught Bioprocesses questions: Why ? How ? How fast?
What mechanism ?
Modelling

13. Learning tools used Bioprocess analysis (theory) Computer simulation
Bioprocess execution and analysis (Chemostat project)
Spreadsheets for data processing and analysis
Peer reviewed websites of scientific analysis of literature
Using computer learning activities
Industry trip
Focussed scientific writing.

14. Link between Research and Teaching
A number of undergraduates  honours  PhD  Senior Engineers (Water Corporation, Design companies, Bioprocess Operators)
Teaching topics drawn from own research projects and publications.
Input from current researchers into the project
Link to industry.
So, on many of the topics you talk to science experts, not just “teachters that obtained their knowledge from books”

15. http://sphinx.murdoch.edu.au/ units/extern/BIO301/teach/index.htm
Bioprocessing – Biotechnology:
Make money from bioprocesses
Inputs are of lower value than outputs (products)
Computer based learning activities (CBLA) are on
units/extern/BIO301/teach/index.htm

22. Lecture overview L1-3
Lecture 1: Intro, study guide, what is a bioreactor,
Learning by interacting
Lecture 2: 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, kLa
Lecture 3: 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

23. Molecular diffusion relies on random movement resulting in uniform distribution of molecules
The general principle of microbial degradation is based on taking up chemical compounds from the medium into the cell and processing it here. There is a number of exceptions that we don’t want to consider now. If a bacterial cell is suspended in still solution those chemical compounds that the bacterium needs seem to “flow” towards it, while compounds that the bacterium does not use do not. This seems to be a handy principle allowing the bacterium to obtain exactly what it needs. However, as this “apparently free delivery” of desired compounds involves shifting molecules from the bulk solution towards the cell, shouldn’t there be some energy source to do the work ? To verify whether the bacterial cell itself may be involved in this apparently directed flux of useful compounds, a test can be carried out with dead bacterial cells showing that the directed molecular flux does not occur to dead cells. Most science students have heard about the principle behind this phenomenon (diffusion). Let us try to go beyond merely learning the definition, the phenomenon or the mathematical formula of molecular diffusion and try to visualise or simulate what is happening.

24. Oxygen Transfer Rate (OTR)
Overview
Diffusion, how does it work, how can we predict it?
Diffusion is random … and yet predictable.
A simple model simulation can show that although the diffusion movement is random,
it can be precisely predicted for large number of molecules (e.g. Fick’s law of diffusion)

25. 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?

26. Oxygen solubility (cS)
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).
The saturation concentration is also the oxygen solubility
How soluble is oxygen?

27. Oxygen solubility (cS)
Oxygen is not very polar  poorly soluble in water.
Oxygen Solubility is described by Henry’s Law which applies to all gases
p = partial pressure of oxygen
k = constant depending on gas type, solution
and temperature
cS = concentration of oxygen dissolved in water
p = k*cS
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)

28. Oxygen solubility (cS)
Examples of using the proportionality between partial pressure of oxygen in the atmosphere and the saturation concentration cS:
p = partial pressure of oxygen
k = constant depending on gas type, solution
and temperature
cS = concentration of oxygen dissolved in water
p = k*cS
If the reactor is operated under 2 times atmospheric pressure (200kPa instead of 100 kPa air pressure), the new saturation concentration will be abou 16 mg/L instead of 8 mg/L.
If air (partial pressure = 0.21* 100 kPa) is replaced by pure oxygen atmosphere (partial pressure 100kPa) the oxygen saturation concentration is about 40 mg/L (more precise 8*100/21) instead of 8 mg/L.
How to calculate partial pressure? (refer to CBLA)

29. Concentration cs (mg/L)
Oxygen solubility (cS)
Effect of temperature
cs =
468
( T)
Concentration cs (mg/L)
Oxygen Saturation
Temperature (°C)
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).

30. Oxygen Transfer Rate (OTR)
(gradient, driving force)
Question: What is the driving force for oxygen dissolution?
At oxygen saturation concentration (cs): dynamic equilibrium exists between oxygen transferred from the air to water and vice versa.  No driving force
OTR
Answer: The difference between cS and the actual dissolved oxygen concentration (cL) is the driving force. OTR is proportional to the that difference. Thus:
OTR ~ (cS – cL)
Need to determine the proportionality factor

31. OTR – depends on DO (cL)
Significance of OTR: critical to know and to control for
all aerobic bioreactors
1. Deoxygenation (N2, sulfite + Co catalyst)
2. Aeration and monitoring dissolved oxygen concentration
(D.O. or cL) as function of time
3. OTR = slope of the aeration curve (mg/L.h or ppm/h) 5 10 8
Air On
cL (ppm)
Time (min)

32. OTR – depends on DO (cL)
4. Observation: OTR decreases over time (and with incr. cL)
5. OTR is not a good measure of aeration capacity of a bioreactor
6. OTR is highest at cL = zero (Standard OTR)
7. OTR is zero at oxygen saturation concentrations (cs)
8. OTR is negatively correlated to cL
9. 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 = kLa (cs - cL)
Mg/L/h h mg/L

33. OTR –Significance of gradient
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

34. 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 (cL)
11. The kLa value is a suitable parameter as it divides
OTR by saturation deficit:
OTR
(cs - cL)
kLa =
12. kLa = the key parameter oxygen transfer capacity.
How to determine it?

35. Lec 2 summary:
Oxygen is poorly soluble depending mainly on
partial pressure in headspace
Temperature
OTR is driven and proportional to driving force (cS-cL)
kLa is the proportionality factor (first order kinetics)
kLa describes the performance of a bioreactor to provide
Oxygen to microbes
Next lecture: quantify kLA

36. Lec 3 outlook: Aeration curve
Quantify OTR at a given point of an aeration curve
Quick estimate of kLa
Graphical determination of kLa
Mathematical determination of kLa
Run computer simulation to obtain data
Oxygen transfer efficiency (OTE)
OTR proportional to cs-cL
OTR inverse proportional to cL

37. OTR – Quick estimate of kLA
Example: determine OTR at 6 mg/L 5 10 8
Air On
cL (mg/L)
Time (min) 6
4.5 min
5 mg/L
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

38. OTR – quick estimate of kLA
kLa = OTR
(cs-cL)
= ppm / h
(8 ppm – 6 ppm)
= 3.3 h-1
Q: Problem with this method?
A: based on one single OTR slope measurement and unreliable to obtain from real data. DO
Time

39. OTR – Graphical determination of kLa
1. Monitor aeration curve
2. Determine graphically the OTR at various oxygen
concentrations (cL) 8 2 4 6 5 10
At 6 ppm: OTR = 25 mg/L/h
At 4 ppm: OTR = 50 mg/L/h
cL (ppm)
At 3 ppm: OTR = 60 mg/L/h
At 0.5 ppm: OTR = 30 ppm/h
Time (min)
3. Tabulate OTR and corresponding cL values
cL (mg/L)
Cs - cL (mg/L)
OTR (mg/L/h)
0.5
3.0
4.0
6.0
8.0
7.5
5.0
4.0
2.0
0.0 30 60 50 25

40. OTR – Graphical determination of kLa
4. Plot OTR values as a function of cs - cL.
Standard OTR
100
kLa = = 12 h-1
70 mg/L/h
6 mg/L
OTR (mg/L/h) cs 50 2 4 6 8
cs- cL (mg/L)
5. A linear correlation exists between kLa and the saturation
deficit (cs - cL) which is the driving force of the reaction.
6. The slope of the plot OTR versus cs - cL is the kLa value.
7. The standard OTR (max OTR) can be read from the intercept with
the cs line. (Standard OTR = 96 ppm/h)

41. • ( ) ( ) Mathematical Determination of kLa
1. OTR is a change of cL over time, thus = dcL/dt
2. kLa = dcL/dt
(cs- cL)
Integration gives •
Concentration (mg/L)
Dissolved Oxygen
ci = 6
co = 3 to ti
Time (min) cs ( )
cs - co
3. kLa = ln
cs - ci
ti - to ( )
8 - 3 ppm
kLa = ln
8 - 6 ppm
min
= ln 2.5
4.4 min
= 0.21 min-1
= 12.5 h-1

42. 4. This method should be carried out for
3 to 4 different intervals. By aver
5. Once the kLa is known it allows to calculate the OTR
at any given oxygen concentration:
OTR = kLa (cs - cL)

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

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

45. Oxygen Transfer Efficiency (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.

46. Oxygen Transfer Efficiency (OTE)
A bioreactor ( 3 m3) 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 = L air/h
(x 60)
= 2520 L O2/h
(x 21%)
= mol O2/h
(÷ 24.5 L/mol)
= 34.3 mmol O2/L.h
(÷ 3000 L)
2. OTR
100 mg/L.h = 3.1 mmol O2/L.h
(÷ 32 g/mol)
% OTE =
3.1 (mmol/L.h)
34.3 (mol/L.h)
X 100
= 9%

47. 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

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

49. OTR – from aeration curve to kLa summary
(first order kinetics)
(cs)
Air on
Dissolved Oxygen
Aeration Curve
Time
max OTR
Slope = kLa
Rate is proportional to concentration  First order kinetics
OTR (mg/L.h)
Dissolved oxygen [mg/L]
OTR = kLa (O2 saturation (cS) – O2 concentration (cL))

50. OTR – Aeration curve from CBLA
The transfer of oxygen from solution to headspace is important
During aeration of oxygen free water, the dissolved oxygen increases in a characteristic way

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