**8. Microbial characterisation and activity**

#### **8.1. Correlation of U(VI) reduction to enzyme activity**

Proteins make up a large fraction of the biomass of actively grown microbes. To determine microbial activity over time, protein concentration was determined using a UV/Vis Spectro‐ photometer (WPA, Light Wave II, and Labotech, South Africa) at the wavelength of 595 nm using Coomassie Dye as a complexing agent to facilitate protein detection. Samples required pre-treatment to reduce interferences during the spectrophotometric analyses. Cell lysis was achieved by ultrasonification of acid treated cells. Results showed that microbial activity decreased with increasing U(VI) reduction (Figure 7). These results served as a confirmation of enzymatic activity as responsible agent for U(VI) reduction.

#### **8.2. Culture composition analysis**

The phylogenetic characterization of cells from the mine dump soil was conducted after subculturing the cells in nutrient or Luria-Bettani broth. Individual colonies from a serially diluted preparation were carefully examined for colony morphology and cell morphology by Gramstaining. This process, we recognize, could eliminate a wide range of potential U(VI) reducers especially anaerobic species in the samples. But at this stage, we were targeting the species that can survive under facultative anaerobic conditions.

The purified colonies were streaked on nutrient agar followed by incubating at 30°C for 18 hours in preparation for 16S rRNA gene sequence analysis. Microbial pure cultures were grown from loop-fulls from individual colonies, transferred to fresh media containing low amounts (30-75 mg/L) of uranyl nitrate. The process was repeated at least three times for each colony type to achieve close to a pure culture of each identified species.

deposits show that they are composed of the following elements U>Cu>P>Os>Ca>Co>Fe (according to their descending order of their weight %). The higher copper (Cu) peak results from the specimen to support grid used. Phosphorous observed in the spectrum could either be from the added phosphorous or could microbially produced. On the other hand no uranium

**Figure 6.** (a) TEM Scan of bacterial cells indicating deposition of uranium species on cell surface and (b) EDX spectrum

Proteins make up a large fraction of the biomass of actively grown microbes. To determine microbial activity over time, protein concentration was determined using a UV/Vis Spectro‐ photometer (WPA, Light Wave II, and Labotech, South Africa) at the wavelength of 595 nm using Coomassie Dye as a complexing agent to facilitate protein detection. Samples required pre-treatment to reduce interferences during the spectrophotometric analyses. Cell lysis was achieved by ultrasonification of acid treated cells. Results showed that microbial activity decreased with increasing U(VI) reduction (Figure 7). These results served as a confirmation

The phylogenetic characterization of cells from the mine dump soil was conducted after subculturing the cells in nutrient or Luria-Bettani broth. Individual colonies from a serially diluted preparation were carefully examined for colony morphology and cell morphology by Gramstaining. This process, we recognize, could eliminate a wide range of potential U(VI) reducers especially anaerobic species in the samples. But at this stage, we were targeting the species

The purified colonies were streaked on nutrient agar followed by incubating at 30°C for 18 hours in preparation for 16S rRNA gene sequence analysis. Microbial pure cultures were

was observed in the metal free biomass (Results not shown).

(a) (b)

Crystals/precipitate

Bacteria 

194 Applied Bioremediation - Active and Passive Approaches

**8. Microbial characterisation and activity**

**8.1. Correlation of U(VI) reduction to enzyme activity**

of enzymatic activity as responsible agent for U(VI) reduction.

that can survive under facultative anaerobic conditions.

**8.2. Culture composition analysis**

of precipitate.

Genomic DNA was extracted from purified colonies according to the protocol described for the Wizard Genomic DNA purification kit (Promega Corporation, Madison, WI, USA). 16S rRNA genes were amplified by 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 min at 94°C, 30 cycles of 30s at 94°C, 1 min at 50°C and 2 min at 72°C, and a final extension step of 10 min at 72°C). PCR fragments were then cloned into pGEM-T-easy (Promega) [Promega Wizard® Genomic DNA Purifica‐ tion Kit (Version 12/2010)]. The 16S rRNA gene sequences of the strains were aligned with reference sequences from *Desulfovibrio sp.*, *Geobacter sp.*, *Acinetobacter sp.*, *Anthrobacter sp.*, and *Shewanella putrefaciens* using Ribosomal Database Project II 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 method [65]. U(VI) concentration, mg/L 60 80 100 120 cell-free control Sodium Azide Heat-killed cells Live-cells

U(VI) reducing colonies were identified from the genera *Bacilli*, *Acinobacter*, *Actinomycetes* and *Chrysebactreium*. Sections of phylogenetic tree diagrams with closet associations to know species are shown in Figures 8d. The associations shown Figure 8 have been reported among U(VI) reducing groups in literature. Fowle et al. [66] has shown that *Bacillus* species are effective biosorbents for uranium. Additionally, the capability of *Anthrobacter* species isolated from a uranium-contaminated site in accumulating uranium intracellularly as uranium precipitates closely associate with polyphosphate granules was also reported [21]. Time, h 0 10 20 30 40 50 0 20 40

**Figure 3.** Evaluation of abiotic U(VI) reduction in heat-killed and azide exposed cells

**Figure 7.** Evaluation of U(VI) reduction, protein concentration and total uranium under an initial concentration of 400 mg/L. **Figure 7.** Evaluation of U(VI) reduction, protein concentration and total uranium under an initial concentration of 400 mg/L.

2

**Figure 8.** Phylogenetic analysis results showing the predominance of the Gram-positive (a) *Microbacterieceae*  and *Anthrobacteriae*, and Gram-negative (b) *Acinetobater* under low U(VI) exposure. Colonies, Y10 in figure 8c did not reduce uranium. Another uranium (VI) reducing species, Y6, was also identified among the Bacilli shown in Figure 8d. **Figure 8.** Phylogenetic analysis results showing the predominance of the Gram-positive (a) *Microbacterieceae* and An‐ *throbacteriae*, and Gram-negative (b) *Acinetobater* under low U(VI) exposure. Colonies Y10 in figure 8c did not reduce uranium. Another uranium (VI) reducing species, Y6, was also identified among the Bacilli shown in Figure 8d.

In the phylogenetic analysis, the scale indicated at the bottom of the plots, e.g., 0.005 for Figure 8a represents the genetic distance, while the percentage numbers at the nodes indicate the level of bootstrap based on neighbour-joining analysis of 1000 replicates. The three species related to *Actinomycetes* were tolerant at 75 mg/L of U(VI) suggesting the capability of the species in reducing U(VI) in a basal mineral medium (BMM) amended with D-glucose (Figure 8a). The species related to *Acinobacter* as indicated in Figure 8b were also tolerant to U(VI) at concen‐ tration levels around 75 mg/L with D-glucose as a sole added carbon source. The group presented in Figure 8c, although tolerant to U(VI), did not reduce U(VI) under the conditions tested. Three species of 16S rRNA gene of *Bacilli* were tolerant at 75 mg/L and at least one of these, Colony Y6, was able to reduce U(VI) in a basal mineral medium (BMM) amended with D-glucose as a sole added carbon source.

3

**9. U(VI) removal kinetics**

**9.1. Kinetic model adaptation**

where: *U*<sup>0</sup>

kinetic parameters *ku*

capacity of the cells.

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 such as U(VI). Shen and Wang [67] demon‐ strated that the rate of U(VI) reduction by enzymes can be expressed as the Monod equation

> *u u dU k U <sup>X</sup> dt K U*

(mg cells/L); *ku* = specific rate of U(VI) reduction(mg U(VI)/mg cells/h); and *Ku*

0

*u*

*U U X X*

proportion to the amount of U(VI) reduced due to the toxicity of U(VI):

= initial U(VI) concentration (mg/L); *X*<sup>0</sup>

and *Ku*

**9.2. Uranium (VI) reduction under inhibiting conditions**

tuting Equation 3 into Equation 2 yields the following equation:

where: *U* = U(VI) concentration at time, *t* (mg/L); *X* = density of active bacterial cells at time, *t*

constant (mg/L). However, the active cell concentration, *X*, may be assumed to decrease in

0

*u*

*T*

(mg cells/L); and *Tu* = maximum U(VI) reduction capacity of cells (mg U(VI)/mg cell). Substi‐

0

U(VI) reduction data obtained with the pure cultures and the mixed culture were analyzed using Equation 4. Parameters in Equation 4 can be analyzed using simulation software such as AQUASIM or SigmaPlot. The model is calibrated using batch data over the incubation period. The values collected under non-inhibiting conditions are suitable for estimating the

estimated under overloaded conditions since this parameter is related to the U(VI) reduction

The inhibition model is suitable for application where the U(VI) loading per cell is very high. This is expected during startup (inoculation) of a systems with U(VI) already present. Such would be the case during the initial operation *in situ* bioremediation system. To account for

+ è ø

*u c dU kU U U <sup>X</sup> dt K U T* - æ ö -= - ç ÷

0

since these respond to cell growth dynamics. The parameter *Tu*


Bioremediation of Radiotoxic Elements under Natural Environmental Conditions


= initial cells density of U(VI)-reducing strains

= half-velocity

http://dx.doi.org/10.5772/56909

197

(4)

is

if viable cell concentration *X* is correlated to enzymes produced *E*:

## **9. U(VI) removal kinetics**

#### **9.1. Kinetic model adaptation**

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 such as U(VI). Shen and Wang [67] demon‐ strated that the rate of U(VI) reduction by enzymes can be expressed as the Monod equation if viable cell concentration *X* is correlated to enzymes produced *E*:

$$-\frac{d\mathbf{U}}{dt} = \frac{k\_{\mu} \cdot \mathbf{U}}{K\_{\mu} + \mathbf{U}} \cdot \mathbf{X} \tag{2}$$

where: *U* = U(VI) concentration at time, *t* (mg/L); *X* = density 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-velocity constant (mg/L). However, 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):

$$X = X\_0 - \frac{\mathcal{U}\_0 - \mathcal{U}}{T\_u} \tag{3}$$

where: *U*<sup>0</sup> = initial U(VI) concentration (mg/L); *X*<sup>0</sup> = initial cells density of U(VI)-reducing strains (mg cells/L); and *Tu* = maximum U(VI) reduction capacity of cells (mg U(VI)/mg cell). Substi‐ tuting Equation 3 into Equation 2 yields the following equation:

$$-\frac{d\mathcal{U}}{dt} = \frac{k\_u \cdot \mathcal{U}}{K\_u + \mathcal{U}} \left( X\_0 - \frac{\mathcal{U}\_0 - \mathcal{U}}{T\_c} \right) \tag{4}$$

U(VI) reduction data obtained with the pure cultures and the mixed culture were analyzed using Equation 4. Parameters in Equation 4 can be analyzed using simulation software such as AQUASIM or SigmaPlot. The model is calibrated using batch data over the incubation period. The values collected under non-inhibiting conditions are suitable for estimating the kinetic parameters *ku* and *Ku* since these respond to cell growth dynamics. The parameter *Tu* is estimated under overloaded conditions since this parameter is related to the U(VI) reduction capacity of the cells.

#### **9.2. Uranium (VI) reduction under inhibiting conditions**

3

**Y9** *Acinetobacter junii*

in Figure 8d.

61

0.005

 *Acinetobacter baumannii*

 *Acinetobacter venetianus Psychrobacter immobilis*

0.5 0.01

D-glucose as a sole added carbon source.

 *Kocuria palustris Kocuria rosea Kocuria polaris Kocuria aegyptia Kocuria turfanensis*

> 98 96

> > 44 100

 *Chryseobacterium indoltheticum*

(b) (c) (d)

 *Chryseobacterium scophthalmum Chryseobacterium aquaticum Streptomyces albus subsp. albus*

**Y3**

100

*Arthrobacter soli Arthrobacter protophormiae*

*Arthrobacter ramosus Arthrobacter globiformis Arthrobacter pascens*

*Arthrobacter creatinolyticus*

**Y8**

100

 *Arthrobacter sulfonivorans*

**Y5**

66 100

> **Y11**  *Bacillus pumilus Bacillus altitudinis Bacillus safensis* **Y7**

64

0.005

**Figure 8.** Phylogenetic analysis results showing the predominance of the Gram-positive (a) *Microbacterieceae*  and *Anthrobacteriae*, and Gram-negative (b) *Acinetobater* under low U(VI) exposure. Colonies, Y10 in figure 8c did not reduce uranium. Another uranium (VI) reducing species, Y6, was also identified among the Bacilli shown

**Figure 8.** Phylogenetic analysis results showing the predominance of the Gram-positive (a) *Microbacterieceae* and An‐ *throbacteriae*, and Gram-negative (b) *Acinetobater* under low U(VI) exposure. Colonies Y10 in figure 8c did not reduce uranium. Another uranium (VI) reducing species, Y6, was also identified among the Bacilli shown in Figure 8d.

In the phylogenetic analysis, the scale indicated at the bottom of the plots, e.g., 0.005 for Figure 8a represents the genetic distance, while the percentage numbers at the nodes indicate the level of bootstrap based on neighbour-joining analysis of 1000 replicates. The three species related to *Actinomycetes* were tolerant at 75 mg/L of U(VI) suggesting the capability of the species in reducing U(VI) in a basal mineral medium (BMM) amended with D-glucose (Figure 8a). The species related to *Acinobacter* as indicated in Figure 8b were also tolerant to U(VI) at concen‐ tration levels around 75 mg/L with D-glucose as a sole added carbon source. The group presented in Figure 8c, although tolerant to U(VI), did not reduce U(VI) under the conditions tested. Three species of 16S rRNA gene of *Bacilli* were tolerant at 75 mg/L and at least one of these, Colony Y6, was able to reduce U(VI) in a basal mineral medium (BMM) amended with

*Microbacterium aerolatum Microbacterium paraoxydans Microbacterium ginsengiterrae Streptomyces albus subsp. albus*

 *Bacillus stratosphericus*

98 **Y6**

 *Bacillus licheniformis*

 *Listeria monocytogenes*

 **Y1**

96

75 99 45

57

**Y10**

89

79

93

(a)

196 Applied Bioremediation - Active and Passive Approaches

35

The inhibition model is suitable for application where the U(VI) loading per cell is very high. This is expected during startup (inoculation) of a systems with U(VI) already present. Such would be the case during the initial operation *in situ* bioremediation system. To account for toxic inhibition in such situations, a simple Monods non-competitive inhibition kinetic model incorparating inhibition term, K is suggested:

$$-r\_u = \frac{k\_u \mathcal{U}}{\binom{K\_u + \mathcal{U}}{\mathcal{K}} \binom{\left(1 - \frac{\mathcal{U}\_T}{\mathcal{U}\_0}\right)}{\mathcal{K}}} \left(X\_0 - \frac{\mathcal{U}\_0 - \mathcal{U}}{T\_u}\right) \tag{5}$$

The reaction term *ru* is dependent on the amount of biomass accumulated in the void space of the column. However, due to space limitations, cells may only grow to a certain maximum concentration. The time at which the cells reach the maximum allowable concentration is dependent on initial cells, U(VI) toxicity, and hydraulic loading rate. These conditions cause

Bioremediation of Radiotoxic Elements under Natural Environmental Conditions

max

*t t*

æ ö <sup>+</sup> ç ÷ ç ÷ è ø

*X*

*b*

(8)

199

http://dx.doi.org/10.5772/56909

0

where: *X* = viable cell density (mg/L) at any time *t* (h); *Xmax* = maximum attainable viable cell concentration (mg/L) in the barrier column, *t*<sup>0</sup> = logistic interval (h); and *b* = pitch (dimension‐ less). The impact of the adsorptive process was determined to be minimal during continuous flow operation for an extended period of time. This is because reaction sites tend to become

The chapter addresses the main feature of various U(VI) remediation techniques involving the *in situ* bioremediation using permeable reactive barrier. The technique is well known for its effectiveness for remediating organic pollutants. However, its effectiveness for removal of metallic species is hindered by possible accumulation of precipitates. In our preliminary batch studies it was observed that isolated organisms are capable of immobilizing U(VI) by means of more than one mechanism, i.e., biosorption and enzymatic reduction. These results open a new research field for understanding which of these mechanism is predominant and in what sequence does the U(VI) reduction take place under anaerobic conditions. Modelling *in situ* U(VI) bioreduction involve many uncertain parameters, including those of aqueous U(VI) speciation, surface complexation, and bioreduction kinetics. Therefore, for efficient applica‐ tion, sensitivity analysis is needed to simplify the models such as presented. Furthermore, reoxidation of the biologically reduced uranium needs to be included in future models to

0

= +

*X X*

1

the cells to follow a logistic curve defined by Equation 8:

saturated as the system approaches equilibrium.

evaluate long-term stability of bioreduction techniques.

)

)

**10. Conclusion**

**Nomenclature**

*Af* -

*A -* effective cross sectional area (m2

biomass surface area (m2

*b -* pitch factor (dimensionless)

where: *ku* = maximum specific rate of U(VI) reduction (1/h); *Ku* = half-velocity constant (mg/L); *UT* = U(VI) toxicity threshold concentration (mg/L); *Xo* = initial biomass concentration (mg/L); *K* = limiting constant (mg/L); and *Tu* = U(VI) reduction capacity (mg U(VI) reduced/mg cells).

#### **9.3. Continuous flow systems**

Continuous flow systems better simulate actual systems especially where *in situ* bioremedia‐ tion is planned. Batch systems cannot simulated the effects of diffusion, clogging of pores, advection rates. Packed columns have been used in simulating the operational conditions of a barrier system [68]. The non-steady state dynamic process of uranium removal in packed column is represented by Equation 6. The mass balance of uranium (VI) across the packed column includes U(VI) reduction rate (*ru* ), mass transport rate (*j u* ), adsorption rate (*qu* ). Due to the inclusion of the interstitual term *u* and the mass transport term *j u* , the predominant process affecting performance during the transient-state in the advection and diffussion:

$$\frac{d(\mathcal{U}\cdot V)}{dt} = A \sum\_{l=0}^{l=L\_{\tilde{l}}} \varkappa(\mathcal{U}\_{\text{in}} - \mathcal{U}) - r\_u \cdot \Delta V - j\_u \cdot A\_f - q\_u \cdot \Delta V \tag{6}$$

where: *U* = effluent U(VI) concentration (mg/L); *V* = volume of the reactor (L); *Uin* = influent U(VI) concentration (mg/L); *Q* = influent flow rate (L/h); *ru* = U(VI) reduction rate coefficient (mg/L/h); *t* = time (h); *Af =* biomass surface area (m2 ); *Ju* = flux of dissolved species into the biofilm (mg/m2 /h); and *qu* = rate of U(VI) removal by adsorption (1/h). The interstitial velocity *u* (m/h) is assumed to be constant throughout the entire column. The diffusional flux (*Ju* ) can be expresed using Fick's law:

$$\frac{\partial \mathbf{c}\_i}{\partial t} = D\_w \frac{\partial^2 \mathbf{c}\_i}{\partial \mathbf{x}^2} \tag{7}$$

Where: **c***<sup>i</sup>* = concentration of dissolved species (mg/L); *Dw* = diffusivity of dissolved species in water (m2 /h); *t* = time (h); and *x =* spatial coordinate (m).

The reaction term *ru* is dependent on the amount of biomass accumulated in the void space of the column. However, due to space limitations, cells may only grow to a certain maximum concentration. The time at which the cells reach the maximum allowable concentration is dependent on initial cells, U(VI) toxicity, and hydraulic loading rate. These conditions cause the cells to follow a logistic curve defined by Equation 8:

$$X = X\_0 + \frac{X\_{\text{max}}}{1 + \left(\frac{t}{t\_0}\right)^b} \tag{8}$$

where: *X* = viable cell density (mg/L) at any time *t* (h); *Xmax* = maximum attainable viable cell concentration (mg/L) in the barrier column, *t*<sup>0</sup> = logistic interval (h); and *b* = pitch (dimension‐ less). The impact of the adsorptive process was determined to be minimal during continuous flow operation for an extended period of time. This is because reaction sites tend to become saturated as the system approaches equilibrium.

#### **10. Conclusion**

toxic inhibition in such situations, a simple Monods non-competitive inhibition kinetic model

1 *<sup>T</sup>*

ç ÷ è ø

where: *ku* = maximum specific rate of U(VI) reduction (1/h); *Ku* = half-velocity constant (mg/L); *UT* = U(VI) toxicity threshold concentration (mg/L); *Xo* = initial biomass concentration (mg/L);

Continuous flow systems better simulate actual systems especially where *in situ* bioremedia‐ tion is planned. Batch systems cannot simulated the effects of diffusion, clogging of pores, advection rates. Packed columns have been used in simulating the operational conditions of a barrier system [68]. The non-steady state dynamic process of uranium removal in packed column is represented by Equation 6. The mass balance of uranium (VI) across the packed

), mass transport rate (*j*

*in u u f u*

); *Ju*

2 2

Where: **c***<sup>i</sup>* = concentration of dissolved species (mg/L); *Dw* = diffusivity of dissolved species in

*i i Dw <sup>t</sup> <sup>x</sup>* ¶ ¶ <sup>=</sup> ¶ ¶

= rate of U(VI) removal by adsorption (1/h). The interstitial velocity *u* (m/h)

= - - D - - D å (6)

æ ö ç ÷ è ø æ ö - - = ç ÷ - æ öè ø ç ÷ <sup>+</sup> ç ÷

*k U U U r X*

*<sup>u</sup> <sup>U</sup> <sup>u</sup> <sup>U</sup>*

0

*T*

= U(VI) reduction capacity (mg U(VI) reduced/mg cells).

*u*

*u*

), adsorption rate (*qu*

= U(VI) reduction rate coefficient

= flux of dissolved species into the biofilm

**c c** (7)

, the predominant process

(5)

). Due to

= influent

) can be

0

( ) <sup>0</sup>

*K UK*

*u*

the inclusion of the interstitual term *u* and the mass transport term *j*

0 ( ) ( ) *<sup>i</sup> l L*

/h); *t* = time (h); and *x =* spatial coordinate (m).

*l*

U(VI) concentration (mg/L); *Q* = influent flow rate (L/h); *ru*

=

=

affecting performance during the transient-state in the advection and diffussion:

*dU V A uU U r V j A q V dt*

where: *U* = effluent U(VI) concentration (mg/L); *V* = volume of the reactor (L); *Uin*

is assumed to be constant throughout the entire column. The diffusional flux (*Ju*

*=* biomass surface area (m2

*u*

incorparating inhibition term, K is suggested:

198 Applied Bioremediation - Active and Passive Approaches

*K* = limiting constant (mg/L); and *Tu*

column includes U(VI) reduction rate (*ru*

**9.3. Continuous flow systems**

(mg/L/h); *t* = time (h); *Af*

/h); and *qu*

expresed using Fick's law:

(mg/m2

water (m2

The chapter addresses the main feature of various U(VI) remediation techniques involving the *in situ* bioremediation using permeable reactive barrier. The technique is well known for its effectiveness for remediating organic pollutants. However, its effectiveness for removal of metallic species is hindered by possible accumulation of precipitates. In our preliminary batch studies it was observed that isolated organisms are capable of immobilizing U(VI) by means of more than one mechanism, i.e., biosorption and enzymatic reduction. These results open a new research field for understanding which of these mechanism is predominant and in what sequence does the U(VI) reduction take place under anaerobic conditions. Modelling *in situ* U(VI) bioreduction involve many uncertain parameters, including those of aqueous U(VI) speciation, surface complexation, and bioreduction kinetics. Therefore, for efficient applica‐ tion, sensitivity analysis is needed to simplify the models such as presented. Furthermore, reoxidation of the biologically reduced uranium needs to be included in future models to evaluate long-term stability of bioreduction techniques.

### **Nomenclature**


**References**

[1] IAEA. Nuclear Technology Review. International Atomic Energy Agency Scientific

Bioremediation of Radiotoxic Elements under Natural Environmental Conditions

http://dx.doi.org/10.5772/56909

201

[2] Greve, K., Niesen, E., Ladefogen, O. Evaluation of health hazards by exposure to

[3] Ajlouni, AMS. Health consequences of nuclear fission products. Journal of Applied

[4] World Nuclear Association (WNA); 2008. http://www.world-nuclear.org/info/

[5] Tikilili PV, Chirwa EMN. Characterization and Biodegradation of Polycyclic Aromat‐ ic Hydrocarbons in Radioactive Wastewater. Journal of Hazardous Materials 2011;

[6] Bouwer EJ, Zehnder AJB. Bioremediation of organic compounds-putting microbial

[7] Craig DK. Chemical and Radiological Toxicity of Uranium and its Compounds, Re‐ port WSRC-TR-2001-00331, Contract No. DE-AC09-96SR18500, Westinghouse Savan‐

[8] Chirwa EMN. Developments in bioremediation for separation/recovery. K.L. Nash and G.J. Lumetta (Eds.), in Advanced Separation Techniques for Nuclear Fuel Re‐ processing and Radioactive Waste Treatment, Woodhead Publishing, Ltd, Cam‐

[9] Doherty R, Phillips DH, McGeough KL, Walsh KP, Kalin RM. Development of modi‐ fied flyash as a permeable reactive barrier medium for a former manufactured gas

[10] IAEA. Treatment of Liquid Effluent from Uranium Mines and Miles. Report of a Coordinated Research Project 1996-2000. International Atomic Energy Agency (IAEA),

[11] Gavrilescu M. Overview of in situ remediation technologies for sites and groundwa‐ ter. Environmental. Engineering and Management Journal 2006; 5(1) 79-114.

[12] Olexsey RA, Parker RA. Current and future *in situ* treatment techniques for the reme‐ diation of hazardous substances in soil, sediments, and groundwater I. Twardowska, H.E. Allen, M.M. Häggblom, S. Stefaniak (Eds.), Soil and Water Pollution Monitor‐ ing, Protection and Remediation, NATO Science Series, IV. Earth and Environmental

[13] Zaganiaris EJ. Ion Exchange Resins in Uranium Hydrometallurgy, Books on Demand

plant site. Northern Ireland. Environmental Geology 2006; 50(1) 37-46.

and Technical Publication Series, Vienna, Austria; 2009.

Science and Environmental Management 2007; 11(3) 11-14.

metabolism to work. Trends Biotechnology 1993; 11(8) 360-367.

nah River Company, Aiken/U.S. Department of Energy; 2001.

inf88.html (accessed 7 November 2012).

192(3) 1589-1596.

bridge, UK; 2011. p436-472.

2004; Vienna, Austria.

GmbH, Paris, France; 2009.

Science, Springer, Netherlands 2006; 69, 211-219

strontium in drinking water. Toxicology Letters 2007; 172(1) S210.


### **Author details**

Phalazane Johanna Mtimunye and Evans M. N. Chirwa

\*Address all correspondence to: mtimunyepj@gmail.com

Water Utilization Division, Department of Chemical Engineering, University of Pretoria, Pretoria, South Africa

## **References**

*Dw -* diffusivity of dissolved species in water (m2

200 Applied Bioremediation - Active and Passive Approaches

/h)

*Tu -* U(VI) reduction capacity (mg U(VI) reduced/mg cells)

*U*0 - initial value, U(VI) concentration at time zero (mg/L)

*Xmax-* maximum attainable viable cell concentration (mg/L)

Phalazane Johanna Mtimunye and Evans M. N. Chirwa

\*Address all correspondence to: mtimunyepj@gmail.com

Water Utilization Division, Department of Chemical Engineering, University of Pretoria,

U(VI) toxicity threshold concentration (mg/L)

*U -* effluent U(VI) concentration at time, t (mg/L)

*U*in - influent U(VI) concentration (mg/L)

*X* - biomass concentration at time *t* (mg/L)

– initial biomass concentration (mg cells/L)

*Ju -* U(VI) flux rate (mg/m2

*Q -* inflow rate (L/h)

*K* -

*qm* -

*UT* -

*X*0-

*t -* time (h)

*ku -* reaction rate coefficient (1/h)

inhibition coefficient (mg/L)

*Ku -* half-velocity constant (mg/L)

*ru -* U(VI) reduction rate (mg/L/h)

*t*0 - logistic time interval (h)

*V -* volume of the reactor (L) *∆V -* differential volume (L)

*x* - spatial coordinate (m)

**Author details**

Pretoria, South Africa

*qu -* rate of U(VI) by adsorption (mg/L/h)

/h)

maximum specific uptake of metal corresponding to site saturation (mg/g)


[14] Traut DE, Nichols IL, Seidel DC. Design requirements for uranium ion exchange from ammonium bicarbonate solutions in a fluidized system. Department of the Inte‐ rior, Bureau of Mines, USA; 1978.

[28] Dadachova E, Bryan RA, Huang X, Moadel T, Schweitzer AD, Aisen P, Nosanchuk JD, Casadevall A. Ionizing radiation changes the electronic properties of melanin and

Bioremediation of Radiotoxic Elements under Natural Environmental Conditions

http://dx.doi.org/10.5772/56909

203

[29] Francis AJ, Gillow JB, Dodge CJ, Harris R, Beveridge TJ, Papenguth HW. Uranium association with halophilic and non-halophilic bacteria and archaea. Radiochimica

[30] Nakajima A, Tsuruta T. Competitive biosorption of thorium and uranium by Micro‐ coccus luteus. Journal of Radioanalytical and Nuclear Chemistry 2004; 260(1) 13-18.

[31] Kratochvil D, Volesky B. Advances in the biosorption of heavy metals, Trends in Bio‐

[32] Sar P, D'Souza SF. Biosorption of thorium (IV) by a Pseudomonas strain. Biotechnol‐

[33] Jroundi F, Merroun ML, Arias JM, Rossberg A, Selenska-Pobell S, González-Muñoz MT. Spectroscopic and microscopic characterization of uranium biomineralization

[34] Suzuki Y, Banfield JF. Geomicrobiology of uranium. Reviews in Mineralogy Geo‐

[35] Macaskie LE, Bonthrone KM, Yong P, Goddard DT. Enzymically mediated biopreci‐ pitation of uranium by a Citrobacter sp. a concerted role for exocellular lipopolysac‐ charide and associated phosphatase in biomineral formation. Microbiology 2000;

[36] Reeder RJ, Nugent M, Tait CD, Morris DE, Heald SM, Beck KM, Hess WP. A Lanzir‐ otti Coprecipitation of uranium(VI) with calcite: XAFS, micro-XAS, and lumines‐ cence characterization. Geochimica et Cosmoschimica Acta 2001; 65(20) 3491–3503.

[37] Lovley DR, Widman PK, Woodwar, JC, Phillips EJP. Reduction of uranium by cyto‐ chrome *c*3 of *Desulfovibrio vulgaris*. Applied Environmental Microbiology 1991; 59(11)

[38] Gorby YA, Lovley DR. Enzymatic uranium precipitation. Environmental Science and

[39] Anderson C, Pedersen K. In situ growth of *Gallionella* biofilms and partitioning of lanthanides and actinides between biological material and ferric oxyhydroxides. Ge‐

[40] Rothschild LJ, Mancinelli RL. Life in extreme environments. Nature 2001; 409(6823)

[41] Istok JD, Senko JM, Krumholz LR, Watson D, Bogle MA, Peacock A, Chang YJ, White DC. In situ bioreduction of Technetium and Uranium in a nitrate-contaminated

Aquifer. Environmental Science and Technology 2004; 38(2) 468-475.

in*Myxococcus xanthus*. Geomicrobiology Journal 2007; 24(5) 441-449.

enhances the growth of melanized fungi. PLoS One, May 23, 2007.

Acta 2004; 92(8) 481-488.

technology 1998; 16(17) 291-300.

ogy Letters 2002; 24(3) 239-243.

chemistry 1999; 38(1) 393-432

technology 1992; 26(1) 205-207.

obiology 2003; 1(2) 169-178.

146(8) 1855-1867.

3572-3576.

1092-1101.


[28] Dadachova E, Bryan RA, Huang X, Moadel T, Schweitzer AD, Aisen P, Nosanchuk JD, Casadevall A. Ionizing radiation changes the electronic properties of melanin and enhances the growth of melanized fungi. PLoS One, May 23, 2007.

[14] Traut DE, Nichols IL, Seidel DC. Design requirements for uranium ion exchange from ammonium bicarbonate solutions in a fluidized system. Department of the Inte‐

[15] Ross JR, George DR. Recovery of uranium from natural mine waters by countercur‐ rent ion exchange.US Department of Interior, Bureau of Mines, University of Michi‐

[16] Pabby AK, Rizvi SSH, Sastre AM. Membrane techniques for treatment in nuclear waste processing, a global experience. Membrane Technology 2008; 11: 9-13.

[17] Zhou P, Gu P. Extraction of oxidized and reduced forms of uranium from contami‐ nated soils: effects of carbonate concentration and pH. Environmental Science and

[18] Phillips EJP, Landa ER, Lovley DR. Remediation of uranium contaminated soils with bicarbonate extraction and microbial U(VI) reduction. Journal of Industrial Microbi‐

[19] Gramss G, Voight KD, Bergmann H. Plant availability and leaching of heavy metals from ammonium-calcium, carbohydrate, and citric acid-treated uranium-mine-dump

[20] Kantar B, Honeyman BD. Citric acid enhanced remediation of soil contaminated with uranium by soil flushing and soil washing. Journal of Environmental Engineering

[21] Suzuki Y, Banfield J. Resistance to, and accumulation of, uranium by bacteria from a uranium-contaminated site. Geomicrobiology Journal 2004; 21(2) 113-121.

[22] Nancharaiah YV, Joshi HM, Mohan TVK, Venugopalan VP, Narasimhan SV. Aerobic granular biomass: a novel biomaterial for efficient uranium removal. Current Science

[23] Nedelkova M, Merroun ML, Rossberg A, Hennig C, Selenska-Pobell S. Microbacteri‐ um isolates from the vicinity of a radioactive waste depository and their interactions

[24] Bush MB. Ecology of a Changing Planet, 3rd Edition, Prentice Hall, New Jersey,

[25] Nealson KH. Post-Viking microbiology: new approaches, new data, new insights. Origins of life and evolution of the biosphere. Journal of the International Society for

[26] Kalckar HM. Origins of the concept oxidative phosphorylation. Molecular and Cellu‐

[27] Lloyd JR. Microbial reduction of metals and radionuclides. FEMS Microbiology Re‐

soil. Journal of Plant Nutrition and Soil Science 2004; 167, 417-427.

with uranium. FEMS Microbiology Ecology 2007; 59(3) 694-705.

the Study of the Origin of Life 1999; 29(1), 73-93.

lar Biochemistry 1974; 5(1-2), 55-63.

views 2003; 27, 411-425.

rior, Bureau of Mines, USA; 1978.

Technology 2005; 39(12) 4435-4440.

ology 1995; 14(3-4) 203-207.

2006; 132(2) 247-255.

2006; 91(4) 503-509.

USA, 2003.

gan; 1971. p7471-7480.

202 Applied Bioremediation - Active and Passive Approaches


[42] Woolfolk CA, Whiteley HR. Reduction of inorganic compounds with molecular hy‐ drogen by *Micrococcus lactilyticus*. I. Stoichiometry with compounds of arsenic, seleni‐ um, tellurium, transition and other elements. Journal of Bacteriology 1962; 84(4) 647-658.

[54] Kieft TL, Fredrickson JK, Onstott TC, Gorby YA, Kostandarithes HM. Dissimilatory reduction of Fe(III) and other electron acceptors by a *Thermus* isolate. Applied and

Bioremediation of Radiotoxic Elements under Natural Environmental Conditions

[55] Bencheikh-Latmani R, Williams SM, Haucke L, Criddle CS, Wu L. Global transcrip‐ tional profiling of *Shewanella oneidensis* MR-1 during Cr(VI) and U(VI) reduction. Ap‐

[56] Elias DA, Suflita JM, McInerney MJ, Krumholz LR. Periplasmic cytochrome c3 of De‐

[57] Caccavo FJ, Blakemore R, Lovley D. A hydrogen-oxidizing, Fe(III)-reducing microor‐ ganism from the Great Bay Estuary, New Hampshire. Applied and Environmental

[58] Methe BA, Nelson KE, Eisen JA, Paulsen IT, Nelson W. Genome of Geobacter sulfur‐ reducens: metal reduction in subsurface environments. Science 2003; 302(5652)

[59] Wu Q, Sanford RA, Löffler FE. Uranium reduction by Anaeromyxobacter dehalogen‐ ans strain 2CP-C. Applied and Environmental Microbiology 2006; 72(5) 3608-3614.

[60] Renshaw JC, Butchins LJ, Livens FR, May I, Charnock JM, Lloyed JR. Bioreduction of uranium: environmental implications of a pentavalent intermediate. Environmental

[61] Kennedy DW, Marshall MJ, Dohnalkova AC, Saffarini DA, Culley DE. Role of *Shewa‐ nella oneidensis c*-type cytochromes in uranium reduction and localization. ASM 105th

[62] Mukhopadhyay B, Sundquist J, Schmitz JR. Removal of Cr(VI) from Cr-contaminated groundwater through electrochemical addition of Fe(II). Journal of Environmental

[63] Liu S-J, Jiang B, Huang G-Q, Li XG. Laboratory column study for remediation of MTBE-contaminated groundwater using a biological two-layer permeable barrier.

[64] Mukred AM, Hamid AA, Hamzah A, Yusoff WMW. Development of Three Bacterial Consoritum for the Bioremediation of Crude Petroleum-oil in Contaminated Water.

[65] Jukes TH, Cantor CR. Evolution of protein molecules, In Munro, H.N. (Ed.), Mam‐

[66] Fowle DA, Fein JB, Martin AM. Experimental study of uranyl adsorption onto *Bacil‐ lus subtilis*, Environmental Science and Technology 2000; 34(17) 3737-3741.

malian Protein Metabolism. Academic Press, New York, 1969, p21-123.


http://dx.doi.org/10.5772/56909

205

Environmental Microbiology 1999; 65(3) 1214-1221.

sulfovibrio vulgaris is directly involved in H2

Microbiology 1992; 58(10) 3211-3216.

Science and Technology 2005; 39 5657-5660.

General Meet (Abstr.) Q-389; 2004.

Management 2007; 82(1) 66-76.

Water Research 2006; 40(18) 3401-3408.

Journal of Bio sciences 2008; 8(4) 73-79.

1967-1969.

plied and Environmental Microbiology 2005; 71(11) 7453-7460.

tion. Applied and Environmental Microbiology 2004; 70(1) 413-420.


[54] Kieft TL, Fredrickson JK, Onstott TC, Gorby YA, Kostandarithes HM. Dissimilatory reduction of Fe(III) and other electron acceptors by a *Thermus* isolate. Applied and Environmental Microbiology 1999; 65(3) 1214-1221.

[42] Woolfolk CA, Whiteley HR. Reduction of inorganic compounds with molecular hy‐ drogen by *Micrococcus lactilyticus*. I. Stoichiometry with compounds of arsenic, seleni‐ um, tellurium, transition and other elements. Journal of Bacteriology 1962; 84(4)

[43] Lovley DR, Phillips EJP. Reduction of uranium by *Desulfovibrio desulfuricans*. Applied

[44] Coates JD, Bhupathiraju VK, Achenbach LA, McInerney MJ, Lovley DR.*Geobacter hy‐ drogenophilus* and *Geobacter chapellei* and *Geobacter grbiciae*, three new, strictly anaero‐ bic, dissimilatory Fe(III)-reducers. International Journal of Systematic and

[45] Francis AJ, Dodge CJ, Lu F, Halada GP, Clayton CR. XPS and XANES studies of ura‐ nium reduction by *Clostridium sp*. Environmental Science and Technology 1994; 28(4)

[46] Shelobolina ES, Sullivan SA, O'Neill KR, Nevin KP, Lovley DR. Isolation, characteri‐ zation, and U(VI)-reducing potential of a facultatively anaerobic, acid-resistant bacte‐ rium from low-pH, nitrate- and U(VI)-contaminated subsurface sediment and description of *Salmonella subterranea* sp. nov. Applied and Environmental Microbiolo‐

[47] Wu Q, Sanford RA, Löffler FE. Uranium reduction by *Anaeromyxobacter dehalogenans* strain 2CP-C. Applied and Environmental Microbiology 2006; 72(5) 3608-3614. [48] Lloyd JR, Chesnes J, Glasauer S, Bunker DJ, Livens FR, Lovley DR. Reduction of acti‐ nides and fission products by Fe(III)-reducing bacteria. Geomicrobiology Journal

[49] Kashefi K, Lovely DR. Reduction of Fe(III), Mn(IV), and toxic metals at 100°C by *Py‐ robaculum islandicum*. Applied and Environnemental Microbiology 2000; 66(3)

[50] Lloyd JR, Leang C, Hodges-Myerson AL, Coppi MV, Cuifo S. Biochemical and genet‐ ic characterization of PpcA, a periplasmic *c*-type cytochrome in *Geobacter sulfurredu‐*

[51] Wade R, DiChristina TJ. Isolation of U(VI) reduction-deficient mutants of *Shewanella*

[52] Lovley DR, Roden EE, Phillips EJ, Woodward JC. Enzymatic iron and uranium re‐ duction by sulfate-reducing bacteria. Marine Geology 1993; 113(1-2) 41-53.

[53] Payne RB, Gentry DM, Rapp-Giles BJ, Casalot L, Wall JD. Uranium reduction by De‐ sulfovibrio desulfuricans strain G20 and a cytochrome c3 mutant. Applied and Envi‐

and Environmental Microbiology 1992; 58(3) 850-856.

Evolutionary Microbiology 2001; 51(2) 581-588.

*cens*. Biochemical Journal 2003; 369(1) 153-161.

ronmental Microbiology 2002; 68(6) 3129-3132.

*putrefaciens*. FEMS Microbiology Letters 2000; 184(2) 143-148.

647-658.

204 Applied Bioremediation - Active and Passive Approaches

636-639.

gy 2004; 70(5) 2959-2965.

2002; 19(1) 103-120.

1050-1056.


[67] Shen H, Wang Y T. Modeling hexavalent chromium reduction in Escherichia coli ATCC 33456. Biotechnology and Bioengineering 1994; 43(4) 293-300.

**Chapter 9**

**Removal of Hexavalent Chromium from Solutions and**

Chromium (Cr) toxicity is one of the major causes of environmental pollution emanating from tannery effluents. This metal is used in the tanning of hides and leather, the manufacture of stainless steel, electroplating, textile dyeing and as a biocide in the cooling waters of nuclear power plants. Consequently, these industries discharged chromium (VI) bearing effluents which are of significant environmental concerns [1]. Cr exists in nine valence states ranging from -2 to +6. From these, only the hexavalent [Cr (VI)] and trivalent chromium [Cr (III)] have primary environmental significance since they are the most stable oxidized forms in the

Both are found in various bodies of water and wastewaters [2]. Cr (VI) typically exists in one

solution [2].These two divalent oxyanions are very water soluble and poorly adsorbed by soil and organic matter, making them mobile in groundwater. Both chromate anions represent acute and chronic risks to animals and human health, since they are extremely toxic, mutagenic, carcinogenic and teratogenic [3]. In contrast to Cr (VI) forms, the Cr (III) species are predom‐ inantly hydroxides, oxides and sulphates, less water soluble, less mobile, 100 times less toxic [4] and 1,000 times less mutagenic [5]. The principal techniques for recovering or removing Cr (VI), from wastewater are: chemical reduction and precipitation, adsorption on activated carbon, ion exchange and reverse osmosis [6]. However, these methods have certain draw‐ backs, namely high cost, low efficiency, generation of toxic sludge or other wastes that require


© 2013 Acosta-Rodríguez et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


**Contaminated Sites by Different Natural Biomasses**

Ismael Acosta-Rodríguez, Juan F. Cárdenas-González,

Víctor M. Martínez-Juárez

http://dx.doi.org/10.5772/56152

**1. Introduction**

environment.

of these two forms: chromate (CrO4

María de Guadalupe Moctezuma-Zárate and

Additional information is available at the end of the chapter

[68] Mtimunye PJ. Steady-state model for hexavalent chromium reduction in simulated biological reactive barrier: microcosm analysis. Master's Thesis. University of Preto‐ ria, Pretoria, South Africa; 2011. http://upetd.up.ac.za/thesis/available/ etd-09222011-104550/ (accessed on 30/10/2012).
