Biological Uranium (VI) Reduction in Fixed-Media and Suspended Culture Systems

Biological Uranium (VI) Reduction in Fixed-Media and Suspended Culture Systems
q
Biological Uranium (VI) Reduction in
Fixed-Media and Suspended Culture
Systems
by
Phalazane Johanna Mtimunye
A thesis submitted in partial fulfilment
of the requirements for the degree
Philosophiae Doctor (Chemical Technology)
in the
Department of Chemical Engineering
Faculty of Engineering, the Built Environment and Information Technology
University of Pretoria
Pretoria
April 2015
,
ABSTRACT
Biological Uranium (VI) Reduction in Fixed-Media and
Suspended Culture Systems
By
Phalazane Johanna Mtimunye
Supervisor:
Professor EMN Chirwa
Department:
Chemical Engineering
Degree:
Philosophiae Doctor (Chemical Technology)
Tailing dumps and process waste stockpiles at uranium mining sites and nuclear power
processing facilities contain significant levels of uranium. Uranium in the tailing dumps can
exist either as U(VI) or U(IV) depending on the pH and redox conditions within the dump.
However, it is desirable to keep uranium in the dump sites in its tetravalent form, U(IV),
since the hexavalent form, U(VI), is highly mobile and very toxic to aquatic life forms and
humans. Natural attenuation processes such as bacterial reductive/precipitation and
immobilization of soluble uranium emerge as viable method for remediating U(VI)
contaminated sites. For example, dissimilatory metal-reducing bacteria (DMRB) have been
investigated for their capability to remove uranium from aqueous solutions. These bacteria
were able to use U(VI) as an electron acceptor thereby reducing U(VI) to U(IV) which is
easier to remove from solution by precipitation.
In this study, the efficiency of indigenous culture of bacteria from the local contaminated site
in reducing U(VI) was evaluated using both batch and continuous flow bioreactor systems.
Because the stability of uranium in the tailing dumps and stockpiles of uranium concentrate at
uranium mining fields is affected by the pH, redox potential, the presence of complexing
anions in the waste rocks, toxic metals, organics, inhibitors, and chelators, the effect of these
factors in U(VI) bioremediation process was also evaluated in this study. Batch kinetics
ii
studies showed near complete U(VI) removal of up to 400 mg/L. Experiments on suspended
culture bioreactor system conducted in 10 L Erlenmeyer’s flask under shock loading
conditions also showed U(VI) removal of up 400 mg/L. Higher U(VI) removal rates achieved
in a suspended culture system operated without re-inoculation were associated with
continuous addition of nutrients and glucose in a bioreactor over time. This demonstrate the
effectiveness of carbon source and nutrients in enhancing U(VI) reduction process in
bioreactor systems.
Further experiments were conducted in a fixed-film, continuous flow bioreactor system to
evaluate the capacity of the indigenous mixed culture in reducing U(VI) under oxygen
stressed and nutrient deficient conditions. The experiments in the fixed-film bioreactor
system were conducted using columns with four equally spaced intermediate sampling ports
along the length to facilitate finite difference modelling of the U(VI) concentration profile
within the column. Near complete U(VI) removal of up to 85 mg/L was achieved in the
fixed-film bioreactor operated without organic carbon source. At higher U(VI) feed
concentration of 100 mg/L the bioreactor system was able to achieve the removal efficiency
of 60%. A sterile control column on the other hand showed insignificant U(VI) removal over
time, indicating U(VI) removal by biochemical processes. The shift in microbial culture was
monitored in the fixed-film bioreactor after 99 days of exposure to U(VI) using the 16S
rRNA genotype fingerprinting method.
The fate of U(VI) within a complex biofilm structure was predicted and evaluated using
mathematical modelling. The mathematical model developed in this study for describing the
biofilm system incorporated both the mass transport kinetics, microbial growth kinetics, and
reduction kinetics, thus the diffusion-reduction equation. The model successfully captured the
trends of U(VI) removal within the biofilm for different loading conditions. The validity of
the model in predicting U(VI) reduction within the bench-scale biofilm reactor at various
U(VI) concentrations demonstrated the feasibility of the model in predicting field scale
system and improving design and operation of site for clean-up.
iii
Declaration
I, Phalazane Johanna Mtimunye, hereby declare that the work provided in this dissertation
is to the best of my knowledge original (except where cited) and that this work has never
been submitted for another degree at this or any other tertiary education institution.
Signature of candidate…………………………… Date …………………………………..
,,
iv
Dedication
This dissertation is dedicated to
My family
My late father Klaas Mtimunye who has always believed in me and encouraged me to pursue
with my studies; I will forever be grateful for all his teachings and love
My one and only wonderful mother Lena Mtimunye for her ongoing support, endless love,
understanding, for believing in me always and encouraging me to always pray and ask God
for guidance. I really thank God for her because she is special.
My brothers and sisters who were always there for me every step of the way, I will forever be
grateful for their support and I really thank God for them
My friends who were always supportive and there when I needed to talk. I would never trade
them for anything in this world, because they really mean a lot to me and I love them beyond
measures.
v
Acknowledgements
First and foremost, I thank God the Almighty and my Saviour Jesus Christ for the many
blessings that he has bestowed upon me since birth. Without him I cannot achieve anything. I
thank God for the favour and for his sufficient grace in my life and I will forever praise him
for being God in my life and going with me through all my tribulations.
Regarding my doctoral studies at the University of Pretoria, I am thankful to several
individuals that contributed directly through guidance and help during my entire time of
study. I especially would like to express my gratitude to the following persons without whom
this dissertation would not be possible:
Professor Evans Chirwa my study leader who has always been doing his best to assist me and
inspired me through his supervision and motivation. I will forever be grateful for all the
efforts he took to assist in this study. May the good Lord bless him.
Professor Fanus Venter at the Department of Microbiology for assistance with the
characterization of bacterial isolates.
Microscopy Units at the University of Pretoria and NECSA, Phelindaba (South Africa) for
allowing me to use their equipment for the analysis of my samples.
I would also like to express my appreciation to the following organizations that made this
dissertation possible: SASOL Bursary Programme and National Research Foundation (NRF)
for financial support.
My sincere gratitude also goes to Christopher Mahlathi, Jonathan Shock, for their invaluable
advice which contributed effectively to this study.
I would also like to thank all my colleagues and Laboratory Technician for their friendship
and support. I have learned so much from all of you.
I would also like to thank the Pastor and all members of Charisma Community church in
Pretoria for his teachings. They really kept me going, positive, strong, and hopeful that all the
things work out for good for those who trust in the Lord. May the good Lord bless him.
vi
Table of Contents
ABSTRACT...............................................................................................................................ii
Declaration ................................................................................................................................ iv
Dedication .................................................................................................................................. v
Acknowledgements ................................................................................................................... vi
Abbreviations .......................................................................................................................... xvi
Symbol Nomenclature ...........................................................................................................xvii
CHAPTER 1 ............................................................................................................................. 1
INTRODUCTION.................................................................................................................... 1
1.1 Background ...................................................................................................................... 1
1.2 Objectives of the Study .................................................................................................... 3
1.3 Outline of Thesis .............................................................................................................. 4
1.4 Significance of Research and Main Findings ................................................................... 4
CHAPTER 2 ............................................................................................................................. 5
LITERATURE REVIEW ....................................................................................................... 5
2.1 Occurrence of Uranium in the Environment .................................................................... 5
2.2 Radiological Properties .................................................................................................... 5
2.3 Chemical Forms of Uranium ............................................................................................ 6
2.4 Production of Uranium and Its Use .................................................................................. 7
2.5 Uranium as a Fuel for Nuclear Power .............................................................................. 8
2.6 Radioactive Waste .......................................................................................................... 10
2.7 Classification of Radioactive Waste .............................................................................. 11
2.8 Waste from High Temperature Fast Reactors ................................................................ 12
2.9 Chemical and Radiological Toxicity: Risk to Human and Animal Health .................... 12
2.9.1 Chemical Toxicity ................................................................................................... 13
2.9.2 Radiological Toxicity .............................................................................................. 13
2.10 Remediation Strategies ................................................................................................. 14
2.10.1 Physical-Chemical Treatment................................................................................ 14
2.10.2 Biological Treatment Process ................................................................................ 16
2.11 Enzymatic U(VI) Reduction......................................................................................... 22
2.11.1 Geobacter Reductase ............................................................................................. 22
2.11.2 Shewanella Reductase ........................................................................................... 23
vii
2.11.3 Electron Donors and Competing Electron Acceptors............................................ 24
2.12 Cellular Localization .................................................................................................... 24
2.13 Emerging Treatment Technologies .............................................................................. 25
2.13.1 Biofilm Systems .................................................................................................... 25
2.13.2 Reactive Barrier Systems....................................................................................... 26
2.14 Summary ...................................................................................................................... 28
CHAPTER 3 ........................................................................................................................... 29
EXPERIMENTAL METHODS ........................................................................................... 29
3.1 Bacterial Culture ............................................................................................................ 29
3.1.1 Source and Isolation of U(VI) Reducing Microorganisms ...................................... 29
3.1.2 Purification of Indigenous Bacteria ......................................................................... 29
3.2 Growth Media ................................................................................................................ 30
3.2.1 Basal Mineral Media ............................................................................................... 30
3.2.2 Commercial Broth and Agar.................................................................................... 30
3.3 Characterisation of Microbial Community .................................................................... 30
3.4 Chemical Reagents and Standards ................................................................................. 31
3.4.1 Uranium Stock ......................................................................................................... 31
3.4.2 Arsenazo III Reagent ............................................................................................... 31
3.5 Experimental Batches ..................................................................................................... 31
3.5.1 Preliminary U(VI) Reduction Studies ..................................................................... 31
3.5.2 U(VI) Reduction on a Mixed-Culture of Bacteria ................................................... 32
3.5.3 Abiotic U(VI) Reduction Experiments .................................................................... 32
3.5.4 U(VI) Reduction Pathway Targets and Inhibitors ................................................... 33
3.6 Continuous Flow Suspended-Cell Bioreactor ................................................................ 33
3.6.1 Reactor Setup ........................................................................................................... 33
3.6.2 Start-up Culture ....................................................................................................... 34
3.6.3 Reactors Operation .................................................................................................. 35
3.7 Continuous Flow Biofilm Rector System ...................................................................... 35
3.7.1 Reactor Set-up ......................................................................................................... 35
3.7.2 Start-up Culture ....................................................................................................... 35
3.7.3 Reactor Start up ....................................................................................................... 36
3.7.4 Reactors Operation .................................................................................................. 36
3.8 Evaluation of Biomass Yield.......................................................................................... 37
viii
3.8.1 Total Biomass .......................................................................................................... 37
3.8.2 Viable Biomass Analysis ......................................................................................... 38
3.8.3 Protein Concentration .............................................................................................. 39
3.9 Analytical Methods ........................................................................................................ 39
3.9.1 Elemental Analysis by ICP-MS ............................................................................... 39
3.9.2 Determination of U(VI) ........................................................................................... 40
3.9.3 Determination of Total Uranium ............................................................................. 41
3.9.4 X-ray Powder Diffraction Analysis (XRD) ............................................................. 41
3.9.5 Fourier Transform Infrared spectroscopy (FTIR) ................................................... 41
3.9.6 Raman Spectroscopy ............................................................................................... 42
3.9.7 U(VI) Deposition Analysis using TEM ................................................................... 42
3.9.8 Elemental Scan using EDX ..................................................................................... 42
3.9.9 Scanning Electron Microscopy (SEM) .................................................................... 43
3.10 Statistical Methods ....................................................................................................... 43
3.10.1 Reliability Analysis ............................................................................................... 43
3.10.2 Quality Assurance.................................................................................................. 44
CHAPTER 4 ........................................................................................................................... 45
RESULTS FROM BATCH KINETIC STUDIES .............................................................. 45
4.1 Overview ........................................................................................................................ 45
4.2 Microbial Analysis ......................................................................................................... 45
4.3 Preliminary U(VI) Reduction Studies ............................................................................ 48
4.3.1 Performance Evaluation of Individual Isolates. ...................................................... 50
4.4 Mixed-Culture Performance ........................................................................................... 51
4.4.1 Abiotic U(VI) Removal ........................................................................................... 51
4.4.2 The Effect of Thioredoxin Inhibitors....................................................................... 51
4.4.3 The Effect of NADH-dehydrogenase Inhibitors ..................................................... 52
4.4.4 Biotic U(VI) Reduction ........................................................................................... 52
4.4.5 Biomass Analysis .................................................................................................... 55
4.4.6 Fate of Reduced Uranium Species in Cells ............................................................. 55
4.4.7 FTIR Spectroscopy .................................................................................................. 57
4.4.8 X-Ray Diffraction Analysis ..................................................................................... 59
4.5 Modelling Theory........................................................................................................... 61
4.5.1 Kinetic Model Adaptation ....................................................................................... 61
ix
4.5.2 Toxicity Effect of U(VI) .......................................................................................... 63
4.5.3 Parameter Estimation ............................................................................................... 63
4.6 Sensitivity Analysis ........................................................................................................ 68
4.7 Summary ........................................................................................................................ 68
CHAPTER 5 ........................................................................................................................... 70
KINETIC STUDIES OF CONTINOUS-FLOW SYSTEMS ............................................. 70
5.1 Background .................................................................................................................... 70
5.2 Conceptual Basis of Suspended Growth System ........................................................... 70
5.3 Suspended Growth System Kinetic Studies ................................................................... 71
5.3.1 U(VI) Removal Efficiency ...................................................................................... 71
5.3.2 Microbial Activity ................................................................................................... 72
5.3.3 The Effect of Nitrate ................................................................................................ 73
5.3.4 Impact of Redox and pH Conditions ....................................................................... 73
5.3.5 Performance Evaluation of the Suspended Growth System .................................... 74
5.4 General Principles of Bioremediation Technologies ..................................................... 75
5.4.1 Conceptual Basis of Biofilm System ....................................................................... 76
5.5 Attached Growth System Kinetic Studies ...................................................................... 78
5.5.1 Evaluation of the Abiotic Process ........................................................................... 78
5.5.2 Temporal Variation.................................................................................................. 79
5.5.3 U(VI) Concentration Profiles .................................................................................. 80
5.5.4 Biomass Analysis .................................................................................................... 83
5.6 Microbial Shift Dynamics .............................................................................................. 84
5.6.1 Characterization of Initial Inoculated Culture ......................................................... 84
5.7 Summary ........................................................................................................................ 88
CHAPTER 6 ........................................................................................................................... 89
MODELLING OF CONTIONOUS-FLOW SYSTEM ...................................................... 89
6.1 Biofilm Systems Background......................................................................................... 89
6.2 Basic Biofilm Model Assumptions ................................................................................ 90
6.3 Model Approach ............................................................................................................. 91
6.3.2 Analytical Methods of Biofilm Measurements ....................................................... 92
6.3.3 Hydraulic Characteristics ........................................................................................ 92
6.3.4 Liquid Layer Effect ................................................................................................. 93
6.4 Reactor Mass Balance .................................................................................................... 94
x
6.4.1 Mass Balance of Dissolved Species ........................................................................ 94
6.4.2 Biofilm Zone Mass Balance .................................................................................... 97
6.4.3 Biomass Mass Balance at Liquid Zone ................................................................... 98
6.5 Initialization and Simulation .......................................................................................... 99
6.6 Parameter Optimization.................................................................................................. 99
6.7 U(VI) Removal Kinetics .............................................................................................. 100
6.7.1 Bulk Liquid Phase Kinetics ................................................................................... 100
6.7.2 Biofilm Zone Kinetics ........................................................................................... 100
6.8 Model Validation.......................................................................................................... 103
6.9 Biofilm Thickness Kinetics .......................................................................................... 104
6.10 Steady-state Analysis ................................................................................................. 105
6.10.1 Model Formulation .............................................................................................. 105
6.11 Summary of Kinetic Parameters ................................................................................ 108
6.12 Summary .................................................................................................................... 109
CHAPTER 7 ......................................................................................................................... 110
SUMMARY AND CONCLUSIONS .................................................................................. 110
CHAPTER 8 ......................................................................................................................... 113
ENGINEERING SIGNIFICANCE AND RECOMMENDATIONS............................... 113
8.1 Significance of the Biofilm Reactor ........................................................................... 113
8.2 Future Research and Recommendations .................................................................... 113
REFERENCES ..................................................................................................................... 115
APPENDIX A ....................................................................................................................... 131
PROTEIN ANALYSIS STANDARD CURVE..................................................................... 131
APPENDIX B ....................................................................................................................... 132
Octave Version 3.0................................................................................................................. 132
APPENDIX C ....................................................................................................................... 133
Octave Version 3.0................................................................................................................. 133
RUNGE_KUTTA METHOD ................................................................................................ 133
xi
List of Figures
Figure 2-1: Nuclear fuel closed cycle ....................................................................................... 9
Figure 2-2: Microbial reduction of U(VI) to U(IV). Energy Transduction and Metal
Reduction (Mtimunye and Chirwa, 2013). ........................................................... 20
Figure 2-3: Theoretical representation of the microbial permeable reactive barrier system as
an intervention for U(VI) pollution in an unconfined aquifer system. ................. 27
,
Figure 3-1: Laboratory set-up of a suspended cells continuous flow reactor. ........................ 34
Figure 3-2: Laboratory set-up of a fixed-film continuous flow reactor. ................................. 36
<
Figure
4-1:
Phylogenetic
Microbacterieceae
analysis
and
results
showing
Anthrobacteriae,
the
(b)
predominance
of
Acinetobacter,
(a)
(c)
Chryseobacrerium, and (d) Bacillus species under U(VI) exposure. ................... 47
Figure 4-2: U(VI) reduction by individual species at the initial U(VI) concentration of (a),
(b) 30 mg/L, and (c) 75 mg/L after 48 hours of incubation. ................................. 49
Figure 4-3: Abiotic U(VI) reduction at the initial U(VI) concentration of 100 mg/L. ........... 53
Figure 4-4: U(VI) reduction at (a) low initial U(VI) concentrations (100-200 mg/L), (b) high
initial U(VI) concentrations (300-600 mg/L), and (c) pure isolates against mixed
culture.................................................................................................................... 54
Figure 4-5: Analysis of cell concentration during batch studies operation at various initial
U(VI) concentration (100-600 mg/L) (a) viable cell concentration before and after
12-24 hours of operation using plate count method, (b) protein concentration
before operation and after 48 hours of operation using BSA method. ................. 55
Figure 4-6: TEM scan and EDX spectrum of precipitate of (a) metal loaded biomass (Y6)
indicating deposition of uranium species on cell surface and EDX spectrum of
precipitate, (b) metal-free biomass........................................................................ 56
Figure 4-7: FTIR spectra of bacterial cell with and without metal. ........................................ 58
Figure 4- 8: Raman spectra of a mixed culture of bacterial with uranium and without
uranium. ................................................................................................................ 59
Figure 4-9: Background subtracted powder diffraction pattern of bacteria reduced uranyl
nitrate powder overlaid with stick pattern of (a) UO3, (b) U3O8, (c) deuterium
nitride uranyl phosphate, and (d) plutonyl hydrogen phosphate hydrate. ............. 60
Figure 4-10: Batch culture model validation at various U(VI) initial concentration of (a) 100
mg/L, (b) 200 mg/L, (c) 300 mg/L, (d) 400 mg/L, and (e) 600 mg/L. ................. 67
xii
Figure 4-11: Sensitivity test for the initial U(VI) concentration of 100 mg/L with respect to
optimized parameters in anaerobic batch system. ................................................. 68
,,
Figure 5-1: Evaluation of U(VI) reduction in at the initial U(VI) concentration of 100, 150,
200, and 400 mg/L and initial protein concentration of 184 mg/L. ...................... 72
Figure 5-2: Simultaneous evaluation of nitrate (62 mg/L) and U(VI) (100 mg/L) reduction.73
Figure 5-3: Evaluation of U(VI) reduction, and oxidation reduction potential (ORP) at the
initial U(VI) concentration of 100 mg/L in a suspended-growth biological reactor
system within the first 24 hours of operation. ....................................................... 74
Figure 5-4: Theoretical representation of the microbial permeable reactive barrier system as
an intervention for U(VI) pollution in an unconfined aquifer system. The graph
shows the U(VI) concentration and biomass propagation under optimum
operation conditions. U = hydroxide precipitates of reduction products. The
number of complexed hydroxyl ions, n, will depend on the charge on the
uraninite group UxOyn+ (Mtimunye and Chirwa, 2013). ....................................... 77
Figure 5-5: Performance of cell-free control reactor (R2) showing characteristics of
exponential rise in the effluent U(VI) as compared to the tracer. ......................... 78
Figure 5-6: Performance of attached growth system (R1) and cell-free control system (R2) in
stabilizing U(VI) under oxygen stressed conditions. Biomass reactor (R1) effluent
represents average experimental data from the last port. ...................................... 80
Figure 5- 7: Evaluation of U(VI) removal across the biofilm reactor over time at initial feed
concentration of (a) 75 mg/L, (b) 85 mg/L, and (c) 100 mg/L. ............................ 81
Figure 5- 8: Evaluation of U(VI) effluent across the reactor at initial feed concentration of
(a) 75 mg/L and (b) 100 mg/L. ............................................................................. 82
Figure 5- 9: Evaluation of biomass in the biofilm reactor showing rise to the viable attached
biomass density. .................................................................................................... 84
Figure 5- 10: SEM analyses of a support material (a) without cells, control, (b) with cells
attached on it as a biofilm. .................................................................................... 85
Figure 5- 11: Phylogenetic analysis results showing the predominance of the Gram-positive
bacteria (a-f) belonging to Microbacterieceae, Anthrobacteriae, Bacilli group
after shock loading treatment of U(VI). ................................................................ 87
,
Figure 6-1: Conceptual biofilm model.................................................................................... 92
Figure 6-2: Model simulation at the liquid phase of (a) U(VI) effluent (b) biomass activity in
the reactor inoculated with live culture from the local environment. ................. 101
xiii
Figure 6-3: Model simulation at the solid phase of (a) U(VI) effluent (b) biomass activity in
the reactor inoculated with live culture from the local environment. ................. 102
Figure 6-4: Simulation of biofilm thickness over time in the biofilm reactor ...................... 105
Figure 6-5: Model simulation of effluent U(VI) across the biofilm at (a) 75 mg/L, (b) 85
mg/L, and (c) 100 mg/L. Experimental data is the average effluent U(VI)
concentration of the last three sampling times where near constant U(VI) removal
was observed. ...................................................................................................... 107
xiv
List of Tables
Table 2-1: U(VI) reducing bacteria, their source, and preferred environmental conditions ... 21
,
Table 3-1: Biofilm Reactor Specification ............................................................................... 37
Table 3-2: Mineral composition of the tailing dumps soil samples ........................................ 40
,,
Table 4-1: Partial sequencing of URB isolated from soil samples of abandoned uranium mine
under facultative anaerobic conditions. ................................................................ 46
Table 4-2: Performance of individual species of isolates in reducing U(VI) ......................... 50
Table 4-3: Optimum kinetic parameters obtained using Monod-kinetic model with a constant
active biomass. ...................................................................................................... 64
Table 4-4: Optimum kinetic parameters obtained using cell inhibition model incorporated
with cell reduction capacity (Tu) (Equation 4-7). .................................................. 65
Table 4-5: Optimum kinetic parameters for pseudo-second order kinetic model incorporated
with cell inactivation term (Equation 4-8). ........................................................... 66
Table 6-1: Summary of kinetic parameters optimized in the biofilm system and applied
constraints. .......................................................................................................... 103
Table 6-2: Comparison of kinetic parameters at the bulk and solid phase ........................... 108
xv
Abbreviations
APHA
American public health agency
BLAST
Basic Logical Alignment Search Tool
U
Uranium
U(VI)
Hexavalent uranium
U(IV)
Tetravalent uranium
URB
U(VI) reducing bacteria
CFU
Colony forming units
DMRB
Dissimilatory metal reducing bacteria
DNA
Deoxyribonucleic acid
ETC
Electron transport chain
BMM
Basal mineral medium
NADH
Nicotinamide adenine dinucleotide
NADPH
Nicotinamide adenine dinucleotide phosphate
ORP
Oxidation-Reduction Potential
pH
Potential hydrogen
ppm
Parts per million
PVC
Polyvinyl chloride
PRB
Permeable reactive barrier
RT-PCR
Reverse transcriptase- Polymerase chain reaction
rDNA
Ribosomal deoxyribonucleic acid
rRNA
Ribosomal Ribonucleic acid
rpm
Rotation per minute
SEM
Scanning electron microscopy
SRB
Sulphate reducing bacteria
TEM
Transmission electron microscopy
US EPA
United States Environmental Protection Agency
WHO
World Health Organization
xvi
Symbol Nomenclature
Af
A(t)
bx
Dxw
Duw
dp
ID
ju
jx
ku
Ku
biofilm surface area [L2]
effective cross-sectional area of a reactor [L2]
cell death rate [T-1]
diffusion coefficient of particulate matter [L2T-1]
dissolved species diffusion coefficient [L2T-1]
particle size [L]
internal diameter [L]
dissolved species flux rate [ML-2T-1]
flux rate of particulate matter [ML-2T-1]
reaction rate coefficient [L3M-1T-1]
half velocity U(VI) concentration [ML-3]
kad
kd
kLU
µ
adsorption rate coefficient [T-1]
cell detachment rate [TM-1L-1]
mass transport coefficient[LT-1]
maximum specific cell growth rate [T-1]
Lf
Lw
L
ρf
Q
qc
ru
rx
Tu
t
U
U
biofilm thickness [L]
stagnant film thickness [L]
length of the reactor [L]
cell density [ML-3]
inflow rate [L-3T-1]
adsorption rate [ML-3T-1]
U(VI) reduction rate [ML-3T-1]
cell production rate [ML-3T-1]
U(VI) reduction capacity coefficient [MM-1]
time [T]
U(VI) concentration at time, t [ML-3]
U(VI) concentration at the surface [ML-3]
UB
Uf
Ur
U(VI) concentration in the bulk liquid phase [ML-3]
U(VI) concentration in the biofilm phase [ML-3]
U(VI) toxicity threshold concentration [ML-3]
Equilibrium concentration at surface area [ML-3]
flow velocity [LT-1]
volume of the reactor [L3]
biomass concentration at time, t [ML-3]
max
S
U eq
ѵ
V
X
Subscripts
U
B
f
w
o
s
uranium
in the bulk liquid phase
in biofilm
in water
initial
surface
xvii
CHAPTER 1
INTRODUCTION
1.1 Background
Energy affects every aspect of our lives. In the recent years, the demand for electricity in
many developed or developing countries around the world such as South africa has escalated.
The consumption of electricity in South Africa has been steadily increasing since the 1980s
and it is predicted that, by the year 2025, the electricity demand will exceed supply (Musango
et al., 2009). The unprecedented increase of energy demand due to population growth,
urbanisation, and industrialization puts a stress on the current non-renewable energy source –
fossil fuel. Generation of electricity using fossil fuel, notably coal and natural gas, contributes
significantly to greenhouse gases in the atmosphere. Concerns over energy resource
availability, global warming, and energy security have led to the future use of what was once
considered as a death market, nuclear power, to sustain economic growth. It has been
reported by Mourogov and co-workers (2002) that nuclear power can assist to reduce the
current output of CO2 emissions associated with the burning of fossil fuel in the atmosphere
by approximately 8% (Mourogov et al., 2002; Ngwenya, 2011). Among all the proposed
alternative energy sources such as wind, solar, and geothermal energy, nuclear energy offers
the most feasible altenative to fossil fuels as a base-load generation capacity. The other
alternatives such as solar and wind power can only be used as peak load capacity substitues
using the currently available technologies.
Although nuclear power holds promise of cleaner production in terms of carbon emission, the
technology introduces the problem of short-term and long-term radiotoxicity from waste
generated in the reactors and in processes for producing and reprocessing nuclear fuel. The
waste from nuclear fuel reactors contains approximately 95% U-238, 3% fission products
plus transuranic isotopes, 1% plutonium, and 1% U-235 (Soudek et al, 2006; WNA, 2008;
Chabalala, 2011). The waste component originating from nuclear energy generation accounts
for over 95% of the total volume of the radioactive waste and is classified as high level waste
(HLW). Large quantities of low-level waste are also created due to the leakage of uranium
fission products [cesium (70Cs+), strontium (90Sr2+), and cobalt (60Co2+)] into the spent fuel
pools from cracks in the fuel cladding (Singh et al., 2008). Fission products comprise of
1
lighter elements than uranium and transuranic elements. Among the above listed fission
elements, strontium (90Sr2+) causes the most environmental concern due to its relatively long
half-live of radioactive decay. Upon reaching the environment, radiostrontium-90 (90Sr2+)
may easily be taken up by plants and other animal life forms (Ajlouni, 2007). Moreover,
because its chemical properties resemble that of Ca2+ which is a critical component of the
mammalian bone structure,
90
Sr2+ may be easily incorporated into bone tissue. When
incorporated in the organism in such manner,
90
Sr2+ may continuously irradiate localized
tissues with eventual development of bone sacroma and leukaemia (Chen, 1997). Therefore
as a result of their radiotoxicity to living organisms in the environment uranium and its
fission products are considered as the most hazardous elements in the nuclear fuel waste
stream that requires special attention.
In the past, radioactive waste from the nuclear reactors was stored underground for decades
using engineered systems with the primary objective of permanently isolating the disposed
waste from the biosphere (Merroun et al., 2008). The main concern about this method of
disposal is associated to the possibility of radioactive waste escaping and migrating from the
radioactive waste repository site into groundwater systems rendering groundwater unsuitable
for use as portable water supply. Cleanup of sites already contaminated with uranium and
other radionuclides involves application of abiotic processes with pump-and-treat or dig- andtreat methods that require follow up precipitation or immobilization steps using chemicals
(Gavirelsceu, 2009; Mtimunye and Chirwa, 2013). These methods are not suitable for
treatment of contamination at large scale since they are cost intensive. Additionally, chemical
products used for treatment generate harmful residuals and by-products that are also difficult
to treat. Microbial reduction of highly mobile U(VI) to relatively insoluble U(IV) as a normal
function of their metabolism offers promise as a technology that could play an important role
in the remediation of U(VI) polluted sites.
In situ immobilization of uranium has been suggested as a potential alternative strategy for
containing or attenuating the spread of U(VI) in groundwater systems. Recently, a more
detailed and long term investigation on in situ bioremediation of uranium was carried out at
the field site in Rifle, Colorado (Anderson et al., 2003; Wu et al., 2006; Chirwa, 2011) using
pure culture of Geobacter species. In situ bioremediation of uranium at the site was
facilitated by addition of external electron donor to stimulate the growth of Geobacter
species.
2
Although, the later study was effective for fundamental understanding of interaction taking
place between the cells and the metals, results from the previous study does not provide a
robust understanding between the field and laboratory studies. This is because in nature
microorganisms rarely exist as separate pure cultures. Moreover, the addition of external
carbon source does not give a clear indication of the cells potential in reducing metals in
actual groundwater systems characterized by low nutrient concentration.
The present study evaluates the potential of indigenous mixed-culture of bacteria in reducing
U(VI) in the environment under nutrient deficient conditions without the addition of any
external organic carbon source. The remidaiation technology proposed in this study has the
potential of minimizing cost and negative impacts associated with addition of foreign
materials into the actual system. Fundamental knowledge and understanding of kinetic
processes taking place within a bioreactor system will be valuable in developing appropriate
remediation and waste management strategies as well as predicting the microbial impacts on
the long-term stewardship of contaminated sites.
1.2 Objectives of the Study
The main objective of this study was to evaluate the prospect of uranium control in the
environment and to achieve separation and recovery of radionuclides in waste using natural
microbial processes. To achieve the primary objective, different experimental tasks were
conducted on U(VI) reduction process:
•
To investigate the kinetics of U(VI) reduction in indigenous U(VI) reducing bacteria
under oxygen stressed conditions in batch reactors over a wide range of initial U(VI)
concentrations.
•
To characterize the electron flow pathway of U(VI) reduction in facultative anaerobic
bacteria.
•
To evaluate U(VI) reduction in continuous-flow bioreactor systems (suspended-growth
and fixed-film bioreactor systems) over a range of U(VI) feed concentrations.
•
To investigate change in the microbial culture diversity during U(VI) bioremediation in
continuous-flow bioreactor systems.
•
To develop a mathematical model that predicts the movement of the contaminant across
the biofilm reactor at both transient and steady-state.
3
1.3 Outline of Thesis
The outline of this dissertation is subdivided into three main parts:
Literature Review – The initial step towards the methodology of this study was to collect as
much information as possible related to the impacts of U(VI) contamination in the
environment and current treatment practices from literature. This section contains the
background information of the study and the records of recent developments on the U(VI)
bioremediation process. The information is focused on the occurrence of uranium in the
environment, impact of uranium on human health, animals, and microorganisms, remediation
strategies, U(VI) reducing microorganisms, and biological U(VI) reduction pathways.
Materials and Methods – illustrate all the materials and methods used to conduct the
research.
U(VI) Reduction Kinetic Studies – contains the performance evaluation of U(VI) reduction
bacteria under various conditions, the kinetic modeling of the batch and continuous-flow
bioreactor system.
1.4 Significance of Research and Main Findings
Nuclear energy is currenly receiving special attention as an alternative energy source in many
countries around the world due to its ability of producing electricity with low carbon outputs.
Although the perception of the public towards the nuclear power technology is steadily
improving; however some of the leading problems associated with this technology still
remain. Currently, no suitable alternative route of radioactive waste treatment has been yet
formulated, while in the interim huge amount of nuclear spent fuel are discharged globally
(Lior, 2008). Many tailings sites all over the world remain unremediated mainly due to cost
and the ineffeciency related to the currently used conventional methods. In this study,
experimental results on a packed-bed bioreactor system demonstrated the feasibility of
biological treatment of U(VI) contaminated waste stream with a further possibility of
recovery of the reduced uranium. Both processes could contribute in the protection of natural
water resources from radiotoxic wastewater arising from uranium mineral processing
faclities, medical and research facilities.
4
CHAPTER 2
LITERATURE REVIEW
2.1 Occurrence of Uranium in the Environment
Uranium in its elemental form is characterised by a silver-white colour. It is a ductile,
malleable, and pyrophoric metal with an atomic number of 92. Uranium is slightly softer than
steel and has a specific density of (19 g/cm3) and it is 1.6 times more dense than lead (Blesie
et al., 2003). Uranium is ubiquitous in the environment. It is found in varying but small
amounts in air, soil, rocks, ocean, and the seas. It is actually more abundant than metals such
as gold, silver, cadmium, and more or less as common as tin, arsenic and cobalt (Todorov and
Ilieva, 2006). Uranium can exist in the environment as complex ores, soluble oxyions, and
hydroxide complexes. Examples of natural uranium compounds are pitchblende, uraninite,
carnotite, autunite, uranophane, and tobernite. These compounds can be detected in monazite
sands, phosphate rocks, and phosphate fertilizers. The concentration of natural uranium in the
earth’s crust is about 2.8 mg/kg. Vast amounts of uranium occur in the world’s oceans,
groundwater, plants, and animals. On average about 90 µg of uranium exist in human body
from normal intakes of air, water, and plants. About 66% of uranium is found in the skeleton,
16% in liver, 8% in kidneys, and 10% in other tissues (WHO, 2001). Volcanic eruptions can
intermittently increase the uranium concentration above the background level in the locale of
the eruption. However, the main input of uranium to water bodies is determined to be from
weathering of rocks, wet precipitation, dry fallouts from the atmosphere, and run-off from
terrestrial systems.
2.2 Radiological Properties
In the earth crust, natural uranium exist mainly as three different radioactive isotopes,
namely: U-238 (99.26%), U-235 (0.72%), and traces of U-234 (0.01%) (Bleise et al., 2003;
WNA, 2008). These isotopes have similar chemical properties, but different radiological
properties. Uranium-238 (U-238) and uranium-235 (U-235) are the parent nuclides of two
independent decay series, whereas U-234 is a decay product of the U-238 series. All uranium
isotopes undergo the same chemical reactions in nature and possess almost identical physical
characteristics such as melting point, boiling point and volatility. Radiological properties
such as the decay rate, half-life, and specific activity are different for each isotope. Uranium5
238 has a specific radioactivity of 12.455 Bq/g (half-life of 4.47×109 years), U-235 has a
specific radioactivity of 80 Bq/g (half-life of 7×108 years), and U-234 has a specific
radioactivity 231×106 Bq/g (half-life of 2.46×105 years) (Bleise et al., 2003; WNA, 2008).
The smaller amount of U-234 is more radioactive than any other uranium isotope. The low
concentration of U-234 in nature is attributed to its fast decay rate as evidenced by its short
half-life (2.46×105 years).
2.3 Chemical Forms of Uranium
Uranium exists in the environment mainly as oxides, organic or inorganic complexes, and
rarely as a free metal ion (Mtimunye and Chirwa, 2013). Free elemental uranium primarily
exists in higher oxidation states typically bound to oxygen. The oxygen bound uranium exists
mainly as triuranium octaoxide also known as pitchblende (U3O8), uraninite (UO2), and
uranium trioxide (UO3) (Stefaniak et al., 2009). U3O8 is relatively insoluble in water and
relatively stable over a wide range of environmental conditions. UO2 on the other hand is not
as stable as U3O8 in the environment as it may undergo alteration under various
environmental conditions (Senanayake et al., 2005). Upon exposure to air, UO2 is subjected
to oxidation and as a result produces a secondary mineral (UO22+) which complexes easily
with phosphates, carbonates, silicates, and sulphates (Senanayake et al., 2005; Stefaniak et
al., 2009).
The chemistry of uranium and other radionuclides in the environment is totally dependent on
their oxidation states. The natural uranium exists in the four oxidation states, i.e., trivalent
uranium [U(III)], tetravalent uranium [U(IV]), pentavalent uranium [U(V)], and hexavalent
uranium [U(VI)]. U(IV) and U(VI) are the most stable oxidation states in the environment
(Francis, 1998; Gavrilescu et al., 2009). Uranium (III) may easily oxidize to U(IV) while
U(V) readily disproportionate to U(IV) under most reducing conditions found in nature. The
highly soluble U(VI) ion mainly exist as UO22+ (uranyl) under oxidising conditions, while
U(IV) exist as sparingly soluble UO2 (uraninite) under reducing conditions. In soil of pH
range 4-7.5, uranium typically exits in the hydrolysed form UO2(OH)42- while in water
uranium typically exists as hydroxyl carbonate complexes such as (UO2)2CO3(OH)3-,
UO2(CO3)22-, UO2CO30, and UO2(CO3)4- (Roh et al., 2000).
6
2.4 Production of Uranium and Its Use
Although there are several uranium mining activities around the world, about 66% of all the
uranium extracted comes from only ten mines. The rest of the sources are distributed among
the low output mines and uranium recovered from waste streams of gold and copper mining.
Uranium mining involves open cut mining (30%), underground mining (50%), and in situ
leach (ISL) mining (20%). Open cut mining is applied where the ore bodies lie close to the
surface (250 m deep), whereas underground mining is applied where the ore bodies lie
deeper, and involves construction of access tunnels and shafts. In the case of ore bodies that
lie in groundwater resources, in situ leaching mining is applied which involves oxygenating
of groundwater and pumping it out to a treatment plant on the surface. In South Africa,
uranium production has generally been a by-product of gold or copper mining. The
concentration of uranium recovered as a by-product from the treatment of other ores is
however relatively small as compared to that from the ore bodies mined primarily for their
uranium content. Thus, it is about 10% of that from the ore bodies mined primarily for their
uranium content. In South Africa only about 7% of the world’s available uranium can be
recovered from waste streams of gold and copper processing.
For many years (from as early as 79 AD) prior to the discovery of its radioactive properties,
uranium was primarily used as a colorant in ceramic glazes, producing orange-red to lemonyellow color. It was also used in early photographs for tinting and shading. Later in 1896,
Henry Becquerel discovered its radioactive properties (Gavrilescu et al., 2009). Soon after
that, old uranium deposits were mined to obtain its decay product, radium (Ra) which was
used in luminous paint, particularly for dials of watches, and aircraft instruments. From 1940
to 1970, almost all of the uranium that was mined was used in the production of nuclear
weapons. For example, during the later stages of World War II, the entire Cold War, and to a
lesser extent afterwards, uranium has been used as the fissile explosive material to produce
nuclear bombs (1950-1980). In recent times, uranium is significantly used as a fuel in nuclear
reactors to generate electricity. Smaller specially built reactors have been used with uranium
as a fuel to produce isotopes for medical and industrial purposes around the world. Moreover,
uranyl acetate and uranyl formate is still used to produce electron-dense stains in
transmission electron microscopy to increase the contrast of biological specimens in ultrathin
sections and in negative staining of viruses, isolated cell organelles, and macromolecules. In
very small amounts uranium salts are still also used as mordents of silk or wool and in leather
and wood industries for stains and dyes (ATSDR, 1999).
7
2.5 Uranium as a Fuel for Nuclear Power
Uranium is sourced from rich ores with concentrations up to 10%. However, ores with
uranium oxide concentration as low as 0.2% are also mined and are the most common
(Sovacool, 2008; Tudiver, 2009). Uranium producers have been able to utilise ores with
uranium oxide concentration as low as 0.0004%. Uranium is recovered from ore by
communition of the rocks followed by leaching using alternative solutions of acid and/or
alkaline chemicals. The end product from ore milling and leaching results into a bright
yellow powder called yellow cake (U3O8) which is about 75-90% uranium oxide (Sovacool,
2008). Before this uranium oxide concentrate can be used in a reactor for generating
electricity, it must first be converted into uranium hexafluoride (UF6), which is used in a
gaseous diffusion enrichment process. During the uranium enrichment process, U235
concentration is increased to least 3.5% for atypical commercial light water reactor and up to
4-5% for other modern reactors while at the same time the U238 isotope is decreased notably.
Suffice to say U235 is the only natural occurring isotope that can sustain a fission chain
reaction by capturing neutrons and splitting into two parts yielding large amount of energy
(Soudek et al., 2006; WNA, 2008). On average, the specific radioactivity of natural uranium
is 25 kBq/g, double that of U238. During its decay process uranium may generate 0.1
watts/tonne which is enough to warm the Earth's mantle (WNA, 2008).
After the enrichment process, about 85% of oxide comes out as waste in the form of depleted
UF6 and the remaining 15% emerges as enriched uranium and is converted into ceramic
pellets of UO2. Fresh UO2 which contains up to 5% of U235 (hereafter presented as U-235) is
then packaged in zirconium alloy tubes and bundled together to form fuel rod assembles for
reactors. Thereafter, the used reactor fuel which contains up to 95% U238 (also presented as
U-238), 3% fission products and transuranic isotopes, 1% plutonium, 1% U-235 is removed
and stored to be reprocessed prior to disposal (Soudek et al., 2006; WNA, 2008). During the
reprocessing stage, uranium (U-235) and plutonium (Pu-239) are separated from the spent
fuel using the PUREX method and then reused as mixed oxide (MOX) fuel in the reactor.
This process is referred to as the close fuel cycle (Figure 2-1).
As of the year 2010, there were approximately 438 nuclear power plants in operation in 31
countries around the world providing about 14% of the world’s primary energy needs. The
world’s nuclear generating capacity currently stands at about 372 GWe, with the United
States of America, and France being the leading producers of the world nuclear energy, at
8
27%, and 17%, respectively (IAEA, 2009; 2011). The slow progression towards wider
application of nuclear energy technology in many countries of the world since 1986 has
mainly been due to concerns over famous reactor accidents such as those which occurred in
Three Mile Island, Chernobyl, and Fukushima; the possibility of proliferation of atomic bomb
making materials to renegade regimes and terrorists; and long term radiation contamination
(Mtimunye and Chirwa, 2013).
Waste Rock
Open pit/ underground Mining
Uranium Mill
Tailings
Milling
Uranium ore
Uranium Ore Concentrate (U3O8)
Conversion to Uranium hexafluoride (UF6)
UF6 Enrichment (eUF6)
Fuel fabrication
Reprocessing
Uranium
MOX
Plutonium
235
Enriched UO2, increase 0.7%U
to 3-5% U
235
Reactor
Spent Fuel
Interim
storage
Disposal
Figure 2-1: Nuclear fuel closed cycle
In the developed world, most nuclear power plants in operation today have reached or are
nearing their design life. Most of these power plants were constructed in the 1960’s and
1970’s. These reactors include light water cool reactors (LWRs), pressurized water reactors
(PWRs), and boiling water reactors (BWRs) all of which rely on enriched uranium oxide as a
9
fuel and water as a coolant. These reactors need to be decommissioned and dismantled and be
replaced by new environmentally sustainable nuclear power reactors with improved safety
features. Examples of these new power generation reactors include high temperature reactor
(HTR) and the Pebble Bed Reactor (PBR) technology. This fourth generation (Generation
IV) reactor technology utilizes graphite as the neutron moderator and inert gas such as helium
instead of water in the reactor core as a coolant (Koster et al., 2003). Because these reactors
can be allowed to operate at higher temperatures than the conventional water cooled reactors,
the efficiency of the system is greatly enhanced. To avoid catastrophic events such as
Chernobyl 1984 in Ukraine, new designs with inherent safety based on helium-cooled, selfregulating Bryton cycle have been researched (IAEA, 2002; Poullikkas, 2013). Systems such
as the Pebble Bed Reactor prevent fuel elements from ever coming into contact with each
other by encasing them in graphic and carbide protective layers. It is therefore said that a
PBR cannot melt down under overloaded conditions (McConnell, 2012; Poullikkas, 2013).
2.6 Radioactive Waste
Uranium mining has always been a strategic issue for profit generation in countries involved
in nuclear energy, quite often prioritized over the environment protection. Uranium ore
mining and milling of lower grade uranium ore with uranium oxide concentration of (0.1%0.2%) to produce the uranium concentrate (U3O8) yields large amount of radioactive waste.
This is mainly because about 1000 tons of rocks are required to produce 1 ton of yellow cake
of 75-90% purity. The waste rock generated from uranium ore mining contain minerals of
interest such as radium (Ra) which has high commercial value and base metals. Extraction of
Ra from the waste rocks also releases prodigious quantities of uranium waste which become
an ever growing environmental legacy. The uranium waste resulting from uranium ore
mining and milling to generate U3O8 concentrate and other minerals of commercial value
ultimately yield a fine sandy tailing which contains a wide range of radioactive materials
associated with mineral ore processing (WNA, 2008; Stefaniak, 2009). This waste is
radioactive and, if not treated or managed properly, may cause long-term radiation pollution
to air and water resources.
Uranium mining to extract Ra and U3O8 is not the only source of potential radioactive
pollution in the environment. Other activities such as radioisotope manufacturing and
biomedical research have also contributed significant amounts of radioactive waste into the
environment (Tikilili and Chirwa, 2011). Moreover, the radioactive waste generated from
10
various industrial activities contains various radioactive materials such as irradiated organic
compounds and fission products (Ngwenya, 2011; Tikilili and Chirwa, 2011).
2.7 Classification of Radioactive Waste
Several categories of radioactive waste are produced in the nuclear industry ranging from
highly radioactive waste to low radiation level waste. A detailed categorization of the
radioactive waste is provided by the United States Nuclear Regulatory Commission
(http://www.nrc.gov/waste); the main categories are summarized below.
Low Level Waste (LLW): primarily generated from hospitals, radioisotope manufacturing
industries, and nuclear fuel cycles. It comprises of lightly contaminated items like, papers,
working tools and clothes from power plant operation. It accounts for about 1% of the total
volume of the radioactive waste. It does not require shielding during handling and
transportation and is suitable for shallow land burial.
Intermediate Level Waste (ILW): results from fuel processing, and nuclear reactor
decommissioning. It comprises of used filters, steel components from within reactor. It
accounts for about 4% of the total volume of the radioactive waste. Shielding of ILW
generally depends on the source of the waste. For example, the waste from reactors such as
filters does not require shielding and can be buried in a shallow repository as a result of its
short-live radioactivity. Waste from fuel processing on the other hand requires shielding and
should be buried deep underground taking into consideration longer half-lives.
High Level Waste (HLW): results from nuclear weapons processing and from the use of
uranium fuel in nuclear reactors. The high level waste includes uranium and its fission
products, and transuranic elements which accounts for over 95% of the total radioactivity of
radioactive waste (IAEA, 2009). The lightweight fission products emanating from nuclear
fuel processing plants includes caesium (Cs-137), strontium (Sr-90), and cobalt (Co-60).
These elements are characterised by very high radiological decay rates and short half-lives.
As a result of the long half-lives of these elements, the waste containing these elements may
not be disposed off and handled as the LLW and ILW.
Transuranic Waste (TRU): As defined by United States of America’s regulations,
transuranic (TRU) waste is without regard to source or form, waste that is contaminated with
alpha-emitting trans-uranium radionuclides with half-lives greater than 20 years, and activity
11
greater than 100 nCi/g of waste but not including HLW. Transuranic elements are elements
with atomic number beyond that of uranium (92). These elements include plutonium,
neptunium, americium, and others. Transuranic elements have been released in the
environment (air, soil, and water) as consequence of nuclear weapon testing, and reactor
accidents. It consists of clothing, tools, rags, residues, debris and other such items
contaminated with small amounts of radioactive elements mostly plutonium. Because of the
long half-lives of these elements, TRU waste may not be disposed off as either LLW or ILW.
It does not have the very high radioactivity of HLW or its high heat generation. The United
States currently permanently disposes off transuranic waste of military origin at the Waste
Isolation Pilot Plant.
2.8 Waste from High Temperature Fast Reactors
High Temperature Gas-Cooled Reactors (HTGR), also known as Fast Reactors, mostly utilise
graphite as the fission reaction moderator. Graphite in the fast reactors is used either as part
of the structural materials for the reactor core vessel or as fuel containment elements in the
form of pebbles (spheres). The graphite used from natural sources contains non-carbon
impurities within the carbon matrix. Among these impurities are oxygen and nitrogen from
entrapped air, cobalt, chromium, calcium, iron, and sulfur (Khripunov et al., 2006). Upon
exposure to high neutron flux, most of the impregnated impurities are expected to transmute
to unstable radioactive forms. Impurities such as transitional metals Cr6+ and Co2+ may also
be found in the radioactive forms.
Improper disposal of radioactive wastes from nuclear power plants and various industrial
activities as a result of cost related issues and other issues may pose a threat to living
organisms including mammals as these elements may easily be taken up by plants and other
animal life forms upon reaching the environment (Ajlouni, 2007).
2.9 Chemical and Radiological Toxicity: Risk to Human and Animal Health
Uranium compounds from the environment can enter the human body through three main
routes of exposure thus, ingestion, inhalation, and dermal contact. Inhalation and ingestion is
the most likely route of uranium exposure while dermal contact is relatively an unimportant
type of exposure. Uranium has both chemical and radiological toxicity. The permissible body
level for soluble compounds is based on chemical toxicity, while the permissible body level
for insoluble compounds is based on radiological toxicity. The toxicity of uranium
12
compounds is closely related to its mobility. That is, the more soluble the uranium
compound, the more toxic it is to organisms (Craig, 2001; Winde, 2010). The less soluble
uranium compounds which include UO2, U3O8, UO3, UF4, uranium hydrides, and carbides
are less reactive in mammalian cells as they dissolve slowly in body fluids (weeks for UO3 to
years for U3O8 and UO2) while the highly soluble uranium compounds such as UF6, UCl4,
UO2F2, UO2(NO3)2, UO2Cl2, uranyl acetate, uranyl sulphates, and uranyl carbonates, exhibit
high toxicity to mammalian cells.
2.9.1 Chemical Toxicity
The major chemical toxicity associated with exposure to soluble uranium compounds through
inhalation or digestion is kidney failure. The inhaled or digested uranium compounds enter
the blood stream where they are filtered by the kidneys. At lower intake levels around 25 to
40 mg, damage can be detected by the presence of protein and dead cells in the urine.
However, high uranium intake ranging from about 50 to 150 mg, may cause acute liver or
kidney failure and even death (Choy et al., 2006; Xie et al., 2008). The high toxicity effect
associated with insoluble uranium compounds is largely due to lung irradiation by inhaled
particles. After entering the bloodstream, the adsorbed insoluble uranium compounds tend to
bioaccumulate and stay for years in bone tissue because of uranium affinity for phosphate.
Additionally, the accumulation of these insoluble uranium compounds in lungs over time
may lead to increased risk of cancer (WHO, 2001).
2.9.2 Radiological Toxicity
Several human health effects are also associated with exposure to radiation from uranium. In
general, U-235 and U-234 pose much greater radiological health risk than U-238 as they have
much shorter half-life, decay quicker, and therefore are more radioactive. All uranium
isotopes (U234, U235, U238) emit (alpha) α-particles that have little penetrating ability that are
unable to penetrate even the superficial keratin layer of human skin. This is because the
particles are relatively large and have a positive charge. Therefore, radiation hazard from
soluble uranium compounds primarily occurs when uranium compounds are ingested or
inhaled, representing an internal radiation hazard (Craig, 2001).
Uranium isotopes may also emit beta and gamma particles during their decaying process to
stable lead isotopes. Beta-particles have greater ability to penetrate the skin than alpha
particles while gamma rays are have extremely high penetrating ability than both alpha and
13
beta particles, and may present both an internal and external hazard. Consequently, exposure
to low levels of external radiation emanating from uranium decay products in the vicinity of
large quantities of uranium in storage or in processing facility may result to radiation hazard.
At the exposure levels associated with the handling and processing of uranium, the primary
radiation health effect of concern is associated to the increased probability of developing
cancer over time as the uranium uptake increases (UNSCEAR, 1999; Mtimunye and Chirwa
2013). Uranium is also known as a teratogen as it can cause birth defects.
The huge volume of radiotoxic waste on soil, surface water, and groundwater systems
associated with improper disposal of spent fuel waste from the nuclear reactor has led to
multidisciplinary studies that evaluate the impact of uranium and its decay products in the
environment.
2.10 Remediation Strategies
Treatment is performed on nuclear waste to achieve one or all of the four targets for handling
of waste: waste minimization, toxicity reduction, volume reduction, and/or security
(deterrence of proliferation). The targets can be achieved through physical, chemical, or
biological processes that may be applied either in situ or ex situ.
,,,,
2.10.1 Physical-Chemical Treatment
Physical-chemical treatment strategy for uranium and other radioactive waste involves the
physical extraction of the radioactive component based on its chemical charge or size to
reduce the volume of radioactive waste followed by treatment of the bulky waste using
conventional methods (Chirwa, 2011). Processes that have been tried include ion exchange,
chemical oxidation, membrane, and adsorption processes.
Ion exchange Process
Ion exchange is a unit process by which ions of given species are displaced from an insoluble
exchange material by ions of a different species in a solution. In the ion exchange process
uranium-containing solution enters one end of the column under pressure and passes through
a resin bed which separates the uranium from the solution. Most ion exchange resins are not
selective and therefore may not be effective in removing metallic elements from nuclear
waste. Several specially designed resins that target specific species by manipulating the
composition of the functional groups have been tested for removal of uranium from waste
14
streams (VanLam et al., 2000; Zaganiaris, 2009). Although, proven to be successful on pilot
scale, full implementation of ion exchange for uranium separation is hindered by high cost.
Additionally the ion exchange resin surfaces are not self-regenerating, and therefore have
limited capacity for adsorption (Zaganiaris, 2009).
Membrane Processes
A membrane is a semi-permeable barrier between two phases, which restrict the movement of
molecules in a very strict manner. These movements are based on size exclusion, differences
in diffusion coefficients, electrical charge, and solubility. Conventional membrane systems
used in treating uranium includes, nano-pore filtration, ultrafiltration, microfiltration, and
reverse osmosis (Pabby et al., 2008). Nano-pore membrane technologies have high potential
due to their ability to separate radioisotopes from water or gas streams. Membrane processes
are quite dependable and possess significant processing capabilities such as the ability to
capture pollutants for cleaning and recycling. Lately, the economic viability of these
processes has improved due to the decline in cost of membranes. However, the common
limitation associated with the membrane processes is the generation of considerable
quantities of radioactive solid waste in the brine. Furthermore, the treated liquid effluent is
not pure enough for environmental discharge or recycling.
Chemical Extraction
Chemical extraction processes involve the use of sodium carbonate/bicarbonate and citric
acid to extract uranium from contaminated soil (Phillips et al., 1995; Gramss et al., 2004).
Although this process is proven to be effective in recovering or extracting uranium from the
contaminated soil, extra care should be taken with quantity of citric acid or sodium carbonate
used, because additional quantities may result into further uranium migration which may
heavily pollute many natural ecosystems (Gramss et al., 2004; Kantar and Honeyman, 2006).
On the other hand, oxidizing/reducing agents added to matrix to treat one metal could
transform other metals in the system into mobile and toxic forms (NAS, 1974). Additionally,
the long-term stability of reaction products is of concern since changes in soil and water
chemistry might create conditions where the detoxified forms are reversed back to toxic
forms.
15
2.10.2 Biological Treatment Process
Biological methods have been proposed to improve or substitute the conventional physicochemical methods for the remediation of contaminated environments. Biological methods can
be applied either in situ or ex situ. However, for areas that have already been contaminated, in
situ treatment options are preferred for preventing further migration of the pollutants. In situ
treatment options are considered as environmentally friendly waste management methods as
they cause fewer disturbances on site and also minimize the risk associated with toxic waste
transportation (Doherty et al., 2006; Gavrilescu, 2006; Olexsey and Parker, 2006).
Unlike organic compounds, toxic metals cannot be degraded or destroyed but can only be
reduced from a high oxidation state to a lower oxidation state. Microbes have the potential to
interact with metals and radionuclides in natural and synthetic environments altering their
physical and chemical state such as its oxidation state, solubility, and sorption properties.
Different mechanisms by which microbes remove or immobilize metals and radionuclides
include (i) biosorption to cell components or extracellular polymeric substance (EPS), (ii)
bioaccumulation, (iii) bioprecipitation by reaction with inorganic ligands such as phosphate,
and (iv) bioreduction of soluble metal to insoluble metal (Suzuki and Banfield, 2004;
Nancharaiah et al., 2006; Merroun et al., 2006; Nedelkova et al., 2007; Sivaswamy et al.,
2011).
Biosorption
Biosorption is the term used to describe the uptake or binding of heavy metals or
radionuclides to cellular components. This biosorption process involves both adsorption and
absorption mechanisms. In this process uranium-bearing water is brought into contact with
either living or dead biomass functional groups such as (carboxyl, hydroxyl, amine, and
phosphate group) on their surface wall. Since the cell surface layer is in direct contact with
the external environment, the charged groups on the surface layer are able to interact with
ions or charged molecules present in the uranium-bearing water. As a result, metal cations
become electrostatically attracted and bound to the cell surface layer. Some bacterial species
may produce micro-molecules outside their own cell wall called extracellular polymeric
substances (EPS) capable of immobilizing metals (Comte et al., 2008). Different studies on
biosorption demonstrated that uranium biosorption is reversible, species-specific, and
depends upon the chemistry and pH of the solution, physiological state of cells as well as the
16
presence of the extracellular soluble polymers (Francis et al., 2004; Nakajima and Tsuruta,
2004).
The biosorbents used in the biosorption process may be viewed as the natural ion-exchange
materials that may avoid the potential problems encountered with ion-exchange resin such as
incapability of resin regeneration. In this process desorption and recovery of heavy metals
and radionuclides from biosorbents using sulphuric acids, hydrochloric acid, sodium
hydroxide, or other complexing reagents for further reuse is easy (Kratchvil and Volesky,
1998; Valls and deLorenzo, 2002). Additionally, biological process improvement through
genetic engineering of cells using live cells as biosorbents is possible. Although, biosorption
of radionuclides to the cell surface and polymer substance is a promising technology for
remediation of contaminated waters, the effectiveness of this process is highly affected by pH
of the solution and saturation of the biosorbent when metal interactive sites are occupied and
also the complexation of metal with carbonates which may result in slower biosorption rates.
In previous studies by Sar and DSouza (2002) and Jroundi et al. (2007) it was observed that
biosorption under acidic conditions is not favoured in several species of bacteria. This is
because at low pH, the protons (H+) compete with UO22+ for sorption sites (surface hydroxyl
groups–SOH), thus indicating poor selectivity of the biosorbent surface against competing
ions. The other limitation associated with biosorption process is that the biosorbents rarely
facilitate the change in the valence state of target species (Mtimunye and Chirwa, 2013).
Bioaccumulation
Bioaccumulation is an active process wherein metals are taken up into living cells and
sequestrated intracellularly by complexing with specific metal-binding components or by
precipitation. Intracellular accumulation of metals occurs among all classes of
microorganisms as chemical surrogates by an energy-dependent transport system. Unlike
metabolically essential metals such as Fe, Cu, Zn, Co, and Mn, which accumulates
intracellularly via energy transport system, uranium has no known essential biological
function and may be transported into microbial cells only due to increased membrane
permeability resulting from uranium toxicity in the living cell (Francis et al., 2004; Suzuki
and Banfield, 2004; Geissler et al., 2010). Therefore, intracellular accumulation of uranium is
considered as metabolism-independent process as there is no direct evidence of uranium
transporters in microorganisms.
17
It has been demonstrated in many studies that bacterial cells can intracellularly immobilise
uranium through chelation by polyphosphate bodies. However, the major drawback
associated with the use of active uptake systems is the requirement of metabolically active
cells and also the challenge in metal desorption and recovery (Macaskie et al., 2000). For
metal recovery, the cells will need to be destroyed in order to release the metal either by lysis
or by incineration. Therefore, in this case, the media or the cell used for the uptake of metals
cannot be reused.
Bioprecepitation
Bioprecipitation also known as biocrystallization or biomineralization is the process by which
metals and radionuclides can be precipitated with microbial generated ligands such as
phosphate (PO4-), sulphide (S2-), oxalate (C2O42-), or carbonate (CO32-) (Macaskie et al.,
1992; Joeng et al., 1997). In these processes bacteria interact strongly with metals and
radionuclides, eventually precipitating them as carbonates and hydroxide minerals at the
surface of the cell (VanRoy et al., 1997). Macaskie and other researchers investigated the
accumulation of UO22+ as U-phosphate on Citrobacter sp., using enzymatically liberated
inorganic phosphate ligand (Macaskie et al., 1992; Merroun et al., 2006; Beazley et al., 2007;
Jroundi et al., 2007). Cells showed no saturation constrains and it could accumulate several
times their own weight of precipitated metal.
The above method showed that the secretion of inorganic compounds such as orthophosphate
groups can directly bind U(VI) and form insoluble polycrystalline uranyl hydrogen phosphate
(UO2HPO4.4H2O)
or
Accumulation
these
of
meta-autunite-like
uranyl
mineral
phosphate
groups
phase
(Ca(UO2)2(PO4)2.3H2O).
within
certain
cell-surface
lipopolysaccharides (LPS) provides a nucleation site for precipitation, resulting in efficient
removal of radionuclides in the solution and also preventing fouling of the cell surface
(Renshaw et al., 2007). This indicates that precipitation and biosorption are overlapping
phenomena, and it can be difficult to assign the contribution of each to metal immobilization.
In addition to direct precipitation by microbially generated ligands, actinides can also be
removed from solution by chemisorption to biogenic minerals (Macaskie et al., 1994).
The limitations of this method during application in industrial processes could be similar to
those encountered in biosorption. Firstly, the process is hindered by the formation of
negatively charged uranyl carbonate complexes, arising from microbial metabolism of the
carbon source under anaerobic conditions and the U(VI)-carbonate complex formed may also
18
enhance U(IV) oxidation over time (Ginder-Vogel and Fendorf, 2008). Additionally, these
processes may precipitate metals other than uranium and forms insoluble uranyl-complex on
the cell surface, which may eventually result in cell surface saturation.
Bioreduction
Reduction of the highly toxic and mobile U(VI) to the sparingly soluble U(IV) using
appropriate microbes in the form of bio-flocs has been proposed as a mechanism for
preventing the migration of U(VI) in groundwater (Lovley et al., 1992; Gorby and Lovley,
1992). An electron donor such as acetate, lactate, ethanol, or glucose could be introduced into
the polluted environments to stimulate U(VI) reduction by native microbial species at the site
(Anderson and Pedersen, 2003). Where native cultures do not have the U(VI) reducing
capability, processes such as molecular bioaugmentation have been proposed whereby
genetic material from U(VI) reducing bacteria is introduced into the environment using broad
spectrum plasmids that can be easily taken up by some of the native bacteria (Chirwa, 2011).
Microorganisms are known to have evolved biochemical pathways for degradation or
transformation of toxic compounds from their immediate environment either for survival or
to derive energy by using toxic compounds as electron donors or acceptors (Istok et al., 2004;
Merroun and Solenska-Pobell, 2008). This process has been conserved over billions of years,
such that, to this day, all life on earth depends on variants of this pathway (Nealson, 1999;
Bush, 2003). The overall transfer of electrons from a carbon source such as lactate to active
uranium species can be represented as follows (Figure 2-2):
Microbial U(VI) reduction was first reported in crude extracts from Micrococcus lactilyticus
by assaying the consumption of hydrogen which was dependent on the presence of U(VI)
(Woolfolk and Whiteley, 1962). To date, U(VI) reduction capability has been identified in
more than 25 species of phylogenetically diverse prokaryotes. Examples of these are the
mesophilic sulphate-reducing bacteria (Desulfovibro sp.) (Lovley and Phillips, 1992), Fe(III)reducing bacteria (Geobacter and Shawanella sp.) (Coates et al., 2001), fermentative bacteria
from Clostridium sp., (Francis et al., 1994), Acidotolerant bacteria (Shelobolina et al., 2004),
Thermoterabacterium (Khijniak et al., 2005), Myxobacteria sp. (Wu et al., 2006) and others
as shown in Table 2-1 below.
19
Soluble U(VI)
as electron
sink
Organic
carbon
(CHO, acetate,
ethanol, etc)
n⋅e-
Electron flow
Insoluble
reduced form
U(IV)
CO2 + H2O
4+
-
U + 4OH → U(OH)
4(s) ↓
Figure 2-2: Microbial reduction of U(VI) to U(IV). Energy Transduction and Metal
Reduction (Mtimunye and Chirwa, 2013).
An example of a balanced stoichiometric relationship during U(VI) reduction using lactate as
an electron donor is represented as follows:
UO 2
2+
URB
+ 0.5CH 3 CH 2 COO − + 0.5H 2 O 
→ UO 2 + 0.5CH 3 COO − + 0.5CO 2 + 2H +
(2-1)
where: URB represent U(VI) reducing bacteria or enzyme. It can be seen in Equation 2-1 that
UO22+ needs to accept two electrons in order to be converted to UO2 .
Researchers such as Lovley and co-workers (1991) were the first to demonstrate the
importance of dissimilatory metal-reducing bacteria (DMRB) in reducing toxic form of
uranium (U), iron (Fe), manganese (Mn), and other toxic metals (Lovley et al., 1991; Wade
and DiChristina, 2000; Lloyd et al., 2003). In this process energy is conserved for anaerobic
growth of these organisms (Lovley et al, 1993; Wu et al., 2006). Since the ability to reduce
U(VI) enzymatically is not restricted to Fe(III)-reducing bacteria, other organisms such as
Clostridium, Desulfovibrio desulfuricans, Desulfosporosinus sp., Desulfovibrio vulgaris, and
Anaeromyxobacter Dehalogenans were also able to reduce uranium via a respiratory process
that does not conserve energy to support anaerobic growth (Lovley and Phillips, 1992 and
1994; Francis et al., 1994; Suzuki et al, 2004; Wu et al., 2006 ).
20
Table 2-1: U(VI) reducing bacteria, their source, and preferred environmental conditions
Bacterium
Source of Culture
Anaeromyxobacter
dehalogenans str. 2CP-C
Stream sediments
Cellulomonas
flaigena
ATCC 482
Clostridium
sphenoides
ATCC 19403
Desulfomicrobium
norvegicum DSM 765
Desulfotomaculum reducens
Desulfovibrio baarsii DSM
2075
Desulfovibrio desulfuricans
strain ATCC 29577
Desulfovibrio desulfuricans
strain G20
Desulfovibrio sp. UFZ B
490
Desulfovibriovulgaris
Hildenborough
Geobacter metallireducens
GS-15
Geobacter sulfurreducens
Pseudomonas putida
Sugar cane field
Mine pit water
Sediment core
Salt water, USA
Ditch mud, Germany
Tar sand mixture, UK
Oil reservoir, Alaska
Uranium dump, Germany
Wealden clay, England
Growth Condition, Energy
Source
Anaerobic, 2-chlorophenol
Aerobic/anaerobic, glucose
and others
Anaerobic, glucose, citric
acid
Anaerobic,
acetate
and
others
Anaerobic, lactate and others
Anaerobic, ethanol and
others
Anaerobic,
acetate
and
lactate
Anaerobic, acetate, lactate,
glucose
Anaerobic, ethanol, TCA
metabolites
Anaerobic, lactate
Sediment, Potomac River,
USA
Sediments, Norman
Uranium mill tailing sites
Anaerobic, acetate, formate,
phenol
Anaerobic, acetate, formate
Anaerobic,
glucose,
pyruvate
Pseudomonas sp. CRB5
Chromate containing sewage Anaerobic, lactate and others
Pyrobaculum islandicum
Iceland geothermal power Anaerobic,
elemental
plant
sulphur, iron, thiosulfate
Shewanella alga BrY
Estuary
sediment,
New Facultative
anaerobic,
Hemisphere
insoluble mineral oxides
Shewanella oneidensis MR- Sediment, Onedia Lake, New Anaerobic, lactate
1
York
Shewanella
putrefaciens Oil pipe line, Canada
Anaerobic, formate, lactate
strain 200
Thermoanaerobacter sp
Geothermal spring
Anaerobic, glucose, peptone,
pyruvate
Thermus scotoductus
Hot tap water, Iceland
Aerobic, acetate
Thermoterrabacterium
Hotspring in Yellowstone, Anaerobic, citrate, glycerol
ferrireducens
USA
*Adapted from (Chirwa, 2011)
The unique physiological property of DMRB, (Geobacter and Shawanella) is that they are
obligate anaerobes that are required to respire anaerobically on their terminal electron
21
acceptor such as Fe(III) and Mn(IV) oxide. DMRB respiring solid such as Fe(III) and Mn(IV)
oxide as anaerobic electron acceptor, are presented with unique physiological problem of
engaging electron transport system with poorly soluble minerals. Therefore, in order to
overcome the problem of respiring solid electron acceptor which are unable to contact inner
membrane (IM) localized electron transport system, Fe(III) and Mn(IV) respiring DMRB are
postulated to employ a variety of novel respiration strategies not found in other gramnegative bacteria that respire on soluble electron acceptors such as O2, NO3-, SO42-, CO2.
Radionuclides such as U(VI) and Tc(VII) are relatively soluble in the environment, typically
as anionic uranyl-carbonate complexes. The solubility of the radionuclides U(VI) and Tc(VII)
under natural pH, indicate that these soluble species are more bioavailable than the (Fe(III)
and Mn(IV)) oxide as they may easily enter the cell periplasm through porins or channels in
the outer membrane.
2.11 Enzymatic U(VI) Reduction
Members
of
genera
Shewanella,
Geobacter,
Clostridium,
Desulfovibrio,
and
Desulfosporosinus have been used in the reduction of U(VI) under both aerobic and
anaerobic growth conditions (DiChristina et al., 2005). The mechanism by which Shewanella
and Geobacter species enzymatically reduce U(VI) to U(IV) involves a dissimilatory
respiratory process where energy is conserved for cell growth (Lovley et al., 1993). In the
above organisms, the electron transport pathway is believed to include c-type cytochrome on
the membrane (Lloyd et al., 2002). The enzymatic U(VI) reduction activity is affected by
U(VI) chemical speciation, electron donors, complexing-ligands, and competing electron
acceptors.
2.11.1 Geobacter Reductase
Several genes of Geobacter sulfurreducens which include trihaeme periplasmic cytochrome,
c7, diheme periplasmic cytochrome, and tetraheme cytochrome, c3, display U(VI) reductase
activity in vitro. However, mutants deficient in either cytochrome-c3 or cytochrome-c7
preserve U(VI) reduction activity in vivo (Lloyd et al., 2003). These findings suggest that
either cytochrome c3 and c7 are not the physiological U(VI) reductases in G. sulfurreducens
or that the electron transport pathway to U(VI) is highly branched and consist of multiple
U(VI) terminal reductases. The highly branched nature of the U(VI) reduction pathway in G.
sulfurreducens is reflected by the finding that Fe(III) reduction deficient c7 mutants are also
22
deficient in U(VI) reduction activity (Lloyd et al., 2003; DiChristina et al., 2005).
Interestingly, although this organism is proficient at reducing a broad range of extracellular
Fe(III) and Mn(IV) minerals, and UO22+, it was observed to be inefficient in reducing, NpO2+,
the reduced species of neptunyl (NpO22+) exiting in the spent fuel nuclear waste (Renshaw et
al., 2005; Geissler et al., 2010). The latter authors suggested that the enzyme system
responsible for uranium reduction in G. sulfurreducens is specific for hexavalent actinides
and is capable of transferring one electron to an actinyl ion, and the instability of the resulting
U(V) then generates U(IV) via disproportionation.
2.11.2 Shewanella Reductase
To date, only four strains of bacteria have been reported to conserve metabolic energy from
dissimilatory U(VI) respiration to support growth, i.e., Shewanella putrefaciens (formally
known as Pseudomonas sp.), G. metallireducens, Desulfotomaculum reducens, and
Thermoterrabacterium ferrireducens (Lovley and Phillips, 1992; Kennedy et al., 2004;
Shelobolina et al., 2004; Wall and Krumholz, 2006). Early work with S. putrefaciens showed
that cells limited for Fe were unable to use Fe(III) as a terminal electron acceptor (Obuekwe
and Westlake, 1982; Wall and Krumholz, 2006). These cells lost their orange colour under
Fe(II) conditions which indicated a major decrease in c-type cytochrome content (Kennedy et
al., 2004). The interpretation of these observations was that cytochromes were involved in the
transfer of electrons to the terminal electron acceptor or were the terminal reductases.
Subsequently, various cytochromes of S. putrefaciens were shown to localize in the periplasm
with either the cytoplasmic or the outer membrane (Myers and Myers, 1992).
Comparison of uraninite (UO2(s)) deposition by mutants lacking outer membrane decaheme ctype cytochromes (MtrC) showed accumulation predominantly in the periplasm versus the
deposition of UO2(s) external to wild-type cells (Kennedy et al., 2004). This result indicate
that U(VI) reduction is not eliminated by any of the single mutants analysed and also
supports the hypothesis that uranium reductase are likely nonspecific low potential electron
donors present in both the periplasm and outer membrane. It remains to be determined
whether the mutants altered for U(VI) reduction are similarly affected in their ability to use
U(VI) as terminal electron acceptor for growth.
23
2.11.3 Electron Donors and Competing Electron Acceptors
U(VI) reduction by Shawanella is couple to oxidation of various electron donors such as
hydrogen, lactate, formate or pyruvate (Lovley et al, 1991). It has been reported by Liu and
co-workers (2002) that hydrogen is the most preferred electron donor as higher U(VI)
reduction was observed with H2 as an electron donor (Aubert et al., 2000; Liu et al., 2002).
The observed increased U(VI) reduction rate coupled to H2 oxidation rather than lactate
oxidation was attributed to (i) the rapid flow of electrons from the periplasmic H2hydrogenase through the electron transport chain to the terminal electron acceptor; and (ii)
the faster mass flux of neutrally charged H2 to the enzymatic site of oxidation which does not
require an active transport system.
The presence of competing terminal electron acceptors such as O2, NO3-, Fe(III), and Mn(IV)
may interfere with microbial U(VI) reduction in a system. To evaluate the interference of
U(VI) in the presence of various competitive electron acceptors, competition between SO42and U(VI) reduction was explored in different approaches with the SRB (Spear et al., 2000).
On the first approach Spear and co-workers (2000) reported that a mixed culture of SRB and
a pure culture of D. desulfuricans was able to simultaneously reduce SO42- and U(VI) when
provided at equal molar concentrations or equal electron equivalent concentrations. On the
second approach similar competition experiment was carried out with D. vulgaris in the
presence of Fe(III), SO42-, and U(VI) (Elias et al., 2004). The results showed that, in the
presence of lactate as electron donor, the reactions were discreet with Fe(III) reduced first,
followed by U(VI), and finally SO42-. However, when H2 was used instead of lactate as
electron donor, Fe(III) was reduced first again and U(VI) and SO42- appeared to be
simultaneously reduced.
2.12 Cellular Localization
The subcellular location of enzymatic U(VI) reduction in DMRB has been examined recently
using TEM. TEM analysis confirmed precipitated uraninite (UO2(s)) both outside of the cell
and within the periplasm of gram-negative DMRB (Lovely and Phillips, 1992; Lloyd et al.,
2003; DiChristina et al., 2005; Wall and Krumholz, 2006), suggesting that U(VI)-complexes
do not generally have access to intracellular enzymes. Interestingly, for the gram-positive
bacterium Desulfosporosinus, uraninite was found in an analogous location concentrated in
the region between the cytoplasmic membrane and cell wall (Suzuki et al., 2004). These
24
findings suggest that U(VI) reductases may be localized on the periplasmic of the
cytoplasmic membrane or in the periplasm its self or both. Identification of U(VI) reduction
products of Desulfosporosinus as nano-meter sized UO2(s)-particles further suggest that the
localization of the reduced uranium species within the cell cytoplasm may be associated to
the diffusion of the nano-size UO2(s)-particles from the cell periplasm.
Cytoplasmic uraninite deposit location has also been reported in few studies in Pseudomonas
sp, and D. desulfuricans strain G-20 (McLean and Beveridge, 2001; Sani et al., 2004;
Merroun and Selenska-Pobell, 2008). When TEM thin sections of Pseudomonas isolates were
examined, U(IV) was found inside as well as concentrated at the envelope. Because uranium
has no biological known function, the mechanisms of intracellular uraninite precipitation are
still not well understood. McLean and Beveridge (2001) speculated that the presence of
uranium precipitate in the cytoplasm of Pseudomonas may be due to the presence of
polyphosphate granules observed in the cell which might protect the cell by forming strong
complexes with uranium, thus sequestering it in cytoplasm.
In the case of D. desulfuricans G-20 the internal deposition of uraninite observed in cells that
had been grow in a medium intended to limit heavy metal precipitation and maximize toxicity
(Sani et al., 2004). To prevent the formation of strong complexes, the medium had no
specifically added carbonate or phosphate. Such modifications may also alter the physiology
of the bacterium and stimulating uptake of the toxic metal to the cytoplasm. This findings
indicate that the cytoplasmic deposition of U(IV) in Desulfovibrio may be associated to
nutritional stresses on U(VI) reduction.
With the exception of these rare reports of cytoplasmic uraninite, the localized precipitation
of insoluble U(IV) in the periplasm and outside of both gram-negative and gram-positive
cells suggests that U(VI) complexes do not generally have access to intracellular enzymes.
The best candidates for the reductases would be electron carrier proteins or enzymes exposed
to the outside of the cytoplasmic membrane, within the periplasm, and/or in the outer
membrane (Wall and Krumholz, 2006).
2.13 Emerging Treatment Technologies
2.13.1 Biofilm Systems
In natural environment such as groundwater aquifers microbial community generally exist as
biofilms or bio-flocs which are significant for potential metal immobilization (Chirwa, 2011).
25
Biofilm are formed when bacterial species adhere to surfaces in moist environments by
excreting a slimy, glue-like substance, extracellular polymeric substances (EPS). The EPS
which composed of polysaccharides, proteins, free nucleic acid, and water allows the
complex development of the biofilm structure. The complex nature of the biofilm structure
makes the organism to be more resistant to environmental changes. At the initial stage the
formation of the biofilm is believed to be an active process coupled to the cell’s central
metabolism (Kjelleberg and Hermanson, 1984; Paul, 1984). Within the biofilm system,
complex processes such as nutrient cycling, mass transport resistance, cell and substrate
diffusion, and biofilm loss at the surface may take place.
Unlike most activated sludge systems, biofilm systems have the advantage of lower-carry
over biomass. Thus imply that the microbes in the biofilm reactor may be retained at flow
rates greater than the washout flow rates and immobilized as the dense layer growth attached
to the solid surface. Biofilm is also play an important role in the cell division cycle. Meadows
(1971) observed that Pseudomonas fluorescens, and Aeromonas liquifaciens cells undergo
cell division only during their most stable attachment phase. The complexity in biofilms
processes presented above, sometimes presents an advantage when complex metabolic
processes and co-operation between different species in the community of organisms is
required to remove a particular compound. Studies by Nkalambayausi-Chirwa and Wang
(2001), showed the effectiveness of biofilm systems in removing two pollutants
simultaneously. Optimum removal of the two pollutants was achieved in the reactor which
was inoculated with both slightly facultative Cr(VI)-reducers, Escherichia coli, and the
obligate aerobic phenol degraders, Pseudomonas putida. Results from this study showed that
biofilm systems are self-optimised system in which metabolites formed from phenol
degradation in aerobic layer supported the growth of Cr(VI) reducing bacteria in deeper layer
of the biofilm.
2.13.2 Reactive Barrier Systems
Waste from nuclear power generation and other radionuclide processing facilities is usually
stored in specifically engineered facilities for decade’s prior final disposal (Merroun and
Seleska-Pobell, 2008). In underground repositories the main concern is high probability of
radionuclides escape into groundwater systems causing groundwater contamination. In areas
where contamination has actually occurred further migration of the pollutants is prevented in
situ using permeable reactive barriers (PRB). Permeable reactive barriers (PRB) are created
26
by extending the permeable reactive material to intercept a plume of contaminated
groundwater (Figure 2-3). The wall of the PRB is engineered to be at least as permeable as
the surrounding aquifer materials such that it allows passage of groundwater while treating
groundwater contaminants in situ. Treatment of pollutants in groundwater can be both biotic
and abiotic. Abiotic PBR treatment involves the use of neutralizing agents such as lime,
adsorbents, and zero-valent iron (Fe0) while biotic PBR use microbes as a permeable reactive
material. The processes by which the biological permeable reactive barrier promotes in situ
containment and stabilization of contaminants in groundwater systems include degradation,
adsorption, precipitation, and reduction.
Figure 2-3: Theoretical representation of the permeable reactive barrier system as an
intervention for U(VI) pollution in an unconfined aquifer system.
Chemical PRB has been tested in batch studies using fine grinned zero valent iron (Fe0) as a
reactive material (Thijs et al., 2004; Gavrilescu et al., 2009). Results from the later study
demonstrated the effectiveness of Fe0 in uranium removal, with the removal efficiency of
more than 99.9%. The problem associated with the use of Fe0 as a reactive barrier material in
PRB’s is that they do not provide a permanent solution as the use of chemicals to treat certain
pollutants in groundwater systems may also form toxic species as a result of incomplete
chemical reaction. Furthermore, the replacement of the reactive barrier material and the
disposing of the spent reactant may drive up the cost of the process.
27
2.14 Summary
The remediation of uranium-contaminated water systems utilizing both physico-chemical and
biological methods have been evaluated in this study. The remediation of uranium
contaminated sites using traditional physico-chemical methods such as pump-and-treat or
excavation followed by chemical treatment has been shown to be costly and disruptive to
ecosystems. Biological methods on the other hand are of great interest as they are costeffective, and environmentally friendly. Microorganisms play important roles in the
environmental fate of toxic metals with prosperity of physical-chemical and biological
mechanisms effecting transformations between soluble and insoluble phases. As an endeavor
to solve the problem of soil and groundwater contaminated with uranium and other toxic
metals, studies on in situ bioremediation of toxic metals have been conducted.
The main limitation associated with in situ bioremediation of uranium and other toxic metals
is that unlike organic compounds, metals are not destroyed but rather trapped in the aquifer
matrix in a reduced state. The fate of such reduced metals in a system and foreseeable
blockage by hydroxide species remains a challenge. This is mainly because removal of
reduced metal precipitate trapped in aquifer matrix during in situ treatment is a scientific
intensive procedure that requires detailed investigation. While detailed investigations
concerning the fate of the reduced metal precipitate in aquifer systems are still underway,
pump-and-treat approach using bioreactor systems could serve as a prospective measure in
preventing further U(VI) contamination to surrounding aquifers.
28
CHAPTER 3
EXPERIMENTAL METHODS
3.1 Bacterial Culture
3.1.1 Source and Isolation of U(VI) Reducing Microorganisms
Microorganisms were isolated from soil samples collected from the tailing dumps of an
abandoned uranium mine in Phalaborwa, Limpopo (South Africa). The samples were
collected in sterile containers and stored at 4°C in the refrigerator until used. Bacteria cultures
were isolated from the soil samples using the enrichment culture technique. To isolate the
U(VI) tolerant species, a gram (1 g) of soil sample was added to 100 mL of sterile basal
mineral medium (BMM). The medium was amended with D-glucose as sole added carbon
source and 75 mg/L of U(VI). The inoculum was grown under anaerobic conditions for 24
hours at 30±2°C in 100 mL serum bottles purged with nitrogen gas (99.9% N2) and sealed
with rubber stoppers and aluminium seals. After 24 hours enriched bacterial strains were
isolated by serial dilution.
3.1.2 Purification of Indigenous Bacteria
Individual colonies were obtained by depositing 0.1 mL of ten times serially diluted sample
from the 7th to the 10th test tube into the petri dishes containing sterile nutrient agar (NA)
using the spread method. The plates were then incubated for about 24-48 hours at 30±2°C in
anaerobic gas packs to develop separate identifiable colonies. Individual colonies based on
their colour and morphology were then sub-cultured into a 100 mL sterile nutrient broth (NB)
using a heat sterile wire loop. Cells were allowed to grow for 24 hours and then 1mL of 24
hours grown culture was serially diluted and then 0.1 mL of diluted sample from 7th to the
10th tube was deposited on a nutrient agar plates. This preparation was conducted inside
anaerobic glove bags filled with 99.9% pure N2 gas. The plates were thereafter transferred
into anaerobic gas packs followed by incubation for 24-48 hours at 30±2°C. The process was
repeated at least three times in order to achieve close to pure culture for each identified
species. The pure cultures were then preserved at 4ºC on sealed agar slants under a nitrogen
environment and were sub-cultured monthly to preserve viability. Several species of bacteria
were un-culturable under the above conditions, but the target was to isolate U(VI) tolerant
organisms with a high probability of being able to reduce U(VI).
29
3.2 Growth Media
3.2.1 Basal Mineral Media
Basal Mineral Medium (BMM) was prepared by dissolving: 10 mM NH4Cl, 30 mM
Na2HPO4, 20 mM KH2PO4, 0.8 mM Na2SO4, 0.2 mM MgSO4, 50 µM CaCl2, 0.1 µM ZnCl2,
0.2 µM CuCl2, 0.1 µM NaBr, 0.05 µM Na2MoO2, 0.1 µM MnCl2, 0.1 µM KI, 0.2 µM H3BO3,
0.1 µM CoCl2, and 0.1 µM NiCl2 into 1 L of distilled water as according to Roslev et al.
(1998). The medium was then amended with 25 mL of glucose solution prepared by
dissolving 5 g D-glucose in 1L distilled water. The glucose solution was amended to act as a
carbon and energy source for the bacteria. The prepared medium was sterilized before use by
autoclaving at 121°C at 115 kg/cm2 for 15 minutes.
3.2.2 Commercial Broth and Agar
The first three media, nutrient broth (NB), nutrient agar (NA), and Plate count (PC) agar
(Merck, Johannesburg, South Africa) were prepared by dissolving 31 g, 16 g, and 23 g of
powder, respectively in 1000 mL of distilled water. The nutrient agar and plate count agar
media were cooled at room temperature after sterilization at 121°C at 115 kg/cm2 for 15
minutes and then dispensed into petri dishes to form agar plates for colony development.
3.3 Characterisation of Microbial Community
The phylogenetic characterization of cells was performed on isolated individual colonies of
bacteria from the 7th to the 10th tube in the serial dilution preparation. Individual colonies
from the purified cultures were then prepared for 16S rRNA (16 Svedburg unit ribosomal
Ribo-Nucleic-Acid) genotype fingerprinting. Genomic DNA was extracted from the purified
colonies according to the protocol described for the Wizard Genomic DNA purification kit
(Promega Corporation, Madison, WI, USA). 16S rRNA genes were then amplified by using a
reverse transcriptase-polymerase chain reaction (RT-PCR) using primers pA and pH1 (Primer
pA corresponds to position 8-27; Primer pH to position 1541-1522 of the 16S gene under the
following reaction conditions: 1 minute at 94ºC, 30 cycles of 30 s at 94ºC, 1 minute at 50ºC
and 2 minutes at 72ºC, and a final extension step of 10 minutes at 72ºC). PCR fragments were
then cloned into pGEM-T-easy (Promega) [Promega Wizard® Genomic DNA Purification
Kit (Version 12/2010)]. The 16S rRNA gene sequences of the strains were aligned with
reference sequences from Desulfovibrio spp., Geobacter sp., Acinetobacter spp.,
Anthrobacter spp., and Shewanella putrefaciens using Ribosomal Database Project II
30
programs. Sequence alignment was verified manually using the program BIOEDIT. Pairwise
evolutionary distances based on an unambiguous stretch of 1274 bp were computed by using
the Jukes and Cantor (1969) method.
3.4 Chemical Reagents and Standards
Sodium chloride solution (0.85% NaCl) was prepared by dissolving 0.85 g of sodium
chloride salt in 100 mL distilled water and sterilized by autoclaving at 121°C for 15 minutes.
All chemicals used were of analytical grade obtained from Sigma Aldrich, Johannesburg,
South Africa.
3.4.1 Uranium Stock
U(VI) stock solution (1000 mg/L) was purchased from (Sigma, South Africa) as uranyl
nitrate (UO2(NO)3.6H2O). The U(VI) stock solution was used throughout the experiments to
serve as U(VI) source. The standard solutions of U(VI) were prepared from the U(VI) stock
solutions in 50 mL volumetric flasks by diluting a specific volume of U(VI) stock solution
with BMM amended with D-glucose to give desirable final U(VI) concentration ranging from
(0-80 mg/L).
3.4.2 Arsenazo III Reagent
Arsenazo III reagent was prepared by dissolving 0.07 g (1,8-dihydroxynaphthalene-3,6
disulphonic acid-2,7-bis[(azo-2)-phenylarsonic acid]) in 24.8 mL of 70% perchloric acid
(HClO4) (Merck, SA) and then filled the volumetric flask up to 2 L with distilled water to
give a red-pink color. The solution was kept at 4°C until further use.
3.5 Experimental Batches
3.5.1 Preliminary U(VI) Reduction Studies
Preliminary U(VI) removal kinetic studies were conducted in batch reactor systems to
evaluate the efficiency of each isolate in reducing U(VI) as individual species. The isolates
were grown overnight as individual pure isolates in a sterile nutrient broth. The overnight
grown cells were then harvested by centrifuging at 6000 rpm (2820 g) for 10 minutes. The
supernatant was decanted and the remaining pellet was washed three times with sterile 0.85%
NaCl solution. The washed pellet was then re-suspended into different serum bottles
containing sterile BMM amended with D-glucose and U(VI) concentration ranging from (3031
75 mg/L). The serum bottles were then purged with 99.9% pure N2 gas for about (5-10
minutes) to expel residual oxygen in the serum bottles prior sealing the bottles with rubber
stoppers and aluminium seal. The serum bottles were then incubated on a rotary shaker at
30±2°C with continuous shaking on a lateral shaker (Labotec, Gauteng, South Africa) at 120
rpm. To determine U(VI) concentration over time, aliquots of 2 mL were taken from different
serum bottles, centrifuged using a 2 mL eppendorf tube at 6000 rpm (2820 g) in a Minispin
Microcentrifuge (Eppendorf, Hamburg, Germany). The supernatant was then used for U(VI)
concentration analysis.
3.5.2 U(VI) Reduction on a Mixed-Culture of Bacteria
U(VI) reduction experiments on a mixed-culture of bacteria which was grown over night in a
sterile nutrient broth under anaerobic conditions were conducted. The overnight grown cells
were harvested by centrifuging at 6000 rpm (2820 g) for 10 minutes. The supernatant was
decanted and the remaining pellet was washed three times with sterile 0.85% NaCl solution
under an anaerobic glove bag purged with 99.9% (N2) gas. Anaerobic U(VI) reduction
experiment were conducted in 100 mL serum bottles by adding U(VI) stock solution into the
BMM amended with D-glucose to give the desirable effective final U(VI) concentration
ranging between (100-600 mg/L).
Prior to inoculating the serum bottles with the washed cells, 2 mL of a sample was withdrawn
from each serum bottle at various U(VI) concentration to determining the absorbance of
U(VI) before inoculating the bottles with viable cells. The washed cells were then resuspended into 100 mL serum bottles under an anaerobic glove bag purged with 99.9% (N2)
gas. The samples in the bottles were then directly purged with 99.9% (N2) gas for about 10
minutes to expel any oxygen gas before sealing with silicon rubber stopper and aluminium
seals. The samples were then incubated at 30±2°C with continuous shaking on a lateral
shaker at 120 rpm. U(VI) reduction was monitored by withdrawing 2 mL of the sample at
regular time intervals using a sterile syringe. The withdrawn samples were then centrifuged
using a 2 mL eppendorf tube at 6000 rpm (2820 g) for 10 minutes in a Minispin
Microcentrifuge before U(VI) analysis to remove suspended cells.
3.5.3 Abiotic U(VI) Reduction Experiments
Cell free medium and heat-killed cultures were used to determine the extent of abiotic U(VI)
reduction in batch experiments. Overnight grown cells were heat killed by autoclaving at
32
121ºC for 20 minutes in several cycles. The heat-killed culture cells were then harvested by
centrifuging at 6000 rpm (2820 g) for 10 minutes and then washed three times with sterile
0.85% NaCl solution followed by res-suspension into serum bottles containing BMM
amended with D-glucose and U(VI) solution to the desirable U(VI) concentration of 100
mg/L. The cell-free control contained only fresh BMM amended with D-glucose and U(VI)
solution to the desirable concentration of 100 mg U(VI)/L. The 100 mL serum bottles were
then purged with 99.9% (N2) for about (5-10 minutes) to expel residual oxygen prior closing
and sealing with a silicon rubber stopper. All experiments biotic and abiotic were conducted
in triplicates at 30±2ºC with continuous shaking on lateral shaker at 120 rpm.
3.5.4 U(VI) Reduction Pathway Targets and Inhibitors
To evaluate the effectiveness of enzymatic U(VI) reduction process, overnight grown cells
were harvested by centrifuging at 6000 rpm (2820 g) for 10 minutes. One set of overnight
grown cells was exposed to (0.1%) of rotenone (C23H22O6), a compound that inhibits the
flow of electrons from NADH to the ubiquinone (Q) in the cell membrane of many bacterial
cells by binding to the (Q) binding site of NADH-dehydrogenase (Gomes et al., 2001;
Vehovszky et al., 2010). The other set of overnight grown cells was exposed to (0.1%)
cadmium chloride (CdCl2), the known inhibitor of thioredoxin which is responsible for a
number of different important cellular functions of all living organisms including humans
(Zeller and Klug, 2006). Cadmium has been shown to inhibit thioredoxin by binding at Cys32
and Asp26 residues of E. coli thioredoxin (Rollin-Genetet et al., 2004; Li and Krumholz,
2009). The experimental conditions were kept the same (100 mL serum bottles containing
BMM amended with D-glucose and 100 mg U(VI)/L solution, and incubated at 30±2ºC under
anaerobic conditions).
3.6 Continuous Flow Suspended-Cell Bioreactor
3.6.1 Reactor Setup
The continuous flow reactor was constructed from a 10 L flat-bottomed glass flask (Figure 31). The glass reactor was used instead of the plastic to minimize the adsorption of uranium by
the reactor itself. A rubber stopper was plugged on the opening at the top of the reactor to
maintain anaerobic conditions. Four holes fitting glass tubes were drilled in the rubber
stopper. The four ports on the rubber stopper include (i) the influent port, (ii) nitrogen inlet
port, (iii) the outlet port that was used to maintain the reactor volume of 8L by allowing
33
excessive volume to escape as waste, and (iv) the effluent port. Additional port was drilled to
directly insert the probe which measures the pH, ORP, and temperature (pHC101, MTC101,
Hach, USA) simultaneously in a system. The reactor was placed on a magnetic stirrer (Velp
Scientifica, Labex Pty Ltd, South Africa) and a sterile magnetic stirrer bar was inserted into a
reactor prior closing it with the rubber stopper to achieve completely mixed conditions at
30±2°C.
Figure 3-1: Laboratory set-up of a suspended cells continuous flow reactor.
3.6.2 Start-up Culture
A mixed-culture of bacteria from the soil samples of the tailing dumps of the abandoned
uranium mine was cultivated for 24 hours in the sterile nutrient broth. The cultivated cells
were then harvested by centrifuging at 6000 rpm (2820 g) for 10 minutes. The supernatant
was decanted and the remaining pellet was washed three times with sterile 0.85% NaCl
solution. The washed pellet was then mixed with sterile BMM amended with D-glucose as
carbon source and directly re-suspended in 10 L flat-bottomed glass flask containing sterile
BMM amended with D-glucose using the inlet port.
34
3.6.3 Reactors Operation
During the experimental run, sterile BMM amended with D-glucose and U(VI) solution of
specific or target concentration ranging from (100-400 mg/L) was fed into a 10 L glass flask
sealed with a rubber stopper through ports using pre-calibrated peristaltic pump which was
initially calibrated to maintain a hydraulic retention time of approximately 24 hours
(Masterflex, Cole-Palmer Inst. Co., Niles, Illinois). The flask was thoroughly purged with
99.9% (N2) over time to expel residual oxygen in the flask which is continuously operated.
The oxidation reduction potential (ORP) and the pH of the solution was measured
continuously using ORP and pH probe (pHC101, MTC101, Hach, USA). The experiments
were conducted at 30±2ºC. Samples were then withdrawn from the effluent port for U(VI)
analysis.
3.7 Continuous Flow Biofilm Rector System
3.7.1 Reactor Set-up
Two columns constructed from a Plexiglas (PVC glass), (1 m long, 0.1 m internal diameter)
were installed in a laboratory as continuous flow columns. Each column consisted of an
influent port, four equally space intermediate sampling ports with bed heights of (0.2 m, 0.4
m, 0.6 m, and 0.8 m), and the final effluent port as shown in Figure 3-2. The columns were
packed with bio-cell filters (Happykoi, South Africa) and then closed on both ends with PVC
caps. A provision for biomass analysis on the biomass growth support medium was made on
PVC cap placed on the top end of the column. The two packed columns were then installed
vertically on the stand by clamping. The temperature in the control room where the columns
were operated was maintained at 30±2°C. The pore volume which is essential for studying
the movement of solute through a support media was calculated as a difference between the
weight of the saturated sample and the weight of a dry sample in a column.
3.7.2 Start-up Culture
Reconstituted mixed-culture of bacteria from the soil samples of the tailing dumps of the
abandoned uranium mine was cultivated for 24 hours in the sterile nutrient broth. The
cultivated cells were then harvested by centrifuging at 6000 rpm (2820 g) for 10 minutes. The
supernatant was decanted and the remaining pellet was washed three times with sterile 0.85%
NaCl solution. The washed pellet was then mixed with diluted sterile BMM amended with
diluted D-glucose solution as carbon source.
35
Figure 3-2: Laboratory set-up of a fixed-film continuous flow reactor.
3.7.3 Reactor Start up
Prior experimental run, distilled water was fed through each column from the bottom inlet
through a peristaltic pump to check for leaks in the columns and saturate pores with water.
Flow rates were also measured and adjusted to establish the hydraulic residence time (HRT)
of approximately 24 hours in each reactor. One reactor columns (R1) was then seeded with
viable cells solution amended with BMM and D-glucose. The viable cells solutions was fed
into (R1) for 2.5 weeks through re-circulation using a pre-calibrated peristaltic pump without
disturbance to allow near uniform distribution and attachment of cells to the bio-cell filter and
also to sustain the growth of microorganisms in the reactor.
3.7.4 Reactors Operation
During the experimental run, sterile BMM and U(VI) solution of specific or target
concentration ranging from (75-100 mg/L) was continuously fed into the reactors which were
operated as packed beds. One column (R1) was seeded with the mixed-culture of bacteria and
operated as a biofilm reactor, while the other column (R2) was operated as control reactor
36
without the addition of any cells. The microbial activity in the biofilm reactor was confirmed
through protein concentration analysis prior feeding simulated U(VI) containing plume water
into R1. U(VI) containing plume water was continuously and simultaneously fed into both
column reactors (R1 and R2) from the bottom inlet using a pre-calibrated double headed
peristaltic pump. The experiments were conducted for 99 days under oxygen stressed and
nutrient deficient conditions. Samples were then withdrawn from each sampling port over
time for U(VI) analysis. The column and the packing specification are given in Table 3-1.
Table 3-1: Biofilm Reactor Specification
Column and packing material properties
Value
Height of the column
1m
Diameter of column
0.1 m
Total volume of reactor
7.85 L
Total surface area of column
0.3298 m2
Name of packing material
Bio-cell filters
Particle size
0.013 m×0.01 m
Specific surface area
650 m2/m3
Density
0.179 kg/L
Packing Weight in the column
1.404 kg
Porosity
95%
3.8 Evaluation of Biomass Yield
3.8.1 Total Biomass
In a suspended cell system samples (5 mL) were withdrawn at regular time intervals,
centrifuged for 10 minutes at 6000 rpm (2820 g). The supernatant was used to analyse U(VI)
concentration and the settled pellet was used for biomass analysis. The centrifuged sample
was filtered through a pre-weighed Whatman filter paper No.41 of 20 µm. The filter paper
containing a wet biomass was dried in the oven at 75-80°C and cooled to room temperature
in a desiccator and weighed until a constant weight was achieved. The difference between the
37
dried filter paper with cells and the empty filter paper was considered as a biomass
concentration per 5 mL.
For measurement of the attached cells in a biofilm reactor, sample (biofilm support media)
was extracted from the column using sterile tweezers. The sample was then washed with
gentle shaking for about 15 minutes in 10 mL distilled water to remove sorbet medium. The
washed sample was then dried in an oven at 45±5°C for about 5 hours, cooled to room
temperature in a desiccator. The sample was then washed again with distilled water three
times for 15 minutes by vigorous shaking, and the dehydrated into 30% ethanol to ensure cell
detachment. The sample was then allowed to further dry in oven over nigh at 50±5°C, cooled
to room temperature in a desiccator. Cell detachment on the sample was confirmed using
microscope (Zeiss, Germany). The total biomass was calculated as a difference between the
bio-cell filter with biomass and bio-cell filter without biomass.
3.8.2 Viable Biomass Analysis
Samples (1 mL) were withdrawn from experimental batches at regular time intervals of 0-72
hours for the analysis of viable cell concentration. The withdrawn samples from each batch
reactor over time were then serially diluted in 10 test tubes containing 9 mL of sterile 0.85%
NaCl solution. The diluted sample (0.1 mL) from the 7th to the 10th tube was then transferred
into a PC agar plate using the spread method. The PC agar plates were then incubated for 1824 hours at 30±2°C. Colonies were counted after incubation and multiplied by a dilution
factor. The bacterial count was reported as colony forming units (CFU) per mL of sample.
For the biofilm reactor the sample (biofilm support media) was extracted from the column
using sterile tweezers. The sample extracted from the column was initially weighed and then
placed into a 9 mL sterile buffered solution (Ringer’s solution) solution which was prepared
by dissolving 2 Ringer’s tables into 1 L distilled water as per manufacture instruction (Merck,
Johannesburg, South Africa). The solution containing the bio-cell filter was then agitated
over several times to dislodge most of the microbes without destroying them. The supernatant
was serially diluted up to 10 times dilution factor. From each tube, 0.1 mL of the solution was
transferred into the agar plate using a spread method. This was done in triplicate for each
dilution to have statistical representivity. The plates were then incubated for (2-5) days at
30±2°C. The number of colonies were then counted and multiplied by a dilution factor. The
bacterial count was reported as colony forming units (CFU) per mL of sample.
38
3.8.3 Protein Concentration
Proteins make up a large fraction of the biomass of actively grown microbes. Total protein
concentration in a cell was determined in a UV/ Vis spectrophotometer at the wavelength of
595 nm using Coomassie dye as a complexing agent to facilitate protein detection. The
accuracy and the precision of the method were determined by measuring the concentration of
the Bovine Serum Albumin (BSA) standard solutions according to the protocol described for
the Coomassie Plus Brandford Assay Kit. To measure protein concentration 2 mL of the
unfiltered sample was withdrawn and then diluted with 0.1 M of HNO3 for about 15-20
minutes in order to facilitate protein extraction. The well mixed aliquot of 0.5 mL was
pippeted in an eppendorf tube, mixed with 1.5 mL of the Comassie Plus Reagent, allowed to
stand for 5-10 minutes and centrifuged for 10 minutes in order to settle the available pellet
prior analysing in a UV/ Vis spectrophotometer. The amount of protein was estimated by
interpolation from standard curve prepared with BSA.
3.9 Analytical Methods
3.9.1 Elemental Analysis by ICP-MS
Metallic elements of the soil samples collected from the tailing dumps of the abandoned
uranium mine in Phalaborwa, South Africa were characterised using Inductively-Coupled
Plasma-Mass Spectrometry (ICP-MS) Spectromass 2000 (Spectro Analytical Instruments,
Kleve, Germany). The elements were extracted from the soil sample as according to Zhou
and Gu (2005). The pre-weight 5 g of soil sample was suspended in 25 mL of 0.1 M NaHCO3
under room temperature (20±5°C). The soil sample was thoroughly mixed with NaHCO3 by
vortex and then allowed to stand for 24 hours. After 24 hours the sample was centrifuged for
10 minutes in three cycles at 6000 rpm to remove soil particles and elemental precipitates
formed in the aliquot. The aliquot was then diluted with deionized water up to 50 mL. The
sample was then analysed using ICP-MS for total uranium and other elements in the
Laboratory at NECSA Limited, Phelindaba, South Africa. This analysis was mainly
performed to confirm the background uranium concentration at the study site and also to
reveal other elements present in the soil sample. Background uranium concentration in the
samples was detected at levels as high as 29 mg/kg (72 mg/L) much higher than the values
observed in natural soils (0.3-11.7 mg/kg). Table 3-2 shows elementary soil composition of
significant presence.
39
Table 3-2: Mineral composition of the tailing dumps soil samples
Element
Symbol
Mass concentration (mg/L)
Aluminium
Al
8.2096
Bismuth
Bi
8.5385
Boron
B
0.3472
Calcium
Ca
677.54
Iron
Fe
299.65
Magnesium
Mg
216.90
Manganese
Mn
6.0716
Sodium
Na
3.4397
Potassium
K
4.2016
Uranium
U
72
3.9.2 Determination of U(VI)
U(VI) reductase activity was determined by measuring the decrease in U(VI) in the solution
using UV/Vis spectrophotometer (WPA, Light Wave II, and Labotech, South Africa).
Arsenazo III (1,8-dihydroxynaphthalene-3,6 disulphonic acid-2,7-bis [(azo-2)-phenylarsonic
acid]), a non-specific chromogenic reagent, was selected as the complexing agent for
facilitating U(VI) detection (Bhatti et al., 1991). Measurement of U(VI) was carried out by
sampling 2 mL of solution from the reactors using disposable syringes. The withdrawn
sample was then centrifuged at 6000 rpm (2820 g) for 10 minutes using MinispinMicrocentrifuge. The centrifuged sample (0.5-1 mL) was then diluted with 0.4 mL of 2.5%
diethylene-triaminepenta acetic acid (DTPA) and diluted up to mark with BMM in a 10 L
volumetric flask. The homogenous solution was the mixed with 2 mL of complexing reagent
(Arsenazo III), allowed to stand for full colour development prior analysis for U(VI) at 651
nm. In the presence of hexavalent uranium the reddish-pink complexing reagent changed into
blue color. DTPA was added to mask the interference caused by other cations (Shrivastsva et
al., 2013).
40
3.9.3 Determination of Total Uranium
For total uranium analysis, an unfiltered sample (0.5 mL) withdrawn from the reactor was
digested with 1 mL of 2 M HNO3, centrifuged for 10 minutes at 6000 rpm (2820 g). The
supernatant was collected and diluted up to mark with BMM. Total uranium was then
measured using inductively-coupled plasma mass spectrometry (ICP-MS) which was
previously calibrated against the uranium atomic adsorption standard solutions ranging from
(0-100 mg/L). The linear graphs/calibration curves with the regression of 99.5% were then
obtained by plotting absorbance versus the known concentration data of uranium.
3.9.4 X-ray Powder Diffraction Analysis (XRD)
To ascertain the chemical nature of radionuclides bound to the biomass the XRD analysis of
metal loaded sample was conducted in the Laboratory at NECSA Limited, South Africa.
After the bio-removal process the metal loaded sample was concentrated by centrifuging at
600 rpm for 10 minutes. The supernatant was decanted and the remaining pellet was dried at
60±10°C for 72 hours. The dried sample of uranium loaded biomass was grinded to near even
fine particle using mortar pestle method and then loaded into sealed sample holder to prevent
sample and equipment contamination. The sample was then analysed in XRD using Bruker
powder diffraction meter (Model D8 Advanced) with Cu-Kα radiation. The diffraction
pattern was recorded from 8-84° (2θ) with step size of 0.04° and time per step size 8.1 s. The
chemical nature of uranium crystals was determined by comparison with the powder
diffraction standard files in 2007 PDF-2 database.
3.9.5 Fourier Transform Infrared spectroscopy (FTIR)
To elucidate the chemical or functional groups involved in metal binding on the bacterial
surface the FTIR analysis of control (metal-free) and uranium-loaded sample was conducted.
For FTIR analysis cells were incubated with and without uranium for 24 hours. After 24
hours of incubation the cells were the harvested by centrifuging at 6000 rpm for 10 minutes.
The supernatant was discarded and the remaining pellet was dried at 60±10°C in an oven for
about 72 hours. The dried samples were then grinded using mortar pestle method to near even
particle size prior analysis on the (ATR-FTIR). Infrared spectra of uranium-free and uraniumloaded biomass were recorded within a range of 400-4000 cm-1 using a Bruker Tensor 70
FTIR spectrometer. The ATR-FTIR instrument resolution was set at 4 cm-1. The reflectance
spectra were recorded and averaged over 32 scans, using the total internal reflectance
41
configuration with a HarrickTM Mvp-pro cell consisting of a diamond crystal. Spectra were
viewed in OMNIC software.
,
3.9.6 Raman Spectroscopy
For detailed and conclusive sample characterisation, Raman spectrum analysis for the
previously prepared powder sample was conducted. Compared to the Infrared spectra, Raman
spectrum is very specific, effective in analysing inorganic material and it is also not affected
by the presence of water molecules in a sample. The Raman spectra of the sample were
obtained with a Ram II (FT-Raman) spectrometer (Bruker), fitted with a Germanium detector
cooled with liquid nitrogen. The 1064 nm wavelength radiation was used with a 50 mW laser
power setting. The spectral resolution on the instrument was set at 4 cm-1.
3.9.7 U(VI) Deposition Analysis using TEM
In order to establish whether cells were deposited on the surface or inside the cells
Transmission Electron Microscopy (TEM) of bacterial cells was performed in the
Microscopy Laboratory, University of Pretoria following the methodology by Mathews
(1986) and Hayat (1981). Metal free (control) and metal loaded bacterial cells were
concentrated by centrifugation and then fixed in 1-2% glutaraldehyde. Thereafter, the
material was washed three times with phosphate buffer (pH 7) followed by fixing in 0.5 %
osmium tetraoxide stain for 2 hours.
Cells were dehydrated through a graded ethanol series (30%, 50%, 70%, 90%, 100%, 100%,
and 100%), infiltrated with 50% Quetol epoxy resin and embedded in pure Quetol epoxy
resin for 3 hours (Glauert, 1975). Cells were then polymerised at 60°C for 39 hours and cut
into ultrathin sections using Reichert Ultracut E Ultra-microtome (Reichart, Germany). The
sections were loaded in carbon coated copper grid and stained with uranyl acetate and
Reynolds’ lead citrate for 2 minutes, and then rinsed in water. The ultra-thin copper coated
samples were then observed under a TEM (Joel JEM-2100F, Joel, Tokyo, Japan) equipped
with Energy-Dispersive X-ray spectroscopy (EDX) (Oxford Instrument, UK).
3.9.8 Elemental Scan using EDX
EDX spectroscopy of the metal-free and metal-loaded sample was conducted to achieve the
conclusive identification or characterisation of the deposited elements on the cell surface. The
EDX was set at the acceleration voltage of 200 kV. For accurate prediction of each element
42
in the sample a threshold was set to zero for all quantitative results with sigma below 1. To
stimulate the emission of characteristic X-rays from a specimen, a high-energy beam of X-ray
is focused to the ultra-thin sample (100 nm) with density of (10 g/cm3). The X-ray energy
released by focusing the X-ray beam to the sample allowed the characterization of elemental
composition of the specimen to be measured. EDX characterization capabilities were due to
the fundamental principle that each element has a unique atomic structure allowing unique set
of peaks on its X-ray emission spectrum. The weight % of each element in the sample was
determined by measuring the line intensity of each element in the sample.
3.9.9 Scanning Electron Microscopy (SEM)
Surface morphology of the culture attached to the support material and grown as a biofilm
was evaluated using Scanning electron microscopy (SEM) (Joel, JSM-5800LV). The biofilm
on the support material was fixed in a 2.5% glutaradehyde in 0.1 M phosphate buffer (pH
7.0) solution. The fixative solution was decanted off and cells attached to the support material
were then washed in a phosphate buffer, prior dehydrating in a series of ethanol solutions
(30%, 50%, 70%, 80%, and 90%). Samples were dried in liquid CO2 and then mounted on
stubs with double sided tape, coated with gold, and then observed under SEM.
3.10 Statistical Methods
3.10.1 Reliability Analysis
The required number of determinations for each sample was established using Statistical
Reliability Test as describe by Sawyer and co-workers (2003). A grid of three determinations
by five different operators was obtained for each method and the reliability factor Rm was
determined from variances using the equation below:
Rm =
S 2 B − S 2W
S B 2 (n − 1) SW 2
where: Rm= interclass correlation coefficient, n = number of experimental units (classes),
S2B= between experimental unit variability, and SW2= pooled within experimental unit
variability. To achieve a target reliability of R2=0.95 (95%) the required number of
determination was obtained by factoring the reliability based on the power test below:
m=
R ∗ (1 − R m )
R m (1 − R ∗ )
43
where: number of repetition required to obtain the target reliability, R*= target reliability
coefficient, Rm = calculated reliability coefficient (interclass). For the uranium solution
triplicate determination were required to achieve reliability factor of 0.95.
3.10.2 Quality Assurance
Prior to U(VI) analysis the UV/Vis spectrophotometer was calibrated. The calibration curve
was prepared in a BMM solution using the Arsenazo III method at λ = 561 nm. From the
stock solution of 1000 ppm uranyl nitrate serial dilution of known uranium concentrations
ranging from 0-80 mg/L were prepared and their absorbance was measured at 651 nm. The
intermediate precision of the method was evaluated using two different systems in the same
laboratory to measure same samples. The relative standard deviation obtained for two
systems using the same samples were 0.34 and 0.36, respectively.
The linearity of the method was evaluated using U(VI) standard concentrations of 0, 2, 10,
20, 30, 40, 50, 60, and 80 mg U(VI)/L, but the linearity was found to be at 0, 20, 30, 40, 50,
60, and 80 mg/L. The linear graphs/calibration curves with the regression of 99.7% were then
obtained by plotting absorbance versus the known concentration data of U(VI). The equation
of the calibration curve obtained was found to be linear in the standard uranium concentration
and was used for calculating unknown uranium concentration. To ensure that U(VI) analysis
method is dependable over a long term, routine analysis of three randomly selected uranium
standards were read in the pre-calibrated instrument. The absorbance’s of randomly selected
uranium standards were then compared to those in the linear standard curve with (R2=99.7%).
If the absorbance of uranium standards with the same concentration read significantly
different from one another then the instrument was re-calibrated prior further analysis.
In the case of protein analysis the calibration curve was prepared using BSA standard
solutions. It was observed that under standard assay conditions, the absorbance measurements
at λ=590 nm with the range of (0-0.645) was linear to protein concentration ranging from 0750 mg/L. With this range the correlation coefficient was 0.997 (R2=99.7%). This method
could directly measure proteins solution without dilution at concentration ranging from 101000 mg/L (Lopez et al., 2010). This simple procedure increased the accuracy of assay by
minimizing the error that may occur when diluting unknown protein concentration. For the
greatest accuracy in estimating total protein concentration in unknown sample a standard
curve was prepared each time the assay is performed.
44
CHAPTER 4
RESULTS FROM BATCH KINETIC STUDIES
4.1 Overview
The leakage of nuclear spent fuel waste from underground repositories and the leachate of
uranium from deposits have led to huge amount of uranium contamination in water systems.
As a first step towards addressing the problem of U(VI) contamination in water bodies,
studies on radioactive waste treatment using biological processes have been widely and
successfully conducted in batch reactor systems, such as closed and sealed serum bottles
(Chabalala and Chirwa, 2010, 2011; Reed et al., 2007; Luo et al., 2007). Batch reactor
systems were observed to be effective in treating U(VI) in aqueous solutions under controlled
environmental conditions. Although batch studies were observed to be effective in treating
U(VI), the results obtained from batch kinetics studies cannot be directly extrapolated into the
actual site for in situ bioremediation. This is because U(VI) transport through a saturated
porous media is highly dynamic process that cannot be fully defined through batch kinetic
studies.
As an initial step towards understanding the complex process associated with subsurface
U(VI) reduction, continuous flow systems were evaluated in this study. This is mainly
because unlike batch systems, continuous flow systems take hydrodynamic issues into
consideration. The performance of the microbial batch systems in removing U(VI) under
oxygen stressed conditions was evaluated using the pseudo-second order reaction kinetic
model. The kinetic parameters obtained from the batch kinetic studies were then adjusted and
used as an initial tool for easy development and evaluation of continuous flow system; this is
discussed in Chapter 5 and Chapter 6.
4.2 Microbial Analysis
Thirteen species of U(VI) tolerant bacteria were identified from the 16S rRNA gene analysis
of cultures isolated from the uranium mine tailing dumps. Of the 13 isolated U(VI) reducing
and tolerant bacteria under anaerobic conditions at 75 mg U(VI)/L, only nine species could
be sub-cultured under facultative anaerobic conditions. The other four species although
produced a fingerprinting during analysis they could not be sub-cultured under facultative
45
anaerobic
conditions,
suggesting
that
they
are
strictly
anaerobes.
Phylogenetic
characterization yielded 93 to 99% homologs associated with the Bacilli, Microbacterieceae,
Anthrobacteriae, and Acinetobater groups as shown in Table 4-1.
Among the identified homologs, were species previously reported to exhibit U(VI) reducing
activity and resistance to toxic effects of a range of metals. Fowle and co-workers (2000)
showed that some Bacillus species are effective biosorbents of uranium. Additionally, Suzuki
and Banfield (2004) observed intracellular accumulation of uranium in Anthrobacter species
isolated from a uranium-contaminated site. In the study by the later authors, the precipitation
of the uranium species inside the cells was localised around polyphosphate granules as
UO22+-phosphate complexes showing that the polyphosphate played a role in removal of
uranium from solution.
Table 4-1: Partial sequencing of URB isolated from soil samples of abandoned uranium mine
under facultative anaerobic conditions.
Pure Culture
NCBI Blast
% Identity
Y1
Kocuria turfanesis
Y3
Arthrobacter creatinolyticus
99 Actinomycetes from
Micrococcaceae
93
Y5
Microbacterium aerolatum
100
Y6
Bacillus licheniformis
100
Y7
Bacillus altitudinis
100
Y8
Anthrobacter sulfonivorans
100
Y9
Acinetobacter baumanii
100
Y10
Chryseobacterium indoltheticum
100
Y11
Bacillus pumilus
100
46
Figure 4-1: Phylogenetic analysis results showing the predominance of (a)
Microbacterieceae and Anthrobacteriae, (b) Acinetobacter, (c) Chryseobacrerium, and (d)
Bacillus species under U(VI) exposure.
47
A phylogenetic tree with closest association to know the purified cultures grown under
micro-aerobic conditions based on a basic BLAST search of rRNA sequencing in the NCBI
database was constructed (Figure 4-1a-d). Colonies Y10 in Figure 4-1c is not reported in
literature as any metal reducing species. Another uranium (VI) reducing species, Y6, was also
identified among the Bacilli shown in Figure 4-1d. In the phylogenetic analysis, the scale
indicated at the bottom of the plots represents the genetic distance, while the percentage
numbers at the nodes indicate the level of bootstrap based on neighbour-joining analysis of
1000 replicates.
4.3 Preliminary U(VI) Reduction Studies
Preliminary experiments on different bacterial species isolated from the tailing dumps of the
abandoned uranium mine were conducted to evaluate the effectiveness of each isolate in
reducing U(VI). Uranium (VI) reduction experiments on individual bacterial species were
initially conducted at low U(VI) concentration of 30 mg/L. All the experiments were
conducted in triplicates at 30±2°C. Data in Figure 4-2a and Figure 4-2b shows that all tested
isolates (Y1, Y3, Y5, Y6, Y7, Y8, Y9, Y10, Y11) were able to reduce U(VI) in the solution
effectively as individual pure isolates. These figures also demonstrate that significant U(VI)
removal in all tested isolates was achieved within the first few hours of incubation ranging
from 1 to 4 hours. Instantaneous U(VI) removal observed within the first few hours of
incubation at the initial U(VI) concentration of 30 mg/L was attributed to physical chemical
processes taking place in the system at near neutral pH in the presence of high nutrients
concentrations.
Although significant U(VI) removal in all tested species was observed within the first few
hours of incubation, Figure 4-2b shows the increase in U(VI) concentration in other species
(Y7, Y8, Y9, Y10, and Y11) after 4 hours of incubation. The species (Y7, Y8, and Y9) were
determined among nitrate reducing species that can release enzymes that oxidizes U(IV) to
U(VI) under anaerobic conditions in the presence of nitrate (Selenska-Pobell et al., 2008;
Akob et al., 2007). Therefore, the increase in U(VI) concentration observed in these species
was associated to the possibility of enzymatic U(IV) re-oxidation to U(VI).
The effectiveness of each isolate in reducing U(VI) was further evaluated at higher initial
U(VI) concentration of 75 mg/L, which is the background uranium concentration at the study
site. Results in Figure 4-2c show U(VI) removal efficiency of more than 50% in Y1, Y3, Y5,
48
and Y6 within 48 hours of incubation. The reduced U(VI) removal efficiency achieved in
other tested species (Y7-Y11) at the initial U(VI) concentration of 75 mg/L was associated to
the frequent U(IV) oxidation observed and also to susceptibility of these species to U(VI)
toxicity at higher U(VI) concentrations. The susceptibility of these species to U(VI) toxicity
was confirmed by significant decrease in microbial activity observed after 48 days of
incubation at initial U(VI) concentration of 75 mg/L.
40
40
30
(a)
U(VI) concentration at 30 mg/L
U(VI) concentration, m g/L
U (V I) concentra tion, m g/L
U(VI) concentration at 30 mg/L
Y1
Y3
Y5
Y6
20
10
30
Y7
Y8
Y9
Y11
Y10
(b)
20
10
0
0
0
5
10
15
20
25
0
5
10
Time, h
15
20
25
Time, h
120
Removal efficieny at 75 mg U(VI)/L
U(VI) Removal Efficency, %
100
(c)
80
60
40
20
0
Y1
Y3
Y5
Y6
Y7
Y8
Y9
Y10
Y11
U(VI) reducing species
Figure 4-2: U(VI) reduction by individual species at the initial U(VI) concentration of (a),
(b) 30 mg/L, and (c) 75 mg/L after 48 hours of incubation.
49
4.3.1 Performance Evaluation of Individual Isolates.
The performance of each isolate (Y1-Y11) in reducing U(VI) was evaluated over time at
lower and higher U(VI) concentration of 30 mg/L and 75 mg/L, respectively (Table 4-2).
Results show higher U(VI) removal efficiency of more than 50% on species Y1, Y3, Y5, and
Y6 at initial U(VI) concentrations up to 75 mg/L. In other tested species (Y7, Y8, Y9, Y10,
and Y11) higher removal efficiency of more than 50% was achieved at lower initial U(VI)
concentration of 30 mg/L. However, increasing U(VI) concentration to 75 mg/L, significant
decrease in U(VI) removal efficiency was achieved.
Table 4-2: Performance of individual species of isolates in reducing U(VI)
Pure
Culture
Initial U(VI)
Concentration
(mg/L)
Initial Protein
concentration
(mg/L)
--36.56
Protein
concentration
after
operation(mg/L)
--9.4
Removal
Efficiency
after operation
(%)
100
95.4
Y1
30
75
Y3
30
75
--39.89
--7.3
100
88.8
Y5
30
75
--44
--10.7
94
92.5
Y6
30
75
--50.17
--10.5
88.2
86
Y7
30
75
--53.2
--1.47
93.5
55
Y8
30
75
--48.78
--2
91.2
47.3
Y9
30
75
--54.3
--0
82
29
Y10
30
75
--44.33
--0
84
19
Y11
30
75
--48
--1.3
60
40
--- no data
It is also demonstrated in Table 4-2 that after 48 days of operation at 75 mg/L the decrease in
protein concentration was observed in all species but more pronounced in Y7, Y8, Y9, Y10,
50
and Y11. The highest performing pure isolates with removal efficiency of at least 60% and
with insignificant re-oxidation observed at 75 mg U(VI)/L were then used in this study for
further U(VI) reduction kinetic studies.
4.4 Mixed-Culture Performance
4.4.1 Abiotic U(VI) Removal
Abiotic U(VI) reduction activity was evaluated by conducting the experiments at 100 mg
U(VI)/L using cell-free and heat-killed culture controls. U(VI) reduction over time in the
abiotic controls was shown to be insignificant (Figure 4-3). However, instantaneous U(VI)
removal of 26.4% was observed in heat-killed cultures within the first 2 hours of incubation.
U(VI) reduction trends observed in heat-killed cells suggested that instantaneous U(VI)
reduction may be facilitated by interaction taking place on the cell surface at near neutral pH.
For effective abiotic evaluation, the cells were killed by exposing them to heat (120°C) over
several cycles prior inoculating them in U(VI) solution. Exposure of cells to higher
temperatures in several cycles was conducted to ensure near complete cell death as it was
suspected that the cultures of bacteria used in this study are capable of escaping destruction
by heat. This was evident by significant U(VI) removal observed previously in heat-killed
cultures which were not heated using the efficient heat-kill method (Mtimunye and Chirwa,
2013).
Live cell cultures, on the other hand, showed best performance with near complete U(VI)
reduction within the first 6 hours of incubation suggesting that the observed U(VI) removal
was metabolically linked. This suggests that biological U(VI) reduction by live-cell culture is
facilitated by the catabolic oxidation of organic substrates which result in the production of
NADH which is effective in mobilising electrons through the cytoplasmic membrane via
NADH-dehydrogenase (Figure 4-3).
4.4.2 The Effect of Thioredoxin Inhibitors
In earlier studies, thioredoxin was determined to be one of the principle electron donors in the
cytoplasm of living bacteria (Zeller and Klug, 2006; Li and Krumholz, 2009). In this study,
deactivation of thioredoxin activity by CdCl2 resulted in the discontinuation of biological
U(VI) reduction (Figure 4-3). However, since uranium species were mainly detected on cell
surfaces, this suggests that thioredoxin either influenced external factors responsible for
U(VI) reduction or a component of thioredoxin itself is excreted into the periplasm of the
51
U(VI) reducing cells. The observed U(VI) removal immediately after incubating the culture
with U(VI) solution was consistent with U(VI) removal by abiotic processes. Similar trends
were also observed in rotenone (C23H22O6) exposed cells. Inhibitory effects of U(VI)
reduction by the thioredoxin inhibitor, CdCl2, after 5-6 hours demonstrated thioredoxin is
directly or indirectly involved in U(VI) reduction by live-cultures.
4.4.3 The Effect of NADH-dehydrogenase Inhibitors
The role of NADH-dehydrogenase was elucidated in this study. The objective of this
component of the study was to determine whether U(VI) reduction is associated with the
membrane ETR system. NADH-dehydrogenase serves as a gateway into the ETR. U(VI)
reduction under NADH-dehydrogenase inhibited state could imply that U(VI) reduction in
the isolated cultures is uncoupled from the ETR or that U(VI) draws electrons from other
process for its reduction.
Results in Figure 4-3 showed that in the presence of C23H22O6, immediate U(VI) reduction
was observed within the first 6 hours of incubation. The immediate U(VI) removal may be
attributed to physical-chemical and bisorptive processes occurring during the first few hours
of incubation. However, inhibition effects were also observed after 5-6 hours of incubation,
demonstrating the involvement of enzymatic U(VI) reduction process in the system. The
insignificant U(VI) removal observed in the cell-free medium indicate that U(VI) reduction is
a metabolically mediated biological process.
4.4.4 Biotic U(VI) Reduction
To evaluate U(VI) reduction under anaerobic conditions batch experiments were conducted at
varying U(VI) concentration of 100 to 600 mg/L under near neutral pH using mixed-culture
of bacteria. Experimentation under varying initial concentration using harvested and
concentrated cells showed that the mixed-culture achieved near complete U(VI) reduction
under initial U(VI) concentration up to 400 mg/L (Figure 4-4). Similar to heat-killed cultures
instantaneous U(VI) removal was observed in all tested concentrations (100-600 mg
U(VI)/L) within first few hours of incubation (1-4 hours), suggesting U(VI) removal by
interactions taking place on the cell surface at near neutral pH.
At higher initial concentration of 600 mg/L complete loss of U(VI) reduction activity was
observed after 6 hours of incubation. The loss or finite U(VI) reduction activity observed at
52
600 mg/L after 6 hours of operation was directly correlated to loss of cell viability. Viable
cell concentration in the experimental run of 600 mg/L decreased from 109 to 103 cells/mL
after 12 hours incubation. The deactivation of cells was attributed to toxicity effects of U(VI)
to microbial cell activity at higher initial U(VI) concentration.
Figure 4-4c shows the performance of pure isolates in reducing U(VI) as individual species
against the reconstituted mixed-culture. The results in Figure 4-4c show that microorganisms
existing as a community, thus mixed-culture, possess significant stability and metabolic
capabilities than pure isolates which can be linked to the effectiveness of synergistic
interactions among members of bacterial communities (Martins et al., 2010; Mtimunye and
Chirwa, 2013).
120
U(VI) concentration, mg/L
100
80
60
40
Cell-free control
Heat-killed cells
CdCl2 exposed cells
20
Rotenone exposed cells
Live-cells
0
0
10
20
30
40
50
Time, h
Figure 4-3: Abiotic U(VI) reduction at the initial U(VI) concentration of 100 mg/L.
53
200
U(VI) Concentrion, mg/L
U(VI) reduction at low concentration
150
100 mg/L
200 mg/L
(a)
100
50
0
0
10
20
30
40
50
60
Time, h
700
U(VI) reduction at high concentration
U(VI) Concentration, mg/L
600
(b)
500
400
300 mg/L
400 mg/L
600 mg/L
300
200
100
0
0
20
40
60
80
Time, h
100
pure culture versus mixed-culture
U(VI) concenration, mg/L
80
Y1
Y5
Y6
Y3
mixed-culture
(c)
60
40
20
0
0
10
20
30
40
50
Time, h
Figure 4-4: U(VI) reduction at (a) low initial U(VI) concentrations (100-200 mg/L), (b) high
initial U(VI) concentrations (300-600 mg/L), and (c) pure isolates against mixed culture
54
4.4.5 Biomass Analysis
Viable biomass concentration was used to determine the level of cells viability during batch
system operation. Figure 4-5a shows change in biomass viability after batch system operation
at various initial U(VI) concentration ranging from 100-600 mg/L. Figure 4-5a shows notable
decline in cell viability at higher initial U(VI) concentration (300-600 mg/L). Decrease in
viable cell concentration observed at higher initial U(VI) concentrations may be attributed to
U(VI) toxicity effect on cells at higher U(VI) concentration. To determine the reliability of
the plate count method and to confirm the microbial activity of the viable cells in the batch
systems, protein concentration analysis was also conducted (Figure 4-5b). The results from
plate count method correlates with those of protein analysis, indicating the decrease in
microbial activity over time.
80
(a)
10
protein concentration
cells before operation
after operation
Protein concentration, mg/L
V ia b le ce ll c o n c e n tra tio n , C F U (1 *1 0 ^y )
12
8
6
4
100 ppm
200 ppm
300 ppm
400 ppm
600 ppm
(b)
60
40
20
2
0
0
100
200
300
400
500
0
600
10
20
30
40
50
Time, hours
initial U(VI) concentration, mg/L
Figure 4-5: Analysis of cell concentration during batch studies operation at various initial
U(VI) concentration (100-600 mg/L) (a) viable cell concentration before and after 12-24
hours of operation using plate count method, (b) protein concentration before operation and
after 48 hours of operation using BSA method.
4.4.6 Fate of Reduced Uranium Species in Cells
The distribution and localization of uranium deposits in the cells was established using TEM.
TEM of uranium-loaded cells revealed a dark electron opaque region extracellularly,
suggesting that the metal reductase activity in the isolated species is associated with the
55
periplasm and outer cell membrane (Figure 4-6a). Conclusive identification of the deposited
elements was achieved with EDX analysis. Using EDX coupled with TEM for conclusive
identification or characterization of the deposited elements it was possible to confirm that the
uranium loaded sample contained significant amount of uranium species in the precipitate as
compare to the uranium-free sample which contained traces of uranium species which may be
associated to the uranyl acetate dye used to stain the sample for TEM analysis (Figure 4-6b).
Quantitative Results
Weight (%)
(a)
P
Ca
Fe
Co
Cu
Os
U
Bacterium
Precipitate
Quantitative Results
Weight (%)
(b)
C
Cu
Fe
P
Ti
U
Bacterium
Figure 4-6: TEM scan and EDX spectrum of precipitate of (a) metal loaded biomass (Y6)
indicating deposition of uranium species on cell surface and EDX spectrum of precipitate, (b)
metal-free biomass.
56
It was observed in Figure 4-6a that the constituent percentage of uranium which was
calculated from the sum of all observed peak areas dived by the peak area of uranium at a
certain beam energy length was relatively higher than other associated elements identified in
the precipitate such as calcium, cobalt, copper, iron, and phosphorus. Most of the elements
identified in the precipitate result from the BMM which was used for U(VI) reduction kinetic
studies. In addition to its presence in the precipitate, phosphorus is also a well-known
important element of the bacterial cell wall (Beazley et al., 2007; Choudhary and Sar, 2011).
The presence of copper observed in Figure 4-6a is due to the copper grid which was used to
load the sample for analysis.
4.4.7 FTIR Spectroscopy
Functional groups of the bacterial cells involved in uranium binding were determined using
FTIR. The FTIR spectral analysis of control (metal-free) and uranium loaded cells was
applied. The FTIR spectroscopy allows certain characteristic peaks to be assigned to specific
functional groups present in the bacterial cell surface. Correspondence of the IR frequencies
was based on known data from the literature (Kazy et al., 2009; Choudhary and Sar, 2009;
Martins et al., 2009, 2010). The FTIR spectra from (400-4000 cm-1) of control cells (metalfree) and metal loaded cells are shown in Figure 4-7. The spectra of control showed a broad
band from (3000-3600 cm-1) with a maximum around 3300 cm-1, bands corresponding to the
N-H bond of amino groups along with the O-H of hydroxyl groups. In a uranium loaded
sample a change in peak intensity was observed suggesting involvement of amino and
hydroxyl groups in metal binding to bacterial surface (Choudhary and Sar, 2009, Martins et
al., 2010).
The control spectra showed the presence of two peaks between (2800-3000 cm-1) which can
be ascribed to the asymmetric stretching C-H bond of the –CH2 groups combined with that of
–CH3 groups. Figure 4-7 shows that both control and metal loaded cells revealed peaks of
protein related bands. The C=O stretching of amide (amide I) and N-H/C=O (amide II) bands
were prominent between 1500 cm-1 and 1700 cm-1. The spectrum of control showed the
bands of amide I and amide II at (1622 and 1529 cm-1) respectively while the spectrum of
metal loaded cells showed a shift in position of 1622 cm-1 to 1639 cm-1 and of 1529 to 1520
cm-1. The intense amide bands shift in metal loaded sample presents the possible interaction
of metals with cellular proteins.
57
3273
2087
2917
2316
1520
1639
Transmittance, %
2841
1240
833
2925
902
1359
3281
994
1444
503
1385
1232
919
1529
control
metal-loaded
1622
1054
513
4000
3000
2000
1000
wavenumbers, cm
0
-1
Figure 4-7: FTIR spectra of bacterial cell with and without metal.
The clear peak observed at 1444 cm-1 region in a control sample was attributed to the
presence of carboxyl group. The role of carboxylic group in uranium binding was confirmed
by decreased intensity and shift of peak observed at 1359 cm-1 in a metal loaded sample
(Pagnanelli, et al., 2000; Choudhary and Sar, 2011). Strong peaks in a control sample
between (1054-1232 cm-1) region are attributed to the presence of both carboxyl and
phosphate group respectively. The groups mostly belong to various cellular components like,
peptidoglycan, cell associated polysaccharides, phospholipids, and peptides and the groups
are able to complex different metals (Martins et al., 2010). Following metal sorption a shift of
these peaks indicates strong interaction of uranium with these functional groups. A decrease
in intensity and gradual shift of the peak 1232 cm-1 in control sample to a lower energy in
uranium loaded sample clearly indicates the weakening of P=O character as a result of
uranium binding phosphate.
In both spectrums a strong absorbance between (900-1100 cm-1) also ascertains the presence
of carboxyl groups. The peak change position in uranium loaded sample around 900-833 cm-1
could be assigned to asymmetric stretching vibration of uranium species. The overall IR
spectroscopic analyses suggest that carboxylic, amide, and phosphorus groups of bacteria are
dominant functional groups involve in uranium interaction. For detailed sample
58
characterisation, Raman spectra analysis was conducted. The Raman spectrum is preferred
for detailed analysis as it is not affected by the presence of water molecules in a sample and is
more specific. The Raman spectra of a metal loaded sample demonstrated strong peaks in the
frequency range (190-1000 cm-1) as opposed to the metal-free sample (Figure 4-8). The
strong vibrational bands between (191-1055 cm-1) in a Raman spectrum is assigned to the
symmetric stretching of O-U-O (Palacios and Taylor, 2000; Stefaniak et al., 2009). Similar
peaks which indicate the presence of uranium mineral in the metal loaded sample were
observed in the infrared spectra between (900-833 cm-1). This indicates that the vibrations of
uranium minerals are both IR and Raman active although strong and projective in the Raman
spectra as it is less destructed.
0.014
control
metal-loaded
Raman Intensity, counts
0.012
1055.0
0.010
191.0
0.008
817.7
0.006
0.004
0.002
0.000
4000
3000
2000
1000
0
Raman shift, cm-1
Figure 4-8: Raman spectra of a mixed culture of bacterial with uranium and without
uranium.
4.4.8 X-Ray Diffraction Analysis
The chemical nature of cell bounded radionuclides was ascertained by X-ray diffraction
powder spectroscopy. Characterization of the mineral phase by XRD gave a spectrum that in
accordance with PDF 2 database is consistent with the presence of uranium oxide as (UO3
and U3O8), and with the presence of uranium phosphate as (deuterium nitride uranyl
phosphate, plutonyl hydrogen phosphate hydrate) (Figure 4-9a-d). The crystalline uranium
phosphate formation following uranium accumulation indicates possible complexation of
such metal with uranium facilitating metal nucleation and precipitation in crystal state.
59
Lin (Counts)
9000
8000
(a)
7000
6000
5000
4000
3000
2000
1000
0
10
20
30
40
50
60
70
80
2-Theta - Scale
Y + 1.2 mm - File: UO2 powder_rep1.raw - Type: 2Th/Th locked - Start: 8.000 ° - End: 84.979 ° - Step: 0.039 ° - Step time: 1538.9 s - Temp.: 25 °C (Room) - Time Started: 10 s - 2-Theta: 8.000 ° - Theta: 4.000 ° - Chi:
Operations: Strip kAlpha2 0.500 | Enh. Background 21.380,1.000 | Enh. Background 38.019,1.000 | Enh. Background 38.019,1.000 | Enh. Backgro
01-072-0509 (I) - Uranium Oxide - UO3 - Y: 7.11 % - d x by: 1. - WL: 1.5406 - Tetragonal - a 6.89000 - b 6.89000 - c 19.94000 - alpha 90.000 - beta 90.000 - gamma 90.000 - Body-centered - I41/amd (141) - 16 - 946.
Lin (Counts)
9000
8000
7000
(b)
6000
5000
4000
3000
2000
1000
0
10
20
30
40
50
60
70
80
2-Theta - Scale
Y + 1.2 mm - File: UO2 powder_rep1.raw - Type: 2Th/Th locked - Start: 8.000 ° - End: 84.979 ° - Step: 0.039 ° - Step time: 1538.9 s - Temp.: 25 °C (Room) - Time Started: 10 s - 2-Theta: 8.000 ° - Theta: 4.000 ° - Chi:
Operations: Strip kAlpha2 0.500 | Enh. Background 21.380,1.000 | Enh. Background 38.019,1.000 | Enh. Background 38.019,1.000 | Enh. Backgro
01-076-1850 (A) - Uranium Oxide - U3O8 - Y: 5.09 % - d x by: 1. - WL: 1.5406 - Orthorhombic - a 11.91000 - b 6.71000 - c 8.27000 - alpha 90.000 - beta 90.000 - gamma 90.000 - Base-centered - Cmcm (63) - 4 - 660
Lin (Counts)
9000
(c)
8000
7000
6000
5000
4000
3000
2000
1000
0
10
20
30
40
50
60
70
80
2-Theta - Scale
Lin (Counts)
Y + 1.2 mm - File: UO2 powder_rep1.raw - Type: 2Th/Th locked - Start: 8.000 ° - End: 84.979 ° - Step: 0.039 ° - Step time: 1538.9 s - Temp.: 25 °C (Room) - Time Started: 10 s - 2-Theta: 8.000 ° - Theta: 4.000 ° - Chi:
Operations: Strip kAlpha2 0.500 | Enh. Background 21.380,1.000 | Enh. Background 38.019,1.000 | Enh. Background 38.019,1.000 | Enh. Backgro
01-076-2228 (N) - Deuterium Nitride Uranyl Phosphate - ND4UO2PO4(D2O)3 - Y: 34.23 % - d x by: 1. - WL: 1.5406 - Tetragonal - a 7.02210 - b 7.02210 - c 18.09119 - alpha 90.000 - beta 90.000 - gamma 90.000 - Pr
8000
(d)
7000
6000
5000
4000
3000
2000
1000
0
10
20
30
40
50
60
70
80
2-Theta - Scale
Y + 1.2 mm - File: UO2 powder_rep1.raw - Type: 2Th/Th locked - Start: 8.000 ° - End: 84.979 ° - Step: 0.039 ° - Step time: 1538.9 s - Temp.: 25 °C (Room) - Time Started: 10 s - 2-Theta: 8.000 ° - Theta: 4.000 ° - Chi:
Operations: Strip kAlpha2 0.500 | Enh. Background 21.380,1.000 | Enh. Background 38.019,1.000 | Enh. Background 38.019,1.000 | Enh. Backgro
00-032-0441 (N) - Plutonyl Hydrogen Phosphate Hydrate - HPuO2PO4·xH2O - Y: 8.79 % - d x by: 1. - WL: 1.5406 - Tetragonal - a 7.02000 - b 7.02000 - c 8.85000 - alpha 90.000 - beta 90.000 - gamma 90.000 - 436.
Figure 4-9: Background subtracted powder diffraction pattern of bacteria reduced uranyl
nitrate powder overlaid with stick pattern of (a) UO3, (b) U3O8, (c) deuterium nitride uranyl
phosphate, and (d) plutonyl hydrogen phosphate hydrate.
60
These observations indicate the role of phosphate groups in uranium binding. Phosphate
groups from intracellular phosphate or from cell membrane and wall materials may act as
primary metal binding site creating negative surface charge conductive to cation binding
(Merroun et al., 2003; Kazy et al., 2009; Choudhary and Sar 2011). The involvement of
phosphate groups in uranium binding on the test biomass was also indicated by EDX and
FTIR analysis. The presence of UO3 and U3O8 indicates that the mineral phase was composed
by a mixture of U(VI) and U(IV). The presence of U(IV) in the precipitate generated during
U(VI) removal experiments using live cells, suggest a mechanism of enzymatic reduction
where U(VI) is converted to insoluble U(IV). The presence of U(VI) species in the precipitate
may be associated to slightly re-oxidation of U(IV) due to oxygen exposure or may be
associated to U(VI) complexation with phosphate.
4.5 Modelling Theory
4.5.1 Kinetic Model Adaptation
Batch experiments on the isolated cultures were initially conducted to evaluate the rate
equations of kinetic constants for processes taking place in the batch reactor system. Batch
reactors are often used in the early stage for development due to their ease of operation and
analysis. As a results of batch systems none-complexity batch kinetics studied were
conducted to evaluate the fundamental of each process associated with biological mediated
U(VI) reduction in a system. In this study high levels of U(VI) and the presence of metabolic
inhibitors in a biological system inhibited both the cell microbial activity and U(VI) reduction
activity in mixed culture of bacteria.
These observations led us to evaluate U(VI) reduction model based on enzymatic U(VI)
reduction kinetics. To model a biological U(VI) reducing system, the reaction scheme, rate
equations, and kinetic constants for the processes taking place in the batch reactor are chosen
from published models on enzymatic reduction hexavalent toxic metals (Shen and Wang,
1994; Srinath et al., 2002; Viamajala, 2003). Biochemical studies on U(VI) reduction
suggested that U(VI) reducing mechanisms may be coupled to the membrane-electron
transport system in U(VI) reducing bacteria and the rate of U(VI) reduction catalyzed by
enzymes can be expressed as follows:
61
U(VI) + E
k1
→
←
k2
k3
E*U(VI) →
E + U(IV)
(4-1)
where: E = enzyme, E*U(VI) = enzyme-U(VI) complex , k1 = rate constant for complex
formulation, k2 = rate constant for reverse complex formulation, k3 = rate constant for U(IV)
formation.
Let U(VI) = U and E*U(VI) = E*
The rate laws of formation of E* in (Equation 4-1) result in the following equation:
dE *
= k 1U (E − E * ) − k 2 E * − k 3 E *
dt
(4-2)
E* is the representative enzyme that is logically proportional to viable cell concentration, X
as the only metabolic component in culture. E* can either be formed or destroyed such that
dE *
is
dt
approximately zero, thus
dE
≈0 .
dt
Therefore the mass balance represented in (Equation
4-2) can be expressed in the form of E* as following:
E* =
k1UE
=
k1U + k 2 + k 3
UE
k + k3
U+ 2
k1
(4-3)
Then U(VI) reduction rate in (Equation 4-2) can be expressed as:
− dU
dt
=
k 3 UE
k + k3
U + 2
k1
Analogous to Monod kinetics, k3 is analogous to maximum specific U(VI) reduction rate (ku),
k + k3
E is analogous to biomass concentration (X) and 2
is analogous to half saturation
k1
constant (Ku).
−
k ⋅U
dU
= u
⋅X
dt
Ku + U
(4-4)
where: U = U(VI) concentration at time, t (mg/L); X = concentration of active bacterial cells
at time, t (mg cells/L); ku = specific rate of U(VI) reduction (mg U(VI)/mg cells/h); and Ku =
half-saturation coefficient (mg/L).
62
4.5.2 Toxicity Effect of U(VI)
U(VI) reduction was conducted in batch reactors using pre-concentrated and washed cells
(resting cells) with very high viable cell concentration of 108-1010 cell/mL. In this case cell
growth kinetics is relatively less important and may be ignored as the concentration of cells is
at its maximum, indicating that future production of new cells is limited (Shen and Wang,
1993 and 1997). It was also determined from early studies (Shen and Wang, 1997, Chirwa
and Wang, 2000) that the rate and the extend of U(VI) reduction in bacterial system depends
on the number of active cells in the reactor, the initial U(VI) concentration, and U(VI)
reduction capacity per cell (Tu). This indicates that the amount of U(VI) reduced under
resting cells conditions will be proportional to the amount of cells inactivated by U(VI).
Therefore, in that case the active cell concentration, X, may be assumed to decrease in
proportion to the amount of U(VI) reduced due to the toxicity of U(VI) and the reduction
capacity of U(VI) may be incorporate with the toxicity effect of U(VI) on active cells as
follows:
1 d (X o − X )
=
Tu d (U o − U )
(4-5)
Integrating Equation (4-5) and interpreting in terms of active cell concentration yield the
following equation:
X = X0 −
U0 −U
Tu
(4-6)
where: U0 = initial U(VI) concentration (mg/L); X0 = initial active cell concentration (mg
cells/L); U = U(VI) concentration at time t; X = active cell concentration at time t; and Tu =
maximum U(VI) reduction capacity of cells (mg U(VI)/mg cell). Substituting Equation 4-6
into Equation 4-4 yields the following Monod saturation equation:
−
k ⋅U
dU
= u
dt
Ku +U

U −U
X0 − 0

Tu





(4-7)
4.5.3 Parameter Estimation
The unknown kinetic parameters in the developed model were determined by performing a
nonlinear regression analysis using the Computer Program for Identification and Simulation
63
of Aquatic Systems (AQUASIM 2.0), (Riechert, 1998). For each parameter, a search was
carried out through a range of values. Trial values of the unknown parameters were initially
guessed values. Constrains were also enforced to set upper and lower limits for each
parameter so that nonsensical or invalid parameter values were omitted. Whenever
optimization converged at/or very close to a constraint, the constraint was relaxed until the
constraint no longer forced the model.
Equation 4-4 was initially used to fit the experimental data at various initial U(VI)
concentrations. The results showed that the values of the specific rate of U(VI) reduction (ku)
and half-velocity constant (Ku) were not constant over a wide range of different U(VI)
concentrations (Table 4-3). The enzymatic expression in Equation 4-4 which does not
incorporate cell reduction capacity did not predict the data well over time. These results
indicated that U(VI) reduction on live cells is affected by U(VI) toxicity on organisms as a
result of its oxidising power which in turn resulted to a decrease in biomass activity over
time. The results also demonstrate that the enzymatic expression in Equation 4-4 will not
adequately describe the total pathway of U(VI) reduction over time.
Table 4-3: Optimum kinetic parameters obtained using Monod-kinetic model with a constant
active biomass.
U(VI) concentration ku
Ku
χ2
(mg/L)
(1/h)
(mg/L)
(Chi)
100
9.9997554
4197.1419
415.94142
200
9.9994544
4781.2558
2606.0715
300
0.1148374
8.3211232
26928.123
400
0.14261743
8.0549127
53531.653
600
0.003259105
119.20757
184220.08
To account for U(VI) toxicity in batch cultures the kinetic model (Equation 4-7) which
incorporates cell reduction capacity was evaluated. The results showed that the values of ku,
and Ku were not constant over different U(VI) concentration (Table 4-4), which indicates that
the kinetic rates were directly affected by the increase in U(VI) concentration.
64
Table 4-4: Optimum kinetic parameters obtained using cell inhibition model incorporated
with cell reduction capacity (Tu) (Equation 4-7).
ku
Ku
Tu
Xo
χ2
(1/h)
(mg/L)
(mg/mg)
(mg/L)
(Chi)
100
9.9242689
2038.5628
1.0191318
307
338.55
200
9.8847096
2035.0568
1.0161327
339
2196.98
300
9.2528476
2319.5472
1.0002405
259
2875.30
400
9.1043222
2496.4806
1.0185975
312
1807.28
600
9.9701954
2001.5095
1.0010612
167
10528.74
U(VI)
concentration
(mg/L)
Uncertainties obtained using Equation 4-7 at various U(VI) concentration did not allow
accurate estimation of Ku. The values of Ku at various initial U(VI) concentrations were
observed to be much greater than that of U, thus [Ku] >> [U]. Therefore, for such case the
Monod saturation equation in Equation 4-7 was simplified to pseudo-second order kinetic
equation as follows:

U −U 
dU

= − k uU  X o − o
dt
Tu 

(4-8)
In order to verify the validity of the model the kinetic parameters optimised using 200 mg/L
data were used to simulate U(VI) concentration at a broader range and the results were
plotted against the experimental data (Figure 4-10a-e). The pseudo-second order kinetic
model in Equation 4-8 produced near constants kinetic parameters (ku and Tu) (Table 4-5).
65
Table 4-5: Optimum kinetic parameters for pseudo-second order kinetic model incorporated
with cell inactivation term (Equation 4-8).
U(VI)
concentration ku
Tu
Xo
χ2
(mg/mg)
(mg/L)
(Chi)
(mg/L)
(L/mg/h)
100
0.012
1.00723
140.30
211.72
200
0.012
1.00723
180.82
736.59
300
0.010
1.00723
258.36
1598.42
400
0.010
1.00723
310.54
1923.00
600
0.012
1.00723
163.09
2831.44
The model captured well the trend data under experimental conditions investigated with an R
squared value of 99% and the mean square fitting error (δ2) of 1.261. At the highest U(VI)
concentration of 600 mg/L slight difficulty in fitting the parameters was observed, mainly due
to excessive loss active biomass due to toxicity. The R2 value of the model was determined
as:
R2 = 1−
S reg
(4-9)
S tot
2
Where: S reg
2
i =n
 i =n

 i=n

=  ∑ U i , exp − ∑ U i , predicted  and S tot =  ∑ U i , exp − U  , i=1, 2, 3…n.
i =0
 i =0

 i=0

The mean square fitting error was estimated as:
 ∑ (U exp − U predictate d )
δ u = 
 (n − p) 

1

2
(4-10)
where: n = number of data points used for curve fitting, p = number of fitting parameters,
Uexp = experimental U(VI) concentration (ML-3), Upredicted = predicted U(VI) concentration
(ML-3).
66
200
100
U (VI) concentration (m g/L)
U (V I) concentration (m g/L)
experiment
model
(a)
80
60
40
experiment
model
(b)
150
100
50
20
0
0
0
2
4
6
0
8
10
20
40
50
Time (h)
Time (h)
400
300
350
experiment
model
(c)
U (V I) co nce ntra tio n (m g/L )
250
U (V I) concentration (m g/L)
30
200
150
100
experiment
model
(d)
300
250
200
150
100
50
50
0
0
0
20
40
60
80
0
20
40
60
80
Time (h)
Time (h)
600
experiment
model
U(VI) concentration (mg/L)
(e)
500
400
300
200
100
0
20
40
60
80
Time (h)
Figure 4-10: Batch culture model validation at various U(VI) initial concentration of (a) 100
mg/L, (b) 200 mg/L, (c) 300 mg/L, (d) 400 mg/L, and (e) 600 mg/L.
67
4.6 Sensitivity Analysis
Sensitivity analysis was evaluated to compare the effect of different kinetic parameters (ku
and Tu) on a pseudo-second order model. Figure 4-11 illustrates the dependence of sensitivity
response curve of each optimized kinetic parameter. The results show that the model in
Equation 4-8 was highly sensitive to minor adjustment in (ku and Tu) within the first 10 hours
of incubation indicating the period of activity. The kinetic parameter Tu was observed to be
significantly sensitive, than that of ku this demonstrated the effectiveness of cell U(VI)
reduction capacity over time.
14
12
ku
Tu
10
Sensitivity, mg/L
8
6
4
2
0
-2
-4
-6
-8
0
5
10
15
20
Time, h
Figure 4-11: Sensitivity test for the initial U(VI) concentration of 100 mg/L with respect to
optimized parameters in anaerobic batch system.
4.7 Summary
It is demonstrated in this chapter that, for successful design and operation of suspended
growth biological system in wastewater treatment, it is essential to understand the types of
microorganisms involved. The mechanisms of radionuclide-bacteria interaction was
elucidated by employing several analytic techniques such as TEM, EDX, FTIR spectroscopy,
XRD, and RAMAN spectroscopy. The analysis from these techniques indicated U(VI)
removal by means of more than one mechanism. TEM analysis demonstrated extracellular
U(VI) reduction by the culture. Additionally, EDX did not only identify uranium in the
precipitate, but also the phosphorus which is an essential element in the bacterial cell wall.
FIR analysis demonstrated the involvement cell functional groups such as phosphate,
68
carboxylic, and amide group in U(VI) removal in a solution. The XRD analysis indicated the
presence of U(IV) in the precipitate indicating enzymatic reduction, where U(VI) is
converted to U(IV). The involvement of enzymatic U(VI) reduction was also confirmed by
complete prohibition of U(VI) reduction observed in this study in the presence of NADHdehydrogenase inhibitor.
The phosphate observed in the EDX analysis, FTIR analysis, and XRD analysis indicated that
the phosphate groups from intracellular phosphate or from cell membrane and wall materials
may act as primary metal binding site creating negative surface charge conductive to cation
binding. The results from this chapter demonstrated that U(VI) reduction by live cells can be
carried out by two mechanisms: biosorption, and enzymatic reduction. The results also
suggest that the process of U(VI) reduction in live cells can be divided into two steps: in the
first step U(VI) is adsorbed to the cell surface by interaction between metals and functional
groups displayed on the cell surface. The interaction taking place on the cell surface includes
ion exchange, micro-precipitation, complexation, and nucleation. The second step involves
enzymatic reduction of adsorbed U(VI) species on the cell surface to U(IV) (Nilanjana et al.,
2008).
Biosorption using live-cells offers a potential for biological process improvement through
genetic engineering of metabolizing cells. The species used in this study offers a potential of
instantaneously removing the dissolved species of U(VI) from the solution through
biosorption and then enzymatically reducing the adsorbed U(VI) species to U(IV).
Extracellular U(VI) reduction observed in this study present an opportunity to recover
uranium for further use.
A kinetic model for describing microbial U(VI) reduction by incorporating the toxicity effect
of U(VI) was evaluated. The kinetic parameters (ku, and Tu) were adequately described by
pseudo-second order model and were capable of predicting U(VI) reduction for a broad range
of initial U(VI) concentrations or cell densities with smaller uncertainties. The sensitivity of
each kinetic parameter (ku, and Tu) in the model was shown be significant indicating that the
two kinetic parameters are very essential for the scale up of the reactor. This model offers
quantitative insights of kinetics of microbial U(VI) reduction and may be useful for
evaluating reactor designs and improved for advance reactive transport modelling.
69
CHAPTER 5
KINETIC STUDIES OF CONTINOUS-FLOW SYSTEMS
5.1 Background
Continuous-flow systems have the potential of treating large volumes of wastewater
continuously under shock loading conditions at relatively lower cost. Additionally, where in
situ bioremediation is planned continuous-flow systems may be effective in simulating the
effects of diffusion, clogging of pores, and advection rates in the actual system. Results from
continuous-flow systems may be sufficient to understand kinetic process taking place in the
system with respect to hydrodynamic issues. Generally, the success of biological treatment of
contaminated environments is prominently determined by fundamental knowledge and
understanding of microbial processes taking place in the system at the laboratory level and
the ability to replicate those processes at the actual system. This study evaluates the
performance of the bench-scale continuous-flow systems, i.e. suspended-growth system and
attached-growth system in reducing U(VI) in the environment with respect to abrupt changes
in U(VI) concentration.
5.2 Conceptual Basis of Suspended Growth System
Experiments on suspended growth system were conducted to quantify the capacity of the
mixed-culture of bacteria in reducing U(VI) under shock loading conditions. In a suspended
growth system the mixed-culture of bacteria, Bacilli, Microbacterieceae, Anthrobacteriae,
and Acinetobater species responsible for U(VI) reduction were grown as a bio-floc and then
suspended in a system. The suspended culture was maintained in liquid suspension by
appropriate mixing methods. The system was operated under anaerobic conditions at low
velocities for quiescent mixing of U(VI) and biomass. U(VI) feed solution amended with
BMM and glucose as a sole added carbon source was continuously fed into the reactor.
Nutrients and carbon source were continuously added in a suspended growth system to
stimulate the growth of suspended culture as the system was operated without re-inoculation.
The system was not overloaded with higher U(VI) concentration until a near constant U(VI)
effluent concentration of the operated feed was achieved. To evaluate the performance of the
system the influent and effluent U(VI) concentration were measured regularly under
70
sustained hydraulic loading. Factors affecting U(VI) removal in the system such as the effect
of nitrate, the change in microbial activity, oxidation-reduction potential, and pH were also
continuously evaluated in the system.
5.3 Suspended Growth System Kinetic Studies
5.3.1 U(VI) Removal Efficiency
Time series data in a reactor (Figure 5-1) shows near complete U(VI) removal in all treatment
at initial U(VI) feed concentration ranging from (100-400 mg/L). It is observed in Figure 5-1
that the response of the bioreactor to the increase in U(VI) feed concentration of 150 mg/L,
200 mg/L, and 400 mg/L was achieved after 9 hours, 38 hours, and 165 hours of operation,
respectively. The delayed response of the reactor to the feed concentration was attributed to
the effectiveness of the mixed-culture in stabilizing U(VI) in the bioreactor. Consequently,
the response of the reactor to near feed concentration observed thereafter may be associated
to insufficient residence time of the feed at higher concentration in the reactor as the reactor
was operated without re-circulation. However, although the response of the reactor to the
feed concentration was detected over time, subsequent recovery of the system was attained in
all operated U(VI) feed concentrations. This demonstrates the effectiveness of the mixedculture used in this study in reducing U(VI).
Figure 5-1 also demonstrates that the flexibility of the reactor in accommodating sudden
fluctuation in U(VI) feed concentration improved with time when certain favourable
conditions were sustained. This was evident by the improvement of the reactor performance
after shock loading treatment of 150 mg/L. Removal efficiency of 65% was observed after
shock loading treatment of 150 mg U(VI)/L, while on the other hand near complete U(VI)
reduction was achieved at higher U(VI) feed concentration of 200 and 400 mg/L. Throughout
the entire period of system operation, the new feed concentration was not introduced into the
reactor until a near constant concentration of the previously feed U(VI) concentration was
achieved.
71
100 mg/L
150 mg/L
200 mg/L
400 mg/L
U(VI) concenrtation, mg/L
400
150
protein mg/L
300
100
200
50
100
0
0
100
200
300
400
Protein concentration, mg/L
200
500
0
500
Time, h
Figure 5-1: Evaluation of U(VI) reduction in at the initial U(VI) concentration of 100, 150,
200, and 400 mg/L and initial protein concentration of 184 mg/L.
5.3.2 Microbial Activity
Protein concentration, which served as surrogate parameter for microbial activity in a
suspended culture system was analysed over time. The steep decline of protein concentration
observed in Figure 5-1 within the first 6-12 hours of operation may be attributed to initial
exposure to high uranium concentration. Microbial activity entered a log growth phase
between 28 and 35 hours of incubation followed by the stationery phase after 100 hours of
operation. The increase in protein concentration observed between 28 and 35 hours of
operation may be associated to the adaptation of a mixed-culture of bacteria to U(VI)
exposure. At this stage the presence of U(VI), glucose, and nutrients in the reactor was
assumed to be beneficial for the cell activity. The stabilisation of the cell activity observed
between 100-300 hours of operation demonstrates that during this period cells were able to
reduce uranium via a respiratory process that does not conserve energy to support anaerobic
growth. After operating the system at highest U(VI) feed concentration of 400 mg/L
excessive loss of microbial activity was observed. The excessive loss of microbial activity
observed after shock loading treatment of 400 mg/L demonstrated that at higher influent
loadings, U(VI) was reduced at the expense of metabolic activity in suspended cells.
72
5.3.3 The Effect of Nitrate
The capability of the isolated species in reducing uranium in the presence of nitrate which is a
common pollutant co-existing with uranium in the nuclear waste was evaluated. Since nitrate
has the high reduction potential than uranium it was expected that the presence of NO3- in the
system will inhibit U(VI) reduction. The results from this study showed that the presence of
nitrate in the system at the concentration of 62 mg/L, background nitrate concentration at the
study site did not have any inhibition effect on U(VI) reduction. These results are in
agreement with those reported by Madden and co-workers (2007) and Boonchayaanant and
co-workers (2009) evaluated at nitrate concentration of 6 mg/L. In this study near complete
U(VI) reduction was achieved with very little loss of nitrate at near neutral pH using glucose
as a sole added carbon source (Figure 5-2). It was therefore suggested from this observation
that nitrate at the initial concentration of 62 mg/L was not acting inhibitor in U(VI) reduction
process.
100
Concentration, mg/L
80
60
U(VI)
NO3
40
20
0
0
5
10
15
20
25
Time, h
Figure 5-2: Simultaneous evaluation of nitrate (62 mg/L) and U(VI) (100 mg/L) reduction.
5.3.4 Impact of Redox and pH Conditions
The reactivity and mobility of radionuclides in biological system depends upon the ambient
pH and redox reaction. The U(VI) reduction profile observed in Figure 5-3 at the initial
U(VI) feed concentration of 100 mg/L showed a good correlation with the ORP of the
solution. The negative ORP observed in the system during the first 6 hours of incubation
reflected the reducing conditions when the culture was still highly anaerobic after purging
73
with N2 gas. After 6 hours of operation the ORP increased to a positive value due to the
removal of electrons from the system during U(VI) reduction to a lower oxidation state
(Figure 5-3). The pH in the continuous flow system was near constant ranging from pH (6.56) mainly because the feed solution was buffered by potassium phosphate which was
introduced into the system as part of the BMM medium.
200
100
100
U(VI) at 100 mg/L
0
ORP
60
-100
40
ORP, mV
U(VI) concentration, mg/L
80
-200
20
-300
0
0
5
10
15
20
-400
25
Time, h
Figure 5-3: Evaluation of U(VI) reduction, and oxidation reduction potential (ORP) at the
initial U(VI) concentration of 100 mg/L in a suspended-growth biological reactor system
within the first 24 hours of operation.
5.3.5 Performance Evaluation of the Suspended Growth System
The overall performance of the suspended culture in reducing U(VI) in a reactor under shock
loading conditions is summarized in Table 5-1. The results shows that the suspended culture
effectively reduced U(VI) at various shock loading treatment over time under near neutral pH
(6-7.5) in the presence of glucose as a sole added carbon source. In addition to reducing
U(VI) effectively, high percentage uranium recovery was also achieved in the tested culture
at various U(VI) concentration ranging from (100-400 mg/L). Since U(VI) and U(IV) are the
predominant forms of uranium in the environment, it was assumed using results from batch
kinetic studies that U(VI) is completely reduced to U(IV). U(IV) was determined as a
difference of total uranium and U(VI).
,
74
Table 5-1: Performance evaluation of U(VI) reduction in suspended growth system at near
neutral pH
U(VI)
feed Initial Protein Protein
concentration, concentration, concentration
after
(mg/L)
(mg/L)
operation,
(mg/L)
HRT
(h)
100
184.3
31
150
31
200
400
24
U(VI)
removal
efficiency
after
operation,
(%)
100
Total
uranium
recovered
after
operation,
(%)
88
29.9
75
65
91
29.9
19
136
95
95
19
0
213
98
96
5.4 General Principles of Bioremediation Technologies
The distribution and biodiversity of microorganisms inhabiting contaminated sites with genes
that facilitate metal-microbe interactions is crucial for in situ bioremediation of metal
contaminated environments (Ngwenya, 2011). Studies on in situ immobilisation of metals
such as uranium, chromium, and other harmful metals using microbial barriers have been
widely attempted at the laboratory level. The lack of specific application of in situ uranium
bioremediation to the actual sites has mainly been due to the unavailability of
microorganisms capable of growing under nutrient deficient or oligotrophic conditions, and
also due to the lack of information on the faith of the reduced metal species in the
environment.
Recently, experiments at a field site in Rifle, Colorado were conducted to determine if results
obtained from the laboratory sediment inoculated with pure culture of Geobacter sp. could be
extrapolated to in situ uranium bioremediation at the actual site (Anderson et al., 2003; Wu et
al., 2006). In the later study, in situ bioremediation was facilitated by the addition of an
external carbon source, acetate to stimulate the growth of Geobacter species. The growth of
these species was targeted due to their known ability in coupling acetate oxidation with U(VI)
reduction (Brodie et al., 2006; Nyman et al., 2006; Chirwa, 2011). Results from the previous
study showed that continuous injection of acetate at the site over time yielded conditions that
were less favourable for the growth of Geobacter species and more favourable for the growth
75
of SRB. Consequently, the predominance of SRB in the system over time resulted in reduced
activity of Geobacter species and decrease in U(VI) removal rates.
In this study a mixed-culture of bacteria from the soil samples of the abounded uranium mine
in Phalaborwa, Limpopo, South Africa was evaluated for its potential in reducing U(VI) in
the organic source free environment without introducing external nutrients. Results from this
study could serve as the initial step towards possible development of in situ U(VI)
bioremediation process for the target site.
5.4.1 Conceptual Basis of Biofilm System
The mixed-culture of uranium reducing bacteria in this study was grown on a support media
as a biofilm. The bio-cell filters used as biofilm support media possess large specific surface
area and high porosity. The experiments on the treatment of U(VI) containing water were
conducted in bench-scale fixed-film bioreactor system. The performance of the fixed-film
bioreactor system in treating U(VI) containing plume water was evaluated under oxygen
stressed and nutrient deficient conditions. This was done to evaluate the ability of the mixedculture of bacteria in reducing continual influx of U(VI) under natural aquifer conditions
characterized by large specific surface area, high pore volume, and low nutrient
concentration. The bio-cell filters used as support growth media were plastic material with
geometric shape representative of fractured and porous aquifer system expected at the study
site due to excessive mining.
The column inoculated with a mixed-culture of U(VI) reducing bacteria (R1), and the cellfree, control column (R2) were installed in the laboratory as previously discussed and
demonstrated in Figure 3-4 and operated as packed-bed continuous-flow reactor. To ensure
completely submerged conditions the reactors were operated in an up flow mode at the flow
rate of 0.33 L/h and actual hydraulic retention time of approximately 24 hours. The entire
packed-bed reactor had a total surface area of 0.33 m2 for biomass attachment and a clean bed
pore volume of 7.5 L. The biofilm reactor (R1) was operated without any external nutrients
and organic carbon source. This is of great environmental importance as the addition of
external organic carbon source may not effectively predict the potential risks of uranium
migration within tailings and depository sites. Furthermore, addition of external organic
carbon source may yield conditions that encourage the potential growth of foreign species at
site and in turn decrease U(VI) removal rates.
76
The performance of each column was evaluated based on the influent and effluent U(VI)
concentration under sustained hydraulic loading. The shift in microbial community was
evaluated using 16S rRNA gene sequencing for microbial culture. This analysis was done
after column operation to determine the shift in species to the original inoculum. A
conceptual representation of the permeable reactive barrier constructed by inoculating
Vadose Zone
specialized cultures of bacteria in a selected barrier zone is presented in Figure 5-4.
Bed Rock
Aquifer Zone
W.T.
h = hydraulic head; L = reactor length
W.T. = water table
Permeable reactive
barrier
Clean water
Concentration U, Xa
Pollutant plume
Barrier Zone
U
Xa
UxOy⋅(OH)n
Reduced species
Distance x
Figure 5-4: Theoretical representation of the microbial permeable reactive barrier system as
an intervention for U(VI) pollution in an unconfined aquifer system. The graph shows the
U(VI) concentration and biomass propagation under optimum operation conditions. U =
hydroxide precipitates of reduction products. The number of complexed hydroxyl ions, n,
will depend on the charge on the uraninite group UxOyn+ (Mtimunye and Chirwa, 2013).
Theoretically, the decreasing concentration of U(VI) across the barrier is envisioned if barrier
is inoculated with U(VI) reducing bacterial species. In the case of U(VI) reduction across a
barrier system, we expect to utilise U(VI) as an electron acceptor in a dissimilatory
respiration process in which the organisms introduced in the barrier (Xa) will require U(VI) at
77
optimum concentration to optimise their growth. If the organisms require U(VI) as a growth
limiting electron sink, their survival away from the barrier zone will be limited. This will
prevent increased microbial counts in the aquifer water if the aquifer downstream of the
direction of flow is utilised as a drinking water supply source.
5.5 Attached Growth System Kinetic Studies
5.5.1 Evaluation of the Abiotic Process
Operation of the reactor without added biomass (R2) showed characteristics of exponential
rise following effluent tracer line for clean-bed reactor (Figure 5-5). Low effluent U(VI)
concentration observed in (R2) within the first few days of operation may be attributed to the
presence of water in the reactor which was initially fed in the reactor to saturate pores and to
adjust flow rates to the required reactor hydraulic retention time. Exponential rise of U(VI)
effluent in the control reactor suggest that the adsorption processes were insignificant over
time, i.e., the reactor reached equilibrium with respect to adsorption during operation. The
data in Figure 5-5 also indicates that U(VI) was not retained in the column as effluent levels
always approached the influent levels over time. This data demonstrates that the control
reactor which was used in tracer analysis approached flow characteristics of mixed reactor
over time with respect to physical properties such as clean- bed mean hydraulic residence
time, advection, and porosity.
100
U(VI) concentration, mg/L
80
60
effluent
Tracer line
influent
40
20
0
0
20
40
60
80
100
Time, days
Figure 5-5: Performance of cell-free control reactor (R2) showing characteristics of
exponential rise in the effluent U(VI) as compared to the tracer.
78
5.5.2 Temporal Variation
The performance of fixed-film bioreactor system in treating U(VI) contaminated plume water
was evaluated over time. Figure 5-6 demonstrates near complete U(VI) removal after 29 days
of operation at the initial U(VI) feed concentration of 75 mg/L. Increasing U(VI) feed
concentration to 85 mg/L, near complete U(VI) removal was achieved 13 days after the feed
was increased. Near complete U(VI) removal achieved at loading treatment of 75 and 85
mg/L may be associated to various active processes taking place within the biofilm reactor at
the initial stage. Moreover, enhanced or improved U(VI) reduction rates observed at the
loading treatment of 85 mg/L may be attributed to the improvement of the biofilm system
over time when certain favourable conditions were sustained. Similar trends of reactor
improvement after the treatment of initial U(VI) feed concentration were also observed in a
continuous-flow suspended growth system.
After complete U(VI) removal was observed at 85 mg/L the system was challenged by
increasing the U(VI) feed concentration to 100 mg/L. Increasing U(VI) concentration up to
100 mg/L the biofilm system achieved U(VI) removal efficiency of 60%. The insignificant
U(VI) removal observed in the bioreactor after 66 days of operation at the loading treatment
of 100 mg/L may be attributed to limited diffusion of dissolved U(VI) species across the
biofilm layer. The limited metal-microbe interactions achieved in the bioreactor over time
may be associated to uranium precipitate [U(OH4)(s)] observed around the biofilm layer after
complete U(VI) reduction of up to 85 mg/L was achieved. These results demonstrate the
potential of accumulated reduced metal precipitates in changing groundwater hydrodynamics
and physically plugging critical aquifers features. Figure 5-6 shows that in all loading
treatments, U(VI) concentration in the biofilm system did not rise up to the actual added
U(VI) feed concentration, demonstrating the ability of the bioreactor system in stabilizing
U(VI) under a range of influent U(VI) concentrations.
79
120
75 mg/L
100 mg/L
85 mg/L
U(VI) concentration, mg/L
100
80
R1 effluent
R2 efffluent
Influent
60
40
20
0
0
20
40
60
80
100
Time, days
,
,
Figure 5-6: Performance of attached growth system (R1) and cell-free control system (R2) in
stabilizing U(VI) under oxygen stressed conditions. Biomass reactor (R1) effluent represents
average experimental data from the last port.
5.5.3 U(VI) Concentration Profiles
U(VI) removal across the biofilm system (R1) was evaluated over the entire period of
operation using data collected from equally spaced longitudinal sampling ports. Figure 5-7a
demonstrate that at the initial U(VI) feed concentration of 75 mg/L under non-steady
conditions, U(VI) removal was notably higher at the first sampling port from the bottom of
the reactor (port 1, h= 0.2 m) than in (port 2, h= 0.4 m). Higher U(VI) removal observed in
port 1 may be due to (i) the possibility of high accumulation of biomass at the bottom part of
the reactor as the cells were inoculated in the reactor in the up-flow mode, and/or (ii) delayed
response of the reactor to the feed concentration. Operating the biofilm reactor at the higher
U(VI) feed concentration of 85 mg/L and 100 mg/L, respectively, Figure 5-7 b and Figure 57c shows near constant U(VI) removal across the column over time.
80
100
80
(a)
60
U (V I) concentration, m g/L
U (V I) con cen tration , m g/L
80
port1 (R1)
port2 (R1)
port3 (R1)
port4 (R1)
control (R2)
influent
40
20
(b)
60
port 1 (R1)
port 2 (R1)
port 3 (R1)
port 4 (R1)
control (R2)
influent
40
20
0
0
0
5
10
15
20
25
30
30
32
34
Time, days
36
38
40
42
44
Time, days
100
U(VI) concentration, mg/L
80
port 1 (R1)
port 2 (R1)
port 3 (R1)
port 4 (R1)
control (R2)
influent
(c)
60
40
20
0
40
50
60
70
80
90
100
Time, days
Figure 5- 7: Evaluation of U(VI) removal across the biofilm reactor over time at initial feed
concentration of (a) 75 mg/L, (b) 85 mg/L, and (c) 100 mg/L.
Spatial Variation at Discreet Times
To determine or depict when near constant U(VI) removal was achieved across the reactor,
data collected from equally spaced longitudinal sampling ports at discreet times was
analysed. The results in Figure 5-8a show that at the initial U(VI) feed concentration of 75
mg/L the rate of U(VI) removal from the first 17 days of operation varied significantly over
length. Figure 5-8a also demonstrate near constant U(VI) removal across the reactor after 20
days of operation. These results are in agreement with tracer analysis results whereby
81
significant increase in effluent concentration to the influent level was observed after 20 days
of operation.
40
9 days
17 days
24 days
27 days
28 days
29 days
U(VI) concentration, mg/L
(a)
30
20
10
0
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Length, m
50
(b)
U(VI) concentration, mg/L
48
46
44
42
45 days
53 days
66 days
72 days
86 days
91 days
95 days
99 days
40
38
36
34
32
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Length, m
Figure 5- 8: Evaluation of U(VI) effluent across the reactor at initial feed concentration of
(a) 75 mg/L and (b) 100 mg/L.
On the other hand data in Figure 5-8b show immediate increase of effluent U(VI)
concentration to about 40 mg/L, when influent U(VI) concentration was increased to 100
mg/L. Thereafter, near constant U(VI) effluent concentration was observed across the column
over time. The near constant U(VI) effluent concentration (with variance of about 5%)
82
observed along the four intermediate sampling ports may be attributed to distribution of fluid
residence times across the porous system which may cause a degree of fluid mixing in axial
direction. However, although near constant U(VI) effluent concentration was observed across
the reactor, higher U(VI) removal rates were consistently achieved at first sampling (port 1,
h= 0.2 m) and the last sampling point (port 4, h= 0.8 m) over time.
5.5.4 Biomass Analysis
The growth curve in Figure 5-9 shows insignificant change in attached cells population
number per surface area within the first 7 days of operation which may be attributed to initial
exposure of cells to U(VI). The biomass population exponentially increased after 15 days of
operation. After about 18 days of operation, the biofilm was assumed to be at the mature
stage generating processes that contributes to the life of the biofilm, and play role in biofilm
survival, and biofilm spread. The increase in viable attached biomass population between 1543 days of operation may be attributed to cell defence mechanism such as cell acclimation to
the U(VI) toxicity.
The near constant growth of biomass observed between 50 and 90 days operation. Near
constant attached cell growth may be attributed to maximum attainable cell growth on the
surface of the biofilm due to the accumulated uranium precipitate. A slight increase in viable
cells observed after 90 days of operation may be attributed to change in community.
Scanning electron microscopy (SEM) was used to determine the surface morphology of the
culture attached to the growth support material (Figure 5-10). Figure 5-10b shows the
evidence of biofilm and crystals on the support material.
83
30
Viable attached biomass , g/m
2
100mg/L
25
85mg/L
75mg/L
20
R1 biomass
15
10
5
0
0
20
40
60
80
100
Time, d
Figure 5- 9: Evaluation of biomass in the biofilm reactor showing rise to the viable attached
biomass density.
5.6 Microbial Shift Dynamics
5.6.1 Characterization of Initial Inoculated Culture
The mixed-culture of bacteria isolated from the uranium contaminated soil samples was
grown under micro-aerobic conditions and inoculated in the column containing support
medium as a start-up culture. The start-up culture of U(VI) reducing bacteria was identified
from the 16S rRNA gene analysis as phenotypes of Bacillius, Microbacterieceae,
Anthrobacteriae, and Acinetobater. After operating the reactor for 99 days under oxygen
stressed and nutrient deficient conditions, the presence and the absence of U(VI) reducers
initially inoculated in the reactor was monitored by 16S rRNA fingerprinting method. Results
show the predominance of Acinotobacter spp., Bacillus spp., Rhodococcus spp.,
Cellulosimicrobium spp., and Curtobacterium spp., after column operation (Figure 5-11).
These species are characteristic of bacterial communities commonly found in the soil and are
closely related to the original inoculum.
84
(a)
(b)
Figure 5- 10: SEM analyses of a support material (a) without cells, control, (b) with cells
attached on it as a biofilm.
The Cellulosimicrobium spp., Rhodococcus spp., and Curtobacterium spp., are known
species of bacteria belonging to the family Microbacterieceae within the order of
Actinomycetales. These species are Gram-positive, facultative anaerobes that are also related
to Bacilli but differ in the DNA encoding of the 16S rRNA. These species are known to have
extensive metabolic capabilities under aerobic to micro-aerobic conditions. Elwakeel and coworkers (2012) showed the effectiveness of Cellulosimicrobium spp., isolated from the
radioactive waste in treating thorium contaminated aqueous solutions. The presence of these
bacterial species which are closely related to the initially inoculated culture after column
operation under oxygen stressed and nutrient deficient conditions demonstrate the
effectiveness of these phenotypes in reducing and tolerating U(VI) under shock loading
conditions. No foreign bacterial species were identified in the reactor after operation. The
insignificant change of the microbial community in the reactor after operation may be
attributed to the operation of the reactor without external carbon source as it is well known
from the literature that the addition of such may effectively result in the change of the
microbial community in the system (Wall and Krumholz, 2006; Chirwa, 2011).
85
Lysinibacillus boronitolerans
74
Acinetobacter johnsoniistrain ATCC 17909T
Bacillus massiliensis
7a
Bacillus fusiformis
Acinetobacter schindleri
(a)
95
Bacillus sphaericus
Acinetobacter haemolyticus ATCC17906T
(b)
Acinetobacter tandoii
72
78
Bacillus odysseyi
Bacillus silvestris
Acinetobacter tjernbergiae
Bacillus pycnus
Acinetobacter bouvetii
Bacillus arenosi LMG 22166
98
Acinetobacter junii ATCC 17908T
10 0
Acinetobacter johnsonii
85
94
Bacillus neidei
Acinetobacter grimontii
Bacillus psychrodurans DSM 11713
Acinetobacter gerneri
1 00
Bacillus psychrotolerans DSM 11706
Acinetobacter baumanni ATCC 19606T
Bacillus subtilis
Acinetobacter venetianus ATCC 31012
70
Bacillus arbutinivorans
Acinetobacter radioresistens
89
Acinetobacter ursingii
99
Acinetobacter lwoffii ATCC 17925
Bacillus novalis LMG 21837
Bacillus bataviensis LMG 21833
Acinetobacter baylyi
Bacillus pocheonensis
Acinetobacter baylyi
Bacillus niacini
Acinetobacter towneri
98
Bacillus drentensis
F7b
Acinetobacter calcoaceticus
99
Bacillus arvi LMG 22165
Bacillus aestuarii
Acinetobacter towneri
Brevibacterium casei
Psychrobacter immobilis
0.02
0.01
90 Curtobacterium citreum DSM 20528
(c)
Curtobacterium albidum DSM 20512
71
Curtobacterium ammoniigenes NBRC 101786
Curtobacterium luteum DSM20542
87
Curtobacterium pusillum DSM 20527
90
Curtobacterium flaccumfaciens pv. flaccumfaciens LMG3645
Curtobacterium herbarum DSM 14013T
98
F7d
Curtobacterium ginsengisoli
Rathayibacter toxicus
90
Rathayibacter tritici DSM 7486
98
100
Clavibacter michiganense DSM 46364
0.005
86
Rathayibacter carexis
Rhodococcus globerulus
91
96
Rhodococcus baikonurensis
Rhodococcus erythreus
(d)
Rhodococcus equi DSM20307T
(e)
Rhodococcus yunnanensis
100
Aerococcus urinaeequi
Rhodococcus fascians
100
Rhodococcus kroppenstedtii
100
92
Rhodococcus corynebacterioides
F7c
Aerococcus suis
Rhodococcus triatomae
Aerococcus urinaehominis
Rhodococcus coprophilus DSM43347T
78
Rhodococcus zopfii ATCC 51349T
100
F8a
Aerococcus viridans ATCC 11563
Aerococcus sanguinicola
Rhodococcus aetherovorans
Aerococcus christensenii
Rhodococcus ruber
93
Rhodococcus rhodochrous
70
Aerococcus urinae NCFB 2893
Rhodococcus pyridinovorans
98
Streptococcus defectivus
Rhodococcus gordoniae
Rhodococcus rhodnii
0.01
Corynebacterium diphtheriae NCTC 11397
0.01
(f)
Cellulosimicrobium cellulans
79
100
F8b
Cellulosimicrobium cellulans
74
Cellulomonas pachnodae
100
Cellulosimicrobium vaiabile
Cellulomonas turbata
Cellulomonas humiferus
72
97
Cellulomonas fimi
Beutenbergia cavernosa
0.005
Figure 5- 11: Phylogenetic analysis results showing the predominance of the Gram-positive bacteria (a-f) belonging to Microbacterieceae,
Anthrobacteriae, Bacilli group after shock loading treatment of U(VI).
87
5.7 Summary
Continuous-flow bioreactor systems have the potential of treating shock loadings of U(VI) in
both suspended growth and attached growth system. The mixed-culture of bacteria in the
suspended growth system was observed to be effective in reducing U(VI) in the solution at
relatively higher initial U(VI) feed concentration ranging from (100-400 mg/L). The
suspended culture was able to reduce or stabilize U(VI) in the system at concentrations up to
400 mg/L. Higher U(VI) removal rates observed in the suspended culture system which was
operated without re-inoculation with fresh cells may be attributed to continuous addition of
concentrated nutrients and glucose solution in the system. These demonstrates the
effectiveness of nutrients and glucose in enhancing U(VI) removal in the system by
stimulating the activity of viable URB.
The fixed-bed bioreactor was operated under oxygen and nutrient deficient conditions
without addition of external organic carbon source. The results from this study showed that
the biofilm system was able to stabilize U(VI) up to the initial feed concentration of 100
mg/L, which is much higher than the background uranium concentration at the study site.
Higher U(VI) removal rates observed in biofilm system under shock loading treatment
without biostimulation may be attributed to the effectiveness of the mixed-culture and
interrelationships that occur within the biofilm structure.
Results presented here have strong implications of ex situ biological reduction of U(VI)
through the use of the bioreactor systems. Moreover, operation of the biofilm system under
oxygen stressed and nutrient deficient conditions with continual influx of the contaminant
also demonstrated the ability of indigenous culture in reducing U(VI) in situ. These results
could be effective towards successful development and proper design of biological
containment barrier technologies at U(VI) contaminated aquifers. The complex nature of the
biofilm which is attributed to complex processes within the attached growth biofilm system
such as mass transport resistance, cell and substrate diffusion, and biofilm detachment often
pose difficulty in analysing biofilm system experimentally. Therefore, for effective analysis
of a complex biofilm system a mathematical model that effectively approximates or simulates
the observed process behaviour should be developed.
88
CHAPTER 6
MODELLING OF CONTIONOUS-FLOW SYSTEM
6.1 Biofilm Systems Background
The second component of the study utilising the continuous flow process capitalises on the
improved performance observed in attached growth biofilm systems. Attached growth
technologies such as trickle-bed reactor systems, rotating biological contactors (RBCs),
membrane bioreactors (MBRs), and anaerobic sludge blanket reactors (ASBR) have been
widely used for treatment of both municipal and industrial wastewater. Biofilm system have
been observed to provide better treatment efficiency of wastewater streams due the high
volumetric density of microorganisms accumulated in the presence of large surface area
inducing biofilm resistance to environmental changes (Rittman and McCarthy, 2001;
Kermani et al., 2008). However, the efficiency of biofilm systems in treating contaminated
water is not only dependent on the capability of the microbial culture to degrade or transform
pollutants but is also dependent on the microbial interactions within the biofilm matrix. These
interactions include (i) community level interdependencies, (ii) substrate concentration
profiles with varying biofilm depth, (iii) and biofilm loss rates influenced by surface shear
created by hydrodynamic loading.
The biofilm system is very complex in structure and heterogeneous in composition. Model
performance of the biofilm is therefore achieved by approximations and space averaged
values (Rao et al., 2010). Generally, mathematical models that resemble real system and
phenomena taking place within it are very rare. This is due to the complexity associated with
hydrodynamic regime and mass transfer characteristics within the biofilm system. In practice,
mathematical models are primarily developed to provide adequate and critical information
required for conceptual understanding and optimum design and operation of biofilm system
at the actual site.
Biofilm models previously presented by Wanner et al. (1995), Chirwa and Wang (2005), and
Rittman and Davantzis (1983) were developed under the assumption of the two-dimensional
propagation of biomass and substrate removal constrained within the biofilm space. Each of
the above models oversimplified the internal structure of the biofilm into a homogeneous
89
matrix with a singular diffusion and reaction rate property. The results from the previous
models were observed to be effective for routine reactor design. The problem associated with
the application of such models to real practical problems is that they could not generate
sufficient information required for optimum operation of microbial barrier system at actual
site. Therefore, there is a need to develop a mathematical model that could simulate near real
system situation under shock loading conditions.
This study is one of the few efforts to develop a fixed-film mathematical model that predict
the fate of U(VI) across the biofilm system under oxygen stressed and nutrient deficient
conditions. The model in this study takes into consideration the physical properties of the
system and the microbial growth kinetics of the bacteria composing the biofilm. Numerical
solutions of this model is essential for fundamental understanding of a complex biofilm
system from hydrological, chemical, and biological point of view under natural aquatic
system conditions.
6.2 Basic Biofilm Model Assumptions
•
Biofilm is treated as a continuum: variables are described by average quantities such
as concentrations and volume fraction
•
∆U 
Gradients of system properties 
 are in orders of magnitude greater perpendicular
 ∆t 
to substratum than in other direction, thus the flow in the column is considered to be
one-dimensional for biofilm modelling.
•
The flow has no radial gradient in velocity: perfectly mixed in radial direction
•
The reactor approached mixed reactor flow characteristics over time with respect to
hydraulic residence times, porosity, and advection.
•
The porous medium is homogeneous
•
Since the biofilm consisted of 95 % water, the porosity was assumed to be constant
•
Biofilm consist of one liquid phase and one solid phase, whereby each phase consists
of mass of particulate matter.
90
•
The flow is saturated, which means that all available pores space are filled with fluid,
this is exclusive of dead end pores where water is trapped.
•
Liquid phase consist of both dissolved components and particulate components
•
Assume complete reduction of U(VI) to U(IV)
•
U(IV) generated due to biotransformation is either precipitated and retained or
adsorbed onto the media almost immediately
•
Change in temperature and pH is insignificant
6.3 Model Approach
Generally there are three predominant mechanisms influencing transport and removal of
dissolved species in a porous media, i.e, (i) advection, (ii) molecular diffusion, and (iii)
kinematic (mechanical) dispersion. Within the biofilm itself, the rate of removal is influenced
by adsorption processes at the liquid-biofilm interface and conversion rate within the biofilm
matrix. For the purpose of discussing the mass transport dynamics in the biofilm, the biofilm
is divided into two parts: away from the biofilm surface (bulk solution) and approximately on
the biofilm surface. The model developed for the biofilm system is based on the mass
balances which describe in mathematical terms the (i) transportation of the substance in the
bulk liquid solution which is controlled by advection, (ii) the transportation of the dissolved
substances towards the biofilm surface which is controlled by diffusion, (ii) the microbial
processes causing population dynamics (thus microbial growth, cell attachment and
detachment). To simulate the fate of U(VI) across the biofilm system under oxygen stressed
conditions, the general mathematical expression of diffusion-reaction equation that describe
the transport of dissolved species from the bulk phase into the biofilm and vice-versa and, is
evaluated in this study. Figure 6-1 below shows the conceptual biofilm model in the biofilm
reactor:
91
∆z
DIFFUSION
adsorption
REACTION
reactants
products
erosion
0
SUBSTRATUM
Lf
BIOFILM
Lw
z
BULK
Figure 6-1: Conceptual biofilm model
6.3.2 Analytical Methods of Biofilm Measurements
For effective model development parameters, Af, Xf, and Lf were initially calculated using the
experimental data as following:
A f = Va v
Lf =
Xf =
Ww
Af ρ
(6-2)
f
Wd
A f αL f
(6-3)
(6-4)
where: Af = available biofilm surface area (L2), V= volume of the reactor (L), aV = specific
surface area of the particles (L2L-3), ρf = wet biofilm density (ML-3), Ww = wet weight of
attached biomass (M), Wd = dry weight of attached biomass (M), Xf = biofilm density (ML-3),
Lf = thickness of biofilm layer (L), and α= biofilm density factor. Values of α are in the range
of 0.9-1.0 by (Moller et al., 1998). In this study α = 0.95 was used. The surface area of the
biofilm is expected to be less than the total surface area of the filter material due to
incomplete biofilm coverage.
6.3.3 Hydraulic Characteristics
The cross-sectional area of the reactor A(t) affects the interfacial fluid velocity ν (LT-1) and
the stagnant liquid layer (Lw) around the support media. This is because the void (pore)
92
volume available for free flow of water in microbial barrier column decreased as biomass
grows around the support media. This resulted in decrease in the available cross-sectional
area of the reactor [A(t)] and constrained flow with increasing time. The initial value of crosssectional area of the reactor [A(t)] before biomass attachment is computed as a function of
pore volume as follows:
A(0) =
π (ID) 2  Vs 
4
⋅  
 VT 
(6-5)
where: VT = π(ID)2⋅h/4, the empty-column volume (L3), Vs = volume of void space occupied
by water (L3), ID = internal diameter of the reactor column (L), and h = the height of the
packed-bed reactor (L).
6.3.4 Liquid Layer Effect
In order to estimate the stagnant liquid boundary layer (Lw) in the fixed film reactor the
parameters: Q (inflow rate); A (cross sectional area of a reactor); dp (diameter of the filter
media); Duw (diffusion coefficient of U species in water); and υ (kinematic viscosity of
water) are required. Empirical correlations by (Frosslings, 1938; Wilke and Chang, 1955;
Sherwood et al., 1975; Cussler, 2003; Basmadjiaan, 2004; Incropera et al., 2011) are used to
calculate (Lw) using Schmidt number (Sc), Sherwood number (Sh), Reynolds number (Re) as
follows:
Sh =
K LU d p
Duw
(6-6)
The Sherwood number is often expressed as a function of non-dimensional Reynolds number
Schmidt number (Sc) as follows:
Re =
Sc =
νd p
υ
(6-7)
υ
Duw
(6-8)
where: dp = average particle size (L), Duw = diffusion coefficient of dissolved uranium species
in water (L2T-1); υ = kinematic viscosity; K LU = mass transfer coefficient (LT-1).
L w = N + B Re m Sc n
(6-9)
where: N (depends on geometry of biofilm and it runs from 0, 1, 2, and 3); B= 0.6; m=1/2; n
=1/3
93
Therefore the equation (6-9) above can be represented as:


  ν 1/ 2 
1

⋅
Lw = 0.6 ⋅ 
 D 1/ 3υ1/ 6   d 1/ 2 

 uw
  p 
−1
(6-10)
where: Duw = diffusion coefficient of dissolved species of U(VI) in water (L2T-1), ν = Q/εA(t)
is the interfacial velocity (LT-1), Q = flow rate across the bulk liquid zone (L3T-1), dp =
average particle size (diameter) (L), υ = kinematic viscosity (L2T-1), and A(t) = effective
cross sectional area of the reactor column (L2). The diffusion coefficient of U(VI) in water
Duw = 6×10-6 m2/d, determined from standard 1M of uranyl nitrate at (25°C, dynamic
viscosity =1.01 centipoises= 1.01 g/cm/s, and kinematic viscosity of ( υ =
µ
=4.2 cm2/s) was
ρ
used in this study (Ondrejcin, 1961).
6.4 Reactor Mass Balance
6.4.1 Mass Balance of Dissolved Species
In general terms the mass balance of dissolved species across the bulk liquid zone of the
packed-bed reactor at a transient state can be represent by various physico-chemical and
biological processes described below:
Advection
The transport of dissolved U(VI) species from one point to another governed by bulk motion
of fluid as follows:
−dU B
V B = Q(U in − U B )
dt
(6-11)
where: UB = U(VI) concentration at the bulk liquid zone at time, t (ML-3), VB = bulk liquid
volume (L3), Uin = influent U(VI) concentration (ML-3), Q = influent flow rate (L3T-1), and t =
time (T).
Molecular Diffusion
The transport of all dissolved species across the boundary layer (Lw) into the biofilm is
caused by random molecular motions and collusions of particles themselves. Molecular
diffusion is the only means of mass transport mechanism within the biofilm that follows
Fick’s law and can be defined as a function of external mass transfer resistance (KLU) across
the biofilm surface area and bulk U(VI) concentration as follows:
94
(
)
D
−dU B
V B = K LU A f U B − U sf = uw A f U B − U s f = j u A f
dt
Lw
(
)
(6-12)
where: Af = total biofilm surface area (L2), Duw = diffusion coefficient of dissolved uranium
species in water (L2T-1), Lw = the thickness of the stagnant liquid layer, which may decrease
the flux of dissolved particles into the biofilm (L), UB = U(VI) concentration at the bulk zone
at time, t (ML-3), Usf = liquid-biofilm interface U(VI) concentration (ML-3). In most mass
transfer limited reactions UB˃˃ Usf, thus Usf is negligible and may therefore be omitted in the
equation above. The external mass transfer resistance, KLU, (LT-1) can be visualized by
introducing a boundary layer (Lw) as follows:
K LU =
Duw
Lw
(6-13)
Adsorption
The rate at which U(VI) is removed across the reactor is dependent on the rate at which
U(VI) is transported across the liquid layer by diffusion and adsorbed within the biofilm
matrix. The rate at which U(VI) can be reduced on the surface area of the biofilm is defines
as:
− dU B
= k ad U eq − U B = q u
dt
(
)
(6-14)
where: kad = U(VI) adsorption rate coefficient (T-1), Ueq= equilibrium bulk liquid U(VI)
concentration (ML-3), Usf = liquid-biofilm interface U(VI) concentration (ML-3).
Microbial-Reduction
The rate of U(VI) reduction in the biological system is highly dependent on the number of
active cells present in the reactor, and the capacity of cells to produce enzymes that can
reduce U(VI) under various loading concentrations. A fraction of cells leaving the biofilm
and exiting the reactor after time equivalent to HRT of the reactor are assumed to be at
resting conditions. It has been shown in batch kinetic studies that resting cells may reduce
U(VI) without the accompanying cell growth. It is suggested therefore that the amount of
U(VI) reduced under resting cells conditions will be proportional to the amount of cells
inactivated by U(VI) (Chirwa and Wang, 2005).
The inhibitory effects observed in the reactor over time at higher initial U(VI) concentration
of 100 mg/L under oxygen stressed conditions suggested incorporation of U(VI) toxicity
95
threshold concentration, Ur, and deactivation coefficient of cells in the system. Therefore, a
mathematical model incorporating U(VI) toxicity threshold concentration, Ur, and
deactivation coefficient of cells in the system was used during simulation of U(VI) effluent
concentration:
− dU B
=
dt
k uU B
  U B
  1− U
Ku +U B  K  r







U −U B
 X B − in

Tu X B






 = ruB


(6-15)
where: ku= specific rate of U(VI) reduction (L3M-1T-1), Ku = half-velocity coefficient (ML-3),
X0B = initial cell concentration at the bulk zone (ML-3), Uin = influent U(VI) concentration
(ML-3), K = dimensionless U(VI) inhibition factor (MM-1), Ur = inhibition threshold
concentration (ML- 3), Tu= maximum U(VI) reduction capacity of cells [g U(VI) reduced/g
cells] (MM-1)].
The overall non-linier equations from Equation 6-11 to Equation 6-15 governing the liquid
phase at transient state yield the following mass balance equation of the dissolved species
across the bulk liquid zone of the reactor:
dU B
V B = Q(U in − U B ) − ru BV B − q u V B − j u A f
dt
(6-16)
where: UB = U(VI) concentration at the bulk liquid zone at time, t (ML-3), VB = bulk liquid
volume (L3), Uin = influent U(VI) concentration (ML-3), Q = influent flow rate (L3T-1),
ruB=U(VI) reduction rate coefficient at the bulk phase (ML-3T-1), qu= rate of U(VI) removal by
adsorption (T-1), ju= U(VI) flux rate (ML2T-1), Af = surface area in the biofilm reactor (L2), t =
time (T), and ru = dissolved species removal rate (ML-3T-1),
The terms qu, ju, ru in the above equations represent adsorption, diffusion processes, and
reaction by suspended or inert cells in the bulk liquid respectively. The term qu in the above
equation can approach equilibrium easily whereas the terms ru and ju depend on the active
biomass. The term ju in Equation 6-16 applies across the stagnant liquid layer and the entire
biofilm depth.
96
6.4.2 Biofilm Zone Mass Balance
The flow of dissolved species across the biofilm layer was expected to decrease over time
due to the thickness of the mass transfer boundary layer by reduced uranium precipitate.
Therefore, as a result of these the transport of dissolved uranium species across the surface of
the biofilm over time was based on molecular diffusion which follows Fick’s law as follows:
j u = Duw
dU f
at 0 <z <L
dz
(6-17)
A mass balance of the dissolved species over an infinitesimal film segment δz gives:
d
j u = ruf
dz
(6-18)
Therefore, the partial differential equation describing molecular diffusion of a particulate
matter in water inside the biofilm is represented as follows:
dU f
dt
=
=
dU f
dt
d
dz
=
j u + ru f
(6-19)
dU f 
d 
 + ruf
Duw

dz 
dz 
(6-20)
Because the diffusion of species across biofilm is influenced by the volume fraction
(porosity) the diffusion-reaction biofilm equation for U(VI) removal rate and biomass growth
rate within the biofilm is computed as a function of porosity as follows:
ε
dU f
dt
dU f
dt
=
= εDuw
d 2U f
dz 2
+ ruf
(6-21)
dju ruf
+
dz ε
(6-22)
,,
where: ju= Duw(dU/dz) flux rate of dissolved species (ML-2T-1), Uf = U(VI) concentration at
biofilm zone (ML-3), ruf = removal rate of dissolve uranium species in the biofilm (ML-3T-1),
δz = infinitesimal region across the biofilm (L), ε= biofilm porosity constant. The reaction
rate is defined as follows:
,
ruf = −
k uU f X f
 1−U f
  U
Ku +U  K  r











(6-23)
where: where: ku= specific rate of U(VI) reduction (L3M-1T-1), Ku = saturation coefficient
(ML-3), Xf = biomass concentration at the biofilm zone (ML-3), Uin = influent U(VI)
97
concentration (ML-3), K = dimensionless U(VI) inhibition factor (M-1M-1), Ur = inhibition
threshold concentration (ML-3), ruf = removal rate of dissolved uranium species in biofilm
(ML-3T-1). The boundary conditions for dissolved species at the liquid-biofilm interface are
defined as:
(
j u = K LU U B (t ) − U f , s (t , L f )
)
ju = 0
at z = Lf
at z = 0
[ inner boundary]
(6-24)
[outer boundary]
(6-25)
6.4.3 Biomass Mass Balance at Liquid Zone
Various kinetic models can be used to represent the various biological processes in a system.
In the bulk-liquid zone of the biofilm the accumulation of cells in the zone is related to the
cell detachment from the biofilm, bulk phase net cell growth, as well as cell death rate. The
mass balance of cells across the bulk liquid zone and in the actual biofilm zone of the reactor
is generally represented as:
dX B
V B = Q( X in − X B ) + rXB V B + Φ (ν ). X f L f A f
dt
ν 2
Φ (ν ) = k d A f ρ f 
 2
dX
dt
f
=
(6-26)




(6-27)
dj x rxf
+
dz
ε
(6-28)
where: XB = viable cell concentration in the bulk liquid zone at time, t (ML-3), bx = cell death
rate coefficient (L3T-1), Φ(ν ) = cell detachment rate (T-1)_a function of the interfacial velocity
ν (LT-1), kd = cell detachment rate coefficient (TM-1L-1), Af = surface area in the biofilm (L2), ν
= interfacial velocity (LT-1), jx =Dxw(dX/dt) mass flux rate of biomass (ML-2T-1), rxf = biomass
production rate in the biofilm (ML-3T-1), ε= biofilm porosity (LL-1) . Since there was no
continuous addition of biomass over time the term QXin in Equation (6-26) is equal to zero.
Due to bio-cell filters rougher surface and limited shear forces of liquid across the biofilm
layer limited cell detachment was expected. Moreover, due to the dependence of cell
attachment on metabolism most of the cells present in the bulk liquid through detachment
which is minimal in this system were expected to be more susceptible to U(VI) toxicity than
attached cells. Thus, the viable cell concentration in the bulk liquid zone was expected to be
either less than or equivalent to the inert cell concentration. In this study we assume that the
98
viable suspended cell concentration (XB) is equal to suspended inert biomass (XiB), thus XB =
XiB, at XiB ˃˃0.
The reaction rate is defined as follows:
 Uf
rxf = µ max 
 Ku +U f


U −U f
 X f − in

Tu


 − bx X


f
ν 2
− kd Af ρ f 
 2

A

X f L f f

Vf

(6-29)
,,,
where: Ku = saturation coefficient (ML-3), Xf = biomass concentration at the biofilm zone (ML3
), Uin = influent U(VI) concentration (ML-3), Tu= maximum U(VI) reduction capacity of cells
[g U(VI) reduced/g cells] (MM-1)], µ max = maximum attainable cell growth rate (T-1). Because
the transport of cells across the biofilm is by physical displacement and that of dissolved
substance is by molecular diffusion, jx is expected to be lower than ju. The boundary
conditions for biomass at the liquid-biofilm interface are defined as:
ν 2
jx = kd Af ρ f 
 2

jx= 0

.X f L f


at z = Lf
at z = 0
[ inner boundary ]
[ outer boundary ]
(6-30)
(6-31)
6.5 Initialization and Simulation
The application of the biofilm model was initially evaluated in the cell-free reactor which
resulted in the characteristic of exponential curve showing saturation of absorption process in
the system. This indicates that the predominant processes across the biofilm over time are
limited to mass transport by diffusion, reduction, and cell growth. The biofilm model was
used in combination with U(VI) reduction rate kinetic parameters adapted from the anaerobic
batch culture system. However, adjustments of these reduction rate kinetic parameters were
allowed in the continuous flow biofilm system due to different culture sensitivity in the two
systems. Physical parameters were determined from known literature values (Ondrejcin,
1961). Mass transport and adsorption parameters were estimated from continuous-flow
reactor data. Since the accuracy of simulation of performance also depends on the prediction
of viable biomass in the rector, the viable cell concentration in this study was predicted based
on direct measurement of viable cells using the plate count method.
6.6 Parameter Optimization
The model defined by a set of partial differential equations was very stiff in nature. Solution
without practical constraints resulted in convergence to false optima for several parameters.
99
To avoid convergence to nonsensical values, upper and lower constraints upper and lower
constrains were set for each parameter to allow the omission of invalid parameter values.
Whenever optimization converged at or very close to a constraint, the constraint was relaxed
until the constraint no longer forced the model. This process was repeated until unique values
lying away from the constraints, but between the set limits were found for each parameter.
The inverse of the mean residual sum of squares computed as the global variance was used as
a fitness function during parameter optimization. Based on the optimised values and other
operating parameters, the model calculated the time series data of U(VI) concentration within
the reactor. The simulated U(VI) concentration using the model was then compared with the
measured experimental data and the deviations between the two are used determine the
accuracy of the model using Equation 4-10 defined in Chapter 4.
6.7 U(VI) Removal Kinetics
6.7.1 Bulk Liquid Phase Kinetics
Equation 6-16 and Equation 6-26 were solved numerically using the computer programme for
evaluating numerical methods Octave 3.0. Appendix B shows the code used to solve the
equation in the bulk liquid zone. Figure 6-2a shows the simulation of effluent concentration
at the bulk liquid zone, and data in Figure 6-2b shows the simulated biomass growth at the
bulk liquid zone. The model predicted well the change in U(VI) concentration at the bulk
liquid zone with respect to biomass growth. The inhibitory conditions observed in the
simulated effluent at bulk liquid zone at higher initial U(VI) concentration corresponded well
to the decreased growth rate of viable biomass observed over in the bulk zone.
6.7.2 Biofilm Zone Kinetics
Equation 6-22 and Equation 6-28 were solved numerically using the computer programme for
evaluating numerical methods Octave 3.0. The model for biofilm reactor at the biofilm
surface was initially tested with the experimental data of 75 mg/L. The kinetic parameters
obtained at 75 mg/L were then used to simulate U(VI) effluent concentration under various
loading conditions of 85 mg/L and 100 mg/L respectively.
Figure 6-3a and Figure 6-3b shows simulation of effluent concentration and biomass growth
at the biofilm zone. The kinetic parameters summarized in Table 6-1 shows that the kinetic
parameters obtained at the experimental run of 75 mg/L were maintained at various initial
100
concentrations with only minor adjustment on the half saturation concentration (Ku) at initial
higher concentrations. The adjustment of the kinetic parameter (Ku) may be associated to the
breakthrough characteristics observed in the packed-bed reactor at 85 mg/L with moderate
dispersion depicting an exponential rise up to maximum point and then followed by reduction
in effluent as U(VI) reducing culture become more established.
80
(a)
simulated UB
UB, mg/L
60
40
20
0
0
20
40
60
80
100
Time, d
90
(b)
80
simulated XB
XB, mg/L
70
60
50
40
30
0
20
40
60
80
100
Time, d
Figure 6-2: Model simulation at the liquid phase of (a) U(VI) effluent (b) biomass activity in
the reactor inoculated with live culture from the local environment.
For numerical simulation the attached viable cell concentration was initialised by values (Xf,
init
= 60 mg/L) determined using analytic methods. It is observed in Figure 6-3a and Figure 6-
3b that regardless of the lower initial biomass concentration in the biofilm reactor high
bioconversion rates were observed in the continuous flow biofilm system than in the batch
reactor system. The reaction rate coefficients obtained from the continuous flow attached
growth system (ku= 0.75) is much higher than the one previously observed in batch cultures
101
in this study (ku=0.012). It is also observed that the reaction rate (ku= 0.75) at the biofilm
zone is much higher than the one observed at the bulk liquid zone (ku= 0.5). This may be
attributed to the shielding effect or mass transport resistance against toxic effects on cell
towards biofilm.
100
(a)
U(VI) concentration, mg/L
80
simulate effluent
experimental data
influent
60
40
20
0
0
20
40
60
80
100
Time, days
50
(b)
Attached biomass , g/m
2
40
simulated biomass
30
20
10
0
0
20
40
60
80
100
Time, d
Figure 6-3: Model simulation at the solid phase of (a) U(VI) effluent (b) biomass activity in
the reactor inoculated with live culture from the local environment.
102
Table 6-1: Summary of kinetic parameters optimized in the biofilm system and applied
constraints.
Parameter Symbol
Definition
Constrains
[lower,
upper]
Optimum value
[output]
Uin (mg/L)
Influent uranium
--
75-100
concentration
Ku (mg/L)
Half velocity concentration
[0, 2]
0.5
[email protected] 100 mg/L
ku (L/mg/d)
Specific reduction rate
[0, 1]
0.75
Xfin (mg/L)
Initial biofilm cell
[40-80]
80
concentration
kd (d/mg/m)
Cell detachment coefficient
[0-1000]
0.006
bx (d-1)
Cell death rate
[0- 5 ]
0.0005
Tu(mg/mg)
U(VI) reduction capacity
[0- 5]
1.00
Ur (mg/L)
U(VI) toxicity threshold
--
100
Theta (%)
Porosity
--
95
rho_s (kg/m3)
biofilm density
--
2300
Qin (L/d)
Influent flow rate
--
0.00792
Duw (m2/s)
Dispersion coefficient
--
6×10-6
Dxw (m2/s)
Cell diffusion coefficient
--
1.108×10-6
A (m2)
Cross sectional area
--
Column properties
Af (m2)
Available surface area
--
Column properties
--- Constant values
6.8 Model Validation
The developed mathematical model incorporated with inhibitory conditions was evaluated for
its effectiveness in simulating the fate of U(VI) in the biofilm system over time under various
loading conditions. Kinetic parameters of the mathematical model were obtained by solving
Equation 6-16, 6-22, 6-26, and 6-28 using a Computer Program for Solving Numerical
103
Problems (Octave 3.0). The validity of the developed model was tested using broader range
of measured experimental data. This is known as the inverse problem approach. Table 6-1
indicates good fit between the model in Equation 6-26 and experimental data for different
initial U(VI) levels with an R2 > 95%.
6.9 Biofilm Thickness Kinetics
The rate of biofilm thickness propagation is correlated to the rate at which cells and particles
suspended in the bulk fluid are attached to the biofilm surface and the rate by which cells are
detached from the biofilm surface area as follows:
dL f
dt
=UL
(6-32)
where: UL = velocity by which particular components are attached and detached from biofilm
surface.
dL f
 1
=
dt
 1−ε
Af 
1 
 1

X f bx L f −
Φ (ν )X f L f

ρ f 
V f 
ρf
(
)
(6-33)
ν 2 


2


Φ (ν ) = k d A f ρ f 
where: ρf = biofilm density (ML-3), Af = available biofilm surface area (L2); Vf = volume of
the biofilm (L3), Xf = biomass density (ML-3), and Lf = thickness of biofilm layer (L).
Equation 6-33 was simulated using a fourth-order Runge-Kutta routine for solution of
ordinary and partial differential equations in A Computer Program for Solving Numerical
Problems (Octave 3.0) (Appendix B). For numerical simulation the initial biofilm thickness
was determined from the literature. Figure 6-4 shows that the thickness of the biofilm was
increasing over time until a near constant growth rate was achieved in the reactor between
60-99 days. The increase in biofilm thickness is associated with the increase in cell
growth/attachment while near constant biofilm thickness observed was associated to steady
state conditions whereby attachment and detachment of cells occurs simultaneously in the
system and roughly assumed to be equal.
104
0.0005
0.0004
simulated Lf
Lf , m
0.0003
0.0002
0.0001
0.0000
0
20
40
60
80
100
Time, days
Figure 6-4: Simulation of biofilm thickness over time in the biofilm reactor
6.10 Steady-state Analysis
6.10.1 Model Formulation
To facilitate the spatial modelling of U(VI) across the column, samples were collected from
equally spaced longitudinal sampling ports. The stable state condition of each experiment
was observed with regard to minimal variation of U(VI) concentration in the reactor. An
average effluent data from the last three sampling times with a deviation of 5% was
considered as a data point for each experimental run. Generally, biological reactor systems
operate under either mass transport limited or reaction rate limited kinetics. This implies that
the removal of dissolved species in the biofilm is not only determined by the total amount of
biomass in the reactor, but by the available surface area and the flux of the dissolved species
across the mass transfer boundary layer into the biofilm. In one dimensional model where the
U(VI) concentration varies only in the axial direction, the rate of mass transfer is considered
to be proportional to the concentration difference between the interface and the bulk fluid.
Under steady state there can be no accumulation of the component at the interface. The mass
transported from the bulk liquid to the film interface moves from interface to the solid
surface.
The mass balance of the dissolved species in the reactor at steady-state between segment,
z+∆z, may be represented as follows:
Fuz − Fu z
z
z + ∆z
+ ru aν ( A∆Z ) = 0
Dividing equation by A∆Z and taking the limit as A∆Z→0 we get the following:
105
(6-34)
1 dFuz
+ ru aν = 0
A dz
(6-35)
Expressing Fuz (molar flow rate of U(VI)) in terms of concentration, thus Fuz = νAU the
equation above can be represented as follows:
ν
dU
+ ru aν = 0
dz
(6-36)
For reactions at steady state the disappearance of the dissolved species U on the surface is
equal to flux of the species to the particle surface, thus ru = Wru
The boundary condition at external surface is:
ru = Wru = K LU (U B − U fs )
(6-37)
Therefore the differential equation governing the dissolved species in a biofilm system is
given as:
ν
dU
= K LU aν ( U B −U fs )
dz
(6-38)
where: KLU = mass transfer coefficient (LT-1), av = specific surface area of particle (L2L-3), ν=
superficial velocity (LT-1).
With boundary conditions:
UB= Uin
at z =0
(6-39)
The interfacial concentration of U(VI) across the reactor can be computed from the total mass
flux term and bulk liquid concentration as follows:
U sf = U B −
ju
K LU
(6-40)
Equation 6-38 was simulated using a fourth-order Runge-Kutta routine for solution of
ordinary and partial differential equations in A Computer Program for Solving Numerical
Problems (Octave 3.0). Figure 6-5a-c shows that the model depicted the near constant U(VI)
removal over time across the reactor at various U(VI) concentration. The near constant U(VI)
concentration observed across the porous biofilm system over time at the initial concentration
of 100 mg/L was mainly attributed to mass transport limitation across the biofilm layer which
resulted in the system being reaction rate limited. The model simulated well the experimental
data at last three sampling times under various loading conditions with an R2 value of 96 %.
106
8
U(VI) concentration, mg/L
(a)
6
4
experimental data
simulated data
2
0
0.2
0.4
0.6
0.8
1.0
Length, m
U(VI) concentration, mg/L
2
(b)
1
0
experimental data
simulated data
-1
-2
0.2
0.4
0.6
0.8
1.0
Length, m
U(VI) concentration, mg/L
50
experimental data
simulated data
45
(c)
40
35
30
0.2
0.4
0.6
0.8
1.0
Length, m
Figure 6-5: Model simulation of effluent U(VI) across the biofilm at (a) 75 mg/L, (b) 85
mg/L, and (c) 100 mg/L. Experimental data is the average effluent U(VI) concentration of the
last three sampling times where near constant U(VI) removal was observed over time.
107
6.11 Summary of Kinetic Parameters
The diffusion-reduction equation was used to model the biofilm system under various loading
conditions at transient state. Kinetic parameters initially optimised in batch systems were
adjusted and applied to continuous flow system. Minor adjustments were applied to inhibition
parameters due to the low level of biomass in continuous flow biofilm system. Other
parameters such as the mass transport kinetic parameters were determined from physicalchemical properties related to the continuous flow column. Table 6-2 below shows the direct
comparison of optimum kinetic parameters in the bulk liquid phase and the solid phase of the
reactor.
Table 6-2: Comparison of kinetic parameters at the bulk and solid phase
Parameters Description
Units
Bulk phase
Solid phase
[output]
[output]
bx
Death rate coefficient
1/d
0.05
0.0005
ku
Reaction rate coefficient
mg/L/h
0.5
0.75
Ku
Saturation coefficient
mg/L
2.5
[0.5-1.5]
Tu
Finite cell reduction capacity
mg/mg
2.5
1
Data in Table 6-2 above shows higher biological activity in the biofilm zone than in the bulk
liquid zone, indicating higher bioconversion rates in the biofilm zone due to the shielding
effects of transport resistance against toxic effects on cells inside the biofilm. This finding is
also confirmed by the higher biomass death rate observed in the bulk zone than that observed
in the biofilm zone.
The model output of biomass represents the biomass/density for each category, thus the total
biomass for each category or section. Because in this study the sample for viable attached
biomass was taken from only one sampling point due to oxygen stressed condition required in
an operated close system, direct comparison of measured data with model data output XfnLF
was difficult. The model for saturated column at the steady state was determined by an
ordinary differential equation as shown in Equation 6-38 which incorporated the mass
transport kinetic parameters.
108
6.12 Summary
The numerical methods for describing bio-kinetics in an anaerobic fixed-media bioreactor
were determined and validated using experimental data. Results show that the mathematical
model developed in this study was capable of simulating or predicting the fate of U(VI) in the
biofilm reactor under oxygen stressed and nutrient deficient conditions without any added
organic carbon source. Mass transport kinetics and U(VI) removal kinetics in the biofilm
reactor were represented by diffusion-reduction model. The model showed that uranium (VI)
removal efficiency in the biofilm reactor was limited by mass transfer processes across the
biofilm layer. The developed model predicted well U(VI) effluent concentration under
various influent U(VI) concentrations in the biofilm zone with 97% confidence. Moreover,
kinetics obtained from continuous flow biofilm reactor showed higher biological activity than
those observed previously in batch cultures. Although the model tracked successful trends in
effluent U(VI) concentration in the biofilm reactor modification of the model is still required
to take into consideration the change available biofilm surface area, change in mean residence
time distribution, and working volume which may occur due to accumulated precipitate in the
reactor or due to biomass growth. The modification of the model could result into a proper
model that can in detail predict field scale system that can aid in defective design and
operation of site for clean-up.
109
CHAPTER 7
SUMMARY AND CONCLUSIONS
Industrial activities such as uranium ore mining and milling, nuclear power generation,
radioisotope manufacturing, and other activities has resulted into a huge amount of radiotoxic
waste into the environment. Because uranium and its fission products are known to be
radiotoxic on living organisms treatment of U(VI) contaminated surface and sub-surface
water is required. As an initiation towards addressing the problem of U(VI) contamination in
the environment, experimental studies were conducted in this study in batch and continuous
flow bioreactor systems using indigenous cultures from the local environment. Experimental
studies on batch and suspended growth bioreactor system demonstrated U(VI) reduction
efficiency under oxygen stressed conditions in the presence of glucose as sole added carbon
source.
For bioremediation of subsurface water, a more practical system was demonstrated by
operating an attached growth biofilm system under oxygen stressed and nutrient deficient
conditions. The fate of U(VI) in the attached growth system was simulated by a developed
mathematical model which was validated using the experimental data, thus inverse
proportion. The following is a summary of the conclusions on both batch and continuousflow bioreactor systems (suspended growth and attached growth system):
1. The rapid rate of U(VI) removal observed within the first few hours of incubation in both
batch reactors inoculated with heat-killed cells and live-cells at initial U(VI) concentration of
100 mg/L demonstrated U(VI) removal by interaction taking place on the cell surface at near
neutral pH, thus physico-chemical processes.
2. The decreased rate of U(VI) removal observed thereafter when physico-chemical processes
were saturated demonstrated U(VI) reduction by enzymatic processes. This was confirmed by
the insignificant U(VI) removal observed in heat-killed cultures over time.
3. The inhibitory effects observed in rotenone (C23H22O6), and thioredoxin exposed cells
further confirmed the involvement of enzymatic process in U(VI) reduction.
110
4. Near complete U(VI) removal was observed in batch kinetic studies at concentration up to
400 mg/L. Inhibitory effects observed at higher initial concentration of 600 mg/L after
removal efficiency of 30% was achieved was associated to U(VI) toxicity to cells at higher
initial U(VI) concentration.
5. The presence of nitrate which a common co-pollutant existing with uranium in the nuclear
waste did not inhibit U(VI) removal efficiency in the system and also insignificant nitrate
removal observed over time in the system indicated that nitrate was not a competitive
electron acceptor under operating conditions of this study.
6. Mass balance analysis of uranium species aided by TEM coupled with EDX suggest that
most U(VI) reduction occurred on the cell surface of the isolated species. This finding
indicates the possibility of easy uranium recovery for beneficial use.
7. The performance of the cultures in reducing U(VI) in batch system at various U(VI)
concentrations was well represented by pseudo-second order kinetic model with the cell
deactivation term. The pseudo-second order model (Equation 4-8) fitted well the batch
experimental data at various initial U(VI) concentration [100-600] with an R2 value of 99%.
8. The continuous-flow suspended growth system demonstrated high removal efficiency than
both batch and attached growth system. Higher performance of suspended growth system in
effectively reducing U(VI) at higher initial concentration up to 400 mg/L was attributed to (i)
high initial protein concentration, (ii) continuous purging of the reactor with N2 which
increased the anaerobic conditions in the systems and hence favour reducing conditions, and
(iii) continuous addition of BMM amended with glucose which greatly enhanced U(VI)
removal in the system.
9. Near complete U(VI) removal under high influent U(VI) loading of 400 mg/L in the
suspended growth system was observed under low biological activity, indicating that U(VI)
was not used as an electron acceptor to generate energy for cell growth, thus U(VI) was
reduced at the expense of metabolic activity in cells.
10. Near complete U(VI) removal was observed in attached growth system at highest U(VI)
feed concentration of 85 mg/L which is higher than the current background uranium
concentration at the study site.
111
11. The continuous-flow suspended bioreactor system did not stabilize in various feed
concentration until a quasi-steady state was achieved.
12. Mass transport kinetics and U(VI) removal kinetics in the biofilm reactor was represented
by diffusion-reduction model formulated using a set of differential equations which were
solved using a computer programme for solving numerical problems, Octave 3.0. The
diffusion-reduction model predicted well U(VI) effluent concentrations with 97% confidence.
14. The steady state model (Equation 6-38) predicted mass transport limitation and reaction
rate limitation on the biofilm surface layer over time.
112
CHAPTER 8
ENGINEERING SIGNIFICANCE AND RECOMMENDATIONS
8.1 Significance of the Biofilm Reactor
Biological treatment processes for U(VI) contaminated groundwater systems offer a great
advantage over the currently used physical-chemical processes due to their cost effectiveness
and environmentally compatibility. Among the proposed biological systems, attached growth
systems are markedly known for their higher pollutant removal efficiency. U(VI) is removed
from the wastewater under oxygen stressed and nutrient deficient conditions by quantitatively
transforming it to U(IV), which is easily precipitated from water as an insoluble hydroxide
[UOH4(s)].
In-situ treatment of uranium contaminated groundwater may be accomplished by introducing
the U(VI) reducing bacteria into aquifers through injection wells. This technology has been
attempted at a field site in Rifle, Colorado using pure isolates (Anderson et al., 2003).
Although, this study was effective for fundamental understanding of interaction taking place
between the cells and the metals, the problem at this site was the need to introduce an
external carbon source which stimulated the growth of non-essential species that could
compete with target species for space an micronutrients and increases the risk of increasing
background COD and therefore polluting the groundwater environment.
The biological treatment technology proposed in this study can be utilized for treatment of
process water effluent streams and in remediation of U(VI) contaminated sites as part of a
pump-and-treat bioremediation process. A model is developed to aid in the evaluation of
reactor performance and to establish loading limits. The model parameters determined from
the batch and continuous flow processes may be useful during scale up to the pilot stage of
the study.
8.2 Future Research and Recommendations
This work represents an effort at using fixed-film bioreactors to reduce U(VI) under nutrient
deficient conditions without biostimulation. Although the biological reduction processes have
been considered for removal of metals in wastewater streams, the application in packed bed
media and underground in situ barriers has been hampered by lack of means of removal of
precipitated metals in the medium. During U(VI) reduction process, the U(IV) formed
113
hydrolyses easily into [U(OH)4](s) which tends to accumulate in the reactor or barrier system.
Therefore, in order to achieve optimum application of this technology, future studies for
mobilizing the uranium precipitate in the reactor by flushing the reactor with the weak
organic acid such as citric acid must be conducted. Organic acids are preferred to use than
inorganic acids as they produce biodegradable organic waste product which are less harmful
to the environment (Gavrilescu et al., 2009; Huang et al., 1998; Joshi-Tope et al., 1995;
Francis et al., 1993). Moreover, since in the actual system environmental contamination is
not only limited to single element, it is important to understand how bacteria can interact with
other radionuclides that co-exist with uranium in nature. Results from such studies would
provide sufficient knowledge to make decisions about how to manage or remove
radionuclides from the environment.
In this study the provision was made to analyse the attached microbial growth per surface
area at only one end of the reactor. This was due to the difficulty or rather the impossibility of
sampling for at various locations in a closed reactor system which was operated under oxygen
stressed conditions. These results on attached biomass do not provide a clear indication of the
overall change in attached microbial growth across the reactor for the entire reactor.
Therefore, in order to circumvent such limitations in the close biofilm system, advanced
experimental techniques such as micro sensors and gene probes must be applied directly
within the biofilm for effective measurements of many soluble compounds such as nitrate,
oxygen, and others within the biofilm and total biofilm accumulation. Experimental results
from such advanced techniques will provide more details especially on biomass analysis and
could be effective for validation of the developed biofilm model in a continuous flow closed
system.
114
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APPENDIX A
PROTEIN ANALYSIS STANDARD CURVE
***************************************************************************
131
APPENDIX B
Octave Version 3.0
**************************************************************************
132
APPENDIX C
Octave Version 3.0
RUNGE_KUTTA METHOD
***************************************************************************
% Author Ido Schwartz
clc;
% Clears the screen
clear all;
#_________________________________________________________________________
Q = 0.00792;
V = 0.00785;
Uin =[75 85 100];
Du = 5.976×10-6;
Lw = 1.108×10-3;
A = 0.00785;
rho_s =2300000;
a= 0.3298;
kg =Du/Lw;
Xf= 60;
b=0.0005;
kd=0.006;
porosity = 0.95;
u= 1.0627;
#__________________________________________________________________________
#Simulation parameters
initial_time = 0;
final_time = 120;
h=2;
% step size
133
x = initial_time:h:final_time;
% Calculates up to final_time
y = zeros (1, length(x));
#_________________________________________________________________________________
F_xy = @(Lf,t)(((1/(1-ε))*(1/rho_s))*(Xf*Lf))-1/rho*(kd*A*(u^2/2)*Xf*A/V*Lf));
#_________________________________________________________________________________
#RK algorithm
for i=1:(length(x)-1)
% calculation loop
k_1 = F_xy(x(i),y(i));
k_2 = F_xy(x(i)+0.5*h,y(i)+0.5*h*k_1);
k_3 = F_xy((x(i)+0.5*h),(y(i)+0.5*h*k_2));
k_4 = F_xy((x(i)+h),(y(i)+k_3*h));
y(i+1) = y(i) + (1/6)*(k_1+2*k_2+2*k_3+k_4)*h; % main equation
end
vv = [y' x']
plot(x,y,'--')
xlabel 'time (d)'
ylabel 'Lf (m)'
134
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